From 45cf8513ad13e38c67aedcd26904b83da433ca04 Mon Sep 17 00:00:00 2001 From: LuckyBunnyLee Date: Tue, 17 Jun 2025 17:34:53 -0700 Subject: [PATCH 1/8] k-comp code --- utils.py | 34 ++++++++++++++++++++++++++++++++++ 1 file changed, 34 insertions(+) diff --git a/utils.py b/utils.py index be59325..7b3d0d2 100644 --- a/utils.py +++ b/utils.py @@ -7,6 +7,7 @@ import matplotlib.pyplot as plt from dataclasses import dataclass import primitive_fucntions as pf +import importlib # ---------------------------------------------------------------------# @@ -133,3 +134,36 @@ def get_elapsed_time(self): if self._running: return time.perf_counter() - self._start_time return self._elapsed_time + +class KComplexity: + def __init__(self): + self.prim = importlib.import_module('primitive_fucntions') + self.call_counts = {} + self._wrap_prim_functions() + + def _wrap_prim_functions(self): + for name in dir(self.prim): + func = getattr(self.prim, name) + if callable(func) and not name.startswith("__"): + self.call_counts[name] = 0 + wrapper_func = self._make_wrapper(func, name) + setattr(self.prim, name, wrapper_func) + + def _make_wrapper(self, func, name): + def wrapper(*args, **kwargs): + self.call_counts[name] += 1 + return func(*args, **kwargs) + return wrapper + + """get dictionary of each prim function call count""" + def get_prim_counts(self): + return dict(self.call_counts) + + """get total number of prim function calls""" + def get_k_complexity(self): + return sum(self.call_counts.values()) + + """reset all prim function call counts to zero""" + def reset(self): + for key in self.call_counts: + self.call_counts[key] = 0 \ No newline at end of file From 6cc47f148f52179870b276bd1500426031e50cd1 Mon Sep 17 00:00:00 2001 From: LuckyBunnyLee Date: Mon, 23 Jun 2025 20:02:15 -0700 Subject: [PATCH 2/8] new changes --- cog.py | 21 +++++++++++++++++++++ experiments.ipynb | 44 ++++++++++++++++++++++++++++---------------- playground.ipynb | 4 ++-- utils.py | 16 ++++++++++++++-- 4 files changed, 65 insertions(+), 20 deletions(-) create mode 100644 cog.py diff --git a/cog.py b/cog.py new file mode 100644 index 0000000..6ccf1bd --- /dev/null +++ b/cog.py @@ -0,0 +1,21 @@ +from utils import Element, KComplexity +import primitive_fucntions as pf + +a = Element("a", 1, "red") +b = Element("b", 2, "blue") +c = Element("c", 3, "green") +d = Element("d", 4, "yellow") + +Elements = {a, b, c, d} + +def cog_1(E): + pf.sample(E) + among_us = [] + pf.add(a, among_us) + pf.add(pf.sample(E), among_us) + pf.remove(b, among_us) + +kc = KComplexity() +cog_1(Elements) +print(kc.get_k_complexity()) +print(kc.get_prim_counts()) \ No newline at end of file diff --git a/experiments.ipynb b/experiments.ipynb index 0562298..d3cfb7a 100644 --- a/experiments.ipynb +++ b/experiments.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 11, + "execution_count": 8, "id": "08bf7d5a", "metadata": {}, "outputs": [], @@ -19,7 +19,7 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 9, "id": "cd152c0d", "metadata": {}, "outputs": [], @@ -40,10 +40,22 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 12, "id": "5bfc8429", "metadata": {}, - "outputs": [], + "outputs": [ + { + "ename": "TypeError", + "evalue": "unhashable type: 'Element'", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mTypeError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[1;32mIn[12], line 1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m train_1 \u001b[38;5;241m=\u001b[39m {a,b,c,d}\n\u001b[0;32m 2\u001b[0m train_2 \u001b[38;5;241m=\u001b[39m {a,b,e,f}\n\u001b[0;32m 3\u001b[0m test_1 \u001b[38;5;241m=\u001b[39m {c,d,e,f}\n", + "\u001b[1;31mTypeError\u001b[0m: unhashable type: 'Element'" + ] + } + ], "source": [ "train_1 = {a,b,c,d}\n", "train_2 = {a,b,e,f}\n", @@ -65,7 +77,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "id": "88c86b73", "metadata": {}, "outputs": [], @@ -75,7 +87,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "id": "321f3986-476b-44b9-affe-caa29093b36a", "metadata": {}, "outputs": [], @@ -94,7 +106,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "id": "b3cbc0bd", "metadata": {}, "outputs": [], @@ -104,7 +116,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "id": "84dc2684-1ed4-41cf-9f24-5b81b4f55864", "metadata": { "scrolled": true @@ -127,7 +139,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "id": "164196ea-7f89-400f-bdaf-0b57b53bf1d6", "metadata": {}, "outputs": [], @@ -144,7 +156,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": null, "id": "6bef8a1f-c98d-4e78-bffa-7d867276314e", "metadata": {}, "outputs": [ @@ -181,7 +193,7 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": null, "id": "42551054", "metadata": {}, "outputs": [], @@ -209,7 +221,7 @@ }, { "cell_type": "code", - "execution_count": 71, + "execution_count": null, "id": "3712fe91", "metadata": {}, "outputs": [], @@ -219,7 +231,7 @@ }, { "cell_type": "code", - "execution_count": 72, + "execution_count": null, "id": "3a971260", "metadata": {}, "outputs": [ @@ -247,7 +259,7 @@ }, { "cell_type": "code", - "execution_count": 74, + "execution_count": null, "id": "7f77d49a", "metadata": {}, "outputs": [ @@ -281,7 +293,7 @@ ], "metadata": { "kernelspec": { - "display_name": ".venv", + "display_name": "lot_venv", "language": "python", "name": "python3" }, @@ -295,7 +307,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.13.2" + "version": "3.13.5" } }, "nbformat": 4, diff --git a/playground.ipynb b/playground.ipynb index ffece1a..adbabfe 100644 --- a/playground.ipynb +++ b/playground.ipynb @@ -210,7 +210,7 @@ ], "metadata": { "kernelspec": { - "display_name": ".venv", + "display_name": "lot_venv", "language": "python", "name": "python3" }, @@ -224,7 +224,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.13.2" + "version": "3.13.5" } }, "nbformat": 4, diff --git a/utils.py b/utils.py index 7b3d0d2..228dc01 100644 --- a/utils.py +++ b/utils.py @@ -11,6 +11,7 @@ # ---------------------------------------------------------------------# +""" @dataclass class Element: # n-dimensional element name : str @@ -20,6 +21,17 @@ def __repr__(self): return f"Element(object={self.name}, attribute 1={self.attribute1}, attribute 2={self.attribute2})" def __str__(self): return f"{self.name}, {self.attribute1}, {self.attribute2})" +""" + +class Element: # n-dimensional element + def __init__(self, name, attribute1, attribute2=None): + self.name = name + self.attribute1 = attribute1 + self.attribute2 = attribute2 + def __repr__(self): + return f"Element(object={self.name}, attribute 1={self.attribute1}, attribute 2={self.attribute2})" + def __str__(self): + return f"{self.name}, {self.attribute1}, {self.attribute2})" @dataclass class Associations: # n-dimensional association @@ -54,8 +66,8 @@ def build_graph(self): G.add_edge(obj.name, obj.attribute2, label="attribute") if self.associations: self.associations.build_updates(G) # Build associations - if self.graph: - self.graph = G + if self.graph: + self.graph = G return G def visualize(self): plt.figure(figsize=(10, 8)) From 8db9dab0a06df9f82bbd3908a60309f1acafdc88 Mon Sep 17 00:00:00 2001 From: LuckyBunnyLee Date: Tue, 24 Jun 2025 00:29:00 -0700 Subject: [PATCH 3/8] among us --- cog_testing.ipynb | 0 primitive_fucntions.py | 7 ++++--- 2 files changed, 4 insertions(+), 3 deletions(-) create mode 100644 cog_testing.ipynb diff --git a/cog_testing.ipynb b/cog_testing.ipynb new file mode 100644 index 0000000..e69de29 diff --git a/primitive_fucntions.py b/primitive_fucntions.py index 55fd25c..c86f0e7 100644 --- a/primitive_fucntions.py +++ b/primitive_fucntions.py @@ -114,9 +114,10 @@ def write_all(S, bias, type): """Returns a sequential list of all members of a type Time complexity: O(n) where n is number of tokens""" result = [] - for element in S: - if getattr(element, bias) == type: - result = pair(result, element) + #for element in S: + #if getattr(element, bias) == type: + #result = pair(result, element) + type_elements = [u for u, v, d in S.edges(data=True) if v == type and d["label"] == bias] return result # Additional functions From 4338f481f5f0922bb6645ebe23cca60b9a3d01d7 Mon Sep 17 00:00:00 2001 From: LuckyBunnyLee Date: Tue, 24 Jun 2025 19:56:27 -0700 Subject: [PATCH 4/8] among us --- cog_testing.ipynb | 19 +++++++++++++++++ experiments.ipynb | 54 ++++++++++++++++++++++++----------------------- 2 files changed, 47 insertions(+), 26 deletions(-) diff --git a/cog_testing.ipynb b/cog_testing.ipynb index e69de29..9bf8f20 100644 --- a/cog_testing.ipynb +++ b/cog_testing.ipynb @@ -0,0 +1,19 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "id": "081f22f1", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "language_info": { + "name": "python" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/experiments.ipynb b/experiments.ipynb index d3cfb7a..6420776 100644 --- a/experiments.ipynb +++ b/experiments.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 8, + "execution_count": 2, "id": "08bf7d5a", "metadata": {}, "outputs": [], @@ -19,7 +19,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 3, "id": "cd152c0d", "metadata": {}, "outputs": [], @@ -40,22 +40,10 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 4, "id": "5bfc8429", "metadata": {}, - "outputs": [ - { - "ename": "TypeError", - "evalue": "unhashable type: 'Element'", - "output_type": "error", - "traceback": [ - "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[1;31mTypeError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[1;32mIn[12], line 1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m train_1 \u001b[38;5;241m=\u001b[39m {a,b,c,d}\n\u001b[0;32m 2\u001b[0m train_2 \u001b[38;5;241m=\u001b[39m {a,b,e,f}\n\u001b[0;32m 3\u001b[0m test_1 \u001b[38;5;241m=\u001b[39m {c,d,e,f}\n", - "\u001b[1;31mTypeError\u001b[0m: unhashable type: 'Element'" - ] - } - ], + "outputs": [], "source": [ "train_1 = {a,b,c,d}\n", "train_2 = {a,b,e,f}\n", @@ -77,7 +65,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "id": "88c86b73", "metadata": {}, "outputs": [], @@ -87,7 +75,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "id": "321f3986-476b-44b9-affe-caa29093b36a", "metadata": {}, "outputs": [], @@ -106,7 +94,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 7, "id": "b3cbc0bd", "metadata": {}, "outputs": [], @@ -116,7 +104,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "id": "84dc2684-1ed4-41cf-9f24-5b81b4f55864", "metadata": { "scrolled": true @@ -124,7 +112,7 @@ "outputs": [ { "data": { - "image/png": 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" ] @@ -139,7 +127,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "id": "164196ea-7f89-400f-bdaf-0b57b53bf1d6", "metadata": {}, "outputs": [], @@ -156,7 +144,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 10, "id": "6bef8a1f-c98d-4e78-bffa-7d867276314e", "metadata": {}, "outputs": [ @@ -193,7 +181,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 11, "id": "42551054", "metadata": {}, "outputs": [], @@ -221,10 +209,24 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 12, "id": "3712fe91", "metadata": {}, - "outputs": [], + "outputs": [ + { + "ename": "AttributeError", + "evalue": "'set' object has no attribute 'elements'", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mAttributeError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[1;32mIn[12], line 1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m times \u001b[38;5;241m=\u001b[39m \u001b[43mrunReordering\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtrain_1\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m20\u001b[39;49m\u001b[43m)\u001b[49m\n", + "Cell \u001b[1;32mIn[11], line 6\u001b[0m, in \u001b[0;36mrunReordering\u001b[1;34m(element_set, n_runs)\u001b[0m\n\u001b[0;32m 4\u001b[0m time_list \u001b[38;5;241m=\u001b[39m []\n\u001b[0;32m 5\u001b[0m \u001b[38;5;66;03m# 1-D\u001b[39;00m\n\u001b[1;32m----> 6\u001b[0m time_list\u001b[38;5;241m.\u001b[39mappend(\u001b[43mcf\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43miterate\u001b[49m\u001b[43m(\u001b[49m\u001b[43melement_set\u001b[49m\u001b[43m)\u001b[49m[\u001b[38;5;241m1\u001b[39m])\n\u001b[0;32m 7\u001b[0m time_list\u001b[38;5;241m.\u001b[39mappend(cf\u001b[38;5;241m.\u001b[39mpalindrome(element_set)[\u001b[38;5;241m1\u001b[39m])\n\u001b[0;32m 8\u001b[0m time_list\u001b[38;5;241m.\u001b[39mappend(cf\u001b[38;5;241m.\u001b[39malternate(element_set)[\u001b[38;5;241m1\u001b[39m])\n", + "File \u001b[1;32mc:\\Users\\desig\\Desktop\\vs code\\LoT\\LoT-modeling\\cognitive_functions.py:10\u001b[0m, in \u001b[0;36miterate\u001b[1;34m(S)\u001b[0m\n\u001b[0;32m 7\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21miterate\u001b[39m(S: ElementSet): \u001b[38;5;66;03m# 112233 \u001b[39;00m\n\u001b[0;32m 8\u001b[0m \n\u001b[0;32m 9\u001b[0m \u001b[38;5;66;03m# preprocessing (not part of measured cognitive process)\u001b[39;00m\n\u001b[1;32m---> 10\u001b[0m n \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mlen\u001b[39m(\u001b[43mS\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43melements\u001b[49m) \u001b[38;5;66;03m# number of elements in the set\u001b[39;00m\n\u001b[0;32m 11\u001b[0m chunks \u001b[38;5;241m=\u001b[39m defaultdict(\u001b[38;5;28mlist\u001b[39m) \n\u001b[0;32m 12\u001b[0m stopwatch \u001b[38;5;241m=\u001b[39m Stopwatch()\n", + "\u001b[1;31mAttributeError\u001b[0m: 'set' object has no attribute 'elements'" + ] + } + ], "source": [ "times = runReordering(train_1, 20)" ] From 7c31455b837267c8c95d2428bcff16fbf3a33562 Mon Sep 17 00:00:00 2001 From: LuckyBunnyLee Date: Tue, 24 Jun 2025 20:33:36 -0700 Subject: [PATCH 5/8] new commit --- cog_testing.ipynb | 434 +++++++++++++++++++++++++++++++++++++++++++++- experiments.ipynb | 28 +-- playground.ipynb | 23 +-- 3 files changed, 458 insertions(+), 27 deletions(-) diff --git a/cog_testing.ipynb b/cog_testing.ipynb index 9bf8f20..8eb1c54 100644 --- a/cog_testing.ipynb +++ b/cog_testing.ipynb @@ -2,16 +2,444 @@ "cells": [ { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "id": "081f22f1", "metadata": {}, "outputs": [], - "source": [] + "source": [ + "import numpy as np\n", + "import seaborn as sns\n", + "import matplotlib.pyplot as plt\n", + "import pandas as pd\n", + "from utils import Element\n", + "import warnings\n", + "import cognitive_functions as cf\n", + "warnings.filterwarnings('ignore')" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "831c5eaf", + "metadata": {}, + "outputs": [], + "source": [ + "a = Element('A1','A','1')\n", + "b = Element('A2','A','2')\n", + "c = Element('B1','B','1')\n", + "d = Element('B2','B','2')\n", + "e = Element('C1','C','1')\n", + "f = Element('C2','C','2')\n", + "g = Element('D1','D','1')\n", + "h = Element('D2','D','2')\n", + "i = Element('E1','E','1')\n", + "j = Element('E2','E','2')\n", + "k = Element('F1','F','1')\n", + "l = Element('F2','F','2')" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "8e512e91", + "metadata": {}, + "outputs": [], + "source": [ + "train_1 = {a,b,c,d}\n", + "train_2 = {a,b,e,f}\n", + "test_1 = {c,d,e,f}\n", + "test_2 = {a,b,c,d,e,f}\n", + "test_3 = {g,h,i,j}\n", + "test_4 = {g,h,k,l}\n", + "test_5 = {i,j,k,l}\n", + "test_6 = {g,h,i,j,k,l}" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "030b28dc", + "metadata": {}, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'KComplexity' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mNameError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[1;32mIn[4], line 10\u001b[0m\n\u001b[0;32m 7\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21;01mcognitive_functions\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mas\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21;01mcf\u001b[39;00m\n\u001b[0;32m 8\u001b[0m warnings\u001b[38;5;241m.\u001b[39mfilterwarnings(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mignore\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[1;32m---> 10\u001b[0m kc \u001b[38;5;241m=\u001b[39m \u001b[43mKComplexity\u001b[49m()\n\u001b[0;32m 11\u001b[0m kc\u001b[38;5;241m.\u001b[39mreset()\n\u001b[0;32m 12\u001b[0m cf\u001b[38;5;241m.\u001b[39miterate(train_1)\n", + "\u001b[1;31mNameError\u001b[0m: name 'KComplexity' is not defined" + ] + } + ], + "source": [ + "import numpy as np\n", + "import seaborn as sns\n", + "import matplotlib.pyplot as plt\n", + "import pandas as pd\n", + "from utils import Element\n", + "import warnings\n", + "import cognitive_functions as cf\n", + "warnings.filterwarnings('ignore')\n", + "\n", + "kc = KComplexity()\n", + "kc.reset()\n", + "cf.iterate(train_1)\n", + "kc.get_k_complexity()\n", + "kc.get_prim_counts()\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "034a7977", + "metadata": {}, + "outputs": [ + { + "ename": "AttributeError", + "evalue": "'set' object has no attribute 'edges'", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mAttributeError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[1;32mIn[21], line 12\u001b[0m\n\u001b[0;32m 10\u001b[0m kc \u001b[38;5;241m=\u001b[39m KComplexity()\n\u001b[0;32m 11\u001b[0m kc\u001b[38;5;241m.\u001b[39mreset()\n\u001b[1;32m---> 12\u001b[0m \u001b[43mcf\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mpalindrome\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtrain_1\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 13\u001b[0m kc\u001b[38;5;241m.\u001b[39mget_k_complexity()\n\u001b[0;32m 14\u001b[0m kc\u001b[38;5;241m.\u001b[39mget_prim_counts()\n", + "File \u001b[1;32mc:\\Users\\desig\\Desktop\\vs code\\LoT\\LoT-modeling\\cognitive_functions.py:67\u001b[0m, in \u001b[0;36mpalindrome\u001b[1;34m(S)\u001b[0m\n\u001b[0;32m 65\u001b[0m pf\u001b[38;5;241m.\u001b[39msetminus(S, element)\n\u001b[0;32m 66\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m _ \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mrange\u001b[39m(n):\n\u001b[1;32m---> 67\u001b[0m element \u001b[38;5;241m=\u001b[39m \u001b[43mpf\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mwrite_random\u001b[49m\u001b[43m(\u001b[49m\u001b[43mS\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbias\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mgetattr\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mbasis\u001b[49m\u001b[43m[\u001b[49m\u001b[43mn\u001b[49m\u001b[38;5;241;43m-\u001b[39;49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[38;5;241;43m-\u001b[39;49m\u001b[43m_\u001b[49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbias\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 68\u001b[0m pf\u001b[38;5;241m.\u001b[39mpair(rev,element)\n\u001b[0;32m 69\u001b[0m pf\u001b[38;5;241m.\u001b[39msetminus(S, element)\n", + "File \u001b[1;32mc:\\Users\\desig\\Desktop\\vs code\\LoT\\LoT-modeling\\utils.py:167\u001b[0m, in \u001b[0;36mKComplexity._make_wrapper..wrapper\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m 165\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21mwrapper\u001b[39m(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[0;32m 166\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcall_counts[name] \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m\n\u001b[1;32m--> 167\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[1;32mc:\\Users\\desig\\Desktop\\vs code\\LoT\\LoT-modeling\\utils.py:167\u001b[0m, in \u001b[0;36mKComplexity._make_wrapper..wrapper\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m 165\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21mwrapper\u001b[39m(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[0;32m 166\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcall_counts[name] \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m\n\u001b[1;32m--> 167\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", + " \u001b[1;31m[... skipping similar frames: KComplexity._make_wrapper..wrapper at line 167 (1 times)]\u001b[0m\n", + "File \u001b[1;32mc:\\Users\\desig\\Desktop\\vs code\\LoT\\LoT-modeling\\utils.py:167\u001b[0m, in \u001b[0;36mKComplexity._make_wrapper..wrapper\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m 165\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21mwrapper\u001b[39m(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[0;32m 166\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcall_counts[name] \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m\n\u001b[1;32m--> 167\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[1;32mc:\\Users\\desig\\Desktop\\vs code\\LoT\\LoT-modeling\\primitive_fucntions.py:97\u001b[0m, in \u001b[0;36mwrite_random\u001b[1;34m(G, bias, type)\u001b[0m\n\u001b[0;32m 92\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"Returns one unused member of particular type\u001b[39;00m\n\u001b[0;32m 93\u001b[0m \u001b[38;5;124;03mTime complexity: O(n) to filter tokens\"\"\"\u001b[39;00m\n\u001b[0;32m 94\u001b[0m \u001b[38;5;66;03m# for element in S:\u001b[39;00m\n\u001b[0;32m 95\u001b[0m \u001b[38;5;66;03m# if getattr(element, bias) == type:\u001b[39;00m\n\u001b[0;32m 96\u001b[0m \u001b[38;5;66;03m# return element\u001b[39;00m\n\u001b[1;32m---> 97\u001b[0m type_elements \u001b[38;5;241m=\u001b[39m [u \u001b[38;5;28;01mfor\u001b[39;00m u, v, d \u001b[38;5;129;01min\u001b[39;00m \u001b[43mG\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43medges\u001b[49m(data\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m) \u001b[38;5;28;01mif\u001b[39;00m v \u001b[38;5;241m==\u001b[39m \u001b[38;5;28mtype\u001b[39m \u001b[38;5;129;01mand\u001b[39;00m d[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mlabel\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m==\u001b[39m bias]\n\u001b[0;32m 99\u001b[0m \u001b[38;5;66;03m### WRITE CODE\u001b[39;00m\n\u001b[0;32m 100\u001b[0m \u001b[38;5;66;03m### maybe add a random list shuffling thing here\u001b[39;00m\n\u001b[0;32m 101\u001b[0m \u001b[38;5;66;03m### to make it less predictable\u001b[39;00m\n\u001b[0;32m 103\u001b[0m \u001b[38;5;28;01mpass\u001b[39;00m\n", + "\u001b[1;31mAttributeError\u001b[0m: 'set' object has no attribute 'edges'" + ] + } + ], + "source": [ + "import numpy as np\n", + "import seaborn as sns\n", + "import matplotlib.pyplot as plt\n", + "import pandas as pd\n", + "from utils import Element\n", + "import warnings\n", + "import cognitive_functions as cf\n", + "warnings.filterwarnings('ignore')\n", + "\n", + "kc = KComplexity()\n", + "kc.reset()\n", + "cf.palindrome(train_1)\n", + "kc.get_k_complexity()\n", + "kc.get_prim_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "df882383", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'add': 0,\n", + " 'append': 0,\n", + " 'check_if_same_type': 0,\n", + " 'dim_set': 0,\n", + " 'flip': 1,\n", + " 'implement': 0,\n", + " 'list_create': 0,\n", + " 'merge': 0,\n", + " 'pair': 1,\n", + " 'remove': 0,\n", + " 'remove_item': 0,\n", + " 'sample': 1,\n", + " 'setminus': 1,\n", + " 'write_all': 0,\n", + " 'write_all_set': 0,\n", + " 'write_random': 0}" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import numpy as np\n", + "import seaborn as sns\n", + "import matplotlib.pyplot as plt\n", + "import pandas as pd\n", + "from utils import Element\n", + "import warnings\n", + "import cognitive_functions as cf\n", + "warnings.filterwarnings('ignore')\n", + "\n", + "kc = KComplexity()\n", + "kc.reset()\n", + "cf.alternate(train_1)\n", + "kc.get_k_complexity()\n", + "kc.get_prim_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "da9b45ff", + "metadata": {}, + "outputs": [ + { + "ename": "TypeError", + "evalue": "chaining() missing 1 required positional argument: 'associations'", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mTypeError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[1;32mIn[29], line 12\u001b[0m\n\u001b[0;32m 10\u001b[0m kc \u001b[38;5;241m=\u001b[39m KComplexity()\n\u001b[0;32m 11\u001b[0m kc\u001b[38;5;241m.\u001b[39mreset()\n\u001b[1;32m---> 12\u001b[0m \u001b[43mcf\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mchaining\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtrain_1\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 13\u001b[0m kc\u001b[38;5;241m.\u001b[39mget_k_complexity()\n\u001b[0;32m 14\u001b[0m kc\u001b[38;5;241m.\u001b[39mget_prim_counts()\n", + "\u001b[1;31mTypeError\u001b[0m: chaining() missing 1 required positional argument: 'associations'" + ] + } + ], + "source": [ + "import numpy as np\n", + "import seaborn as sns\n", + "import matplotlib.pyplot as plt\n", + "import pandas as pd\n", + "from utils import Element\n", + "import warnings\n", + "import cognitive_functions as cf\n", + "warnings.filterwarnings('ignore')\n", + "\n", + "kc = KComplexity()\n", + "kc.reset()\n", + "cf.chaining(train_1)\n", + "kc.get_k_complexity()\n", + "kc.get_prim_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "590c9d20", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'add': 0,\n", + " 'append': 0,\n", + " 'check_if_same_type': 0,\n", + " 'dim_set': 0,\n", + " 'flip': 0,\n", + " 'implement': 0,\n", + " 'list_create': 0,\n", + " 'merge': 0,\n", + " 'pair': 0,\n", + " 'remove': 0,\n", + " 'remove_item': 0,\n", + " 'sample': 0,\n", + " 'setminus': 0,\n", + " 'write_all': 0,\n", + " 'write_all_set': 0,\n", + " 'write_random': 0}" + ] + }, + "execution_count": 30, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import numpy as np\n", + "import seaborn as sns\n", + "import matplotlib.pyplot as plt\n", + "import pandas as pd\n", + "from utils import Element\n", + "import warnings\n", + "import cognitive_functions as cf\n", + "warnings.filterwarnings('ignore')\n", + "\n", + "kc = KComplexity()\n", + "kc.reset()\n", + "cf.seriate(train_1)\n", + "kc.get_k_complexity()\n", + "kc.get_prim_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "7e2d4e07", + "metadata": {}, + "outputs": [ + { + "ename": "AttributeError", + "evalue": "'set' object has no attribute 'edges'", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mAttributeError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[1;32mIn[31], line 12\u001b[0m\n\u001b[0;32m 10\u001b[0m kc \u001b[38;5;241m=\u001b[39m KComplexity()\n\u001b[0;32m 11\u001b[0m kc\u001b[38;5;241m.\u001b[39mreset()\n\u001b[1;32m---> 12\u001b[0m \u001b[43mcf\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mserial_crossed\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtrain_1\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 13\u001b[0m kc\u001b[38;5;241m.\u001b[39mget_k_complexity()\n\u001b[0;32m 14\u001b[0m kc\u001b[38;5;241m.\u001b[39mget_prim_counts()\n", + "File \u001b[1;32mc:\\Users\\desig\\Desktop\\vs code\\LoT\\LoT-modeling\\cognitive_functions.py:145\u001b[0m, in \u001b[0;36mserial_crossed\u001b[1;34m(S)\u001b[0m\n\u001b[0;32m 143\u001b[0m pf\u001b[38;5;241m.\u001b[39msetminus(S, element)\n\u001b[0;32m 144\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m _ \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mrange\u001b[39m(n):\n\u001b[1;32m--> 145\u001b[0m element \u001b[38;5;241m=\u001b[39m \u001b[43mpf\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mwrite_random\u001b[49m\u001b[43m(\u001b[49m\u001b[43mS\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbias\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mgetattr\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mresult\u001b[49m\u001b[43m[\u001b[49m\u001b[43m_\u001b[49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbias\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 146\u001b[0m pf\u001b[38;5;241m.\u001b[39mpair(result, element)\n\u001b[0;32m 147\u001b[0m pf\u001b[38;5;241m.\u001b[39msetminus(S, element)\n", + "File \u001b[1;32mc:\\Users\\desig\\Desktop\\vs code\\LoT\\LoT-modeling\\utils.py:167\u001b[0m, in \u001b[0;36mKComplexity._make_wrapper..wrapper\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m 165\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21mwrapper\u001b[39m(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[0;32m 166\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcall_counts[name] \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m\n\u001b[1;32m--> 167\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[1;32mc:\\Users\\desig\\Desktop\\vs code\\LoT\\LoT-modeling\\utils.py:167\u001b[0m, in \u001b[0;36mKComplexity._make_wrapper..wrapper\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m 165\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21mwrapper\u001b[39m(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[0;32m 166\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcall_counts[name] \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m\n\u001b[1;32m--> 167\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", + " \u001b[1;31m[... skipping similar frames: KComplexity._make_wrapper..wrapper at line 167 (9 times)]\u001b[0m\n", + "File \u001b[1;32mc:\\Users\\desig\\Desktop\\vs code\\LoT\\LoT-modeling\\utils.py:167\u001b[0m, in \u001b[0;36mKComplexity._make_wrapper..wrapper\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m 165\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21mwrapper\u001b[39m(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[0;32m 166\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcall_counts[name] \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m\n\u001b[1;32m--> 167\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[1;32mc:\\Users\\desig\\Desktop\\vs code\\LoT\\LoT-modeling\\primitive_fucntions.py:97\u001b[0m, in \u001b[0;36mwrite_random\u001b[1;34m(G, bias, type)\u001b[0m\n\u001b[0;32m 92\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"Returns one unused member of particular type\u001b[39;00m\n\u001b[0;32m 93\u001b[0m \u001b[38;5;124;03mTime complexity: O(n) to filter tokens\"\"\"\u001b[39;00m\n\u001b[0;32m 94\u001b[0m \u001b[38;5;66;03m# for element in S:\u001b[39;00m\n\u001b[0;32m 95\u001b[0m \u001b[38;5;66;03m# if getattr(element, bias) == type:\u001b[39;00m\n\u001b[0;32m 96\u001b[0m \u001b[38;5;66;03m# return element\u001b[39;00m\n\u001b[1;32m---> 97\u001b[0m type_elements \u001b[38;5;241m=\u001b[39m [u \u001b[38;5;28;01mfor\u001b[39;00m u, v, d \u001b[38;5;129;01min\u001b[39;00m \u001b[43mG\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43medges\u001b[49m(data\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m) \u001b[38;5;28;01mif\u001b[39;00m v \u001b[38;5;241m==\u001b[39m \u001b[38;5;28mtype\u001b[39m \u001b[38;5;129;01mand\u001b[39;00m d[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mlabel\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m==\u001b[39m bias]\n\u001b[0;32m 99\u001b[0m \u001b[38;5;66;03m### WRITE CODE\u001b[39;00m\n\u001b[0;32m 100\u001b[0m \u001b[38;5;66;03m### maybe add a random list shuffling thing here\u001b[39;00m\n\u001b[0;32m 101\u001b[0m \u001b[38;5;66;03m### to make it less predictable\u001b[39;00m\n\u001b[0;32m 103\u001b[0m \u001b[38;5;28;01mpass\u001b[39;00m\n", + "\u001b[1;31mAttributeError\u001b[0m: 'set' object has no attribute 'edges'" + ] + } + ], + "source": [ + "import numpy as np\n", + "import seaborn as sns\n", + "import matplotlib.pyplot as plt\n", + "import pandas as pd\n", + "from utils import Element\n", + "import warnings\n", + "import cognitive_functions as cf\n", + "warnings.filterwarnings('ignore')\n", + "\n", + "kc = KComplexity()\n", + "kc.reset()\n", + "cf.serial_crossed(train_1)\n", + "kc.get_k_complexity()\n", + "kc.get_prim_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "092f34e3", + "metadata": {}, + "outputs": [ + { + "ename": "KeyboardInterrupt", + "evalue": "", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)", + "Cell \u001b[1;32mIn[32], line 12\u001b[0m\n\u001b[0;32m 10\u001b[0m kc \u001b[38;5;241m=\u001b[39m KComplexity()\n\u001b[0;32m 11\u001b[0m kc\u001b[38;5;241m.\u001b[39mreset()\n\u001b[1;32m---> 12\u001b[0m \u001b[43mcf\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcenter_embedded\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtrain_1\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 13\u001b[0m kc\u001b[38;5;241m.\u001b[39mget_k_complexity()\n\u001b[0;32m 14\u001b[0m kc\u001b[38;5;241m.\u001b[39mget_prim_counts()\n", + "File \u001b[1;32mc:\\Users\\desig\\Desktop\\vs code\\LoT\\LoT-modeling\\cognitive_functions.py:158\u001b[0m, in \u001b[0;36mcenter_embedded\u001b[1;34m(S)\u001b[0m\n\u001b[0;32m 156\u001b[0m result \u001b[38;5;241m=\u001b[39m []\n\u001b[0;32m 157\u001b[0m \u001b[38;5;28;01mwhile\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(S) \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[1;32m--> 158\u001b[0m element \u001b[38;5;241m=\u001b[39m \u001b[43mpf\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msample\u001b[49m\u001b[43m(\u001b[49m\u001b[43mS\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 159\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(result) \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m0\u001b[39m \u001b[38;5;129;01mor\u001b[39;00m pf\u001b[38;5;241m.\u001b[39mcheck_if_same_type(element, result[\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m], bias[\u001b[38;5;241m0\u001b[39m]):\n\u001b[0;32m 160\u001b[0m pf\u001b[38;5;241m.\u001b[39mpair(result, element)\n", + "File \u001b[1;32mc:\\Users\\desig\\Desktop\\vs code\\LoT\\LoT-modeling\\utils.py:167\u001b[0m, in \u001b[0;36mKComplexity._make_wrapper..wrapper\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m 165\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21mwrapper\u001b[39m(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[0;32m 166\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcall_counts[name] \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m\n\u001b[1;32m--> 167\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[1;32mc:\\Users\\desig\\Desktop\\vs code\\LoT\\LoT-modeling\\utils.py:167\u001b[0m, in \u001b[0;36mKComplexity._make_wrapper..wrapper\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m 165\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21mwrapper\u001b[39m(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[0;32m 166\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcall_counts[name] \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m\n\u001b[1;32m--> 167\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", + " \u001b[1;31m[... skipping similar frames: KComplexity._make_wrapper..wrapper at line 167 (10 times)]\u001b[0m\n", + "File \u001b[1;32mc:\\Users\\desig\\Desktop\\vs code\\LoT\\LoT-modeling\\utils.py:167\u001b[0m, in \u001b[0;36mKComplexity._make_wrapper..wrapper\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m 165\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21mwrapper\u001b[39m(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[0;32m 166\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcall_counts[name] \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m\n\u001b[1;32m--> 167\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[1;32mc:\\Users\\desig\\Desktop\\vs code\\LoT\\LoT-modeling\\primitive_fucntions.py:45\u001b[0m, in \u001b[0;36msample\u001b[1;34m(collection)\u001b[0m\n\u001b[0;32m 42\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[0;32m 44\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(collection, \u001b[38;5;28mset\u001b[39m):\n\u001b[1;32m---> 45\u001b[0m collection \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mtuple\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mcollection\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;66;03m# Convert to tuple for sampling\u001b[39;00m\n\u001b[0;32m 47\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m random\u001b[38;5;241m.\u001b[39msample(collection, \u001b[38;5;241m1\u001b[39m)[\u001b[38;5;241m0\u001b[39m]\n", + "\u001b[1;31mKeyboardInterrupt\u001b[0m: " + ] + } + ], + "source": [ + "import numpy as np\n", + "import seaborn as sns\n", + "import matplotlib.pyplot as plt\n", + "import pandas as pd\n", + "from utils import Element\n", + "import warnings\n", + "import cognitive_functions as cf\n", + "warnings.filterwarnings('ignore')\n", + "\n", + "kc = KComplexity()\n", + "kc.reset()\n", + "cf.center_embedded(train_1)\n", + "kc.get_k_complexity()\n", + "kc.get_prim_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ca81ceaf", + "metadata": {}, + "outputs": [ + { + "ename": "AttributeError", + "evalue": "'set' object has no attribute 'edges'", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mAttributeError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[1;32mIn[33], line 12\u001b[0m\n\u001b[0;32m 10\u001b[0m kc \u001b[38;5;241m=\u001b[39m KComplexity()\n\u001b[0;32m 11\u001b[0m kc\u001b[38;5;241m.\u001b[39mreset()\n\u001b[1;32m---> 12\u001b[0m \u001b[43mcf\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtail_recursive\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtrain_1\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 13\u001b[0m kc\u001b[38;5;241m.\u001b[39mget_k_complexity()\n\u001b[0;32m 14\u001b[0m kc\u001b[38;5;241m.\u001b[39mget_prim_counts()\n", + "File \u001b[1;32mc:\\Users\\desig\\Desktop\\vs code\\LoT\\LoT-modeling\\cognitive_functions.py:178\u001b[0m, in \u001b[0;36mtail_recursive\u001b[1;34m(S)\u001b[0m\n\u001b[0;32m 176\u001b[0m element \u001b[38;5;241m=\u001b[39m pf\u001b[38;5;241m.\u001b[39msample(S)\n\u001b[0;32m 177\u001b[0m pf\u001b[38;5;241m.\u001b[39msetminus(S, element)\n\u001b[1;32m--> 178\u001b[0m paired_element \u001b[38;5;241m=\u001b[39m \u001b[43mpf\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mwrite_random\u001b[49m\u001b[43m(\u001b[49m\u001b[43mS\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbias\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mgetattr\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43melement\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbias\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 179\u001b[0m result \u001b[38;5;241m=\u001b[39m pf\u001b[38;5;241m.\u001b[39mappend(result, pf\u001b[38;5;241m.\u001b[39mmerge(element, paired_element))\n\u001b[0;32m 180\u001b[0m pf\u001b[38;5;241m.\u001b[39msetminus(S, paired_element)\n", + "File \u001b[1;32mc:\\Users\\desig\\Desktop\\vs code\\LoT\\LoT-modeling\\utils.py:167\u001b[0m, in \u001b[0;36mKComplexity._make_wrapper..wrapper\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m 165\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21mwrapper\u001b[39m(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[0;32m 166\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcall_counts[name] \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m\n\u001b[1;32m--> 167\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[1;32mc:\\Users\\desig\\Desktop\\vs code\\LoT\\LoT-modeling\\utils.py:167\u001b[0m, in \u001b[0;36mKComplexity._make_wrapper..wrapper\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m 165\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21mwrapper\u001b[39m(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[0;32m 166\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcall_counts[name] \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m\n\u001b[1;32m--> 167\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", + " \u001b[1;31m[... skipping similar frames: KComplexity._make_wrapper..wrapper at line 167 (11 times)]\u001b[0m\n", + "File \u001b[1;32mc:\\Users\\desig\\Desktop\\vs code\\LoT\\LoT-modeling\\utils.py:167\u001b[0m, in \u001b[0;36mKComplexity._make_wrapper..wrapper\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m 165\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21mwrapper\u001b[39m(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[0;32m 166\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcall_counts[name] \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m\n\u001b[1;32m--> 167\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[1;32mc:\\Users\\desig\\Desktop\\vs code\\LoT\\LoT-modeling\\primitive_fucntions.py:97\u001b[0m, in \u001b[0;36mwrite_random\u001b[1;34m(G, bias, type)\u001b[0m\n\u001b[0;32m 92\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"Returns one unused member of particular type\u001b[39;00m\n\u001b[0;32m 93\u001b[0m \u001b[38;5;124;03mTime complexity: O(n) to filter tokens\"\"\"\u001b[39;00m\n\u001b[0;32m 94\u001b[0m \u001b[38;5;66;03m# for element in S:\u001b[39;00m\n\u001b[0;32m 95\u001b[0m \u001b[38;5;66;03m# if getattr(element, bias) == type:\u001b[39;00m\n\u001b[0;32m 96\u001b[0m \u001b[38;5;66;03m# return element\u001b[39;00m\n\u001b[1;32m---> 97\u001b[0m type_elements \u001b[38;5;241m=\u001b[39m [u \u001b[38;5;28;01mfor\u001b[39;00m u, v, d \u001b[38;5;129;01min\u001b[39;00m \u001b[43mG\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43medges\u001b[49m(data\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m) \u001b[38;5;28;01mif\u001b[39;00m v \u001b[38;5;241m==\u001b[39m \u001b[38;5;28mtype\u001b[39m \u001b[38;5;129;01mand\u001b[39;00m d[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mlabel\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m==\u001b[39m bias]\n\u001b[0;32m 99\u001b[0m \u001b[38;5;66;03m### WRITE CODE\u001b[39;00m\n\u001b[0;32m 100\u001b[0m \u001b[38;5;66;03m### maybe add a random list shuffling thing here\u001b[39;00m\n\u001b[0;32m 101\u001b[0m \u001b[38;5;66;03m### to make it less predictable\u001b[39;00m\n\u001b[0;32m 103\u001b[0m \u001b[38;5;28;01mpass\u001b[39;00m\n", + "\u001b[1;31mAttributeError\u001b[0m: 'set' object has no attribute 'edges'" + ] + } + ], + "source": [ + "import numpy as np\n", + "import seaborn as sns\n", + "import matplotlib.pyplot as plt\n", + "import pandas as pd\n", + "from utils import Element\n", + "import warnings\n", + "import cognitive_functions as cf\n", + "warnings.filterwarnings('ignore')\n", + "\n", + "kc = KComplexity()\n", + "kc.reset()\n", + "cf.tail_recursive(train_1)\n", + "kc.get_k_complexity()\n", + "kc.get_prim_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c2134ce3", + "metadata": {}, + "outputs": [ + { + "ename": "TypeError", + "evalue": "find_bias() missing 1 required positional argument: 'clock'", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mTypeError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[1;32mIn[34], line 12\u001b[0m\n\u001b[0;32m 10\u001b[0m kc \u001b[38;5;241m=\u001b[39m KComplexity()\n\u001b[0;32m 11\u001b[0m kc\u001b[38;5;241m.\u001b[39mreset()\n\u001b[1;32m---> 12\u001b[0m \u001b[43mcf\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfind_bias\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtrain_1\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 13\u001b[0m kc\u001b[38;5;241m.\u001b[39mget_k_complexity()\n\u001b[0;32m 14\u001b[0m kc\u001b[38;5;241m.\u001b[39mget_prim_counts()\n", + "\u001b[1;31mTypeError\u001b[0m: find_bias() missing 1 required positional argument: 'clock'" + ] + } + ], + "source": [ + "import numpy as np\n", + "import seaborn as sns\n", + "import matplotlib.pyplot as plt\n", + "import pandas as pd\n", + "from utils import Element\n", + "import warnings\n", + "import cognitive_functions as cf\n", + "warnings.filterwarnings('ignore')\n", + "\n", + "kc = KComplexity()\n", + "kc.reset()\n", + "cf.find_bias(train_1)\n", + "kc.get_k_complexity()\n", + "kc.get_prim_counts()" + ] } ], "metadata": { + "kernelspec": { + "display_name": "lot_venv", + "language": "python", + "name": "python3" + }, "language_info": { - "name": "python" + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.13.5" } }, "nbformat": 4, diff --git a/experiments.ipynb b/experiments.ipynb index 6420776..ddf759e 100644 --- a/experiments.ipynb +++ b/experiments.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 2, + "execution_count": 1, "id": "08bf7d5a", "metadata": {}, "outputs": [], @@ -19,7 +19,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 2, "id": "cd152c0d", "metadata": {}, "outputs": [], @@ -40,7 +40,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 3, "id": "5bfc8429", "metadata": {}, "outputs": [], @@ -65,7 +65,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 4, "id": "88c86b73", "metadata": {}, "outputs": [], @@ -75,7 +75,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 5, "id": "321f3986-476b-44b9-affe-caa29093b36a", "metadata": {}, "outputs": [], @@ -94,7 +94,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 6, "id": "b3cbc0bd", "metadata": {}, "outputs": [], @@ -104,7 +104,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 7, "id": "84dc2684-1ed4-41cf-9f24-5b81b4f55864", "metadata": { "scrolled": true @@ -112,7 +112,7 @@ "outputs": [ { "data": { - "image/png": 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" ] @@ -127,7 +127,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 8, "id": "164196ea-7f89-400f-bdaf-0b57b53bf1d6", "metadata": {}, "outputs": [], @@ -144,7 +144,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 9, "id": "6bef8a1f-c98d-4e78-bffa-7d867276314e", "metadata": {}, "outputs": [ @@ -181,7 +181,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 10, "id": "42551054", "metadata": {}, "outputs": [], @@ -209,7 +209,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 11, "id": "3712fe91", "metadata": {}, "outputs": [ @@ -220,8 +220,8 @@ "traceback": [ "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[1;31mAttributeError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[1;32mIn[12], line 1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m times \u001b[38;5;241m=\u001b[39m \u001b[43mrunReordering\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtrain_1\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m20\u001b[39;49m\u001b[43m)\u001b[49m\n", - "Cell \u001b[1;32mIn[11], line 6\u001b[0m, in \u001b[0;36mrunReordering\u001b[1;34m(element_set, n_runs)\u001b[0m\n\u001b[0;32m 4\u001b[0m time_list \u001b[38;5;241m=\u001b[39m []\n\u001b[0;32m 5\u001b[0m \u001b[38;5;66;03m# 1-D\u001b[39;00m\n\u001b[1;32m----> 6\u001b[0m time_list\u001b[38;5;241m.\u001b[39mappend(\u001b[43mcf\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43miterate\u001b[49m\u001b[43m(\u001b[49m\u001b[43melement_set\u001b[49m\u001b[43m)\u001b[49m[\u001b[38;5;241m1\u001b[39m])\n\u001b[0;32m 7\u001b[0m time_list\u001b[38;5;241m.\u001b[39mappend(cf\u001b[38;5;241m.\u001b[39mpalindrome(element_set)[\u001b[38;5;241m1\u001b[39m])\n\u001b[0;32m 8\u001b[0m time_list\u001b[38;5;241m.\u001b[39mappend(cf\u001b[38;5;241m.\u001b[39malternate(element_set)[\u001b[38;5;241m1\u001b[39m])\n", + "Cell \u001b[1;32mIn[11], line 1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m times \u001b[38;5;241m=\u001b[39m \u001b[43mrunReordering\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtrain_1\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m20\u001b[39;49m\u001b[43m)\u001b[49m\n", + "Cell \u001b[1;32mIn[10], line 6\u001b[0m, in \u001b[0;36mrunReordering\u001b[1;34m(element_set, n_runs)\u001b[0m\n\u001b[0;32m 4\u001b[0m time_list \u001b[38;5;241m=\u001b[39m []\n\u001b[0;32m 5\u001b[0m \u001b[38;5;66;03m# 1-D\u001b[39;00m\n\u001b[1;32m----> 6\u001b[0m time_list\u001b[38;5;241m.\u001b[39mappend(\u001b[43mcf\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43miterate\u001b[49m\u001b[43m(\u001b[49m\u001b[43melement_set\u001b[49m\u001b[43m)\u001b[49m[\u001b[38;5;241m1\u001b[39m])\n\u001b[0;32m 7\u001b[0m time_list\u001b[38;5;241m.\u001b[39mappend(cf\u001b[38;5;241m.\u001b[39mpalindrome(element_set)[\u001b[38;5;241m1\u001b[39m])\n\u001b[0;32m 8\u001b[0m time_list\u001b[38;5;241m.\u001b[39mappend(cf\u001b[38;5;241m.\u001b[39malternate(element_set)[\u001b[38;5;241m1\u001b[39m])\n", "File \u001b[1;32mc:\\Users\\desig\\Desktop\\vs code\\LoT\\LoT-modeling\\cognitive_functions.py:10\u001b[0m, in \u001b[0;36miterate\u001b[1;34m(S)\u001b[0m\n\u001b[0;32m 7\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21miterate\u001b[39m(S: ElementSet): \u001b[38;5;66;03m# 112233 \u001b[39;00m\n\u001b[0;32m 8\u001b[0m \n\u001b[0;32m 9\u001b[0m \u001b[38;5;66;03m# preprocessing (not part of measured cognitive process)\u001b[39;00m\n\u001b[1;32m---> 10\u001b[0m n \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mlen\u001b[39m(\u001b[43mS\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43melements\u001b[49m) \u001b[38;5;66;03m# number of elements in the set\u001b[39;00m\n\u001b[0;32m 11\u001b[0m chunks \u001b[38;5;241m=\u001b[39m defaultdict(\u001b[38;5;28mlist\u001b[39m) \n\u001b[0;32m 12\u001b[0m stopwatch \u001b[38;5;241m=\u001b[39m Stopwatch()\n", "\u001b[1;31mAttributeError\u001b[0m: 'set' object has no attribute 'elements'" ] diff --git a/playground.ipynb b/playground.ipynb index adbabfe..7ec06f6 100644 --- a/playground.ipynb +++ b/playground.ipynb @@ -22,7 +22,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ @@ -38,14 +38,17 @@ "metadata": {}, "outputs": [ { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" + "ename": "AttributeError", + "evalue": "'ElementSet' object has no attribute 'graph'", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mAttributeError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[1;32mIn[3], line 3\u001b[0m\n\u001b[0;32m 1\u001b[0m S \u001b[38;5;241m=\u001b[39m {obj1, obj2, obj3, obj4}\n\u001b[0;32m 2\u001b[0m assoc \u001b[38;5;241m=\u001b[39m Associations({obj1: obj2, obj3: obj4})\n\u001b[1;32m----> 3\u001b[0m S \u001b[38;5;241m=\u001b[39m \u001b[43mElementSet\u001b[49m\u001b[43m(\u001b[49m\u001b[43mS\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43massoc\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 4\u001b[0m S\u001b[38;5;241m.\u001b[39mgraph\n", + "File \u001b[1;32mc:\\Users\\desig\\Desktop\\vs code\\LoT\\LoT-modeling\\utils.py:54\u001b[0m, in \u001b[0;36mElementSet.__init__\u001b[1;34m(self, elements, associations)\u001b[0m\n\u001b[0;32m 52\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39melements \u001b[38;5;241m=\u001b[39m elements\n\u001b[0;32m 53\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39massociations \u001b[38;5;241m=\u001b[39m associations\n\u001b[1;32m---> 54\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mgraph \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mbuild_graph\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[1;32mc:\\Users\\desig\\Desktop\\vs code\\LoT\\LoT-modeling\\utils.py:69\u001b[0m, in \u001b[0;36mElementSet.build_graph\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m 67\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39massociations:\n\u001b[0;32m 68\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39massociations\u001b[38;5;241m.\u001b[39mbuild_updates(G) \u001b[38;5;66;03m# Build associations\u001b[39;00m\n\u001b[1;32m---> 69\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mgraph\u001b[49m:\n\u001b[0;32m 70\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mgraph \u001b[38;5;241m=\u001b[39m G\n\u001b[0;32m 71\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m G\n", + "\u001b[1;31mAttributeError\u001b[0m: 'ElementSet' object has no attribute 'graph'" + ] } ], "source": [ @@ -57,7 +60,7 @@ }, { "cell_type": "code", - "execution_count": 53, + "execution_count": null, "metadata": {}, "outputs": [ { From 4e3699aff088474fbc43e7cd38463bb14884a2cc Mon Sep 17 00:00:00 2001 From: LuckyBunnyLee Date: Thu, 10 Jul 2025 18:14:26 -0700 Subject: [PATCH 6/8] amongustest123 --- cog_testing.ipynb | 447 ----------------------------------------- cognitive_functions.py | 264 +++++++++++------------- experiments.ipynb | 4 +- midtest/midcf.py | 273 +++++++++++++++++++++++++ midtest/midpf.py | 160 +++++++++++++++ midtest/midtest.ipynb | 296 +++++++++++++++++++++++++++ midtest/midutils.py | 182 +++++++++++++++++ newprim.py | 223 ++++++++++++++++++++ newtest.ipynb | 296 +++++++++++++++++++++++++++ oldtest/oldcf.py | 271 +++++++++++++++++++++++++ oldtest/oldpf.py | 160 +++++++++++++++ oldtest/oldtest.ipynb | 393 ++++++++++++++++++++++++++++++++++++ oldtest/oldutils.py | 181 +++++++++++++++++ oldtest/random.py | 79 ++++++++ palindrome_test.py | 42 ++++ playground.ipynb | 55 +++-- primitive_fucntions.py | 38 ++-- utils.py | 3 +- 18 files changed, 2727 insertions(+), 640 deletions(-) delete mode 100644 cog_testing.ipynb create mode 100644 midtest/midcf.py create mode 100644 midtest/midpf.py create mode 100644 midtest/midtest.ipynb create mode 100644 midtest/midutils.py create mode 100644 newprim.py create mode 100644 newtest.ipynb create mode 100644 oldtest/oldcf.py create mode 100644 oldtest/oldpf.py create mode 100644 oldtest/oldtest.ipynb create mode 100644 oldtest/oldutils.py create mode 100644 oldtest/random.py create mode 100644 palindrome_test.py diff --git a/cog_testing.ipynb b/cog_testing.ipynb deleted file mode 100644 index 8eb1c54..0000000 --- a/cog_testing.ipynb +++ /dev/null @@ -1,447 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "id": "081f22f1", - "metadata": {}, - "outputs": [], - "source": [ - "import numpy as np\n", - "import seaborn as sns\n", - "import matplotlib.pyplot as plt\n", - "import pandas as pd\n", - "from utils import Element\n", - "import warnings\n", - "import cognitive_functions as cf\n", - "warnings.filterwarnings('ignore')" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "831c5eaf", - "metadata": {}, - "outputs": [], - "source": [ - "a = Element('A1','A','1')\n", - "b = Element('A2','A','2')\n", - "c = Element('B1','B','1')\n", - "d = Element('B2','B','2')\n", - "e = Element('C1','C','1')\n", - "f = Element('C2','C','2')\n", - "g = Element('D1','D','1')\n", - "h = Element('D2','D','2')\n", - "i = Element('E1','E','1')\n", - "j = Element('E2','E','2')\n", - "k = Element('F1','F','1')\n", - "l = Element('F2','F','2')" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "8e512e91", - "metadata": {}, - "outputs": [], - "source": [ - "train_1 = {a,b,c,d}\n", - "train_2 = {a,b,e,f}\n", - "test_1 = {c,d,e,f}\n", - "test_2 = {a,b,c,d,e,f}\n", - "test_3 = {g,h,i,j}\n", - "test_4 = {g,h,k,l}\n", - "test_5 = {i,j,k,l}\n", - "test_6 = {g,h,i,j,k,l}" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "030b28dc", - "metadata": {}, - "outputs": [ - { - "ename": "NameError", - "evalue": "name 'KComplexity' is not defined", - "output_type": "error", - "traceback": [ - "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[1;31mNameError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[1;32mIn[4], line 10\u001b[0m\n\u001b[0;32m 7\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21;01mcognitive_functions\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mas\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21;01mcf\u001b[39;00m\n\u001b[0;32m 8\u001b[0m warnings\u001b[38;5;241m.\u001b[39mfilterwarnings(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mignore\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[1;32m---> 10\u001b[0m kc \u001b[38;5;241m=\u001b[39m \u001b[43mKComplexity\u001b[49m()\n\u001b[0;32m 11\u001b[0m kc\u001b[38;5;241m.\u001b[39mreset()\n\u001b[0;32m 12\u001b[0m cf\u001b[38;5;241m.\u001b[39miterate(train_1)\n", - "\u001b[1;31mNameError\u001b[0m: name 'KComplexity' is not defined" - ] - } - ], - "source": [ - "import numpy as np\n", - "import seaborn as sns\n", - "import matplotlib.pyplot as plt\n", - "import pandas as pd\n", - "from utils import Element\n", - "import warnings\n", - "import cognitive_functions as cf\n", - "warnings.filterwarnings('ignore')\n", - "\n", - "kc = KComplexity()\n", - "kc.reset()\n", - "cf.iterate(train_1)\n", - "kc.get_k_complexity()\n", - "kc.get_prim_counts()\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "034a7977", - "metadata": {}, - "outputs": [ - { - "ename": "AttributeError", - "evalue": "'set' object has no attribute 'edges'", - "output_type": "error", - "traceback": [ - "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[1;31mAttributeError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[1;32mIn[21], line 12\u001b[0m\n\u001b[0;32m 10\u001b[0m kc \u001b[38;5;241m=\u001b[39m KComplexity()\n\u001b[0;32m 11\u001b[0m kc\u001b[38;5;241m.\u001b[39mreset()\n\u001b[1;32m---> 12\u001b[0m \u001b[43mcf\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mpalindrome\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtrain_1\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 13\u001b[0m kc\u001b[38;5;241m.\u001b[39mget_k_complexity()\n\u001b[0;32m 14\u001b[0m kc\u001b[38;5;241m.\u001b[39mget_prim_counts()\n", - "File \u001b[1;32mc:\\Users\\desig\\Desktop\\vs code\\LoT\\LoT-modeling\\cognitive_functions.py:67\u001b[0m, in \u001b[0;36mpalindrome\u001b[1;34m(S)\u001b[0m\n\u001b[0;32m 65\u001b[0m pf\u001b[38;5;241m.\u001b[39msetminus(S, element)\n\u001b[0;32m 66\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m _ \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mrange\u001b[39m(n):\n\u001b[1;32m---> 67\u001b[0m element \u001b[38;5;241m=\u001b[39m \u001b[43mpf\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mwrite_random\u001b[49m\u001b[43m(\u001b[49m\u001b[43mS\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbias\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mgetattr\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mbasis\u001b[49m\u001b[43m[\u001b[49m\u001b[43mn\u001b[49m\u001b[38;5;241;43m-\u001b[39;49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[38;5;241;43m-\u001b[39;49m\u001b[43m_\u001b[49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbias\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 68\u001b[0m pf\u001b[38;5;241m.\u001b[39mpair(rev,element)\n\u001b[0;32m 69\u001b[0m pf\u001b[38;5;241m.\u001b[39msetminus(S, element)\n", - "File \u001b[1;32mc:\\Users\\desig\\Desktop\\vs code\\LoT\\LoT-modeling\\utils.py:167\u001b[0m, in \u001b[0;36mKComplexity._make_wrapper..wrapper\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m 165\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21mwrapper\u001b[39m(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[0;32m 166\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcall_counts[name] \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m\n\u001b[1;32m--> 167\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[1;32mc:\\Users\\desig\\Desktop\\vs code\\LoT\\LoT-modeling\\utils.py:167\u001b[0m, in \u001b[0;36mKComplexity._make_wrapper..wrapper\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m 165\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21mwrapper\u001b[39m(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[0;32m 166\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcall_counts[name] \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m\n\u001b[1;32m--> 167\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", - " \u001b[1;31m[... skipping similar frames: KComplexity._make_wrapper..wrapper at line 167 (1 times)]\u001b[0m\n", - "File \u001b[1;32mc:\\Users\\desig\\Desktop\\vs code\\LoT\\LoT-modeling\\utils.py:167\u001b[0m, in \u001b[0;36mKComplexity._make_wrapper..wrapper\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m 165\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21mwrapper\u001b[39m(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[0;32m 166\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcall_counts[name] \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m\n\u001b[1;32m--> 167\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[1;32mc:\\Users\\desig\\Desktop\\vs code\\LoT\\LoT-modeling\\primitive_fucntions.py:97\u001b[0m, in \u001b[0;36mwrite_random\u001b[1;34m(G, bias, type)\u001b[0m\n\u001b[0;32m 92\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"Returns one unused member of particular type\u001b[39;00m\n\u001b[0;32m 93\u001b[0m \u001b[38;5;124;03mTime complexity: O(n) to filter tokens\"\"\"\u001b[39;00m\n\u001b[0;32m 94\u001b[0m \u001b[38;5;66;03m# for element in S:\u001b[39;00m\n\u001b[0;32m 95\u001b[0m \u001b[38;5;66;03m# if getattr(element, bias) == type:\u001b[39;00m\n\u001b[0;32m 96\u001b[0m \u001b[38;5;66;03m# return element\u001b[39;00m\n\u001b[1;32m---> 97\u001b[0m type_elements \u001b[38;5;241m=\u001b[39m [u \u001b[38;5;28;01mfor\u001b[39;00m u, v, d \u001b[38;5;129;01min\u001b[39;00m \u001b[43mG\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43medges\u001b[49m(data\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m) \u001b[38;5;28;01mif\u001b[39;00m v \u001b[38;5;241m==\u001b[39m \u001b[38;5;28mtype\u001b[39m \u001b[38;5;129;01mand\u001b[39;00m d[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mlabel\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m==\u001b[39m bias]\n\u001b[0;32m 99\u001b[0m \u001b[38;5;66;03m### WRITE CODE\u001b[39;00m\n\u001b[0;32m 100\u001b[0m \u001b[38;5;66;03m### maybe add a random list shuffling thing here\u001b[39;00m\n\u001b[0;32m 101\u001b[0m \u001b[38;5;66;03m### to make it less predictable\u001b[39;00m\n\u001b[0;32m 103\u001b[0m \u001b[38;5;28;01mpass\u001b[39;00m\n", - "\u001b[1;31mAttributeError\u001b[0m: 'set' object has no attribute 'edges'" - ] - } - ], - "source": [ - "import numpy as np\n", - "import seaborn as sns\n", - "import matplotlib.pyplot as plt\n", - "import pandas as pd\n", - "from utils import Element\n", - "import warnings\n", - "import cognitive_functions as cf\n", - "warnings.filterwarnings('ignore')\n", - "\n", - "kc = KComplexity()\n", - "kc.reset()\n", - "cf.palindrome(train_1)\n", - "kc.get_k_complexity()\n", - "kc.get_prim_counts()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "df882383", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{'add': 0,\n", - " 'append': 0,\n", - " 'check_if_same_type': 0,\n", - " 'dim_set': 0,\n", - " 'flip': 1,\n", - " 'implement': 0,\n", - " 'list_create': 0,\n", - " 'merge': 0,\n", - " 'pair': 1,\n", - " 'remove': 0,\n", - " 'remove_item': 0,\n", - " 'sample': 1,\n", - " 'setminus': 1,\n", - " 'write_all': 0,\n", - " 'write_all_set': 0,\n", - " 'write_random': 0}" - ] - }, - "execution_count": 22, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "import numpy as np\n", - "import seaborn as sns\n", - "import matplotlib.pyplot as plt\n", - "import pandas as pd\n", - "from utils import Element\n", - "import warnings\n", - "import cognitive_functions as cf\n", - "warnings.filterwarnings('ignore')\n", - "\n", - "kc = KComplexity()\n", - "kc.reset()\n", - "cf.alternate(train_1)\n", - "kc.get_k_complexity()\n", - "kc.get_prim_counts()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "da9b45ff", - "metadata": {}, - "outputs": [ - { - "ename": "TypeError", - "evalue": "chaining() missing 1 required positional argument: 'associations'", - "output_type": "error", - "traceback": [ - "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[1;31mTypeError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[1;32mIn[29], line 12\u001b[0m\n\u001b[0;32m 10\u001b[0m kc \u001b[38;5;241m=\u001b[39m KComplexity()\n\u001b[0;32m 11\u001b[0m kc\u001b[38;5;241m.\u001b[39mreset()\n\u001b[1;32m---> 12\u001b[0m \u001b[43mcf\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mchaining\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtrain_1\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 13\u001b[0m kc\u001b[38;5;241m.\u001b[39mget_k_complexity()\n\u001b[0;32m 14\u001b[0m kc\u001b[38;5;241m.\u001b[39mget_prim_counts()\n", - "\u001b[1;31mTypeError\u001b[0m: chaining() missing 1 required positional argument: 'associations'" - ] - } - ], - "source": [ - "import numpy as np\n", - "import seaborn as sns\n", - "import matplotlib.pyplot as plt\n", - "import pandas as pd\n", - "from utils import Element\n", - "import warnings\n", - "import cognitive_functions as cf\n", - "warnings.filterwarnings('ignore')\n", - "\n", - "kc = KComplexity()\n", - "kc.reset()\n", - "cf.chaining(train_1)\n", - "kc.get_k_complexity()\n", - "kc.get_prim_counts()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "590c9d20", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{'add': 0,\n", - " 'append': 0,\n", - " 'check_if_same_type': 0,\n", - " 'dim_set': 0,\n", - " 'flip': 0,\n", - " 'implement': 0,\n", - " 'list_create': 0,\n", - " 'merge': 0,\n", - " 'pair': 0,\n", - " 'remove': 0,\n", - " 'remove_item': 0,\n", - " 'sample': 0,\n", - " 'setminus': 0,\n", - " 'write_all': 0,\n", - " 'write_all_set': 0,\n", - " 'write_random': 0}" - ] - }, - "execution_count": 30, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "import numpy as np\n", - "import seaborn as sns\n", - "import matplotlib.pyplot as plt\n", - "import pandas as pd\n", - "from utils import Element\n", - "import warnings\n", - "import cognitive_functions as cf\n", - "warnings.filterwarnings('ignore')\n", - "\n", - "kc = KComplexity()\n", - "kc.reset()\n", - "cf.seriate(train_1)\n", - "kc.get_k_complexity()\n", - "kc.get_prim_counts()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "7e2d4e07", - "metadata": {}, - "outputs": [ - { - "ename": "AttributeError", - "evalue": "'set' object has no attribute 'edges'", - "output_type": "error", - "traceback": [ - "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[1;31mAttributeError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[1;32mIn[31], line 12\u001b[0m\n\u001b[0;32m 10\u001b[0m kc \u001b[38;5;241m=\u001b[39m KComplexity()\n\u001b[0;32m 11\u001b[0m kc\u001b[38;5;241m.\u001b[39mreset()\n\u001b[1;32m---> 12\u001b[0m \u001b[43mcf\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mserial_crossed\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtrain_1\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 13\u001b[0m kc\u001b[38;5;241m.\u001b[39mget_k_complexity()\n\u001b[0;32m 14\u001b[0m kc\u001b[38;5;241m.\u001b[39mget_prim_counts()\n", - "File \u001b[1;32mc:\\Users\\desig\\Desktop\\vs code\\LoT\\LoT-modeling\\cognitive_functions.py:145\u001b[0m, in \u001b[0;36mserial_crossed\u001b[1;34m(S)\u001b[0m\n\u001b[0;32m 143\u001b[0m pf\u001b[38;5;241m.\u001b[39msetminus(S, element)\n\u001b[0;32m 144\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m _ \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mrange\u001b[39m(n):\n\u001b[1;32m--> 145\u001b[0m element \u001b[38;5;241m=\u001b[39m \u001b[43mpf\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mwrite_random\u001b[49m\u001b[43m(\u001b[49m\u001b[43mS\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbias\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mgetattr\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mresult\u001b[49m\u001b[43m[\u001b[49m\u001b[43m_\u001b[49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbias\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 146\u001b[0m pf\u001b[38;5;241m.\u001b[39mpair(result, element)\n\u001b[0;32m 147\u001b[0m pf\u001b[38;5;241m.\u001b[39msetminus(S, element)\n", - "File \u001b[1;32mc:\\Users\\desig\\Desktop\\vs code\\LoT\\LoT-modeling\\utils.py:167\u001b[0m, in \u001b[0;36mKComplexity._make_wrapper..wrapper\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m 165\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21mwrapper\u001b[39m(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[0;32m 166\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcall_counts[name] \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m\n\u001b[1;32m--> 167\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[1;32mc:\\Users\\desig\\Desktop\\vs code\\LoT\\LoT-modeling\\utils.py:167\u001b[0m, in \u001b[0;36mKComplexity._make_wrapper..wrapper\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m 165\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21mwrapper\u001b[39m(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[0;32m 166\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcall_counts[name] \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m\n\u001b[1;32m--> 167\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", - " \u001b[1;31m[... skipping similar frames: KComplexity._make_wrapper..wrapper at line 167 (9 times)]\u001b[0m\n", - "File \u001b[1;32mc:\\Users\\desig\\Desktop\\vs code\\LoT\\LoT-modeling\\utils.py:167\u001b[0m, in \u001b[0;36mKComplexity._make_wrapper..wrapper\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m 165\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21mwrapper\u001b[39m(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[0;32m 166\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcall_counts[name] \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m\n\u001b[1;32m--> 167\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[1;32mc:\\Users\\desig\\Desktop\\vs code\\LoT\\LoT-modeling\\primitive_fucntions.py:97\u001b[0m, in \u001b[0;36mwrite_random\u001b[1;34m(G, bias, type)\u001b[0m\n\u001b[0;32m 92\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"Returns one unused member of particular type\u001b[39;00m\n\u001b[0;32m 93\u001b[0m \u001b[38;5;124;03mTime complexity: O(n) to filter tokens\"\"\"\u001b[39;00m\n\u001b[0;32m 94\u001b[0m \u001b[38;5;66;03m# for element in S:\u001b[39;00m\n\u001b[0;32m 95\u001b[0m \u001b[38;5;66;03m# if getattr(element, bias) == type:\u001b[39;00m\n\u001b[0;32m 96\u001b[0m \u001b[38;5;66;03m# return element\u001b[39;00m\n\u001b[1;32m---> 97\u001b[0m type_elements \u001b[38;5;241m=\u001b[39m [u \u001b[38;5;28;01mfor\u001b[39;00m u, v, d \u001b[38;5;129;01min\u001b[39;00m \u001b[43mG\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43medges\u001b[49m(data\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m) \u001b[38;5;28;01mif\u001b[39;00m v \u001b[38;5;241m==\u001b[39m \u001b[38;5;28mtype\u001b[39m \u001b[38;5;129;01mand\u001b[39;00m d[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mlabel\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m==\u001b[39m bias]\n\u001b[0;32m 99\u001b[0m \u001b[38;5;66;03m### WRITE CODE\u001b[39;00m\n\u001b[0;32m 100\u001b[0m \u001b[38;5;66;03m### maybe add a random list shuffling thing here\u001b[39;00m\n\u001b[0;32m 101\u001b[0m \u001b[38;5;66;03m### to make it less predictable\u001b[39;00m\n\u001b[0;32m 103\u001b[0m \u001b[38;5;28;01mpass\u001b[39;00m\n", - "\u001b[1;31mAttributeError\u001b[0m: 'set' object has no attribute 'edges'" - ] - } - ], - "source": [ - "import numpy as np\n", - "import seaborn as sns\n", - "import matplotlib.pyplot as plt\n", - "import pandas as pd\n", - "from utils import Element\n", - "import warnings\n", - "import cognitive_functions as cf\n", - "warnings.filterwarnings('ignore')\n", - "\n", - "kc = KComplexity()\n", - "kc.reset()\n", - "cf.serial_crossed(train_1)\n", - "kc.get_k_complexity()\n", - "kc.get_prim_counts()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "092f34e3", - "metadata": {}, - "outputs": [ - { - "ename": "KeyboardInterrupt", - "evalue": "", - "output_type": "error", - "traceback": [ - "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[1;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)", - "Cell \u001b[1;32mIn[32], line 12\u001b[0m\n\u001b[0;32m 10\u001b[0m kc \u001b[38;5;241m=\u001b[39m KComplexity()\n\u001b[0;32m 11\u001b[0m kc\u001b[38;5;241m.\u001b[39mreset()\n\u001b[1;32m---> 12\u001b[0m \u001b[43mcf\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcenter_embedded\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtrain_1\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 13\u001b[0m kc\u001b[38;5;241m.\u001b[39mget_k_complexity()\n\u001b[0;32m 14\u001b[0m kc\u001b[38;5;241m.\u001b[39mget_prim_counts()\n", - "File \u001b[1;32mc:\\Users\\desig\\Desktop\\vs code\\LoT\\LoT-modeling\\cognitive_functions.py:158\u001b[0m, in \u001b[0;36mcenter_embedded\u001b[1;34m(S)\u001b[0m\n\u001b[0;32m 156\u001b[0m result \u001b[38;5;241m=\u001b[39m []\n\u001b[0;32m 157\u001b[0m \u001b[38;5;28;01mwhile\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(S) \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[1;32m--> 158\u001b[0m element \u001b[38;5;241m=\u001b[39m \u001b[43mpf\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msample\u001b[49m\u001b[43m(\u001b[49m\u001b[43mS\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 159\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(result) \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m0\u001b[39m \u001b[38;5;129;01mor\u001b[39;00m pf\u001b[38;5;241m.\u001b[39mcheck_if_same_type(element, result[\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m], bias[\u001b[38;5;241m0\u001b[39m]):\n\u001b[0;32m 160\u001b[0m pf\u001b[38;5;241m.\u001b[39mpair(result, element)\n", - "File \u001b[1;32mc:\\Users\\desig\\Desktop\\vs code\\LoT\\LoT-modeling\\utils.py:167\u001b[0m, in \u001b[0;36mKComplexity._make_wrapper..wrapper\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m 165\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21mwrapper\u001b[39m(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[0;32m 166\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcall_counts[name] \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m\n\u001b[1;32m--> 167\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[1;32mc:\\Users\\desig\\Desktop\\vs code\\LoT\\LoT-modeling\\utils.py:167\u001b[0m, in \u001b[0;36mKComplexity._make_wrapper..wrapper\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m 165\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21mwrapper\u001b[39m(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[0;32m 166\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcall_counts[name] \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m\n\u001b[1;32m--> 167\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", - " \u001b[1;31m[... skipping similar frames: KComplexity._make_wrapper..wrapper at line 167 (10 times)]\u001b[0m\n", - "File \u001b[1;32mc:\\Users\\desig\\Desktop\\vs code\\LoT\\LoT-modeling\\utils.py:167\u001b[0m, in \u001b[0;36mKComplexity._make_wrapper..wrapper\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m 165\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21mwrapper\u001b[39m(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[0;32m 166\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcall_counts[name] \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m\n\u001b[1;32m--> 167\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[1;32mc:\\Users\\desig\\Desktop\\vs code\\LoT\\LoT-modeling\\primitive_fucntions.py:45\u001b[0m, in \u001b[0;36msample\u001b[1;34m(collection)\u001b[0m\n\u001b[0;32m 42\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[0;32m 44\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(collection, \u001b[38;5;28mset\u001b[39m):\n\u001b[1;32m---> 45\u001b[0m collection \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mtuple\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mcollection\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;66;03m# Convert to tuple for sampling\u001b[39;00m\n\u001b[0;32m 47\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m random\u001b[38;5;241m.\u001b[39msample(collection, \u001b[38;5;241m1\u001b[39m)[\u001b[38;5;241m0\u001b[39m]\n", - "\u001b[1;31mKeyboardInterrupt\u001b[0m: " - ] - } - ], - "source": [ - "import numpy as np\n", - "import seaborn as sns\n", - "import matplotlib.pyplot as plt\n", - "import pandas as pd\n", - "from utils import Element\n", - "import warnings\n", - "import cognitive_functions as cf\n", - "warnings.filterwarnings('ignore')\n", - "\n", - "kc = KComplexity()\n", - "kc.reset()\n", - "cf.center_embedded(train_1)\n", - "kc.get_k_complexity()\n", - "kc.get_prim_counts()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "ca81ceaf", - "metadata": {}, - "outputs": [ - { - "ename": "AttributeError", - "evalue": "'set' object has no attribute 'edges'", - "output_type": "error", - "traceback": [ - "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[1;31mAttributeError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[1;32mIn[33], line 12\u001b[0m\n\u001b[0;32m 10\u001b[0m kc \u001b[38;5;241m=\u001b[39m KComplexity()\n\u001b[0;32m 11\u001b[0m kc\u001b[38;5;241m.\u001b[39mreset()\n\u001b[1;32m---> 12\u001b[0m \u001b[43mcf\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtail_recursive\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtrain_1\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 13\u001b[0m kc\u001b[38;5;241m.\u001b[39mget_k_complexity()\n\u001b[0;32m 14\u001b[0m kc\u001b[38;5;241m.\u001b[39mget_prim_counts()\n", - "File \u001b[1;32mc:\\Users\\desig\\Desktop\\vs code\\LoT\\LoT-modeling\\cognitive_functions.py:178\u001b[0m, in \u001b[0;36mtail_recursive\u001b[1;34m(S)\u001b[0m\n\u001b[0;32m 176\u001b[0m element \u001b[38;5;241m=\u001b[39m pf\u001b[38;5;241m.\u001b[39msample(S)\n\u001b[0;32m 177\u001b[0m pf\u001b[38;5;241m.\u001b[39msetminus(S, element)\n\u001b[1;32m--> 178\u001b[0m paired_element \u001b[38;5;241m=\u001b[39m \u001b[43mpf\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mwrite_random\u001b[49m\u001b[43m(\u001b[49m\u001b[43mS\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbias\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mgetattr\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43melement\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbias\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 179\u001b[0m result \u001b[38;5;241m=\u001b[39m pf\u001b[38;5;241m.\u001b[39mappend(result, pf\u001b[38;5;241m.\u001b[39mmerge(element, paired_element))\n\u001b[0;32m 180\u001b[0m pf\u001b[38;5;241m.\u001b[39msetminus(S, paired_element)\n", - "File \u001b[1;32mc:\\Users\\desig\\Desktop\\vs code\\LoT\\LoT-modeling\\utils.py:167\u001b[0m, in \u001b[0;36mKComplexity._make_wrapper..wrapper\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m 165\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21mwrapper\u001b[39m(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[0;32m 166\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcall_counts[name] \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m\n\u001b[1;32m--> 167\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[1;32mc:\\Users\\desig\\Desktop\\vs code\\LoT\\LoT-modeling\\utils.py:167\u001b[0m, in \u001b[0;36mKComplexity._make_wrapper..wrapper\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m 165\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21mwrapper\u001b[39m(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[0;32m 166\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcall_counts[name] \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m\n\u001b[1;32m--> 167\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", - " \u001b[1;31m[... skipping similar frames: KComplexity._make_wrapper..wrapper at line 167 (11 times)]\u001b[0m\n", - "File \u001b[1;32mc:\\Users\\desig\\Desktop\\vs code\\LoT\\LoT-modeling\\utils.py:167\u001b[0m, in \u001b[0;36mKComplexity._make_wrapper..wrapper\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m 165\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21mwrapper\u001b[39m(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[0;32m 166\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcall_counts[name] \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m\n\u001b[1;32m--> 167\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[1;32mc:\\Users\\desig\\Desktop\\vs code\\LoT\\LoT-modeling\\primitive_fucntions.py:97\u001b[0m, in \u001b[0;36mwrite_random\u001b[1;34m(G, bias, type)\u001b[0m\n\u001b[0;32m 92\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"Returns one unused member of particular type\u001b[39;00m\n\u001b[0;32m 93\u001b[0m \u001b[38;5;124;03mTime complexity: O(n) to filter tokens\"\"\"\u001b[39;00m\n\u001b[0;32m 94\u001b[0m \u001b[38;5;66;03m# for element in S:\u001b[39;00m\n\u001b[0;32m 95\u001b[0m \u001b[38;5;66;03m# if getattr(element, bias) == type:\u001b[39;00m\n\u001b[0;32m 96\u001b[0m \u001b[38;5;66;03m# return element\u001b[39;00m\n\u001b[1;32m---> 97\u001b[0m type_elements \u001b[38;5;241m=\u001b[39m [u \u001b[38;5;28;01mfor\u001b[39;00m u, v, d \u001b[38;5;129;01min\u001b[39;00m \u001b[43mG\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43medges\u001b[49m(data\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m) \u001b[38;5;28;01mif\u001b[39;00m v \u001b[38;5;241m==\u001b[39m \u001b[38;5;28mtype\u001b[39m \u001b[38;5;129;01mand\u001b[39;00m d[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mlabel\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m==\u001b[39m bias]\n\u001b[0;32m 99\u001b[0m \u001b[38;5;66;03m### WRITE CODE\u001b[39;00m\n\u001b[0;32m 100\u001b[0m \u001b[38;5;66;03m### maybe add a random list shuffling thing here\u001b[39;00m\n\u001b[0;32m 101\u001b[0m \u001b[38;5;66;03m### to make it less predictable\u001b[39;00m\n\u001b[0;32m 103\u001b[0m \u001b[38;5;28;01mpass\u001b[39;00m\n", - "\u001b[1;31mAttributeError\u001b[0m: 'set' object has no attribute 'edges'" - ] - } - ], - "source": [ - "import numpy as np\n", - "import seaborn as sns\n", - "import matplotlib.pyplot as plt\n", - "import pandas as pd\n", - "from utils import Element\n", - "import warnings\n", - "import cognitive_functions as cf\n", - "warnings.filterwarnings('ignore')\n", - "\n", - "kc = KComplexity()\n", - "kc.reset()\n", - "cf.tail_recursive(train_1)\n", - "kc.get_k_complexity()\n", - "kc.get_prim_counts()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "c2134ce3", - "metadata": {}, - "outputs": [ - { - "ename": "TypeError", - "evalue": "find_bias() missing 1 required positional argument: 'clock'", - "output_type": "error", - "traceback": [ - "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[1;31mTypeError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[1;32mIn[34], line 12\u001b[0m\n\u001b[0;32m 10\u001b[0m kc \u001b[38;5;241m=\u001b[39m KComplexity()\n\u001b[0;32m 11\u001b[0m kc\u001b[38;5;241m.\u001b[39mreset()\n\u001b[1;32m---> 12\u001b[0m \u001b[43mcf\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfind_bias\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtrain_1\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 13\u001b[0m kc\u001b[38;5;241m.\u001b[39mget_k_complexity()\n\u001b[0;32m 14\u001b[0m kc\u001b[38;5;241m.\u001b[39mget_prim_counts()\n", - "\u001b[1;31mTypeError\u001b[0m: find_bias() missing 1 required positional argument: 'clock'" - ] - } - ], - "source": [ - "import numpy as np\n", - "import seaborn as sns\n", - "import matplotlib.pyplot as plt\n", - "import pandas as pd\n", - "from utils import Element\n", - "import warnings\n", - "import cognitive_functions as cf\n", - "warnings.filterwarnings('ignore')\n", - "\n", - "kc = KComplexity()\n", - "kc.reset()\n", - "cf.find_bias(train_1)\n", - "kc.get_k_complexity()\n", - "kc.get_prim_counts()" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "lot_venv", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.13.5" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/cognitive_functions.py b/cognitive_functions.py index 816d459..837f44a 100644 --- a/cognitive_functions.py +++ b/cognitive_functions.py @@ -1,225 +1,201 @@ import primitive_fucntions as pf from collections import defaultdict -from utils import Stopwatch, Element, ElementSet, Associations - -# 1-D +from utils import Stopwatch, ElementSet, Associations -def iterate(S: ElementSet): # 112233 +# --- Cognitive Functions using Graph Node Structure --- # - # preprocessing (not part of measured cognitive process) - n = len(S.elements) # number of elements in the set - chunks = defaultdict(list) +def iterate(S: ElementSet): + n = len(S.elements) + chunks = defaultdict(list) stopwatch = Stopwatch() - # --- # - # select attribute which chunking is based on - - ### ADD CODE HERE - """ graph algo here""" - bias = find_bias(S.elements, stopwatch) - for _ in range(n//2): - element = pf.sample(S) - result = None - time_elapsed = None + bias = find_bias(S, stopwatch) + for _ in range(n // 2): + element = pf.sample(S.elements) - # """ non graph algo here""" bias = find_bias(S, stopwatch) stopwatch.start() for _ in range(n): - element = pf.sample(S) # select an element in the set + element = pf.sample(S.elements) sorter = getattr(element, bias) chunks[sorter].append(element) - pf.setminus(S, element) + pf.setminus(S.elements, element) stopwatch.stop() - n = len(chunks) # reassign n - chunks = {tuple(v) for k, v in chunks.items()} + + chunks = {tuple(v) for v in chunks.values()} stopwatch.start() result = [] - for _ in range(n): + for _ in range(len(chunks)): chunk = pf.sample(chunks) stopwatch.stop() temp = list(chunk) stopwatch.start() - pf.append(result, temp) + result = pf.append(result, temp) pf.setminus(chunks, chunk) stopwatch.stop() time_elapsed = stopwatch.get_elapsed_time() - return (result, time_elapsed) -def palindrome(S): - # 123321 - # preprocessing (not part of measured cognitive process) - n = len(S) // 2 # number of elements in basis +def palindrome(S: ElementSet): + n = len(S.elements) // 2 stopwatch = Stopwatch() - # select attribute which chunking is based on bias = find_bias(S, stopwatch) stopwatch.start() basis, rev = [], [] - # write_random() based implementation - ### WRITE CODE HERE - while (len(S) > n): - element = pf.sample(S) - if len(basis)==0 or not (any(pf.check_if_same_type(element, chosen, bias) for chosen in basis)): + + while len(S.elements) > n: + element = pf.sample(S.elements) + if len(basis) == 0 or not any(pf.check_if_same_type(element, chosen, bias) for chosen in basis): pf.pair(basis, element) - pf.setminus(S, element) - for _ in range(n): - element = pf.write_random(S, bias, getattr(basis[n-1-_], bias)) - pf.pair(rev,element) - pf.setminus(S, element) - result = pf.append(basis,rev) + pf.setminus(S.elements, element) + + for i in range(n): + target_type = getattr(basis[n - 1 - i], bias) + candidates = [u for u, v, d in S.graph.edges(data=True) if v == target_type and d['label'] == bias and u in S.elements] + if candidates: + element = pf.sample(candidates) + pf.pair(rev, element) + pf.setminus(S.elements, element) + + result = pf.append(basis, rev) stopwatch.stop() - time_elapsed = stopwatch.get_elapsed_time() - - return (result, time_elapsed) + return (result, stopwatch.get_elapsed_time()) -def alternate(S): - # 121212 - # preprocessing (not part of measured cognitive process) - n = len(S) # number of elements in the set +def alternate(S: ElementSet): stopwatch = Stopwatch() - # --- # - # select attribute which chunking is based on - ### ADD CODE HERE - ### subject knows what types of attributes are there - ### and what type of attribute to select - - bias = find_bias(S,stopwatch,two_flag=True) + bias = find_bias(S, stopwatch, two_flag=True) result = [] - while (len(S) > 0): - element = pf.sample(S) + + while len(S.elements) > 0: + element = pf.sample(S.elements) if len(result) == 0 or not pf.check_if_same_type(element, result[-1], bias): - pf.pair(result, element) - pf.setminus(S, element) - time_elapsed = stopwatch.get_elapsed_time() + pf.pair(result, element) + pf.setminus(S.elements, element) - return (result, time_elapsed) + return (result, stopwatch.get_elapsed_time()) -def chaining(S, associations: dict): - # preprocessing (not part of measured cognitive process) - n = len(S) # number of elements in the set +def chaining(S: ElementSet, associations: Associations): stopwatch = Stopwatch() - # --- # stopwatch.start() chunks = [] result = [] - while (len(S) > 0): - element = pf.sample(S) - if element in associations.keys(): + + while len(S.elements) > 0: + element = pf.sample(S.elements) + if element in associations.associations: chunk = [] pf.pair(chunk, element) - pf.setminus(S, element) + pf.setminus(S.elements, element) + while True: - next_element = pf.sample(S) - if next_element == associations[element]: + next_element = pf.sample(S.elements) + if next_element == associations.associations[element]: pf.pair(chunk, next_element) - pf.setminus(S, next_element) + pf.setminus(S.elements, next_element) pf.pair(chunks, chunk) break - else: - continue - else: - continue - stopwatch.stop() - time_elapsed = stopwatch.get_elapsed_time() - return (result, time_elapsed) + result = chunks + stopwatch.stop() + return (result, stopwatch.get_elapsed_time()) -def seriate(S): +def seriate(S: ElementSet): # 123123 pass -# -------- 2-D -------- # - -def serial_crossed(S): - n = len(S) // 2 # number of elements in the basis +def serial_crossed(S: ElementSet): + n = len(S.elements) // 2 stopwatch = Stopwatch() bias = find_bias(S, stopwatch, higher_dim=True) result = [] - while len(S) > n: - element = pf.sample(S) + + while len(S.elements) > n: + element = pf.sample(S.elements) if len(result) == 0 or pf.check_if_same_type(element, result[-1], bias[0]): pf.pair(result, element) - pf.setminus(S, element) - for _ in range(n): - element = pf.write_random(S, bias[1], getattr(result[_], bias[1])) - pf.pair(result, element) - pf.setminus(S, element) - time_elapsed = stopwatch.get_elapsed_time() - return (result, time_elapsed) + pf.setminus(S.elements, element) + + for i in range(n): + target_type = getattr(result[i], bias[1]) + candidates = [u for u, v, d in S.graph.edges(data=True) if v == target_type and d['label'] == bias[1] and u in S.elements] + if candidates: + element = pf.sample(candidates) + pf.pair(result, element) + pf.setminus(S.elements, element) -def center_embedded(S): - n = len(S) // 2 # number of elements in the basis - # + return (result, stopwatch.get_elapsed_time()) + +def center_embedded(S: ElementSet): + n = len(S.elements) // 2 stopwatch = Stopwatch() bias = find_bias(S, stopwatch, higher_dim=True) result = [] - while len(S) > 0: - element = pf.sample(S) + + while len(S.elements) > 0: + element = pf.sample(S.elements) if len(result) == 0 or pf.check_if_same_type(element, result[-1], bias[0]): pf.pair(result, element) - pf.setminus(S, element) - for _ in range(n): - element = pf.write_random(S, bias[1], getattr(result[n - 1 - _], bias[1])) - pf.pair(result, element) - pf.setminus(S, element) + pf.setminus(S.elements, element) + if len(result) == n: + break + + for i in range(n): + target_type = getattr(result[n - 1 - i], bias[1]) + candidates = [u for u, v, d in S.graph.edges(data=True) if v == target_type and d['label'] == bias[1] and u in S.elements] + if candidates: + element = pf.sample(candidates) + pf.pair(result, element) + pf.setminus(S.elements, element) + stopwatch.stop() - time_elapsed = stopwatch.get_elapsed_time() - return (result, time_elapsed) + return (result, stopwatch.get_elapsed_time()) -def tail_recursive(S): +def tail_recursive(S: ElementSet): stopwatch = Stopwatch() bias = find_bias(S, stopwatch, two_flag=True, higher_dim=True) stopwatch.start() result = [] - while len(S) > 0: - element = pf.sample(S) - pf.setminus(S, element) - paired_element = pf.write_random(S, bias[0], getattr(element, bias[0])) - result = pf.append(result, pf.merge(element, paired_element)) - pf.setminus(S, paired_element) - stopwatch.stop() - time_elapsed = stopwatch.get_elapsed_time() - return (result, time_elapsed) + while len(S.elements) > 0: + element = pf.sample(S.elements) + pf.setminus(S.elements, element) + target_type = getattr(element, bias[0]) + candidates = [u for u, v, d in S.graph.edges(data=True) if v == target_type and d['label'] == bias[0] and u in S.elements] + if candidates: + paired_element = pf.sample(candidates) + result = pf.append(result, pf.merge(element, paired_element)) + pf.setminus(S.elements, paired_element) -# ---------------------------------------------------------------------# - -# utils - -def find_bias(S,clock,two_flag=False,higher_dim=False): - """ - Count unique values for both attributes, - select the attribute with exactly 2 types while the other has != 2 types - - Input Arguments: - S: set of elements to be experimented with - clock: stopwatch used to time primitive functions - two_flag: flag to indicate if the bias required needs only two attribute types - higher_dim: flag to indicate if the set of elements is 2-dimensional + stopwatch.stop() + return (result, stopwatch.get_elapsed_time()) - Output: - bias: the bias lol, the attribute the flip selected - """ - if higher_dim == True: - chunk_bias, serial_bias = None, None - attribute_counts = {attr: len(set(getattr(obj, attr) for obj in S)) - for attr in ["attribute1", "attribute2"]} - chunk_bias = find_bias(S, clock, two_flag) +def find_bias(S, clock, two_flag=False, higher_dim=False): + if isinstance(S, ElementSet): + elements = S.elements + else: + elements = S + + if higher_dim: + attribute_counts = { + attr: len(set(getattr(obj, attr) for obj in elements)) + for attr in ["attribute1", "attribute2"] + } + chunk_bias = find_bias(elements, clock, two_flag) clock.start() serial_bias = 'attribute1' if chunk_bias == 'attribute2' else 'attribute2' clock.stop() return (chunk_bias, serial_bias) else: - bias = None - attribute_counts = {attr: len(set(getattr(obj, attr) for obj in S)) - for attr in ["attribute1", "attribute2"]} + attribute_counts = { + attr: len(set(getattr(obj, attr) for obj in elements)) + for attr in ["attribute1", "attribute2"] + } if attribute_counts["attribute1"] == 2 and attribute_counts["attribute2"] != 2: - bias = "attribute1" if not two_flag else "attribute1" + return "attribute1" elif attribute_counts["attribute2"] == 2 and attribute_counts["attribute1"] != 2: - bias = "attribute2" if not two_flag else "attribute1" + return "attribute2" else: clock.start() - bias = "attribute1" if pf.flip(0.5) else "attribute2" # Default random selection + bias = "attribute1" if pf.flip(0.5) else "attribute2" clock.stop() - return bias \ No newline at end of file + return bias diff --git a/experiments.ipynb b/experiments.ipynb index ddf759e..4be28c0 100644 --- a/experiments.ipynb +++ b/experiments.ipynb @@ -112,7 +112,7 @@ "outputs": [ { "data": { - "image/png": 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" ] @@ -222,7 +222,7 @@ "\u001b[1;31mAttributeError\u001b[0m Traceback (most recent call last)", "Cell \u001b[1;32mIn[11], line 1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m times \u001b[38;5;241m=\u001b[39m \u001b[43mrunReordering\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtrain_1\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m20\u001b[39;49m\u001b[43m)\u001b[49m\n", "Cell \u001b[1;32mIn[10], line 6\u001b[0m, in \u001b[0;36mrunReordering\u001b[1;34m(element_set, n_runs)\u001b[0m\n\u001b[0;32m 4\u001b[0m time_list \u001b[38;5;241m=\u001b[39m []\n\u001b[0;32m 5\u001b[0m \u001b[38;5;66;03m# 1-D\u001b[39;00m\n\u001b[1;32m----> 6\u001b[0m time_list\u001b[38;5;241m.\u001b[39mappend(\u001b[43mcf\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43miterate\u001b[49m\u001b[43m(\u001b[49m\u001b[43melement_set\u001b[49m\u001b[43m)\u001b[49m[\u001b[38;5;241m1\u001b[39m])\n\u001b[0;32m 7\u001b[0m time_list\u001b[38;5;241m.\u001b[39mappend(cf\u001b[38;5;241m.\u001b[39mpalindrome(element_set)[\u001b[38;5;241m1\u001b[39m])\n\u001b[0;32m 8\u001b[0m time_list\u001b[38;5;241m.\u001b[39mappend(cf\u001b[38;5;241m.\u001b[39malternate(element_set)[\u001b[38;5;241m1\u001b[39m])\n", - "File \u001b[1;32mc:\\Users\\desig\\Desktop\\vs code\\LoT\\LoT-modeling\\cognitive_functions.py:10\u001b[0m, in \u001b[0;36miterate\u001b[1;34m(S)\u001b[0m\n\u001b[0;32m 7\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21miterate\u001b[39m(S: ElementSet): \u001b[38;5;66;03m# 112233 \u001b[39;00m\n\u001b[0;32m 8\u001b[0m \n\u001b[0;32m 9\u001b[0m \u001b[38;5;66;03m# preprocessing (not part of measured cognitive process)\u001b[39;00m\n\u001b[1;32m---> 10\u001b[0m n \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mlen\u001b[39m(\u001b[43mS\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43melements\u001b[49m) \u001b[38;5;66;03m# number of elements in the set\u001b[39;00m\n\u001b[0;32m 11\u001b[0m chunks \u001b[38;5;241m=\u001b[39m defaultdict(\u001b[38;5;28mlist\u001b[39m) \n\u001b[0;32m 12\u001b[0m stopwatch \u001b[38;5;241m=\u001b[39m Stopwatch()\n", + "File \u001b[1;32mc:\\Users\\desig\\OneDrive\\Desktop\\VS Code\\LoT Modeling\\LoT Code\\LoT-modeling\\cognitive_functions.py:10\u001b[0m, in \u001b[0;36miterate\u001b[1;34m(S)\u001b[0m\n\u001b[0;32m 7\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21miterate\u001b[39m(S: ElementSet): \u001b[38;5;66;03m# 112233 \u001b[39;00m\n\u001b[0;32m 8\u001b[0m \n\u001b[0;32m 9\u001b[0m \u001b[38;5;66;03m# preprocessing (not part of measured cognitive process)\u001b[39;00m\n\u001b[1;32m---> 10\u001b[0m n \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mlen\u001b[39m(\u001b[43mS\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43melements\u001b[49m) \u001b[38;5;66;03m# number of elements in the set\u001b[39;00m\n\u001b[0;32m 11\u001b[0m chunks \u001b[38;5;241m=\u001b[39m defaultdict(\u001b[38;5;28mlist\u001b[39m) \n\u001b[0;32m 12\u001b[0m stopwatch \u001b[38;5;241m=\u001b[39m Stopwatch()\n", "\u001b[1;31mAttributeError\u001b[0m: 'set' object has no attribute 'elements'" ] } diff --git a/midtest/midcf.py b/midtest/midcf.py new file mode 100644 index 0000000..d4cc343 --- /dev/null +++ b/midtest/midcf.py @@ -0,0 +1,273 @@ +import midpf as pf +from collections import defaultdict +from midutils import Stopwatch, Element, ElementSet, Associations + +# 1-D + +def iterate(S: ElementSet): # 112233 + + # preprocessing (not part of measured cognitive process) + n = len(S.elements) # number of elements in the set + chunks = defaultdict(list) + stopwatch = Stopwatch() + # --- # + # select attribute which chunking is based on + + ### ADD CODE HERE + """ graph algo here""" + bias = find_bias(S.elements, stopwatch) + for _ in range(n//2): + element = pf.sample(S.elements) + result = None + time_elapsed = None + + + # """ non graph algo here""" + bias = find_bias(S.elements, stopwatch) + stopwatch.start() + for _ in range(n): + element = pf.sample(S.elements) # select an element in the set + sorter = getattr(element, bias) + chunks[sorter].append(element) + pf.setminus(S.elements, element) + stopwatch.stop() + n = len(chunks) # reassign n + chunks = {tuple(v) for k, v in chunks.items()} + stopwatch.start() + result = [] + for _ in range(n): + chunk = pf.sample(chunks) + stopwatch.stop() + temp = list(chunk) + stopwatch.start() + result = pf.append(result, temp) + pf.setminus(chunks, chunk) + stopwatch.stop() + time_elapsed = stopwatch.get_elapsed_time() + + return (result, time_elapsed) + +def palindrome(S: ElementSet): + n = len(S.elements) // 2 + stopwatch = Stopwatch() + bias = find_bias(S.elements, stopwatch) + stopwatch.start() + basis, rev = [], [] + + while len(S.elements) > n: + element = pf.sample(S.elements) + if len(basis) == 0 or not any(pf.check_if_same_type(element, chosen, bias) for chosen in basis): + pf.pair(basis, element) + pf.setminus(S.elements, element) + + for _ in range(n): + element = pf.write_random(S.elements, bias, getattr(basis[n-1-_], bias)) + pf.pair(rev, element) + pf.setminus(S.elements, element) + + result = pf.append(basis, rev) + stopwatch.stop() + time_elapsed = stopwatch.get_elapsed_time() + return (result, time_elapsed) + +def alternate(S: ElementSet): + # 121212 + n = len(S.elements) # Number of elements in the ElementSet + stopwatch = Stopwatch() + + bias = find_bias(S.elements, stopwatch, two_flag=True) + result = [] + + while len(S.elements) > 0: + element = pf.sample(S.elements) + if len(result) == 0 or not pf.check_if_same_type(element, result[-1], bias): + pf.pair(result, element) + pf.setminus(S.elements, element) + + time_elapsed = stopwatch.get_elapsed_time() + return (result, time_elapsed) + + +def chaining(S: ElementSet, associations: dict): + # preprocessing (not part of measured cognitive process) + n = len(S.elements) # number of elements in the set + stopwatch = Stopwatch() + # --- # + stopwatch.start() + chunks = [] + result = [] + while (len(S.elements) > 0): + element = pf.sample(S.elements) + if element in associations.associations: + chunk = [] + pf.pair(chunk, element) + pf.setminus(S.elements, element) + while True: + next_element = pf.sample(S.elements) + if next_element == associations.associations[element]: + pf.pair(chunk, next_element) + pf.setminus(S.elements, next_element) + pf.pair(chunks, chunk) + break + else: + continue + else: + continue + result = chunks + stopwatch.stop() + time_elapsed = stopwatch.get_elapsed_time() + + return (result, time_elapsed) + +def seriate(S: ElementSet): + # 123123 + pass + +# -------- 2-D -------- # + +def serial_crossed(S: ElementSet): + n = len(S.elements) // 2 # number of elements in the basis + stopwatch = Stopwatch() + bias = find_bias(S.elements, stopwatch, higher_dim=True) + result = [] + while len(S.elements) > n: + element = pf.sample(S.elements) + if len(result) == 0 or pf.check_if_same_type(element, result[-1], bias[0]): + pf.pair(result, element) + pf.setminus(S.elements, element) + for _ in range(n): + element = pf.write_random(S.elements, bias[1], getattr(result[_], bias[1])) + pf.pair(result, element) + pf.setminus(S.elements, element) + time_elapsed = stopwatch.get_elapsed_time() + return (result, time_elapsed) + +def center_embedded(S: ElementSet): + n = len(S.elements) // 2 # number of elements in the basis + # + stopwatch = Stopwatch() + bias = find_bias(S.elements, stopwatch, higher_dim=True) + result = [] + while len(S.elements) > 0: + element = pf.sample(S.elements) + if len(result) == 0 or pf.check_if_same_type(element, result[-1], bias[0]): + pf.pair(result, element) + pf.setminus(S.elements, element) + if len(result) == n: + break + for _ in range(n): + element = pf.write_random(S.elements, bias[1], getattr(result[n - 1 - _], bias[1])) + pf.pair(result, element) + pf.setminus(S.elements, element) + stopwatch.stop() + time_elapsed = stopwatch.get_elapsed_time() + return (result, time_elapsed) + +def tail_recursive(S: ElementSet): + stopwatch = Stopwatch() + bias = find_bias(S.elements, stopwatch, two_flag=True, higher_dim=True) + stopwatch.start() + result = [] + while len(S.elements) > 0: + element = pf.sample(S.elements) + pf.setminus(S.elements, element) + paired_element = pf.write_random(S.elements, bias[0], getattr(element, bias[0])) + result = pf.append(result, pf.merge(element, paired_element)) + pf.setminus(S.elements, paired_element) + stopwatch.stop() + time_elapsed = stopwatch.get_elapsed_time() + return (result, time_elapsed) + + +# ---------------------------------------------------------------------# + +# utils + +def find_bias(S,clock,two_flag=False,higher_dim=False): + + #Count unique values for both attributes, + #select the attribute with exactly 2 types while the other has != 2 types + + #Input Arguments: + #S: set of elements to be experimented with + #clock: stopwatch used to time primitive functions + #two_flag: flag to indicate if the bias required needs only two attribute types + #higher_dim: flag to indicate if the set of elements is 2-dimensional + + #Output: + #bias: the bias lol, the attribute the flip selected + + if higher_dim == True: + chunk_bias, serial_bias = None, None + attribute_counts = {attr: len(set(getattr(obj, attr) for obj in S)) + for attr in ["attribute1", "attribute2"]} + chunk_bias = find_bias(S, clock, two_flag) + clock.start() + serial_bias = 'attribute1' if chunk_bias == 'attribute2' else 'attribute2' + clock.stop() + return (chunk_bias, serial_bias) + else: + bias = None + attribute_counts = {attr: len(set(getattr(obj, attr) for obj in S)) + for attr in ["attribute1", "attribute2"]} + if attribute_counts["attribute1"] == 2 and attribute_counts["attribute2"] != 2: + bias = "attribute1" if not two_flag else "attribute1" + elif attribute_counts["attribute2"] == 2 and attribute_counts["attribute1"] != 2: + bias = "attribute2" if not two_flag else "attribute1" + else: + clock.start() + bias = "attribute1" if pf.flip(0.5) else "attribute2" # Default random selection + clock.stop() + return bias +''' + +def find_bias(S, clock, two_flag=False, higher_dim=False): + + Count unique values for both attributes, + select the attribute with exactly 2 types while the other has != 2 types + + Input Arguments: + S: set of elements or ElementSet + clock: stopwatch used to time primitive functions + two_flag: flag to indicate if the bias required needs only two attribute types + higher_dim: flag to indicate if the set of elements is 2-dimensional + + Output: + bias: the attribute selected + + # Handle both raw set/list and ElementSet + if isinstance(S, ElementSet): + elements = S.elements + else: + elements = S + + if higher_dim: + chunk_bias, serial_bias = None, None + attribute_counts = { + attr: len(set(getattr(obj, attr) for obj in elements)) + for attr in ["attribute1", "attribute2"] + } + chunk_bias = find_bias(elements, clock, two_flag) + clock.start() + serial_bias = 'attribute1' if chunk_bias == 'attribute2' else 'attribute2' + clock.stop() + return (chunk_bias, serial_bias) + else: + bias = None + attribute_counts = { + attr: len(set(getattr(obj, attr) for obj in elements)) + for attr in ["attribute1", "attribute2"] + } + + if attribute_counts["attribute1"] == 2 and attribute_counts["attribute2"] != 2: + bias = "attribute1" + elif attribute_counts["attribute2"] == 2 and attribute_counts["attribute1"] != 2: + bias = "attribute2" + else: + clock.start() + bias = "attribute1" if pf.flip(0.5) else "attribute2" + clock.stop() + + return bias + +''' \ No newline at end of file diff --git a/midtest/midpf.py b/midtest/midpf.py new file mode 100644 index 0000000..d5338b6 --- /dev/null +++ b/midtest/midpf.py @@ -0,0 +1,160 @@ +import random + +SEED = 42 +random.seed(SEED) +# Functions on lists (strings) + +def pair(L, C): + """Concatenates character C onto list L + Time complexity: O(1) amortized for lists, O(n) for strings""" + L.append(C) # O(1) amortized + +def append(X, Y): + """Append lists X and Y + Time complexity: O(n+m) where n=len(X), m=len(Y)""" + return X + Y + +# Random functions + +def flip(p): + """Returns true with probability p + Time complexity: O(1)""" + return random.random() < p + +# Set functions + +# def union(set1, set2): +# """Union of twos sets +# Time complexity: O(len(set1) + len(set2))""" +# return set1 | set2 + + +def setminus(set1, s): + #Remove a string from a set + #Time complexity: O(1) for single item, O(len(s)) for set s + set1.remove(s) + +def sample(collection): + #Sample from a set or list of strings. + #Time complexity: O(1) for non-empty sets if using random.choice, + #O(n) for lists using random.sample. + if not collection: + return None + + if isinstance(collection, set): + collection = tuple(collection) # Convert to tuple for sampling + + return random.sample(collection, 1)[0] + + +# # Function calls with memoization + +# memoization_cache = {} +# def F(z): +# """Generic factor function +# Time complexity: Depends on implementation""" +# pass + +# def Fm(z): +# """Memoized version of factor function +# Time complexity: O(1) for repeated calls""" +# if z not in memoization_cache: +# memoization_cache[z] = F(z) +# return memoization_cache[z] + +# Token-related functions + +# def create_tokens(): +# """Initiates a list of tokens [A1, A2, B3, B4] +# Time complexity: O(1)""" +# return ["A1", "A2", "B3", "B4"] + +def add(T, list): + """Adds token T to a list + Time complexity: O(n) due to copying""" + result = list.copy() + result.append(T) + return result + +def remove(T, list): + """Removes token T from a list + Time complexity: O(n) for search and removal""" + result = list.copy() + if T in result: + result.remove(T) + return result + +def check_if_same_type(e1, e2, bias): + """Returns True if tokens are same type + Time complexity: O(1)""" + return getattr(e1,bias) == getattr(e2,bias) + + + +def write_random(S, bias, type): + #Returns one unused member of particular type + #Time complexity: O(n) to filter tokens + for element in S: + if getattr(element, bias) == type: + return element + #type_elements = [u for u, v, d in G.edges(data=True) if v == type and d["label"] == bias] + + ### WRITE CODE + ### maybe add a random list shuffling thing here + ### to make it less predictable + + pass + + + +def implement(FUN, N): + """Keeps implementing a function N times + Time complexity: O(N * T) where T is time of FUN""" + results = [] + for _ in range(N): + results.append(FUN()) + return results + +def write_all(S, bias, type): + """Returns a sequential list of all members of a type + Time complexity: O(n) where n is number of tokens""" + result = [] + for element in S: + if getattr(element, bias) == type: + result = pair(result, element) + return result + +# Additional functions + +def list_create(M): + """Create a blank list with slots for M items + Time complexity: O(M)""" + return [None] * M + +def merge(I, J): + """Merge two items I and J to create a list + Time complexity: O(1)""" + return [I, J] + +def remove_item(I, L): + """Remove item I from list L + Time complexity: O(n) for search and removal""" + result = L.copy() + if I in result: + result.remove(I) + return result + +def dim_set(D): + """Create a set containing items classified by dimension D + Time complexity: O(n*m) where n is number of items, m is time of D function""" + def classify(items, dimension_func=D): + result = set() + for item in items: + result.add(dimension_func(item)) + return result + return classify + +def write_all_set(S): + """Write all items belonging to a particular set S + Time complexity: O(n log n) due to sorting""" + return " - ".join(sorted(S)) \ No newline at end of file diff --git a/midtest/midtest.ipynb b/midtest/midtest.ipynb new file mode 100644 index 0000000..47bae71 --- /dev/null +++ b/midtest/midtest.ipynb @@ -0,0 +1,296 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "081f22f1", + "metadata": {}, + "outputs": [], + "source": [ + "from midutils import Element, KComplexity, ElementSet, Associations\n", + "import midcf as cf" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "831c5eaf", + "metadata": {}, + "outputs": [], + "source": [ + "a = Element('A1','A','1')\n", + "b = Element('A2','A','2')\n", + "c = Element('B1','B','1')\n", + "d = Element('B2','B','2')" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "030b28dc", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "18\n", + "{'add': 0, 'append': 2, 'check_if_same_type': 0, 'dim_set': 0, 'flip': 2, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 0, 'remove': 0, 'remove_item': 0, 'sample': 8, 'setminus': 6, 'write_all': 0, 'write_all_set': 0, 'write_random': 0}\n", + "Result: [Element(object=A1, attribute 1=A, attribute 2=1), Element(object=A2, attribute 1=A, attribute 2=2), Element(object=B2, attribute 1=B, attribute 2=2), Element(object=B1, attribute 1=B, attribute 2=1)]\n", + "Elapsed time: 3.140006447210908e-05\n" + ] + } + ], + "source": [ + "element_set = {a,b,c,d}\n", + "S = ElementSet(element_set)\n", + "kc = KComplexity()\n", + "result, elapsed_time = cf.iterate(S)\n", + "print(kc.get_k_complexity())\n", + "print(kc.get_prim_counts())\n", + "print(\"Result:\", result)\n", + "print(\"Elapsed time:\", elapsed_time)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "034a7977", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "15\n", + "{'add': 0, 'append': 1, 'check_if_same_type': 1, 'dim_set': 0, 'flip': 1, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 4, 'remove': 0, 'remove_item': 0, 'sample': 2, 'setminus': 4, 'write_all': 0, 'write_all_set': 0, 'write_random': 2}\n", + "Result: [Element(object=B2, attribute 1=B, attribute 2=2), Element(object=A2, attribute 1=A, attribute 2=2), Element(object=A1, attribute 1=A, attribute 2=1), Element(object=B1, attribute 1=B, attribute 2=1)]\n", + "Elapsed time: 3.8300000596791506e-05\n" + ] + } + ], + "source": [ + "element_set = {a,b,c,d}\n", + "S = ElementSet(element_set)\n", + "kc = KComplexity()\n", + "result, elapsed_time = cf.palindrome(S)\n", + "print(kc.get_k_complexity())\n", + "print(kc.get_prim_counts())\n", + "print(\"Result:\", result)\n", + "print(\"Elapsed time:\", elapsed_time)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "df882383", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "16\n", + "{'add': 0, 'append': 0, 'check_if_same_type': 3, 'dim_set': 0, 'flip': 1, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 4, 'remove': 0, 'remove_item': 0, 'sample': 4, 'setminus': 4, 'write_all': 0, 'write_all_set': 0, 'write_random': 0}\n", + "Result: [Element(object=A2, attribute 1=A, attribute 2=2), Element(object=A1, attribute 1=A, attribute 2=1), Element(object=B2, attribute 1=B, attribute 2=2), Element(object=B1, attribute 1=B, attribute 2=1)]\n", + "Elapsed time: 4.099973011761904e-06\n" + ] + } + ], + "source": [ + "element_set = {a,b,c,d}\n", + "S = ElementSet(element_set)\n", + "kc = KComplexity()\n", + "result, elapsed_time = cf.alternate(S)\n", + "print(kc.get_k_complexity())\n", + "print(kc.get_prim_counts())\n", + "print(\"Result:\", result)\n", + "print(\"Elapsed time:\", elapsed_time)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "da9b45ff", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "18\n", + "{'add': 0, 'append': 0, 'check_if_same_type': 0, 'dim_set': 0, 'flip': 0, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 6, 'remove': 0, 'remove_item': 0, 'sample': 8, 'setminus': 4, 'write_all': 0, 'write_all_set': 0, 'write_random': 0}\n", + "Result: [[Element(object=A1, attribute 1=A, attribute 2=1), Element(object=A2, attribute 1=A, attribute 2=2)], [Element(object=B1, attribute 1=B, attribute 2=1), Element(object=B2, attribute 1=B, attribute 2=2)]]\n", + "Elapsed time: 0.00010889998520724475\n" + ] + } + ], + "source": [ + "element_set = {a,b,c,d}\n", + "assoc = Associations({a: b, c: d})\n", + "S = ElementSet(element_set, assoc)\n", + "kc = KComplexity()\n", + "\n", + "result, elapsed_time = cf.chaining(S, assoc)\n", + "print(kc.get_k_complexity())\n", + "print(kc.get_prim_counts())\n", + "print(\"Result:\", result)\n", + "print(\"Elapsed time:\", elapsed_time)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "590c9d20", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "0\n", + "{'add': 0, 'append': 0, 'check_if_same_type': 0, 'dim_set': 0, 'flip': 0, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 0, 'remove': 0, 'remove_item': 0, 'sample': 0, 'setminus': 0, 'write_all': 0, 'write_all_set': 0, 'write_random': 0}\n", + "Result: [[Element(object=A1, attribute 1=A, attribute 2=1), Element(object=A2, attribute 1=A, attribute 2=2)], [Element(object=B1, attribute 1=B, attribute 2=1), Element(object=B2, attribute 1=B, attribute 2=2)]]\n", + "Elapsed time: 0.00010889998520724475\n" + ] + } + ], + "source": [ + "element_set = {a,b,c,d}\n", + "S = ElementSet(element_set)\n", + "kc = KComplexity()\n", + "cf.seriate(S)\n", + "print(kc.get_k_complexity())\n", + "print(kc.get_prim_counts())\n", + "print(\"Result:\", result)\n", + "print(\"Elapsed time:\", elapsed_time)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "7e2d4e07", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "14\n", + "{'add': 0, 'append': 0, 'check_if_same_type': 1, 'dim_set': 0, 'flip': 1, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 4, 'remove': 0, 'remove_item': 0, 'sample': 2, 'setminus': 4, 'write_all': 0, 'write_all_set': 0, 'write_random': 2}\n", + "Result: [Element(object=B2, attribute 1=B, attribute 2=2), Element(object=B1, attribute 1=B, attribute 2=1), Element(object=A2, attribute 1=A, attribute 2=2), Element(object=A1, attribute 1=A, attribute 2=1)]\n", + "Elapsed time: 7.199996616691351e-06\n" + ] + } + ], + "source": [ + "element_set = {a,b,c,d}\n", + "S = ElementSet(element_set)\n", + "kc = KComplexity()\n", + "result, elapsed_time = cf.serial_crossed(S)\n", + "print(kc.get_k_complexity())\n", + "print(kc.get_prim_counts())\n", + "print(\"Result:\", result)\n", + "print(\"Elapsed time:\", elapsed_time)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "092f34e3", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "14\n", + "{'add': 0, 'append': 0, 'check_if_same_type': 1, 'dim_set': 0, 'flip': 1, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 4, 'remove': 0, 'remove_item': 0, 'sample': 2, 'setminus': 4, 'write_all': 0, 'write_all_set': 0, 'write_random': 2}\n", + "Result: [Element(object=A1, attribute 1=A, attribute 2=1), Element(object=A2, attribute 1=A, attribute 2=2), Element(object=B2, attribute 1=B, attribute 2=2), Element(object=B1, attribute 1=B, attribute 2=1)]\n", + "Elapsed time: 7.700000423938036e-06\n" + ] + } + ], + "source": [ + "element_set = {a,b,c,d}\n", + "S = ElementSet(element_set)\n", + "kc = KComplexity()\n", + "result, elapsed_time = cf.center_embedded(S)\n", + "print(kc.get_k_complexity())\n", + "print(kc.get_prim_counts())\n", + "print(\"Result:\", result)\n", + "print(\"Elapsed time:\", elapsed_time)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "ca81ceaf", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "13\n", + "{'add': 0, 'append': 2, 'check_if_same_type': 0, 'dim_set': 0, 'flip': 1, 'implement': 0, 'list_create': 0, 'merge': 2, 'pair': 0, 'remove': 0, 'remove_item': 0, 'sample': 2, 'setminus': 4, 'write_all': 0, 'write_all_set': 0, 'write_random': 2}\n", + "Result: [Element(object=B1, attribute 1=B, attribute 2=1), Element(object=B2, attribute 1=B, attribute 2=2), Element(object=A1, attribute 1=A, attribute 2=1), Element(object=A2, attribute 1=A, attribute 2=2)]\n", + "Elapsed time: 5.110001075081527e-05\n" + ] + } + ], + "source": [ + "element_set = {a,b,c,d}\n", + "S = ElementSet(element_set)\n", + "kc = KComplexity()\n", + "result, elapsed_time = cf.tail_recursive(S)\n", + "print(kc.get_k_complexity())\n", + "print(kc.get_prim_counts())\n", + "print(\"Result:\", result)\n", + "print(\"Elapsed time:\", elapsed_time)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "5c80b83a", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "S.visualize()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "lot_venv", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.13.5" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/midtest/midutils.py b/midtest/midutils.py new file mode 100644 index 0000000..74694e5 --- /dev/null +++ b/midtest/midutils.py @@ -0,0 +1,182 @@ +from functools import cached_property, cache, partial +import time +from operator import attrgetter +from tabulate import tabulate +import networkx as nx +from typing import Literal +import matplotlib.pyplot as plt +from dataclasses import dataclass +import midpf as pf +import importlib + +# ---------------------------------------------------------------------# + +""" +@dataclass +class Element: # n-dimensional element + name : str + attribute1 : int | float | str + attribute2 : int | float | str | None = None + def __repr__(self): + return f"Element(object={self.name}, attribute 1={self.attribute1}, attribute 2={self.attribute2})" + def __str__(self): + return f"{self.name}, {self.attribute1}, {self.attribute2})" +""" + +class Element: # n-dimensional element + def __init__(self, name, attribute1, attribute2=None): + self.name = name + self.attribute1 = attribute1 + self.attribute2 = attribute2 + def __repr__(self): + return f"Element(object={self.name}, attribute 1={self.attribute1}, attribute 2={self.attribute2})" + def __str__(self): + return f"{self.name}, {self.attribute1}, {self.attribute2})" + +@dataclass +class Associations: # n-dimensional association + associations: dict + positional: bool = False + def __repr__(self): + raise NotImplementedError + def build_updates(self, graph): + if self.positional: + for key, value in self.associations.items(): + nx.set_node_attributes(graph, {key.name: {"position": value}}) + else: + for key, value in self.associations.items(): + graph.add_edge(key.name, value.name, label="precedes", directed=True) + + +class ElementSet: # n-dimensional element set + def __init__(self, elements: set, associations: Associations = None): + self.elements = elements + self.associations = associations + self.graph = self.build_graph() + def __repr__(self): + raise NotImplementedError + def build_graph(self): + G = nx.MultiGraph() # Create a directed graph + for obj in self.elements: + G.add_node(obj.name, type='element') # Add object as a node + G.add_node(obj.attribute1, type='attribute1') # Add color as a node + G.add_edge(obj.name, obj.attribute1, label="attribute") # Add directed edge with label + if obj.attribute2: + # If the object has a second attribute, add it as a node and edge + G.add_node(obj.attribute2, type='attribute2') # Add shape as a node + G.add_edge(obj.name, obj.attribute2, label="attribute") + if self.associations: + self.associations.build_updates(G) # Build associations + if hasattr(self, 'graph') and self.graph: + self.graph = G + return G + def visualize(self): + plt.figure(figsize=(10, 8)) + pos = nx.spring_layout(self.graph) + + # Draw nodes with different colors based on type + node_colors = [] + for node, data in self.graph.nodes(data=True): + if data['type'] == 'element': + node_colors.append('skyblue') + elif data['type'] == 'attribute1': + node_colors.append('lightgreen') + elif data['type'] == 'attribute2': + node_colors.append('lightcoral') + + nx.draw(self.graph, pos, with_labels=True, node_color=node_colors, node_size=500, font_size=10) + edge_labels = nx.get_edge_attributes(self.graph, 'label') + nx.draw_networkx_edge_labels(self.graph, pos, edge_labels=edge_labels) + plt.show() + @cached_property + def attribute1_types(self): + """Returns a set of unique attribute1 types.""" + return set(obj.attribute1 for obj in self.elements) + @cached_property + def attribute2_types(self): + """Returns a set of unique attribute2 types.""" + return set(obj.attribute2 for obj in self.elements if obj.attribute2 is not None) + def attribute_items(self, attribute): + def get_type(type_): + + return getattr(self, f"{attribute}_types", set()) + + + + + +def pretty_view(sequence): + """Prints a sequence of elements in a pretty format.""" + cute = list(zip(*map(attrgetter("name", "attribute1", "attribute2"), sequence))) + # Print as a table + print(tabulate(zip(*cute), headers=["object", "attribute 1", "attribute 2"], tablefmt="grid")) + + + +# ---------------------------------------------------------------------# + +class Stopwatch: + def __init__(self): + self._start_time = None + self._elapsed_time = 0 + self._running = False + + def start(self): + """Start or resume the stopwatch.""" + if not self._running: + self._start_time = time.perf_counter() - self._elapsed_time + self._running = True + # print("Stopwatch started.") + + def stop(self): + """Stop the stopwatch and display the elapsed time.""" + if self._running: + self._elapsed_time = time.perf_counter() - self._start_time + self._running = False + # print(f"Stopwatch stopped. Elapsed time: {self._elapsed_time:.2f} seconds.") + + def reset(self): + """Reset the stopwatch to zero.""" + self._elapsed_time = 0 + if self._running: + self._start_time = time.perf_counter() + # print("Stopwatch reset.") + + def get_elapsed_time(self): + """Get the current elapsed time without stopping the stopwatch.""" + if self._running: + return time.perf_counter() - self._start_time + return self._elapsed_time + +class KComplexity: + def __init__(self): + self.prim = importlib.import_module('midpf') + self.call_counts = {} + self._wrap_prim_functions() + + def _wrap_prim_functions(self): + for name in dir(self.prim): + func = getattr(self.prim, name) + if callable(func) and not name.startswith("__"): + self.call_counts[name] = 0 + wrapper_func = self._make_wrapper(func, name) + setattr(self.prim, name, wrapper_func) + + def _make_wrapper(self, func, name): + def wrapper(*args, **kwargs): + self.call_counts[name] += 1 + return func(*args, **kwargs) + return wrapper + + """get dictionary of each prim function call count""" + def get_prim_counts(self): + return dict(self.call_counts) + + """get total number of prim function calls""" + def get_k_complexity(self): + return sum(self.call_counts.values()) + + """reset all prim function call counts to zero""" + def reset(self): + for key in self.call_counts: + self.call_counts[key] = 0 \ No newline at end of file diff --git a/newprim.py b/newprim.py new file mode 100644 index 0000000..3ff9241 --- /dev/null +++ b/newprim.py @@ -0,0 +1,223 @@ +import random + +SEED = 42 +random.seed(SEED) +# Functions on lists (strings) + +def pair(L, C): + """Concatenates character C onto list L + Time complexity: O(1) amortized for lists, O(n) for strings""" + L.append(C) # O(1) amortized + +def append(X, Y): + """Append lists X and Y + Time complexity: O(n+m) where n=len(X), m=len(Y)""" + return X + Y + +# Random functions + +def flip(p): + """Returns true with probability p + Time complexity: O(1)""" + return random.random() < p + +# Set functions + +# def union(set1, set2): +# """Union of twos sets +# Time complexity: O(len(set1) + len(set2))""" +# return set1 | set2 + +""" +def setminus(set1, s): + #Remove a string from a set + #Time complexity: O(1) for single item, O(len(s)) for set s + set1.remove(s) +""" + +def setminus(set1, s): + """ + Removes element `s` from `set1`, which may be a set, list, or ElementSet. + Time complexity: + - O(1) for sets and ElementSet + - O(n) for lists + """ + if hasattr(set1, "elements"): # ElementSet + try: + set1.elements.remove(s) + set1.graph = set1.build_graph() # Sync graph with element change + except KeyError: + pass # Already removed or not found + elif isinstance(set1, set) or isinstance(set1, list): + set1.remove(s) + else: + raise TypeError(f"setminus does not support type: {type(set1)}") + + +""" + +def sample(collection): + #Sample from a set or list of strings. + #Time complexity: O(1) for non-empty sets if using random.choice, + #O(n) for lists using random.sample. + if not collection: + return None + + if isinstance(collection, set): + collection = tuple(collection) # Convert to tuple for sampling + + return random.sample(collection, 1)[0] + +""" + +def sample(collection): + """ + Samples a single Element from an ElementSet or a collection of Elements. + + Args: + collection: An ElementSet, set, list, or tuple of Element objects. + + Returns: + A single randomly selected Element. + """ + if not collection: + return None + + # Handle ElementSet + if hasattr(collection, 'elements'): + collection = collection.elements + + # Make sure it's a sequence + if isinstance(collection, set): + collection = tuple(collection) + + return random.sample(collection, 1)[0] + + +# # Function calls with memoization + +# memoization_cache = {} +# def F(z): +# """Generic factor function +# Time complexity: Depends on implementation""" +# pass + +# def Fm(z): +# """Memoized version of factor function +# Time complexity: O(1) for repeated calls""" +# if z not in memoization_cache: +# memoization_cache[z] = F(z) +# return memoization_cache[z] + +# Token-related functions + +# def create_tokens(): +# """Initiates a list of tokens [A1, A2, B3, B4] +# Time complexity: O(1)""" +# return ["A1", "A2", "B3", "B4"] + +def add(T, list): + """Adds token T to a list + Time complexity: O(n) due to copying""" + result = list.copy() + result.append(T) + return result + +def remove(T, list): + """Removes token T from a list + Time complexity: O(n) for search and removal""" + result = list.copy() + if T in result: + result.remove(T) + return result + +def check_if_same_type(e1, e2, bias): + """Returns True if tokens are same type + Time complexity: O(1)""" + return getattr(e1,bias) == getattr(e2,bias) + +""" + +def write_random(G, bias, type): + #Returns one unused member of particular type + #Time complexity: O(n) to filter tokens + # for element in S: + # if getattr(element, bias) == type: + # return element + type_elements = [u for u, v, d in G.edges(data=True) if v == type and d["label"] == bias] + + ### WRITE CODE + ### maybe add a random list shuffling thing here + ### to make it less predictable + + pass +""" + +def write_random(S, bias, type): + """ + Returns a random element from S that matches a given bias and type. + Works whether S is an ElementSet or raw graph. + """ + G = S.graph if hasattr(S, "graph") else S # Unwrap ElementSet if needed + + type_elements = [u for u, v, d in G.edges(data=True) if v == type and d["label"] == bias] + if not type_elements: + return None + + element_name = random.choice(type_elements) + for obj in S.elements if hasattr(S, "elements") else S: + if getattr(obj, bias) == type and obj.name == element_name: + return obj + + +def implement(FUN, N): + """Keeps implementing a function N times + Time complexity: O(N * T) where T is time of FUN""" + results = [] + for _ in range(N): + results.append(FUN()) + return results + +def write_all(S, bias, type): + """Returns a sequential list of all members of a type + Time complexity: O(n) where n is number of tokens""" + result = [] + for element in S: + if getattr(element, bias) == type: + result = pair(result, element) + return result + +# Additional functions + +def list_create(M): + """Create a blank list with slots for M items + Time complexity: O(M)""" + return [None] * M + +def merge(I, J): + """Merge two items I and J to create a list + Time complexity: O(1)""" + return [I, J] + +def remove_item(I, L): + """Remove item I from list L + Time complexity: O(n) for search and removal""" + result = L.copy() + if I in result: + result.remove(I) + return result + +def dim_set(D): + """Create a set containing items classified by dimension D + Time complexity: O(n*m) where n is number of items, m is time of D function""" + def classify(items, dimension_func=D): + result = set() + for item in items: + result.add(dimension_func(item)) + return result + return classify + +def write_all_set(S): + """Write all items belonging to a particular set S + Time complexity: O(n log n) due to sorting""" + return " - ".join(sorted(S)) \ No newline at end of file diff --git a/newtest.ipynb b/newtest.ipynb new file mode 100644 index 0000000..ae74e8a --- /dev/null +++ b/newtest.ipynb @@ -0,0 +1,296 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "081f22f1", + "metadata": {}, + "outputs": [], + "source": [ + "from utils import Element, KComplexity, ElementSet, Associations\n", + "import cognitive_functions as cf" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "831c5eaf", + "metadata": {}, + "outputs": [], + "source": [ + "a = Element('A1','A','1')\n", + "b = Element('A2','A','2')\n", + "c = Element('B1','B','1')\n", + "d = Element('B2','B','2')" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "030b28dc", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "18\n", + "{'add': 0, 'append': 2, 'check_if_same_type': 0, 'dim_set': 0, 'flip': 2, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 0, 'remove': 0, 'remove_item': 0, 'sample': 8, 'setminus': 6, 'write_all': 0, 'write_all_set': 0, 'write_random': 0}\n", + "Result: [Element(object=A2, attribute 1=A, attribute 2=2), Element(object=A1, attribute 1=A, attribute 2=1), Element(object=B1, attribute 1=B, attribute 2=1), Element(object=B2, attribute 1=B, attribute 2=2)]\n", + "Elapsed time: 3.0399998649954796e-05\n" + ] + } + ], + "source": [ + "element_set = {a,b,c,d}\n", + "S = ElementSet(element_set)\n", + "kc = KComplexity()\n", + "result, elapsed_time = cf.iterate(S)\n", + "print(kc.get_k_complexity())\n", + "print(kc.get_prim_counts())\n", + "print(\"Result:\", result)\n", + "print(\"Elapsed time:\", elapsed_time)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "034a7977", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "9\n", + "{'add': 0, 'append': 1, 'check_if_same_type': 1, 'dim_set': 0, 'flip': 1, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 2, 'remove': 0, 'remove_item': 0, 'sample': 2, 'setminus': 2, 'write_all': 0, 'write_all_set': 0, 'write_random': 0}\n", + "Result: [Element(object=B1, attribute 1=B, attribute 2=1), Element(object=A1, attribute 1=A, attribute 2=1)]\n", + "Elapsed time: 7.37000082153827e-05\n" + ] + } + ], + "source": [ + "element_set = {a,b,c,d}\n", + "S = ElementSet(element_set)\n", + "kc = KComplexity()\n", + "result, elapsed_time = cf.palindrome(S)\n", + "print(kc.get_k_complexity())\n", + "print(kc.get_prim_counts())\n", + "print(\"Result:\", result)\n", + "print(\"Elapsed time:\", elapsed_time)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "df882383", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "16\n", + "{'add': 0, 'append': 0, 'check_if_same_type': 3, 'dim_set': 0, 'flip': 1, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 4, 'remove': 0, 'remove_item': 0, 'sample': 4, 'setminus': 4, 'write_all': 0, 'write_all_set': 0, 'write_random': 0}\n", + "Result: [Element(object=A1, attribute 1=A, attribute 2=1), Element(object=A2, attribute 1=A, attribute 2=2), Element(object=B1, attribute 1=B, attribute 2=1), Element(object=B2, attribute 1=B, attribute 2=2)]\n", + "Elapsed time: 5.4000120144337416e-06\n" + ] + } + ], + "source": [ + "element_set = {a,b,c,d}\n", + "S = ElementSet(element_set)\n", + "kc = KComplexity()\n", + "result, elapsed_time = cf.alternate(S)\n", + "print(kc.get_k_complexity())\n", + "print(kc.get_prim_counts())\n", + "print(\"Result:\", result)\n", + "print(\"Elapsed time:\", elapsed_time)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "da9b45ff", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "15\n", + "{'add': 0, 'append': 0, 'check_if_same_type': 0, 'dim_set': 0, 'flip': 0, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 6, 'remove': 0, 'remove_item': 0, 'sample': 5, 'setminus': 4, 'write_all': 0, 'write_all_set': 0, 'write_random': 0}\n", + "Result: [[Element(object=B1, attribute 1=B, attribute 2=1), Element(object=B2, attribute 1=B, attribute 2=2)], [Element(object=A1, attribute 1=A, attribute 2=1), Element(object=A2, attribute 1=A, attribute 2=2)]]\n", + "Elapsed time: 3.7699996028095484e-05\n" + ] + } + ], + "source": [ + "element_set = {a,b,c,d}\n", + "assoc = Associations({a: b, c: d})\n", + "S = ElementSet(element_set, assoc)\n", + "kc = KComplexity()\n", + "\n", + "result, elapsed_time = cf.chaining(S, assoc)\n", + "print(kc.get_k_complexity())\n", + "print(kc.get_prim_counts())\n", + "print(\"Result:\", result)\n", + "print(\"Elapsed time:\", elapsed_time)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "590c9d20", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "0\n", + "{'add': 0, 'append': 0, 'check_if_same_type': 0, 'dim_set': 0, 'flip': 0, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 0, 'remove': 0, 'remove_item': 0, 'sample': 0, 'setminus': 0, 'write_all': 0, 'write_all_set': 0, 'write_random': 0}\n", + "Result: [[Element(object=B1, attribute 1=B, attribute 2=1), Element(object=B2, attribute 1=B, attribute 2=2)], [Element(object=A1, attribute 1=A, attribute 2=1), Element(object=A2, attribute 1=A, attribute 2=2)]]\n", + "Elapsed time: 3.7699996028095484e-05\n" + ] + } + ], + "source": [ + "element_set = {a,b,c,d}\n", + "S = ElementSet(element_set)\n", + "kc = KComplexity()\n", + "cf.seriate(S)\n", + "print(kc.get_k_complexity())\n", + "print(kc.get_prim_counts())\n", + "print(\"Result:\", result)\n", + "print(\"Elapsed time:\", elapsed_time)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "7e2d4e07", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "28\n", + "{'add': 0, 'append': 0, 'check_if_same_type': 11, 'dim_set': 0, 'flip': 1, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 2, 'remove': 0, 'remove_item': 0, 'sample': 12, 'setminus': 2, 'write_all': 0, 'write_all_set': 0, 'write_random': 0}\n", + "Result: [Element(object=B2, attribute 1=B, attribute 2=2), Element(object=A2, attribute 1=A, attribute 2=2)]\n", + "Elapsed time: 6.799993570894003e-06\n" + ] + } + ], + "source": [ + "element_set = {a,b,c,d}\n", + "S = ElementSet(element_set)\n", + "kc = KComplexity()\n", + "result, elapsed_time = cf.serial_crossed(S)\n", + "print(kc.get_k_complexity())\n", + "print(kc.get_prim_counts())\n", + "print(\"Result:\", result)\n", + "print(\"Elapsed time:\", elapsed_time)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "092f34e3", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "8\n", + "{'add': 0, 'append': 0, 'check_if_same_type': 1, 'dim_set': 0, 'flip': 1, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 2, 'remove': 0, 'remove_item': 0, 'sample': 2, 'setminus': 2, 'write_all': 0, 'write_all_set': 0, 'write_random': 0}\n", + "Result: [Element(object=A1, attribute 1=A, attribute 2=1), Element(object=A2, attribute 1=A, attribute 2=2)]\n", + "Elapsed time: 7.399969035759568e-06\n" + ] + } + ], + "source": [ + "element_set = {a,b,c,d}\n", + "S = ElementSet(element_set)\n", + "kc = KComplexity()\n", + "result, elapsed_time = cf.center_embedded(S)\n", + "print(kc.get_k_complexity())\n", + "print(kc.get_prim_counts())\n", + "print(\"Result:\", result)\n", + "print(\"Elapsed time:\", elapsed_time)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "ca81ceaf", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "9\n", + "{'add': 0, 'append': 0, 'check_if_same_type': 0, 'dim_set': 0, 'flip': 1, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 0, 'remove': 0, 'remove_item': 0, 'sample': 4, 'setminus': 4, 'write_all': 0, 'write_all_set': 0, 'write_random': 0}\n", + "Result: []\n", + "Elapsed time: 9.6399977337569e-05\n" + ] + } + ], + "source": [ + "element_set = {a,b,c,d}\n", + "S = ElementSet(element_set)\n", + "kc = KComplexity()\n", + "result, elapsed_time = cf.tail_recursive(S)\n", + "print(kc.get_k_complexity())\n", + "print(kc.get_prim_counts())\n", + "print(\"Result:\", result)\n", + "print(\"Elapsed time:\", elapsed_time)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "5c80b83a", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "S.visualize()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "lot_venv", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.13.5" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/oldtest/oldcf.py b/oldtest/oldcf.py new file mode 100644 index 0000000..566f981 --- /dev/null +++ b/oldtest/oldcf.py @@ -0,0 +1,271 @@ +import oldpf as pf +from collections import defaultdict +from oldutils import Stopwatch, Element, ElementSet, Associations + +# 1-D + +def iterate(S): # 112233 + + # preprocessing (not part of measured cognitive process) + n = len(S) # number of elements in the set + chunks = defaultdict(list) + stopwatch = Stopwatch() + # --- # + # select attribute which chunking is based on + + ### ADD CODE HERE + """ graph algo here""" + bias = find_bias(S, stopwatch) + for _ in range(n//2): + element = pf.sample(S) + result = None + time_elapsed = None + + + # """ non graph algo here""" + bias = find_bias(S, stopwatch) + stopwatch.start() + for _ in range(n): + element = pf.sample(S) # select an element in the set + sorter = getattr(element, bias) + chunks[sorter].append(element) + pf.setminus(S, element) + stopwatch.stop() + n = len(chunks) # reassign n + chunks = {tuple(v) for k, v in chunks.items()} + stopwatch.start() + result = [] + for _ in range(n): + chunk = pf.sample(chunks) + stopwatch.stop() + temp = list(chunk) + stopwatch.start() + result = pf.append(result, temp) + pf.setminus(chunks, chunk) + stopwatch.stop() + time_elapsed = stopwatch.get_elapsed_time() + + return (result, time_elapsed) + +def palindrome(S): + # 123321 + # preprocessing (not part of measured cognitive process) + n = len(S) // 2 # number of elements in basis + stopwatch = Stopwatch() + # select attribute which chunking is based on + bias = find_bias(S, stopwatch) + stopwatch.start() + basis, rev = [], [] + # write_random() based implementation + ### WRITE CODE HERE + while (len(S) > n): + element = pf.sample(S) + if len(basis)==0 or not (any(pf.check_if_same_type(element, chosen, bias) for chosen in basis)): + pf.pair(basis, element) + pf.setminus(S, element) + for _ in range(n): + element = pf.write_random(S, bias, getattr(basis[n-1-_], bias)) + pf.pair(rev,element) + pf.setminus(S, element) + result = pf.append(basis,rev) + stopwatch.stop() + time_elapsed = stopwatch.get_elapsed_time() + + return (result, time_elapsed) + +def alternate(S): + # 121212 + # preprocessing (not part of measured cognitive process) + n = len(S) # number of elements in the set + stopwatch = Stopwatch() + # --- # + # select attribute which chunking is based on + ### ADD CODE HERE + ### subject knows what types of attributes are there + ### and what type of attribute to select + + bias = find_bias(S,stopwatch,two_flag=True) + result = [] + while (len(S) > 0): + element = pf.sample(S) + if len(result) == 0 or not pf.check_if_same_type(element, result[-1], bias): + pf.pair(result, element) + pf.setminus(S, element) + time_elapsed = stopwatch.get_elapsed_time() + + return (result, time_elapsed) + +def chaining(S, associations: dict): + # preprocessing (not part of measured cognitive process) + n = len(S) # number of elements in the set + stopwatch = Stopwatch() + # --- # + stopwatch.start() + chunks = [] + result = [] + while (len(S) > 0): + element = pf.sample(S) + if element in associations.keys(): + chunk = [] + pf.pair(chunk, element) + pf.setminus(S, element) + while True: + next_element = pf.sample(S) + if next_element == associations[element]: + pf.pair(chunk, next_element) + pf.setminus(S, next_element) + pf.pair(chunks, chunk) + break + else: + continue + else: + continue + result = chunks + stopwatch.stop() + time_elapsed = stopwatch.get_elapsed_time() + + return (result, time_elapsed) + +def seriate(S): + # 123123 + pass + +# -------- 2-D -------- # + +def serial_crossed(S): + n = len(S) // 2 # number of elements in the basis + stopwatch = Stopwatch() + bias = find_bias(S, stopwatch, higher_dim=True) + result = [] + while len(S) > n: + element = pf.sample(S) + if len(result) == 0 or pf.check_if_same_type(element, result[-1], bias[0]): + pf.pair(result, element) + pf.setminus(S, element) + for _ in range(n): + element = pf.write_random(S, bias[1], getattr(result[_], bias[1])) + pf.pair(result, element) + pf.setminus(S, element) + time_elapsed = stopwatch.get_elapsed_time() + return (result, time_elapsed) + + + +def center_embedded(S): + n = len(S) // 2 # number of elements in the basis + # + stopwatch = Stopwatch() + bias = find_bias(S, stopwatch, higher_dim=True) + result = [] + while len(S) > 0: + element = pf.sample(S) + if len(result) == 0 or pf.check_if_same_type(element, result[-1], bias[0]): + pf.pair(result, element) + pf.setminus(S, element) + if len(result) == n: + break + for _ in range(n): + element = pf.write_random(S, bias[1], getattr(result[n - 1 - _], bias[1])) + pf.pair(result, element) + pf.setminus(S, element) + stopwatch.stop() + time_elapsed = stopwatch.get_elapsed_time() + return (result, time_elapsed) + +''' + +def center_embedded(S): + n = len(S) // 2 + stopwatch = Stopwatch() + bias = find_bias(S, stopwatch, higher_dim=True) + result = [] + + while len(S) > 0: + element = pf.sample(S) + if len(result) == 0 or pf.check_if_same_type(element, result[-1], bias[0]): + pf.pair(result, element) + if element in S: + pf.setminus(S, element) + else: + raise ValueError("[ERROR] Tried to remove an element not in S during first half.") + if len(result) == n: + break + if len(result) < n: + raise RuntimeError(f"[ERROR] Could not find enough matching elements for first half. Needed {n}, got {len(result)}") + # Second half of the result + if len(S) < n: + raise RuntimeError(f"[ERROR] Not enough elements left in S to complete second half. Needed {n}, have {len(S)}") + for _ in range(n): + ref_attr = getattr(result[n - 1 - _], bias[1], None) + if ref_attr is None: + raise AttributeError(f"[ERROR] Element at position {n - 1 - _} has no attribute '{bias[1]}'") + element = pf.write_random(S, bias[1], ref_attr) + if element is None: + raise ValueError(f"[ERROR] write_random() failed to find match for attribute '{ref_attr}'") + pf.pair(result, element) + if element in S: + pf.setminus(S, element) + else: + raise ValueError("[ERROR] Tried to remove an element not in S during second half.") + stopwatch.stop() + time_elapsed = stopwatch.get_elapsed_time() + return (result, time_elapsed) + +''' + +def tail_recursive(S): + stopwatch = Stopwatch() + bias = find_bias(S, stopwatch, two_flag=True, higher_dim=True) + stopwatch.start() + result = [] + while len(S) > 0: + element = pf.sample(S) + pf.setminus(S, element) + paired_element = pf.write_random(S, bias[0], getattr(element, bias[0])) + result = pf.append(result, pf.merge(element, paired_element)) + pf.setminus(S, paired_element) + stopwatch.stop() + time_elapsed = stopwatch.get_elapsed_time() + return (result, time_elapsed) + + +# ---------------------------------------------------------------------# + +# utils + +def find_bias(S,clock,two_flag=False,higher_dim=False): + ''' + Count unique values for both attributes, + select the attribute with exactly 2 types while the other has != 2 types + + Input Arguments: + S: set of elements to be experimented with + clock: stopwatch used to time primitive functions + two_flag: flag to indicate if the bias required needs only two attribute types + higher_dim: flag to indicate if the set of elements is 2-dimensional + + Output: + bias: the bias lol, the attribute the flip selected + ''' + if higher_dim == True: + chunk_bias, serial_bias = None, None + attribute_counts = {attr: len(set(getattr(obj, attr) for obj in S)) + for attr in ["attribute1", "attribute2"]} + chunk_bias = find_bias(S, clock, two_flag) + clock.start() + serial_bias = 'attribute1' if chunk_bias == 'attribute2' else 'attribute2' + clock.stop() + return (chunk_bias, serial_bias) + else: + bias = None + attribute_counts = {attr: len(set(getattr(obj, attr) for obj in S)) + for attr in ["attribute1", "attribute2"]} + if attribute_counts["attribute1"] == 2 and attribute_counts["attribute2"] != 2: + bias = "attribute1" if not two_flag else "attribute1" + elif attribute_counts["attribute2"] == 2 and attribute_counts["attribute1"] != 2: + bias = "attribute2" if not two_flag else "attribute1" + else: + clock.start() + bias = "attribute1" if pf.flip(0.5) else "attribute2" # Default random selection + clock.stop() + return bias \ No newline at end of file diff --git a/oldtest/oldpf.py b/oldtest/oldpf.py new file mode 100644 index 0000000..d5338b6 --- /dev/null +++ b/oldtest/oldpf.py @@ -0,0 +1,160 @@ +import random + +SEED = 42 +random.seed(SEED) +# Functions on lists (strings) + +def pair(L, C): + """Concatenates character C onto list L + Time complexity: O(1) amortized for lists, O(n) for strings""" + L.append(C) # O(1) amortized + +def append(X, Y): + """Append lists X and Y + Time complexity: O(n+m) where n=len(X), m=len(Y)""" + return X + Y + +# Random functions + +def flip(p): + """Returns true with probability p + Time complexity: O(1)""" + return random.random() < p + +# Set functions + +# def union(set1, set2): +# """Union of twos sets +# Time complexity: O(len(set1) + len(set2))""" +# return set1 | set2 + + +def setminus(set1, s): + #Remove a string from a set + #Time complexity: O(1) for single item, O(len(s)) for set s + set1.remove(s) + +def sample(collection): + #Sample from a set or list of strings. + #Time complexity: O(1) for non-empty sets if using random.choice, + #O(n) for lists using random.sample. + if not collection: + return None + + if isinstance(collection, set): + collection = tuple(collection) # Convert to tuple for sampling + + return random.sample(collection, 1)[0] + + +# # Function calls with memoization + +# memoization_cache = {} +# def F(z): +# """Generic factor function +# Time complexity: Depends on implementation""" +# pass + +# def Fm(z): +# """Memoized version of factor function +# Time complexity: O(1) for repeated calls""" +# if z not in memoization_cache: +# memoization_cache[z] = F(z) +# return memoization_cache[z] + +# Token-related functions + +# def create_tokens(): +# """Initiates a list of tokens [A1, A2, B3, B4] +# Time complexity: O(1)""" +# return ["A1", "A2", "B3", "B4"] + +def add(T, list): + """Adds token T to a list + Time complexity: O(n) due to copying""" + result = list.copy() + result.append(T) + return result + +def remove(T, list): + """Removes token T from a list + Time complexity: O(n) for search and removal""" + result = list.copy() + if T in result: + result.remove(T) + return result + +def check_if_same_type(e1, e2, bias): + """Returns True if tokens are same type + Time complexity: O(1)""" + return getattr(e1,bias) == getattr(e2,bias) + + + +def write_random(S, bias, type): + #Returns one unused member of particular type + #Time complexity: O(n) to filter tokens + for element in S: + if getattr(element, bias) == type: + return element + #type_elements = [u for u, v, d in G.edges(data=True) if v == type and d["label"] == bias] + + ### WRITE CODE + ### maybe add a random list shuffling thing here + ### to make it less predictable + + pass + + + +def implement(FUN, N): + """Keeps implementing a function N times + Time complexity: O(N * T) where T is time of FUN""" + results = [] + for _ in range(N): + results.append(FUN()) + return results + +def write_all(S, bias, type): + """Returns a sequential list of all members of a type + Time complexity: O(n) where n is number of tokens""" + result = [] + for element in S: + if getattr(element, bias) == type: + result = pair(result, element) + return result + +# Additional functions + +def list_create(M): + """Create a blank list with slots for M items + Time complexity: O(M)""" + return [None] * M + +def merge(I, J): + """Merge two items I and J to create a list + Time complexity: O(1)""" + return [I, J] + +def remove_item(I, L): + """Remove item I from list L + Time complexity: O(n) for search and removal""" + result = L.copy() + if I in result: + result.remove(I) + return result + +def dim_set(D): + """Create a set containing items classified by dimension D + Time complexity: O(n*m) where n is number of items, m is time of D function""" + def classify(items, dimension_func=D): + result = set() + for item in items: + result.add(dimension_func(item)) + return result + return classify + +def write_all_set(S): + """Write all items belonging to a particular set S + Time complexity: O(n log n) due to sorting""" + return " - ".join(sorted(S)) \ No newline at end of file diff --git a/oldtest/oldtest.ipynb b/oldtest/oldtest.ipynb new file mode 100644 index 0000000..95c2711 --- /dev/null +++ b/oldtest/oldtest.ipynb @@ -0,0 +1,393 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 13, + "id": "dd606f7f", + "metadata": {}, + "outputs": [], + "source": [ + "import oldpf as pf\n", + "import oldcf as cf\n", + "from oldutils import Element, KComplexity, Associations" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "67d013a8", + "metadata": {}, + "outputs": [], + "source": [ + "a = Element('A1','A','1')\n", + "b = Element('A2','A','2')\n", + "c = Element('B1','B','1')\n", + "d = Element('B2','B','2')" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "162df936", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "18\n", + "{'add': 0, 'append': 2, 'check_if_same_type': 0, 'dim_set': 0, 'flip': 2, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 0, 'remove': 0, 'remove_item': 0, 'sample': 8, 'setminus': 6, 'write_all': 0, 'write_all_set': 0, 'write_random': 0}\n", + "Result: [Element(object=A1, attribute 1=A, attribute 2=1), Element(object=A2, attribute 1=A, attribute 2=2), Element(object=B2, attribute 1=B, attribute 2=2), Element(object=B1, attribute 1=B, attribute 2=1)]\n", + "Elapsed time: 4.650000482797623e-05\n" + ] + } + ], + "source": [ + "train_1 = {a,b,c,d}\n", + "kc = KComplexity()\n", + "result, time_elapsed = cf.iterate(train_1)\n", + "print(kc.get_k_complexity())\n", + "print(kc.get_prim_counts())\n", + "print(\"Result:\", result)\n", + "print(\"Elapsed time:\", time_elapsed)" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "29d799b6", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "15\n", + "{'add': 0, 'append': 1, 'check_if_same_type': 1, 'dim_set': 0, 'flip': 1, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 4, 'remove': 0, 'remove_item': 0, 'sample': 2, 'setminus': 4, 'write_all': 0, 'write_all_set': 0, 'write_random': 2}\n", + "Result: [Element(object=B2, attribute 1=B, attribute 2=2), Element(object=A1, attribute 1=A, attribute 2=1), Element(object=A2, attribute 1=A, attribute 2=2), Element(object=B1, attribute 1=B, attribute 2=1)]\n", + "Elapsed time: 6.579997716471553e-05\n" + ] + } + ], + "source": [ + "train_1 = {a,b,c,d}\n", + "kc = KComplexity()\n", + "result, time_elapsed = cf.palindrome(train_1)\n", + "print(kc.get_k_complexity())\n", + "print(kc.get_prim_counts())\n", + "print(\"Result:\", result)\n", + "print(\"Elapsed time:\", time_elapsed)" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "56cb5c75", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "30\n", + "{'add': 0, 'append': 0, 'check_if_same_type': 10, 'dim_set': 0, 'flip': 1, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 4, 'remove': 0, 'remove_item': 0, 'sample': 11, 'setminus': 4, 'write_all': 0, 'write_all_set': 0, 'write_random': 0}\n", + "Result: [Element(object=A2, attribute 1=A, attribute 2=2), Element(object=B1, attribute 1=B, attribute 2=1), Element(object=A1, attribute 1=A, attribute 2=1), Element(object=B2, attribute 1=B, attribute 2=2)]\n", + "Elapsed time: 1.1900003300979733e-05\n" + ] + } + ], + "source": [ + "train_1 = {a,b,c,d}\n", + "kc = KComplexity()\n", + "result, time_elapsed = cf.alternate(train_1)\n", + "print(kc.get_k_complexity())\n", + "print(kc.get_prim_counts())\n", + "print(\"Result:\", result)\n", + "print(\"Elapsed time:\", time_elapsed)" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "18a226e1", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "17\n", + "{'add': 0, 'append': 0, 'check_if_same_type': 0, 'dim_set': 0, 'flip': 0, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 6, 'remove': 0, 'remove_item': 0, 'sample': 7, 'setminus': 4, 'write_all': 0, 'write_all_set': 0, 'write_random': 0}\n", + "Result: [[Element(object=B1, attribute 1=B, attribute 2=1), Element(object=B2, attribute 1=B, attribute 2=2)], [Element(object=A1, attribute 1=A, attribute 2=1), Element(object=A2, attribute 1=A, attribute 2=2)]]\n", + "Elapsed time: 6.429999484680593e-05\n" + ] + } + ], + "source": [ + "train_1 = {a,b,c,d}\n", + "assoc = {a: b, c: d}\n", + "kc = KComplexity()\n", + "result, time_elapsed = cf.chaining(train_1, assoc)\n", + "print(kc.get_k_complexity())\n", + "print(kc.get_prim_counts())\n", + "print(\"Result:\", result)\n", + "print(\"Elapsed time:\", time_elapsed)" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "id": "f335aebe", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "0\n", + "{'add': 0, 'append': 0, 'check_if_same_type': 0, 'dim_set': 0, 'flip': 0, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 0, 'remove': 0, 'remove_item': 0, 'sample': 0, 'setminus': 0, 'write_all': 0, 'write_all_set': 0, 'write_random': 0}\n", + "Result: [[Element(object=B1, attribute 1=B, attribute 2=1), Element(object=B2, attribute 1=B, attribute 2=2)], [Element(object=A1, attribute 1=A, attribute 2=1), Element(object=A2, attribute 1=A, attribute 2=2)]]\n", + "Elapsed time: 6.429999484680593e-05\n" + ] + } + ], + "source": [ + "train_1 = {a,b,c,d}\n", + "kc = KComplexity()\n", + "cf.seriate(train_1)\n", + "print(kc.get_k_complexity())\n", + "print(kc.get_prim_counts())\n", + "print(\"Result:\", result)\n", + "print(\"Elapsed time:\", time_elapsed)" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "id": "571dd1f4", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "20\n", + "{'add': 0, 'append': 0, 'check_if_same_type': 4, 'dim_set': 0, 'flip': 1, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 4, 'remove': 0, 'remove_item': 0, 'sample': 5, 'setminus': 4, 'write_all': 0, 'write_all_set': 0, 'write_random': 2}\n", + "Result: [Element(object=A1, attribute 1=A, attribute 2=1), Element(object=B1, attribute 1=B, attribute 2=1), Element(object=A2, attribute 1=A, attribute 2=2), Element(object=B2, attribute 1=B, attribute 2=2)]\n", + "Elapsed time: 1.7200014553964138e-05\n" + ] + } + ], + "source": [ + "train_1 = {a,b,c,d}\n", + "kc = KComplexity()\n", + "result, time_elapsed = cf.serial_crossed(train_1)\n", + "print(kc.get_k_complexity())\n", + "print(kc.get_prim_counts())\n", + "print(\"Result:\", result)\n", + "print(\"Elapsed time:\", time_elapsed)" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "id": "deae7813", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "24\n", + "{'add': 0, 'append': 0, 'check_if_same_type': 6, 'dim_set': 0, 'flip': 1, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 4, 'remove': 0, 'remove_item': 0, 'sample': 7, 'setminus': 4, 'write_all': 0, 'write_all_set': 0, 'write_random': 2}\n", + "Result: [Element(object=B1, attribute 1=B, attribute 2=1), Element(object=A1, attribute 1=A, attribute 2=1), Element(object=A2, attribute 1=A, attribute 2=2), Element(object=B2, attribute 1=B, attribute 2=2)]\n", + "Elapsed time: 1.4699995517730713e-05\n" + ] + } + ], + "source": [ + "train_1 = {a,b,c,d}\n", + "kc = KComplexity()\n", + "result, time_elapsed = cf.center_embedded(train_1)\n", + "print(kc.get_k_complexity())\n", + "print(kc.get_prim_counts())\n", + "print(\"Result:\", result)\n", + "print(\"Elapsed time:\", time_elapsed)" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "id": "ad5a4286", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "13\n", + "{'add': 0, 'append': 2, 'check_if_same_type': 0, 'dim_set': 0, 'flip': 1, 'implement': 0, 'list_create': 0, 'merge': 2, 'pair': 0, 'remove': 0, 'remove_item': 0, 'sample': 2, 'setminus': 4, 'write_all': 0, 'write_all_set': 0, 'write_random': 2}\n", + "Result: [Element(object=A2, attribute 1=A, attribute 2=2), Element(object=B2, attribute 1=B, attribute 2=2), Element(object=B1, attribute 1=B, attribute 2=1), Element(object=A1, attribute 1=A, attribute 2=1)]\n", + "Elapsed time: 8.3099992480129e-05\n" + ] + } + ], + "source": [ + "train_1 = {a,b,c,d}\n", + "kc = KComplexity()\n", + "result, time_elapsed = cf.tail_recursive(train_1)\n", + "print(kc.get_k_complexity())\n", + "print(kc.get_prim_counts())\n", + "print(\"Result:\", result)\n", + "print(\"Elapsed time:\", time_elapsed)" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "id": "ffe74253", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[[4.29997453e-06 4.39997530e-06 1.89998536e-06 2.29998841e-06\n", + " 2.00001523e-06 2.40001827e-06]\n", + " [4.20003198e-06 3.90000059e-06 1.79998460e-06 1.99998613e-06\n", + " 2.00001523e-06 2.30001751e-06]\n", + " [3.90002970e-06 4.20000288e-06 1.99998613e-06 2.19998765e-06\n", + " 1.89998536e-06 2.19998765e-06]\n", + " [4.29997453e-06 4.39997530e-06 1.90001447e-06 2.10001599e-06\n", + " 1.99998613e-06 2.09998689e-06]\n", + " [4.00000135e-06 3.90002970e-06 1.89998536e-06 1.79998460e-06\n", + " 1.90001447e-06 2.30001751e-06]\n", + " [4.00000135e-06 3.79999983e-06 1.90001447e-06 2.00001523e-06\n", + " 2.09998689e-06 2.29998841e-06]\n", + " [4.69997758e-06 3.90002970e-06 1.79998460e-06 1.99998613e-06\n", + " 2.09998689e-06 2.10001599e-06]\n", + " [3.90000059e-06 3.69999907e-06 1.80001371e-06 1.90001447e-06\n", + " 2.00001523e-06 2.20001675e-06]\n", + " [4.30003274e-06 4.30000364e-06 1.79998460e-06 2.09998689e-06\n", + " 2.09998689e-06 2.40001827e-06]\n", + " [4.30000364e-06 3.90000059e-06 1.80001371e-06 2.10001599e-06\n", + " 2.10001599e-06 2.20001675e-06]\n", + " [4.00003046e-06 3.69999907e-06 1.90001447e-06 2.00001523e-06\n", + " 1.62000069e-05 5.00003807e-06]\n", + " [1.22000056e-05 7.00002420e-06 2.19998765e-06 3.39999679e-06\n", + " 2.29998841e-06 2.20001675e-06]\n", + " [4.40003350e-06 4.40000440e-06 1.89998536e-06 2.20001675e-06\n", + " 2.20001675e-06 2.30001751e-06]\n", + " [4.50003427e-06 4.60000592e-06 2.09998689e-06 2.39998917e-06\n", + " 2.30001751e-06 2.20001675e-06]\n", + " [4.40003350e-06 4.20000288e-06 1.99998613e-06 2.19998765e-06\n", + " 2.09998689e-06 2.39998917e-06]\n", + " [4.39997530e-06 4.10000212e-06 2.00001523e-06 2.50001904e-06\n", + " 2.09998689e-06 2.29998841e-06]\n", + " [4.39997530e-06 4.10000212e-06 2.00001523e-06 2.10001599e-06\n", + " 2.40001827e-06 2.19998765e-06]\n", + " [4.30000364e-06 3.79999983e-06 1.99998613e-06 2.19998765e-06\n", + " 2.10001599e-06 2.40001827e-06]\n", + " [4.60003503e-06 4.10000212e-06 1.99998613e-06 2.09998689e-06\n", + " 2.19998765e-06 2.39998917e-06]\n", + " [4.19997377e-06 4.00000135e-06 2.20001675e-06 2.30001751e-06\n", + " 2.10001599e-06 2.39998917e-06]]\n" + ] + } + ], + "source": [ + "import numpy as np\n", + "\n", + "def runReordering(element_set, n_runs):\n", + " times = []\n", + " for _ in range(n_runs + 1):\n", + " time_list = []\n", + " # 1-D\n", + " time_list.append(cf.iterate(element_set)[1])\n", + " time_list.append(cf.palindrome(element_set)[1])\n", + " time_list.append(cf.alternate(element_set)[1])\n", + " # time_list.append(cf.seriate(element_set)[1])\n", + " # 2-D\n", + " time_list.append(cf.serial_crossed(element_set)[1])\n", + " time_list.append(cf.center_embedded(element_set)[1])\n", + " time_list.append(cf.tail_recursive(element_set)[1]) \n", + "\n", + " times.append(time_list)\n", + " \n", + " times = np.array(times)[1:]\n", + " \n", + " return (times)\n", + "\n", + "times = runReordering(train_1, 20)\n", + "print(times)" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "id": "33262df1", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iterate 0.000005\n", + "Palindrome 0.000004\n", + "Alternate 0.000002\n", + "Serial Crossed 0.000002\n", + "Center Embedded 0.000003\n", + "Tail Recursive 0.000002\n", + "dtype: float64\n" + ] + } + ], + "source": [ + "import pandas as pd\n", + "import seaborn as sns\n", + "import matplotlib.pyplot as plt\n", + "\n", + "df = pd.DataFrame(times, columns=['Iterate', 'Palindrome', 'Alternate', 'Serial Crossed', 'Center Embedded', 'Tail Recursive'])\n", + "sns.boxplot(data=df)\n", + "plt.title('Reordering Times for Cognitive Functions')\n", + "plt.xlabel('Cognitive Functions')\n", + "plt.ylabel('Time (s)')\n", + "plt.xticks(rotation=45)\n", + "plt.grid(True)\n", + "plt.show() \n", + "print(df.mean())" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "lot_venv", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.13.5" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/oldtest/oldutils.py b/oldtest/oldutils.py new file mode 100644 index 0000000..b841c52 --- /dev/null +++ b/oldtest/oldutils.py @@ -0,0 +1,181 @@ +from functools import cached_property, cache, partial +import time +from operator import attrgetter +from tabulate import tabulate +import networkx as nx +from typing import Literal +import matplotlib.pyplot as plt +from dataclasses import dataclass +import oldpf as pf +import importlib + +# ---------------------------------------------------------------------# + +""" +@dataclass +class Element: # n-dimensional element + name : str + attribute1 : int | float | str + attribute2 : int | float | str | None = None + def __repr__(self): + return f"Element(object={self.name}, attribute 1={self.attribute1}, attribute 2={self.attribute2})" + def __str__(self): + return f"{self.name}, {self.attribute1}, {self.attribute2})" +""" + +class Element: # n-dimensional element + def __init__(self, name, attribute1, attribute2=None): + self.name = name + self.attribute1 = attribute1 + self.attribute2 = attribute2 + def __repr__(self): + return f"Element(object={self.name}, attribute 1={self.attribute1}, attribute 2={self.attribute2})" + def __str__(self): + return f"{self.name}, {self.attribute1}, {self.attribute2})" + +class Associations: # n-dimensional association + def __init__(self, associations: dict, positional: bool = False): + self.associations = associations + self.positional = positional + def __repr__(self): + raise NotImplementedError + def build_updates(self, graph): + if self.positional: + for key, value in self.associations.items(): + nx.set_node_attributes(graph, {key.name: {"position": value}}) + else: + for key, value in self.associations.items(): + graph.add_edge(key.name, value.name, label="precedes", directed=True) + +class ElementSet: # n-dimensional element set + def __init__(self, elements: set, associations: Associations = None): + self.elements = elements + self.associations = associations + self.graph = self.build_graph() + def __repr__(self): + raise NotImplementedError + def build_graph(self): + G = nx.MultiGraph() # Create a directed graph + for obj in self.elements: + G.add_node(obj.name, type='element') # Add object as a node + G.add_node(obj.attribute1, type='attribute1') # Add color as a node + G.add_edge(obj.name, obj.attribute1, label="attribute") # Add directed edge with label + if obj.attribute2: + # If the object has a second attribute, add it as a node and edge + G.add_node(obj.attribute2, type='attribute2') # Add shape as a node + G.add_edge(obj.name, obj.attribute2, label="attribute") + if self.associations: + self.associations.build_updates(G) # Build associations + if self.graph: + self.graph = G + return G + def visualize(self): + plt.figure(figsize=(10, 8)) + pos = nx.spring_layout(self.graph) + + # Draw nodes with different colors based on type + node_colors = [] + for node, data in self.graph.nodes(data=True): + if data['type'] == 'element': + node_colors.append('skyblue') + elif data['type'] == 'attribute1': + node_colors.append('lightgreen') + elif data['type'] == 'attribute2': + node_colors.append('lightcoral') + + nx.draw(self.graph, pos, with_labels=True, node_color=node_colors, node_size=500, font_size=10) + edge_labels = nx.get_edge_attributes(self.graph, 'label') + nx.draw_networkx_edge_labels(self.graph, pos, edge_labels=edge_labels) + plt.show() + @cached_property + def attribute1_types(self): + """Returns a set of unique attribute1 types.""" + return set(obj.attribute1 for obj in self.elements) + @cached_property + def attribute2_types(self): + """Returns a set of unique attribute2 types.""" + return set(obj.attribute2 for obj in self.elements if obj.attribute2 is not None) + def attribute_items(self, attribute): + def get_type(type_): + + return getattr(self, f"{attribute}_types", set()) + + + + + +def pretty_view(sequence): + """Prints a sequence of elements in a pretty format.""" + cute = list(zip(*map(attrgetter("name", "attribute1", "attribute2"), sequence))) + # Print as a table + print(tabulate(zip(*cute), headers=["object", "attribute 1", "attribute 2"], tablefmt="grid")) + + + +# ---------------------------------------------------------------------# + +class Stopwatch: + def __init__(self): + self._start_time = None + self._elapsed_time = 0 + self._running = False + + def start(self): + """Start or resume the stopwatch.""" + if not self._running: + self._start_time = time.perf_counter() - self._elapsed_time + self._running = True + # print("Stopwatch started.") + + def stop(self): + """Stop the stopwatch and display the elapsed time.""" + if self._running: + self._elapsed_time = time.perf_counter() - self._start_time + self._running = False + # print(f"Stopwatch stopped. Elapsed time: {self._elapsed_time:.2f} seconds.") + + def reset(self): + """Reset the stopwatch to zero.""" + self._elapsed_time = 0 + if self._running: + self._start_time = time.perf_counter() + # print("Stopwatch reset.") + + def get_elapsed_time(self): + """Get the current elapsed time without stopping the stopwatch.""" + if self._running: + return time.perf_counter() - self._start_time + return self._elapsed_time + +class KComplexity: + def __init__(self): + self.prim = importlib.import_module('oldpf') + self.call_counts = {} + self._wrap_prim_functions() + + def _wrap_prim_functions(self): + for name in dir(self.prim): + func = getattr(self.prim, name) + if callable(func) and not name.startswith("__"): + self.call_counts[name] = 0 + wrapper_func = self._make_wrapper(func, name) + setattr(self.prim, name, wrapper_func) + + def _make_wrapper(self, func, name): + def wrapper(*args, **kwargs): + self.call_counts[name] += 1 + return func(*args, **kwargs) + return wrapper + + """get dictionary of each prim function call count""" + def get_prim_counts(self): + return dict(self.call_counts) + + """get total number of prim function calls""" + def get_k_complexity(self): + return sum(self.call_counts.values()) + + """reset all prim function call counts to zero""" + def reset(self): + for key in self.call_counts: + self.call_counts[key] = 0 \ No newline at end of file diff --git a/oldtest/random.py b/oldtest/random.py new file mode 100644 index 0000000..59fd7f8 --- /dev/null +++ b/oldtest/random.py @@ -0,0 +1,79 @@ +import oldpf as pf +from oldutils import Stopwatch, Element, KComplexity + +a = Element('A1','A','1') +b = Element('A2','A','2') +c = Element('B1','B','1') +d = Element('B2','B','2') + +train_1 = {a,b,c,d} + +def palindrome(S): + # 123321 + # preprocessing (not part of measured cognitive process) + n = len(S) // 2 # number of elements in basis + stopwatch = Stopwatch() + # select attribute which chunking is based on + bias = find_bias(S, stopwatch) + stopwatch.start() + basis, rev = [], [] + # write_random() based implementation + ### WRITE CODE HERE + while (len(S) > n): + element = pf.sample(S) + if len(basis)==0 or not (any(pf.check_if_same_type(element, chosen, bias) for chosen in basis)): + pf.pair(basis, element) + pf.setminus(S, element) + for _ in range(n): + element = pf.write_random(S, bias, getattr(basis[n-1-_], bias)) + pf.pair(rev,element) + pf.setminus(S, element) + result = pf.append(basis,rev) + stopwatch.stop() + time_elapsed = stopwatch.get_elapsed_time() + + return (result, time_elapsed) + +def find_bias(S,clock,two_flag=False,higher_dim=False): + ''' + Count unique values for both attributes, + select the attribute with exactly 2 types while the other has != 2 types + + Input Arguments: + S: set of elements to be experimented with + clock: stopwatch used to time primitive functions + two_flag: flag to indicate if the bias required needs only two attribute types + higher_dim: flag to indicate if the set of elements is 2-dimensional + + Output: + bias: the bias lol, the attribute the flip selected + ''' + if higher_dim == True: + chunk_bias, serial_bias = None, None + attribute_counts = {attr: len(set(getattr(obj, attr) for obj in S)) + for attr in ["attribute1", "attribute2"]} + chunk_bias = find_bias(S, clock, two_flag) + clock.start() + serial_bias = 'attribute1' if chunk_bias == 'attribute2' else 'attribute2' + clock.stop() + return (chunk_bias, serial_bias) + else: + bias = None + attribute_counts = {attr: len(set(getattr(obj, attr) for obj in S)) + for attr in ["attribute1", "attribute2"]} + if attribute_counts["attribute1"] == 2 and attribute_counts["attribute2"] != 2: + bias = "attribute1" if not two_flag else "attribute1" + elif attribute_counts["attribute2"] == 2 and attribute_counts["attribute1"] != 2: + bias = "attribute2" if not two_flag else "attribute1" + else: + clock.start() + bias = "attribute1" if pf.flip(0.5) else "attribute2" # Default random selection + clock.stop() + return bias + +kc = KComplexity() +result, time_elapsed = palindrome(train_1) +print(kc.get_k_complexity()) +print(kc.get_prim_counts()) +print("Result:", result) +print("Elapsed time:", time_elapsed) diff --git a/palindrome_test.py b/palindrome_test.py new file mode 100644 index 0000000..58edb09 --- /dev/null +++ b/palindrome_test.py @@ -0,0 +1,42 @@ +from cognitive_functions import find_bias +from utils import Element, ElementSet, Stopwatch, KComplexity +import primitive_fucntions as pf + +def palindrome(S: ElementSet): + n = len(S.elements) // 2 + stopwatch = Stopwatch() + bias = find_bias(S.elements, stopwatch) + stopwatch.start() + basis, rev = [], [] + + while len(S.elements) > n: + element = pf.sample(S) + if len(basis) == 0 or not any(pf.check_if_same_type(element, chosen, bias) for chosen in basis): + pf.pair(basis, element) + pf.setminus(S, element) + + for _ in range(n): + element = pf.write_random(S, bias, getattr(basis[n-1-_], bias)) + pf.pair(rev, element) + pf.setminus(S, element) + + result = pf.append(basis, rev) + stopwatch.stop() + time_elapsed = stopwatch.get_elapsed_time() + return (result, time_elapsed) + +e1 = Element("obj1", "red", "circle") +e2 = Element("obj2", "blue", "square") +e3 = Element("obj3", "red", "circle") +e4 = Element("obj4", "blue", "square") + +element_set = ElementSet(elements=set([e1, e2, e3, e4])) + +kc = KComplexity() + +result, elapsed_time = palindrome(element_set) + +print(kc.get_k_complexity()) +print(kc.get_prim_counts()) +print("Result:", result) +print("Elapsed time:", elapsed_time) \ No newline at end of file diff --git a/playground.ipynb b/playground.ipynb index 7ec06f6..0897d34 100644 --- a/playground.ipynb +++ b/playground.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 1, + "execution_count": 10, "metadata": {}, "outputs": [], "source": [ @@ -22,7 +22,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 11, "metadata": {}, "outputs": [], "source": [ @@ -34,21 +34,18 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 12, "metadata": {}, "outputs": [ { - "ename": "AttributeError", - "evalue": "'ElementSet' object has no attribute 'graph'", - "output_type": "error", - "traceback": [ - "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[1;31mAttributeError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[1;32mIn[3], line 3\u001b[0m\n\u001b[0;32m 1\u001b[0m S \u001b[38;5;241m=\u001b[39m {obj1, obj2, obj3, obj4}\n\u001b[0;32m 2\u001b[0m assoc \u001b[38;5;241m=\u001b[39m Associations({obj1: obj2, obj3: obj4})\n\u001b[1;32m----> 3\u001b[0m S \u001b[38;5;241m=\u001b[39m \u001b[43mElementSet\u001b[49m\u001b[43m(\u001b[49m\u001b[43mS\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43massoc\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 4\u001b[0m S\u001b[38;5;241m.\u001b[39mgraph\n", - "File \u001b[1;32mc:\\Users\\desig\\Desktop\\vs code\\LoT\\LoT-modeling\\utils.py:54\u001b[0m, in \u001b[0;36mElementSet.__init__\u001b[1;34m(self, elements, associations)\u001b[0m\n\u001b[0;32m 52\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39melements \u001b[38;5;241m=\u001b[39m elements\n\u001b[0;32m 53\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39massociations \u001b[38;5;241m=\u001b[39m associations\n\u001b[1;32m---> 54\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mgraph \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mbuild_graph\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[1;32mc:\\Users\\desig\\Desktop\\vs code\\LoT\\LoT-modeling\\utils.py:69\u001b[0m, in \u001b[0;36mElementSet.build_graph\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m 67\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39massociations:\n\u001b[0;32m 68\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39massociations\u001b[38;5;241m.\u001b[39mbuild_updates(G) \u001b[38;5;66;03m# Build associations\u001b[39;00m\n\u001b[1;32m---> 69\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mgraph\u001b[49m:\n\u001b[0;32m 70\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mgraph \u001b[38;5;241m=\u001b[39m G\n\u001b[0;32m 71\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m G\n", - "\u001b[1;31mAttributeError\u001b[0m: 'ElementSet' object has no attribute 'graph'" - ] + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" } ], "source": [ @@ -60,12 +57,12 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 13, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -80,12 +77,12 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 14, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -132,7 +129,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 15, "metadata": {}, "outputs": [ { @@ -157,7 +154,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 16, "metadata": {}, "outputs": [], "source": [ @@ -176,21 +173,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 17, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "2 --(color)--> blue\n", - "2 --(shape)--> square\n", - "4 --(color)--> blue\n", - "4 --(shape)--> circle\n", - "3 --(color)--> yellow\n", - "3 --(shape)--> circle\n", - "1 --(color)--> yellow\n", - "1 --(shape)--> square\n" + "4 --(attribute1)--> blue\n", + "4 --(attribute2)--> circle\n", + "3 --(attribute1)--> yellow\n", + "3 --(attribute2)--> circle\n", + "2 --(attribute1)--> blue\n", + "2 --(attribute2)--> square\n", + "1 --(attribute1)--> yellow\n", + "1 --(attribute2)--> square\n" ] } ], diff --git a/primitive_fucntions.py b/primitive_fucntions.py index c86f0e7..d5338b6 100644 --- a/primitive_fucntions.py +++ b/primitive_fucntions.py @@ -28,16 +28,16 @@ def flip(p): # Time complexity: O(len(set1) + len(set2))""" # return set1 | set2 + def setminus(set1, s): - """Remove a string from a set - Time complexity: O(1) for single item, O(len(s)) for set s""" + #Remove a string from a set + #Time complexity: O(1) for single item, O(len(s)) for set s set1.remove(s) def sample(collection): - """Sample from a set or list of strings. - Time complexity: O(1) for non-empty sets if using random.choice, - O(n) for lists using random.sample. - """ + #Sample from a set or list of strings. + #Time complexity: O(1) for non-empty sets if using random.choice, + #O(n) for lists using random.sample. if not collection: return None @@ -46,6 +46,7 @@ def sample(collection): return random.sample(collection, 1)[0] + # # Function calls with memoization # memoization_cache = {} @@ -88,13 +89,15 @@ def check_if_same_type(e1, e2, bias): Time complexity: O(1)""" return getattr(e1,bias) == getattr(e2,bias) -def write_random(G, bias, type): - """Returns one unused member of particular type - Time complexity: O(n) to filter tokens""" - # for element in S: - # if getattr(element, bias) == type: - # return element - type_elements = [u for u, v, d in G.edges(data=True) if v == type and d["label"] == bias] + + +def write_random(S, bias, type): + #Returns one unused member of particular type + #Time complexity: O(n) to filter tokens + for element in S: + if getattr(element, bias) == type: + return element + #type_elements = [u for u, v, d in G.edges(data=True) if v == type and d["label"] == bias] ### WRITE CODE ### maybe add a random list shuffling thing here @@ -102,6 +105,8 @@ def write_random(G, bias, type): pass + + def implement(FUN, N): """Keeps implementing a function N times Time complexity: O(N * T) where T is time of FUN""" @@ -114,10 +119,9 @@ def write_all(S, bias, type): """Returns a sequential list of all members of a type Time complexity: O(n) where n is number of tokens""" result = [] - #for element in S: - #if getattr(element, bias) == type: - #result = pair(result, element) - type_elements = [u for u, v, d in S.edges(data=True) if v == type and d["label"] == bias] + for element in S: + if getattr(element, bias) == type: + result = pair(result, element) return result # Additional functions diff --git a/utils.py b/utils.py index 228dc01..743341c 100644 --- a/utils.py +++ b/utils.py @@ -47,6 +47,7 @@ def build_updates(self, graph): for key, value in self.associations.items(): graph.add_edge(key.name, value.name, label="precedes", directed=True) + class ElementSet: # n-dimensional element set def __init__(self, elements: set, associations: Associations = None): self.elements = elements @@ -66,7 +67,7 @@ def build_graph(self): G.add_edge(obj.name, obj.attribute2, label="attribute") if self.associations: self.associations.build_updates(G) # Build associations - if self.graph: + if hasattr(self, 'graph') and self.graph: self.graph = G return G def visualize(self): From 0ff692d63260350a83248b20f511be54a42f3b30 Mon Sep 17 00:00:00 2001 From: LuckyBunnyLee Date: Tue, 22 Jul 2025 04:06:41 -0700 Subject: [PATCH 7/8] finished k_comp --- cog.py | 30 ++- cognitive_functions.py | 59 ++++- midtest/midtest.ipynb | 95 +++++--- newtest.ipynb | 503 +++++++++++++++++++++++++++++++++++------ utils.py | 104 ++++++++- 5 files changed, 677 insertions(+), 114 deletions(-) diff --git a/cog.py b/cog.py index 6ccf1bd..15ddb65 100644 --- a/cog.py +++ b/cog.py @@ -18,4 +18,32 @@ def cog_1(E): kc = KComplexity() cog_1(Elements) print(kc.get_k_complexity()) -print(kc.get_prim_counts()) \ No newline at end of file +#print(kc.get_prim_counts()) + +''' +element_set = {a,b,c,d} +S = ElementSet(element_set) +kc = KComplexity() +cf.iterate(S) +print(kc.get_cog_name() + ' k-complexity: ', kc.get_k_complexity()) +print(kc.get_cog_name() + ' primitive count: ', kc.get_prim_counts()) +print('Total K-complexity: ', kc.get_total_k_complexity()) +print('Total primitive counts: ', kc.get_total_prim_counts()) + +kc.plot_prim_counts() +kc.plot_total_prim_counts() +kc.plot_cog_vs_prim() + +element_set = {a,b,c,d} +S = ElementSet(element_set) +cf.palindrome(S) +print(kc.get_cog_name() + ' k-complexity: ', kc.get_k_complexity()) +print(kc.get_cog_name() + ' primitive count: ', kc.get_prim_counts()) +print('Total K-complexity: ', kc.get_total_k_complexity()) +print('Total primitive counts: ', kc.get_total_prim_counts()) + + +kc.plot_prim_counts() +kc.plot_total_prim_counts() +kc.plot_cog_vs_prim() +''' \ No newline at end of file diff --git a/cognitive_functions.py b/cognitive_functions.py index 837f44a..94f231b 100644 --- a/cognitive_functions.py +++ b/cognitive_functions.py @@ -103,6 +103,61 @@ def seriate(S: ElementSet): # 123123 pass +def serial_crossed(S: ElementSet): + n = len(S.elements) // 2 # number of elements in the basis + stopwatch = Stopwatch() + bias = find_bias(S.elements, stopwatch, higher_dim=True) + result = [] + while len(S.elements) > n: + element = pf.sample(S.elements) + if len(result) == 0 or pf.check_if_same_type(element, result[-1], bias[0]): + pf.pair(result, element) + pf.setminus(S.elements, element) + for _ in range(n): + element = pf.write_random(S.elements, bias[1], getattr(result[_], bias[1])) + pf.pair(result, element) + pf.setminus(S.elements, element) + time_elapsed = stopwatch.get_elapsed_time() + return (result, time_elapsed) + +def center_embedded(S: ElementSet): + n = len(S.elements) // 2 # number of elements in the basis + # + stopwatch = Stopwatch() + bias = find_bias(S.elements, stopwatch, higher_dim=True) + result = [] + while len(S.elements) > 0: + element = pf.sample(S.elements) + if len(result) == 0 or pf.check_if_same_type(element, result[-1], bias[0]): + pf.pair(result, element) + pf.setminus(S.elements, element) + if len(result) == n: + break + for _ in range(n): + element = pf.write_random(S.elements, bias[1], getattr(result[n - 1 - _], bias[1])) + pf.pair(result, element) + pf.setminus(S.elements, element) + stopwatch.stop() + time_elapsed = stopwatch.get_elapsed_time() + return (result, time_elapsed) + +def tail_recursive(S: ElementSet): + stopwatch = Stopwatch() + bias = find_bias(S.elements, stopwatch, two_flag=True, higher_dim=True) + stopwatch.start() + result = [] + while len(S.elements) > 0: + element = pf.sample(S.elements) + pf.setminus(S.elements, element) + paired_element = pf.write_random(S.elements, bias[0], getattr(element, bias[0])) + result = pf.append(result, pf.merge(element, paired_element)) + pf.setminus(S.elements, paired_element) + stopwatch.stop() + time_elapsed = stopwatch.get_elapsed_time() + return (result, time_elapsed) + +''' + def serial_crossed(S: ElementSet): n = len(S.elements) // 2 stopwatch = Stopwatch() @@ -169,8 +224,10 @@ def tail_recursive(S: ElementSet): stopwatch.stop() return (result, stopwatch.get_elapsed_time()) +''' + def find_bias(S, clock, two_flag=False, higher_dim=False): - if isinstance(S, ElementSet): + if hasattr(S, 'elements'): elements = S.elements else: elements = S diff --git a/midtest/midtest.ipynb b/midtest/midtest.ipynb index 47bae71..5d3057a 100644 --- a/midtest/midtest.ipynb +++ b/midtest/midtest.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 1, + "execution_count": 433, "id": "081f22f1", "metadata": {}, "outputs": [], @@ -13,7 +13,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 434, "id": "831c5eaf", "metadata": {}, "outputs": [], @@ -26,7 +26,36 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 435, + "id": "cecfb41f", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "33\n", + "{'add': 0, 'append': 3, 'check_if_same_type': 1, 'dim_set': 0, 'flip': 3, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 4, 'remove': 0, 'remove_item': 0, 'sample': 10, 'setminus': 10, 'write_all': 0, 'write_all_set': 0, 'write_random': 2}\n" + ] + } + ], + "source": [ + "element_set = {a,b,c,d}\n", + "S = ElementSet(element_set)\n", + "kc = KComplexity()\n", + "cf.iterate(S)\n", + "\n", + "element_set = {a,b,c,d}\n", + "S = ElementSet(element_set)\n", + "result, elapsed_time = cf.palindrome(S)\n", + "\n", + "print(kc.get_k_complexity())\n", + "print(kc.get_prim_counts())" + ] + }, + { + "cell_type": "code", + "execution_count": 436, "id": "030b28dc", "metadata": {}, "outputs": [ @@ -36,8 +65,8 @@ "text": [ "18\n", "{'add': 0, 'append': 2, 'check_if_same_type': 0, 'dim_set': 0, 'flip': 2, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 0, 'remove': 0, 'remove_item': 0, 'sample': 8, 'setminus': 6, 'write_all': 0, 'write_all_set': 0, 'write_random': 0}\n", - "Result: [Element(object=A1, attribute 1=A, attribute 2=1), Element(object=A2, attribute 1=A, attribute 2=2), Element(object=B2, attribute 1=B, attribute 2=2), Element(object=B1, attribute 1=B, attribute 2=1)]\n", - "Elapsed time: 3.140006447210908e-05\n" + "Result: [Element(object=A2, attribute 1=A, attribute 2=2), Element(object=A1, attribute 1=A, attribute 2=1), Element(object=B2, attribute 1=B, attribute 2=2), Element(object=B1, attribute 1=B, attribute 2=1)]\n", + "Elapsed time: 0.0016532998997718096\n" ] } ], @@ -54,7 +83,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 437, "id": "034a7977", "metadata": {}, "outputs": [ @@ -64,8 +93,8 @@ "text": [ "15\n", "{'add': 0, 'append': 1, 'check_if_same_type': 1, 'dim_set': 0, 'flip': 1, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 4, 'remove': 0, 'remove_item': 0, 'sample': 2, 'setminus': 4, 'write_all': 0, 'write_all_set': 0, 'write_random': 2}\n", - "Result: [Element(object=B2, attribute 1=B, attribute 2=2), Element(object=A2, attribute 1=A, attribute 2=2), Element(object=A1, attribute 1=A, attribute 2=1), Element(object=B1, attribute 1=B, attribute 2=1)]\n", - "Elapsed time: 3.8300000596791506e-05\n" + "Result: [Element(object=A1, attribute 1=A, attribute 2=1), Element(object=B2, attribute 1=B, attribute 2=2), Element(object=B1, attribute 1=B, attribute 2=1), Element(object=A2, attribute 1=A, attribute 2=2)]\n", + "Elapsed time: 0.0017292997799813747\n" ] } ], @@ -82,7 +111,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 438, "id": "df882383", "metadata": {}, "outputs": [ @@ -92,8 +121,8 @@ "text": [ "16\n", "{'add': 0, 'append': 0, 'check_if_same_type': 3, 'dim_set': 0, 'flip': 1, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 4, 'remove': 0, 'remove_item': 0, 'sample': 4, 'setminus': 4, 'write_all': 0, 'write_all_set': 0, 'write_random': 0}\n", - "Result: [Element(object=A2, attribute 1=A, attribute 2=2), Element(object=A1, attribute 1=A, attribute 2=1), Element(object=B2, attribute 1=B, attribute 2=2), Element(object=B1, attribute 1=B, attribute 2=1)]\n", - "Elapsed time: 4.099973011761904e-06\n" + "Result: [Element(object=B1, attribute 1=B, attribute 2=1), Element(object=A2, attribute 1=A, attribute 2=2), Element(object=B2, attribute 1=B, attribute 2=2), Element(object=A1, attribute 1=A, attribute 2=1)]\n", + "Elapsed time: 0.00031679985113441944\n" ] } ], @@ -110,7 +139,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 439, "id": "da9b45ff", "metadata": {}, "outputs": [ @@ -118,10 +147,10 @@ "name": "stdout", "output_type": "stream", "text": [ - "18\n", - "{'add': 0, 'append': 0, 'check_if_same_type': 0, 'dim_set': 0, 'flip': 0, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 6, 'remove': 0, 'remove_item': 0, 'sample': 8, 'setminus': 4, 'write_all': 0, 'write_all_set': 0, 'write_random': 0}\n", - "Result: [[Element(object=A1, attribute 1=A, attribute 2=1), Element(object=A2, attribute 1=A, attribute 2=2)], [Element(object=B1, attribute 1=B, attribute 2=1), Element(object=B2, attribute 1=B, attribute 2=2)]]\n", - "Elapsed time: 0.00010889998520724475\n" + "14\n", + "{'add': 0, 'append': 0, 'check_if_same_type': 0, 'dim_set': 0, 'flip': 0, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 6, 'remove': 0, 'remove_item': 0, 'sample': 4, 'setminus': 4, 'write_all': 0, 'write_all_set': 0, 'write_random': 0}\n", + "Result: [[Element(object=B1, attribute 1=B, attribute 2=1), Element(object=B2, attribute 1=B, attribute 2=2)], [Element(object=A1, attribute 1=A, attribute 2=1), Element(object=A2, attribute 1=A, attribute 2=2)]]\n", + "Elapsed time: 0.0013715000823140144\n" ] } ], @@ -140,7 +169,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 440, "id": "590c9d20", "metadata": {}, "outputs": [ @@ -150,8 +179,8 @@ "text": [ "0\n", "{'add': 0, 'append': 0, 'check_if_same_type': 0, 'dim_set': 0, 'flip': 0, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 0, 'remove': 0, 'remove_item': 0, 'sample': 0, 'setminus': 0, 'write_all': 0, 'write_all_set': 0, 'write_random': 0}\n", - "Result: [[Element(object=A1, attribute 1=A, attribute 2=1), Element(object=A2, attribute 1=A, attribute 2=2)], [Element(object=B1, attribute 1=B, attribute 2=1), Element(object=B2, attribute 1=B, attribute 2=2)]]\n", - "Elapsed time: 0.00010889998520724475\n" + "Result: [[Element(object=B1, attribute 1=B, attribute 2=1), Element(object=B2, attribute 1=B, attribute 2=2)], [Element(object=A1, attribute 1=A, attribute 2=1), Element(object=A2, attribute 1=A, attribute 2=2)]]\n", + "Elapsed time: 0.0013715000823140144\n" ] } ], @@ -168,7 +197,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 441, "id": "7e2d4e07", "metadata": {}, "outputs": [ @@ -176,10 +205,10 @@ "name": "stdout", "output_type": "stream", "text": [ - "14\n", - "{'add': 0, 'append': 0, 'check_if_same_type': 1, 'dim_set': 0, 'flip': 1, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 4, 'remove': 0, 'remove_item': 0, 'sample': 2, 'setminus': 4, 'write_all': 0, 'write_all_set': 0, 'write_random': 2}\n", - "Result: [Element(object=B2, attribute 1=B, attribute 2=2), Element(object=B1, attribute 1=B, attribute 2=1), Element(object=A2, attribute 1=A, attribute 2=2), Element(object=A1, attribute 1=A, attribute 2=1)]\n", - "Elapsed time: 7.199996616691351e-06\n" + "24\n", + "{'add': 0, 'append': 0, 'check_if_same_type': 6, 'dim_set': 0, 'flip': 1, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 4, 'remove': 0, 'remove_item': 0, 'sample': 7, 'setminus': 4, 'write_all': 0, 'write_all_set': 0, 'write_random': 2}\n", + "Result: [Element(object=A1, attribute 1=A, attribute 2=1), Element(object=B1, attribute 1=B, attribute 2=1), Element(object=A2, attribute 1=A, attribute 2=2), Element(object=B2, attribute 1=B, attribute 2=2)]\n", + "Elapsed time: 0.0003237000200897455\n" ] } ], @@ -196,7 +225,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 442, "id": "092f34e3", "metadata": {}, "outputs": [ @@ -204,10 +233,10 @@ "name": "stdout", "output_type": "stream", "text": [ - "14\n", - "{'add': 0, 'append': 0, 'check_if_same_type': 1, 'dim_set': 0, 'flip': 1, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 4, 'remove': 0, 'remove_item': 0, 'sample': 2, 'setminus': 4, 'write_all': 0, 'write_all_set': 0, 'write_random': 2}\n", - "Result: [Element(object=A1, attribute 1=A, attribute 2=1), Element(object=A2, attribute 1=A, attribute 2=2), Element(object=B2, attribute 1=B, attribute 2=2), Element(object=B1, attribute 1=B, attribute 2=1)]\n", - "Elapsed time: 7.700000423938036e-06\n" + "18\n", + "{'add': 0, 'append': 0, 'check_if_same_type': 3, 'dim_set': 0, 'flip': 1, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 4, 'remove': 0, 'remove_item': 0, 'sample': 4, 'setminus': 4, 'write_all': 0, 'write_all_set': 0, 'write_random': 2}\n", + "Result: [Element(object=A2, attribute 1=A, attribute 2=2), Element(object=B2, attribute 1=B, attribute 2=2), Element(object=B1, attribute 1=B, attribute 2=1), Element(object=A1, attribute 1=A, attribute 2=1)]\n", + "Elapsed time: 0.0003361999988555908\n" ] } ], @@ -224,7 +253,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 443, "id": "ca81ceaf", "metadata": {}, "outputs": [ @@ -235,7 +264,7 @@ "13\n", "{'add': 0, 'append': 2, 'check_if_same_type': 0, 'dim_set': 0, 'flip': 1, 'implement': 0, 'list_create': 0, 'merge': 2, 'pair': 0, 'remove': 0, 'remove_item': 0, 'sample': 2, 'setminus': 4, 'write_all': 0, 'write_all_set': 0, 'write_random': 2}\n", "Result: [Element(object=B1, attribute 1=B, attribute 2=1), Element(object=B2, attribute 1=B, attribute 2=2), Element(object=A1, attribute 1=A, attribute 2=1), Element(object=A2, attribute 1=A, attribute 2=2)]\n", - "Elapsed time: 5.110001075081527e-05\n" + "Elapsed time: 0.002274699741974473\n" ] } ], @@ -252,13 +281,13 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 444, "id": "5c80b83a", "metadata": {}, "outputs": [ { "data": { - "image/png": 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", "text/plain": [ "
" ] diff --git a/newtest.ipynb b/newtest.ipynb index ae74e8a..f55b6b6 100644 --- a/newtest.ipynb +++ b/newtest.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 1, + "execution_count": 333, "id": "081f22f1", "metadata": {}, "outputs": [], @@ -13,7 +13,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 334, "id": "831c5eaf", "metadata": {}, "outputs": [], @@ -26,7 +26,251 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 335, + "id": "e64a7c0f", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "iterate k-complexity: 18\n", + "iterate primitive count: {'add': 0, 'append': 2, 'check_if_same_type': 0, 'dim_set': 0, 'flip': 2, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 0, 'remove': 0, 'remove_item': 0, 'sample': 8, 'setminus': 6, 'write_all': 0, 'write_all_set': 0, 'write_random': 0}\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "palindrome k-complexity: 11\n", + "palindrome primitive count: {'add': 0, 'append': 1, 'check_if_same_type': 2, 'dim_set': 0, 'flip': 1, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 2, 'remove': 0, 'remove_item': 0, 'sample': 3, 'setminus': 2, 'write_all': 0, 'write_all_set': 0, 'write_random': 0}\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "alternate k-complexity: 18\n", + "alternate primitive count: {'add': 0, 'append': 0, 'check_if_same_type': 4, 'dim_set': 0, 'flip': 1, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 4, 'remove': 0, 'remove_item': 0, 'sample': 5, 'setminus': 4, 'write_all': 0, 'write_all_set': 0, 'write_random': 0}\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "chaining k-complexity: 15\n", + "chaining primitive count: {'add': 0, 'append': 0, 'check_if_same_type': 0, 'dim_set': 0, 'flip': 0, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 6, 'remove': 0, 'remove_item': 0, 'sample': 5, 'setminus': 4, 'write_all': 0, 'write_all_set': 0, 'write_random': 0}\n" + ] + }, + { + "data": { + "image/png": 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", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "serial_crossed k-complexity: 16\n", + "serial_crossed primitive count: {'add': 0, 'append': 0, 'check_if_same_type': 2, 'dim_set': 0, 'flip': 1, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 4, 'remove': 0, 'remove_item': 0, 'sample': 3, 'setminus': 4, 'write_all': 0, 'write_all_set': 0, 'write_random': 2}\n" + ] + }, + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "center_embedded k-complexity: 20\n", + "center_embedded primitive count: {'add': 0, 'append': 0, 'check_if_same_type': 4, 'dim_set': 0, 'flip': 1, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 4, 'remove': 0, 'remove_item': 0, 'sample': 5, 'setminus': 4, 'write_all': 0, 'write_all_set': 0, 'write_random': 2}\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "tail_recursive k-complexity: 13\n", + "tail_recursive primitive count: {'add': 0, 'append': 2, 'check_if_same_type': 0, 'dim_set': 0, 'flip': 1, 'implement': 0, 'list_create': 0, 'merge': 2, 'pair': 0, 'remove': 0, 'remove_item': 0, 'sample': 2, 'setminus': 4, 'write_all': 0, 'write_all_set': 0, 'write_random': 2}\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Total K-complexity: 111\n", + "Total primitive counts: {'add': 0, 'append': 5, 'check_if_same_type': 12, 'dim_set': 0, 'flip': 7, 'implement': 0, 'list_create': 0, 'merge': 2, 'pair': 20, 'remove': 0, 'remove_item': 0, 'sample': 31, 'setminus': 28, 'write_all': 0, 'write_all_set': 0, 'write_random': 6}\n" + ] + }, + { + "data": { + "image/png": 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", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "element_set = {a,b,c,d}\n", + "S = ElementSet(element_set)\n", + "kc = KComplexity()\n", + "cf.iterate(S)\n", + "print(kc.get_cog_name() + ' k-complexity: ', kc.get_k_complexity())\n", + "print(kc.get_cog_name() + ' primitive count: ', kc.get_prim_counts())\n", + "kc.plot_prim_counts()\n", + "\n", + "element_set = {a,b,c,d}\n", + "S = ElementSet(element_set)\n", + "cf.palindrome(S)\n", + "print(kc.get_cog_name() + ' k-complexity: ', kc.get_k_complexity())\n", + "print(kc.get_cog_name() + ' primitive count: ', kc.get_prim_counts())\n", + "kc.plot_prim_counts()\n", + "\n", + "element_set = {a,b,c,d}\n", + "S = ElementSet(element_set)\n", + "cf.alternate(S)\n", + "print(kc.get_cog_name() + ' k-complexity: ', kc.get_k_complexity())\n", + "print(kc.get_cog_name() + ' primitive count: ', kc.get_prim_counts())\n", + "kc.plot_prim_counts()\n", + "\n", + "element_set = {a,b,c,d}\n", + "S = ElementSet(element_set)\n", + "assoc = Associations({a: b, c: d})\n", + "cf.chaining(S, assoc)\n", + "print(kc.get_cog_name() + ' k-complexity: ', kc.get_k_complexity())\n", + "print(kc.get_cog_name() + ' primitive count: ', kc.get_prim_counts())\n", + "kc.plot_prim_counts()\n", + "\n", + "element_set = {a,b,c,d}\n", + "S = ElementSet(element_set)\n", + "cf.seriate(S)\n", + "print(kc.get_cog_name() + ' k-complexity: ', kc.get_k_complexity())\n", + "print(kc.get_cog_name() + ' primitive count: ', kc.get_prim_counts())\n", + "kc.plot_prim_counts()\n", + "\n", + "element_set = {a,b,c,d}\n", + "S = ElementSet(element_set)\n", + "cf.serial_crossed(S)\n", + "print(kc.get_cog_name() + ' k-complexity: ', kc.get_k_complexity())\n", + "print(kc.get_cog_name() + ' primitive count: ', kc.get_prim_counts())\n", + "kc.plot_prim_counts()\n", + "\n", + "element_set = {a,b,c,d}\n", + "S = ElementSet(element_set)\n", + "cf.center_embedded(S)\n", + "print(kc.get_cog_name() + ' k-complexity: ', kc.get_k_complexity())\n", + "print(kc.get_cog_name() + ' primitive count: ', kc.get_prim_counts())\n", + "kc.plot_prim_counts()\n", + "\n", + "element_set = {a,b,c,d}\n", + "S = ElementSet(element_set)\n", + "cf.tail_recursive(S)\n", + "print(kc.get_cog_name() + ' k-complexity: ', kc.get_k_complexity())\n", + "print(kc.get_cog_name() + ' primitive count: ', kc.get_prim_counts())\n", + "kc.plot_prim_counts()\n", + "\n", + "print('Total K-complexity: ', kc.get_total_k_complexity())\n", + "print('Total primitive counts: ', kc.get_total_prim_counts())\n", + "kc.plot_total_prim_counts()\n", + "kc.plot_cog_vs_prim()" + ] + }, + { + "cell_type": "code", + "execution_count": 336, "id": "030b28dc", "metadata": {}, "outputs": [ @@ -34,11 +278,21 @@ "name": "stdout", "output_type": "stream", "text": [ - "18\n", - "{'add': 0, 'append': 2, 'check_if_same_type': 0, 'dim_set': 0, 'flip': 2, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 0, 'remove': 0, 'remove_item': 0, 'sample': 8, 'setminus': 6, 'write_all': 0, 'write_all_set': 0, 'write_random': 0}\n", - "Result: [Element(object=A2, attribute 1=A, attribute 2=2), Element(object=A1, attribute 1=A, attribute 2=1), Element(object=B1, attribute 1=B, attribute 2=1), Element(object=B2, attribute 1=B, attribute 2=2)]\n", - "Elapsed time: 3.0399998649954796e-05\n" + "Result: [Element(object=A1, attribute 1=A, attribute 2=1), Element(object=A2, attribute 1=A, attribute 2=2), Element(object=B1, attribute 1=B, attribute 2=1), Element(object=B2, attribute 1=B, attribute 2=2)]\n", + "Elapsed time: 0.0018539996817708015\n", + "iterate k-complexity: 18\n", + "iterate primitive count: {'add': 0, 'append': 2, 'check_if_same_type': 0, 'dim_set': 0, 'flip': 2, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 0, 'remove': 0, 'remove_item': 0, 'sample': 8, 'setminus': 6, 'write_all': 0, 'write_all_set': 0, 'write_random': 0}\n" ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" } ], "source": [ @@ -46,15 +300,16 @@ "S = ElementSet(element_set)\n", "kc = KComplexity()\n", "result, elapsed_time = cf.iterate(S)\n", - "print(kc.get_k_complexity())\n", - "print(kc.get_prim_counts())\n", "print(\"Result:\", result)\n", - "print(\"Elapsed time:\", elapsed_time)\n" + "print(\"Elapsed time:\", elapsed_time)\n", + "print(kc.get_cog_name() + ' k-complexity: ', kc.get_k_complexity())\n", + "print(kc.get_cog_name() + ' primitive count: ', kc.get_prim_counts())\n", + "kc.plot_prim_counts()" ] }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 337, "id": "034a7977", "metadata": {}, "outputs": [ @@ -62,11 +317,21 @@ "name": "stdout", "output_type": "stream", "text": [ - "9\n", - "{'add': 0, 'append': 1, 'check_if_same_type': 1, 'dim_set': 0, 'flip': 1, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 2, 'remove': 0, 'remove_item': 0, 'sample': 2, 'setminus': 2, 'write_all': 0, 'write_all_set': 0, 'write_random': 0}\n", - "Result: [Element(object=B1, attribute 1=B, attribute 2=1), Element(object=A1, attribute 1=A, attribute 2=1)]\n", - "Elapsed time: 7.37000082153827e-05\n" + "Result: [Element(object=B1, attribute 1=B, attribute 2=1), Element(object=B2, attribute 1=B, attribute 2=2)]\n", + "Elapsed time: 0.0015916000120341778\n", + "palindrome k-complexity: 9\n", + "palindrome primitive count: {'add': 0, 'append': 1, 'check_if_same_type': 1, 'dim_set': 0, 'flip': 1, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 2, 'remove': 0, 'remove_item': 0, 'sample': 2, 'setminus': 2, 'write_all': 0, 'write_all_set': 0, 'write_random': 0}\n" ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" } ], "source": [ @@ -74,15 +339,16 @@ "S = ElementSet(element_set)\n", "kc = KComplexity()\n", "result, elapsed_time = cf.palindrome(S)\n", - "print(kc.get_k_complexity())\n", - "print(kc.get_prim_counts())\n", "print(\"Result:\", result)\n", - "print(\"Elapsed time:\", elapsed_time)" + "print(\"Elapsed time:\", elapsed_time)\n", + "print(kc.get_cog_name() + ' k-complexity: ', kc.get_k_complexity())\n", + "print(kc.get_cog_name() + ' primitive count: ', kc.get_prim_counts())\n", + "kc.plot_prim_counts()\n" ] }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 338, "id": "df882383", "metadata": {}, "outputs": [ @@ -90,11 +356,21 @@ "name": "stdout", "output_type": "stream", "text": [ - "16\n", - "{'add': 0, 'append': 0, 'check_if_same_type': 3, 'dim_set': 0, 'flip': 1, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 4, 'remove': 0, 'remove_item': 0, 'sample': 4, 'setminus': 4, 'write_all': 0, 'write_all_set': 0, 'write_random': 0}\n", - "Result: [Element(object=A1, attribute 1=A, attribute 2=1), Element(object=A2, attribute 1=A, attribute 2=2), Element(object=B1, attribute 1=B, attribute 2=1), Element(object=B2, attribute 1=B, attribute 2=2)]\n", - "Elapsed time: 5.4000120144337416e-06\n" + "Result: [Element(object=B1, attribute 1=B, attribute 2=1), Element(object=B2, attribute 1=B, attribute 2=2), Element(object=A1, attribute 1=A, attribute 2=1), Element(object=A2, attribute 1=A, attribute 2=2)]\n", + "Elapsed time: 0.0003559999167919159\n", + "alternate k-complexity: 22\n", + "alternate primitive count: {'add': 0, 'append': 0, 'check_if_same_type': 6, 'dim_set': 0, 'flip': 1, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 4, 'remove': 0, 'remove_item': 0, 'sample': 7, 'setminus': 4, 'write_all': 0, 'write_all_set': 0, 'write_random': 0}\n" ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" } ], "source": [ @@ -102,15 +378,16 @@ "S = ElementSet(element_set)\n", "kc = KComplexity()\n", "result, elapsed_time = cf.alternate(S)\n", - "print(kc.get_k_complexity())\n", - "print(kc.get_prim_counts())\n", "print(\"Result:\", result)\n", - "print(\"Elapsed time:\", elapsed_time)" + "print(\"Elapsed time:\", elapsed_time)\n", + "print(kc.get_cog_name() + ' k-complexity: ', kc.get_k_complexity())\n", + "print(kc.get_cog_name() + ' primitive count: ', kc.get_prim_counts())\n", + "kc.plot_prim_counts()\n" ] }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 339, "id": "da9b45ff", "metadata": {}, "outputs": [ @@ -118,29 +395,39 @@ "name": "stdout", "output_type": "stream", "text": [ - "15\n", - "{'add': 0, 'append': 0, 'check_if_same_type': 0, 'dim_set': 0, 'flip': 0, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 6, 'remove': 0, 'remove_item': 0, 'sample': 5, 'setminus': 4, 'write_all': 0, 'write_all_set': 0, 'write_random': 0}\n", - "Result: [[Element(object=B1, attribute 1=B, attribute 2=1), Element(object=B2, attribute 1=B, attribute 2=2)], [Element(object=A1, attribute 1=A, attribute 2=1), Element(object=A2, attribute 1=A, attribute 2=2)]]\n", - "Elapsed time: 3.7699996028095484e-05\n" + "Result: [[Element(object=A1, attribute 1=A, attribute 2=1), Element(object=A2, attribute 1=A, attribute 2=2)], [Element(object=B1, attribute 1=B, attribute 2=1), Element(object=B2, attribute 1=B, attribute 2=2)]]\n", + "Elapsed time: 0.0021164000499993563\n", + "chaining k-complexity: 20\n", + "chaining primitive count: {'add': 0, 'append': 0, 'check_if_same_type': 0, 'dim_set': 0, 'flip': 0, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 6, 'remove': 0, 'remove_item': 0, 'sample': 10, 'setminus': 4, 'write_all': 0, 'write_all_set': 0, 'write_random': 0}\n" ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" } ], "source": [ "element_set = {a,b,c,d}\n", + "S = ElementSet(element_set)\n", "assoc = Associations({a: b, c: d})\n", - "S = ElementSet(element_set, assoc)\n", "kc = KComplexity()\n", - "\n", "result, elapsed_time = cf.chaining(S, assoc)\n", - "print(kc.get_k_complexity())\n", - "print(kc.get_prim_counts())\n", "print(\"Result:\", result)\n", - "print(\"Elapsed time:\", elapsed_time)" + "print(\"Elapsed time:\", elapsed_time)\n", + "print(kc.get_cog_name() + ' k-complexity: ', kc.get_k_complexity())\n", + "print(kc.get_cog_name() + ' primitive count: ', kc.get_prim_counts())\n", + "kc.plot_prim_counts()" ] }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 340, "id": "590c9d20", "metadata": {}, "outputs": [ @@ -148,11 +435,19 @@ "name": "stdout", "output_type": "stream", "text": [ - "0\n", - "{'add': 0, 'append': 0, 'check_if_same_type': 0, 'dim_set': 0, 'flip': 0, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 0, 'remove': 0, 'remove_item': 0, 'sample': 0, 'setminus': 0, 'write_all': 0, 'write_all_set': 0, 'write_random': 0}\n", - "Result: [[Element(object=B1, attribute 1=B, attribute 2=1), Element(object=B2, attribute 1=B, attribute 2=2)], [Element(object=A1, attribute 1=A, attribute 2=1), Element(object=A2, attribute 1=A, attribute 2=2)]]\n", - "Elapsed time: 3.7699996028095484e-05\n" + "seriate k-complexity: 0\n", + "seriate primitive count: {'add': 0, 'append': 0, 'check_if_same_type': 0, 'dim_set': 0, 'flip': 0, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 0, 'remove': 0, 'remove_item': 0, 'sample': 0, 'setminus': 0, 'write_all': 0, 'write_all_set': 0, 'write_random': 0}\n" ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" } ], "source": [ @@ -160,15 +455,14 @@ "S = ElementSet(element_set)\n", "kc = KComplexity()\n", "cf.seriate(S)\n", - "print(kc.get_k_complexity())\n", - "print(kc.get_prim_counts())\n", - "print(\"Result:\", result)\n", - "print(\"Elapsed time:\", elapsed_time)" + "print(kc.get_cog_name() + ' k-complexity: ', kc.get_k_complexity())\n", + "print(kc.get_cog_name() + ' primitive count: ', kc.get_prim_counts())\n", + "kc.plot_prim_counts()" ] }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 341, "id": "7e2d4e07", "metadata": {}, "outputs": [ @@ -176,11 +470,21 @@ "name": "stdout", "output_type": "stream", "text": [ - "28\n", - "{'add': 0, 'append': 0, 'check_if_same_type': 11, 'dim_set': 0, 'flip': 1, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 2, 'remove': 0, 'remove_item': 0, 'sample': 12, 'setminus': 2, 'write_all': 0, 'write_all_set': 0, 'write_random': 0}\n", - "Result: [Element(object=B2, attribute 1=B, attribute 2=2), Element(object=A2, attribute 1=A, attribute 2=2)]\n", - "Elapsed time: 6.799993570894003e-06\n" + "Result: [Element(object=B2, attribute 1=B, attribute 2=2), Element(object=A2, attribute 1=A, attribute 2=2), Element(object=B1, attribute 1=B, attribute 2=1), Element(object=A1, attribute 1=A, attribute 2=1)]\n", + "Elapsed time: 0.0004013997968286276\n", + "serial_crossed k-complexity: 14\n", + "serial_crossed primitive count: {'add': 0, 'append': 0, 'check_if_same_type': 1, 'dim_set': 0, 'flip': 1, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 4, 'remove': 0, 'remove_item': 0, 'sample': 2, 'setminus': 4, 'write_all': 0, 'write_all_set': 0, 'write_random': 2}\n" ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" } ], "source": [ @@ -188,15 +492,16 @@ "S = ElementSet(element_set)\n", "kc = KComplexity()\n", "result, elapsed_time = cf.serial_crossed(S)\n", - "print(kc.get_k_complexity())\n", - "print(kc.get_prim_counts())\n", "print(\"Result:\", result)\n", - "print(\"Elapsed time:\", elapsed_time)" + "print(\"Elapsed time:\", elapsed_time)\n", + "print(kc.get_cog_name() + ' k-complexity: ', kc.get_k_complexity())\n", + "print(kc.get_cog_name() + ' primitive count: ', kc.get_prim_counts())\n", + "kc.plot_prim_counts()" ] }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 342, "id": "092f34e3", "metadata": {}, "outputs": [ @@ -204,11 +509,21 @@ "name": "stdout", "output_type": "stream", "text": [ - "8\n", - "{'add': 0, 'append': 0, 'check_if_same_type': 1, 'dim_set': 0, 'flip': 1, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 2, 'remove': 0, 'remove_item': 0, 'sample': 2, 'setminus': 2, 'write_all': 0, 'write_all_set': 0, 'write_random': 0}\n", - "Result: [Element(object=A1, attribute 1=A, attribute 2=1), Element(object=A2, attribute 1=A, attribute 2=2)]\n", - "Elapsed time: 7.399969035759568e-06\n" + "Result: [Element(object=A1, attribute 1=A, attribute 2=1), Element(object=B1, attribute 1=B, attribute 2=1), Element(object=B2, attribute 1=B, attribute 2=2), Element(object=A2, attribute 1=A, attribute 2=2)]\n", + "Elapsed time: 0.0003448999486863613\n", + "center_embedded k-complexity: 14\n", + "center_embedded primitive count: {'add': 0, 'append': 0, 'check_if_same_type': 1, 'dim_set': 0, 'flip': 1, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 4, 'remove': 0, 'remove_item': 0, 'sample': 2, 'setminus': 4, 'write_all': 0, 'write_all_set': 0, 'write_random': 2}\n" ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" } ], "source": [ @@ -216,15 +531,16 @@ "S = ElementSet(element_set)\n", "kc = KComplexity()\n", "result, elapsed_time = cf.center_embedded(S)\n", - "print(kc.get_k_complexity())\n", - "print(kc.get_prim_counts())\n", "print(\"Result:\", result)\n", - "print(\"Elapsed time:\", elapsed_time)" + "print(\"Elapsed time:\", elapsed_time)\n", + "print(kc.get_cog_name() + ' k-complexity: ', kc.get_k_complexity())\n", + "print(kc.get_cog_name() + ' primitive count: ', kc.get_prim_counts())\n", + "kc.plot_prim_counts()" ] }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 343, "id": "ca81ceaf", "metadata": {}, "outputs": [ @@ -232,11 +548,21 @@ "name": "stdout", "output_type": "stream", "text": [ - "9\n", - "{'add': 0, 'append': 0, 'check_if_same_type': 0, 'dim_set': 0, 'flip': 1, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 0, 'remove': 0, 'remove_item': 0, 'sample': 4, 'setminus': 4, 'write_all': 0, 'write_all_set': 0, 'write_random': 0}\n", - "Result: []\n", - "Elapsed time: 9.6399977337569e-05\n" + "Result: [Element(object=A2, attribute 1=A, attribute 2=2), Element(object=B2, attribute 1=B, attribute 2=2), Element(object=A1, attribute 1=A, attribute 2=1), Element(object=B1, attribute 1=B, attribute 2=1)]\n", + "Elapsed time: 0.0029325999785214663\n", + "tail_recursive k-complexity: 13\n", + "tail_recursive primitive count: {'add': 0, 'append': 2, 'check_if_same_type': 0, 'dim_set': 0, 'flip': 1, 'implement': 0, 'list_create': 0, 'merge': 2, 'pair': 0, 'remove': 0, 'remove_item': 0, 'sample': 2, 'setminus': 4, 'write_all': 0, 'write_all_set': 0, 'write_random': 2}\n" ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" } ], "source": [ @@ -244,31 +570,64 @@ "S = ElementSet(element_set)\n", "kc = KComplexity()\n", "result, elapsed_time = cf.tail_recursive(S)\n", - "print(kc.get_k_complexity())\n", - "print(kc.get_prim_counts())\n", "print(\"Result:\", result)\n", - "print(\"Elapsed time:\", elapsed_time)" + "print(\"Elapsed time:\", elapsed_time)\n", + "print(kc.get_cog_name() + ' k-complexity: ', kc.get_k_complexity())\n", + "print(kc.get_cog_name() + ' primitive count: ', kc.get_prim_counts())\n", + "kc.plot_prim_counts()" ] }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 344, "id": "5c80b83a", "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Total K-complexity: 13\n", + "Total primitive counts: {'add': 0, 'append': 2, 'check_if_same_type': 0, 'dim_set': 0, 'flip': 1, 'implement': 0, 'list_create': 0, 'merge': 2, 'pair': 0, 'remove': 0, 'remove_item': 0, 'sample': 2, 'setminus': 4, 'write_all': 0, 'write_all_set': 0, 'write_random': 2}\n" + ] + }, + { + "data": { + "image/png": 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", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" } ], "source": [ - "S.visualize()" + "S.visualize()\n", + "print('Total K-complexity: ', kc.get_total_k_complexity())\n", + "print('Total primitive counts: ', kc.get_total_prim_counts())\n", + "kc.plot_total_prim_counts()\n", + "kc.plot_cog_vs_prim()" ] } ], diff --git a/utils.py b/utils.py index 743341c..1cbb269 100644 --- a/utils.py +++ b/utils.py @@ -8,6 +8,9 @@ from dataclasses import dataclass import primitive_fucntions as pf import importlib +import copy +from collections import defaultdict +import numpy as np # ---------------------------------------------------------------------# @@ -151,32 +154,119 @@ def get_elapsed_time(self): class KComplexity: def __init__(self): self.prim = importlib.import_module('primitive_fucntions') + self.cog = importlib.import_module('cognitive_functions') self.call_counts = {} + self.total_calls = {} + self.cog_func_calls = defaultdict(list) self._wrap_prim_functions() + self._wrap_cog_functions() + self.current_cog_name = None def _wrap_prim_functions(self): for name in dir(self.prim): func = getattr(self.prim, name) if callable(func) and not name.startswith("__"): self.call_counts[name] = 0 - wrapper_func = self._make_wrapper(func, name) - setattr(self.prim, name, wrapper_func) + self.total_calls[name] = 0 + wrapper_func = self._make_prim_wrapper(func, name) + setattr(self.prim, name, self._make_prim_wrapper(func, name)) - def _make_wrapper(self, func, name): + def _wrap_cog_functions(self): + for name in dir(self.cog): + if name.startswith("__") or name == "find_bias": + continue + func = getattr(self.cog, name) + if callable(func): + setattr(self.cog, name, self._make_cog_wrapper(func, name)) + + def _make_prim_wrapper(self, func, name): def wrapper(*args, **kwargs): self.call_counts[name] += 1 + self.total_calls[name] += 1 return func(*args, **kwargs) return wrapper + + def _make_cog_wrapper(self, func, name): + def wrapper(*args, **kwargs): + self.reset() + result = func(*args, **kwargs) + self.cog_func_calls[name].append(copy.deepcopy(self.call_counts)) + self.current_cog_name = name + return result + return wrapper - """get dictionary of each prim function call count""" + def get_cog_name(self): + return self.current_cog_name + def get_prim_counts(self): return dict(self.call_counts) - """get total number of prim function calls""" + def get_total_prim_counts(self): + return dict(self.total_calls) + def get_k_complexity(self): return sum(self.call_counts.values()) - """reset all prim function call counts to zero""" + def get_total_k_complexity(self): + return sum(self.total_calls.values()) + def reset(self): for key in self.call_counts: - self.call_counts[key] = 0 \ No newline at end of file + self.call_counts[key] = 0 + + def plot_prim_counts(self): + data = self.get_prim_counts() + plt.bar(data.keys(), data.values()) + plt.xticks(rotation=45, ha='right') + plt.ylabel("Call Count") + plt.title(self.get_cog_name() + " Primitive Function Usage") + plt.tight_layout() + plt.show() + + def plot_total_prim_counts(self): + data = self.get_total_prim_counts() + plt.bar(data.keys(), data.values()) + plt.xticks(rotation=45, ha='right') + plt.ylabel("Call Count") + plt.title("Total Primitive Function Usage") + plt.tight_layout() + plt.show() + + def plot_cog_vs_prim(self): + import matplotlib.pyplot as plt + import matplotlib.cm as cm + import matplotlib.colors as mcolors + + prim_names = list(self.call_counts.keys()) + + valid_cog_fns = {"iterate", "palindrome", "alternate", "chaining", "seriate", "serial_crossed", "center_embedded", "tail_recursive"} + cog_names = [cog for cog in self.cog_func_calls if cog in valid_cog_fns and len(self.cog_func_calls[cog]) > 0] + + averaged_data = [] + cog_labels = [] + for cog in cog_names: + call_count = len(self.cog_func_calls[cog]) + cog_labels.append(f"{cog} ({call_count}x)") + + summed = defaultdict(int) + for d in self.cog_func_calls[cog]: + for k in d: + summed[k] += d[k] + avg = {k: summed[k] / call_count for k in prim_names} + averaged_data.append(avg) + + color_map = cm.get_cmap('tab20', len(prim_names)) + colors = {prim: color_map(i) for i, prim in enumerate(prim_names)} + + bottom = np.zeros(len(cog_labels)) + for prim in prim_names: + heights = [d[prim] for d in averaged_data] + plt.bar(cog_labels, heights, bottom=bottom, label=prim, color=colors[prim]) + bottom += heights + + plt.xticks(rotation=45, ha='right') + plt.ylabel("Total Primitive Calls") + plt.title("All Cognitive Function Calls with Primitive Usage Breakdown") + plt.legend(title="Primitive Functions", bbox_to_anchor=(1.05, 1), loc='upper left') + plt.tight_layout() + plt.show() From 670651db632a191b0adf7e80dbd21730703702d7 Mon Sep 17 00:00:00 2001 From: LuckyBunnyLee Date: Tue, 29 Jul 2025 12:59:11 -0700 Subject: [PATCH 8/8] finished finished this time --- newtest.ipynb | 768 +++++++++++++++++++++++++++++++++++--------------- utils.py | 47 ++- 2 files changed, 577 insertions(+), 238 deletions(-) diff --git a/newtest.ipynb b/newtest.ipynb index f55b6b6..3b19bbc 100644 --- a/newtest.ipynb +++ b/newtest.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 333, + "execution_count": 25, "id": "081f22f1", "metadata": {}, "outputs": [], @@ -13,7 +13,7 @@ }, { "cell_type": "code", - "execution_count": 334, + "execution_count": 26, "id": "831c5eaf", "metadata": {}, "outputs": [], @@ -26,7 +26,7 @@ }, { "cell_type": "code", - "execution_count": 335, + "execution_count": 27, "id": "e64a7c0f", "metadata": {}, "outputs": [ @@ -34,67 +34,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "iterate k-complexity: 18\n", - "iterate primitive count: {'add': 0, 'append': 2, 'check_if_same_type': 0, 'dim_set': 0, 'flip': 2, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 0, 'remove': 0, 'remove_item': 0, 'sample': 8, 'setminus': 6, 'write_all': 0, 'write_all_set': 0, 'write_random': 0}\n" - ] - }, - { - "data": { - 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", 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", 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "chaining k-complexity: 15\n", - "chaining primitive count: {'add': 0, 'append': 0, 'check_if_same_type': 0, 'dim_set': 0, 'flip': 0, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 6, 'remove': 0, 'remove_item': 0, 'sample': 5, 'setminus': 4, 'write_all': 0, 'write_all_set': 0, 'write_random': 0}\n" + "Total K-complexity: 54\n", + "Total primitive counts: {'add': 0, 'append': 6, 'check_if_same_type': 4, 'dim_set': 0, 'flip': 6, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 8, 'remove': 0, 'remove_item': 0, 'sample': 16, 'setminus': 14, 'write_all': 0, 'write_all_set': 0, 'write_random': 0}\n" ] }, { "data": { - "image/png": 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", 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", 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" ] @@ -102,17 +48,9 @@ "metadata": {}, "output_type": "display_data" }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "seriate k-complexity: 0\n", - "seriate primitive count: {'add': 0, 'append': 0, 'check_if_same_type': 0, 'dim_set': 0, 'flip': 0, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 0, 'remove': 0, 'remove_item': 0, 'sample': 0, 'setminus': 0, 'write_all': 0, 'write_all_set': 0, 'write_random': 0}\n" - ] - }, { "data": { - "image/png": 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", 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", 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" ] @@ -120,83 +58,167 @@ "metadata": {}, "output_type": "display_data" }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "serial_crossed k-complexity: 16\n", - "serial_crossed primitive count: {'add': 0, 'append': 0, 'check_if_same_type': 2, 'dim_set': 0, 'flip': 1, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 4, 'remove': 0, 'remove_item': 0, 'sample': 3, 'setminus': 4, 'write_all': 0, 'write_all_set': 0, 'write_random': 2}\n" - ] - }, { "data": { - "image/png": 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Cognitive Function (calls)
iterate (1x)020020000008600018
palindrome (4x)044040008008800036
Total Counts for each Primitive Function06406000800161400054
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", 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Total K-complexity: 111\n", - "Total primitive counts: {'add': 0, 'append': 5, 'check_if_same_type': 12, 'dim_set': 0, 'flip': 7, 'implement': 0, 'list_create': 0, 'merge': 2, 'pair': 20, 'remove': 0, 'remove_item': 0, 'sample': 31, 'setminus': 28, 'write_all': 0, 'write_all_set': 0, 'write_random': 6}\n" - ] - }, - { - "data": { - "image/png": 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", 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", - "text/plain": [ - "
" + " add append check_if_same_type \\\n", + "Cognitive Function (calls) \n", + "iterate (1x) 0 2 0 \n", + "palindrome (4x) 0 4 4 \n", + "Total Counts for each Primitive Function 0 6 4 \n", + "\n", + " dim_set flip implement \\\n", + "Cognitive Function (calls) \n", + "iterate (1x) 0 2 0 \n", + "palindrome (4x) 0 4 0 \n", + "Total Counts for each Primitive Function 0 6 0 \n", + "\n", + " list_create merge pair remove \\\n", + "Cognitive Function (calls) \n", + "iterate (1x) 0 0 0 0 \n", + "palindrome (4x) 0 0 8 0 \n", + "Total Counts for each Primitive Function 0 0 8 0 \n", + "\n", + " remove_item sample setminus \\\n", + "Cognitive Function (calls) \n", + "iterate (1x) 0 8 6 \n", + "palindrome (4x) 0 8 8 \n", + "Total Counts for each Primitive Function 0 16 14 \n", + "\n", + " write_all write_all_set \\\n", + "Cognitive Function (calls) \n", + "iterate (1x) 0 0 \n", + "palindrome (4x) 0 0 \n", + "Total Counts for each Primitive Function 0 0 \n", + "\n", + " write_random Total \n", + "Cognitive Function (calls) \n", + "iterate (1x) 0 18 \n", + "palindrome (4x) 0 36 \n", + "Total Counts for each Primitive Function 0 54 " ] }, "metadata": {}, @@ -208,69 +230,33 @@ "S = ElementSet(element_set)\n", "kc = KComplexity()\n", "cf.iterate(S)\n", - "print(kc.get_cog_name() + ' k-complexity: ', kc.get_k_complexity())\n", - "print(kc.get_cog_name() + ' primitive count: ', kc.get_prim_counts())\n", - "kc.plot_prim_counts()\n", "\n", "element_set = {a,b,c,d}\n", "S = ElementSet(element_set)\n", "cf.palindrome(S)\n", - "print(kc.get_cog_name() + ' k-complexity: ', kc.get_k_complexity())\n", - "print(kc.get_cog_name() + ' primitive count: ', kc.get_prim_counts())\n", - "kc.plot_prim_counts()\n", - "\n", - "element_set = {a,b,c,d}\n", - "S = ElementSet(element_set)\n", - "cf.alternate(S)\n", - "print(kc.get_cog_name() + ' k-complexity: ', kc.get_k_complexity())\n", - "print(kc.get_cog_name() + ' primitive count: ', kc.get_prim_counts())\n", - "kc.plot_prim_counts()\n", "\n", "element_set = {a,b,c,d}\n", "S = ElementSet(element_set)\n", - "assoc = Associations({a: b, c: d})\n", - "cf.chaining(S, assoc)\n", - "print(kc.get_cog_name() + ' k-complexity: ', kc.get_k_complexity())\n", - "print(kc.get_cog_name() + ' primitive count: ', kc.get_prim_counts())\n", - "kc.plot_prim_counts()\n", - "\n", - "element_set = {a,b,c,d}\n", - "S = ElementSet(element_set)\n", - "cf.seriate(S)\n", - "print(kc.get_cog_name() + ' k-complexity: ', kc.get_k_complexity())\n", - "print(kc.get_cog_name() + ' primitive count: ', kc.get_prim_counts())\n", - "kc.plot_prim_counts()\n", - "\n", - "element_set = {a,b,c,d}\n", - "S = ElementSet(element_set)\n", - "cf.serial_crossed(S)\n", - "print(kc.get_cog_name() + ' k-complexity: ', kc.get_k_complexity())\n", - "print(kc.get_cog_name() + ' primitive count: ', kc.get_prim_counts())\n", - "kc.plot_prim_counts()\n", + "cf.palindrome(S)\n", "\n", "element_set = {a,b,c,d}\n", "S = ElementSet(element_set)\n", - "cf.center_embedded(S)\n", - "print(kc.get_cog_name() + ' k-complexity: ', kc.get_k_complexity())\n", - "print(kc.get_cog_name() + ' primitive count: ', kc.get_prim_counts())\n", - "kc.plot_prim_counts()\n", + "cf.palindrome(S)\n", "\n", "element_set = {a,b,c,d}\n", "S = ElementSet(element_set)\n", - "cf.tail_recursive(S)\n", - "print(kc.get_cog_name() + ' k-complexity: ', kc.get_k_complexity())\n", - "print(kc.get_cog_name() + ' primitive count: ', kc.get_prim_counts())\n", - "kc.plot_prim_counts()\n", + "cf.palindrome(S)\n", "\n", "print('Total K-complexity: ', kc.get_total_k_complexity())\n", "print('Total primitive counts: ', kc.get_total_prim_counts())\n", "kc.plot_total_prim_counts()\n", - "kc.plot_cog_vs_prim()" + "kc.plot_cog_vs_prim()\n", + "kc.show_cog_prim_table()" ] }, { "cell_type": "code", - "execution_count": 336, + "execution_count": 28, "id": "030b28dc", "metadata": {}, "outputs": [ @@ -278,15 +264,15 @@ "name": "stdout", "output_type": "stream", "text": [ - "Result: [Element(object=A1, attribute 1=A, attribute 2=1), Element(object=A2, attribute 1=A, attribute 2=2), Element(object=B1, attribute 1=B, attribute 2=1), Element(object=B2, attribute 1=B, attribute 2=2)]\n", - "Elapsed time: 0.0018539996817708015\n", + "Result: [Element(object=B1, attribute 1=B, attribute 2=1), Element(object=A1, attribute 1=A, attribute 2=1), Element(object=B2, attribute 1=B, attribute 2=2), Element(object=A2, attribute 1=A, attribute 2=2)]\n", + "Elapsed time: 4.589976742863655e-05\n", "iterate k-complexity: 18\n", "iterate primitive count: {'add': 0, 'append': 2, 'check_if_same_type': 0, 'dim_set': 0, 'flip': 2, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 0, 'remove': 0, 'remove_item': 0, 'sample': 8, 'setminus': 6, 'write_all': 0, 'write_all_set': 0, 'write_random': 0}\n" ] }, { "data": { - "image/png": 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SJlxrHvz/73//+/i7nGOPPbay0korxZI0U0wxRWWRRRaJ5UbSuIJ33323ssUWW8TXcP+23nrrWKql1ne855574vhi/HCPL7zwwspBBx0U21DNjTfeWFljjTXiteXBZ9M/X3755R/8jiKNwrNiRUREMrDI/VBJFZFWxRg7ERHpsZAVnYOYwwWcH+0m0p3QYiciIj0WYhHTubJkJROrSBwhRZ87qlsn0sqYPCEiIj0WEliuvvrq8OGHH8azmlddddWYEa2ok+6KFjsRERGRkmCMnYiIiEhJUNiJiIiIlIRuHWPH+X1UDKdQ5IQeKyQiIiLSHSBq7osvvgj9+vWLBclLK+wQdUWdVygiIiLSynDs4BxzzFFeYYelLn3Ros4tFBEREWklRo4cGQ1ZSfeUVtgl9yuiTmEnIiIiZWZ8ws5MnhAREREpCQo7ERERkZKgsBMREREpCQo7ERERkZKgsBMREREpCQo7ERERkZKgsBMREREpCQo7ERERkZLQVGE3evTocOSRR4Z55503TDHFFGH++ecPxxxzTDwTTUREREQmjKaePHHCCSeEc845J1x22WVh8cUXD08++WTYeeedQ9++fcN+++3XzKaJiIiIdDuaKuwefvjhsPnmm4dNN900/jzPPPOEq6++Ojz++OPNbJaIiIhIt6SprtjVVlst3HPPPeGVV16JPz/77LPhoYceCptssknN148aNSoehJs/RERERKQFLHaHHXZYFGeLLLJImHjiiWPM3XHHHRe23377mq8fMmRIGDx4cMPbKSIirc88h93WkM95a+j/eplEWpGmWuyuu+66cOWVV4arrroqPP300zHW7uSTT47/1mLQoEFhxIgRbY/hw4c3vM0iIiIirUpTLXaHHHJItNr9/Oc/jz8vueSS4e23346WuYEDB471+t69e8eHiIiIiLSYxe7rr78OE03Uvgm4ZMeMGdO0NomIiIh0V5pqsevfv3+MqZtrrrliuZN//OMf4dRTTw277LJLM5slIiIi0i1pqrA744wzYoHivfbaK3z88cehX79+Yffddw9HHXVUM5slIiIi0i1pqrDr06dPGDZsWHyIiIiISNfwrFgRERGRkqCwExERESkJCjsRERGRkqCwExERESkJCjsRERGRkqCwExERESkJCjsRERGRkqCwExERESkJCjsRERGRkqCwExERESkJCjsRERGRkqCwExERESkJCjsRERGRkqCwExERESkJCjsRERGRkqCwExERESkJCjsRERGRkqCwExERESkJCjsRERGRkqCwExERESkJCjsRERGRkqCwExERESkJCjsRERGRkqCwExERESkJCjsRERGRktBUYTfPPPOEXr16jfXYe++9m9ksERERkW7JJM388CeeeCKMHj267ecXXnghbLjhhmHrrbduZrNEREREuiVNFXYzzTRTu5+HDh0a5p9//rD22ms3rU0iIiIi3ZWWibH77rvvwhVXXBF22WWX6I4VERERkW5kscu5+eabw3/+85+w0047dfiaUaNGxUdi5MiRDWqdiIiISOvTMha7iy66KGyyySahX79+Hb5myJAhoW/fvm2POeecs6FtFBEREWllWkLYvf322+Huu+8Ou+666zhfN2jQoDBixIi2x/DhwxvWRhEREZFWpyVcsZdcckmYeeaZw6abbjrO1/Xu3Ts+RERERKQFLXZjxoyJwm7gwIFhkklaQmeKiIiIdEuaLuxwwb7zzjsxG1ZEREREOk/TTWQbbbRRqFQqzW6GiIiISLen6RY7ERERESkGhZ2IiIhISVDYiYiIiJQEhZ2IiIhISVDYiYiIiJQEhZ2IiIhISVDYiYiIiJQEhZ2IiIhISVDYiYiIiJQEhZ2IiIhISVDYiYiIiJQEhZ2IiIhISVDYiYiIiJQEhZ2IiIhISVDYiYiIiJQEhZ2IiIhISVDYiYiIiJQEhZ2IiIhISVDYiYiIiJQEhZ2IiIhISVDYiYiIiJQEhZ2IiIhISVDYiYiIiJQEhZ2IiIhISVDYiYiIiJQEhZ2IiIhISWi6sHvvvffCDjvsEGaYYYYwxRRThCWXXDI8+eSTzW6WiIiISLdjkmZ++Oeffx5WX331sO6664bbb789zDTTTOHVV18N0003XTObJSIiItItaaqwO+GEE8Kcc84ZLrnkkrbn5p133mY2SURERKTb0lRX7C233BJWWGGFsPXWW4eZZ545LLvssuGCCy5oZpNEREREui1NFXZvvPFGOOecc8KCCy4Y7rzzzrDnnnuG/fbbL1x22WU1Xz9q1KgwcuTIdg8RERERaQFX7JgxY6LF7vjjj48/Y7F74YUXwrnnnhsGDhw41uuHDBkSBg8e3ISWioiI/DDzHHZbQz7nraGbNuRzpPvRVIvdbLPNFhZbbLF2zy266KLhnXfeqfn6QYMGhREjRrQ9hg8f3qCWioiIiLQ+TbXYkRH78ssvt3vulVdeCXPPPXfN1/fu3Ts+RERERKTFLHYHHHBAePTRR6Mr9rXXXgtXXXVVOP/888Pee+/dzGaJiIiIdEuaKuxWXHHFcNNNN4Wrr746LLHEEuGYY44Jw4YNC9tvv30zmyUiIiLSLWmqKxY222yz+BARERGRbn6kmIiIiIgUg8JOREREpCQo7ERERERKgsJOREREpCQo7ERERERKgsJOREREpCQo7ERERERKgsJOREREpCQo7ERERERKgsJOREREpCQo7ERERERKgsJOREREpCQo7ERERERKgsJOREREpCQo7ERERERKgsJOREREpCQo7ERERERKgsJOREREpCQo7ERERERKgsJOREREpCQo7ERERERKgsJOREREpCQo7ERERERKgsJOREREpCQo7ERERER6qrC7/PLLw6hRo8Z6/rvvvou/ExEREZFuIux23nnnMGLEiLGe/+KLL+LvJoTf/va3oVevXu0eiyyyyIQ2SURERERCCJNM6B9UKpUowKp59913Q9++fSe4AYsvvni4++67/3+DJpngJomIiIjIhAi7ZZddts2qtv7667cTYKNHjw5vvvlm+NGPfjThDZhkkjDrrLNO8N+JiIiISCeF3YABA+K/zzzzTNh4443D1FNP3fa7ySabLMwzzzxhyy23DBPKq6++Gvr16xcmn3zysOqqq4YhQ4aEueaaa4LfR0RERKSnM97C7uijj47/IuC22WabKMS6ysorrxwuvfTSsPDCC4cPPvggDB48OKy55prhhRdeCH369Bnr9SRt5IkbI0eO7HIbRERERMrCBAe0DRw4sC0L9uOPPw5jxoxp9/sJsbZtsskmbf+/1FJLRaE399xzh+uuuy788pe/HOv1WPMQfyIiIiJSQFYsrlOsalNMMUUUYfPOO298YMnj364w7bTThoUWWii89tprNX8/aNCgmJGbHsOHD+/S54mIiIj0aIvdTjvtFBMebr311jDbbLPVzJDtLF9++WV4/fXXw4477ljz9717944PERERESlA2JE88dRTTxVSb+7ggw8O/fv3j5a/999/P8bxTTzxxGHbbbft8nuLiIiI9DQmWNgttthi4dNPPy3kw6l9h4j797//HWaaaaawxhprhEcffTT+v4iIiIjUWdidcMIJ4dBDDw3HH398WHLJJcOkk07a7vfTTDPNeL/XNddcM6EfLyIiIiJFCbsNNtgg/kuR4lonUlCsWERERES6gbC777776tMSEREREWmssFt77bW79okiIiIi0hrC7sEHHxzn79daa62utEdEREREGiXs1llnnbGey2vZGWMnIiIi0k1Onvj888/bPThW7I477ggrrrhi+Otf/1qfVoqIiIhI8Ra7vn37jvXchhtuGCabbLJw4IEHxuLFIiIiItINLHYdMcsss4SXX365qLcTERERkXpb7J577rmx6td98MEHYejQoWGZZZaZ0LcTERERkWYJO8QbyRIIupxVVlklXHzxxUW1S0RERETqLezefPPNdj9PNNFE8WzXySeffELfSkRERESaKezmnnvuIj9fRERERJqZPPHAAw+E/v37hwUWWCA+fvKTn4S//e1vRbVJRERERBoh7K644oqwwQYbhCmnnDLst99+8THFFFOE9ddfP1x11VWdaYOIiIiINMMVe9xxx4UTTzwxHHDAAW3PIe5OPfXUcMwxx4TtttuuiHaJiIiISL0tdm+88UZ0w1aDO7Y6sUJEREREWljYzTnnnOGee+4Z6/m77747/k5EREREuokr9qCDDoqu12eeeSasttpq8bm///3v4dJLLw2nn356PdooIiIiIvUQdnvuuWeYddZZwymnnBKuu+66+Nyiiy4arr322rD55ptP6NuJiIiISLOEHWyxxRbxISIiIiLdMMbu888/D2eccUYYOXLkWL8bMWJEh78TERERkRYTdmeeeWZ48MEHwzTTTDPW7/r27RsLFCPuRERERKTFhd2NN94Y9thjjw5/v/vuu4cbbrihqHaJiIiISL2E3euvvx4WXHDBDn/P73iNiIiIiLS4sJt44onD+++/3+Hv+d1EE3Xq6FkRERERKYDxVmLLLrtsuPnmmzv8/U033RRfIyIiIiItLuz22WefWLuOJIrRo0e3Pc//kzRx2mmnhb333rvTDRk6dGjo1atX2H///Tv9HiIiIiI9mfGuY7fllluGQw89NJ46cfjhh4f55puv7ezYL7/8MhxyyCFhq6226lQjnnjiiXDeeeeFpZZaqlN/LyIiIiITeFbscccdFx599NGw0047hX79+oXZZpst7LzzzuGRRx6JFrfOgCjcfvvtwwUXXBCmm266Tr2HiIiIiHTi5ImVVlopPooC9+2mm24aNthgg3DssceO87WjRo2Kj4QFkUVERES6eKRYUVxzzTXh6aefjq7Y8WHIkCFh8ODBdW+XiIiISHekafVJhg8fHn7961+HK6+8Mkw++eTj9TeDBg2Kx5elB+8hIiIiIk222D311FPh448/Dsstt1y7DFuOLSPzFpcrtfNyevfuHR8iIiIi0kLCbv311w/PP/98u+dIxFhkkUXCb37zm7FEnYiIiIi0qLDr06dPWGKJJdo9N9VUU4UZZphhrOdFREREpCBhx4kSFA8eH0iGEBEREZEWFXYDBgyof0tCCPfff39DPkdERESkxwq7o48+uv4tEREREZHuWe5ERERERJpgseOor/GNsfvss8+62iYRERERqZewGzZsWGfeW0RERERaTdgNHDiw/i0RERERkebVsfv222/Dd9991+65aaaZpmstEhEREZHGJE989dVXYZ999gkzzzxzLChM/F3+EBEREZFuIuwOPfTQcO+994Zzzjknntt64YUXhsGDB4d+/fqFyy+/vD6tFBEREZHiXbF//vOfo4BbZ5114tmua665ZlhggQXC3HPPHa688sqw/fbbT+hbioiIiEgzLHaUM5lvvvna4ulSeZM11lgjPPjgg0W0SUREREQaIewQdW+++Wb8/0UWWSRcd911bZa8aaedtjNtEBEREZFmCDvcr88++2z8/8MOOyycddZZYfLJJw8HHHBAOOSQQ4pok4iIiIg0IsYOAZfYYIMNwksvvRSeeuqpGGe31FJLdaYNIiIiItLsOnZA0gQPEREREekmrlhKnCy22GJh5MiRY/1uxIgRYfHFFw9/+9vfim6fiIiIiBQt7Dgvdrfddqt5skTfvn3D7rvvHk499dTxfTsRERERaZawI2HiRz/6UYe/32ijjWKsnYiIiIi0uLD76KOPwqSTTtrh7yeZZJLwySefFNUuEREREamXsJt99tnDCy+80OHvn3vuuTDbbLNN6OeLiIiISKOF3Y9//ONw5JFHhm+//Xas333zzTfh6KOPDptttllR7RIRERGRepU7OeKII8If//jHsNBCC4V99tknLLzwwvF56thRpHj06NHh8MMPn9DPFxEREZFGC7tZZpklPPzww2HPPfcMgwYNCpVKJT7fq1evsPHGG0dxx2tEREREpBsUKKYQ8V/+8pfw+eefh9deey2KuwUXXDBMN9109WuhiIiIiNTv5AmE3IorrtiZPxURERGRZidPiIiIiEhro7ATERERKQlNFXbnnHNOWGqppeIxZTxWXXXVcPvttzezSSIiIiLdlqYKuznmmCMMHTo0HkX25JNPhvXWWy9svvnm4Z///GczmyUiIiLSc5IniqJ///7tfj7uuOOiFe/RRx8Niy++eNPaJSIiItIdaaqwy6HA8fXXXx+++uqr6JKtxahRo+IjMXLkyAa2UERERKS1aXryxPPPPx+mnnrq0Lt377DHHnuEm266KSy22GI1XztkyJDQt2/ftsecc87Z8PaKiIiItCpNF3YcTfbMM8+Exx57LJ5qMXDgwPDiiy/WfC0nXowYMaLtMXz48Ia3V0RERKRVabordrLJJgsLLLBA/P/ll18+PPHEE+H0008P55133livxarHQ0RERERa0GJXzZgxY9rF0YmIiIhIN7DY4VrdZJNNwlxzzRW++OKLcNVVV4X7778/3Hnnnc1sloiIiEi3pKnC7uOPPw6/+MUvwgcffBCTIShWjKjbcMMNm9ksERERkW5JU4XdRRdd1MyPFxERESkVLRdjJyIiIiKdQ2EnIiIiUhIUdiIiIiIlQWEnIiIiUhIUdiIiIiIlQWEnIiIiUhIUdiIiIiIlQWEnIiIiUhIUdiIiIiIlQWEnIiIiUhIUdiIiIiIlQWEnIiIiUhIUdiIiIiIlQWEnIiIiUhIUdiIiIiIlQWEnIiIiUhIUdiIiIiIlQWEnIiIiUhIUdiIiIiIlQWEnIiIiUhIUdiIiIiIlQWEnIiIiUhIUdiIiIiIlQWEnIiIiUhIUdiIiIiIlQWEnIiIiUhKaKuyGDBkSVlxxxdCnT58w88wzhwEDBoSXX365mU0SERER6bY0Vdg98MADYe+99w6PPvpouOuuu8L3338fNtpoo/DVV181s1kiIiIi3ZJJmvnhd9xxR7ufL7300mi5e+qpp8Jaa63VtHaJiIiIdEeaKuyqGTFiRPx3+umnr/n7UaNGxUdi5MiRDWubiIiISKvTMsJuzJgxYf/99w+rr756WGKJJTqMyRs8eHDoqcxz2G0N+Zy3hm7akM/pzngvRESkFWmZrFhi7V544YVwzTXXdPiaQYMGRateegwfPryhbRQRERFpZVrCYrfPPvuEW2+9NTz44INhjjnm6PB1vXv3jg8RERERaTFhV6lUwr777htuuummcP/994d55523mc0RERER6dZM0mz361VXXRX+9Kc/xVp2H374YXy+b9++YYoppmhm00RERES6HU2NsTvnnHNirNw666wTZptttrbHtdde28xmiYiIiHRLmu6KFREREZGSZcWKiIiISNdQ2ImIiIiUBIWdiIiISElQ2ImIiIiUBIWdiIiISElQ2ImIiIiUBIWdiIiISElQ2ImIiIiUBIWdiIiISElQ2ImIiIiUBIWdiIiISElQ2ImIiIiUBIWdiIiISElQ2ImIiIiUBIWdiIiISElQ2ImIiIiUBIWdiIiISElQ2ImIiIiUBIWdiIiISElQ2ImIiIiUBIWdiIiISElQ2ImIiIiUBIWdiIiISElQ2ImIiIiUBIWdiIiISEloqrB78MEHQ//+/UO/fv1Cr169ws0339zM5oiIiIh0a5oq7L766quw9NJLh7POOquZzRAREREpBZM088M32WST+BARERGRrmOMnYiIiEhJaKrFbkIZNWpUfCRGjhzZ1PaIiIiItBLdymI3ZMiQ0Ldv37bHnHPO2ewmiYiIiLQM3UrYDRo0KIwYMaLtMXz48GY3SURERKRl6Fau2N69e8eHiIiIiLSYsPvyyy/Da6+91vbzm2++GZ555pkw/fTTh7nmmquZTRMRERHpdjRV2D355JNh3XXXbfv5wAMPjP8OHDgwXHrppU1smYiIiEj3o6nCbp111gmVSqWZTRAREREpDd0qeUJEREREOkZhJyIiIlISFHYiIiIiJUFhJyIiIlISFHYiIiIiJUFhJyIiIlISFHYiIiIiJUFhJyIiIlISFHYiIiIiJUFhJyIiIlISFHYiIiIiJUFhJyIiIlISFHYiIiIiJUFhJyIiIlISFHYiIiIiJUFhJyIiIlISFHYiIiIiJUFhJyIiIlISFHYiIiIiJUFhJyIiIlISFHYiIiIiJUFhJyIiIlISFHYiIiIiJUFhJyIiIlISFHYiIiIiJUFhJyIiIlISWkLYnXXWWWGeeeYJk08+eVh55ZXD448/3uwmiYiIiHQ7mi7srr322nDggQeGo48+Ojz99NNh6aWXDhtvvHH4+OOPm900ERERkW5F04XdqaeeGnbbbbew8847h8UWWyyce+65YcoppwwXX3xxs5smIiIi0q1oqrD77rvvwlNPPRU22GCD/9+giSaKPz/yyCPNbJqIiIhIt2OSZn74p59+GkaPHh1mmWWWds/z80svvTTW60eNGhUfiREjRsR/R44cGXoCY0Z93ZDP6SnXsyt4L0Raj1YYl63QBikf6X5XKpXWFnYTypAhQ8LgwYPHen7OOedsSnvKSt9hzW6BJLwXIq1HK4zLVmiDNJ4vvvgi9O3bt3WF3Ywzzhgmnnji8NFHH7V7np9nnXXWsV4/aNCgmGiRGDNmTPjss8/CDDPMEHr16hVaTV0jOIcPHx6mmWYa22AbbINtaJk2NPvzbYNtsA0TBpY6RF2/fv1+8LVNFXaTTTZZWH755cM999wTBgwY0CbW+HmfffYZ6/W9e/eOj5xpp502tDJ0jmZ3ENtgG2yDbWjFz7cNtsE2jD8/ZKlrGVcsFriBAweGFVZYIay00kph2LBh4auvvopZsiIiIiIy/jRd2G2zzTbhk08+CUcddVT48MMPwzLLLBPuuOOOsRIqRERERKTFhR3gdq3leu3O4DKm6HK169g22AbbYBua3YZmf75tsA22oX70qoxP7qyIiIiItDxNP3lCRERERIpBYSciIiJSEhR2IiIiIiVBYSciIlJCDKHvmSjsJoB777232U0IW221VTjiiCMcsE5aIiLjnB85kcl5suehsBtPXnjhhbDBBhu0O9KsGayyyiph6NCh4aSTTurRAzZNWj0ZrkFP7gOtiPdDWqFf7LHHHmHJJZeMJzn1dHFX6YHfXWE3niy88MLh0ksvDeedd144+OCDm9KG0aNHx88+88wz47m5p5xySvj+++8b2gYmimbzyCOPhGeffTb+/+677x7OOOOMhreho+vQyEmEzUYSt2effXa46667Qk+eNPO2NKNd+WaDouvSeMY1PzVy7kr975VXXgmjRo1q+CZ0xx13DN988000RrBuNEPcvfrqq23/f+6554ZPP/00NJox/ydsW22uqjvUsZPx5+qrr6707t278rvf/a6hn/vf//637f9fffXVyh577FGZaKKJKr///e8ro0ePbkgb8s+55ZZbKuedd17l4osvrvzrX/9qyOePGTOm8uGHH1ZmnXXWyg477FD5xS9+UZlyyikrzzzzTKWR5Nfh7bffrrzyyisd/r5ecM3ph8cdd1zlN7/5TWXqqaeO/aKR5N/zq6++in30u+++G+t3jeLf//535Ysvvqh8//33bf2lUeSf9atf/aqy+uqrV0aOHFlpNo28Bh3d82bMT5deemll0KBBlf3337/yxz/+sdKMa37zzTdX5plnnsppp53WNi7qzUMPPdT2/48//nj8/LXXXrtt/WhUf3jkkUcqyy23XLwPv/71ryu9evWqvPbaa5Vmcdppp1V++tOfxrny7rvvrpQdhd0ETBh33XVX5eijj46DhY56+OGHN7wthxxySGXxxRev7LjjjpVFF100irsTTjihoRP4oYceWunXr1+lf//+lSWXXLKy0korxQHcKP7xj39UZphhhsqkk05aufbaa9ueb+Q1SNdhoYUWigJro402qgwdOrRhbfnss88q5557bmXyySevTDPNNJXhw4fH55OoaeQietJJJ8VJc9VVV63st99+lZdffrnSaLj266yzTmWFFVaI/77++usN+dzq+8zGY+ONN6488MADlWbw7LPPxs0n4+KFF16o2cZ6kH/GhRdeGOfJM888s/Kf//yn4UKfOXKWWWaJom7LLbeszD///JWDDjqo0kj+9Kc/VaaYYorK2Wef3bANF3Mw69I111zTdHHHpobNN+tEnz59Kk899dRYBopGccIJJ1Rmmmmmyk477VRZccUVK8svv3xD16tmoLAbT2699dY4UFnEGKz77LNPZeKJJ64cfPDBDWvDn//852iZYTfEAGFxP/HEE6O4499GDJorrriiMvvss8cJAxAXCBsmsnrDhMR3fPLJJysLLrhgbMfAgQPjz4l6LiD59cVSyedff/31ldtuu63yy1/+MooKFpNGwQTORE6fwHJXq5315rDDDqvMOOOMlYsuuiiOC4T+YostFi1njYINFhP3H/7wh2ixmG+++eKm55NPPqnr52KtzTn99NNjH2DDM2LEiEqjueGGG2KfXHnllSvrr79+XFCxGjWSI444IvaHVVZZJfYD/v3444/rOjbz97399tujkHnsscfizwhcNj/MW42Ce8/1P/bYY+PP3377bbwGCF7mqs8//7xun816xPdtprhLn3HWWWfFTedSSy0V58tRo0Y1ROSPrnp/NuD33HNP/P/nn3++stdee1UWXnjhyiWXXNI0o0C9UdjVAMGUgxVku+22i4t34ssvv4wDFXH3P//zPw1pFwsXg4SJIofdMe0455xz6m6xYeJGTMF1110XBy6fm9xx9diddjQR/P3vf48T1rbbbtu2I6wH1dcbU/5RRx0VLRIJJmt2hssuu2w7K2I9rwOux+eeey4Kqr59+8Y2NZJ//vOflaWXXrryt7/9Lf6MwEVMnH/++e0my3pOmlgqsRjfcccdbZufaaedNl6TnKLbgAUIy2B6b/oI42DeeeeNm45Eoyyo9H+s2Gy00mKO6GdRqyd5n+S7Mjc8/fTTcXFnMV1jjTWiwKuHuCMMJVmq0/tecMEFbfeFTRf9Mc1PzNmpr9YTrLb0AdqCyMP9t+aaa8YN2Nxzz125/PLL6zou6JuTTTZZw8Vd9b3FekyYDCEzCHyEXr3HQ96Gu+++u/Lwww9XNtxww3Yu6hdffDGKu0UWWaS0ljuFXRXsLGabbbZ2cVPERzBBYVrOwSqxyy67xAm0EaZ+Fi0EXIppSwMUC94kk0wS24H4qwfpsw488MC4E2XAMFGlSZMBhdXmjDPOqHzzzTd1GahYH5jMTznllMp7770Xn7v//vvjYsrkkXbpTOyI7iLYfvvto7U2tYWFhOvMo1rQI2xXW221yu67714pmvw6MFmykKe4HQQe1wRxl8d+HnnkkfH61KMNwGQ555xzxgWCe5P3B67FZZdd1uaKqxcsHljr6J9/+ctfYhuSuGF8YkVLloIi+eijj9qu/6efftp2H/jOiIm0+am3BTUtziziAwYMiP//1ltvxfvC4pVI46VI8v6AyCdEYr311qu89NJLbW1j88XcSfhIsqAWISi414RB4F57//33257HCkOYSuoLqT8CsXaIrCQyi4ZrkPoacWV4Mqaffvp4X1KfxE3/85//vFJvOhJ3zJXco6L7ZPX8xIaT65E2vaydiLt0HYCNKGOmKPJ+dfDBB1emmmqqaMHmPpx66qntXssauu+++1amm266uCEtGwq7GhP2MsssEy0RufWJBYLJCRGVg2sWtw9ikJ1a0YMkX5TY/TExbLLJJu0SFmgnrmFcMUXtiDraWV911VVtwgaLXYJFlJ0R8S31gPfFxbbuuuvGeDYE7n333Rd/RzwTpnVcULgC2S0XtZgjZNMCnt7ziSeeiFYhJqq0iOUTKveoHmICWJgQMsQQ8T2TmEVAMXkxmW299daVDTbYIF6voibwr7/+uu3/00RILB33HDGPmMknbcYJorjeiS1YyhgPLKQs5MlamHbm9JXUT+oB8WyMhbSIcR8QF9yj3Xbbre7iLi1mXHvuBd8ZUUcCRx4bfMABB4zliSiyT7JA4k3gXyx2efsQd1iKcNEW6YbEYo4lDBGdhCuCIm1yc1cb/ZdxidelHpayN998M8ZuIWDSfEF4CnMkfTTNy3w+4RpF9YdxWUCZu2qJO0KK9t5770pR5NeTsAgsYayJ9AUSWPj+rF1cG+boXXfdNY5ZRG89xsUbb7wR12/c3mxs6fu4p/O5IfUVNsTNiPurNwq7GoOEyYdFG5GQAsFZqBAV7AZzccfgwQWHmb/oQcKCyY6UgPQUCI3VjvgN2kdmKu6OH/3oR/GR6Kq4qzZn33jjjXFyTt+R3RC7INqCBYvFhEmTLKh6mNqxQiJkUiwdO28mboRsPmExSI855pi2NnSlLdWZriycZAGn2KlHH300XgNEFJYK7hsBw7gFseIWRX4vcDcusMAClTvvvDNay7AE4H7761//Gn/P/WEhoS/svPPOhWWoskAhkIBFCcGYrC9rrbVWvBd5jB+LKBP35ptvXpd4muOPP77N3Y1lkO/KxJ1bqGjDj3/84/ioZ0wP1jH6Phs7xkEu7sjerof1NkEfxHpO37v33nujsEBQ5iEjwPxBuEJRWbr5HEVfpE9i1eY7kw2Mu/Hdd99t93rE9Z577lnIIprfT+ZIPhOL/TvvvNO2+WRsIipY2PlsRC/Cs14Z0/RD7gUJRNzz6o0d14MwFjaEaRPQVarnacZp8i4kEDXV4o5+Wg8xwzqIeE/ubjZbbMDTvJ3c0ltssUVMaqlHBj3z0I477thOuCL68a7kYSLVlE3cKewyUgdDRN10001xwWJHmNK0ETiYsXEB/OQnP6lsttlm0f1V1EDNJxs6KBYIdv0zzzxzzOYhZgSYxIn5Y2fK7ojJJA2Srk5Y+d8zKfDZLBZYxAgMZ0FngaDcChMGpm4snOzIUxuKHiSIteTq5hpwXRBZaRFNYitve1fagJgmAD6P28MCxn1HZKYFErGLoGBRR0AgtLhGaVIvcvHAtYzVOM+8BYQlO1+sMrUoQmizs2VBYhdOTCU/J7j2SyyxROwD9FnKCjBGsG7XY+LGQsq1ZmziboMPPvggjlPGCNab3/72t1FwsjErsg0dvQeCgjYxTnJxl7IUWfCKhrYgZOlvCax0fB7uYLwHXBcWUhbbouao6s0OSVtDhgxp6+94D7gXxHPl4i6nK2Mzjam8XzMukrhLblmuPeOSrEwEL3N1kfNTrbHNZgIPDv2QeTt9HsKSrHEEMJvAIsg/HwGb5mHmI4R97m3C+EBZKMKMcoqcp3mvrbbaKsYVAptuLHYp1jWF53BNmB9r3ceuwnsRijLRRBNF938O4g5rIvMYc1TZUdhVgTWIxQvXH4s7bg0WqVQ+gd0HnRdhxw6ULJuiYXHAjZV2PpiymZgwY2OpSIMCqxKLSlpwujpI8skC8UgiANZJJmisQmnCTnERWMkQFPxbVBtqLZ64mVmw2Y2y68oD4wnIZfEqqk4UMXJYWlgwWSiwiiR+9rOfxb7AwpnEHd+dNiH6sKCm9hfpiuX+M2mzaNeyACHuEOBcn3yyLlJYbrPNNvHzcwGfvisuPixCXDusyYyLIqymtTJwGQMIaEQUG5u02WHiRtAhKllEWcyKbEPeL3HF88iFP5ZrrJS5uOO64LaulzWA74yoP/nkk9ueY3FlE8Ycxv3Aupq7RouCPsCGkj6BhTrva2yEEdaUGanOHC5ybsivK5Y72pO7ZfmXjQBW1XoICeZGEteqLXfcDzYVzFu0EUs68zYuwqJho4eATfMUIpd7wpyQizvEHmO3KKrnFrxcrJWsG6xbeXwj8xfraV69oNZ7FLFWsKEaNmxYvAb8m4Po556wSS9bFmw1CrsMgmrZVSW3EoMSVywChwU9L7DI7+rRObDMYAHBrZnX4mLgIO5wwZK6Xy1kirSKsFhizsZylcMkyeTJpFFLuHS1Dfnfs7NNQc5YTxFa7EZJnsitRZtuumlhmX9M0sRmJLcnQpYJMXe940KoFndMqlgvEeNYSYq0mub3n+/KzjzFreWvQ1AhLOq54WFxwgKCdSqJ+3yh5P7lsXhFLqJYSrE6cC9YKBFPWKhw9SSXfK3+V7R1BncagoX4RsRTHqPDBohrw8Ygt2oW1Y5a74cVgnkht47RH3FHPvjgg4UlTdTqk8TVMh7YVKTyRwnmLiy8/L5ouOa485iH8qB4NnlJ3KVs2XrNkfRtwhKYC/AoVP+OeDI2fHlIRNFwb9l8prAEPEpYyegT9E2uTx4DXNT3z9+HOTr9zGYKSxnzdG4d5DWEMVVnqhfVBvp+dazz8ccfH8Udgj8Hj1MjsvWbjcKuStFjkSJuJL/xJCqwK2LxTLvxesHukjgtFjEm5+rdCHFLKc6qHoOESYiFgiB8rCPV4HohVqXobMe8DSyeWKhwtXEPWEDIJMP6QIwEbibEDUImj+vr6kBlYuJzAfcZ94FrgMjNLXcsVohvxEa6DggOdqlYeTtyQXXmVAuCspN7CWsALieERa3is/WYuKtBcBPviIDJA+Grs7GLnjRZPLHGVSc6IaYpVJ3KndRzsqYNfHeSdbgXxK6xeNBfc3FHv0GEFw0uPTY2+aYKSzqLOfGu9SLvD/RHNripjzNfcF+w1lS7GREeRcfUDR48OIoWRD2ihnuPyEsbDa4P1kI8KilbuV7Q/4g35n5jLc5BxDBH0I48a7dI2EQh5hiHqZwJFrs0T9M3iS3MRW6Rm29iCrHOY70G4vgobYNFLM8UZ55G8BW1uaneaCGucbGyLvG9//1/fQFxh1sWwT+u9ygjCrsq2InnQdgpPoAdBwMF90ZRO7COXAtMmliomKCqY6dw72Chqod7B8sHVjA+A/cKlgdiRvI6biwgXKMiXSw57Db5XERdngpPu3CFMnFgHWMypaxJEXEzaZDjQsDKwITMRMGEifWSe1Et7tgNE7tEQdT02VhIWPg7ayXJJxtKldDXsIYgEpJVACsh/QJxXytuqsiJmzgl2oH7N7ceU2KEjQ4TOBsMkjW4H/VIUiAeBhFLTCVux+qSGSkWFrdsPcUdmzvuQwpOp7wLfQTrEFZDrlMSXLkVowj4PlgpWcT4rlxvhETa0DAf4FWoR0Hm6j6JxwB3M4t1OnmH+REBQdJErSzoouYqXHnE/eZZzukUGgR+gpg/YoCLvgeAO5WxkBI1EHdsCNkA5m5Z4t7w/NQrEzmR5j8+iw15ijdG4HFNSOypx7ikzzE3YXzAS5HAgsrmmLIqrJnMnWy+6xF/jRuae0/CGHMz8xT9c//9948bbu5ZErh5ol1PoMcKuzRQMeGy40iTBTs+JknM/Tlk2RA/gEWtCPLBxuBgUmCwIA6AXRZBvwyOjgLji0yZT/XZUsFGJiQSNFiwmdBZNIjpYzGnTfVaPIkPSuU0GJzcH3a/KZ4J0Yu4RNQUFdeXw0SYFs/ElVdeWVPcsbCle5D+LaKGH1YJRAzWGGI4sVbSphTPyeRNvAwWwnrE7QBxi7hdsU5yz5nEsQ5gqQJCFLCgskvONztF9guC8/lcrKGISSZtMu1y4czYZUKnJhXCoqjrUb0YItZoDwKLMYpLPBWoxt3G/aFt+d/VY0FlQ4W4YfHESoarCfGLZaijeaIICEpnESX7kjGJq5HvnIQc/YLMaTZd1RnlRYCgZsPHI8UMpnHP/cD9l59+k/phkfeA/s/GjU0VG5s0TzE3MncTxsHGkzhHPC71uA7VpO/JBoMNHxu/FJOdl6Mq8joQlsHcwJhMpPUBmJuJM2R+xCWb5sauzNN5eS/eL82B1XF0iL0ll1wy3ivA20PoUqMKhbcKPVLY5bt9zNdYaVJtH9wsuFgYpEzY1Kli98eklnZpRYIpnwWJyYCYtrz+EmILQcHCWp3GXg9oCybzZLpH3DGBc23mmGOO6PIgMD2Jl6IXLoQLwo4SBTww8zNIWUTzwZpTZBuwEDIhsogxQeeFRBF3ZLtxj5L4ThSZsMAEyf1OrjUsgsTqpGyzZD1lYiuqfEQ1WMe432kB5V7QL7FQsglJZW9oCxNuPQQ2Ahp3Wx6OwKSNiMQFh6BjAcGKxj2h/AuLbrLadYW8TxGAzmYit1oTgM24SOMAEYw7koW16A0PwomFicU0WWixDLKAYyliA4LA4/5Ux8QWBW41RFs6nqyjPolrEHFbjz5JQXTuO5bZtPnkWvNAdFcfEZV+3xXS+wN9gDGBuGdsslbg5kunSLAJZY7G08F6kUIlGgX9n2vDRotELrwO9RIzzIXEH3O/Gf+4ZFlH+VwSm/I420RX+gTzMesgVQgS9DmspKkge/5d11133RiyVE1PEnc9UtgBLiRcKSxiTJS4/lLWIdY7YrnYFbPAY8ErKk09h4mSnU8KPGYHSBvycw0Rk0zcWCSKonrCS4OOa4DIZRJNMGGxYCCsiDtLlpnqY7aKgHZwzSnhQuwMCyiTKDEqfH6RwbfjagPXh1M0aAfZnglEBiI8P92haBCXWMJY0FkoqrPLsNBUB6oXuZAi2rjP6eQONj/ENBFDRz9A3BGsXX0WapECG3GGux+hVr2hwaKO249xwmvYgHG/EB8sLOlMyCLGBoKNPsB3xjqQLHQsHMn1x3hgEcmr1xcl7ggD4LOJISKukg1WEhIJFlbuDdehqGLQ1feSDR7XGldodZ9k7qRPVhdu70qf7KgvYbVns4XAyl1rCAmuTyqB1FWqQ22whJIslSdpIRKojYYbvjq+tNECIl0v5gVcwGyAUhvqIbIxdrDZxprP2oQnA9cvwpq5K/dqFDUOcP3zSJUi+M5swnNvQboO//M//xONEGWPoxsXPVLYsShhDcDlBbhvmBjoqCxiTB7JpcPOuF4HmrNQpGPKatVnS+nqJAvUY4CyGFXvLNmZs3BVT+yUu2AQIXjrcapC7tJMBZFz+OxaQbD1AoGDG4GFHZd0AvdoPavGc61xB1MHi6D4/Egk3J+43HKXU1epNfmxQGChwLXCxia5O5iw06kjqShyvcAaRY1IrDTVpxXQ/9h8kHmariF1DmlrHu/TlfvB4oXbj80XFiLKNWARof8jPLkGJMpgIWHTUXThW9xcuOOxijEHkbRAjB1toG3VFBX3m3slWKyx2qaC03gwqvskfYTrgEWxCPLrx3WnDfmJJlhqERL0jSRiGBOI+iIEFeINi1uC9+TzuN/pDNr8d4gI3MBsBOvF+PSpWnNJPQUm94RYNowQKTSCPppOfKiHIYb1mX6YDA+EJRCqgbeLOSKd8LH66qu3u4c9kR4p7FgYiD8guwsLCRa5VK09HZnF4poHjNcDJi1cSVhAquuzMWA4eiVPIChS3BEviFjCCoDATZYRXNGUDEhnjKYFA8HBBMfiWV3osiiqvx/iKtUHw5LX6J0wn88uFIsJ/WFcbZ1Q8omYiTHfPKRaVIj+9Do2I2SiFnnOY/XRdSl+LkGfIM4zbTBw9xA3Q3B6ve5FHqOImEI04eqpVYQa6KdM4giOoqzqWOwZe3kpDcQV1kJip8j+YyOG1S6vl1fk+OTaMy9VW0YRM4ia6ljCIgQlool+h9UTlyrhJ6nEE2Oe37HBS9+XzSd9ko1g0RtPBBPfExccVss85jVZ7tgI89ncj6KC85n/kuUzjQ82C1wP4geTRTivi8fvaGP1veosnbV+F2U1H1dfyj8jXWueY3ywlmHZrkd2PmOSzS59kuoUSdylEIxUqJ843MUWW6xHuV1r0SOFXb6AYEanQ6S4MnbD7MxwuRWV+dlRRydWi8mbHV9eZBRBwSAhO7coCwATUvo+CDlcCwgKhAuTIxZLsk6ZJDGn50dEpQGMu4sFj51ZI8CiSUYVsUv1OtXih+Be0A5csvUIhicxBTcXE1KejZ2sM8Q04lYo+iSF/O9JFGKBJlGGDU4aC/QRhAyTJ5scXB95geQiJ0+uMZZRJu10TBZgFUBc0h9riTvEHK8pqgwRizhjgY0W7chhk0UMUQqLyC3XRS8kuMBx86V7kfo9FnbcX111Oefk5TiIs0Uw8f1TLb50vXHR06Z06g59EotlEWMz749YCLHCYC1EPCK25pprrnYWM0QofRULUYr94x4UNV9iIcJanOLFiH3lZ8ZDirFNn8X3TjU3u0p+HQiHQDQiprHSj6uP5d8b0dPZ/jihSSdcH8qKpCMl63HaDMlCjEn6JptdElfwLCVxRx9hfqjedH7fg8VdjxV2CeKlCDRNaelUtydmpB4lTXBXIKQQkykAnbIFuHz4l4mMRZRBwoRVlHuHxYFgV0zUCDN23rkLFlcvCyQTJ+KO37NbzivW57uzRsE1IqaoiKyqrm4C6pFlh4hmkUZAMWlxz/NabfQTJjUWMMRXPSYsLED0P6xTuFfTwp0siFhLeY6NDlbTehRbTRm4iFkWM/ofoRIJhBuik9fVOpO56NAA3KAsJCxU1ac2cC9y61G9YNPFhhNrZF4XkfIaJAqk49S6CkKaPpYLbK4/m81aiSgITtyV3B8sy0X0yXxMsYHAlYewS6KWsUcMH30wDxN57LHHYjYoG55UpLcoEM5cB+53EndsbPFapM1Oals9wFpNLCEbKfo9bUG01Mq6z9uA14fXVhfIHh/4LLwT6X6M71zHmsa6WY/5ibAQ4vkQ9wms5fQDYm2rYzvLevbrhNLjhR0TNwdGI3qY5Iixy9O4u0I+4IgBYhfM4sjnMWmnzEcmSjJ8GJBYbhB2RVuoKFPATofPTotC9YLIgMTNwe4H10IKFi/SOjQ+z0MrBr4WfQQOwi7FVBIfgvsNl0K+eFULqSInLLKQcVvQN5K7g0Wr+qBsLCJYMOohsInbo3xECormXxJnqmOWsJZUH11VT5gDENp8bnLx4m4ifAGXUNFgfcDdmWcBU8aEeQJxQSwbAg8XJZuBrhTBzuF9UyIU8wF9lJJOuJgRdwi5HxqrRfVJ5kEEPuKC+ML8yDbuO0IOwc3vE9wbYq+YN9mMFNk/CFehUDviMRd3qbxNR6Kiq7DBwkKZkqSIN+bzqpM0IP++xL0RkpCO2ZtQEKt4a3LX+oTO0UULKvoA36k65ppxQv/Eclek9bos9HhhlyZVTLyksNcjTZ2AZAQd7gMmCMz2WEJYJFIsG8+loPUiy0ekwccumIWKmBUGboofTAOxepAeddRRcXKplbremc9PAgGrZV5vq6OJOH+eGK9alpruRP59CIin8DP3geDvBAsr4i5Vby+a6kmaSRMhme5Nnu2Ie6NWkH7REzdWIRZlINORNqRgeQKi80k7tb9R4o5NH/cCiyauR9zihE6kDVFR7WCDh5ilnA4LOBbTJNyI66MEEc/j9sSKkwueovoDblZcq3n4CfMhMbicgZxbkjpjDfqhzydhipAESmlgASIZAlGb1yzkeuMGRcjlGx5EeFdOd0j3kXhCxFoea8qmp1rcMVdjSc1rq3WF6jGFaKG/AZbIfFwyJlK9uPzvGDMYJTpTiDdZHyGdYEGs3PiIu7wNeTx4Z6g1nliPsVAnUZu/hrGIEMXbIe1R2P0fdN56LBjEH5A1xkkFTAzpM3CpIOw6Ot+zaJcnu1kWaxbSVHOrOjkknX2aJkvEaFEJJLgTsFgyYTMBIRwT1dc9/5mFjQWv1tmP3YX8XhIHwkSNa5FFmmuci1YWLCyqWCyop1gPiOvDUogLns9PZ0vm2YdM8AiKokTEuDZVuNJwBdOGPOMSywV9lWzgRCNDAZJVkyr6hDLkbSvCJZ3qpGEV5H4wP7CQkenHwppEFmOXa4HVoqizX6vhPmPNZ57KEzMoOUSsJ642+gPlkIoOiWADQTwjFsoEbcCSiyelo+9cZFgAwhIvBRZDXL5Y01M2dhJ3uVu2qH6Yl41KJ4ekgugk0DEm8qQ6rhVxnvlxaVQLYL7ojKgj85hNA993QsVdPk8TQkHIRL6GTAj5+7NO5QaFVGYJUZ+vn/RV2t/oOaE7oLCrI3Q44lBwb7EbTZ0+TUi4nci0YjJvpOuRQFzczliM0iTO4pLXzyP2inZ3Nig4P2iZ3TTxe2SbsSvG5cT3xj1d6/UJhAaxfrUsR90RAvOJYcR9xGKNqKFfIPDzCT6V86hH9iuTPwsXfY+FC0sEQjMXkalyPQtIPSZNCtyykNDvaQOWMCxD9LkEsURsiAgcb/bEzf0iVAIXbMoQLgKENQsU7tU8/AMLP+KOMdOI0wtSP0PE0he477m4Iw6Z+YIEoqJDRHg/viviovooR5K0GB9sQutRHB7oW4xLNo8IJKxweG8Q8wiqFHudYu6q29gVEOupJiYWQEQsY497ztyMFZe4ugRiB2suQifNkymTOT9lYkLB4oVbc0LEXT5PsymhrSmJpStwdGI6cYkNaILvjXilrSQa8ns2WxMaD9hTUNgVSK3OhZgjXoiOny9cgBuWmJF6l1WpNRgRdwSfkirOThzrUb4TxzqRDnfuynVgZ8nCyG43WaaYzBGRWAhyM3ot10Kt0ya6I3wfztjEvZQWTe4HlhIWLyb1WkkARbo+WZxYQHADJxCQ3H/EJRMpljOsZCQU1SPDDcsP1g++M2MCkY/rDQsmSQmMFXbhxM7k9eGaPXHjlqWNlNkowgWHwMZ6zeKZn6aQwELNmCSBI7dY1ovUz3CzJnGXz0t5LcGiLHbpniJYsFAxFyIo8nuNuMPSX3RdsjyjFTFF9mleroTPw82HuEvfnfm6KPcr3xGRiMUc4Ypoyd8bTwWxhCRrkDiAO5zxgTs+T6rjUevM6AmFTTab7fERd9Wb767M0/m9RlhTzoSwAK4/gj8/A5gNEB4uxgSVAuoxP5UFhV1B5J2LAUpMWzrFIHVasgsxVxPTgLWCTkp8USM7Zj4oaSOHJOMmrUdGEwMxFXAllit3pyZxh1WQTN2crsSLtCq41bD6IGarT45IsW6InSKvf24Fpb/h2kJU5TthoD8iuFjIKHtCxmPR/YE2sEgjIhGTxOPQ9xA1jA3iDukHnAaDpYoJvVklbjqC+8Yi15V4LqA0C6KOTHiyvhE0LO754fapz/C6os6nnhBxx/gjlq1aVHbFszCueY5NH/2fRZvxkH8OFrV69AFiG7EE8ZlsuKq9E4gL4rvISMc9WAQISJJAEmzosLhRQqf62rLJIpGODRDtQ2ynMVGPCgEdiTusl7XqZyaPShHzNH0fd24qvo7YJwkEUZ8XiMfTQV/J6wjK2CjsCgaRRPYpHZ4J++ijj26LEWH3h8uJgUyJAY4iSi64Zom7nK4OknzgY4kh+YJJESGBgMOVlcdOMEmRgclCntrEpIJboDtb6jq6l/QDgvFZSKprJBK0jduxHu7XdF+ZNLHE8fn5sXGJ6kSZIidNhBwuJgRk/h1ZvBB3xFcxaeP6yn/fahN3rXITEwLuTsq65CVGUsV+rJTV4q7RojZ3yzJPVXsZiuiPzIMkZuDuxxqVYsuSuMMVh5W/o6MPiwBxhWDivGXcemReImxwjefgliVIv/r0k86ASCJmMfVp5j/EI5sYNn24IasFJNftpZdeitbEosTMuNYasqFribt0lnoCyzqW3SJEHQYG5gDWiLyMD2sj789amk5oavXKCa2Cwq6L5IOEHQbuE8zm7MpJ38cihwUkTRi4nejAefJAV+twdbZsSD0CgFOwMZNUfq4lA5bJgYksFxDVkzWWpXofV1VP8mtKqQiyXqmLmBZsxB0B6LieOiqAXeSpFsSjsGClhYk4GBZOJsr86J/qzyxy0sRySwwTEzQWXBaqHERdCtDPT+Ao28RNtiXhDyyI1SeZ4Pbk2mAxpbRMva7B+Lxf6gu0qWhhzT0m/AM3JG5t3G300RRDh7jDes08Wi8XNB4VktrykAT6KGMS0Z2EZqIrx9R1dP3J8sxLeCD4GJfV4q66rE2RpaeYp9nsVZ/HzKajWtyxnuXuWARgUUcbcr2ZI3HD5uIxrY1UUmCTUc8zusuGwq4gSFHHOkV8QA6xElhJkshh4iJ+DbdsfrpDEQOVAFpqz5FhRpLC+FYqTzvCzkBAdZoYaAvu1nSeaPW1QNwhahm81cdX0Z4yxUpQFoJ6YyQAEA+CRQBRnyZr4mfYpVcfDVV0G8jyQzjlwedsQFjEiN+px7mOOSS+YMFmHBCGwP0nrrLavchYIM6vbGKu1ljDUo97q7ouGUKKPkMySfX46Cwdjakfus55xinvUcTYJI6QxJ1U9BlLEPMEfZQ5K4kY4pKLtF7n35dxQDgA4pL5OgfrJNZsvCzVlruuks/FbOjo63gqchGPO5Y4TsQl8wLuT+aPosjvOd+Vwr/E+OEhIQY6TwxCuDFWq4+PTP2is+O0o36EG5w5AtcrXq9qwwHxja1mvW9lFHYFwETE5MQkVR0vBsRGkMGT70LIJOL1+a6xq4s4CygTIjFtiEncnLUGYHU5ESwFnT0+DTdrck8lyyNJF1hncC1VCxcyIov83q1CvgghnJg0UwFTYkewSHHCRALLHQHT6Yziornttttif8hdrvl9x8WBsOToumoLWlEwGWOZyb838XRYY5i8q8VdrczoMkACUXIzJwFHfC2ZprlVJLlli0qmqrYeM+aGDRvWJubHp4YkLtkiPh+Io8Qyk9rDHIG4pdwOsadYt6u/e2fFXa1aoCnJgI0OLl8EXnXtNeYzRDcbjXpsNOn3xLQyDxLfR73KXNylE2gYI1i5iz5VBbjOzA0UB8/PpqZ8SC7umJuIKS2K/HpiDEiJU+k7YrljPWJexLJbC8Xd+KGw6wS1Bjw7QXZhTArVWUpMqOzO8vgcOjMdu4gzLrEWIiTS4dW42xioeWHRRHVGE8HqnSknwgSVLFBpwUasJssfgoLJmviR6lIFCJ6yDNBctKTvxKKQAn6JFWQXmk6YYBOQFksmsnrFUGEVJiCfvtpREWrazuRdjwUsnbmK2xExkYNVmYUL91f1Ql42UUeAPgHyWIJIXklWOizqZDki7rpSqmJ8N31kN+L+TUcGdnQkWX796UPUD6OtXT1KEWsc8wCJJ2wiES/EVwLPIfJI7EmejSL6Ae1GrADXmLkuZZ4iMBFObMSrkyZwhxZlSc+/BzVEietLmy0KtbOxqhZ3WDIJR6nHSS9sKCltlY5gY37Cm5BqWXK98o1eUXNDfh1YO1gnMShwD7AaJoGd3LJUECD+UTqHwm4CyTs6A5OdZ4o1wA2JtYxgW4Jz2aGzU2dix71SL8guTGnhiLy8qCUunWQZqZWm3pngV+K1EKoIB6xRgHuJhZyFK9XrI4YEcUc8V606VN1d3DEpEhfCwpmDi4c4FfpGXjU+LTDEV+bB2PUQd2wm2JWnmLXcgoE1r1aQdtFQm42sTuLKqk8roH8SjpBfm7LBdSaulP7A9yeOClGVjk8jmYQEAtziiJ96wAJOP0iZmGSi04Z8Q5KoVUOyM/NDtcsPbwaWmGSZYWNHElEqp5SuDYK/yLHABjsVA+c7V5eUQViyGWdz09l6neN7HUg24PO4DjlJ3DFG8hN56jU3EN/MvMX8k8qZYLFL6wjXibbkFQyKnBu4BvTHVBmA8c9nEleZkgyxcFO/j41P2TZ6jUJhNwHknQxTMVYyRBwxChR6ZTAgYNiNsvtkl45rlIm76GOI8kFPcVl2N5QJYCLLK5UzcBiweYJDV0RdXvmbg7ox1aezCSmcyQBl0cjFHbEaBIUXHbfSbPg+uDVwe+f1+Kgcz30gADkXLogsrCZ5RmS9oGYdpRqYSHN3EzGeCPL8lIl6ghWZMUJGdPVxfSwwrVLKpB4Qw5iySrFS4f5L58ymccQ1YRx1NhSiI9L7kySQPpPrTb9MZwFjXcf1W714F1VuiGB3LH4s4vmJBCQSEePGPIG4Q9wSq5sosk8ksYJVqFbdM8YH4wFLZn6aQ5FwjxGQtIMSN5C7WBF0uGUZJ/WOeYV0HfAscO2TlwWBh4GAOaooMVd9ogSb/LReYM2mnw0ePDiulcQdU7Q7vbasoRmNQGHXCUgKyHfBmI4ZtFjlEHY8sGjRafMYp64egdPRYMMCgLuPNiAq8t0ZsTzUTkowWXelnEg+6fLdEHZkcyWrJYtZtbhjIud6lCk5Ik02uA7YXWKByE/SICOa+4GFhGBxrFfEHDJ55wVG6wkLOu4OXB+IfkQ2u2DuVyOtpXx/Jm7aU6uYatnEHZZarE9s6HCpIeixWpEdn9e1TO6+oo7GyvtTuqa4FXE3pnN4840GfZO+kYsuNoW45roq6thM4GJMp9ngiqW0CdYx5h5KjJARS0kk3HFFHg+Wg4hAOLAJR7CkjNe8zyH+cIl3tT5hLbDQ77LLLjE8hjhrvBrJip6LO0QOm8NGzJGpn2CMQNRy/9NpM3lYQFfbkvdHPEl8Bi5nDCDMR1gLkxEixfnR9/KsZEVd51DYTSCYixkQKeg5xSgQdIvrAnFH3BDijrIWBKgXcb5j9akRDAhitdIkwecnlwc7TwYOoo6dar6Is5jkB6t3FrKmcL/i5kBUUtw2iUXEHd8dt2wjXH7NIt0T3DhYRhB3uTWOhZxYsuQOYjFrRNHd/BpjMUrWAvoCArsZhX8RdyzgWKfqmQncbLC4EPyNa5UFHYs9fYAkknTdCY/AQoO7vB5nVONypD8C8bNYCvEg5G5ArDTMD7mlGcsRVuZkUekKhKEwHxG7haDjOjAG2FRwPYjPxZKHW7bIWLJ0LbnGuVjE3TvrrLNGcZdbsFOCU1EFiKvvJRm2rAHEUvNZzItcg3QKT63kiEbNkSRxkNTF5o+QCTwPRRYkzw0hWGhziz0bG1zQaVNBP0X0M3+WbaPXDBR2EwgJEEzaxCjgRshjFIilYQFlAWfXkWLuGDTV9Yg6Cy5gFg4+F6shEwfCAhM2afKICHbCDFZ2zHml8qImDKxxiFnEIyIS4UpcBhaKdF4g4pfXkP1Vpp1X9TXMXdNY7pi4Eb25KxLLJhN7rUy9rrQhHSlUi3xyRPzTVwkmL6oNnQEL984771wqcZ9DRiHxk1hrU1wVCRMImrx2I2Kb5+txlCD3FfGMgE9gscNKj5hicaVPInCwoubWY8ZzfipCVyH+ljkAzwXXJMWQ4XalH+QUsZinsUBsI5/BfISgTuWY2AhjucNyjqhEdDJXFlWnLh+LuXikHYSiAHMBVns2OamkTTPGYhqDXAf6IyElqR1FCis2OiRrkDhSvY5x7QGRi5GA9SuhuOsaCrtOkMQSCzm7jrTbwyWLtQp3VxokJC6wY0uxLF1ZxBFQiDUGIx0fNwvxfAiJFPxLrA6FJ5nE6rWIs3iREJJbGxCuLGBkOyVxR/vKNEDziRuLKbGNLFCp+DBWkFriLqeroiaPlUy7/vFpb04z70lqU9nEHfeeBZxsPur1peuMe54xSk0yrBGILsQOJysUTbqmWET5jNztitBhs0fCCkXTc+txPYUF8xFJInkbcXsiquoB3gxELHXx+P5YCieaaKK2bFjaQq1ANtuIvHrEtBG7hpDDvQp8Np+XDABYMBF21PTr6kkmHTE+G+laY7DIvoAVjs0Dsb7p+qe5h+LTPE8/xdPBo7sn07USCrsuDBoWdWohMakzQIlRyOtSdfW8zXzgYZFDPJGgkBcvZafFwsECUks8FrmApu+NeGERS1aItEAgKHH5MGBzd28ZxF1+HbE+MCGxy8QygjsDVzgCnwf3BEttrZqGXQFLRCqbgpsXl874XNtWs5a2WnuKdDfj9sTljfUrjX1co4xbNnyIu6IOku+oRiXuPbJMKbmTauclUcMmhHIWjbbcYjUmFpg5krFRj8/Fi8LGlzp1wGYXd3D1aQbM1VjOijxRIsF4pGQInhu8J5T0oV/wL/cDqy7XnnIzuOrrcYRgI/5ufKCf4e5HaFfXLeVz8SBw6gjxqPWwFvZkFHZdgJgJ6hIRm8CEXq8Ji0mBHR/WAD4nT0VPMQwILWIUGpF5ijsHMZMyvHLhQewQ7S2bRSaB1ZQkgJSuD0xMCL100gYiHIsEGWZFihiswezycSWRbVidZVqL/PNxsxUVEiC1IUkGyxiinv9vBFiCsI4TFpHuN5YrstHvvffeDv+uUWOUNiEoEXW4gOsV44mQw8WNqGacYpFLGcFAQkhRonpccM1xP2LVZ+O3++67x6xbwmeILYN8nSjyCEHc3yTLYamkD4zv6UMI3SLXrtQmLLZ4tYjz/aF6qYq64lDYdREmERZxFvWuWuhqDTjEErEIZBXh+kPg1QpAJz4Bq0CjrCHE6yBqCb5G5LD7wv2QVwwv20AlGYTFEosku9H8WrPzpGZZipsqMl0//3vic7AG5GcNj8/fIT5JcBkfMSjFZAEj7up9vRFzWItJYMJahRs4WfRZ4BEWudWuWRBCwHUp0lKY+jdubZLVsFRyBBcnXCCiEHVpDmIzjIUMsVOPOZKyKemIMr4j3hw+DxFLTDJ9IR21WF3TsSiop0liCkKSbGc+C+9KLXdvdVhJPdqV7jVrA5Y7whFyj1bZ1odWQmFXMEXueihdgvUrr0tHDSpS1DlAu9r12uj4JXbAiE4mEx6Ijq6eJdjKsBNngkLAJWtMckezwGIhqC4j09XrkN9LJmh24riAEZe4ZVNWWf666kzLdMJIqjYv9QcRQ8wp47RIK1FHYxsLVaoHRlIVMWZssrCWpELArUIR81Pq35SWwd3Kxpb3xe2KSOF85vxzuBbEcdUqlN5VmPO43sQvcr9JEkG0cC8opZJegxsea3s9BA1ldSgdkzwJlDbiOlSfRwzVcwPehiIyoX9I3LHxJ8mu+vxZKR6FXYuCRWjVVVeNMWvVRzIlcYerLz/brxmCigWFyQRXSz2OwGmlxYfnKBFAMgwu0bxaPS5OxG2tY9yKaAOiLA+4xyKAWz4Xd5CKjRZdbFYmHMYFdR6Lqo+W9wc2EHgJcO2leD7GH+Mfa+6WW24ZT0VhcceiV0bIdmWThYUuD08hI5+wFUq+EO9KPCoWzXTkYr3AOougRNAzPqnhh3cl3Z98fu6quKv+ezw6uLrTXJHXLCT2MCWw5H/XqLkhF3dcGzxPUl8Udi0MkzfijgW82jpHLAXZl5Q7aSXKYF7PxTEZvsSGpGQQfkdsJRMUFjpKWmBZxTJCEktR3z9vA8kaFDYlADkP+GYBoxg09cnoH2Q6siNOMLEr6ppLPbIeSZTCKkcfpM9hKcrPbQaEDmWZCOSvV/HfZl9XvhseDcD9TKYlYwR3K1ZtklXwIhCbms5nrjeUueK6E/NMTUDENfGPRW6+88z4VMyXOYjPREzmR0oC89eAAQPanazBhoCyWUXMDROSgcsGOK/0IPVBYdfirgmEBXEyPNKZrwmsQ2UQUq0K9Z2wmJIcQ8kEXF0JxB0Z0VhEOCaHUjcptqnIe0KMDIkSjz76aM3f77HHHjFgnPi5/Og6XDO4yevlYpHmwHyQjunCMs5iTRITyUz5Il29aJZN3BECQX/fd999Y804soDxYuCWxZpOvBuZuIzJWkWAGwGx11gU85qCXYVxzVFtaexTdgqhh0WOjR1xz8wZ+XUioS2Pv8Y1z7yVnzLRCFd67skpa3Jdq6CwazJ5B2fXRTICEzXp8AkmbAJPmSBqnSmpuCuGPNkB9xnXm0kQd/Pll18eF8+8Uj/lG7AKYDVL2ch5IdoJhTid5FqnDSxYWODS4eVY5UimwVKB1SZNlMT+0V/yfkBmbkdiULovJMFwNFW1eKM/EApQfcpNma0iJCUgnLBQ4QLlZ8DVh8hpVkhIdSZ6GpdFxNtScJlyOohYLG55/CaWe85bxUJJrTw2/sxPZGnnhah51Drab3zb0NUMXDbFZQjXaWUUdi0C7jYmZo4kY+GmiGZa0JNblkU+PyhZiiOfsBBpuG4Ids6FGhldiDuyzxIEKbPQMnl2JZaK+B8Cq6stK4hL3EoIN2Jo2KHTP4gZyks5JFhE3A2XF+LJEDIpvjPda8Q97tmelvWMQMGKlV8LEigoN5K7LBtNtYjryuYb8ZSfCMIcgMUNa2X155CdS0kZLHeE8eCCrUch6lbLwJX2KOxaAJIhSM9PFhbiZXD9UdgRF1+C+Al2o1ro6gfZc8QtET9HbGP1zpbAZO4LAdn5DpQahlT078zZn1hhcksLu98UcE1WGzWgKLNCPNGDDz4Yn8eqS20sd77lpCNxTn9MAeh5n+HIOjKlWy0DtpFgvWKMcGZ3o2Lq6g0ud9zMaZwj0nDBkjhHEhfxe7XO4yb5jkSqNBcVOU+0agau/H8Udk0GixBulJT5yjE07MjJ5mJHxs4rt9wlFHfFkF9HhDPxORR8xS2KdY76U9UV6hHeuEJyFws76uoYyPGBeoTEBSEU2cViiUHEMXGTRQbsgqvPFcWSZ3ZZOckXQ5JziO1E/Oc1E7HGcJIBmwqOxaIMTzrmryfCNeDYNBLK6p392qz+gHBCRCUQfJw+Uy3uqouQd7VPdKcMXPlfFHYNJh9kyUTOQCS2ikWeAsTpSJzbb789ZryxG8oLO0rXwW2Qi6X7778/CuxcRHP9sZzibujo+KEidsLUPEsnh7DLxirHmbu4k/LTCyhrQuwMrpY8bkbKCRnvJO9wv5kHqAOWynrg0qIgMXMDfYFEnjSf9ERxxwaZcVOPOnXNIh/fxFZjuWdDd+edd7Y9z+YfCy51/Fg/iMWmSHNRtFoGrowfCrsGkk+47L4YGHndMYptsgMjaB7YnZFxyQ5JC11xUBaBgN90TVkMsJKxSFaXJkDcYbkjaLmex3Eh7giKplo9JwVQL484S0qapHgU2kJgNKVV6nUsk7TOpo9it/QDYBMyyyyzREtxbhnGZY+FpNFnv0rjIIaNfsD4J8MVQZ+LOxK6CB8h5m3FFVcsLAu4FTJwpXMo7JrgXiHwlEBnXHp5nAxuWGofUQeJxR1zN67AesRJ9HTSNeWas7tkAiJuhASGvBAwMIkyOVUfZN0occdEmQ4PJzjeRbzcoo57TPwSm4m88C7/j7hjUSWGalzvIeVYK+64444ooDjLFTjVgo1dtbijvyDEiioS3woZuNJ5FHYNhvgtRF2e5ZR2O+zSWcSxEFGQloD8Mh/R1WxwryLmsIphJWXyTEKqOmuLxJZGCKla4o7EGtwruaXGRbycpLIlHAHHJq/6GDjEHTGZLKCdiemU7hVfSZYrIioniTuqJPD/1ZQtA1cmHIVdA2Exxr2SaqERHI+JmgFK/EyyynA8F5lDZTqiq1XBlYX7u5aVrFZmXSPFHTF3BCNTyqL67EspB/liiQUGwUZIBuVtyHJdf/3143yQg6DDmm9/KC9YbYmpQ1SRAQ+5ixVBh9uTkzVIHClrBq50jl78J0hD4FLvtttu4b333gtrr712uOuuu8IUU0wR+vbtGz799NPw2Wefhfvuuy9MPfXUbX8zevToMPHEEze13WXnH//4R9hll13CcsstF04++eTw4osvhh122CEsvfTS4dRTTw3zzTdfU9pEX5l77rnDZZdd1tYnxowZEyaaaKKGt0fqy5///Odwyy23hDnnnDMcddRR8bnXX389bLnllmGWWWYJgwYNCuuss85Yf+f8UD6uv/76cMcdd4Sf/OQn4ZRTTgnvv/9+eOaZZ+Ic8N1334XJJpssvu7WW28NDzzwQDjhhBMKmxNYo3r16hWuuOKKOO+tttpq8fl99903PPLII2HAgAHx/1mzgLVs9tlnb/t756fWwDtQBzrSygyYzTffPPTp0yecffbZYcMNNwy/+93vwpVXXhn69+8fZptttij0cpy068+yyy4bLr744vD000+HQw45JCy++OLxZyaoeeaZp2ltoo/QV6accsq25500ywcbuiFDhoQ//OEP4aWXXmp7fv755w9//OMfw8cffxxOPPHEcOedd471t84P5Vsv/vnPf8bHQgstFO87Qg5R/9VXX8X/R9zBZpttFk466aQ4JyCousJ///vftjXqnXfeCeecc044/PDDw1//+tf4/BlnnBFFHhsQNr9vvvlmWH/99cOee+7Z7n2cn1oDLXZN4MsvvwzffvttmHHGGdue+/GPfxymn376uFOS5tCKVrK0g3YnXB5q3ctXX301HHzwweGVV14JRx55ZNhuu+3afvfGG2+ENdZYI/z85z+PFmQpD2l8J4HPGgArrrhimHnmmcNtt90WLWV77713mGSSScL9998fN3oIMX4umsMOOywaGb744oso7r7++uu42d1oo43i7/l/PE3//ve/oyHioYcearMgSgvRSReu1ICTAKqDnXOqg0+pS0YmEwGoJkq0BgQOk0zRSvFL9ofykPcrYmwpY5JqJPL/FBomrq66biXZ85a2KS/HHXdcjLMmSx/IQKWmKcl2QOYppUwooF7r2K7unIErxaPFriDYTf/rX/8Kzz777Hj/zVNPPRVOO+20uGvDQsQOrF47MRl/tJJJva0zv/3tb6Ob9fvvvw8jRowIgwcPjtbi1157LcYwMQ/86le/CltvvXW79zCmrnxwT7fddttwww03hKmmmirst99+Yauttoo/v/XWW7FvEO+GK57nzj///EL6QN4fCT2hH7L20P8Sd999dxg2bFh0/x566KFhgw02GKvt9scWpA5isceB5Y3d1imnnNJWfXt8D+Mmwy3tmqoPgJfmoZVM6gVFX2eaaaZoBfnyyy9jxjPlTVK9LwrAYimh6Ow999zT7OZKAyDznZNmOMWB0yU47QYPEKWOOLmh2jJWpPW2GRm4Ul80RxQAOxYsOwSWYrnbddddwwwzzDDOv/m/UjMxnivtmiaddNIGtVh+iHRPRLpKHtjO/z/++OPRUk/cEvFKxE0df/zxYbHFFosWvAUXXDAMHTo0BqfXyoSVckAfSDGTVElgHXnyySdjwgKJCtNMM014++23wz777BOef/75dp6coqxkZODSBqxxxHGSwEMMeJ6kgZUOazL9kaQu6QbUWTiWGurO5XBuHgci5+eNdmT5yZ+/+eab22IrRKScHHXUUZWhQ4dWZp999nisHfXp8gPUKVJ++OGHj1V42Ni68oF35thjj41nAFPbFKsY93m55ZarnHjiiW2vOeCAA+JpOEX1ger1iPOIqVH34osvVh555JHKoosuGut6YkmGWseTtVL8sdRGYddJ9ttvv5j0kEzkFLbFlE1wK0f+cM5rR4Mp/xnTe9++fccqQioi3Zt8ASQZgsLXuL04/5m5g/OJOV0gT5BYc801K5dffnn82XCA8kN/wBW/0korVXbeeed4fvhWW20VC6cnUj/oqrjL+1M6jxxWWGGFGEoEJE7gciVR46uvvorPmRzR/VDYdZJ0BBh89NFHbRM5g4GK8Zyvl7KLOhpc5557boyt4ZQJESkn999/f6zgP2zYsPjzmWee2XZMXB6nS0Ys8VVa6HoWn3zySTwfHIHFMXIzzDBDPOUhp0iR36wMXGkcxth1EgoJExOXKnSTDUtcFjWGiJmhqCg1gR599NF28TUpdovMJuIaLrzwwpgBJSLl48MPPwy//OUvYxHyb775Jj63xx57hC222CIWgiVm6Wc/+1ksVs4JA8RXET9FtqH0DKhnSn944oknYp04asfdc889dYn5pV9xisXtt98eM3EpQky/ZA167LHHYlY2sXZk4hJTZ9x398RyJ12EQo4UdHz33Xdj+YKlllqqbUJfb731wqyzzhqOPvroGBybOPfcc2Mx0ssvvzz89Kc/bWLrRaTePPfcc/FoMArO/v73vw/LL798XGApPsuRUCRMzDvvvLHMhCWPeiZ56RGSa+gjCPz8+aLg2MpLL700rLLKKuG6664LCy+8cPj888/j5yIs99prr3Z90JIm3Q+FXQFw1AtHhbHb4bzHXNyR6cbO6KyzzorPvfzyy/Fc0gMOOEBLnUgPEncDBw4MK6ywQhRwaY6oxkW051It4orsC6le6oEHHhg9R1Ru4LMwMlx99dXhb3/7W7jooovia/E+LbnkkoV8rjQHhV1BkCLOAcnV4o5jYjgwOR+gpLBT5kREetaRdSyoWGN+/etfxzOJReoNFmHOnMVzRMFrQgPWXXfdsNJKK8XyXFjpeM1vfvObeEbtX/7yFzcX3RyFXcHijlgJznbExM0Enu++2CF5koFIzxZ3u+++e9zYsdjighVpBIg2ziF+77334qaCGLqbb745DBo0KCy33HLtrIZajrs3Crs6uGVXX331MP/884cbb7yx2c0RkRaDWCZcYCROudGTRvLpp59GtysFsQkP6NOnT9h///3DEUcc0faaesT1SWNR2I2DvINPSGcny6h3795O2iJSE88jlmaDmOPUiZVXXjkmVEh5UNh1QC7kON6HtO+DDjroB/+ueqJ24haRWmgZkbJn4EpzUHFUccopp8R/6eAElJL2TRkTUsJ/CAZGEnHUshs5cqSiTkRq4iIqzep3yZ5DAkWqm2h/LA+qjgzSvMkQIlMIUnFGCkb+UCBpvtshfma77bYLr776agNaLSIiMv5UizgTJcqFwi6DEiVUfr/33nvDNttsE5+jSGMu2nCt8sjJT5Q477zzYtp4KkQqIiIi0igUdv9HEm+cFsHxP3fffXesFs/z1KFLVbhxrSYz9ogRI9qeS6KOY8Iuvvhiiw+LiIhIwzF5oirBYdSoUTGj9a677orFHJdZZpkwfPjwmOk6zzzzxCPEiLvDTUsdICp6AydLkGVECQMEoYiIiEij6fHCLhd1Z599dkx4ID5urrnmiuJuv/32i0eDXXDBBdFSh7BLr99hhx2iJe/hhx+OrlsSLzjQW0RERKQZ9Hhhl8CFysHIJ598clhnnXWisMMyR3br9ttvH/r37x+tcbXgpAlOnejo/EcRERGRRqCwCyGWM+HsRk6KIP07hzRwkikQd0sssUT8fxEREZFWxOSJEMLLL78cFlhggbD00ku3PZf0LmngG264Ybjoooti7F11RqyIiIhIq9CjhR3WOCCGDrcrwg1Bl8qX8PvbbrstvPPOO9EVe/vtt8f4OsWdiIiItCI9SthVC7JUlHGjjTYKf//738NVV10VBV1KjqCcySWXXBKeeOKJdn/naRIiIiLSivxvcbYelv1KTB1WOE6U2HbbbcOmm24aY+x23nnnKOYoY0LZEwoNY80bMGBAs5svIiIi8oP0uOQJsl9vuOGGsOCCC0bX66233hqLES+22GLh8ssvD7/73e/CNNNMEx+zzDJL/B0163DLeuyKiIiItDI9Sthdc8014YADDohijuO+/vSnP4UtttgiXHfddW0nRZBI8emnn8b6dCuuuGK08hF/l06eEBEREWlVepRawf2KgEPUYbXD9XruuefG53DBfv/992HhhReOj9yFq6gTERGR7kCPygL4/PPPozXulltuCbvssks48cQTw69+9av4u2uvvTYcf/zxMbYux0QJERER6S5MVOYyJtWsvvrq4ZVXXonHfx177LFhzz33jM9zTBhij4xY4u5EREREuiOl8jHmRYWBGDpcrCRBbLzxxvFx8803R6sdIg7XLP9/+OGHh48++ij+Lr0PvxcRERHpTpQmeYI4OU6PGDp0aPz5sMMOC2eddVaYd955wwsvvBD233//cMopp4Tvvvsu7LrrruH555+Pz6+wwgphqqmmCnfccYfZryIiItKtKY3Fbo011giHHHJILFOCyHvggQfiY6655goPP/xw2HrrraPL9YILLgiXXnpprE/34osvhnnmmSfMP//8Zr+KiIhIt6cUKobMVSxyWN722GOP8MYbb4RFFlkkLLXUUlGo/eQnP4kxdPyLgDvppJPC7LPPHh/5eyjqREREpDvT7ZVM7jrdYYcdosVu++23j8Luyy+/DNNOO22MmSO+DnFH3Tosd+edd17o06dP2/uY/SoiIiLdnW6tZrCyJVFH/NxBBx0Ull566fCHP/wh/Otf/wq///3v42tIhEji7uqrrw7vv/9+tO6JiIiIlIlubbFLVjbOdL344oujkKNcCee/Yq3DLYvwGzRoUHwt4m7zzTePj+rzY0VERES6O91a2ME999wTrr/++liqhDp1id122y0Kub322ita7MiSrRZxijoREREpE91e2FGLbsoppwyLL75423OpDh2nSkw99dQx9o5EiYEDBza1rSIiIiL1pNsKuyTevvnmm3YnTaSyfPx74403huWWWy7WqFtvvfWa2FoRERGR+tNtfZHpZIh11103vPrqq2HYsGFtz/P46quvYhLF3XffHTbaaKNYyoQ6dSIiIiJlpRQnT5x//vlhn332iWe/brbZZmGyySYLxx9/fCxC/NRTT1mfTkRERHoEpRB2fAVq1O23337RLUvtOmLqbr31Vo8JExERkR5DKYRd4tNPPw0jRoyIZUw8JkxERER6GqUSdtVYp05ERER6EqUWdiIiIiI9Cc1ZIiIiIiVBYSciIiJSEhR2IiIiIiVBYSciIiJSEhR2IiIiIiVBYSciIiJSEhR2IiIiIiVBYSciIiJSEhR2IiIiIiVBYSciIiJSEhR2IiIiIqEc/D87N9hOou7cCwAAAABJRU5ErkJggg==", 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", 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" ] @@ -309,7 +295,7 @@ }, { "cell_type": "code", - "execution_count": 337, + "execution_count": 29, "id": "034a7977", "metadata": {}, "outputs": [ @@ -317,15 +303,15 @@ "name": "stdout", "output_type": "stream", "text": [ - "Result: [Element(object=B1, attribute 1=B, attribute 2=1), Element(object=B2, attribute 1=B, attribute 2=2)]\n", - "Elapsed time: 0.0015916000120341778\n", + "Result: [Element(object=B1, attribute 1=B, attribute 2=1), Element(object=A2, attribute 1=A, attribute 2=2)]\n", + "Elapsed time: 8.070003241300583e-05\n", "palindrome k-complexity: 9\n", "palindrome primitive count: {'add': 0, 'append': 1, 'check_if_same_type': 1, 'dim_set': 0, 'flip': 1, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 2, 'remove': 0, 'remove_item': 0, 'sample': 2, 'setminus': 2, 'write_all': 0, 'write_all_set': 0, 'write_random': 0}\n" ] }, { "data": { - "image/png": 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", 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", "text/plain": [ "
" ] @@ -337,7 +323,6 @@ "source": [ "element_set = {a,b,c,d}\n", "S = ElementSet(element_set)\n", - "kc = KComplexity()\n", "result, elapsed_time = cf.palindrome(S)\n", "print(\"Result:\", result)\n", "print(\"Elapsed time:\", elapsed_time)\n", @@ -348,7 +333,7 @@ }, { "cell_type": "code", - "execution_count": 338, + "execution_count": 30, "id": "df882383", "metadata": {}, "outputs": [ @@ -356,15 +341,15 @@ "name": "stdout", "output_type": "stream", "text": [ - "Result: [Element(object=B1, attribute 1=B, attribute 2=1), Element(object=B2, attribute 1=B, attribute 2=2), Element(object=A1, attribute 1=A, attribute 2=1), Element(object=A2, attribute 1=A, attribute 2=2)]\n", - "Elapsed time: 0.0003559999167919159\n", - "alternate k-complexity: 22\n", - "alternate primitive count: {'add': 0, 'append': 0, 'check_if_same_type': 6, 'dim_set': 0, 'flip': 1, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 4, 'remove': 0, 'remove_item': 0, 'sample': 7, 'setminus': 4, 'write_all': 0, 'write_all_set': 0, 'write_random': 0}\n" + "Result: [Element(object=A2, attribute 1=A, attribute 2=2), Element(object=B2, attribute 1=B, attribute 2=2), Element(object=A1, attribute 1=A, attribute 2=1), Element(object=B1, attribute 1=B, attribute 2=1)]\n", + "Elapsed time: 1.209997572004795e-05\n", + "alternate k-complexity: 18\n", + "alternate primitive count: {'add': 0, 'append': 0, 'check_if_same_type': 4, 'dim_set': 0, 'flip': 1, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 4, 'remove': 0, 'remove_item': 0, 'sample': 5, 'setminus': 4, 'write_all': 0, 'write_all_set': 0, 'write_random': 0}\n" ] }, { "data": { - "image/png": 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nlYEDB8ZrwftSLobvn5dtufXWWyv9+/evTDHFFK1KelSXO4EvvvgiluKh/3ENKOtBeZm8VM3E+ntb178WTzzxRGXzzTePfZS28R323HPPyrvvvtvqdffdd19lq622im3iO/LvTjvtVHnttddaXkP7KM3D59Pvl19++crtt99e8zvS5xg/008/fSxls9tuu8Wxx3e65pprWr32jTfeqPz85z+PfYHrQRtp8w033NCu7yjSGXrxn/pKRxERkfJB8W6sfRRdxtIt0hVQ2ImIiHwPxJvmWd2EK+Aq5wi6Dz74oMMZ3yL1whg7ERGRdpRGQtxRFonkC2LzONqOTFtFnXQltNiJiIh8D1dddVUsi0TyBCWRqEfHubGcESzSlVDYiYiIiJQE69iJiIiIlASFnYiIiEhJ6NbJE1T+fv/992MBzTIfhSQiIiI9l0qlEo/toyh3daH0Ugk7RF17DigXERER6e6MHDkynp5SWmGXDpzmi84wwwzNbo6IiIhI4YwZMyYaspLuKa2wS+5XRJ3CTkRERMpMe8LOTJ4QERERKQkKOxEREZGSoLATERERKQkKOxEREZGSoLATERERKQkKOxEREZGSoLATERERKQkKOxEREZGS0FRht8ACC8Rie9WP/fffv5nNEhEREemWNPXkiaeeeiqMGzeu5ecXX3wxbLTRRmH77bdvZrNEREREuiVNFXazzTZbq5+HDh0aFl544bDOOus0rU0iIiIi3ZUuc1bst99+G6644opwyCGHtHkW2tixY+MjPxRXRERERLqYsLvlllvC559/Hnbbbbc2XzNkyJAwePDghrZLRES6BwsceUdDPuftoZs15HNEunVW7EUXXRQ23XTTMPfcc7f5mkGDBoXRo0e3PEaOHNnQNoqIiIh0ZbqExe5f//pXuPfee8NNN9000df16dMnPkRERESki1rsLrnkkjD77LOHzTbTvC0iIiLSbYXd+PHjo7AbMGBAmGKKLmFAFBEREemWNF3Y4YJ95513wh577NHspoiIiIh0a5puItt4441DpVJpdjNEREREuj1Nt9iJiIiISDEo7ERERERKgsJOREREpCQo7ERERERKgsJOREREpCQo7ERERERKgsJOREREpCQo7ERERERKgsJOREREpCQo7ERERERKgsJOREREpCQo7ERERERKgsJOREREpCQo7ERERERKgsJOREREpCQo7ERERERKgsJOREREpCQo7ERERERKgsJOREREpCQo7ERERERKgsJOREREpCQo7ERERERKgsJOREREpCQo7ERERERKgsJOREREpCQo7ERERERKgsJOREREpCQo7ERERERKgsJOREREpCQo7ERERERKgsJOREREpCQ0Xdi99957Yddddw2zzDJLmHrqqcPSSy8dnn766WY3S0RERKTbMUUzP/yzzz4La665ZlhvvfXCXXfdFWabbbYwYsSIMNNMMzWzWSIiIiLdkqYKu5NPPjn069cvXHLJJS3PLbjggs1skoiIiEi3pamu2Ntuuy2stNJKYfvttw+zzz57WH755cOFF17Y5uvHjh0bxowZ0+ohIiIiIl3AYvfmm2+Gc889NxxyyCHhqKOOCk899VQ48MADQ+/evcOAAQMmeP2QIUPC4MGDm9JW+V8WOPKOhnzO20M3a8jniIiIlImmWuzGjx8fVlhhhXDSSSdFa93ee+8d9tprr3DeeefVfP2gQYPC6NGjWx4jR45seJtFREREuipNFXZzzTVX6N+/f6vnllhiifDOO+/UfH2fPn3CDDPM0OohIiIiIl1A2JER++qrr7Z67rXXXgvzzz9/09okIiIi0l1pqrA7+OCDwxNPPBFdsa+//nq46qqrwgUXXBD233//ZjZLREREpFvSVGG38sorh5tvvjlcffXVYamllgrHH398GDZsWNhll12a2SwRERGRbklTs2Jh8803jw8RERER6eZHiomIiIhIMSjsREREREqCwk5ERESkJCjsREREREqCwk5ERESkJCjsREREREqCwk5ERESkJCjsREREREqCwk5ERESkJCjsREREREqCwk5ERESkJCjsREREREqCwk5ERESkJCjsREREREqCwk5ERESkJCjsREREREqCwk5ERESkJCjsREREREqCwk5ERESkJCjsREREREqCwk5ERESkJCjsREREREqCwk5ERESkJCjsREREREqCwk5ERESkJCjsREREREqCwk5ERESkJCjsREREREqCwk5ERESkJCjsREREREqCwk5ERESkJDRV2P32t78NvXr1avVYfPHFm9kkERERkW7LFM1uwJJLLhnuvffelp+nmKLpTRIRERHpljRdRSHk5pxzzmY3Q0RERKTb0/QYuxEjRoS55547LLTQQmGXXXYJ77zzTpuvHTt2bBgzZkyrh4iIiIh0AWG36qqrhksvvTQMHz48nHvuueGtt94Ka6+9dvjiiy9qvn7IkCGhb9++LY9+/fo1vM0iIiIiXZWmCrtNN900bL/99mGZZZYJm2yySbjzzjvD559/Hq677rqarx80aFAYPXp0y2PkyJENb7OIiIhIV6XpMXY5M844Y/jBD34QXn/99Zq/79OnT3yIiIiISBeMscv58ssvwxtvvBHmmmuuZjdFREREpNvRVGF32GGHhYceeii8/fbb4bHHHgvbbLNNmHzyycNOO+3UzGaJiIiIdEua6op99913o4j75JNPwmyzzRbWWmut8MQTT8T/FxEREZFuJOyuueaaZn68iIiISKnoUjF2IiIiIjLpKOxERERESoLCTkRERKQkKOxERERESoLCTkRERKQkKOxERERESoLCTkRERKQkKOxERERESoLCTkRERKQkKOxERERESoLCTkRERKQkKOxERERESoLCTkRERKQkKOxEREREeqqwu+yyy8LYsWMneP7bb7+NvxMRERGRbiLsdt999zB69OgJnv/iiy/i70RERESkmwi7SqUSevXqNcHz7777bujbt29R7RIRERGRDjJFe1+4/PLLR0HHY4MNNghTTPH//3TcuHHhrbfeCj/60Y86+vkiIiIi0mhht/XWW8d/n3vuubDJJpuE6aabruV3vXv3DgsssEDYdttt69NKERERESlO2B133HHxXwTcDjvsEKaaaqr2/qmIiIiIdCVhlxgwYEBLFuxHH30Uxo8f3+r38803X3GtExEREZH6CbsRI0aEPfbYIzz22GM1kyqItxMRERGRbiDsdtttt5g4cfvtt4e55pqrZoasiIiIiHQDYUfyxDPPPBMWX3zx+rRIRERERBpTx65///5h1KhRk/ZpIiIiItJ1hN3JJ58cjjjiiPDggw+GTz75JIwZM6bVQ0RERES6iSt2ww03jP9SpDjH5AkRERGRbibsHnjggfq0REREREQaK+zWWWedzn2iiIiIiHQNYffwww9P9Pc//OEPO9MeEREREWmUsFt33XUneC6vZWeMnYiIiEg3yYr97LPPWj04Vmz48OFh5ZVXDn/9618nuSFDhw6NAvGggw6a5PcQERER6cl02GLXt2/fCZ7baKONQu/evcMhhxwSixd3lKeeeiqcf/75YZlllunw34qIiIjIJFrs2mKOOeYIr776aof/7ssvvwy77LJLuPDCC8NMM81UVHNEREREehwdttj94x//mKB+3b///e/oSl1uueU63ID9998/bLbZZrE+3gknnDDR144dOzY+EhZEFhEREemEsEO8EQuHoMtZbbXVwsUXX9yh97rmmmvCs88+G12x7WHIkCFh8ODBHfoMEZF6ssCRdzTss94eulnDPku6dn+wL0hhwu6tt95q9fNkk00WZptttjDVVFN16H1GjhwZfvWrX4V77rmn3X87aNCgGMeXW+z69evXoc8VERERKSsdFnbzzz9/IR9MkgUZtSussEKrUinUyTvrrLOiy3XyySdv9Td9+vSJDxEREREpKHnioYceCltssUVYZJFF4mPLLbcMjzzySIfeg7NmX3jhhfDcc8+1PFZaaaWYSMH/V4s6ERERESlY2F1xxRUx0WGaaaYJBx54YHxMPfXUUahdddVV7X6f6aefPiy11FKtHtNOO22YZZZZ4v+LiIiISJ1dsSeeeGI45ZRTwsEHH9zyHOLu9NNPD8cff3zYeeedO/qWIiIiItIMYffmm29GN2w1uGOPOuqoTjXmwQcf7NTfi4iIiPRkOuyKJQv1vvvum+D5e++91wxVERERke5ksTv00EOj65UEhzXWWCM+9+ijj4ZLL700/OEPf6hHG0VERESkHsJuv/32C3POOWc47bTTwnXXXRefW2KJJcK1114bttpqq46+nYiIiIg0S9jBNttsEx8iIiIi0g1j7D777LNw5pln1jyfdfTo0W3+TkRERES6mLDjNAhOhZhhhhkm+F3fvn1jgWLEnYiIiIh0cWF34403hn333bfN3++zzz7hhhtuKKpdIiIiIlIvYffGG2+ERRddtM3f8zteIyIiIiJdXNhxduv777/f5u/53WSTTdLRsyIiIiJSAO1WYssvv3y45ZZb2vz9zTffHF8jIiIiIl283MnAgQPDjjvuGOadd95Yyw4LHowbNy6cc8454YwzzghXXXVVPdsqIiIiIkUIu2233TYcccQR8dSJo48+Oiy00EItZ8d++eWX4fDDDw/bbbdde99ORERERJpZoPjEE0+Mp0tceeWV4fXXXw+VSiWss846Yeeddw6rrLJK0W0TERERkXqePIGAU8SJiIiIdD1MYxUREREpCQo7ERERkZKgsBMREREpCQo7ERERkZKgsBMRERHpSVmxnCjRq1evdr3hs88+29k2iYiIiEi9hN3WW289Ke8tIiIiIl1N2B133HH1b4mIiIiIdApj7ERERER6ksVupplmaneM3aefftrZNomIiIhIvYTdsGHDJuW9RURERKSrCbsBAwbUvyUiIiIiUn9h1xbffPNN+Pbbb1s9N8MMM3SuRSIiIiLSmOSJr776KgwcODDMPvvsYdppp43xd/lDRERERLqJsDviiCPC/fffH84999zQp0+f8Kc//SkMHjw4zD333OGyyy6rTytFREREpHhX7F/+8pco4NZdd92w++67h7XXXjssssgiYf755w9XXnll2GWXXTr6liIiIiLSDIsd5UwWWmihlni6VN5krbXWCg8//HARbRIRERGRRgg7RN1bb70V/3/xxRcP1113XYslb8YZZ+zQe+HOXWaZZaJA5LH66quHu+66q6NNEhEREZFJEXa4X59//vn4/0ceeWQ4++yzw1RTTRUOPvjgcPjhh3foveadd94wdOjQ8Mwzz4Snn346rL/++mGrrbYKL730UkebJSIiItLj6XCMHQIuseGGG4ZXXnklCjPi7LC+dYQtttii1c8nnnhitOI98cQTYckll+xo00RERER6NJ2qYwckTfDoLOPGjQvXX399LKeCS7YWY8eOjY/EmDFjOv25IiIiIj3OFUuJk/79+9cUU6NHj44WtkceeaTDDXjhhRfCdNNNF0un7LvvvuHmm2+On1OLIUOGhL59+7Y8+vXr1+HPExEREQk9XdhxXuxee+1V82QJRNY+++wTTj/99A43YLHFFgvPPfdcePLJJ8N+++0Xjy97+eWXa7520KBBUUSmx8iRIzv8eSIiIiKhpws7EiZ+9KMftfn7jTfeOMbadZTevXvH+LwVV1wxWuSWXXbZ8Ic//KHma7HqpQza9BARERGRDgq7Dz/8MEw55ZRt/n6KKaYIH3/8cegs48ePbxVHJyIiIiIFJ0/MM8884cUXX4zWtVr84x//CHPNNVfoCLhWN9100zDffPOFL774Ilx11VXhwQcfDHfffXeH3kdEREREOiDsfvzjH4ff/OY30R1L3bqcr7/+Ohx33HFh880379CHf/TRR+HnP/95+Pe//x3j9CiXgqjbaKONOvQ+IiIiItIBYXfMMceEm266KfzgBz8IAwcOjEkPQB07ihRTruToo4/u0IdfdNFFHW+xiIiIiHRO2M0xxxzhsccei5mruFArlUp8vlevXmGTTTaJ4o7XiIiIiEg3KFBMIeI777wzfPbZZ+H111+P4m7RRRcNM800U/1aKCIiIiL1O3kCIbfyyitPyp+KiIiISLPLnYiIiIhI10ZhJyIiIlISFHYiIiIiJUFhJyIiIlISFHYiIiIiJUFhJyIiIlISFHYiIiIiJUFhJyIiIlISFHYiIiIiJUFhJyIiIlISFHYiIiIiJUFhJyIiIlISFHYiIiIiJUFhJyIiIlISFHYiIiIiJUFhJyIiIlISFHYiIiIiJUFhJyIiIlISFHYiIiIiJUFhJyIiIlISFHYiIiIiJUFhJyIiIlISFHYiIiIiJUFhJyIiIlISFHYiIiIiJUFhJyIiIlISFHYiIiIiJUFhJyIiIlISmirshgwZElZeeeUw/fTTh9lnnz1svfXW4dVXX21mk0RERES6LU0Vdg899FDYf//9wxNPPBHuueee8N1334WNN944fPXVV81sloiIiEi3ZIpmfvjw4cNb/XzppZdGy90zzzwTfvjDHzatXSIiIiLdkS4VYzd69Oj478wzz9zspoiIiIh0O5pqscsZP358OOigg8Kaa64ZllpqqZqvGTt2bHwkxowZ08AWioiIiHRtuozFjli7F198MVxzzTUTTbbo27dvy6Nfv34NbaOIiIhIV6ZLCLuBAweG22+/PTzwwANh3nnnbfN1gwYNiu7a9Bg5cmRD2ykiIiLSlWmqK7ZSqYQDDjgg3HzzzeHBBx8MCy644ERf36dPn/gQERERkS4m7HC/XnXVVeHWW2+Ntew++OCD+Dxu1qmnnrqZTRMRERHpdjTVFXvuuedGl+q6664b5pprrpbHtdde28xmiYiIiHRLmu6KFREREZESJU+IiIiISOdR2ImIiIiUBIWdiIiISElQ2ImIiIiUBIWdiIiISElQ2ImIiIiUBIWdiIiISElQ2ImIiIiUBIWdiIiISElQ2ImIiIiUBIWdiIiISElQ2ImIiIiUBIWdiIiISElQ2ImIiIiUBIWdiIiISElQ2ImIiIiUBIWdiIiISElQ2ImIiIiUBIWdiIiISElQ2ImIiIiUBIWdiIiISElQ2ImIiIiUBIWdiIiISElQ2ImIiIiUBIWdiIiISElQ2ImIiIiUBIWdiIiISElQ2ImIiIiUBIWdiIiISElQ2ImIiIiUBIWdiIiISEloqrB7+OGHwxZbbBHmnnvu0KtXr3DLLbc0szkiIiIi3ZqmCruvvvoqLLvssuHss89uZjNERERESsEUzfzwTTfdND5EREREpPMYYyciIiJSEppqsesoY8eOjY/EmDFjmtoeERERka5EtxJ2Q4YMCYMHD252M0TCAkfe0ZDPeXvoZg35HBERKQfdyhU7aNCgMHr06JbHyJEjm90kERERkS5Dt7LY9enTJz5EREREpIsJuy+//DK8/vrrLT+/9dZb4bnnngszzzxzmG+++ZrZNBEREZFuR1OF3dNPPx3WW2+9lp8POeSQ+O+AAQPCpZde2sSWiYiIiHQ/mirs1l133VCpVJrZBBEREZHS0K2SJ0RERESkbRR2IiIiIiVBYSciIiJSEhR2IiIiIiVBYSciIiJSEhR2IiIiIiVBYSciIiJSEhR2IiIiIiVBYSciIiJSEhR2IiIiIiVBYSciIiJSEhR2IiIiIiVBYSciIiJSEhR2IiIiIiVBYSciIiJSEhR2IiIiIiVBYSciIiJSEhR2IiIiIiVBYSciIiJSEhR2IiIiIiVBYSciIiJSEhR2IiIiIiVBYSciIiJSEhR2IiIiIiVBYSciIiJSEhR2IiIiIiVBYSciIiJSEhR2IiIiIiVBYSciIiJSEhR2IiIiIiVBYSciIiJSErqEsDv77LPDAgssEKaaaqqw6qqrhr///e/NbpKIiIhIt6Ppwu7aa68NhxxySDjuuOPCs88+G5ZddtmwySabhI8++qjZTRMRERHpVjRd2J1++ulhr732Crvvvnvo379/OO+888I000wTLr744mY3TURERKRb0VRh9+2334ZnnnkmbLjhhv+/QZNNFn9+/PHHm9k0ERERkW7HFM388FGjRoVx48aFOeaYo9Xz/PzKK69M8PqxY8fGR2L06NHx3zFjxjSgtQLjx/6nIZ/T1e+p10Ea3RfA/tD1x2VXaIOUj3S/K5VK1xZ2HWXIkCFh8ODBEzzfr1+/prRH6kffYc1uQdfA6yA59oeuQVe4D12hDdJ4vvjii9C3b9+uK+xmnXXWMPnkk4cPP/yw1fP8POecc07w+kGDBsVEi8T48ePDp59+GmaZZZbQq1ev0NXUNYJz5MiRYYYZZrANtsE22IYu04Zmf75tsA22oWNgqUPUzT333N/72qYKu969e4cVV1wx3HfffWHrrbduEWv8PHDgwAle36dPn/jImXHGGUNXhs7R7A5iG2yDbbANXfHzbYNtsA3t5/ssdV3GFYsFbsCAAWGllVYKq6yyShg2bFj46quvYpasiIiIiLSfpgu7HXbYIXz88cfh2GOPDR988EFYbrnlwvDhwydIqBARERGRLi7sALdrLddrdwaXMUWXq13HtsE22Abb0Ow2NPvzbYNtsA31o1elPbmzIiIiItLlafrJEyIiIiJSDAo7ERERkZKgsBMREREpCQo7ERGREmIIfc9EYdcB7r///mY3IWy33XbhmGOOccA6aYmITHR+5EQm58meh8Kunbz44othww03bHWkWTNYbbXVwtChQ8Opp57aowdsmrR6MlyDntwHuiLeD+kK/WLfffcNSy+9dDzJqaeLu0oP/O4Ku3ay2GKLhUsvvTScf/754bDDDmtKG8aNGxc/+6yzzorn5p522mnhu+++a2gbmCiazeOPPx6ef/75+P/77LNPOPPMMxvehrauQyMnETYbSdyec8454Z577gk9edLM29KMduWbDYquS+OZ2PzUyLkr9b/XXnstjB07tuGb0J/97Gfh66+/jsYI1o1miLsRI0a0/P95550XRo0aFRrN+P8Ttl1trqo71LGT9nP11VdX+vTpU/nd737X0M/973//2/L/I0aMqOy7776VySabrPLHP/6xMm7cuIa0If+c2267rXL++edXLr744so///nPhnz++PHjKx988EFlzjnnrOy6666Vn//855Vpppmm8txzz1UaSX4d/vWvf1Vee+21Nn9fL7jm9MMTTzyx8utf/7oy3XTTxX7RSPLv+dVXX8U++u23307wu0bxySefVL744ovKd99919JfGkX+WXvvvXdlzTXXrIwZM6bSbBp5Ddq6582Yny699NLKoEGDKgcddFDlpptuqjTjmt9yyy2VBRZYoHLGGWe0jIt687e//a3l///+97/Hz19nnXVa1o9G9YfHH3+8ssIKK8T78Ktf/arSq1evyuuvv15pFmeccUblJz/5SZwr77333krZUdh1YMK45557Kscdd1wcLHTUo48+uuFtOfzwwytLLrlk5Wc/+1lliSWWiOLu5JNPbugEfsQRR1TmnnvuyhZbbFFZeumlK6usskocwI3if/7nfyqzzDJLZcopp6xce+21Lc838hqk6/CDH/wgCqyNN964MnTo0Ia15dNPP62cd955lammmqoywwwzVEaOHBmfT6KmkYvoqaeeGifN1VdfvXLggQdWXn311Uqj4dqvu+66lZVWWin++8YbbzTkc6vvMxuPTTbZpPLQQw9VmsHzzz8fN5+MixdffLFmG+tB/hl/+tOf4jx51llnVT7//POGC33myDnmmCOKum233bay8MILVw499NBKI7n11lsrU089deWcc85p2IaLOZh16Zprrmm6uGNTw+abdWL66aevPPPMMxMYKBrFySefXJltttkqu+22W2XllVeurLjiig1dr5qBwq6d3H777XGgsogxWAcOHFiZfPLJK4cddljD2vCXv/wlWmbYDTFAWNxPOeWUKO74txGD5oorrqjMM888ccIAxAXChoms3jAh8R2ffvrpyqKLLhrbMWDAgPhzop4LSH59sVTy+ddff33ljjvuqPziF7+IooLFpFEwgTOR0yew3NVqZ7058sgjK7POOmvloosuiuMCod+/f/9oOWsUbLCYuC+//PJosVhooYXipufjjz+u6+dirc35wx/+EPsAG57Ro0dXGs0NN9wQ++Sqq65a2WCDDeKCitWokRxzzDGxP6y22mqxH/DvRx99VNexmb/vXXfdFYXMk08+GX9G4LL5Yd5qFNx7rv8JJ5wQf/7mm2/iNUDwMld99tlndfts1iO+bzPFXfqMs88+O246l1lmmThfjh07tiEif1zV+7MBv+++++L/v/DCC5Vf/vKXlcUWW6xyySWXNM0oUG8UdjVAMOVgBdl5553j4p348ssv40BF3B111FENaRcLF4OEiSKH3THtOPfcc+tusWHiRkzBddddFwcun5vccfXYnbY1ETz66KNxwtppp51adoT1oPp6Y8o/9thjo0UiwWTNznD55ZdvZUWs53XA9fiPf/wjCqq+ffvGNjWSl156qbLssstWHnnkkfgzAhcxccEFF7SaLOs5aWKpxGI8fPjwls3PjDPOGK9JTtFtwAKEZTC9N32EcbDgggvGTUeiURZU+j9WbDZaaTFH9LOo1ZO8T/JdmRueffbZuLizmK611lpR4NVD3BGGkizV6X0vvPDClvvCpov+mOYn5uzUV+sJVlv6AG1B5OH+W3vtteMGbP75569cdtlldR0X9M3evXs3XNxV31usx4TJEDKDwEfo1Xs85G249957K4899lhlo402auWifvnll6O4W3zxxUtruVPYVcHOYq655moVN0V8BBMUpuUcrBJ77LFHnEAbYepn0ULApZi2NECx4E0xxRSxHYi/epA+65BDDok7UQYME1WaNBlQWG3OPPPMytdff12XgYr1gcn8tNNOq7z33nvxuQcffDAupkweaZfOxI7oLoJddtklWmtTW1hIuM48qgU9wnaNNdao7LPPPpWiya8DkyULeYrbQeBxTRB3eeznb37zm3h96tEGYLLs169fXCC4N3l/4Fr8+c9/bnHF1QsWD6x19M8777wztiGJG8YnVrRkKSiSDz/8sOX6jxo1quU+8J0RE2nzU28LalqcWcS33nrr+P9vv/12vC8sXok0Xook7w+IfEIk1l9//corr7zS0jY2X8ydhI8kC2oRgoJ7TRgE7rX333+/5XmsMISppL6Q+iMQa4fISiKzaLgGqa8RV4YnY+aZZ473JfVJ3PQ77rhjpd60Je6YK7lHRffJ6vmJDSfXI216WTsRd+k6ABtRxkxR5P3qsMMOq0w77bTRgs19OP3001u9ljX0gAMOqMw000xxQ1o2FHY1JuzlllsuWiJy6xMLBJMTIioH1yxuH8QgO7WiB0m+KLH7Y2LYdNNNWyUs0E5cw7hiitoRtbWzvuqqq1qEDRa7BIsoOyPiW+oB74uLbb311ovxbAjcBx54IP6OeCZM67igcAWyWy5qMUfIpgU8vedTTz0VrUJMVGkRyydU7lE9xASwMCFkiCHieyYxi4Bi8mIy23777SsbbrhhvF5FTeD/+c9/Wv4/TYTE0nHPEfOImXzSZpwgiuud2IKljPHAQspCnqyFaWdOX0n9pB4Qz8ZYSIsY9wFxwT3aa6+96i7u0mLGtede8J0RdSRw5LHBBx988ASeiCL7JAsk3gT+xWKXtw9xh6UIF22Rbkgs5ljCENFJuCIo0iY3d7XRfxmXeF3qYSl76623YuwWAibNF4SnMEfSR9O8zOcTrlFUf5iYBZS5q5a4I6Ro//33rxRFfj0Ji8ASxppIXyCBhe/P2sW1YY7ec88945hF9NZjXLz55ptx/cbtzcaWvo97Op8bUl9hQ9yMuL96o7CrMUiYfFi0EQkpEJyFClHBbjAXdwweXHCY+YseJCyY7EgJSE+B0FjtiN+gfWSm4u740Y9+FB+Jzoq7anP2jTfeGCfn9B3ZDbELoi1YsFhMmDTJgqqHqR0rJEImxdKx82biRsjmExaD9Pjjj29pQ2faUp3pysJJFnCKnXriiSfiNUBEYangvhEwjFsQK25R5PcCd+MiiyxSufvuu6O1DEsA7re//vWv8ffcHxYS+sLuu+9eWIYqCxQCCViUEIzJ+vLDH/4w3os8xo9FlIl7q622qks8zUknndTi7sYyyHdl4s4tVLThxz/+cXzUM6YH6xh9n40d4yAXd2Rv18N6m6APYj2n791///1RWCAo85ARYP4gXKGoLN18jqIv0iexavOdyQbG3fjuu++2ej3ier/99itkEc3vJ3Mkn4nF/p133mnZfDI2ERUs7Hw2ohfhWa+Mafoh94IEIu559caO60EYCxvCtAnoLNXzNOM0eRcSiJpqcUc/rYeYYR1EvCd3N5stNuBp3k5u6W222SYmtdQjg5556Gc/+1kr4Yrox7uSh4lUUzZxp7DLSB0MEXXzzTfHBYsdYUrTRuBgxsYFsOWWW1Y233zz6P4qaqDmkw0dFAsEu/7ZZ589ZvMQMwJM4sT8sTNld8RkkgZJZyes/O+ZFPhsFgssYgSGs6CzQFBuhQkDUzcWTnbkqQ1FDxLEWnJ1cw24LoistIgmsZW3vTNtQEwTAJ/H7WEB474jMtMCidhFULCoIyAQWlyjNKkXuXjgWsZqnGfeAsKSnS9WmVoUIbTZ2bIgsQsnppKfE1z7pZZaKvYB+ixlBRgjWLfrMXFjIeVaMzZxt8G///3vOE4ZI1hvfvvb30bBycasyDa09R4ICtrEOMnFXcpSZMErGtqCkKW/JbDS8Xm4g/EecF1YSFlsi5qjqjc7JG0NGTKkpb/jPeBeEM+Vi7uczozNNKbyfs24SOIuuWW59oxLsjIRvMzVRc5PtcY2mwk8OPRD5u30eQhLssYRwGwCiyD/fARsmoeZjxD2ubcJ4wNloQgzyilynua9tttuuxhXCGy6sdilWNcUnsM1YX6sdR87C+9FKMpkk00W3f85iDusicxjzFFlR2FXBdYgFi9cfyzuuDVYpFL5BHYfdF6EHTtQsmyKhsUBN1ba+WDKZmLCjI2lIg0KrEosKmnB6ewgyScLxCOJAFgnmaCxCqUJO8VFYCVDUPBvUW2otXjiZmbBZjfKrisPjCcgl8WrqDpRxMhhaWHBZKHAKpL46U9/GvsCC2cSd3x32oTow4Ka2l+kK5b7z6TNol3LAoS4Q4BzffLJukhhucMOO8TPzwV8+q64+LAIce2wJjMuirCa1srAZQwgoBFRbGzSZoeJG0GHqGQRZTErsg15v8QVzyMX/liusVLm4o7rgtu6XtYAvjOi/ve//33LcyyubMKYw7gfWFdz12hR0AfYUNInsFDnfY2NMMKaMiPVmcNFzg35dcVyR3tytyz/shHAqloPIcHcSOJateWO+8GmgnmLNmJJZ97GRVg0bPQQsGmeQuRyT5gTcnGH2GPsFkX13IKXi7WSdYN1K49vZP5iPc2rF9R6jyLWCjZUw4YNi9eAf3MQ/dwTNully4KtRmGXQVAtu6rkVmJQ4opF4LCg5wUW+V09OgeWGSwguDXzWlwMHMQdLlhS96uFTJFWERZLzNlYrnKYJJk8mTRqCZfOtiH/e3a2KcgZ6ylCi90oyRO5tWizzTYrLPOPSZrYjOT2RMgyIeaud1wI1eKOSRXrJWIcK0mRVtP8/vNd2ZmnuLX8dQgqhEU9NzwsTlhAsE4lcZ8vlNy/PBavyEUUSylWB+4FCyXiCQsVrp7kkq/V/4q2zuBOQ7AQ34h4ymN02ABxbdgY5FbNotpR6/2wQjAv5NYx+iPuyIcffriwpIlafZK4WsYDm4pU/ijB3IWFl98XDdccdx7zUB4UzyYvibuULVuvOZK+TVgCcwEeherfEU/Ghi8PiSga7i2bzxSWgEcJKxl9gr7J9cljgIv6/vn7MEenn9lMYSljns6tg7yGMKbqTPWi2kDfr451Pumkk6K4Q/Dn4HFqRLZ+s1HYVSl6LFLEjeQ3nkQFdkUsnmk3Xi/YXRKnxSLG5Fy9GyFuKcVZ1WOQMAmxUBCEj3WkGlwvxKoUne2Yt4HFEwsVrjbuAQsImWRYH4iRwM2EuEHI5HF9nR2oTEx8LuA+4z5wDRC5ueWOxQrxjdhI1wHBwS4VK29bLqhJOdWCoOzkXsIagMsJYVGr+Gw9Ju5qENzEOyJg8kD46mzsoidNFk+scdWJTohpClWncif1nKxpA9+dZB3uBbFrLB7011zc0W8Q4UWDS4+NTb6pwpLOYk68a73I+wP9kQ1u6uPMF9wXrDXVbkaER9ExdYMHD46iBVGPqOHeI/LSRoPrg7UQj0rKVq4X9D/ijbnfWItzEDHMEbQjz9otEjZRiDnGYSpngsUuzdP0TWILc5Fb5OabmEKs81ivgTg+SttgEcszxZmnEXxFbW6qN1qIa1ysrEt870/+ry8g7nDLIvgn9h5lRGFXBTvxPAg7xQew42Cg4N4oagfWlmuBSRMLFRNUdewU7h0sVPVw72D5wArGZ+BewfJAzEhex40FhGtUpIslh90mn4uoy1PhaReuUCYOrGNMppQ1KSJuJg1yXAhYGZiQmSiYMLFeci+qxR27YWKXKIiaPhsLCQv/pFpJ8smGUiX0NawhiIRkFcBKSL9A3NeKmypy4iZOiXbg/s2tx5QYYaPDBM4Gg2QN7kc9khSIh0HEElOJ27G6ZEaKhcUtW09xx+aO+5CC0ynvQh/BOoTVkOuUBFduxSgCvg9WShYxvivXGyGRNjTMB3gV6lGQubpP4jHA3cxinU7eYX5EQJA0USsLuqi5Clcecb95lnM6hQaBnyDmjxjgou8B4E5lLKREDcQdG0I2gLlblrg3PD/1ykROpPmPz2JDnuKNEXhcExJ76jEu6XPMTRgf8FIksKCyOaasCmsmcyeb73rEX+OG5t6TMMbczDxF/zzooIPihpt7lgRunmjXE+ixwi4NVEy47DjSZMGOj0kSc38OWTbED2BRK4J8sDE4mBQYLIgDYJdF0C+Do63A+CJT5lN9tlSwkQmJBA0WbCZ0Fg1i+ljMaVO9Fk/ig1I5DQYn94fdb4pnQvQiLhE1RcX15TARpsUzceWVV9YUdyxs6R6kf4uo4YdVAhGDNYYYTqyVtCnFczJ5Ey+DhbAecTtA3CJuV6yT3HMmcawDWKqAEAUsqOyS881Okf2C4Hw+F2soYpJJm0y7XDgzdpnQqUmFsCjqelQvhog12oPAYoziEk8FqnG3cX9oW/539VhQ2VAhblg8sZLhakL8Yhlqa54oAoLSWUTJvmRM4mrkOychR78gc5pNV3VGeREgqNnw8Ugxg2nccz9w/+Wn36R+WOQ9oP+zcWNTxcYmzVPMjczdhHGw8STOEY9LPa5DNel7ssFgw8fGL8Vk5+WoirwOhGUwNzAmE2l9AOZm4gyZH3HJprmxM/N0Xt6L90tzYHUcHWJv6aWXjvcK8PYQutSoQuFdhR4p7PLdPuZrrDSptg9uFlwsDFImbOpUsftjUku7tCLBlM+CxGRATFtefwmxhaBgYa1OY68HtAWTeTLdI+6YwLk28847b3R5EJiexEvRCxfCBWFHiQIemPkZpCyi+WDNKbINWAiZEFnEmKDzQqKIO7LduEdJfCeKTFhgguR+J9caFkFidVK2WbKeMrEVVT6iGqxj3O+0gHIv6JdYKNmEpLI3tIUJtx4CGwGNuy0PR2DSRkTigkPQsYBgReOeUP6FRTdZ7TpD3qcIQGczkVutCcBmXKRxgAjGHcnCWvSGB+HEwsRimiy0WAZZwLEUsQFB4HF/qmNiiwK3GqItHU/WVp/ENYi4rUefpCA69x3LbNp8cq15ILqrj4hKv+8M6f2BPsCYQNwzNlkrcPOlUyTYhDJH4+lgvUihEo2C/s+1YaNFIhdeh3qJGeZC4o+534x/XLKso3wuiU15nG2iM32C+Zh1kCoECfocVtJUkD3/ruutt14MWaqmJ4m7HinsABcSrhQWMSZKXH8p6xDrHbFc7IpZ4LHgFZWmnsNEyc4nBR6zA6QN+bmGiEkmbiwSRVE94aVBxzVA5DKJJpiwWDAQVsSdJctM9TFbRUA7uOaUcCF2hgWUSZQYFT6/yODbibWB68MpGrSDbM8EIgMRnp/uUDSISyxhLOgsFNXZZVhoqgPVi1xIEW3c53RyB5sfYpqIoaMfIO4I1q4+C7VIgY04w92PUKve0GBRx+3HOOE1bMC4X4gPFpZ0JmQRYwPBRh/gO2MdSBY6Fo7k+mM8sIjk1euLEneEAfDZxBARV8kGKwmJBAsr94brUFQx6Op7yQaPa40rtLpPMnfSJ6sLt3emT7bVl7Das9lCYOWuNYQE1yeVQOos1aE2WEJJlsqTtBAJ1EbDDV8dX9poAZGuF/MCLmA2QKkN9RDZGDvYbGPNZ23Ck4HrF2HN3JV7NYoaB7j+eaRKEXxnNuG5tyBdh6OOOioaIcoeRzcxeqSwY1HCGoDLC3DfMDHQUVnEmDySS4edcb0ONGehSMeU1arPltLVSRaoxwBlMareWbIzZ+Gqntgpd8EgQvDW41SF3KWZCiLn8Nm1gmDrBQIHNwILOy7pBO7RelaN51rjDqYOFkHx+ZFIuD9xueUup85Sa/JjgcBCgWuFjU1ydzBhp1NHUlHkeoE1ihqRWGmqTyug/7H5IPM0XUPqHNLWPN6nM/eDxQu3H5svLESUa8AiQv9HeHINSJTBQsKmo+jCt7i5cMdjFWMOImmBGDvaQNuqKSruN/dKsFhjtU0Fp/FgVPdJ+gjXAYtiEeTXj+tOG/ITTbDUIiToG0nEMCYQ9UUIKsQbFrcE78nncb/TGbT57xARuIHZCNaL9vSpWnNJPQUm94RYNowQKTSCPppOfKiHIYb1mX6YDA+EJRCqgbeLOSKd8LHmmmu2uoc9kR4p7FgYiD8guwsLCRa5VK09HZnF4poHjNcDJi1cSVhAquuzMWA4eiVPIChS3BEviFjCCoDATZYRXNGUDEhnjKYFA8HBBMfiWV3osiiqvx/iKtUHw5LX6J0wn88uFIsJ/WFibe0o+UTMxJhvHlItKkR/eh2bETJRizznsfrouhQ/l6BPEOeZNhi4e4ibITi9Xvcij1FETCGacPXUKkIN9FMmcQRHUVZ1LPaMvbyUBuIKayGxU2T/sRHDapfXyytyfHLtmZeqLaOIGURNdSxhEYIS0US/w+qJS5Xwk1TiiTHP79jgpe/L5pM+yUaw6I0ngonviQsOq2Ue85osd2yE+WzuR1HB+cx/yfKZxgebBa4H8YPJIpzXxeN3tLH6Xk0qk2r9LspqPrG+lH9GutY8x/hgLcOyXY/sfMYkm136JNUpkrhLIRipUD9xuP379+9Rbtda9Ehhly8gmNHpECmujN0wOzNcbkVlfrbV0YnVYvJmx5cXGUVQMEjIzi3KAsCElL4PQg7XAoIC4cLkiMWSrFMmSczp+RFRaQDj7mLBY2fWCLBoklFF7FK9TrX4PrgXtAOXbD2C4UlMwc3FhJRnYyfrDDGNuBWKPkkh/3sShVigSZRhg5PGAn0EIcPkySYH10deILnIyZNrjGWUSTsdkwVYBRCX9Mda4g4xx2uKKkPEIs5YYKNFO3LYZBFDlMIicst10QsJLnDcfOlepH6PhR33V2ddzjl5OQ7ibBFMfP9Uiy9db1z0tCmdukOfxGJZxNjM+yMWQqwwWAsRj4it+eabr5XFDBFKX8VClGL/uAdFzZdYiLAWp3gxYl/5mfGQYmzTZ/G9U83NzpJfB8IhEI2Iaaz0E+tj+fdG9Exqf+xo0gnXh7Ii6UjJepw2Q7IQY5K+yWaXxBU8S0nc0UeYH6o3nd/1YHHXY4VdgngpAk1TWjrV7YkZqUdJE9wVCCnEZApAp2wBLh/+ZSJjEWWQMGEV5d5hcSDYFRM1woydd+6CxdXLAsnEibjj9+yW84r1+e6sUXCNiCkqIquqs5uAemTZIaJZpBFQTFrc87xWG/2ESY0FDPFVjwkLCxD9D+sU7tW0cCcLItZSnmOjg9W0HsVWUwYuYpbFjP5HqEQC4Ybo5HW1zmQuOjQANygLCQtV9akN3IvcelQv2HSx4cQamddFpLwGiQLpOLXOgpCmj+UCm+vPZrNWIgqCE3cl9wfLchF9Mh9TbCBw5SHskqhl7BHDRx/Mw0SefPLJmA3KhicV6S0KhDPXgfudxB0bW7wWabOT2lYPsFYTS8hGin5PWxAttbLu8zbg9eG11QWy2wOfhXci3Y/2znWsaayb9ZifCAshng9xn8BaTj8g1rY6trOsZ792lB4v7Ji4OTAa0cMkR4xdnsbdGfIBRwwQu2AWRz6PSTtlPjJRkuHDgMRyg7Ar2kJFmQJ2Onx2WhSqF0QGJG4Odj+4FlKweJHWofY8D10x8LXoI3AQdimmkvgQ3G+4FPLFq1pIFTlhkYWM24K+kdwdLFrVB2VjEcGCUQ+BTdwe5SNSUDT/kjhTHbOEtaT66Kp6whyA0OZzk4sXdxPhC7iEigbrA+7OPAuYMibME4gLYtkQeLgo2Qx0pgh2Du+bEqGYD+ijlHTCxYy4Q8h931gtqk8yDyLwERfEF+ZHtnHfEXIIbn6f4N4Qe8W8yWakyP5BuAqF2hGPubhL5W3aEhWdhQ0WFsqUJEW8MZ9XnaQB+fcl7o2QhHTMXkdBrOKtyV3rHZ2jixZU9AG+U3XMNeOE/onlrkjrdVno8cIuTaqYeElhr0eaOgHJCDrcB0wQmO2xhLBIpFg2nktB60WWj0iDj10wCxUxKwzcFD+YBmL1ID322GPj5FIrdX1SPj8JBKyWeb2ttibi/HlivGpZaroT+fchIJ7Cz9wHgr8TLKyIu1S9vWiqJ2kmTYRkujd5tiPujVpB+kVP3FiFWJSBTEfakILlCYjOJ+3U/kaJOzZ93AssmrgecYsTOpE2REW1gw0eYpZyOizgWEyTcCOujxJEPI/bEytOLniK6g+4WXGt5uEnzIfE4HIGcm5JmhRr0Pd9PglThCRQSgMLEMkQiNq8ZiHXGzcoQi7f8CDCO3O6Q7qPxBMi1vJYUzY91eKOuRpLal5brTNUjylEC/0NsETm45IxkerF5X/HmMEoMSmFeJP1EdIJFsTKtUfc5W3I48EnhVrjifUYC3UStflrGIsIUbwd0hqF3f9B563HgkH8AVljnFTAxJA+A5cKwq6t8z2Ldnmym2WxZiFNNbeqk0PS2adpskSMFpVAgjsBiyUTNhMQwjFRfd3zn1nYWPBqnf3YXcjvJXEgTNS4Flmkuca5aGXBwqKKxYJ6ivWAuD4shbjg+fx0tmSefcgEj6AoSkRMbFOFKw1XMG3IMy6xXNBXyQZONDIUIFk1qaJPKEPetiJc0qlOGlZB7gfzAwsZmX4srElkMXa5Flgtijr7tRruM9Z85qk8MYOSQ8R64mqjP1AOqeiQCDYQxDNioUzQBiy5eFLa+s5FhgUgLPFSYDHE5Ys1PWVjJ3GXu2WL6od52ah0ckgqiE4CHWMiT6rjWhHnmR+XRrUA5otJEXVkHrNp4Pt2VNzl8zQhFIRM5GtIR8jfn3UqNyikMkuI+nz9pK/S/kbPCd0BhV0docMRh4J7i91o6vRpQsLtRKYVk3kjXY8E4uJ2xmKUJnEWl7x+HrFXtHtSg4Lzg5bZTRO/R7YZu2JcTnxv3NO1Xp9AaBDrV8ty1B0hMJ8YRtxHLNaIGvoFAj+f4FM5j3pkvzL5s3DR91i4sEQgNHMRmSrXs4DUY9KkwC0LCf2eNmAJwzJEn0sQS8SGiMDxZk/c3C9CJXDBpgzhIkBYs0DhXs3DP7DwI+4YM404vSD1M0QsfYH7nos74pCZL0ggKjpEhPfjuyIuqo9yJEmL8cEmtB7F4YG+xbhk84hAwgqH9wYxj6BKsdcp5q66jZ0BsZ5qYmIBRMQy9rjnzM1YcYmrSyB2sOYidNI8mTKZ81MmOgoWL9yaHRF3+TzNpoS2piSWzsDRienEJTagCb434pW2kmjI79lsdTQesKegsCuQWp0LMUe8EB0/X7gANywxI/Uuq1JrMCLuCD4lVZydONajfCeOdSId7tyZ68DOkoWR3W6yTDGZIyKxEORm9FquhVqnTXRH+D6csYl7KS2a3A8sJSxeTOq1kgCKdH2yOLGA4AZOICC5/4hLJlIsZ1jJSCiqR4Yblh+sH3xnxgQiH9cbFkySEhgr7MKJncnrwzV74sYtSxsps1GECw6BjfWaxTM/TSGBhZoxSQJHbrGsF6mf4WZN4i6fl/JagkVZ7NI9RbBgoWIuRFDk9xpxh6W/6LpkeUYrYors07xcCZ+Hmw9xl74783VR7le+IyIRiznCFdGSvzeeCmIJSdYgcQB3OOMDd3yeVMej1pnRHYVNNpvt9oi76s13Z+bp/F4jrClnQlgA1x/Bn58BzAYIDxdjgkoB9ZifyoLCriDyzsUAJaYtnWKQOi3ZhZiriWnAWkEnJb6okR0zH5S0kUOScZPWI6OJgZgKuBLLlbtTk7jDKkimbk5n4kW6KrjVsPogZqtPjkixboidIq9/bgWlv+HaQlTlO2GgPyK4WMgoe0LGY9H9gTawSCMiEZPE49D3EDWMDeIO6QecBoOligm9WSVu2oL7xiLXmXguoDQLoo5MeLK+ETQs7vnh9qnP8LqizqfuiLhj/BHLVi0qO+NZmNg8x6aP/s+izXjIPweLWj36ALGNWIL4TDZc1d4JxAXxXWSk4x4sAgQkSSAJNnRY3CihU31t2WSRSMcGiPYhttOYqEeFgLbEHdbLWvUzk0eliHmavo87NxVfR+yTBIKozwvE4+mgr+R1BGVCFHYFg0gi+5QOz4R93HHHtcSIsPvD5cRApsQARxElF1yzxF1OZwdJPvCxxJB8waSIkEDA4crKYyeYpMjAZCFPbWJSwS3QnS11bd1L+gHB+Cwk1TUSCdrG7VgP92u6r0yaWOL4/PzYuER1okyRkyZCDhcTAjL/jixeiDviq5i0cX3lv+9qE3etchMdAXcnZV3yEiOpYj9Wympx12hRm7tlmaeqvQxF9EfmQRIzcPdjjUqxZUnc4YrDyt/W0YdFgLhCMHHeMm49Mi8RNrjGc3DLEqRfffrJpIBIImYx9WnmP8Qjmxg2fbghqwUk1+2VV16J1sSixMzE1hqyoWuJu3SWegLLOpbdIkQdBgbmANaIvIwPayPvz1qaTmjq6pUTugoKu06SDxJ2GLhPMJuzKyd9H4scFpA0YeB2ogPnyQOdrcM1qWVD6hEAnIKNmaTycy0ZsEwOTGS5gKierLEs1fu4qnqSX1NKRZD1Sl3EtGAj7ghAx/XUVgHsIk+1IB6FBSstTMTBsHAyUeZH/1R/ZpGTJpZbYpiYoLHgslDlIOpSgH5+AkfZJm6yLQl/YEGsPskEtyfXBosppWXqdQ3a836pL9CmooU195jwD9yQuLVxt9FHUwwd4g7rNfNovVzQeFRIastDEuijjElEdxKaic4cU9fW9SfLMy/hgeBjXFaLu+qyNkWWnmKeZrNXfR4zm45qccd6lrtjEYBFHW3I9WaOxA2bi8e0NlJJgU1GPc/oLhsKu4IgRR3rFPEBOcRKYCVJIoeJi/g13LL56Q5FDFQCaKk9R4YZSQrtrVSedoSTAgHVaWKgLbhb03mi1dcCcYeoZfBWH19Fe8oUK0FZCOqNkQBAPAgWAUR9mqyJn2GXXn00VNFtIMsP4ZQHn7MBYREjfqce5zrmkPiCBZtxQBgC95+4ymr3ImOBOL+yiblaYw1LPe6t6rpkCCn6DMkk1eNjUmlrTH3fdc4zTnmPIsYmcYQk7qSiz1iCmCfoo8xZScQQl1yk9Tr/vowDwgEQl8zXOVgnsWbjZam23HWWfC5mQ0dfx1ORi3jcscRxIi6ZF3B/Mn8URX7P+a4U/iXGDw8JMdB5YhDCjbFafXxk6heTOk7b6ke4wZkjcL3i9ao2HBDf2NWs910ZhV0BMBExOTFJVceLAbERZPDkuxAyiXh9vmvs7CLOAsqESEwbYhI3Z60BWF1OBEvBpB6fhps1uaeS5ZGkC6wzuJaqhQsZkUV+765CvgghnJg0UwFTYkewSHHCRALLHQHT6Yziornjjjtif8hdrvl9x8WBsOToumoLWlEwGWOZyb838XRYY5i8q8VdrczoMkACUXIzJwFHfC2ZprlVJLlli0qmqrYeM+aGDRvWIubbU0MSl2wRnw/EUWKZSe1hjkDcUm6H2FOs29XffVLFXa1aoCnJgI0OLl8EXnXtNeYzRDcbjXpsNOn3xLQyDxLfR73KXNylE2gYI1i5iz5VBbjOzA0UB8/PpqZ8SC7umJuIKS2K/HpiDEiJU+k7YrljPWJexLJbC8Vd+1DYTQK1Bjw7QXZhTArVWUpMqOzO8vgcOjMdu4gzLrEWIiTS4dW42xioeWHRRHVGE8Hqk1JOhAkqWaDSgo1YTZY/BAWTNfEj1aUKEDxlGaC5aEnfiUUhBfwSK8guNJ0wwSYgLZZMZPWKocIqTEA+fbWtItS0ncm7HgtYOnMVtyNiIgerMgsX7q/qhbxsoo4AfQLksQSRvJKsdFjUyXJE3HWmVEV7N31kN+L+TUcGtnUkWX796UPUD6OtnT1KEWsc8wCJJ2wiES/EVwLPIfJI7EmejSL6Ae1GrADXmLkuZZ4iMBFObMSrkyZwhxZlSc+/BzVEietLmy0KtbOxqhZ3WDIJR6nHSS9sKCltlY5gY37Cm5BqWXK98o1eUXNDfh1YO1gnMShwD7AaJoGd3LJUECD+USYNhV0HyTs6A5OdZ4o1wA2JtYxgW4Jz2aGzU2dix71SL8guTGnhiLy8qCUunWQZqZWmPinBr8RrIVQRDlijAPcSCzkLV6rXRwwJ4o54rlp1qLq7uGNSJC6EhTMHFw9xKvSNvGp8WmCIr8yDsesh7thMsCtPMWu5BQNrXq0g7aKhNhtZncSVVZ9WQP8kHCG/NmWD60xcKf2B708cFaIqHZ9GMgkJBLjFET/1gAWcfpAyMclEpw35hiRRq4bkpMwP1S4/vBlYYpJlho0dSUSpnFK6Ngj+IscCG+xUDJzvXF1SBmHJZpzNzaTW62zvdSDZgM/jOuQkcccYyU/kqdfcQHwz8xbzTypngsUurSNcJ9qSVzAocm7gGtAfU2UAxj+fSVxlSjLEwk39PjY+ZdvoNQqFXQfIOxmmYqxkiDhiFCj0ymBAwLAbZffJLh3XKBN30ccQ5YOe4rLsbigTwESWVypn4DBg8wSHzoi6vPI3B3Vjqk9nE1I4kwHKopGLO2I1CAovOm6l2fB9cGvg9s7r8VE5nvtAAHIuXBBZWE3yjMh6Qc06SjUwkebuJmI8EeT5KRP1BCsyY4SM6Orj+lhgukopk3pADGPKKsVKhfsvnTObxhHXhHE0qaEQbZHenySB9Jlcb/plOgsY6zqu3+rFu6hyQwS7Y/FjEc9PJCCRiBg35gnEHeKWWN1EkX0iiRWsQrXqnjE+GA9YMvPTHIqEe4yApB2UuIHcxYqgwy3LOKl3zCuk64BngWufvCwIPAwEzFFFibnqEyXY5Kf1Ams2/Wzw4MFxrSTumKLd6bVlDc1oBAq7SYCkgHwXjOmYQYtVDmHHA4sWnTaPcersEThtDTYsALj7aAOiIt+dEctD7aQEk3Vnyonkky7fDWFHNleyWrKYVYs7JnKuR5mSI9Jkg+uA3SUWiPwkDTKiuR9YSAgWx3pFzCGTd15gtJ6woOPuwPWB6EdkswvmfjXSWsr3Z+KmPbWKqZZN3GGpxfrEhg6XGoIeqxXZ8Xldy+TuK+porLw/pWuKWxF3YzqHN99o0DfpG7noYlOIa66zoo7NBC7GdJoNrlhKm2AdY+6hxAgZsZREwh1X5PFgOYgIhAObcARLynjN+xziD5d4Z+sT1gIL/R577BHDY4izxquRrOi5uEPksDlsxByZ+gnGCEQt9z+dNpOHBXS2LXl/xJPEZ+ByxgDCfIS1MBkhUpwffS/PSlbUTRoKuw6CuZgBkYKeU4wCQbe4LhB3xA0h7ihrQYB6Eec7Vp8awYAgVitNEnx+cnmw82TgIOrYqeaLOItJfrD6pELWFO5X3ByISorbJrGIuOO745ZthMuvWaR7ghsHywjiLrfGsZATS5bcQSxmjSi6m19jLEbJWkBfQGA3o/Av4o4FHOtUPTOBmw0WF4K/ca2yoGOxpw+QRJKuO+ERWGhwl9fjjGpcjvRHIH4WSyEehNwNiJWG+SG3NGM5wsqcLCqdgTAU5iNitxB0XAfGAJsKrgfxuVjycMsWGUuWriXXOBeLuHvnnHPOKO5yC3ZKcCqqAHH1vSTDljWAWGo+i3mRa5BO4amVHNGoOZIkDpK62PwRMoHnociC5LkhBAttbrFnY4MLOm0q6KeIfubPsm30moHCroOQAMGkTYwCboQ8RoFYGhZQFnB2HSnmjkFTXY9oUsEFzMLB52I1ZOJAWGDCJk0eEcFOmMHKjjmvVF7UhIE1DjGLeEREIlyJy8BCkc4LRPzyGrK/yrTzqr6GuWsayx0TN6I3d0Vi2WRir5Wp15k2pCOFapFPjoh/+irB5EW1YVLAwr377ruXStznkFFI/CTW2hRXRcIEgiav3YjY5vl6HCXIfUU8I+ATWOyw0iOmWFzpkwgcrKi59ZjxnJ+K0FmIv2UOwHPBNUkxZLhd6Qc5RSzmaSwQ28hnMB8hqFM5JjbCWO6wnCMqEZ3MlUXVqcvHYi4eaQehKMBcgNWeTU4qadOMsZjGINeB/khISWpHkcKKjQ7JGiSOVK9jXHtA5GIkYP1KKO46h8JuEkhiiYWcXUfa7eGSxVqFuysNEhIX2LGlWJbOLOIIKMQag5GOj5uFeD6ERAr+JVaHwpNMYvVaxFm8SAjJrQ0IVxYwsp2SuKN9ZRqg+cSNxZTYRhaoVHwYK0gtcZfTWVGTx0qmXX972pvTzHuS2lQ2cce9ZwEnm496fek6455njFKTDGsEoguxw8kKRZOuKRZRPiN3uyJ02OyRsELR9Nx6XE9hwXxEkkjeRtyeiKp6gDcDEUtdPL4/lsLJJpusJRuWtlArkM02Iq8eMW3EriHkcK8Cn83nJQMAFkyEHTX9OnuSSVu0ZyNdawwW2RewwrF5INY3Xf8091B8mufpp3g6eHT3ZLquhMKuE4OGRZ1aSEzqDFBiFPK6VJ09bzMfeFjkEE8kKOTFS9lpsXCwgNQSj0UuoOl7I15YxJIVIi0QCEpcPgzY3N1bBnGXX0esD0xI7DKxjODOwBWOwOfBPcFSW6umYWfAEpHKpuDmxaXTnmvb1aylXa09RbqbcXvi8sb6lcY+rlHGLRs+xF1RB8m3VaMS9x5ZppTcSbXzkqhhE0I5i0ZbbrEaEwvMHMnYqMfn4kVh40udOmCzizu4+jQD5mosZ0WeKJFgPFIyBM8N3hNK+tAv+Jf7gVWXa0+5GVz19ThCsBF/1x7oZ7j7EdrVdUv5XDwInDpCPGo9rIU9GYVdJyBmgrpExCYwoddrwmJSYMeHNYDPyVPRUwwDQosYhUZknuLOQcykDK9ceBA7RHvLZpFJYDUlCSCl6wMTE0IvnbSBCMciQYZZkSIGazC7fFxJZBtWZ5nWIv983GxFhQRIbUiSwTKGqOf/GwGWIKzjhEWk+43limz0+++/v82/a9QYpU0ISkQdLuB6xXgi5HBxI6oZp1jkUkYwkBBSlKieGFxz3I9Y9dn47bPPPjHrlvAZYssgXyeKPEIQ9zfJclgq6QPtPX0IoVvk2pXahMUWrxZxvt9XL1VRVxwKu07CJMIizqLeWQtdrQGHWCIWgawiXH8IvFoB6MQnYBVolDWEeB1ELcHXiBx2X7gf8orhZRuoJIOwWGKRZDeaX2t2ntQsS3FTRabr539PfA7WgPys4fb8HeKTBJf2iEEpJgsYcVfv642Yw1pMAhPWKtzAyaLPAo+wyK12zYIQAq5LkZbC1L9xa5OshqWSI7g44QIRhahLcxCbYSxkiJ16zJGUTUlHlPEd8ebweYhYYpLpC+moxeqajkVBPU0SUxCSZDvzWXhXarl7q8NK6tGudK9ZG7DcEY6Qe7TKtj50JRR2BVPkrofSJVi/8rp01KAiRZ0DtKtdr42OX2IHjOhkMuGB6OjsWYJdGXbiTFAIuGSNSe5oFlgsBNVlZDp7HfJ7yQTNThwXMOISt2zKKstfV51pmU4YSdXmpf4gYog5ZZwWaSVqa2xjoUr1wEiqIsaMTRbWklQIuKtQxPyU+jelZXC3srHlfXG7IlI4nzn/HK4FcVy1CqV3FuY8rjfxi9xvkkQQLdwLSqmk1+CGx9peD0FDWR1KxyRPAqWNuA7V5xFD9dyAt6GITOjvE3ds/Emyqz5/VopHYddFwSK0+uqrx5i16iOZkrjD1Zef7dcMQcWCwmSCq6UeR+B0pcWH5ygRQDIMLtG8Wj0uTsRtrWPcimgDoiwPuMcigFs+F3eQio0WXWxWOg7jgjqPRdVHy/sDGwi8BLj2Ujwf44/xjzV32223jaeisLhj0SsjZLuyycJCl4enkJFP2AolX4h3JR4Vi2Y6crFeYJ1FUCLoGZ/U8MO7ku5PPj93VtxV/z0eHVzdaa7IaxYSe5gSWPK/a9TckIs7rg2eJ6kvCrsuDJM34o4FvNo6RywF2ZeUO+lKlMG8notjMnyJDUnJIPyO2EomKCx0lLTAsoplhCSWor5/3gaSNShsSgByHvDNAkYxaOqT0T/IdGRHnGBiV9Q1l3pkPZIohVWOPkifw1KUn9sMCB3KMhHIX6/iv82+rnw3PBqA+5lMS8YI7las2iSr4EUgNjWdz1xvKHPFdSfmmZqAiGviH4vcfOeZ8amYL3MQn4mYzI+UBOavrbfeutXJGmwIKJtVxNzQkQxcNsB5pQepDwq7Lu6aQFgQJ8MjnfmawDpUBiHVVaG+ExZTkmMomYCrK4G4IyMaiwjH5FDqJsU2FXlPiJEhUeKJJ56o+ft99903BowTP5cfXYdrBjd5vVws0hyYD9IxXVjGWaxJYiKZKV+kqxfNsok7QiDo7wcccECsGUcWMF4M3LJY04l3IxOXMVmrCHAjIPYai2JeU7CzMK45qi2NfcpOIfSwyLGxI+6ZOSO/TiS05fHXuOaZt/JTJhrhSs89OWVNrusqKOyaTN7B2XWRjMBETTp8ggmbwFMmiFpnSiruiiFPdsB9xvVmEsTdfNlll8XFM6/UT/kGrAJYzVI2cl6ItqMQp5Nc67SBBQsLXDq8HKscyTRYKrDapImS2D/6S94PyMxtSwxK94UkGI6mqhZv9AdCAapPuSmzVYSkBIQTFipcoPwMuPoQOc0KCanORE/jsoh4WwouU04HEYvFLY/fxHLPeatYKKmVx8af+Yks7bwQNY9aR/u1tw2dzcBlU1yGcJ2ujMKui4C7jYmZI8lYuCmimRb05JZlkc8PSpbiyCcsRBquG4Kdc6FGRhfijuyzBEHKLLRMnp2JpSL+h8DqassK4hK3EsKNGBp26PQPYobyUg4JFhF3w+WFeDKETIrvTPcacY97tqdlPSNQsGLl14IECsqN5C7LRlMt4jqz+UY85SeCMAdgccNaWf05ZOdSUgbLHWE8uGDrUYi6q2XgSmsUdl0AkiFIz08WFuJlcP1R2BEXX4L4CXajWujqB9lzxC0RP0dsY/XOlsBk7gsB2fkOlBqGVPSflLM/scLklhZ2vyngmqw2akBRZoV4oocffjg+j1WX2ljufMtJW+Kc/pgC0PM+w5F1ZEp3tQzYRoL1ijHCmd2NiqmrN7jccTOncY5IwwVL4hxJXMTv1TqPm+Q7EqnSXFTkPNFVM3Dl/6OwazJYhHCjpMxXjqFhR042Fzsydl655S6huCuG/DoinInPoeArblGsc9Sfqq5Qj/DGFZK7WNhRV8dAtgfqERIXhFBkF4slBhHHxE0WGbALrj5XFEue2WXlJF8MSc4hthPxn9dMxBrDSQZsKjgWizI86Zi/ngjXgGPTSCird/Zrs/oDwgkRlUDwcfpMtbirLkLe2T7RnTJw5X9R2DWYfJAlEzkDkdgqFnkKEKcjce66666Y8cZuKC/sKJ0Ht0Eulh588MEosHMRzfXHcoq7oa3jh4rYCVPzLJ0cwi4bqxxn7uJOyk8voKwJsTO4WvK4GSknZLyTvMP9Zh6gDlgq64FLi4LEzA30BRJ50nzSE8UdG2TGTT3q1DWLfHwTW43lng3d3Xff3fI8m38suNTxY/0gFpsizUXR1TJwpX0o7BpIPuGy+2Jg5HXHKLbJDoygeWB3RsYlOyQtdMVBWQQCftM1ZTHASsYiWV2aAHGH5Y6g5Xoex4W4IyiaavWcFEC9POIsKWmS4lFoC4HRlFap17FM0nU2fRS7pR8Am5A55pgjWopzyzAueywkjT77VRoHMWz0A8Y/Ga4I+lzckdBF+AgxbyuvvHJhWcBdIQNXJg2FXRPcKwSeEuiMSy+Pk8ENS+0j6iCxuGPuxhVYjziJnk66plxzdpdMQMSNkMCQFwIGJlEmp+qDrBsl7pgo0+HhBMe7iJdb1HGPiV9iM5EX3uX/EXcsqsRQTew9pBxrxfDhw6OA4ixX4FQLNnbV4o7+ghArqkh8V8jAlUlHYddgiN9C1OVZTmm3wy6dRRwLEQVpCcgv8xFdzQb3KmIOqxhWUibPJKSqs7ZIbGmEkKol7kiswb2SW2pcxMtJKlvCEXBs8qqPgUPcEZPJAjopMZ3SveIryXJFROUkcUeVBP6/mrJl4ErHUdg1EBZj3CupFhrB8ZioGaDEzySrDMdzkTlUpiO6uiq4snB/17KS1cqsa6S4I+aOYGRKWVSffSnlIF8sscAg2AjJoLwNWa4bbLBBnA9yEHRY8+0P5QWrLTF1iCoy4CF3sSLocHtysgaJI2XNwJVJoxf/CdIQuNR77bVXeO+998I666wT7rnnnjD11FOHvn37hlGjRoVPP/00PPDAA2G66aZr+Ztx48aFySefvKntLjv/8z//E/bYY4+wwgorhN///vfh5ZdfDrvuumtYdtllw+mnnx4WWmihprSJvjL//POHP//5zy19Yvz48WGyySZreHukvvzlL38Jt912W+jXr1849thj43NvvPFG2HbbbcMcc8wRBg0aFNZdd90J/s75oXxcf/31Yfjw4WHLLbcMp512Wnj//ffDc889F+eAb7/9NvTu3Tu+7vbbbw8PPfRQOPnkkwubE1ijevXqFa644oo4762xxhrx+QMOOCA8/vjjYeutt47/z5oFrGXzzDNPy987P3UNvAN1oC2tzIDZaqutwvTTTx/OOeecsNFGG4Xf/e534corrwxbbLFFmGuuuaLQy3HSrj/LL798uPjii8Ozzz4bDj/88LDkkkvGn5mgFlhggaa1iT5CX5lmmmlannfSLB9s6IYMGRIuv/zy8Morr7Q8v/DCC4ebbropfPTRR+GUU04Jd9999wR/6/xQvvXipZdeio8f/OAH8b4j5BD1X331Vfx/xB1svvnm4dRTT41zAoKqM/z3v/9tWaPeeeedcO6554ajjz46/PWvf43Pn3nmmVHksQFh8/vWW2+FDTbYIOy3336t3sf5qWugxa4JfPnll+Gbb74Js846a8tzP/7xj8PMM88cd0rSHLqilSztoN0Jl4da93LEiBHhsMMOC6+99lr4zW9+E3beeeeW37355pthrbXWCjvuuGO0IEt5SOM7CXzWAFh55ZXD7LPPHu64445oKdt///3DFFNMER588MG40UOI8XPRHHnkkdHI8MUXX0Rx95///CdudjfeeOP4e/4fT9Mnn3wSDRF/+9vfWiyI0oWYRBeu1ICTAKqDnXOqg0+pS0YmEwGoJkp0DQgcJpmiK8Uv2R/KQ96viLGljEmqkcj/U2iYuLrqupVkz1vapryceOKJMc6aLH0gA5WapiTbAZmnlDKhgHqtY7u6cwauFI8Wu4JgN/3Pf/4zPP/88+3+m2eeeSacccYZcdeGhYgdWL12YtJ+tJJJva0zv/3tb6Ob9bvvvgujR48OgwcPjtbi119/PcYwMQ/svffeYfvtt2/1HsbUlQ/u6U477RRuuOGGMO2004YDDzwwbLfddvHnt99+O/YN4t1wxfPcBRdcUEgfyPsjoSf0Q9Ye+l/i3nvvDcOGDYvu3yOOOCJsuOGGE7Td/tgFqYNY7HFgeWO3ddppp7VU327vYdxkuKVdU/UB8NI8tJJJvaDo62yzzRatIF9++WXMeKa8Sar3RQFYLCUUnb3vvvua3VxpAGS+c9IMpzhwugSn3eABotQRJzdUW8aKtN42IwNX6ovmiAJgx4Jlh8BSLHd77rlnmGWWWSb6N/9XaibGc6Vd05RTTtmgFsv3ke6JSGfJA9v5/7///e/RUk/cEvFKxE2ddNJJoX///tGCt+iii4ahQ4fG4PRambBSDugDKWaSKgmsI08//XRMWCBRYYYZZgj/+te/wsCBA8MLL7zQypNTlJWMDFzagDWOOE4SeIgBz5M0sNJhTaY/ktQl3YA6C8dSQ925HM7N40Dk/LzRtiw/+fO33HJLS2yFiJSTY489tjJ06NDKPPPME4+1oz5dfoA6RcqPPvroCQoPG1tXPvDOnHDCCfEMYGqbYhXjPq+wwgqVU045peU1Bx98cDwNp6g+UL0ecR4xNepefvnlyuOPP15ZYoklYl1PLMlQ63iyrhR/LLVR2E0iBx54YEx6SCZyCttiyia4lSN/OOe1rcGU/4zpvW/fvhMUIRWR7k2+AJIMQeFr3F6c/8zcwfnEnC6QJ0isvfbalcsuuyz+bDhA+aE/4IpfZZVVKrvvvns8P3y77baLhdMTqR90Vtzl/SmdRw4rrbRSDCUCEidwuZKo8dVXX8XnTI7ofijsJpF0BBh8+OGHLRM5g4GK8Zyvl7KL2hpc5513Xoyt4ZQJESknDz74YKzgP2zYsPjzWWed1XJMXB6nS0Ys8VVa6HoWH3/8cTwfHIHFMXKzzDJLPOUhp0iR36wMXGkcxthNIhQSJiYuVegmG5a4LGoMETNDUVFqAj3xxBOt4mtS7BaZTcQ1/OlPf4oZUCJSPj744IPwi1/8IhYh//rrr+Nz++67b9hmm21iIVhiln7605/GYuWcMEB8FfFTZBtKz4B6pvSHp556KtaJo3bcfffdV5eYX/oVp1jcddddMROXIsT0S9agJ598MmZlE2tHJi4xdcZ9d08sd9JJKORIQcd33303li9YZpllWib09ddfP8w555zhuOOOi8GxifPOOy8WI73sssvCT37ykya2XkTqzT/+8Y94NBgFZ//4xz+GFVdcMS6wFJ/lSCgSJhZccMFYZsKSRz2TvPQIyTX0EQR+/nxRcGzlpZdeGlZbbbVw3XXXhcUWWyx89tln8XMRlr/85S9b9UFLmnQ/FHYFwFEvHBXGbofzHnNxR6YbO6Ozzz47Pvfqq6/Gc0kPPvhgLXUiPUjcDRgwIKy00kpRwKU5ohoX0Z5LtYgrsi+keqmHHHJI9BxRuYHPwshw9dVXh0ceeSRcdNFF8bV4n5ZeeulCPleag8KuIEgR54DkanHHMTEcmJwPUFLYKXMiIj3ryDoWVKwxv/rVr+KZxCL1BoswZ87iOaLgNaEB6623XlhllVVieS6sdLzm17/+dTyj9s4773Rz0c1R2BUs7oiV4GxHTNxM4Pnuix2SJxmI9Gxxt88++8SNHYstLliRRoBo4xzi9957L24qiKG75ZZbwqBBg8IKK6zQymqo5bh7o7Crg1t2zTXXDAsvvHC48cYbm90cEeliEMuEC4zEKTd60khGjRoV3a4UxCY8YPrppw8HHXRQOOaYY1peU4+4PmksCruJkHfwjnR2soz69OnjpC0iNfE8Ymk2iDlOnVh11VVjQoWUB4VdG+RCjuN9SPs+9NBDv/fvqidqJ24RqYWWESl7Bq40BxVHFaeddlr8lw5OQClp35QxISX8+2BgJBFHLbsxY8Yo6kSkJi6i0qx+l+w5JFCkuon2x/Kg6sggzZsMITKFIBVnpGDk9wWS5rsd4md23nnnMGLEiAa0WkREpP1UizgTJcqFwi6DEiVUfr///vvDDjvsEJ+jSGMu2nCt8sjJT5Q4//zzY9p4KkQqIiIi0igUdv9HEm+cFsHxP/fee2+sFs/z1KFLVbhxrSYz9ujRo1ueS6KOY8Iuvvhiiw+LiIhIwzF5oirBYezYsTGj9Z577onFHJdbbrkwcuTImOm6wAILxCPEiLvDTUsdICp6AydLkGVECQMEoYiIiEij6fHCLhd155xzTkx4ID5uvvnmi+LuwAMPjEeDXXjhhdFSh7BLr991112jJe+xxx6LrlsSLzjQW0RERKQZ9Hhhl8CFysHIv//978O6664bhR2WObJbd9lll7DFFltEa1wtOGmCUyfaOv9RREREpBEo7EKI5Uw4u5GTIkj/ziENnGQKxN1SSy0V/19ERESkK2LyRAjh1VdfDYssskhYdtllW55Lepc08I022ihcdNFFMfauOiNWREREpKvQo4Ud1jgghg63K8INQZfKl/D7O+64I7zzzjvRFXvXXXfF+DrFnYiIiHRFepSwqxZkqSjjxhtvHB599NFw1VVXRUGXkiMoZ3LJJZeEp556qtXfeZqEiIiIdEX+tzhbD8t+JaYOKxwnSuy0005hs802izF2u+++exRzlDGh7AmFhrHmbb311s1uvoiIiMj30uOSJ8h+veGGG8Kiiy4aXa+33357LEbcv3//cNlll4Xf/e53YYYZZoiPOeaYI/6OmnW4ZT12RURERLoyPUrYXXPNNeHggw+OYo7jvm699dawzTbbhOuuu67lpAgSKUaNGhXr06288srRykf8XTp5QkRERKSr0qPUCu5XBByiDqsdrtfzzjsvPocL9rvvvguLLbZYfOQuXEWdiIiIdAd6VBbAZ599Fq1xt912W9hjjz3CKaecEvbee+/4u2uvvTacdNJJMbYux0QJERER6S5MVuYyJtWsueaa4bXXXovHf51wwglhv/32i89zTBhij4xY4u5EREREuiOl8jHmRYWBGDpcrCRBbLLJJvFxyy23RKsdIg7XLP9/9NFHhw8//DD+Lr0PvxcRERHpTpQmeYI4OU6PGDp0aPz5yCOPDGeffXZYcMEFw4svvhgOOuigcNppp4Vvv/027LnnnuGFF16Iz6+00kph2mmnDcOHDzf7VURERLo1pbHYrbXWWuHwww+PZUoQeQ899FB8zDfffOGxxx4L22+/fXS5XnjhheHSSy+N9elefvnlsMACC4SFF17Y7FcRERHp9pRCxZC5ikUOy9u+++4b3nzzzbD44ouHZZZZJgq1LbfcMsbQ8S8C7tRTTw3zzDNPfOTvoagTERGR7ky3VzK563TXXXeNFrtddtklCrsvv/wyzDjjjDFmjvg6xB1167DcnX/++WH66adveR+zX0VERKS7063VDFa2JOqInzv00EPDsssuGy6//PLwz3/+M/zxj3+MryERIom7q6++Orz//vvRuiciIiJSJrq1xS5Z2TjT9eKLL45CjnIlnP+KtQ63LMJv0KBB8bWIu6222io+qs+PFREREenudGthB/fdd1+4/vrrY6kS6tQl9tprryjkfvnLX0aLHVmy1SJOUSciIiJlotsLO2rRTTPNNGHJJZdseS7VoeNUiemmmy7G3pEoMWDAgKa2VURERKSedFthl8Tb119/3eqkiVSWj39vvPHGsMIKK8Qadeuvv34TWysiIiJSf7qtLzKdDLHeeuuFESNGhGHDhrU8z+Orr76KSRT33ntv2HjjjWMpE+rUiYiIiJSVUpw8ccEFF4SBAwfGs18333zz0Lt373DSSSfFIsTPPPOM9elERESkR1AKYcdXoEbdgQceGN2y1K4jpu7222/3mDARERHpMZRC2CVGjRoVRo8eHcuYeEyYiIiI9DRKJeyqsU6diIiI9CRKLexEREREehKas0RERERKgsJOREREpCQo7ERERERKgsJOREREpCQo7ERERERKgsJOREREpCQo7ERERERKgsJOREREpCQo7ERERERKgsJOREREpCQo7ERERERCOfh/CwK5fjWVuOwAAAAASUVORK5CYII=", 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", "text/plain": [ "
" ] @@ -376,7 +361,6 @@ "source": [ "element_set = {a,b,c,d}\n", "S = ElementSet(element_set)\n", - "kc = KComplexity()\n", "result, elapsed_time = cf.alternate(S)\n", "print(\"Result:\", result)\n", "print(\"Elapsed time:\", elapsed_time)\n", @@ -387,7 +371,7 @@ }, { "cell_type": "code", - "execution_count": 339, + "execution_count": 31, "id": "da9b45ff", "metadata": {}, "outputs": [ @@ -396,14 +380,14 @@ "output_type": "stream", "text": [ "Result: [[Element(object=A1, attribute 1=A, attribute 2=1), Element(object=A2, attribute 1=A, attribute 2=2)], [Element(object=B1, attribute 1=B, attribute 2=1), Element(object=B2, attribute 1=B, attribute 2=2)]]\n", - "Elapsed time: 0.0021164000499993563\n", - "chaining k-complexity: 20\n", - "chaining primitive count: {'add': 0, 'append': 0, 'check_if_same_type': 0, 'dim_set': 0, 'flip': 0, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 6, 'remove': 0, 'remove_item': 0, 'sample': 10, 'setminus': 4, 'write_all': 0, 'write_all_set': 0, 'write_random': 0}\n" + "Elapsed time: 7.329997606575489e-05\n", + "chaining k-complexity: 21\n", + "chaining primitive count: {'add': 0, 'append': 0, 'check_if_same_type': 0, 'dim_set': 0, 'flip': 0, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 6, 'remove': 0, 'remove_item': 0, 'sample': 11, 'setminus': 4, 'write_all': 0, 'write_all_set': 0, 'write_random': 0}\n" ] }, { "data": { - "image/png": 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", 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", 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" ] @@ -416,7 +400,6 @@ "element_set = {a,b,c,d}\n", "S = ElementSet(element_set)\n", "assoc = Associations({a: b, c: d})\n", - "kc = KComplexity()\n", "result, elapsed_time = cf.chaining(S, assoc)\n", "print(\"Result:\", result)\n", "print(\"Elapsed time:\", elapsed_time)\n", @@ -427,7 +410,7 @@ }, { "cell_type": "code", - "execution_count": 340, + "execution_count": 32, "id": "590c9d20", "metadata": {}, "outputs": [ @@ -441,7 +424,7 @@ }, { "data": { - "image/png": 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", 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", 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" ] @@ -453,7 +436,6 @@ "source": [ "element_set = {a,b,c,d}\n", "S = ElementSet(element_set)\n", - "kc = KComplexity()\n", "cf.seriate(S)\n", "print(kc.get_cog_name() + ' k-complexity: ', kc.get_k_complexity())\n", "print(kc.get_cog_name() + ' primitive count: ', kc.get_prim_counts())\n", @@ -462,7 +444,7 @@ }, { "cell_type": "code", - "execution_count": 341, + "execution_count": 33, "id": "7e2d4e07", "metadata": {}, "outputs": [ @@ -470,15 +452,15 @@ "name": "stdout", "output_type": "stream", "text": [ - "Result: [Element(object=B2, attribute 1=B, attribute 2=2), Element(object=A2, attribute 1=A, attribute 2=2), Element(object=B1, attribute 1=B, attribute 2=1), Element(object=A1, attribute 1=A, attribute 2=1)]\n", - "Elapsed time: 0.0004013997968286276\n", + "Result: [Element(object=B2, attribute 1=B, attribute 2=2), Element(object=B1, attribute 1=B, attribute 2=1), Element(object=A2, attribute 1=A, attribute 2=2), Element(object=A1, attribute 1=A, attribute 2=1)]\n", + "Elapsed time: 1.0700197890400887e-05\n", "serial_crossed k-complexity: 14\n", "serial_crossed primitive count: {'add': 0, 'append': 0, 'check_if_same_type': 1, 'dim_set': 0, 'flip': 1, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 4, 'remove': 0, 'remove_item': 0, 'sample': 2, 'setminus': 4, 'write_all': 0, 'write_all_set': 0, 'write_random': 2}\n" ] }, { "data": { - "image/png": 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pOYsIAegINwQyljtKnbjyMo57773X1raj1EW/fv2sFQ8rCkLk+++/t+cNuBEfeeQRG6dH6QtX7sRZGOMC14+Jl5AAxD4WGlfvMBUkSuBWY0JncncB+Y6rrrrKWocpH+JKdpD4smDBAns/EAnbc08XBn0DaxOWQtoE9xqRmY5gxKVP3TiSHRDzhExwzvRRLMPEbuIyp42xCMGdzHGJ5UwWX0ofx+1Im0EIskDhe+kPCGFK6UQFpY64Hlj/6U/0Ia4xx0ag8bqD43PfKNmCQGZcYiygHzsxiuhEgNL26c94Fug3LJL8ts99RbDRT1lUuXInWHHDFs5hw4bZMYy4Vfod15F7R9IE15h/izJIrtNyhUgHSixcddVVtiQH5UEoB8G/77vvvm3eO2/evOC0004L9txzT1vygHIIf/zjH4Np06ZtU16BEgxFKXfywgsvBM2bNw8qV64c1K1bN7jtttsSJR78shHFLXfifz8lQ3baaSdblqRt27bB448/XuB7mzRpkvSzK1asCPr06RPstddeQcWKFW05Ekpa+Dz99NNBly5dgn322ce+p3bt2sEFF1wQLFu2LPGem2++2R53t912s+fRqFGj4JZbbilQGgS+/vrroFevXrbkxY477hjUrFkzOPHEE+0xfD7++GN73lwz3kMZj4ceeqhY5U6S3R+fwq5LqnInlCjxceU/wiUskp1DuNwJPPDAA7bsDaVI/HIhqdoCJWi4vuEyNT6//vprMGjQoKB+/fr2fnFvaR933HHHNvejONfEv4edOnVKlI+59tprg6lTpyYtd5Lsu7gG4VIwlNy47rrrbGkh2gXt44wzzrDHcsycOTNo3bq1/U1+SY9kfW7z5s3BkCFDEt9Xq1Yte038UjvAeSQr01OcvvjZZ58FPXr0sP2jQoUK9v+UEuF5n7lz59ryOPQfrh3vo+3Pnj27wPto55T/4T30I9pYst9I2R5KOO2xxx62PFH37t1tiR/eN2zYsG36Oe/lOrjrS/mhsWPHFuk3ivhRjv/kWlwKIYQQIjUk1hxyyCHm0UcfLXZ5IFG2UIydEEIIkUcky8bFNUtYCYlLQhSGYuyEyDIENacqIQHE7RFnJIQou7U5iY0lZpAagK4UEbF+4bqKQoSRK1aILEMQdmElJAgI9zdcF0KULdgRhGLH7D5CUhbllCgKft1110VW7FnEFwk7IbIMmampCp8C2a9kxgkhhBDFRcJOCCGEECImKHlCCCGEECImlDlnPVu1/Pjjj7ZAa3G3/RFCCCGEyDY4Vyl8za5K/jaRyShzwg5Rp6wiIYQQQpQ2li5dancJKowyJ+zcVkpcHLZ7EUIIIYTIZ9auXWuNUk7DFEaZE3bO/Yqok7ATQgghRGmhKCFkSp4QQgghhIgJEnZCCCGEEDFBwk4IIYQQIiZI2AkhhBBCxAQJOyGEEEKImCBhJ4QQQggREyTshBBCCCFigoSdEEIIIURMyBthN2zYMFt4b8CAAYW+b9KkSaZRo0amcuXKplmzZubll1/O2jkKIYQQQuQzeSHsPvzwQzNmzBjTvHnzQt83c+ZM07NnT3P++eebefPmme7du9vHwoULs3auQgghhBD5Ss6F3bp168zZZ59tHnjgAbP77rsX+t677rrLHHfcceaqq64yBx98sLnppptMq1atzD333JO18xVCCCGEyFdyLuwuvvhi061bN9OpU6ftvnfWrFnbvK9r1672+VRs3LjRbp7rP4QQQggh4kiFXB78iSeeMHPnzrWu2KKwfPlyU7169QLP8TfPp2Lo0KFmyJAhaZ+rEEIUl7rXvJSV43w7rFtWjiOKh+6/KFMWu6VLl5rLLrvMPPbYYzYRIlMMGjTIrFmzJvHguEIIIYQQcSRnFrs5c+aYlStX2hg5x5YtW8yMGTNszBwu1B122KHAZ2rUqGFWrFhR4Dn+5vlUVKpUyT6EEEIIIeJOzix2xx57rFmwYIGZP39+4nHooYfaRAr+HRZ10L59ezNt2rQCz02dOtU+L4QQQghR1smZxa5KlSqmadOmBZ7bZZddzJ577pl4vlevXqZmzZo2Tg5w3Xbs2NGMGDHCJlwQozd79mwzduzYnPwGIYQQQoh8IudZsYWxZMkSs2zZssTfHTp0MBMnTrRCrkWLFubpp582kydP3kYgCiGEEEKURXKaFRtm+vTphf4NZ555pn0IIYQQQohSZLETQgghhBBFR8JOCCGEECImSNgJIYQQQsQECTshhBBCiJggYSeEEEIIERMk7IQQQgghYoKEnRBCCCFETJCwE0IIIYSICRJ2QgghhBAxQcJOCCGEECImSNgJIYQQQsQECTshhBBCiJggYSeEEEIIERMk7IQQQgghYoKEnRBCCCFETJCwE0IIIYSICRJ2QgghhBAxQcJOCCGEECImSNgJIYQQQsQECTshhBBCiJggYSeEEEIIERMk7IQQQgghYoKEnRBCCCFETJCwE0IIIYSICRJ2QgghhBAxIafC7v777zfNmzc3VatWtY/27dubV155JeX7x48fb8qVK1fgUbly5ayesxBCCCFEvlIhlwfff//9zbBhw0yDBg1MEATmX//6lznllFPMvHnzTJMmTZJ+BgG4aNGixN+IOyGEEEIIkWNhd9JJJxX4+5ZbbrFWvPfeey+lsEPI1ahRI0tnKIQQQghResibGLstW7aYJ554wqxfv966ZFOxbt06U6dOHVOrVi1r3fvkk0+yep5CCCGEEPlKTi12sGDBAivkNmzYYHbddVfz3HPPmcaNGyd9b8OGDc24ceNsXN6aNWvMHXfcYTp06GDFHW7dZGzcuNE+HGvXrs3YbxFCCCGEKNMWO8Ta/Pnzzfvvv28uuugi07t3b/Ppp58mfS8CsFevXqZly5amY8eO5tlnnzV77723GTNmTMrvHzp0qKlWrVrigaVPCCGEECKO5FzYVaxY0dSvX9+0bt3airAWLVqYu+66q0if3XHHHc0hhxxivvrqq5TvGTRokLXuucfSpUsjPHshhBBCiPwh58IuzNatWwu4TrcXl4crd9999035nkqVKiXKqbiHEEIIIUQcyWmMHda0448/3tSuXdv8+uuvZuLEiWb69Onm1Vdfta/jdq1Zs6a15MGNN95o2rVrZy18v/zyixk+fLj57rvvTN++fXP5M4QQQggh8oKcCruVK1da8bZs2TIb/0ZSBKKuc+fO9vUlS5aY8uX/Z1RcvXq16devn1m+fLnZfffdrft25syZKZMthBBCCCHKEjkVdg899FChr2O98xk5cqR9CCGEEEKIUhBjJ4QQQgghSoaEnRBCCCFETJCwE0IIIYSICRJ2QgghhBAxQcJOCCGEECImSNgJIYQQQsQECTshhBBCiJggYSeEEEIIERMk7IQQQgghYoKEnRBCCCFETJCwE0IIIYSICRJ2QgghhBAxQcJOCCGEECImSNgJIYQQQsQECTshhBBCiJggYSeEEEIIERMk7IQQQgghYoKEnRBCCCFETJCwE0IIIYSICRJ2QgghhBAxQcJOCCGEECImSNgJIYQQQsQECTshhBBCiJggYSeEEEIIERMk7IQQQgghYoKEnRBCCCFETMipsLv//vtN8+bNTdWqVe2jffv25pVXXin0M5MmTTKNGjUylStXNs2aNTMvv/xy1s5XCCGEECKfyamw23///c2wYcPMnDlzzOzZs80xxxxjTjnlFPPJJ58kff/MmTNNz549zfnnn2/mzZtnunfvbh8LFy7M+rkLIYQQQuQb5YIgCEwesccee5jhw4db8RamR48eZv369ebFF19MPNeuXTvTsmVLM3r06CJ9/9q1a021atXMmjVrrJVQCCEyRd1rXsrKcb4d1i0rxxHFQ/dfREVxtEvexNht2bLFPPHEE1a44ZJNxqxZs0ynTp0KPNe1a1f7vBBCCCFEWadCrk9gwYIFVsht2LDB7Lrrrua5554zjRs3Tvre5cuXm+rVqxd4jr95PhUbN260D1/1CiGEEELEkZxb7Bo2bGjmz59v3n//fXPRRReZ3r17m08//TSy7x86dKg1X7pHrVq1IvtuIYQQQoh8IufCrmLFiqZ+/fqmdevWVoS1aNHC3HXXXUnfW6NGDbNixYoCz/E3z6di0KBB1iftHkuXLo38NwghhBBC5AM5F3Zhtm7dWsB16oPLdtq0aQWemzp1asqYPKhUqVKinIp7CCGEEELEkZzG2GFNO/74403t2rXNr7/+aiZOnGimT59uXn31Vft6r169TM2aNa0lDy677DLTsWNHM2LECNOtWzebbEGZlLFjx+byZwghhBBC5AU5FXYrV6604m3ZsmU2/o1ixYi6zp0729eXLFliypf/n1GxQ4cOVvxdf/315tprrzUNGjQwkydPNk2bNs3hrxBCCCGEyA9yKuweeuihQl/HehfmzDPPtA8hhBBCCJHnMXZCCCGEEKJkSNgJIYQQQsQECTshhBBCiJggYSeEEEIIERMk7IQQQgghYoKEnRBCCCFETJCwE0IIIYSICRJ2QgghhBAxQcJOCCGEECImSNgJIYQQQsQECTshhBBCiJggYSeEEEIIERMk7IQQQgghYoKEnRBCCCFETJCwE0IIIYSICRJ2QgghhBAxQcJOCCGEECImSNgJIYQQQsQECTshhBBCiJggYSeEEEIIERMk7IQQQgghYoKEnRBCCCFETJCwE0IIIYSICRJ2QgghhBAxQcJOCCGEEKKsCrsJEyaYjRs3bvP8pk2b7GtCCCGEEKKUCLs+ffqYNWvWbPP8r7/+al8rDkOHDjVt2rQxVapUMfvss4/p3r27WbRoUaGfGT9+vClXrlyBR+XKlYv7M4QQQgghYkexhV0QBFZMhfn+++9NtWrVivVdb731lrn44ovNe++9Z6ZOnWo2b95sunTpYtavX1/o56pWrWqWLVuWeHz33XfF/RlCCCGEELGjQlHfeMghhyQsZMcee6ypUOF/H92yZYtZvHixOe6444p18ClTpmxjjcNyN2fOHPOHP/wh5ec4hxo1ahTrWEIIIYQQcafIwg43KcyfP9907drV7LrrronXKlasaOrWrWtOP/30tE7GuXj32GOPQt+3bt06U6dOHbN161bTqlUrc+utt5omTZqkdWwhhBBCiDIj7AYPHmz/j4Dr0aNH5HFtiLQBAwaYww8/3DRt2jTl+xo2bGjGjRtnmjdvboXgHXfcYTp06GA++eQTs//++2/zfhI9/GSPtWvXRnreQgghhBClTtg5evfunciCXblypRVkPrVr1y7RiRBrt3DhQvPOO+8U+r727dvbhwNRd/DBB5sxY8aYm266KWmCxpAhQ0p0TkIIIYQQsU6e+PLLL82RRx5pdtppJ+sOrVevnn1gyeP/JaF///7mxRdfNG+++WZSq1th7Ljjjjb+76uvvkr6+qBBg6xlzz2WLl1aonMUQgghhIidxe7cc8+1iRMIsX333TdphmxxMmwvueQS89xzz5np06eXSBiSuLFgwQJzwgknJH29UqVK9iGEEEIIEXeKLexIniBrtVGjRmkfHPfrxIkTzfPPP29r2S1fvtw+T9kULILQq1cvU7NmTetShRtvvNG0a9fO1K9f3/zyyy9m+PDhttxJ37590z4fIYQQQogyJewaN25sVq1aFcnB77//fvv/o446qsDzDz/8sLUMwpIlS0z58v/zGK9evdr069fPisDdd9/dtG7d2sycOdOelxBCCCFEWabYwu62224zV199tS0x0qxZMxvjFi4eXBxX7PbAReszcuRI+xBCCCGEEGkKu06dOtn/U6Q42Y4UxLwJIYQQQohSIOzIXBVCCCGEEDEQdh07dszMmQghhBBCiOwKuxkzZhT6emF7vAohhBBCiDwSduEMVvBr2SnGTgghhBCilOw8QbkR/8G2YlOmTDFt2rQxr732WmbOUgghhBBCRG+xo3hwmM6dO5uKFSuagQMH2uLFQgghhBCiFFjsUlG9enWzaNGiqL5OCCGEEEJk2mL38ccfb1O/btmyZWbYsGGmZcuWxf06IYQQQgiRK2GHeCNZIrxrBPu3jhs3LqrzEkIIIYQQmRZ2ixcvLvA3+7juvffepnLlysX9KiGEEEIIkUthV6dOnSiPL4QQQgghcpk88dZbb5mTTjrJ1K9f3z5OPvlk8/bbb0d1TkIIIYQQIhvC7tFHHzWdOnUyO++8s7n00kvtY6eddjLHHnusmThxYknOQQghhBBC5MIVe8stt5jbb7/dXH755YnnEHd33nmnuemmm8xZZ50VxXkJIYQQQohMW+y++eYb64YNgzs2nFghhBBCCCHyWNjVqlXLTJs2bZvnX3/9dfuaEEIIIYQoJa7YK664wrpe58+fbzp06GCfe/fdd8348ePNXXfdlYlzFEIIIYQQmRB2F110kalRo4YZMWKEeeqpp+xzBx98sHnyySfNKaecUtyvE0IIIYQQuRJ2cOqpp9qHEEIIIYQohTF2q1evNnfffbdZu3btNq+tWbMm5WtCCCGEECLPhN0999xjZsyYYapWrbrNa9WqVbMFihF3QgghhBAiz4XdM888Yy688MKUr19wwQXm6aefjuq8hBBCCCFEpoTd119/bRo0aJDydV7jPUIIIYQQIs+F3Q477GB+/PHHlK/zWvnyJdp6VgghhBBCRECRldghhxxiJk+enPL15557zr5HCCGEEELkubDr37+/rV1HEsWWLVsSz/NvkiZGjhxpLr744mIdfOjQoaZNmzamSpUqZp999jHdu3c3ixYt2u7nJk2aZBo1amQqV65smjVrZl5++eViHVcIIYQQokwLu9NPP91cffXVdteJPfbYw1rnePDvAQMGmIEDB5ozzjijWAd/6623rBh87733zNSpU83mzZtNly5dzPr161N+ZubMmaZnz57m/PPPN/PmzbNikMfChQuLdWwhhBBCiLhRLgiCoDgf+OCDD8xjjz1mvvrqK8NHDzroIHPWWWeZtm3bpn0yP/30k7XcIfj+8Ic/JH1Pjx49rPB78cUXE8+1a9fOtGzZ0owePXq7x6DWHuVZqL2XrHSLEEJERd1rXsrKcb4d1i0rxxHFQ/dfREVxtEuxd55AwEUh4pLBCQNWwFTMmjXLWgd9unbtmjL+b+PGjfbhUBFlIYQQQsSVEm0plgm2bt1qXbqHH364adq0acr3LV++3FSvXr3Ac/zN86ni+IYMGRL5+QohhMhvZDETZbEN5E19EmLtiJN74oknIv3eQYMGWUugeyxdujTS7xdCCCGEyBfywmJHxi0xc2xZtv/++xf63ho1apgVK1YUeI6/eT4ZlSpVsg8hhBBCiLiTU4sdyReIOmrgvfHGG6ZevXrb/Uz79u3NtGnTCjxHRi3PCyGEEEKUZSrk2v06ceJE8/zzz9tadi5OjsyPnXbayf67V69epmbNmjZWDi677DLTsWNHW1OvW7du1nU7e/ZsM3bs2Fz+FCGEEEKI0iHsqFdXrly5In3h3Llzi3zw+++/3/7/qKOOKvD8ww8/bM4991z77yVLlhTYqqxDhw5WDF5//fXm2muvtXvUkhFbWMKFEEIIIURZoEjCjgLAmaAoJfSmT5++zXNnnnmmfQghhBBCiGIKu8GDBxflbUIIIYQQIofkTbkTIYQQQgiRBYvd7rvvXuQYu59//jnNUxJCCCGEEBkTdqNGjSrRlwshhBBCiDwTdr179878mQghhBBCiNzVsduwYYPZtGlTgeeqVq2a3hkJIYQQQojsJE+sX7/e7haxzz77mF122cXG3/kPIYQQQghRSoTd1Vdfbbf/orgwe7A++OCDZsiQIWa//fYzEyZMyMxZCiGEEEKI6F2x//73v62AY7eIPn36mCOPPNLUr1/f1KlTxzz22GPm7LPPLu5XCiGEEEKIXFjsKGdywAEHJOLpXHmTI444wsyYMSOKcxJCCCGEENkQdoi6xYsX2383atTIPPXUUwlL3m677VaScxBCCCGEELkQdrhfP/roI/vva665xtx7772mcuXK5vLLLzdXXXVVFOckhBBCCCGyEWOHgHN06tTJfP7552bOnDk2zq558+YlOQchhBBCCJHrOnZA0gQPIYQQQghRSlyxlDhp3LixWbt27TavrVmzxjRp0sS8/fbbUZ+fEEIIIYSIWtixX2y/fv2S7ixRrVo1c8EFF5g777yzqF8nhBBCCCFyJexImDjuuONSvt6lSxcbayeEEEIIIfJc2K1YscLsuOOOKV+vUKGC+emnn6I6LyGEEEIIkSlhV7NmTbNw4cKUr3/88cdm3333Le7xhRBCCCFEtoXdCSecYP7+97+bDRs2bPPa77//bgYPHmxOPPHEqM5LCCGEEEJkqtzJ9ddfb5599llz0EEHmf79+5uGDRva56ljR5HiLVu2mOuuu664xxdCCCGEENkWdtWrVzczZ840F110kRk0aJAJgsA+X65cOdO1a1cr7niPEEIIIYQoBQWKKUT88ssvm9WrV5uvvvrKirsGDRqY3XffPXNnKIQQQgghMrfzBEKuTZs2JfmoEEIIIYTIdfKEEEIIIYTIbyTshBBCCCFiQk6F3YwZM8xJJ51k9ttvP5uEMXny5ELfP336dPu+8GP58uVZO2chhBBCiHwlp8Ju/fr1pkWLFjajtjgsWrTILFu2LPHYZ599MnaOQgghhBCxTp6IiuOPP94+igtCbrfddsvIOQkhhBBClFZKZYxdy5Yt7fZlnTt3Nu+++26h7924caNZu3ZtgYcQQgghRBwpVcIOMTd69GjzzDPP2EetWrXMUUcdZebOnZvyM0OHDjXVqlVLPPiMEEIIIUQcyakrtriwjZnbygw6dOhgvv76azNy5EjzyCOPJP0Mu2QMHDgw8TcWO4k7IYQQQsSRUiXsktG2bVvzzjvvpHy9UqVK9iGEEEIIEXdKlSs2GfPnz7cuWiGEEEKIsk5OLXbr1q2ze846Fi9ebIXaHnvsYWrXrm3dqD/88IOZMGGCfX3UqFGmXr16pkmTJmbDhg3mwQcfNG+88YZ57bXXcvgrhBBCCCHyg5wKu9mzZ5ujjz468beLhevdu7cZP368rVG3ZMmSxOubNm0yV1xxhRV7O++8s2nevLl5/fXXC3yHEEIIIURZJafCjozWIAhSvo6487n66qvtQwghhBBCxDDGTgghhBBC/H8k7IQQQgghYoKEnRBCCCFETJCwE0IIIYSICRJ2QgghhBAxQcJOCCGEECImSNgJIYQQQsQECTshhBBCiJggYSeEEEIIERMk7IQQQgghYoKEnRBCCCFETJCwE0IIIYSICRJ2QgghhBAxQcJOCCGEECImSNgJIYQQQsQECTshhBBCiJggYSeEEEIIERMk7IQQQgghYoKEnRBCCCFETJCwE0IIIYSICRJ2QgghhBAxQcJOCCGEECImSNgJIYQQQsQECTshhBBCiJggYSeEEEIIERMk7IQQQgghYkJOhd2MGTPMSSedZPbbbz9Trlw5M3ny5O1+Zvr06aZVq1amUqVKpn79+mb8+PFZOVchhBBCiHwnp8Ju/fr1pkWLFubee+8t0vsXL15sunXrZo4++mgzf/58M2DAANO3b1/z6quvZvxchRBCCCHynQq5PPjxxx9vH0Vl9OjRpl69embEiBH274MPPti88847ZuTIkaZr164ZPFMhhBBCiPynVMXYzZo1y3Tq1KnAcwg6nk/Fxo0bzdq1aws8hBBCCCHiSE4tdsVl+fLlpnr16gWe42/E2u+//2522mmnbT4zdOhQM2TIkCyepXDUvealrBzn22HdTD5S1n+/EEKI7FOqLHYlYdCgQWbNmjWJx9KlS3N9SkIIIYQQGaFUWexq1KhhVqxYUeA5/q5atWpSax2QPctDCCGEECLulCqLXfv27c20adMKPDd16lT7vBBCCCFEWSenwm7dunW2bAkPV86Efy9ZsiThRu3Vq1fi/RdeeKH55ptvzNVXX20+//xzc99995mnnnrKXH755Tn7DUIIIYQQ+UJOhd3s2bPNIYccYh8wcOBA++8bbrjB/r1s2bKEyANKnbz00kvWSkf9O8qePPjggyp1IoQQQgiR6xi7o446ygRBkPL1ZLtK8Jl58+Zl+MyEEEIIIUofpSrGTgghhBBCpEbCTgghhBAiJkjYCSGEEELEBAk7IYQQQoiYIGEnhBBCCBETJOyEEEIIIWKChJ0QQgghREyQsBNCCCGEiAkSdkIIIYQQMUHCTgghhBAiJkjYCSGEEELEBAk7IYQQQoiYIGEnhBBCCBETJOyEEEIIIWKChJ0QQgghREyQsBNCCCGEiAkSdkIIIYQQMUHCTgghhBAiJkjYCSGEEELEBAk7IYQQQoiYIGEnhBBCCBETJOyEEEIIIWKChJ0QQgghREyQsBNCCCGEiAkSdkIIIYQQMSEvhN29995r6tataypXrmwOO+ww88EHH6R87/jx4025cuUKPPicEEIIIURZJ+fC7sknnzQDBw40gwcPNnPnzjUtWrQwXbt2NStXrkz5mapVq5ply5YlHt99911Wz1kIIYQQIh/JubC78847Tb9+/UyfPn1M48aNzejRo83OO+9sxo0bl/IzWOlq1KiReFSvXj2r5yyEEEIIkY/kVNht2rTJzJkzx3Tq1Ol/J1S+vP171qxZKT+3bt06U6dOHVOrVi1zyimnmE8++SRLZyyEEEIIkb/kVNitWrXKbNmyZRuLG38vX7486WcaNmxorXnPP/+8efTRR83WrVtNhw4dzPfff5/0/Rs3bjRr164t8BBCCCGEiCM5d8UWl/bt25tevXqZli1bmo4dO5pnn33W7L333mbMmDFJ3z906FBTrVq1xAMrnxBCCCFEHMmpsNtrr73MDjvsYFasWFHgef4mdq4o7LjjjuaQQw4xX331VdLXBw0aZNasWZN4LF26NJJzF0IIIYTIN3Iq7CpWrGhat25tpk2blngO1yp/Y5krCrhyFyxYYPbdd9+kr1eqVMlm0foPIYQQQog4UiHXJ0Cpk969e5tDDz3UtG3b1owaNcqsX7/eZskCbteaNWtalyrceOONpl27dqZ+/frml19+McOHD7flTvr27ZvjXyKEEEIIUcaFXY8ePcxPP/1kbrjhBpswQezclClTEgkVS5YssZmyjtWrV9vyKLx39913txa/mTNn2lIpQgghhBBlmZwLO+jfv799JGP69OkF/h45cqR9CCGEEEKIUp4VK4QQQgghkiNhJ4QQQggREyTshBBCCCFigoSdEEIIIURMkLATQgghhIgJEnZCCCGEEDFBwk4IIYQQIiZI2AkhhBBCxAQJOyGEEEKImCBhJ4QQQggREyTshBBCCCFigoSdEEIIIURMkLATQgghhIgJEnZCCCGEEDFBwk4IIYQQIiZI2AkhhBBCxAQJOyGEEEKImCBhJ4QQQggREyTshBBCCCFigoSdEEIIIURMkLATQgghhIgJEnZCCCGEEDFBwk4IIYQQIiZI2AkhhBBCxAQJOyGEEEKImCBhJ4QQQggRE/JC2N17772mbt26pnLlyuawww4zH3zwQaHvnzRpkmnUqJF9f7NmzczLL7+ctXMVQgghhMhXci7snnzySTNw4EAzePBgM3fuXNOiRQvTtWtXs3LlyqTvnzlzpunZs6c5//zzzbx580z37t3tY+HChVk/dyGEEEKIfCLnwu7OO+80/fr1M3369DGNGzc2o0ePNjvvvLMZN25c0vffdddd5rjjjjNXXXWVOfjgg81NN91kWrVqZe65556sn7sQQgghRD6RU2G3adMmM2fOHNOpU6f/nVD58vbvWbNmJf0Mz/vvByx8qd4vhBBCCFFWqJDLg69atcps2bLFVK9evcDz/P35558n/czy5cuTvp/nk7Fx40b7cKxZs8b+f+3atRH8AlEYWzf+lpXj5Ou9LOu/X6gNlPXrn+vjCxObe+C+PwiC/BZ22WDo0KFmyJAh2zxfq1atnJyPiJ5qo0yZpqz/fqE2UNavf66PL0zW7sGvv/5qqlWrlr/Cbq+99jI77LCDWbFiRYHn+btGjRpJP8PzxXn/oEGDbHKGY+vWrebnn382e+65pylXrpzJJ1DkCM6lS5eaqlWr6vg6vo5fxs5Bx9fxy/Lx8+Ec1ubBNUgGljpE3X777bfd9+ZU2FWsWNG0bt3aTJs2zWa2OuHF3/3790/6mfbt29vXBwwYkHhu6tSp9vlkVKpUyT58dtttN5PP0Jhy2aB0fB2/LB8/H85Bx9fxy/Lx8+EcqubBNQizPUtd3rhisab17t3bHHrooaZt27Zm1KhRZv369TZLFnr16mVq1qxpXapw2WWXmY4dO5oRI0aYbt26mSeeeMLMnj3bjB07Nse/RAghhBAit+Rc2PXo0cP89NNP5oYbbrAJEC1btjRTpkxJJEgsWbLEZso6OnToYCZOnGiuv/56c+2115oGDRqYyZMnm6ZNm+bwVwghhBBC5J6cCzvA7ZrK9Tp9+vRtnjvzzDPtI27gMqZQc9h1rOPr+Dp+2TgHHV/HL8vHz4dzqJQH1yBdygVFyZ0VQgghhBB5T853nhBCCCGEENEgYSeEEEIIERMk7IQQQgghYoKEnRBCCBFzFE5fdpCwyzBvvPFGzo59xhln2LIwZb1Dl/XfL4Qo2zAGstOSxsKygYRdBlm4cKHp1KlTgS3Nskm7du3MsGHDzPDhw8tsh3YDWlmF319W730+oXsgctUWLrzwQtOsWTO7q1NZFHdBGfu9IGGXQRo2bGjGjx9vxowZY6688sqsHnvLli32mPfcc4/dL5edOjZv3pzVc2AgySWzZs0yH330kf33BRdcYO6+++68+P3ZHGhYXDhhe99999nt98rioOqfR7bPyV9cUIxd5McYlK3xybW3L774wmzcuDHrC80///nP5vfff7dGBuaFbIu7L7/8MvHv0aNHm1WrVmXt2Fv/T8zm01iUFahjJzLL448/HlSqVCm48cYbs3K8//73v4l/f/nll8GFF14YlC9fPvjnP/8ZbNmyJSvn4B/nhRdeCMaMGROMGzcu+OyzzzJ+7K1btwbLly8PatSoEZxzzjlBr169gp133jmYP39+kC383//dd98FX3zxRcrXMwXXmnZ3yy23BH/729+CXXfd1baHbOH/xvXr19t2uWnTpm1eywb/+c9/gl9//TXYvHlzoo1kA/84f/nLX4LDDz88WLt2bZBrsvX7U93nbNx//xjjx48PBg0aFAwYMCB49tlng2xf58mTJwd169YNRo4cmegDmeadd95J/PuDDz6wx+/YsWNifshGG5g1a1bQqlUre/0vu+yyoFy5csFXX30VZJuRI0cGp512mh0HX3/99SDuSNhleFCZOnVqMHjwYNupaNTXXXdd1s7hqquuCpo0aRL8+c9/Dg4++GAr7m677basDepw9dVXB/vtt19w0kknBc2aNQvatm1rO3k2mDdvXrDnnnsGO+64Y/Dkk08mns/27z/ooIOswOrSpUswbNiwrJ3Hzz//HIwePTqoXLlyULVq1WDp0qX2eSdusjWpDh8+3A6q7du3Dy699NJg0aJFQTbhmh911FHBoYceav//9ddfZ/yY4XvLQqNr167BW2+9FeSCjz76yC4w6QcLFy5Meo5R43//gw8+aMfBe+65J/jll1+yKu4ZB6tXr25F3emnnx4ceOCBwRVXXBFki+effz7Yaaedgvvuuy9rCyvGWOabJ554IqfijkUMi2vmgCpVqgRz5szZxviQaW677bZg7733Ds4999ygTZs2QevWrbM2B+UKCbsM8uKLL9oOzcRGp+7fv3+www47BFdeeWXGj/3vf//bWmhYMdGJmORvv/12K+74fzY61qOPPhrUrFnTDiiAyEDgMNBlEgYrft/s2bODBg0a2HPo3bu3/duRqUnFv65YKDn2pEmTgpdeeik4//zzrbhggskWDOwM8LQFLHfJzjOTXHPNNcFee+0VPPTQQ7YPIO4bN25srWfZgIUUg/ojjzxiLRgHHHCAXeT89NNPGTsmFlqfu+66y953Fjdr1qwJss3TTz9t2+Fhhx0WHHvssXaCxYKULa6//nrbBtq1a2fvPf9fuXJlxvqh/52vvPKKFTPvv/++/Rthy0KHsSkbcL+55jfffLP9e8OGDfa3I3QZj1avXp2xYzPP8FtzJe7c99977712Ydm8eXM7Jm7cuDGjY/CW0PeyuJ42bZr994IFC4K//vWvQcOGDYOHH344J4v9bCBhFxEIJx+sImeddZadzB3r1q2zHRpxd+2112b0fJjI6EgMJD6smjn+/fffn3HLDQM6ggqeeuop27k5rnPNRb16TTVQvPvuu3Yw69mzZ2LFGDXh64y5/4YbbrAWCgeDOKvHQw45pIAFMZPXABfkxx9/bEVVtWrV7Dlli08++SRo0aJF8Pbbb9u/EbeIirFjxxYYTDM1qGKhxEI8ZcqUxGJnt912s9fCJ8rjYwnCKui+l3ZBm69Xr55dZDiyYTUF2jtWaxZVbmJH6DPZZQq/DfI7GQPmzp1rJ3om2COOOMIKvKjFHaEmzirtvvOBBx5I3A8WWLQ/NwYxHru2mSmw1HLfOQ9EHq7AI4880i606tSpE0yYMCGjfYD2WLFixayKu/D9xFpMGAwhMYh6hF6m2r9/7Ndffz2YOXNm0Llz5wJu6U8//dSKu0aNGsXWcidhFwGsQvbdd98CcVTEUTCAYYb2wVJx3nnn2cE1k+4AJjEEnItpcx0YC16FChXs8RF/mcAda+DAgXalSudiIHMDKp0PC87dd98d/P7775F3aKwRDPIjRowIfvjhB/vc9OnT7eTK4OJW7wz4CO10Ofvss6111p0HkwvXl0dYwCNoO3ToEFxwwQVB1PjXgIGUSd3F8yDwuB6IOz/W8+9//7u9NlEfHxhMa9WqZScN7onfBrgO//rXvxJuuUzAhIK1jvb48ssv2+M7gUM/xJLmrAdRsWLFisQ1X7VqVeLa81sRFW6hk2mrqZuomdC7d+9u//3tt9/a+8Gk5nD9Iyr8NoCwJxzimGOOCT7//PPEebHQYmwkTMRZTtMVFtxfQh5wt/3444+J57HKEIri7r9rf0CsHULLCcwo4be7tkVsGZ6KPfbYw94L1wZxzf/pT38KMk0qccd4yL2Jsh2GxyAWlVwLt7BlPkTcuWsALDbpI+nit6Err7wy2GWXXaylmmt/5513Fngv8+Ill1wS7L777nbBGTck7CIazFu2bGmtE74ViomDwQsx5YNrFncQYpAVXVQdyZ+kWB0ycBx//PEFEhY4P1zCuGeiWjWlWnFPnDgxIXCw2DmYVFlFEfsSNXwn7rajjz7axrQhbt988037GvFNmOBxSeESZCUdxcSOgHWTufu+Dz/80FqHGMTcpOYPtNybqEWFg8kKQUNcEb/RCVlEFAMcA96ZZ54ZdOrUyV6rKAb23377LfFvN1ASS8d9RsAjavzBnD6BIM5kQgvWMto/EyuTurMUulU77cO1jaghno127yY1rj0ig/vSr1+/jIs7N8lxzbkH/F5EHQkcfvzv5Zdfvo23Iao2yKSJ14D/Y7Hzzw1xh8UIF21U7kis41jDEM9OsCIs3ELWd73RXumDeFSitpYtXrzYxnEhYty4QPgJYyBt0o27HJuwjKjaQGGWT8aoZOKOUKGLL744kuP715EQCCxizHPcfxJX+O3MS1wXxuC+ffva/ongjbIffPPNN3YuxtXNopU2jkva7/+ubbDYzWa8X7aQsIuoMzE4MYkjGFxwOJMXAoMVoy/u6GS45HAFRNWRmDxZrRKc7oKjsdoR38F5kZmKG+S4446zD0e64i5s+n7mmWfsoO1+GysnVkycC5YsJhgGVDKlojbHY4FEzLhYOlbkDOiIWH8wozPfdNNNieOX9DzCma5MomT/ujiq9957z/52RBSWC+4XwcS4B7HaRoV/D3A71q9fP3j11VetxQwLAa641157zb7OfWGCoQ306dMnkixVJi1EEjBRIRadJeYPf/iDvQd+fB+TKgP6KaecEnmcza233ppwc2MV5DcyqPtWKo5/wgkn2Eem4nywjtHOWbzR5n1xR7Z2Jiy2DtodlnLa2xtvvGFFBoLSDwsBxgrCE6LI0vXHItoebRArNr+XTGDcjt9//32B9yOqL7roorQnVv8eMg5yPCzzS5YsSSww6YeICyZ6jovYRXRmIkuadsf1J1mI+xxewHEdCFNh4eeEf7qEx2H6pPMiOBA4YXFH24xa2DC3Ididm5uFFQtsNy47l/Spp55qk1mizJRnnPnzn/9cQKwi8vGc+GEgYeIm7iTs0sQ1RsTUc889ZycxVo0upRuhg7kbN8HJJ58cnHjiidYdlm6H9gciGjMWCSwB++yzj838IZ4EGNiJ9WPVygqKwcZ1pHQHM//zDBocmwkEqxjB4kzuTBqUW2FAwSyOZZOVujuHKDsUYs25t/n9XBOElptUneDyz7ukx0dEEwzvx+xhAeM+IzDdZInIRVgwwSMkEFpcGzfYRzmh4FbGSuxn3gLCklUxFppkpCuwWfkySbE6J46Svx1c86ZNm9r7Tjul7AD9AUt21KVPsIxyjemDuN5g2bJltj/SJ7Dk/OMf/7BikwVYVMdP9XmEBedDn/DFnctYZAKMGs4FEUsbc2Cl43i4g/EQcE2YWJl8oxIW/uKG5KyhQ4cm2jdeAu4BcV2+uPMpaT90/cdvw/QBJ+6cW5ZrTh8kOxOhyzgc1RiUrA+zeMAzQ7tjXHbHQlSSIY7wZbEXBf7xEa9unGXcQcz7XiSMCpR+InzIJ6pxmO8544wzbEwhsKjGYufiWl3oDdeDMTDZ/SspfAdhJuXLl7eufh/EHVZExinGoLgjYRcBWIaY0HADMtnj8mDicmUVWKnQ0BF2rFDJzIkKJgxcWm51hLmbQQtTN5YL13GwLjHRuEko3Y7kDyaIRxICsEoycGMdcgO5i53AUoaw4P9RnEOyyRQXM5M3K1VWZ36QPAG7TGZR1JAiRg6rC5MnkwcWEscf//hHe++ZRJ244zdzPog+LKfu3KN0xXLfGcyZwJNZgxB3CG+ujT+IRyUse/ToYY/ti3b3O3H1YRniumFBpg+kay1Nln1Lm0c4I6RYyLjFDYM6gg5ByaTK5BbV8f12iPudhy/2sVJjnfTFHdcDd3WmrAT8XoT8HXfckXiOyZYFF+MU9wGrqu8ejQLuOwtH2gEWab9tsdBFUFNqJJw1HNUY4F9PLHeci++W5f+If6ypUQoKYOwjMS1sueMesIhgbOL8sJgzLuMujBoWdIhXNx4hcLkX9H1f3CH26KdREB4/8Fwx/zEnMCf5cY2MUcyRfnWCZN+RzhzAwmnUqFH2d/N/H0Q+94EFeNyyYMNI2KUJgbesvpyric6LKxahwwTvF2PktagtNFhDcGv6tbnoXIg7XLCk9YfFTJTuJyZPTN9YsHwYQBlYGVSSCZh0zsH/LKteF/yMxRSxxUqV5AnfatStW7dIMgEZvInfcG5PBCwDpe9qx70QFncMtlgtEeFYTKK0lvr3nd/Jit3FrvnvQ1QhMjK1uGHCwiKClcoJen/i5L75sXhRTapYSLFCcA+YOBFQWKlw/zg3fLL2FqWlBtcaooWYRsSTH7vDYodrwmLAt2ZGcQ5h3PdhnWAM8C1ktEHckjNmzIgkaSJZGyR+lvbPIsKVOXIwRmHV5fUo4Vrj1mOs8YPkWcw5ceeyZTMxDtKOCUGgz+M1CL9GTBkLOz/0IWq4nywyXRgCniIsZbQD2iPXxo/1jeK3+9/BGOz+ZuGExYxx2LcM8h5Ck8JZ6ekemzYejmO+9dZbrbhD4PvgRcp0Nn4+IGGXJqwCsEwRV+I3FhIWWD0xmbqVetSw8iRei0mNATu8ciGGycVbRYXfoRikmDwIxsdaEgaXDHEsUWY++sdnMsVKhduN686kQpYZ1ghiKXA7IXAQM35MXzodmkGLYwKuNK4/vx1x61vumLwQ3YgO9/sRHqxgseqmckkV9xpg/SBY27mcsBLghkJkJCtEG/WAHgahTZwjQsYPig9nYEc5qDKZYo0LJzQhoilO7cqdZGog5/j8ZpJzuP7ErjGp0D59cUdbQXhHDe49FjL+AgqrORM7sa2ZwG8DtD8WsK5NMy5wP7DchN2NCJAoY+qGDBlihQtCHmHD/UbkuYUF1wVLId4Sl6WcCWhvxBNzj7EO+yBkGAs4Bz9jN0pYMCHm6HOunAkWOzcO0x6JK/QFblSLa+IJscJjrQZi+Chng2XMzwxnHEbwRb2gQlDjYmWu4bf+5//uPeIOtywCv7DviCMSdhHAKt0PznaxBKxO6FC4PtJdqaVyOzCYYqVi8ArHUOHywUqVCZcPlhAsYRwDtwvWCGJK/HpuTCpcm6hcLz6sRDkmos5PleeccIcysGAhY6ClrEm68TRuIMC9gNWBgZrBhIEUqyX3ICzuWCUTx0SRVHdcrCWIgJJaTPwBiVIltC2sIwgGZy3ASkh7QNQni6GKakAnbolzwPXrW4wpM8KihoGdRQWJGtyHqBMViJVBvBJHiesxXDrDxbzils2UuGMBx7V3geqUdaFdYCXCYsj1cYLLt2pEAb8FCyWTG7+T64yocAsY+j6eg6iLMYfbIJ4BXM1M3G5nHcY/hARJE8kyn6MYk3DpEdvrZza73WYQ9Q7i/Yjzjerau9+PO5V275I0EHcs/Fjo+W5Z4t7w6GQi+9jHjXEciwW3iylG4HE9SOaJug/Sxhh/MCzgiXBgOWUBTEkV5kHGRxbXUcZW43rmXpMMxrjLOERbHDBggF1Mc5+cqPUT6MoCEnYl6NCYfVmduAGFVSEDKC4BHzJziDXAspYOfmekAzFo0KEQCcAqjIBgOlCqAPkoU+pdnTZX3JEBiwQNJm8GeiYSYvqY2DmnTEymxAu5shp0Yu4JK2MX34TgRVgibKKKK3QwQLqJ1PHYY48lFXdMdO7au/9HUbsPSwViBssMMZtYKjknF7/JoE4cDRbCTMTzEK+I2xXLJPeZwR2LARYrIBwByymraH9hE1VbIEifY2IFRUgyoJN95wtm+iiDPfWqEBhRXIfwxIhY41wQWPRH3OCuKDWuN+4J5+V/LhOZuCyeEDlMpljKcEEhfLESpRoT0oVAdSZWsjDpf7gc+b1OyNEWyJZmgRXOIE8XhDQLOx4uVtD1b+4DbkB/hxvX7qK69rR1FmgsnljEuLGIsY+xmXANFpfENuJRifr3J8P9RhYVLOxY4LmYa7/cVFTXgPALxgD6n8ON/cDYS4whYyAuWTf+lWQc9kt28T1ufAvH0SH2mjVrZu8P4MUhHClbBcHzBQm7IuJbATBzY7VxNYBwweB+oTMzmFPDihUig55bzUUBpn4mKAYLYtr82kyILYQFk2w4zT0TcC6Y1Z1pH3HHwM412X///a07hEB1J2KinMwQLwg7ShfwwA1AZ2ZS9Tu1T1THxzrIQMmkxsDtFxhF3JEFx71xotsRZcICgyf32bnZsAgSw+My0ZzVlMEvinISYbCQcY/dhMo9oC1inWTh4UrdcB4MyFELa4Qzrjc//IABHQGJOw5Bx6SCJY17QdkXJmFntSspfhsiGJ3Fg2+hJjCbPuDaPOIXlySTbNSLG8QTExaTq7PKYhlkMsdqxKIDgcd9Cce/RgEuNkSb25osVRvERYiwjboNUvSce4011i0wucY8ENvhLaPc6yXFfTdw32n/CHr6IHMALj+3iwQLTcZgPBnMAy4kIlvQ3rkuLKpI2MK7kAlhw3hHjDH3mH6OS5a5kWOSxOTH0zpK0g4Ya5nbqDDgoH1hGXXF1v3fd/TRR9swpDBlSdxJ2BUD3Eq4WZjYGERxA7osRKx3xHWxYmbCx4IXVTo7MICyOnIByawQOba/5yEiksEcC0VUhAdD1zH57YhbBlgHAxqTCOKK+DNnpQlvt5UunAPXmfItxNQwoTLAEr/CsaMIzt3e8bku7J7BOZDx6UBsIL793R2iBnGJNYzJnQkknHmGtSYcuB7VxIpo4966HTtY6BDjRAwd9x5xRwB3eE/UqIQ14gz3PkItvIDBco77j37Be1hocZ8QIUw2br/IdPsBgo37zm/FauAsdEwozgVI22dy8avaRyXucP1zbGKLiKVkMeVEhYOJlnvCNYiiCHT4/rGQ4xrjDg23QcZG2mC4MHtJ22CqtoN1noUVIst3tSEouC6u1FE6hENosH6SFOUnYiEYqJOG6z0cS5ptMeGuFf0fFzALHncOUYtrDBgsprHaM+/grcDti6BmfPI9F+m2d9z8PFz1B34nC2zfG+B++7XXXmsNC3GPoysMCbsiwkSFlQAXGODWYfCgUTOxMcA4Vw+r5qg3OWfycNuTJavR5tLZSRjIREwdE1R45cmKncksPOBT+oIOh9CNencF363piiH7cNxkwbKZAJGDi4FJHle0A/doJqvJc41xB1MfiwB5f5skXKC433w3VDokGxyZNLBa4HJhEePcIQzkbqcRVxA5E2CRohYkFpvwrgW0NxYbZJ+6a0dtQ87TjwEq6T1gMsP9x0ILSxHlG7CO0NYRnfx2kmOwlrDIiLoALm4vXPBYxhhnSFwgxo5z4NzCRJGF6XsdmLix1Loi03gowm2QdsE1wJqYLv5143pzfH8HE6yzCAragxMytH+EfLqiCvGGxc3B93Es7rHbf9Z/DUGBC5gFX6YoSjtKNmZkSmByL4hpw8DgwiBok27nhyiNKsy1tDlnTCD8gHAMPFiMA25Xj8MPP7zAfSuLSNgVESYM4hTI/sJigkXOVXJ3W2cx2fpB5FHCgIZrCWtIuEYbnYrtWfwkgijFHXGCCCYsAwhbZynBBU05AbfXqJtEEB4MgEym4UKYURD+bQgsVy8MS142V8kcmxUq1hPuf2HnWVz8AZpB018suBpViH33PhYfZKNGtf9jeLs6Fz/noB0Q2+kWFbiAiKchWD0T98CPTURQIZxw/yQrPA20SwZ4hEcU1nOs8vQzv6QG4gpLIXFUZAOy6MJq59fKi7Ivcs0Ze8IWUUQN4iYcR5iuoEQ40c6wduJSJbzElXCib/MaCzn3W1lk0gZZ8EX5uxFN/D5cclgr/fhWZ7ljsctxuQ9RBOkzvjlrp+sLLA64DsQNOguwXxOP1zi/8P0pKSW1dEdhIS+s7fjf764xz9EfmKewZEdZ+Ju+x0KW9kelCSfuXJiFK75PrG3jxo3LlNs1GRJ2JZhYMLfTiFx8GStlVnC44NLNAE3VGYjZYkBnRegXHkVY0JHIyo3KKsCA5X4HQg7XA8ICAcPAiaWSzFMGUEzu/nZRrpPj/mISZPWWabBmknFFLFMmdrTYHtwDzgGXbCYC40lIwe3FoOVnXztLDbGMuB6i3FHB/yxJQUzWJMewmHHtnnaBoGFwZUGDa8QvjhzV4Mq1xSLKgO62ygIsBQhL2l8ycYeY4z1RlBtiQqfds6jiHHxYUBFT5EIgfCt11BMMrm9cfu4euHaONR13WDruZh+/LAfxtIgmfrurw+euM255zsftqkMbxFqZbj/02x/WQawyWAoRjgiu2rVrF7CaIUBpm1iKXNwf1z6KMRFrEdZhFzNGjCt/0/ZdLK07Dr/X1dVMF/8aEPqAaEREY40vrF35vxkBVJI2WNxkE64N5UXcdpFR7ipDUhB9j3bIQpZkFbxFTtzRJhgDwovKzWVY3EnYlQDipwhIdenrVL0npiTKkia4MRBSiEgXjE4pA9xA/J9BjgmVjsRgFpXLhwmDgFjM2QgzVuS+CxZXLxMmgyrijtdZSftV7P0VXDbg+hBjlE7WVRSiP+rMO0A8M2EjohjYuNd+zTbaBwMfkxoCLOpBDUsQbQ4rFe5VN4k76yFWUp5jUYO1NOoCrC77FhHL5EZ7IyTCgXBDcPK+ZHsvRxkKgBuUCYaJK7xrA9fftyJlChZYLCqxRPq1ECm1QcKA20otHRDQtClfWHPdWVQmS0BBbOK25L5gSU63Dfr9hwUDLj2EnROz9DPi92hzfijI+++/bzNCWdy4Qr1RgFjm93OPnbhj4YpXwi1s3HllAqzTxBGyaKKdcy4ImGTZ9f454NXhveGi2NuD4+CBcPehqOMZ8xVzYZRjEGEfxPEh5h1YxbnvxNOG4zjjuvdrcZGwKwEM6mwqjfhhECTGzk/5Lgl+hyQmiNUxEyXHYSB3GZAMoGQD0WGx4CDsorZSUb6AVRHHdhNFeIKk0+ICYaWE68EFkEdlJSrK85BvAbLpnk/4tyLsXCwlMSS44nA7+BNaWExF1Q7IPsatQXtw7hAmsvBG2lhIsGpELayJ2aOchAuY5v8ky4RjmLCehLewyhT0c8Q1x3TuXdxPhCrgKooarBK4PP0MYMqYMCYgNIhnQ+DhqmQBkE7hawff6RKe6Pe0SUo24V5G3CHkttcvo2iDjHWIekQGcYX+Vm3ca4QcQpvXHdwTYrEYG1l8RNUmCEehEDvC0Rd3rqRNKoGRLiymsE66ZChiijleOEkD/N9K7BshCG5bveKAUMUT47vTizsGRzUGcc/5HeFYavoDbRHLXVRW6jghYZfGgItZmFT3KNPZCVRG0OFaYADBrI9VhInDxbLxnAtgj7KUhOugrJCZvIhnoXO7uEHXWcMd+YYbbrCDT7L09uIe2wkFLJZ+/a1UA7T/PLFeyaw2pQX/txAcT8Fnrj8B4Q4mWsSdq+weJeHBm0EVEenuiZ/5iPsjWbB+lCtlrENM0EDWI8d3gfMES/sDujv3bIg7FnZcfyyZuB9xhRMm4RY/UZ0DizmELCV0mMyxlDrhRlwf5YZ4HtcnFh1f+ETRBnCz4lr1w0sY74i1Zc9j36JUXKvQ9o5NYhThB5TUwBJEMgRi1q9TyHXGFYqQ8xc3iO+S7vDg7h1xhIg1P66UBU5Y3DEWYz3166ylQ7j/IGBoY4AV0u+D9AFXM87/HH0EY0Nxi/I6yyO43SuIlSuKuPOP78d6F4dk/Ya5FUu0E7L+e+hzCFA8GaIgEnZpQEOPciIhRoFsMnYsYOBw342bBWGXap/PqF2erHSZuJlYXR2ucFKI2wPVDaSI0SgSR3A1YK1kIGdwQjQ6wtfa/5uJjgkw2Z6QpQH/HhIrwgCOi5EJm2vrC1YmMSypWDGon5iJmD6shLjdObbbb9LPRmTgR1hEISYKWzzhVsMNzPH9zEssGbRNsoAd2XL9O2smVfUJW/DPKwpXtKuZhlWQ+8BYwARHBiATrRNa9FOuA9aMKPZ+DcO9xWrPeOQnZVBeiNhO3G60AcoeRRn+wIKBOEYskw6Oj/UWL0mq3xpVGACiEi8E1kLcvVjNXfa1E3e+WzaqdueXhXK7hbjC5yTI0Qf8pDmuE7Gd/lZpVARgXCiuqCPjmEUCv7W44s4fhwmXIDzCnx+Kgv+9zD2+kcCVUULE+3Mi7ZLzzma/Ly1I2OUJNE7iU3B1sVJ1HcMNVrihyMRigM+m+5FAXdzNWI7c4M6E49fPIw6L8y5J0LC/ITOrbGL3yERjxYwLit+MazrZ+x0IDuL8klmQShsE6RO7iEuJiRtxQ3tA2PsDvyvrEXX2KxMCkxntjckM6wQi0xeQrpo9k0rUgyqFbplcaOccH2sYFiLamIPYIhZABJLnclDnHhEWgQvWZQZHAYKaiQv3qh/igTUfcUcfyfROBq5dIWC5/9xrX9wRZ8y4QMJQlKEgfBe/EZER3qaRRCz6AgvNKAu/O2hL9D8WiAgkrHB4ZRDwCCoXU+1i7sLnlw4IdFf7EgsgApZ+xn1m7MVyS1ydA+GDBRfR48ZCl8Hs7zJRHLB84d4sjrjzx2EWIZynS14pCWyL6HZRYoHp4LciWDlHkgd5nUVVceMAywoSdjkiWUNEzBE/ROfwJzLADUs8SabKqYTxOyzijkBV0spZoWNF8lfoWCzcBtAlvQasOpkoWQk76xSDPAISq4Fvbk/mdki220Rpg9/Cnpu4nNwkyn3AcsKExmCfLBkgKvcnExaTCi5gB+KRe46wZKDFeoaljOShKDPfAAsQ1hB+K30AYY8bDssliQn0DVboxNX4NeJyOajjluX8KLcRhTsOYY21msnU31XBgUWa/kcCh2+tzASuXeFmdeLOH3/8GoJRWOzcfUS0YKVivENY+PcXcYdFP8o6ZX5GK2KK7FO/XAnHwuWHuHO/mfE4Kvcrvw+RiHUc0YqA8b8bbwRxhCRrkESAG5z+gAveT5rjkWxv6OLAIprFdFHEXXhxXZJx2L+3iGnKmRACwDVH4Pt7/rLQwWtF26cKQNTjT5yQsMsBfkOkAxPT5nYzcA2cTENM2sQ9YL2gQRNvlM1G7HdczpENlXGVRp15SYd1BV2J6fLdqU7cYREkS9enpLEk+QouNixACNnwzhEu3g3RE9V1962ftDFcXQgrf6UMtEFEF5MbZU/IfoyyDXB8JmwEJEKSGB3aGsKGvkC8IfeeXV+wVjHY56KsTSq4V0x6JY3rclCWBVFH1jtZ3ggbJnp/k3vXTnhfuntQF1fc0deIZwsLypJ6EAoby1jc0daZxGn7/jGwqkV934lnxCrE8VhYhb0PCA1ivcg8x1UYBQhIEkAcLNywuFE2J3xNWVCRKMeCh/NDZLs+EHUVgFTiDstlshqZzmOSzjhMG8eN6wqrI+5J/EDE+8Xf8WLQNvzagWJbJOxyCCKJ7FM6BYP44MGDE/EjrA5xQdHRKT3A9kTOFZcrceeTTofyBwasMiReMGAiKBBwuLb8GAsGMDIxmdTd+TDo4DYorZa6VPeQ+09gPhNMuCYiwdy4H6N2v7p7yaCKJY5j+1vFOcLJMVENqgg5XE6IR/+3MZkh7oi1YkDHFea/nk+DerLSE8UBlyclXfwyI66CPxbKsLjLpqD13bKMR2FvQrrtj7GOpAzc+1ikXHyZE3e45rDmp9reMF0QVwgm9lXGxUcWJuIGd7gPblkC9sO7nZQEhBKxiq4NM8YhHlm0sLjDJRkWkFyzzz//3FoToxA2hc0jZEAnE3duf3QHVnSsuemIOowG9HPGfr9cD/Md38v86HZdyueKCPmEhF0W8TsSqxFcKpjVWamT2o9FDmuIG1BwQ9HY/QSCdOtylbR0SBRiMrxnLIHIDGD+Ppd0bAYPBjlfSIQHcSxMmdy2KpP415LSEWS9UgfRTd6IOwLScUelKnidzqTmH594FSYxN1kRH8NEykDqbwkUPl5UgyrWWmKaGLyx2jJx+SDqXKC+v/NGnAZ1Mi8JdWCCDO9eguuT64KllJIymfj9Rfkud/85nygFNfeVEA9ckbizcb/RJl0MHeIOSzVjZSZcz3hMSFrzww9ok/Q9hLYTmY6SbktX2HUn49Mv54Hgow+GxV24lE1UpaUYh1nUhfdeZpERFnfMVb47FgGY7vaFXGPGP9ywvmh08x0VElhQZHL/7bghYZcDSGHHQkUsgQ+xFFhMnNBhUCN+Dbesv7tDFJ2ZAFtqz5F9RqJCUSuZuxVjcSHI2g0cnAfuVrevaPg6IO4QtHTy8DZWnEtcYiooE0HtMRIBiBnBUoCYd4M4cTWs3sPbREV5fDL/EE9+MDqLDiY2Ynqi3O8xDMkuWKxp94QdcM+JpQy7GGn7xPjFScwl61dY5XF3hWuUIaZoJySShPtDSUjVf7Z3ff2sU74j3X5I/CCJOq7YMxYhxgPaJOOSEzLEHkdlqfZ/J20e9z/CkvHYB6sklmu8KGHLXbr4Yy0LN9o23ghfuOOOJXYTcUn/xwXKOBEF/n3md1IAmPg+PCDEOPuJQAg3+mV4a0jXForbJ1O1GVzfjAO4XvFkhQ0CxDTmk4U+35GwyzIMUgxcDGDhmDEgdoJsH3/FQrYR7/dXlelO6EyoDJbEtSEmcXUm66ThkiJYD0qybRpuVueuclZHEi6w1OBqCosXsiOj/M35gD8xIZ4YUF1hU+JLsEyxw4QDyx2B1G5P4ih56aWXbBvwXa7+vcYFgqhku7qwFS0KGKix0vi/l3g6LDMM7GFxlywburRDwpBzMTsBRywt2aa+lcS5ZaNInApbi+lfo0aNSgj4otSLxCWb7rGB2EksNe5cGAsQtZTXIc4US3b4N5dE3CWr9emSDFjU4O5F4IXrrzFmIbRZWGRiMUk7J36VsY74PupS+uLO7TRDn8CqHeUuKsD1ZQygELi//zRlRHxxx/hDDGm6+NeQRb5LjnK/C8sdcwxjHpbcZEjcFQ0JuwyTbEBgpcgqjUEjnMXEQMvqzY/ZoeHTCaLY8xJrIYLCbW6N643O7BccdYSzngheL25JEQYvZ4VykzdC1Vn9EBYM4sSWhEsYIHri0JF98eJ+D5OFCwomTpCVqtthAvHvJk8Gu0zEU2EJJjCf9pmq8DTnzaAe9aTm9l3F9Yio8MGKzESGOyw8qcdJ1BGsT7A8ViGSVpyVDus5GY+Iu5KWrSjq4o5MR1y/bmvAVNuR+deddkNNMc4zne0SscbR30k4YaGIgCGmEngOkUcij/NepHvvOV8EC3BdGctc5iniEuHEQjucNIE7NCqLuf8bqBFKXJ9bWFGMnUVUWNxhxSTkJOpdXVg0UrbKbb3GGITHwNWs5Fr5C7p0xwD/tzMnMPdhJOC6Yy10otq5ZakOQMyjKBkSdhnE7wx0XFalLh4BVyTWMoJxCd5l1c7qncEel0umINvQpZAj8vyil7h5nKUkWSp7cQNkidtCpCIgsEgB7iYmdSYyV6uP+BLEHXFdyepTlWZxx4BJ7AgTqQ+uH2JYaBN+NXk38RBX6QdpRy3uWECwWndxa75VA2tessDtKKE+G5mdxJaFdy2gPRJ+4F+TOMH1JY6UNsBvJ6YKYeW2TiORhEQC3OGIoKhhMufeu4xMss45vr8AcSSrF1nccSDs+sNjgWXGWWpYwJEw5EomuWuCyI+q3bOAdkW/+a3hMjKIShbbLGRKUo+zONeAhAOOxzXwceKOPuHvupOJMYD4ZcYmxhhXzgSLnZsjuEach1+hIIoxgN9N23NZ//RxjkUcpUscxJJNzT4WOHFazGUTCbsM4TdIzMpYyRBxxDFQ9JUOg4hhpcrKlJU7rlEG86i3JvIHBQrNshKihAADnV/JnE5Gp/aTHEoq6vwK4WzgjSnf7VtIUU06MhOJL+6I5SBIPOqYllzCb8Hlgbvbr8VHRXmuP8HJvoBBaGFF8bMjMwE16yjfwEDru6CI60SI+7tMZAqsxvQJsqDD2/Ix6eRDKZNMQOyiyyzFWoUr0O0z6/oN14N+U5Kwh1S47yZZwB2P60w7dPv/YknH7RueyKMoLUTwO9Y+JnV/ZwKShohzYzxA3CFqicl1RNUOnGDBQpSsBhp9gbaPBdPfzSFKuK8ISM6Dsjbgu1gRdLhl6ReZjG8Fdw3wHnDNnRcFgcfin3EoXTEX3lGCxbubB7Ba06aGDBli5z9iiinO7d4bx/CLbCFhl2FIDPBXx5iZ6dRY5RB2PLBq0cD9eKd0t8dJ1SGxCuD24xwQF/4Kjvgeais5GMRLWlLEH4z5XQg7Mr2cxZLJLSzuGOC5FnFJjnADEu4FVqBYJfxdNMiE5j5gMSGAHCsW8YYM6n7h0UzB5I47BNcIQh9xzSqZ+5QtKym/m0Gdc0lWXDVO4g7rLFYoFm+41xDxWK/IhPdrWDrXX1Tbk4WvJe5F3I5u/11/YUFbpD34wovFH266dEQdiwfcjG7HGlyxlDbBQsb4QpkRMmIpfYR7LqrtwXwQFIgIFtmIFpfx6rcxxB9u8HRrEiYDS/x5551nw1+Io8Zz4SzmvrhD8LAIzPQ46NoGhgYELffc7SrjhwGU9Dz8tod3iO/GzYxRg/EGK6EzLLj4PtqZn4ksUVcyJOwyCKZlOo0LhHZxDATl4tJA3BFHhLijvAXB6lHs+RjeNYLOQ8yWG0Q4vnOHsDKlkyHqWMn6EzoTjL/Rekkgqwr3Ky4QBCVFbp1QRNzxu3HLZtr1lyvcvcC9g6UEcedb45jUiSlzbiImuEwX3/WvLZYjZ0Hg/iOss138F3HHZI6FKlMZwLkG6wtB4bhWmdyxznPfSSBx15tQCKw1uMmj3oca1yPtD4iTxUqIp8B3B2KxYRzwLctYkLAqOytLSSHUhDGHGC4EHb+f9s4igutAHC6WPNyyUcWTuevHdfWFIq7eGjVqWHHnW6tdIlNUBYjD948MW8Z4YqU5FmMfv9/ttJMsOSIb4yAJHCRuscgjPALvQlTX3hk3sMj6VnkWMLid3QKCNonIZ2yM02IuV0jYZRASIBjIiWPAxeDHMRBfw2TKRM4KxcXc0bHC9YpKCi5gJhOOi9WQgQWBgbmbNHrEBKtkOjSrab+SeRQDCtY4hCzCEQGJaCVuA4uF208Q4ct7yAyLywotfO18tzSWOwZ0BK/vksSqyYCfLIOvpMd32wwlwx88Efy0TwLMozh+ScCi3adPn9gIeh8yDImZxELrYqxImEDY+LUaEdk8H/W2gdxLRDOi3YHFDms8gooJlzaI0MF66luL6bv+7gjpQJwtfR3vBNfCxZHhduXe+6Q7ubt2Tzwj38+Yg4h2JZdY6GK5w0KOoERwMhZGVafO73e+eOQ8CDcB+jzWeRY1roxNtvud629cA9ofYSPuHKIQWCxoSNIgWSQ8N3G9AWHL4p85ySFxlx4SdhnGiSUmdFYobjWISxaLFa4v15FIXGBF52Jc0pnQEVGINTosnQT3C/F8CAoXHEz8DsUpGeQyMaEzmZEM4lsfEK1MaGRFOXHHucWlI/sDOpZSYhqZtFzxYawiycSdTzrixo+PdJaAopyrT67uhTufOIk77jeTOVl+1Opz1xeXPP2R+mRYKRBeiB52WIgSdy2xhPL9vtsVwcOijkQViqP71uJMCQzGHJJD/PPD9Ymwihq8FYhXauLxu7ESli9fPpENy3lQH5DFNCIvEzFtxK8h5HCvAsfmeG6Bj/USYUc9v3R3L0lGURbKyfpbFPcfKxwLBWJ53TV3YwvFpnmeNokXg0dpTpLLNyTsMozrWEzu1EpioKcDE8fg16pKd+9Nv3NikUNAkaTgFzRlNcZkwqSSTDxGNaG634yAYVJzVgk3aSAmcQPRsX1Xb2kXd/71wyLBoMVKFEsJrg5c4Ah7HtwLLLTJahmWFKwTrmQKLl7cPEW5pvlkJc2nc4nS1YzrE1c3FjDXz3GP0kdZ3CHuothUPlUtStx8ZJpSYsfVzXPihkUHpS2yaa3FSky8L+Mg/SDqY+IlYWFLnTpgMYsrOLyzAWMxlrMod5Rw0PcoG4JnBu8IJXxoC/yf+4All2tOmRnc81FvFZiNzxUGbQrXPuI6XI+U4+EhYJcR4k6jtBIKCbusQUwFdYuIX2CQz8RgBgwarAixEHAcP13dxTsgtohnyHT2KS4eBI3L/vIFCLFEnGucrDMOrKUkA7iUfmDwQui5XTYQ31gpyD6LSsxgAWblj3uJ7MNwpmky/GPjcosqDEAUhMQYrGMIef6dabAIYQknBMLdYyxYZJ6/8cYbKT+Xjf7I+SAmEXW4fzMR04mQw62NkKY/YpFzmcBAIkgUQnp7cK1xRWK9Z4F3wQUX2KxbwmOIMwN/Hohqq0Dc3iTCYaXkvhd1ZyFEbhTzkjsXLLR4qojj3V4NVIm66JCwyyIMMkzmTO7pWuiSdUoEE3ELZCDhAkTgJQtIJ5YBS0E2rCPE8CBoCchG6LBKwzXhVxaPU4cmEYTJE2skK1b/GrM6pX6Zi6GKKqXf/ywxO1gI/P2Fi/I5hCeJLUURgyK9DGDEXSavM2IO6zDJSlitcAE7yz2TPQLDt9rlAkIGuB5RWQldW8aVTTIaFkq24GJ3C0QUos6NMyx2sZAheDIxBlI2xW1Rxu/DW8PxELDEHXP/3XaK4RqOUUDNTBJSEJFkOHMcvCfJXL3h0JEoz8ndW8Z8LHeEHfheqjiN+/mGhF0OidJiR+kSLGB+XTpqU5HGzubaYddrNuOZWB0jOBlseCA+SrrXYL7DCp1BDAHnLDPOFc2Ei+UgXD4mnWvg3z8GblbouH8RlrhlXdaZ/75wxqXbVcRVoReZAzFDjCl9MiqLUao+jKXK1QgjeYpYMxZUWFBcMeB8IKpdDSgng7uVhSvfidsVocI+zP4xuAbEdCUrhp4ujGtcZ+IWucckiCBguAeUUnHvwfWOZT1qcUMZHUrGOG8BJYy4BuH9hyE8BuBRSDf7uTBxx4Ke5LnwvrMieiTsYgCWofbt29u4tfAWTU7c4fLz9//LtqhikmGwwQUT9fY4+TQh8RzlA0iCwS3qV7HHzYmwTbZ9W7rHR5T5gfdYCXDF++IOXBHSKAvPiuJBP6CuYxS10vw2wIIBbwAuPhfLR1+jn2PBPf300+0uKEz0WPTiBNmuLKaw0PnhJ2TdE5ZCqRfiWok9xZLptlTMFFhkEZSIePoi9fvwnrj74o+/6Yi78Gfx1uDidmOCX6eQuEOXuOJ/LtNjgC/uuB54k0RmkbCLCQzqiDsm87B1jngLsjApd5IvlHYzvC+Kye4lfsQlgvAaMZUMYljoKG+BRRVLCckrUfx2//gkalDslABlPwicSY0i0NQqo02Q9ciK2cGAL1GXG6LOgCQhCqscbY42hsXI36MZEDyUXyKgPxMFgHN5LflNeCwAtzNZl/QH3K1YsElQwVNAHKrbhznTUMaK601MM7UAEdXEPUa1uPYz4F1RX8YZjoeQ9LeLBMao7t27F9hVg0UAJbHSGQOKk3nL4tav3iAyg4RdKaMwtwUCg/gZHm7PVwdWotIupvIRaj9hKSUphlIKuL4ciDsyobGQsJUOJW5crFNU94LYGRIl3nvvvaSvX3jhhTaInPg5f7s6XDa4x6N2vYjsQ793W3VhBWfiJmGJxCV/wg5PpHERd4Q60LYvueQSWzOO7F+8FLhlsZoT70YWLn0vWRHgbEBsNRZFv5ZgOtB/2aLN9XHKSiH0sMixgCOumbHBv0YkrPmx1bjjGZv8XSYy6Tr3PTRxTJrLJyTsShF+Z2BlRkICAzjp8g4GcoJUGUCS7TMpcZcefrIDrjSuMwMkruYJEybYydSv3E9JB6wFWM5cFrJflLY4ELvj3Okcn0kMC5zb0ByrHAk0WC+w4LiBlLg/2oh/78nKTSUGRemCxBe2qAqLN9oArv/wbjZxtJSQlIBwwkqFC5S/AbcfQidXYR/hrHPXB9ONq6XYMuVzELBY3Px4TSz07LuKdZI6eSzqGYPIyvaLT/NIto3f9o6dbuYtC97SHoaT70jYlUJwvTFgsyUZkzhFNt3k7tyyTPj+psoiffxBDZGGS4cgaF+okfWFuCMzzUEAMxMvA2tJ46qICSLYOmxlQVjiakK4EVvDyp02QRyRX97BwcSi1XK8IK4MQePiOd39RdDjni0rmc6IFCxZ/jUggYJyI77bMtuERVxJF9eIKH8XEPo6FjcsleFjkJlLKRksd4To4IKNsvh0vmTeiuRI2JUySIYgfd9ZW4ijwQVIEUhcfQ5iLFitykIXPWTVEcdE/BwxjeFVL0HL3A8Ctf1VKrULqfBf3H1Ascj4VhdWxy4Im2w3akRRYoUYoxkzZtjnseRSL0sr4/iQSpDT/lxQut9O2KKO7Oh8yoDNFliw6A/syZ2tmLpMgpsdF7Prz4g0XLAkxZGoRexesv22SawjYcqNN1GMB/mWeSu2RcKuFIFlCPeKy3xlmxpW6mR7sWpjdeZb7hwSd+nhXz8EM3E7FIDFNYp1jrpU4cr1CG7cJL7rhdV2OPZxe1CDkFghRCKrXKwyiDgGdLLMgFVyeH9RLHnKPosP/gRJMg6xnAh+v0Yilhl2NGARwfZYlN1xW/qVJfjtbJdGwlims19z0QYQUIgpB4KPXWbC4i5cbLyk7aA0ZN6KgkjY5TF+R3RmdDorcVZM+BQgdlvmvPLKKzYTjpWTXwRSlBxcC75gmj59uhXWvnjmumMxxSWRaluidFfJ1D5zu4Ww+sYqx167uJj8XQwoa0JMDS4YP55GxAcy20nW4R7T36kN5sp74OaiIDFjAPefxB03bpQlcccCmD6SiTp1ucDvx8RNY6Fn4fbqq68mnmdhj9WWGn7MDcRZU6A5XfIl81YUDwm7PMUfiFmh0Yn8GmQU42SVRgA9sIIj85LVlCx06UO5BIKC3bVkksBSxqQZLlmAuMNyR0BzprbkQtwRLE0Fe3YNoFYesZWUNHHxKpwHAdOUVcnENk0i94s7it5y74FFR/Xq1a1l2LcE46bHapLNvV9F5iGWjXtPPyfDFRHvizuStggRIfatTZs2aWcA5zLzVqSHhF2eu10IUiUAGteeHz+DG5baSNRJYqLHNI5LMMpYirKOu5Zca1agDFLElpDE4BcDBgZYBrDwZtfZEHcMpG5DcQLlNaHHT9RxX4lpYvHgF+Dl34g7JlriqQr7DlF654EpU6ZYIcVersCOFizgwuKONoIgS7cIfC4zb0X6SNjlMcRxIer8TCi3MmL1zoSOpYjitATmx3WbrlyCexUxh2UM6ygDqxNT4cwuEloyLaaSiTuSaXC7+FYbTejxwZUtYds3FnPhrd8Qd8RhMqkWN4ZTlI6YSrJcEVM+TtxRAYF/hymJtT6fMm9FyZGwy1OYmHG7uJpoBMpjzqYTE1fjLDRs0UWWUVy26cpHcG3h9k5mKUuWcZctcUfMHcHKlLUI74cpSi/+BIo1BsFG6AUlbchyPfbYY22/90HQYbVXG4gXWGqJqUNckekOvosVQYf7k101SBqJS+atSI9y/MeIvIPb0q9fP/PDDz+Yjh07mqlTp5qddtrJVKtWzaxatcr8/PPP5s033zS77rpr4jNbtmwxO+ywQ07PO67MmzfPnHfeeaZVq1bmjjvuMJ9++qk555xzTIsWLcydd95pDjjggKyfD+2jTp065l//+leiHWzdutWUL18+q+ciMsO///1v88ILL5hatWqZG264wT739ddfm9NPP91Ur17dDBo0yBx11FHbfE7jQDyYNGmSmTJlijn55JPNiBEjzI8//mjmz59v+/qmTZtMxYoV7ftefPFF89Zbb5nbbrst7b7PvFOuXDnz6KOP2jGtQ4cO9vlLLrnEzJo1y3Tv3t3+m3kImJ9q1qyZ+LzGn/xAdyDHpNLVdK5TTjnFVKlSxdx3332mc+fO5sYbbzSPPfaYOemkk8y+++5rhZ6PBvPMccghh5hx48aZuXPnmquuuso0adLE/s0gVrdu3ZycD+2C9rHzzjsnntegGg9YuA0dOtQ88sgj5vPPP088f+CBB5pnn33WrFy50tx+++3m1Vdf3eazGgfiMRd88skn9nHQQQfZe42QQ8ivX7/e/htxByeeeKIZPny47fsIq5Lw3//+NzHvLFmyxNx///3muuuuM6+99pp9/u6777Yij8UGC9vFixebY4891lx00UUFvkfjT34gi12es27dOrNhwwaz1157JZ474YQTzB577GFXVcKUaUuZW2FrpVy6SXb/vvzyS3PllVeaL774wvz97383Z511VuK1b775xhxxxBHmT3/6k7UYi9KN68dO1DO+Q5s2bcw+++xjXnrpJWsxu/jii02FChXM9OnT7YIOQcbfUXHNNddYw8Gvv/5qxd1vv/1mF7JdunSxr/NvvEf/+c9/rHHhnXfeSVgORR6RpitXlBB2BQgHQfuEA1WpUUa2E8GqSpTILQQXk0yRL/FMagOlG78dEUtLGRNXE5F/U2iYuLpwfUqy5FXOJl7ccsstNoaaTHwgE5V6pSTSARmolDKhSHqy7btKU+atyByy2OUAVtmfffaZ+eijj4r8mTlz5piRI0falR2WIlZpUa/WRNGRpUxEban5xz/+Yd2smzdvNmvWrDFDhgyx1uGvvvrKxjXR3//yl7+YM888s8B3KKYuHnAfe/bsaZ5++mmzyy67mEsvvdScccYZ9u9vv/3Wtgfi3nC/89zYsWPTuu9+2yOshDbHfEJbc7z++utm1KhR1u179dVXm06dOm1zzmp7eUgGRaNIApY3VmQjRoxIVOou6ibdZL65FVZ4M3iRfWQpE1FBIdi9997bWkbWrVtns5wpb+JqgFEUFusJBWinTZuW69MVGYIMd3aUYTcHdpdgRxu8O5Q0YgeHsIUsCottNjNvRXaQqSHLsLrBwkMQKpa7vn37mj333LPQz/xfWRob1+VWWDvuuGOWzlikwt0LIYqLH+TOvz/44ANrkSeWiRgmYqhuvfVW07hxY2vBa9CggRk2bJgNWE+WCStKL9x3FydJBQTmiNmzZ9vEBRIWqlatar777jvTv39/s2DBggJemnStZWTecmysccRskqxDXLefnIGVDssxbY+kLVEKyJKALPNQd86HPfbYPNnfdzSVBch/fvLkyYn4CyFE6eaGG24Ihg0bFtSsWdNuY0d9On9TdYqRX3fdddsUHlZsXTzA83LzzTfbfX+pW4p1jHvbqlWr4Pbbb0+85/LLL7c73qR738NzDHsPU6Pu008/DWbNmhUcfPDBtmYnVmNIti1ZvsQWi9RI2GWBSy+91CY9ODM6BW4xexMAy1ZA7POaquP5f2Oer1at2jbFSYUQpQN/UiQZgkLXuMLY55kxgv2I2WnAT5A48sgjgwkTJti/5f6PJ7QB3O9t27YN+vTpY/cGP+OMM2xxdIe79yUVd37bcXuMw6GHHmrDg4DECVyuJGisX7/ePqfkiNKHhF0WcFuAwYoVKxIDPB2HSvLsxecykVJ1xNGjR9uYG3aZEEKUbqZPn26r+o8aNcr+fc899yS2hvPjccmIJdZKFrr489NPP9m9vxFabB2355572t0efKIQ9tnOvBXZRzF2WYBCwsTEuWreZMMSn0UdImJpKDZK/aD33nuvQNyNi+Ei+4kYiAcffNBmSQkhSi/Lly83559/vi02/vvvv9vnLrzwQnPqqafa4rDEMf3xj3+0RcnZbYBYK2KpyEAU8YVapbSBDz/80NaLo4bctGnTIo3rpQ2xe8Urr7xiM3ApQkwbZF55//33bQY2sXZk4BJTp1ju0onKnWQRij5S/PH777+3ZQ2aN2+eGOiPOeYYU6NGDTN48GAbQOsYPXq0LVI6YcIEc9ppp+Xw7IUQUfHxxx/brcEoPvvPf/7TtG7d2k66FKJleygSJurVq2dLT6i0UdnBL0FCQg3tAlHvP58ubEU5fvx4065dO/PUU0+Zhg0bmtWrV9vjISj/+te/FmhvKmlS+pCwyzJsB8NWYayM2AfSF3dkwLGKuvfee+1zixYtsvuTXn755bLUCRFDcde7d29z6KGHWgHnxoIwmljLFmERF8X9dzVQBw4caL1BVGPgGBgOHn/8cfP222+bhx56yL4Xj1KzZs3S/h0id0jY5QDSydlMOSzu2EqGzZX9TkyaO2VOhBDx3KKOSRbLzGWXXWb3IBYiSrD+stcs3iCKWxMGcPTRR5u2bdvakltY6XjP3/72N7s37csvv6yFRClHwi6H4o54CvZ8xBzOwO6v0FhNaUcDIcqGuLvgggvsAo4JGBesEFGDaGPP4R9++MEuIIihmzx5shk0aJBp1apVAWuhrMSlGwm7HLtlDz/8cHPggQeaZ555JtenI4TIEcQ34RYjQUoLOpEpVq1aZd2uFL8mFKBKlSpmwIAB5vrrr0+8J8p4PpEbJOwiwu8MxekYZCRVqlRJg7kQZRztPyyyCWKOXScOO+wwm1Ah4oOEXQT4Qo5tf0gRv+KKK7b7ufAArgFdiLKNrCUiDpm3IrdIRaTBiBEj7P/pDASfkiJOGRPSx7cHnciJOGrZrV27VqJOiDKOJlaRjTbm7DkkULgaiWp78UFKooSQEk42EVlF4Ao5UlRye0Gn/sqIuJqzzjrLfPnll1k4ayGEEGWdsIhTokS8kLArIZQooSL8G2+8YXr06GGfo6CjL9pwrfLw8XeUGDNmjE0xdwVKhRBCCCHSQcKuBDjxxm4RbAv0+uuv2yryPE8dOlexG9eqM3mvWbMm8ZwTdWwTNm7cOBUfFkIIIUQkKHmimPgJDhs3brQZrVOnTrWFH1u2bGmWLl1qM13r1q1rtxAj7g43LTWDqP4N7CxBRhKlDRCEQgghhBBRIGFXQlF333332YQH4uNq165txd2ll15qtwZ74IEHrKUOYefef84551hL3syZM63rlsQLNvoWQgghhIgKCbsSgAuVTZTvuOMOc9RRR1lhh2WO7Nazzz7bnHTSSdYalwx2mmDXiVT7QgohhBBClBQJu2JCORP2dGSnCFLFfUgZJ5kCcde0aVP7byGEEEKIbKHkiWKyaNEiU79+fdOiRYvEc04bkzLeuXNn89BDD9nYu3BGrBBCCCFEJpGwKyJY44AYOtyuCDcEnStfwusvvfSSWbJkiXXFvvLKKza+TuJOCCGEENlCwi4FYUHmCjh26dLFvPvuu2bixIlW0LnkCMqZPPzww+bDDz8s8DntJiGEEEKIbPH/C66JlNmvxNRhhWNHiZ49e5pu3brZGLs+ffpYMUcZE8qeUGgYa1737t1zffpCCCGEKKMoeWI72a9PP/20adCggXW9vvjii7YYcePGjc2ECRPMjTfeaKpWrWof1atXt69Rsw63rLZoEUIIIUS2kbBLwRNPPGEuv/xyK+bY7uv55583p556qnnqqacSO0WQSLFq1Spbn65NmzbWykf8ndt5QgghhBAim0iBpAD3KwIOUYfVDtfr6NGj7XO4YDdv3mwaNmxoH74LV6JOCCGEELlCkf0pWL16tbXGvfDCC+a8884zt99+u/nLX/5iX3vyySfNrbfeamPrfJQoIYQQQohcUuaViCtjEubwww83X3zxhd3+6+abbzYXXXSRfZ5twhB7ZMQSdyeEEEIIkS+UWb+hX1QYiKHDxUoSRNeuXe1j8uTJ1mqHiMM1y7+vu+46s2LFCvua+x5eF0IIIYTINWUyeYI4OXaPGDZsmP37mmuuMffee6+pV6+eWbhwoRkwYIAZMWKE2bRpk+nbt69ZsGCBff7QQw81u+yyi5kyZYqyX4UQQgiRd5RJi90RRxxhrrrqKlumBJH31ltv2Uft2rXNzJkzzZlnnmldrg888IAZP368rU/36aefmrp165oDDzxQ2a9CCCGEyEvKnDIhcxWLHJa3Cy+80HzzzTemUaNGpnnz5laonXzyyTaGjv8j4IYPH25q1qxpH/53SNQJIYQQIt8oU+rEd52ec8451mJ39tlnW2G3bt06s9tuu9mYOeLrEHfUrcNyN2bMGFOlSpXE9yj7VQghhBD5SJlRKFjZnKgjfu6KK64wLVq0MI888oj57LPPzD//+U/7HhIhnLh7/PHHzY8//mite0IIIYQQ+U6Zsdg5Kxt7uo4bN84KOcqVsP8r1jrcsgi/QYMG2fci7k455RT7CO8fK4QQQgiRj5QZYQfTpk0zkyZNsqVKqFPn6NevnxVyf/3rX63FjizZsIiTqBNCCCFEvlOmhB216HbeeWfTpEmTxHOuDh27Suy666429o5Eid69e+f0XIUQQgghikuZEHZOvP3+++8FdppwJfz4/zPPPGNatWpla9Qdc8wxOTxbIYQQQoiSUSb8i25niKOPPtp8+eWXZtSoUYnneaxfv94mUbz++uumS5cutpQJdeqEEEIIIUoTZW7nibFjx5r+/fvbvV9PPPFEU7FiRXPrrbfaIsRz5sxRfTohhBBClFrKnLDj51Kj7tJLL7VuWWrXEVP34osvapswIYQQQpRqypywc6xatcqsWbPGljHRNmFCCCGEiANlVtiFUZ06IYQQQpR2JOyEEEIIIWKCTFRCCCGEEDFBwk4IIYQQIiZI2AkhhBBCxAQJOyGEEEKImCBhJ4QQQggREyTshBBCCCFigoSdEEIIIURMkLATQgghhIgJEnZCCCGEEDFBwk4IIYQQIiZI2AkhhBBCmHjw/wCKjZ/t/lYd5QAAAABJRU5ErkJggg==", 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", 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" ] @@ -490,7 +472,6 @@ "source": [ "element_set = {a,b,c,d}\n", "S = ElementSet(element_set)\n", - "kc = KComplexity()\n", "result, elapsed_time = cf.serial_crossed(S)\n", "print(\"Result:\", result)\n", "print(\"Elapsed time:\", elapsed_time)\n", @@ -501,7 +482,7 @@ }, { "cell_type": "code", - "execution_count": 342, + "execution_count": 34, "id": "092f34e3", "metadata": {}, "outputs": [ @@ -509,15 +490,15 @@ "name": "stdout", "output_type": "stream", "text": [ - "Result: [Element(object=A1, attribute 1=A, attribute 2=1), Element(object=B1, attribute 1=B, attribute 2=1), Element(object=B2, attribute 1=B, attribute 2=2), Element(object=A2, attribute 1=A, attribute 2=2)]\n", - "Elapsed time: 0.0003448999486863613\n", - "center_embedded k-complexity: 14\n", - "center_embedded primitive count: {'add': 0, 'append': 0, 'check_if_same_type': 1, 'dim_set': 0, 'flip': 1, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 4, 'remove': 0, 'remove_item': 0, 'sample': 2, 'setminus': 4, 'write_all': 0, 'write_all_set': 0, 'write_random': 2}\n" + "Result: [Element(object=B1, attribute 1=B, attribute 2=1), Element(object=A1, attribute 1=A, attribute 2=1), Element(object=A2, attribute 1=A, attribute 2=2), Element(object=B2, attribute 1=B, attribute 2=2)]\n", + "Elapsed time: 1.1899974197149277e-05\n", + "center_embedded k-complexity: 26\n", + "center_embedded primitive count: {'add': 0, 'append': 0, 'check_if_same_type': 7, 'dim_set': 0, 'flip': 1, 'implement': 0, 'list_create': 0, 'merge': 0, 'pair': 4, 'remove': 0, 'remove_item': 0, 'sample': 8, 'setminus': 4, 'write_all': 0, 'write_all_set': 0, 'write_random': 2}\n" ] }, { "data": { - "image/png": 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", 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", 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" ] @@ -529,7 +510,6 @@ "source": [ "element_set = {a,b,c,d}\n", "S = ElementSet(element_set)\n", - "kc = KComplexity()\n", "result, elapsed_time = cf.center_embedded(S)\n", "print(\"Result:\", result)\n", "print(\"Elapsed time:\", elapsed_time)\n", @@ -540,7 +520,7 @@ }, { "cell_type": "code", - "execution_count": 343, + "execution_count": 35, "id": "ca81ceaf", "metadata": {}, "outputs": [ @@ -548,15 +528,15 @@ "name": "stdout", "output_type": "stream", "text": [ - "Result: [Element(object=A2, attribute 1=A, attribute 2=2), Element(object=B2, attribute 1=B, attribute 2=2), Element(object=A1, attribute 1=A, attribute 2=1), Element(object=B1, attribute 1=B, attribute 2=1)]\n", - "Elapsed time: 0.0029325999785214663\n", + "Result: [Element(object=B1, attribute 1=B, attribute 2=1), Element(object=B2, attribute 1=B, attribute 2=2), Element(object=A1, attribute 1=A, attribute 2=1), Element(object=A2, attribute 1=A, attribute 2=2)]\n", + "Elapsed time: 5.9200217947363853e-05\n", "tail_recursive k-complexity: 13\n", "tail_recursive primitive count: {'add': 0, 'append': 2, 'check_if_same_type': 0, 'dim_set': 0, 'flip': 1, 'implement': 0, 'list_create': 0, 'merge': 2, 'pair': 0, 'remove': 0, 'remove_item': 0, 'sample': 2, 'setminus': 4, 'write_all': 0, 'write_all_set': 0, 'write_random': 2}\n" ] }, { "data": { - "image/png": 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", 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JnhPJPb5Yx02MEBSZRzF2osi4QT44WblVvL9qZ3AjOzOb4LJhcCMDc+PGjTv83pWOQGhR6BZBOm/evB0+567DDZRY3Byu7EZRSWQddNa1nW2xc8YZZ9h7SyYyIgWx4k+0Rb3eKMB1F2fHEyYZ4qtwg3/44Yf2Zx8mH+4tE1zQ2sTPqZZ+8OHZ+G0HyD5MZrHbGbi5KHFCZiexUT7+NXCviuJSQzjRFmnP/r1FGGAlw/0ZFnwXdd6CdRGxEJFRj1WKhQ9wf4LnjyUNYe76TKIxh3/7ZT2Av8E1SWap30co3YM4DFqyODbZ9kGIb9tZ+yOmlHPA7Z8qidy9HBdLGJ6QZG5iQPiyUCHkIHiu7j4lum+Q6k4lwX7CcyS+lu/nefvg9saCLjKPLHaiyCAkAGsT9b6IQ8KCxIRDh+bflAtgACUNnkEoVetEKiDYmMhZ0RMnRjo/JQ1wz2Adw7KFmAOsZkxeBFETY8ZKknNFQFFWAQsd14UFktIIuC0YFMeNG2ctfrhFiwIlTpjcu3btaq0HDNy4KqgDR227wuD+UcEeqxMr9aA4Kc71RqHtYU3hXjBZM4G5xItkQgIRRCkcnhsiOSi6/vGPf1irAqVFEPp8HqsC7j/aBH+bDsRVkmzAsXEbIjCJW0u1HArPk9AGvpdSLsQyYRXke3FnugUH9worJTGafA5Xm2/p9cHFSftBlNDOXbkTLE5hbvHlxgnqzFGWhAmec8bKT3wuz8K5Omnr9A/iUJs3b27Pn2dPgP6IESPi1jGeIc+I9s69QfwkcoXS10k4whJHH+EzlDBB8Plij7GA8QvhTFIJ58sYhzWLcQHRyDklg/6MO5ZzDRbhpR/ynADBQ0kQrhlws5KwAjwLrp22Tf9nnGGBzCLFL3uTCMYDRDL3GsHOtSLesb5SyoS2x32inA8xjJwH4wXjoKtZWVy4RyQccW+p+UdpFe4t4x39yYHYZZHrEr9EhslC5q2IELfeemusRo0athyCnwr/wgsvxJo1axarWLFirE6dOrE77rgjNm7cuJ2my6dT7mTy5MkJf79gwYLYH/7wB1t6gNIXpP//8Y9/jM2cObPA5yiJQEmH/fbbz36O8imUWNiyZUv8M/Pnz7flJSg5UKtWrdjdd9+dtMQHZSaCcExKAhx44IH2O/h/z549Y59//nmR7sFDDz1kf0eZi2TlDop6vUHccSljUxjuehOVhinOveBzwRIWic4hUbmTzz77LHbMMcfYcgn8zpWLSHR8x7nnnhsvI5IMSrpQxoUSFLwaNmxoz3HJkiUp3xPHtm3bYn/7299i++67b6xSpUq2hMXSpUuTljsJfpdr534pGNfXOnToYO9FlSpVYm3btrXlKhwbN26MnXPOObE999yzQEmPZO1sxowZsSOPPDL+fd26dYt98sknBT7jnkmwbE9h9z/I5s2bYzfffLO9x7RT7ne7du1ijz32WIHP0f+uueaaWPPmzW2753P8+4EHHijwOc6RZ7vHHnvYe9y3b19bqiXRNU6aNCl+3CZNmth7eMYZZ9j3gowdO9aWGuJ+cHzKpVx77bWx77//fqfXeMUVV8Tq1au3w/s872Tlcfxzve+++2x75Hoou8PYxPPwy5DsjLfeesuWOnL3jnH53nvvjf/+22+/tWVqaB+UlTnrrLPstQVLzhSl3AnliuiXbuw55JBD7LOj7JAP/YDx0y+7IjJHGf6TafEohBBC5BNYtbASplOiJghle7AmkpTjXMulHdznFLqmKoArkiwyi2LshBBCRBZcjsEacGxvh2s03e0Ng1COBZc2Gazi/8CVjEs70R66IjPIYifyBjKqdlaKhNgfpcsLIYoKMZRkiVIPjvhMYs7Y2o6xhESR4NZ5QpR0lDwh8gZqK5EssLPVn7+BuhBCFAYJJiSUkGhEpjhZwwT3Y1WTqBNRRBY7kTeQrbazUgFkf5LpJYQQQogdkbATQgghhIgISp4QQgghhIgIpS7GjkrnFHukeKI2IxZCCCFEvuO2lCMBiGLUhVHqhB2ijq1ZhBBCCCFKEitWrLC7kxRGqRN2bpsTbg7bqwghhBBC5DMbNmywRil/q7ZklDph59yviDoJOyGEEEKUFIoSQqbkCSGEEEKIiCBhJ4QQQggRESTshBBCCCEigoSdEEIIIUREkLATQgghhIgIEnZCCCGEEBFBwk4IIYQQIiJI2AkhhBBCRIS8EXbDhg2zhff69+9f6OcmT55sGjZsaCpWrGiaNm1qXnrppaydoxBCCCFEPpMXwu799983Y8aMMc2aNSv0c3PmzDE9e/Y0F1xwgVmwYIHp0aOHfS1evDhr5yqEEEIIka/kXNht3LjRnHvuueahhx4ye+21V6Gfveeee8xJJ51krrnmGnPYYYeZW2+91bRq1crcd999WTtfIYQQQoh8JefC7rLLLjNdu3Y1nTp12uln586du8PnunTpYt9PxpYtW+zmuf5LCCGEECKKlMvlwSdNmmQ++OAD64otCqtWrTLVqlUr8B4/834yhg4daoYMGZL2uQohhBDFoc51U7NynK+Hdc3KcUTJIGcWuxUrVpgrr7zSPP744zYRIlMMGjTIrF+/Pv7iuEIIIYQQUSRnFrv58+ebNWvW2Bg5x7Zt28zs2bNtzBwu1F122aXA31SvXt2sXr26wHv8zPvJqFChgn0JIYQQQkSdnFnsTjjhBLNo0SKzcOHC+Ovwww+3iRT8OyjqoH379mbmzJkF3ps+fbp9XwghhBCitJMzi13lypVNkyZNCry3++67m3322Sf+fq9evUyNGjVsnBzguu3YsaMZMWKETbggRm/evHlm7NixObkGIYQQQoh8IudZsYWxfPlys3LlyvjPHTp0MBMnTrRCrnnz5ubpp582U6ZM2UEgCiGEEEKURsrEYrGYKUVQ7qRq1ao2kaJKlSq5Ph0hhBARRVmxIhfaJa8tdkIIIYQQouhI2AkhhBBCRAQJOyGEEEKIiCBhJ4QQQggRESTshBBCCCEigoSdEEIIIUREkLATQgghhIgIEnZCCCGEEBFBwk4IIYQQIiJI2AkhhBBCRAQJOyGEEEKIiCBhJ4QQQggRESTshBBCCCEigoSdEEIIIUREkLATQgghhIgIEnZCCCGEEBFBwk4IIYQQIiJI2AkhhBBCRAQJOyGEEEKIiCBhJ4QQQggRESTshBBCCCEigoSdEEIIIUREkLATQgghhIgIEnZCCCGEEBFBwk4IIYQQIiLkVNg9+OCDplmzZqZKlSr21b59e/Pyyy8n/fz48eNNmTJlCrwqVqyY1XMWQgghhMhXyuXy4AcddJAZNmyYqV+/vonFYubf//636d69u1mwYIFp3Lhxwr9BAC5ZsiT+M+JOCCGEEELkWNh169atwM+33XabteK98847SYUdQq569epZOkMhhBBCiJJD3sTYbdu2zUyaNMls2rTJumSTsXHjRlO7dm1Ts2ZNa937+OOPs3qeQgghhBD5Sk4tdrBo0SIr5DZv3mz22GMP89xzz5lGjRol/GyDBg3MuHHjbFze+vXrzV133WU6dOhgxR1u3URs2bLFvhwbNmzI2LUIIYQQQpRqix1ibeHChebdd981l156qendu7f55JNPEn4WAdirVy/TokUL07FjR/Pss8+a/fbbz4wZMybp9w8dOtRUrVo1/sLSJ4QQQggRRXIu7MqXL2/q1atnWrdubUVY8+bNzT333FOkv911111Ny5YtzdKlS5N+ZtCgQda6514rVqwI8eyFEEIIIfKHnAu7INu3by/gOt1ZXB6u3AMOOCDpZypUqBAvp+JeQgghhBBRJKcxdljTTj75ZFOrVi3zyy+/mIkTJ5pZs2aZV155xf4et2uNGjWsJQ9uueUW065dO2vh+/nnn83w4cPNN998Yy688MJcXoYQQgghRF6QU2G3Zs0aK95Wrlxp499IikDUde7c2f5++fLlpmzZ/xkV161bZ/r27WtWrVpl9tprL+u+nTNnTtJkCyGEEEKI0kSZGJWBSxFkxSIiibeTW1YIIUSmqHPd1Kwc5+thXbNyHFEytEvexdgJIYQQQojUkLATQgghhIgIEnZCCCGEEBFBwk4IIYQQIiJI2AkhhBBCRAQJOyGEEEKIiCBhJ4QQQggRESTshBBCCCEigoSdEEIIIUREkLATQgghhIgIEnZCCCGEEBFBwk4IIYQQIiJI2AkhhBBCRAQJOyGEEEKIiCBhJ4QQQggRESTshBBCCCEigoSdEEIIIUREkLATQgghhIgIEnZCCCGEEBFBwk4IIYQQIiJI2AkhhBBCRAQJOyGEEEKIiCBhJ4QQQggRESTshBBCCCEigoSdEEIIIUREkLATQgghhIgIORV2Dz74oGnWrJmpUqWKfbVv3968/PLLhf7N5MmTTcOGDU3FihVN06ZNzUsvvZS18xVCCCGEyGdyKuwOOuggM2zYMDN//nwzb948c/zxx5vu3bubjz/+OOHn58yZY3r27GkuuOACs2DBAtOjRw/7Wrx4cdbPXQghhBAi3ygTi8ViJo/Ye++9zfDhw614C3L22WebTZs2mRdffDH+Xrt27UyLFi3M6NGji/T9GzZsMFWrVjXr16+3VkIhhBAiE9S5bmpWjvP1sK5ZOY7IHcXRLnkTY7dt2zYzadIkK9xwySZi7ty5plOnTgXe69Kli31fCCGEEKK0Uy7XJ7Bo0SIr5DZv3mz22GMP89xzz5lGjRol/OyqVatMtWrVCrzHz7yfjC1bttiXr3qFEEIIIaJIzi12DRo0MAsXLjTvvvuuufTSS03v3r3NJ598Etr3Dx061Jov3atmzZqhfbcQQgghRD6Rc2FXvnx5U69ePdO6dWsrwpo3b27uueeehJ+tXr26Wb16dYH3+Jn3kzFo0CDrk3avFStWhH4NQgghhBD5QM6FXZDt27cXcJ364LKdOXNmgfemT5+eNCYPKlSoEC+n4l5CCCGEEFEkpzF2WNNOPvlkU6tWLfPLL7+YiRMnmlmzZplXXnnF/r5Xr16mRo0a1pIHV155penYsaMZMWKE6dq1q022oEzK2LFjc3kZQgghhBB5QU6F3Zo1a6x4W7lypY1/o1gxoq5z587298uXLzdly/7PqNihQwcr/m688UZz/fXXm/r165spU6aYJk2a5PAqhBBCCCHyg7yrY5dpVMdOCCFENlAdO1Gq69gJIYQQQoj0kLATQgghhIgIEnZCCCGEEBFBwk4IIYQQIiJI2AkhhBBCRAQJOyGEEEKIiCBhJ4QQQggRESTshBBCCCEigoSdEEIIIUREkLATQgghhIgIEnZCCCGEEBFBwk4IIYQQIiJI2AkhhBBCRAQJOyGEEEKIiCBhJ4QQQggRESTshBBCCCEigoSdEEIIIUREkLATQgghhIgIEnZCCCGEEBFBwk4IIYQQIiJI2AkhhBBCRAQJOyGEEEKIiCBhJ4QQQggRESTshBBCCCEigoSdEEIIIURpFXYTJkwwW7Zs2eH9rVu32t8JIYQQQogSIuz69Olj1q9fv8P7v/zyi/1dcRg6dKhp06aNqVy5stl///1Njx49zJIlSwr9m/Hjx5syZcoUeFWsWLG4lyGEEEIIETmKLexisZgVU0G+/fZbU7Vq1WJ91xtvvGEuu+wy884775jp06eb33//3Zx44olm06ZNhf5dlSpVzMqVK+Ovb775priXIYQQQggROcoV9YMtW7aMW8hOOOEEU67c//5027ZtZtmyZeakk04q1sGnTZu2gzUOy938+fPNMccck/TvOIfq1asX61hCCCGEEFGnyMIONyksXLjQdOnSxeyxxx7x35UvX97UqVPHnHHGGWmdjHPx7r333oV+buPGjaZ27dpm+/btplWrVub22283jRs3TuvYQgghhBClRtgNHjzY/h8Bd/bZZ4ce14ZI69+/vznyyCNNkyZNkn6uQYMGZty4caZZs2ZWCN51112mQ4cO5uOPPzYHHXTQDp8n0cNP9tiwYUOo5y2EEEIIUeKEnaN3797xLNg1a9ZYQeZTq1atlE6EWLvFixebt956q9DPtW/f3r4ciLrDDjvMjBkzxtx6660JEzSGDBmS0jkJIYQQQkQ6eeKLL74wRx99tNltt92sO7Ru3br2hSWP/6dCv379zIsvvmhef/31hFa3wth1111t/N/SpUsT/n7QoEHWsudeK1asSOkchRBCCCEiZ7H7y1/+YhMnEGIHHHBAwgzZ4mTYXn755ea5554zs2bNSkkYkrixaNEic8oppyT8fYUKFexLCCGEECLqFFvYkTxB1mrDhg3TPjju14kTJ5rnn3/e1rJbtWqVfZ+yKVgEoVevXqZGjRrWpQq33HKLadeunalXr575+eefzfDhw225kwsvvDDt8xFCCCGEKFXCrlGjRmbt2rWhHPzBBx+0/z/22GMLvP/II49YyyAsX77clC37P4/xunXrTN++fa0I3GuvvUzr1q3NnDlz7HkJIYQQQpRmysTwhxaD1157zdx44422xEjTpk1tjFuweHA+Q1YsFkHi7fL9XIUQQpRc6lw3NSvH+XpY16wcR5QM7VJsi12nTp3s/ylSnGhHCmLehBBCCCFE9im2sCNzVQghhBBCREDYdezYMTNnIoQQQgghsivsZs+eXejvC9vjVQghhBBC5JGwC2awgl/LTjF2QgghhBAlZOcJyo34L7YVmzZtmmnTpo159dVXM3OWQgghhBAifIsd6bZBOnfubMqXL28GDhxoixcLIYQQQogSYLFLRrVq1cySJUvC+johhBBCCJFpi91HH320Q/26lStXmmHDhpkWLVoU9+uEEEIIIUSuhB3ijWSJ4IYV7N86bty4sM5LCCGEEEJkWtgtW7aswM/s47rffvuZihUrFverhBBCCCFELoVd7dq1wzy+EEIIIYTIZfLEG2+8Ybp162bq1atnX6eddpp58803wzonIYQQQgiRDWH32GOPmU6dOplKlSqZK664wr522203c8IJJ5iJEyemcg5CCCGEECIEysSCWRA74bDDDjMXXXSRGTBgQIH37777bvPQQw+ZTz/91OQzGzZssLX41q9fb6pUqZLr0xFCCBFR6lw3NSvH+XpY16wcR5QM7VJsi91XX31l3bBBcMcGEyuEEEIIIUT2KLawq1mzppk5c+YO78+YMcP+TgghhBBClJCs2KuuusrG1S1cuNB06NDBvvf222+b8ePHm3vuuScT5yiEEEIIITIh7C699FJTvXp1M2LECPPUU0/F4+6efPJJ07179+J+nRBCCCGEyJWwg9NPP92+hBBCCCFECYyxW7dunbn33nttZkYQsjSS/U4IIYQQQuSZsLvvvvvM7NmzE6bZkoJLgWLEnRBCCCGEyHNh98wzz5hLLrkk6e8vvvhi8/TTT4d1XkIIIYQQIlPC7ssvvzT169dP+nt+x2eEEEIIIUSeC7tddtnFfP/990l/z+/Klk1p61khhBBCCBECRVZiLVu2NFOmTEn6++eee85+RgghhBBC5Lmw69evn61dRxLFtm3b4u/zb5ImRo4caS677LJiHXzo0KGmTZs2pnLlymb//fc3PXr0MEuWLNnp302ePNk0bNjQVKxY0TRt2tS89NJLxTquEEIIIUSpFnZnnHGGufbaa+2uE3vvvbe1zvHi3/379zcDBw40Z555ZrEO/sYbb1gx+M4775jp06eb33//3Zx44olm06ZNSf9mzpw5pmfPnuaCCy4wCxYssGKQ1+LFi4t1bCGEEEKIqFEmFovFivMH7733nnn88cfN0qVLDX966KGHmnPOOce0bds27ZP54YcfrOUOwXfMMcck/MzZZ59thd+LL74Yf69du3amRYsWZvTo0Ts9BrX2KM9C7b1EpVuEEEKIMKhz3dSsHOfrYV2zchyRO4qjXYq98wQCLgwRlwhOGLACJmPu3LnWOujTpUuXpPF/W7ZssS+HiigLIYQQIqqktKVYJti+fbt16R555JGmSZMmST+3atUqU61atQLv8TPvJ4vjGzJkiCmNaLUoSjvZ6ANq//mLxkBRGttA3tQnIdaOOLlJkyaF+r2DBg2ylkD3WrFiRajfL4QQQgiRL+SFxY6MW2Lm2LLsoIMOKvSz1atXN6tXry7wHj/zfiIqVKhgX0IIIYQQUSenFjuSLxB11MB77bXXTN26dXf6N+3btzczZ84s8B4ZtbwvhBBCCFGaKZdr9+vEiRPN888/b2vZuTg5Mj922203++9evXqZGjVq2Fg5uPLKK03Hjh1tTb2uXbta1+28efPM2LFjc3kpQgghhBAlQ9hRr65MmTJF+sIPPvigyAd/8MEH7f+PPfbYAu8/8sgj5i9/+Yv99/LlywtsVdahQwcrBm+88UZz/fXX2z1qyYgtLOFCCCGEEKI0UCRhRwHgTFCUEnqzZs3a4b2zzjrLvoQQQgghRDGF3eDBg4vyMSGEEEIIkUPyptyJEEIIIYTIgsVur732KnKM3U8//ZTmKQkhhBBCiIwJu1GjRqX05UIIIYQQIs+EXe/evTN/JkIIIYQQInd17DZv3my2bt1a4L0qVaqkd0ZCCCGEECI7yRObNm2yu0Xsv//+Zvfdd7fxd/5LCCGEEEKUEGF37bXX2u2/KC7MHqwPP/ywGTJkiDnwwAPNhAkTMnOWQgghhBAifFfsf/7zHyvg2C2iT58+5uijjzb16tUztWvXNo8//rg599xzi/uVQgghhBAiFxY7ypkcfPDB8Xg6V97kqKOOMrNnzw7jnIQQQgghRDaEHaJu2bJl9t8NGzY0Tz31VNySt+eee6ZyDkIIIYQQIhfCDvfrhx9+aP993XXXmfvvv99UrFjRDBgwwFxzzTVhnJMQQgghhMhGjB0CztGpUyfz2Wefmfnz59s4u2bNmqVyDkIIIYQQItd17ICkCV5CCCGEEKKEuGIpcdKoUSOzYcOGHX63fv1607hxY/Pmm2+GfX5CCCGEECJsYcd+sX379k24s0TVqlXNxRdfbO6+++6ifp0QQgghhMiVsCNh4qSTTkr6+xNPPNHG2gkhhBBCiDwXdqtXrza77rpr0t+XK1fO/PDDD2GdlxBCCCGEyJSwq1Gjhlm8eHHS33/00UfmgAMOKO7xhRBCCCFEtoXdKaecYv7+97+bzZs37/C73377zQwePNiceuqpYZ2XEEIIIYTIVLmTG2+80Tz77LPm0EMPNf369TMNGjSw71PHjiLF27ZtMzfccENxjy+EEEIIIbIt7KpVq2bmzJljLr30UjNo0CATi8Xs+2XKlDFdunSx4o7PCCGEEEKIElCgmELEL730klm3bp1ZunSpFXf169c3e+21V+bOUAghhBBCZG7nCYRcmzZtUvlTIYQQQgiR6+QJIYQQQgiR30jYCSGEEEJEhJwKu9mzZ5tu3bqZAw880CZhTJkypdDPz5o1y34u+Fq1alXWzlkIIYQQIl/JqbDbtGmTad68uc2oLQ5LliwxK1eujL/233//jJ2jEEIIIUSkkyfC4uSTT7av4oKQ23PPPTNyTkIIIYQQJZUSGWPXokULu31Z586dzdtvv13oZ7ds2WI2bNhQ4CWEEEIIEUVKlLBDzI0ePdo888wz9lWzZk1z7LHHmg8++CDp3wwdOtRUrVo1/uJvhBBCCCGiSE5dscWFbczcVmbQoUMH8+WXX5qRI0eaRx99NOHfsEvGwIED4z9jsZO4E0IIIUQUKVHCLhFt27Y1b731VtLfV6hQwb6EEEIIIaJOiXLFJmLhwoXWRSuEEEIIUdrJqcVu48aNds9Zx7Jly6xQ23vvvU2tWrWsG/W7774zEyZMsL8fNWqUqVu3rmncuLHZvHmzefjhh81rr71mXn311RxehRBCCCFEfpBTYTdv3jxz3HHHxX92sXC9e/c248ePtzXqli9fHv/91q1bzVVXXWXFXqVKlUyzZs3MjBkzCnyHEEIIIURpJafCjozWWCyW9PeIO59rr73WvoQQQgghRARj7IQQQgghxP8hYSeEEEIIEREk7IQQQgghIoKEnRBCCCFERJCwE0IIIYSICBJ2QgghhBARQcJOCCGEECIiSNgJIYQQQkQECTshhBBCiIggYSeEEEIIEREk7IQQQgghIoKEnRBCCCFERJCwE0IIIYSICBJ2QgghhBARQcJOCCGEECIiSNgJIYQQQkQECTshhBBCiIggYSeEEEIIEREk7IQQQgghIoKEnRBCCCFERJCwE0IIIYSICBJ2QgghhBARQcJOCCGEECIiSNgJIYQQQkQECTshhBBCiIggYSeEEEIIERFyKuxmz55tunXrZg488EBTpkwZM2XKlJ3+zaxZs0yrVq1MhQoVTL169cz48eOzcq5CCCGEEPlOToXdpk2bTPPmzc39999fpM8vW7bMdO3a1Rx33HFm4cKFpn///ubCCy80r7zySsbPVQghhBAi3ymXy4OffPLJ9lVURo8eberWrWtGjBhhfz7ssMPMW2+9ZUaOHGm6dOmSwTMVQgghhMh/SlSM3dy5c02nTp0KvIeg4/1kbNmyxWzYsKHASwghhBAiiuTUYldcVq1aZapVq1bgPX5GrP32229mt9122+Fvhg4daoYMGZLFsxTi/6hz3dSsHOfrYV2zchwhhBD5T4my2KXCoEGDzPr16+OvFStW5PqUhBBCCCEyQomy2FWvXt2sXr26wHv8XKVKlYTWOiB7lpcQQgghRNQpURa79u3bm5kzZxZ4b/r06fZ9IYQQQojSTk6F3caNG23ZEl6unAn/Xr58edyN2qtXr/jnL7nkEvPVV1+Za6+91nz22WfmgQceME899ZQZMGBAzq5BCCGEECJfyKmwmzdvnmnZsqV9wcCBA+2/b7rpJvvzypUr4yIPKHUydepUa6Wj/h1lTx5++GGVOhFCCCGEyHWM3bHHHmtisVjS3yfaVYK/WbBgQYbPTAghhBCi5FGiYuyEEEIIIURyJOyEEEIIISKChJ0QQgghRESQsBNCCCGEiAgSdkIIIYQQEUHCTgghhBAiIkjYCSGEEEJEBAk7IYQQQoiIIGEnhBBCCBERJOyEEEIIISKChJ0QQgghRESQsBNCCCGEiAgSdkIIIYQQEUHCTgghhBAiIkjYCSGEEEJEBAk7IYQQQoiIIGEnhBBCCBERJOyEEEIIISKChJ0QQgghRESQsBNCCCGEiAgSdkIIIYQQEUHCTgghhBAiIkjYCSGEEEJEBAk7IYQQQoiIIGEnhBBCCBER8kLY3X///aZOnTqmYsWK5ogjjjDvvfde0s+OHz/elClTpsCLvxNCCCGEKO3kXNg9+eSTZuDAgWbw4MHmgw8+MM2bNzddunQxa9asSfo3VapUMStXroy/vvnmm6yesxBCCCFEPpJzYXf33Xebvn37mj59+phGjRqZ0aNHm0qVKplx48Yl/RusdNWrV4+/qlWrltVzFkIIIYTIR3Iq7LZu3Wrmz59vOnXq9L8TKlvW/jx37tykf7dx40ZTu3ZtU7NmTdO9e3fz8ccfZ+mMhRBCCCHyl5wKu7Vr15pt27btYHHj51WrViX8mwYNGlhr3vPPP28ee+wxs337dtOhQwfz7bffJvz8li1bzIYNGwq8hBBCCCGiSM5dscWlffv2plevXqZFixamY8eO5tlnnzX77befGTNmTMLPDx061FStWjX+wsonhBBCCBFFcirs9t13X7PLLruY1atXF3ifn4mdKwq77rqradmypVm6dGnC3w8aNMisX78+/lqxYkUo5y6EEEIIkW/kVNiVL1/etG7d2sycOTP+Hq5VfsYyVxRw5S5atMgccMABCX9foUIFm0Xrv4QQQgghoki5XJ8ApU569+5tDj/8cNO2bVszatQos2nTJpslC7hda9SoYV2qcMstt5h27dqZevXqmZ9//tkMHz7clju58MILc3wlQgghhBClXNidffbZ5ocffjA33XSTTZggdm7atGnxhIrly5fbTFnHunXrbHkUPrvXXntZi9+cOXNsqRQhhBBCiNJMzoUd9OvXz74SMWvWrAI/jxw50r6EEEIIIUQJz4oVQgghhBCJkbATQgghhIgIEnZCCCGEEBFBwk4IIYQQIiJI2AkhhBBCRAQJOyGEEEKIiCBhJ4QQQggRESTshBBCCCEigoSdEEIIIUREkLATQgghhIgIEnZCCCGEEBFBwk4IIYQQIiJI2AkhhBBCRAQJOyGEEEKIiCBhJ4QQQggRESTshBBCCCEigoSdEEIIIUREkLATQgghhIgIEnZCCCGEEBFBwk4IIYQQIiJI2AkhhBBCRAQJOyGEEEKIiCBhJ4QQQggRESTshBBCCCEigoSdEEIIIUREkLATQgghhIgIeSHs7r//flOnTh1TsWJFc8QRR5j33nuv0M9PnjzZNGzY0H6+adOm5qWXXsrauQohhBBC5Cs5F3ZPPvmkGThwoBk8eLD54IMPTPPmzU2XLl3MmjVrEn5+zpw5pmfPnuaCCy4wCxYsMD169LCvxYsXZ/3chRBCCCHyiZwLu7vvvtv07dvX9OnTxzRq1MiMHj3aVKpUyYwbNy7h5++55x5z0kknmWuuucYcdthh5tZbbzWtWrUy9913X9bPXQghhBAin8ipsNu6dauZP3++6dSp0/9OqGxZ+/PcuXMT/g3v+58HLHzJPi+EEEIIUVool8uDr1271mzbts1Uq1atwPv8/NlnnyX8m1WrViX8PO8nYsuWLfblWL9+vf3/hg0bTNTZvuXXrBynNNzLVND9Lx3PQPc/f8l1H8z18YWJzDNw3x+LxfJb2GWDoUOHmiFDhuzwfs2aNXNyPlGk6qhcn0HpRvc/t+j+i1y3gVwfX5isPYNffvnFVK1aNX+F3b777mt22WUXs3r16gLv83P16tUT/g3vF+fzgwYNsskZju3bt5uffvrJ7LPPPqZMmTImn0CRIzhXrFhhqlSpouPr+Dp+KTsHHV/HL83Hz4dz2JAH9yARWOoQdQceeOBOP5tTYVe+fHnTunVrM3PmTJvZ6oQXP/fr1y/h37Rv397+vn///vH3pk+fbt9PRIUKFezLZ8899zT5DI0plw1Kx9fxS/Px8+EcdHwdvzQfPx/OoUoe3IMgO7PU5Y0rFmta7969zeGHH27atm1rRo0aZTZt2mSzZKFXr16mRo0a1qUKV155penYsaMZMWKE6dq1q5k0aZKZN2+eGTt2bI6vRAghhBAit+Rc2J199tnmhx9+MDfddJNNgGjRooWZNm1aPEFi+fLlNlPW0aFDBzNx4kRz4403muuvv97Ur1/fTJkyxTRp0iSHVyGEEEIIkXtyLuwAt2sy1+usWbN2eO+ss86yr6iBy5hCzUHXsY6v4+v4peMcdHwdvzQfPx/OoUIe3IN0KRMrSu6sEEIIIYTIe3K+84QQQgghhAgHCTshhBBCiIggYSeEEEIIEREk7IQQQoiIo3D60oOEXYZ57bXXcnbsM88805aFKe0durRfvxCidMMYyE5LGgtLBxJ2GWTx4sWmU6dOBbY0yybt2rUzw4YNM8OHDy+1HdoNaKUVrr+0Pvt8Qs9A5KotXHLJJaZp06Z2V6fSKO5ipex6QcIugzRo0MCMHz/ejBkzxlx99dVZPfa2bdvsMe+77z67Xy47dfz+++9ZPQcGklwyd+5c8+GHH9p/X3zxxebee+/Ni+vP5kDD4sIJ2wceeMBuv1caB1X/PLJ9Tv7igmLsIj/GoGyNT669ff7552bLli1ZX2j++c9/Nr/99ps1MjAvZFvcffHFF/F/jx492qxduzZrx97+/8VsPo1FWYE6diKzPPHEE7EKFSrEbrnllqwc77///W/831988UXskksuiZUtWzb2z3/+M7Zt27asnIN/nBdeeCE2ZsyY2Lhx42Kffvppxo+9ffv22KpVq2LVq1ePnXfeebFevXrFKlWqFFu4cGEsW/jX/80338Q+//zzpL/PFNxr2t1tt90W+9vf/hbbY489bHvIFv41btq0ybbLrVu37vC7bPDjjz/Gfvnll9jvv/8ebyPZwD/ORRddFDvyyCNjGzZsiOWabF1/suecjefvH2P8+PGxQYMGxfr37x979tlnY9m+z1OmTInVqVMnNnLkyHgfyDRvvfVW/N/vvfeePX7Hjh3j80M22sDcuXNjrVq1svf/yiuvjJUpUya2dOnSWLYZOXJk7A9/+IMdB2fMmBGLOhJ2GR5Upk+fHhs8eLDtVDTqG264IWvncM0118QaN24c+/Of/xw77LDDrLi74447sjaow7XXXhs78MADY926dYs1bdo01rZtW9vJs8GCBQti++yzT2zXXXeNPfnkk/H3s339hx56qBVYJ554YmzYsGFZO4+ffvopNnr06FjFihVjVapUia1YscK+78RNtibV4cOH20G1ffv2sSuuuCK2ZMmSWDbhnh977LGxww8/3P7/yy+/zPgxg8+WhUaXLl1ib7zxRiwXfPjhh3aBST9YvHhxwnMMG//7H374YTsO3nfffbGff/45q+KecbBatWpW1J1xxhmxQw45JHbVVVfFssXzzz8f22233WIPPPBA1hZWjLHMN5MmTcqpuGMRw+KaOaBy5cqx+fPn72B8yDR33HFHbL/99ov95S9/ibVp0ybWunXrrM1BuULCLoO8+OKLtkMzsdGp+/XrF9tll11iV199dcaP/Z///MdaaFgx0YmY5O+8804r7vh/NjrWY489FqtRo4YdUACRgcBhoMskDFZc37x582L169e359C7d2/7syNTk4p/X7FQcuzJkyfHpk6dGrvgggusuGCCyRYM7AzwtAUsd4nOM5Ncd911sX333Tf2r3/9y/YBxH2jRo2s9SwbsJBiUH/00UetBePggw+2i5wffvghY8fEQutzzz332OfO4mb9+vWxbPP000/bdnjEEUfETjjhBDvBYkHKFjfeeKNtA+3atbPPnv+vWbMmY/3Q/86XX37Zipl3333X/oywZaHD2JQNeN7c83/84x/2582bN9trR+gyHq1bty5jx2ae4VpzJe7c999///12YdmsWTM7Jm7ZsiWjY/C2wPeyuJ45c6b996JFi2J//etfYw0aNIg98sgjOVnsZwMJu5BAOPlgFTnnnHPsZO7YuHGj7dCIu+uvvz6j58NERkdiIPFh1czxH3zwwYxbbhjQEVTw1FNP2c7NcZ1rLuzVa7KB4u2337aDWc+ePeMrxrAJ3mfM/TfddJO1UDgYxFk9tmzZsoAFMZP3ABfkRx99ZEVV1apV7Tlli48//jjWvHnz2Jtvvml/RtwiKsaOHVtgMM3UoIqFEgvxtGnT4oudPffc094LnzCPjyUIq6D7XtoFbb5u3bp2keHIhtUUaO9YrVlUuYkdoc9klyn8Nsh1MgZ88MEHdqJngj3qqKOswAtb3BFq4qzS7jsfeuih+PNggUX7c2MQ47Frm5kCSy3PnfNA5OEKPProo+1Cq3bt2rEJEyZktA/QHsuXL59VcRd8nliLCYMhJAZRj9DLVPv3jz1jxozYnDlzYp07dy7glv7kk0+suGvYsGFkLXcSdiHAKuSAAw4oEEdFHAUDGGZoHywV559/vh1cM+kOYBJDwLmYNteBseCVK1fOHh/xlwncsQYOHGhXqnQuBjI3oNL5sODce++9sd9++y30Do01gkF+xIgRse+++86+N2vWLDu5Mri41TsDPkI7Xc4991xrnXXnweTC/eUVFPAI2g4dOsQuvvjiWNj494CBlEndxfMg8LgfiDs/1vPvf/+7vTdhHx8YTGvWrGknDZ6J3wa4D//+97/jbrlMwISCtY72+NJLL9njO4FDP8SS5qwHYbF69er4PV+7dm383nOtiAq30Mm01dRN1EzoPXr0sP/++uuv7fNgUnO4/hEWfhtA2BMOcfzxx8c+++yz+Hmx0GJsJEzEWU7TFRY8X0IecLd9//338fexyhCK4p6/a39ArB1CywnMMOHaXdsitgxPxd57722fhWuDuOb/9Kc/xTJNMnHHeMizCbMdBscgFpXcC7ewZT5E3Ll7ACw26SPp4rehq6++Orb77rtbSzX3/u677y7wWebFyy+/PLbXXnvZBWfUkLALaTBv0aKFtU74VigmDgYvxJQPrlncQYhBVnRhdSR/kmJ1yMBx8sknF0hY4PxwCeOeCWvVlGzFPXHixLjAwWLnYFJlFUXsS9jwnbjbjjvuOBvThrh9/fXX7e+Ib8IEj0sKlyAr6TAmdgSsm8zd973//vvWOsQg5iY1f6Dl2YQtKhxMVgga4oq4RidkEVEMcAx4Z511VqxTp072XoUxsP/666/xf7uBklg6njMCHlHjD+b0CQRxJhNasJbR/plYmdSdpdCt2mkfrm2EDfFstHs3qXHvERk8l759+2Zc3LlJjnvOM+B6EXUkcPjxvwMGDNjB2xBWG2TSxGvA/7HY+eeGuMNihIs2LHck1nGsYYhnJ1gRFm4h67veaK/0QTwqYVvLli1bZuO4EDFuXCD8hDGQNunGXY5NWEZYbaAwyydjVCJxR6jQZZddFsrx/ftICAQWMeY5nj+JK1w78xL3hTH4wgsvtP0TwRtmP/jqq6/sXIyrm0UrbRyXtN//XdtgsZvNeL9sIWEXUmdicGISRzC44HAmLwQGK0Zf3NHJcMnhCgirIzF5slolON0FR2O1I76D8yIzFTfISSedZF+OdMVd0PT9zDPP2EHbXRsrJ1ZMnAuWLCYYBlQypcI2x2OBRMy4WDpW5AzoiFh/MKMz33rrrfHjp3oewUxXJlGyf10c1TvvvGOvHRGF5YLnRTAx7kGstmHhPwPcjvXq1Yu98sor1mKGhQBX3Kuvvmp/z3NhgqEN9OnTJ5QsVSYtRBIwUSEWnSXmmGOOsc/Aj+9jUmVA7969e+hxNrfffnvczY1VkGtkUPetVBz/lFNOsa9MxflgHaOds3ijzfvijmztTFhsHbQ7LOW0t9dee82KDASlHxYCjBWEJ4SRpeuPRbQ92iBWbK6XTGDcjt9++22BzyOqL7300rQnVv8ZMg5yPCzzy5cvjy8w6YeICyZ6jovYRXRmIkuadsf9J1mI5xxcwHEfCFNh4eeEf7oEx2H6pPMiOBA4QXFH2wxb2DC3Ididm5uFFQtsNy47l/Tpp59uk1nCzJRnnPnzn/9cQKwi8vGc+GEgQaIm7iTs0sQ1RsTUc889ZycxVo0upRuhg7kbN8Fpp50WO/XUU607LN0O7Q9ENGYsElgC9t9/f5v5QzwJMLAT68eqlRUUg43rSOkOZv7fM2hwbCYQrGIEizO5M2lQboUBBbM4lk1W6u4cwuxQiDXn3ub6uScILTepOsHln3eqx0dEEwzvx+xhAeM5IzDdZInIRVgwwSMkEFrcGzfYhzmh4FbGSuxn3gLCklUxFppEpCuwWfkySbE6J46Snx3c8yZNmtjnTjul7AD9AUt22KVPsIxyj+mDuN5g5cqVtj/SJ7Dk3HzzzVZssgAL6/jJ/h5hwfnQJ3xx5zIWmQDDhnNBxNLGHFjpOB7uYDwE3BMmVibfsISFv7ghOWvo0KHx9o2XgGdAXJcv7nxS7Yeu//htmD7gxJ1zy3LP6YNkZyJ0GYfDGoMS9WEWD3hmaHeMy+5YiEoyxBG+LPbCwD8+4tWNs4w7iHnfi4RRgdJPhA/5hDUO8z1nnnmmjSkEFtVY7Fxcqwu94X4wBiZ6fqnCdxBmUrZsWevq90HcYUVknGIMijoSdiGAZYgJDTcgkz0uDyYuV1aBlQoNHWHHCpXMnLBgwsCl5VZHmLsZtDB1Y7lwHQfrEhONm4TS7Uj+YIJ4JCEAqyQDN9YhN5C72AksZQgL/h/GOSSaTHExM3mzUmV15gfJE7DLZBZGDSli5LC6MHkyeWAhcfzxj3+0z55J1Ik7rpnzQfRhOXXnHqYrlufOYM4EnsgahLhDeHNv/EE8LGF59tln22P7ot1dJ64+LEPcNyzI9IF0raWJsm9p8whnhBQLGbe4YVBH0CEomVSZ3MI6vt8Ocb/z8sU+Vmqsk764437grs6UlYDrRcjfdddd8feYbFlwMU7xHLCq+u7RMOC5s3CkHWCR9tsWC10ENaVGglnDYY0B/v3Ecse5+G5Z/o/4x5oapqAAxj4S04KWO54BiwjGJs4PiznjMu7CsGFBh3h14xECl2dB3/fFHWKPfhoGwfEDzxXzH3MCc5If18gYxRzpVydI9B3pzAEsnEaNGmWvm//7IPJ5DizAo5YFG0TCLk0IvGX15VxNdF5csQgdJni/GCO/C9tCgzUEt6Zfm4vOhbjDBUtaf1DMhOl+YvLE9I0Fy4cBlIGVQSWRgEnnHPy/ZdXrgp+xmCK2WKmSPOFbjbp27RpKJiCDN/Ebzu2JgGWg9F3tuBeC4o7BFqslIhyLSZjWUv+5c52s2F3smv85RBUiI1OLGyYsLCJYqZyg9ydOnpsfixfWpIqFFCsEz4CJEwGFlQr3j3PDJ2pvYVpqcK0hWohpRDz5sTssdrgnLAZ8a2YY5xDEfR/WCcYA30JGG8QtOXv27FCSJhK1QeJnaf8sIlyZIwdjFFZdfh8m3Gvceow1fpA8izkn7ly2bCbGQdoxIQj0ebwGwd8RU8bCzg99CBueJ4tMF4aApwhLGe2A9si98WN9w7h2/zsYg93PLJywmDEO+5ZBPkNoUjArPd1j08aDccy33367FXcIfB+8SJnOxs8HJOzShFUAliniSvzGQsICqycmU7dSDxtWnsRrMakxYAdXLsQwuXirsPA7FIMUkwfB+FhLguCSIY4lzMxH//hMplipcLtx35lUyDLDGkEsBW4nBA5ixo/pS6dDM2hxTMCVxv3n2hG3vuWOyQvRjehw14/wYAWLVTeZS6q49wDrB8HazuWElQA3FCIjUSHasAf0IAht4hwRMn5QfDADO8xBlckUa1wwoQkRTXFqV+4kUwM5x+eaSc7h/hO7xqRC+/TFHW0F4R02uPdYyPgLKKzmTOzEtmYCvw3Q/ljAujbNuMDzwHITdDciQMKMqRsyZIgVLgh5hA3PG5HnFhbcFyyFeEtclnImoL0RT8wzxjrsg5BhLOAc/IzdMGHBhJijz7lyJljs3DhMeySu0Be4YS2uiSfECo+1Gojho5wNljE/M5xxGMEX9oIKQY2LlbmGa/3x/z97xB1uWQR+Yd8RRSTsQoBVuh+c7WIJWJ3QoXB9pLtSS+Z2YDDFSsXgFYyhwuWDlSoTLh8sIVjCOAZuF6wRxJT49dyYVLg3YblefFiJckxEnZ8qzznhDmVgwULGQEtZk3TjadxAgHsBqwMDNYMJAylWS55BUNyxSiaOiSKp7rhYSxABqVpM/AGJUiW0LawjCAZnLcBKSHtA1CeKoQprQCduiXPA9etbjCkzwqKGgZ1FBYkaPIewExWIlUG8EkeJ6zFYOsPFvOKWzZS4YwHHvXeB6pR1oV1gJcJiyP1xgsu3aoQB14KFksmN6+Q+IyrcAoa+j+cg7GLMwTaIZwBXMxO321mH8Q8hQdJEosznMMYkXHrE9vqZzW63GUS9g3g/4nzDuvfu+nGn0u5dkgbijoUfCz3fLUvcGx6dTGQf+7gxjmOx4HYxxQg87gfJPGH3QdoY4w+GBTwRDiynLIApqcI8yPjI4jrM2GpczzxrksEYdxmHaIv9+/e3i2mekxO1fgJdaUDCLoUOjdmX1YkbUFgVMoDiEvAhM4dYAyxr6eB3RjoQgwYdCpEArMIICKYDJQuQDzOl3tVpc8UdGbBI0GDyZqBnIiGmj4mdc8rEZEq8kCurQSfmmbAydvFNCF6EJcImrLhCBwOkm0gdjz/+eEJxx0Tn7r37fxi1+7BUIGawzBCziaWSc3LxmwzqxNFgIcxEPA/xirhdsUzynBncsRhgsQLCEbCcsor2FzZhtQWC9DkmVlCEJAM62Xe+YKaPMthTrwqBEcZ9CE6MiDXOBYFFf8QN7opS43rjmXBe/t9lIhOXxRMih8kUSxkuKIQvVqJkY0K6EKjOxEoWJv0PlyPX64QcbYFsaRZYwQzydEFIs7Dj5WIFXf/mOeAG9He4ce0urHtPW2eBxuKJRYwbixj7GJsJ12BxSWwjHpWwrz8R7hpZVLCwY4HnYq79clNh3QPCLxgD6H8ON/YDYy8xhoyBuGTd+JfKOOyX7OJ73PgWjKND7DVt2tQ+H8CLQzhStgqC5wsSdkXEtwJg5sZq42oA4YLB/UJnZjCnhhUrRAY9t5oLA0z9TFAMFsS0+bWZEFsICybZYJp7JuBcMKs70z7ijoGde3LQQQdZdwiB6k7EhDmZIV4QdpQu4IUbgM7MpOp3ap+wjo91kIGSSY2B2y8wirgjC45n40S3I8yEBQZPnrNzs2ERJIbHZaI5qymDXxjlJIJgIeMZuwmVZ0BbxDrJwsOVuuE8GJDDFtYIZ1xvfvgBAzoCEnccgo5JBUsaz4KyL0zCzmqXKn4bIhidxYNvoSYwmz7g2jziF5ckk2zYixvEExMWk6uzymIZZDLHasSiA4HHcwnGv4YBLjZEm9uaLFkbxEWIsA27DVL0nGeNNdYtMLnHvBDbwS2j3O9TxX038Nxp/wh6+iBzAC4/t4sEC03GYDwZzAMuJCJb0N65LyyqSNjCu5AJYcN4R4wxz5h+jkuWuZFjksTkx9M6UmkHjLXMbVQYcNC+sIy6Yuv+9R133HE2DClIaRJ3EnbFALcSbhYmNgZR3IAuCxHrHXFdrJiZ8LHghZXODgygrI5cQDIrRI7t73mIiGQwx0IRFsHB0HVMrh1xywDrYEBjEkFcEX/mrDTB7bbShXPgPlO+hZgaJlQGWOJXOHYYwbk7Oz73hd0zOAcyPh2IDcS3v7tD2CAusYYxuTOBBDPPsNYEA9fDmlgRbTxbt2MHCx1inIih49kj7gjgDu6JGpawRpzh3keoBRcwWM5x/9Ev+AwLLZ4TIoTJxu0XmW4/QLDx3LlWrAbOQseE4lyAtH0mF7+qfVjiDtc/xya2iFhKFlNOVDiYaHkm3IMwikAHnx8LOe4x7tBgG2RspA0GC7On2gaTtR2s8yysEFm+qw1BwX1xpY7SIRhCg/WTpCg/EQvBQJ00XO/BWNJsiwl3r+j/uIBZ8LhzCFtcY8BgMY3VnnkHbwVuXwQ145PvuUi3vePm5+WqP3CdLLB9b4C79uuvv94aFqIeR1cYEnZFhIkKKwEuMMCtw+BBo2ZiY4Bxrh5WzWFvcs7k4bYnS1SjzaWzkzCQiZg6JqjgypMVO5NZcMCn9AUdDqEb9u4KvlvTFUP24biJgmUzASIHFwOTPK5oB+7RTFaT5x7jDqY+FgHy/jZJuEBxv/luqHRINDgyaWC1wOXCIsa5QxjI3U4jriByJsAiRS1ILDbBXQtobyw2yD51947ahpynHwOU6jNgMsP9x0ILSxHlG7CO0NYRnVw7yTFYS1hkhF0AF7cXLngsY4wzJC4QY8c5cG5BwsjC9L0OTNxYal2RaTwUwTZIu+AeYE1MF/++cb85vr+DCdZZBAXtwQkZ2j9CPl1RhXjD4ubg+zgWz9jtP+v/DkGBC5gFX6YoSjtKNGZkSmDyLIhpw8DgwiBok27nhzCNKsy1tDlnTCD8gHAMPFiMA25XjyOPPLLAcyuNSNgVESYM4hTI/sJigkXOVXJ3W2cx2fpB5GHCgIZrCWtIsEYbnYrtWfwkgjDFHXGCCCYsAwhbZynBBU05AbfXqJtEEB4MgEymwUKYYRC8NgSWqxeGJS+bq2SOzQoV6wnPv7DzLC7+AM2g6S8WXI0qxL77HIsPslHD2v8xuF2di59z0A6I7XSLClxAxNMQrJ6JZ+DHJiKoEE64fxIVngbaJQM8wiMM6zlWefqZX1IDcYWlkDgqsgFZdGG182vlhdkXueeMPUGLKKIGcROMI0xXUCKcaGdYO3GpEl7iSjjRt/kdCzl3rSwyaYMs+MK8bkQT14dLDmulH9/qLHcsdjkuzyGMIH3GN2ftdH2BxQH3gbhBZwH2a+LxO84v+HxSJVVLdxgW8sLajv/97h7zHv2BeQpLdpiFv+l7LGRpf1SacOLOhVm44vvE2jZq1KhUuV0TIWGXwsSCuZ1G5OLLWCmzgsMFl24GaLLOQMwWAzorQr/wKMKCjkRWblhWAQYsdx0IOVwPCAsEDAMnlkoyTxlAMbn720W5To77i0mQ1VumwZpJxhWxTJnY0WJn8Aw4B1yymQiMJyEFtxeDlp997Sw1xDLieghzRwX/b0kKYrImOYbFjGv3tAsEDYMrCxpcI35x5LAGV+4tFlEGdLdVFmApQFjS/hKJO8Qcnwmj3BATOu2eRRXn4MOCipgiFwLhW6nDnmBwfePyc8/AtXOs6bjD0nE3+/hlOYinRTRx7a4On7vPuOU5H7erDm0Qa2W6/dBvf1gHscpgKUQ4Irhq1apVwGqGAKVtYilycX/c+zDGRKxFWIddzBgxrvxM23extO44XK+rq5ku/j0g9AHRiIjGGl9Yu/KvGQGUShssbrIJ94byIm67yDB3lSEpiL5HO2QhS7IK3iIn7mgTjAHBReXvpVjcSdilAPFTBKS69HWq3hNTEmZJE9wYCClEpAtGp5QBbiD+zyDHhEpHYjALy+XDhEFALOZshBkrct8Fi6uXCZNBFXHH71lJ+1Xs/RVcNuD+EGOUTtZVGKI/7Mw7QDwzYSOiGNh41n7NNtoHAx+TGgIs7EENSxBtDisV7lU3iTvrIVZS3mNRg7U07AKsLvsWEcvkRnsjJMKBcENw8rlEey+HGQqAG5QJhokruGsD99+3ImUKFlgsKrFE+rUQKbVBwoDbSi0dENC0KV9Yc99ZVCZKQEFs4rbkuWBJTrcN+v2HBQMuPYSdE7P0M+L3aHN+KMi7775rM0JZ3LhCvWGAWOb6ecZO3LFwxSvhFjbuvDIB1mniCFk00c45FwRMoux6/xzw6vDZYFHsncFx8EC451DU8Yz5irkwzDGIsA/i+BDzDqziPHfiaYNxnFHd+7W4SNilAIM6m0ojfhgEibHzU75Twe+QxASxOmai5DgM5C4DkgGUbCA6LBYchF3YVirKF7Aq4thuoghOkHRaXCCslHA9uADysKxERXkf8i1ANt3zCV4rws7FUhJDgisOt4M/oQXFVFjtgOxj3Bq0B+cOYSILbqSNhQSrRtjCmpg9ykm4gGn+T7JMMIYJ60lwC6tMQT9HXHNM597F/USoAq6isMEqgcvTzwCmjAljAkKDeDYEHq5KFgDpFL528J0u4Yl+T5ukZBPuZcQdQm5n/TKMNshYh6hHZBBX6G/VxrNGyCG0+b2DZ0IsFmMji4+w2gThKBRiRzj64s6VtEkmMNKFxRTWSZcMRUwxxwsmaYB/rcS+EYLgttUrDghVPDG+O724Y3BYYxDPnOsIxlLTH2iLWO7CslJHCQm7NAZczMKkuoeZzk6gMoIO1wIDCGZ9rCJMHC6WjfdcAHuYpSRcB2WFzORFPAud28UNus4a7Mg33XSTHXwSpbcX99hOKGCx9OtvJRug/feJ9UpktSkp+NdCcDwFn7n/BIQ7mGgRd66ye5gEB28GVUSkeyZ+5iPuj0TB+mGulLEOMUEDWY8c3wXOEyztD+ju3LMh7ljYcf+xZOJ+xBVOmIRb/IR1DizmELKU0GEyx1LqhBtxfZQb4n1cn1h0fOETRhvAzYpr1Q8vYbwj1pY9j32LUnGtQjs7NolRhB9QUgNLEMkQiFm/TiH3GVcoQs5f3CC+U93hwT074ggRa35cKQucoLhjLMZ66tdZS4dg/0HA0MYAK6TfB+kDrmac/3f0EYwNxS3K6yyP4HavIFauKOLOP74f610cEvUb5lYs0U7I+p+hzyFA8WSIgkjYpQENPcyJhBgFssnYsYCBw303bhaEXbJ9PsN2ebLSZeJmYnV1uIJJIW4PVDeQIkbDSBzB1YC1koGcwQnR6Ajea/9nJjomwER7QpYE/GdIrAgDOC5GJmzurS9YmcSwpGLFoH5iJmL6sBLidufYbr9JPxuRgR9hEYaYKGzxhFsNNzDH9zMvsWTQNskCdmTL9e+smVTVJ2zBP68wXNGuZhpWQZ4DYwETHBmATLROaNFPuQ9YM8LY+zUIzxarPeORn5RBeSFiO3G70QYoexRm+AMLBuIYsUw6OD7WW7wkya41rDAARCVeCKyFuHuxmrvsayfufLdsWO3OLwvldgtxhc9JkKMP+Elz3CdiO/2t0qgIwLhQXFFHxjGLBK61uOLOH4cJlyA8wp8fioL/vcw9vpHAlVFCxPtzIu2S885mvy8pSNjlCTRO4lNwdbFSdR3DDVa4ocjEYoDPpvuRQF3czViO3ODOhOPXzyMOi/NOJWjY35CZVTaxe2SisWLGBcU145pO9HkHgoM4v0QWpJIGQfrELuJSYuJG3NAeEPb+wO/KeoSd/cqEwGRGe2MywzqByPQFpKtmz6QS9qBKoVsmF9o5x8cahoWINuYgtogFEIHkuRzUeUaEReCCdZnBYYCgZuLCveqHeGDNR9zRRzK9k4FrVwhYnj/P2hd3xBkzLpAwFGYoCN/FNSIygts0kohFX2ChGWbhdwdtif7HAhGBhBUOrwwCHkHlYqpdzF3w/NIBge5qX2IBRMDSz3jOjL1YbomrcyB8sOAietxY6DKY/V0migOWL9ybxRF3/jjMIoTzdMkrqcC2iG4XJRaYDq4Vwco5kjzI71lUFTcOsLQgYZcjEjVExBzxQ3QOfyID3LDEk2SqnEoQv8Mi7ghUJa2cFTpWJH+FjsXCbQCd6j1g1clEyUrYWacY5BGQWA18c3sit0Oi3SZKGlwLe27icnKTKM8BywkTGoN9omSAsNyfTFhMKriAHYhHnjnCkoEW6xmWMpKHwsx8AyxAWEO4VvoAwh43HJZLEhPoG6zQiavxa8TlclDHLcv5UW4jDHccwhprNZOpv6uCA4s0/Y8EDt9amQlcu8LN6sSdP/74NQTDsNi554howUrFeIew8J8v4g6Lfph1yvyMVsQU2ad+uRKOhcsPceeumfE4LPcr14dIxDqOaEXA+N+NN4I4QpI1SCLADU5/wAXvJ83xSrQ3dHFgEc1iuijiLri4TmUc9p8tYppyJoQAcM8R+P6evyx08FrR9qkCEPb4EyUk7HKA3xDpwMS0ud0MXAMn0xCTNnEPWC9o0MQbZbMR+x2Xc2RDZVylYWde0mFdQVdiunx3qhN3WATJ0vVJNZYkX8HFhgUIIRvcOcLFuyF6wrrvvvWTNoarC2Hlr5SBNojoYnKj7AnZj2G2AY7PhI2AREgSo0NbQ9jQF4g35Nmz6wvWKgb7XJS1SQbPikkv1bguB2VZEHVkvZPljbBhovc3uXfthM+luwd1ccUdfY14tqCgTNWDUNhYxuKOts4kTtv3j4FVLeznTjwjViGOx8Iq6H1AaBDrReY5rsIwQECSAOJg4YbFjbI5wXvKgopEORY8nB8i2/WBsKsAJBN3WC4T1ch0HpN0xmHaOG5cV1gdcU/iByLeL/6OF4O24dcOFDsiYZdDEElkn9IpGMQHDx4cjx9hdYgLio5O6QG2J3KuuFyJO590OpQ/MGCVIfGCARNBgYDDteXHWDCAkYnJpO7Oh0EHt0FJtdQle4Y8fwLzmWCCNREJ5sb9GLb71T1LBlUscRzb3yrOEUyOCWtQRcjhckI8+tfGZIa4I9aKAR1XmP/7fBrUE5WeKA64PCnp4pcZcRX8sVAGxV02Ba3vlmU8CnoT0m1/jHUkZeDexyLl4sucuMM1hzU/2faG6YK4QjCxrzIuPrIwETe4w31wyxKwH9ztJBUQSsQqujbMGId4ZNHC4g6XZFBAcs8+++wza00MQ9gUNo+QAZ1I3Ln90R1Y0bHmpiPqMBrQzxn7/XI9zHd8L/Oj23Upnysi5BMSdlnE70isRnCpYFZnpU5qPxY5rCFuQMENRWP3EwjSrcuVaumQMMRkcM9YApEZwPx9LunYDB4Mcr6QCA7iWJgyuW1VJvHvJaUjyHqlDqKbvBF3BKTjjkpW8DqdSc0/PvEqTGJusiI+homUgdTfEih4vLAGVay1xDQxeGO1ZeLyQdS5QH1/540oDepkXhLqwAQZ3L0E1yf3BUspJWUycf1F+S73/DmfMAU1z5UQD1yRuLNxv9EmXQwd4g5LNWNlJlzPeExIWvPDD2iT9D2EthOZjlS3pSvsvpPx6ZfzQPDRB4PiLljKJqzSUozDLOqCey+zyAiKO+Yq3x2LAEx3+0LuMeMfblhfNLr5jgoJLCgyuf921JCwywGksGOhIpbAh1gKLCZO6DCoEb+GW9bf3SGMzkyALbXnyD4jUaGolczdirG4EGTtBg7OA3er21c0eB8QdwhaOnlwGyvOJSoxFZSJoPYYiQDEjGApQMy7QZy4GlbvwW2iwjw+mX+IJz8YnUUHExsxPWHu9xiEZBcs1rR7wg545sRSBl2MtH1i/KIk5hL1K6zyuLuCNcoQU7QTEkmC/SEVkvWfnd1fP+uU70i3HxI/SKKOK/aMRYjxgDbJuOSEDLHHYVmq/eukzeP+R1gyHvtglcRyjRclaLlLF3+sZeFG28Yb4Qt33LHEbiIu6f+4QBknwsB/zlwnBYCJ78MDQoyznwiEcKNfBreGdG2huH0yWZvB9c04gOsVT1bQIEBMYz5Z6PMdCbsswyDFwMUAFowZA2InyPbxVyxkG/F5f1WZ7oTOhMpgSVwbYhJXZ6JOGiwpgvUglW3TcLM6d5WzOpJwgaUGV1NQvJAdGeY15wP+xIR4YkB1hU2JL8EyxQ4TDix3BFK7PYnDZOrUqbYN+C5X/1njAkFUsl1d0IoWBgzUWGn86yWeDssMA3tQ3CXKhi7pkDDkXMxOwBFLS7apbyVxbtkwEqeC1mL616hRo+ICvij1InHJpntsIHYSS407F8YCRC3ldYgzxZIdvOZUxF2iWp8uyYBFDe5eBF6w/hpjFkKbhUUmFpO0c+JXGeuI76MupS/u3E4z9Ams2mHuogLcX8YACoH7+09TRsQXd4w/xJCmi38PWeS75Ch3XVjumGMY87DkJkLirmhI2GWYRAMCK0VWaQwawSwmBlpWb37MDg2fThDGnpdYCxEUbnNrXG90Zr/gqCOY9UTwenFLijB4OSuUm7wRqs7qh7BgECe2JFjCANEThY7sixd3PUwWLiiYOEFWqm6HCcS/mzwZ7DIRT4UlmMB82meywtOcN4N62JOa23cV1yOiwgcrMhMZ7rDgpB4lUUewPsHyWIVIWnFWOqznZDwi7lItW1HUxR2Zjrh+3daAybYj8+877YaaYpxnOtslYo2jv5NwwkIRAUNMJfAeIo9EHue9SPfZc74IFuC+Mpa5zFPEJcKJhXYwaQJ3aFgWc/8aqBFKXJ9bWFGMnUVUUNxhxSTkJOxdXVg0UrbKbb3GGITHwNWs5F75C7p0xwD/2pkTmPswEnDfsRY6Ue3cslQHIOZRpIaEXQbxOwMdl1Wpi0fAFYm1jGBcgndZtbN6Z7DH5ZIpyDZ0KeSIPL/oJW4eZylJlMpe3ABZ4rYQqQgILFKAu4lJnYnM1eojvgRxR1xXovpUJVncMWASO8JE6oPrhxgW2oRfTd5NPMRV+kHaYYs7FhCs1l3cmm/VwJqXKHA7TKjPRmYnsWXBXQtoj4Qf+PckSnB/iSOlDXDtxFQhrNzWaSSSkEiAOxwRFDZM5jx7l5FJ1jnH9xcgjkT1Ios7DgRdf3gssMw4Sw0LOBKGXMkkd08Q+WG1exbQrug31xosI4OoZLHNQiaVepzFuQckHHA87oGPE3f0CX/XnUyMAcQvMzYxxrhyJljs3BzBPeI8/AoFYYwBXDdtz2X908c5FnGULnEQSzY1+1jgRGkxl00k7DKE3yAxK2MlQ8QRx0DRVzoMIoaVKitTVu64RhnMw96ayB8UKDTLSogSAgx0fiVzOhmd2k9ySFXU+RXC2cAbU77bt5CimnRkJhJf3BHLQZB42DEtuYRrweWBu9uvxUdFee4/wcm+gEFoYUXxsyMzATXrKN/AQOu7oIjrRIj7u0xkCqzG9AmyoIPb8jHp5EMpk0xA7KLLLMVahSvQ7TPr+g33g36TSthDMtx3kyzgjsd9ph26/X+xpOP2DU7kYZQWIvgdax+Tur8zAUlDxLkxHiDuELXE5DrCagdOsGAhSlQDjb5A28eC6e/mECY8VwQk50FZG/BdrAg63LL0i0zGt4K7B3gPuOfOi4LAY/HPOJSumAvuKMHi3c0DWK1pU0OGDLHzHzHFFOd2n41i+EW2kLDLMCQG+KtjzMx0aqxyCDteWLVo4H68U7rb4yTrkFgFcPtxDogLfwVHfA+1lRwM4qmWFPEHY64LYUeml7NYMrkFxR0DPPciKskRbkDCvcAKFKuEv4sGmdA8BywmBJBjxSLekEHdLzyaKZjccYfgGkHoI65ZJfOcsmUl5boZ1DmXRMVVoyTusM5ihWLxhnsNEY/1ikx4v4alc/2FtT1Z8F7iXsTt6Pbf9RcWtEXagy+8WPzhpktH1LF4wM3odqzBFUtpEyxkjC+UGSEjltJHuOfC2h7MB0GBiGCRjWhxGa9+G0P84QZPtyZhIrDEn3/++Tb8hThqPBfOYu6LOwQPi8BMj4OubWBoQNDyzN2uMn4YQKrn4bc9vEN8N25mjBqMN1gJnWHBxffRzvxMZIm61JCwyyCYluk0LhDaxTEQlItLA3FHHBHijvIWBKuHsedjcNcIOg8xW24Q4fjOHcLKlE6GqGMl60/oTDD+RuupQFYV7ldcIAhKitw6oYi447pxy2ba9Zcr3LPAvYOlBHHnW+OY1Ikpc24iJrhMF9/17y2WI2dB4PkjrLNd/Bdxx2SOhSpTGcC5BusLQeG4Vpncsc7z3EkgcfebUAisNbjJw96HGtcj7Q+Ik8VKiKfAdwdisWEc8C3LWJCwKjsrS6oQasKYQwwXgo7rp72ziOA+EIeLJQ+3bFjxZO7+cV99oYirt3r16lbc+dZql8gUVgHi4PMjw5YxnlhpjsXYx/W7nXYSJUdkYxwkgYPELRZ5hEfgXQjr3jvjBhZZ3yrPAga3s1tA0CYR+YyNUVrM5QoJuwxCAgQDOXEMuBj8OAbia5hMmchZobiYOzpWsF5RquACZjLhuFgNGVgQGJi7SaNHTLBKpkOzmvYrmYcxoGCNQ8giHBGQiFbiNrBYuP0EEb58hsywqKzQgvfOd0tjuWNAR/D6Lkmsmgz4iTL4Uj2+22YoEf7gieCnfRJgHsbxUwGLdp8+fSIj6H3IMCRmEguti7EiYQJh49dqRGTzftjbBvIsEc2IdgcWO6zxCComXNogQgfrqW8tpu/6uyOkA3G29HW8E9wLF0eG25Vn75Pu5O7aPfGMfD9jDiLalVxioYvlDgs5ghLByVgYVp06v9/54pHzINwE6PNY51nUuDI22e53rr9xD2h/hI24cwhDYLGgIUmDZJHg3MT9BoQti3/mJIfEXXpI2GUYJ5aY0FmhuNUgLlksVri+XEcicYEVnYtxSWdCR0Qh1uiwdBLcL8TzIShccDDxOxSnZJDLxITOZEYyiG99QLQyoZEV5cQd5xaVjuwP6FhKiWlk0nLFh7GKJBJ3PumIGz8+0lkCinKuPrl6Fu58oiTueN5M5mT5UavP3V9c8vRH6pNhpUB4IXrYYSFM3L3EEsr3+25XBA+LOhJVKI7uW4szJTAYc0gO8c8P1yfCKmzwViBeqYnHdWMlLFu2bDwblvOgPiCLaUReJmLaiF9DyOFeBY7N8dwCH+slwo56funuXpKIoiyUE/W3MJ4/VjgWCsTyunvuxhaKTfM+bRIvBq+SnCSXb0jYZRjXsZjcqZXEQE8HJo7Br1WV7t6bfufEIoeAIknBL2jKaozJhEklkXgMa0J114yAYVJzVgk3aSAmcQPRsX1Xb0kXd/79wyLBoMVKFEsJrg5c4Ah7XjwLLLSJahmmCtYJVzIFFy9unqLc03yykubTuYTpasb1iasbC5jr57hH6aMs7hB3YWwqn6wWJW4+Mk0psePq5jlxw6KD0hbZtNZiJSbel3GQfhD2MfGSsLClTh2wmMUVHNzZgLEYy1mYO0o46HuUDcEzg3eEEj60Bf7Pc8CSyz2nzAzu+bC3CszG3xUGbQrXPuI6WI+U4+EhYJcR4k7DtBIKCbusQUwFdYuIX2CQz8RgBgwarAixEHAcP13dxTsgtohnyHT2KS4eBI3L/vIFCLFEnGuUrDMOrKUkA7iUfmDwQui5XTYQ31gpyD4LS8xgAWblj3uJ7MNgpmki/GPjcgsrDEAUhMQYrGMIef6dabAIYQknBMI9YyxYZJ6/9tprSf8uG/2R80FMIupw/2YiphMhh1sbIU1/xCLnMoGBRJAwhPTO4F7jisR6zwLv4osvtlm3hMcQZwb+PBDWVoG4vUmEw0rJcy/qzkKI3DDmJXcuWGjxVBHHu7MaqBJ14SFhl0UYZJjMmdzTtdAl6pQIJuIWyEDCBYjASxSQTiwDloJsWEeI4UHQEpCN0GGVhmvCrywepQ5NIgiTJ9ZIVqz+PWZ1Sv0yF0MVVkq//7fE7GAh8PcXLsrfITxJbCmKGBTpZQAj7jJ5nxFzWIdJVsJqhQvYWe6Z7BEYvtUuFxAywP0Iy0ro2jKubJLRsFCyBRe7WyCiEHVunGGxi4UMwZOJMZCyKW6LMq4Pbw3HQ8ASd8zzd9spBms4hgE1M0lIQUSS4cxx8J4kcvUGQ0fCPCf3bBnzsdwRduB7qaI07ucbEnY5JEyLHaVLsID5demoTUUaO5trB12v2YxnYnWM4GSw4YX4SHWvwXyHFTqDGALOWWacK5oJF8tBsHxMOvfAf34M3KzQcf8iLHHLuqwz/3PBjEu3q4irQi8yB2KGGFP6ZFgWo2R9GEuVqxFG8hSxZiyosKC4YsD5QFi7GlBOBncrC1e+E7crQoV9mP1jcA+I6UpUDD1dGNe4z8Qt8oxJEEHA8AwopeI+g+sdy3rY4oYyOpSMcd4CShhxD4L7D0NwDMCjkG72c2HijgU9yXPBfWdF+EjYRQAsQ+3bt7dxa8Etmpy4w+Xn7/+XbVHFJMNggwsm7O1x8mlC4j3KB5AEg1vUr2KPmxNhm2j7tnSPjyjzA++xEuCK98UduCKkYRaeFcWDfkBdxzBqpfltgAUD3gBcfC6Wj75GP8eCe8YZZ9hdUJjosehFCbJdWUxhofPDT8i6JyyFUi/EtRJ7iiXTbamYKbDIIigR8fRF6vfhPXHPxR9/0xF3wb/FW4OL240Jfp1C4g5d4or/d5keA3xxx/3AmyQyi4RdRGBQR9wxmQetc8RbkIVJuZN8oaSb4X1RTHYv8SMuEYTfEVPJIIaFjvIWWFSxlJC8Esa1+8cnUYNipwQo+0HgTGoUgaZWGW2CrEdWzA4GfIm63BB2BiQJUVjlaHO0MSxG/h7NgOCh/BIB/ZkoAJzLe8k14bEA3M5kXdIfcLdiwSZBBU8BcahuH+ZMQxkr7jcxzdQCRFQT9xjW4trPgHdFfRlnOB5C0t8uEhijevToUWBXDRYBlMRKZwwoTuYti1u/eoPIDBJ2JYzC3BYIDOJneLk9Xx1YiUq6mMpHqP2EpZSkGEop4PpyIO7IhMZCwlY6lLhxsU5hPQtiZ0iUeOeddxL+/pJLLrFB5MTP+dvV4bLBPR6260VkH/q926oLKzgTNwlLJC75E3ZwIo2KuCPUgbZ9+eWX25pxZP/ipcAti9WceDeycOl7iYoAZwNiq7Eo+rUE04H+yxZtro9TVgqhh0WOBRxxzYwN/j0iYc2PrcYdz9jk7zKRSde576GJYtJcPiFhV4LwOwMrMxISGMBJl3cwkBOkygCSaJ9Jibv08JMdcKVxnxkgcTVPmDDBTqZ+5X5KOmAtwHLmspD9orTFgdgd507n+ExiWODchuZY5UigwXqBBccNpMT90Ub8Z09WbjIxKEoWJL6wRVVQvNEGcP0Hd7OJoqWEpASEE1YqXKD8DLj9EDq5CvsIZp27PphuXC3Flimfg4DF4ubHa2KhZ99VrJPUyWNRzxhEVrZffJpXom38dnbsdDNvWfCW9DCcfEfCrgSC640Bmy3JmMQpsukmd+eWZcL3N1UW6eMPaog0XDoEQftCjawvxB2ZaQ4CmJl4GVhTjasiJohg66CVBWGJqwnhRmwNK3faBHFEfnkHBxOLVsvRgrgyBI2L53TPF0GPe7a0ZDojUrBk+feABArKjfhuy2wTFHGpLq4RUf4uIPR1LG5YKoPHIDOXUjJY7gjRwQUbZvHpfMm8FYmRsCthkAxB+r6zthBHgwuQIpC4+hzEWLBalYUufMiqI46J+DliGoOrXoKWeR4EavurVGoXUuG/uPuAYpHxrS6sjl0QNtlu1IiixAoxRrNnz7bvY8mlXpZWxtEhmSCn/bmgdL+dsEUd2dH5lAGbLbBg0R/YkztbMXWZBDc7LmbXnxFpuGBJiiNRi9i9RPttk1hHwpQbb8IYD/It81bsiIRdCQLLEO4Vl/nKNjWs1Mn2YtXG6sy33Dkk7tLDv38IZuJ2KACLaxTrHHWpgpXrEdy4SXzXC6vtYOzjzqAGIbFCiERWuVhlEHEM6GSZAavk4P6iWPKUfRYd/AmSZBxiORH8fo1ELDPsaMAigu2xKLvjtvQrTXDtbJdGwlims19z0QYQUIgpB4KPXWaC4i5YbDzVdlASMm9FQSTs8hi/IzozOp2VOCsmfAoQuy1zXn75ZZsJx8rJLwIpUgfXgi+YZs2aZYW1L56571hMcUkk25Yo3VUytc/cbiGsvrHKsdcuLiZ/FwPKmhBTgwvGj6cR0YHMdpJ1eMb0d2qDufIeuLkoSMwYwPMncceNG6VJ3LEApo9kok5dLvD7MXHTWOhZuL3yyivx91nYY7Wlhh9zA3HWFGhOl3zJvBXFQ8IuT/EHYlZodCK/BhnFOFmlEUAPrODIvGQ1JQtd+lAugaBgdy+ZJLCUMWkGSxYg7rDcEdCcqS25EHcES1PBnl0DqJVHbCUlTVy8CudBwDRlVTKxTZPI/eKOorc8e2DRUa1aNWsZ9i3BuOmxmmRz71eReYhl49nTz8lwRcT74o6kLUJEiH1r06ZN2hnAucy8FekhYZfnbheCVAmAxrXnx8/ghqU2EnWSmOgxjeMSDDOWorTj7iX3mhUogxSxJSQx+MWAgQGWASy42XU2xB0DqdtQnEB5TejRE3U8V2KaWDz4BXj5N+KOiZZ4qsK+Q5TceWDatGlWSLGXK7CjBQu4oLijjSDI0i0Cn8vMW5E+EnZ5DHFciDo/E8qtjFi9M6FjKaI4LYH5Ud2mK5fgXkXMYRnDOsrA6sRUMLOLhJZMi6lE4o5kGtwuvtVGE3p0cGVL2PaNxVxw6zfEHXGYTKrFjeEUJSOmkixXxJSPE3dUQODfQVKx1udT5q1IHQm7PIWJGbeLq4lGoDzmbDoxcTXOQsMWXWQZRWWbrnwE1xZu70SWskQZd9kSd8TcEaxMWYvgfpii5OJPoFhjEGyEXlDShizXE044wfZ7HwQdVnu1gWiBpZaYOsQVme7gu1gRdLg/2VWDpJGoZN6K9CjDf4zIO3gsffv2Nd99953p2LGjmT59utltt91M1apVzdq1a81PP/1kXn/9dbPHHnvE/2bbtm1ml112yel5R5UFCxaY888/37Rq1crcdddd5pNPPjHnnXeead68ubn77rvNwQcfnPXzoX3Url3b/Pvf/463g+3bt5uyZctm9VxEZvjPf/5jXnjhBVOzZk1z00032fe+/PJLc8YZZ5hq1aqZQYMGmWOPPXaHv9M4EA0mT55spk2bZk477TQzYsQI8/3335uFCxfavr5161ZTvnx5+7kXX3zRvPHGG+aOO+5Iu+8z75QpU8Y89thjdkzr0KGDff/yyy83c+fONT169LD/Zh4C5qcaNWrE/17jT36gJ5BjkulqOlf37t1N5cqVzQMPPGA6d+5sbrnlFvP444+bbt26mQMOOMAKPR8N5pmjZcuWZty4ceaDDz4w11xzjWncuLH9mUGsTp06OTkf2gXto1KlSvH3NahGAxZuQ4cONY8++qj57LPP4u8fcsgh5tlnnzVr1qwxd955p3nllVd2+FuNA9GYCz7++GP7OvTQQ+2zRsgh5Ddt2mT/jbiDU0891QwfPtz2fYRVKvz3v/+NzzvLly83Dz74oLnhhhvMq6++at+/9957rchjscHCdtmyZeaEE04wl156aYHv0fiTH8hil+ds3LjRbN682ey7777x90455RSz995721WVMKXaUuZW2Fopl2wSPb8vvvjCXH311ebzzz83f//7380555wT/91XX31ljjrqKPOnP/3JWoxFycb1YyfqGd+hTZs2Zv/99zdTp061FrPLLrvMlCtXzsyaNcsu6BBk/BwW1113nTUc/PLLL1bc/frrr3Yhe+KJJ9rf82+8Rz/++KM1Lrz11ltxy6HII9J05YoUYVeAYBC0TzBQlRplZDsRrKpEidxCcDHJFPkSz6Q2ULLx2xGxtJQxcTUR+TeFhomrC9anJEte5WyixW233WZjqMnEBzJRqVdKIh2QgUopE4qkJ9q+qyRl3orMIYtdDmCV/emnn5oPP/ywyH8zf/58M3LkSLuyw1LEKi3s1ZooOrKUibAtNTfffLN1s/7+++9m/fr1ZsiQIdY6vHTpUhvXRH+/6KKLzFlnnVXgOxRTFw14jj179jRPP/202X333c0VV1xhzjzzTPvz119/bdsDcW+433lv7NixaT13v+0RVkKbYz6hrTlmzJhhRo0aZd2+1157renUqdMO56y2l4dkUDSKBGB5Y0U2YsSIeKXuom7STeabW2EFN4MX2UeWMhEWFILdb7/9rGVk48aNNsuZ8iauBhhFYbGeUIB25syZuT5dkSHIcGdHGXZzYHcJdrTBu0NJI3ZwCFrIwrDYZjPzVmQHmRqyDKsbLDwEoWK5u/DCC80+++xT6N/8/7I0Nq7LrbB23XXXLJ2xSIZ7FkIUFz/InX+/99571iJPLBMxTMRQ3X777aZRo0bWgle/fn0zbNgwG7CeKBNWlFx47i5OkgoIzBHz5s2ziQskLFSpUsV88803pl+/fmbRokUFvDTpWsvIvOXYWOOI2SRZh7huPzkDKx2WY9oeSVuiBJAlAVnqoe6cD3vssXmyv+9oMguQ//6UKVPi8RdCiJLNTTfdFBs2bFisRo0adhs76tP5m6pTjPyGG27YofCwYuuiAZ6Xf/zjH3bfX+qWYh3j2bZq1Sp25513xj8zYMAAu+NNus89OMew9zA16j755JPY3LlzY4cddpit2YnVGBJtS5YvscUiORJ2WeCKK66wSQ/OjE6BW8zeBMCyFRD7vCbreP7PmOerVq26Q3FSIUTJwJ8USYag0DWuMPZ5ZoxgP2J2GvATJI4++ujYhAkT7M9y/0cT2gDu97Zt28b69Olj9wY/88wzbXF0h3v2qYo7v+24Pcbh8MMPt+FBQOIELlcSNDZt2mTfU3JEyUPCLgu4LcBg9erV8QGejkMlefbic5lIyTri6NGjbcwNu0wIIUo2s2bNslX9R40aZX++77774lvD+fG4ZMQSayULXfT54Ycf7N7fCC22jttnn33sbg8+YQj7bGfeiuyjGLssQCFhYuJcNW+yYYnPog4RsTQUG6V+0DvvvFMg7sbFcJH9RAzEww8/bLOkhBAll1WrVpkLLrjAFhv/7bff7HuXXHKJOf30021xWOKY/vjHP9qi5Ow2QKwVsVRkIIroQq1S2sD7779v68VRQ27mzJmhxvXShti94uWXX7YZuBQhpg0yr7z77rs2A5tYOzJwialTLHfJROVOsghFHyn++O2339qyBs2aNYsP9Mcff7ypXr26GTx4sA2gdYwePdoWKZ0wYYL5wx/+kMOzF0KExUcffWS3BqP47D//+U/TunVrO+lSiJbtoUiYqFu3ri09odJGpQe/BAkJNbQLRL3/frqwFeX48eNNu3btzFNPPWUaNGhg1q1bZ4+HoPzrX/9aoL2ppEnJQ8Iuy7AdDFuFsTJiH0hf3JEBxyrq/vvvt+8tWbLE7k86YMAAWeqEiKC46927tzn88MOtgHNjQRBNrKWLoIgL4/m7GqgDBw603iCqMXAMDAdPPPGEefPNN82//vUv+1k8Sk2bNk37OkTukLDLAaSTs5lyUNyxlQybK/udmDR3ypwIIaK5RR2TLJaZK6+80u5BLESYYP1lr1m8QRS3JgzguOOOM23btrUlt7DS8Zm//e1vdm/al156SQuJEo6EXQ7FHfEU7PmIOZyB3V+hsZrSjgZClA5xd/HFF9sFHBMwLlghwgbRxp7D3333nV1AEEM3ZcoUM2jQINOqVasC1kJZiUs2EnY5dsseeeSR5pBDDjHPPPNMrk9HCJEjiG/CLUaClBZ0IlOsXbvWul0pfk0oQOXKlU3//v3NjTfeGP9MmPF8IjdI2IWE3xmK0zHISKpQoYIGcyFKOdp/WGQTxBy7ThxxxBE2oUJEBwm7EPCFHNv+kCJ+1VVX7fTvggO4BnQhSjeylogoZN6K3CIVkQYjRoyw/6czEHxKijhlTEgf3xl0IifiqGW3YcMGiTohSjmaWEU22piz55BA4Wokqu1FBymJFCElnGwisorAFXKkqOTOgk79lRFxNeecc4754osvsnDWQgghSjtBEadEiWghYZcilCihIvxrr71mzj77bPseBR190YZrlZePv6PEmDFjbIq5K1AqhBBCCJEOEnYp4MQbu0WwLdCMGTNsFXnepw6dq9iNa9WZvNevXx9/z4k6tgkbN26cig8LIYQQIhSUPFFM/ASHLVu22IzW6dOn28KPLVq0MCtWrLCZrnXq1LFbiBF3h5uWmkFU/wZ2liAjidIGCEIhhBBCiDCQsEtR1D3wwAM24YH4uFq1allxd8UVV9itwR566CFrqUPYuc+fd9551pI3Z84c67ol8YKNvoUQQgghwkLCLgVwobKJ8l133WWOPfZYK+ywzJHdeu6555pu3bpZa1wi2GmCXSeS7QsphBBCCJEqEnbFhHIm7OnIThGkivuQMk4yBeKuSZMm9t9CCCGEENlCyRPFZMmSJaZevXqmefPm8fecNiZlvHPnzuZf//qXjb0LZsQKIYQQQmQSCbsigjUOiKHD7YpwQ9C58iX8furUqWb58uXWFfvyyy/b+DqJOyGEEEJkCwm7JAQFmSvgeOKJJ5q3337bTJw40Qo6lxxBOZNHHnnEvP/++wX+TrtJCCGEECJb/F/BNZE0+5WYOqxw7CjRs2dP07VrVxtj16dPHyvmKGNC2RMKDWPN69GjR65PXwghhBClFCVP7CT79emnnzb169e3rtcXX3zRFiNu1KiRmTBhgrnllltMlSpV7KtatWr2d9Sswy2rLVqEEEIIkW0k7JIwadIkM2DAACvm2O7r+eefN6effrp56qmn4jtFkEixdu1aW5+uTZs21spH/J3beUIIIYQQIptIgSQB9ysCDlGH1Q7X6+jRo+17uGB///1306BBA/vyXbgSdUIIIYTIFYrsT8K6deusNe6FF14w559/vrnzzjvNRRddZH/35JNPmttvv93G1vkoUUIIIYQQuaTUKxFXxiTIkUceaT7//HO7/dc//vEPc+mll9r32SYMsUdGLHF3QgghhBD5Qqn1G/pFhYEYOlysJEF06dLFvqZMmWKtdog4XLP8+4YbbjCrV6+2v3Pfw++FEEIIIXJNqUyeIE6O3SOGDRtmf77uuuvM/fffb+rWrWsWL15s+vfvb0aMGGG2bt1qLrzwQrNo0SL7/uGHH2523313M23aNGW/CiGEECLvKJUWu6OOOspcc801tkwJIu+NN96wr1q1apk5c+aYs846y7pcH3roITN+/Hhbn+6TTz4xderUMYcccoiyX4UQQgiRl5Q6ZULmKhY5LG+XXHKJ+eqrr0zDhg1Ns2bNrFA77bTTbAwd/0fADR8+3NSoUcO+/O+QqBNCCCFEvlGq1InvOj3vvPOsxe7cc8+1wm7jxo1mzz33tDFzxNch7qhbh+VuzJgxpnLlyvHvUfarEEIIIfKRUqNQsLI5UUf83FVXXWWaN29uHn30UfPpp5+af/7zn/YzJEI4cffEE0+Y77//3lr3hBBCCCHynVJjsXNWNvZ0HTdunBVylCth/1esdbhlEX6DBg2yn0Xcde/e3b6C+8cKIYQQQuQjpUbYwcyZM83kyZNtqRLq1Dn69u1rhdxf//pXa7EjSzYo4iTqhBBCCJHvlCphRy26SpUqmcaNG8ffc3Xo2FVijz32sLF3JEr07t07p+cqhBBCCFFcSoWwc+Ltt99+K7DThCvhx/+feeYZ06pVK1uj7vjjj8/h2QohhBBCpEap8C+6nSGOO+4488UXX5hRo0bF3+e1adMmm0QxY8YMc+KJJ9pSJtSpE0IIIYQoSZS6nSfGjh1r+vXrZ/d+PfXUU0358uXN7bffbosQz58/X/XphBBCCFFiKXXCjsulRt0VV1xh3bLUriOm7sUXX9Q2YUIIIYQo0ZQ6YedYu3atWb9+vS1jom3ChBBCCBEFSq2wC6I6dUIIIYQo6UjYCSGEEEJEBJmohBBCCCEigoSdEEIIIUREkLATQgghhIgIEnZCCCGEEBFBwk4IIYQQIiJI2AkhhBBCRAQJOyGEEEKIiCBhJ4QQQggRESTshBBCCCEigoSdEEIIIUREkLATQgghhDDR4P8BWfLGd7/dqOIAAAAASUVORK5CYII=", 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" ] @@ -568,7 +548,6 @@ "source": [ "element_set = {a,b,c,d}\n", "S = ElementSet(element_set)\n", - "kc = KComplexity()\n", "result, elapsed_time = cf.tail_recursive(S)\n", "print(\"Result:\", result)\n", "print(\"Elapsed time:\", elapsed_time)\n", @@ -579,13 +558,13 @@ }, { "cell_type": "code", - "execution_count": 344, + "execution_count": 36, "id": "5c80b83a", "metadata": {}, "outputs": [ { "data": { - "image/png": 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", + "image/png": 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", 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" ] @@ -597,13 +576,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "Total K-complexity: 13\n", - "Total primitive counts: {'add': 0, 'append': 2, 'check_if_same_type': 0, 'dim_set': 0, 'flip': 1, 'implement': 0, 'list_create': 0, 'merge': 2, 'pair': 0, 'remove': 0, 'remove_item': 0, 'sample': 2, 'setminus': 4, 'write_all': 0, 'write_all_set': 0, 'write_random': 2}\n" + "Total K-complexity: 119\n", + "Total primitive counts: {'add': 0, 'append': 5, 'check_if_same_type': 13, 'dim_set': 0, 'flip': 7, 'implement': 0, 'list_create': 0, 'merge': 2, 'pair': 20, 'remove': 0, 'remove_item': 0, 'sample': 38, 'setminus': 28, 'write_all': 0, 'write_all_set': 0, 'write_random': 6}\n" ] }, { "data": { - "image/png": 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", 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", 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", + "image/png": 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", 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addappendcheck_if_same_typedim_setflipimplementlist_createmergepairremoveremove_itemsamplesetminuswrite_allwrite_all_setwrite_randomTotal
Cognitive Function (calls)
iterate (1x)020020000008600018
palindrome (1x)01101000200220009
alternate (1x)004010004005400018
chaining (1x)0000000060011400021
seriate (1x)00000000000000000
serial_crossed (1x)001010004002400214
center_embedded (1x)007010004008400226
tail_recursive (1x)020010020002400213
Total Counts for each Primitive Function05130700220003828006119
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" + ], + "text/plain": [ + " add append check_if_same_type \\\n", + "Cognitive Function (calls) \n", + "iterate (1x) 0 2 0 \n", + "palindrome (1x) 0 1 1 \n", + "alternate (1x) 0 0 4 \n", + "chaining (1x) 0 0 0 \n", + "seriate (1x) 0 0 0 \n", + "serial_crossed (1x) 0 0 1 \n", + "center_embedded (1x) 0 0 7 \n", + "tail_recursive (1x) 0 2 0 \n", + "Total Counts for each Primitive Function 0 5 13 \n", + "\n", + " dim_set flip implement \\\n", + "Cognitive Function (calls) \n", + "iterate (1x) 0 2 0 \n", + "palindrome (1x) 0 1 0 \n", + "alternate (1x) 0 1 0 \n", + "chaining (1x) 0 0 0 \n", + "seriate (1x) 0 0 0 \n", + "serial_crossed (1x) 0 1 0 \n", + "center_embedded (1x) 0 1 0 \n", + "tail_recursive (1x) 0 1 0 \n", + "Total Counts for each Primitive Function 0 7 0 \n", + "\n", + " list_create merge pair remove \\\n", + "Cognitive Function (calls) \n", + "iterate (1x) 0 0 0 0 \n", + "palindrome (1x) 0 0 2 0 \n", + "alternate (1x) 0 0 4 0 \n", + "chaining (1x) 0 0 6 0 \n", + "seriate (1x) 0 0 0 0 \n", + "serial_crossed (1x) 0 0 4 0 \n", + "center_embedded (1x) 0 0 4 0 \n", + "tail_recursive (1x) 0 2 0 0 \n", + "Total Counts for each Primitive Function 0 2 20 0 \n", + "\n", + " remove_item sample setminus \\\n", + "Cognitive Function (calls) \n", + "iterate (1x) 0 8 6 \n", + "palindrome (1x) 0 2 2 \n", + "alternate (1x) 0 5 4 \n", + "chaining (1x) 0 11 4 \n", + "seriate (1x) 0 0 0 \n", + "serial_crossed (1x) 0 2 4 \n", + "center_embedded (1x) 0 8 4 \n", + "tail_recursive (1x) 0 2 4 \n", + "Total Counts for each Primitive Function 0 38 28 \n", + "\n", + " write_all write_all_set \\\n", + "Cognitive Function (calls) \n", + "iterate (1x) 0 0 \n", + "palindrome (1x) 0 0 \n", + "alternate (1x) 0 0 \n", + "chaining (1x) 0 0 \n", + "seriate (1x) 0 0 \n", + "serial_crossed (1x) 0 0 \n", + "center_embedded (1x) 0 0 \n", + "tail_recursive (1x) 0 0 \n", + "Total Counts for each Primitive Function 0 0 \n", + "\n", + " write_random Total \n", + "Cognitive Function (calls) \n", + "iterate (1x) 0 18 \n", + "palindrome (1x) 0 9 \n", + "alternate (1x) 0 18 \n", + "chaining (1x) 0 21 \n", + "seriate (1x) 0 0 \n", + "serial_crossed (1x) 2 14 \n", + "center_embedded (1x) 2 26 \n", + "tail_recursive (1x) 2 13 \n", + "Total Counts for each Primitive Function 6 119 " + ] + }, + "metadata": {}, + "output_type": "display_data" } ], "source": [ @@ -627,7 +928,8 @@ "print('Total K-complexity: ', kc.get_total_k_complexity())\n", "print('Total primitive counts: ', kc.get_total_prim_counts())\n", "kc.plot_total_prim_counts()\n", - "kc.plot_cog_vs_prim()" + "kc.plot_cog_vs_prim()\n", + "kc.show_cog_prim_table()" ] } ], diff --git a/utils.py b/utils.py index 1cbb269..465c151 100644 --- a/utils.py +++ b/utils.py @@ -219,7 +219,7 @@ def plot_prim_counts(self): plt.bar(data.keys(), data.values()) plt.xticks(rotation=45, ha='right') plt.ylabel("Call Count") - plt.title(self.get_cog_name() + " Primitive Function Usage") + plt.title(self.get_cog_name() + " Primitive Function Usage" + " (" + str(self.get_k_complexity()) + " calls)") plt.tight_layout() plt.show() @@ -228,7 +228,7 @@ def plot_total_prim_counts(self): plt.bar(data.keys(), data.values()) plt.xticks(rotation=45, ha='right') plt.ylabel("Call Count") - plt.title("Total Primitive Function Usage") + plt.title("Total Primitive Function Usage" + " (" + str(self.get_total_k_complexity()) + " total calls)") plt.tight_layout() plt.show() @@ -252,8 +252,9 @@ def plot_cog_vs_prim(self): for d in self.cog_func_calls[cog]: for k in d: summed[k] += d[k] - avg = {k: summed[k] / call_count for k in prim_names} - averaged_data.append(avg) + summed_data = {k: summed[k] for k in prim_names} + averaged_data.append(summed_data) + color_map = cm.get_cmap('tab20', len(prim_names)) colors = {prim: color_map(i) for i, prim in enumerate(prim_names)} @@ -266,7 +267,43 @@ def plot_cog_vs_prim(self): plt.xticks(rotation=45, ha='right') plt.ylabel("Total Primitive Calls") - plt.title("All Cognitive Function Calls with Primitive Usage Breakdown") + plt.title("All Cognitive Function Calls with Primitive Usage Breakdown" + " (" + str(self.get_total_k_complexity()) + " total primitive calls)") plt.legend(title="Primitive Functions", bbox_to_anchor=(1.05, 1), loc='upper left') plt.tight_layout() plt.show() + + def show_cog_prim_table(self): + from IPython.display import display + import pandas as pd + + prim_names = list(self.call_counts.keys()) + valid_cog_fns = {"iterate", "palindrome", "alternate", "chaining", "seriate", "serial_crossed", "center_embedded", "tail_recursive"} + + table_data = {} + row_labels = [] + + for cog in self.cog_func_calls: + if cog not in valid_cog_fns or len(self.cog_func_calls[cog]) == 0: + continue + + call_count = len(self.cog_func_calls[cog]) + label = f"{cog} ({call_count}x)" + row_labels.append(label) + + summed = defaultdict(int) + for d in self.cog_func_calls[cog]: + for k in d: + summed[k] += d[k] + + row = [summed.get(pf, 0) for pf in prim_names] + table_data[label] = row + + df = pd.DataFrame.from_dict(table_data, orient='index', columns=prim_names) + total_row = df.sum(numeric_only=True) + total_row.name = "Total Counts for each Primitive Function" + df = pd.concat([df, pd.DataFrame([total_row])]) + df["Total"] = df.sum(axis=1) + df.index.name = "Cognitive Function (calls)" + + display(df) +