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StephenNneji merged 2 commits into from
Nov 29, 2024
Merged

Fixes lint failing on runner and adds example for user guide #96

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0cc4159
Fixes lint failing on runner and adds example for user guide
StephenNneji Nov 29, 2024
8078512
Addresses review comment
StephenNneji Nov 29, 2024
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4 changes: 2 additions & 2 deletions RATapi/events.py
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Original file line number Diff line number Diff line change
@@ -1,5 +1,5 @@
import os
from typing import Callable, List, Union
from typing import Callable, Union

from RATapi.rat_core import EventBridge, EventTypes, PlotEventData, ProgressEventData

Expand All @@ -21,7 +21,7 @@ def notify(event_type: EventTypes, data: Union[str, PlotEventData, ProgressEvent
callback(data)


def get_event_callback(event_type: EventTypes) -> List[Callable[[Union[str, PlotEventData, ProgressEventData]], None]]:
def get_event_callback(event_type: EventTypes) -> list[Callable[[Union[str, PlotEventData, ProgressEventData]], None]]:
"""Returns all callbacks registered for the given event type.

Parameters
Expand Down
213 changes: 213 additions & 0 deletions RATapi/examples/extras/two_contrast_example.py
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@@ -0,0 +1,213 @@
import numpy as np

import RATapi as RAT


def two_contrast_example():
# Two contrast example for the user guide
problem = RAT.Project(name="DSPC monolayers")
parameters = [
RAT.models.Parameter(name="Tails Thickness", min=10, value=20, max=30, fit=True),
RAT.models.Parameter(name="Heads Thickness", min=3, value=11, max=16, fit=True),
RAT.models.Parameter(name="Tails Roughness", min=2, value=5, max=9, fit=True),
RAT.models.Parameter(name="Heads Roughness", min=2, value=5, max=9, fit=True),
RAT.models.Parameter(name="Deuterated Tails SLD", min=4e-6, value=6e-6, max=2e-5, fit=True),
RAT.models.Parameter(name="Hydrogenated Tails SLD", min=-0.6e-6, value=-0.4e-6, max=0, fit=True),
RAT.models.Parameter(name="Deuterated Heads SLD", min=1e-6, value=3e-6, max=8e-6, fit=True),
RAT.models.Parameter(name="Hydrogenated Heads SLD", min=0.1e-6, value=1.4e-6, max=3e-6, fit=True),
RAT.models.Parameter(name="Heads Hydration", min=0, value=0.3, max=0.5, fit=True),
]

problem.parameters.extend(parameters)
H_Heads = RAT.models.Layer(
name="Hydrogenated Heads",
thickness="Heads Thickness",
SLD="Hydrogenated Heads SLD",
roughness="Heads Roughness",
hydration="Heads Hydration",
hydrate_with="bulk out",
)

D_Heads = RAT.models.Layer(
name="Deuterated Heads",
thickness="Heads Thickness",
SLD="Deuterated Heads SLD",
roughness="Heads Roughness",
hydration="Heads Hydration",
hydrate_with="bulk out",
)

D_Tails = RAT.models.Layer(
name="Deuterated Tails", thickness="Tails Thickness", SLD="Deuterated Tails SLD", roughness="Tails Roughness"
)

H_Tails = RAT.models.Layer(
name="Hydrogenated Tails",
thickness="Tails Thickness",
SLD="Hydrogenated Tails SLD",
roughness="Tails Roughness",
)

problem.layers.extend([H_Heads, D_Heads, H_Tails, D_Tails])

problem.background_parameters.set_fields(0, name="Backs Value ACMW")
problem.background_parameters.set_fields(0, value=5.5e-6)
problem.background_parameters.append(name="Backs Value D2O", min=1e-8, value=2.8e-6, max=1e-5)

problem.backgrounds.append(name="Background D2O", type="constant", value_1="Backs Value D2O")
problem.backgrounds.set_fields(0, name="Background ACMW", value_1="Backs Value ACMW")

problem.bulk_out.append(name="SLD ACMW", min=-0.6e-6, value=-0.56e-6, max=-0.3e-6, fit=True)

d13acmw20 = np.array(
[
[5.1793e-02, 1.8087e-05, 7.9683e-07],
[5.4383e-02, 1.4582e-05, 6.3691e-07],
[5.7102e-02, 1.3621e-05, 5.5407e-07],
[5.9957e-02, 1.2409e-05, 4.8014e-07],
[6.2955e-02, 1.0992e-05, 4.1824e-07],
[6.6103e-02, 1.0619e-05, 3.7541e-07],
[6.9408e-02, 1.0162e-05, 3.4945e-07],
[7.2878e-02, 1.0716e-05, 3.3763e-07],
[7.6522e-02, 8.3468e-06, 2.8040e-07],
[8.0348e-02, 7.5250e-06, 2.5702e-07],
[8.4365e-02, 6.4395e-06, 2.2528e-07],
[8.8584e-02, 6.0544e-06, 2.0545e-07],
[9.3013e-02, 5.9517e-06, 1.9417e-07],
[9.7664e-02, 5.6433e-06, 1.8108e-07],
[1.0255e-01, 4.8172e-06, 1.6076e-07],
[1.0767e-01, 4.8066e-06, 1.5520e-07],
[1.1306e-01, 4.1559e-06, 1.4115e-07],
[1.1871e-01, 4.1418e-06, 1.3926e-07],
[1.2465e-01, 3.4580e-06, 1.2273e-07],
[1.3088e-01, 3.2376e-06, 1.1791e-07],
[1.3742e-01, 3.0976e-06, 1.1948e-07],
[1.4429e-01, 2.7478e-06, 1.1518e-07],
[1.5151e-01, 2.5492e-06, 1.1573e-07],
[1.5908e-01, 2.7500e-06, 1.2812e-07],
[1.6704e-01, 2.1813e-06, 2.0450e-07],
[1.7539e-01, 1.8609e-06, 5.4900e-07],
[1.8416e-01, 1.9405e-06, 1.5660e-07],
[1.9337e-01, 1.7421e-06, 2.3280e-07],
[2.0304e-01, 1.8050e-06, 3.9820e-07],
[2.1319e-01, 1.5801e-06, 1.4110e-07],
[2.2385e-01, 1.6724e-06, 7.7900e-08],
[2.3504e-01, 1.4150e-06, 4.0820e-07],
[2.4679e-01, 1.4340e-06, 5.3180e-07],
[2.5913e-01, 1.3102e-06, 2.6000e-07],
[2.7209e-01, 1.3702e-06, 2.8540e-07],
[2.8569e-01, 1.2468e-06, 2.3230e-07],
[2.9998e-01, 1.2956e-06, 5.3240e-07],
[3.1497e-01, 1.2947e-06, 3.9940e-07],
[3.3072e-01, 1.2488e-06, 2.1390e-07],
[3.4726e-01, 1.4620e-06, 3.3640e-07],
[3.6462e-01, 1.3056e-06, 2.1600e-07],
[3.8285e-01, 1.4553e-06, 2.3170e-07],
[4.0200e-01, 1.1579e-06, 2.6740e-07],
[4.2210e-01, 1.1753e-06, 3.0940e-07],
[4.4320e-01, 1.0066e-06, 5.2040e-07],
[4.6536e-01, 1.1043e-06, 3.1870e-07],
[4.8863e-01, 1.2969e-06, 4.1670e-07],
[5.1306e-01, 1.2495e-06, 2.0890e-07],
[5.3871e-01, 1.3898e-06, 4.7560e-07],
[5.6565e-01, 1.1225e-06, 3.0470e-07],
[5.8877e-01, 8.3346e-07, 3.8944e-07],
]
)

d70d2o20 = np.array(
[
[5.1793e-02, 1.4943e-04, 3.2517e-06],
[5.4383e-02, 1.1882e-04, 2.5846e-06],
[5.7102e-02, 9.2164e-05, 2.0507e-06],
[5.9957e-02, 7.7813e-05, 1.7070e-06],
[6.2955e-02, 6.1143e-05, 1.3983e-06],
[6.6103e-02, 4.8033e-05, 1.1343e-06],
[6.9408e-02, 4.1379e-05, 1.0006e-06],
[7.2878e-02, 3.5090e-05, 8.6919e-07],
[7.6522e-02, 3.0350e-05, 7.5890e-07],
[8.0348e-02, 2.4115e-05, 6.5226e-07],
[8.4365e-02, 2.0755e-05, 5.7445e-07],
[8.8584e-02, 1.7500e-05, 4.9617e-07],
[9.3013e-02, 1.5011e-05, 4.3754e-07],
[9.7664e-02, 1.3632e-05, 3.9907e-07],
[1.0255e-01, 1.2997e-05, 3.7469e-07],
[1.0767e-01, 1.1656e-05, 3.4282e-07],
[1.1306e-01, 1.0820e-05, 3.2299e-07],
[1.1871e-01, 9.5831e-06, 3.0088e-07],
[1.2465e-01, 8.9996e-06, 2.8102e-07],
[1.3088e-01, 8.6498e-06, 2.7363e-07],
[1.3742e-01, 7.9412e-06, 2.7158e-07],
[1.4429e-01, 7.4042e-06, 2.6829e-07],
[1.5151e-01, 6.8321e-06, 2.6877e-07],
[1.5908e-01, 5.6809e-06, 2.6232e-07],
[1.6704e-01, 5.6646e-06, 2.8607e-07],
[1.7539e-01, 4.7762e-06, 2.7767e-07],
[1.8416e-01, 4.1971e-06, 2.7353e-07],
[1.9337e-01, 4.1815e-06, 2.9140e-07],
[2.0304e-01, 3.2725e-06, 2.3160e-07],
[2.1319e-01, 2.3244e-06, 4.2270e-07],
[2.2385e-01, 2.2892e-06, 1.4970e-07],
[2.3504e-01, 1.9198e-06, 8.1460e-07],
[2.4679e-01, 1.4828e-06, 1.0840e-07],
[2.5913e-01, 1.1450e-06, 4.7440e-07],
[2.7209e-01, 1.3047e-06, 1.8840e-07],
[2.8569e-01, 9.6081e-07, 3.9385e-07],
[2.9998e-01, 8.2280e-07, 2.3955e-07],
[3.1497e-01, 6.3219e-07, 3.5324e-07],
[3.3072e-01, 6.1254e-07, 5.0846e-07],
[3.4726e-01, 7.4092e-07, 2.2312e-07],
[3.6462e-01, 6.3584e-07, 4.2866e-07],
[3.8285e-01, 7.7287e-07, 2.9493e-07],
[4.0200e-01, 9.4637e-07, 2.3347e-07],
[4.2210e-01, 7.0576e-07, 3.3494e-07],
[4.4320e-01, 7.8969e-07, 2.3371e-07],
[4.6536e-01, 5.8374e-07, 3.2624e-07],
[4.8863e-01, 5.6711e-07, 6.0419e-07],
[5.1306e-01, 4.7782e-07, 3.4822e-07],
[5.3871e-01, 6.3813e-07, 4.3279e-07],
[5.6565e-01, 4.6186e-07, 1.8863e-07],
[5.8877e-01, 5.6129e-07, 4.3960e-07],
]
)

problem.data.append(name="H-tail / D-head / ACMW", data=d13acmw20)
problem.data.append(name="D-tail / H-head / D2O", data=d70d2o20)

problem.contrasts.append(
name="D-tail/H-Head/D2O",
background="Background D2O",
resolution="Resolution 1",
scalefactor="Scalefactor 1",
bulk_out="SLD D2O",
bulk_in="SLD Air",
data="D-tail / H-head / D2O",
)

problem.contrasts.append(
name="H-tail/D-Head/ACMW",
background="Background ACMW",
resolution="Resolution 1",
scalefactor="Scalefactor 1",
bulk_out="SLD ACMW",
bulk_in="SLD Air",
data="D-tail / H-head / D2O",
)

problem.contrasts.set_fields(0, model=["Deuterated Tails", "Hydrogenated Heads"])
problem.contrasts.set_fields(1, model=["Hydrogenated Tails", "Deuterated Heads"])

problem.background_parameters.set_fields(0, fit=True)
problem.background_parameters.set_fields(1, fit=True)
problem.scalefactors.set_fields(0, fit=True)
problem.bulk_out.set_fields(0, fit=True)

return problem


if __name__ == "__main__":
problem = two_contrast_example()
controls = RAT.Controls()
problem, results = RAT.run(problem, controls)

RAT.plotting.plot_ref_sld(problem, results, True)
3 changes: 2 additions & 1 deletion RATapi/utils/convert.py
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Original file line number Diff line number Diff line change
@@ -1,8 +1,9 @@
"""Utilities for converting input files to Python `Project`s."""

import json
from collections.abc import Iterable
from pathlib import Path
from typing import Iterable, Union
from typing import Union

from numpy import array, empty
from scipy.io.matlab import MatlabOpaque, loadmat
Expand Down
10 changes: 5 additions & 5 deletions RATapi/wrappers.py
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Original file line number Diff line number Diff line change
@@ -1,6 +1,6 @@
import pathlib
from contextlib import suppress
from typing import Callable, Tuple
from typing import Callable

import numpy as np
from numpy.typing import ArrayLike
Expand Down Expand Up @@ -47,12 +47,12 @@ def __init__(self, filename: str) -> None:
self.engine.cd(str(path.parent), nargout=0)
self.function_name = path.stem

def getHandle(self) -> Callable[[ArrayLike, ArrayLike, ArrayLike, int, int], Tuple[ArrayLike, float]]:
def getHandle(self) -> Callable[[ArrayLike, ArrayLike, ArrayLike, int, int], tuple[ArrayLike, float]]:
"""Returns a wrapper for the custom MATLAB function

Returns
-------
wrapper : Callable[[ArrayLike, ArrayLike, ArrayLike, int, int], Tuple[ArrayLike, float]]
wrapper : Callable[[ArrayLike, ArrayLike, ArrayLike, int, int], tuple[ArrayLike, float]]
The wrapper function for the MATLAB callback

"""
Expand Down Expand Up @@ -95,12 +95,12 @@ class DylibWrapper:
def __init__(self, filename, function_name) -> None:
self.engine = RATapi.rat_core.DylibEngine(filename, function_name)

def getHandle(self) -> Callable[[ArrayLike, ArrayLike, ArrayLike, int, int], Tuple[ArrayLike, float]]:
def getHandle(self) -> Callable[[ArrayLike, ArrayLike, ArrayLike, int, int], tuple[ArrayLike, float]]:
"""Returns a wrapper for the custom dynamic library function

Returns
-------
wrapper : Callable[[ArrayLike, ArrayLike, ArrayLike, int, int], Tuple[ArrayLike, float]]
wrapper : Callable[[ArrayLike, ArrayLike, ArrayLike, int, int], tuple[ArrayLike, float]]
The wrapper function for the dynamic library callback

"""
Expand Down
32 changes: 19 additions & 13 deletions tests/test_inputs.py
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Original file line number Diff line number Diff line change
Expand Up @@ -832,19 +832,25 @@ def check_cells_equal(actual_cells, expected_cells) -> None:
mocked_matlab_future = mock.MagicMock()
mocked_engine = mock.MagicMock()
mocked_matlab_future.result.return_value = mocked_engine
with mock.patch.object(
RATapi.wrappers.MatlabWrapper,
"loader",
mocked_matlab_future,
), mock.patch.object(RATapi.rat_core, "DylibEngine", mock.MagicMock()), mock.patch.object(
RATapi.inputs,
"get_python_handle",
mock.MagicMock(return_value=dummy_function),
), mock.patch.object(
RATapi.wrappers.MatlabWrapper,
"getHandle",
mock.MagicMock(return_value=dummy_function),
), mock.patch.object(RATapi.wrappers.DylibWrapper, "getHandle", mock.MagicMock(return_value=dummy_function)):
with (
mock.patch.object(
RATapi.wrappers.MatlabWrapper,
"loader",
mocked_matlab_future,
),
mock.patch.object(RATapi.rat_core, "DylibEngine", mock.MagicMock()),
mock.patch.object(
RATapi.inputs,
"get_python_handle",
mock.MagicMock(return_value=dummy_function),
),
mock.patch.object(
RATapi.wrappers.MatlabWrapper,
"getHandle",
mock.MagicMock(return_value=dummy_function),
),
mock.patch.object(RATapi.wrappers.DylibWrapper, "getHandle", mock.MagicMock(return_value=dummy_function)),
):
assert list(actual_cells.f14) == expected_cells.f14

for index in chain(range(3, 6), range(7, 14), range(15, 21)):
Expand Down