From 2cc89d4400d732ea1f60e04b32cbc1cc0ed967a7 Mon Sep 17 00:00:00 2001 From: domna Date: Wed, 15 Oct 2025 22:12:19 +0200 Subject: [PATCH 1/9] Use mkdocs with restructuring --- docs/Makefile | 30 - docs/_static/basic_usage.png | Bin 299935 -> 0 bytes docs/_static/custom_fitting.png | Bin 55484 -> 0 bytes docs/_static/mueller_matrix.png | Bin 582482 -> 0 bytes docs/_static/multilayer.png | Bin 398859 -> 0 bytes docs/_static/style.css | 23 - docs/authors.rst | 2 - docs/changelog.rst | 2 - docs/conf.py | 321 ----- docs/contributing.rst | 1 - docs/database.rst | 6 - docs/dispersions.rst | 279 ---- docs/experiment.rst | 8 - docs/helpers.rst | 8 - docs/index.md | 4 + docs/index.rst | 91 -- docs/installation.rst | 49 - docs/js/mathjax.js | 19 + docs/kkr.rst | 5 - docs/license.rst | 7 - docs/materials.rst | 41 - docs/modules.rst | 20 - docs/plot.rst | 91 -- docs/read_write.rst | 11 - docs/reference/api_documentation.md | 9 + docs/requirements.txt | 1855 --------------------------- docs/result.rst | 8 - docs/solvers.rst | 49 - docs/structure.rst | 41 - mkdocs.yml | 29 + pyproject.toml | 10 +- src/elli/kkr/kkr.py | 28 +- 32 files changed, 80 insertions(+), 2967 deletions(-) delete mode 100644 docs/Makefile delete mode 100644 docs/_static/basic_usage.png delete mode 100644 docs/_static/custom_fitting.png delete mode 100644 docs/_static/mueller_matrix.png delete mode 100644 docs/_static/multilayer.png delete mode 100644 docs/_static/style.css delete mode 100644 docs/authors.rst delete mode 100644 docs/changelog.rst delete mode 100644 docs/conf.py delete mode 100644 docs/contributing.rst delete mode 100644 docs/database.rst delete mode 100644 docs/dispersions.rst delete mode 100644 docs/experiment.rst delete mode 100644 docs/helpers.rst create mode 100644 docs/index.md delete mode 100644 docs/index.rst delete mode 100644 docs/installation.rst create mode 100644 docs/js/mathjax.js delete mode 100644 docs/kkr.rst delete mode 100644 docs/license.rst delete mode 100644 docs/materials.rst delete mode 100644 docs/modules.rst delete mode 100644 docs/plot.rst delete mode 100644 docs/read_write.rst create mode 100644 docs/reference/api_documentation.md delete mode 100644 docs/requirements.txt delete mode 100644 docs/result.rst delete mode 100644 docs/solvers.rst delete mode 100644 docs/structure.rst create mode 100644 mkdocs.yml diff --git a/docs/Makefile b/docs/Makefile deleted file mode 100644 index 428783ea..00000000 --- a/docs/Makefile +++ /dev/null @@ -1,30 +0,0 @@ -# Makefile for Sphinx documentation -# - -# You can set these variables from the command line, and also -# from the environment for the first two. -SPHINXOPTS ?= -SPHINXBUILD ?= sphinx-build -SOURCEDIR = . -BUILDDIR = _build -AUTODOCDIR = api - -# User-friendly check for sphinx-build -ifeq ($(shell which $(SPHINXBUILD) >/dev/null 2>&1; echo $?), 1) -$(error "The '$(SPHINXBUILD)' command was not found. 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- if tuple(sphinx.__version__.split(".")) >= ("1", "7"): - # This is a rudimentary parse_version to avoid external dependencies - args = args[1:] - - # apidoc.main(args) -except Exception as e: - print("Running `sphinx-apidoc` failed!\n{}".format(e)) - -# -- General configuration --------------------------------------------------- - -# If your documentation needs a minimal Sphinx version, state it here. -# needs_sphinx = '1.0' - -# Add any Sphinx extension module names here, as strings. They can be extensions -# coming with Sphinx (named 'sphinx.ext.*') or your custom ones. -extensions = [ - "sphinx.ext.autodoc", - "sphinx.ext.autosectionlabel", - "sphinx.ext.intersphinx", - "sphinx.ext.todo", - "sphinx.ext.autosummary", - "sphinx.ext.viewcode", - "sphinx.ext.coverage", - "sphinx.ext.doctest", - "sphinx.ext.ifconfig", - "sphinx.ext.mathjax", - "sphinx.ext.napoleon", - "sphinx_plotly_directive", - "sphinx_rtd_theme", - "sphinx_mdinclude", - "sphinx_gallery.gen_gallery", - "sphinxcontrib.mermaid", -] - -plotly_html_show_source_link = False -plotly_html_show_formats = False -plotly_pre_code = "import elli" - - -image_scrapers = ( - "matplotlib", - plotly_sg_scraper, -) - -sphinx_gallery_conf = { - "examples_dirs": "../examples/gallery", # path to your example scripts - "gallery_dirs": "auto_examples", # path to where to save gallery generated output - "capture_repr": ("_repr_html_", "__repr__"), - "image_scrapers": image_scrapers, - "remove_config_comments": True, - "download_all_examples": False, - "show_signature": False, - "first_notebook_cell": None, - "within_subsection_order": FileNameSortKey, -} - -# Add any paths that contain templates here, relative to this directory. -templates_path = ["_templates"] - -# The suffix of source filenames. -source_suffix = [".rst", ".md"] - -autoclass_content = "both" - -# The encoding of source files. -# source_encoding = 'utf-8-sig' - -# The master toctree document. -master_doc = "index" - -# General information about the project. -project = "pyElli" -copyright = "2021, dobener" - -# The version info for the project you're documenting, acts as replacement for -# |version| and |release|, also used in various other places throughout the -# built documents. -# -# version: The short X.Y version. -# release: The full version, including alpha/beta/rc tags. -# If you don’t need the separation provided between version and release, -# just set them both to the same value. -try: - from elli import __version__ as version -except ImportError: - version = "" - -if not version or version.lower() == "unknown": - version = os.getenv("READTHEDOCS_VERSION", "unknown") # automatically set by RTD - -release = version - -# The language for content autogenerated by Sphinx. Refer to documentation -# for a list of supported languages. -# language = None - -# There are two options for replacing |today|: either, you set today to some -# non-false value, then it is used: -# today = '' -# Else, today_fmt is used as the format for a strftime call. -# today_fmt = '%B %d, %Y' - -# List of patterns, relative to source directory, that match files and -# directories to ignore when looking for source files. -exclude_patterns = ["_build", "Thumbs.db", ".DS_Store", ".venv"] - -# The reST default role (used for this markup: `text`) to use for all documents. -# default_role = None - -# If true, '()' will be appended to :func: etc. cross-reference text. -# add_function_parentheses = True - -# If true, the current module name will be prepended to all description -# unit titles (such as .. function::). -# add_module_names = True - -# If true, sectionauthor and moduleauthor directives will be shown in the -# output. They are ignored by default. -# show_authors = False - -# The name of the Pygments (syntax highlighting) style to use. -pygments_style = "sphinx" - -# A list of ignored prefixes for module index sorting. -# modindex_common_prefix = [] - -# If true, keep warnings as "system message" paragraphs in the built documents. -# keep_warnings = False - -# If this is True, todo emits a warning for each TODO entries. The default is False. -todo_emit_warnings = True - -# Typehint settings -autodoc_typehints = "none" - -# -- Options for HTML output ------------------------------------------------- - -# The theme to use for HTML and HTML Help pages. See the documentation for -# a list of builtin themes. -html_theme = "sphinx_rtd_theme" - -# Theme options are theme-specific and customize the look and feel of a theme -# further. For a list of options available for each theme, see the -# documentation. -html_theme_options = {"sidebar_width": "300px", "page_width": "1200px"} - -# Add any paths that contain custom themes here, relative to this directory. -# html_theme_path = [] - -# The name for this set of Sphinx documents. If None, it defaults to -# " v documentation". -# html_title = None - -# A shorter title for the navigation bar. Default is the same as html_title. -# html_short_title = None - -# The name of an image file (relative to this directory) to place at the top -# of the sidebar. -html_logo = "../logo/logo_bw.svg" - -# The name of an image file (within the static path) to use as favicon of the -# docs. This file should be a Windows icon file (.ico) being 16x16 or 32x32 -# pixels large. -# html_favicon = None - -# Add any paths that contain custom static files (such as style sheets) here, -# relative to this directory. They are copied after the builtin static files, -# so a file named "default.css" will overwrite the builtin "default.css". -html_static_path = ["_static"] -html_css_files = ["style.css"] - -# If not '', a 'Last updated on:' timestamp is inserted at every page bottom, -# using the given strftime format. -# html_last_updated_fmt = '%b %d, %Y' - -# If true, SmartyPants will be used to convert quotes and dashes to -# typographically correct entities. -# html_use_smartypants = True - -# Custom sidebar templates, maps document names to template names. -# html_sidebars = {} - -# Additional templates that should be rendered to pages, maps page names to -# template names. -# html_additional_pages = {} - -# If false, no module index is generated. -# html_domain_indices = True - -# If false, no index is generated. -# html_use_index = True - -# If true, the index is split into individual pages for each letter. -# html_split_index = False - -# If true, links to the reST sources are added to the pages. -# html_show_sourcelink = True - -# If true, "Created using Sphinx" is shown in the HTML footer. Default is True. -# html_show_sphinx = True - -# If true, "(C) Copyright ..." is shown in the HTML footer. Default is True. -# html_show_copyright = True - -# If true, an OpenSearch description file will be output, and all pages will -# contain a tag referring to it. The value of this option must be the -# base URL from which the finished HTML is served. -# html_use_opensearch = '' - -# This is the file name suffix for HTML files (e.g. ".xhtml"). -# html_file_suffix = None - -# Output file base name for HTML help builder. -htmlhelp_basename = "pyElli-doc" - - -# -- Options for LaTeX output ------------------------------------------------ - -latex_elements = { - # The paper size ("letterpaper" or "a4paper"). - # "papersize": "letterpaper", - # The font size ("10pt", "11pt" or "12pt"). - # "pointsize": "10pt", - # Additional stuff for the LaTeX preamble. - # "preamble": "", -} - -# Grouping the document tree into LaTeX files. List of tuples -# (source start file, target name, title, author, documentclass [howto/manual]). -latex_documents = [ - ("index", "user_guide.tex", "pyElli Documentation", "dobener", "manual") -] - -# The name of an image file (relative to this directory) to place at the top of -# the title page. -# latex_logo = "" - -# For "manual" documents, if this is true, then toplevel headings are parts, -# not chapters. -# latex_use_parts = False - -# If true, show page references after internal links. -# latex_show_pagerefs = False - -# If true, show URL addresses after external links. -# latex_show_urls = False - -# Documents to append as an appendix to all manuals. -# latex_appendices = [] - -# If false, no module index is generated. -# latex_domain_indices = True - -# -- External mapping -------------------------------------------------------- -python_version = ".".join(map(str, sys.version_info[0:2])) -intersphinx_mapping = { - "sphinx": ("https://www.sphinx-doc.org/en/master", None), - "python": ("https://docs.python.org/" + python_version, None), - "matplotlib": ("https://matplotlib.org", None), - "numpy": ("https://numpy.org/doc/stable", None), - "sklearn": ("https://scikit-learn.org/stable", None), - "pandas": ("https://pandas.pydata.org/pandas-docs/stable", None), - "scipy": ("https://docs.scipy.org/doc/scipy/reference", None), - "setuptools": ("https://setuptools.readthedocs.io/en/stable/", None), - "pyscaffold": ("https://pyscaffold.org/en/stable", None), -} - -print(f"loading configurations for {project} {version} ...", file=sys.stderr) diff --git a/docs/contributing.rst b/docs/contributing.rst deleted file mode 100644 index 4fc50161..00000000 --- a/docs/contributing.rst +++ /dev/null @@ -1 +0,0 @@ -.. mdinclude:: ../CONTRIBUTING.md diff --git a/docs/database.rst b/docs/database.rst deleted file mode 100644 index 859f815a..00000000 --- a/docs/database.rst +++ /dev/null @@ -1,6 +0,0 @@ -=================== -Dispersion Database -=================== - -.. autoclass:: elli.db.RII - :members: diff --git a/docs/dispersions.rst b/docs/dispersions.rst deleted file mode 100644 index a73b004b..00000000 --- a/docs/dispersions.rst +++ /dev/null @@ -1,279 +0,0 @@ -=========== -Dispersions -=========== - -The dispersions are the central part of pyElli and the transfer-matrix method. -They describe the change of dielectric function or refractive index with the wavelength. -In pyElli the default wavelength unit is nm. -Each dispersion has two distinct sets of parameters: - - * Parameters which can be given only once (single parameters). - * Parameters which can be given in multiple sets (repeated parameters), - e.g. a set of oscillator parameters. - -The syntax for each of the parameter sets is different. -For the single parameters they are given in the class constructor: - - .. highlight:: python - .. code-block:: python - - Cauchy(n0=1.458, n1=3.54e-3, n2=0, k0=0, k1=0, k2=0) - -Repeated parameters are added via the add() function: - - .. highlight:: python - .. code-block:: python - - Sellmeier().add(A=1, B=1).add(A=1, B=2) - -For dispersions having both, single and repeated parameters can be used together: - - .. highlight:: python - .. code-block:: python - - TaucLorentz(Eg=2).add(A=10, E=2.5, C=0.1) - -If parameters are not fully provided, they are set to their respective default values. -The available parameters and their respective default values -are given in the respective class documentation. - -All classes inherit from the abstract base class `Dispersion`_. -It provides basic functionality, such as returning dataframes or arrays -containing the wavelength dependent dielectric function of the -dispersion relation at current parameter set. - -Dispersions can be added with the `+` operator, or if you want to chain -more than two dispersions together you may have a look at the `DispersionSum`_ class. - -PyElli also provides tabulated dispersions from the Refractiveindex.info database. -They can be accessed with the :class:`RII` class. - - -Constant Refractive Index -========================= -.. autoclass:: elli.dispersions.ConstantRefractiveIndex - -Epsilon Infinity -================ -.. autoclass:: elli.dispersions.EpsilonInf - -Cauchy -====== -.. autoclass:: elli.dispersions.Cauchy - -.. plotly:: - - fig = elli.Cauchy(n0=1.45, n1=36).get_dielectric_df().plot(backend="plotly") - fig.update_xaxes(title="Wavelength (nm)") - fig.update_yaxes(title="Dielectric function") - fig.data[1].visible = "legendonly" - fig.update_layout(title="Cauchy dispersion with n0=1.45 and n1=36") - -.. autoclass:: elli.dispersions.CauchyUrbach - -.. plotly:: - - fig = elli.CauchyUrbach(n0=1.45, B=0.005, D=0.0001).get_dielectric_df().plot(backend="plotly") - fig.update_xaxes(title="Wavelength (nm)") - fig.update_yaxes(title="Dielectric function") - fig.update_layout(title="CauchyUrbach dispersion with n0=1.45, B=0.005, D=0.0001, Eg=2 and Eu=0.5") - -.. autoclass:: elli.dispersions.CauchyCustomExponent - -Sellmeier -========= -.. autoclass:: elli.dispersions.Sellmeier - -.. plotly:: - - fig = elli.Sellmeier().add(A=1, B=1e-2).get_dielectric_df().plot(backend="plotly") - fig.update_xaxes(title="Wavelength (nm)") - fig.update_yaxes(title="Dielectric function") - fig.data[1].visible = "legendonly" - fig.update_layout(title="Sellmeier dispersion with A=1 and B=1e-2") - -.. autoclass:: elli.dispersions.SellmeierCustomExponent - -Drude -===== - -Energy parameters ------------------ -.. autoclass:: elli.dispersions.DrudeEnergy - -.. plotly:: - - fig = elli.DrudeEnergy(A=10, gamma=0.1).get_dielectric_df().plot(backend="plotly") - fig.update_xaxes(title="Wavelength (nm)") - fig.update_yaxes(title="Dielectric function") - fig.update_layout(title="Drude dispersion with A=10 and gamma=0.1") - -Resistivity parameters ----------------------- -.. autoclass:: elli.dispersions.DrudeResistivity - -.. plotly:: - - fig = elli.DrudeResistivity(rho_opt=1e-8, tau=1e-8).get_dielectric_df().plot(backend="plotly") - fig.update_xaxes(title="Wavelength (nm)") - fig.update_yaxes(title="Dielectric function") - fig.update_layout(title="Drude dispersion with rho_opt=tau=1e-8") - -Lorentz -======= - -Wavelength parameters ---------------------- -.. autoclass:: elli.dispersions.LorentzLambda - -.. plotly:: - - fig = elli.LorentzLambda().add(1, 500, 100).get_dielectric_df().plot(backend="plotly") - fig.update_xaxes(title="Wavelength (nm)") - fig.update_yaxes(title="Dielectric function") - fig.update_layout(title="Lorentz dispersion with A=1, lambda_r=500 and gamma=100") - - -Energy parameters ------------------ -.. autoclass:: elli.dispersions.LorentzEnergy - -.. plotly:: - - fig = elli.LorentzEnergy().add(1, 2, 0.2).get_dielectric_df().plot(backend="plotly") - fig.update_xaxes(title="Wavelength (nm)") - fig.update_yaxes(title="Dielectric function") - fig.update_layout(title="Lorentz dispersion with A=1, E=2 and gamma=0.2") - -Tauc-Lorentz -============ -.. autoclass:: elli.dispersions.TaucLorentz - -.. plotly:: - - fig = elli.TaucLorentz(Eg=2).add(20, 2.2, 1).get_dielectric_df().plot(backend="plotly") - fig.update_xaxes(title="Wavelength (nm)") - fig.update_yaxes(title="Dielectric function") - fig.update_layout(title="Tauc-Lorentz dispersion with Eg=2 and A=20, E=2.2 and C=1") - -Cody-Lorentz -============ -.. autoclass:: elli.dispersions.CodyLorentz - -.. plotly:: - - fig = elli.CodyLorentz().get_dielectric_df().plot(backend="plotly") - fig.update_xaxes(title="Wavelength (nm") - fig.update_yaxes(title="Dielectric function") - fig.update_layout(title="Cody-Lorentz dispersion with default values") - - -Gaussian -======== -.. autoclass:: elli.dispersions.Gaussian - -.. plotly:: - - fig = elli.Gaussian().add(1, 2, 0.2).get_dielectric_df().plot(backend="plotly") - fig.update_xaxes(title="Wavelength (nm)") - fig.update_yaxes(title="Dielectric function") - fig.update_layout(title="Gaussian dispersion with A=1, E=2 and sigma=0.2") - -Tanguy -====== -.. autoclass:: elli.dispersions.Tanguy - -.. plotly:: - - fig = elli.Tanguy(Eg=2.5).get_dielectric_df().plot(backend="plotly") - fig.update_xaxes(title="Wavelength (nm)") - fig.update_yaxes(title="Dielectric function") - fig.update_layout(title="Tanguy dispersion with Eg=2.5 and default values") - -Poles -===== -.. autoclass:: elli.dispersions.Poles - -.. plotly:: - - fig = elli.Poles(A_ir=10, A_uv=100, E_uv=8).get_dielectric_df().plot(backend="plotly") - fig.update_xaxes(title="Wavelength (nm)") - fig.update_yaxes(title="Dielectric function") - fig.data[1].visible = "legendonly" - fig.update_layout(title="Poles dispersion with A_ir=10, A_uv=100, E_uv=8") - -Polynomial -========== -.. autoclass:: elli.dispersions.Polynomial - -.. plotly:: - - fig = elli.Polynomial(e0=2.5).add(f=500, e=-2).get_dielectric_df().plot(backend="plotly") - fig.update_xaxes(title="Wavelength (nm)") - fig.update_yaxes(title="Dielectric function") - fig.data[1].visible = "legendonly" - fig.update_layout(title="Polynomial dispersion with e0=2.5, f_1=500, e_1=-2") - -Tabulated values -================= - -Refractive index values ------------------------ -.. autoclass:: elli.dispersions.Table - -Epsilon values --------------- -.. autoclass:: elli.dispersions.TableEpsilon - :members: - -Pseudo dielectric function --------------------------- -.. autoclass:: elli.dispersions.PseudoDielectricFunction - :members: - -Spectraray tables ------------------ -.. autoclass:: elli.dispersions.TableSpectraRay - :members: - -Abstract classes -================ -These classes serve as basic interfaces for dispersions and -convenient + generalized handling. - -Dispersion ----------- -This is the abstract base class which is the parent class of all dispersions. -It supplies basic functionalities, such as extracting wavelength dependent -epsilon or refractive index values. - -.. autoclass:: elli.dispersions.base_dispersion.Dispersion - :members: - -DispersionFactory ------------------ -This factory class returns a fully initialized class identified -by a string. -This is useful if you determine the appropriate dispersion relation -during runtime of your program. - -.. autoclass:: elli.dispersions.base_dispersion.DispersionFactory - :members: - -DispersionSum -------------- -This object can be used to add an arbitrary number of dispersions. -The overloaded `+` operator of the dispersion base class creates an instance -of this object with two classes as parameters. -If you want to chain a lot of dispersions, it may be more performant to use -this class directly. - -.. autoclass:: elli.dispersions.base_dispersion.DispersionSum - :members: - - -InvalidParameters ------------------ -This exception is thrown whenever a dispersion got invalid parameters. - -.. autoexception:: elli.dispersions.base_dispersion.InvalidParameters diff --git a/docs/experiment.rst b/docs/experiment.rst deleted file mode 100644 index 69e6ea38..00000000 --- a/docs/experiment.rst +++ /dev/null @@ -1,8 +0,0 @@ -========== -Experiment -========== - -.. automodule:: elli.experiment - :members: - :undoc-members: - :show-inheritance: diff --git a/docs/helpers.rst b/docs/helpers.rst deleted file mode 100644 index 6340c12c..00000000 --- a/docs/helpers.rst +++ /dev/null @@ -1,8 +0,0 @@ -================= -Helper functions -================= -Helper functions for generation rotation matrices and -conversions for wavelengths and ellipsometric quantities. - -.. automodule:: elli.utils - :members: diff --git a/docs/index.md b/docs/index.md new file mode 100644 index 00000000..021c6284 --- /dev/null +++ b/docs/index.md @@ -0,0 +1,4 @@ +# Welcome to pyElli + +PyElli is an open-source numerical solver for spectral ellipsometry employing well-known 2x2 and 4x4 solver algorithms. It is intended for a broad range of problems such as simple fitting of layered structures, anisotropic layers and any other polarized light interaction with layered 1D structures. It serves as a system for the day to day ellipsometry task at hand and aims to make optical model generation standardized and reproducible. + diff --git a/docs/index.rst b/docs/index.rst deleted file mode 100644 index c45c3bbb..00000000 --- a/docs/index.rst +++ /dev/null @@ -1,91 +0,0 @@ -====== -pyElli -====== - -PyElli is an open-source numerical solver for spectral ellipsometry employing well-known -2x2 and 4x4 solver algorithms. It is intended for a broad range of problems -such as simple fitting of layered structures, anisotropic layers and any -other polarized light interaction with layered 1D structures. -It serves as a system for the day to day ellipsometry task at hand -and aims to make optical model generation standardized and reproducible. - -PyElli is build to be easily extendable by optical models. -However, pyElli comes with batteries included and already offers a wide range -of :doc:`dispersion models` and the material database of Refractiveindex.info. - -Most of the models presented in the -comprehensive book of Fujiwara and Collins [1]_ are present and additionally -a lot of other models used by ellipsometry vendor software are included. - -The material database offers the dispersions seen on the `website `_ -and can be accessed by using the :class:`elli.db.RII` module. - -To start you may want to dive into :ref:`install`. -The bast way to start is to have a look at the :doc:`basic usage` or -the :doc:`other examples`. - -PyElli consists of a set of classes which work together to create a full -light interaction experiment. -In the image below you see the set of different classes and how they work together -to evaluate a modeled system. - -.. mermaid:: - - graph LR - Dx(Dispersion x) --> AM - Dy(Dispersion y) --> AM - Dz(Dispersion z) --> AM - D(Dispersion) --> M - M(Material) --> L - AM(AnisotropicMaterial) --> L - M -- front Material --> S - AM -- back Material --> S - L(Layers) --> S & S - S(Structure) --> E(Experiment) - S --> |evaluate| R(Result) - E --> R - -It starts by building a set of dispersions and plugging them into materials classes the specific -number of dispersions depends on whether it is an :class:`IsotropicMaterial` or an :class:`AnisotropicMaterial`. -These materials classes also support creating effective medium layers for inclusions or roughnesses. -The next step is building a :class:`Structure` from these materials. -The :class:`Structure` needs as least two materials for the incoming and outgoing materials, -but can contain arbitrary more :class:`layers` which are only limited by the computational resources. -The :class:`VaryingMixtureLayer` class can also account for gradient changes of materials in z-direction -of a layer, which is useful for gradient layers or roughness modeling. -As the last step the :class:`Structure` is plugged into an :class:`Experiment`, which contains -the experimental conditions, such as light polarization. -By evaluating the experiment a :class:`Result` class containing the calculated data is returned. -The creation of an experiment can be skipped by calling the :meth:`evaluate` method directly -on a :class:`Structure` class if you want to use standard experimental settings. - -.. rubric:: References - -.. [1] H. Fujiwara and R. W. Collins, - Spectroscopic Ellipsometry for Photovoltaics, - Volume 1: Fundamental Principles and Solar Cell Characterization, - Ed. 1, Springer Series in Optical Sciences 212 (2018). - https://doi.org/10.1007/978-3-319-75377-5 - - - -Contents -======== - -.. toctree:: - :maxdepth: 2 - - installation - auto_examples/index - modules - -Misc -==== - -.. toctree:: - :maxdepth: 1 - - Contributions & Help - License - Authors - Changelog diff --git a/docs/installation.rst b/docs/installation.rst deleted file mode 100644 index 0f7e0dd0..00000000 --- a/docs/installation.rst +++ /dev/null @@ -1,49 +0,0 @@ -.. _installation: - -======== -Install -======== -The installers for all releases are available at the -`Python package Index (PyPI) `_. - -To install the package in your current virtual environment execute - - .. code-block:: shell - - pip install "pyElli[fitting]" - -This installs pyElli with the additional fitting capabilities and interactive widgets. -If you don't want to have this functionality just drop the `[fitting]` in the end. - -To increase performance of the 4x4 Solver, it is recommended to -install PyTorch manually, as it is too big to include in the standard installation. -Installation information can be found at the `PyTorch Website `_. -The CPU variant is sufficient, if you want to save some space. - -A complete environment for pyElli is also available as a -`Docker Container `_. -To pull and run it directly just execute - - .. code-block:: shell - - docker run -p 8888:8888 domna/pyelli - -from your local docker install. After startup a link should -appear in your console. Click it and you will be directed -to a jupyter server with the latest release of pyElli available. - -To install the latest development version use: - - .. code-block:: shell - - pip install git+https://github.com/pyEllips/pyElli.git - -The source code is hosted on `GitHub `_, -to manually install from source, clone the repository and run `pip install -e .` in -the folder to install it in development mode: - - .. code-block:: shell - - git clone --recurse-submodules https://github.com/PyEllips/pyElli - cd pyElli - pip install -e . diff --git a/docs/js/mathjax.js b/docs/js/mathjax.js new file mode 100644 index 00000000..5209b3c1 --- /dev/null +++ b/docs/js/mathjax.js @@ -0,0 +1,19 @@ +window.MathJax = { + tex: { + inlineMath: [["\\(", "\\)"]], + displayMath: [["\\[", "\\]"]], + processEscapes: true, + processEnvironments: true, + }, + options: { + ignoreHtmlClass: ".*|", + processHtmlClass: "arithmatex", + }, +}; + +document$.subscribe(() => { + MathJax.startup.output.clearCache(); + MathJax.typesetClear(); + MathJax.texReset(); + MathJax.typesetPromise(); +}); diff --git a/docs/kkr.rst b/docs/kkr.rst deleted file mode 100644 index 7d17742c..00000000 --- a/docs/kkr.rst +++ /dev/null @@ -1,5 +0,0 @@ -Kramers-Kronig relations -============================== - -.. automodule:: elli.kkr.kkr - :members: diff --git a/docs/license.rst b/docs/license.rst deleted file mode 100644 index 64375288..00000000 --- a/docs/license.rst +++ /dev/null @@ -1,7 +0,0 @@ -.. _license: - -======= -License -======= - -.. literalinclude:: ../LICENSE.txt diff --git a/docs/materials.rst b/docs/materials.rst deleted file mode 100644 index 22e65277..00000000 --- a/docs/materials.rst +++ /dev/null @@ -1,41 +0,0 @@ -================ -Materials & EMA -================ - -.. automodule:: elli.materials - -Abstract base classes ---------------------- -.. autoclass:: elli.materials.Material - :members: - -.. autoclass:: elli.materials.MixtureMaterial - :members: - -.. autoclass:: elli.materials.SingleMaterial - :members: - -Isotropic and non-isotropic materials -------------------------------------- -.. autoclass:: elli.materials.IsotropicMaterial - :members: - -.. autoclass:: elli.materials.UniaxialMaterial - :members: - -.. autoclass:: elli.materials.BiaxialMaterial - :members: - -Effective medium approximations -------------------------------- -.. autoclass:: elli.materials.VCAMaterial - :members: - -.. autoclass:: elli.materials.BruggemanEMA - :members: - -.. autoclass:: elli.materials.MaxwellGarnettEMA - :members: - -.. autoclass:: elli.materials.LooyengaEMA - :members: diff --git a/docs/modules.rst b/docs/modules.rst deleted file mode 100644 index c5f16dda..00000000 --- a/docs/modules.rst +++ /dev/null @@ -1,20 +0,0 @@ -.. _modules: - -************* -API Reference -************* - -.. toctree:: - :maxdepth: 2 - - database - dispersions - materials - structure - experiment - solvers - result - plot - read_write - helpers - kkr diff --git a/docs/plot.rst b/docs/plot.rst deleted file mode 100644 index 31acd250..00000000 --- a/docs/plot.rst +++ /dev/null @@ -1,91 +0,0 @@ -==================== -Fitting and plotting -==================== - -Interactive fitting -------------------- -PyElli offers several classes and decorators to make fitting easy. -The central idea is to construct a class containing the measurement data and an optical model -which is fitted to the data with `lmfit `_. -Since pyElli uses lmfit under the hood you may take advantage of its vast capabilities. - -To make creation of the fitting classes as easy as possible pyElli contains decorators to -automatically instantiate the class by providing a function containing the optical model. - -Here you see an example of invoking such a decorator with a measurement dataframe **psi_delta** and -parameters **params**, an lmfit `Parameter `_ -or :class:`ParamsHist` object to create a -:class:`FitRho` class. - -.. code-block:: python - - @fit(psi_delta, params) - def model(lbda, params): - ... - -In the :code:`model` function the actual optical model should be constructed and an -:class:`Experiment` object -should be returned. -A detailed example on how to use this decorator you find in the :doc:`basic usage` example. - -Psi/Delta fitting -^^^^^^^^^^^^^^^^^ -Fitting decorator and class to fit Psi/Delta experiments. - -.. automodule:: elli.fitting.decorator_psi_delta - :members: - :show-inheritance: - -Mueller matrix fitting -^^^^^^^^^^^^^^^^^^^^^^ -Fitting decorator and class to fit mueller matrix experiments. - -.. automodule:: elli.fitting.decorator_mmatrix - :members: - :show-inheritance: - -Fitting base class -^^^^^^^^^^^^^^^^^^ -This is the base class providing basic fitting features. -This class is not intended to be used directly, it rather should -be inherited from in additional fitting classes. - -.. automodule:: elli.fitting.decorator - :members: - :show-inheritance: - -Parameter class ---------------- -The parameter class extending lmfit's Parameter class by a history -of parameter changes. - -.. automodule:: elli.fitting.params_hist - :members: - :show-inheritance: - -Plotting --------- - -Mueller matrix -^^^^^^^^^^^^^^ -This is a helper class to plot a mueller matrix dataframe. - -.. automodule:: elli.plot.mueller_matrix - :members: - :show-inheritance: - -Structure -^^^^^^^^^ -Plots a refractive index slice through a stack of materials. - -.. automodule:: elli.plot.structure - :members: - :show-inheritance: - - - - - - - - diff --git a/docs/read_write.rst b/docs/read_write.rst deleted file mode 100644 index c22983f3..00000000 --- a/docs/read_write.rst +++ /dev/null @@ -1,11 +0,0 @@ -Reading and writing -=================== - -.. automodule:: elli.importer.nexus - :members: - -.. automodule:: elli.importer.spectraray - :members: - -.. automodule:: elli.importer.woollam - :members: diff --git a/docs/reference/api_documentation.md b/docs/reference/api_documentation.md new file mode 100644 index 00000000..8a3789aa --- /dev/null +++ b/docs/reference/api_documentation.md @@ -0,0 +1,9 @@ +# API Documentation + +## Kramers-Kronig relations + +::: elli.kkr + +## Refractiveindex.info database + +::: elli.db.RII \ No newline at end of file diff --git a/docs/requirements.txt b/docs/requirements.txt deleted file mode 100644 index 657197ad..00000000 --- a/docs/requirements.txt +++ /dev/null @@ -1,1855 +0,0 @@ -# This file was autogenerated by uv via the following command: -# uv pip compile --extra=fitting --extra=dev --extra=docs --generate-hashes --output-file=docs/requirements.txt requirements/dev-requirements.txt pyproject.toml -alabaster==1.0.0 \ - --hash=sha256:c00dca57bca26fa62a6d7d0a9fcce65f3e026e9bfe33e9c538fd3fbb2144fd9e \ - --hash=sha256:fc6786402dc3fcb2de3cabd5fe455a2db534b371124f1f21de8731783dec828b - # via sphinx -anywidget==0.9.15 \ - --hash=sha256:1891c11897aaf7cff8809f996413f618f97d786b6097f7e46266423969a726a0 \ - --hash=sha256:fd7876332e47f380e0428f552f26b7227f5694d4e0a257bbc23354d9b9e9a73c - # via - # -r requirements/dev-requirements.txt - # pyelli (pyproject.toml) -asteval==1.0.6 \ - --hash=sha256:1aa8e7304b2e171a90d64dd269b648cacac4e46fe5de54ac0db24776c0c4a19f \ - --hash=sha256:5e119ed306e39199fd99c881cea0e306b3f3807f050c9be79829fe274c6378dc - # via - # -r requirements/dev-requirements.txt - # lmfit -asttokens==3.0.0 \ - --hash=sha256:0dcd8baa8d62b0c1d118b399b2ddba3c4aff271d0d7a9e0d4c1681c79035bbc7 \ - --hash=sha256:e3078351a059199dd5138cb1c706e6430c05eff2ff136af5eb4790f9d28932e2 - # via - # -r requirements/dev-requirements.txt - # stack-data -attrs==25.1.0 \ - --hash=sha256:1c97078a80c814273a76b2a298a932eb681c87415c11dee0a6921de7f1b02c3e \ - --hash=sha256:c75a69e28a550a7e93789579c22aa26b0f5b83b75dc4e08fe092980051e1090a - # via - # -r requirements/dev-requirements.txt - # jsonschema - # referencing -babel==2.17.0 \ - --hash=sha256:0c54cffb19f690cdcc52a3b50bcbf71e07a808d1c80d549f2459b9d2cf0afb9d \ - --hash=sha256:4d0b53093fdfb4b21c92b5213dba5a1b23885afa8383709427046b21c366e5f2 - # via sphinx -certifi==2025.1.31 \ - --hash=sha256:3d5da6925056f6f18f119200434a4780a94263f10d1c21d032a6f6b2baa20651 \ - --hash=sha256:ca78db4565a652026a4db2bcdf68f2fb589ea80d0be70e03929ed730746b84fe - # via requests -cfgv==3.4.0 \ - --hash=sha256:b7265b1f29fd3316bfcd2b330d63d024f2bfd8bcb8b0272f8e19a504856c48f9 \ - --hash=sha256:e52591d4c5f5dead8e0f673fb16db7949d2cfb3f7da4582893288f0ded8fe560 - # via - # -r requirements/dev-requirements.txt - # pre-commit -chardet==5.2.0 \ - --hash=sha256:1b3b6ff479a8c414bc3fa2c0852995695c4a026dcd6d0633b2dd092ca39c1cf7 \ - --hash=sha256:e1cf59446890a00105fe7b7912492ea04b6e6f06d4b742b2c788469e34c82970 - # via - # -r requirements/dev-requirements.txt - # pyelli (pyproject.toml) -charset-normalizer==3.4.1 \ - --hash=sha256:0167ddc8ab6508fe81860a57dd472b2ef4060e8d378f0cc555707126830f2537 \ - --hash=sha256:01732659ba9b5b873fc117534143e4feefecf3b2078b0a6a2e925271bb6f4cfa \ - --hash=sha256:01ad647cdd609225c5350561d084b42ddf732f4eeefe6e678765636791e78b9a \ - --hash=sha256:04432ad9479fa40ec0f387795ddad4437a2b50417c69fa275e212933519ff294 \ - --hash=sha256:0907f11d019260cdc3f94fbdb23ff9125f6b5d1039b76003b5b0ac9d6a6c9d5b \ - --hash=sha256:0924e81d3d5e70f8126529951dac65c1010cdf117bb75eb02dd12339b57749dd \ - --hash=sha256:09b26ae6b1abf0d27570633b2b078a2a20419c99d66fb2823173d73f188ce601 \ - --hash=sha256:09b5e6733cbd160dcc09589227187e242a30a49ca5cefa5a7edd3f9d19ed53fd \ - --hash=sha256:0af291f4fe114be0280cdd29d533696a77b5b49cfde5467176ecab32353395c4 \ - --hash=sha256:0f55e69f030f7163dffe9fd0752b32f070566451afe180f99dbeeb81f511ad8d \ - --hash=sha256:1a2bc9f351a75ef49d664206d51f8e5ede9da246602dc2d2726837620ea034b2 \ - --hash=sha256:22e14b5d70560b8dd51ec22863f370d1e595ac3d024cb8ad7d308b4cd95f8313 \ - --hash=sha256:234ac59ea147c59ee4da87a0c0f098e9c8d169f4dc2a159ef720f1a61bbe27cd \ - 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--hash=sha256:89149166622f4db9b4b6a449256291dc87a99ee53151c74cbd82a53c8c2f6ccd \ - --hash=sha256:8bfa33f4f2672964266e940dd22a195989ba31669bd84629f05fab3ef4e2d125 \ - --hash=sha256:8c60ca7339acd497a55b0ea5d506b2a2612afb2826560416f6894e8b5770d4a9 \ - --hash=sha256:91b36a978b5ae0ee86c394f5a54d6ef44db1de0815eb43de826d41d21e4af3de \ - --hash=sha256:955f8851919303c92343d2f66165294848d57e9bba6cf6e3625485a70a038d11 \ - --hash=sha256:97f68b8d6831127e4787ad15e6757232e14e12060bec17091b85eb1486b91d8d \ - --hash=sha256:9b23ca7ef998bc739bf6ffc077c2116917eabcc901f88da1b9856b210ef63f35 \ - --hash=sha256:9f0b8b1c6d84c8034a44893aba5e767bf9c7a211e313a9605d9c617d7083829f \ - --hash=sha256:aabfa34badd18f1da5ec1bc2715cadc8dca465868a4e73a0173466b688f29dda \ - --hash=sha256:ab36c8eb7e454e34e60eb55ca5d241a5d18b2c6244f6827a30e451c42410b5f7 \ - --hash=sha256:b010a7a4fd316c3c484d482922d13044979e78d1861f0e0650423144c616a46a \ - --hash=sha256:b1ac5992a838106edb89654e0aebfc24f5848ae2547d22c2c3f66454daa11971 \ - --hash=sha256:b7b2d86dd06bfc2ade3312a83a5c364c7ec2e3498f8734282c6c3d4b07b346b8 \ - --hash=sha256:b97e690a2118911e39b4042088092771b4ae3fc3aa86518f84b8cf6888dbdb41 \ - --hash=sha256:bc2722592d8998c870fa4e290c2eec2c1569b87fe58618e67d38b4665dfa680d \ - --hash=sha256:c0429126cf75e16c4f0ad00ee0eae4242dc652290f940152ca8c75c3a4b6ee8f \ - --hash=sha256:c30197aa96e8eed02200a83fba2657b4c3acd0f0aa4bdc9f6c1af8e8962e0757 \ - --hash=sha256:c4c3e6da02df6fa1410a7680bd3f63d4f710232d3139089536310d027950696a \ - --hash=sha256:c75cb2a3e389853835e84a2d8fb2b81a10645b503eca9bcb98df6b5a43eb8886 \ - --hash=sha256:c96836c97b1238e9c9e3fe90844c947d5afbf4f4c92762679acfe19927d81d77 \ - --hash=sha256:d7f50a1f8c450f3925cb367d011448c39239bb3eb4117c36a6d354794de4ce76 \ - --hash=sha256:d973f03c0cb71c5ed99037b870f2be986c3c05e63622c017ea9816881d2dd247 \ - --hash=sha256:d98b1668f06378c6dbefec3b92299716b931cd4e6061f3c875a71ced1780ab85 \ - --hash=sha256:d9c3cdf5390dcd29aa8056d13e8e99526cda0305acc038b96b30352aff5ff2bb \ - --hash=sha256:dad3e487649f498dd991eeb901125411559b22e8d7ab25d3aeb1af367df5efd7 \ - --hash=sha256:dccbe65bd2f7f7ec22c4ff99ed56faa1e9f785482b9bbd7c717e26fd723a1d1e \ - --hash=sha256:dd78cfcda14a1ef52584dbb008f7ac81c1328c0f58184bf9a84c49c605002da6 \ - --hash=sha256:e218488cd232553829be0664c2292d3af2eeeb94b32bea483cf79ac6a694e037 \ - --hash=sha256:e358e64305fe12299a08e08978f51fc21fac060dcfcddd95453eabe5b93ed0e1 \ - --hash=sha256:ea0d8d539afa5eb2728aa1932a988a9a7af94f18582ffae4bc10b3fbdad0626e \ - --hash=sha256:eab677309cdb30d047996b36d34caeda1dc91149e4fdca0b1a039b3f79d9a807 \ - --hash=sha256:eb8178fe3dba6450a3e024e95ac49ed3400e506fd4e9e5c32d30adda88cbd407 \ - --hash=sha256:ecddf25bee22fe4fe3737a399d0d177d72bc22be6913acfab364b40bce1ba83c \ - --hash=sha256:eea6ee1db730b3483adf394ea72f808b6e18cf3cb6454b4d86e04fa8c4327a12 \ - --hash=sha256:f08ff5e948271dc7e18a35641d2f11a4cd8dfd5634f55228b691e62b37125eb3 \ - --hash=sha256:f30bf9fd9be89ecb2360c7d94a711f00c09b976258846efe40db3d05828e8089 \ - --hash=sha256:fa88b843d6e211393a37219e6a1c1df99d35e8fd90446f1118f4216e307e48cd \ - --hash=sha256:fc54db6c8593ef7d4b2a331b58653356cf04f67c960f584edb7c3d8c97e8f39e \ - --hash=sha256:fd4ec41f914fa74ad1b8304bbc634b3de73d2a0889bd32076342a573e0779e00 \ - --hash=sha256:ffc9202a29ab3920fa812879e95a9e78b2465fd10be7fcbd042899695d75e616 - # via requests -comm==0.2.2 \ - --hash=sha256:3fd7a84065306e07bea1773df6eb8282de51ba82f77c72f9c85716ab11fe980e \ - --hash=sha256:e6fb86cb70ff661ee8c9c14e7d36d6de3b4066f1441be4063df9c5009f0a64d3 - # via - # -r requirements/dev-requirements.txt - # ipykernel - # ipywidgets -contourpy==1.3.1 \ - --hash=sha256:041b640d4ec01922083645a94bb3b2e777e6b626788f4095cf21abbe266413c1 \ - --hash=sha256:05e806338bfeaa006acbdeba0ad681a10be63b26e1b17317bfac3c5d98f36cda \ - --hash=sha256:08d9d449a61cf53033612cb368f3a1b26cd7835d9b8cd326647efe43bca7568d \ - --hash=sha256:0ffa84be8e0bd33410b17189f7164c3589c229ce5db85798076a3fa136d0e509 \ - --hash=sha256:113231fe3825ebf6f15eaa8bc1f5b0ddc19d42b733345eae0934cb291beb88b6 \ - --hash=sha256:14c102b0eab282427b662cb590f2e9340a9d91a1c297f48729431f2dcd16e14f \ - --hash=sha256:174e758c66bbc1c8576992cec9599ce8b6672b741b5d336b5c74e35ac382b18e \ - --hash=sha256:19c1555a6801c2f084c7ddc1c6e11f02eb6a6016ca1318dd5452ba3f613a1751 \ - --hash=sha256:19d40d37c1c3a4961b4619dd9d77b12124a453cc3d02bb31a07d58ef684d3d86 \ - --hash=sha256:1bf98051f1045b15c87868dbaea84f92408337d4f81d0e449ee41920ea121d3b \ - --hash=sha256:20914c8c973f41456337652a6eeca26d2148aa96dd7ac323b74516988bea89fc \ - --hash=sha256:287ccc248c9e0d0566934e7d606201abd74761b5703d804ff3df8935f523d546 \ - --hash=sha256:2ba94a401342fc0f8b948e57d977557fbf4d515f03c67682dd5c6191cb2d16ec \ - --hash=sha256:31c1b55c1f34f80557d3830d3dd93ba722ce7e33a0b472cba0ec3b6535684d8f \ - --hash=sha256:36987a15e8ace5f58d4d5da9dca82d498c2bbb28dff6e5d04fbfcc35a9cb3a82 \ - --hash=sha256:3a04ecd68acbd77fa2d39723ceca4c3197cb2969633836ced1bea14e219d077c \ - --hash=sha256:3e8b974d8db2c5610fb4e76307e265de0edb655ae8169e8b21f41807ccbeec4b \ - --hash=sha256:3ea9924d28fc5586bf0b42d15f590b10c224117e74409dd7a0be3b62b74a501c \ - --hash=sha256:4318af1c925fb9a4fb190559ef3eec206845f63e80fb603d47f2d6d67683901c \ - --hash=sha256:44a29502ca9c7b5ba389e620d44f2fbe792b1fb5734e8b931ad307071ec58c53 \ - --hash=sha256:47734d7073fb4590b4a40122b35917cd77be5722d80683b249dac1de266aac80 \ - --hash=sha256:4d76d5993a34ef3df5181ba3c92fabb93f1eaa5729504fb03423fcd9f3177242 \ - --hash=sha256:4dbbc03a40f916a8420e420d63e96a1258d3d1b58cbdfd8d1f07b49fcbd38e85 \ - --hash=sha256:500360b77259914f7805af7462e41f9cb7ca92ad38e9f94d6c8641b089338124 \ - --hash=sha256:523a8ee12edfa36f6d2a49407f705a6ef4c5098de4f498619787e272de93f2d5 \ - --hash=sha256:573abb30e0e05bf31ed067d2f82500ecfdaec15627a59d63ea2d95714790f5c2 \ - --hash=sha256:5b75aa69cb4d6f137b36f7eb2ace9280cfb60c55dc5f61c731fdf6f037f958a3 \ - --hash=sha256:61332c87493b00091423e747ea78200659dc09bdf7fd69edd5e98cef5d3e9a8d \ - --hash=sha256:805617228ba7e2cbbfb6c503858e626ab528ac2a32a04a2fe88ffaf6b02c32bc \ - --hash=sha256:841ad858cff65c2c04bf93875e384ccb82b654574a6d7f30453a04f04af71342 \ - --hash=sha256:89785bb2a1980c1bd87f0cb1517a71cde374776a5f150936b82580ae6ead44a1 \ - --hash=sha256:8eb96e79b9f3dcadbad2a3891672f81cdcab7f95b27f28f1c67d75f045b6b4f1 \ - --hash=sha256:974d8145f8ca354498005b5b981165b74a195abfae9a8129df3e56771961d595 \ - --hash=sha256:9ddeb796389dadcd884c7eb07bd14ef12408aaae358f0e2ae24114d797eede30 \ - --hash=sha256:a045f341a77b77e1c5de31e74e966537bba9f3c4099b35bf4c2e3939dd54cdab \ - --hash=sha256:a0cffcbede75c059f535725c1680dfb17b6ba8753f0c74b14e6a9c68c29d7ea3 \ - --hash=sha256:a761d9ccfc5e2ecd1bf05534eda382aa14c3e4f9205ba5b1684ecfe400716ef2 \ - --hash=sha256:a7895f46d47671fa7ceec40f31fae721da51ad34bdca0bee83e38870b1f47ffd \ - --hash=sha256:a9fa36448e6a3a1a9a2ba23c02012c43ed88905ec80163f2ffe2421c7192a5d7 \ - --hash=sha256:ab29962927945d89d9b293eabd0d59aea28d887d4f3be6c22deaefbb938a7277 \ - --hash=sha256:abbb49fb7dac584e5abc6636b7b2a7227111c4f771005853e7d25176daaf8453 \ - --hash=sha256:ac4578ac281983f63b400f7fe6c101bedc10651650eef012be1ccffcbacf3697 \ - --hash=sha256:adce39d67c0edf383647a3a007de0a45fd1b08dedaa5318404f1a73059c2512b \ - --hash=sha256:ade08d343436a94e633db932e7e8407fe7de8083967962b46bdfc1b0ced39454 \ - --hash=sha256:b2bdca22a27e35f16794cf585832e542123296b4687f9fd96822db6bae17bfc9 \ - --hash=sha256:b2f926efda994cdf3c8d3fdb40b9962f86edbc4457e739277b961eced3d0b4c1 \ - --hash=sha256:b457d6430833cee8e4b8e9b6f07aa1c161e5e0d52e118dc102c8f9bd7dd060d6 \ - --hash=sha256:c414fc1ed8ee1dbd5da626cf3710c6013d3d27456651d156711fa24f24bd1291 \ - --hash=sha256:cb76c1a154b83991a3cbbf0dfeb26ec2833ad56f95540b442c73950af2013750 \ - --hash=sha256:dfd97abd83335045a913e3bcc4a09c0ceadbe66580cf573fe961f4a825efa699 \ - --hash=sha256:e914a8cb05ce5c809dd0fe350cfbb4e881bde5e2a38dc04e3afe1b3e58bd158e \ - --hash=sha256:ece6df05e2c41bd46776fbc712e0996f7c94e0d0543af1656956d150c4ca7c81 \ - --hash=sha256:efa874e87e4a647fd2e4f514d5e91c7d493697127beb95e77d2f7561f6905bd9 \ - --hash=sha256:f611e628ef06670df83fce17805c344710ca5cde01edfdc72751311da8585375 - # via - # -r requirements/dev-requirements.txt - # matplotlib -coverage==7.6.12 \ - --hash=sha256:00b2086892cf06c7c2d74983c9595dc511acca00665480b3ddff749ec4fb2a95 \ - --hash=sha256:0533adc29adf6a69c1baa88c3d7dbcaadcffa21afbed3ca7a225a440e4744bf9 \ - --hash=sha256:06097c7abfa611c91edb9e6920264e5be1d6ceb374efb4986f38b09eed4cb2fe \ - --hash=sha256:07e92ae5a289a4bc4c0aae710c0948d3c7892e20fd3588224ebe242039573bf0 \ - --hash=sha256:0a9d8be07fb0832636a0f72b80d2a652fe665e80e720301fb22b191c3434d924 \ - --hash=sha256:0e549f54ac5f301e8e04c569dfdb907f7be71b06b88b5063ce9d6953d2d58574 \ - --hash=sha256:0ef01d70198431719af0b1f5dcbefc557d44a190e749004042927b2a3fed0702 \ - --hash=sha256:0f16f44025c06792e0fb09571ae454bcc7a3ec75eeb3c36b025eccf501b1a4c3 \ - --hash=sha256:14d47376a4f445e9743f6c83291e60adb1b127607a3618e3185bbc8091f0467b \ - --hash=sha256:1a936309a65cc5ca80fa9f20a442ff9e2d06927ec9a4f54bcba9c14c066323f2 \ - --hash=sha256:1ceeb90c3eda1f2d8c4c578c14167dbd8c674ecd7d38e45647543f19839dd6ea \ - --hash=sha256:1f7ffa05da41754e20512202c866d0ebfc440bba3b0ed15133070e20bf5aeb5f \ - --hash=sha256:200e10beb6ddd7c3ded322a4186313d5ca9e63e33d8fab4faa67ef46d3460af3 \ - --hash=sha256:220fa6c0ad7d9caef57f2c8771918324563ef0d8272c94974717c3909664e674 \ - --hash=sha256:2251fabcfee0a55a8578a9d29cecfee5f2de02f11530e7d5c5a05859aa85aee9 \ - --hash=sha256:2458f275944db8129f95d91aee32c828a408481ecde3b30af31d552c2ce284a0 \ - --hash=sha256:299cf973a7abff87a30609879c10df0b3bfc33d021e1adabc29138a48888841e \ - --hash=sha256:2b996819ced9f7dbb812c701485d58f261bef08f9b85304d41219b1496b591ef \ - --hash=sha256:3688b99604a24492bcfe1c106278c45586eb819bf66a654d8a9a1433022fb2eb \ - --hash=sha256:3a1e465f398c713f1b212400b4e79a09829cd42aebd360362cd89c5bdc44eb87 \ - --hash=sha256:488c27b3db0ebee97a830e6b5a3ea930c4a6e2c07f27a5e67e1b3532e76b9ef1 \ - --hash=sha256:48cfc4641d95d34766ad41d9573cc0f22a48aa88d22657a1fe01dca0dbae4de2 \ - --hash=sha256:4b467a8c56974bf06e543e69ad803c6865249d7a5ccf6980457ed2bc50312703 \ - --hash=sha256:53c56358d470fa507a2b6e67a68fd002364d23c83741dbc4c2e0680d80ca227e \ - --hash=sha256:5d1095bbee1851269f79fd8e0c9b5544e4c00c0c24965e66d8cba2eb5bb535fd \ - --hash=sha256:641dfe0ab73deb7069fb972d4d9725bf11c239c309ce694dd50b1473c0f641c3 \ - --hash=sha256:64cbb1a3027c79ca6310bf101014614f6e6e18c226474606cf725238cf5bc2d4 \ - --hash=sha256:66fe626fd7aa5982cdebad23e49e78ef7dbb3e3c2a5960a2b53632f1f703ea45 \ - --hash=sha256:676f92141e3c5492d2a1596d52287d0d963df21bf5e55c8b03075a60e1ddf8aa \ - --hash=sha256:69e62c5034291c845fc4df7f8155e8544178b6c774f97a99e2734b05eb5bed31 \ - --hash=sha256:704c8c8c6ce6569286ae9622e534b4f5b9759b6f2cd643f1c1a61f666d534fe8 \ - --hash=sha256:78f5243bb6b1060aed6213d5107744c19f9571ec76d54c99cc15938eb69e0e86 \ - --hash=sha256:79cac3390bfa9836bb795be377395f28410811c9066bc4eefd8015258a7578c6 \ - --hash=sha256:7ae6eabf519bc7871ce117fb18bf14e0e343eeb96c377667e3e5dd12095e0288 \ - --hash=sha256:7e39e845c4d764208e7b8f6a21c541ade741e2c41afabdfa1caa28687a3c98cf \ - --hash=sha256:8161d9fbc7e9fe2326de89cd0abb9f3599bccc1287db0aba285cb68d204ce929 \ - --hash=sha256:8bec2ac5da793c2685ce5319ca9bcf4eee683b8a1679051f8e6ec04c4f2fd7dc \ - --hash=sha256:959244a17184515f8c52dcb65fb662808767c0bd233c1d8a166e7cf74c9ea985 \ - --hash=sha256:9b148068e881faa26d878ff63e79650e208e95cf1c22bd3f77c3ca7b1d9821a3 \ - --hash=sha256:aa6f302a3a0b5f240ee201297fff0bbfe2fa0d415a94aeb257d8b461032389bd \ - --hash=sha256:ace9048de91293e467b44bce0f0381345078389814ff6e18dbac8fdbf896360e \ - --hash=sha256:ad7525bf0241e5502168ae9c643a2f6c219fa0a283001cee4cf23a9b7da75879 \ - --hash=sha256:b01a840ecc25dce235ae4c1b6a0daefb2a203dba0e6e980637ee9c2f6ee0df57 \ - --hash=sha256:b076e625396e787448d27a411aefff867db2bffac8ed04e8f7056b07024eed5a \ - --hash=sha256:b172f8e030e8ef247b3104902cc671e20df80163b60a203653150d2fc204d1ad \ - --hash=sha256:b1f097878d74fe51e1ddd1be62d8e3682748875b461232cf4b52ddc6e6db0bba \ - --hash=sha256:b95574d06aa9d2bd6e5cc35a5bbe35696342c96760b69dc4287dbd5abd4ad51d \ - --hash=sha256:bda1c5f347550c359f841d6614fb8ca42ae5cb0b74d39f8a1e204815ebe25750 \ - --hash=sha256:cec6b9ce3bd2b7853d4a4563801292bfee40b030c05a3d29555fd2a8ee9bd68c \ - --hash=sha256:d1a987778b9c71da2fc8948e6f2656da6ef68f59298b7e9786849634c35d2c3c \ - --hash=sha256:d74c08e9aaef995f8c4ef6d202dbd219c318450fe2a76da624f2ebb9c8ec5d9f \ - --hash=sha256:e18aafdfb3e9ec0d261c942d35bd7c28d031c5855dadb491d2723ba54f4c3015 \ - --hash=sha256:e216c5c45f89ef8971373fd1c5d8d1164b81f7f5f06bbf23c37e7908d19e8558 \ - --hash=sha256:e695df2c58ce526eeab11a2e915448d3eb76f75dffe338ea613c1201b33bab2f \ - --hash=sha256:e7575ab65ca8399c8c4f9a7d61bbd2d204c8b8e447aab9d355682205c9dd948d \ - --hash=sha256:e995b3b76ccedc27fe4f477b349b7d64597e53a43fc2961db9d3fbace085d69d \ - --hash=sha256:ea31689f05043d520113e0552f039603c4dd71fa4c287b64cb3606140c66f425 \ - --hash=sha256:eb5507795caabd9b2ae3f1adc95f67b1104971c22c624bb354232d65c4fc90b3 \ - --hash=sha256:eb8668cfbc279a536c633137deeb9435d2962caec279c3f8cf8b91fff6ff8953 \ - --hash=sha256:ecea0c38c9079570163d663c0433a9af4094a60aafdca491c6a3d248c7432827 \ - --hash=sha256:f25d8b92a4e31ff1bd873654ec367ae811b3a943583e05432ea29264782dc32c \ - --hash=sha256:f60a297c3987c6c02ffb29effc70eadcbb412fe76947d394a1091a3615948e2f \ - --hash=sha256:f973643ef532d4f9be71dd88cf7588936685fdb576d93a79fe9f65bc337d9d73 - # via - # -r requirements/dev-requirements.txt - # pytest-cov -cycler==0.12.1 \ - --hash=sha256:85cef7cff222d8644161529808465972e51340599459b8ac3ccbac5a854e0d30 \ - --hash=sha256:88bb128f02ba341da8ef447245a9e138fae777f6a23943da4540077d3601eb1c - # via - # -r requirements/dev-requirements.txt - # matplotlib -debugpy==1.8.13 \ - --hash=sha256:06859f68e817966723ffe046b896b1bd75c665996a77313370336ee9e1de3e90 \ - --hash=sha256:2b8de94c5c78aa0d0ed79023eb27c7c56a64c68217d881bee2ffbcb13951d0c1 \ - --hash=sha256:31abc9618be4edad0b3e3a85277bc9ab51a2d9f708ead0d99ffb5bb750e18503 \ - --hash=sha256:32b6857f8263a969ce2ca098f228e5cc0604d277447ec05911a8c46cf3e7e307 \ - --hash=sha256:3872ce5453b17837ef47fb9f3edc25085ff998ce63543f45ba7af41e7f7d370f \ - --hash=sha256:3dae443739c6b604802da9f3e09b0f45ddf1cf23c99161f3a1a8039f61a8bb89 \ - --hash=sha256:46abe0b821cad751fc1fb9f860fb2e68d75e2c5d360986d0136cd1db8cad4428 \ - --hash=sha256:4caca674206e97c85c034c1efab4483f33971d4e02e73081265ecb612af65377 \ - --hash=sha256:5268ae7fdca75f526d04465931cb0bd24577477ff50e8bb03dab90983f4ebd02 \ - --hash=sha256:62f9b4a861c256f37e163ada8cf5a81f4c8d5148fc17ee31fb46813bd658cdcc \ - --hash=sha256:63ca7670563c320503fea26ac688988d9d6b9c6a12abc8a8cf2e7dd8e5f6b6ea \ - --hash=sha256:6fab771639332bd8ceb769aacf454a30d14d7a964f2012bf9c4e04c60f16e85b \ - --hash=sha256:79ce4ed40966c4c1631d0131606b055a5a2f8e430e3f7bf8fd3744b09943e8e8 \ - --hash=sha256:7d9a05efc6973b5aaf076d779cf3a6bbb1199e059a17738a2aa9d27a53bcc888 \ - --hash=sha256:837e7bef95bdefba426ae38b9a94821ebdc5bea55627879cd48165c90b9e50ce \ - --hash=sha256:887d54276cefbe7290a754424b077e41efa405a3e07122d8897de54709dbe522 \ - --hash=sha256:924464d87e7d905eb0d79fb70846558910e906d9ee309b60c4fe597a2e802590 \ - --hash=sha256:a0bd87557f97bced5513a74088af0b84982b6ccb2e254b9312e29e8a5c4270eb \ - --hash=sha256:acf39a6e98630959763f9669feddee540745dfc45ad28dbc9bd1f9cd60639391 \ - --hash=sha256:cb56c2db69fb8df3168bc857d7b7d2494fed295dfdbde9a45f27b4b152f37520 \ - --hash=sha256:d4ba115cdd0e3a70942bd562adba9ec8c651fe69ddde2298a1be296fc331906f \ - --hash=sha256:dc7b77f5d32674686a5f06955e4b18c0e41fb5a605f5b33cf225790f114cfeec \ - --hash=sha256:ea869fe405880327497e6945c09365922c79d2a1eed4c3ae04d77ac7ae34b2b5 \ - --hash=sha256:ed93c3155fc1f888ab2b43626182174e457fc31b7781cd1845629303790b8ad1 \ - --hash=sha256:eee02b2ed52a563126c97bf04194af48f2fe1f68bb522a312b05935798e922ff \ - --hash=sha256:f14d2c4efa1809da125ca62df41050d9c7cd9cb9e380a2685d1e453c4d450ccb - # via - # -r requirements/dev-requirements.txt - # ipykernel -decorator==5.2.1 \ - --hash=sha256:65f266143752f734b0a7cc83c46f4618af75b8c5911b00ccb61d0ac9b6da0360 \ - --hash=sha256:d316bb415a2d9e2d2b3abcc4084c6502fc09240e292cd76a76afc106a1c8e04a - # via - # -r requirements/dev-requirements.txt - # ipython -dill==0.3.9 \ - --hash=sha256:468dff3b89520b474c0397703366b7b95eebe6303f108adf9b19da1f702be87a \ - --hash=sha256:81aa267dddf68cbfe8029c42ca9ec6a4ab3b22371d1c450abc54422577b4512c - # via - # -r requirements/dev-requirements.txt - # lmfit -distlib==0.3.9 \ - --hash=sha256:47f8c22fd27c27e25a65601af709b38e4f0a45ea4fc2e710f65755fa8caaaf87 \ - --hash=sha256:a60f20dea646b8a33f3e7772f74dc0b2d0772d2837ee1342a00645c81edf9403 - # via - # -r requirements/dev-requirements.txt - # virtualenv -docutils==0.21.2 \ - --hash=sha256:3a6b18732edf182daa3cd12775bbb338cf5691468f91eeeb109deff6ebfa986f \ - --hash=sha256:dafca5b9e384f0e419294eb4d2ff9fa826435bf15f15b7bd45723e8ad76811b2 - # via - # myst-parser - # sphinx - # sphinx-mdinclude - # sphinx-rtd-theme -exceptiongroup==1.2.2 \ - --hash=sha256:3111b9d131c238bec2f8f516e123e14ba243563fb135d3fe885990585aa7795b \ - --hash=sha256:47c2edf7c6738fafb49fd34290706d1a1a2f4d1c6df275526b62cbb4aa5393cc - # via - # -r requirements/dev-requirements.txt - # ipython - # pytest -executing==2.2.0 \ - --hash=sha256:11387150cad388d62750327a53d3339fad4888b39a6fe233c3afbb54ecffd3aa \ - --hash=sha256:5d108c028108fe2551d1a7b2e8b713341e2cb4fc0aa7dcf966fa4327a5226755 - # via - # -r requirements/dev-requirements.txt - # stack-data -fastjsonschema==2.21.1 \ - --hash=sha256:794d4f0a58f848961ba16af7b9c85a3e88cd360df008c59aac6fc5ae9323b5d4 \ - --hash=sha256:c9e5b7e908310918cf494a434eeb31384dd84a98b57a30bcb1f535015b554667 - # via - # -r requirements/dev-requirements.txt - # nbformat -filelock==3.17.0 \ - --hash=sha256:533dc2f7ba78dc2f0f531fc6c4940addf7b70a481e269a5a3b93be94ffbe8338 \ - --hash=sha256:ee4e77401ef576ebb38cd7f13b9b28893194acc20a8e68e18730ba9c0e54660e - # via - # -r requirements/dev-requirements.txt - # virtualenv -flexcache==0.3 \ - --hash=sha256:18743bd5a0621bfe2cf8d519e4c3bfdf57a269c15d1ced3fb4b64e0ff4600656 \ - --hash=sha256:d43c9fea82336af6e0115e308d9d33a185390b8346a017564611f1466dcd2e32 - # via - # -r requirements/dev-requirements.txt - # pint -flexparser==0.4 \ - --hash=sha256:266d98905595be2ccc5da964fe0a2c3526fbbffdc45b65b3146d75db992ef6b2 \ - --hash=sha256:3738b456192dcb3e15620f324c447721023c0293f6af9955b481e91d00179846 - # via - # -r requirements/dev-requirements.txt - # pint -fonttools==4.56.0 \ - --hash=sha256:003548eadd674175510773f73fb2060bb46adb77c94854af3e0cc5bc70260049 \ - --hash=sha256:0073b62c3438cf0058488c002ea90489e8801d3a7af5ce5f7c05c105bee815c3 \ - --hash=sha256:1088182f68c303b50ca4dc0c82d42083d176cba37af1937e1a976a31149d4d14 \ - --hash=sha256:133bedb9a5c6376ad43e6518b7e2cd2f866a05b1998f14842631d5feb36b5786 \ - --hash=sha256:14a3e3e6b211660db54ca1ef7006401e4a694e53ffd4553ab9bc87ead01d0f05 \ - --hash=sha256:17f39313b649037f6c800209984a11fc256a6137cbe5487091c6c7187cae4685 \ - --hash=sha256:193b86e9f769320bc98ffdb42accafb5d0c8c49bd62884f1c0702bc598b3f0a2 \ - --hash=sha256:2d351275f73ebdd81dd5b09a8b8dac7a30f29a279d41e1c1192aedf1b6dced40 \ - --hash=sha256:300c310bb725b2bdb4f5fc7e148e190bd69f01925c7ab437b9c0ca3e1c7cd9ba \ - --hash=sha256:331954d002dbf5e704c7f3756028e21db07097c19722569983ba4d74df014000 \ - --hash=sha256:38b947de71748bab150259ee05a775e8a0635891568e9fdb3cdd7d0e0004e62f \ - --hash=sha256:3cf4f8d2a30b454ac682e12c61831dcb174950c406011418e739de592bbf8f76 \ - --hash=sha256:3fd3fccb7b9adaaecfa79ad51b759f2123e1aba97f857936ce044d4f029abd71 \ - --hash=sha256:442ad4122468d0e47d83bc59d0e91b474593a8c813839e1872e47c7a0cb53b10 \ - --hash=sha256:47b5e4680002ae1756d3ae3b6114e20aaee6cc5c69d1e5911f5ffffd3ee46c6b \ - --hash=sha256:53f5e9767978a4daf46f28e09dbeb7d010319924ae622f7b56174b777258e5ba \ - --hash=sha256:62b4c6802fa28e14dba010e75190e0e6228513573f1eeae57b11aa1a39b7e5b1 \ - --hash=sha256:62cc1253827d1e500fde9dbe981219fea4eb000fd63402283472d38e7d8aa1c6 \ - --hash=sha256:654ac4583e2d7c62aebc6fc6a4c6736f078f50300e18aa105d87ce8925cfac31 \ - --hash=sha256:661a8995d11e6e4914a44ca7d52d1286e2d9b154f685a4d1f69add8418961563 \ - --hash=sha256:6c1d38642ca2dddc7ae992ef5d026e5061a84f10ff2b906be5680ab089f55bb8 \ - --hash=sha256:6e81c1cc80c1d8bf071356cc3e0e25071fbba1c75afc48d41b26048980b3c771 \ - --hash=sha256:705837eae384fe21cee5e5746fd4f4b2f06f87544fa60f60740007e0aa600311 \ - --hash=sha256:7ef04bc7827adb7532be3d14462390dd71287644516af3f1e67f1e6ff9c6d6df \ - --hash=sha256:86b2a1013ef7a64d2e94606632683f07712045ed86d937c11ef4dde97319c086 \ - --hash=sha256:8d1613abd5af2f93c05867b3a3759a56e8bf97eb79b1da76b2bc10892f96ff16 \ - --hash=sha256:965d0209e6dbdb9416100123b6709cb13f5232e2d52d17ed37f9df0cc31e2b35 \ - --hash=sha256:96a4271f63a615bcb902b9f56de00ea225d6896052c49f20d0c91e9f43529a29 \ - --hash=sha256:9d94449ad0a5f2a8bf5d2f8d71d65088aee48adbe45f3c5f8e00e3ad861ed81a \ - --hash=sha256:9da650cb29bc098b8cfd15ef09009c914b35c7986c8fa9f08b51108b7bc393b4 \ - --hash=sha256:a05d1f07eb0a7d755fbe01fee1fd255c3a4d3730130cf1bfefb682d18fd2fcea \ - --hash=sha256:a114d1567e1a1586b7e9e7fc2ff686ca542a82769a296cef131e4c4af51e58f4 \ - --hash=sha256:a1af375734018951c31c0737d04a9d5fd0a353a0253db5fbed2ccd44eac62d8c \ - --hash=sha256:b23d30a2c0b992fb1c4f8ac9bfde44b5586d23457759b6cf9a787f1a35179ee0 \ - --hash=sha256:bc871904a53a9d4d908673c6faa15689874af1c7c5ac403a8e12d967ebd0c0dc \ - --hash=sha256:bce60f9a977c9d3d51de475af3f3581d9b36952e1f8fc19a1f2254f1dda7ce9c \ - --hash=sha256:bd9825822e7bb243f285013e653f6741954d8147427aaa0324a862cdbf4cbf62 \ - --hash=sha256:ca7962e8e5fc047cc4e59389959843aafbf7445b6c08c20d883e60ced46370a5 \ - --hash=sha256:d0cb73ccf7f6d7ca8d0bc7ea8ac0a5b84969a41c56ac3ac3422a24df2680546f \ - --hash=sha256:d54a45d30251f1d729e69e5b675f9a08b7da413391a1227781e2a297fa37f6d2 \ - --hash=sha256:d6ca96d1b61a707ba01a43318c9c40aaf11a5a568d1e61146fafa6ab20890793 \ - --hash=sha256:d6f195c14c01bd057bc9b4f70756b510e009c83c5ea67b25ced3e2c38e6ee6e9 \ - --hash=sha256:e2cad98c94833465bcf28f51c248aaf07ca022efc6a3eba750ad9c1e0256d278 \ - --hash=sha256:e2e993e8db36306cc3f1734edc8ea67906c55f98683d6fd34c3fc5593fdbba4c \ - --hash=sha256:e9270505a19361e81eecdbc2c251ad1e1a9a9c2ad75fa022ccdee533f55535dc \ - --hash=sha256:f20e2c0dfab82983a90f3d00703ac0960412036153e5023eed2b4641d7d5e692 \ - --hash=sha256:f36a0868f47b7566237640c026c65a86d09a3d9ca5df1cd039e30a1da73098a0 \ - --hash=sha256:f59746f7953f69cc3290ce2f971ab01056e55ddd0fb8b792c31a8acd7fee2d28 \ - --hash=sha256:fa760e5fe8b50cbc2d71884a1eff2ed2b95a005f02dda2fa431560db0ddd927f \ - --hash=sha256:ffda9b8cd9cb8b301cae2602ec62375b59e2e2108a117746f12215145e3f786c - # via - # -r requirements/dev-requirements.txt - # matplotlib -h5py==3.13.0 \ - --hash=sha256:10894c55d46df502d82a7a4ed38f9c3fdbcb93efb42e25d275193e093071fade \ - --hash=sha256:1870e46518720023da85d0895a1960ff2ce398c5671eac3b1a41ec696b7105c3 \ - --hash=sha256:21daf38171753899b5905f3d82c99b0b1ec2cbbe282a037cad431feb620e62ec \ - --hash=sha256:22ffe2a25770a2d67213a1b94f58006c14dce06933a42d2aaa0318c5868d1508 \ - --hash=sha256:337af114616f3656da0c83b68fcf53ecd9ce9989a700b0883a6e7c483c3235d4 \ - --hash=sha256:357e6dc20b101a805ccfd0024731fbaf6e8718c18c09baf3b5e4e9d198d13fca \ - --hash=sha256:477c58307b6b9a2509c59c57811afb9f598aedede24a67da808262dfa0ee37b4 \ - --hash=sha256:4f97ecde7ac6513b21cd95efdfc38dc6d19f96f6ca6f2a30550e94e551458e0a \ - --hash=sha256:5540daee2b236d9569c950b417f13fd112d51d78b4c43012de05774908dff3f5 \ - --hash=sha256:560e71220dc92dfa254b10a4dcb12d56b574d2d87e095db20466b32a93fec3f9 \ - --hash=sha256:56dd172d862e850823c4af02dc4ddbc308f042b85472ffdaca67f1598dff4a57 \ - --hash=sha256:57c4c74f627c616f02b7aec608a8c706fe08cb5b0ba7c08555a4eb1dde20805a \ - --hash=sha256:782ff0ac39f455f21fd1c8ebc007328f65f43d56718a89327eec76677ebf238a \ - --hash=sha256:82690e89c72b85addf4fc4d5058fb1e387b6c14eb063b0b879bf3f42c3b93c35 \ - --hash=sha256:851ae3a8563d87a5a0dc49c2e2529c75b8842582ccaefbf84297d2cfceeacd61 \ - --hash=sha256:8a8e38ef4ceb969f832cc230c0cf808c613cc47e31e768fd7b1106c55afa1cb8 \ - --hash=sha256:9c82ece71ed1c2b807b6628e3933bc6eae57ea21dac207dca3470e3ceaaf437c \ - --hash=sha256:be949b46b7388074c5acae017fbbe3e5ba303fd9daaa52157fdfef30bbdacadd \ - --hash=sha256:c10f061764d8dce0a9592ce08bfd5f243a00703325c388f1086037e5d619c5f1 \ - --hash=sha256:d2cf6a231a07c14acd504a945a6e9ec115e0007f675bde5e0de30a4dc8d86a31 \ - --hash=sha256:d571644958c5e19a61c793d8d23cd02479572da828e333498c9acc463f4a3997 \ - --hash=sha256:d6f13f9b5ce549448c01e4dfe08ea8d1772e6078799af2c1c8d09e941230a90d \ - --hash=sha256:e520ec76de00943dd017c8ea3f354fa1d2f542eac994811943a8faedf2a7d5cb \ - --hash=sha256:e79d8368cd9295045956bfb436656bea3f915beaa11d342e9f79f129f5178763 \ - --hash=sha256:f35640e81b03c02a88b8bf99fb6a9d3023cc52f7c627694db2f379e0028f2868 \ - --hash=sha256:fb267ce4b83f9c42560e9ff4d30f60f7ae492eacf9c7ede849edf8c1b860e16b - # via - # -r requirements/dev-requirements.txt - # pyelli (pyproject.toml) -identify==2.6.9 \ - --hash=sha256:c98b4322da415a8e5a70ff6e51fbc2d2932c015532d77e9f8537b4ba7813b150 \ - --hash=sha256:d40dfe3142a1421d8518e3d3985ef5ac42890683e32306ad614a29490abeb6bf - # via - # -r requirements/dev-requirements.txt - # pre-commit -idna==3.10 \ - --hash=sha256:12f65c9b470abda6dc35cf8e63cc574b1c52b11df2c86030af0ac09b01b13ea9 \ - --hash=sha256:946d195a0d259cbba61165e88e65941f16e9b36ea6ddb97f00452bae8b1287d3 - # via requests -imagesize==1.4.1 \ - --hash=sha256:0d8d18d08f840c19d0ee7ca1fd82490fdc3729b7ac93f49870406ddde8ef8d8b \ - --hash=sha256:69150444affb9cb0d5cc5a92b3676f0b2fb7cd9ae39e947a5e11a36b4497cd4a - # via sphinx -importlib-resources==6.5.2 \ - --hash=sha256:185f87adef5bcc288449d98fb4fba07cea78bc036455dd44c5fc4a2fe78fed2c \ - --hash=sha256:789cfdc3ed28c78b67a06acb8126751ced69a3d5f79c095a98298cd8a760ccec - # via - # -r requirements/dev-requirements.txt - # pyelli (pyproject.toml) -iniconfig==2.0.0 \ - --hash=sha256:2d91e135bf72d31a410b17c16da610a82cb55f6b0477d1a902134b24a455b8b3 \ - --hash=sha256:b6a85871a79d2e3b22d2d1b94ac2824226a63c6b741c88f7ae975f18b6778374 - # via - # -r requirements/dev-requirements.txt - # pytest -ipykernel==6.29.5 \ - --hash=sha256:afdb66ba5aa354b09b91379bac28ae4afebbb30e8b39510c9690afb7a10421b5 \ - --hash=sha256:f093a22c4a40f8828f8e330a9c297cb93dcab13bd9678ded6de8e5cf81c56215 - # via - # -r requirements/dev-requirements.txt - # nbmake -ipython==8.34.0 \ - --hash=sha256:0419883fa46e0baa182c5d50ebb8d6b49df1889fdb70750ad6d8cfe678eda6e3 \ - --hash=sha256:c31d658e754673ecc6514583e7dda8069e47136eb62458816b7d1e6625948b5a - # via - # -r requirements/dev-requirements.txt - # pyelli (pyproject.toml) - # ipykernel - # ipywidgets -ipywidgets==8.1.5 \ - --hash=sha256:3290f526f87ae6e77655555baba4f36681c555b8bdbbff430b70e52c34c86245 \ - --hash=sha256:870e43b1a35656a80c18c9503bbf2d16802db1cb487eec6fab27d683381dde17 - # via - # -r requirements/dev-requirements.txt - # pyelli (pyproject.toml) - # anywidget -jedi==0.19.2 \ - --hash=sha256:4770dc3de41bde3966b02eb84fbcf557fb33cce26ad23da12c742fb50ecb11f0 \ - --hash=sha256:a8ef22bde8490f57fe5c7681a3c83cb58874daf72b4784de3cce5b6ef6edb5b9 - # via - # -r requirements/dev-requirements.txt - # ipython -jinja2==3.1.6 \ - --hash=sha256:0137fb05990d35f1275a587e9aee6d56da821fc83491a0fb838183be43f66d6d \ - --hash=sha256:85ece4451f492d0c13c5dd7c13a64681a86afae63a5f347908daf103ce6d2f67 - # via - # myst-parser - # sphinx -jsonschema==4.23.0 \ - --hash=sha256:d71497fef26351a33265337fa77ffeb82423f3ea21283cd9467bb03999266bc4 \ - --hash=sha256:fbadb6f8b144a8f8cf9f0b89ba94501d143e50411a1278633f56a7acf7fd5566 - # via - # -r requirements/dev-requirements.txt - # nbformat -jsonschema-specifications==2024.10.1 \ - --hash=sha256:0f38b83639958ce1152d02a7f062902c41c8fd20d558b0c34344292d417ae272 \ - --hash=sha256:a09a0680616357d9a0ecf05c12ad234479f549239d0f5b55f3deea67475da9bf - # via - # -r requirements/dev-requirements.txt - # jsonschema -jupyter-client==8.6.3 \ - --hash=sha256:35b3a0947c4a6e9d589eb97d7d4cd5e90f910ee73101611f01283732bd6d9419 \ - --hash=sha256:e8a19cc986cc45905ac3362915f410f3af85424b4c0905e94fa5f2cb08e8f23f - # via - # -r requirements/dev-requirements.txt - # ipykernel - # nbclient -jupyter-core==5.7.2 \ - --hash=sha256:4f7315d2f6b4bcf2e3e7cb6e46772eba760ae459cd1f59d29eb57b0a01bd7409 \ - --hash=sha256:aa5f8d32bbf6b431ac830496da7392035d6f61b4f54872f15c4bd2a9c3f536d9 - # via - # -r requirements/dev-requirements.txt - # ipykernel - # jupyter-client - # nbclient - # nbformat -jupyterlab-widgets==3.0.13 \ - --hash=sha256:a2966d385328c1942b683a8cd96b89b8dd82c8b8f81dda902bb2bc06d46f5bed \ - --hash=sha256:e3cda2c233ce144192f1e29914ad522b2f4c40e77214b0cc97377ca3d323db54 - # via - # -r requirements/dev-requirements.txt - # ipywidgets -kiwisolver==1.4.8 \ - --hash=sha256:01c3d31902c7db5fb6182832713d3b4122ad9317c2c5877d0539227d96bb2e50 \ - --hash=sha256:034d2c891f76bd3edbdb3ea11140d8510dca675443da7304205a2eaa45d8334c \ - --hash=sha256:085940635c62697391baafaaeabdf3dd7a6c3643577dde337f4d66eba021b2b8 \ - --hash=sha256:08e77738ed7538f036cd1170cbed942ef749137b1311fa2bbe2a7fda2f6bf3cc \ - --hash=sha256:111793b232842991be367ed828076b03d96202c19221b5ebab421ce8bcad016f \ - --hash=sha256:11e1022b524bd48ae56c9b4f9296bce77e15a2e42a502cceba602f804b32bb79 \ - --hash=sha256:151dffc4865e5fe6dafce5480fab84f950d14566c480c08a53c663a0020504b6 \ - --hash=sha256:16523b40aab60426ffdebe33ac374457cf62863e330a90a0383639ce14bf44b2 \ - --hash=sha256:1732e065704b47c9afca7ffa272f845300a4eb959276bf6970dc07265e73b605 \ - --hash=sha256:1c8ceb754339793c24aee1c9fb2485b5b1f5bb1c2c214ff13368431e51fc9a09 \ - --hash=sha256:23454ff084b07ac54ca8be535f4174170c1094a4cff78fbae4f73a4bcc0d4dab \ - --hash=sha256:23d5f023bdc8c7e54eb65f03ca5d5bb25b601eac4d7f1a042888a1f45237987e \ - --hash=sha256:257af1622860e51b1a9d0ce387bf5c2c4f36a90594cb9514f55b074bcc787cfc \ - --hash=sha256:286b18e86682fd2217a48fc6be6b0f20c1d0ed10958d8dc53453ad58d7be0bf8 \ - --hash=sha256:291331973c64bb9cce50bbe871fb2e675c4331dab4f31abe89f175ad7679a4d7 \ - --hash=sha256:2f0121b07b356a22fb0414cec4666bbe36fd6d0d759db3d37228f496ed67c880 \ - --hash=sha256:3452046c37c7692bd52b0e752b87954ef86ee2224e624ef7ce6cb21e8c41cc1b \ - --hash=sha256:34d142fba9c464bc3bbfeff15c96eab0e7310343d6aefb62a79d51421fcc5f1b \ - --hash=sha256:369b75d40abedc1da2c1f4de13f3482cb99e3237b38726710f4a793432b1c5ff \ - --hash=sha256:36dbbfd34838500a31f52c9786990d00150860e46cd5041386f217101350f0d3 \ - --hash=sha256:370fd2df41660ed4e26b8c9d6bbcad668fbe2560462cba151a721d49e5b6628c \ - --hash=sha256:3a96c0e790ee875d65e340ab383700e2b4891677b7fcd30a699146f9384a2bb0 \ - --hash=sha256:3b9b4d2892fefc886f30301cdd80debd8bb01ecdf165a449eb6e78f79f0fabd6 \ - --hash=sha256:3cd3bc628b25f74aedc6d374d5babf0166a92ff1317f46267f12d2ed54bc1d30 \ - --hash=sha256:3ddc373e0eef45b59197de815b1b28ef89ae3955e7722cc9710fb91cd77b7f47 \ - --hash=sha256:4191ee8dfd0be1c3666ccbac178c5a05d5f8d689bbe3fc92f3c4abec817f8fe0 \ - --hash=sha256:54a62808ac74b5e55a04a408cda6156f986cefbcf0ada13572696b507cc92fa1 \ - --hash=sha256:577facaa411c10421314598b50413aa1ebcf5126f704f1e5d72d7e4e9f020d90 \ - --hash=sha256:641f2ddf9358c80faa22e22eb4c9f54bd3f0e442e038728f500e3b978d00aa7d \ - --hash=sha256:65ea09a5a3faadd59c2ce96dc7bf0f364986a315949dc6374f04396b0d60e09b \ - --hash=sha256:68269e60ee4929893aad82666821aaacbd455284124817af45c11e50a4b42e3c \ - --hash=sha256:69b5637c3f316cab1ec1c9a12b8c5f4750a4c4b71af9157645bf32830e39c03a \ - --hash=sha256:7506488470f41169b86d8c9aeff587293f530a23a23a49d6bc64dab66bedc71e \ - --hash=sha256:768cade2c2df13db52475bd28d3a3fac8c9eff04b0e9e2fda0f3760f20b3f7fc \ - --hash=sha256:77e6f57a20b9bd4e1e2cedda4d0b986ebd0216236f0106e55c28aea3d3d69b16 \ - --hash=sha256:782bb86f245ec18009890e7cb8d13a5ef54dcf2ebe18ed65f795e635a96a1c6a \ - --hash=sha256:7a3ad337add5148cf51ce0b55642dc551c0b9d6248458a757f98796ca7348712 \ - --hash=sha256:7cd2785b9391f2873ad46088ed7599a6a71e762e1ea33e87514b1a441ed1da1c \ - --hash=sha256:7e9a60b50fe8b2ec6f448fe8d81b07e40141bfced7f896309df271a0b92f80f3 \ - --hash=sha256:84a2f830d42707de1d191b9490ac186bf7997a9495d4e9072210a1296345f7dc \ - --hash=sha256:856b269c4d28a5c0d5e6c1955ec36ebfd1651ac00e1ce0afa3e28da95293b561 \ - --hash=sha256:858416b7fb777a53f0c59ca08190ce24e9abbd3cffa18886a5781b8e3e26f65d \ - --hash=sha256:87b287251ad6488e95b4f0b4a79a6d04d3ea35fde6340eb38fbd1ca9cd35bbbc \ - --hash=sha256:88c6f252f6816a73b1f8c904f7bbe02fd67c09a69f7cb8a0eecdbf5ce78e63db \ - --hash=sha256:893f5525bb92d3d735878ec00f781b2de998333659507d29ea4466208df37bed \ - --hash=sha256:89c107041f7b27844179ea9c85d6da275aa55ecf28413e87624d033cf1f6b751 \ - --hash=sha256:918139571133f366e8362fa4a297aeba86c7816b7ecf0bc79168080e2bd79957 \ - --hash=sha256:99cea8b9dd34ff80c521aef46a1dddb0dcc0283cf18bde6d756f1e6f31772165 \ - --hash=sha256:a17b7c4f5b2c51bb68ed379defd608a03954a1845dfed7cc0117f1cc8a9b7fd2 \ - --hash=sha256:a3c44cb68861de93f0c4a8175fbaa691f0aa22550c331fefef02b618a9dcb476 \ - --hash=sha256:a4d3601908c560bdf880f07d94f31d734afd1bb71e96585cace0e38ef44c6d84 \ - --hash=sha256:a5ce1e481a74b44dd5e92ff03ea0cb371ae7a0268318e202be06c8f04f4f1246 \ - --hash=sha256:a66f60f8d0c87ab7f59b6fb80e642ebb29fec354a4dfad687ca4092ae69d04f4 \ - --hash=sha256:b21dbe165081142b1232a240fc6383fd32cdd877ca6cc89eab93e5f5883e1c25 \ - --hash=sha256:b47a465040146981dc9db8647981b8cb96366fbc8d452b031e4f8fdffec3f26d \ - --hash=sha256:b5773efa2be9eb9fcf5415ea3ab70fc785d598729fd6057bea38d539ead28271 \ - --hash=sha256:b83dc6769ddbc57613280118fb4ce3cd08899cc3369f7d0e0fab518a7cf37fdb \ - --hash=sha256:bade438f86e21d91e0cf5dd7c0ed00cda0f77c8c1616bd83f9fc157fa6760d31 \ - --hash=sha256:bcb1ebc3547619c3b58a39e2448af089ea2ef44b37988caf432447374941574e \ - --hash=sha256:be4816dc51c8a471749d664161b434912eee82f2ea66bd7628bd14583a833e85 \ - --hash=sha256:c07b29089b7ba090b6f1a669f1411f27221c3662b3a1b7010e67b59bb5a6f10b \ - --hash=sha256:c2b9a96e0f326205af81a15718a9073328df1173a2619a68553decb7097fd5d7 \ - --hash=sha256:c5020c83e8553f770cb3b5fc13faac40f17e0b205bd237aebd21d53d733adb03 \ - --hash=sha256:c72941acb7b67138f35b879bbe85be0f6c6a70cab78fe3ef6db9c024d9223e5b \ - --hash=sha256:c8bf637892dc6e6aad2bc6d4d69d08764166e5e3f69d469e55427b6ac001b19d \ - --hash=sha256:cc978a80a0db3a66d25767b03688f1147a69e6237175c0f4ffffaaedf744055a \ - --hash=sha256:ce2cf1e5688edcb727fdf7cd1bbd0b6416758996826a8be1d958f91880d0809d \ - --hash=sha256:d47b28d1dfe0793d5e96bce90835e17edf9a499b53969b03c6c47ea5985844c3 \ - --hash=sha256:d47cfb2650f0e103d4bf68b0b5804c68da97272c84bb12850d877a95c056bd67 \ - --hash=sha256:d5536185fce131780ebd809f8e623bf4030ce1b161353166c49a3c74c287897f \ - --hash=sha256:d561d2d8883e0819445cfe58d7ddd673e4015c3c57261d7bdcd3710d0d14005c \ - --hash=sha256:d6af5e8815fd02997cb6ad9bbed0ee1e60014438ee1a5c2444c96f87b8843502 \ - --hash=sha256:d6d6bd87df62c27d4185de7c511c6248040afae67028a8a22012b010bc7ad062 \ - --hash=sha256:dace81d28c787956bfbfbbfd72fdcef014f37d9b48830829e488fdb32b49d954 \ - --hash=sha256:e063ef9f89885a1d68dd8b2e18f5ead48653176d10a0e324e3b0030e3a69adeb \ - --hash=sha256:e7a019419b7b510f0f7c9dceff8c5eae2392037eae483a7f9162625233802b0a \ - --hash=sha256:eaa973f1e05131de5ff3569bbba7f5fd07ea0595d3870ed4a526d486fe57fa1b \ - --hash=sha256:eb158fe28ca0c29f2260cca8c43005329ad58452c36f0edf298204de32a9a3ed \ - --hash=sha256:ed33ca2002a779a2e20eeb06aea7721b6e47f2d4b8a8ece979d8ba9e2a167e34 \ - --hash=sha256:fc2ace710ba7c1dfd1a3b42530b62b9ceed115f19a1656adefce7b1782a37794 - # via - # -r requirements/dev-requirements.txt - # matplotlib -lark==1.2.2 \ - --hash=sha256:c2276486b02f0f1b90be155f2c8ba4a8e194d42775786db622faccd652d8e80c \ - --hash=sha256:ca807d0162cd16cef15a8feecb862d7319e7a09bdb13aef927968e45040fed80 - # via - # -r requirements/dev-requirements.txt - # pyelli (pyproject.toml) -lmfit==1.3.2 \ - --hash=sha256:2b834f054cd7a5172f3b431345b292e5d95ea387d6f96d60ad35a11b8efee6ac \ - --hash=sha256:31beeae1f027c1b8c14dcd7f2e8488a80b75fb389e77fca677549bdc2fe597bb - # via - # -r requirements/dev-requirements.txt - # pyelli (pyproject.toml) -markdown-it-py==3.0.0 \ - --hash=sha256:355216845c60bd96232cd8d8c40e8f9765cc86f46880e43a8fd22dc1a1a8cab1 \ - --hash=sha256:e3f60a94fa066dc52ec76661e37c851cb232d92f9886b15cb560aaada2df8feb - # via - # mdit-py-plugins - # myst-parser -markupsafe==3.0.2 \ - --hash=sha256:0bff5e0ae4ef2e1ae4fdf2dfd5b76c75e5c2fa4132d05fc1b0dabcd20c7e28c4 \ - --hash=sha256:0f4ca02bea9a23221c0182836703cbf8930c5e9454bacce27e767509fa286a30 \ - --hash=sha256:1225beacc926f536dc82e45f8a4d68502949dc67eea90eab715dea3a21c1b5f0 \ - --hash=sha256:131a3c7689c85f5ad20f9f6fb1b866f402c445b220c19fe4308c0b147ccd2ad9 \ - --hash=sha256:15ab75ef81add55874e7ab7055e9c397312385bd9ced94920f2802310c930396 \ - --hash=sha256:1a9d3f5f0901fdec14d8d2f66ef7d035f2157240a433441719ac9a3fba440b13 \ - --hash=sha256:1c99d261bd2d5f6b59325c92c73df481e05e57f19837bdca8413b9eac4bd8028 \ - --hash=sha256:1e084f686b92e5b83186b07e8a17fc09e38fff551f3602b249881fec658d3eca \ - --hash=sha256:2181e67807fc2fa785d0592dc2d6206c019b9502410671cc905d132a92866557 \ - --hash=sha256:2cb8438c3cbb25e220c2ab33bb226559e7afb3baec11c4f218ffa7308603c832 \ - --hash=sha256:3169b1eefae027567d1ce6ee7cae382c57fe26e82775f460f0b2778beaad66c0 \ - --hash=sha256:3809ede931876f5b2ec92eef964286840ed3540dadf803dd570c3b7e13141a3b \ - --hash=sha256:38a9ef736c01fccdd6600705b09dc574584b89bea478200c5fbf112a6b0d5579 \ - --hash=sha256:3d79d162e7be8f996986c064d1c7c817f6df3a77fe3d6859f6f9e7be4b8c213a \ - --hash=sha256:444dcda765c8a838eaae23112db52f1efaf750daddb2d9ca300bcae1039adc5c \ - --hash=sha256:48032821bbdf20f5799ff537c7ac3d1fba0ba032cfc06194faffa8cda8b560ff \ - --hash=sha256:4aa4e5faecf353ed117801a068ebab7b7e09ffb6e1d5e412dc852e0da018126c \ - --hash=sha256:52305740fe773d09cffb16f8ed0427942901f00adedac82ec8b67752f58a1b22 \ - --hash=sha256:569511d3b58c8791ab4c2e1285575265991e6d8f8700c7be0e88f86cb0672094 \ - --hash=sha256:57cb5a3cf367aeb1d316576250f65edec5bb3be939e9247ae594b4bcbc317dfb \ - --hash=sha256:5b02fb34468b6aaa40dfc198d813a641e3a63b98c2b05a16b9f80b7ec314185e \ - --hash=sha256:6381026f158fdb7c72a168278597a5e3a5222e83ea18f543112b2662a9b699c5 \ - --hash=sha256:6af100e168aa82a50e186c82875a5893c5597a0c1ccdb0d8b40240b1f28b969a \ - --hash=sha256:6c89876f41da747c8d3677a2b540fb32ef5715f97b66eeb0c6b66f5e3ef6f59d \ - --hash=sha256:6e296a513ca3d94054c2c881cc913116e90fd030ad1c656b3869762b754f5f8a \ - --hash=sha256:70a87b411535ccad5ef2f1df5136506a10775d267e197e4cf531ced10537bd6b \ - --hash=sha256:7e94c425039cde14257288fd61dcfb01963e658efbc0ff54f5306b06054700f8 \ - --hash=sha256:846ade7b71e3536c4e56b386c2a47adf5741d2d8b94ec9dc3e92e5e1ee1e2225 \ - --hash=sha256:88416bd1e65dcea10bc7569faacb2c20ce071dd1f87539ca2ab364bf6231393c \ - --hash=sha256:88b49a3b9ff31e19998750c38e030fc7bb937398b1f78cfa599aaef92d693144 \ - --hash=sha256:8c4e8c3ce11e1f92f6536ff07154f9d49677ebaaafc32db9db4620bc11ed480f \ - --hash=sha256:8e06879fc22a25ca47312fbe7c8264eb0b662f6db27cb2d3bbbc74b1df4b9b87 \ - --hash=sha256:9025b4018f3a1314059769c7bf15441064b2207cb3f065e6ea1e7359cb46db9d \ - --hash=sha256:93335ca3812df2f366e80509ae119189886b0f3c2b81325d39efdb84a1e2ae93 \ - --hash=sha256:9778bd8ab0a994ebf6f84c2b949e65736d5575320a17ae8984a77fab08db94cf \ - --hash=sha256:9e2d922824181480953426608b81967de705c3cef4d1af983af849d7bd619158 \ - --hash=sha256:a123e330ef0853c6e822384873bef7507557d8e4a082961e1defa947aa59ba84 \ - --hash=sha256:a904af0a6162c73e3edcb969eeeb53a63ceeb5d8cf642fade7d39e7963a22ddb \ - --hash=sha256:ad10d3ded218f1039f11a75f8091880239651b52e9bb592ca27de44eed242a48 \ - --hash=sha256:b424c77b206d63d500bcb69fa55ed8d0e6a3774056bdc4839fc9298a7edca171 \ - --hash=sha256:b5a6b3ada725cea8a5e634536b1b01c30bcdcd7f9c6fff4151548d5bf6b3a36c \ - --hash=sha256:ba8062ed2cf21c07a9e295d5b8a2a5ce678b913b45fdf68c32d95d6c1291e0b6 \ - --hash=sha256:ba9527cdd4c926ed0760bc301f6728ef34d841f405abf9d4f959c478421e4efd \ - --hash=sha256:bbcb445fa71794da8f178f0f6d66789a28d7319071af7a496d4d507ed566270d \ - --hash=sha256:bcf3e58998965654fdaff38e58584d8937aa3096ab5354d493c77d1fdd66d7a1 \ - --hash=sha256:c0ef13eaeee5b615fb07c9a7dadb38eac06a0608b41570d8ade51c56539e509d \ - --hash=sha256:cabc348d87e913db6ab4aa100f01b08f481097838bdddf7c7a84b7575b7309ca \ - --hash=sha256:cdb82a876c47801bb54a690c5ae105a46b392ac6099881cdfb9f6e95e4014c6a \ - --hash=sha256:cfad01eed2c2e0c01fd0ecd2ef42c492f7f93902e39a42fc9ee1692961443a29 \ - --hash=sha256:d16a81a06776313e817c951135cf7340a3e91e8c1ff2fac444cfd75fffa04afe \ - --hash=sha256:d8213e09c917a951de9d09ecee036d5c7d36cb6cb7dbaece4c71a60d79fb9798 \ - --hash=sha256:e07c3764494e3776c602c1e78e298937c3315ccc9043ead7e685b7f2b8d47b3c \ - --hash=sha256:e17c96c14e19278594aa4841ec148115f9c7615a47382ecb6b82bd8fea3ab0c8 \ - --hash=sha256:e444a31f8db13eb18ada366ab3cf45fd4b31e4db1236a4448f68778c1d1a5a2f \ - --hash=sha256:e6a2a455bd412959b57a172ce6328d2dd1f01cb2135efda2e4576e8a23fa3b0f \ - --hash=sha256:eaa0a10b7f72326f1372a713e73c3f739b524b3af41feb43e4921cb529f5929a \ - --hash=sha256:eb7972a85c54febfb25b5c4b4f3af4dcc731994c7da0d8a0b4a6eb0640e1d178 \ - --hash=sha256:ee55d3edf80167e48ea11a923c7386f4669df67d7994554387f84e7d8b0a2bf0 \ - --hash=sha256:f3818cb119498c0678015754eba762e0d61e5b52d34c8b13d770f0719f7b1d79 \ - --hash=sha256:f8b3d067f2e40fe93e1ccdd6b2e1d16c43140e76f02fb1319a05cf2b79d99430 \ - --hash=sha256:fcabf5ff6eea076f859677f5f0b6b5c1a51e70a376b0579e0eadef8db48c6b50 - # via jinja2 -matplotlib==3.10.1 \ - --hash=sha256:01e63101ebb3014e6e9f80d9cf9ee361a8599ddca2c3e166c563628b39305dbb \ - --hash=sha256:02582304e352f40520727984a5a18f37e8187861f954fea9be7ef06569cf85b4 \ - --hash=sha256:057206ff2d6ab82ff3e94ebd94463d084760ca682ed5f150817b859372ec4401 \ - --hash=sha256:0721a3fd3d5756ed593220a8b86808a36c5031fce489adb5b31ee6dbb47dd5b2 \ - --hash=sha256:0f69dc9713e4ad2fb21a1c30e37bd445d496524257dfda40ff4a8efb3604ab5c \ - --hash=sha256:11b65088c6f3dae784bc72e8d039a2580186285f87448babb9ddb2ad0082993a \ - --hash=sha256:1985ad3d97f51307a2cbfc801a930f120def19ba22864182dacef55277102ba6 \ - --hash=sha256:19b06241ad89c3ae9469e07d77efa87041eac65d78df4fcf9cac318028009b01 \ - --hash=sha256:2589659ea30726284c6c91037216f64a506a9822f8e50592d48ac16a2f29e044 \ - --hash=sha256:35e87384ee9e488d8dd5a2dd7baf471178d38b90618d8ea147aced4ab59c9bea \ - --hash=sha256:3f06bad951eea6422ac4e8bdebcf3a70c59ea0a03338c5d2b109f57b64eb3972 \ - --hash=sha256:4c59af3e8aca75d7744b68e8e78a669e91ccbcf1ac35d0102a7b1b46883f1dd7 \ - --hash=sha256:4f0647b17b667ae745c13721602b540f7aadb2a32c5b96e924cd4fea5dcb90f1 \ - --hash=sha256:56c5d9fcd9879aa8040f196a235e2dcbdf7dd03ab5b07c0696f80bc6cf04bedd \ - --hash=sha256:5d45d3f5245be5b469843450617dcad9af75ca50568acf59997bed9311131a0b \ - --hash=sha256:648406f1899f9a818cef8c0231b44dcfc4ff36f167101c3fd1c9151f24220fdc \ - --hash=sha256:66e907a06e68cb6cfd652c193311d61a12b54f56809cafbed9736ce5ad92f107 \ - --hash=sha256:7e496c01441be4c7d5f96d4e40f7fca06e20dcb40e44c8daa2e740e1757ad9e6 \ - --hash=sha256:8e875b95ac59a7908978fe307ecdbdd9a26af7fa0f33f474a27fcf8c99f64a19 \ - --hash=sha256:8e8e25b1209161d20dfe93037c8a7f7ca796ec9aa326e6e4588d8c4a5dd1e473 \ - --hash=sha256:a144867dd6bf8ba8cb5fc81a158b645037e11b3e5cf8a50bd5f9917cb863adfe \ - --hash=sha256:a3dfb036f34873b46978f55e240cff7a239f6c4409eac62d8145bad3fc6ba5a3 \ - --hash=sha256:a97ff127f295817bc34517255c9db6e71de8eddaab7f837b7d341dee9f2f587f \ - --hash=sha256:aa3854b5f9473564ef40a41bc922be978fab217776e9ae1545c9b3a5cf2092a3 \ - --hash=sha256:bc411ebd5889a78dabbc457b3fa153203e22248bfa6eedc6797be5df0164dbf9 \ - --hash=sha256:c42eee41e1b60fd83ee3292ed83a97a5f2a8239b10c26715d8a6172226988d7b \ - --hash=sha256:c96f2c2f825d1257e437a1482c5a2cf4fee15db4261bd6fc0750f81ba2b4ba3d \ - --hash=sha256:cfd414bce89cc78a7e1d25202e979b3f1af799e416010a20ab2b5ebb3a02425c \ - --hash=sha256:d0673b4b8f131890eb3a1ad058d6e065fb3c6e71f160089b65f8515373394698 \ - --hash=sha256:d3809916157ba871bcdd33d3493acd7fe3037db5daa917ca6e77975a94cef779 \ - --hash=sha256:dc6ab14a7ab3b4d813b88ba957fc05c79493a037f54e246162033591e770de6f \ - --hash=sha256:e8d2d0e3881b129268585bf4765ad3ee73a4591d77b9a18c214ac7e3a79fb2ba \ - --hash=sha256:e9b4bb156abb8fa5e5b2b460196f7db7264fc6d62678c03457979e7d5254b7be \ - --hash=sha256:ff2ae14910be903f4a24afdbb6d7d3a6c44da210fc7d42790b87aeac92238a16 - # via - # -r requirements/dev-requirements.txt - # pyelli (pyproject.toml) -matplotlib-inline==0.1.7 \ - --hash=sha256:8423b23ec666be3d16e16b60bdd8ac4e86e840ebd1dd11a30b9f117f2fa0ab90 \ - --hash=sha256:df192d39a4ff8f21b1895d72e6a13f5fcc5099f00fa84384e0ea28c2cc0653ca - # via - # -r requirements/dev-requirements.txt - # ipykernel - # ipython -mdit-py-plugins==0.4.2 \ - --hash=sha256:0c673c3f889399a33b95e88d2f0d111b4447bdfea7f237dab2d488f459835636 \ - --hash=sha256:5f2cd1fdb606ddf152d37ec30e46101a60512bc0e5fa1a7002c36647b09e26b5 - # via myst-parser -mdurl==0.1.2 \ - --hash=sha256:84008a41e51615a49fc9966191ff91509e3c40b939176e643fd50a5c2196b8f8 \ - --hash=sha256:bb413d29f5eea38f31dd4754dd7377d4465116fb207585f97bf925588687c1ba - # via markdown-it-py -mistune==3.1.2 \ - --hash=sha256:4b47731332315cdca99e0ded46fc0004001c1299ff773dfb48fbe1fd226de319 \ - --hash=sha256:733bf018ba007e8b5f2d3a9eb624034f6ee26c4ea769a98ec533ee111d504dff - # via sphinx-mdinclude -myst-parser==4.0.1 \ - --hash=sha256:5cfea715e4f3574138aecbf7d54132296bfd72bb614d31168f48c477a830a7c4 \ - --hash=sha256:9134e88959ec3b5780aedf8a99680ea242869d012e8821db3126d427edc9c95d - # via pyelli (pyproject.toml) -nbclient==0.10.2 \ - --hash=sha256:4ffee11e788b4a27fabeb7955547e4318a5298f34342a4bfd01f2e1faaeadc3d \ - --hash=sha256:90b7fc6b810630db87a6d0c2250b1f0ab4cf4d3c27a299b0cde78a4ed3fd9193 - # via - # -r requirements/dev-requirements.txt - # nbmake -nbformat==5.10.4 \ - --hash=sha256:322168b14f937a5d11362988ecac2a4952d3d8e3a2cbeb2319584631226d5b3a \ - --hash=sha256:3b48d6c8fbca4b299bf3982ea7db1af21580e4fec269ad087b9e81588891200b - # via - # -r requirements/dev-requirements.txt - # nbclient - # nbmake -nbmake==1.5.5 \ - --hash=sha256:239dc868ea13a7c049746e2aba2c229bd0f6cdbc6bfa1d22f4c88638aa4c5f5c \ - --hash=sha256:c6fbe6e48b60cacac14af40b38bf338a3b88f47f085c54ac5b8639ff0babaf4b - # via - # -r requirements/dev-requirements.txt - # pyelli (pyproject.toml) -nest-asyncio==1.6.0 \ - --hash=sha256:6f172d5449aca15afd6c646851f4e31e02c598d553a667e38cafa997cfec55fe \ - --hash=sha256:87af6efd6b5e897c81050477ef65c62e2b2f35d51703cae01aff2905b1852e1c - # via - # -r requirements/dev-requirements.txt - # ipykernel -nodeenv==1.9.1 \ - --hash=sha256:6ec12890a2dab7946721edbfbcd91f3319c6ccc9aec47be7c7e6b7011ee6645f \ - --hash=sha256:ba11c9782d29c27c70ffbdda2d7415098754709be8a7056d79a737cd901155c9 - # via - # -r requirements/dev-requirements.txt - # pre-commit -numpy==2.2.3 \ - --hash=sha256:0391ea3622f5c51a2e29708877d56e3d276827ac5447d7f45e9bc4ade8923c52 \ - --hash=sha256:12c045f43b1d2915eca6b880a7f4a256f59d62df4f044788c8ba67709412128d \ - --hash=sha256:136553f123ee2951bfcfbc264acd34a2fc2f29d7cdf610ce7daf672b6fbaa693 \ - --hash=sha256:1402da8e0f435991983d0a9708b779f95a8c98c6b18a171b9f1be09005e64d9d \ - --hash=sha256:16372619ee728ed67a2a606a614f56d3eabc5b86f8b615c79d01957062826ca8 \ - --hash=sha256:1ad78ce7f18ce4e7df1b2ea4019b5817a2f6a8a16e34ff2775f646adce0a5027 \ - --hash=sha256:1b416af7d0ed3271cad0f0a0d0bee0911ed7eba23e66f8424d9f3dfcdcae1304 \ - --hash=sha256:1f45315b2dc58d8a3e7754fe4e38b6fce132dab284a92851e41b2b344f6441c5 \ - --hash=sha256:2376e317111daa0a6739e50f7ee2a6353f768489102308b0d98fcf4a04f7f3b5 \ - --hash=sha256:23c9f4edbf4c065fddb10a4f6e8b6a244342d95966a48820c614891e5059bb50 \ - --hash=sha256:246535e2f7496b7ac85deffe932896a3577be7af8fb7eebe7146444680297e9a \ - --hash=sha256:2e8da03bd561504d9b20e7a12340870dfc206c64ea59b4cfee9fceb95070ee94 \ - --hash=sha256:34c1b7e83f94f3b564b35f480f5652a47007dd91f7c839f404d03279cc8dd021 \ - --hash=sha256:39261798d208c3095ae4f7bc8eaeb3481ea8c6e03dc48028057d3cbdbdb8937e \ - --hash=sha256:3b787adbf04b0db1967798dba8da1af07e387908ed1553a0d6e74c084d1ceafe \ - --hash=sha256:3c2ec8a0f51d60f1e9c0c5ab116b7fc104b165ada3f6c58abf881cb2eb16044d \ - --hash=sha256:435e7a933b9fda8126130b046975a968cc2d833b505475e588339e09f7672890 \ - --hash=sha256:4d8335b5f1b6e2bce120d55fb17064b0262ff29b459e8493d1785c18ae2553b8 \ - --hash=sha256:4d9828d25fb246bedd31e04c9e75714a4087211ac348cb39c8c5f99dbb6683fe \ - --hash=sha256:52659ad2534427dffcc36aac76bebdd02b67e3b7a619ac67543bc9bfe6b7cdb1 \ - --hash=sha256:5266de33d4c3420973cf9ae3b98b54a2a6d53a559310e3236c4b2b06b9c07d4e \ - --hash=sha256:5521a06a3148686d9269c53b09f7d399a5725c47bbb5b35747e1cb76326b714b \ - --hash=sha256:596140185c7fa113563c67c2e894eabe0daea18cf8e33851738c19f70ce86aeb \ - --hash=sha256:5b732c8beef1d7bc2d9e476dbba20aaff6167bf205ad9aa8d30913859e82884b \ - --hash=sha256:5ebeb7ef54a7be11044c33a17b2624abe4307a75893c001a4800857956b41094 \ - --hash=sha256:712a64103d97c404e87d4d7c47fb0c7ff9acccc625ca2002848e0d53288b90ea \ - --hash=sha256:7678556eeb0152cbd1522b684dcd215250885993dd00adb93679ec3c0e6e091c \ - --hash=sha256:77974aba6c1bc26e3c205c2214f0d5b4305bdc719268b93e768ddb17e3fdd636 \ - --hash=sha256:783145835458e60fa97afac25d511d00a1eca94d4a8f3ace9fe2043003c678e4 \ - --hash=sha256:7bfdb06b395385ea9b91bf55c1adf1b297c9fdb531552845ff1d3ea6e40d5aba \ - --hash=sha256:7c8dde0ca2f77828815fd1aedfdf52e59071a5bae30dac3b4da2a335c672149a \ - --hash=sha256:83807d445817326b4bcdaaaf8e8e9f1753da04341eceec705c001ff342002e5d \ - --hash=sha256:87eed225fd415bbae787f93a457af7f5990b92a334e346f72070bf569b9c9c95 \ - --hash=sha256:8fb62fe3d206d72fe1cfe31c4a1106ad2b136fcc1606093aeab314f02930fdf2 \ - --hash=sha256:95172a21038c9b423e68be78fd0be6e1b97674cde269b76fe269a5dfa6fadf0b \ - --hash=sha256:9f48ba6f6c13e5e49f3d3efb1b51c8193215c42ac82610a04624906a9270be6f \ - --hash=sha256:a0c03b6be48aaf92525cccf393265e02773be8fd9551a2f9adbe7db1fa2b60f1 \ - --hash=sha256:a5ae282abe60a2db0fd407072aff4599c279bcd6e9a2475500fc35b00a57c532 \ - --hash=sha256:aee2512827ceb6d7f517c8b85aa5d3923afe8fc7a57d028cffcd522f1c6fd082 \ - --hash=sha256:c8b0451d2ec95010d1db8ca733afc41f659f425b7f608af569711097fd6014e2 \ - --hash=sha256:c9aa4496fd0e17e3843399f533d62857cef5900facf93e735ef65aa4bbc90ef0 \ - --hash=sha256:cbc6472e01952d3d1b2772b720428f8b90e2deea8344e854df22b0618e9cce71 \ - --hash=sha256:cdfe0c22692a30cd830c0755746473ae66c4a8f2e7bd508b35fb3b6a0813d787 \ - --hash=sha256:cf802eef1f0134afb81fef94020351be4fe1d6681aadf9c5e862af6602af64ef \ - --hash=sha256:d42f9c36d06440e34226e8bd65ff065ca0963aeecada587b937011efa02cdc9d \ - --hash=sha256:d5b47c440210c5d1d67e1cf434124e0b5c395eee1f5806fdd89b553ed1acd0a3 \ - --hash=sha256:d9b4a8148c57ecac25a16b0e11798cbe88edf5237b0df99973687dd866f05e1b \ - --hash=sha256:daf43a3d1ea699402c5a850e5313680ac355b4adc9770cd5cfc2940e7861f1bf \ - --hash=sha256:dbdc15f0c81611925f382dfa97b3bd0bc2c1ce19d4fe50482cb0ddc12ba30020 \ - --hash=sha256:deaa09cd492e24fd9b15296844c0ad1b3c976da7907e1c1ed3a0ad21dded6f76 \ - --hash=sha256:e37242f5324ffd9f7ba5acf96d774f9276aa62a966c0bad8dae692deebec7716 \ - --hash=sha256:ed2cf9ed4e8ebc3b754d398cba12f24359f018b416c380f577bbae112ca52fc9 \ - --hash=sha256:f2712c5179f40af9ddc8f6727f2bd910ea0eb50206daea75f58ddd9fa3f715bb \ - --hash=sha256:f4ca91d61a4bf61b0f2228f24bbfa6a9facd5f8af03759fe2a655c50ae2c6610 \ - --hash=sha256:f6b3dfc7661f8842babd8ea07e9897fe3d9b69a1d7e5fbb743e4160f9387833b - # via - # -r requirements/dev-requirements.txt - # pyelli (pyproject.toml) - # contourpy - # h5py - # lmfit - # matplotlib - # pandas - # scipy -packaging==24.2 \ - --hash=sha256:09abb1bccd265c01f4a3aa3f7a7db064b36514d2cba19a2f694fe6150451a759 \ - --hash=sha256:c228a6dc5e932d346bc5739379109d49e8853dd8223571c7c5b55260edc0b97f - # via - # -r requirements/dev-requirements.txt - # ipykernel - # matplotlib - # plotly - # pytest - # sphinx -pandas==2.2.3 \ - --hash=sha256:062309c1b9ea12a50e8ce661145c6aab431b1e99530d3cd60640e255778bd43a \ - --hash=sha256:15c0e1e02e93116177d29ff83e8b1619c93ddc9c49083f237d4312337a61165d \ - --hash=sha256:1948ddde24197a0f7add2bdc4ca83bf2b1ef84a1bc8ccffd95eda17fd836ecb5 \ - --hash=sha256:1db71525a1538b30142094edb9adc10be3f3e176748cd7acc2240c2f2e5aa3a4 \ - --hash=sha256:22a9d949bfc9a502d320aa04e5d02feab689d61da4e7764b62c30b991c42c5f0 \ - --hash=sha256:29401dbfa9ad77319367d36940cd8a0b3a11aba16063e39632d98b0e931ddf32 \ - --hash=sha256:31d0ced62d4ea3e231a9f228366919a5ea0b07440d9d4dac345376fd8e1477ea \ - --hash=sha256:3508d914817e153ad359d7e069d752cdd736a247c322d932eb89e6bc84217f28 \ - --hash=sha256:37e0aced3e8f539eccf2e099f65cdb9c8aa85109b0be6e93e2baff94264bdc6f \ - --hash=sha256:381175499d3802cde0eabbaf6324cce0c4f5d52ca6f8c377c29ad442f50f6348 \ - --hash=sha256:38cf8125c40dae9d5acc10fa66af8ea6fdf760b2714ee482ca691fc66e6fcb18 \ - --hash=sha256:3b71f27954685ee685317063bf13c7709a7ba74fc996b84fc6821c59b0f06468 \ - --hash=sha256:3fc6873a41186404dad67245896a6e440baacc92f5b716ccd1bc9ed2995ab2c5 \ - --hash=sha256:4850ba03528b6dd51d6c5d273c46f183f39a9baf3f0143e566b89450965b105e \ - --hash=sha256:4f18ba62b61d7e192368b84517265a99b4d7ee8912f8708660fb4a366cc82667 \ - --hash=sha256:56534ce0746a58afaf7942ba4863e0ef81c9c50d3f0ae93e9497d6a41a057645 \ - --hash=sha256:59ef3764d0fe818125a5097d2ae867ca3fa64df032331b7e0917cf5d7bf66b13 \ - --hash=sha256:5dbca4c1acd72e8eeef4753eeca07de9b1db4f398669d5994086f788a5d7cc30 \ - --hash=sha256:5de54125a92bb4d1c051c0659e6fcb75256bf799a732a87184e5ea503965bce3 \ - --hash=sha256:61c5ad4043f791b61dd4752191d9f07f0ae412515d59ba8f005832a532f8736d \ - --hash=sha256:6374c452ff3ec675a8f46fd9ab25c4ad0ba590b71cf0656f8b6daa5202bca3fb \ - --hash=sha256:63cc132e40a2e084cf01adf0775b15ac515ba905d7dcca47e9a251819c575ef3 \ - --hash=sha256:66108071e1b935240e74525006034333f98bcdb87ea116de573a6a0dccb6c039 \ - --hash=sha256:6dfcb5ee8d4d50c06a51c2fffa6cff6272098ad6540aed1a76d15fb9318194d8 \ - --hash=sha256:7c2875855b0ff77b2a64a0365e24455d9990730d6431b9e0ee18ad8acee13dbd \ - --hash=sha256:7eee9e7cea6adf3e3d24e304ac6b8300646e2a5d1cd3a3c2abed9101b0846761 \ - --hash=sha256:800250ecdadb6d9c78eae4990da62743b857b470883fa27f652db8bdde7f6659 \ - --hash=sha256:86976a1c5b25ae3f8ccae3a5306e443569ee3c3faf444dfd0f41cda24667ad57 \ - --hash=sha256:8cd6d7cc958a3910f934ea8dbdf17b2364827bb4dafc38ce6eef6bb3d65ff09c \ - --hash=sha256:99df71520d25fade9db7c1076ac94eb994f4d2673ef2aa2e86ee039b6746d20c \ - --hash=sha256:a5a1595fe639f5988ba6a8e5bc9649af3baf26df3998a0abe56c02609392e0a4 \ - --hash=sha256:ad5b65698ab28ed8d7f18790a0dc58005c7629f227be9ecc1072aa74c0c1d43a \ - --hash=sha256:b1d432e8d08679a40e2a6d8b2f9770a5c21793a6f9f47fdd52c5ce1948a5a8a9 \ - --hash=sha256:b8661b0238a69d7aafe156b7fa86c44b881387509653fdf857bebc5e4008ad42 \ - --hash=sha256:ba96630bc17c875161df3818780af30e43be9b166ce51c9a18c1feae342906c2 \ - --hash=sha256:bc6b93f9b966093cb0fd62ff1a7e4c09e6d546ad7c1de191767baffc57628f39 \ - --hash=sha256:c124333816c3a9b03fbeef3a9f230ba9a737e9e5bb4060aa2107a86cc0a497fc \ - --hash=sha256:cd8d0c3be0515c12fed0bdbae072551c8b54b7192c7b1fda0ba56059a0179698 \ - --hash=sha256:d9c45366def9a3dd85a6454c0e7908f2b3b8e9c138f5dc38fed7ce720d8453ed \ - --hash=sha256:f00d1345d84d8c86a63e476bb4955e46458b304b9575dcf71102b5c705320015 \ - --hash=sha256:f3a255b2c19987fbbe62a9dfd6cff7ff2aa9ccab3fc75218fd4b7530f01efa24 \ - --hash=sha256:fffb8ae78d8af97f849404f21411c95062db1496aeb3e56f146f0355c9989319 - # via - # -r requirements/dev-requirements.txt - # pyelli (pyproject.toml) - # sphinx-plotly-directive -parso==0.8.4 \ - --hash=sha256:a418670a20291dacd2dddc80c377c5c3791378ee1e8d12bffc35420643d43f18 \ - --hash=sha256:eb3a7b58240fb99099a345571deecc0f9540ea5f4dd2fe14c2a99d6b281ab92d - # via - # -r requirements/dev-requirements.txt - # jedi -pexpect==4.9.0 \ - --hash=sha256:7236d1e080e4936be2dc3e326cec0af72acf9212a7e1d060210e70a47e253523 \ - --hash=sha256:ee7d41123f3c9911050ea2c2dac107568dc43b2d3b0c7557a33212c398ead30f - # via - # -r requirements/dev-requirements.txt - # ipython -pillow==11.1.0 \ - --hash=sha256:015c6e863faa4779251436db398ae75051469f7c903b043a48f078e437656f83 \ - --hash=sha256:0a2f91f8a8b367e7a57c6e91cd25af510168091fb89ec5146003e424e1558a96 \ - --hash=sha256:11633d58b6ee5733bde153a8dafd25e505ea3d32e261accd388827ee987baf65 \ - --hash=sha256:2062ffb1d36544d42fcaa277b069c88b01bb7298f4efa06731a7fd6cc290b81a \ - --hash=sha256:31eba6bbdd27dde97b0174ddf0297d7a9c3a507a8a1480e1e60ef914fe23d352 \ - --hash=sha256:3362c6ca227e65c54bf71a5f88b3d4565ff1bcbc63ae72c34b07bbb1cc59a43f \ - --hash=sha256:368da70808b36d73b4b390a8ffac11069f8a5c85f29eff1f1b01bcf3ef5b2a20 \ - --hash=sha256:36ba10b9cb413e7c7dfa3e189aba252deee0602c86c309799da5a74009ac7a1c \ - --hash=sha256:3764d53e09cdedd91bee65c2527815d315c6b90d7b8b79759cc48d7bf5d4f114 \ - --hash=sha256:3a5fe20a7b66e8135d7fd617b13272626a28278d0e578c98720d9ba4b2439d49 \ - --hash=sha256:3cdcdb0b896e981678eee140d882b70092dac83ac1cdf6b3a60e2216a73f2b91 \ - --hash=sha256:4637b88343166249fe8aa94e7c4a62a180c4b3898283bb5d3d2fd5fe10d8e4e0 \ - --hash=sha256:4db853948ce4e718f2fc775b75c37ba2efb6aaea41a1a5fc57f0af59eee774b2 \ - --hash=sha256:4dd43a78897793f60766563969442020e90eb7847463eca901e41ba186a7d4a5 \ - --hash=sha256:54251ef02a2309b5eec99d151ebf5c9904b77976c8abdcbce7891ed22df53884 \ - --hash=sha256:54ce1c9a16a9561b6d6d8cb30089ab1e5eb66918cb47d457bd996ef34182922e \ - --hash=sha256:593c5fd6be85da83656b93ffcccc2312d2d149d251e98588b14fbc288fd8909c \ - --hash=sha256:5bb94705aea800051a743aa4874bb1397d4695fb0583ba5e425ee0328757f196 \ - --hash=sha256:67cd427c68926108778a9005f2a04adbd5e67c442ed21d95389fe1d595458756 \ - --hash=sha256:70ca5ef3b3b1c4a0812b5c63c57c23b63e53bc38e758b37a951e5bc466449861 \ - --hash=sha256:73ddde795ee9b06257dac5ad42fcb07f3b9b813f8c1f7f870f402f4dc54b5269 \ - --hash=sha256:758e9d4ef15d3560214cddbc97b8ef3ef86ce04d62ddac17ad39ba87e89bd3b1 \ - --hash=sha256:7d33d2fae0e8b170b6a6c57400e077412240f6f5bb2a342cf1ee512a787942bb \ - --hash=sha256:7fdadc077553621911f27ce206ffcbec7d3f8d7b50e0da39f10997e8e2bb7f6a \ - --hash=sha256:8000376f139d4d38d6851eb149b321a52bb8893a88dae8ee7d95840431977081 \ - --hash=sha256:837060a8599b8f5d402e97197d4924f05a2e0d68756998345c829c33186217b1 \ - --hash=sha256:89dbdb3e6e9594d512780a5a1c42801879628b38e3efc7038094430844e271d8 \ - --hash=sha256:8c730dc3a83e5ac137fbc92dfcfe1511ce3b2b5d7578315b63dbbb76f7f51d90 \ - --hash=sha256:8e275ee4cb11c262bd108ab2081f750db2a1c0b8c12c1897f27b160c8bd57bbc \ - --hash=sha256:9044b5e4f7083f209c4e35aa5dd54b1dd5b112b108648f5c902ad586d4f945c5 \ - --hash=sha256:93a18841d09bcdd774dcdc308e4537e1f867b3dec059c131fde0327899734aa1 \ - --hash=sha256:9409c080586d1f683df3f184f20e36fb647f2e0bc3988094d4fd8c9f4eb1b3b3 \ - --hash=sha256:96f82000e12f23e4f29346e42702b6ed9a2f2fea34a740dd5ffffcc8c539eb35 \ - --hash=sha256:9aa9aeddeed452b2f616ff5507459e7bab436916ccb10961c4a382cd3e03f47f \ - --hash=sha256:9ee85f0696a17dd28fbcfceb59f9510aa71934b483d1f5601d1030c3c8304f3c \ - --hash=sha256:a07dba04c5e22824816b2615ad7a7484432d7f540e6fa86af60d2de57b0fcee2 \ - --hash=sha256:a3cd561ded2cf2bbae44d4605837221b987c216cff94f49dfeed63488bb228d2 \ - --hash=sha256:a697cd8ba0383bba3d2d3ada02b34ed268cb548b369943cd349007730c92bddf \ - --hash=sha256:a76da0a31da6fcae4210aa94fd779c65c75786bc9af06289cd1c184451ef7a65 \ - --hash=sha256:a85b653980faad27e88b141348707ceeef8a1186f75ecc600c395dcac19f385b \ - --hash=sha256:a8d65b38173085f24bc07f8b6c505cbb7418009fa1a1fcb111b1f4961814a442 \ - --hash=sha256:aa8dd43daa836b9a8128dbe7d923423e5ad86f50a7a14dc688194b7be5c0dea2 \ - --hash=sha256:ab8a209b8485d3db694fa97a896d96dd6533d63c22829043fd9de627060beade \ - --hash=sha256:abc56501c3fd148d60659aae0af6ddc149660469082859fa7b066a298bde9482 \ - --hash=sha256:ad5db5781c774ab9a9b2c4302bbf0c1014960a0a7be63278d13ae6fdf88126fe \ - --hash=sha256:ae98e14432d458fc3de11a77ccb3ae65ddce70f730e7c76140653048c71bfcbc \ - --hash=sha256:b20be51b37a75cc54c2c55def3fa2c65bb94ba859dde241cd0a4fd302de5ae0a \ - --hash=sha256:b523466b1a31d0dcef7c5be1f20b942919b62fd6e9a9be199d035509cbefc0ec \ - --hash=sha256:b5d658fbd9f0d6eea113aea286b21d3cd4d3fd978157cbf2447a6035916506d3 \ - --hash=sha256:b6123aa4a59d75f06e9dd3dac5bf8bc9aa383121bb3dd9a7a612e05eabc9961a \ - --hash=sha256:bd165131fd51697e22421d0e467997ad31621b74bfc0b75956608cb2906dda07 \ - --hash=sha256:bf902d7413c82a1bfa08b06a070876132a5ae6b2388e2712aab3a7cbc02205c6 \ - --hash=sha256:c12fc111ef090845de2bb15009372175d76ac99969bdf31e2ce9b42e4b8cd88f \ - --hash=sha256:c1eec9d950b6fe688edee07138993e54ee4ae634c51443cfb7c1e7613322718e \ - --hash=sha256:c640e5a06869c75994624551f45e5506e4256562ead981cce820d5ab39ae2192 \ - --hash=sha256:cc1331b6d5a6e144aeb5e626f4375f5b7ae9934ba620c0ac6b3e43d5e683a0f0 \ - --hash=sha256:cfd5cd998c2e36a862d0e27b2df63237e67273f2fc78f47445b14e73a810e7e6 \ - --hash=sha256:d3d8da4a631471dfaf94c10c85f5277b1f8e42ac42bade1ac67da4b4a7359b73 \ - --hash=sha256:d44ff19eea13ae4acdaaab0179fa68c0c6f2f45d66a4d8ec1eda7d6cecbcc15f \ - --hash=sha256:dd0052e9db3474df30433f83a71b9b23bd9e4ef1de13d92df21a52c0303b8ab6 \ - --hash=sha256:dd0e081319328928531df7a0e63621caf67652c8464303fd102141b785ef9547 \ - --hash=sha256:dda60aa465b861324e65a78c9f5cf0f4bc713e4309f83bc387be158b077963d9 \ - --hash=sha256:e06695e0326d05b06833b40b7ef477e475d0b1ba3a6d27da1bb48c23209bf457 \ - --hash=sha256:e1abe69aca89514737465752b4bcaf8016de61b3be1397a8fc260ba33321b3a8 \ - --hash=sha256:e267b0ed063341f3e60acd25c05200df4193e15a4a5807075cd71225a2386e26 \ - --hash=sha256:e5449ca63da169a2e6068dd0e2fcc8d91f9558aba89ff6d02121ca8ab11e79e5 \ - --hash=sha256:e63e4e5081de46517099dc30abe418122f54531a6ae2ebc8680bcd7096860eab \ - --hash=sha256:f189805c8be5ca5add39e6f899e6ce2ed824e65fb45f3c28cb2841911da19070 \ - --hash=sha256:f7955ecf5609dee9442cbface754f2c6e541d9e6eda87fad7f7a989b0bdb9d71 \ - --hash=sha256:f86d3a7a9af5d826744fabf4afd15b9dfef44fe69a98541f666f66fbb8d3fef9 \ - --hash=sha256:fbd43429d0d7ed6533b25fc993861b8fd512c42d04514a0dd6337fb3ccf22761 - # via - # -r requirements/dev-requirements.txt - # matplotlib - # sphinx-gallery -pint==0.24.4 \ - --hash=sha256:35275439b574837a6cd3020a5a4a73645eb125ce4152a73a2f126bf164b91b80 \ - --hash=sha256:aa54926c8772159fcf65f82cc0d34de6768c151b32ad1deb0331291c38fe7659 - # via - # -r requirements/dev-requirements.txt - # pyelli (pyproject.toml) -platformdirs==4.3.6 \ - --hash=sha256:357fb2acbc885b0419afd3ce3ed34564c13c9b95c89360cd9563f73aa5e2b907 \ - --hash=sha256:73e575e1408ab8103900836b97580d5307456908a03e92031bab39e4554cc3fb - # via - # -r requirements/dev-requirements.txt - # jupyter-core - # pint - # virtualenv -plotly==5.24.1 \ - --hash=sha256:dbc8ac8339d248a4bcc36e08a5659bacfe1b079390b8953533f4eb22169b4bae \ - --hash=sha256:f67073a1e637eb0dc3e46324d9d51e2fe76e9727c892dde64ddf1e1b51f29089 - # via - # -r requirements/dev-requirements.txt - # pyelli (pyproject.toml) - # sphinx-plotly-directive -pluggy==1.5.0 \ - --hash=sha256:2cffa88e94fdc978c4c574f15f9e59b7f4201d439195c3715ca9e2486f1d0cf1 \ - --hash=sha256:44e1ad92c8ca002de6377e165f3e0f1be63266ab4d554740532335b9d75ea669 - # via - # -r requirements/dev-requirements.txt - # pytest -pre-commit==4.1.0 \ - --hash=sha256:ae3f018575a588e30dfddfab9a05448bfbd6b73d78709617b5a2b853549716d4 \ - --hash=sha256:d29e7cb346295bcc1cc75fc3e92e343495e3ea0196c9ec6ba53f49f10ab6ae7b - # via - # -r requirements/dev-requirements.txt - # pyelli (pyproject.toml) -prompt-toolkit==3.0.50 \ - --hash=sha256:544748f3860a2623ca5cd6d2795e7a14f3d0e1c3c9728359013f79877fc89bab \ - --hash=sha256:9b6427eb19e479d98acff65196a307c555eb567989e6d88ebbb1b509d9779198 - # via - # -r requirements/dev-requirements.txt - # ipython -psutil==7.0.0 \ - --hash=sha256:101d71dc322e3cffd7cea0650b09b3d08b8e7c4109dd6809fe452dfd00e58b25 \ - --hash=sha256:1e744154a6580bc968a0195fd25e80432d3afec619daf145b9e5ba16cc1d688e \ - --hash=sha256:1fcee592b4c6f146991ca55919ea3d1f8926497a713ed7faaf8225e174581e91 \ - --hash=sha256:39db632f6bb862eeccf56660871433e111b6ea58f2caea825571951d4b6aa3da \ - --hash=sha256:4b1388a4f6875d7e2aff5c4ca1cc16c545ed41dd8bb596cefea80111db353a34 \ - --hash=sha256:4cf3d4eb1aa9b348dec30105c55cd9b7d4629285735a102beb4441e38db90553 \ - --hash=sha256:7be9c3eba38beccb6495ea33afd982a44074b78f28c434a1f51cc07fd315c456 \ - --hash=sha256:84df4eb63e16849689f76b1ffcb36db7b8de703d1bc1fe41773db487621b6c17 \ - --hash=sha256:a5f098451abc2828f7dc6b58d44b532b22f2088f4999a937557b603ce72b1993 \ - --hash=sha256:ba3fcef7523064a6c9da440fc4d6bd07da93ac726b5733c29027d7dc95b39d99 - # via - # -r requirements/dev-requirements.txt - # ipykernel -psygnal==0.12.0 \ - --hash=sha256:0cdb387d1d6f00649c970a8084e4ae3fcd3e38ac12b5c51d086fc9e01d8f7530 \ - --hash=sha256:15f39abd8bee2926e79da76bec31a258d03dbe3e61d22d6251f65caefbae5d54 \ - --hash=sha256:25a9f2db710a6cd2566b3e0e03cf6e04d56276f36ac86b42fa22d81f9a4ac0f2 \ - --hash=sha256:2998e59d12f113ed961e11b30ade9a37b3e0263157cac99d7ab11f5730d4febb \ - --hash=sha256:2a9ee1e6c441074fe71765b0a96c75b19d72c8198ec5bdea7e97e06a6fe9bd41 \ - --hash=sha256:2d5a953a50fc8263bb23bc558b926cf691f70c9c781c68c64c983fb8cbead910 \ - --hash=sha256:2f4c1fed9337f57778109c397b6b9591961123ce4bbeb068115c0468964fc2b4 \ - --hash=sha256:33946be4b9b4efe9e5ced2800b040314c113e898e1310a02751c840af02674d5 \ - --hash=sha256:742abb2d0e230521b208161eeab06abb682a19239e734e543a269214c84a54d2 \ - --hash=sha256:7986828b57861b3341803e519e09189cd93800adede9cfc450e72e1c4ea93f35 \ - --hash=sha256:7a67ec8e0c8a6553dd56ed653f87c46ef652b0c512bb8c8f8c5adcff3907751f \ - --hash=sha256:8d2a99803f3152c469d3642d36c04d680213a20e114245558e026695adf9a9c2 \ - --hash=sha256:a708d8af50b11d55c58bb36cc7e042f02561011398b869b749a62832a656706c \ - --hash=sha256:aa1ce36ff7872d32f281ca6aab027c6d64abdef19ed269bc73a82e80f2a4fbb0 \ - --hash=sha256:ae2bd6edcf911fbff34ed75150e8f8dfb246ebf203514c7c1e4397cabbb1368a \ - --hash=sha256:b410dab639353320044856cef68bd9aa940f8e1399da2f57522356b42bc4cf5d \ - --hash=sha256:bc2324cef7ba3f4d30d32895f8cb7d5cf9ad7bcfdb7955aa92a0fbfe7537ec3f \ - --hash=sha256:c455c972071bc06403795f802623b54b0ba3217b7399520aee5e1e4ca71908e0 \ - --hash=sha256:cc763dbab05fb75f4517c8bd31ede6a4f27e68c59adca55b81a9d7bc875156e0 \ - --hash=sha256:cd075d7bbe82f0615cfef953ed19ca54feba08f1686b42655c02d6ade0b0beb5 \ - --hash=sha256:d6fbeee192beab90ca23d9d3ee3bf1eb7ef5f00e815fa53e23e402feee617242 \ - --hash=sha256:d779f20c6977ec9d5b9fece23b4b28bbcf0a7773539a4a176b5527aea5da27c7 \ - --hash=sha256:dac134c8890e3d0e413ab701fcb56a882f9b151a6a9d625080736c36833b26ed \ - --hash=sha256:df404cfaedff3e58e81407371e596a1a0f0f81e8e5b16e85ea420e030ff558b6 \ - --hash=sha256:e5e6c338e9ccb712f27bf74ae3bbfcf276308b8b01c293342255d69b7eeba61f \ - --hash=sha256:e69d74edb336e5e959ef5680c5393f8f6c7b7561fdcb9014dc2535c6ef3ea194 \ - --hash=sha256:ef3cae9af7a22f3c855cbc5b2cb219c5410b1076eaa6541f48cdb2c901a06ad7 - # via - # -r requirements/dev-requirements.txt - # anywidget -ptyprocess==0.7.0 \ - --hash=sha256:4b41f3967fce3af57cc7e94b888626c18bf37a083e3651ca8feeb66d492fef35 \ - --hash=sha256:5c5d0a3b48ceee0b48485e0c26037c0acd7d29765ca3fbb5cb3831d347423220 - # via - # -r requirements/dev-requirements.txt - # pexpect -pure-eval==0.2.3 \ - --hash=sha256:1db8e35b67b3d218d818ae653e27f06c3aa420901fa7b081ca98cbedc874e0d0 \ - --hash=sha256:5f4e983f40564c576c7c8635ae88db5956bb2229d7e9237d03b3c0b0190eaf42 - # via - # -r requirements/dev-requirements.txt - # stack-data -py-cpuinfo==9.0.0 \ - --hash=sha256:3cdbbf3fac90dc6f118bfd64384f309edeadd902d7c8fb17f02ffa1fc3f49690 \ - --hash=sha256:859625bc251f64e21f077d099d4162689c762b5d6a4c3c97553d56241c9674d5 - # via - # -r requirements/dev-requirements.txt - # pytest-benchmark -pygments==2.19.1 \ - --hash=sha256:61c16d2a8576dc0649d9f39e089b5f02bcd27fba10d8fb4dcc28173f7a45151f \ - --hash=sha256:9ea1544ad55cecf4b8242fab6dd35a93bbce657034b0611ee383099054ab6d8c - # via - # -r requirements/dev-requirements.txt - # ipython - # nbmake - # sphinx - # sphinx-mdinclude -pyparsing==3.2.1 \ - --hash=sha256:506ff4f4386c4cec0590ec19e6302d3aedb992fdc02c761e90416f158dacf8e1 \ - --hash=sha256:61980854fd66de3a90028d679a954d5f2623e83144b5afe5ee86f43d762e5f0a - # via - # -r requirements/dev-requirements.txt - # matplotlib -pytest==8.3.5 \ - --hash=sha256:c69214aa47deac29fad6c2a4f590b9c4a9fdb16a403176fe154b79c0b4d4d820 \ - --hash=sha256:f4efe70cc14e511565ac476b57c279e12a855b11f48f212af1080ef2263d3845 - # via - # -r requirements/dev-requirements.txt - # pyelli (pyproject.toml) - # nbmake - # pytest-benchmark - # pytest-cov -pytest-benchmark==5.1.0 \ - --hash=sha256:922de2dfa3033c227c96da942d1878191afa135a29485fb942e85dff1c592c89 \ - --hash=sha256:9ea661cdc292e8231f7cd4c10b0319e56a2118e2c09d9f50e1b3d150d2aca105 - # via - # -r requirements/dev-requirements.txt - # pyelli (pyproject.toml) -pytest-cov==6.0.0 \ - --hash=sha256:eee6f1b9e61008bd34975a4d5bab25801eb31898b032dd55addc93e96fcaaa35 \ - --hash=sha256:fde0b595ca248bb8e2d76f020b465f3b107c9632e6a1d1705f17834c89dcadc0 - # via - # -r requirements/dev-requirements.txt - # pyelli (pyproject.toml) -python-dateutil==2.9.0.post0 \ - --hash=sha256:37dd54208da7e1cd875388217d5e00ebd4179249f90fb72437e91a35459a0ad3 \ - --hash=sha256:a8b2bc7bffae282281c8140a97d3aa9c14da0b136dfe83f850eea9a5f7470427 - # via - # -r requirements/dev-requirements.txt - # jupyter-client - # matplotlib - # pandas -pytz==2025.1 \ - --hash=sha256:89dd22dca55b46eac6eda23b2d72721bf1bdfef212645d81513ef5d03038de57 \ - --hash=sha256:c2db42be2a2518b28e65f9207c4d05e6ff547d1efa4086469ef855e4ab70178e - # via - # -r requirements/dev-requirements.txt - 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--hash=sha256:f19dae58b616ac56b96f2e2290f2d18730a898a171f447f491cc059b073ca1fa \ - --hash=sha256:f1f31661a80cc46aba381bed475a9135b213ba23ca7ff6797251af31510920ce \ - --hash=sha256:f2c307fbe86e18ab3c885b7e01de942145f539165c3360e2af0f094dd440acd9 \ - --hash=sha256:f32718ee37c07932cc336096dc7403525301fd626349b6eff8470fe0f996d8d7 \ - --hash=sha256:f39d1227e8256d19899d953e6e19ed2ccb689102e6d85e024da5acf410f301eb \ - --hash=sha256:f5eeeb82feec1fc5cbafa5ee9022e87ffdb3a8c48afa035b356fcd20fc7f533f \ - --hash=sha256:f92a002462154c176dac63a8f1f6582ab56eb394ef4914d65a9417f5d9fde218 \ - --hash=sha256:f9ba5def063243793dec6603ad1392f735255cbc7202a3a484c14f99ec290705 \ - --hash=sha256:fc409c18884eaf9ddde516d53af4f2db64a8bc7d81b1a0c274b8aa4e929958e8 - # via - # -r requirements/dev-requirements.txt - # ipykernel - # jupyter-client -rapidfuzz==3.12.2 \ - --hash=sha256:02e6466caa0222d5233b1f05640873671cd99549a5c5ba4c29151634a1e56080 \ - --hash=sha256:09227bd402caa4397ba1d6e239deea635703b042dd266a4092548661fb22b9c6 \ - --hash=sha256:095776b11bb45daf7c2973dd61cc472d7ea7f2eecfa454aef940b4675659b92f \ - --hash=sha256:0b9a75e0385a861178adf59e86d6616cbd0d5adca7228dc9eeabf6f62cf5b0b1 \ - --hash=sha256:0f05b7b95f9f87254b53fa92048367a8232c26cee7fc8665e4337268c3919def \ - --hash=sha256:17e1a3a8b4b5125cfb63a6990459b25b87ea769bdaf90d05bb143f8febef076a \ - --hash=sha256:195adbb384d89d6c55e2fd71e7fb262010f3196e459aa2f3f45f31dd7185fe72 \ - --hash=sha256:19fa5bc4301a1ee55400d4a38a8ecf9522b0391fc31e6da5f4d68513fe5c0026 \ - --hash=sha256:1a314d170ee272ac87579f25a6cf8d16a031e1f7a7b07663434b41a1473bc501 \ - --hash=sha256:1ae9ded463f2ca4ba1eb762913c5f14c23d2e120739a62b7f4cc102eab32dc90 \ - --hash=sha256:1d982a651253ffe8434d9934ff0c1089111d60502228464721a2a4587435e159 \ - --hash=sha256:21d5b3793c6f5aecca595cd24164bf9d3c559e315ec684f912146fc4e769e367 \ - --hash=sha256:24081077b571ec4ee6d5d7ea0e49bc6830bf05b50c1005028523b9cd356209f3 \ - --hash=sha256:296bf0fd4f678488670e262c87a3e4f91900b942d73ae38caa42a417e53643b1 \ - --hash=sha256:29ca445e320e5a8df3bd1d75b4fa4ecfa7c681942b9ac65b55168070a1a1960e \ - --hash=sha256:2b9e43cf2213e524f3309d329f1ad8dbf658db004ed44f6ae1cd2919aa997da5 \ - --hash=sha256:2dee7d740a2d5418d4f964f39ab8d89923e6b945850db833e798a1969b19542a \ - --hash=sha256:2f9b0adc3d894beb51f5022f64717b6114a6fabaca83d77e93ac7675911c8cc5 \ - --hash=sha256:30bf15c1ecec2798b713d551df17f23401a3e3653ad9ed4e83ad1c2b06e86100 \ - --hash=sha256:32691aa59577f42864d5535cb6225d0f47e2c7bff59cf4556e5171e96af68cc1 \ - --hash=sha256:36d3ef4f047ed1bc96fa29289f9e67a637ddca5e4f4d3dc7cb7f50eb33ec1664 \ - --hash=sha256:39b343b6cb4b2c3dbc8d2d4c5ee915b6088e3b144ddf8305a57eaab16cf9fc74 \ - --hash=sha256:3b3c4df0321df6f8f0b61afbaa2ced9622750ee1e619128db57a18533d139820 \ - --hash=sha256:3f2ddd5b99b254039a8c82be5749d4d75943f62eb2c2918acf6ffd586852834f \ - --hash=sha256:40c0f16d62d6553527de3dab2fb69709c4383430ea44bce8fb4711ed4cbc6ae3 \ - --hash=sha256:42e7f747b55529a6d0d1588695d71025e884ab48664dca54b840413dea4588d8 \ - --hash=sha256:46a616c0e13cff2de1761b011e0b14bb73b110182f009223f1453d505c9a975c \ - --hash=sha256:5032cbffa245b4beba0067f8ed17392ef2501b346ae3c1f1d14b950edf4b6115 \ - --hash=sha256:50a9c54c0147b468363119132d514c5024fbad1ed8af12bd8bd411b0119f9208 \ - --hash=sha256:5385398d390c6571f0f2a7837e6ddde0c8b912dac096dc8c87208ce9aaaa7570 \ - --hash=sha256:544a47190a0d25971658a9365dba7095397b4ce3e897f7dd0a77ca2cf6fa984e \ - --hash=sha256:54bb69ebe5ca0bd7527357e348f16a4c0c52fe0c2fcc8a041010467dcb8385f7 \ - --hash=sha256:54e53662d71ed660c83c5109127c8e30b9e607884b7c45d2aff7929bbbd00589 \ - --hash=sha256:55a43be0e0fa956a919043c19d19bd988991d15c59f179d413fe5145ed9deb43 \ - --hash=sha256:55bcc003541f5f16ec0a73bf6de758161973f9e8d75161954380738dd147f9f2 \ - --hash=sha256:58d9ae5cf9246d102db2a2558b67fe7e73c533e5d769099747921232d88b9be2 \ - --hash=sha256:5df0cecc2852fcb078ed1b4482fac4fc2c2e7787f3edda8920d9a4c0f51b1c95 \ - --hash=sha256:648adc2dd2cf873efc23befcc6e75754e204a409dfa77efd0fea30d08f22ef9d \ - --hash=sha256:6906a7eb458731e3dd2495af1d0410e23a21a2a2b7ced535e6d5cd15cb69afc5 \ - --hash=sha256:6938738e00d9eb6e04097b3f565097e20b0c398f9c58959a2bc64f7f6be3d9da \ - --hash=sha256:69f6ecdf1452139f2b947d0c169a605de578efdb72cbb2373cb0a94edca1fd34 \ - --hash=sha256:6c506bdc2f304051592c0d3b0e82eed309248ec10cdf802f13220251358375ea \ - --hash=sha256:6c7152d77b2eb6bfac7baa11f2a9c45fd5a2d848dbb310acd0953b3b789d95c9 \ - --hash=sha256:71cf1ea16acdebe9e2fb62ee7a77f8f70e877bebcbb33b34e660af2eb6d341d9 \ - --hash=sha256:758b10380ad34c1f51753a070d7bb278001b5e6fcf544121c6df93170952d705 \ - --hash=sha256:7635fe34246cd241c8e35eb83084e978b01b83d5ef7e5bf72a704c637f270017 \ - --hash=sha256:780b4469ee21cf62b1b2e8ada042941fd2525e45d5fb6a6901a9798a0e41153c \ - --hash=sha256:78fafaf7f5a48ee35ccd7928339080a0136e27cf97396de45259eca1d331b714 \ - --hash=sha256:7957f5d768de14f6b2715303ccdf224b78416738ee95a028a2965c95f73afbfb \ - --hash=sha256:7a6eaec2ef658dd650c6eb9b36dff7a361ebd7d8bea990ce9d639b911673b2cb \ - --hash=sha256:7e2574cf4aa86065600b664a1ac7b8b8499107d102ecde836aaaa403fc4f1784 \ - --hash=sha256:8117dab9b26a1aaffab59b4e30f80ac4d55e61ad4139a637c149365960933bee \ - --hash=sha256:83eb7ef732c2f8533c6b5fbe69858a722c218acc3e1fc190ab6924a8af7e7e0e \ - --hash=sha256:85a54ce30345cff2c79cbcffa063f270ad1daedd0d0c3ff6e541d3c3ba4288cf \ - --hash=sha256:941f31038dba5d3dedcfcceba81d61570ad457c873a24ceb13f4f44fcb574260 \ - --hash=sha256:96fa00bc105caa34b6cd93dca14a29243a3a7f0c336e4dcd36348d38511e15ac \ - --hash=sha256:97fb05e1ddb7b71a054040af588b0634214ee87cea87900d309fafc16fd272a4 \ - --hash=sha256:9a11e1d036170bbafa43a9e63d8c309273564ec5bdfc5439062f439d1a16965a \ - --hash=sha256:9b1e6f48e1ffa0749261ee23a1c6462bdd0be5eac83093f4711de17a42ae78ad \ - --hash=sha256:9f9132c55d330f0a1d34ce6730a76805323a6250d97468a1ca766a883d6a9a25 \ - --hash=sha256:a057cdb0401e42c84b6516c9b1635f7aedd5e430c6e388bd5f6bcd1d6a0686bb \ - --hash=sha256:a3692d4ab36d44685f61326dca539975a4eda49b2a76f0a3df177d8a2c0de9d2 \ - --hash=sha256:a749fd2690f24ef256b264a781487746bbb95344364fe8fe356f0eef7ef206ba \ - --hash=sha256:acb63c5072c08058f8995404201a52fc4e1ecac105548a4d03c6c6934bda45a3 \ - --hash=sha256:b0ba1ccc22fff782e7152a3d3d0caca44ec4e32dc48ba01c560b8593965b5aa3 \ - --hash=sha256:b3745c6443890265513a3c8777f2de4cb897aeb906a406f97741019be8ad5bcc \ - --hash=sha256:b4c5a0413589aef936892fbfa94b7ff6f7dd09edf19b5a7b83896cc9d4e8c184 \ - --hash=sha256:b63170d9db00629b5b3f2862114d8d6ee19127eaba0eee43762d62a25817dbe0 \ - --hash=sha256:b9f8177b24ccc0a843e85932b1088c5e467a7dd7a181c13f84c684b796bea815 \ - --hash=sha256:bccfb30c668620c5bc3490f2dc7d7da1cca0ead5a9da8b755e2e02e2ef0dff14 \ - --hash=sha256:bd9a67cfc83e8453ef17ddd1c2c4ce4a74d448a197764efb54c29f29fb41f611 \ - --hash=sha256:c4c852cd8bed1516a64fd6e2d4c6f270d4356196ee03fda2af1e5a9e13c34643 \ - --hash=sha256:c988a4fc91856260355773bf9d32bebab2083d4c6df33fafeddf4330e5ae9139 \ - --hash=sha256:cf165a76870cd875567941cf861dfd361a0a6e6a56b936c5d30042ddc9def090 \ - --hash=sha256:d41e8231326e94fd07c4d8f424f6bed08fead6f5e6688d1e6e787f1443ae7631 \ - --hash=sha256:d5a3425a6c50fd8fbd991d8f085ddb504791dae6ef9cc3ab299fea2cb5374bef \ - --hash=sha256:d7701769f110332cde45c41759cb2a497de8d2dca55e4c519a46aed5fbb19d1a \ - --hash=sha256:dccf8d4fb5b86d39c581a59463c596b1d09df976da26ff04ae219604223d502f \ - --hash=sha256:dda45f47b559be72ecbce45c7f71dc7c97b9772630ab0f3286d97d2c3025ab71 \ - --hash=sha256:dfb337f1832c1231e3d5621bd0ebebb854e46036aedae3e6a49c1fc08f16f249 \ - --hash=sha256:e0c7989ff32c077bb8fd53253fd6ca569d1bfebc80b17557e60750e6909ba4fe \ - --hash=sha256:e3ceb87c11d2d0fbe8559bb795b0c0604b84cfc8bb7b8720b5c16e9e31e00f41 \ - --hash=sha256:e5fd3ce849b27d063755829cda27a9dab6dbd63be3801f2a40c60ec563a4c90f \ - --hash=sha256:e88c6e68fca301722fa3ab7fd3ca46998012c14ada577bc1e2c2fc04f2067ca6 \ - --hash=sha256:e956b3f053e474abae69ac693a52742109d860ac2375fe88e9387d3277f4c96c \ - --hash=sha256:e9c4d984621ae17404c58f8d06ed8b025e167e52c0e6a511dfec83c37e9220cd \ - --hash=sha256:edd84b0a323885493c893bad16098c5e3b3005d7caa995ae653da07373665d97 \ - --hash=sha256:efa22059c765b3d8778083805b199deaaf643db070f65426f87d274565ddf36a \ - --hash=sha256:f177e1eb6e4f5261a89c475e21bce7a99064a8f217d2336fb897408f46f0ceaf \ - --hash=sha256:f21af27c5e001f0ba1b88c36a0936437dfe034c452548d998891c21125eb640f \ - --hash=sha256:f43b773a4d4950606fb25568ecde5f25280daf8f97b87eb323e16ecd8177b328 \ - --hash=sha256:f4b3334a8958b689f292d5ce8a928140ac98919b51e084f04bf0c14276e4c6ba \ - --hash=sha256:f7c9a003002434889255ff5676ca0f8934a478065ab5e702f75dc42639505bba \ - --hash=sha256:fe2dfc454ee51ba168a67b1e92b72aad251e45a074972cef13340bbad2fd9438 - # via - # -r requirements/dev-requirements.txt - # pyelli (pyproject.toml) -referencing==0.36.2 \ - --hash=sha256:df2e89862cd09deabbdba16944cc3f10feb6b3e6f18e902f7cc25609a34775aa \ - --hash=sha256:e8699adbbf8b5c7de96d8ffa0eb5c158b3beafce084968e2ea8bb08c6794dcd0 - # via - # -r requirements/dev-requirements.txt - # jsonschema - # jsonschema-specifications -requests==2.32.4 \ - --hash=sha256:27babd3cda2a6d50b30443204ee89830707d396671944c998b5975b031ac2b2c \ - --hash=sha256:27d0316682c8a29834d3264820024b62a36942083d52caf2f14c0591336d3422 - # via sphinx -rpds-py==0.23.1 \ - --hash=sha256:09cd7dbcb673eb60518231e02874df66ec1296c01a4fcd733875755c02014b19 \ - --hash=sha256:0f3288930b947cbebe767f84cf618d2cbe0b13be476e749da0e6a009f986248c \ - --hash=sha256:0fced9fd4a07a1ded1bac7e961ddd9753dd5d8b755ba8e05acba54a21f5f1522 \ - --hash=sha256:112b8774b0b4ee22368fec42749b94366bd9b536f8f74c3d4175d4395f5cbd31 \ - --hash=sha256:11dd60b2ffddba85715d8a66bb39b95ddbe389ad2cfcf42c833f1bcde0878eaf \ - --hash=sha256:178f8a60fc24511c0eb756af741c476b87b610dba83270fce1e5a430204566a4 \ - --hash=sha256:1b08027489ba8fedde72ddd233a5ea411b85a6ed78175f40285bd401bde7466d \ - --hash=sha256:1bf5be5ba34e19be579ae873da515a2836a2166d8d7ee43be6ff909eda42b72b \ - --hash=sha256:1ed7de3c86721b4e83ac440751329ec6a1102229aa18163f84c75b06b525ad7e \ - --hash=sha256:1eedaaccc9bb66581d4ae7c50e15856e335e57ef2734dbc5fd8ba3e2a4ab3cb6 \ - --hash=sha256:243241c95174b5fb7204c04595852fe3943cc41f47aa14c3828bc18cd9d3b2d6 \ - --hash=sha256:26bb3e8de93443d55e2e748e9fd87deb5f8075ca7bc0502cfc8be8687d69a2ec \ - --hash=sha256:271fa2184cf28bdded86bb6217c8e08d3a169fe0bbe9be5e8d96e8476b707122 \ - --hash=sha256:28358c54fffadf0ae893f6c1050e8f8853e45df22483b7fff2f6ab6152f5d8bf \ - --hash=sha256:285019078537949cecd0190f3690a0b0125ff743d6a53dfeb7a4e6787af154f5 \ - --hash=sha256:2893d778d4671ee627bac4037a075168b2673c57186fb1a57e993465dbd79a93 \ - --hash=sha256:2a54027554ce9b129fc3d633c92fa33b30de9f08bc61b32c053dc9b537266fed \ - --hash=sha256:2c6ae11e6e93728d86aafc51ced98b1658a0080a7dd9417d24bfb955bb09c3c2 \ - 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--hash=sha256:a20cb698c4a59c534c6701b1c24a968ff2768b18ea2991f886bd8985ce17a89f \ - --hash=sha256:a970bfaf130c29a679b1d0a6e0f867483cea455ab1535fb427566a475078f27f \ - --hash=sha256:a98f510d86f689fcb486dc59e6e363af04151e5260ad1bdddb5625c10f1e95f8 \ - --hash=sha256:a9d3b728f5a5873d84cba997b9d617c6090ca5721caaa691f3b1a78c60adc057 \ - --hash=sha256:ad76f44f70aac3a54ceb1813ca630c53415da3a24fd93c570b2dfb4856591017 \ - --hash=sha256:ae28144c1daa61366205d32abd8c90372790ff79fc60c1a8ad7fd3c8553a600e \ - --hash=sha256:b03a8d50b137ee758e4c73638b10747b7c39988eb8e6cd11abb7084266455165 \ - --hash=sha256:b5a96fcac2f18e5a0a23a75cd27ce2656c66c11c127b0318e508aab436b77428 \ - --hash=sha256:b5ef909a37e9738d146519657a1aab4584018746a18f71c692f2f22168ece40c \ - --hash=sha256:b79f5ced71efd70414a9a80bbbfaa7160da307723166f09b69773153bf17c590 \ - --hash=sha256:b91cceb5add79ee563bd1f70b30896bd63bc5f78a11c1f00a1e931729ca4f1f4 \ - --hash=sha256:b92f5654157de1379c509b15acec9d12ecf6e3bc1996571b6cb82a4302060447 \ - --hash=sha256:c04ca91dda8a61584165825907f5c967ca09e9c65fe8966ee753a3f2b019fe1e \ - 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--hash=sha256:d6adb81564af0cd428910f83fa7da46ce9ad47c56c0b22b50872bc4515d91966 \ - --hash=sha256:d6f6512a90bd5cd9030a6237f5346f046c6f0e40af98657568fa45695d4de59d \ - --hash=sha256:d7031d493c4465dbc8d40bd6cafefef4bd472b17db0ab94c53e7909ee781b9ef \ - --hash=sha256:d9f75a06ecc68f159d5d7603b734e1ff6daa9497a929150f794013aa9f6e3f12 \ - --hash=sha256:db7707dde9143a67b8812c7e66aeb2d843fe33cc8e374170f4d2c50bd8f2472d \ - --hash=sha256:e0397dd0b3955c61ef9b22838144aa4bef6f0796ba5cc8edfc64d468b93798b4 \ - --hash=sha256:e0df046f2266e8586cf09d00588302a32923eb6386ced0ca5c9deade6af9a149 \ - --hash=sha256:e14f86b871ea74c3fddc9a40e947d6a5d09def5adc2076ee61fb910a9014fb35 \ - --hash=sha256:e5963ea87f88bddf7edd59644a35a0feecf75f8985430124c253612d4f7d27ae \ - --hash=sha256:e768267cbe051dd8d1c5305ba690bb153204a09bf2e3de3ae530de955f5b5580 \ - --hash=sha256:e9cb79ecedfc156c0692257ac7ed415243b6c35dd969baa461a6888fc79f2f07 \ - --hash=sha256:ed6f011bedca8585787e5082cce081bac3d30f54520097b2411351b3574e1219 \ - --hash=sha256:f3429fb8e15b20961efca8c8b21432623d85db2228cc73fe22756c6637aa39e7 \ - --hash=sha256:f35eff113ad430b5272bbfc18ba111c66ff525828f24898b4e146eb479a2cdda \ - --hash=sha256:f3a6cb95074777f1ecda2ca4fa7717caa9ee6e534f42b7575a8f0d4cb0c24013 \ - --hash=sha256:f7356a6da0562190558c4fcc14f0281db191cdf4cb96e7604c06acfcee96df15 \ - --hash=sha256:f88626e3f5e57432e6191cd0c5d6d6b319b635e70b40be2ffba713053e5147dd \ - --hash=sha256:fad784a31869747df4ac968a351e070c06ca377549e4ace94775aaa3ab33ee06 \ - --hash=sha256:fc869af5cba24d45fb0399b0cfdbcefcf6910bf4dee5d74036a57cf5264b3ff4 \ - --hash=sha256:fee513135b5a58f3bb6d89e48326cd5aa308e4bcdf2f7d59f67c861ada482bf8 - # via - # -r requirements/dev-requirements.txt - # jsonschema - # referencing -ruff==0.8.5 \ - --hash=sha256:03a90200c5dfff49e4c967b405f27fdfa81594cbb7c5ff5609e42d7fe9680da5 \ - --hash=sha256:1098d36f69831f7ff2a1da3e6407d5fbd6dfa2559e4f74ff2d260c5588900317 \ - --hash=sha256:134ae019ef13e1b060ab7136e7828a6d83ea727ba123381307eb37c6bd5e01cb \ - --hash=sha256:4020d8bf8d3a32325c77af452a9976a9ad6455773bcb94991cf15bd66b347e47 \ - --hash=sha256:587c5e95007612c26509f30acc506c874dab4c4abbacd0357400bd1aa799931b \ - --hash=sha256:5ad11a5e3868a73ca1fa4727fe7e33735ea78b416313f4368c504dbeb69c0f88 \ - --hash=sha256:622b82bf3429ff0e346835ec213aec0a04d9730480cbffbb6ad9372014e31bbd \ - --hash=sha256:7512e8cb038db7f5db6aae0e24735ff9ea03bb0ed6ae2ce534e9baa23c1dc9ea \ - --hash=sha256:762f113232acd5b768d6b875d16aad6b00082add40ec91c927f0673a8ec4ede8 \ - --hash=sha256:7b75ac29715ac60d554a049dbb0ef3b55259076181c3369d79466cb130eb5afd \ - --hash=sha256:8710ffd57bdaa6690cbf6ecff19884b8629ec2a2a2a2f783aa94b1cc795139ed \ - --hash=sha256:9d99cf80b0429cbebf31cbbf6f24f05a29706f0437c40413d950e67e2d4faca4 \ - --hash=sha256:b5462d7804558ccff9c08fe8cbf6c14b7efe67404316696a2dde48297b1925bb \ - --hash=sha256:c01c048f9c3385e0fd7822ad0fd519afb282af9cf1778f3580e540629df89725 \ - --hash=sha256:c9d526a62c9eda211b38463528768fd0ada25dad524cb33c0e99fcff1c67b5dc \ - --hash=sha256:d56de7220a35607f9fe59f8a6d018e14504f7b71d784d980835e20fc0611cd50 \ - --hash=sha256:f69ab37771ea7e0715fead8624ec42996d101269a96e31f4d31be6fc33aa19b7 \ - --hash=sha256:f99be814d77a5dac8a8957104bdd8c359e85c86b0ee0e38dca447cb1095f70fb - # via - # -r requirements/dev-requirements.txt - # pyelli (pyproject.toml) -scipy==1.15.2 \ - --hash=sha256:01edfac9f0798ad6b46d9c4c9ca0e0ad23dbf0b1eb70e96adb9fa7f525eff0bf \ - --hash=sha256:03205d57a28e18dfd39f0377d5002725bf1f19a46f444108c29bdb246b6c8a11 \ - --hash=sha256:08b57a9336b8e79b305a143c3655cc5bdbe6d5ece3378578888d2afbb51c4e37 \ - --hash=sha256:11e7ad32cf184b74380f43d3c0a706f49358b904fa7d5345f16ddf993609184d \ - --hash=sha256:28a0d2c2075946346e4408b211240764759e0fabaeb08d871639b5f3b1aca8a0 \ - --hash=sha256:2b871df1fe1a3ba85d90e22742b93584f8d2b8e6124f8372ab15c71b73e428b8 \ - --hash=sha256:302093e7dfb120e55515936cb55618ee0b895f8bcaf18ff81eca086c17bd80af \ - --hash=sha256:42dabaaa798e987c425ed76062794e93a243be8f0f20fff6e7a89f4d61cb3d40 \ - --hash=sha256:447ce30cee6a9d5d1379087c9e474628dab3db4a67484be1b7dc3196bfb2fac9 \ - --hash=sha256:4c6676490ad76d1c2894d77f976144b41bd1a4052107902238047fb6a473e971 \ - --hash=sha256:54c462098484e7466362a9f1672d20888f724911a74c22ae35b61f9c5919183d \ - --hash=sha256:597a0c7008b21c035831c39927406c6181bcf8f60a73f36219b69d010aa04737 \ - --hash=sha256:5a6fd6eac1ce74a9f77a7fc724080d507c5812d61e72bd5e4c489b042455865e \ - --hash=sha256:5ea7ed46d437fc52350b028b1d44e002646e28f3e8ddc714011aaf87330f2f32 \ - --hash=sha256:601881dfb761311045b03114c5fe718a12634e5608c3b403737ae463c9885d53 \ - --hash=sha256:62ca1ff3eb513e09ed17a5736929429189adf16d2d740f44e53270cc800ecff1 \ - --hash=sha256:69ea6e56d00977f355c0f84eba69877b6df084516c602d93a33812aa04d90a3d \ - --hash=sha256:6a8e34cf4c188b6dd004654f88586d78f95639e48a25dfae9c5e34a6dc34547e \ - --hash=sha256:6d0194c37037707b2afa7a2f2a924cf7bac3dc292d51b6a925e5fcb89bc5c776 \ - --hash=sha256:6f223753c6ea76983af380787611ae1291e3ceb23917393079dcc746ba60cfb5 \ - --hash=sha256:6f5e296ec63c5da6ba6fa0343ea73fd51b8b3e1a300b0a8cae3ed4b1122c7462 \ - --hash=sha256:7cd5b77413e1855351cdde594eca99c1f4a588c2d63711388b6a1f1c01f62274 \ - --hash=sha256:869269b767d5ee7ea6991ed7e22b3ca1f22de73ab9a49c44bad338b725603301 \ - --hash=sha256:87994da02e73549dfecaed9e09a4f9d58a045a053865679aeb8d6d43747d4df3 \ - --hash=sha256:888307125ea0c4466287191e5606a2c910963405ce9671448ff9c81c53f85f58 \ - --hash=sha256:92233b2df6938147be6fa8824b8136f29a18f016ecde986666be5f4d686a91a4 \ - --hash=sha256:9412f5e408b397ff5641080ed1e798623dbe1ec0d78e72c9eca8992976fa65aa \ - --hash=sha256:9b18aa747da280664642997e65aab1dd19d0c3d17068a04b3fe34e2559196cb9 \ - --hash=sha256:9de9d1416b3d9e7df9923ab23cd2fe714244af10b763975bea9e4f2e81cebd27 \ - --hash=sha256:a2ec871edaa863e8213ea5df811cd600734f6400b4af272e1c011e69401218e9 \ - --hash=sha256:a5080a79dfb9b78b768cebf3c9dcbc7b665c5875793569f48bf0e2b1d7f68f6f \ - --hash=sha256:a8bf5cb4a25046ac61d38f8d3c3426ec11ebc350246a4642f2f315fe95bda655 \ - --hash=sha256:b09ae80010f52efddb15551025f9016c910296cf70adbf03ce2a8704f3a5ad20 \ - --hash=sha256:b5e025e903b4f166ea03b109bb241355b9c42c279ea694d8864d033727205e65 \ - --hash=sha256:bad78d580270a4d32470563ea86c6590b465cb98f83d760ff5b0990cb5518a93 \ - --hash=sha256:bae43364d600fdc3ac327db99659dcb79e6e7ecd279a75fe1266669d9a652828 \ - --hash=sha256:c4697a10da8f8765bb7c83e24a470da5797e37041edfd77fd95ba3811a47c4fd \ - --hash=sha256:c90ebe8aaa4397eaefa8455a8182b164a6cc1d59ad53f79943f266d99f68687f \ - --hash=sha256:cd58a314d92838f7e6f755c8a2167ead4f27e1fd5c1251fd54289569ef3495ec \ - --hash=sha256:cf72ff559a53a6a6d77bd8eefd12a17995ffa44ad86c77a5df96f533d4e6c6bb \ - --hash=sha256:def751dd08243934c884a3221156d63e15234a3155cf25978b0a668409d45eb6 \ - --hash=sha256:e7c68b6a43259ba0aab737237876e5c2c549a031ddb7abc28c7b47f22e202ded \ - --hash=sha256:ecf797d2d798cf7c838c6d98321061eb3e72a74710e6c40540f0e8087e3b499e \ - --hash=sha256:f031846580d9acccd0044efd1a90e6f4df3a6e12b4b6bd694a7bc03a89892b28 \ - --hash=sha256:fb530e4794fc8ea76a4a21ccb67dea33e5e0e60f07fc38a49e821e1eae3b71a0 \ - --hash=sha256:fe8a9eb875d430d81755472c5ba75e84acc980e4a8f6204d402849234d3017db - # via - # -r requirements/dev-requirements.txt - # pyelli (pyproject.toml) - # lmfit -six==1.17.0 \ - --hash=sha256:4721f391ed90541fddacab5acf947aa0d3dc7d27b2e1e8eda2be8970586c3274 \ - --hash=sha256:ff70335d468e7eb6ec65b95b99d3a2836546063f63acc5171de367e834932a81 - # via - # -r requirements/dev-requirements.txt - # python-dateutil -snowballstemmer==2.2.0 \ - --hash=sha256:09b16deb8547d3412ad7b590689584cd0fe25ec8db3be37788be3810cbf19cb1 \ - --hash=sha256:c8e1716e83cc398ae16824e5572ae04e0d9fc2c6b985fb0f900f5f0c96ecba1a - # via sphinx -sphinx==8.1.3 \ - --hash=sha256:09719015511837b76bf6e03e42eb7595ac8c2e41eeb9c29c5b755c6b677992a2 \ - --hash=sha256:43c1911eecb0d3e161ad78611bc905d1ad0e523e4ddc202a58a821773dc4c927 - # via - # pyelli (pyproject.toml) - # myst-parser - # sphinx-gallery - # sphinx-mdinclude - # sphinx-rtd-theme - # sphinxcontrib-jquery - # sphinxcontrib-mermaid -sphinx-gallery==0.19.0 \ - --hash=sha256:4c28751973f81769d5bbbf5e4ebaa0dc49dff8c48eb7f11131eb5f6e4aa25f0e \ - --hash=sha256:8400cb5240ad642e28a612fdba0667f725d0505a9be0222d0243de60e8af2eb3 - # via pyelli (pyproject.toml) -sphinx-mdinclude==0.6.2 \ - --hash=sha256:447462e82cb8be61404a2204227f920769eb923d2f57608e3325f3bb88286b4c \ - --hash=sha256:648e78edb067c0e4bffc22943278d49d54a0714494743592032fa3ad82a86984 - # via pyelli (pyproject.toml) -sphinx-plotly-directive==0.1.3 \ - --hash=sha256:030df1d817a8668ba63db0f491879d9d3f32ebb0266c59266b2fac99c88eed86 \ - --hash=sha256:95a49e4ab96d311afcd801e965f0adfbcd21334c17bbb2ca7d3a2161fdc60b01 - # via pyelli (pyproject.toml) -sphinx-rtd-theme==3.0.2 \ - --hash=sha256:422ccc750c3a3a311de4ae327e82affdaf59eb695ba4936538552f3b00f4ee13 \ - --hash=sha256:b7457bc25dda723b20b086a670b9953c859eab60a2a03ee8eb2bb23e176e5f85 - # via pyelli (pyproject.toml) -sphinxcontrib-applehelp==2.0.0 \ - --hash=sha256:2f29ef331735ce958efa4734873f084941970894c6090408b079c61b2e1c06d1 \ - --hash=sha256:4cd3f0ec4ac5dd9c17ec65e9ab272c9b867ea77425228e68ecf08d6b28ddbdb5 - # via sphinx -sphinxcontrib-devhelp==2.0.0 \ - --hash=sha256:411f5d96d445d1d73bb5d52133377b4248ec79db5c793ce7dbe59e074b4dd1ad \ - --hash=sha256:aefb8b83854e4b0998877524d1029fd3e6879210422ee3780459e28a1f03a8a2 - # via sphinx -sphinxcontrib-htmlhelp==2.1.0 \ - --hash=sha256:166759820b47002d22914d64a075ce08f4c46818e17cfc9470a9786b759b19f8 \ - --hash=sha256:c9e2916ace8aad64cc13a0d233ee22317f2b9025b9cf3295249fa985cc7082e9 - # via sphinx -sphinxcontrib-jquery==4.1 \ - --hash=sha256:1620739f04e36a2c779f1a131a2dfd49b2fd07351bf1968ced074365933abc7a \ - --hash=sha256:f936030d7d0147dd026a4f2b5a57343d233f1fc7b363f68b3d4f1cb0993878ae - # via sphinx-rtd-theme -sphinxcontrib-jsmath==1.0.1 \ - --hash=sha256:2ec2eaebfb78f3f2078e73666b1415417a116cc848b72e5172e596c871103178 \ - --hash=sha256:a9925e4a4587247ed2191a22df5f6970656cb8ca2bd6284309578f2153e0c4b8 - # via sphinx -sphinxcontrib-mermaid==1.0.0 \ - --hash=sha256:2e8ab67d3e1e2816663f9347d026a8dee4a858acdd4ad32dd1c808893db88146 \ - --hash=sha256:60b72710ea02087f212028feb09711225fbc2e343a10d34822fe787510e1caa3 - # via pyelli (pyproject.toml) -sphinxcontrib-qthelp==2.0.0 \ - --hash=sha256:4fe7d0ac8fc171045be623aba3e2a8f613f8682731f9153bb2e40ece16b9bbab \ - --hash=sha256:b18a828cdba941ccd6ee8445dbe72ffa3ef8cbe7505d8cd1fa0d42d3f2d5f3eb - # via sphinx -sphinxcontrib-serializinghtml==2.0.0 \ - --hash=sha256:6e2cb0eef194e10c27ec0023bfeb25badbbb5868244cf5bc5bdc04e4464bf331 \ - --hash=sha256:e9d912827f872c029017a53f0ef2180b327c3f7fd23c87229f7a8e8b70031d4d - # via sphinx -stack-data==0.6.3 \ - --hash=sha256:836a778de4fec4dcd1dcd89ed8abff8a221f58308462e1c4aa2a3cf30148f0b9 \ - --hash=sha256:d5558e0c25a4cb0853cddad3d77da9891a08cb85dd9f9f91b9f8cd66e511e695 - # via - # -r requirements/dev-requirements.txt - # ipython -tenacity==9.0.0 \ - --hash=sha256:807f37ca97d62aa361264d497b0e31e92b8027044942bfa756160d908320d73b \ - --hash=sha256:93de0c98785b27fcf659856aa9f54bfbd399e29969b0621bc7f762bd441b4539 - # via - # -r requirements/dev-requirements.txt - # plotly -tomli==2.2.1 \ - --hash=sha256:023aa114dd824ade0100497eb2318602af309e5a55595f76b626d6d9f3b7b0a6 \ - --hash=sha256:02abe224de6ae62c19f090f68da4e27b10af2b93213d36cf44e6e1c5abd19fdd \ - --hash=sha256:286f0ca2ffeeb5b9bd4fcc8d6c330534323ec51b2f52da063b11c502da16f30c \ - --hash=sha256:2d0f2fdd22b02c6d81637a3c95f8cd77f995846af7414c5c4b8d0545afa1bc4b \ - --hash=sha256:33580bccab0338d00994d7f16f4c4ec25b776af3ffaac1ed74e0b3fc95e885a8 \ - --hash=sha256:400e720fe168c0f8521520190686ef8ef033fb19fc493da09779e592861b78c6 \ - --hash=sha256:40741994320b232529c802f8bc86da4e1aa9f413db394617b9a256ae0f9a7f77 \ - --hash=sha256:465af0e0875402f1d226519c9904f37254b3045fc5084697cefb9bdde1ff99ff \ - --hash=sha256:4a8f6e44de52d5e6c657c9fe83b562f5f4256d8ebbfe4ff922c495620a7f6cea \ - --hash=sha256:4e340144ad7ae1533cb897d406382b4b6fede8890a03738ff1683af800d54192 \ - --hash=sha256:678e4fa69e4575eb77d103de3df8a895e1591b48e740211bd1067378c69e8249 \ - --hash=sha256:6972ca9c9cc9f0acaa56a8ca1ff51e7af152a9f87fb64623e31d5c83700080ee \ - --hash=sha256:7fc04e92e1d624a4a63c76474610238576942d6b8950a2d7f908a340494e67e4 \ - --hash=sha256:889f80ef92701b9dbb224e49ec87c645ce5df3fa2cc548664eb8a25e03127a98 \ - --hash=sha256:8d57ca8095a641b8237d5b079147646153d22552f1c637fd3ba7f4b0b29167a8 \ - --hash=sha256:8dd28b3e155b80f4d54beb40a441d366adcfe740969820caf156c019fb5c7ec4 \ - --hash=sha256:9316dc65bed1684c9a98ee68759ceaed29d229e985297003e494aa825ebb0281 \ - --hash=sha256:a198f10c4d1b1375d7687bc25294306e551bf1abfa4eace6650070a5c1ae2744 \ - --hash=sha256:a38aa0308e754b0e3c67e344754dff64999ff9b513e691d0e786265c93583c69 \ - --hash=sha256:a92ef1a44547e894e2a17d24e7557a5e85a9e1d0048b0b5e7541f76c5032cb13 \ - --hash=sha256:ac065718db92ca818f8d6141b5f66369833d4a80a9d74435a268c52bdfa73140 \ - --hash=sha256:b82ebccc8c8a36f2094e969560a1b836758481f3dc360ce9a3277c65f374285e \ - --hash=sha256:c954d2250168d28797dd4e3ac5cf812a406cd5a92674ee4c8f123c889786aa8e \ - --hash=sha256:cb55c73c5f4408779d0cf3eef9f762b9c9f147a77de7b258bef0a5628adc85cc \ - --hash=sha256:cd45e1dc79c835ce60f7404ec8119f2eb06d38b1deba146f07ced3bbc44505ff \ - --hash=sha256:d3f5614314d758649ab2ab3a62d4f2004c825922f9e370b29416484086b264ec \ - --hash=sha256:d920f33822747519673ee656a4b6ac33e382eca9d331c87770faa3eef562aeb2 \ - --hash=sha256:db2b95f9de79181805df90bedc5a5ab4c165e6ec3fe99f970d0e302f384ad222 \ - --hash=sha256:e59e304978767a54663af13c07b3d1af22ddee3bb2fb0618ca1593e4f593a106 \ - --hash=sha256:e85e99945e688e32d5a35c1ff38ed0b3f41f43fad8df0bdf79f72b2ba7bc5272 \ - --hash=sha256:ece47d672db52ac607a3d9599a9d48dcb2f2f735c6c2d1f34130085bb12b112a \ - --hash=sha256:f4039b9cbc3048b2416cc57ab3bda989a6fcf9b36cf8937f01a6e731b64f80d7 - # via - # -r requirements/dev-requirements.txt - # coverage - # pytest - # sphinx -tornado==6.5.1 \ - --hash=sha256:02420a0eb7bf617257b9935e2b754d1b63897525d8a289c9d65690d580b4dcf7 \ - --hash=sha256:13ce6e3396c24e2808774741331638ee6c2f50b114b97a55c5b442df65fd9692 \ - --hash=sha256:253b76040ee3bab8bcf7ba9feb136436a3787208717a1fb9f2c16b744fba7331 \ - --hash=sha256:308473f4cc5a76227157cdf904de33ac268af770b2c5f05ca6c1161d82fdd95e \ - --hash=sha256:5cae6145f4cdf5ab24744526cc0f55a17d76f02c98f4cff9daa08ae9a217448a \ - --hash=sha256:84ceece391e8eb9b2b95578db65e920d2a61070260594819589609ba9bc6308c \ - --hash=sha256:908e7d64567cecd4c2b458075589a775063453aeb1d2a1853eedb806922f568b \ - --hash=sha256:9e9ca370f717997cb85606d074b0e5b247282cf5e2e1611568b8821afe0342d6 \ - --hash=sha256:b77e9dfa7ed69754a54c89d82ef746398be82f749df69c4d3abe75c4d1ff4888 \ - --hash=sha256:caec6314ce8a81cf69bd89909f4b633b9f523834dc1a352021775d45e51d9401 \ - --hash=sha256:d50065ba7fd11d3bd41bcad0825227cc9a95154bad83239357094c36708001f7 \ - --hash=sha256:e0a36e1bc684dca10b1aa75a31df8bdfed656831489bc1e6a6ebed05dc1ec365 - # via - # -r requirements/dev-requirements.txt - # ipykernel - # jupyter-client -traitlets==5.14.3 \ - --hash=sha256:9ed0579d3502c94b4b3732ac120375cda96f923114522847de4b3bb98b96b6b7 \ - --hash=sha256:b74e89e397b1ed28cc831db7aea759ba6640cb3de13090ca145426688ff1ac4f - # via - # -r requirements/dev-requirements.txt - # comm - # ipykernel - # ipython - # ipywidgets - # jupyter-client - # jupyter-core - # matplotlib-inline - # nbclient - # nbformat -typing-extensions==4.12.2 \ - --hash=sha256:04e5ca0351e0f3f85c6853954072df659d0d13fac324d0072316b67d7794700d \ - --hash=sha256:1a7ead55c7e559dd4dee8856e3a88b41225abfe1ce8df57b7c13915fe121ffb8 - # via - # -r requirements/dev-requirements.txt - # anywidget - # flexcache - # flexparser - # ipython - # mistune - # pint - # referencing -tzdata==2025.1 \ - --hash=sha256:24894909e88cdb28bd1636c6887801df64cb485bd593f2fd83ef29075a81d694 \ - --hash=sha256:7e127113816800496f027041c570f50bcd464a020098a3b6b199517772303639 - # via - # -r requirements/dev-requirements.txt - # pandas -uncertainties==3.2.2 \ - --hash=sha256:e62c86fdc64429828229de6ab4e11466f114907e6bd343c077858994cc12e00b \ - --hash=sha256:fd8543355952f4052786ed4150acaf12e23117bd0f5bd03ea07de466bce646e7 - # via - # -r requirements/dev-requirements.txt - # lmfit -urllib3==2.5.0 \ - --hash=sha256:3fc47733c7e419d4bc3f6b3dc2b4f890bb743906a30d56ba4a5bfa4bbff92760 \ - --hash=sha256:e6b01673c0fa6a13e374b50871808eb3bf7046c4b125b216f6bf1cc604cff0dc - # via requests -uv==0.8.6 \ - --hash=sha256:0b524de39f317bd8733c38cf100b6f8091d44e06b23f7752523ad1ad1454ede3 \ - --hash=sha256:132e73f1e9fe05edc6c06c00416f7c721c48298786fd7293be6c584793170bbc \ - --hash=sha256:1913f5627c57076c88dd38b0173bdb006ae9b8dbd92b1798a1acc9d744c1a7cc \ - --hash=sha256:2ac28509db2e52613a59264bdb150d13274ed13e5b305f7e274da8cd83033985 \ - --hash=sha256:37227aaf1e41c7eda3d7f0028e747a2a2eed3f3506b0adc121a4366e8281115b \ - --hash=sha256:4d4e042f6bd9f143094051a05de758684028f451e563846cbc0c6f505b530cca \ - --hash=sha256:4e81380549151e34ae96d56499438444ba58591ca9f2fc6ba0a867152601849e \ - --hash=sha256:57a98367bfad38e870e1a8a6626464796ffcee6e937d429fbd7b25ddf46bb36f \ - --hash=sha256:5b201ebc1c5c76c3a415fa4edcb25a0e06263d2255319d6d52275c775e926e23 \ - --hash=sha256:6acdc77099906ba64bc1b725bef973c10905d7e9596d1b25f271db772bc9e8e4 \ - --hash=sha256:7796acc3c5b84d5ee5e10cc6cf92eb61c19f6551855d0aa89ef5925e4a371fbf \ - --hash=sha256:7c1f48279ff61940143c78b969094e13324988eabcfcd4799f4350d9d36c1d48 \ - --hash=sha256:993af2c295856c5ca053678a8dadc11ce2f85485513ed1568c16e98d5dfa88bf \ - --hash=sha256:c9de4adac36a62e4bddd959ce65fb4bb09b0cbfd95946d50390f2a9c186ecb9c \ - --hash=sha256:d96ff3a1d06a6a00ed94dfb2996228153b3b5bfc892174b7556216ab872a91b1 \ - --hash=sha256:deab2ce32d2dd7a1c0de459aa23470c60feb0ea24e67c9c5c5988d8bf4eb4a09 \ - --hash=sha256:e35cc1ef79d3dce2b6aeffbfb280d02d5ad741d4ca07874bdf0a4d85c841d9de \ - --hash=sha256:ee67acf1b211be2cfbeaec16cde13c8325810d32ff85963a9dedd1f9d7c61ef7 \ - --hash=sha256:fdceb1ef554df0ddc620bfe83fdcf740829e489c62f78ba1f089abd62c71c63e - # via - # -r requirements/dev-requirements.txt - # pyelli (pyproject.toml) -virtualenv==20.29.3 \ - --hash=sha256:3e3d00f5807e83b234dfb6122bf37cfadf4be216c53a49ac059d02414f819170 \ - --hash=sha256:95e39403fcf3940ac45bc717597dba16110b74506131845d9b687d5e73d947ac - # via - # -r requirements/dev-requirements.txt - # pre-commit -wcwidth==0.2.13 \ - --hash=sha256:3da69048e4540d84af32131829ff948f1e022c1c6bdb8d6102117aac784f6859 \ - --hash=sha256:72ea0c06399eb286d978fdedb6923a9eb47e1c486ce63e9b4e64fc18303972b5 - # via - # -r requirements/dev-requirements.txt - # prompt-toolkit -widgetsnbextension==4.0.13 \ - --hash=sha256:74b2692e8500525cc38c2b877236ba51d34541e6385eeed5aec15a70f88a6c71 \ - --hash=sha256:ffcb67bc9febd10234a362795f643927f4e0c05d9342c727b65d2384f8feacb6 - # via - # -r requirements/dev-requirements.txt - # ipywidgets diff --git a/docs/result.rst b/docs/result.rst deleted file mode 100644 index 3b35ed84..00000000 --- a/docs/result.rst +++ /dev/null @@ -1,8 +0,0 @@ -====== -Result -====== - -.. automodule:: elli.result - :members: - :undoc-members: - :show-inheritance: diff --git a/docs/solvers.rst b/docs/solvers.rst deleted file mode 100644 index 39e734c3..00000000 --- a/docs/solvers.rst +++ /dev/null @@ -1,49 +0,0 @@ -******* -Solvers -******* - -For calculation of light interaction in material stacks the transfer matrix method is used. -In pyElli the :class:`Solver` classes provide the necessary toolset for two kinds of transfer matrix algorithms. -They are not intended to be used directly, but rather to be provided in the evaluation in the :class:`Structure` class. -The :class:`Solver2x2` is a simple and fast algorithm for isotropic materials. -It splits the calculation into two 2x2 matrices, one for the s and one for the p polarized light. - -The :class:`Solver4x4` is a more complex algorithm for anisotropic materials. -It employs a full 4x4 matrix formulation for all light interaction. -It is based on the Berreman matrix formalism [1]_. -In the Berreman formalism a propagator for matrix exponentials is needed. -pyElli provides different implementations to be used in the calculation of the transfer matrices. -The :class:`PropagatorEig` is based on solving the eigenvalues of the first order approximation of the matrix exponential. -Although, it is very fast it is not very accurate. -The :class:`PropagatorExpm` is solving the matrix exponential by the Pade approximation. -It can use SciPy as backend, but for performance-critical tasks, it is recommended to install PyTorch. - -.. rubric:: References - -.. [1] Dwight W. Berreman, "Optics in Stratified and Anisotropic Media: 4×4-Matrix Formulation," J. Opt. Soc. Am. 62, 502-510 (1972) - - - -Solver base class (Solver) -========================== - -.. automodule:: elli.solver - :members: - :undoc-members: - :show-inheritance: - -2x2 Matrix Solver (Solver2x2) -============================= - -.. automodule:: elli.solver2x2 - :members: - :undoc-members: - :show-inheritance: - -4x4 Matrix Solver (Solver4x4) -============================= - -.. automodule:: elli.solver4x4 - :members: - :undoc-members: - :show-inheritance: diff --git a/docs/structure.rst b/docs/structure.rst deleted file mode 100644 index dda5a147..00000000 --- a/docs/structure.rst +++ /dev/null @@ -1,41 +0,0 @@ -========== -Structures -========== - -.. automodule:: elli.structure - -Layers ------- - -Abstract base classes -~~~~~~~~~~~~~~~~~~~~~ - -.. autoclass:: elli.structure.AbstractLayer - :members: - -.. autoclass:: elli.structure.InhomogeneousLayer - :members: - -Homogeneous layers -~~~~~~~~~~~~~~~~~~ - -.. autoclass:: elli.structure.Layer - :members: - -.. autoclass:: elli.structure.RepeatedLayers - :members: - -Inhomogeneous layers -~~~~~~~~~~~~~~~~~~~~ - -.. autoclass:: elli.structure.TwistedLayer - :members: - -.. autoclass:: elli.structure.VaryingMixtureLayer - :members: - -Structure Class ---------------- - -.. autoclass:: elli.structure.Structure - :members: diff --git a/mkdocs.yml b/mkdocs.yml new file mode 100644 index 00000000..6e30f267 --- /dev/null +++ b/mkdocs.yml @@ -0,0 +1,29 @@ +site_name: PyElli +site_url: https://pyellips.github.com/pyElli/docs +theme: + name: material + features: + - navigation.instant + - navigation.tabs + +plugins: + - search + - mkdocstrings: + default_handler: python + locale: en + handlers: + python: + options: + show_source: false + +extra: + version: + provider: mike + +markdown_extensions: + - pymdownx.arithmatex: + generic: true + +extra_javascript: + - js/mathjax.js + - https://unpkg.com/mathjax@3/es5/tex-mml-chtml.js \ No newline at end of file diff --git a/pyproject.toml b/pyproject.toml index 012702bf..90566184 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -54,13 +54,9 @@ dev = [ "pre-commit", ] docs = [ - "sphinx!=5.1.0", - "sphinx_rtd_theme", - "sphinx-mdinclude", - "sphinx-gallery", - "sphinx-plotly-directive", - "sphinxcontrib-mermaid", - "myst_parser", + "mkdocs-material", + "mkdocstrings[python]", + "mike", ] [project.urls] diff --git a/src/elli/kkr/kkr.py b/src/elli/kkr/kkr.py index 05bdab1f..2b880911 100644 --- a/src/elli/kkr/kkr.py +++ b/src/elli/kkr/kkr.py @@ -151,9 +151,10 @@ def re2im(re: np.ndarray, x: np.ndarray) -> np.ndarray: The underlying formula reads: - .. math:: - \Delta \Im(x_i) = \Im(x_i) - \Im(\infty) = - \frac{2}{\pi} \int_0^\infty \frac{x_i \Re(x)}{x^2 - x_i^2} dx + $$ + \Delta \Im(x_i) = \Im(x_i) - \Im(\infty) = + \frac{2}{\pi} \int_0^\infty \frac{x_i \Re(x)}{x^2 - x_i^2} dx + $$ Args: re (numpy.ndarray): The real values to transform. @@ -173,9 +174,10 @@ def im2re(im: np.ndarray, x: np.ndarray) -> np.ndarray: The underlying formula reads: - .. math:: - \Delta \Re(x_i) = \Re(x_i) - \Re(\infty) = - \frac{2}{\pi} \int_0^\infty \frac{x \Im(x)}{x^2 - x_i^2} dx + $$ + \Delta \Re(x_i) = \Re(x_i) - \Re(\infty) = + \frac{2}{\pi} \int_0^\infty \frac{x \Im(x)}{x^2 - x_i^2} dx + $$ Args: im (numpy.ndarray): The imaginary values to transform. @@ -196,9 +198,10 @@ def re2im_reciprocal(re: np.ndarray, x: np.ndarray) -> np.ndarray: The underlying formula reads: - .. math:: - \Delta \Im(x_i) = \Im(x_i) - \Im(\infty) = - \frac{2}{\pi} \int_0^\infty \frac{\Re(x)}{x_i - \frac{x^2}{x_i}} dx + $$ + \Delta \Im(x_i) = \Im(x_i) - \Im(\infty) = + \frac{2}{\pi} \int_0^\infty \frac{\Re(x)}{x_i - \frac{x^2}{x_i}} dx + $$ Args: re (numpy.ndarray): The real values to transform. @@ -219,9 +222,10 @@ def im2re_reciprocal(im: np.ndarray, x: np.ndarray) -> np.ndarray: The underlying formula reads: - .. math:: - \Delta \Re(x_i) = \Re(x_i) - \Re(\infty) = - \frac{2}{\pi} \int_0^\infty \frac{x \Im(x)}{1 - \frac{x^2}{x_i^2}} dx + $$ + \Delta \Re(x_i) = \Re(x_i) - \Re(\infty) = + \frac{2}{\pi} \int_0^\infty \frac{x \Im(x)}{1 - \frac{x^2}{x_i^2}} dx + $$ Args: im (numpy.ndarray): The imaginary values to transform. From 810b22d41686e7b0dadf670feec5b674a3a5fbfb Mon Sep 17 00:00:00 2001 From: domna Date: Fri, 17 Oct 2025 22:28:02 +0200 Subject: [PATCH 2/9] More structure --- docs/contributing.md | 1 + docs/explanation/class_structure.md | 0 docs/explanation/data_structure.md | 0 docs/explanation/index.md | 0 docs/howto/custom_fitting.md | 3 +++ docs/howto/index.md | 1 + docs/howto/mueller_matrix.md | 3 +++ docs/index.md | 2 +- docs/reference/changelog.md | 1 + docs/reference/index.md | 1 + docs/tutorial/getting_started.md | 2 ++ docs/tutorial/index.md | 1 + docs/tutorial/working_with_dispersions.md | 1 + mkdocs.yml | 29 ++++++++++++++++++++++- pyproject.toml | 3 ++- 15 files changed, 45 insertions(+), 3 deletions(-) create mode 100644 docs/contributing.md create mode 100644 docs/explanation/class_structure.md create mode 100644 docs/explanation/data_structure.md create mode 100644 docs/explanation/index.md create mode 100644 docs/howto/custom_fitting.md create mode 100644 docs/howto/index.md create mode 100644 docs/howto/mueller_matrix.md create mode 100644 docs/reference/changelog.md create mode 100644 docs/reference/index.md create mode 100644 docs/tutorial/getting_started.md create mode 100644 docs/tutorial/index.md create mode 100644 docs/tutorial/working_with_dispersions.md diff --git a/docs/contributing.md b/docs/contributing.md new file mode 100644 index 00000000..0801e40f --- /dev/null +++ b/docs/contributing.md @@ -0,0 +1 @@ +# Contributing to pyElli \ No newline at end of file diff --git a/docs/explanation/class_structure.md b/docs/explanation/class_structure.md new file mode 100644 index 00000000..e69de29b diff --git a/docs/explanation/data_structure.md b/docs/explanation/data_structure.md new file mode 100644 index 00000000..e69de29b diff --git a/docs/explanation/index.md b/docs/explanation/index.md new file mode 100644 index 00000000..e69de29b diff --git a/docs/howto/custom_fitting.md b/docs/howto/custom_fitting.md new file mode 100644 index 00000000..a16fd3b4 --- /dev/null +++ b/docs/howto/custom_fitting.md @@ -0,0 +1,3 @@ +# Custom Fitting + +Custom fitting \ No newline at end of file diff --git a/docs/howto/index.md b/docs/howto/index.md new file mode 100644 index 00000000..a5ded53b --- /dev/null +++ b/docs/howto/index.md @@ -0,0 +1 @@ +# How-Tos \ No newline at end of file diff --git a/docs/howto/mueller_matrix.md b/docs/howto/mueller_matrix.md new file mode 100644 index 00000000..722d5a94 --- /dev/null +++ b/docs/howto/mueller_matrix.md @@ -0,0 +1,3 @@ +# Mueller Matrix + +Mueller matrix \ No newline at end of file diff --git a/docs/index.md b/docs/index.md index 021c6284..c5ca0e1f 100644 --- a/docs/index.md +++ b/docs/index.md @@ -1,4 +1,4 @@ -# Welcome to pyElli +# Getting Started with pyElli PyElli is an open-source numerical solver for spectral ellipsometry employing well-known 2x2 and 4x4 solver algorithms. It is intended for a broad range of problems such as simple fitting of layered structures, anisotropic layers and any other polarized light interaction with layered 1D structures. It serves as a system for the day to day ellipsometry task at hand and aims to make optical model generation standardized and reproducible. diff --git a/docs/reference/changelog.md b/docs/reference/changelog.md new file mode 100644 index 00000000..90cb31c6 --- /dev/null +++ b/docs/reference/changelog.md @@ -0,0 +1 @@ +--8<-- "CHANGELOG.md" \ No newline at end of file diff --git a/docs/reference/index.md b/docs/reference/index.md new file mode 100644 index 00000000..4a938e09 --- /dev/null +++ b/docs/reference/index.md @@ -0,0 +1 @@ +# Reference \ No newline at end of file diff --git a/docs/tutorial/getting_started.md b/docs/tutorial/getting_started.md new file mode 100644 index 00000000..1ea992a8 --- /dev/null +++ b/docs/tutorial/getting_started.md @@ -0,0 +1,2 @@ +# Getting started + diff --git a/docs/tutorial/index.md b/docs/tutorial/index.md new file mode 100644 index 00000000..de8ecfe6 --- /dev/null +++ b/docs/tutorial/index.md @@ -0,0 +1 @@ +# Tutorials \ No newline at end of file diff --git a/docs/tutorial/working_with_dispersions.md b/docs/tutorial/working_with_dispersions.md new file mode 100644 index 00000000..047c01f0 --- /dev/null +++ b/docs/tutorial/working_with_dispersions.md @@ -0,0 +1 @@ +# Working with Dispersions \ No newline at end of file diff --git a/mkdocs.yml b/mkdocs.yml index 6e30f267..54aa1bab 100644 --- a/mkdocs.yml +++ b/mkdocs.yml @@ -1,13 +1,39 @@ site_name: PyElli -site_url: https://pyellips.github.com/pyElli/docs +site_description: | + The documentation of pyElli +repo_url: https://github.com/PyEllips/pyElli +edit_uri: "" theme: name: material features: - navigation.instant - navigation.tabs + - navigation.indexes + +nav: + - Getting Started: + - index.md + - contributing.md + - Tutorials: + - tutorial/index.md + - tutorial/getting_started.md + - How-Tos: + - howto/index.md + - howto/custom_fitting.md + - howto/mueller_matrix.md + - Learning: + - explanation/index.md + - explanation/data_structure.md + - explanation/class_structure.md + - Reference: + - reference/index.md + - reference/changelog.md plugins: - search + - api-autonav: + modules: ['src/elli'] + nav_section_title: "Reference" - mkdocstrings: default_handler: python locale: en @@ -21,6 +47,7 @@ extra: provider: mike markdown_extensions: + - pymdownx.snippets - pymdownx.arithmatex: generic: true diff --git a/pyproject.toml b/pyproject.toml index 90566184..2c46e997 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -55,7 +55,8 @@ dev = [ ] docs = [ "mkdocs-material", - "mkdocstrings[python]", + "mkdocstrings[python]>=0.18", + "mkdocs-autoapi", "mike", ] From 815bed1fa7a6d46b7bf5ec5c2e1b0a68fcab0651 Mon Sep 17 00:00:00 2001 From: domna Date: Sat, 18 Oct 2025 09:51:32 +0200 Subject: [PATCH 3/9] Install instructions --- docs/contributing.md | 4 +- docs/index.md | 21 +- docs/tutorial/getting_started.md | 2 - docs/tutorial/simple_fit.md | 1 + mkdocs.yml | 2 +- pyproject.toml | 3 +- uv.lock | 4232 ++++++++++++++++++++++++++++++ 7 files changed, 4258 insertions(+), 7 deletions(-) delete mode 100644 docs/tutorial/getting_started.md create mode 100644 docs/tutorial/simple_fit.md create mode 100644 uv.lock diff --git a/docs/contributing.md b/docs/contributing.md index 0801e40f..aeb15027 100644 --- a/docs/contributing.md +++ b/docs/contributing.md @@ -1 +1,3 @@ -# Contributing to pyElli \ No newline at end of file +# Contributing + +We're happy that you are interested in contributing to pyElli! \ No newline at end of file diff --git a/docs/index.md b/docs/index.md index c5ca0e1f..aad06496 100644 --- a/docs/index.md +++ b/docs/index.md @@ -1,4 +1,23 @@ # Getting Started with pyElli -PyElli is an open-source numerical solver for spectral ellipsometry employing well-known 2x2 and 4x4 solver algorithms. It is intended for a broad range of problems such as simple fitting of layered structures, anisotropic layers and any other polarized light interaction with layered 1D structures. It serves as a system for the day to day ellipsometry task at hand and aims to make optical model generation standardized and reproducible. +PyElli is an open-source numerical solver for spectral ellipsometry employing well-known 2x2 and 4x4 solver algorithms. +It is intended for a broad range of problems such as simple fitting of layered structures, +anisotropic layers and any other polarized light interaction with layered 1D structures. +It serves as a system for the day to day ellipsometry task at hand and aims to make optical model generation standardized and reproducible. +PyElli can be installed directly from [PyPI](https://pypi.org/project/pyElli/). +Installation is as simple as + +``` +pip install pyelli +``` + +## Fitting dependencies + +PyElli has the optional dependency `fitting` to install dependencies to use additional +fitting capabilities and interactive widgets with jupyter notebooks. +If you want to use those you can directly install the dependencies along with pyElli: + +``` +pip install 'pyelli[fitting]' +``` \ No newline at end of file diff --git a/docs/tutorial/getting_started.md b/docs/tutorial/getting_started.md deleted file mode 100644 index 1ea992a8..00000000 --- a/docs/tutorial/getting_started.md +++ /dev/null @@ -1,2 +0,0 @@ -# Getting started - diff --git a/docs/tutorial/simple_fit.md b/docs/tutorial/simple_fit.md new file mode 100644 index 00000000..bba5c6f1 --- /dev/null +++ b/docs/tutorial/simple_fit.md @@ -0,0 +1 @@ +# Performing a Simple Fit diff --git a/mkdocs.yml b/mkdocs.yml index 54aa1bab..b3208019 100644 --- a/mkdocs.yml +++ b/mkdocs.yml @@ -16,7 +16,7 @@ nav: - contributing.md - Tutorials: - tutorial/index.md - - tutorial/getting_started.md + - tutorial/simple_fit.md - How-Tos: - howto/index.md - howto/custom_fitting.md diff --git a/pyproject.toml b/pyproject.toml index 2c46e997..1588ce45 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -50,13 +50,12 @@ dev = [ "pytest-cov", "nbmake", "ruff==0.8.5", - "uv", "pre-commit", ] 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docs/reference/kkr.md | 3 + docs/reference/solvers.md | 25 ++++ docs/tutorial/simple_fit.md | 87 ++++++++++++++ docs/tutorial/working_with_dispersions.md | 7 +- mkdocs.yml | 16 ++- pyproject.toml | 1 + src/elli/kkr/kkr.py | 28 +++-- uv.lock | 109 ++++++++++-------- 11 files changed, 216 insertions(+), 63 deletions(-) create mode 100644 docs/explanation/formula_dispersions.md rename docs/howto/{custom_fitting.md => fitting_multiple_angles.md} (100%) create mode 100644 docs/reference/kkr.md create mode 100644 docs/reference/solvers.md diff --git a/.gitignore b/.gitignore index 56ea5615..5fca4075 100644 --- a/.gitignore +++ b/.gitignore @@ -56,3 +56,6 @@ MANIFEST # Ignore pyenv virtualenv python version .python-version + +# Mkdocs build +site diff --git a/docs/explanation/formula_dispersions.md b/docs/explanation/formula_dispersions.md new file mode 100644 index 00000000..e69de29b diff --git a/docs/howto/custom_fitting.md b/docs/howto/fitting_multiple_angles.md similarity index 100% rename from docs/howto/custom_fitting.md rename to docs/howto/fitting_multiple_angles.md diff --git a/docs/reference/kkr.md b/docs/reference/kkr.md new file mode 100644 index 00000000..6fce1334 --- /dev/null +++ b/docs/reference/kkr.md @@ -0,0 +1,3 @@ +# Kramers-Kronig Relations + +::: elli.kkr.kkr \ No newline at end of file diff --git a/docs/reference/solvers.md b/docs/reference/solvers.md new file mode 100644 index 00000000..2c9b031c --- /dev/null +++ b/docs/reference/solvers.md @@ -0,0 +1,25 @@ +# Solvers + +For calculation of light interaction in material stacks the transfer matrix method is used. +In pyElli the :class:`Solver` classes provide the necessary toolset for two kinds of transfer matrix algorithms. +They are not intended to be used directly, but rather to be provided in the evaluation in the :class:`Structure` class. +The :class:`Solver2x2` is a simple and fast algorithm for isotropic materials. +It splits the calculation into two 2x2 matrices, one for the s and one for the p polarized light. + +The :class:`Solver4x4` is a more complex algorithm for anisotropic materials. +It employs a full 4x4 matrix formulation for all light interaction. +It is based on the Berreman matrix formalism [1]_. +In the Berreman formalism a propagator for matrix exponentials is needed. +pyElli provides different implementations to be used in the calculation of the transfer matrices. +The :class:`PropagatorEig` is based on solving the eigenvalues of the first order approximation of the matrix exponential. +Although, it is very fast it is not very accurate. +The :class:`PropagatorExpm` is solving the matrix exponential by the Pade approximation. +It can use SciPy as backend, but for performance-critical tasks, it is recommended to install PyTorch. + +## Solver2x2 + +::: elli.solver2x2.Solver2x2 + +## Solver4x4 + +::: elli.solver4x4.Solver4x4 \ No newline at end of file diff --git a/docs/tutorial/simple_fit.md b/docs/tutorial/simple_fit.md index bba5c6f1..91ba4ed6 100644 --- a/docs/tutorial/simple_fit.md +++ b/docs/tutorial/simple_fit.md @@ -1 +1,88 @@ # Performing a Simple Fit + +```python +import elli +from elli.fitting import ParamsHist, fit +``` + +## Reading data + +```python +ANGLE = 70 +psi_delta = elli.read_nexus_psi_delta("SiO2onSi.ellips.nxs").loc[ANGLE].loc[210:800] +``` + +## Setting parameters + +```python +params = ParamsHist() +params.add("SiO2_n0", value=1.452, min=-100, max=100, vary=False) +params.add("SiO2_n1", value=36.0, min=-40000, max=40000, vary=False) +params.add("SiO2_n2", value=0, min=-40000, max=40000, vary=False) +params.add("SiO2_k0", value=0, min=-100, max=100, vary=False) +params.add("SiO2_k1", value=0, min=-40000, max=40000, vary=False) +params.add("SiO2_k2", value=0, min=-40000, max=40000, vary=False) +params.add("SiO2_d", value=20, min=0, max=40000, vary=True) +``` + +```python +rii_db = elli.db.RII() +Si = rii_db.get_mat("Si", "Aspnes") +``` + +## Building the Fitting Model + +```python +SiO2_dispersion = elli.Cauchy( + params["SiO2_n0"], + params["SiO2_n1"], + params["SiO2_n2"], + params["SiO2_k0"], + params["SiO2_k1"], + params["SiO2_k2"], +) +``` + +```python +SiO2 = SiO2_dispersion.get_mat() +``` + +```python +structure = elli.Structure( + elli.AIR, + [elli.Layer(SiO2, params["SiO2_d"])], + Si, +) +``` + +```python +structure.evaluate(lbda, ANGLE, solver=elli.Solver2x2) +``` + +## Putting it all together + +```python +@fit(psi_delta, params) +def model(lbda, params): + SiO2 = elli.Cauchy( + params["SiO2_n0"], + params["SiO2_n1"], + params["SiO2_n2"], + params["SiO2_k0"], + params["SiO2_k1"], + params["SiO2_k2"], + ).get_mat() + + structure = elli.Structure( + elli.AIR, + [elli.Layer(SiO2, params["SiO2_d"])], + Si, + ) + + return structure.evaluate(lbda, ANGLE, solver=elli.Solver2x2) +``` + +```python +fit_stats = model.fit() +model.plot() +``` \ No newline at end of file diff --git a/docs/tutorial/working_with_dispersions.md b/docs/tutorial/working_with_dispersions.md index 047c01f0..95789de2 100644 --- a/docs/tutorial/working_with_dispersions.md +++ b/docs/tutorial/working_with_dispersions.md @@ -1 +1,6 @@ -# Working with Dispersions \ No newline at end of file +# Working with Dispersions + +TODO: +- How to construct and add dispersions +- Formula dispersions +- How to load dispersions from rii \ No newline at end of file diff --git a/mkdocs.yml b/mkdocs.yml index b3208019..3f6e063d 100644 --- a/mkdocs.yml +++ b/mkdocs.yml @@ -1,4 +1,4 @@ -site_name: PyElli +site_name: PyElli Documentation site_description: | The documentation of pyElli repo_url: https://github.com/PyEllips/pyElli @@ -9,6 +9,9 @@ theme: - navigation.instant - navigation.tabs - navigation.indexes + palette: + primary: cyan + accent: teal nav: - Getting Started: @@ -25,12 +28,16 @@ nav: - explanation/index.md - explanation/data_structure.md - explanation/class_structure.md + - explanation/formula_dispersions.md - Reference: - reference/index.md + - reference/solvers.md + - reference/kkr.md - reference/changelog.md plugins: - search + - plotly - api-autonav: modules: ['src/elli'] nav_section_title: "Reference" @@ -40,6 +47,7 @@ plugins: handlers: python: options: + show_root_heading: false show_source: false extra: @@ -50,6 +58,12 @@ markdown_extensions: - pymdownx.snippets - pymdownx.arithmatex: generic: true + - footnotes + - pymdownx.superfences: + custom_fences: + - name: plotly + class: mkdocs-plotly + format: !!python/name:mkdocs_plotly_plugin.fences.fence_plotly extra_javascript: - js/mathjax.js diff --git a/pyproject.toml b/pyproject.toml index 1588ce45..333017f8 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -56,6 +56,7 @@ docs = [ "mkdocs-material", "mkdocstrings[python]>=0.18", "mkdocs-api-autonav", + "mkdocs-plotly-plugin", "mike", ] diff --git a/src/elli/kkr/kkr.py b/src/elli/kkr/kkr.py index 2b880911..c322af86 100644 --- a/src/elli/kkr/kkr.py +++ b/src/elli/kkr/kkr.py @@ -1,8 +1,8 @@ -r"""Calculate Kramers-Kronig relations according to Maclaurin's formula [1]_. +r"""Calculate Kramers-Kronig relations according to Maclaurin's formula[^1]. Here, the differential formulation is used, which means that the transformation always diverges to zero at infinity, leaving a free infinity offset. -This offset is typically referred to as :math:`\epsilon(\infty)` in spectroscopy. +This offset is typically referred to as $\epsilon(\infty)$ in spectroscopy. Since the Kramers-Kronig relation integrates over the whole spectrum for each point, it is very sensitive to sampling changes and non-zero values. @@ -16,15 +16,13 @@ For the transformation of the real to imaginary part you need to be especially cautios. Typically, in spectroscopy the real part of the dielectric function is non-zero throughout the whole spectrum -and especially :math:`\epsilon(\infty) \ne 0`. +and especially $\epsilon(\infty) \ne 0$. This makes the Kramers-Kronig transformation virtually impossible in these cases as it suffers from major uncertanties. Hence, this transformation is included in pyElli only for completeness and for the -special cases it may be applicable. +special cases in which it may be applicable. -.. rubric:: References - -.. [1] Ohta and Ishida, Appl. Spectroscopy 42, 952 (1988), https://doi.org/10.1366/0003702884430380 +[^1]: [Ohta and Ishida, Appl. Spectroscopy 42, 952 (1988)](https://doi.org/10.1366/0003702884430380) """ # pylint: disable=invalid-name @@ -60,7 +58,7 @@ def _integrate_im_reciprocal( x_i (numpy.ndarray): The current point around which to integrate. (shape (m, 1)) Returns: - numpy.ndarray: The integral sum. (shape (m,)) + The integral sum. (shape (m,)) """ return np.sum(im / (x * (1.0 - x * x / (x_i * x_i))), axis=1) @@ -75,7 +73,7 @@ def _integrate_re(re: np.ndarray, x: np.ndarray, x_i: np.ndarray) -> np.ndarray: x_i (numpy.ndarray): The current point around which to integrate. (shape (m, 1)) Returns: - numpy.ndarray: The real sum. (shape (m,)) + The real sum. (shape (m,)) """ return np.sum(x_i * re / (x * x - x_i * x_i), axis=1) @@ -92,7 +90,7 @@ def _integrate_re_reciprocal( x_i (float): The current point around which to integrate. (shape (m, 1)) Returns: - numpy.ndarray: The real sum. (shape (m,)) + The real sum. (shape (m,)) """ return np.sum(re / (x_i - x * x / x_i), axis=1) @@ -116,7 +114,7 @@ def _calc_kkr( ValueError: y and x axis must have the same length. Returns: - np.ndarray: The kkr transformed y-axis + The kkr transformed y-axis """ if len(t) != len(x): @@ -161,7 +159,7 @@ def re2im(re: np.ndarray, x: np.ndarray) -> np.ndarray: x (numpy.ndarray): The axis on which to transform. Returns: - numpy.ndarray: The transformed imaginary part. + The transformed imaginary part. """ return _calc_kkr(re, x, _integrate_re) @@ -184,7 +182,7 @@ def im2re(im: np.ndarray, x: np.ndarray) -> np.ndarray: x (numpy.ndarray): The axis on which to transform. Returns: - numpy.ndarray: The transformed real part. + The transformed real part. """ return _calc_kkr(im, x, _integrate_im) @@ -208,7 +206,7 @@ def re2im_reciprocal(re: np.ndarray, x: np.ndarray) -> np.ndarray: x (numpy.ndarray): The reciprocal axis on which to transform. Returns: - numpy.ndarray: The transformed imaginary part. + The transformed imaginary part. """ return _calc_kkr(re, x, _integrate_re_reciprocal) @@ -232,7 +230,7 @@ def im2re_reciprocal(im: np.ndarray, x: np.ndarray) -> np.ndarray: x (numpy.ndarray): The reciprocal axis on which to transform. Returns: - numpy.ndarray: The transformed real part. + The transformed real part. 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We are happy to assist. + +## Reporting an Issue + +If you are encountering problems with pyElli or have a feature request +please open an issue at our [Github Issues Page](https://github.com/PyEllips/pyElli/issues). + +Please try to provide a minimal example for reproducing the issue. +This makes it a lot easier for the developers to work on the problem. + +If you are not entirely sure whether the problem you're encountering is actually a bug +or if you want to discuss some feature ideas feel free to post on our [Github Discussion Page](https://github.com/orgs/PyEllips/discussions) + +## Making a Pull Request + +```sh +git clone --recurse-submodules https://github.com/PyEllips/pyElli +cd pyElli +``` + +=== "pip" + + ```sh + pip install -e '.[dev,docs,fitting] + ``` + +=== "uv" + + ```sh + uv sync --extra dev --extra docs --extra fitting + ``` \ No newline at end of file diff --git a/mkdocs.yml b/mkdocs.yml index 3f6e063d..1db53a7c 100644 --- a/mkdocs.yml +++ b/mkdocs.yml @@ -9,6 +9,7 @@ theme: - navigation.instant - navigation.tabs - navigation.indexes + - content.code.copy palette: primary: cyan accent: teal @@ -22,7 +23,7 @@ nav: - tutorial/simple_fit.md - How-Tos: - howto/index.md - - howto/custom_fitting.md + - howto/fitting_multiple_angles.md - howto/mueller_matrix.md - Learning: - explanation/index.md @@ -55,10 +56,17 @@ extra: provider: mike markdown_extensions: + - pymdownx.highlight: + anchor_linenums: true + line_spans: __span + pygments_lang_class: true + - pymdownx.inlinehilite - pymdownx.snippets - pymdownx.arithmatex: generic: true - footnotes + - pymdownx.tabbed: + alternate_style: true - pymdownx.superfences: custom_fences: - name: plotly From 8e716f072b08c8ef2b9d36e6b3730894ca6e0546 Mon Sep 17 00:00:00 2001 From: domna Date: Wed, 22 Oct 2025 21:32:22 +0200 Subject: [PATCH 6/9] Finalize contributing --- docs/contributing.md | 58 ++++++++++++++++++----- docs/explanation/index.md | 1 + docs/howto/fitting_multiple_angles.md | 2 +- docs/howto/mueller_matrix.md | 2 +- docs/tutorial/working_with_dispersions.md | 11 +++-- mkdocs.yml | 1 + 6 files changed, 57 insertions(+), 18 deletions(-) diff --git a/docs/contributing.md b/docs/contributing.md index 99e4b29c..f7c5a012 100644 --- a/docs/contributing.md +++ b/docs/contributing.md @@ -2,39 +2,75 @@ We're happy that you are interested in contributing to pyElli! -There are several ways of contributing to pyElli. -The easiest is reporting issues or starting discussions. -If you want to dive deeper feel free to open a pull request or contact us -if you need some help. -We're eager to help you if you want to contribute code to pyElli even if you feel -you don't bring a lot of knowledge (yet). We are happy to assist. +You can contribute by reporting issues, starting discussions or open pull requests yourself +to contribute code directly. +In case you need help don't hesitate to ask for it. ## Reporting an Issue If you are encountering problems with pyElli or have a feature request -please open an issue at our [Github Issues Page](https://github.com/PyEllips/pyElli/issues). +open an issue at pyElli's [Github Issues Page](https://github.com/PyEllips/pyElli/issues). -Please try to provide a minimal example for reproducing the issue. -This makes it a lot easier for the developers to work on the problem. +Ideally, you'll provide a minimal example to reproduce the issue. +This will make it a lot easier to work on the problem. If you are not entirely sure whether the problem you're encountering is actually a bug -or if you want to discuss some feature ideas feel free to post on our [Github Discussion Page](https://github.com/orgs/PyEllips/discussions) +or if you want to discuss some feature ideas feel free to post on pyElli's [Github Discussion Page](https://github.com/orgs/PyEllips/discussions) ## Making a Pull Request +In case you want to contribute your own code to pyElli you can open a pull request. +To do this you need to fork pyElli first and create the pull request from your fork. +[Github's excellent documentation on the topic](https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/proposing-changes-to-your-work-with-pull-requests/creating-a-pull-request-from-a-fork) will be helpful if you need help to create a fork. + +### Setting up the repository and development environment + +First, clone the repo to start working on the code. +Replace `https://github.com/PyEllips/pyElli` with the url of your fork. + ```sh git clone --recurse-submodules https://github.com/PyEllips/pyElli cd pyElli ``` +In the next step we install the package in development mode. +We recommend using [uv](https://docs.astral.sh/uv/), which will manage a dedicated python +virtual environment for the project. +However, any virtual environment should work. + +=== "uv" + + ```sh + uv sync --extra dev --extra docs --extra fitting + ``` + === "pip" ```sh pip install -e '.[dev,docs,fitting] ``` +Now you're ready to make your changes to the code. + +### Testing + +Before opening a pull request please ensure that the tests pass and the code passes +the linting checks and is formatted properly. +We use the tool [ruff](https://docs.astral.sh/ruff/) to check linting and formatting +and [pytest](https://docs.pytest.org/en/stable/) for testing. + === "uv" ```sh - uv sync --extra dev --extra docs --extra fitting + uv run pytest + uv run ruff check . + uv run ruff format . + ``` + +=== "pip" + + ```sh + pytest + ruff check . + ruff format . ``` \ No newline at end of file diff --git a/docs/explanation/index.md b/docs/explanation/index.md index e69de29b..5d05ca7b 100644 --- a/docs/explanation/index.md +++ b/docs/explanation/index.md @@ -0,0 +1 @@ +# Learning \ No newline at end of file diff --git a/docs/howto/fitting_multiple_angles.md b/docs/howto/fitting_multiple_angles.md index a16fd3b4..def2e600 100644 --- a/docs/howto/fitting_multiple_angles.md +++ b/docs/howto/fitting_multiple_angles.md @@ -1,3 +1,3 @@ -# Custom Fitting +# Fitting Multiple Angles Custom fitting \ No newline at end of file diff --git a/docs/howto/mueller_matrix.md b/docs/howto/mueller_matrix.md index 722d5a94..e41c3bdb 100644 --- a/docs/howto/mueller_matrix.md +++ b/docs/howto/mueller_matrix.md @@ -1,3 +1,3 @@ -# Mueller Matrix +# Mueller Matrix Fitting Mueller matrix \ No newline at end of file diff --git a/docs/tutorial/working_with_dispersions.md b/docs/tutorial/working_with_dispersions.md index 95789de2..5d811f9a 100644 --- a/docs/tutorial/working_with_dispersions.md +++ b/docs/tutorial/working_with_dispersions.md @@ -1,6 +1,7 @@ -# Working with Dispersions +# Working with Dispersions Models -TODO: -- How to construct and add dispersions -- Formula dispersions -- How to load dispersions from rii \ No newline at end of file +## Adding Dispersions + +## Using a Formula Dispersion + +## Using Dispersions from refractiveindex.info \ No newline at end of file diff --git a/mkdocs.yml b/mkdocs.yml index 1db53a7c..bce12c7e 100644 --- a/mkdocs.yml +++ b/mkdocs.yml @@ -21,6 +21,7 @@ nav: - Tutorials: - tutorial/index.md - tutorial/simple_fit.md + - tutorial/working_with_dispersions.md - How-Tos: - howto/index.md - howto/fitting_multiple_angles.md From 9201373645bf9ae4ab73e0f5df0dd8e0f1c8987f Mon Sep 17 00:00:00 2001 From: domna Date: Sun, 2 Nov 2025 20:47:58 +0100 Subject: [PATCH 7/9] simple fit tutorial --- docs/index.md | 4 +- docs/tutorial/simple_fit.md | 107 ++++++++++++++++++++++++++++-------- 2 files changed, 87 insertions(+), 24 deletions(-) diff --git a/docs/index.md b/docs/index.md index aad06496..e32266bd 100644 --- a/docs/index.md +++ b/docs/index.md @@ -8,7 +8,7 @@ It serves as a system for the day to day ellipsometry task at hand and aims to m PyElli can be installed directly from [PyPI](https://pypi.org/project/pyElli/). Installation is as simple as -``` +```sh pip install pyelli ``` @@ -18,6 +18,6 @@ PyElli has the optional dependency `fitting` to install dependencies to use addi fitting capabilities and interactive widgets with jupyter notebooks. If you want to use those you can directly install the dependencies along with pyElli: -``` +```sh pip install 'pyelli[fitting]' ``` \ No newline at end of file diff --git a/docs/tutorial/simple_fit.md b/docs/tutorial/simple_fit.md index 91ba4ed6..50ed347a 100644 --- a/docs/tutorial/simple_fit.md +++ b/docs/tutorial/simple_fit.md @@ -1,5 +1,27 @@ # Performing a Simple Fit +In this tutorial we will perform a simple fit with pyElli. +We determine the thickness of a silicon dioxide layer on top of silicon. +This fit is often carried out as calibration and benchmark fit for ellipsometers and +is widely used for quality control of silicon wafers. +Here, we will use it to make our first steps with pyElli. + +Please make sure you meet the following prerequesits: + +- You are in a python environment with pyElli [installed](../index.md). +- We recommend to run the code in a jupyter or jupyter compatible environment. +However, you _can_ run this code in a repl or python file directly as well. +It will just not display the fitting widgets. +- An understanding of ellipsometry, in particular Psi/Delta measurement data. + +## Importing the packages + +First, we need to import pyElli itself. +Additionally, we import the `ParamsHist` class, which is a small wrapper around lmfit's `Parameter` class. +It stores a parameter history to retrieve previous fit configurations. +We'll also import the function `fit` from pyEllis fitting module. +This is a function decorator, which we will use to display our interactive fitting widget. + ```python import elli from elli.fitting import ParamsHist, fit @@ -7,46 +29,70 @@ from elli.fitting import ParamsHist, fit ## Reading data +We need some measurement data to perform a fit on and load an example [data set](https://github.com/PyEllips/pyElli/blob/master/examples/Basic%20Usage/SiO2onSi.ellips.nxs) of a psi delta measurement in the standardized [NeXus format](https://manual.nexusformat.org/classes/contributed_definitions/NXellipsometry.html#nxellipsometry) with pyElli's included `read_nexus_psi_delta` function. +Lets select a measurement angle of 70 degrees (`.loc[ANGLE]`) from the data and +restrict the wavelength range in between 210 nm and 800 nm (`.loc[210:800]`). +The restriction is necessary because we're using tabulated literature values for silicon, which are only provided in this wavelength range. + ```python ANGLE = 70 -psi_delta = elli.read_nexus_psi_delta("SiO2onSi.ellips.nxs").loc[ANGLE].loc[210:800] +psi_delta = ( + elli.read_nexus_psi_delta("SiO2onSi.ellips.nxs") + .loc[ANGLE] + .loc[210:800] +) ``` ## Setting parameters +To fit our data we need some actual fitting parameters. +We'll use our `ParamsHist` class which is a wrapper around lmfit's Parameters class. +The names of the paramters are freely choosable but we recommend to use some material and parameter name combination. +We'll use standard literature values for the silicon dioxide dispersion parameters $n_0$ (`SiO2_n0`) and $n_1$ (`SiO2_n1`). +For now, we won't vary these parameters in the fit, hence we set `vary=False` in the parameter definition. +Last but not least, we'll add a thickness parameter of the silicon dioxide layer with an initial guess of the materials thickness. +We set the `min` and `max` values to reasonable values and `vary=True` since we want to fit the thickness of the layer. + ```python params = ParamsHist() -params.add("SiO2_n0", value=1.452, min=-100, max=100, vary=False) -params.add("SiO2_n1", value=36.0, min=-40000, max=40000, vary=False) -params.add("SiO2_n2", value=0, min=-40000, max=40000, vary=False) -params.add("SiO2_k0", value=0, min=-100, max=100, vary=False) -params.add("SiO2_k1", value=0, min=-40000, max=40000, vary=False) -params.add("SiO2_k2", value=0, min=-40000, max=40000, vary=False) -params.add("SiO2_d", value=20, min=0, max=40000, vary=True) +params.add("SiO2_n0", value=1.452, vary=False) +params.add("SiO2_n1", value=36.0, vary=False) +params.add("SiO2_d", value=20, min=1, max=1000, vary=True) ``` +## Building the Fit Model + +We're ready to build a model! +First we need to construct our materials. +We have a silicon substrate which we load from the included [refractiveindex.info](https://refractiveindex.info) material database. +We are going to use the tabulated values from [Aspnes et al.](https://refractiveindex.info/?shelf=main&book=Si&page=Aspnes). + ```python rii_db = elli.db.RII() Si = rii_db.get_mat("Si", "Aspnes") ``` -## Building the Fitting Model +For the silicon dioxide layer we need a formula to insert our fitting values. +Here, we could also use tabulated values since we won't vary the parameters of the Cauchy model but in general it's a good practice to fit the material parameters, too. ```python SiO2_dispersion = elli.Cauchy( - params["SiO2_n0"], - params["SiO2_n1"], - params["SiO2_n2"], - params["SiO2_k0"], - params["SiO2_k1"], - params["SiO2_k2"], + params["SiO2_n0"], params["SiO2_n1"], 0, 0, 0, 0, ) ``` +The above snippet created a dispersion and now we need to generate a material from it. For anisotropic materials this can be done by calling `get_mat()`. + ```python SiO2 = SiO2_dispersion.get_mat() ``` +Now, we we put our materials together in a `Structure`. +It consists of a front-layer, which is air (`elli.AIR`) in this case (but will be air in most experiments you do) and a back layer which is silicon here. +In between is the most important part: the array of layers. +Here, we only have a single layer of silicon dioxide. +In the `Layer` specify the material and the thickness (`SiO2_d`). + ```python structure = elli.Structure( elli.AIR, @@ -55,22 +101,25 @@ structure = elli.Structure( ) ``` +In the last step we just need to evaluate our model for a set of wavelengths (`lbda`) at a given angle (`ANGLE`). +Additionally, we need the specify the solver (`elli.Solver2x2` in this case). + ```python structure.evaluate(lbda, ANGLE, solver=elli.Solver2x2) ``` ## Putting it all together +In this section we simply put the parts together: building the materials, the structure and evaluating it with the appropriate parameters. +We use the `@fit` decorator here, which takes the measurement data `psi_delta` and our fit parameter class `params`. +The `@fit` decorator generates a fit class to perform fitting on. +If this code snippet is executed in a jupyter environment it will display a fit widget in which you can alter the parameter and see the direct feedback as well as performing the fit. + ```python @fit(psi_delta, params) def model(lbda, params): SiO2 = elli.Cauchy( - params["SiO2_n0"], - params["SiO2_n1"], - params["SiO2_n2"], - params["SiO2_k0"], - params["SiO2_k1"], - params["SiO2_k2"], + params["SiO2_n0"], params["SiO2_n1"], 0, 0, 0, 0, ).get_mat() structure = elli.Structure( @@ -82,7 +131,21 @@ def model(lbda, params): return structure.evaluate(lbda, ANGLE, solver=elli.Solver2x2) ``` +By calling `fit()` we perform the fit and with `plot()` we can generate a plot of the resulting fit. +This part is optional if you used the fitting widget of the `@fit` decorator, since the widget will call these for you. ```python fit_stats = model.fit() model.plot() -``` \ No newline at end of file +``` + +Finally, we extract the actual thickness of the silicon dioxide layer by extracting the parameter from `fit_stats`. +``` +fit_stats.params["SiO2_d].value +``` + +It should return a value $\approx 2.066\,\text{nm}$. + +## Congrats 🎉 + +You have sucessfully performed a simple fit with pyElli. +Feel free to explore with this code, e.g., you may want to try varying the material parameters during the fit or using different angles from the measurement (50 or 60 degrees is also available). From 5dd63642d2a0f15ae70204aff8ccd4d42d3520c0 Mon Sep 17 00:00:00 2001 From: domna Date: Sat, 22 Nov 2025 23:16:30 +0100 Subject: [PATCH 8/9] Add mktestdocs --- docs/tutorial/simple_fit.md | 2 ++ pyproject.toml | 1 + tests/test_docs.py | 11 +++++++++++ uv.lock | 11 +++++++++++ 4 files changed, 25 insertions(+) create mode 100644 tests/test_docs.py diff --git a/docs/tutorial/simple_fit.md b/docs/tutorial/simple_fit.md index 50ed347a..ee87ac74 100644 --- a/docs/tutorial/simple_fit.md +++ b/docs/tutorial/simple_fit.md @@ -23,6 +23,7 @@ We'll also import the function `fit` from pyEllis fitting module. This is a function decorator, which we will use to display our interactive fitting widget. ```python +import numpy as np import elli from elli.fitting import ParamsHist, fit ``` @@ -105,6 +106,7 @@ In the last step we just need to evaluate our model for a set of wavelengths (`l Additionally, we need the specify the solver (`elli.Solver2x2` in this case). ```python +lbda = np.linspace(210, 800, 100) structure.evaluate(lbda, ANGLE, solver=elli.Solver2x2) ``` diff --git a/pyproject.toml b/pyproject.toml index 333017f8..e6aa620a 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -51,6 +51,7 @@ dev = [ "nbmake", "ruff==0.8.5", "pre-commit", + "mktestdocs>=0.2.5", ] docs = [ "mkdocs-material", diff --git a/tests/test_docs.py b/tests/test_docs.py new file mode 100644 index 00000000..b4696f43 --- /dev/null +++ b/tests/test_docs.py @@ -0,0 +1,11 @@ +import os +import pathlib + +from mktestdocs import check_md_file + + +def test_simple_fit(): + proj_dir = pathlib.Path(__file__).resolve().parent / ".." + os.chdir(proj_dir / "examples" / "Basic Usage") + fpath = proj_dir / "docs" / "tutorial" / "simple_fit.md" + check_md_file(fpath=fpath, memory=True) diff --git a/uv.lock b/uv.lock index f14cb56b..c45088d9 100644 --- a/uv.lock +++ b/uv.lock @@ -2164,6 +2164,15 @@ wheels = [ { url = "https://files.pythonhosted.org/packages/d5/8f/ce008599d9adebf33ed144e7736914385e8537f5fc686fdb7cceb8c22431/mkdocstrings_python-1.18.2-py3-none-any.whl", hash = "sha256:944fe6deb8f08f33fa936d538233c4036e9f53e840994f6146e8e94eb71b600d", size = 138215, upload-time = "2025-08-28T16:11:18.176Z" }, ] +[[package]] +name = "mktestdocs" +version = "0.2.5" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/fd/04/aced274f9ea76dfdb7a36c1b729863ebbf61e94b60a0d1eefa2556a61df5/mktestdocs-0.2.5.tar.gz", hash = "sha256:7935d4e665b34b690cdf14749abb842723652485f67af12dce51099bcb98e105", size = 10519, upload-time = "2025-07-25T12:39:29.073Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/4f/eb/3686be82dfeb12eb968f002254464e282722e4ac52c465c2998764583f34/mktestdocs-0.2.5-py3-none-any.whl", hash = "sha256:2b20d2387b2025597f3129773edef16d09b08b1b6d31da6cc51af5b693c10430", size = 9096, upload-time = "2025-07-25T12:39:27.985Z" }, +] + [[package]] name = "nbclient" version = "0.10.2" @@ -3031,6 +3040,7 @@ dependencies = [ [package.optional-dependencies] dev = [ + { name = "mktestdocs" }, { name = "nbmake" }, { name = "pre-commit" }, { name = "pytest" }, @@ -3073,6 +3083,7 @@ requires-dist = [ { name = "mkdocs-material", marker = "extra == 'docs'" }, { name = "mkdocs-plotly-plugin", marker = "extra == 'docs'" }, { name = "mkdocstrings", extras = ["python"], marker = "extra == 'docs'", specifier = ">=0.18" }, + { name = "mktestdocs", marker = "extra == 'dev'", specifier = ">=0.2.5" }, { name = "nbmake", marker = "extra == 'dev'" }, { name = "numpy", specifier = ">=1.20" }, { name = "numpy", marker = "python_full_version < '3.10'", specifier = "<2.0.0" }, From 059d8352b478ded1d6f71980696db21eb514aa47 Mon Sep 17 00:00:00 2001 From: domna Date: Sun, 23 Nov 2025 10:50:12 +0100 Subject: [PATCH 9/9] Add tutorials main page --- docs/tutorial/index.md | 9 ++++++++- mkdocs.yml | 4 ++++ 2 files changed, 12 insertions(+), 1 deletion(-) diff --git a/docs/tutorial/index.md b/docs/tutorial/index.md index de8ecfe6..6fadb300 100644 --- a/docs/tutorial/index.md +++ b/docs/tutorial/index.md @@ -1 +1,8 @@ -# Tutorials \ No newline at end of file +# Tutorials + +Our tutorials provide step-by-step guides for getting started with pyElli. +We tried to keep everything simple and unambigious, while still providing the necessary details for understanding how things work. + +A great first step is to follow the [performing a simple fit tutorial](simple_fit.md). +The [working with dispersion models](working_with_dispersions.md) covers goes through using pre-built dispersion models, +load literature values from [refractiveindex.info](https://refractiveindex.info) and explains how to built your own dispersion model. \ No newline at end of file diff --git a/mkdocs.yml b/mkdocs.yml index bce12c7e..253cda24 100644 --- a/mkdocs.yml +++ b/mkdocs.yml @@ -7,8 +7,12 @@ theme: name: material features: - navigation.instant + - navigation.instant.progress + - navigation.path - navigation.tabs - navigation.indexes + - navigation.footer + - navigation.top - content.code.copy palette: primary: cyan

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