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build info version 1 # This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done. -config: 713559574e2a71cb94ab036b601ffd09 +config: 608bac64e8b48a97b902e87aaf2e9228 tags: 645f666f9bcd5a90fca523b33c5a78b7 diff --git a/doc/_build/html/PTO_Junction_moore.html b/doc/_build/html/PTO_Junction_moore.html index 23acc1f..b9deba2 100644 --- a/doc/_build/html/PTO_Junction_moore.html +++ b/doc/_build/html/PTO_Junction_moore.html @@ -3,9 +3,9 @@ - + - + Analysis of PTO Domain Wall Junction — TEMUL Toolkit v0.1.2 documentation @@ -13,23 +13,28 @@ + + + + + + - @@ -51,7 +56,7 @@ - TEMUL Toolkit + TEMUL Toolkit @@ -148,6 +153,8 @@ + +

@@ -146,6 +150,8 @@ + +
-

- - © Copyright 2020, Eoghan O'Connell + © Copyright 2020, Eoghan O'Connell.

- Built with Sphinx using a + Built with Sphinx using a - theme + theme provided by Read the Docs. -
diff --git a/doc/_build/html/_sources/PTO_Junction_moore.rst.txt b/doc/_build/html/_sources/PTO_Junction_moore.rst.txt index f11ca86..3eae08c 100644 --- a/doc/_build/html/_sources/PTO_Junction_moore.rst.txt +++ b/doc/_build/html/_sources/PTO_Junction_moore.rst.txt @@ -97,7 +97,7 @@ Note that sometimes the 0 and 1 axes directions are constructed vice versa. >>> vmax = 30 >>> cmap = 'inferno' >>> theoretical_value = round(3.929/10, 3) # units of nm - >>> strain_map = tmlp.get_strain_map(sublattice1, zone_vector_index_B, + >>> strain_map = tml.get_strain_map(sublattice1, zone_vector_index_B, ... theoretical_value, sampling=sampling, ... units=units, vmin=vmin, vmax=vmax, cmap=cmap) diff --git a/doc/_build/html/_sources/PTO_supercrystal_hadjimichael.rst.txt b/doc/_build/html/_sources/PTO_supercrystal_hadjimichael.rst.txt index d250296..4e17bec 100644 --- a/doc/_build/html/_sources/PTO_supercrystal_hadjimichael.rst.txt +++ b/doc/_build/html/_sources/PTO_supercrystal_hadjimichael.rst.txt @@ -19,7 +19,7 @@ where you will find the python scripts and interactive python notebooks: The :python:`calculate_atom_plane_curvature` function has been adapted from the MATLAB script written by Dr. Marios Hadjimichael for the publication -M. Hadjimichael *et al*, `Metal-ferroelectric supercrystals with periodically +M. Hadjimichael, Y. Li *et al*, `Metal-ferroelectric supercrystals with periodically curved metallic layers, Nature Materials 2020 `_. This MATLAB script can also be found in the same folder. diff --git a/doc/_build/html/_sources/api_doc.rst.txt b/doc/_build/html/_sources/api_doc.rst.txt index 9df620b..d038844 100644 --- a/doc/_build/html/_sources/api_doc.rst.txt +++ b/doc/_build/html/_sources/api_doc.rst.txt @@ -9,6 +9,9 @@ Classes Model Refiner ============= +.. This won't work because PyPrismatic isn't dependency + This of course needs to be fixed, but the fix is to + overhaul the Model Refiner class .. autoclass:: temul.model_refiner.Model_Refiner :members: :undoc-members: @@ -17,9 +20,17 @@ Model Refiner Modules ------- -Polarisation -============ -.. automodule:: temul.polarisation +TopoTEM (Polarisation) +====================== +.. automodule:: temul.topotem.polarisation + :members: + :undoc-members: + +.. automodule:: temul.topotem.fft_mapping + :members: + :undoc-members: + +.. automodule:: temul.topotem.lattice_structure_tools :members: :undoc-members: diff --git a/doc/_build/html/_sources/news.rst.txt b/doc/_build/html/_sources/news.rst.txt index 58c76f4..b3af5ca 100644 --- a/doc/_build/html/_sources/news.rst.txt +++ b/doc/_build/html/_sources/news.rst.txt @@ -7,30 +7,52 @@ News ---- .. new version additions: - Corrected atom_deviation_from_straight_line_fit function. - Added documentation for how to find the polarisation vectors - Added "code_tutorials" ipynb examples - Corrected plot_polarisation_vectors vector quiver key - Created "polar_colorwheel" `plot_style` for plot_polarisation_vectors by - using a HSV to RGB 2D colorwheel and mapping the angles and magnitudes to - these values. Used code from PixStem for colorwheel visualisation. - Fixed norm and cmap scaling for the colorbar for "contour", "colorwheel" and - "colormap" plot_styles. Now they scale nicely and ticks can be input to all three. - Added invert_y_axis param for plot_polarisation_vectors function - plot_polarisation_vectors function now returns the Axes object - Added workflows webpage, .py and .ipynb files - Added vector correction functions - Added marios PTO paper links and notebook - Added Kalani PTO paper branch - - -**03/11/2020: Version 0.1.2 released** + + +16/02/2021: Version 0.1.4 released +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ +The polarisation, structure tools and fft mapping has now +been refactored into the topotem module. The temul +functionality remains the same i.e. ``import temul.api as tml`. + + +16/02/2021: Version 0.1.3 released +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +First articles uses and citations for the TEMUL Toolkit! +This version updated the Publication Examples folder with two newly published +articles. The folder contains interactive and raw code on how to reproduce the +data in the publications. Congrats to those involved! + * M. Hadjimichael, Y. Li *et al*, `Metal-ferroelectric supercrystals with periodically curved metallic layers, Nature Materials 2020 `_ + * K. Moore *et al* `Highly charged 180 degree head-to-head domain walls in lead titanate, Nature Communications Physics 2020 `_ +If you have a question or issue with using the publication examples, please make +an issue on `GitHub `_. + +Code changes in this version: + * The :python:`atom_deviation_from_straight_line_fit` function has been **corrected** and expanded. For a use case, see :ref:`Finding Polarisation Vectors ` + * Corrected the :python:`plot_polarisation_vectors` function's vector quiver key. + * Created the "polar_colorwheel" :python:`plot_style` for :python:`plot_polarisation_vectors` by using a HSV to RGB 2D colorwheel and mapping the angles and magnitudes to these values. Used code from `PixStem `_ for colorwheel visualisation. + * Fixed :python:`norm` and :python:`cmap` scaling for the colorbar for the "contour", "colorwheel" and "colormap" :python:`plot_styles`. Now each of these :python:`plot_styles` scale nicely, and colorbar :python:`ticks` may be specified. + * Added invert_y_axis param for plot_polarisation_vectors function, useful for testing if angles are displaying correctly. + * :python:`plot_polarisation_vectors` function now returns a Matplotlib :python:`Axes` object, which can be used to further edit the layout/presentation of the plotted map. + * Added functions to correct for possible off-zone tilt in the atomic columns. Use with caution. + +Documentation changes in this version: + * Added documentation for :ref:`how to find the polarisation vectors `. + * Added "code_tutorials" ipynb (interactive Jupyter Notebook) examples. See the `GitHub repository `_ for downloads. + * The :ref:`workflows ` folder in "code_tutorials/workflows" also contains starting workflows for analysis of different materials. See the `GitHub repository `_ for downloads. + * Added "publication_examples" tutorial ipynb (interactive Jupyter Notebook) examples. See the `GitHub repository `_ for downloads. + + +03/11/2020: Version 0.1.2 released +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ This version contains minor changes from the 0.1.1 release. It removes pyCifRW as a dependency. -**02/11/2020: Version 0.1.1 released** +02/11/2020: Version 0.1.1 released +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ This version contains many changes to the TEMUL Toolkit. diff --git a/doc/_build/html/_sources/polarisation_vectors_tutorial.rst.txt b/doc/_build/html/_sources/polarisation_vectors_tutorial.rst.txt index 9207e18..a071c4e 100644 --- a/doc/_build/html/_sources/polarisation_vectors_tutorial.rst.txt +++ b/doc/_build/html/_sources/polarisation_vectors_tutorial.rst.txt @@ -210,7 +210,7 @@ Prepare and Plot the dummy dataset .. code-block:: python - >>> from temul.polarisation import plot_polarisation_vectors + >>> import temul.api as tml >>> from temul.dummy_data import get_polarisation_dummy_dataset >>> atom_lattice = get_polarisation_dummy_dataset(image_noise=True) >>> sublatticeA = atom_lattice.sublattice_list[0] @@ -264,7 +264,7 @@ Vector magnitude plot with red arrows: .. code-block:: python - >>> plot_polarisation_vectors(x, y, u, v, image=image, + >>> tml.plot_polarisation_vectors(x, y, u, v, image=image, ... unit_vector=False, save=None, ... plot_style='vector', color='r', ... overlay=False, title='Vector Arrows', @@ -277,7 +277,7 @@ Vector magnitude plot with red arrows overlaid on the image, no title: .. code-block:: python - >>> plot_polarisation_vectors(x, y, u, v, image=image, + >>> tml.plot_polarisation_vectors(x, y, u, v, image=image, ... unit_vector=False, save=None, ... plot_style='vector', color='r', ... overlay=True, monitor_dpi=50) @@ -290,7 +290,7 @@ Vector magnitude plot with colormap viridis: .. code-block:: python - >>> plot_polarisation_vectors(x, y, u, v, image=image, + >>> tml.plot_polarisation_vectors(x, y, u, v, image=image, ... unit_vector=False, save=None, ... plot_style='colormap', monitor_dpi=50, ... overlay=False, cmap='viridis') @@ -304,7 +304,7 @@ Vector angle plot with colormap viridis (:python:`vector_rep='angle'`): .. code-block:: python - >>> plot_polarisation_vectors(x, y, u, v, image=image, + >>> tml.plot_polarisation_vectors(x, y, u, v, image=image, ... unit_vector=False, save=None, ... plot_style='colormap', monitor_dpi=50, ... overlay=False, cmap='cet_colorwheel', @@ -318,7 +318,7 @@ Colormap arrows with sampling specified in the parameters and with scalebar: .. code-block:: python - >>> plot_polarisation_vectors(x, y, u, v, image=sublatticeA.image, + >>> tml.plot_polarisation_vectors(x, y, u, v, image=sublatticeA.image, ... sampling=3.0321, units='pm', monitor_dpi=50, ... unit_vector=False, plot_style='colormap', ... overlay=True, save=None, cmap='viridis', @@ -332,7 +332,7 @@ Vector plot with colormap viridis and unit vectors: .. code-block:: python - >>> plot_polarisation_vectors(x, y, u, v, image=image, + >>> tml.plot_polarisation_vectors(x, y, u, v, image=image, ... unit_vector=True, save=None, monitor_dpi=50, ... plot_style='colormap', color='r', ... overlay=False, cmap='viridis') @@ -345,7 +345,7 @@ Change the vectors to unit vectors on a Matplotlib tricontourf map: .. code-block:: python - >>> plot_polarisation_vectors(x, y, u, v, image=image, unit_vector=True, + >>> tml.plot_polarisation_vectors(x, y, u, v, image=image, unit_vector=True, ... plot_style='contour', overlay=False, ... pivot='middle', save=None, monitor_dpi=50, ... color='darkgray', cmap='viridis') @@ -359,7 +359,7 @@ and vector arrows: .. code-block:: python - >>> plot_polarisation_vectors(x, y, u, v, image=image, + >>> tml.plot_polarisation_vectors(x, y, u, v, image=image, ... unit_vector=False, plot_style='contour', ... overlay=True, pivot='middle', save=None, ... color='red', cmap='cet_colorwheel', @@ -376,7 +376,7 @@ Plot a partly transparent angle tricontourf map with no vector arrows: .. code-block:: python - >>> plot_polarisation_vectors(x, y, u, v, image=image, remove_vectors=True, + >>> tml.plot_polarisation_vectors(x, y, u, v, image=image, remove_vectors=True, ... unit_vector=True, plot_style='contour', ... overlay=True, pivot='middle', save=None, ... cmap='cet_colorwheel', alpha=0.5, @@ -392,7 +392,7 @@ Plot a partly transparent angle tricontourf map with no vector arrows: .. code-block:: python >>> import colorcet as cc # can also just use cmap="cet_colorwheel" - >>> plot_polarisation_vectors(x, y, u, v, image=image, + >>> tml.plot_polarisation_vectors(x, y, u, v, image=image, ... unit_vector=True, plot_style="colorwheel", ... vector_rep="angle", ... overlay=False, cmap=cc.cm.colorwheel, @@ -406,7 +406,7 @@ Plot a partly transparent angle tricontourf map with no vector arrows: .. code-block:: python - >>> plot_polarisation_vectors(x, y, u, v, image=image, + >>> tml.plot_polarisation_vectors(x, y, u, v, image=image, ... plot_style="polar_colorwheel", ... unit_vector=False, overlay=False, ... save=None, monitor_dpi=50) @@ -419,7 +419,7 @@ Plot a partly transparent angle tricontourf map with no vector arrows: >>> U = np.reshape(np.cos(X), 1024) >>> V = np.reshape(np.sin(Y), 1024) >>> X, Y = np.reshape(X, 1024), np.reshape(Y, 1024) - >>> ax = plot_polarisation_vectors(X, Y, U, -V, image=image_temp, + >>> ax = tml.plot_polarisation_vectors(X, Y, U, -V, image=image_temp, ... plot_style="polar_colorwheel", ... overlay=False, invert_y_axis=False, ... save=None, monitor_dpi=None) @@ -439,7 +439,7 @@ matplotlib-scalebar for more custom features. >>> scbar_dict = {"dx": 3.0321, "units": "pm", "location": "lower left", ... "box_alpha":0.0, "color": "black", "scale_loc": "top"} - >>> plot_polarisation_vectors(x, y, u, v, image=sublatticeA.image, + >>> tml.plot_polarisation_vectors(x, y, u, v, image=sublatticeA.image, ... sampling=3.0321, units='pm', monitor_dpi=50, ... unit_vector=False, plot_style='colormap', ... overlay=False, save=None, cmap='viridis', @@ -453,14 +453,14 @@ Plot a tricontourf for quadrant visualisation using a custom matplotlib cmap: .. code-block:: python - >>> import temul.signal_plotting as tmlplot + >>> import temul.api as tml >>> from matplotlib.colors import from_levels_and_colors - >>> zest = tmlplot.hex_to_rgb(tmlplot.color_palettes('zesty')) + >>> zest = tml.hex_to_rgb(tml.color_palettes('zesty')) >>> zest.append(zest[0]) # make the -180 and 180 degree colour the same - >>> expanded_zest = tmlplot.expand_palette(zest, [1,2,2,2,1]) + >>> expanded_zest = tml.expand_palette(zest, [1,2,2,2,1]) >>> custom_cmap, _ = from_levels_and_colors( - ... levels=range(9), colors=tmlplot.rgb_to_dec(expanded_zest)) - >>> plot_polarisation_vectors(x, y, u, v, image=image, + ... levels=range(9), colors=tml.rgb_to_dec(expanded_zest)) + >>> tml.plot_polarisation_vectors(x, y, u, v, image=image, ... unit_vector=False, plot_style='contour', ... overlay=False, pivot='middle', save=None, ... cmap=custom_cmap, levels=9, monitor_dpi=50, diff --git a/doc/_build/html/_sources/using_temul.rst.txt b/doc/_build/html/_sources/using_temul.rst.txt index ff66f4b..c0873d9 100644 --- a/doc/_build/html/_sources/using_temul.rst.txt +++ b/doc/_build/html/_sources/using_temul.rst.txt @@ -13,3 +13,8 @@ Checkout the tutorials in the table of contents above or on the left of the page One can also view the extensive :ref:`documentation `, where each function is described and examples of their use given. +To use the vast majority of the temul functionality, +import it from the api module:: + + import temul.api as tml + diff --git a/doc/_build/html/_static/basic.css b/doc/_build/html/_static/basic.css index f013fe3..c2e4f88 100644 --- a/doc/_build/html/_static/basic.css +++ b/doc/_build/html/_static/basic.css @@ -4,7 +4,7 @@ * * Sphinx stylesheet -- basic theme. * - * :copyright: Copyright 2007-2020 by the Sphinx team, see AUTHORS. + * :copyright: Copyright 2007-2021 by the Sphinx team, see AUTHORS. * :license: BSD, see LICENSE for details. * */ @@ -130,7 +130,7 @@ ul.search li a { font-weight: bold; } -ul.search li div.context { +ul.search li p.context { color: #888; margin: 2px 0 0 30px; text-align: left; @@ -277,25 +277,25 @@ p.rubric { font-weight: bold; } -img.align-left, .figure.align-left, object.align-left { +img.align-left, figure.align-left, .figure.align-left, object.align-left { clear: left; float: left; margin-right: 1em; } -img.align-right, .figure.align-right, object.align-right { +img.align-right, figure.align-right, .figure.align-right, object.align-right { clear: right; float: right; margin-left: 1em; } -img.align-center, .figure.align-center, object.align-center { +img.align-center, figure.align-center, .figure.align-center, object.align-center { display: block; margin-left: auto; margin-right: auto; } -img.align-default, .figure.align-default { +img.align-default, figure.align-default, .figure.align-default { display: block; margin-left: auto; margin-right: auto; @@ -319,7 +319,8 @@ img.align-default, .figure.align-default { /* -- sidebars -------------------------------------------------------------- */ -div.sidebar { +div.sidebar, +aside.sidebar { margin: 0 0 0.5em 1em; border: 1px solid #ddb; padding: 7px; @@ -377,12 +378,14 @@ div.body p.centered { /* -- content of sidebars/topics/admonitions -------------------------------- */ div.sidebar > :last-child, +aside.sidebar > :last-child, div.topic > :last-child, div.admonition > :last-child { margin-bottom: 0; } div.sidebar::after, +aside.sidebar::after, div.topic::after, div.admonition::after, blockquote::after { @@ -455,20 +458,22 @@ td > :last-child { /* -- figures --------------------------------------------------------------- */ -div.figure { +div.figure, figure { margin: 0.5em; padding: 0.5em; } -div.figure p.caption { +div.figure p.caption, figcaption { padding: 0.3em; } -div.figure p.caption span.caption-number { +div.figure p.caption span.caption-number, +figcaption span.caption-number { font-style: italic; } -div.figure p.caption span.caption-text { +div.figure p.caption span.caption-text, +figcaption span.caption-text { } /* -- field list styles ----------------------------------------------------- */ @@ -503,6 +508,63 @@ table.hlist td { vertical-align: top; } +/* -- object description styles --------------------------------------------- */ + +.sig { + font-family: 'Consolas', 'Menlo', 'DejaVu Sans Mono', 'Bitstream Vera Sans Mono', monospace; +} + +.sig-name, code.descname { + background-color: transparent; + font-weight: bold; +} + +.sig-name { + font-size: 1.1em; +} + +code.descname { + font-size: 1.2em; +} + +.sig-prename, code.descclassname { + background-color: transparent; +} + +.optional { + font-size: 1.3em; +} + +.sig-paren { + font-size: larger; +} + +.sig-param.n { + font-style: italic; +} + +/* C++ specific styling */ + +.sig-inline.c-texpr, +.sig-inline.cpp-texpr { + font-family: unset; +} + +.sig.c .k, .sig.c .kt, +.sig.cpp .k, .sig.cpp .kt { + color: #0033B3; +} + +.sig.c .m, +.sig.cpp .m { + color: #1750EB; +} + +.sig.c .s, .sig.c .sc, +.sig.cpp .s, .sig.cpp .sc { + color: #067D17; +} + /* -- other body styles ----------------------------------------------------- */ @@ -629,14 +691,6 @@ dl.glossary dt { font-size: 1.1em; } -.optional { - font-size: 1.3em; -} - -.sig-paren { - font-size: larger; -} - .versionmodified { font-style: italic; } @@ -764,8 +818,13 @@ div.code-block-caption code { } table.highlighttable td.linenos, +span.linenos, div.doctest > div.highlight span.gp { /* gp: Generic.Prompt */ - user-select: none; + user-select: none; + -webkit-user-select: text; /* Safari fallback only */ + -webkit-user-select: none; /* Chrome/Safari */ + -moz-user-select: none; /* Firefox */ + -ms-user-select: none; /* IE10+ */ } div.code-block-caption span.caption-number { @@ -780,16 +839,6 @@ div.literal-block-wrapper { margin: 1em 0; } -code.descname { - background-color: transparent; - font-weight: bold; - font-size: 1.2em; -} - -code.descclassname { - background-color: transparent; -} - code.xref, a code { background-color: transparent; font-weight: bold; diff --git a/doc/_build/html/_static/doctools.js b/doc/_build/html/_static/doctools.js index daccd20..61ac9d2 100644 --- a/doc/_build/html/_static/doctools.js +++ b/doc/_build/html/_static/doctools.js @@ -4,7 +4,7 @@ * * Sphinx JavaScript utilities for all documentation. * - * :copyright: Copyright 2007-2020 by the Sphinx team, see AUTHORS. + * :copyright: Copyright 2007-2021 by the Sphinx team, see AUTHORS. * :license: BSD, see LICENSE for details. * */ @@ -29,9 +29,14 @@ if (!window.console || !console.firebug) { /** * small helper function to urldecode strings + * + * See https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/decodeURIComponent#Decoding_query_parameters_from_a_URL */ jQuery.urldecode = function(x) { - return decodeURIComponent(x).replace(/\+/g, ' '); + if (!x) { + return x + } + return decodeURIComponent(x.replace(/\+/g, ' ')); }; /** @@ -285,9 +290,10 @@ var Documentation = { initOnKeyListeners: function() { $(document).keydown(function(event) { var activeElementType = document.activeElement.tagName; - // don't navigate when in search box or textarea + // don't navigate when in search box, textarea, dropdown or button if (activeElementType !== 'TEXTAREA' && activeElementType !== 'INPUT' && activeElementType !== 'SELECT' - && !event.altKey && !event.ctrlKey && !event.metaKey && !event.shiftKey) { + && activeElementType !== 'BUTTON' && !event.altKey && !event.ctrlKey && !event.metaKey + && !event.shiftKey) { switch (event.keyCode) { 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b/doc/_build/html/_static/language_data.js index 86a6422..70c1c29 100644 --- a/doc/_build/html/_static/language_data.js +++ b/doc/_build/html/_static/language_data.js @@ -5,7 +5,7 @@ * This script contains the language-specific data used by searchtools.js, * namely the list of stopwords, stemmer, scorer and splitter. * - * :copyright: Copyright 2007-2020 by the Sphinx team, see AUTHORS. + * :copyright: Copyright 2007-2021 by the Sphinx team, see AUTHORS. * :license: BSD, see LICENSE for details. * */ @@ -13,7 +13,8 @@ var stopwords = ["a","and","are","as","at","be","but","by","for","if","in","into","is","it","near","no","not","of","on","or","such","that","the","their","then","there","these","they","this","to","was","will","with"]; -/* Non-minified version JS is _stemmer.js if file is provided */ +/* Non-minified version is copied as a separate JS file, is available */ + /** * Porter Stemmer */ @@ -199,7 +200,6 @@ var Stemmer = function() { - var splitChars = (function() { var result = {}; var singles = [96, 180, 187, 191, 215, 247, 749, 885, 903, 907, 909, 930, 1014, 1648, diff --git a/doc/_build/html/_static/pygments.css b/doc/_build/html/_static/pygments.css index 1da7f1c..ff153c5 100644 --- a/doc/_build/html/_static/pygments.css +++ b/doc/_build/html/_static/pygments.css @@ -1,5 +1,10 @@ +pre { line-height: 125%; } +td.linenos .normal { color: inherit; background-color: transparent; padding-left: 5px; padding-right: 5px; } +span.linenos { color: inherit; background-color: transparent; padding-left: 5px; padding-right: 5px; } +td.linenos .special { color: #000000; background-color: #ffffc0; padding-left: 5px; padding-right: 5px; } +span.linenos.special { color: #000000; background-color: #ffffc0; padding-left: 5px; padding-right: 5px; } .highlight .hll { background-color: #ffffcc } -.highlight { background: #f8f8f8; } +.highlight { background: #f8f8f8; } .highlight .c { color: #408080; font-style: italic } /* Comment */ .highlight .err { border: 1px solid #FF0000 } /* Error */ .highlight .k { color: #008000; font-weight: bold } /* Keyword */ diff --git a/doc/_build/html/_static/searchtools.js b/doc/_build/html/_static/searchtools.js index 970d0d9..e09f926 100644 --- a/doc/_build/html/_static/searchtools.js +++ b/doc/_build/html/_static/searchtools.js @@ -4,7 +4,7 @@ * * Sphinx JavaScript utilities for the full-text search. * - * :copyright: Copyright 2007-2020 by the Sphinx team, see AUTHORS. + * :copyright: Copyright 2007-2021 by the Sphinx team, see AUTHORS. * :license: BSD, see LICENSE for details. * */ @@ -59,10 +59,10 @@ var Search = { _pulse_status : -1, htmlToText : function(htmlString) { - var htmlElement = document.createElement('span'); - htmlElement.innerHTML = htmlString; - $(htmlElement).find('.headerlink').remove(); - docContent = $(htmlElement).find('[role=main]')[0]; + var virtualDocument = document.implementation.createHTMLDocument('virtual'); + var htmlElement = $(htmlString, virtualDocument); + htmlElement.find('.headerlink').remove(); + docContent = htmlElement.find('[role=main]')[0]; if(docContent === undefined) { console.warn("Content block not found. Sphinx search tries to obtain it " + "via '[role=main]'. Could you check your theme or template."); @@ -248,7 +248,7 @@ var Search = { // results left, load the summary and display it if (results.length) { var item = results.pop(); - var listItem = $('

  • '); + var listItem = $('
  • '); var requestUrl = ""; var linkUrl = ""; if (DOCUMENTATION_OPTIONS.BUILDER === 'dirhtml') { @@ -273,9 +273,9 @@ var Search = { if (item[3]) { listItem.append($(' (' + item[3] + ')')); Search.output.append(listItem); - listItem.slideDown(5, function() { + setTimeout(function() { displayNextItem(); - }); + }, 5); } else if (DOCUMENTATION_OPTIONS.HAS_SOURCE) { $.ajax({url: requestUrl, dataType: "text", @@ -285,16 +285,16 @@ var Search = { listItem.append(Search.makeSearchSummary(data, searchterms, hlterms)); } Search.output.append(listItem); - listItem.slideDown(5, function() { + setTimeout(function() { displayNextItem(); - }); + }, 5); }}); } else { // no source available, just display title Search.output.append(listItem); - listItem.slideDown(5, function() { + setTimeout(function() { displayNextItem(); - }); + }, 5); } } // search finished, update title and status message @@ -379,6 +379,13 @@ var Search = { return results; }, + /** + * See https://developer.mozilla.org/en-US/docs/Web/JavaScript/Guide/Regular_Expressions + */ + escapeRegExp : function(string) { + return string.replace(/[.*+\-?^${}()|[\]\\]/g, '\\$&'); // $& means the whole matched string + }, + /** * search for full-text terms in the index */ @@ -402,13 +409,14 @@ var Search = { ]; // add support for partial matches if (word.length > 2) { + var word_regex = this.escapeRegExp(word); for (var w in terms) { - if (w.match(word) && !terms[word]) { + if (w.match(word_regex) && !terms[word]) { _o.push({files: terms[w], score: Scorer.partialTerm}) } } for (var w in titleterms) { - if (w.match(word) && !titleterms[word]) { + if (w.match(word_regex) && !titleterms[word]) { _o.push({files: titleterms[w], score: Scorer.partialTitle}) } } @@ -501,7 +509,7 @@ var Search = { var excerpt = ((start > 0) ? '...' : '') + $.trim(text.substr(start, 240)) + ((start + 240 - text.length) ? '...' : ''); - var rv = $('
    ').text(excerpt); + var rv = $('

    ').text(excerpt); $.each(hlwords, function() { rv = rv.highlightText(this, 'highlighted'); }); diff --git a/doc/_build/html/_static/underscore-1.13.1.js b/doc/_build/html/_static/underscore-1.13.1.js new file mode 100644 index 0000000..ffd77af --- /dev/null +++ b/doc/_build/html/_static/underscore-1.13.1.js @@ -0,0 +1,2042 @@ +(function (global, factory) { + typeof exports === 'object' && typeof module !== 'undefined' ? module.exports = factory() : + typeof define === 'function' && define.amd ? define('underscore', factory) : + (global = typeof globalThis !== 'undefined' ? globalThis : global || self, (function () { + var current = global._; + var exports = global._ = factory(); + exports.noConflict = function () { global._ = current; return exports; }; + }())); +}(this, (function () { + // Underscore.js 1.13.1 + // https://underscorejs.org + // (c) 2009-2021 Jeremy Ashkenas, Julian Gonggrijp, and DocumentCloud and Investigative Reporters & Editors + // Underscore may be freely distributed under the MIT license. + + // Current version. + var VERSION = '1.13.1'; + + // Establish the root object, `window` (`self`) in the browser, `global` + // on the server, or `this` in some virtual machines. We use `self` + // instead of `window` for `WebWorker` support. + var root = typeof self == 'object' && self.self === self && self || + typeof global == 'object' && global.global === global && global || + Function('return this')() || + {}; + + // Save bytes in the minified (but not gzipped) version: + var ArrayProto = Array.prototype, ObjProto = Object.prototype; + var SymbolProto = typeof Symbol !== 'undefined' ? Symbol.prototype : null; + + // Create quick reference variables for speed access to core prototypes. + var push = ArrayProto.push, + slice = ArrayProto.slice, + toString = ObjProto.toString, + hasOwnProperty = ObjProto.hasOwnProperty; + + // Modern feature detection. + var supportsArrayBuffer = typeof ArrayBuffer !== 'undefined', + supportsDataView = typeof DataView !== 'undefined'; + + // All **ECMAScript 5+** native function implementations that we hope to use + // are declared here. + var nativeIsArray = Array.isArray, + nativeKeys = Object.keys, + nativeCreate = Object.create, + nativeIsView = supportsArrayBuffer && ArrayBuffer.isView; + + // Create references to these builtin functions because we override them. + var _isNaN = isNaN, + _isFinite = isFinite; + + // Keys in IE < 9 that won't be iterated by `for key in ...` and thus missed. + var hasEnumBug = !{toString: null}.propertyIsEnumerable('toString'); + var nonEnumerableProps = ['valueOf', 'isPrototypeOf', 'toString', + 'propertyIsEnumerable', 'hasOwnProperty', 'toLocaleString']; + + // The largest integer that can be represented exactly. + var MAX_ARRAY_INDEX = Math.pow(2, 53) - 1; + + // Some functions take a variable number of arguments, or a few expected + // arguments at the beginning and then a variable number of values to operate + // on. This helper accumulates all remaining arguments past the function’s + // argument length (or an explicit `startIndex`), into an array that becomes + // the last argument. Similar to ES6’s "rest parameter". + function restArguments(func, startIndex) { + startIndex = startIndex == null ? func.length - 1 : +startIndex; + return function() { + var length = Math.max(arguments.length - startIndex, 0), + rest = Array(length), + index = 0; + for (; index < length; index++) { + rest[index] = arguments[index + startIndex]; + } + switch (startIndex) { + case 0: return func.call(this, rest); + case 1: return func.call(this, arguments[0], rest); + case 2: return func.call(this, arguments[0], arguments[1], rest); + } + var args = Array(startIndex + 1); + for (index = 0; index < startIndex; index++) { + args[index] = arguments[index]; + } + args[startIndex] = rest; + return func.apply(this, args); + }; + } + + // Is a given variable an object? + function isObject(obj) { + var type = typeof obj; + return type === 'function' || type === 'object' && !!obj; + } + + // Is a given value equal to null? + function isNull(obj) { + return obj === null; + } + + // Is a given variable undefined? + function isUndefined(obj) { + return obj === void 0; + } + + // Is a given value a boolean? + function isBoolean(obj) { + return obj === true || obj === false || toString.call(obj) === '[object Boolean]'; + } + + // Is a given value a DOM element? + function isElement(obj) { + return !!(obj && obj.nodeType === 1); + } + + // Internal function for creating a `toString`-based type tester. + function tagTester(name) { + var tag = '[object ' + name + ']'; + return function(obj) { + return toString.call(obj) === tag; + }; + } + + var isString = tagTester('String'); + + var isNumber = tagTester('Number'); + + var isDate = tagTester('Date'); + + var isRegExp = tagTester('RegExp'); + + var isError = tagTester('Error'); + + var isSymbol = tagTester('Symbol'); + + var isArrayBuffer = tagTester('ArrayBuffer'); + + var isFunction = tagTester('Function'); + + // Optimize `isFunction` if appropriate. Work around some `typeof` bugs in old + // v8, IE 11 (#1621), Safari 8 (#1929), and PhantomJS (#2236). + var nodelist = root.document && root.document.childNodes; + if (typeof /./ != 'function' && typeof Int8Array != 'object' && typeof nodelist != 'function') { + isFunction = function(obj) { + return typeof obj == 'function' || false; + }; + } + + var isFunction$1 = isFunction; + + var hasObjectTag = tagTester('Object'); + + // In IE 10 - Edge 13, `DataView` has string tag `'[object Object]'`. + // In IE 11, the most common among them, this problem also applies to + // `Map`, `WeakMap` and `Set`. + var hasStringTagBug = ( + supportsDataView && hasObjectTag(new DataView(new ArrayBuffer(8))) + ), + isIE11 = (typeof Map !== 'undefined' && hasObjectTag(new Map)); + + var isDataView = tagTester('DataView'); + + // In IE 10 - Edge 13, we need a different heuristic + // to determine whether an object is a `DataView`. + function ie10IsDataView(obj) { + return obj != null && isFunction$1(obj.getInt8) && isArrayBuffer(obj.buffer); + } + + var isDataView$1 = (hasStringTagBug ? ie10IsDataView : isDataView); + + // Is a given value an array? + // Delegates to ECMA5's native `Array.isArray`. + var isArray = nativeIsArray || tagTester('Array'); + + // Internal function to check whether `key` is an own property name of `obj`. + function has$1(obj, key) { + return obj != null && hasOwnProperty.call(obj, key); + } + + var isArguments = tagTester('Arguments'); + + // Define a fallback version of the method in browsers (ahem, IE < 9), where + // there isn't any inspectable "Arguments" type. + (function() { + if (!isArguments(arguments)) { + isArguments = function(obj) { + return has$1(obj, 'callee'); + }; + } + }()); + + var isArguments$1 = isArguments; + + // Is a given object a finite number? + function isFinite$1(obj) { + return !isSymbol(obj) && _isFinite(obj) && !isNaN(parseFloat(obj)); + } + + // Is the given value `NaN`? + function isNaN$1(obj) { + return isNumber(obj) && _isNaN(obj); + } + + // Predicate-generating function. Often useful outside of Underscore. + function constant(value) { + return function() { + return value; + }; + } + + // Common internal logic for `isArrayLike` and `isBufferLike`. + function createSizePropertyCheck(getSizeProperty) { + return function(collection) { + var sizeProperty = getSizeProperty(collection); + return typeof sizeProperty == 'number' && sizeProperty >= 0 && sizeProperty <= MAX_ARRAY_INDEX; + } + } + + // Internal helper to generate a function to obtain property `key` from `obj`. + function shallowProperty(key) { + return function(obj) { + return obj == null ? void 0 : obj[key]; + }; + } + + // Internal helper to obtain the `byteLength` property of an object. + var getByteLength = shallowProperty('byteLength'); + + // Internal helper to determine whether we should spend extensive checks against + // `ArrayBuffer` et al. + var isBufferLike = createSizePropertyCheck(getByteLength); + + // Is a given value a typed array? + var typedArrayPattern = /\[object ((I|Ui)nt(8|16|32)|Float(32|64)|Uint8Clamped|Big(I|Ui)nt64)Array\]/; + function isTypedArray(obj) { + // `ArrayBuffer.isView` is the most future-proof, so use it when available. + // Otherwise, fall back on the above regular expression. + return nativeIsView ? (nativeIsView(obj) && !isDataView$1(obj)) : + isBufferLike(obj) && typedArrayPattern.test(toString.call(obj)); + } + + var isTypedArray$1 = supportsArrayBuffer ? isTypedArray : constant(false); + + // Internal helper to obtain the `length` property of an object. + var getLength = shallowProperty('length'); + + // Internal helper to create a simple lookup structure. + // `collectNonEnumProps` used to depend on `_.contains`, but this led to + // circular imports. `emulatedSet` is a one-off solution that only works for + // arrays of strings. + function emulatedSet(keys) { + var hash = {}; + for (var l = keys.length, i = 0; i < l; ++i) hash[keys[i]] = true; + return { + contains: function(key) { return hash[key]; }, + push: function(key) { + hash[key] = true; + return keys.push(key); + } + }; + } + + // Internal helper. Checks `keys` for the presence of keys in IE < 9 that won't + // be iterated by `for key in ...` and thus missed. Extends `keys` in place if + // needed. + function collectNonEnumProps(obj, keys) { + keys = emulatedSet(keys); + var nonEnumIdx = nonEnumerableProps.length; + var constructor = obj.constructor; + var proto = isFunction$1(constructor) && constructor.prototype || ObjProto; + + // Constructor is a special case. + var prop = 'constructor'; + if (has$1(obj, prop) && !keys.contains(prop)) keys.push(prop); + + while (nonEnumIdx--) { + prop = nonEnumerableProps[nonEnumIdx]; + if (prop in obj && obj[prop] !== proto[prop] && !keys.contains(prop)) { + keys.push(prop); + } + } + } + + // Retrieve the names of an object's own properties. + // Delegates to **ECMAScript 5**'s native `Object.keys`. + function keys(obj) { + if (!isObject(obj)) return []; + if (nativeKeys) return nativeKeys(obj); + var keys = []; + for (var key in obj) if (has$1(obj, key)) keys.push(key); + // Ahem, IE < 9. + if (hasEnumBug) collectNonEnumProps(obj, keys); + return keys; + } + + // Is a given array, string, or object empty? + // An "empty" object has no enumerable own-properties. + function isEmpty(obj) { + if (obj == null) return true; + // Skip the more expensive `toString`-based type checks if `obj` has no + // `.length`. + var length = getLength(obj); + if (typeof length == 'number' && ( + isArray(obj) || isString(obj) || isArguments$1(obj) + )) return length === 0; + return getLength(keys(obj)) === 0; + } + + // Returns whether an object has a given set of `key:value` pairs. + function isMatch(object, attrs) { + var _keys = keys(attrs), length = _keys.length; + if (object == null) return !length; + var obj = Object(object); + for (var i = 0; i < length; i++) { + var key = _keys[i]; + if (attrs[key] !== obj[key] || !(key in obj)) return false; + } + return true; + } + + // If Underscore is called as a function, it returns a wrapped object that can + // be used OO-style. This wrapper holds altered versions of all functions added + // through `_.mixin`. Wrapped objects may be chained. + function _$1(obj) { + if (obj instanceof _$1) return obj; + if (!(this instanceof _$1)) return new _$1(obj); + this._wrapped = obj; + } + + _$1.VERSION = VERSION; + + // Extracts the result from a wrapped and chained object. + _$1.prototype.value = function() { + return this._wrapped; + }; + + // Provide unwrapping proxies for some methods used in engine operations + // such as arithmetic and JSON stringification. + _$1.prototype.valueOf = _$1.prototype.toJSON = _$1.prototype.value; + + _$1.prototype.toString = function() { + return String(this._wrapped); + }; + + // Internal function to wrap or shallow-copy an ArrayBuffer, + // typed array or DataView to a new view, reusing the buffer. + function toBufferView(bufferSource) { + return new Uint8Array( + bufferSource.buffer || bufferSource, + bufferSource.byteOffset || 0, + getByteLength(bufferSource) + ); + } + + // We use this string twice, so give it a name for minification. + var tagDataView = '[object DataView]'; + + // Internal recursive comparison function for `_.isEqual`. + function eq(a, b, aStack, bStack) { + // Identical objects are equal. `0 === -0`, but they aren't identical. + // See the [Harmony `egal` proposal](https://wiki.ecmascript.org/doku.php?id=harmony:egal). + if (a === b) return a !== 0 || 1 / a === 1 / b; + // `null` or `undefined` only equal to itself (strict comparison). + if (a == null || b == null) return false; + // `NaN`s are equivalent, but non-reflexive. + if (a !== a) return b !== b; + // Exhaust primitive checks + var type = typeof a; + if (type !== 'function' && type !== 'object' && typeof b != 'object') return false; + return deepEq(a, b, aStack, bStack); + } + + // Internal recursive comparison function for `_.isEqual`. + function deepEq(a, b, aStack, bStack) { + // Unwrap any wrapped objects. + if (a instanceof _$1) a = a._wrapped; + if (b instanceof _$1) b = b._wrapped; + // Compare `[[Class]]` names. + var className = toString.call(a); + if (className !== toString.call(b)) return false; + // Work around a bug in IE 10 - Edge 13. + if (hasStringTagBug && className == '[object Object]' && isDataView$1(a)) { + if (!isDataView$1(b)) return false; + className = tagDataView; + } + switch (className) { + // These types are compared by value. + case '[object RegExp]': + // RegExps are coerced to strings for comparison (Note: '' + /a/i === '/a/i') + case '[object String]': + // Primitives and their corresponding object wrappers are equivalent; thus, `"5"` is + // equivalent to `new String("5")`. + return '' + a === '' + b; + case '[object Number]': + // `NaN`s are equivalent, but non-reflexive. + // Object(NaN) is equivalent to NaN. + if (+a !== +a) return +b !== +b; + // An `egal` comparison is performed for other numeric values. + return +a === 0 ? 1 / +a === 1 / b : +a === +b; + case '[object Date]': + case '[object Boolean]': + // Coerce dates and booleans to numeric primitive values. Dates are compared by their + // millisecond representations. Note that invalid dates with millisecond representations + // of `NaN` are not equivalent. + return +a === +b; + case '[object Symbol]': + return SymbolProto.valueOf.call(a) === SymbolProto.valueOf.call(b); + case '[object ArrayBuffer]': + case tagDataView: + // Coerce to typed array so we can fall through. + return deepEq(toBufferView(a), toBufferView(b), aStack, bStack); + } + + var areArrays = className === '[object Array]'; + if (!areArrays && isTypedArray$1(a)) { + var byteLength = getByteLength(a); + if (byteLength !== getByteLength(b)) return false; + if (a.buffer === b.buffer && a.byteOffset === b.byteOffset) return true; + areArrays = true; + } + if (!areArrays) { + if (typeof a != 'object' || typeof b != 'object') return false; + + // Objects with different constructors are not equivalent, but `Object`s or `Array`s + // from different frames are. + var aCtor = a.constructor, bCtor = b.constructor; + if (aCtor !== bCtor && !(isFunction$1(aCtor) && aCtor instanceof aCtor && + isFunction$1(bCtor) && bCtor instanceof bCtor) + && ('constructor' in a && 'constructor' in b)) { + return false; + } + } + // Assume equality for cyclic structures. The algorithm for detecting cyclic + // structures is adapted from ES 5.1 section 15.12.3, abstract operation `JO`. + + // Initializing stack of traversed objects. + // It's done here since we only need them for objects and arrays comparison. + aStack = aStack || []; + bStack = bStack || []; + var length = aStack.length; + while (length--) { + // Linear search. Performance is inversely proportional to the number of + // unique nested structures. + if (aStack[length] === a) return bStack[length] === b; + } + + // Add the first object to the stack of traversed objects. + aStack.push(a); + bStack.push(b); + + // Recursively compare objects and arrays. + if (areArrays) { + // Compare array lengths to determine if a deep comparison is necessary. + length = a.length; + if (length !== b.length) return false; + // Deep compare the contents, ignoring non-numeric properties. + while (length--) { + if (!eq(a[length], b[length], aStack, bStack)) return false; + } + } else { + // Deep compare objects. + var _keys = keys(a), key; + length = _keys.length; + // Ensure that both objects contain the same number of properties before comparing deep equality. + if (keys(b).length !== length) return false; + while (length--) { + // Deep compare each member + key = _keys[length]; + if (!(has$1(b, key) && eq(a[key], b[key], aStack, bStack))) return false; + } + } + // Remove the first object from the stack of traversed objects. + aStack.pop(); + bStack.pop(); + return true; + } + + // Perform a deep comparison to check if two objects are equal. + function isEqual(a, b) { + return eq(a, b); + } + + // Retrieve all the enumerable property names of an object. + function allKeys(obj) { + if (!isObject(obj)) return []; + var keys = []; + for (var key in obj) keys.push(key); + // Ahem, IE < 9. + if (hasEnumBug) collectNonEnumProps(obj, keys); + return keys; + } + + // Since the regular `Object.prototype.toString` type tests don't work for + // some types in IE 11, we use a fingerprinting heuristic instead, based + // on the methods. It's not great, but it's the best we got. + // The fingerprint method lists are defined below. + function ie11fingerprint(methods) { + var length = getLength(methods); + return function(obj) { + if (obj == null) return false; + // `Map`, `WeakMap` and `Set` have no enumerable keys. + var keys = allKeys(obj); + if (getLength(keys)) return false; + for (var i = 0; i < length; i++) { + if (!isFunction$1(obj[methods[i]])) return false; + } + // If we are testing against `WeakMap`, we need to ensure that + // `obj` doesn't have a `forEach` method in order to distinguish + // it from a regular `Map`. + return methods !== weakMapMethods || !isFunction$1(obj[forEachName]); + }; + } + + // In the interest of compact minification, we write + // each string in the fingerprints only once. + var forEachName = 'forEach', + hasName = 'has', + commonInit = ['clear', 'delete'], + mapTail = ['get', hasName, 'set']; + + // `Map`, `WeakMap` and `Set` each have slightly different + // combinations of the above sublists. + var mapMethods = commonInit.concat(forEachName, mapTail), + weakMapMethods = commonInit.concat(mapTail), + setMethods = ['add'].concat(commonInit, forEachName, hasName); + + var isMap = isIE11 ? ie11fingerprint(mapMethods) : tagTester('Map'); + + var isWeakMap = isIE11 ? ie11fingerprint(weakMapMethods) : tagTester('WeakMap'); + + var isSet = isIE11 ? ie11fingerprint(setMethods) : tagTester('Set'); + + var isWeakSet = tagTester('WeakSet'); + + // Retrieve the values of an object's properties. + function values(obj) { + var _keys = keys(obj); + var length = _keys.length; + var values = Array(length); + for (var i = 0; i < length; i++) { + values[i] = obj[_keys[i]]; + } + return values; + } + + // Convert an object into a list of `[key, value]` pairs. + // The opposite of `_.object` with one argument. + function pairs(obj) { + var _keys = keys(obj); + var length = _keys.length; + var pairs = Array(length); + for (var i = 0; i < length; i++) { + pairs[i] = [_keys[i], obj[_keys[i]]]; + } + return pairs; + } + + // Invert the keys and values of an object. The values must be serializable. + function invert(obj) { + var result = {}; + var _keys = keys(obj); + for (var i = 0, length = _keys.length; i < length; i++) { + result[obj[_keys[i]]] = _keys[i]; + } + return result; + } + + // Return a sorted list of the function names available on the object. + function functions(obj) { + var names = []; + for (var key in obj) { + if (isFunction$1(obj[key])) names.push(key); + } + return names.sort(); + } + + // An internal function for creating assigner functions. + function createAssigner(keysFunc, defaults) { + return function(obj) { + var length = arguments.length; + if (defaults) obj = Object(obj); + if (length < 2 || obj == null) return obj; + for (var index = 1; index < length; index++) { + var source = arguments[index], + keys = keysFunc(source), + l = keys.length; + for (var i = 0; i < l; i++) { + var key = keys[i]; + if (!defaults || obj[key] === void 0) obj[key] = source[key]; + } + } + return obj; + }; + } + + // Extend a given object with all the properties in passed-in object(s). + var extend = createAssigner(allKeys); + + // Assigns a given object with all the own properties in the passed-in + // object(s). + // (https://developer.mozilla.org/docs/Web/JavaScript/Reference/Global_Objects/Object/assign) + var extendOwn = createAssigner(keys); + + // Fill in a given object with default properties. + var defaults = createAssigner(allKeys, true); + + // Create a naked function reference for surrogate-prototype-swapping. + function ctor() { + return function(){}; + } + + // An internal function for creating a new object that inherits from another. + function baseCreate(prototype) { + if (!isObject(prototype)) return {}; + if (nativeCreate) return nativeCreate(prototype); + var Ctor = ctor(); + Ctor.prototype = prototype; + var result = new Ctor; + Ctor.prototype = null; + return result; + } + + // Creates an object that inherits from the given prototype object. + // If additional properties are provided then they will be added to the + // created object. + function create(prototype, props) { + var result = baseCreate(prototype); + if (props) extendOwn(result, props); + return result; + } + + // Create a (shallow-cloned) duplicate of an object. + function clone(obj) { + if (!isObject(obj)) return obj; + return isArray(obj) ? obj.slice() : extend({}, obj); + } + + // Invokes `interceptor` with the `obj` and then returns `obj`. + // The primary purpose of this method is to "tap into" a method chain, in + // order to perform operations on intermediate results within the chain. + function tap(obj, interceptor) { + interceptor(obj); + return obj; + } + + // Normalize a (deep) property `path` to array. + // Like `_.iteratee`, this function can be customized. + function toPath$1(path) { + return isArray(path) ? path : [path]; + } + _$1.toPath = toPath$1; + + // Internal wrapper for `_.toPath` to enable minification. + // Similar to `cb` for `_.iteratee`. + function toPath(path) { + return _$1.toPath(path); + } + + // Internal function to obtain a nested property in `obj` along `path`. + function deepGet(obj, path) { + var length = path.length; + for (var i = 0; i < length; i++) { + if (obj == null) return void 0; + obj = obj[path[i]]; + } + return length ? obj : void 0; + } + + // Get the value of the (deep) property on `path` from `object`. + // If any property in `path` does not exist or if the value is + // `undefined`, return `defaultValue` instead. + // The `path` is normalized through `_.toPath`. + function get(object, path, defaultValue) { + var value = deepGet(object, toPath(path)); + return isUndefined(value) ? defaultValue : value; + } + + // Shortcut function for checking if an object has a given property directly on + // itself (in other words, not on a prototype). Unlike the internal `has` + // function, this public version can also traverse nested properties. + function has(obj, path) { + path = toPath(path); + var length = path.length; + for (var i = 0; i < length; i++) { + var key = path[i]; + if (!has$1(obj, key)) return false; + obj = obj[key]; + } + return !!length; + } + + // Keep the identity function around for default iteratees. + function identity(value) { + return value; + } + + // Returns a predicate for checking whether an object has a given set of + // `key:value` pairs. + function matcher(attrs) { + attrs = extendOwn({}, attrs); + return function(obj) { + return isMatch(obj, attrs); + }; + } + + // Creates a function that, when passed an object, will traverse that object’s + // properties down the given `path`, specified as an array of keys or indices. + function property(path) { + path = toPath(path); + return function(obj) { + return deepGet(obj, path); + }; + } + + // Internal function that returns an efficient (for current engines) version + // of the passed-in callback, to be repeatedly applied in other Underscore + // functions. + function optimizeCb(func, context, argCount) { + if (context === void 0) return func; + switch (argCount == null ? 3 : argCount) { + case 1: return function(value) { + return func.call(context, value); + }; + // The 2-argument case is omitted because we’re not using it. + case 3: return function(value, index, collection) { + return func.call(context, value, index, collection); + }; + case 4: return function(accumulator, value, index, collection) { + return func.call(context, accumulator, value, index, collection); + }; + } + return function() { + return func.apply(context, arguments); + }; + } + + // An internal function to generate callbacks that can be applied to each + // element in a collection, returning the desired result β€” either `_.identity`, + // an arbitrary callback, a property matcher, or a property accessor. + function baseIteratee(value, context, argCount) { + if (value == null) return identity; + if (isFunction$1(value)) return optimizeCb(value, context, argCount); + if (isObject(value) && !isArray(value)) return matcher(value); + return property(value); + } + + // External wrapper for our callback generator. Users may customize + // `_.iteratee` if they want additional predicate/iteratee shorthand styles. + // This abstraction hides the internal-only `argCount` argument. + function iteratee(value, context) { + return baseIteratee(value, context, Infinity); + } + _$1.iteratee = iteratee; + + // The function we call internally to generate a callback. It invokes + // `_.iteratee` if overridden, otherwise `baseIteratee`. + function cb(value, context, argCount) { + if (_$1.iteratee !== iteratee) return _$1.iteratee(value, context); + return baseIteratee(value, context, argCount); + } + + // Returns the results of applying the `iteratee` to each element of `obj`. + // In contrast to `_.map` it returns an object. + function mapObject(obj, iteratee, context) { + iteratee = cb(iteratee, context); + var _keys = keys(obj), + length = _keys.length, + results = {}; + for (var index = 0; index < length; index++) { + var currentKey = _keys[index]; + results[currentKey] = iteratee(obj[currentKey], currentKey, obj); + } + return results; + } + + // Predicate-generating function. Often useful outside of Underscore. + function noop(){} + + // Generates a function for a given object that returns a given property. + function propertyOf(obj) { + if (obj == null) return noop; + return function(path) { + return get(obj, path); + }; + } + + // Run a function **n** times. + function times(n, iteratee, context) { + var accum = Array(Math.max(0, n)); + iteratee = optimizeCb(iteratee, context, 1); + for (var i = 0; i < n; i++) accum[i] = iteratee(i); + return accum; + } + + // Return a random integer between `min` and `max` (inclusive). + function random(min, max) { + if (max == null) { + max = min; + min = 0; + } + return min + Math.floor(Math.random() * (max - min + 1)); + } + + // A (possibly faster) way to get the current timestamp as an integer. + var now = Date.now || function() { + return new Date().getTime(); + }; + + // Internal helper to generate functions for escaping and unescaping strings + // to/from HTML interpolation. + function createEscaper(map) { + var escaper = function(match) { + return map[match]; + }; + // Regexes for identifying a key that needs to be escaped. + var source = '(?:' + keys(map).join('|') + ')'; + var testRegexp = RegExp(source); + var replaceRegexp = RegExp(source, 'g'); + return function(string) { + string = string == null ? '' : '' + string; + return testRegexp.test(string) ? string.replace(replaceRegexp, escaper) : string; + }; + } + + // Internal list of HTML entities for escaping. + var escapeMap = { + '&': '&', + '<': '<', + '>': '>', + '"': '"', + "'": ''', + '`': '`' + }; + + // Function for escaping strings to HTML interpolation. + var _escape = createEscaper(escapeMap); + + // Internal list of HTML entities for unescaping. + var unescapeMap = invert(escapeMap); + + // Function for unescaping strings from HTML interpolation. + var _unescape = createEscaper(unescapeMap); + + // By default, Underscore uses ERB-style template delimiters. Change the + // following template settings to use alternative delimiters. + var templateSettings = _$1.templateSettings = { + evaluate: /<%([\s\S]+?)%>/g, + interpolate: /<%=([\s\S]+?)%>/g, + escape: /<%-([\s\S]+?)%>/g + }; + + // When customizing `_.templateSettings`, if you don't want to define an + // interpolation, evaluation or escaping regex, we need one that is + // guaranteed not to match. + var noMatch = /(.)^/; + + // Certain characters need to be escaped so that they can be put into a + // string literal. + var escapes = { + "'": "'", + '\\': '\\', + '\r': 'r', + '\n': 'n', + '\u2028': 'u2028', + '\u2029': 'u2029' + }; + + var escapeRegExp = /\\|'|\r|\n|\u2028|\u2029/g; + + function escapeChar(match) { + return '\\' + escapes[match]; + } + + // In order to prevent third-party code injection through + // `_.templateSettings.variable`, we test it against the following regular + // expression. It is intentionally a bit more liberal than just matching valid + // identifiers, but still prevents possible loopholes through defaults or + // destructuring assignment. + var bareIdentifier = /^\s*(\w|\$)+\s*$/; + + // JavaScript micro-templating, similar to John Resig's implementation. + // Underscore templating handles arbitrary delimiters, preserves whitespace, + // and correctly escapes quotes within interpolated code. + // NB: `oldSettings` only exists for backwards compatibility. + function template(text, settings, oldSettings) { + if (!settings && oldSettings) settings = oldSettings; + settings = defaults({}, settings, _$1.templateSettings); + + // Combine delimiters into one regular expression via alternation. + var matcher = RegExp([ + (settings.escape || noMatch).source, + (settings.interpolate || noMatch).source, + (settings.evaluate || noMatch).source + ].join('|') + '|$', 'g'); + + // Compile the template source, escaping string literals appropriately. + var index = 0; + var source = "__p+='"; + text.replace(matcher, function(match, escape, interpolate, evaluate, offset) { + source += text.slice(index, offset).replace(escapeRegExp, escapeChar); + index = offset + match.length; + + if (escape) { + source += "'+\n((__t=(" + escape + "))==null?'':_.escape(__t))+\n'"; + } else if (interpolate) { + source += "'+\n((__t=(" + interpolate + "))==null?'':__t)+\n'"; + } else if (evaluate) { + source += "';\n" + evaluate + "\n__p+='"; + } + + // Adobe VMs need the match returned to produce the correct offset. + return match; + }); + source += "';\n"; + + var argument = settings.variable; + if (argument) { + // Insure against third-party code injection. (CVE-2021-23358) + if (!bareIdentifier.test(argument)) throw new Error( + 'variable is not a bare identifier: ' + argument + ); + } else { + // If a variable is not specified, place data values in local scope. + source = 'with(obj||{}){\n' + source + '}\n'; + argument = 'obj'; + } + + source = "var __t,__p='',__j=Array.prototype.join," + + "print=function(){__p+=__j.call(arguments,'');};\n" + + source + 'return __p;\n'; + + var render; + try { + render = new Function(argument, '_', source); + } catch (e) { + e.source = source; + throw e; + } + + var template = function(data) { + return render.call(this, data, _$1); + }; + + // Provide the compiled source as a convenience for precompilation. + template.source = 'function(' + argument + '){\n' + source + '}'; + + return template; + } + + // Traverses the children of `obj` along `path`. If a child is a function, it + // is invoked with its parent as context. Returns the value of the final + // child, or `fallback` if any child is undefined. + function result(obj, path, fallback) { + path = toPath(path); + var length = path.length; + if (!length) { + return isFunction$1(fallback) ? fallback.call(obj) : fallback; + } + for (var i = 0; i < length; i++) { + var prop = obj == null ? void 0 : obj[path[i]]; + if (prop === void 0) { + prop = fallback; + i = length; // Ensure we don't continue iterating. + } + obj = isFunction$1(prop) ? prop.call(obj) : prop; + } + return obj; + } + + // Generate a unique integer id (unique within the entire client session). + // Useful for temporary DOM ids. + var idCounter = 0; + function uniqueId(prefix) { + var id = ++idCounter + ''; + return prefix ? prefix + id : id; + } + + // Start chaining a wrapped Underscore object. + function chain(obj) { + var instance = _$1(obj); + instance._chain = true; + return instance; + } + + // Internal function to execute `sourceFunc` bound to `context` with optional + // `args`. Determines whether to execute a function as a constructor or as a + // normal function. + function executeBound(sourceFunc, boundFunc, context, callingContext, args) { + if (!(callingContext instanceof boundFunc)) return sourceFunc.apply(context, args); + var self = baseCreate(sourceFunc.prototype); + var result = sourceFunc.apply(self, args); + if (isObject(result)) return result; + return self; + } + + // Partially apply a function by creating a version that has had some of its + // arguments pre-filled, without changing its dynamic `this` context. `_` acts + // as a placeholder by default, allowing any combination of arguments to be + // pre-filled. Set `_.partial.placeholder` for a custom placeholder argument. + var partial = restArguments(function(func, boundArgs) { + var placeholder = partial.placeholder; + var bound = function() { + var position = 0, length = boundArgs.length; + var args = Array(length); + for (var i = 0; i < length; i++) { + args[i] = boundArgs[i] === placeholder ? arguments[position++] : boundArgs[i]; + } + while (position < arguments.length) args.push(arguments[position++]); + return executeBound(func, bound, this, this, args); + }; + return bound; + }); + + partial.placeholder = _$1; + + // Create a function bound to a given object (assigning `this`, and arguments, + // optionally). + var bind = restArguments(function(func, context, args) { + if (!isFunction$1(func)) throw new TypeError('Bind must be called on a function'); + var bound = restArguments(function(callArgs) { + return executeBound(func, bound, context, this, args.concat(callArgs)); + }); + return bound; + }); + + // Internal helper for collection methods to determine whether a collection + // should be iterated as an array or as an object. + // Related: https://people.mozilla.org/~jorendorff/es6-draft.html#sec-tolength + // Avoids a very nasty iOS 8 JIT bug on ARM-64. #2094 + var isArrayLike = createSizePropertyCheck(getLength); + + // Internal implementation of a recursive `flatten` function. + function flatten$1(input, depth, strict, output) { + output = output || []; + if (!depth && depth !== 0) { + depth = Infinity; + } else if (depth <= 0) { + return output.concat(input); + } + var idx = output.length; + for (var i = 0, length = getLength(input); i < length; i++) { + var value = input[i]; + if (isArrayLike(value) && (isArray(value) || isArguments$1(value))) { + // Flatten current level of array or arguments object. + if (depth > 1) { + flatten$1(value, depth - 1, strict, output); + idx = output.length; + } else { + var j = 0, len = value.length; + while (j < len) output[idx++] = value[j++]; + } + } else if (!strict) { + output[idx++] = value; + } + } + return output; + } + + // Bind a number of an object's methods to that object. Remaining arguments + // are the method names to be bound. Useful for ensuring that all callbacks + // defined on an object belong to it. + var bindAll = restArguments(function(obj, keys) { + keys = flatten$1(keys, false, false); + var index = keys.length; + if (index < 1) throw new Error('bindAll must be passed function names'); + while (index--) { + var key = keys[index]; + obj[key] = bind(obj[key], obj); + } + return obj; + }); + + // Memoize an expensive function by storing its results. + function memoize(func, hasher) { + var memoize = function(key) { + var cache = memoize.cache; + var address = '' + (hasher ? hasher.apply(this, arguments) : key); + if (!has$1(cache, address)) cache[address] = func.apply(this, arguments); + return cache[address]; + }; + memoize.cache = {}; + return memoize; + } + + // Delays a function for the given number of milliseconds, and then calls + // it with the arguments supplied. + var delay = restArguments(function(func, wait, args) { + return setTimeout(function() { + return func.apply(null, args); + }, wait); + }); + + // Defers a function, scheduling it to run after the current call stack has + // cleared. + var defer = partial(delay, _$1, 1); + + // Returns a function, that, when invoked, will only be triggered at most once + // during a given window of time. Normally, the throttled function will run + // as much as it can, without ever going more than once per `wait` duration; + // but if you'd like to disable the execution on the leading edge, pass + // `{leading: false}`. To disable execution on the trailing edge, ditto. + function throttle(func, wait, options) { + var timeout, context, args, result; + var previous = 0; + if (!options) options = {}; + + var later = function() { + previous = options.leading === false ? 0 : now(); + timeout = null; + result = func.apply(context, args); + if (!timeout) context = args = null; + }; + + var throttled = function() { + var _now = now(); + if (!previous && options.leading === false) previous = _now; + var remaining = wait - (_now - previous); + context = this; + args = arguments; + if (remaining <= 0 || remaining > wait) { + if (timeout) { + clearTimeout(timeout); + timeout = null; + } + previous = _now; + result = func.apply(context, args); + if (!timeout) context = args = null; + } else if (!timeout && options.trailing !== false) { + timeout = setTimeout(later, remaining); + } + return result; + }; + + throttled.cancel = function() { + clearTimeout(timeout); + previous = 0; + timeout = context = args = null; + }; + + return throttled; + } + + // When a sequence of calls of the returned function ends, the argument + // function is triggered. The end of a sequence is defined by the `wait` + // parameter. If `immediate` is passed, the argument function will be + // triggered at the beginning of the sequence instead of at the end. + function debounce(func, wait, immediate) { + var timeout, previous, args, result, context; + + var later = function() { + var passed = now() - previous; + if (wait > passed) { + timeout = setTimeout(later, wait - passed); + } else { + timeout = null; + if (!immediate) result = func.apply(context, args); + // This check is needed because `func` can recursively invoke `debounced`. + if (!timeout) args = context = null; + } + }; + + var debounced = restArguments(function(_args) { + context = this; + args = _args; + previous = now(); + if (!timeout) { + timeout = setTimeout(later, wait); + if (immediate) result = func.apply(context, args); + } + return result; + }); + + debounced.cancel = function() { + clearTimeout(timeout); + timeout = args = context = null; + }; + + return debounced; + } + + // Returns the first function passed as an argument to the second, + // allowing you to adjust arguments, run code before and after, and + // conditionally execute the original function. + function wrap(func, wrapper) { + return partial(wrapper, func); + } + + // Returns a negated version of the passed-in predicate. + function negate(predicate) { + return function() { + return !predicate.apply(this, arguments); + }; + } + + // Returns a function that is the composition of a list of functions, each + // consuming the return value of the function that follows. + function compose() { + var args = arguments; + var start = args.length - 1; + return function() { + var i = start; + var result = args[start].apply(this, arguments); + while (i--) result = args[i].call(this, result); + return result; + }; + } + + // Returns a function that will only be executed on and after the Nth call. + function after(times, func) { + return function() { + if (--times < 1) { + return func.apply(this, arguments); + } + }; + } + + // Returns a function that will only be executed up to (but not including) the + // Nth call. + function before(times, func) { + var memo; + return function() { + if (--times > 0) { + memo = func.apply(this, arguments); + } + if (times <= 1) func = null; + return memo; + }; + } + + // Returns a function that will be executed at most one time, no matter how + // often you call it. Useful for lazy initialization. + var once = partial(before, 2); + + // Returns the first key on an object that passes a truth test. + function findKey(obj, predicate, context) { + predicate = cb(predicate, context); + var _keys = keys(obj), key; + for (var i = 0, length = _keys.length; i < length; i++) { + key = _keys[i]; + if (predicate(obj[key], key, obj)) return key; + } + } + + // Internal function to generate `_.findIndex` and `_.findLastIndex`. + function createPredicateIndexFinder(dir) { + return function(array, predicate, context) { + predicate = cb(predicate, context); + var length = getLength(array); + var index = dir > 0 ? 0 : length - 1; + for (; index >= 0 && index < length; index += dir) { + if (predicate(array[index], index, array)) return index; + } + return -1; + }; + } + + // Returns the first index on an array-like that passes a truth test. + var findIndex = createPredicateIndexFinder(1); + + // Returns the last index on an array-like that passes a truth test. + var findLastIndex = createPredicateIndexFinder(-1); + + // Use a comparator function to figure out the smallest index at which + // an object should be inserted so as to maintain order. Uses binary search. + function sortedIndex(array, obj, iteratee, context) { + iteratee = cb(iteratee, context, 1); + var value = iteratee(obj); + var low = 0, high = getLength(array); + while (low < high) { + var mid = Math.floor((low + high) / 2); + if (iteratee(array[mid]) < value) low = mid + 1; else high = mid; + } + return low; + } + + // Internal function to generate the `_.indexOf` and `_.lastIndexOf` functions. + function createIndexFinder(dir, predicateFind, sortedIndex) { + return function(array, item, idx) { + var i = 0, length = getLength(array); + if (typeof idx == 'number') { + if (dir > 0) { + i = idx >= 0 ? idx : Math.max(idx + length, i); + } else { + length = idx >= 0 ? Math.min(idx + 1, length) : idx + length + 1; + } + } else if (sortedIndex && idx && length) { + idx = sortedIndex(array, item); + return array[idx] === item ? idx : -1; + } + if (item !== item) { + idx = predicateFind(slice.call(array, i, length), isNaN$1); + return idx >= 0 ? idx + i : -1; + } + for (idx = dir > 0 ? i : length - 1; idx >= 0 && idx < length; idx += dir) { + if (array[idx] === item) return idx; + } + return -1; + }; + } + + // Return the position of the first occurrence of an item in an array, + // or -1 if the item is not included in the array. + // If the array is large and already in sort order, pass `true` + // for **isSorted** to use binary search. + var indexOf = createIndexFinder(1, findIndex, sortedIndex); + + // Return the position of the last occurrence of an item in an array, + // or -1 if the item is not included in the array. + var lastIndexOf = createIndexFinder(-1, findLastIndex); + + // Return the first value which passes a truth test. + function find(obj, predicate, context) { + var keyFinder = isArrayLike(obj) ? findIndex : findKey; + var key = keyFinder(obj, predicate, context); + if (key !== void 0 && key !== -1) return obj[key]; + } + + // Convenience version of a common use case of `_.find`: getting the first + // object containing specific `key:value` pairs. + function findWhere(obj, attrs) { + return find(obj, matcher(attrs)); + } + + // The cornerstone for collection functions, an `each` + // implementation, aka `forEach`. + // Handles raw objects in addition to array-likes. Treats all + // sparse array-likes as if they were dense. + function each(obj, iteratee, context) { + iteratee = optimizeCb(iteratee, context); + var i, length; + if (isArrayLike(obj)) { + for (i = 0, length = obj.length; i < length; i++) { + iteratee(obj[i], i, obj); + } + } else { + var _keys = keys(obj); + for (i = 0, length = _keys.length; i < length; i++) { + iteratee(obj[_keys[i]], _keys[i], obj); + } + } + return obj; + } + + // Return the results of applying the iteratee to each element. + function map(obj, iteratee, context) { + iteratee = cb(iteratee, context); + var _keys = !isArrayLike(obj) && keys(obj), + length = (_keys || obj).length, + results = Array(length); + for (var index = 0; index < length; index++) { + var currentKey = _keys ? _keys[index] : index; + results[index] = iteratee(obj[currentKey], currentKey, obj); + } + return results; + } + + // Internal helper to create a reducing function, iterating left or right. + function createReduce(dir) { + // Wrap code that reassigns argument variables in a separate function than + // the one that accesses `arguments.length` to avoid a perf hit. (#1991) + var reducer = function(obj, iteratee, memo, initial) { + var _keys = !isArrayLike(obj) && keys(obj), + length = (_keys || obj).length, + index = dir > 0 ? 0 : length - 1; + if (!initial) { + memo = obj[_keys ? _keys[index] : index]; + index += dir; + } + for (; index >= 0 && index < length; index += dir) { + var currentKey = _keys ? _keys[index] : index; + memo = iteratee(memo, obj[currentKey], currentKey, obj); + } + return memo; + }; + + return function(obj, iteratee, memo, context) { + var initial = arguments.length >= 3; + return reducer(obj, optimizeCb(iteratee, context, 4), memo, initial); + }; + } + + // **Reduce** builds up a single result from a list of values, aka `inject`, + // or `foldl`. + var reduce = createReduce(1); + + // The right-associative version of reduce, also known as `foldr`. + var reduceRight = createReduce(-1); + + // Return all the elements that pass a truth test. + function filter(obj, predicate, context) { + var results = []; + predicate = cb(predicate, context); + each(obj, function(value, index, list) { + if (predicate(value, index, list)) results.push(value); + }); + return results; + } + + // Return all the elements for which a truth test fails. + function reject(obj, predicate, context) { + return filter(obj, negate(cb(predicate)), context); + } + + // Determine whether all of the elements pass a truth test. + function every(obj, predicate, context) { + predicate = cb(predicate, context); + var _keys = !isArrayLike(obj) && keys(obj), + length = (_keys || obj).length; + for (var index = 0; index < length; index++) { + var currentKey = _keys ? _keys[index] : index; + if (!predicate(obj[currentKey], currentKey, obj)) return false; + } + return true; + } + + // Determine if at least one element in the object passes a truth test. + function some(obj, predicate, context) { + predicate = cb(predicate, context); + var _keys = !isArrayLike(obj) && keys(obj), + length = (_keys || obj).length; + for (var index = 0; index < length; index++) { + var currentKey = _keys ? _keys[index] : index; + if (predicate(obj[currentKey], currentKey, obj)) return true; + } + return false; + } + + // Determine if the array or object contains a given item (using `===`). + function contains(obj, item, fromIndex, guard) { + if (!isArrayLike(obj)) obj = values(obj); + if (typeof fromIndex != 'number' || guard) fromIndex = 0; + return indexOf(obj, item, fromIndex) >= 0; + } + + // Invoke a method (with arguments) on every item in a collection. + var invoke = restArguments(function(obj, path, args) { + var contextPath, func; + if (isFunction$1(path)) { + func = path; + } else { + path = toPath(path); + contextPath = path.slice(0, -1); + path = path[path.length - 1]; + } + return map(obj, function(context) { + var method = func; + if (!method) { + if (contextPath && contextPath.length) { + context = deepGet(context, contextPath); + } + if (context == null) return void 0; + method = context[path]; + } + return method == null ? method : method.apply(context, args); + }); + }); + + // Convenience version of a common use case of `_.map`: fetching a property. + function pluck(obj, key) { + return map(obj, property(key)); + } + + // Convenience version of a common use case of `_.filter`: selecting only + // objects containing specific `key:value` pairs. + function where(obj, attrs) { + return filter(obj, matcher(attrs)); + } + + // Return the maximum element (or element-based computation). + function max(obj, iteratee, context) { + var result = -Infinity, lastComputed = -Infinity, + value, computed; + if (iteratee == null || typeof iteratee == 'number' && typeof obj[0] != 'object' && obj != null) { + obj = isArrayLike(obj) ? obj : values(obj); + for (var i = 0, length = obj.length; i < length; i++) { + value = obj[i]; + if (value != null && value > result) { + result = value; + } + } + } else { + iteratee = cb(iteratee, context); + each(obj, function(v, index, list) { + computed = iteratee(v, index, list); + if (computed > lastComputed || computed === -Infinity && result === -Infinity) { + result = v; + lastComputed = computed; + } + }); + } + return result; + } + + // Return the minimum element (or element-based computation). + function min(obj, iteratee, context) { + var result = Infinity, lastComputed = Infinity, + value, computed; + if (iteratee == null || typeof iteratee == 'number' && typeof obj[0] != 'object' && obj != null) { + obj = isArrayLike(obj) ? obj : values(obj); + for (var i = 0, length = obj.length; i < length; i++) { + value = obj[i]; + if (value != null && value < result) { + result = value; + } + } + } else { + iteratee = cb(iteratee, context); + each(obj, function(v, index, list) { + computed = iteratee(v, index, list); + if (computed < lastComputed || computed === Infinity && result === Infinity) { + result = v; + lastComputed = computed; + } + }); + } + return result; + } + + // Sample **n** random values from a collection using the modern version of the + // [Fisher-Yates shuffle](https://en.wikipedia.org/wiki/Fisher–Yates_shuffle). + // If **n** is not specified, returns a single random element. + // The internal `guard` argument allows it to work with `_.map`. + function sample(obj, n, guard) { + if (n == null || guard) { + if (!isArrayLike(obj)) obj = values(obj); + return obj[random(obj.length - 1)]; + } + var sample = isArrayLike(obj) ? clone(obj) : values(obj); + var length = getLength(sample); + n = Math.max(Math.min(n, length), 0); + var last = length - 1; + for (var index = 0; index < n; index++) { + var rand = random(index, last); + var temp = sample[index]; + sample[index] = sample[rand]; + sample[rand] = temp; + } + return sample.slice(0, n); + } + + // Shuffle a collection. + function shuffle(obj) { + return sample(obj, Infinity); + } + + // Sort the object's values by a criterion produced by an iteratee. + function sortBy(obj, iteratee, context) { + var index = 0; + iteratee = cb(iteratee, context); + return pluck(map(obj, function(value, key, list) { + return { + value: value, + index: index++, + criteria: iteratee(value, key, list) + }; + }).sort(function(left, right) { + var a = left.criteria; + var b = right.criteria; + if (a !== b) { + if (a > b || a === void 0) return 1; + if (a < b || b === void 0) return -1; + } + return left.index - right.index; + }), 'value'); + } + + // An internal function used for aggregate "group by" operations. + function group(behavior, partition) { + return function(obj, iteratee, context) { + var result = partition ? [[], []] : {}; + iteratee = cb(iteratee, context); + each(obj, function(value, index) { + var key = iteratee(value, index, obj); + behavior(result, value, key); + }); + return result; + }; + } + + // Groups the object's values by a criterion. Pass either a string attribute + // to group by, or a function that returns the criterion. + var groupBy = group(function(result, value, key) { + if (has$1(result, key)) result[key].push(value); else result[key] = [value]; + }); + + // Indexes the object's values by a criterion, similar to `_.groupBy`, but for + // when you know that your index values will be unique. + var indexBy = group(function(result, value, key) { + result[key] = value; + }); + + // Counts instances of an object that group by a certain criterion. Pass + // either a string attribute to count by, or a function that returns the + // criterion. + var countBy = group(function(result, value, key) { + if (has$1(result, key)) result[key]++; else result[key] = 1; + }); + + // Split a collection into two arrays: one whose elements all pass the given + // truth test, and one whose elements all do not pass the truth test. + var partition = group(function(result, value, pass) { + result[pass ? 0 : 1].push(value); + }, true); + + // Safely create a real, live array from anything iterable. + var reStrSymbol = /[^\ud800-\udfff]|[\ud800-\udbff][\udc00-\udfff]|[\ud800-\udfff]/g; + function toArray(obj) { + if (!obj) return []; + if (isArray(obj)) return slice.call(obj); + if (isString(obj)) { + // Keep surrogate pair characters together. + return obj.match(reStrSymbol); + } + if (isArrayLike(obj)) return map(obj, identity); + return values(obj); + } + + // Return the number of elements in a collection. + function size(obj) { + if (obj == null) return 0; + return isArrayLike(obj) ? obj.length : keys(obj).length; + } + + // Internal `_.pick` helper function to determine whether `key` is an enumerable + // property name of `obj`. + function keyInObj(value, key, obj) { + return key in obj; + } + + // Return a copy of the object only containing the allowed properties. + var pick = restArguments(function(obj, keys) { + var result = {}, iteratee = keys[0]; + if (obj == null) return result; + if (isFunction$1(iteratee)) { + if (keys.length > 1) iteratee = optimizeCb(iteratee, keys[1]); + keys = allKeys(obj); + } else { + iteratee = keyInObj; + keys = flatten$1(keys, false, false); + obj = Object(obj); + } + for (var i = 0, length = keys.length; i < length; i++) { + var key = keys[i]; + var value = obj[key]; + if (iteratee(value, key, obj)) result[key] = value; + } + return result; + }); + + // Return a copy of the object without the disallowed properties. + var omit = restArguments(function(obj, keys) { + var iteratee = keys[0], context; + if (isFunction$1(iteratee)) { + iteratee = negate(iteratee); + if (keys.length > 1) context = keys[1]; + } else { + keys = map(flatten$1(keys, false, false), String); + iteratee = function(value, key) { + return !contains(keys, key); + }; + } + return pick(obj, iteratee, context); + }); + + // Returns everything but the last entry of the array. Especially useful on + // the arguments object. Passing **n** will return all the values in + // the array, excluding the last N. + function initial(array, n, guard) { + return slice.call(array, 0, Math.max(0, array.length - (n == null || guard ? 1 : n))); + } + + // Get the first element of an array. Passing **n** will return the first N + // values in the array. The **guard** check allows it to work with `_.map`. + function first(array, n, guard) { + if (array == null || array.length < 1) return n == null || guard ? void 0 : []; + if (n == null || guard) return array[0]; + return initial(array, array.length - n); + } + + // Returns everything but the first entry of the `array`. Especially useful on + // the `arguments` object. Passing an **n** will return the rest N values in the + // `array`. + function rest(array, n, guard) { + return slice.call(array, n == null || guard ? 1 : n); + } + + // Get the last element of an array. Passing **n** will return the last N + // values in the array. + function last(array, n, guard) { + if (array == null || array.length < 1) return n == null || guard ? void 0 : []; + if (n == null || guard) return array[array.length - 1]; + return rest(array, Math.max(0, array.length - n)); + } + + // Trim out all falsy values from an array. + function compact(array) { + return filter(array, Boolean); + } + + // Flatten out an array, either recursively (by default), or up to `depth`. + // Passing `true` or `false` as `depth` means `1` or `Infinity`, respectively. + function flatten(array, depth) { + return flatten$1(array, depth, false); + } + + // Take the difference between one array and a number of other arrays. + // Only the elements present in just the first array will remain. + var difference = restArguments(function(array, rest) { + rest = flatten$1(rest, true, true); + return filter(array, function(value){ + return !contains(rest, value); + }); + }); + + // Return a version of the array that does not contain the specified value(s). + var without = restArguments(function(array, otherArrays) { + return difference(array, otherArrays); + }); + + // Produce a duplicate-free version of the array. If the array has already + // been sorted, you have the option of using a faster algorithm. + // The faster algorithm will not work with an iteratee if the iteratee + // is not a one-to-one function, so providing an iteratee will disable + // the faster algorithm. + function uniq(array, isSorted, iteratee, context) { + if (!isBoolean(isSorted)) { + context = iteratee; + iteratee = isSorted; + isSorted = false; + } + if (iteratee != null) iteratee = cb(iteratee, context); + var result = []; + var seen = []; + for (var i = 0, length = getLength(array); i < length; i++) { + var value = array[i], + computed = iteratee ? iteratee(value, i, array) : value; + if (isSorted && !iteratee) { + if (!i || seen !== computed) result.push(value); + seen = computed; + } else if (iteratee) { + if (!contains(seen, computed)) { + seen.push(computed); + result.push(value); + } + } else if (!contains(result, value)) { + result.push(value); + } + } + return result; + } + + // Produce an array that contains the union: each distinct element from all of + // the passed-in arrays. + var union = restArguments(function(arrays) { + return uniq(flatten$1(arrays, true, true)); + }); + + // Produce an array that contains every item shared between all the + // passed-in arrays. + function intersection(array) { + var result = []; + var argsLength = arguments.length; + for (var i = 0, length = getLength(array); i < length; i++) { + var item = array[i]; + if (contains(result, item)) continue; + var j; + for (j = 1; j < argsLength; j++) { + if (!contains(arguments[j], item)) break; + } + if (j === argsLength) result.push(item); + } + return result; + } + + // Complement of zip. Unzip accepts an array of arrays and groups + // each array's elements on shared indices. + function unzip(array) { + var length = array && max(array, getLength).length || 0; + var result = Array(length); + + for (var index = 0; index < length; index++) { + result[index] = pluck(array, index); + } + return result; + } + + // Zip together multiple lists into a single array -- elements that share + // an index go together. + var zip = restArguments(unzip); + + // Converts lists into objects. Pass either a single array of `[key, value]` + // pairs, or two parallel arrays of the same length -- one of keys, and one of + // the corresponding values. Passing by pairs is the reverse of `_.pairs`. + function object(list, values) { + var result = {}; + for (var i = 0, length = getLength(list); i < length; i++) { + if (values) { + result[list[i]] = values[i]; + } else { + result[list[i][0]] = list[i][1]; + } + } + return result; + } + + // Generate an integer Array containing an arithmetic progression. A port of + // the native Python `range()` function. See + // [the Python documentation](https://docs.python.org/library/functions.html#range). + function range(start, stop, step) { + if (stop == null) { + stop = start || 0; + start = 0; + } + if (!step) { + step = stop < start ? -1 : 1; + } + + var length = Math.max(Math.ceil((stop - start) / step), 0); + var range = Array(length); + + for (var idx = 0; idx < length; idx++, start += step) { + range[idx] = start; + } + + return range; + } + + // Chunk a single array into multiple arrays, each containing `count` or fewer + // items. + function chunk(array, count) { + if (count == null || count < 1) return []; + var result = []; + var i = 0, length = array.length; + while (i < length) { + result.push(slice.call(array, i, i += count)); + } + return result; + } + + // Helper function to continue chaining intermediate results. + function chainResult(instance, obj) { + return instance._chain ? _$1(obj).chain() : obj; + } + + // Add your own custom functions to the Underscore object. + function mixin(obj) { + each(functions(obj), function(name) { + var func = _$1[name] = obj[name]; + _$1.prototype[name] = function() { + var args = [this._wrapped]; + push.apply(args, arguments); + return chainResult(this, func.apply(_$1, args)); + }; + }); + return _$1; + } + + // Add all mutator `Array` functions to the wrapper. + each(['pop', 'push', 'reverse', 'shift', 'sort', 'splice', 'unshift'], function(name) { + var method = ArrayProto[name]; + _$1.prototype[name] = function() { + var obj = this._wrapped; + if (obj != null) { + method.apply(obj, arguments); + if ((name === 'shift' || name === 'splice') && obj.length === 0) { + delete obj[0]; + } + } + return chainResult(this, obj); + }; + }); + + // Add all accessor `Array` functions to the wrapper. + each(['concat', 'join', 'slice'], function(name) { + var method = ArrayProto[name]; + _$1.prototype[name] = function() { + var obj = this._wrapped; + if (obj != null) obj = method.apply(obj, arguments); + return chainResult(this, obj); + }; + }); + + // Named Exports + + var allExports = { + __proto__: null, + VERSION: VERSION, + restArguments: restArguments, + isObject: isObject, + isNull: isNull, + isUndefined: isUndefined, + isBoolean: isBoolean, + isElement: isElement, + isString: isString, + isNumber: isNumber, + isDate: isDate, + isRegExp: isRegExp, + isError: isError, + isSymbol: isSymbol, + isArrayBuffer: isArrayBuffer, + isDataView: isDataView$1, + isArray: isArray, + isFunction: isFunction$1, + isArguments: isArguments$1, + isFinite: isFinite$1, + isNaN: isNaN$1, + isTypedArray: isTypedArray$1, + isEmpty: isEmpty, + isMatch: isMatch, + isEqual: isEqual, + isMap: isMap, + isWeakMap: isWeakMap, + isSet: isSet, + isWeakSet: isWeakSet, + keys: keys, + allKeys: allKeys, + values: values, + pairs: pairs, + invert: invert, + functions: functions, + methods: functions, + extend: extend, + extendOwn: extendOwn, + assign: extendOwn, + defaults: defaults, + create: create, + clone: clone, + tap: tap, + get: get, + has: has, + mapObject: mapObject, + identity: identity, + constant: constant, + noop: noop, + toPath: toPath$1, + property: property, + propertyOf: propertyOf, + matcher: matcher, + matches: matcher, + times: times, + random: random, + now: now, + escape: _escape, + unescape: _unescape, + templateSettings: templateSettings, + template: template, + result: result, + uniqueId: uniqueId, + chain: chain, + iteratee: iteratee, + partial: partial, + bind: bind, + bindAll: bindAll, + memoize: memoize, + delay: delay, + defer: defer, + throttle: throttle, + debounce: debounce, + wrap: wrap, + negate: negate, + compose: compose, + after: after, + before: before, + once: once, + findKey: findKey, + findIndex: findIndex, + findLastIndex: findLastIndex, + sortedIndex: sortedIndex, + indexOf: indexOf, + lastIndexOf: lastIndexOf, + find: find, + detect: find, + findWhere: findWhere, + each: each, + forEach: each, + map: map, + collect: map, + reduce: reduce, + foldl: reduce, + inject: reduce, + reduceRight: reduceRight, + foldr: reduceRight, + filter: filter, + select: filter, + reject: reject, + every: every, + all: every, + some: some, + any: some, + contains: contains, + includes: contains, + include: contains, + invoke: invoke, + pluck: pluck, + where: where, + max: max, + min: min, + shuffle: shuffle, + sample: sample, + sortBy: sortBy, + groupBy: groupBy, + indexBy: indexBy, + countBy: countBy, + partition: partition, + toArray: toArray, + size: size, + pick: pick, + omit: omit, + first: first, + head: first, + take: first, + initial: initial, + last: last, + rest: rest, + tail: rest, + drop: rest, + compact: compact, + flatten: flatten, + without: without, + uniq: uniq, + unique: uniq, + union: union, + intersection: intersection, + difference: difference, + unzip: unzip, + transpose: unzip, + zip: zip, + object: object, + range: range, + chunk: chunk, + mixin: mixin, + 'default': _$1 + }; + + // Default Export + + // Add all of the Underscore functions to the wrapper object. + var _ = mixin(allExports); + // Legacy Node.js API. + _._ = _; + + return _; + +}))); +//# sourceMappingURL=underscore-umd.js.map diff --git a/doc/_build/html/_static/underscore.js b/doc/_build/html/_static/underscore.js index 5b55f32..cf177d4 100644 --- a/doc/_build/html/_static/underscore.js +++ b/doc/_build/html/_static/underscore.js @@ -1,31 +1,6 @@ -// Underscore.js 1.3.1 -// (c) 2009-2012 Jeremy Ashkenas, DocumentCloud Inc. -// Underscore is freely distributable under the MIT license. -// Portions of Underscore are inspired or borrowed from Prototype, -// Oliver Steele's Functional, and John Resig's Micro-Templating. -// For all details and documentation: -// http://documentcloud.github.com/underscore -(function(){function q(a,c,d){if(a===c)return a!==0||1/a==1/c;if(a==null||c==null)return a===c;if(a._chain)a=a._wrapped;if(c._chain)c=c._wrapped;if(a.isEqual&&b.isFunction(a.isEqual))return a.isEqual(c);if(c.isEqual&&b.isFunction(c.isEqual))return c.isEqual(a);var 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mr(n,Dn(r))},each:jr,forEach:jr,map:_r,collect:_r,reduce:Ar,foldl:Ar,inject:Ar,reduceRight:xr,foldr:xr,filter:Sr,select:Sr,reject:function(n,r,t){return Sr(n,fr(qn(r)),t)},every:Or,all:Or,some:Mr,any:Mr,contains:Er,includes:Er,include:Er,invoke:Br,pluck:Nr,where:function(n,r){return Sr(n,Dn(r))},max:Ir,min:function(n,r,t){var e,u,o=1/0,i=1/0;if(null==r||"number"==typeof r&&"object"!=typeof n[0]&&null!=n)for(var a=0,f=(n=er(n)?n:jn(n)).length;ae||void 0===t)return 1;if(t - + - + API documentation — TEMUL Toolkit v0.1.2 documentation @@ -13,23 +13,28 @@ + + + + + + - @@ -50,7 +55,7 @@ -
    TEMUL Toolkit + TEMUL Toolkit @@ -98,18 +103,17 @@
  • Masked FFT and iFFT
  • Line Intensity Profile Comparisons
  • Interactive Image Filtering
  • -
  • Analysis of PTO Domain Wall Junction
  • API documentation
    • Classes
    • Modules
        -
      • Polarisation
      • +
      • TopoTEM (Polarisation)
      • Element Tools
      • Intensity Tools
      • Model Creation
      • -
      • Image Simulation Functions
      • +
      • Image Simulation Functions
      • Signal Processing
      • Signal Plotting
      • Input/Output (io)
      • @@ -159,6 +163,8 @@ + +
          @@ -170,7 +176,7 @@
        • - + View page source @@ -190,336 +196,52 @@

          ClassesΒΆ

          Model RefinerΒΆ

          -
          -
          -class temul.model_refiner.Model_Refiner(sublattice_and_elements_dict, comparison_image=None, sampling=None, thickness=10, name='')ΒΆ
          -
          -
          -calibrate_comparison_image(filename=None, percent_to_nn=None, mask_radius='auto', refine=True)ΒΆ
          -
          - -
          -
          -combine_individual_and_element_counts_as_dataframe(split_symbol=['_', '.'])ΒΆ
          -
          - -
          -
          -compare_latest_element_counts()ΒΆ
          -
          - -
          -
          -create_simulation(sublattices='all', filter_image=False, calibrate_image=True, xyz_sizes=None, header_comment='example', filename='refiner_simulation', reference_image='auto', probeStep=1.0, E0=60000.0, integrationAngleMin=0.085, integrationAngleMax=0.186, detectorAngleStep=0.001, interpolationFactor=16, realspacePixelSize=0.0654, numFP=1, cellDimXYZ=None, tileXYZ=None, probeSemiangle=0.03, alphaBeamMax=0.032, scanWindowMin=0.0, scanWindowMax=1.0, numThreads=2, algorithm='prism', delta_image_filter=0.5, max_sigma=6, mask_radius='auto', percent_to_nn=None, refine=True, sigma_offset=0)ΒΆ
          -

          Create and simulate a .xyz file from the sublattice information. -Uses the pyprismatic prism algorithm by default.

          -

          Note: The error resulting from filter=True with percent_to_nn set can -be fixed by setting mask_radius instead of percent_to_nn. -Error is: β€œTypeError: β€˜NoneType’ object is not iterable”

          -
          -
          Parameters
          -
            -
          • sublattices (Atomap Sublattices, default 'all') – If set to β€˜all’, sublattices that exist in the Model_Refiner will -all be used. The sublattice indexes can be specified in a list. -For example [0, 2] will select the first and third sublattices. -A list of sublattice objects can instead be used.

          • -
          • filter_image (Bool, default False) – Choose whether to filter the simulation with a Gaussian to match -the reference_image.

          • -
          • calibrate_image (Bool, default True) – Choose whether to calibrate the simulation with a set -calibration_area and calibration_separation.

          • -
          • xyz_sizes (list, default None) – List of the x, y, z physical size of the reference_image in -angstrom. If None is set, the sizes will be automatically taken -from the image_xyz_sizes attribute.

          • -
          • header_comment (string, default 'example') – The first line comment for the .xyz file.

          • -
          • filename (string, default 'refiner_simulation') – filename with which the .xyz file and simulated .mrc file will be -saved.

          • -
          • delta_image_filter (float, default 0.5) – The change in sigma for the filter Gaussian filter. Small values -will slow the filter down.

          • -
          • max_sigma (float, default 6) – The maximum sigma used for the filter Gaussian filter. Large -values will slow the filter down.

          • -
          • percent_to_nn (float, default None) – The percentage distance to the nearest neighbour atom used for -atomap atom position refinement.

          • -
          • mask_radius (float, default 'auto') – The pixel distance to the nearest neighbour atom used for atomap -atom position refinement

          • -
          • refine (Bool, default True) – Whether to refine the atom positions for the calibrate parameter.

          • -
          • Note (The error resulting from filter=True with percent_to_nn set can) –

          • -
          • fixed by setting mask_radius instead of percent_to_nn. (be) –

          • -
          -
          -
          -

          Examples

          -
          -
          Returns
          -

          -
          -
          Return type
          -

          Updates the comparison_image attribute with the newly simulated model.

          -
          -
          -
          - -
          -
          -property element_countΒΆ
          -
          - -
          -
          -get_element_count_as_dataframe()ΒΆ
          -

          Allows you to view the element count as a Pandas Dataframe. -See image_difference_intensity_model_refiner for an example.

          -
          -
          Returns
          -

          -
          -
          Return type
          -

          Pandas Dataframe

          -
          -
          -
          - -
          -
          -get_individual_elements_as_dataframe(split_symbol=['_', '.'])ΒΆ
          -
          - -
          -
          -image_difference_intensity_model_refiner(sublattices='all', comparison_image='default', change_sublattice=True, filename=None, verbose=False, refinement_method='Intensity')ΒΆ
          -

          Change the elements for sublattice atom positions that don’t match with -comparison_image.

          -

          See image_difference_intensity for details.

          -
          -
          Parameters
          -
            -
          • image_difference_intensity for parameter information. (See) –

          • -
          • refinement_method (string, default "Intensity") – Name passed to self.refinement_history for tracking purposes.

          • -
          -
          -
          -

          Examples

          -
          >>> from temul.model_refiner import (
          -...     get_model_refiner_with_12_vacancies_refined)
          ->>> refiner = get_model_refiner_with_12_vacancies_refined(
          -...     image_noise=True)
          -Changing some atoms
          -Changing some atoms
          -
          -
          -
          >>> history = refiner.element_count_history_list
          ->>> history_df = refiner.get_element_count_as_dataframe()
          ->>> refiner.combine_individual_and_element_counts_as_dataframe()
          -                 Ti_0  Ti_1   Ti_2  Ti_3  Ti_4  Ti_5     Ti
          -0 Initial State   0.0   0.0  400.0   0.0   0.0   0.0  800.0
          -1 Intensity       0.0  12.0  388.0   0.0   0.0   0.0  788.0
          -2 Intensity      12.0   0.0  388.0   0.0   0.0   0.0  776.0
          -3 Intensity      12.0   0.0  388.0   0.0   0.0   0.0  776.0
          -
          -
          -
          >>> refiner.plot_element_count_as_bar_chart(
          -...     element_configs=2, flip_colrows=True, fontsize=24)
          -
          -
          -

          Flip the view of the data

          -
          >>> refiner.plot_element_count_as_bar_chart(
          -...     element_configs=2, flip_colrows=False, fontsize=24)
          ->>> refiner.sublattice_list[0].plot()
          ->>> refiner.comparison_image.plot()
          -
          -
          -
          - -
          -
          -image_difference_position_model_refiner(chosen_sublattice, sublattices='all', comparison_sublattice_list='auto', comparison_image='default', pixel_threshold=5, num_peaks=5, inplace=True, filename=None, refinement_method='Position')ΒΆ
          -

          Find new atom positions that were perhaps missed by the initial -position finding steps. Each sublattice will be updated with new atom -positions if new atom positions are found.

          -

          See image_difference_position for details.

          -
          -
          Parameters
          -
            -
          • image_difference_position for parameter information. (See) –

          • -
          • refinement_method (string, default "Position") – Name passed to self.refinement_history for tracking purposes.

          • -
          -
          -
          -

          Examples

          -
          >>> from temul.model_refiner import (
          -...     get_model_refiner_one_sublattice_3_vacancies)
          ->>> refiner = get_model_refiner_one_sublattice_3_vacancies()
          ->>> refiner.sublattice_list[0].plot()
          ->>> refiner.comparison_image.plot()
          ->>> refiner.image_difference_position_model_refiner(
          -...     pixel_threshold=10,
          -...     chosen_sublattice=refiner.sublattice_list[0])
          -3 new atoms found! Adding new atom positions.
          -
          -
          -
          >>> refiner.sublattice_list[0].plot()
          -
          -
          -

          Combination of Refinements (cont.)

          -
          >>> refiner.image_difference_intensity_model_refiner()
          -Changing some atoms
          -
          -
          -
          >>> refiner.image_difference_intensity_model_refiner()
          -Changing some atoms
          -
          -
          -
          >>> history_df = refiner.get_element_count_as_dataframe()
          ->>> refiner.plot_element_count_as_bar_chart(
          -...     element_configs=2, flip_colrows=True, fontsize=24)
          -
          -
          -
          - -
          -
          -plot_element_count_as_bar_chart(element_configs=0, flip_colrows=True, title='Refinement of Elements', fontsize=16, split_symbol=['_', '.'])ΒΆ
          -

          Allows you to plot the element count as a bar chart. -See image_difference_intensity_model_refiner for an example.

          -
          -
          Parameters
          -
            -
          • element_configs (int, default 0) – Change the plotted data. -element_configs=0 will plot the element configuration counts, -element_configs=1 will plot the individual element counts, and -element_configs=2 will plot the both 0 and 1.

          • -
          • flip_colrows (Bool, default True) – Change how the data is plotted. -flip_colrows=True will take the transpose of the dataframe.

          • -
          • title (string, default "Refinement of Elements") – Title of the bar chart.

          • -
          • fontsize (int, default 16) –

          • -
          • split_symbol (list, default ['_', '.']) – See temul.element_tools.split_and_sort_element for details.

          • -
          -
          -
          -
          - -
          -
          -plot_error_between_comparison_and_reference_image(style='plot')ΒΆ
          -
          - -
          -
          -plot_reference_and_comparison_images(title_reference='Reference', title_comparison='Comparison')ΒΆ
          -
          - -
          -
          -repeating_intensity_refinement(n=5, sublattices='all', comparison_image='default', change_sublattice=True, filename=None, verbose=False, ignore_element_count_comparison=False)ΒΆ
          -
          - -
          -
          -revert_to_previous_refiner_instance()ΒΆ
          -
          - -
          -
          -set_calibration_area(manual_list=None)ΒΆ
          -

          Area that will be used to calibrate a simulation. The pixel separation -can be set with set_calibration_separation. The average intensity of -the atoms chosen by this separation within the area will be set to 1. -The idea is to calibrate the experimental and simulated images with a -known intensity (e.g., single Mo atom in MoS2 is relatively -consistant).

          -

          reference_image can be changed via the Model_refiner.reference_image -attribute.

          -

          manual_list must be a list of two lists, each of length two. -For example: [ [0,0], [50, 50] ]

          -
          - -
          -
          -set_calibration_separation(pixel_separation)ΒΆ
          -
          - -
          -
          -set_image_xyz_sizes(xyz_list)ΒΆ
          -
          - -
          -
          -set_thickness(thickness)ΒΆ
          -
          - -
          -
          -update_element_count_and_refinement_history(refinement_method)ΒΆ
          -
          - -
          -
          -update_element_count_history()ΒΆ
          -
          - -
          -
          -update_error_between_comparison_and_reference_image()ΒΆ
          -
          - -
          -
          -update_refinement_history(refinement_method)ΒΆ
          -
          - -
          -
          -update_sublattices_positions(sublattice_list)ΒΆ
          -
          - -
          -

        ModulesΒΆ

        -
        -

        PolarisationΒΆ

        +
        +

        TopoTEM (Polarisation)ΒΆ

        -
        -temul.polarisation.angle_label(vector_rep='magnitude', units='pix', degrees=False)ΒΆ
        +
        +temul.topotem.polarisation.angle_label(vector_rep='magnitude', units='pix', degrees=False)ΒΆ
        -
        -temul.polarisation.atom_deviation_from_straight_line_fit(sublattice, axis_number, n, second_fit_rigid=True, plot=False)ΒΆ
        +
        +temul.topotem.polarisation.atom_deviation_from_straight_line_fit(sublattice, axis_number, n, second_fit_rigid=True, plot=False)ΒΆ

        Fits the atomic columns in an atom plane to two straight lines using the -first n and second (last) n atomic columns. Computes the distance of +first n and second (last) n atomic columns. Computes the distance of each atomic column from the line halfway between the two fitted lines, as -described in [1]. This is done for every sublattice atom plane along the -chosen axis_number.

        +described in 1. This is done for every sublattice atom plane along the +chosen axis_number.

        The slope of the first fitting will be used for the -second fitting. Setting second_fit_rigid = False will reverse this +second fitting. Setting second_fit_rigid = False will reverse this behaviour.

        Parameters
        • sublattice (Atomap Sublattice object) –

        • -
        • axis_number (int) – The index of the zone axis (translation symmetry) found by the Atomap -function construct_zone_axes(). For sublattices with heavily +

        • axis_number (int) – The index of the zone axis (translation symmetry) found by the Atomap +function construct_zone_axes(). For sublattices with heavily deviating atomic columns, you may need to use sublattice.construct_zone_axes(atom_plane_tolerance=1).

        • -
        • n (int) – The number of columns used at the beginning and end of each atom plane +

        • n (int) – The number of columns used at the beginning and end of each atom plane to fit a straight line.

        • -
        • second_fit_rigid (Bool, default True) – Used to decide whether the first or second fitting’s slope will be -rigid during fitting. With second_fit_rigid=True, the slope of the +

        • second_fit_rigid (bool, default True) – Used to decide whether the first or second fitting’s slope will be +rigid during fitting. With second_fit_rigid=True, the slope of the second fitting will be defined as the slope as the first fitting. The y-intercept is free to move.

        • -
        • plot (Bool, default False) – Whether to plot the atom plane data, first and second fitting, and the +

        • plot (bool, default False) – Whether to plot the atom plane data, first and second fitting, and the line constructed halfway between the two.

        Returns
        -

        x, y, u, v – x, y are the original atom position coordinates sublattice.x_position -and sublattice.y_position for the coordinates included in the chosen -axis_number. u, v are the polarisation vector components pointing +

        x, y, u, v – x, y are the original atom position coordinates sublattice.x_position` +and ``sublattice.y_position for the coordinates included in the chosen +axis_number. u, v are the polarisation vector components pointing towards the halfway line from the atom position coordinates. -These can be input to plot_polarisation_vectors() for visualisation.

        +These can be input to plot_polarisation_vectors() for visualisation.

        Return type

        lists of equal length

        @@ -528,13 +250,13 @@

        Modules

        See also

        -
        get_xyuv_from_line_fit()

        uses _fit_line_clusters to get xyuv from arr

        +
        get_xyuv_from_line_fit

        uses _fit_line_clusters to get xyuv from arr

        References

        -
        1
        +
        1

        Reference: Julie Gonnissen, Dmitry Batuk, Guillaume F. Nataf, Lewys Jones, Artem M. Abakumov, Sandra Van Aert, Dominique Schryvers, Ekhard K. H. Salje, Direct Observation of Ferroelectric @@ -549,8 +271,8 @@

        Modules>>> sublattice.construct_zone_axes(atom_plane_tolerance=1)

        -

        Choose n: how many atom columns should be used to fit the line on each -side of the atom planes. If n is too large, the fitting will appear +

        Choose n`: how many atom columns should be used to fit the line on each +side of the atom planes. If ``n is too large, the fitting will appear incorrect.

        >>> n = 5
         >>> x, y, u, v = tml.atom_deviation_from_straight_line_fit(
        @@ -586,18 +308,18 @@ 

        Modules -
        -temul.polarisation.atom_to_atom_distance_grouped_mean(sublattice, zone_axis_index, aggregation_axis='y', slice_thickness=10, sampling=None, units='pix')ΒΆ
        +
        +temul.topotem.polarisation.atom_to_atom_distance_grouped_mean(sublattice, zone_axis_index, aggregation_axis='y', slice_thickness=10, sampling=None, units='pix')ΒΆ

        Average the atom to atom distances along the chosen zone_axis_index parallel to the chosen axis (β€˜x’ or β€˜y’).

        Parameters
        • sublattice (Atomap Sublattice object) –

        • -
        • zone_axis_index (int) – The zone axes you wish to average along.

        • +
        • zone_axis_index (int) – The zone axes you wish to average along.

        • aggregation_axis (string, default "y") – Axis parallel to which the atom to atom distances will be averaged.

        • -
        • slice_thickness (float, default 10) – thickness of the slices used for aggregation.

        • -
        • sampling (float, default None) – Pixel sampling of the image for calibration.

        • +
        • slice_thickness (float, default 10) – thickness of the slices used for aggregation.

        • +
        • sampling (float, default None) – Pixel sampling of the image for calibration.

        • units (string, default "pix") – Units of the sampling.

        @@ -613,7 +335,8 @@

        Modules
        >>> import numpy as np
         >>> from atomap.dummy_data import get_distorted_cubic_sublattice
         >>> import matplotlib.pyplot as plt
        ->>> from temul.polarisation import atom_to_atom_distance_grouped_mean
        +>>> from temul.topotem.polarisation import (
        +...     atom_to_atom_distance_grouped_mean)
         >>> sublatticeA = get_distorted_cubic_sublattice()
         >>> sublatticeA.construct_zone_axes(atom_plane_tolerance=1)
         >>> sublatticeA.plot()
        @@ -637,8 +360,8 @@ 

        Modules -
        -temul.polarisation.combine_atom_deviations_from_zone_axes(sublattice, image=None, axes=None, sampling=None, units='pix', plot_style='vector', overlay=True, unit_vector=False, degrees=False, save='atom_deviation', title='', color='yellow', cmap=None, pivot='middle', angles='xy', scale_units='xy', scale=None, headwidth=3.0, headlength=5.0, headaxislength=4.5, monitor_dpi=96, no_axis_info=True, scalebar=False)ΒΆ
        +
        +temul.topotem.polarisation.combine_atom_deviations_from_zone_axes(sublattice, image=None, axes=None, sampling=None, units='pix', plot_style='vector', overlay=True, unit_vector=False, degrees=False, save='atom_deviation', title='', color='yellow', cmap=None, pivot='middle', angles='xy', scale_units='xy', scale=None, headwidth=3.0, headlength=5.0, headaxislength=4.5, monitor_dpi=96, no_axis_info=True, scalebar=False)ΒΆ

        Combine the atom deviations of each atom for all zone axes. Good for plotting vortexes and seeing the total deviation from a perfect structure.

        @@ -654,14 +377,14 @@

        Modulesplot_polarisation_vectors() for visualisation.

      Examples

      >>> import atomap.api as am
      ->>> from temul.polarisation import (plot_polarisation_vectors,
      +>>> from temul.topotem.polarisation import (plot_polarisation_vectors,
       ...     combine_atom_deviations_from_zone_axes)
       >>> atom_lattice = am.dummy_data.get_polarization_film_atom_lattice()
       >>> sublatticeA = atom_lattice.sublattice_list[0]
      @@ -684,8 +407,8 @@ 

      Modules -
      -temul.polarisation.correct_off_tilt_vectors(u, v, method='com')ΒΆ
      +
      +temul.topotem.polarisation.correct_off_tilt_vectors(u, v, method='com')ΒΆ

      Useful if your image is off-tilt (electron beam is not perfectly parallel to the atomic columns).

      @@ -705,7 +428,7 @@

      ModulesExamples

      -

      -
      -temul.polarisation.corrected_vectors_via_center_of_mass(u, v)ΒΆ
      +
      +temul.topotem.polarisation.corrected_vectors_via_center_of_mass(u, v)ΒΆ
      -
      -temul.polarisation.delete_atom_planes_from_sublattice(sublattice, zone_axis_index=0, atom_plane_tolerance=0.5, divisible_by=3, offset_from_zero=0, opposite=False)ΒΆ
      +
      +temul.topotem.polarisation.delete_atom_planes_from_sublattice(sublattice, zone_axis_index=0, atom_plane_tolerance=0.5, divisible_by=3, offset_from_zero=0, opposite=False)ΒΆ

      Delete atom_planes from a zone axis. Can choose whether to delete every second, third etc. atom plane, and the offset from the zero index.

      Parameters
      • sublattice (Atomap Sublattice object) –

      • -
      • zone_axis_index (int, default 0) – The zone axis you wish to specify. You are indexing +

      • zone_axis_index (int, default 0) – The zone axis you wish to specify. You are indexing sublattice.zones_axis_average_distances[zone_axis_index]

      • -
      • atom_plane_tolerance (float, default 0.5) – float between 0.0 and 1.0. Closer to 1 means it will find more zones. +

      • atom_plane_tolerance (float, default 0.5) – float between 0.0 and 1.0. Closer to 1 means it will find more zones. See sublattice.construct_zone_axes() for more information.

      • -
      • divisible_by (int, default 3) – If divisible_by is 2, every second atom_plane is deleted, +

      • divisible_by (int, default 3) – If divisible_by is 2, every second atom_plane is deleted, If divisible_by is 4, every fourth atom_plane is deleted, etc.

      • -
      • offset_from_zero (int, default 0) – The atom_plane from which you start deleting. +

      • offset_from_zero (int, default 0) – The atom_plane from which you start deleting. If offset_from_zero is 4, the fourth atom_plane will be the first deleted.

      • -
      • opposite (Bool, default False) – If this is set to True, the atom_plane specified by divisible_by +

      • opposite (bool, default False) – If this is set to True, the atom_plane specified by divisible_by will be kept and all others deleted.

      Examples

      -
      >>> from temul.polarisation import delete_atom_planes_from_sublattice
      +
      >>> from temul.topotem.polarisation import (
      +...     delete_atom_planes_from_sublattice)
       >>> import atomap.dummy_data as dd
       >>> atom_lattice = dd.get_polarization_film_atom_lattice()
       >>> sublatticeA = atom_lattice.sublattice_list[0]
       >>> sublatticeA.construct_zone_axes()
       >>> zone_vec_list = sublatticeA.zones_axis_average_distances[0:2]
      ->>> zones01_A = sublatticeA.get_all_atom_planes_by_zone_vector(
      -...     zone_vec_list)
      ->>> # zones01_A.plot()
      ->>> delete_atom_planes_from_sublattice(
      +
      +
      +

      Plot the planes visually using, it may take some time in large images: +zones01_A = sublatticeA.get_all_atom_planes_by_zone_vector(zone_vec_list) +zones01_A.plot()

      +
      >>> delete_atom_planes_from_sublattice(
       ...         sublatticeA, zone_axis_index=0,
       ...         divisible_by=3, offset_from_zero=1)
      ->>> zones01_B = sublatticeA.get_all_atom_planes_by_zone_vector(
      -...     zone_vec_list)
      ->>> # zones01_A.plot()
       
      +

      zones01_B = sublatticeA.get_all_atom_planes_by_zone_vector(zone_vec_list) +zones01_A.plot()

      -
      -temul.polarisation.find_polarisation_vectors(atom_positions_A, atom_positions_B, save=None)ΒΆ
      +
      +temul.topotem.polarisation.find_polarisation_vectors(atom_positions_A, atom_positions_B, save=None)ΒΆ

      Calculate the vectors from atom_positions_A to atom_positions_B.

      Parameters
        -
      • atom_positions_A (list) – Atom positions list in the form [[x1,y1], [x2,y2], [x3,y3]…].

      • -
      • atom_positions_B (list) – Atom positions list in the form [[x1,y1], [x2,y2], [x3,y3]…].

      • +
      • atom_positions_A (list) – Atom positions list in the form [[x1,y1], [x2,y2], [x3,y3]…].

      • +
      • atom_positions_B (list) – Atom positions list in the form [[x1,y1], [x2,y2], [x3,y3]…].

      • save (string, default None) – If set to a string, the array will be saved.

      @@ -803,7 +528,7 @@

      ModulesExamples

      -
      >>> from temul.polarisation import find_polarisation_vectors
      +
      >>> from temul.topotem.polarisation import find_polarisation_vectors
       >>> pos_A = [[1,2], [3,4], [5,8], [5,2]]
       >>> pos_B = [[1,1], [5,2], [3,1], [6,2]]
       >>> u, v = find_polarisation_vectors(pos_A, pos_B, save=None)
      @@ -817,18 +542,18 @@ 

      Modules -
      -temul.polarisation.full_atom_plane_deviation_from_straight_line_fit(sublattice, axis_number: int = 0, save: str = '')ΒΆ
      +
      +temul.topotem.polarisation.full_atom_plane_deviation_from_straight_line_fit(sublattice, axis_number: int = 0, save: str = '')ΒΆ

      Fit the atoms in an atom plane to a straight line and find the deviation of each atom position from that straight line fit. -To plot all zones see plot_atom_deviation_from_all_zone_axes().

      +To plot all zones see plot_atom_deviation_from_all_zone_axes().

      Parameters
      • sublattice (Atomap Sublattice object) –

      • -
      • axis_number (int, default 0) – The index of the zone axis (translation symmetry) found by the Atomap -function construct_zone_axes().

      • -
      • save (string, default '') – If set to save=None, the array will not be saved.

      • +
      • axis_number (int, default 0) – The index of the zone axis (translation symmetry) found by the Atomap +function construct_zone_axes().

      • +
      • save (string, default '') – If set to save=None, the array will not be saved.

      Returns
      @@ -836,14 +561,14 @@

      Modulesplot_polarisation_vectors() for visualisation.

    Examples

    >>> import atomap.api as am
    ->>> from temul.polarisation import (
    +>>> from temul.topotem.polarisation import (
     ...     full_atom_plane_deviation_from_straight_line_fit,
     ...     plot_polarisation_vectors)
     >>> atom_lattice = am.dummy_data.get_polarization_film_atom_lattice()
    @@ -860,18 +585,18 @@ 

    Modules -
    -temul.polarisation.get_angles_from_uv(u, v, degrees=False, angle_offset=None)ΒΆ
    +
    +temul.topotem.polarisation.get_angles_from_uv(u, v, degrees=False, angle_offset=None)ΒΆ

    Calculate the angle of a vector given the uv components.

    Parameters
      -
    • u (list or 1D NumPy array) –

    • -
    • v (list or 1D NumPy array) –

    • -
    • degrees (Bool, default False) – Change between degrees and radian. Default is radian.

    • -
    • angle_offset (float, default None) – Rotate the angles by the given amount. The function assumes that if you -set degrees=False then the provided angle_offset is in radians, and -if you set degrees=True then the provided angle_offset is in +

    • u (list or 1D NumPy array) –

    • +
    • v (list or 1D NumPy array) –

    • +
    • degrees (bool, default False) – Change between degrees and radian. Default is radian.

    • +
    • angle_offset (float, default None) – Rotate the angles by the given amount. The function assumes that if you +set degrees=False then the provided angle_offset is in radians, and +if you set degrees=True then the provided angle_offset is in degrees.

    @@ -885,19 +610,19 @@

    Modules -
    -temul.polarisation.get_average_polarisation_in_regions(x, y, u, v, image, divide_into=8)ΒΆ
    +
    +temul.topotem.polarisation.get_average_polarisation_in_regions(x, y, u, v, image, divide_into=8)ΒΆ

    This function splits the image into the given number of regions and averages the polarisation of each region.

    Parameters
      -
    • x (list or 1D NumPy array) – xy coordinates on the image

    • -
    • y (list or 1D NumPy array) – xy coordinates on the image

    • -
    • u (list or 1D NumPy array) – uv vector components

    • -
    • v (list or 1D NumPy array) – uv vector components

    • +
    • x (list or 1D NumPy array) – xy coordinates on the image

    • +
    • y (list or 1D NumPy array) – xy coordinates on the image

    • +
    • u (list or 1D NumPy array) – uv vector components

    • +
    • v (list or 1D NumPy array) – uv vector components

    • image (2D NumPy array) –

    • -
    • divide_into (int, default 8) – The number used to divide the image up. If 8, then the image will be +

    • divide_into (int, default 8) – The number used to divide the image up. If 8, then the image will be split into an 8x8 grid.

    @@ -913,7 +638,7 @@

    Modules
    >>> import matplotlib.pyplot as plt
     >>> import numpy as np
     >>> import atomap.api as am
    ->>> from temul.polarisation import (
    +>>> from temul.topotem.polarisation import (
     ...    combine_atom_deviations_from_zone_axes,
     ...    plot_polarisation_vectors, get_average_polarisation_in_regions)
     >>> atom_lattice = am.dummy_data.get_polarization_film_atom_lattice()
    @@ -944,19 +669,19 @@ 

    Modules -
    -temul.polarisation.get_average_polarisation_in_regions_square(x, y, u, v, image, divide_into=4)ΒΆ
    -

    Same as get_average_polarisation_in_regions() but works for non-square +

    +temul.topotem.polarisation.get_average_polarisation_in_regions_square(x, y, u, v, image, divide_into=4)ΒΆ
    +

    Same as get_average_polarisation_in_regions() but works for non-square (rectangular) images.

    Parameters
      -
    • x (list or 1D NumPy array) – xy coordinates on the image

    • -
    • y (list or 1D NumPy array) – xy coordinates on the image

    • -
    • u (list or 1D NumPy array) – uv vector components

    • -
    • v (list or 1D NumPy array) – uv vector components

    • +
    • x (list or 1D NumPy array) – xy coordinates on the image

    • +
    • y (list or 1D NumPy array) – xy coordinates on the image

    • +
    • u (list or 1D NumPy array) – uv vector components

    • +
    • v (list or 1D NumPy array) – uv vector components

    • image (2D NumPy array) –

    • -
    • divide_into (int, default 8) – The number used to divide the image up. If 8, then the image will be +

    • divide_into (int, default 8) – The number used to divide the image up. If 8, then the image will be split into an 8x8 grid.

    @@ -970,7 +695,7 @@

    ModulesExamples

    >>> import atomap.api as am
    ->>> from temul.polarisation import (
    +>>> from temul.topotem.polarisation import (
     ...     combine_atom_deviations_from_zone_axes, plot_polarisation_vectors,
     ...     get_average_polarisation_in_regions_square)
     >>> atom_lattice = am.dummy_data.get_polarization_film_atom_lattice()
    @@ -1001,24 +726,24 @@ 

    Modules -
    -temul.polarisation.get_divide_into(sublattice, averaging_by, sampling, zone_axis_index_A, zone_axis_index_B)ΒΆ
    -

    Calculate the divide_into required to get an averaging of averaging_by. -divide_into can then be used in -temul.polarisation.get_average_polarisation_in_regions. +

    +temul.topotem.polarisation.get_divide_into(sublattice, averaging_by, sampling, zone_axis_index_A, zone_axis_index_B)ΒΆ
    +

    Calculate the divide_into required to get an averaging of averaging_by. +divide_into can then be used in +temul.topotem.polarisation.get_average_polarisation_in_regions. Also finds unit cell size and the number of unit cells in the (square) image along the x axis.

    Parameters
    • sublattice (Atomap Sublattice) –

    • -
    • averaging_by (int or float) – How many unit cells should be averaged. If averaging_by=2, 2x2 unit -cells will be averaged when passing divide_into to -temul.polarisation.get_average_polarisation_in_regions.

    • -
    • sampling (float) – Pixel sampling of the image for calibration.

    • -
    • zone_axis_index_A (int) – Sublattice zone axis indices which should represent the sides of the +

    • averaging_by (int or float) – How many unit cells should be averaged. If averaging_by=2, 2x2 unit +cells will be averaged when passing divide_into to +temul.topotem.polarisation.get_average_polarisation_in_regions.

    • +
    • sampling (float) – Pixel sampling of the image for calibration.

    • +
    • zone_axis_index_A (int) – Sublattice zone axis indices which should represent the sides of the unit cell.

    • -
    • zone_axis_index_B (int) – Sublattice zone axis indices which should represent the sides of the +

    • zone_axis_index_B (int) – Sublattice zone axis indices which should represent the sides of the unit cell.

    @@ -1030,7 +755,7 @@

    ModulesExamples

    -
    >>> from temul.polarisation import get_divide_into
    +
    >>> from temul.topotem.polarisation import get_divide_into
     >>> from atomap.dummy_data import get_simple_cubic_sublattice
     >>> sublattice = get_simple_cubic_sublattice()
     >>> sublattice.construct_zone_axes()
    @@ -1045,27 +770,29 @@ 

    Modules -
    -temul.polarisation.get_strain_map(sublattice, zone_axis_index, theoretical_value, sampling=None, units='pix', vmin=None, vmax=None, cmap='inferno', title='Strain Map', filename=None, return_x_y_z=False, **kwargs)ΒΆ
    +
    +temul.topotem.polarisation.get_strain_map(sublattice, zone_axis_index, theoretical_value, sampling=None, units='pix', vmin=None, vmax=None, cmap='inferno', title='Strain Map', plot=False, filename=None, return_x_y_z=False, **kwargs)ΒΆ

    Calculate the strain across a zone axis of a sublattice.

    Parameters
    • sublattice (Atomap Sublattice object) –

    • -
    • zone_axis_index (int) – The zone axis you wish to specify. You are indexing -sublattice.zones_axis_average_distances[zone_axis_index].

    • -
    • theoretical_value (float) – The theoretical separation between the atoms across (not along) the +

    • zone_axis_index (int) – The zone axis you wish to specify. You are indexing +sublattice.zones_axis_average_distances[zone_axis_index].

    • +
    • theoretical_value (float) – The theoretical separation between the atoms across (not along) the specified zone.

    • -
    • sampling (float, default None) – Pixel sampling of the image for calibration.

    • +
    • sampling (float, default None) – Pixel sampling of the image for calibration.

    • units (string, default "pix") – Units of the sampling.

    • vmin (see Matplotlib for details) –

    • vmax (see Matplotlib for details) –

    • cmap (see Matplotlib for details) –

    • title (string, default "Strain Map") –

    • -
    • filename (string, optional) – If filename is set, the strain signal and plot will be saved.

    • -
    • return_x_y_z (Bool, default False) – If this is set to True, the strain_signal (map), as well as separate +

    • plot (bool) – Set to true if the figure should be plotted.

    • +
    • filename (string, optional) – If filename is set, the strain signal and plot will be saved. +plot must be set to True.

    • +
    • return_x_y_z (bool, default False) – If this is set to True, the strain_signal (map), as well as separate lists of the x, y, and strain values.

    • -
    • **kwargs (Matplotlib keyword arguments passed to imshow().) –

    • +
    • **kwargs (Matplotlib keyword arguments passed to imshow().) –

    Returns
    @@ -1077,7 +804,7 @@

    ModulesExamples

    >>> import atomap.api as am
    ->>> from temul.polarisation import get_strain_map
    +>>> from temul.topotem.polarisation import get_strain_map
     >>> atom_lattice = am.dummy_data.get_polarization_film_atom_lattice()
     >>> sublatticeA = atom_lattice.sublattice_list[0]
     >>> sublatticeA.find_nearest_neighbors()
    @@ -1090,15 +817,15 @@ 

    Modules -
    -temul.polarisation.get_vector_magnitudes(u, v, sampling=None)ΒΆ
    +
    +temul.topotem.polarisation.get_vector_magnitudes(u, v, sampling=None)ΒΆ

    Calculate the magnitude of a vector given the uv components.

    Parameters
      -
    • u (list or 1D NumPy array) –

    • -
    • v (list or 1D NumPy array) –

    • -
    • sampling (float, default None) – If sampling is set, the vector magnitudes (in pix) will be scaled +

    • u (list or 1D NumPy array) –

    • +
    • v (list or 1D NumPy array) –

    • +
    • sampling (float, default None) – If sampling is set, the vector magnitudes (in pix) will be scaled by sampling (nm/pix).

    @@ -1110,7 +837,7 @@

    ModulesExamples

    -
    >>> from temul.polarisation import get_vector_magnitudes
    +
    >>> from temul.topotem.polarisation import get_vector_magnitudes
     >>> import numpy as np
     >>> u, v = [4,3,2,5,6], [8,5,2,1,1] # list input
     >>> vector_mags = get_vector_magnitudes(u,v)
    @@ -1123,32 +850,32 @@ 

    Modules -
    -temul.polarisation.get_xyuv_from_line_fit(arr, n, second_fit_rigid=True, plot=False)ΒΆ
    +
    +temul.topotem.polarisation.get_xyuv_from_line_fit(arr, n, second_fit_rigid=True, plot=False)ΒΆ

    Fits the data in an array to two straight lines using the -first n and second (last) n array value pairs. Computes the distance of +first n and second (last) n array value pairs. Computes the distance of each array value pair from the line halfway between the two fitted lines.

    The slope of the first fitting will be used for the -second fitting. Setting second_fit_rigid = False will reverse this +second fitting. Setting second_fit_rigid = False will reverse this behaviour.

    Parameters
    • arr (2D array-like) – Array-like (e.g., NumPy 2D array) in the form [[x1, y1], [x2, y2]…]

    • -
    • n (int) – The number of arr value pairs used at the beginning and end of the arr +

    • n (int) – The number of arr value pairs used at the beginning and end of the arr to fit a straight line.

    • -
    • second_fit_rigid (Bool, default True) – Used to decide whether the first or second fitting’s slope will be -rigid during fitting. With second_fit_rigid=True, the slope of the +

    • second_fit_rigid (bool, default True) – Used to decide whether the first or second fitting’s slope will be +rigid during fitting. With second_fit_rigid=True, the slope of the second fitting will be defined as the slope as the first fitting. The y-intercept is free to move.

    • -
    • plot (Bool, default False) – Whether to plot the arr data, first and second fitting, and the +

    • plot (bool, default False) – Whether to plot the arr data, first and second fitting, and the line constructed halfway between the two.

    Returns

    x, y, u, v – x, y are the original arr coordinates. u, v are the vector components pointing towards the halfway line from the arr coordinates. -These can be input to plot_polarisation_vectors() for visualisation.

    +These can be input to plot_polarisation_vectors() for visualisation.

    Return type

    lists of equal length

    @@ -1157,7 +884,7 @@

    Modules

    See also

    -
    atom_deviation_from_straight_line_fit()

    Gets xyuv for Sublattice object

    +
    atom_deviation_from_straight_line_fit

    Gets xyuv for Sublattice object

    @@ -1165,20 +892,20 @@

    Modules
    >>> arr = np.array([[1, 2], [2, 2], [3, 2], [4, 2], [5, 2.05],
     ...                 [6, 1], [7, 1], [8, 1], [9, 1], [10, 0.75]])
     >>> x, y, u, v = get_xyuv_from_line_fit(
    -...     arr, n=5, second_fit_rigid=True, plot=True)
    +...     arr, n=5, second_fit_rigid=True, plot=False)
     

    Use the lower (second) cluster to fit the data, making the first cluster rigid

    >>> x, y, u, v = get_xyuv_from_line_fit(
    -...     arr, n=5, second_fit_rigid=False, plot=True)
    +...     arr, n=5, second_fit_rigid=False, plot=False)
     

    -
    -temul.polarisation.plot_atom_deviation_from_all_zone_axes(sublattice, image=None, sampling=None, units='pix', plot_style='vector', overlay=True, unit_vector=False, degrees=False, save='atom_deviation', title='', color='yellow', cmap=None, pivot='middle', angles='xy', scale_units='xy', scale=None, headwidth=3.0, headlength=5.0, headaxislength=4.5, monitor_dpi=96, no_axis_info=True, scalebar=False)ΒΆ
    +
    +temul.topotem.polarisation.plot_atom_deviation_from_all_zone_axes(sublattice, image=None, sampling=None, units='pix', plot_style='vector', overlay=True, unit_vector=False, degrees=False, save='atom_deviation', title='', color='yellow', cmap=None, pivot='middle', angles='xy', scale_units='xy', scale=None, headwidth=3.0, headlength=5.0, headaxislength=4.5, monitor_dpi=96, no_axis_info=True, scalebar=False)ΒΆ

    Plot the atom deviation from a straight line fit for all zone axes constructed by an Atomap sublattice object.

    @@ -1190,84 +917,85 @@

    ModulesExamples

    -
    >>> import atomap.api as am
    ->>> from temul.polarisation import plot_atom_deviation_from_all_zone_axes
    ->>> atom_lattice = am.dummy_data.get_polarization_film_atom_lattice()
    +
    >>> import atomap.dummy_data as dd
    +>>> import temul.api as tml
    +>>> atom_lattice = dd.get_polarization_film_atom_lattice()
     >>> sublatticeA = atom_lattice.sublattice_list[0]
     >>> sublatticeA.find_nearest_neighbors()
     >>> sublatticeA.refine_atom_positions_using_center_of_mass()
     >>> sublatticeA.construct_zone_axes()
    ->>> plot_atom_deviation_from_all_zone_axes(sublatticeA, save=None)
    +>>> tml.plot_atom_deviation_from_all_zone_axes(
    +...     sublatticeA, save=None)
     

    -
    -temul.polarisation.plot_polarisation_vectors(x, y, u, v, image, sampling=None, units='pix', plot_style='vector', overlay=True, unit_vector=False, vector_rep='magnitude', degrees=False, angle_offset=None, save='polarisation_image', title='', color='yellow', cmap=None, alpha=1.0, image_cmap='gray', monitor_dpi=96, no_axis_info=True, invert_y_axis=True, ticks=None, scalebar=False, antialiased=False, levels=20, remove_vectors=False, quiver_units='width', pivot='middle', angles='xy', scale_units='xy', scale=None, headwidth=3.0, headlength=5.0, headaxislength=4.5, width=None, minshaft=1, minlength=1)ΒΆ
    +
    +temul.topotem.polarisation.plot_polarisation_vectors(x, y, u, v, image, sampling=None, units='pix', plot_style='vector', overlay=True, unit_vector=False, vector_rep='magnitude', degrees=False, angle_offset=None, save='polarisation_image', title='', color='yellow', cmap=None, alpha=1.0, image_cmap='gray', monitor_dpi=96, no_axis_info=True, invert_y_axis=True, ticks=None, scalebar=False, antialiased=False, levels=20, remove_vectors=False, quiver_units='width', pivot='middle', angles='xy', scale_units='xy', scale=None, headwidth=3.0, headlength=5.0, headaxislength=4.5, width=None, minshaft=1, minlength=1)ΒΆ

    Plot the polarisation vectors. These can be found with -find_polarisation_vectors() or Atomap’s -get_polarization_from_second_sublattice() function.

    +find_polarisation_vectors() or Atomap’s +get_polarization_from_second_sublattice() function.

    Parameters
    • matplotlib's quiver function for more details. (See) –

    • -
    • x (list or 1D NumPy array) – xy coordinates of the vectors on the image.

    • -
    • y (list or 1D NumPy array) – xy coordinates of the vectors on the image.

    • -
    • u (list or 1D NumPy array) – uv vector components.

    • -
    • v (list or 1D NumPy array) – uv vector components.

    • +
    • x (list or 1D NumPy array) – xy coordinates of the vectors on the image.

    • +
    • y (list or 1D NumPy array) – xy coordinates of the vectors on the image.

    • +
    • u (list or 1D NumPy array) – uv vector components.

    • +
    • v (list or 1D NumPy array) – uv vector components.

    • image (2D NumPy array) – image is used to fit the image. Will flip the y axis, as used for electron microscopy data (top left point is (0, 0) coordinate).

    • -
    • sampling (float, default None) – Pixel sampling (pixel size) of the image for calibration.

    • +
    • sampling (float, default None) – Pixel sampling (pixel size) of the image for calibration.

    • units (string, default "pix") – Units used to display the magnitude of the vectors.

    • plot_style (string, default "vector") – Options are β€œvector”, β€œcolormap”, β€œcontour”, β€œcolorwheel”, β€œpolar_colorwheel”. Note that β€œcolorwheel” will automatically plot the colorbar as an angle. Also note that β€œpolar_colorwheel” will automatically generate a 2D RGB (HSV) list of colors that match with the vector components (uv).

    • -
    • overlay (Bool, default True) – If set to True, the image will be plotting behind the arrows

    • -
    • unit_vector (Bool, default False) – Change the vectors magnitude to unit vectors for plotting purposes. +

    • overlay (bool, default True) – If set to True, the image will be plotting behind the arrows

    • +
    • unit_vector (bool, default False) – Change the vectors magnitude to unit vectors for plotting purposes. Magnitude will still be displayed correctly for colormaps etc.

    • -
    • vector_rep (str, default "magnitude") – How the vectors are represented. This can be either their magnitude -or angle. One may want to use angle when plotting a contour map, +

    • vector_rep (str, default "magnitude") – How the vectors are represented. This can be either their magnitude +or angle. One may want to use angle when plotting a contour map, i.e., view the contours in terms of angles which can be useful for visualising regions of different polarisation.

    • -
    • degrees (Bool, default False) – Change between degrees and radian. Default is radian. -If plot_style=”colorwheel”, then setting degrees=True will convert +

    • degrees (bool, default False) – Change between degrees and radian. Default is radian. +If plot_style="colorwheel", then setting degrees=True will convert the angle unit to degree from the default radians.

    • -
    • angle_offset (float, default None) – If using vector_rep=”angle” or plot_style=”contour”, this angle +

    • angle_offset (float, default None) – If using vector_rep="angle" or plot_style="contour", this angle will rotate the vector angles displayed by the given amount. Useful when you want to offset the angle of the atom planes relative to the polarisation.

    • -
    • save (string, default "polarisation_image") – If set to save=None, the image will not be saved.

    • +
    • save (string) – If set to save=None, the image will not be saved.

    • title (string, default "") – Title of the plot.

    • -
    • color (string, default "r") – Color of the arrows when `plot_style=”vector” or β€œcontour”.

    • -
    • cmap (matplotlib colormap, default "viridis") – Matplotlib cmap used for the vector arrows.

    • -
    • alpha (float, default 1.0) – Transparency of the matplotlib cmap. For plot_style=”colormap” and -plot_style=”colorwheel”, this alpha applies to the vector arrows. -For plot_style=”contour” this alpha applies to the tricontourf map.

    • +
    • color (string, default "r") – Color of the arrows when plot_style="vector" or "contour".

    • +
    • cmap (matplotlib colormap, default "viridis") – Matplotlib cmap used for the vector arrows.

    • +
    • alpha (float, default 1.0) – Transparency of the matplotlib cmap. For plot_style="colormap" and +plot_style="colorwheel", this alpha applies to the vector arrows. +For plot_style="contour" this alpha applies to the tricontourf map.

    • image_cmap (matplotlib colormap, default 'gray') – Matplotlib cmap that will be used for the overlay image.

    • -
    • monitor_dpi (int, default 96) – The DPI of the monitor, generally 96 pixels. Used to scale the image +

    • monitor_dpi (int, default 96) – The DPI of the monitor, generally 96 pixels. Used to scale the image so that large images render correctly. Use a smaller value to enlarge -too-small images. monitor_dpi=None will ignore this param.

    • -
    • no_axis_info (Bool, default True) – This will remove the x and y axis labels and ticks from the plot if set +too-small images. monitor_dpi=None will ignore this param.

    • +
    • no_axis_info (bool, default True) – This will remove the x and y axis labels and ticks from the plot if set to True.

    • -
    • invert_y_axis (Bool, default True) – If set to true, this will flip the y axis, effectively setting the top +

    • invert_y_axis (bool, default True) – If set to true, this will flip the y axis, effectively setting the top left corner of the image as the (0, 0) origin, as in scanning electron microscopy images.

    • ticks (colorbar ticks, default None) – None or list of ticks or Locator If None, ticks are determined automatically from the input.

    • -
    • scalebar (Bool or dict, default False) – Add a matplotlib-scalebar to the plot. If set to True the scalebar will -appear similar to that given by Hyperspy’s plot() function. A custom +

    • scalebar (bool or dict, default False) – Add a matplotlib-scalebar to the plot. If set to True the scalebar will +appear similar to that given by Hyperspy’s plot() function. A custom scalebar can be included as a dictionary and more custom options can be found in the matplotlib-scalebar package. See below for an example.

    • -
    • antialiased (Bool, default False) – Applies only to plot_style=”contour”. Essentially removes the +

    • antialiased (bool, default False) – Applies only to plot_style="contour". Essentially removes the border between regions in the tricontourf map.

    • -
    • levels (int, default 20) – Number of Matplotlib tricontourf levels to be used.

    • -
    • remove_vectors (Bool, default False) – Applies only to plot_style=”contour”. If set to True, do not plot +

    • levels (int, default 20) – Number of Matplotlib tricontourf levels to be used.

    • +
    • remove_vectors (bool, default False) – Applies only to plot_style="contour". If set to True, do not plot the vector arrows.

    • quiver_units (string, default 'width') – The units parameter from the matplotlib quiver function, not to be -confused with the units parameter above for the image units.

    • +confused with the units parameter above for the image units.

    • parameters (ax.quiver) – See matplotlib’s quiver function for the remaining parameters.

    @@ -1279,7 +1007,7 @@

    ModulesExamples

    -
    >>> from temul.polarisation import plot_polarisation_vectors
    +
    >>> import temul.api as tml
     >>> from temul.dummy_data import get_polarisation_dummy_dataset
     >>> atom_lattice = get_polarisation_dummy_dataset()
     >>> sublatticeA = atom_lattice.sublattice_list[0]
    @@ -1294,7 +1022,7 @@ 

    Modules
    >>> ax = plot_polarisation_vectors(x, y, u, v, image=sublatticeA.image,
    +
    >>> ax = tml.plot_polarisation_vectors(x, y, u, v, image=sublatticeA.image,
     ...                           unit_vector=False, save=None,
     ...                           plot_style='vector', color='r',
     ...                           overlay=False, title='Vector Arrows',
    @@ -1302,21 +1030,21 @@ 

    Modules
    >>> ax = plot_polarisation_vectors(x, y, u, v, image=sublatticeA.image,
    +
    >>> ax = tml.plot_polarisation_vectors(x, y, u, v, image=sublatticeA.image,
     ...                           unit_vector=False, save=None,
     ...                           plot_style='vector', color='r',
     ...                           overlay=True, monitor_dpi=50)
     

    vector plot with colormap viridis:

    -
    >>> ax = plot_polarisation_vectors(x, y, u, v, image=sublatticeA.image,
    +
    >>> ax = tml.plot_polarisation_vectors(x, y, u, v, image=sublatticeA.image,
     ...                           unit_vector=False, save=None,
     ...                           plot_style='colormap', monitor_dpi=50,
     ...                           overlay=False, cmap='viridis')
     
    -

    vector plot with colormap viridis, with vector_rep=”angle”:

    -
    >>> ax = plot_polarisation_vectors(x, y, u, v, image=sublatticeA.image,
    +

    vector plot with colormap viridis, with vector_rep="angle":

    +
    >>> ax = tml.plot_polarisation_vectors(x, y, u, v, image=sublatticeA.image,
     ...                           unit_vector=False, save=None,
     ...                           plot_style='colormap', monitor_dpi=50,
     ...                           overlay=False, cmap='cet_colorwheel',
    @@ -1324,7 +1052,7 @@ 

    Modules
    >>> ax = plot_polarisation_vectors(x, y, u, v, image=sublatticeA.image,
    +
    >>> ax = tml.plot_polarisation_vectors(x, y, u, v, image=sublatticeA.image,
     ...                           sampling=3.0321, units='pm', monitor_dpi=50,
     ...                           unit_vector=False, plot_style='colormap',
     ...                           overlay=True, save=None, cmap='viridis',
    @@ -1332,14 +1060,14 @@ 

    Modules
    >>> ax = plot_polarisation_vectors(x, y, u, v, image=sublatticeA.image,
    +
    >>> ax = tml.plot_polarisation_vectors(x, y, u, v, image=sublatticeA.image,
     ...                           unit_vector=True, save=None, monitor_dpi=50,
     ...                           plot_style='colormap', color='r',
     ...                           overlay=False, cmap='viridis')
     

    Change the vectors to unit vectors on a tricontourf map:

    -
    >>> ax = plot_polarisation_vectors(x, y, u, v, image=sublatticeA.image,
    +
    >>> ax = tml.plot_polarisation_vectors(x, y, u, v, image=sublatticeA.image,
     ...                           unit_vector=True, plot_style='contour',
     ...                           overlay=False, pivot='middle', save=None,
     ...                           color='darkgray', cmap='plasma',
    @@ -1347,7 +1075,7 @@ 

    Modules
    >>> ax = plot_polarisation_vectors(x, y, u, v, image=sublatticeA.image,
    +
    >>> ax = tml.plot_polarisation_vectors(x, y, u, v, image=sublatticeA.image,
     ...                           unit_vector=False, plot_style='contour',
     ...                           overlay=True, pivot='middle', save=None,
     ...                           color='red', cmap='cet_colorwheel',
    @@ -1358,7 +1086,7 @@ 

    Modules
    >>> ax = plot_polarisation_vectors(x, y, u, v, image=sublatticeA.image,
    +
    >>> ax = tml.plot_polarisation_vectors(x, y, u, v, image=sublatticeA.image,
     ...                           unit_vector=True, plot_style='contour',
     ...                           overlay=True, pivot='middle', save=None,
     ...                           cmap='cet_colorwheel',
    @@ -1369,7 +1097,7 @@ 

    Modules
    >>> import colorcet as cc
    ->>> ax = plot_polarisation_vectors(x, y, u, v, image=sublatticeA.image,
    +>>> ax = tml.plot_polarisation_vectors(x, y, u, v, image=sublatticeA.image,
     ...                           unit_vector=True, plot_style="colorwheel",
     ...                           vector_rep="angle",
     ...                           overlay=False, cmap=cc.cm.colorwheel,
    @@ -1378,7 +1106,7 @@ 

    Modules
    >>> ax = plot_polarisation_vectors(x, y, u, v, image=sublatticeA.image,
    +
    >>> ax = tml.plot_polarisation_vectors(x, y, u, v, image=sublatticeA.image,
     ...                           plot_style="polar_colorwheel",
     ...                           unit_vector=False, overlay=False,
     ...                           save=None, monitor_dpi=50)
    @@ -1388,7 +1116,7 @@ 

    Modules
    >>> scbar_dict = {"dx": 3.0321, "units": "pm", "location": "lower left",
     ...               "box_alpha":0.0, "color": "black", "scale_loc": "top"}
    ->>> ax = plot_polarisation_vectors(x, y, u, v, image=sublatticeA.image,
    +>>> ax = tml.plot_polarisation_vectors(x, y, u, v, image=sublatticeA.image,
     ...                           sampling=3.0321, units='pm', monitor_dpi=50,
     ...                           unit_vector=False, plot_style='colormap',
     ...                           overlay=False, save=None, cmap='viridis',
    @@ -1396,14 +1124,14 @@ 

    Modules
    >>> import temul.signal_plotting as tmlplot
    +
    >>> import temul.api as tml
     >>> from matplotlib.colors import from_levels_and_colors
    ->>> zest = tmlplot.hex_to_rgb(tmlplot.color_palettes('zesty'))
    +>>> zest = tml.hex_to_rgb(tml.color_palettes('zesty'))
     >>> zest.append(zest[0])  # make the -180 and 180 degree colour the same
    ->>> expanded_zest = tmlplot.expand_palette(zest, [1,2,2,2,1])
    +>>> expanded_zest = tml.expand_palette(zest, [1,2,2,2,1])
     >>> custom_cmap, _ = from_levels_and_colors(
    -...     levels=range(9), colors=tmlplot.rgb_to_dec(expanded_zest))
    ->>> ax = plot_polarisation_vectors(x, y, u, v, image=sublatticeA.image,
    +...     levels=range(9), colors=tml.rgb_to_dec(expanded_zest))
    +>>> ax = tml.plot_polarisation_vectors(x, y, u, v, image=sublatticeA.image,
     ...                           unit_vector=False, plot_style='contour',
     ...                           overlay=False, pivot='middle', save=None,
     ...                           cmap=custom_cmap, levels=9, monitor_dpi=50,
    @@ -1415,32 +1143,32 @@ 

    Modules -
    -temul.polarisation.ratio_of_lattice_spacings(sublattice, zone_axis_index_A, zone_axis_index_B, ideal_ratio_one=True, sampling=1, units='pix', vmin=None, vmax=None, cmap='inferno', title='Spacings Map', filename=None, **kwargs)ΒΆ
    +
    +temul.topotem.polarisation.ratio_of_lattice_spacings(sublattice, zone_axis_index_A, zone_axis_index_B, ideal_ratio_one=True, sampling=1, units='pix', vmin=None, vmax=None, cmap='inferno', title='Spacings Map', filename=None, **kwargs)ΒΆ

    Create a ratio map between two zone axes. Useful to see the tetragonality or shearing of unit cells.

    Parameters
    Returns
    @@ -1453,7 +1181,7 @@

    ModulesExamples

    -

    Use ideal_ratio_one=False to view the direction of tetragonality

    +

    Use ideal_ratio_one=False to view the direction of tetragonality

    >>> ratio_map = ratio_of_lattice_spacings(sublatticeA, 0, 1,
     ...                                       ideal_ratio_one=False)
     
    @@ -1470,30 +1198,32 @@

    Modules -
    -temul.polarisation.rotation_of_atom_planes(sublattice, zone_axis_index, angle_offset=None, degrees=False, sampling=None, units='pix', vmin=None, vmax=None, cmap='inferno', title='Rotation Map', filename=None, return_x_y_z=False, **kwargs)ΒΆ
    +
    +temul.topotem.polarisation.rotation_of_atom_planes(sublattice, zone_axis_index, angle_offset=None, degrees=False, sampling=None, units='pix', vmin=None, vmax=None, cmap='inferno', title='Rotation Map', plot=False, filename=None, return_x_y_z=False, **kwargs)ΒΆ

    Calculate a map of the angles between each atom along the atom planes of a zone axis.

    Parameters
    • sublattice (Atomap Sublattice object) –

    • -
    • zone_axis_index (int) – The zone axis you wish to specify. You are indexing -sublattice.zones_axis_average_distances[zone_axis_index].

    • -
    • angle_offset (float, default None) – The angle which can be considered zero degrees. Useful when the atomic +

    • zone_axis_index (int) – The zone axis you wish to specify. You are indexing +sublattice.zones_axis_average_distances[zone_axis_index].

    • +
    • angle_offset (float, default None) – The angle which can be considered zero degrees. Useful when the atomic planes are at an angle.

    • -
    • degrees (Bool, default False) – Setting to False will return angle values in radian. Setting to True +

    • degrees (bool, default False) – Setting to False will return angle values in radian. Setting to True will return angle values in degrees.

    • -
    • sampling (float, default None) – Pixel sampling of the image for calibration.

    • +
    • sampling (float, default None) – Pixel sampling of the image for calibration.

    • units (string, default "pix") – Units of the sampling.

    • vmin (see Matplotlib for details) –

    • vmax (see Matplotlib for details) –

    • cmap (see Matplotlib for details) –

    • title (string, default "Rotation Map") –

    • -
    • filename (string, optional) – If filename is set, the strain signal and plot will be saved.

    • -
    • return_x_y_z (Bool, default False) – If this is set to True, the rotation_signal (map), as well as separate +

    • plot (bool) – Set to true if the figure should be plotted.

    • +
    • filename (string, optional) – If filename is set, the signal and plot will be saved. +plot must be set to True.

    • +
    • return_x_y_z (bool, default False) – If this is set to True, the rotation_signal (map), as well as separate lists of the x, y, and angle values.

    • -
    • **kwargs (Matplotlib keyword arguments passed to imshow().) –

    • +
    • **kwargs (Matplotlib keyword arguments passed to imshow().) –

    Returns
    @@ -1505,7 +1235,7 @@

    ModulesExamples

    -

    Use angle_offset to effectively change the angle of the horizontal axis +

    Use angle_offset to effectively change the angle of the horizontal axis when calculating angles:

    >>> rotation_map = rotation_of_atom_planes(sublatticeA, 3, angle_offset=45,
     ...                                        degrees=True)
    @@ -1529,17 +1259,199 @@ 

    Modules
    +
    +temul.topotem.fft_mapping.choose_mask_coordinates(image, norm='log')ΒΆ
    +

    Pick the mask locations for an FFT. See get_masked_ifft() for examples and +commit 5ba307b5af0b598bedc0284aa989d44e23fdde4d on Atomap for more details.

    +
    +
    Parameters
    +
      +
    • image (Hyperspy 2D Signal) –

    • +
    • norm (str, default "log") – How to scale the intensity value for the displayed image. +Options are β€œlinear” and β€œlog”.

    • +
    +
    +
    Returns
    +

    +
    +
    Return type
    +

    list of pixel coordinates

    +
    +
    +
    + +
    +
    +temul.topotem.fft_mapping.choose_points_on_image(image, norm='linear', distance_threshold=4)ΒΆ
    +
    + +
    +
    +temul.topotem.fft_mapping.get_masked_ifft(image, mask_coords, mask_radius=10, image_space='real', keep_masked_area=True, plot_masked_fft=False)ΒΆ
    +

    Creates an inverse fast Fourier transform (iFFT) from an image and mask +coordinates. Use choose_mask_coordinates to manually choose mask +coordinates in the FFT.

    +
    +
    Parameters
    +
      +
    • image (Hyperspy 2D Signal) –

    • +
    • mask_coords (list of pixel coordinates) – Pixel coordinates of the masking locations. See the example below for +two simple coordinates found using choose_mask_coordinates.

    • +
    • mask_radius (int, default 10) – Radius in pixels of the mask.

    • +
    • image_space (str, default "real") – If the input image is in Fourier/diffraction/reciprocal space already, +set space=”fourier”.

    • +
    • keep_masked_area (bool, default True) – If True, this will set the mask at the mask_coords. +If False, this will set the mask as everything other than the +mask_coords. Can be thought of as inversing the mask.

    • +
    • plot_masked_fft (bool, default False) – If True, the mask used to filter the FFT will be plotted. Good for +checking that the mask is doing what you want. Can fail sometimes due +to matplotlib plotting issues.

    • +
    +
    +
    Returns
    +

    +
    +
    Return type
    +

    Inverse FFT as a Hyperspy 2D Signal

    +
    +
    +

    Examples

    +
    >>> from temul.dummy_data import get_simple_cubic_signal
    +>>> import temul.api as tml
    +>>> image = get_simple_cubic_signal()
    +>>> mask_coords = tml.choose_mask_coordinates(image) #  manually
    +>>> mask_coords = [[170.2, 170.8],[129.8, 130]]
    +>>> image_ifft = tml.get_masked_ifft(image, mask_coords)
    +>>> image_ifft.plot()
    +
    +
    +

    Plot the masked fft:

    +
    >>> image_ifft = tml.get_masked_ifft(image, mask_coords,
    +...                                  plot_masked_fft=True)
    +
    +
    +

    Use unmasked fft area and plot the masked fft:

    +
    >>> image_ifft = tml.get_masked_ifft(
    +...     image, mask_coords, plot_masked_fft=True, keep_masked_area=False)
    +>>> image_ifft.plot()
    +
    +
    +

    If the input image is already a Fourier transform:

    +
    >>> fft_image = image.fft(shift=True)
    +>>> image_ifft = tml.get_masked_ifft(fft_image, mask_coords,
    +...     image_space='fourier')
    +>>> image_ifft.plot()
    +
    +
    +
    + +
    +
    +temul.topotem.lattice_structure_tools.calculate_atom_plane_curvature(sublattice, zone_vector_index, func='strain_grad', atom_planes=None, sampling=None, units='pix', vmin=None, vmax=None, cmap='inferno', title='Curvature Map', filename=None, plot=False, return_fits=False, **kwargs)ΒΆ
    +

    Calculates the curvature of the sublattice atom planes along the direction +given by zone_vector_index. In the case of [2]_. below, the curvature is +the inverse of the radius of curvature, and is effectively equal to the +second derivative of the displacement direction of the atoms. Because the +first derivative is negligible, the curvature can be calculated as the +strain gradient 3. +With the parameter func="strain_grad", this function calculates the strain +gradient of the atom planes of a Atomap Sublattice object.

    +
    +
    Parameters
    +
      +
    • sublattice (Atomap Sublattice object) –

    • +
    • zone_vector_index (int) – The index of the zone axis (translation symmetry) found by the Atomap +function construct_zone_axes().

    • +
    • func ('strain_grad' or function) – Function that can be used by scipy.optimize.curve_fit. If +func=’strain_grad’, then the +temul.topotem.lattice_structure_tools.sine_wave_function_strain_gradient +function will be used.

    • +
    • atom_planes (tuple, optional) – The starting and ending atom plane to be computed. Useful if only a +section of the image should be fitted with sine waves. Given in the +form e.g., (0, 3).

    • +
    • sampling (float, optional) – sampling of an image in units of units/pix

    • +
    • units (string, default "pix") – Units of sampling, for display purposes.

    • +
    • vmin (see Matplotlib documentation, default None) –

    • +
    • vmax (see Matplotlib documentation, default None) –

    • +
    • cmap (see Matplotlib documentation, default None) –

    • +
    • title (string, default 'Curvature Map') –

    • +
    • filename (string, default None) – Name of the file to be saved.

    • +
    • plot (bool, default False) – If set to True, each atom plane fitting will be plotted along with its +respective atom positions. The fitting parameters (popt) will be +returned as a list.

    • +
    • return_fits (bool, default False) – If set to True, each atom plane fitting will be plotted along with its +respective atom positions. The fitting parameters (popt) will be +returned as a list.

    • +
    • **kwargs – keyword arguments to be passed to scipy.optimize.curve_fit.

    • +
    +
    +
    +

    Examples

    +
    >>> from temul.dummy_data import sine_wave_sublattice
    +>>> import temul.api as tml
    +>>> sublattice = sine_wave_sublattice()
    +>>> sublattice.construct_zone_axes(atom_plane_tolerance=1)
    +>>> sublattice.plot()
    +>>> sampling = 0.05 #  nm/pix
    +>>> cmap='bwr'
    +>>> curvature_map = tml.calculate_atom_plane_curvature(sublattice,
    +...         zone_vector_index=0, sampling=sampling, units='nm', cmap=cmap)
    +
    +
    +

    Just compute several atom planes:

    +
    >>> curvature_map = tml.calculate_atom_plane_curvature(sublattice, 0,
    +...         atom_planes=(0,3), sampling=sampling, units='nm', cmap=cmap)
    +
    +
    +

    You can also provide initial fitting estimations via scipy’s curve_fit:

    +
    >>> p0 = [2, 1, 1, 15]
    +>>> kwargs = {'p0': p0}
    +>>> curvature_map, fittings = tml.calculate_atom_plane_curvature(
    +...     sublattice, zone_vector_index=0, atom_planes=(0,3),
    +...     sampling=sampling, units='nm', cmap=cmap, return_fits=True,
    +...     **kwargs)
    +
    +
    +
    +
    Returns
    +

    +
    +
    Return type
    +

    Curvature Map as a Hyperspy Signal2D

    +
    +
    +

    References

    +
    +
    2
    +

    Function adapted from a script written by +Dr. Marios Hadjimichael, and used in paper_name. The original +MATLAB script can be found in +TEMUL/publication_examples/PTO_marios_hadj

    +
    +
    3
    +

    Landau and Lifshitz, Theory of Elasticity, Vol 7, +pp 47-49, 1981

    +
    +
    +
    + +
    +
    +temul.topotem.lattice_structure_tools.sine_wave_function_strain_gradient(x, a, b, c, d)ΒΆ
    +
    +

    Element ToolsΒΆ

    -
    -temul.element_tools.atomic_radii_in_pixels(sampling, element_symbol)ΒΆ
    +
    +temul.element_tools.atomic_radii_in_pixels(sampling, element_symbol)ΒΆ

    Get the atomic radius of an element in pixels, scaled by an image sampling

    Parameters
      -
    • sampling (float, default None) – sampling of an image in units of nm/pix

    • +
    • sampling (float, default None) – sampling of an image in units of nm/pix

    • element_symbol (string, default None) – Symbol of an element from the periodic table of elements

    @@ -1571,15 +1483,15 @@

    Modules -
    -temul.element_tools.combine_element_lists(lists)ΒΆ
    +
    +temul.element_tools.combine_element_lists(lists)ΒΆ

    Reduce multiple element_lists into one list of strings from a list of -lists, useful for the Model Refiner flattened_element_list.

    +lists, useful for the Model Refiner flattened_element_list.

    -
    -temul.element_tools.get_and_return_element(element_symbol)ΒΆ
    +
    +temul.element_tools.get_and_return_element(element_symbol)ΒΆ

    From the elemental symbol, e.g., β€˜H’ for Hydrogen, provides Hydrogen as a periodictable.core.Element object for further use.

    @@ -1611,8 +1523,8 @@

    Modules -
    -temul.element_tools.get_individual_elements_from_element_list(element_list, split_symbol=['_', '.'])ΒΆ
    +
    +temul.element_tools.get_individual_elements_from_element_list(element_list, split_symbol=['_', '.'])ΒΆ

    Examples

    Single list

    >>> import temul.element_tools as tml_el
    @@ -1640,8 +1552,8 @@ 

    Modules -
    -temul.element_tools.split_and_sort_element(element, split_symbol=['_', '.'])ΒΆ
    +
    +temul.element_tools.split_and_sort_element(element, split_symbol=['_', '.'])ΒΆ

    Extracts info from input atomic column element configuration Split an element and its count, then sort the element for use with other functions.

    @@ -1688,15 +1600,15 @@

    Modules

    Intensity ToolsΒΆ

    -
    -temul.intensity_tools.get_pixel_count_from_image_slice(self, image_data, percent_to_nn=0.4)ΒΆ
    +
    +temul.intensity_tools.get_pixel_count_from_image_slice(self, image_data, percent_to_nn=0.4)ΒΆ

    Fid the number of pixels in an area when calling _get_image_slice_around_atom()

    Parameters
    • image_data (Numpy 2D array) –

    • -
    • percent_to_nn (float, default 0.40) – Determines the boundary of the area surrounding each atomic +

    • percent_to_nn (float, default 0.40) – Determines the boundary of the area surrounding each atomic column, as fraction of the distance to the nearest neighbour.

    @@ -1719,8 +1631,8 @@

    Modules -
    -temul.intensity_tools.get_sublattice_intensity(sublattice, intensity_type='max', remove_background_method=None, background_sub=None, num_points=3, percent_to_nn=0.4, mask_radius=None)ΒΆ
    +
    +temul.intensity_tools.get_sublattice_intensity(sublattice, intensity_type='max', remove_background_method=None, background_sub=None, num_points=3, percent_to_nn=0.4, mask_radius=None)ΒΆ

    Finds the intensity for each atomic column using either max, mean, min, total or all of them at once.

    The intensity values are taken from the area defined by @@ -1740,11 +1652,11 @@

    Modulesint, default 3) – If remove_background_method=”local”, num_points is the number +
  • num_points (int, default 3) – If remove_background_method=”local”, num_points is the number of nearest neighbour values averaged from background_sub

  • -
  • percent_to_nn (float, default 0.40) – Determines the boundary of the area surrounding each atomic +

  • percent_to_nn (float, default 0.40) – Determines the boundary of the area surrounding each atomic column, as fraction of the distance to the nearest neighbour.

  • -
  • mask_radius (float) – Radius of the atomic column in pixels. If chosen, percent_to_nn must +

  • mask_radius (float) – Radius of the atomic column in pixels. If chosen, percent_to_nn must be None.

  • @@ -1752,7 +1664,7 @@

    Modules

    Return type
    -

    Numpy array, shape depending on intensity_type

    +

    Numpy array, shape depending on intensity_type

    Examples

    @@ -1796,8 +1708,8 @@

    Modules -
    -temul.intensity_tools.remove_average_background(sublattice, intensity_type, background_sub, percent_to_nn=0.4, mask_radius=None)ΒΆ
    +
    +temul.intensity_tools.remove_average_background(sublattice, intensity_type, background_sub, percent_to_nn=0.4, mask_radius=None)ΒΆ

    Remove the average background from a sublattice intensity using a background sublattice.

    @@ -1807,9 +1719,9 @@

    Modulesfloat, default 0.4) – Determines the boundary of the area surrounding each atomic +
  • percent_to_nn (float, default 0.4) – Determines the boundary of the area surrounding each atomic column, as fraction of the distance to the nearest neighbour.

  • -
  • mask_radius (float) – Radius of the atomic column in pixels. If chosen, percent_to_nn must +

  • mask_radius (float) – Radius of the atomic column in pixels. If chosen, percent_to_nn must be None.

  • @@ -1817,7 +1729,7 @@

    Modules

    Return type
    -

    Numpy array, shape depending on intensity_type

    +

    Numpy array, shape depending on intensity_type

    Examples

    @@ -1837,8 +1749,8 @@

    Modules -
    -temul.intensity_tools.remove_local_background(sublattice, background_sub, intensity_type, num_points=3, percent_to_nn=0.4, mask_radius=None)ΒΆ
    +
    +temul.intensity_tools.remove_local_background(sublattice, background_sub, intensity_type, num_points=3, percent_to_nn=0.4, mask_radius=None)ΒΆ

    Remove the local background from a sublattice intensity using a background sublattice.

    @@ -1848,11 +1760,11 @@

    Modulesint, default 3) – The number of nearest neighbour values averaged from +
  • num_points (int, default 3) – The number of nearest neighbour values averaged from background_sub

  • -
  • percent_to_nn (float, default 0.40) – Determines the boundary of the area surrounding each atomic +

  • percent_to_nn (float, default 0.40) – Determines the boundary of the area surrounding each atomic column, as fraction of the distance to the nearest neighbour.

  • -
  • mask_radius (float) – Radius of the atomic column in pixels. If chosen, percent_to_nn must +

  • mask_radius (float) – Radius of the atomic column in pixels. If chosen, percent_to_nn must be None.

  • @@ -1860,7 +1772,7 @@

    Modules

    Return type
    -

    Numpy array, shape depending on intensity_type

    +

    Numpy array, shape depending on intensity_type

    Examples

    @@ -1882,13 +1794,13 @@

    Modules

    Model CreationΒΆ

    -
    -temul.model_creation.assign_z_height(sublattice, lattice_type, material)ΒΆ
    +
    +temul.model_creation.assign_z_height(sublattice, lattice_type, material)ΒΆ
    -
    -temul.model_creation.assign_z_height_to_sublattice(sublattice, z_bond_length, material=None, fractional_coordinates=True, atom_layout='bot')ΒΆ
    +
    +temul.model_creation.assign_z_height_to_sublattice(sublattice, z_bond_length, material=None, fractional_coordinates=True, atom_layout='bot')ΒΆ

    Set the z_heights for each atom position in a sublattice.

    Parameters
    @@ -1900,8 +1812,8 @@

    Modules -
    -temul.model_creation.auto_generate_sublattice_element_list(material_type, elements='Au', max_number_atoms_z=10)ΒΆ
    +
    +temul.model_creation.auto_generate_sublattice_element_list(material_type, elements='Au', max_number_atoms_z=10)ΒΆ

    Example

    >>> element_list = auto_generate_sublattice_element_list(
     ...                     material_type='nanoparticle',
    @@ -1912,8 +1824,8 @@ 

    Modules -
    -temul.model_creation.change_sublattice_atoms_via_intensity(sublattice, image_diff_array, darker_or_brighter, element_list, verbose=False)ΒΆ
    +
    +temul.model_creation.change_sublattice_atoms_via_intensity(sublattice, image_diff_array, darker_or_brighter, element_list, verbose=False)ΒΆ

    Change the elements in a sublattice object to a higher or lower combined atomic (Z) number. The aim is to change the sublattice elements so that the experimental image @@ -1932,15 +1844,15 @@

    Modulesint) – if the element should have a lower combined atomic Z number, +
  • darker_or_brighter (int) – if the element should have a lower combined atomic Z number, darker_or_brighter = 0. if the element should have a higher combined atomic Z number, darker_or_brighter = 1 In other words, the image_diff_array will change the given sublattice elements to darker or brighter spots by choosing 0 and 1, respectively.

  • -
  • element_list (list) – list of element configurations

  • -
  • verbose (Bool, default False) – If set to True then atom warnings will be printed as output.

  • +
  • element_list (list) – list of element configurations

  • +
  • verbose (bool, default False) – If set to True then atom warnings will be printed as output.

  • @@ -1966,8 +1878,8 @@

    Modules -
    -temul.model_creation.change_sublattice_pseudo_inplace(new_atom_positions, old_sublattice)ΒΆ
    +
    +temul.model_creation.change_sublattice_pseudo_inplace(new_atom_positions, old_sublattice)ΒΆ

    Create and return a new Sublattice object which is a copy of old_sublattice except with extra atom positions set with new_atom_positions.

    @@ -2017,8 +1929,8 @@

    Modules -
    -temul.model_creation.compare_count_atoms_in_sublattice_list(counter_list)ΒΆ
    +
    +temul.model_creation.compare_count_atoms_in_sublattice_list(counter_list)ΒΆ

    Compare the count of atomap elements in two counter_lists gotten by count_atoms_in_sublattice_list()

    If the counters are the same, then the original atom_lattice is the @@ -2030,7 +1942,7 @@

    ModulesReturns

      -
    • Boolean True if the counters are equal,

    • +
    • boolean True if the counters are equal,

    • boolean False is the counters are not equal.

    @@ -2072,8 +1984,8 @@

    Modules -
    -temul.model_creation.convert_numpy_z_coords_to_z_height_string(z_coords)ΒΆ
    +
    +temul.model_creation.convert_numpy_z_coords_to_z_height_string(z_coords)ΒΆ

    Convert from the output of return_z_coordinates(), which is a 1D numpy array, to a long string, with which I have set up sublattice.atom_list[i].z_height.

    @@ -2088,19 +2000,19 @@

    Modules -
    -temul.model_creation.correct_background_elements(sublattice)ΒΆ
    +
    +temul.model_creation.correct_background_elements(sublattice)ΒΆ

    -
    -temul.model_creation.count_all_individual_elements(individual_element_list, dataframe)ΒΆ
    +
    +temul.model_creation.count_all_individual_elements(individual_element_list, dataframe)ΒΆ

    Perform count_element_in_pandas_df() for all elements in a dataframe. Specify the elements you wish to count in the individual_element_list.

    Parameters
      -
    • individual_element_list (list) –

    • +
    • individual_element_list (list) –

    • dataframe (pandas dataframe) – The dataframe must have column headers as elements or element configurations

    @@ -2126,8 +2038,8 @@

    Modules -
    -temul.model_creation.count_atoms_in_sublattice_list(sublattice_list, filename=None)ΒΆ
    +
    +temul.model_creation.count_atoms_in_sublattice_list(sublattice_list, filename=None)ΒΆ

    Count the elements in a list of Atomap sublattices

    Parameters
    @@ -2169,8 +2081,8 @@

    Modules -
    -temul.model_creation.count_element_in_pandas_df(element, dataframe)ΒΆ
    +
    +temul.model_creation.count_element_in_pandas_df(element, dataframe)ΒΆ

    Count the number of a single element in a dataframe

    Parameters
    @@ -2201,8 +2113,8 @@

    Modules -
    -temul.model_creation.create_dataframe_for_cif(sublattice_list, element_list)ΒΆ
    +
    +temul.model_creation.create_dataframe_for_cif(sublattice_list, element_list)ΒΆ

    Outputs a dataframe from the inputted sublattice(s), which can then be input to temul.io.write_cif_from_dataframe().

    @@ -2216,8 +2128,8 @@

    Modules -
    -temul.model_creation.find_middle_and_edge_intensities(sublattice, element_list, standard_element, scaling_exponent, largest_element_intensity=None, split_symbol=['_', '.'])ΒΆ
    +
    +temul.model_creation.find_middle_and_edge_intensities(sublattice, element_list, standard_element, scaling_exponent, largest_element_intensity=None, split_symbol=['_', '.'])ΒΆ

    Create a list which represents the peak points of the intensity distribution for each atom.

    works for nanoparticles as well, doesn’t matter what @@ -2229,18 +2141,18 @@

    Modules -
    -temul.model_creation.find_middle_and_edge_intensities_for_background(elements_from_sub1, elements_from_sub2, sub1_mode, sub2_mode, element_list_sub1, element_list_sub2, middle_intensity_list_sub1, middle_intensity_list_sub2)ΒΆ
    +
    +temul.model_creation.find_middle_and_edge_intensities_for_background(elements_from_sub1, elements_from_sub2, sub1_mode, sub2_mode, element_list_sub1, element_list_sub2, middle_intensity_list_sub1, middle_intensity_list_sub2)ΒΆ

    -
    -temul.model_creation.get_max_number_atoms_z(sublattice)ΒΆ
    +
    +temul.model_creation.get_max_number_atoms_z(sublattice)ΒΆ
    -
    -temul.model_creation.get_most_common_sublattice_element(sublattice, info='element')ΒΆ
    +
    +temul.model_creation.get_most_common_sublattice_element(sublattice, info='element')ΒΆ

    Find the most common element configuration in a sublattice.

    Parameters
    @@ -2276,13 +2188,13 @@

    Modules -
    -temul.model_creation.get_positions_from_sublattices(sublattice_list)ΒΆ
    +
    +temul.model_creation.get_positions_from_sublattices(sublattice_list)ΒΆ

    -
    -temul.model_creation.image_difference_intensity(sublattice, sim_image, element_list, filename=None, percent_to_nn=0.4, mask_radius=None, change_sublattice=False, verbose=False)ΒΆ
    +
    +temul.model_creation.image_difference_intensity(sublattice, sim_image, element_list, filename=None, percent_to_nn=0.4, mask_radius=None, change_sublattice=False, verbose=False)ΒΆ

    Find the differences in a sublattice’s atom_position intensities. Change the elements of these atom_positions depending on this difference of intensities.

    @@ -2294,18 +2206,18 @@

    Moduleslist) – list of element configurations, used for refinement

  • +
  • element_list (list) – list of element configurations, used for refinement

  • filename (string, default None) – name with which the image will be saved

  • -
  • percent_to_nn (float, default 0.40) – Determines the boundary of the area surrounding each atomic +

  • percent_to_nn (float, default 0.40) – Determines the boundary of the area surrounding each atomic column, as fraction of the distance to the nearest neighbour.

  • -
  • mask_radius (float, default None) – Radius of the mask around each atom. If this is not set, +

  • mask_radius (float, default None) – Radius of the mask around each atom. If this is not set, the radius will be the distance to the nearest atom in the -same sublattice times the percent_to_nn value. -Note: if mask_radius is not specified, the Atom_Position objects +same sublattice times the percent_to_nn value. +Note: if mask_radius is not specified, the Atom_Position objects must have a populated nearest_neighbor_list.

  • -
  • change_sublattice (bool, default False) – If change_sublattice is set to True, all incorrect element assignments +

  • change_sublattice (bool, default False) – If change_sublattice is set to True, all incorrect element assignments will be corrected inplace.

  • -
  • verbose (Bool, default False) – If set to True then atom warnings will be printed as output.

  • +
  • verbose (bool, default False) – If set to True then atom warnings will be printed as output.

  • @@ -2339,8 +2251,8 @@

    Modules -
    -temul.model_creation.image_difference_position(sublattice, sim_image, pixel_threshold, comparison_sublattice_list=None, filename=None, percent_to_nn=0.4, mask_radius=None, num_peaks=5, inplace=True)ΒΆ
    +
    +temul.model_creation.image_difference_position(sublattice, sim_image, pixel_threshold, comparison_sublattice_list=None, filename=None, percent_to_nn=0.4, mask_radius=None, num_peaks=5, inplace=True)ΒΆ

    Find new atomic coordinates by comparing experimental to simulated image. Changes the sublattice inplace using change_sublattice_pseudo_inplace.

    The aim is to change the sublattice elements so that the experimental image @@ -2351,32 +2263,32 @@

    Modules
    • sublattice (Atomap sublattice object) –

    • sim_image (simulated image used for comparison with sublattice image) –

    • -
    • pixel_threshold (int) – minimum pixel distance from current sublattice atoms. If the new atomic +

    • pixel_threshold (int) – minimum pixel distance from current sublattice atoms. If the new atomic coordinates are greater than this distance, they will be created. Choose a pixel_threshold that will not create new atoms in unrealistic positions.

    • filename (string, default None) – name with which the image will be saved

    • -
    • percent_to_nn (float, default 0.40) – Determines the boundary of the area surrounding each atomic +

    • percent_to_nn (float, default 0.40) – Determines the boundary of the area surrounding each atomic column, as fraction of the distance to the nearest neighbour.

    • -
    • mask_radius (float, default None) – Radius of the mask around each atom. If this is not set, +

    • mask_radius (float, default None) – Radius of the mask around each atom. If this is not set, the radius will be the distance to the nearest atom in the -same sublattice times the percent_to_nn value. -Note: if mask_radius is not specified, the Atom_Position objects +same sublattice times the percent_to_nn value. +Note: if mask_radius is not specified, the Atom_Position objects must have a populated nearest_neighbor_list.

    • -
    • num_peaks (int, default 5) – number of new atoms to add

    • -
    • add_sublattice (bool, default False) – If set to True, a new sublattice will be created and returned. +

    • num_peaks (int, default 5) – number of new atoms to add

    • +
    • add_sublattice (bool, default False) – If set to True, a new sublattice will be created and returned. The reason it is set to False is so that one can check if new atoms would be added with the given parameters.

    • sublattice_name (string, default 'sub_new') – the outputted sublattice object name and sublattice.name the new sublattice will be given

    • -
    • inplace (Bool, default True) – If set to True, the input sublattice will be changed inplace and the +

    • inplace (bool, default True) – If set to True, the input sublattice will be changed inplace and the sublattice returned. If set to False, these changes will be output only to a new sublattice.

    Returns

      -
    • Atomap Sublattice object if inplace=False. See the inplace parameter

    • +
    • Atomap Sublattice object if inplace=False. See the inplace parameter

    • for details.

    @@ -2414,8 +2326,8 @@

    Modules -
    -temul.model_creation.image_difference_position_new_sub(sublattice_list, sim_image, pixel_threshold, filename=None, percent_to_nn=0.4, mask_radius=None, num_peaks=5, add_sublattice=False, sublattice_name='sub_new')ΒΆ
    +
    +temul.model_creation.image_difference_position_new_sub(sublattice_list, sim_image, pixel_threshold, filename=None, percent_to_nn=0.4, mask_radius=None, num_peaks=5, add_sublattice=False, sublattice_name='sub_new')ΒΆ

    Find new atomic coordinates by comparing experimental to simulated image. Create a new sublattice to store the new atomic coordinates.

    The aim is to change the sublattice elements so that the experimental image @@ -2425,20 +2337,20 @@

    Modules
    • sublattice_list (list of atomap sublattice objects) –

    • sim_image (simulated image used for comparison with sublattice image) –

    • -
    • pixel_threshold (int) – minimum pixel distance from current sublattice atoms. If the new atomic +

    • pixel_threshold (int) – minimum pixel distance from current sublattice atoms. If the new atomic coordinates are greater than this distance, they will be created. Choose a pixel_threshold that will not create new atoms in unrealistic positions.

    • filename (string, default None) – name with which the image will be saved

    • -
    • percent_to_nn (float, default 0.40) – Determines the boundary of the area surrounding each atomic +

    • percent_to_nn (float, default 0.40) – Determines the boundary of the area surrounding each atomic column, as fraction of the distance to the nearest neighbour.

    • -
    • mask_radius (float, default None) – Radius of the mask around each atom. If this is not set, +

    • mask_radius (float, default None) – Radius of the mask around each atom. If this is not set, the radius will be the distance to the nearest atom in the -same sublattice times the percent_to_nn value. -Note: if mask_radius is not specified, the Atom_Position objects +same sublattice times the percent_to_nn value. +Note: if mask_radius is not specified, the Atom_Position objects must have a populated nearest_neighbor_list.

    • -
    • num_peaks (int, default 5) – number of new atoms to add

    • -
    • add_sublattice (bool, default False) – If set to True, a new sublattice will be created and returned. +

    • num_peaks (int, default 5) – number of new atoms to add

    • +
    • add_sublattice (bool, default False) – If set to True, a new sublattice will be created and returned. The reason it is set to False is so that one can check if new atoms would be added with the given parameters.

    • sublattice_name (string, default 'sub_new') – the outputted sublattice object name and sublattice.name the new @@ -2485,20 +2397,20 @@

      Modules -
      -temul.model_creation.print_sublattice_elements(sublattice, number_of_lines='all')ΒΆ
      +
      +temul.model_creation.print_sublattice_elements(sublattice, number_of_lines='all')ΒΆ
      -
      -temul.model_creation.return_xyz_coordinates(x, y, z_thickness, z_bond_length, number_atoms_z=None, fractional_coordinates=True, atom_layout='bot')ΒΆ
      +
      +temul.model_creation.return_xyz_coordinates(x, y, z_thickness, z_bond_length, number_atoms_z=None, fractional_coordinates=True, atom_layout='bot')ΒΆ

      Produce xyz coordinates for an xy coordinate given the z-dimension information.

      Parameters
        -
      • x (float) – atom position coordinates.

      • -
      • y (float) – atom position coordinates.

      • +
      • x (float) – atom position coordinates.

      • +
      • y (float) – atom position coordinates.

      • other parameters see return_z_coordinates() (for) –

      @@ -2519,8 +2431,8 @@

      Modules -
      -temul.model_creation.return_z_coordinates(z_thickness, z_bond_length, number_atoms_z=None, max_number_atoms_z=None, fractional_coordinates=True, atom_layout='bot')ΒΆ
      +
      +temul.model_creation.return_z_coordinates(z_thickness, z_bond_length, number_atoms_z=None, max_number_atoms_z=None, fractional_coordinates=True, atom_layout='bot')ΒΆ

      Produce fractional z-dimension coordinates for a given thickness and bond length.

      @@ -2531,7 +2443,7 @@

      Modulesbool, default True) – If set to True, the z_coordinates will be centered about 0.5. If set to False, the z_coordinate will start at 0.0.

    @@ -2549,23 +2461,19 @@

    Modules -
    -temul.model_creation.scaling_z_contrast(numerator_sublattice, numerator_element, denominator_sublattice, denominator_element, intensity_type, method, remove_background_method, background_sublattice, num_points, percent_to_nn=0.4, mask_radius=None, split_symbol='_')ΒΆ
    +
    +temul.model_creation.scaling_z_contrast(numerator_sublattice, numerator_element, denominator_sublattice, denominator_element, intensity_type, method, remove_background_method, background_sublattice, num_points, percent_to_nn=0.4, mask_radius=None, split_symbol='_')ΒΆ

    Find new atomic coordinates by comparing experimental to simulated image. Create a new sublattice to store the new atomic coordinates.

    The aim is to change the sublattice elements so that the experimental image -agrees with the simulated image in a realistic manner.

    +agrees with the simulated image in a realistic manner. See [2]_

    Parameters
      -
    • numerator_sublattice (Sublattice object) – Sublattice from which the numerator intensity will be calculated -according to Reference [1].

    • -
    • numerator_element (string) – Element from which the numerator atomic number will be taken -according to Reference [1].

    • -
    • denominator_sublattice (Sublattice object) – Sublattice from which the denominator intensity will be calculated -according to Reference [1].

    • -
    • denominator_element (string) – Element from which the denominator atomic number will be taken -according to Reference [1].

    • +
    • numerator_sublattice (Sublattice object) – Sublattice from which the numerator intensity will be calculated.

    • +
    • numerator_element (string) – Element from which the numerator atomic number will be taken.

    • +
    • denominator_sublattice (Sublattice object) – Sublattice from which the denominator intensity will be calculated.

    • +
    • denominator_element (string) – Element from which the denominator atomic number will be taken.

    • intensity_type (string) – Determines the method used to find the sublattice intensities. The available methods are β€œmax”, β€œmean”, β€œmin”, β€œtotal” and β€œall”.

    • @@ -2574,11 +2482,11 @@

      Modulesint) – If remove_background_method=”local”, num_points is the number +
    • num_points (int) – If remove_background_method=”local”, num_points is the number of nearest neighbour values averaged from background_sublattice.

    • -
    • percent_to_nn (float, default 0.40) – Determines the boundary of the area surrounding each atomic +

    • percent_to_nn (float, default 0.40) – Determines the boundary of the area surrounding each atomic column, as fraction of the distance to the nearest neighbour.

    • -
    • mask_radius (float) – Radius of the atomic column in pixels. If chosen, percent_to_nn must +

    • mask_radius (float) – Radius of the atomic column in pixels. If chosen, percent_to_nn must be None.

    • split_symbol (string, default '_') – The symbols used to split the element into its name and count. @@ -2598,8 +2506,8 @@

      ModulesReferences

      -
      1
      -

      Reference: Krivanek et al. Nature 464, 10.1038/nature08879, (2010)

      +
      2
      +

      Krivanek et al. Nature 464, 10.1038/nature08879, (2010)

      Examples

      @@ -2636,172 +2544,19 @@

      Modules -
      -temul.model_creation.sort_sublattice_intensities(sublattice, intensity_type='max', element_list=[], scalar_method='mode', middle_intensity_list=None, limit_intensity_list=None, remove_background_method=None, background_sublattice=None, num_points=3, intensity_list_real=False, percent_to_nn=0.4, mask_radius=None)ΒΆ
      +
      +temul.model_creation.sort_sublattice_intensities(sublattice, intensity_type='max', element_list=[], scalar_method='mode', middle_intensity_list=None, limit_intensity_list=None, remove_background_method=None, background_sublattice=None, num_points=3, intensity_list_real=False, percent_to_nn=0.4, mask_radius=None)ΒΆ

    -
    -

    Image Simulation FunctionsΒΆ

    -
    -
    -temul.simulations.image_refine_via_intensity_loop(atom_lattice, change_sublattice, calibration_separation, calibration_area, percent_to_nn, mask_radius, element_list, image_sampling, iterations, delta_image_filter, image_size_x_nm, image_size_y_nm, image_size_z_nm, simulation_filename, filename, intensity_type, intensity_refine_name='intensity_refine_', folder_name='refinement_of_intensity')ΒΆ
    -
    - -
    -
    -temul.simulations.image_refine_via_position_loop(image, sublattice_list, filename, xyz_filename, add_sublattice, pixel_threshold, num_peaks, image_size_x_nm, image_size_y_nm, image_size_z_nm, calibration_area, calibration_separation, element_list, element_list_new_sub, middle_intensity_list, limit_intensity_list, delta_image_filter=0.5, intensity_type='max', scalar_method='mode', remove_background_method=None, background_sublattice=None, num_points=3, percent_to_nn=0.4, mask_radius=None, iterations=10, max_sigma=10, E0=60000.0, integrationAngleMin=0.085, integrationAngleMax=0.186, interpolationFactor=16, realspacePixelSize=0.0654, numFP=1, probeSemiangle=0.03, alphaBeamMax=0.032, scanWindowMin=0.0, scanWindowMax=1.0, algorithm='prism', numThreads=2)ΒΆ
    -

    Image Position Loop

    -
    - -
    -
    -temul.simulations.simulate_and_calibrate_with_prismatic(xyz_filename, filename, reference_image, calibration_area, calibration_separation, percent_to_nn=0.4, mask_radius=None, refine=True, scalebar_true=False, probeStep=None, E0=60000.0, integrationAngleMin=0.085, integrationAngleMax=0.186, interpolationFactor=16, realspacePixelSize=0.0654, numFP=1, probeSemiangle=0.03, alphaBeamMax=0.032, scanWindowMin=0.0, scanWindowMax=1.0, algorithm='prism', numThreads=2)ΒΆ
    -

    Simulate an xyz coordinate model with the PyPrismatic fast simulation -software.

    -
    -
    Parameters
    -
      -
    • xyz_filename (string) – filename of the xyz coordinate model. Must be in the prismatic format. -See http://prism-em.com/docs-inputs/ for more information.

    • -
    • filename (string, default None) – name with which the image will be saved

    • -
    • reference_image (hyperspy signal 2D) – image from which calibration information is taken, such -as sampling, pixel height and pixel width

    • -
    • calibration_area (list) – xy pixel coordinates of the image area to be used to calibrate -the intensity. In the form [[0,0], [512,512]] -See calibrate_intensity_distance_with_sublattice_roi()

    • -
    • calibration_separation (int) – pixel separation used for the intensity calibration. -See calibrate_intensity_distance_with_sublattice_roi()

    • -
    • percent_to_nn (float, default 0.40) – Determines the boundary of the area surrounding each atomic -column, as fraction of the distance to the nearest neighbour.

    • -
    • mask_radius (float, default None) – Radius of the mask around each atom. If this is not set, -the radius will be the distance to the nearest atom in the -same sublattice times the percent_to_nn value. -Note: if mask_radius is not specified, the Atom_Position objects -must have a populated nearest_neighbor_list.

    • -
    • refine – See function calibrate_intensity_distance_with_sublattice_roi()

    • -
    • scalebar_true – See function calibrate_intensity_distance_with_sublattice_roi()

    • -
    • probeStep – See function simulate_with_prismatic()

    • -
    • .. etc. (E0) – See function simulate_with_prismatic()

    • -
    -
    -
    Returns
    -

    -
    -
    Return type
    -

    Hyperspy Signal2D

    -
    -
    -
    - -
    -
    -temul.simulations.simulate_and_filter_and_calibrate_with_prismatic(xyz_filename, filename, reference_image, calibration_area, calibration_separation, delta_image_filter=0.1, max_sigma=6, percent_to_nn=0.4, mask_radius=None, refine=True, scalebar_true=False, probeStep=None, E0=60000.0, integrationAngleMin=0.085, integrationAngleMax=0.186, interpolationFactor=16, realspacePixelSize=0.0654, numFP=1, probeSemiangle=0.03, alphaBeamMax=0.032, scanWindowMin=0.0, scanWindowMax=1.0, algorithm='prism', numThreads=2)ΒΆ
    -

    Simulate an xyz coordinate model with the PyPrismatic fast simulation -software.

    -
    -
    Parameters
    -
      -
    • xyz_filename (string) – filename of the xyz coordinate model. Must be in the prismatic format. -See http://prism-em.com/docs-inputs/ for more information.

    • -
    • filename (string, default None) – name with which the image will be saved

    • -
    • reference_image (hyperspy signal 2D) – image from which calibration information is taken, such -as sampling, pixel height and pixel width

    • -
    • calibration_area (list) – xy pixel coordinates of the image area to be used to calibrate -the intensity. In the form [[0,0], [512,512]] -See calibrate_intensity_distance_with_sublattice_roi()

    • -
    • calibration_separation (int) – pixel separation used for the intensity calibration. -See calibrate_intensity_distance_with_sublattice_roi()

    • -
    • percent_to_nn (float, default 0.40) – Determines the boundary of the area surrounding each atomic -column, as fraction of the distance to the nearest neighbour.

    • -
    • mask_radius (float, default None) – Radius of the mask around each atom. If this is not set, -the radius will be the distance to the nearest atom in the -same sublattice times the percent_to_nn value. -Note: if mask_radius is not specified, the Atom_Position objects -must have a populated nearest_neighbor_list.

    • -
    • refine – See function calibrate_intensity_distance_with_sublattice_roi()

    • -
    • scalebar_true – See function calibrate_intensity_distance_with_sublattice_roi()

    • -
    • probeStep – See function simulate_with_prismatic()

    • -
    • .. etc. (E0) – See function simulate_with_prismatic()

    • -
    -
    -
    Returns
    -

    -
    -
    Return type
    -

    Hyperspy Signal2D

    -
    -
    -
    - -
    -
    -temul.simulations.simulate_with_prismatic(xyz_filename, filename, reference_image=None, probeStep=1.0, E0=60000.0, integrationAngleMin=0.085, integrationAngleMax=0.186, detectorAngleStep=0.001, interpolationFactor=16, realspacePixelSize=0.0654, numFP=1, cellDimXYZ=None, tileXYZ=None, probeSemiangle=0.03, alphaBeamMax=0.032, scanWindowMin=0.0, scanWindowMax=1.0, algorithm='prism', numThreads=2)ΒΆ
    -

    Simulate an xyz coordinate model with pyprismatic -fast simulation software.

    -
    -
    Parameters
    -
      -
    • xyz_filename (string) – filename of the xyz coordinate model. Must be in the prismatic format. -See http://prism-em.com/docs-inputs/ for more information.

    • -
    • filename (string, default None) – name with which the image will be saved

    • -
    • reference_image (hyperspy signal 2D) – image from which calibration information is taken, such -as sampling, pixel height and pixel width

    • -
    • probeStep (float, default 1.0) – Should be the sampling of the image, where -sampling = length (in angstrom)/pixels -If you want the probeStep to be calculated from the reference image, -set this to None.

    • -
    • E0 (Prismatic parameters) – See http://prism-em.com/docs-params/

    • -
    • etc. (numThreads) – See http://prism-em.com/docs-params/

    • -
    -
    -
    -

    :param : See http://prism-em.com/docs-params/ -:type : Prismatic parameters -:param cellDimXYZ: A tuple of length 3. Example (2.3, 4.5, 5.6).

    -
    -

    If this is set to None, the cell dimension values from the .xyz file -will be used (default). If it is specified, it will overwrite the .xyz -file values.

    -
    -
    -
    Parameters
    -

    tileXYZ (tuple, default None) – A tuple of length 3. Example (5, 5, 2) would multiply the model in x -and y by 5, and z by 2. -Default of None is just set to (1, 1, 1)

    -
    -
    Returns
    -

    -
    -
    Return type
    -

    Simulated image as a 2D .mrc file

    -
    -
    -

    Examples

    -
    >>> from temul.simulations import simulate_with_prismatic
    ->>> import temul.example_data as example_data
    ->>> file_path = path_to_example_data_MoS2_hex_prismatic()
    ->>> simulate_with_prismatic(
    -...     xyz_filename=file_path,
    -...     filename='prismatic_simulation',
    -...     probeStep=1.0, reference_image=None, E0=60e3,
    -...     integrationAngleMin=0.085,
    -...     integrationAngleMax=0.186,
    -...     interpolationFactor=16,
    -...     realspacePixelSize=0.0654,
    -...     numFP=1, probeSemiangle=0.030, alphaBeamMax=0.032,
    -...     scanWindowMin=0.0, scanWindowMax=1.0,
    -...     algorithm="prism", numThreads=2)
    -
    -
    -
    - +
    +

    Image Simulation FunctionsΒΆ

    Signal ProcessingΒΆ

    -
    -temul.signal_processing.calibrate_intensity_distance_with_sublattice_roi(image, cropping_area, separation, reference_image=None, scalebar_true=False, percent_to_nn=0.2, mask_radius=None, refine=True, filename=None)ΒΆ
    +
    +temul.signal_processing.calibrate_intensity_distance_with_sublattice_roi(image, cropping_area, separation, reference_image=None, scalebar_true=False, percent_to_nn=0.2, mask_radius=None, refine=True, filename=None)ΒΆ

    Calibrates the intensity of an image by using the brightest sublattice. The mean intensity of that sublattice is set to 1.

    @@ -2811,16 +2566,16 @@

    Modulesint, default 8) – Pixel separation between atoms as used by Atomap.

    -
  • reference_image (Hyperspy Signal2D) – Image with which image is compared.

  • -
  • scalebar_true (Bool, default True) – If set to True, the function assumes that image.axes_manager is +

  • separation (int, default 8) – Pixel separation between atoms as used by Atomap.

  • +
  • reference_image (Hyperspy Signal2D) – Image with which image is compared.

  • +
  • scalebar_true (bool, default True) – If set to True, the function assumes that image.axes_manager is calibrated to a unit other than pixel.

  • -
  • mask_radius (int, default None) – Radius in pixels of the mask.

  • -
  • percent_to_nn (float, default 0.2) – Determines the boundary of the area surrounding each atomic +

  • mask_radius (int, default None) – Radius in pixels of the mask.

  • +
  • percent_to_nn (float, default 0.2) – Determines the boundary of the area surrounding each atomic column, as fraction of the distance to the nearest neighbour.

  • -
  • refine (Bool, default False) – If set to True, the atom positions found for the calibration will be +

  • refine (bool, default False) – If set to True, the atom positions found for the calibration will be refined.

  • -
  • filename (str, default None) – If set to a string, the image will be saved.

  • +
  • filename (str, default None) – If set to a string, the image will be saved.

  • Returns
    @@ -2838,37 +2593,15 @@

    Modules>>> image.plot() >>> crop_a = tml.choose_points_on_image(image.data) # manually >>> crop_a = [[10,10],[100,100]] # use above line if trying yourself! ->>> # tml.calibrate_intensity_distance_with_sublattice_roi(image, crop_a, 10) ->>> # image.plot()

    +

    # tml.calibrate_intensity_distance_with_sublattice_roi( +# image, crop_a, 10)

    -
    -temul.signal_processing.choose_mask_coordinates(image, norm='log')ΒΆ
    -

    Pick the mask locations for an FFT. See get_masked_ifft() for examples and -commit 5ba307b5af0b598bedc0284aa989d44e23fdde4d on Atomap for more details.

    -
    -
    Parameters
    -
      -
    • image (Hyperspy 2D Signal) –

    • -
    • norm (str, default "log") – How to scale the intensity value for the displayed image. -Options are β€œlinear” and β€œlog”.

    • -
    -
    -
    Returns
    -

    -
    -
    Return type
    -

    list of pixel coordinates

    -
    -
    -
    - -
    -
    -temul.signal_processing.compare_two_image_and_create_filtered_image(image_to_filter, reference_image, delta_image_filter, max_sigma=6, cropping_area=[[0, 0], [50, 50]], separation=8, filename=None, percent_to_nn=0.4, mask_radius=None, refine=False)ΒΆ
    +
    +temul.signal_processing.compare_two_image_and_create_filtered_image(image_to_filter, reference_image, delta_image_filter, max_sigma=6, cropping_area=[[0, 0], [50, 50]], separation=8, filename=None, percent_to_nn=0.4, mask_radius=None, refine=False)ΒΆ

    Gaussian blur an image for comparison with a reference image. Good for finding the best gaussian blur for a simulation by comparing to an experimental image. @@ -2877,21 +2610,21 @@

    ModulesParameters
    • image_to_filter (Hyperspy Signal2D) – Image you wish to automatically filter.

    • -
    • reference_image (Hyperspy Signal2D) – Image with which image_to_filter is compared.

    • -
    • delta_image_filter (float) – The increment of the Gaussian sigma used.

    • -
    • max_sigma (float, default 6) – The largest (limiting) Gaussian sigma used.

    • +
    • reference_image (Hyperspy Signal2D) – Image with which image_to_filter is compared.

    • +
    • delta_image_filter (float) – The increment of the Gaussian sigma used.

    • +
    • max_sigma (float, default 6) – The largest (limiting) Gaussian sigma used.

    • cropping_area (list of 2 floats, default [[0,0], [50,50]]) – The best method of choosing the area is by using the function β€œchoose_points_on_image(image.data)”. Choose two points on the image. First point is top left of area, second point is bottom right.

    • -
    • separation (int, default 8) – Pixel separation between atoms as used by Atomap.

    • -
    • filename (str, default None) – If set to a string, the plotted and filtered image will be saved.

    • -
    • percent_to_nn (float, default 0.4) – Determines the boundary of the area surrounding each atomic +

    • separation (int, default 8) – Pixel separation between atoms as used by Atomap.

    • +
    • filename (str, default None) – If set to a string, the plotted and filtered image will be saved.

    • +
    • percent_to_nn (float, default 0.4) – Determines the boundary of the area surrounding each atomic column, as fraction of the distance to the nearest neighbour.

    • -
    • mask_radius (int, default None) – Radius in pixels of the mask. If set, then set percent_to_nn=None.

    • -
    • refine (Bool, default False) – If set to True, the calibrate_intensity_distance_with_sublattice_roi -calibration will refine the atom positions for each calibration. May -make the function very slow depending on the size of image_to_filter -and cropping_area.

    • +
    • mask_radius (int, default None) – Radius in pixels of the mask. If set, then set percent_to_nn=None.

    • +
    • refine (bool, default False) – If set to True, the calibrate_intensity_distance_with_sublattice_roi` +calibration will refine the atom positions for each calibration. May +make the function very slow depending on the size of ``image_to_filter` +and ``cropping_area.

    Returns
    @@ -2920,9 +2653,9 @@

    Modules -
    -temul.signal_processing.crop_image_hs(image, cropping_area, scalebar_true=True, filename=None)ΒΆ
    -

    Crop a Hyperspy Signal2D by providing the cropping_area. See the example +

    +temul.signal_processing.crop_image_hs(image, cropping_area, scalebar_true=True, filename=None)ΒΆ
    +

    Crop a Hyperspy Signal2D by providing the cropping_area. See the example below.

    Parameters
    @@ -2931,9 +2664,9 @@

    Modulesbool, default True) – If set to True, the function assumes that image.axes_manager is calibrated to a unit other than pixel.

    -
  • filename (str, default None) – If set to a string, the images and cropping variables will be saved.

  • +
  • filename (str, default None) – If set to a string, the images and cropping variables will be saved.

  • Returns
    @@ -2961,27 +2694,27 @@

    Modules -
    -temul.signal_processing.distance_vector(x1, y1, x2, y2)ΒΆ
    +
    +temul.signal_processing.distance_vector(x1, y1, x2, y2)ΒΆ

    -
    -temul.signal_processing.double_gaussian_fft_filter(image, fwhm_neg, fwhm_pos, neg_min=0.9)ΒΆ
    +
    +temul.signal_processing.double_gaussian_fft_filter(image, fwhm_neg, fwhm_pos, neg_min=0.9)ΒΆ

    Filter an image with a bandpass-like filter.

    Parameters
    • image (Hyperspy Signal2D) –

    • -
    • fwhm_neg (float) – Initial guess in pixels of full width at half maximum (fwhm) of +

    • fwhm_neg (float) – Initial guess in pixels of full width at half maximum (fwhm) of inner (negative) and outer (positive) Gaussian to be applied to fft, respectively. Use the visualise_dg_filter function to find the optimium values.

    • -
    • fwhm_pos (float) – Initial guess in pixels of full width at half maximum (fwhm) of +

    • fwhm_pos (float) – Initial guess in pixels of full width at half maximum (fwhm) of inner (negative) and outer (positive) Gaussian to be applied to fft, respectively. Use the visualise_dg_filter function to find the optimium values.

    • -
    • neg_min (float, default 0.9) – Effective amplitude of the negative Gaussian.

    • +
    • neg_min (float, default 0.9) – Effective amplitude of the negative Gaussian.

    @@ -3004,8 +2737,8 @@

    Modules -
    -temul.signal_processing.double_gaussian_fft_filter_optimised(image, d_inner, d_outer, delta=0.05, sampling=None, units=None, filename=None)ΒΆ
    +
    +temul.signal_processing.double_gaussian_fft_filter_optimised(image, d_inner, d_outer, delta=0.05, sampling=None, units=None, filename=None)ΒΆ

    Filter an image with an double Gaussian (band-pass) filter. The function will automatically find the optimum magnitude of the negative inner Gaussian.

    @@ -3013,19 +2746,19 @@

    ModulesParameters
    • image (Hyperspy Signal2D) – Image to be filtered.

    • -
    • d_inner (float) – Inner diameter of the FFT spots. Effectively the diameter of the +

    • d_inner (float) – Inner diameter of the FFT spots. Effectively the diameter of the negative Gaussian.

    • -
    • d_outer (float) – Outer diameter of the FFT spots. Effectively the diameter of the +

    • d_outer (float) – Outer diameter of the FFT spots. Effectively the diameter of the positive Gaussian.

    • -
    • delta (float, default 0.05) – Increment of the automatic filtering with the negative Gaussian. +

    • delta (float, default 0.05) – Increment of the automatic filtering with the negative Gaussian. Setting this very small will slow down the function, but too high will not allow the function to calculate negative Gaussians near zero.

    • -
    • sampling (float) – image sampling in units/pixel. If set to None, the image.axes_manager +

    • sampling (float) – image sampling in units/pixel. If set to None, the image.axes_manager will be used.

    • -
    • units (str) – Real space units. sampling should then be the value of +

    • units (str) – Real space units. sampling should then be the value of these units/pixel. If set to None, the image.axes_manager will be used.

    • -
    • filename (str, default None) – If set to a string, the following files will be plotted and saved: +

    • filename (str, default None) – If set to a string, the following files will be plotted and saved: negative Gaussian optimumisation, negative Gaussian, positive Gaussian, double Gaussian, FFT and double Gaussian convolution, filtered image, filtered variables table.

    • @@ -3050,17 +2783,17 @@

      Modules -
      -temul.signal_processing.fit_1D_gaussian_to_data(xdata, amp, mu, sigma)ΒΆ
      +
      +temul.signal_processing.fit_1D_gaussian_to_data(xdata, amp, mu, sigma)ΒΆ

      Fitting function for a single 1D gaussian distribution

      Parameters
      • xdata (numpy 1D array) – values input as the x coordinates of the gaussian distribution

      • -
      • amp (float) – amplitude of the gaussian in y-axis

      • -
      • mu (float) – mean value of the gaussianin x-axis, corresponding to y-axis +

      • amp (float) – amplitude of the gaussian in y-axis

      • +
      • mu (float) – mean value of the gaussianin x-axis, corresponding to y-axis amplitude.

      • -
      • sigma (float) – standard deviation of the gaussian distribution

      • +
      • sigma (float) – standard deviation of the gaussian distribution

      Returns
      @@ -3084,8 +2817,8 @@

      Modules -
      -temul.signal_processing.get_cell_image(s, points_x, points_y, method='Voronoi', max_radius='Auto', reduce_func=<function amin>, show_progressbar=True)ΒΆ
      +
      +temul.signal_processing.get_cell_image(s, points_x, points_y, method='Voronoi', max_radius='Auto', reduce_func=<function amin>, show_progressbar=True)ΒΆ

      The same as atomap’s integrate, except instead of summing the region around an atom, it removes the value from all pixels in that region. @@ -3115,7 +2848,7 @@

      Modules... sublattice.y_position) -

      Plot the cell_image which shows, in this case, the background intensity

      +

      Plot the cell_image which shows, in this case, the background intensity

      >>> import matplotlib.pyplot as plt
       >>> im = plt.imshow(cell_image)
       
      @@ -3129,88 +2862,28 @@

      Modules -
      -temul.signal_processing.get_fitting_tools_for_plotting_gaussians(element_list, scaled_middle_intensity_list, scaled_limit_intensity_list, fit_bright_first=True, gaussian_amp=5, gauss_sigma_division=100)ΒΆ
      +
      +temul.signal_processing.get_fitting_tools_for_plotting_gaussians(element_list, scaled_middle_intensity_list, scaled_limit_intensity_list, fit_bright_first=True, gaussian_amp=5, gauss_sigma_division=100)ΒΆ

      Creates a list of parameters and details for fitting the intensities of a sublattice with multiple Gaussians.

      -
      -temul.signal_processing.get_masked_ifft(image, mask_coords, mask_radius=10, image_space='real', keep_masked_area=True, plot_masked_fft=False)ΒΆ
      -

      Creates an inverse fast Fourier transform (iFFT) from an image and mask -coordinates. Use choose_mask_coordinates to manually choose mask -coordinates in the FFT.

      -
      -
      Parameters
      -
        -
      • image (Hyperspy 2D Signal) –

      • -
      • mask_coords (list of pixel coordinates) – Pixel coordinates of the masking locations. See the example below for -two simple coordinates found using choose_mask_coordinates.

      • -
      • mask_radius (int, default 10) – Radius in pixels of the mask.

      • -
      • image_space (str, default "real") – If the input image is in Fourier/diffraction/reciprocal space already, -set space=”fourier”.

      • -
      • keep_masked_area (Bool, default True) – If True, this will set the mask at the mask_coords. -If False, this will set the mask as everything other than the -mask_coords. Can be thought of as inversing the mask.

      • -
      • plot_masked_fft (Bool, default False) – If True, the mask used to filter the FFT will be plotted. Good for -checking that the mask is doing what you want. Can fail sometimes due -to matplotlib plotting issues.

      • -
      -
      -
      Returns
      -

      -
      -
      Return type
      -

      Inverse FFT as a Hyperspy 2D Signal

      -
      -
      -

      Examples

      -
      >>> from temul.dummy_data import get_simple_cubic_signal
      ->>> import temul.api as tml
      ->>> image = get_simple_cubic_signal()
      ->>> mask_coords = tml.choose_mask_coordinates(image) #  manually
      ->>> mask_coords = [[170.2, 170.8],[129.8, 130]]
      ->>> image_ifft = tml.get_masked_ifft(image, mask_coords)
      ->>> image_ifft.plot()
      -
      -
      -

      Plot the masked fft:

      -
      >>> image_ifft = tml.get_masked_ifft(image, mask_coords,
      -...                                  plot_masked_fft=True)
      -
      -
      -

      Use unmasked fft area and plot the masked fft:

      -
      >>> image_ifft = tml.get_masked_ifft(
      -...     image, mask_coords, plot_masked_fft=True, keep_masked_area=False)
      ->>> image_ifft.plot()
      -
      -
      -

      If the input image is already a Fourier transform:

      -
      >>> fft_image = image.fft(shift=True)
      ->>> image_ifft = tml.get_masked_ifft(fft_image, mask_coords,
      -...     image_space='fourier')
      ->>> image_ifft.plot()
      -
      -
      -
      - -
      -
      -temul.signal_processing.get_scaled_middle_limit_intensity_list(sublattice, middle_intensity_list, limit_intensity_list, sublattice_scalar)ΒΆ
      +
      +temul.signal_processing.get_scaled_middle_limit_intensity_list(sublattice, middle_intensity_list, limit_intensity_list, sublattice_scalar)ΒΆ

      Returns the middle and limit lists scaled to the actual intensities in the sublattice. Useful for get_fitting_tools_for_plotting_gaussians().

      -
      -temul.signal_processing.get_xydata_from_list_of_intensities(sublattice_intensity_list, hist_bins=100)ΒΆ
      +
      +temul.signal_processing.get_xydata_from_list_of_intensities(sublattice_intensity_list, hist_bins=100)ΒΆ

      Output x and y data for a histogram of intensities

      Parameters
        -
      • sublattice_intensity_list (list) – See get_subattice_intensity() for more information

      • -
      • hist_bins (int, default 100) – number of bins to sort the intensities into +

      • sublattice_intensity_list (list) – See get_subattice_intensity() for more information

      • +
      • hist_bins (int, default 100) – number of bins to sort the intensities into must be a better way of doing this? maybe automate the binning choice

      @@ -3233,16 +2906,16 @@

      Modules -
      -temul.signal_processing.load_and_compare_images(imageA, imageB, filename=None)ΒΆ
      +
      +temul.signal_processing.load_and_compare_images(imageA, imageB, filename=None)ΒΆ

      Load two images with hyperspy and compare their mean square error and structural simularity index.

      Parameters
        -
      • imageA (str, path to file) – filename of the images to be loaded and compared

      • -
      • imageB (str, path to file) – filename of the images to be loaded and compared

      • -
      • filename (str, default None) – name with which the image will be saved

      • +
      • imageA (str, path to file) – filename of the images to be loaded and compared

      • +
      • imageB (str, path to file) – filename of the images to be loaded and compared

      • +
      • filename (str, default None) – name with which the image will be saved

      Returns
      @@ -3255,14 +2928,14 @@

      Modules -
      -temul.signal_processing.make_gaussian(size, fwhm, center=None)ΒΆ
      +
      +temul.signal_processing.make_gaussian(size, fwhm, center=None)ΒΆ

      Make a square gaussian kernel.

      Parameters
        -
      • size (int) – The length of a side of the square

      • -
      • fwhm (float) – The full-width-half-maximum of the Gaussian, which can be thought of as +

      • size (int) – The length of a side of the square

      • +
      • fwhm (float) – The full-width-half-maximum of the Gaussian, which can be thought of as an effective radius.

      • center (array, default None) – The location of the center of the Gaussian. None will set it to the center of the array.

      • @@ -3285,24 +2958,24 @@

        Modules -
        -temul.signal_processing.make_gaussian_pos_neg(size, fwhm_neg, fwhm_pos, neg_min=0.9, center=None)ΒΆ
        +
        +temul.signal_processing.make_gaussian_pos_neg(size, fwhm_neg, fwhm_pos, neg_min=0.9, center=None)ΒΆ

        See double_gaussian_fft_filter for details

      -
      -temul.signal_processing.mean_and_std_nearest_neighbour_distances(sublattice, nearest_neighbours=5, sampling=None)ΒΆ
      +
      +temul.signal_processing.mean_and_std_nearest_neighbour_distances(sublattice, nearest_neighbours=5, sampling=None)ΒΆ

      Calculates mean and standard deviation of the distance from each atom to its nearest neighbours.

      Parameters
      • sublattice (Atomap Sublattice object) –

      • -
      • nearest_neighbours (int, default 5) – The number of nearest neighbours used to calculate the mean distance +

      • nearest_neighbours (int, default 5) – The number of nearest neighbours used to calculate the mean distance from an atom. As in atomap, choosing 5 gets the 4 nearest neighbours.

      • -
      • sampling (float, default None) – The image sampling in units/pixel. If set to None then the values +

      • sampling (float, default None) – The image sampling in units/pixel. If set to None then the values returned are given in pixels. This may be changed in future versions if Atomap’s Sublattice pixel attribute is updated.

      • @@ -3328,8 +3001,8 @@

        Modules -
        -temul.signal_processing.measure_image_errors(imageA, imageB, filename=None)ΒΆ
        +
        +temul.signal_processing.measure_image_errors(imageA, imageB, filename=None)ΒΆ

        Measure the Mean Squared Error (mse) and Structural Similarity Index (ssm) between two images.

        @@ -3337,7 +3010,7 @@

        Modules

        Returns
        @@ -3364,8 +3037,8 @@

        Modules -
        -temul.signal_processing.mse(imageA, imageB)ΒΆ
        +
        +temul.signal_processing.mse(imageA, imageB)ΒΆ

        Measure the mean squared error between two images of the same shape.

        Parameters
        @@ -3384,8 +3057,8 @@

        Modules -
        -temul.signal_processing.plot_gaussian_fit(xdata, ydata, function, amp, mu, sigma, gauss_art='r--', gauss_label='Gauss Fit', plot_data=True, data_art='ko', data_label='Data Points', plot_fill=False, facecolor='r', alpha=0.5)ΒΆ
        +
        +temul.signal_processing.plot_gaussian_fit(xdata, ydata, function, amp, mu, sigma, gauss_art='r--', gauss_label='Gauss Fit', plot_data=True, data_art='ko', data_label='Data Points', plot_fill=False, facecolor='r', alpha=0.5)ΒΆ
        >>> from temul.signal_processing import (fit_1D_gaussian_to_data,
         ...                                 plot_gaussian_fit,
         ...                                 return_fitting_of_1D_gaussian)
        @@ -3406,8 +3079,8 @@ 

        Modules -
        -temul.signal_processing.plot_gaussian_fitting_for_multiple_fits(sub_ints_all, fitting_tools_all_subs, element_list_all_subs, marker_list, hist_bins=150, plotting_style='hist', filename='Fit of Intensities', mpl_cmaps_list=['viridis'])ΒΆ
        +
        +temul.signal_processing.plot_gaussian_fitting_for_multiple_fits(sub_ints_all, fitting_tools_all_subs, element_list_all_subs, marker_list, hist_bins=150, plotting_style='hist', filename='Fit of Intensities', mpl_cmaps_list=['viridis'])ΒΆ

        plots Gaussian distributions for intensities of a sublattice, over the given parameters (fitting tools).

        Examples

        @@ -3451,23 +3124,37 @@

        Modules -
        -temul.signal_processing.remove_image_intensity_in_data_slice(atom, image_data, percent_to_nn=0.5)ΒΆ
        +
        +temul.signal_processing.remove_image_intensity_in_data_slice(atom, image_data, percent_to_nn=0.5)ΒΆ

        Remove intensity from the area around an atom in a sublattice

        -
        -temul.signal_processing.return_fitting_of_1D_gaussian(function, xdata, ydata, amp, mu, sigma)ΒΆ
        -
        -

        Use the initially found centre (mean/mode) value of a sublattice +

        +temul.signal_processing.return_fitting_of_1D_gaussian(function, xdata, ydata, amp, mu, sigma)ΒΆ
        +

        Use the initially found centre (mean/mode) value of a sublattice histogram (e.g., Mo_1 in an Mo sublattice) as an input mean for a gaussian fit of the data.

        -

        xdata, ydata : see scipy.optimize.curve_fit -amp, mu, sigma : see fit_1D_gaussian_to_data() for more details

        -

        optimised parameters (popt) and estimated covariance (pcov) of the -fitted gaussian function.

        +
        +
        Parameters
        +
          +
        • xdata (see scipy.optimize.curve_fit) –

        • +
        • ydata (see scipy.optimize.curve_fit) –

        • +
        • amp (see fit_1D_gaussian_to_data() for more details) –

        • +
        • mu (see fit_1D_gaussian_to_data() for more details) –

        • +
        • sigma (see fit_1D_gaussian_to_data() for more details) –

        • +
        +
        +
        Returns
        +

          +
        • optimised parameters (popt) and estimated covariance (pcov) of the

        • +
        • fitted gaussian function.

        • +
        +

        +
        +
        +

        Examples

        >>> from temul.signal_processing import (
         ...     get_xydata_from_list_of_intensities,
         ...     return_fitting_of_1D_gaussian,
        @@ -3482,53 +3169,44 @@ 

        Modules... amp, mu, sigma)

        -

        # print(β€œCalculated Mean: ” + str(round(np.mean(xdata),3)) -# + β€œ

        -
        -

        Fitted Mean: ” + str(round(popt_gauss[1],3)))

        -
        -temul.signal_processing.sine_wave_function_strain_gradient(x, a, b, c, d)ΒΆ
        -
        - -
        -
        -temul.signal_processing.toggle_atom_refine_position_automatically(sublattice, min_cut_off_percent, max_cut_off_percent, range_type='internal', method='mode', percent_to_nn=0.05, mask_radius=None, filename=None)ΒΆ
        +
        +temul.signal_processing.toggle_atom_refine_position_automatically(sublattice, min_cut_off_percent, max_cut_off_percent, range_type='internal', method='mode', percent_to_nn=0.05, mask_radius=None, filename=None)ΒΆ

        Sets the β€˜refine_position’ attribute of each Atom Position in a sublattice using a range of intensities.

        Parameters
        • sublattice (Atomap Sublattice object) –

        • -
        • min_cut_off_percent (float, default None) – The lower end of the intensity range is defined as -min_cut_off_percent * method value of max intensity list of -sublattice.

        • -
        • max_cut_off_percent (float, default None) – The upper end of the intensity range is defined as -max_cut_off_percent * method value of max intensity list of -sublattice.

        • -
        • range_type (str, default 'internal') – β€œinternal” provides the refine_position attribute for each -Atom Position as True if the intensity of that Atom Position +

        • min_cut_off_percent (float, default None) – The lower end of the intensity range is defined as +min_cut_off_percent * method value of max intensity list of +sublattice.

        • +
        • max_cut_off_percent (float, default None) – The upper end of the intensity range is defined as +max_cut_off_percent * method value of max intensity list of +sublattice.

        • +
        • range_type (str, default 'internal') – β€œinternal” provides the refine_position attribute for each +Atom Position as True if the intensity of that Atom Position lies between the lower and upper limits defined by -min_cut_off_percent and max_cut_off_percent. -β€œexternal” provides the refine_position attribute for each -Atom Position as True if the intensity of that Atom Position +min_cut_off_percent and max_cut_off_percent. +β€œexternal” provides the refine_position attribute for each +Atom Position as True if the intensity of that Atom Position lies outside the lower and upper limits defined by -min_cut_off_percent and max_cut_off_percent.

        • -
        • method (str, default 'mode') – The method used to aggregate the intensity of the sublattice positions +min_cut_off_percent and max_cut_off_percent.

        • +
        • method (str, default 'mode') – The method used to aggregate the intensity of the sublattice positions max intensity list. Options are β€œmode” and β€œmean”

        • -
        • percent_to_nn (float, default 0.05) – Determines the boundary of the area surrounding each atomic +

        • percent_to_nn (float, default 0.05) – Determines the boundary of the area surrounding each atomic column, as fraction of the distance to the nearest neighbour.

        • -
        • mask_radius (int, default None) – Radius in pixels of the mask.

        • -
        • filename (str, default None) – If set to a string, the Atomap refine_position image will be saved.

        • +
        • mask_radius (int, default None) – Radius in pixels of the mask.

        • +
        • filename (str, default None) – If set to a string, the Atomap refine_position image will be saved.

        Returns

        Return type
        -

        list of the AtomPosition.refine_position=False attribute.

        +

        list of the AtomPosition.refine_position=False attribute.

        Examples

        @@ -3554,22 +3232,22 @@

        Modules -
        -temul.signal_processing.visualise_dg_filter(image, d_inner=7.7, d_outer=21, slider_min=0.1, slider_max=300, slider_step=0.1, plot_lims=0, 1, figsize=15, 7)ΒΆ
        +
        +temul.signal_processing.visualise_dg_filter(image, d_inner=7.7, d_outer=21, slider_min=0.1, slider_max=300, slider_step=0.1, plot_lims=(0, 1), figsize=(15, 7))ΒΆ
        Parameters
        • image (Hyperspy Signal2D) – This image.axes_manager scale should be calibrated.

        • -
        • d_inner (float, default 7.7) – Initial β€˜guess’ of full width at half maximum (fwhm) of +

        • d_inner (float, default 7.7) – Initial β€˜guess’ of full width at half maximum (fwhm) of inner (negative) gaussian to be applied to fft. Can be changed with sliders during visualisation.

        • -
        • d_outer (float, default 14) – Initial β€˜guess’ of full width at half maximum (fwhm) of +

        • d_outer (float, default 14) – Initial β€˜guess’ of full width at half maximum (fwhm) of outer (positive) gaussian to be applied to fft. Can be changed with sliders during visualisation.

        • -
        • slider_min (float, default 0.1) – Minimum value on sliders

        • -
        • slider_max (float, default 300) – Maximum value on sliders

        • -
        • slider_step (float, default 0.1) – Step size on sliders

        • -
        • plot_lims (tuple, default (0, 1)) – Used to plot a smaller section of the FFT image, which can be useful if +

        • slider_min (float, default 0.1) – Minimum value on sliders

        • +
        • slider_max (float, default 300) – Maximum value on sliders

        • +
        • slider_step (float, default 0.1) – Step size on sliders

        • +
        • plot_lims (tuple, default (0, 1)) – Used to plot a smaller section of the FFT image, which can be useful if the information is very small (far away!). Default plots the whole image.

        @@ -3588,37 +3266,32 @@

        Modules

        Signal PlottingΒΆ

        -
        -class temul.signal_plotting.Sublattice_Hover_Intensity(image, sublattice, sublattice_positions, background_sublattice)ΒΆ
        +
        +class temul.signal_plotting.Sublattice_Hover_Intensity(image, sublattice, sublattice_positions, background_sublattice)ΒΆ

        User can hover over sublattice overlaid on STEM image to display the x,y location and intensity of that point.

        -
        -scaled(points)ΒΆ
        +
        +scaled(points)ΒΆ
        -
        -setup_annotation()ΒΆ
        +
        +setup_annotation()ΒΆ

        Draw and hide the annotation box.

        -
        -snap(x, y)ΒΆ
        +
        +snap(x, y)ΒΆ

        Return the value in self.tree closest to x, y.

        -
        -temul.signal_plotting.choose_points_on_image(image, norm='linear', distance_threshold=4)ΒΆ
        -
        - -
        -
        -temul.signal_plotting.color_palettes(pallette)ΒΆ
        +
        +temul.signal_plotting.color_palettes(pallette)ΒΆ

        Color sequences that are useful for creating matplotlib colormaps. Info on β€œzesty” and other options: venngage.com/blog/color-blind-friendly-palette/ @@ -3626,7 +3299,7 @@

        Modules
        Parameters
        -

        palette (str) – Options are β€œzesty” (4 colours), and β€œr_safe” (12 colours).

        +

        palette (str) – Options are β€œzesty” (4 colours), and β€œr_safe” (12 colours).

        Returns

        @@ -3638,8 +3311,8 @@

        Modules -
        -temul.signal_plotting.compare_images_line_profile_one_image(image, line_profile_positions, linewidth=1, sampling='Auto', units='pix', arrow=None, linetrace=None, **kwargs)ΒΆ
        +
        +temul.signal_plotting.compare_images_line_profile_one_image(image, line_profile_positions, linewidth=1, sampling='Auto', units='pix', arrow=None, linetrace=None, **kwargs)ΒΆ

        Plots two line profiles on one image with the line profile intensities in a subfigure. See skimage PR PinkShnack for details on implementing profile_line @@ -3652,8 +3325,8 @@

        Modulesint, default 1) – see profile_line for parameter details.

        -
      • sampling (float, default 'Auto') –

        +
      • linewidth (int, default 1) – see profile_line for parameter details.

      • +
      • sampling (float, default 'Auto') –

        if set to β€˜Auto’ the function will attempt to find the sampling of

        image from image.axes_manager[0].scale.

        arrowstring, default None

        If set, arrows will be plotting on the image. Options are β€˜h’ and @@ -3661,7 +3334,7 @@

        Modulesint, default None) – If set, the line profile will be plotted on the image. +
      • linetrace (int, default None) – If set, the line profile will be plotted on the image. The thickness of the linetrace will be linewidth*linetrace. Name could be improved maybe.

      • kwargs (Matplotlib keyword arguments passed to imshow()) –

      • @@ -3671,8 +3344,8 @@

        Modules -
        -temul.signal_plotting.compare_images_line_profile_two_images(imageA, imageB, line_profile_positions, reduce_func=<function mean>, filename=None, linewidth=1, sampling='auto', units='nm', crop_offset=20, title='Intensity Profile', imageA_title='Experiment', imageB_title='Simulation', marker_A='v', marker_B='o', arrow_markersize=10, figsize=(10, 3), imageB_intensity_offset=0)ΒΆ
        +
        +temul.signal_plotting.compare_images_line_profile_two_images(imageA, imageB, line_profile_positions, reduce_func=<function mean>, filename=None, linewidth=1, sampling='auto', units='nm', crop_offset=20, title='Intensity Profile', imageA_title='Experiment', imageB_title='Simulation', marker_A='v', marker_B='o', arrow_markersize=10, figsize=(10, 3), imageB_intensity_offset=0)ΒΆ

        Plots two line profiles on two images separately with the line profile intensities in a subfigure. See skimage PR PinkShnack for details on implementing profile_line @@ -3687,19 +3360,19 @@

        Modulesint, default 1) – see profile_line for parameter details.

      • -
      • sampling (float, default 'auto') – if set to β€˜auto’ the function will attempt to find the sampling of +

      • reduce_func (ufunc, default np.mean) – See skimage’s profile_line reduce_func parameter for details.

      • +
      • linewidth (int, default 1) – see profile_line for parameter details.

      • +
      • sampling (float, default 'auto') – if set to β€˜auto’ the function will attempt to find the sampling of image from image.axes_manager[0].scale.

      • units (string, default 'nm') –

      • -
      • crop_offset (int, default 20) – number of pixels away from the line_profile_positions coordinates the +

      • crop_offset (int, default 20) – number of pixels away from the line_profile_positions coordinates the image crop will be taken.

      • title (string, default "Intensity Profile") – Title of the plot

      • marker_A (Matplotlib marker) –

      • marker_B (Matplotlib marker) –

      • arrow_markersize (Matplotlib markersize) –

      • figsize (see Matplotlib for details) –

      • -
      • imageB_intensity_offset (float, default 0) – Adds a y axis offset for comparison purposes.

      • +
      • imageB_intensity_offset (float, default 0) – Adds a y axis offset for comparison purposes.

      @@ -3715,7 +3388,7 @@

      Modules... linewidth=3, sampling=0.012, crop_offset=30) -

      To use the new skimage functionality try the reduce_func parameter:

      +

      To use the new skimage functionality try the reduce_func parameter:

      -
      -temul.signal_plotting.expand_palette(palette, expand_list)ΒΆ
      +
      +temul.signal_plotting.expand_palette(palette, expand_list)ΒΆ

      Essentially multiply the palette so that it has the number of instances of each color that you want.

      Parameters
        -
      • palette (list) – Color palette in hex, rgb or dec

      • -
      • expand_list (list) – List of integers that will be used to duplicate colours in the palette.

      • +
      • palette (list) – Color palette in hex, rgb or dec

      • +
      • expand_list (list) – List of integers that will be used to duplicate colours in the palette.

      Returns
      @@ -3767,25 +3440,25 @@

      ModulesExamples

      -
      >>> import temul.signal_plotting as tmlplot
      ->>> zest = tmlplot.color_palettes('zesty')
      ->>> expanded_palette = tmlplot.expand_palette(zest, [1,2,2,2])
      +
      >>> import temul.api as tml
      +>>> zest = tml.color_palettes('zesty')
      +>>> expanded_palette = tml.expand_palette(zest, [1,2,2,2])
       

      -
      -temul.signal_plotting.get_cropping_area(line_profile_positions, crop_offset=20)ΒΆ
      +
      +temul.signal_plotting.get_cropping_area(line_profile_positions, crop_offset=20)ΒΆ

      By inputting the top-left and bottom-right coordinates of a rectangle, this function will add a border buffer (crop_offset) which can be used for cropping of regions in a plot. -See compare_images_line_profile_two_images for use-case

      +See compare_images_line_profile_two_images for use-case

      -
      -temul.signal_plotting.get_polar_2d_colorwheel_color_list(u, v)ΒΆ
      +
      +temul.signal_plotting.get_polar_2d_colorwheel_color_list(u, v)ΒΆ

      make the color_list from the HSV/RGB colorwheel. This color_list will be the same length as u and as v. It works by indexing the angle of the RGB (hue in HSV) array, @@ -3794,14 +3467,14 @@

      Modules -
      -temul.signal_plotting.hex_to_rgb(hex_values)ΒΆ
      +
      +temul.signal_plotting.hex_to_rgb(hex_values)ΒΆ

      Change from hexidecimal color values to rgb color values. Grabs starting two, middle two, last two values in hex, multiplies by 16^1 and 16^0 for the first and second, respectively.

      Parameters
      -

      hex_values (list) – A list of hexidecimal color values as strings e.g., β€˜#F5793A’

      +

      hex_values (list) – A list of hexidecimal color values as strings e.g., β€˜#F5793A’

      Returns

      @@ -3811,39 +3484,39 @@

      ModulesExamples

      -
      >>> import temul.signal_plotting as tmlplot
      ->>> tmlplot.hex_to_rgb(color_palettes('zesty'))
      +
      >>> import temul.api as tml
      +>>> tml.hex_to_rgb(color_palettes('zesty'))
       [(245, 121, 58), (169, 90, 161), (133, 192, 249), (15, 32, 128)]
       

      Create a matplotlib cmap from a palette with the help of matplotlib.colors.from_levels_and_colors()

      >>> from matplotlib.colors import from_levels_and_colors
      ->>> zest = tmlplot.hex_to_rgb(tmlplot.color_palettes('zesty'))
      +>>> zest = tml.hex_to_rgb(tml.color_palettes('zesty'))
       >>> zest.append(zest[0])  # make the top and bottom colour the same
       >>> cmap, norm = from_levels_and_colors(
      -...     levels=[0,1,2,3,4,5], colors=tmlplot.rgb_to_dec(zest))
      +...     levels=[0,1,2,3,4,5], colors=tml.rgb_to_dec(zest))
       

      -
      -temul.signal_plotting.plot_atom_energies(sublattice_list, image=None, vac_or_implants=None, elements_dict_other=None, filename='energy_map', cmap='plasma', levels=20, colorbar_fontsize=16)ΒΆ
      +
      +temul.signal_plotting.plot_atom_energies(sublattice_list, image=None, vac_or_implants=None, elements_dict_other=None, filename='energy_map', cmap='plasma', levels=20, colorbar_fontsize=16)ΒΆ

      Used to plot the energies of atomic column configurations above 0 as calculated by DFT.

      Parameters
      • sublattice_list (list of Atomap Sublattices) –

      • -
      • image (array-like, default None) – The first sublattice image is used if image=None.

      • -
      • vac_or_implants (string, default None) – vac_or_implants options are β€œimplants” and β€œvac”.

      • -
      • elements_dict_other (dict, default None) – A dictionary of {element_config1: energy1, element_config2: energy2, } +

      • image (array-like, default None) – The first sublattice image is used if image=None.

      • +
      • vac_or_implants (string, default None) – vac_or_implants options are β€œimplants” and β€œvac”.

      • +
      • elements_dict_other (dict, default None) – A dictionary of {element_config1: energy1, element_config2: energy2, } The default is Se antisites in monolayer MoS2.

      • filename (string, default "energy_map") – Name with which to save the plot.

      • cmap (Matplotlib colormap, default "plasma") –

      • -
      • levels (int, default 20) – Number of Matplotlib contour map levels.

      • -
      • colorbar_fontsize (int, default 16) –

      • +
      • levels (int, default 20) – Number of Matplotlib contour map levels.

      • +
      • colorbar_fontsize (int, default 16) –

      Returns
      @@ -3857,10 +3530,10 @@

      Modules -
      -temul.signal_plotting.rgb_to_dec(rgb_values)ΒΆ
      +
      +temul.signal_plotting.rgb_to_dec(rgb_values)ΒΆ

      Change RGB color values to decimal color values (between 0 and 1). -Required for use with matplotlib. See Example in hex_to_rgb below.

      +Required for use with matplotlib. See Example in hex_to_rgb below.

      Parameters

      rgb_values (list of tuples) –

      @@ -3878,8 +3551,8 @@

      Modules

      Input/Output (io)ΒΆ

      -
      -temul.io.batch_convert_emd_to_image(extension_to_save, top_level_directory, glob_search='**/*', overwrite=True)ΒΆ
      +
      +temul.io.batch_convert_emd_to_image(extension_to_save, top_level_directory, glob_search='**/*', overwrite=True)ΒΆ

      Convert all .emd files to the chosen extension_to_save file format in the specified directory and all subdirectories.

      @@ -3890,18 +3563,18 @@

      Moduleshttp://hyperspy.org/hyperspy-doc/current/user_guide/io.html

    • top_level_directory (string) – The top-level directory in which the emd files exist. The default glob_search will search this directory and all subdirectories.

    • -
    • glob_search (string, default β€œ**/*”) – Glob search string, see glob for more details: +

    • glob_search (string) – Glob search string, see glob for more details: https://docs.python.org/2/library/glob.html Default will search this directory and all subdirectories.

    • -
    • overwrite (Bool, default True) – Overwrite if the extension_to_save file already exists.

    • +
    • overwrite (bool, default True) – Overwrite if the extension_to_save file already exists.

    -
    -temul.io.convert_vesta_xyz_to_prismatic_xyz(vesta_xyz_filename, prismatic_xyz_filename, delimiter=' | | ', header=None, skiprows=[0, 1], engine='python', occupancy=1.0, rms_thermal_vib=0.05, edge_padding=None, header_comment="Let's make a file!", save=True)ΒΆ
    +
    +temul.io.convert_vesta_xyz_to_prismatic_xyz(vesta_xyz_filename, prismatic_xyz_filename, delimiter='   |    |  ', header=None, skiprows=[0, 1], engine='python', occupancy=1.0, rms_thermal_vib=0.05, edge_padding=None, header_comment="Let's make a file!", save=True)ΒΆ

    Convert from Vesta outputted xyz file format to the prismatic-style xyz format. Lose some information from the .cif or .vesta file but okay for now. @@ -3930,7 +3603,7 @@

    Modulesbool, default True) – whether to output the file as a prismatic formatted xyz file with the name of the file given by β€œprismatic_xyz_filename”.

    @@ -3955,8 +3628,8 @@

    Modules -
    -temul.io.create_dataframe_for_xyz(sublattice_list, element_list, x_size, y_size, z_size, filename, header_comment='top_level_comment')ΒΆ
    +
    +temul.io.create_dataframe_for_xyz(sublattice_list, element_list, x_size, y_size, z_size, filename, header_comment='top_level_comment')ΒΆ

    Creates a Pandas Dataframe and a .xyz file (usable with Prismatic) from the inputted sublattice(s).

    @@ -3990,8 +3663,8 @@

    Modules -
    -temul.io.dm3_stack_to_tiff_stack(loading_file, loading_file_extension='.dm3', saving_file_extension='.tif', crop=False, crop_start=20.0, crop_end=80.0)ΒΆ
    +
    +temul.io.dm3_stack_to_tiff_stack(loading_file, loading_file_extension='.dm3', saving_file_extension='.tif', crop=False, crop_start=20.0, crop_end=80.0)ΒΆ

    Save an image stack filetype to a different filetype, e.g., dm3 to tiff.

    Parameters
    @@ -3999,23 +3672,23 @@

    Modulesbool, default False) – if True, the image will be cropped in the navigation space, +
  • crop (bool, default False) – if True, the image will be cropped in the navigation space, defined by the frames given in crop_start and crop_end

  • -
  • crop_start (float, default 20.0, 80.0) – the start and end frame of the crop

  • -
  • crop_end (float, default 20.0, 80.0) – the start and end frame of the crop

  • +
  • crop_start (float, default 20.0, 80.0) – the start and end frame of the crop

  • +
  • crop_end (float, default 20.0, 80.0) – the start and end frame of the crop

  • -
    -temul.io.load_data_and_sampling(filename, file_extension=None, invert_image=False, save_image=True)ΒΆ
    +
    +temul.io.load_data_and_sampling(filename, file_extension=None, invert_image=False, save_image=True)ΒΆ
    -
    -temul.io.load_prismatic_mrc_with_hyperspy(prismatic_mrc_filename, save_name='calibrated_data_')ΒΆ
    +
    +temul.io.load_prismatic_mrc_with_hyperspy(prismatic_mrc_filename, save_name='calibrated_data_')ΒΆ

    We are aware this is currently producing errors with new versions of Prismatic.

    Open a prismatic .mrc file and save as a hyperspy object. @@ -4041,8 +3714,8 @@

    Modules -
    -temul.io.save_individual_images_from_image_stack(image_stack, output_folder='individual_images')ΒΆ
    +
    +temul.io.save_individual_images_from_image_stack(image_stack, output_folder='individual_images')ΒΆ

    Save each image in an image stack. The images are saved in a new folder. Useful for after running an image series through Rigid Registration.

    @@ -4057,8 +3730,8 @@

    Modules -
    -temul.io.write_cif_from_dataframe(dataframe, filename, chemical_name_common, cell_length_a, cell_length_b, cell_length_c, cell_angle_alpha=90, cell_angle_beta=90, cell_angle_gamma=90, space_group_name_H_M_alt='P 1', space_group_IT_number=1)ΒΆ
    +
    +temul.io.write_cif_from_dataframe(dataframe, filename, chemical_name_common, cell_length_a, cell_length_b, cell_length_c, cell_angle_alpha=90, cell_angle_beta=90, cell_angle_gamma=90, space_group_name_H_M_alt='P 1', space_group_IT_number=1)ΒΆ

    Write a cif file from a Pandas Dataframe. This Dataframe can be created with temul.model_creation.create_dataframe_for_cif().

    @@ -4066,14 +3739,14 @@

    Modules

    @@ -4083,14 +3756,14 @@

    Modules

    Dummy DataΒΆ

    -
    -temul.dummy_data.get_distorted_cubic_signal_adjustable(image_noise=False, y_offset=2)ΒΆ
    +
    +temul.dummy_data.get_distorted_cubic_signal_adjustable(image_noise=False, y_offset=2)ΒΆ

    Generate a test image signal of a distorted cubic atomic structure.

    Parameters
    • image_noise (default False) – If True, will add Gaussian noise to the image.

    • -
    • y_offset (int, default 2) – The magnitude of distortion of the cubic signal.

    • +
    • y_offset (int, default 2) – The magnitude of distortion of the cubic signal.

    Returns
    @@ -4109,14 +3782,14 @@

    Modules -
    -temul.dummy_data.get_distorted_cubic_sublattice_adjustable(image_noise=False, y_offset=2)ΒΆ
    +
    +temul.dummy_data.get_distorted_cubic_sublattice_adjustable(image_noise=False, y_offset=2)ΒΆ

    Generate a test sublattice of a distorted cubic atomic structure.

    Parameters
    • image_noise (default False) – If True, will add Gaussian noise to the image.

    • -
    • y_offset (int, default 2) – The magnitude of distortion of the cubic signal.

    • +
    • y_offset (int, default 2) – The magnitude of distortion of the cubic signal.

    Returns
    @@ -4135,14 +3808,14 @@

    Modules -
    -temul.dummy_data.get_polarisation_dummy_dataset(image_noise=False)ΒΆ
    +
    +temul.dummy_data.get_polarisation_dummy_dataset(image_noise=False)ΒΆ

    Get an Atom Lattice with two sublattices resembling a perovskite film.

    Similar to a perovskite oxide thin film, where the B cations are shifted in the film.

    Parameters
    -

    image_noise (bool, default False) –

    +

    image_noise (bool, default False) –

    Returns

    simple_atom_lattice

    @@ -4170,7 +3843,7 @@

    Modules

    -
    -temul.dummy_data.get_polarised_single_sublattice(image_noise=False)ΒΆ
    +
    +temul.dummy_data.get_polarised_single_sublattice(image_noise=False)ΒΆ
    -
    -temul.dummy_data.get_polarised_single_sublattice_rotated(image_noise=False, rotation=45)ΒΆ
    +
    +temul.dummy_data.get_polarised_single_sublattice_rotated(image_noise=False, rotation=45)ΒΆ
    -
    -temul.dummy_data.get_simple_cubic_signal(image_noise=False, amplitude=1, with_vacancies=False)ΒΆ
    +
    +temul.dummy_data.get_simple_cubic_signal(image_noise=False, amplitude=1, with_vacancies=False)ΒΆ

    Generate a test image signal of a simple cubic atomic structure.

    Parameters
      -
    • image_noise (Bool, default False) – If set to True, will add Gaussian noise to the image.

    • -
    • amplitude (int, list of ints, default 1) – If amplitude is set to an int, that int will be applied to all atoms in +

    • image_noise (bool, default False) – If set to True, will add Gaussian noise to the image.

    • +
    • amplitude (int, list of ints, default 1) – If amplitude is set to an int, that int will be applied to all atoms in the sublattice. If amplitude is set to a list, the atoms will be a distribution set by np.random.randint between the min and max int.

    • -
    • with_vacancies (Bool, default False) – If set to True, the returned signal or sublattice will have some +

    • with_vacancies (bool, default False) – If set to True, the returned signal or sublattice will have some vacancies.

    @@ -4226,18 +3899,18 @@

    Modules -
    -temul.dummy_data.get_simple_cubic_sublattice(image_noise=False, amplitude=1, with_vacancies=False)ΒΆ
    +
    +temul.dummy_data.get_simple_cubic_sublattice(image_noise=False, amplitude=1, with_vacancies=False)ΒΆ

    Generate a test sublattice of a simple cubic atomic structure.

    Parameters
      -
    • image_noise (Bool, default False) – If set to True, will add Gaussian noise to the image.

    • -
    • amplitude (int, list of ints, default 1) – If amplitude is set to an int, that int will be applied to all atoms in +

    • image_noise (bool, default False) – If set to True, will add Gaussian noise to the image.

    • +
    • amplitude (int, list of ints, default 1) – If amplitude is set to an int, that int will be applied to all atoms in the sublattice. If amplitude is set to a list, the atoms will be a distribution set by np.random.randint between the min and max int.

    • -
    • with_vacancies (Bool, default False) – If set to True, the returned signal or sublattice will have some +

    • with_vacancies (bool, default False) – If set to True, the returned signal or sublattice will have some vacancies.

    @@ -4254,12 +3927,12 @@

    Modules>>> sublattice.plot() -

    If you want different atom amplitudes, use amplitude

    +

    If you want different atom amplitudes, use amplitude

    >>> sublattice = get_simple_cubic_sublattice(
     ...     amplitude=[1, 5])
     
    -

    Do not set amplitude to two consecutive numbers, as only amplitudes of +

    Do not set amplitude to two consecutive numbers, as only amplitudes of the lower number (2 below) will be set, see numpy.random.randint for info.

    >>> sublattice = get_simple_cubic_sublattice(
     ...     amplitude=[2,3])
    @@ -4268,20 +3941,20 @@ 

    Modules -
    -temul.dummy_data.get_simple_cubic_sublattice_positions_on_vac(image_noise=False)ΒΆ
    -

    Create a simple cubic structure similar to get_simple_cubic_sublattice +

    +temul.dummy_data.get_simple_cubic_sublattice_positions_on_vac(image_noise=False)ΒΆ
    +

    Create a simple cubic structure similar to get_simple_cubic_sublattice above but the atom positions are also overlaid on the vacancy positions.

    -
    -temul.dummy_data.make_polarised_sublattice_bora_return(image_noise=False)ΒΆ
    +
    +temul.dummy_data.make_polarised_sublattice_bora_return(image_noise=False)ΒΆ
    -
    -temul.dummy_data.polarisation_colorwheel_test_dataset(cmap=<matplotlib.colors.LinearSegmentedColormap object>, plot_XY=True, degrees=False, normalise=False)ΒΆ
    +
    +temul.dummy_data.polarisation_colorwheel_test_dataset(cmap=<matplotlib.colors.LinearSegmentedColormap object>, plot_XY=True, degrees=False, normalise=False)ΒΆ

    Check how the arrows will be plotted on a colorwheel. Note that for STEM images, the y axis is reversed. This is taken into account in the plot_polarisation_vectors function, but not here.

    @@ -4320,16 +3993,16 @@

    Modules -
    -temul.dummy_data.sine_wave_sublattice()ΒΆ
    +
    +temul.dummy_data.sine_wave_sublattice()ΒΆ

    Example DataΒΆ

    -
    -temul.example_data.load_Se_implanted_MoS2_data()ΒΆ
    +
    +temul.example_data.load_Se_implanted_MoS2_data()ΒΆ

    Load an ADF image of Se implanted monolayer MoS2.

    Example

    >>> import temul.example_data as example_data
    @@ -4340,8 +4013,8 @@ 

    Modules -
    -temul.example_data.load_Se_implanted_MoS2_simulation()ΒΆ
    +
    +temul.example_data.load_Se_implanted_MoS2_simulation()ΒΆ

    Get the simulated image of an MoS2 monolayer

    Example

    >>> import temul.example_data as example_data
    @@ -4352,8 +4025,8 @@ 

    Modules -
    -temul.example_data.load_example_Au_nanoparticle()ΒΆ
    +
    +temul.example_data.load_example_Au_nanoparticle()ΒΆ

    Get the emd STEM image of an example Au nanoparticle

    Example

    >>> import temul.example_data as example_data
    @@ -4364,8 +4037,8 @@ 

    Modules -
    -temul.example_data.load_example_Cu_nanoparticle_sim()ΒΆ
    +
    +temul.example_data.load_example_Cu_nanoparticle_sim()ΒΆ

    Get the hspy simulated image of an example Cu nanoparticle

    Example

    >>> import temul.example_data as example_data
    @@ -4376,8 +4049,8 @@ 

    Modules -
    -temul.example_data.path_to_example_data_MoS2_hex_prismatic()ΒΆ
    +
    +temul.example_data.path_to_example_data_MoS2_hex_prismatic()ΒΆ

    Get the path of the xyz file for monolayer MoS2

    Example

    >>> import temul.example_data as example_data
    @@ -4387,8 +4060,8 @@ 

    Modules -
    -temul.example_data.path_to_example_data_MoS2_vesta_xyz()ΒΆ
    +
    +temul.example_data.path_to_example_data_MoS2_vesta_xyz()ΒΆ

    Get the path of the vesta xyz file for bilayer MoS2

    Example

    >>> import temul.example_data as example_data
    @@ -4406,35 +4079,28 @@ 

    Modules - - - - +

    -

    - - © Copyright 2020, Eoghan O'Connell + © Copyright 2020, Eoghan O'Connell.

    - Built with Sphinx using a + Built with Sphinx using a - theme + theme provided by Read the Docs. -

    diff --git a/doc/_build/html/define_roles.html b/doc/_build/html/define_roles.html index 6372a7d..9a354fd 100644 --- a/doc/_build/html/define_roles.html +++ b/doc/_build/html/define_roles.html @@ -3,9 +3,9 @@ - + - + <no title> — TEMUL Toolkit v0.1.2 documentation @@ -13,23 +13,28 @@ + + + + + + - @@ -49,7 +54,7 @@ - TEMUL Toolkit + TEMUL Toolkit @@ -97,7 +102,6 @@
  • Masked FFT and iFFT
  • Line Intensity Profile Comparisons
  • Interactive Image Filtering
  • -
  • Analysis of PTO Domain Wall Junction
  • API documentation
  • @@ -139,6 +143,8 @@ + +
    -

    - - © Copyright 2020, Eoghan O'Connell + © Copyright 2020, Eoghan O'Connell.

    - Built with Sphinx using a + Built with Sphinx using a - theme + theme provided by Read the Docs.
    -

    diff --git a/doc/_build/html/dg_visualiser_tutorial.html b/doc/_build/html/dg_visualiser_tutorial.html index 867f6b6..e090cc6 100644 --- a/doc/_build/html/dg_visualiser_tutorial.html +++ b/doc/_build/html/dg_visualiser_tutorial.html @@ -3,9 +3,9 @@ - + - + Interactive Image Filtering — TEMUL Toolkit v0.1.2 documentation @@ -13,23 +13,28 @@ + + + + + + - @@ -51,7 +56,7 @@ - TEMUL Toolkit + TEMUL Toolkit @@ -104,7 +109,6 @@
  • Return the Filtered Image
  • -
  • Analysis of PTO Domain Wall Junction
  • API documentation
  • @@ -146,6 +150,8 @@ + +
    -

    - - © Copyright 2020, Eoghan O'Connell + © Copyright 2020, Eoghan O'Connell.

    - Built with Sphinx using a + Built with Sphinx using a - theme + theme provided by Read the Docs. -

    diff --git a/doc/_build/html/genindex.html b/doc/_build/html/genindex.html index f56107b..8883a1d 100644 --- a/doc/_build/html/genindex.html +++ b/doc/_build/html/genindex.html @@ -3,9 +3,9 @@ - + - + Index — TEMUL Toolkit v0.1.2 documentation @@ -13,23 +13,28 @@ + + + + + + - @@ -49,7 +54,7 @@ - TEMUL Toolkit + TEMUL Toolkit @@ -138,6 +143,8 @@ + +
    -

    - - © Copyright 2020, Eoghan O'Connell + © Copyright 2020, Eoghan O'Connell.

    - Built with Sphinx using a + Built with Sphinx using a - theme + theme provided by Read the Docs.
    -

    diff --git a/doc/_build/html/search.html b/doc/_build/html/search.html index 21f2ef4..36e894e 100644 --- a/doc/_build/html/search.html +++ b/doc/_build/html/search.html @@ -3,9 +3,9 @@ - + - + Search — TEMUL Toolkit v0.1.2 documentation @@ -13,10 +13,15 @@ + + + + + @@ -27,15 +32,16 @@ + - + @@ -51,7 +57,7 @@ - TEMUL Toolkit + TEMUL Toolkit @@ -140,6 +146,8 @@ + +
      @@ -151,8 +159,6 @@
    • - -
    @@ -180,28 +186,25 @@
    -

    diff --git a/doc/_build/html/searchindex.js b/doc/_build/html/searchindex.js index 22b0c4f..7735388 100644 --- a/doc/_build/html/searchindex.js +++ b/doc/_build/html/searchindex.js @@ -1 +1 @@ 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of PTO Domain Wall Junction","Calculation of Atom Plane Curvature","API documentation","<no title>","Interactive Image Filtering","Welcome to TEMUL Toolkit\u2019s documentation!","Installation","Line Intensity Profile Comparisons","Masked FFT and iFFT","News","Finding Polarisation Vectors","Plot Lattice Structure Maps","Getting started","Analysis 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\ No newline at end of file diff --git a/doc/_build/html/structure_map_tutorial.html b/doc/_build/html/structure_map_tutorial.html index dc2d389..dbe2a00 100644 --- a/doc/_build/html/structure_map_tutorial.html +++ b/doc/_build/html/structure_map_tutorial.html @@ -3,9 +3,9 @@ - + - + Plot Lattice Structure Maps — TEMUL Toolkit v0.1.2 documentation @@ -13,23 +13,28 @@ + + + + + + - @@ -51,7 +56,7 @@ - TEMUL Toolkit + TEMUL Toolkit @@ -105,7 +110,6 @@
  • Masked FFT and iFFT
  • Line Intensity Profile Comparisons
  • Interactive Image Filtering
  • -
  • Analysis of PTO Domain Wall Junction
  • API documentation
  • @@ -147,6 +151,8 @@ + +
    -

    - - © Copyright 2020, Eoghan O'Connell + © Copyright 2020, Eoghan O'Connell.

    - Built with Sphinx using a + Built with Sphinx using a - theme + theme provided by Read the Docs. -
    diff --git a/doc/_build/html/using_temul.html b/doc/_build/html/using_temul.html index 4052dbd..40ade1b 100644 --- a/doc/_build/html/using_temul.html +++ b/doc/_build/html/using_temul.html @@ -3,9 +3,9 @@ - + - + Getting started — TEMUL Toolkit v0.1.2 documentation @@ -13,23 +13,28 @@ + + + + + + - @@ -51,7 +56,7 @@ - TEMUL Toolkit + TEMUL Toolkit @@ -99,7 +104,6 @@
  • Masked FFT and iFFT
  • Line Intensity Profile Comparisons
  • Interactive Image Filtering
  • -
  • Analysis of PTO Domain Wall Junction
  • API documentation
  • @@ -141,6 +145,8 @@ + +
      @@ -152,7 +158,7 @@
    • - + View page source @@ -173,6 +179,11 @@

      Checkout the tutorials in the table of contents above or on the left of the page. One can also view the extensive documentation, where each function is described and examples of their use given.

      +

      To use the vast majority of the temul functionality, +import it from the api module:

      +
      import temul.api as tml
      +
      +
    @@ -180,37 +191,29 @@ - diff --git a/doc/_build/html/workflows.html b/doc/_build/html/workflows.html index db14c4e..c60b2fd 100644 --- a/doc/_build/html/workflows.html +++ b/doc/_build/html/workflows.html @@ -3,9 +3,9 @@ - + - + Analysis Workflows — TEMUL Toolkit v0.1.2 documentation @@ -13,23 +13,28 @@ + + + + + + - @@ -51,7 +56,7 @@ - TEMUL Toolkit + TEMUL Toolkit @@ -99,7 +104,6 @@
  • Masked FFT and iFFT
  • Line Intensity Profile Comparisons
  • Interactive Image Filtering
  • -
  • Analysis of PTO Domain Wall Junction
  • API documentation
  • @@ -141,6 +145,8 @@ + +
    - diff --git a/doc/api_doc.rst b/doc/api_doc.rst index 9df620b..d038844 100644 --- a/doc/api_doc.rst +++ b/doc/api_doc.rst @@ -9,6 +9,9 @@ Classes Model Refiner ============= +.. This won't work because PyPrismatic isn't dependency + This of course needs to be fixed, but the fix is to + overhaul the Model Refiner class .. autoclass:: temul.model_refiner.Model_Refiner :members: :undoc-members: @@ -17,9 +20,17 @@ Model Refiner Modules ------- -Polarisation -============ -.. automodule:: temul.polarisation +TopoTEM (Polarisation) +====================== +.. automodule:: temul.topotem.polarisation + :members: + :undoc-members: + +.. automodule:: temul.topotem.fft_mapping + :members: + :undoc-members: + +.. automodule:: temul.topotem.lattice_structure_tools :members: :undoc-members: diff --git a/temul/api_with_prismatic.py b/temul/api_with_prismatic.py index adb3bf8..47119da 100644 --- a/temul/api_with_prismatic.py +++ b/temul/api_with_prismatic.py @@ -1,10 +1,10 @@ -''' +""" Call this file if you want to use the pyprismatic functions or Model_Refiner class. Currently, model_refiner.py and simulations.py use pyprismatic. -''' +""" # flake8: noqa diff --git a/temul/atomap_devel_temp.py b/temul/atomap_devel_temp.py index d5ba3a7..ecc15d4 100644 --- a/temul/atomap_devel_temp.py +++ b/temul/atomap_devel_temp.py @@ -1,4 +1,4 @@ -''' +""" Should make a PR on atomap for these changes. They are in EOC's personal atomap version. @@ -113,4 +113,4 @@ def add_atoms_with_gui(image, atom_list=None, distance_threshold=4, vmin=vmin, vmax=vmax) new_atom_list = atom_adder_remover.atom_list return new_atom_list -''' +""" diff --git a/temul/dummy_data.py b/temul/dummy_data.py index 50b5f1a..9fadd35 100644 --- a/temul/dummy_data.py +++ b/temul/dummy_data.py @@ -17,14 +17,14 @@ def _make_simple_cubic_testdata(image_noise=False, amplitude=1, """ Parameters ---------- - image_noise : Bool, default False + image_noise : bool, default False If set to True, will add Gaussian noise to the image. amplitude : int, list of ints, default 1 If amplitude is set to an int, that int will be applied to all atoms in the sublattice. If amplitude is set to a list, the atoms will be a distribution set by np.random.randint between the min and max int. - with_vacancies : Bool, default False + with_vacancies : bool, default False If set to True, the returned signal or sublattice will have some vacancies. """ @@ -53,14 +53,14 @@ def get_simple_cubic_signal(image_noise=False, amplitude=1, Parameters ---------- - image_noise : Bool, default False + image_noise : bool, default False If set to True, will add Gaussian noise to the image. amplitude : int, list of ints, default 1 If amplitude is set to an int, that int will be applied to all atoms in the sublattice. If amplitude is set to a list, the atoms will be a distribution set by np.random.randint between the min and max int. - with_vacancies : Bool, default False + with_vacancies : bool, default False If set to True, the returned signal or sublattice will have some vacancies. @@ -87,14 +87,14 @@ def get_simple_cubic_sublattice(image_noise=False, amplitude=1, Parameters ---------- - image_noise : Bool, default False + image_noise : bool, default False If set to True, will add Gaussian noise to the image. amplitude : int, list of ints, default 1 If amplitude is set to an int, that int will be applied to all atoms in the sublattice. If amplitude is set to a list, the atoms will be a distribution set by np.random.randint between the min and max int. - with_vacancies : Bool, default False + with_vacancies : bool, default False If set to True, the returned signal or sublattice will have some vacancies. @@ -108,12 +108,12 @@ def get_simple_cubic_sublattice(image_noise=False, amplitude=1, >>> sublattice = get_simple_cubic_sublattice() >>> sublattice.plot() - If you want different atom amplitudes, use `amplitude` + If you want different atom amplitudes, use ``amplitude`` >>> sublattice = get_simple_cubic_sublattice( ... amplitude=[1, 5]) - Do not set `amplitude` to two consecutive numbers, as only amplitudes of + Do not set ``amplitude`` to two consecutive numbers, as only amplitudes of the lower number (2 below) will be set, see numpy.random.randint for info. >>> sublattice = get_simple_cubic_sublattice( @@ -128,10 +128,10 @@ def get_simple_cubic_sublattice(image_noise=False, amplitude=1, def get_simple_cubic_sublattice_positions_on_vac(image_noise=False): - ''' - Create a simple cubic structure similar to `get_simple_cubic_sublattice` + """ + Create a simple cubic structure similar to ``get_simple_cubic_sublattice`` above but the atom positions are also overlaid on the vacancy positions. - ''' + """ temp_sub = _make_simple_cubic_testdata(image_noise=image_noise, with_vacancies=False).sublattice diff --git a/temul/element_tools.py b/temul/element_tools.py index 4cbc9f8..2db77f3 100644 --- a/temul/element_tools.py +++ b/temul/element_tools.py @@ -5,7 +5,7 @@ def get_and_return_element(element_symbol): - ''' + """ From the elemental symbol, e.g., 'H' for Hydrogen, provides Hydrogen as a periodictable.core.Element object for further use. @@ -32,7 +32,7 @@ def get_and_return_element(element_symbol): >>> print(Moly.number) 42 - ''' + """ for pt_element in pt.elements: if pt_element.symbol == element_symbol: @@ -42,7 +42,7 @@ def get_and_return_element(element_symbol): def atomic_radii_in_pixels(sampling, element_symbol): - ''' + """ Get the atomic radius of an element in pixels, scaled by an image sampling Parameters @@ -73,7 +73,7 @@ def atomic_radii_in_pixels(sampling, element_symbol): >>> radius_pix_S 2.28 - ''' + """ element = get_and_return_element(element_symbol=element_symbol) @@ -87,7 +87,7 @@ def atomic_radii_in_pixels(sampling, element_symbol): def split_and_sort_element(element, split_symbol=['_', '.']): - ''' + """ Extracts info from input atomic column element configuration Split an element and its count, then sort the element for use with other functions. @@ -127,7 +127,7 @@ def split_and_sort_element(element, split_symbol=['_', '.']): >>> info = split_and_sort_element(element='O_6.Mo_3.Ti_5') - ''' + """ splitting_info = [] if '.' in element: @@ -229,9 +229,9 @@ def get_individual_elements_from_element_list( def combine_element_lists(lists): - ''' Reduce multiple element_lists into one list of strings from a list of - lists, useful for the `Model Refiner` `flattened_element_list`. - ''' + """ Reduce multiple element_lists into one list of strings from a list of + lists, useful for the ``Model Refiner`` ``flattened_element_list``. + """ element_list = [i for sublist in lists for i in sublist] element_list = list(set(element_list)) diff --git a/temul/example_scripts.py b/temul/example_scripts.py index 9fd968c..713471d 100644 --- a/temul/example_scripts.py +++ b/temul/example_scripts.py @@ -1,5 +1,5 @@ -''' +""" from temul.model_creation import get_max_number_atoms_z from temul.signal_processing import (get_xydata_from_list_of_intensities, return_fitting_of_1D_gaussian, @@ -384,8 +384,8 @@ ######## Simulate MoS2 with Prismatic Example ######## -''' -''' +""" +""" Steps 1. get the path to the example data @@ -398,10 +398,10 @@ the experimental(reference) image to calculate the probeStep(sampling). Only works if the reference image is loaded into python as a hyperspy 2D signal and if the image is calibrated. -''' +""" -''' +""" # Step 1 @@ -1150,13 +1150,13 @@ #################### import temul.api as tml -''' +""" # Image Registration # def rigid_registration(file, masktype='hann', n=4, findMaxima='gf'): -''' +""" Perform image registraion with the rigid registration package Parameters @@ -1191,8 +1191,8 @@ >>> -''' -''' +""" +""" # Read tiff file. Rearrange axes so final axis iterates over images stack = np.rollaxis(imread(file), 0, 3) @@ -1246,4 +1246,4 @@ # creates a folder and put all the individual images in there save_individual_images_from_image_stack(image_stack=s.stack_registered) -''' +""" diff --git a/temul/external/atomap_devel_012/atom_finding_refining.py b/temul/external/atomap_devel_012/atom_finding_refining.py index d9d8a10..262e0e6 100644 --- a/temul/external/atomap_devel_012/atom_finding_refining.py +++ b/temul/external/atomap_devel_012/atom_finding_refining.py @@ -430,7 +430,7 @@ def _make_circular_mask(centerX, centerY, imageSizeX, imageSizeY, radius): Returns ------- - Boolean Numpy 2D Array + boolean Numpy 2D Array Array with the shape (imageSizeX, imageSizeY) with the mask. See also @@ -622,7 +622,7 @@ def _make_model_from_atom_list( mask_radius : float, optional Radius of the mask around each atom. If this is not set, the radius will be the distance to the nearest atom in the - same sublattice times the `percent_to_nn` value. + same sublattice times the ``percent_to_nn`` value. Returns ------- @@ -712,7 +712,7 @@ def _fit_atom_positions_with_gaussian_model( mask_radius : float, optional Radius of the mask around each atom. If this is not set, the radius will be the distance to the nearest atom in the - same sublattice times the `percent_to_nn` value. + same sublattice times the ``percent_to_nn`` value. centre_free : bool, optional If True (default), the gaussian will be free to move. Setting this to False can be used to find better values for the other parameters @@ -826,8 +826,8 @@ def fit_atom_positions_gaussian( mask_radius : float, optional Radius of the mask around each atom. If this is not set, the radius will be the distance to the nearest atom in the - same sublattice times the `percent_to_nn` value. - Note: if `mask_radius` is not specified, the Atom_Position objects + same sublattice times the ``percent_to_nn`` value. + Note: if ``mask_radius`` is not specified, the Atom_Position objects must have a populated nearest_neighbor_list. This is normally done through the sublattice class, but can also be done manually. See below for an example how to do this. @@ -866,7 +866,7 @@ def fit_atom_positions_gaussian( >>> g_list = fit_atom_positions_gaussian( ... atom_list=atom_list, image_data=image, mask_radius=2) - Not using `mask_radius`, populating the nearest_neighbor_list manually + Not using ``mask_radius``, populating the nearest_neighbor_list manually >>> image = np.zeros((9, 9)) >>> image[2, 2] = 1. diff --git a/temul/external/atomap_devel_012/atom_position.py b/temul/external/atomap_devel_012/atom_position.py index f81e42a..352c9be 100644 --- a/temul/external/atomap_devel_012/atom_position.py +++ b/temul/external/atomap_devel_012/atom_position.py @@ -560,8 +560,8 @@ def refine_position_using_2d_gaussian( mask_radius : float, optional Radius of the mask around each atom. If this is not set, the radius will be the distance to the nearest atom in the - same sublattice times the `percent_to_nn` value. - Note: if `mask_radius` is not specified, the Atom_Position objects + same sublattice times the ``percent_to_nn`` value. + Note: if ``mask_radius`` is not specified, the Atom_Position objects must have a populated nearest_neighbor_list. centre_free : bool, default True If True, the centre parameter will be free, meaning that diff --git a/temul/external/atomap_devel_012/atom_position_old.py b/temul/external/atomap_devel_012/atom_position_old.py index 576e34a..52c7bc1 100644 --- a/temul/external/atomap_devel_012/atom_position_old.py +++ b/temul/external/atomap_devel_012/atom_position_old.py @@ -392,8 +392,8 @@ def refine_position_using_2d_gaussian( mask_radius : float, optional Radius of the mask around each atom. If this is not set, the radius will be the distance to the nearest atom in the - same sublattice times the `percent_to_nn` value. - Note: if `mask_radius` is not specified, the Atom_Position objects + same sublattice times the ``percent_to_nn`` value. + Note: if ``mask_radius`` is not specified, the Atom_Position objects must have a populated nearest_neighbor_list. centre_free : bool, default True If True, the centre parameter will be free, meaning that diff --git a/temul/external/atomap_devel_012/external/add_marker.py b/temul/external/atomap_devel_012/external/add_marker.py index f97de0a..a5ec19d 100644 --- a/temul/external/atomap_devel_012/external/add_marker.py +++ b/temul/external/atomap_devel_012/external/add_marker.py @@ -13,7 +13,7 @@ def add_marker( ---------- marker : marker object or iterable of marker objects The marker or iterable (list, tuple, ...) of markers to add. - See `plot.markers`. If you want to add a large number of markers, + See ``plot.markers``. If you want to add a large number of markers, add them as an iterable, since this will be much faster. plot_on_signal : bool, default True If True, add the marker to the signal diff --git a/temul/external/atomap_devel_012/external/gaussian2d.py b/temul/external/atomap_devel_012/external/gaussian2d.py index 608b0bd..24854b2 100644 --- a/temul/external/atomap_devel_012/external/gaussian2d.py +++ b/temul/external/atomap_devel_012/external/gaussian2d.py @@ -48,12 +48,12 @@ class Gaussian2D(Component): rotation_degrees which will give the angle between the x-axis and the major axis, ergo between the x-axis and the highest sigma. - For convenience the `fwhm_x` and `fwhm_y` attributes can be used to + For convenience the ``fwhm_x`` and ``fwhm_y`` attributes can be used to get and set the full-with-half-maximums. - The `ellipticity` attribute returns `sigma_x`/`sigma_y`. + The ``ellipticity`` attribute returns ``sigma_x`/`sigma_y``. - The `rotation_degrees` attribute returns the angle between + The ``rotation_degrees`` attribute returns the angle between the major axis (the largest sigma), and the positive horizontal axis. """ diff --git a/temul/external/atomap_devel_012/initial_position_finding.py b/temul/external/atomap_devel_012/initial_position_finding.py index 978ac33..5d9a7d8 100644 --- a/temul/external/atomap_devel_012/initial_position_finding.py +++ b/temul/external/atomap_devel_012/initial_position_finding.py @@ -170,10 +170,10 @@ def make_atom_lattice_dumbbell_structure( return(atom_lattice) -''' +""" The log and norm functionality has been added to the atomap upstream master -''' +""" class AtomAdderRemover: diff --git a/temul/external/atomap_devel_012/quantification.py b/temul/external/atomap_devel_012/quantification.py index d883605..af6da10 100644 --- a/temul/external/atomap_devel_012/quantification.py +++ b/temul/external/atomap_devel_012/quantification.py @@ -43,7 +43,7 @@ def _detector_threshold(det_image): Returns ------- threshold_image : NumPy array - Boolean image demonstrating the active region of the detector. + boolean image demonstrating the active region of the detector. Example ------- diff --git a/temul/external/atomap_devel_012/sublattice.py b/temul/external/atomap_devel_012/sublattice.py index e91f129..27ab6a0 100644 --- a/temul/external/atomap_devel_012/sublattice.py +++ b/temul/external/atomap_devel_012/sublattice.py @@ -932,8 +932,8 @@ def refine_atom_positions_using_2d_gaussian( mask_radius : float, optional Radius of the mask around each atom. If this is not set, the radius will be the distance to the nearest atom in the - same sublattice times the `percent_to_nn` value. - Note: if `mask_radius` is not specified, the Atom_Position objects + same sublattice times the ``percent_to_nn`` value. + Note: if ``mask_radius`` is not specified, the Atom_Position objects must have a populated nearest_neighbor_list. rotation_enabled : bool, default True If True, rotation will be enabled for the 2D Gaussians. @@ -1567,14 +1567,14 @@ def get_atom_list_on_image( color=color, markersize=markersize, add_numbers=add_numbers) - ''' + """ element_list = _make_atom_position_element_list( atom_list, scale=self.pixel_size, color=color, markersize=markersize, add_element=add_element) - ''' + """ signal = at.array2signal2d(image, self.pixel_size) add_marker(signal, marker_list, permanent=True, plot_marker=False) diff --git a/temul/external/skimage_devel_0162/profile.py b/temul/external/skimage_devel_0162/profile.py index 27c6dc8..50682c6 100644 --- a/temul/external/skimage_devel_0162/profile.py +++ b/temul/external/skimage_devel_0162/profile.py @@ -26,10 +26,10 @@ def profile_line(image, src, dst, linewidth=1, mode : {'constant', 'nearest', 'reflect', 'mirror', 'wrap'}, optional How to compute any values falling outside of the image. cval : float, optional - If `mode` is 'constant', what constant value to use outside the image. + If ``mode`` is 'constant', what constant value to use outside the image. reduce_func : callable, optional Function used to calculate the aggregation of pixel values - perpendicular to the profile_line direction when `linewidth` > 1. + perpendicular to the profile_line direction when ``linewidth`` > 1. If set to None the unreduced array will be returned. Returns @@ -71,8 +71,8 @@ def profile_line(image, src, dst, linewidth=1, >>> profile_line(img, (1, 0), (1, 3), linewidth=3, reduce_func=np.sum) array([2, 2, 2, 4]) - The unreduced array will be returned when `reduce_func` is None or when - `reduce_func` acts on each pixel value individually. + The unreduced array will be returned when ``reduce_func`` is None or when + ``reduce_func`` acts on each pixel value individually. >>> profile_line(img, (1, 2), (4, 2), linewidth=3, order=0, ... reduce_func=None) diff --git a/temul/intensity_tools.py b/temul/intensity_tools.py index d4898cb..16a3c9c 100644 --- a/temul/intensity_tools.py +++ b/temul/intensity_tools.py @@ -10,7 +10,7 @@ def get_sublattice_intensity(sublattice, num_points=3, percent_to_nn=0.4, mask_radius=None): - ''' + """ Finds the intensity for each atomic column using either max, mean, min, total or all of them at once. @@ -44,12 +44,12 @@ def get_sublattice_intensity(sublattice, Determines the boundary of the area surrounding each atomic column, as fraction of the distance to the nearest neighbour. mask_radius : float - Radius of the atomic column in pixels. If chosen, `percent_to_nn` must + Radius of the atomic column in pixels. If chosen, ``percent_to_nn`` must be None. Returns ------- - Numpy array, shape depending on `intensity_type` + Numpy array, shape depending on ``intensity_type`` Examples -------- @@ -90,7 +90,7 @@ def get_sublattice_intensity(sublattice, ... remove_background_method="average", ... background_sub=sublattice) - ''' + """ if percent_to_nn is not None: sublattice.find_nearest_neighbors() else: @@ -224,7 +224,7 @@ def get_sublattice_intensity(sublattice, def remove_average_background(sublattice, intensity_type, background_sub, percent_to_nn=0.40, mask_radius=None): - ''' + """ Remove the average background from a sublattice intensity using a background sublattice. @@ -242,12 +242,12 @@ def remove_average_background(sublattice, intensity_type, Determines the boundary of the area surrounding each atomic column, as fraction of the distance to the nearest neighbour. mask_radius : float - Radius of the atomic column in pixels. If chosen, `percent_to_nn` must + Radius of the atomic column in pixels. If chosen, ``percent_to_nn`` must be None. Returns ------- - Numpy array, shape depending on `intensity_type` + Numpy array, shape depending on ``intensity_type`` Examples -------- @@ -264,7 +264,7 @@ def remove_average_background(sublattice, intensity_type, ... sublattice, intensity_type="max", ... background_sub=sublattice) - ''' + """ background_sub.find_nearest_neighbors() background_sub.get_atom_column_amplitude_min_intensity( percent_to_nn=percent_to_nn, mask_radius=mask_radius) @@ -368,7 +368,7 @@ def remove_average_background(sublattice, intensity_type, pass -''' +""" sublattice0 = dummy_data.get_simple_cubic_sublattice() inten = get_sublattice_intensity(sublattice=sublattice0, @@ -379,13 +379,13 @@ def remove_average_background(sublattice, intensity_type, can make the mean/mode option better: code blocks aren't needed, just put the if statement lower down where the change is... -''' +""" def remove_local_background(sublattice, background_sub, intensity_type, num_points=3, percent_to_nn=0.40, mask_radius=None): - ''' + """ Remove the local background from a sublattice intensity using a background sublattice. @@ -406,12 +406,12 @@ def remove_local_background(sublattice, background_sub, intensity_type, Determines the boundary of the area surrounding each atomic column, as fraction of the distance to the nearest neighbour. mask_radius : float - Radius of the atomic column in pixels. If chosen, `percent_to_nn` must + Radius of the atomic column in pixels. If chosen, ``percent_to_nn`` must be None. Returns ------- - Numpy array, shape depending on `intensity_type` + Numpy array, shape depending on ``intensity_type`` Examples -------- @@ -427,7 +427,7 @@ def remove_local_background(sublattice, background_sub, intensity_type, ... sublattice, intensity_type="max", ... background_sub=sublattice) - ''' + """ # get background_sub intensity list if percent_to_nn is not None: diff --git a/temul/io.py b/temul/io.py index 8def909..97c330f 100644 --- a/temul/io.py +++ b/temul/io.py @@ -28,11 +28,11 @@ def batch_convert_emd_to_image(extension_to_save, top_level_directory : string The top-level directory in which the emd files exist. The default glob_search will search this directory and all subdirectories. - glob_search : string, default "**/*" + glob_search : string Glob search string, see glob for more details: https://docs.python.org/2/library/glob.html Default will search this directory and all subdirectories. - overwrite : Bool, default True + overwrite : bool, default True Overwrite if the extension_to_save file already exists. """ @@ -137,7 +137,7 @@ def convert_vesta_xyz_to_prismatic_xyz(vesta_xyz_filename, edge_padding=None, header_comment="Let's make a file!", save=True): - ''' + """ Convert from Vesta outputted xyz file format to the prismatic-style xyz format. Lose some information from the .cif or .vesta file but okay for now. @@ -161,7 +161,7 @@ def convert_vesta_xyz_to_prismatic_xyz(vesta_xyz_filename, use a format other than vesta xyz. Maybe .cif or .vesta keeps these? header_comment : string header comment for the file. - save : Bool, default True + save : bool, default True whether to output the file as a prismatic formatted xyz file with the name of the file given by "prismatic_xyz_filename". @@ -182,7 +182,7 @@ def convert_vesta_xyz_to_prismatic_xyz(vesta_xyz_filename, ... engine='python', occupancy=1.0, rms_thermal_vib=0.05, ... header_comment="Let's do this!", save=True) - ''' + """ file = pd.read_csv(vesta_xyz_filename, delimiter=delimiter, @@ -511,7 +511,7 @@ def dm3_stack_to_tiff_stack(loading_file, crop=False, crop_start=20.0, crop_end=80.0): - ''' + """ Save an image stack filetype to a different filetype, e.g., dm3 to tiff. Parameters @@ -528,7 +528,7 @@ def dm3_stack_to_tiff_stack(loading_file, crop_start, crop_end : float, default 20.0, 80.0 the start and end frame of the crop - ''' + """ if '.' in loading_file: file = loading_file filename = loading_file[:-4] @@ -555,7 +555,7 @@ def dm3_stack_to_tiff_stack(loading_file, def save_individual_images_from_image_stack( image_stack, output_folder='individual_images'): - ''' + """ Save each image in an image stack. The images are saved in a new folder. Useful for after running an image series through Rigid Registration. @@ -566,7 +566,7 @@ def save_individual_images_from_image_stack( Name of the folder in which all individual images from the stack will be saved. - ''' + """ # Save each image as a 32 bit tiff )cqn be displayed in DM image_stack_32bit = np.float32(image_stack) folder = os.mkdir(output_folder) @@ -579,7 +579,7 @@ def save_individual_images_from_image_stack( def load_prismatic_mrc_with_hyperspy( prismatic_mrc_filename, save_name='calibrated_data_'): - ''' + """ We are aware this is currently producing errors with new versions of Prismatic. @@ -603,7 +603,7 @@ def load_prismatic_mrc_with_hyperspy( ... "prism_2Doutput_prismatic_simulation.mrc") - ''' + """ # if '.mrc' not in prismatic_mrc_filename: # prismatic_mrc_filename = prismatic_mrc_filename + 'mrc' diff --git a/temul/lattice_structure_tools.py b/temul/lattice_structure_tools.py index 67a80a6..ef2042d 100644 --- a/temul/lattice_structure_tools.py +++ b/temul/lattice_structure_tools.py @@ -2,6 +2,6 @@ raise DeprecationWarning( "\n WARNING: " "To use the lattice_structure_tools " - "functionality please use `import temul.api as tml`. " + "functionality please use ``import temul.api as tml``. " "The temul.lattice_structure_tools module is deprecated and is now " "`temul.topotem.lattice_structure_tools.\n") diff --git a/temul/model_creation.py b/temul/model_creation.py index c27a709..88e3677 100644 --- a/temul/model_creation.py +++ b/temul/model_creation.py @@ -15,7 +15,7 @@ def count_element_in_pandas_df(element, dataframe): - ''' + """ Count the number of a single element in a dataframe Parameters @@ -41,7 +41,7 @@ def count_element_in_pandas_df(element, dataframe): >>> Se_count Counter({0: 9, 1: 8}) - ''' + """ count_of_element = Counter() for element_config in dataframe.columns: @@ -61,7 +61,7 @@ def count_element_in_pandas_df(element, dataframe): def count_all_individual_elements(individual_element_list, dataframe): - ''' + """ Perform count_element_in_pandas_df() for all elements in a dataframe. Specify the elements you wish to count in the individual_element_list. @@ -87,7 +87,7 @@ def count_all_individual_elements(individual_element_list, dataframe): >>> element_count = count_all_individual_elements( ... individual_element_list, dataframe=df) - ''' + """ element_count_dict = {} @@ -102,7 +102,7 @@ def count_all_individual_elements(individual_element_list, dataframe): def count_atoms_in_sublattice_list(sublattice_list, filename=None): - ''' + """ Count the elements in a list of Atomap sublattices Parameters @@ -137,7 +137,7 @@ def count_atoms_in_sublattice_list(sublattice_list, filename=None): >>> no_added_atoms = count_atoms_in_sublattice_list( ... sublattice_list=at_lat_before.sublattice_list) - ''' + """ count_of_sublattice = Counter() for sublattice in sublattice_list: @@ -171,7 +171,7 @@ def count_atoms_in_sublattice_list(sublattice_list, filename=None): def compare_count_atoms_in_sublattice_list(counter_list): - ''' + """ Compare the count of atomap elements in two counter_lists gotten by count_atoms_in_sublattice_list() @@ -185,7 +185,7 @@ def compare_count_atoms_in_sublattice_list(counter_list): Returns ------- - Boolean True if the counters are equal, + boolean True if the counters are equal, boolean False is the counters are not equal. Examples @@ -218,7 +218,7 @@ def compare_count_atoms_in_sublattice_list(counter_list): if break loop: # >>> if compare_count_atoms_in_sublattice_list(counter_list) is True: # >>> break - ''' + """ if len(counter_list) == 2: counter0 = counter_list[0] @@ -230,7 +230,7 @@ def compare_count_atoms_in_sublattice_list(counter_list): def get_most_common_sublattice_element(sublattice, info='element'): - ''' + """ Find the most common element configuration in a sublattice. Parameters @@ -260,7 +260,7 @@ def get_most_common_sublattice_element(sublattice, info='element'): >>> get_most_common_sublattice_element(sublattice, info='z_height') '0.3, 0.6' - ''' + """ element_info = print_sublattice_elements(sublattice) @@ -283,7 +283,7 @@ def change_sublattice_atoms_via_intensity( element_list, verbose=False): - ''' + """ Change the elements in a sublattice object to a higher or lower combined atomic (Z) number. The aim is to change the sublattice elements so that the experimental image @@ -315,7 +315,7 @@ def change_sublattice_atoms_via_intensity( respectively. element_list : list list of element configurations - verbose : Bool, default False + verbose : bool, default False If set to True then atom warnings will be printed as output. Examples @@ -338,7 +338,7 @@ def change_sublattice_atoms_via_intensity( Changing some atoms - ''' + """ for atom in sublattice.atom_list: if atom.elements == '': # raise warning instead of error @@ -423,7 +423,7 @@ def image_difference_intensity(sublattice, mask_radius=None, change_sublattice=False, verbose=False): - ''' + """ Find the differences in a sublattice's atom_position intensities. Change the elements of these atom_positions depending on this difference of intensities. @@ -448,13 +448,13 @@ def image_difference_intensity(sublattice, mask_radius : float, default None Radius of the mask around each atom. If this is not set, the radius will be the distance to the nearest atom in the - same sublattice times the `percent_to_nn` value. - Note: if `mask_radius` is not specified, the Atom_Position objects + same sublattice times the ``percent_to_nn`` value. + Note: if ``mask_radius`` is not specified, the Atom_Position objects must have a populated nearest_neighbor_list. change_sublattice : bool, default False If change_sublattice is set to True, all incorrect element assignments will be corrected inplace. - verbose : Bool, default False + verbose : bool, default False If set to True then atom warnings will be printed as output. Example @@ -484,7 +484,7 @@ def image_difference_intensity(sublattice, ... sim_image=sim_image, ... element_list=element_list) - ''' + """ # np.array().T needs to be taken away for newer atomap versions sublattice_atom_positions = np.array(sublattice.atom_positions).T @@ -605,7 +605,7 @@ def image_difference_position_new_sub(sublattice_list, num_peaks=5, add_sublattice=False, sublattice_name='sub_new'): - ''' + """ Find new atomic coordinates by comparing experimental to simulated image. Create a new sublattice to store the new atomic coordinates. @@ -629,8 +629,8 @@ def image_difference_position_new_sub(sublattice_list, mask_radius : float, default None Radius of the mask around each atom. If this is not set, the radius will be the distance to the nearest atom in the - same sublattice times the `percent_to_nn` value. - Note: if `mask_radius` is not specified, the Atom_Position objects + same sublattice times the ``percent_to_nn`` value. + Note: if ``mask_radius`` is not specified, the Atom_Position objects must have a populated nearest_neighbor_list. num_peaks : int, default 5 number of new atoms to add @@ -675,7 +675,7 @@ def image_difference_position_new_sub(sublattice_list, ... num_peaks=5, ... add_sublattice=True) New Atoms Found! Adding to a new sublattice - ''' + """ image_for_sublattice = sublattice_list[0] diff_image = Signal2D( @@ -784,12 +784,12 @@ def image_difference_position_new_sub(sublattice_list, sub_new_exists = True if filename is not None: - ''' + """ diff_image.plot() diff_image_sub.plot() diff_image_inverse.plot() diff_image_sub_inverse.plot() - ''' + """ plt.figure() plt.suptitle('Image Difference Position' + filename) @@ -834,27 +834,23 @@ def scaling_z_contrast(numerator_sublattice, numerator_element, # make this more flexible, so that 'all' could be calculated in one go # simple loop should do that. - ''' + """ Find new atomic coordinates by comparing experimental to simulated image. Create a new sublattice to store the new atomic coordinates. The aim is to change the sublattice elements so that the experimental image - agrees with the simulated image in a realistic manner. + agrees with the simulated image in a realistic manner. See [2]_ Parameters ---------- numerator_sublattice : Sublattice object - Sublattice from which the numerator intensity will be calculated - according to Reference [1]. + Sublattice from which the numerator intensity will be calculated. numerator_element : string - Element from which the numerator atomic number will be taken - according to Reference [1]. + Element from which the numerator atomic number will be taken. denominator_sublattice : Sublattice object - Sublattice from which the denominator intensity will be calculated - according to Reference [1]. + Sublattice from which the denominator intensity will be calculated. denominator_element : string - Element from which the denominator atomic number will be taken - according to Reference [1]. + Element from which the denominator atomic number will be taken. intensity_type : string Determines the method used to find the sublattice intensities. The available methods are "max", "mean", "min", "total" and @@ -874,7 +870,7 @@ def scaling_z_contrast(numerator_sublattice, numerator_element, Determines the boundary of the area surrounding each atomic column, as fraction of the distance to the nearest neighbour. mask_radius : float - Radius of the atomic column in pixels. If chosen, `percent_to_nn` must + Radius of the atomic column in pixels. If chosen, ``percent_to_nn`` must be None. split_symbol : string, default '_' The symbols used to split the element into its name @@ -891,7 +887,7 @@ def scaling_z_contrast(numerator_sublattice, numerator_element, References ---------- - .. [1] Reference: Krivanek et al. Nature 464, 10.1038/nature08879, (2010) + .. [2] Krivanek et al. Nature 464, 10.1038/nature08879, (2010) Examples -------- @@ -924,7 +920,7 @@ def scaling_z_contrast(numerator_sublattice, numerator_element, ... add_sublattice=True) New Atoms Found! Adding to a new sublattice - ''' + """ if intensity_type == 'all': TypeError print('intensity_type must be "max", "mean", or "min"') @@ -1538,7 +1534,7 @@ def return_z_coordinates(z_thickness, max_number_atoms_z=None, fractional_coordinates=True, atom_layout='bot'): - ''' + """ Produce fractional z-dimension coordinates for a given thickness and bond length. @@ -1552,7 +1548,7 @@ def return_z_coordinates(z_thickness, number_atoms_z : integer, default None number of atoms in the z-dimension. If this is set to an interger value, it will override the use of z_thickness. - centered_atoms : Bool, default True + centered_atoms : bool, default True If set to True, the z_coordinates will be centered about 0.5. If set to False, the z_coordinate will start at 0.0. @@ -1566,7 +1562,7 @@ def return_z_coordinates(z_thickness, # >>> Au_NP_z_coord = return_z_coordinates(z_thickness=20, # z_bond_length=1.5) - ''' + """ if max_number_atoms_z is not None: # print("number_atoms_z has been specified, using @@ -1603,10 +1599,10 @@ def return_z_coordinates(z_thickness, return(z_coords) -''' +""" add intensity used for getting number, and index for later reference with sublattice -''' +""" def return_xyz_coordinates(x, y, @@ -1614,7 +1610,7 @@ def return_xyz_coordinates(x, y, number_atoms_z=None, fractional_coordinates=True, atom_layout='bot'): - ''' + """ Produce xyz coordinates for an xy coordinate given the z-dimension information. @@ -1639,7 +1635,7 @@ def return_xyz_coordinates(x, y, # ... z_bond_length=1.5, # ... number_atoms_z=5) - ''' + """ z_coords = return_z_coordinates( number_atoms_z=number_atoms_z, @@ -1704,7 +1700,7 @@ def assign_z_height_to_sublattice(sublattice, material=None, fractional_coordinates=True, atom_layout='bot'): - ''' + """ Set the z_heights for each atom position in a sublattice. Parameters @@ -1715,7 +1711,7 @@ def assign_z_height_to_sublattice(sublattice, -------- See example_scripts : Model Creation Example - ''' + """ # if material == 'Au_NP_' # z_bond_length = function_to_get_material_info @@ -1838,7 +1834,7 @@ def create_dataframe_for_cif(sublattice_list, element_list): def change_sublattice_pseudo_inplace(new_atom_positions, old_sublattice): - ''' + """ Create and return a new Sublattice object which is a copy of old_sublattice except with extra atom positions set with new_atom_positions. @@ -1878,7 +1874,7 @@ def change_sublattice_pseudo_inplace(new_atom_positions, old_sublattice): ------- An Atomap Sublattice object that combines the new_atom_positions with the information from the old_sublattice. - ''' + """ atom_position_list = np.array(old_sublattice.atom_positions).T.tolist() image = old_sublattice.image @@ -1920,7 +1916,7 @@ def image_difference_position(sublattice, mask_radius=None, num_peaks=5, inplace=True): - ''' + """ Find new atomic coordinates by comparing experimental to simulated image. Changes the sublattice inplace using change_sublattice_pseudo_inplace. @@ -1945,8 +1941,8 @@ def image_difference_position(sublattice, mask_radius : float, default None Radius of the mask around each atom. If this is not set, the radius will be the distance to the nearest atom in the - same sublattice times the `percent_to_nn` value. - Note: if `mask_radius` is not specified, the Atom_Position objects + same sublattice times the ``percent_to_nn`` value. + Note: if ``mask_radius`` is not specified, the Atom_Position objects must have a populated nearest_neighbor_list. num_peaks : int, default 5 number of new atoms to add @@ -1957,14 +1953,14 @@ def image_difference_position(sublattice, sublattice_name : string, default 'sub_new' the outputted sublattice object name and sublattice.name the new sublattice will be given - inplace : Bool, default True - If set to True, the input `sublattice` will be changed inplace and the + inplace : bool, default True + If set to True, the input ``sublattice`` will be changed inplace and the sublattice returned. If set to False, these changes will be output only to a new sublattice. Returns ------- - Atomap Sublattice object if `inplace=False`. See the `inplace` parameter + Atomap Sublattice object if ``inplace=False``. See the ``inplace`` parameter for details. Examples @@ -1994,7 +1990,7 @@ def image_difference_position(sublattice, 400 One can now sort these atom positions into elements. - ''' + """ image_for_sublattice = sublattice.signal diff_image = Signal2D( @@ -2109,12 +2105,12 @@ def image_difference_position(sublattice, # sub_new_exists = True if filename is not None: - ''' + """ diff_image.plot() diff_image_sub.plot() diff_image_inverse.plot() diff_image_sub_inverse.plot() - ''' + """ plt.figure() plt.suptitle('Image Difference Position' + filename) diff --git a/temul/model_refiner.py b/temul/model_refiner.py index 91eaf11..5437972 100644 --- a/temul/model_refiner.py +++ b/temul/model_refiner.py @@ -45,35 +45,35 @@ class Model_Refiner(): def __init__(self, sublattice_and_elements_dict, comparison_image=None, sampling=None, thickness=10, name=''): - ''' + """ Object which is used to refine the elements in a list of Atomap Sublattice objects. There are currently two refinement methods: - 1. Refine with position `image_difference_position_model_refiner` - 2. Refine with intensity `image_difference_intensity_model_refiner`. + 1. Refine with position ``image_difference_position_model_refiner` + 2. Refine with intensity ``image_difference_intensity_model_refiner``. Parameters ---------- sublattice_and_elements_dict : dictionary - A dictionary of the structure `{sublattice: element_list,}` where + A dictionary of the structure ``{sublattice: element_list,}`` where each sublattice is an Atomap sublattice object and each element_list is a list of elements of the form given in the - examples of `get_individual_elements_from_element_list` in the + examples of ``get_individual_elements_from_element_list`` in the element_tools.py module. comparison_image : Hyperspy Signal2D, default None - This is the image with which the first `sublattice` image will be + This is the image with which the first ``sublattice`` image will be compared to refine the list of sublattices' elements. If None is given when the Model Refiner is created, or if the - `comparison_image` is not the same shape as the first sublattice + ``comparison_image`` is not the same shape as the first sublattice image, a warning will be returned. - To set a `comparison_image`, you can either use - `model_refiner.create_simulation` or by setting the - `model_refiner.comparison_image` to an image. + To set a ``comparison_image``, you can either use + ``model_refiner.create_simulation`` or by setting the + ``model_refiner.comparison_image`` to an image. sampling : float, default None - The real space sampling of the `sublattice` images in Angstrom. + The real space sampling of the ``sublattice`` images in Angstrom. The sampling is defined as: sampling = angstrom/pixel. This - sampling will be identical for the `comparison_image`. If it is set + sampling will be identical for the ``comparison_image``. If it is set to None, the sampling will automatically be set by the - `sublattice.signal` object. + ``sublattice.signal`` object. thickness : float, default 10 Physical thickness of the sample in Angstrom. This will be used for the simulation. @@ -103,9 +103,9 @@ def __init__(self, sublattice_and_elements_dict, Examples -------- - For now, see `image_difference_intensity_model_refiner` and - `image_difference_position_model_refiner` below. - ''' + For now, see ``image_difference_intensity_model_refiner`` and + ``image_difference_position_model_refiner`` below. + """ self.sublattice_and_elements_dict = sublattice_and_elements_dict self.sublattice_list = list(sublattice_and_elements_dict.keys()) @@ -227,12 +227,12 @@ def __repr__(self): ) def _auto_mask_radii_init(self): - ''' + """ Automatically set the mask_radius for each sublattice. Use mask_radius='auto' when calling a Model Refiner method. Ideally you could have the mask_radius/percent_to_nn change depending on the atom, but for now depending on the sublattice is okay. - ''' + """ mask_radii = [] for sublattice in self.sublattice_list: @@ -272,14 +272,14 @@ def compare_latest_element_counts(self): self.element_count_history_list[-2:])) def get_element_count_as_dataframe(self): - ''' + """ Allows you to view the element count as a Pandas Dataframe. - See `image_difference_intensity_model_refiner` for an example. + See ``image_difference_intensity_model_refiner`` for an example. Returns ------- Pandas Dataframe - ''' + """ elements_ = [i for sublist in self.element_list for i in sublist] elements_ = list(set(elements_)) @@ -317,26 +317,26 @@ def plot_element_count_as_bar_chart(self, element_configs=0, flip_colrows=True, title="Refinement of Elements", fontsize=16, split_symbol=['_', '.']): - ''' + """ Allows you to plot the element count as a bar chart. - See `image_difference_intensity_model_refiner` for an example. + See ``image_difference_intensity_model_refiner`` for an example. Parameters ---------- element_configs : int, default 0 Change the plotted data. - `element_configs=0` will plot the element configuration counts, - `element_configs=1` will plot the individual element counts, and - `element_configs=2` will plot the both 0 and 1. - flip_colrows : Bool, default True + ``element_configs=0`` will plot the element configuration counts, + ``element_configs=1`` will plot the individual element counts, and + ``element_configs=2`` will plot the both 0 and 1. + flip_colrows : bool, default True Change how the data is plotted. - `flip_colrows=True` will take the transpose of the dataframe. + ``flip_colrows=True`` will take the transpose of the dataframe. title : string, default "Refinement of Elements" Title of the bar chart. fontsize : int, default 16 split_symbol : list, default ['_', '.'] See temul.element_tools.split_and_sort_element for details. - ''' + """ if element_configs == 0: # only element configs df = self.get_element_count_as_dataframe() @@ -368,7 +368,7 @@ def plot_element_count_as_bar_chart(self, element_configs=0, plt.tight_layout() def set_calibration_area(self, manual_list=None): - ''' + """ Area that will be used to calibrate a simulation. The pixel separation can be set with set_calibration_separation. The average intensity of the atoms chosen by this separation within the area will be set to 1. @@ -381,7 +381,7 @@ def set_calibration_area(self, manual_list=None): manual_list must be a list of two lists, each of length two. For example: [ [0,0], [50, 50] ] - ''' + """ if isinstance(manual_list, list): self.calibration_area = manual_list @@ -460,7 +460,7 @@ def image_difference_intensity_model_refiner( filename=None, verbose=False, refinement_method="Intensity"): - ''' + """ Change the elements for sublattice atom positions that don't match with comparison_image. @@ -500,7 +500,7 @@ def image_difference_intensity_model_refiner( >>> refiner.sublattice_list[0].plot() >>> refiner.comparison_image.plot() - ''' + """ self._comparison_image_warning() self._save_refiner_instance() @@ -574,7 +574,7 @@ def image_difference_position_model_refiner( inplace=True, filename=None, refinement_method="Position"): - ''' + """ Find new atom positions that were perhaps missed by the initial position finding steps. Each sublattice will be updated with new atom positions if new atom positions are found. @@ -613,7 +613,7 @@ def image_difference_position_model_refiner( >>> refiner.plot_element_count_as_bar_chart( ... element_configs=2, flip_colrows=True, fontsize=24) - ''' + """ self._comparison_image_warning() self._save_refiner_instance() @@ -625,8 +625,8 @@ def image_difference_position_model_refiner( elif isinstance(sublattices, list): sublattice_list = [self.sublattice_list[i] for i in sublattices] print( - "Warning: Setting `sublattices` to a list can cause overwrite" - "errors. Best use `sublattice='all'` until this is fixed") + "Warning: Setting ``sublattices`` to a list can cause overwrite" + "errors. Best use ``sublattice='all'`` until this is fixed") mask_radius_list = [self.auto_mask_radius[i] for i in sublattices] # elif isinstance(positions_from_sublattices, list): @@ -714,39 +714,39 @@ def create_simulation( Parameters ---------- sublattices : Atomap Sublattices, default 'all' - If set to 'all', sublattices that exist in the `Model_Refiner` will - all be used. The `sublattice` indexes can be specified in a list. + If set to 'all', sublattices that exist in the ``Model_Refiner`` will + all be used. The ``sublattice`` indexes can be specified in a list. For example [0, 2] will select the first and third sublattices. - A list of `sublattice` objects can instead be used. - filter_image : Bool, default False + A list of ``sublattice`` objects can instead be used. + filter_image : bool, default False Choose whether to filter the simulation with a Gaussian to match - the `reference_image`. - calibrate_image : Bool, default True + the ``reference_image``. + calibrate_image : bool, default True Choose whether to calibrate the simulation with a set - `calibration_area` and `calibration_separation`. + ``calibration_area`` and ``calibration_separation``. xyz_sizes : list, default None List of the x, y, z physical size of the reference_image in angstrom. If None is set, the sizes will be automatically taken - from the `image_xyz_sizes` attribute. + from the ``image_xyz_sizes`` attribute. header_comment : string, default 'example' The first line comment for the .xyz file. filename : string, default 'refiner_simulation' filename with which the .xyz file and simulated .mrc file will be saved. delta_image_filter : float, default 0.5 - The change in sigma for the `filter` Gaussian filter. Small values - will slow the `filter` down. + The change in sigma for the ``filter`` Gaussian filter. Small values + will slow the ``filter`` down. max_sigma : float, default 6 - The maximum sigma used for the `filter` Gaussian filter. Large - values will slow the `filter` down. + The maximum sigma used for the ``filter`` Gaussian filter. Large + values will slow the ``filter`` down. percent_to_nn : float, default None The percentage distance to the nearest neighbour atom used for atomap atom position refinement. mask_radius : float, default 'auto' The pixel distance to the nearest neighbour atom used for atomap atom position refinement - refine : Bool, default True - Whether to refine the atom positions for the `calibrate` parameter. + refine : bool, default True + Whether to refine the atom positions for the ``calibrate`` parameter. Note: The error resulting from filter=True with percent_to_nn set can be fixed by setting mask_radius instead of percent_to_nn. @@ -898,7 +898,7 @@ def plot_reference_and_comparison_images( # df -''' Model Refiner Dummy Data examples ''' +""" Model Refiner Dummy Data examples """ def get_model_refiner_two_sublattices(): @@ -1035,7 +1035,7 @@ def get_model_refiner_with_12_vacancies_refined( def get_model_refiner_with_3_vacancies_refined( image_noise=True, test_element='Ti_2', filename=None): - ''' + """ >>> from temul.model_refiner import ( ... get_model_refiner_with_3_vacancies_refined) >>> refiner = get_model_refiner_with_3_vacancies_refined() @@ -1043,7 +1043,7 @@ def get_model_refiner_with_3_vacancies_refined( Changing some atoms Changing some atoms >>> history = refiner.get_element_count_as_dataframe() - ''' + """ refiner = get_model_refiner_one_sublattice_3_vacancies( image_noise=image_noise, test_element=test_element) refiner.auto_mask_radius = [4] diff --git a/temul/polarisation.py b/temul/polarisation.py index fa60020..0e1fa3b 100644 --- a/temul/polarisation.py +++ b/temul/polarisation.py @@ -2,6 +2,6 @@ raise DeprecationWarning( "\n WARNING: " "To use the polarisation " - "functionality please use `import temul.api as tml`. " + "functionality please use ``import temul.api as tml``. " "The temul.polarisation module is deprecated and is now " "`temul.topotem.polarisation.\n") diff --git a/temul/signal_plotting.py b/temul/signal_plotting.py index 5fb31b3..c1fe21b 100644 --- a/temul/signal_plotting.py +++ b/temul/signal_plotting.py @@ -20,7 +20,7 @@ def compare_images_line_profile_one_image(image, arrow=None, linetrace=None, **kwargs): - ''' + """ Plots two line profiles on one image with the line profile intensities in a subfigure. See skimage PR PinkShnack for details on implementing profile_line @@ -48,7 +48,7 @@ def compare_images_line_profile_one_image(image, Name could be improved maybe. kwargs : Matplotlib keyword arguments passed to imshow() - ''' + """ if sampling == 'Auto': if image.axes_manager[0].scale != 1.0: @@ -148,7 +148,7 @@ def compare_images_line_profile_two_images(imageA, imageB, arrow_markersize=10, figsize=(10, 3), imageB_intensity_offset=0): - ''' + """ Plots two line profiles on two images separately with the line profile intensities in a subfigure. See skimage PR PinkShnack for details on implementing profile_line @@ -165,7 +165,7 @@ def compare_images_line_profile_two_images(imageA, imageB, If this is set to a name (string), the image will be saved with that name. reduce_func : ufunc, default np.mean - See skimage's `profile_line` reduce_func parameter for details. + See skimage's ``profile_line`` reduce_func parameter for details. linewidth : int, default 1 see profile_line for parameter details. sampling : float, default 'auto' @@ -173,7 +173,7 @@ def compare_images_line_profile_two_images(imageA, imageB, image from image.axes_manager[0].scale. units : string, default 'nm' crop_offset : int, default 20 - number of pixels away from the `line_profile_positions` coordinates the + number of pixels away from the ``line_profile_positions`` coordinates the image crop will be taken. title : string, default "Intensity Profile" Title of the plot @@ -195,7 +195,7 @@ def compare_images_line_profile_two_images(imageA, imageB, ... imageA, imageB, line_profile_positions, ... linewidth=3, sampling=0.012, crop_offset=30) - To use the new skimage functionality try the `reduce_func` parameter: + To use the new skimage functionality try the ``reduce_func`` parameter: >>> import numpy as np >>> reduce_func = np.sum # can be any ufunc! @@ -219,7 +219,7 @@ def compare_images_line_profile_two_images(imageA, imageB, ... imageA, imageB, line_profile_positions, reduce_func=None, ... imageB_intensity_offset=0.1) - ''' + """ if isinstance(sampling, str): if sampling.lower() == 'auto': @@ -260,7 +260,7 @@ def compare_images_line_profile_two_images(imageA, imageB, crop_x1 = crop_offset + (x1 - x0) crop_y1 = crop_offset + (y1 - y0) - ''' Simulation ''' + """ Simulation """ profile_y_sim = profile_line( image=imageB.data, src=[y0, x0], dst=[y1, x1], linewidth=linewidth, @@ -316,12 +316,12 @@ def compare_images_line_profile_two_images(imageA, imageB, def get_cropping_area(line_profile_positions, crop_offset=20): - ''' + """ By inputting the top-left and bottom-right coordinates of a rectangle, this function will add a border buffer (`crop_offset`) which can be used for cropping of regions in a plot. - See `compare_images_line_profile_two_images` for use-case - ''' + See ``compare_images_line_profile_two_images`` for use-case + """ x0, y0 = line_profile_positions[0] x1, y1 = line_profile_positions[1] @@ -334,7 +334,7 @@ def get_cropping_area(line_profile_positions, crop_offset=20): def plot_atom_energies(sublattice_list, image=None, vac_or_implants=None, elements_dict_other=None, filename='energy_map', cmap='plasma', levels=20, colorbar_fontsize=16): - ''' + """ Used to plot the energies of atomic column configurations above 0 as calculated by DFT. @@ -343,9 +343,9 @@ def plot_atom_energies(sublattice_list, image=None, vac_or_implants=None, ---------- sublattice_list : list of Atomap Sublattices image : array-like, default None - The first sublattice image is used if `image=None`. + The first sublattice image is used if ``image=None``. vac_or_implants :string, default None - `vac_or_implants` options are "implants" and "vac". + ``vac_or_implants`` options are "implants" and "vac". elements_dict_other : dict, default None A dictionary of {element_config1: energy1, element_config2: energy2, } The default is Se antisites in monolayer MoS2. @@ -361,7 +361,7 @@ def plot_atom_energies(sublattice_list, image=None, vac_or_implants=None, The x and y coordinates of the atom positions and the atom energy. - ''' + """ if elements_dict_other is None: energies_dict = {'S_0': 2 * 5.9, @@ -575,7 +575,7 @@ def snap(self, x, y): def color_palettes(pallette): - ''' + """ Color sequences that are useful for creating matplotlib colormaps. Info on "zesty" and other options: venngage.com/blog/color-blind-friendly-palette/ @@ -591,7 +591,7 @@ def color_palettes(pallette): ------- list of hex colours - ''' + """ zesty = ['#F5793A', '#A95AA1', '#85C0F9', '#0F2080'] r_safe = ["#88CCEE", "#CC6677", "#DDCC77", "#117733", "#332288", "#AA4499", "#44AA99", "#999933", "#882255", "#661100", "#6699CC", "#888888"] @@ -605,9 +605,9 @@ def color_palettes(pallette): def rgb_to_dec(rgb_values): - ''' + """ Change RGB color values to decimal color values (between 0 and 1). - Required for use with matplotlib. See Example in `hex_to_rgb` below. + Required for use with matplotlib. See Example in ``hex_to_rgb`` below. Parameters ---------- @@ -617,7 +617,7 @@ def rgb_to_dec(rgb_values): ------- Decimal color values (RGB but scaled from 0 to 1 rather than 0 to 255) - ''' + """ dec_values = [] for rgb_value in rgb_values: dec_values.append(tuple([i/256 for i in rgb_value])) @@ -625,7 +625,7 @@ def rgb_to_dec(rgb_values): def hex_to_rgb(hex_values): - ''' + """ Change from hexidecimal color values to rgb color values. Grabs starting two, middle two, last two values in hex, multiplies by 16^1 and 16^0 for the first and second, respectively. @@ -655,7 +655,7 @@ def hex_to_rgb(hex_values): >>> cmap, norm = from_levels_and_colors( ... levels=[0,1,2,3,4,5], colors=tml.rgb_to_dec(zest)) - ''' + """ hex_values = [i.lstrip('#') for i in hex_values] rgb_values = [] for hex_value in hex_values: @@ -665,7 +665,7 @@ def hex_to_rgb(hex_values): def expand_palette(palette, expand_list): - ''' + """ Essentially multiply the palette so that it has the number of instances of each color that you want. @@ -687,7 +687,7 @@ def expand_palette(palette, expand_list): >>> zest = tml.color_palettes('zesty') >>> expanded_palette = tml.expand_palette(zest, [1,2,2,2]) - ''' + """ expanded_palette = [] for pal, ex in zip(palette, expand_list): for count in range(ex): @@ -707,12 +707,12 @@ def create_rgb_array(): def get_polar_2d_colorwheel_color_list(u, v): - ''' make the color_list from the HSV/RGB colorwheel. + """ make the color_list from the HSV/RGB colorwheel. This color_list will be the same length as u and as v. It works by indexing the angle of the RGB (hue in HSV) array, then indexing the magnitude (r) in the RGB (value in HSV) array, leaving only a single RGB color for each vector. - ''' + """ rgb_array = create_rgb_array() diff --git a/temul/signal_processing.py b/temul/signal_processing.py index ec42af8..c93df24 100644 --- a/temul/signal_processing.py +++ b/temul/signal_processing.py @@ -30,7 +30,7 @@ def get_xydata_from_list_of_intensities( sublattice_intensity_list, hist_bins=100): - ''' + """ Output x and y data for a histogram of intensities Parameters @@ -54,7 +54,7 @@ def get_xydata_from_list_of_intensities( >>> sub1_inten = np.random.normal(mu, sigma, 1000) >>> xdata, ydata = get_xydata_from_list_of_intensities(sub1_inten, ... hist_bins=50) - ''' + """ hist_bins = hist_bins y_array, x_array = np.histogram(sublattice_intensity_list, @@ -72,7 +72,7 @@ def get_xydata_from_list_of_intensities( def fit_1D_gaussian_to_data(xdata, amp, mu, sigma): - ''' + """ Fitting function for a single 1D gaussian distribution Parameters @@ -103,7 +103,7 @@ def fit_1D_gaussian_to_data(xdata, amp, mu, sigma): ... hist_bins=50) >>> gauss_fit_01 = fit_1D_gaussian_to_data(xdata, amp, mu, sigma) - ''' + """ return(amp * (1 / (sigma * (np.sqrt(2 * np.pi)))) * ( np.exp(-((xdata - mu)**2) / ((2 * sigma)**2)))) @@ -115,7 +115,7 @@ def return_fitting_of_1D_gaussian( xdata, ydata, amp, mu, sigma): - ''' + """ Use the initially found centre (mean/mode) value of a sublattice histogram (e.g., Mo_1 in an Mo sublattice) as an input mean for a gaussian fit of the data. @@ -132,7 +132,6 @@ def return_fitting_of_1D_gaussian( Examples -------- - >>> from temul.signal_processing import ( ... get_xydata_from_list_of_intensities, ... return_fitting_of_1D_gaussian, @@ -146,10 +145,7 @@ def return_fitting_of_1D_gaussian( ... xdata, ydata, ... amp, mu, sigma) - # print("Calculated Mean: " + str(round(np.mean(xdata),3)) - # + "\n Fitted Mean: " + str(round(popt_gauss[1],3))) - ''' - + """ popt_gauss, pcov_gauss = scipy.optimize.curve_fit( f=function, xdata=xdata, @@ -169,7 +165,7 @@ def plot_gaussian_fit(xdata, ydata, function, amp, mu, sigma, plot_fill=False, facecolor='r', alpha=0.5): # save_image/filename maybe? - ''' + """ >>> from temul.signal_processing import (fit_1D_gaussian_to_data, ... plot_gaussian_fit, ... return_fitting_of_1D_gaussian) @@ -186,7 +182,7 @@ def plot_gaussian_fit(xdata, ydata, function, amp, mu, sigma, ... plot_data=True, data_art='ko', data_label='Data Points', ... plot_fill=True, facecolor='r', alpha=0.5) - ''' + """ _gaussian_fit = function(xdata=xdata, amp=amp, mu=mu, sigma=sigma) @@ -218,10 +214,10 @@ def get_scaled_middle_limit_intensity_list(sublattice, middle_intensity_list, limit_intensity_list, sublattice_scalar): - ''' + """ Returns the middle and limit lists scaled to the actual intensities in the sublattice. Useful for get_fitting_tools_for_plotting_gaussians(). - ''' + """ middle_intensity_list_real = [] limit_intensity_list_real = [] @@ -241,10 +237,10 @@ def get_fitting_tools_for_plotting_gaussians(element_list, fit_bright_first=True, gaussian_amp=5, gauss_sigma_division=100): - ''' + """ Creates a list of parameters and details for fitting the intensities of a sublattice with multiple Gaussians. - ''' + """ if len(scaled_middle_intensity_list) + 1 != len( scaled_limit_intensity_list): @@ -281,7 +277,7 @@ def plot_gaussian_fitting_for_multiple_fits(sub_ints_all, plotting_style='hist', filename='Fit of Intensities', mpl_cmaps_list=['viridis']): - ''' + """ plots Gaussian distributions for intensities of a sublattice, over the given parameters (fitting tools). @@ -329,7 +325,7 @@ def plot_gaussian_fitting_for_multiple_fits(sub_ints_all, hist_bins=500, filename='Fit of Intensities900') - ''' + """ # set up cyclers for plotting gaussian fits # need to set up a loop here to create as many cyclers as sublattices @@ -474,14 +470,14 @@ def plot_gaussian_fitting_for_multiple_fits(sub_ints_all, pad_inches=None, dpi=900, labels=False) -''' +""" Image Comparison # https://www.pyimagesearch.com/2014/09/15/python-compare-two-images/ -''' +""" def mse(imageA, imageB): - ''' + """ Measure the mean squared error between two images of the same shape. Parameters @@ -493,14 +489,14 @@ def mse(imageA, imageB): ------- Mean squared error - ''' + """ err = np.sum((imageA.astype("float") - imageB.astype("float")) ** 2) err /= float(imageA.shape[0] * imageA.shape[1]) return err def measure_image_errors(imageA, imageB, filename=None): - ''' + """ Measure the Mean Squared Error (mse) and Structural Similarity Index (ssm) between two images. @@ -529,7 +525,7 @@ def measure_image_errors(imageA, imageB, filename=None): >>> print("MSE: {} and SSM: {}".format(mse_number, ssm_number)) MSE: 0.0 and SSM: 1.0 - ''' + """ if imageA.dtype is not imageB.dtype: imageA = imageA.astype('float64') imageB = imageB.astype('float64') @@ -574,7 +570,7 @@ def measure_image_errors(imageA, imageB, filename=None): def load_and_compare_images(imageA, imageB, filename=None): - ''' + """ Load two images with hyperspy and compare their mean square error and structural simularity index. @@ -589,7 +585,7 @@ def load_and_compare_images(imageA, imageB, filename=None): ------- Two floats (mean standard error and structural simularity index) - ''' + """ imageA = hs.load(imageA) imageB = hs.load(imageB) @@ -605,7 +601,7 @@ def compare_two_image_and_create_filtered_image( image_to_filter, reference_image, delta_image_filter, max_sigma=6, cropping_area=[[0, 0], [50, 50]], separation=8, filename=None, percent_to_nn=0.4, mask_radius=None, refine=False): - ''' + """ Gaussian blur an image for comparison with a reference image. Good for finding the best gaussian blur for a simulation by comparing to an experimental image. @@ -616,7 +612,7 @@ def compare_two_image_and_create_filtered_image( image_to_filter : Hyperspy Signal2D Image you wish to automatically filter. reference_image : Hyperspy Signal2D - Image with which `image_to_filter` is compared. + Image with which ``image_to_filter`` is compared. delta_image_filter : float The increment of the Gaussian sigma used. max_sigma : float, default 6 @@ -633,12 +629,12 @@ def compare_two_image_and_create_filtered_image( Determines the boundary of the area surrounding each atomic column, as fraction of the distance to the nearest neighbour. mask_radius : int, default None - Radius in pixels of the mask. If set, then set `percent_to_nn=None`. - refine : Bool, default False - If set to True, the `calibrate_intensity_distance_with_sublattice_roi` + Radius in pixels of the mask. If set, then set ``percent_to_nn=None``. + refine : bool, default False + If set to True, the ``calibrate_intensity_distance_with_sublattice_roi` calibration will refine the atom positions for each calibration. May - make the function very slow depending on the size of `image_to_filter` - and `cropping_area`. + make the function very slow depending on the size of ``image_to_filter` + and ``cropping_area``. Returns ------- @@ -659,7 +655,7 @@ def compare_two_image_and_create_filtered_image( simulation, experiment, 0.25, cropping_area=[[5,5], [200, 200]], separation=11, mask_radius=4, percent_to_nn=None, max_sigma=10) - ''' + """ image_to_filter_data = image_to_filter.data reference_image_data = reference_image.data @@ -786,7 +782,7 @@ def make_gaussian(size, fwhm, center=None): def make_gaussian_pos_neg(size, fwhm_neg, fwhm_pos, neg_min=0.9, center=None): - ''' See double_gaussian_fft_filter for details ''' + """ See double_gaussian_fft_filter for details """ arr_pos = make_gaussian(size, fwhm=fwhm_pos, center=center) nD_Gaussian_pos = Signal2D(arr_pos) @@ -797,7 +793,7 @@ def make_gaussian_pos_neg(size, fwhm_neg, fwhm_pos, neg_min=0.9, center=None): def double_gaussian_fft_filter(image, fwhm_neg, fwhm_pos, neg_min=0.9): - ''' + """ Filter an image with a bandpass-like filter. Parameters @@ -827,7 +823,7 @@ def double_gaussian_fft_filter(image, fwhm_neg, fwhm_pos, neg_min=0.9): >>> image.plot() >>> filtered_image.plot() - ''' + """ image_fft = image.fft(shift=True) fft_data = image_fft.amplitude.data @@ -845,7 +841,7 @@ def double_gaussian_fft_filter(image, fwhm_neg, fwhm_pos, neg_min=0.9): def double_gaussian_fft_filter_optimised(image, d_inner, d_outer, delta=0.05, sampling=None, units=None, filename=None): - ''' + """ Filter an image with an double Gaussian (band-pass) filter. The function will automatically find the optimum magnitude of the negative inner Gaussian. @@ -868,7 +864,7 @@ def double_gaussian_fft_filter_optimised(image, d_inner, d_outer, delta=0.05, image sampling in units/pixel. If set to None, the image.axes_manager will be used. units : str - Real space units. `sampling` should then be the value of + Real space units. ``sampling`` should then be the value of these units/pixel. If set to None, the image.axes_manager will be used. filename : str, default None @@ -890,7 +886,7 @@ def double_gaussian_fft_filter_optimised(image, d_inner, d_outer, delta=0.05, >>> filtered_image = tml.double_gaussian_fft_filter(image, 7.48, 14.96) >>> filtered_image.plot() - ''' + """ # Folder: G:/SuperStem visit/Feb 2019 data/2019_02_18_QMR_S1574_MoS2- # Se-15eV @@ -976,7 +972,7 @@ def double_gaussian_fft_filter_optimised(image, d_inner, d_outer, delta=0.05, idx = np.argwhere(np.diff(np.sign(zero_line - y_axis))).flatten() neg_gauss_amplitude_calculated = x_axis[idx][0] - ''' Filtering the Image with the Chosen Negative Amplitude ''' + """ Filtering the Image with the Chosen Negative Amplitude """ # positive gauss nD_Gaussian.axes_manager[0].scale = reciprocal_sampling nD_Gaussian.axes_manager[1].scale = reciprocal_sampling @@ -1086,7 +1082,7 @@ def double_gaussian_fft_filter_optimised(image, d_inner, d_outer, delta=0.05, pad_inches=None, dpi=600, labels=False) plt.close() - ''' Saving the Variables for the image and filtered Image ''' + """ Saving the Variables for the image and filtered Image """ Filtering_Variables = collections.OrderedDict() Filtering_Variables['filename'] = [filename] Filtering_Variables['Image Size (nm)'] = [physical_image_size] @@ -1127,7 +1123,7 @@ def double_gaussian_fft_filter_optimised(image, d_inner, d_outer, delta=0.05, def visualise_dg_filter(image, d_inner=7.7, d_outer=21, slider_min=0.1, slider_max=300, slider_step=0.1, plot_lims=(0, 1), figsize=(15, 7)): - ''' + """ Parameters ---------- @@ -1159,7 +1155,7 @@ def visualise_dg_filter(image, d_inner=7.7, d_outer=21, slider_min=0.1, >>> image = load_Se_implanted_MoS2_data() >>> tml.visualise_dg_filter(image) - ''' + """ # Get FFT of the image image_fft = image.fft(shift=True) @@ -1275,17 +1271,17 @@ def filter_image(event): filterax._button = filter_button -''' +""" Cropping and Calibrating -''' +""" # cropping done in the scale, so nm, pixel, or whatever you have # cropping_area = choose_points_on_image(image.data) def crop_image_hs(image, cropping_area, scalebar_true=True, filename=None): - ''' - Crop a Hyperspy Signal2D by providing the `cropping_area`. See the example + """ + Crop a Hyperspy Signal2D by providing the ``cropping_area``. See the example below. Parameters @@ -1296,8 +1292,8 @@ def crop_image_hs(image, cropping_area, scalebar_true=True, filename=None): The best method of choosing the area is by using the function "choose_points_on_image(image.data)". Choose two points on the image. First point is top left of area, second point is bottom right. - scalebar_true : Bool, default True - If set to True, the function assumes that `image.axes_manager` is + scalebar_true : bool, default True + If set to True, the function assumes that ``image.axes_manager`` is calibrated to a unit other than pixel. filename : str, default None If set to a string, the images and cropping variables will be saved. @@ -1321,7 +1317,7 @@ def crop_image_hs(image, cropping_area, scalebar_true=True, filename=None): >>> # image_cropped = tml.crop_image_hs(image, cropping_area, False) >>> # image_cropped.plot() - ''' + """ llim, tlim = cropping_area[0] rlim, blim = cropping_area[1] @@ -1367,7 +1363,7 @@ def crop_image_hs(image, cropping_area, scalebar_true=True, filename=None): physical_image_crop_size_y = image_crop.axes_manager[1].scale * \ image_crop.axes_manager[1].size - ''' Saving the Variables for the image and filtered Image ''' + """ Saving the Variables for the image and filtered Image """ Cropping_Variables = collections.OrderedDict() # Cropping_Variables['Image Name'] = [image_name] Cropping_Variables['left (%s)' % unit] = [llim] @@ -1398,7 +1394,7 @@ def calibrate_intensity_distance_with_sublattice_roi(image, refine=True, filename=None): # add max mean min etc. - ''' + """ Calibrates the intensity of an image by using the brightest sublattice. The mean intensity of that sublattice is set to 1. @@ -1413,16 +1409,16 @@ def calibrate_intensity_distance_with_sublattice_roi(image, separation : int, default 8 Pixel separation between atoms as used by Atomap. reference_image : Hyperspy Signal2D - Image with which `image` is compared. - scalebar_true : Bool, default True - If set to True, the function assumes that `image.axes_manager` is + Image with which ``image`` is compared. + scalebar_true : bool, default True + If set to True, the function assumes that ``image.axes_manager`` is calibrated to a unit other than pixel. mask_radius : int, default None Radius in pixels of the mask. percent_to_nn : float, default 0.2 Determines the boundary of the area surrounding each atomic column, as fraction of the distance to the nearest neighbour. - refine : Bool, default False + refine : bool, default False If set to True, the atom positions found for the calibration will be refined. filename : str, default None @@ -1445,7 +1441,7 @@ def calibrate_intensity_distance_with_sublattice_roi(image, # tml.calibrate_intensity_distance_with_sublattice_roi( # image, crop_a, 10) - ''' + """ llim, tlim = cropping_area[0] rlim, blim = cropping_area[1] @@ -1505,7 +1501,7 @@ def toggle_atom_refine_position_automatically(sublattice, percent_to_nn=0.05, mask_radius=None, filename=None): - ''' + """ Sets the 'refine_position' attribute of each Atom Position in a sublattice using a range of intensities. @@ -1514,21 +1510,21 @@ def toggle_atom_refine_position_automatically(sublattice, sublattice : Atomap Sublattice object min_cut_off_percent : float, default None The lower end of the intensity range is defined as - `min_cut_off_percent` * `method` value of max intensity list of - `sublattice`. + ``min_cut_off_percent`` * ``method`` value of max intensity list of + ``sublattice``. max_cut_off_percent : float, default None The upper end of the intensity range is defined as - `max_cut_off_percent` * `method` value of max intensity list of - `sublattice`. + ``max_cut_off_percent`` * ``method`` value of max intensity list of + ``sublattice``. range_type : str, default 'internal' - "internal" provides the `refine_position` attribute for each - `Atom Position` as True if the intensity of that Atom Position + "internal" provides the ``refine_position`` attribute for each + ``Atom Position`` as True if the intensity of that Atom Position lies between the lower and upper limits defined by - `min_cut_off_percent` and `max_cut_off_percent`. - "external" provides the `refine_position` attribute for each - `Atom Position` as True if the intensity of that Atom Position + ``min_cut_off_percent`` and ``max_cut_off_percent``. + "external" provides the ``refine_position`` attribute for each + ``Atom Position`` as True if the intensity of that Atom Position lies outside the lower and upper limits defined by - `min_cut_off_percent` and `max_cut_off_percent`. + ``min_cut_off_percent`` and ``max_cut_off_percent``. method : str, default 'mode' The method used to aggregate the intensity of the sublattice positions max intensity list. Options are "mode" and "mean" @@ -1538,11 +1534,11 @@ def toggle_atom_refine_position_automatically(sublattice, mask_radius : int, default None Radius in pixels of the mask. filename : str, default None - If set to a string, the Atomap `refine_position` image will be saved. + If set to a string, the Atomap ``refine_position`` image will be saved. Returns ------- - list of the `AtomPosition.refine_position=False` attribute. + list of the ``AtomPosition.refine_position=False`` attribute. Examples ------- @@ -1564,7 +1560,7 @@ def toggle_atom_refine_position_automatically(sublattice, >>> sublattice.toggle_atom_refine_position_with_gui() - ''' + """ sublattice.get_atom_column_amplitude_max_intensity( percent_to_nn=percent_to_nn, mask_radius=mask_radius) @@ -1690,7 +1686,7 @@ def _remove_image_slice_around_atom( def get_cell_image(s, points_x, points_y, method='Voronoi', max_radius='Auto', reduce_func=np.min, show_progressbar=True): - ''' + """ The same as atomap's integrate, except instead of summing the region around an atom, it removes the value from all pixels in that region. @@ -1702,7 +1698,7 @@ def get_cell_image(s, points_x, points_y, method='Voronoi', reduce_func : ufunc, default np.min function used to reduce the pixel values around each atom to a float. - For the other parameters see Atomap's `integrate` function. + For the other parameters see Atomap's ``integrate`` function. Returns ------- @@ -1717,7 +1713,7 @@ def get_cell_image(s, points_x, points_y, method='Voronoi', >>> cell_image = get_cell_image(sublattice.image, sublattice.x_position, ... sublattice.y_position) - Plot the `cell_image` which shows, in this case, the background intensity + Plot the ``cell_image`` which shows, in this case, the background intensity >>> import matplotlib.pyplot as plt >>> im = plt.imshow(cell_image) @@ -1728,7 +1724,7 @@ def get_cell_image(s, points_x, points_y, method='Voronoi', >>> cell_image = hs.signals.Signal2D(cell_image) >>> cell_image.plot() - ''' + """ image = s.__array__() if len(image.shape) < 2: @@ -1799,7 +1795,7 @@ def distance_vector(x1, y1, x2, y2): def mean_and_std_nearest_neighbour_distances(sublattice, nearest_neighbours=5, sampling=None): - ''' + """ Calculates mean and standard deviation of the distance from each atom to its nearest neighbours. @@ -1830,7 +1826,7 @@ def mean_and_std_nearest_neighbour_distances(sublattice, >>> mean_scaled, _ = mean_and_std_nearest_neighbour_distances(sublattice, ... sampling=0.0123) - ''' + """ # 5 will get the nearest 4 atoms sublattice.find_nearest_neighbors( nearest_neighbors=nearest_neighbours) diff --git a/temul/simulations.py b/temul/simulations.py index 08f06f6..a34aa23 100644 --- a/temul/simulations.py +++ b/temul/simulations.py @@ -48,7 +48,7 @@ def simulate_and_filter_and_calibrate_with_prismatic( scanWindowMax=1.0, algorithm="prism", numThreads=2): - ''' + """ Simulate an xyz coordinate model with the PyPrismatic fast simulation software. @@ -75,8 +75,8 @@ def simulate_and_filter_and_calibrate_with_prismatic( mask_radius : float, default None Radius of the mask around each atom. If this is not set, the radius will be the distance to the nearest atom in the - same sublattice times the `percent_to_nn` value. - Note: if `mask_radius` is not specified, the Atom_Position objects + same sublattice times the ``percent_to_nn`` value. + Note: if ``mask_radius`` is not specified, the Atom_Position objects must have a populated nearest_neighbor_list. refine, scalebar_true See function calibrate_intensity_distance_with_sublattice_roi() @@ -87,7 +87,7 @@ def simulate_and_filter_and_calibrate_with_prismatic( ------- Hyperspy Signal2D - ''' + """ if len(calibration_area) != 2: raise ValueError('calibration_area must be two points') @@ -150,7 +150,7 @@ def simulate_and_calibrate_with_prismatic( scanWindowMax=1.0, algorithm="prism", numThreads=2): - ''' + """ Simulate an xyz coordinate model with the PyPrismatic fast simulation software. @@ -177,8 +177,8 @@ def simulate_and_calibrate_with_prismatic( mask_radius : float, default None Radius of the mask around each atom. If this is not set, the radius will be the distance to the nearest atom in the - same sublattice times the `percent_to_nn` value. - Note: if `mask_radius` is not specified, the Atom_Position objects + same sublattice times the ``percent_to_nn`` value. + Note: if ``mask_radius`` is not specified, the Atom_Position objects must have a populated nearest_neighbor_list. refine, scalebar_true See function calibrate_intensity_distance_with_sublattice_roi() @@ -189,7 +189,7 @@ def simulate_and_calibrate_with_prismatic( ------- Hyperspy Signal2D - ''' + """ if len(calibration_area) != 2: raise ValueError('calibration_area must be two points') @@ -247,7 +247,7 @@ def simulate_with_prismatic(xyz_filename, scanWindowMax=1.0, algorithm="prism", numThreads=2): - ''' + """ Simulate an xyz coordinate model with pyprismatic fast simulation software. @@ -300,7 +300,7 @@ def simulate_with_prismatic(xyz_filename, ... scanWindowMin=0.0, scanWindowMax=1.0, ... algorithm="prism", numThreads=2) - ''' + """ if '.xyz' not in xyz_filename: simulation_filename = xyz_filename + '.XYZ' @@ -415,9 +415,9 @@ def image_refine_via_intensity_loop(atom_lattice, # atom_lattice_data = atom_lattice.image atom_lattice_signal = atom_lattice.signal - ''' + """ Image Intensity Loop - ''' + """ if len(calibration_area) != 2: raise ValueError('calibration_area_simulation must be two points') @@ -520,10 +520,10 @@ def image_refine_via_intensity_loop(atom_lattice, pad_inches=None, dpi=300, labels=False) plt.close() - ''' + """ Need to add the intensity type to the image_difference_intensity algorithm! - ''' + """ counter_before_refinement = count_atoms_in_sublattice_list( sublattice_list=atom_lattice.sublattice_list, @@ -535,7 +535,7 @@ def image_refine_via_intensity_loop(atom_lattice, else: pass - ''' Sub1 ''' + """ Sub1 """ image_difference_intensity(sublattice=sub1, simulation_image=simulation, element_list=element_list, @@ -546,7 +546,7 @@ def image_refine_via_intensity_loop(atom_lattice, # sub1_info_refined = print_sublattice_elements(sub1) - ''' Sub2 ''' + """ Sub2 """ image_difference_intensity(sublattice=sub2, simulation_image=simulation, element_list=element_list, @@ -557,7 +557,7 @@ def image_refine_via_intensity_loop(atom_lattice, # sub2_info_refined = print_sublattice_elements(sub2) - ''' Sub3 ''' + """ Sub3 """ image_difference_intensity(sublattice=sub3, simulation_image=simulation, element_list=element_list, @@ -594,7 +594,7 @@ def image_refine_via_intensity_loop(atom_lattice, print('Finished Refinement! Repeating every second iteration.') break - ''' Remake XYZ file for further refinement''' + """ Remake XYZ file for further refinement""" # loading_suffix is now saving_suffix create_dataframe_for_xyz( @@ -698,7 +698,7 @@ def image_refine_via_intensity_loop(atom_lattice, pad_inches=None, dpi=300, labels=False) plt.close() - ''' ATOM LATTICE with simulation refinement ''' + """ ATOM LATTICE with simulation refinement """ atom_lattice_int_ref_name = 'Atom_Lattice_' + \ intensity_type + '_refined' + saving_suffix @@ -773,7 +773,7 @@ def image_refine_via_position_loop(image, algorithm="prism", numThreads=2 ): - ''' Image Position Loop ''' + """ Image Position Loop """ df_position_refine = pd.DataFrame(columns=element_list) new_subs = [] @@ -890,9 +890,9 @@ def image_refine_via_position_loop(image, num_points=num_points, percent_to_nn=percent_to_nn, mask_radius=mask_radius) - ''' + """ need to make mask_radius for this too, for the new sublattice - ''' + """ assign_z_height(sublattice=sub_new, lattice_type='chalcogen', @@ -911,7 +911,7 @@ def image_refine_via_position_loop(image, df_position_refine = df_position_refine.append( counter_after_refinement, ignore_index=True).fillna(0) - ''' Remake XYZ file for further refinement''' + """ Remake XYZ file for further refinement""" # loading_suffix is now saving_suffix create_dataframe_for_xyz( @@ -925,7 +925,7 @@ def image_refine_via_position_loop(image, df_position_refine.to_csv(filename + '.csv', sep=',', index=False) - '''Save Atom Lattice Object''' + """Save Atom Lattice Object""" atom_lattice = am_dev.Atom_Lattice(image=image.data, name='All Sublattices ' + filename, sublattice_list=sublattice_list) diff --git a/temul/spectroscopy.py b/temul/spectroscopy.py index cd0659c..5234f8c 100644 --- a/temul/spectroscopy.py +++ b/temul/spectroscopy.py @@ -33,7 +33,7 @@ def Eff_Beta(E_0, E_p, alpha, beta): - '''This function is adapted from the MATLAB code at the back of + """This function is adapted from the MATLAB code at the back of Egerton's book. it calculates: - effective collection angle as a function of the collection semi-angle, @@ -50,7 +50,7 @@ def Eff_Beta(E_0, E_p, alpha, beta): excitation. (eV) alpha = probe convergence semi-angle. 0 for TEM mode, parallel beam (mrad) beta = detector collection semi-angle. (mrad) - ''' + """ F = (1+(E_0/1022))/(1+E_0/511)**2 Fg = (1+E_0/1022)/(1+E_0/511) @@ -88,7 +88,7 @@ def Eff_Beta(E_0, E_p, alpha, beta): def sum_spectra(s, xrange=[0, s.axes_manager[1].size-1], yrange=[ 0, s.axes_manager[1].size-1]): - ''' + """ Sums spectra in spectrum image together using the inputs xrange and y range. If these inputs are left blank then the all the spectra in the SI will be summed. @@ -103,16 +103,16 @@ def sum_spectra(s, xrange=[0, s.axes_manager[1].size-1], yrange=[ i.e. x = sum_spectra(s,xrange[2,5],yrange=[0,8]) default range is the full spectrum image - ''' + """ - '''convert SI into a easier to use form''' + """convert SI into a easier to use form""" spectrum = s.data - '''sum the spectra over the appropriate navigation dimensions''' + """sum the spectra over the appropriate navigation dimensions""" summed_spectrum = np.zeros([np.shape(spectrum)[2], 1]) for x in range(np.shape(spectrum)[2]): summed_spectrum[x] = np.sum( spectrum[yrange[0]:yrange[1]+1, xrange[0]:xrange[1]+1, x]) - '''write the summed spectrum back as a hyperspy signal''' + """write the summed spectrum back as a hyperspy signal""" sample_s = s.inav[0, 0] spectrum_sum = hs.signals.EELSSpectrum( summed_spectrum, axes=[ diff --git a/temul/topotem/fft_mapping.py b/temul/topotem/fft_mapping.py index 59e1845..d18ff98 100644 --- a/temul/topotem/fft_mapping.py +++ b/temul/topotem/fft_mapping.py @@ -46,7 +46,7 @@ def get_masked_ifft(image, mask_coords, mask_radius=10, image_space="real", keep_masked_area=True, plot_masked_fft=False): """ Creates an inverse fast Fourier transform (iFFT) from an image and mask - coordinates. Use `choose_mask_coordinates` to manually choose mask + coordinates. Use ``choose_mask_coordinates`` to manually choose mask coordinates in the FFT. Parameters @@ -54,17 +54,17 @@ def get_masked_ifft(image, mask_coords, mask_radius=10, image_space="real", image : Hyperspy 2D Signal mask_coords : list of pixel coordinates Pixel coordinates of the masking locations. See the example below for - two simple coordinates found using `choose_mask_coordinates`. + two simple coordinates found using ``choose_mask_coordinates``. mask_radius : int, default 10 Radius in pixels of the mask. image_space : str, default "real" If the input image is in Fourier/diffraction/reciprocal space already, set space="fourier". - keep_masked_area : Bool, default True + keep_masked_area : bool, default True If True, this will set the mask at the mask_coords. If False, this will set the mask as everything other than the mask_coords. Can be thought of as inversing the mask. - plot_masked_fft : Bool, default False + plot_masked_fft : bool, default False If True, the mask used to filter the FFT will be plotted. Good for checking that the mask is doing what you want. Can fail sometimes due to matplotlib plotting issues. @@ -107,10 +107,10 @@ def get_masked_ifft(image, mask_coords, mask_radius=10, image_space="real", elif image_space.lower() == 'fourier': fft = image else: - raise ValueError("image_space must be either `real` or `fourier`.") + raise ValueError("image_space must be either ``real`` or ``fourier``.") if len(mask_coords) == 0: - raise ValueError("`mask_coords` has not been set.") + raise ValueError("`mask_coords`` has not been set.") for mask_coord in mask_coords: x_pix = mask_coord[0] diff --git a/temul/topotem/lattice_structure_tools.py b/temul/topotem/lattice_structure_tools.py index 299ffa9..ddfb679 100644 --- a/temul/topotem/lattice_structure_tools.py +++ b/temul/topotem/lattice_structure_tools.py @@ -14,12 +14,12 @@ def calculate_atom_plane_curvature(sublattice, zone_vector_index, **kwargs): """ Calculates the curvature of the sublattice atom planes along the direction - given by `zone_vector_index`. In the case of [1] below, the curvature is + given by ``zone_vector_index``. In the case of [2]_. below, the curvature is the inverse of the radius of curvature, and is effectively equal to the second derivative of the displacement direction of the atoms. Because the first derivative is negligible, the curvature can be calculated as the - strain gradient [2]. - With the parameter func="strain_grad", this function calculates the strain + strain gradient [3]_. + With the parameter ``func="strain_grad"``, this function calculates the strain gradient of the atom planes of a Atomap Sublattice object. Parameters @@ -27,11 +27,11 @@ def calculate_atom_plane_curvature(sublattice, zone_vector_index, sublattice : Atomap Sublattice object zone_vector_index : int The index of the zone axis (translation symmetry) found by the Atomap - function `construct_zone_axes()`. + function ``construct_zone_axes()``. func : 'strain_grad' or function - Function that can be used by `scipy.optimize.curve_fit`. If + Function that can be used by ``scipy.optimize.curve_fit``. If func='strain_grad', then the - `temul.topotem.lattice_structure_tools.sine_wave_function_strain_gradient` + ``temul.topotem.lattice_structure_tools.sine_wave_function_strain_gradient`` function will be used. atom_planes : tuple, optional The starting and ending atom plane to be computed. Useful if only a @@ -45,12 +45,12 @@ def calculate_atom_plane_curvature(sublattice, zone_vector_index, title : string, default 'Curvature Map' filename : string, default None Name of the file to be saved. - plot, return_fits : Bool, default False + plot, return_fits : bool, default False If set to True, each atom plane fitting will be plotted along with its respective atom positions. The fitting parameters (popt) will be returned as a list. **kwargs - keyword arguments to be passed to `scipy.optimize.curve_fit`. + keyword arguments to be passed to ``scipy.optimize.curve_fit``. Examples -------- @@ -84,14 +84,14 @@ def calculate_atom_plane_curvature(sublattice, zone_vector_index, References ---------- - .. [1] Reference: Function adapted from a script written by - Dr. Marios Hadjimichael, and used in paper_name. The original MATLAB script - can be found in TEMUL/publication_examples/PTO_marios_hadj - .. [2] Reference: Landau and Lifshitz, Theory of Elasticity, Vol 7, - pp 47-49, 1981 + .. [2] Function adapted from a script written by + Dr. Marios Hadjimichael, and used in paper_name. The original + MATLAB script can be found in + TEMUL/publication_examples/PTO_marios_hadj + .. [3] Landau and Lifshitz, Theory of Elasticity, Vol 7, + pp 47-49, 1981 """ - if sublattice.zones_axis_average_distances is None: raise Exception( "zones_axis_average_distances is empty. " diff --git a/temul/topotem/polarisation.py b/temul/topotem/polarisation.py index 2f41f0b..af596f7 100644 --- a/temul/topotem/polarisation.py +++ b/temul/topotem/polarisation.py @@ -15,7 +15,7 @@ # good to have an example of getting atom_positions_A and B from sublattice def find_polarisation_vectors(atom_positions_A, atom_positions_B, save=None): - ''' + """ Calculate the vectors from atom_positions_A to atom_positions_B. Parameters @@ -41,7 +41,7 @@ def find_polarisation_vectors(atom_positions_A, atom_positions_B, >>> import numpy as np >>> vectors = np.asarray([u, v]).T - ''' + """ if len(atom_positions_A) != len(atom_positions_B): raise ValueError("atom_positions_A and atom_positions_B must be the " "same length") @@ -156,10 +156,10 @@ def plot_polarisation_vectors( quiver_units='width', pivot='middle', angles='xy', scale_units='xy', scale=None, headwidth=3.0, headlength=5.0, headaxislength=4.5, width=None, minshaft=1, minlength=1): - ''' + """ Plot the polarisation vectors. These can be found with - `find_polarisation_vectors()` or Atomap's - `get_polarization_from_second_sublattice()` function. + ``find_polarisation_vectors()`` or Atomap's + ``get_polarization_from_second_sublattice()`` function. Parameters ---------- @@ -182,69 +182,69 @@ def plot_polarisation_vectors( colorbar as an angle. Also note that "polar_colorwheel" will automatically generate a 2D RGB (HSV) list of colors that match with the vector components (uv). - overlay : Bool, default True - If set to True, the `image` will be plotting behind the arrows - unit_vector : Bool, default False + overlay : bool, default True + If set to True, the ``image`` will be plotting behind the arrows + unit_vector : bool, default False Change the vectors magnitude to unit vectors for plotting purposes. Magnitude will still be displayed correctly for colormaps etc. vector_rep : str, default "magnitude" - How the vectors are represented. This can be either their `magnitude` - or `angle`. One may want to use `angle` when plotting a contour map, + How the vectors are represented. This can be either their ``magnitude`` + or ``angle``. One may want to use ``angle`` when plotting a contour map, i.e., view the contours in terms of angles which can be useful for visualising regions of different polarisation. - degrees : Bool, default False + degrees : bool, default False Change between degrees and radian. Default is radian. - If `plot_style="colorwheel"`, then setting `degrees=True` will convert + If ``plot_style="colorwheel"``, then setting ``degrees=True`` will convert the angle unit to degree from the default radians. angle_offset : float, default None - If using `vector_rep="angle"` or `plot_style="contour"`, this angle + If using ``vector_rep="angle"`` or ``plot_style="contour"``, this angle will rotate the vector angles displayed by the given amount. Useful when you want to offset the angle of the atom planes relative to the polarisation. - save : string, default "polarisation_image" - If set to `save=None`, the image will not be saved. + save : string + If set to ``save=None``, the image will not be saved. title : string, default "" Title of the plot. color : string, default "r" - Color of the arrows when `plot_style="vector" or "contour". - cmap : matplotlib colormap, default "viridis" + Color of the arrows when ``plot_style="vector"`` or ``"contour"``. + cmap : matplotlib colormap, default ``"viridis"`` Matplotlib cmap used for the vector arrows. alpha : float, default 1.0 - Transparency of the matplotlib `cmap`. For `plot_style="colormap"` and - `plot_style="colorwheel"`, this alpha applies to the vector arrows. - For `plot_style="contour"` this alpha applies to the tricontourf map. + Transparency of the matplotlib ``cmap``. For ``plot_style="colormap"`` and + ``plot_style="colorwheel"``, this alpha applies to the vector arrows. + For ``plot_style="contour"`` this alpha applies to the tricontourf map. image_cmap : matplotlib colormap, default 'gray' Matplotlib cmap that will be used for the overlay image. monitor_dpi : int, default 96 The DPI of the monitor, generally 96 pixels. Used to scale the image so that large images render correctly. Use a smaller value to enlarge - too-small images. `monitor_dpi=None` will ignore this param. - no_axis_info : Bool, default True + too-small images. ``monitor_dpi=None`` will ignore this param. + no_axis_info : bool, default True This will remove the x and y axis labels and ticks from the plot if set to True. - invert_y_axis : Bool, default True + invert_y_axis : bool, default True If set to true, this will flip the y axis, effectively setting the top left corner of the image as the (0, 0) origin, as in scanning electron microscopy images. ticks : colorbar ticks, default None None or list of ticks or Locator If None, ticks are determined automatically from the input. - scalebar : Bool or dict, default False + scalebar : bool or dict, default False Add a matplotlib-scalebar to the plot. If set to True the scalebar will - appear similar to that given by Hyperspy's `plot()` function. A custom + appear similar to that given by Hyperspy's ``plot()`` function. A custom scalebar can be included as a dictionary and more custom options can be found in the matplotlib-scalebar package. See below for an example. - antialiased : Bool, default False - Applies only to `plot_style="contour"`. Essentially removes the + antialiased : bool, default False + Applies only to ``plot_style="contour"``. Essentially removes the border between regions in the tricontourf map. levels : int, default 20 Number of Matplotlib tricontourf levels to be used. - remove_vectors : Bool, default False - Applies only to `plot_style="contour"`. If set to True, do not plot + remove_vectors : bool, default False + Applies only to ``plot_style="contour"``. If set to True, do not plot the vector arrows. quiver_units : string, default 'width' The units parameter from the matplotlib quiver function, not to be - confused with the `units` parameter above for the image units. + confused with the ``units`` parameter above for the image units. ax.quiver parameters See matplotlib's quiver function for the remaining parameters. @@ -290,7 +290,7 @@ def plot_polarisation_vectors( ... plot_style='colormap', monitor_dpi=50, ... overlay=False, cmap='viridis') - vector plot with colormap viridis, with `vector_rep="angle"`: + vector plot with colormap viridis, with ``vector_rep="angle"``: >>> ax = tml.plot_polarisation_vectors(x, y, u, v, image=sublatticeA.image, ... unit_vector=False, save=None, @@ -387,7 +387,7 @@ def plot_polarisation_vectors( ... antialiased=True, degrees=True, ... ticks=[180, 90, 0, -90, -180]) - ''' + """ if isinstance(image, np.ndarray): pass @@ -396,7 +396,7 @@ def plot_polarisation_vectors( units = image.axes_manager[-1].units image = image.data else: - raise ValueError("`image` must be a 2D numpy array or 2D Hyperspy " + raise ValueError("``image`` must be a 2D numpy array or 2D Hyperspy " "Signal") u, v = np.array(u), np.array(v) @@ -477,8 +477,8 @@ def plot_polarisation_vectors( elif plot_style == "colorwheel": if vector_rep != "angle": - raise ValueError("`vector_rep` must be set to 'angle' when " - "`plot_style` is set to 'colorwheel'.") + raise ValueError("`vector_rep`` must be set to 'angle' when " + "`plot_style`` is set to 'colorwheel'.") if cmap is None: cmap = cc.cm.colorwheel @@ -577,24 +577,24 @@ def plot_polarisation_vectors( def get_angles_from_uv(u, v, degrees=False, angle_offset=None): - ''' + """ Calculate the angle of a vector given the uv components. Parameters ---------- u,v : list or 1D NumPy array - degrees : Bool, default False + degrees : bool, default False Change between degrees and radian. Default is radian. angle_offset : float, default None Rotate the angles by the given amount. The function assumes that if you - set `degrees=False` then the provided `angle_offset` is in radians, and - if you set `degrees=True` then the provided `angle_offset` is in + set ``degrees=False`` then the provided ``angle_offset`` is in radians, and + if you set ``degrees=True`` then the provided ``angle_offset`` is in degrees. Returns ------- 1D NumPy array - ''' + """ u_comp = np.array(u) v_comp = np.array(v).T @@ -621,7 +621,7 @@ def get_angles_from_uv(u, v, degrees=False, angle_offset=None): def get_vector_magnitudes(u, v, sampling=None): - ''' + """ Calculate the magnitude of a vector given the uv components. Parameters @@ -646,7 +646,7 @@ def get_vector_magnitudes(u, v, sampling=None): >>> sampling = 0.0321 >>> vector_mags = get_vector_magnitudes(u,v, sampling=sampling) - ''' + """ # uv_vector_comp_list = [list(uv) for uv in uv_vector_comp] # u = [row[0] for row in uv_vector_comp_list] @@ -669,7 +669,7 @@ def delete_atom_planes_from_sublattice(sublattice, divisible_by=3, offset_from_zero=0, opposite=False): - ''' + """ Delete atom_planes from a zone axis. Can choose whether to delete every second, third etc. atom plane, and the offset from the zero index. @@ -689,7 +689,7 @@ def delete_atom_planes_from_sublattice(sublattice, The atom_plane from which you start deleting. If offset_from_zero is 4, the fourth atom_plane will be the first deleted. - opposite : Bool, default False + opposite : bool, default False If this is set to True, the atom_plane specified by divisible_by will be kept and all others deleted. @@ -714,7 +714,7 @@ def delete_atom_planes_from_sublattice(sublattice, zones01_B = sublatticeA.get_all_atom_planes_by_zone_vector(zone_vec_list) zones01_A.plot() - ''' + """ sublattice.construct_zone_axes(atom_plane_tolerance=atom_plane_tolerance) zone_vec_needed = sublattice.zones_axis_average_distances[zone_axis_index] @@ -753,12 +753,12 @@ def delete_atom_planes_from_sublattice(sublattice, def _fit_line_clusters(arr, n, second_fit_rigid=True, plot=False): - ''' + """ Fits the data in an array to two straight lines using the - first `n` and second (last) `n` array value pairs. + first ``n`` and second (last) ``n`` array value pairs. The slope of the first fitting will be used for the - second fitting. Setting `second_fit_rigid` = False will reverse this + second fitting. Setting ``second_fit_rigid`` = False will reverse this behaviour. Parameters @@ -768,12 +768,12 @@ def _fit_line_clusters(arr, n, second_fit_rigid=True, plot=False): n : int The number of arr value pairs used at the beginning and end of the arr to fit a straight line. - second_fit_rigid : Bool, default True + second_fit_rigid : bool, default True Used to decide whether the first or second fitting's slope will be - rigid during fitting. With `second_fit_rigid` = True, the slope of the + rigid during fitting. With ``second_fit_rigid`` = True, the slope of the second fitting will be defined as the slope as the first fitting. The y-intercept is free to move. - plot : Bool, default False + plot : bool, default False Whether to plot the arr data, first and second fitting, and the line constructed halfway between the two. @@ -803,7 +803,7 @@ def _fit_line_clusters(arr, n, second_fit_rigid=True, plot=False): >>> fittings = _fit_line_clusters( ... arr, n=5, second_fit_rigid=False, plot=False) - ''' + """ x = arr[:, 0] y = arr[:, 1] @@ -842,13 +842,13 @@ def _fit_line_clusters(arr, n, second_fit_rigid=True, plot=False): def get_xyuv_from_line_fit(arr, n, second_fit_rigid=True, plot=False): - ''' + """ Fits the data in an array to two straight lines using the - first `n` and second (last) `n` array value pairs. Computes the distance of + first ``n`` and second (last) ``n`` array value pairs. Computes the distance of each array value pair from the line halfway between the two fitted lines. The slope of the first fitting will be used for the - second fitting. Setting `second_fit_rigid` = False will reverse this + second fitting. Setting ``second_fit_rigid`` = False will reverse this behaviour. Parameters @@ -858,12 +858,12 @@ def get_xyuv_from_line_fit(arr, n, second_fit_rigid=True, plot=False): n : int The number of arr value pairs used at the beginning and end of the arr to fit a straight line. - second_fit_rigid : Bool, default True + second_fit_rigid : bool, default True Used to decide whether the first or second fitting's slope will be - rigid during fitting. With `second_fit_rigid=True`, the slope of the + rigid during fitting. With ``second_fit_rigid=True``, the slope of the second fitting will be defined as the slope as the first fitting. The y-intercept is free to move. - plot : Bool, default False + plot : bool, default False Whether to plot the arr data, first and second fitting, and the line constructed halfway between the two. @@ -872,7 +872,7 @@ def get_xyuv_from_line_fit(arr, n, second_fit_rigid=True, plot=False): x, y, u, v : lists of equal length x, y are the original arr coordinates. u, v are the vector components pointing towards the halfway line from the arr coordinates. - These can be input to `plot_polarisation_vectors()` for visualisation. + These can be input to ``plot_polarisation_vectors()`` for visualisation. See Also -------- @@ -891,7 +891,7 @@ def get_xyuv_from_line_fit(arr, n, second_fit_rigid=True, plot=False): >>> x, y, u, v = get_xyuv_from_line_fit( ... arr, n=5, second_fit_rigid=False, plot=False) - ''' + """ arr = np.asarray(arr) fittings = _fit_line_clusters(arr=arr, n=n, second_fit_rigid=second_fit_rigid, plot=plot) @@ -926,15 +926,15 @@ def get_xyuv_from_line_fit(arr, n, second_fit_rigid=True, plot=False): def atom_deviation_from_straight_line_fit( sublattice, axis_number, n, second_fit_rigid=True, plot=False): - ''' + """ Fits the atomic columns in an atom plane to two straight lines using the - first `n` and second (last) `n` atomic columns. Computes the distance of + first ``n`` and second (last) ``n`` atomic columns. Computes the distance of each atomic column from the line halfway between the two fitted lines, as - described in [1]. This is done for every sublattice atom plane along the - chosen `axis_number`. + described in [1]_. This is done for every sublattice atom plane along the + chosen ``axis_number``. The slope of the first fitting will be used for the - second fitting. Setting `second_fit_rigid` = False will reverse this + second fitting. Setting ``second_fit_rigid`` = False will reverse this behaviour. Parameters @@ -942,33 +942,33 @@ def atom_deviation_from_straight_line_fit( sublattice : Atomap Sublattice object axis_number : int The index of the zone axis (translation symmetry) found by the Atomap - function `construct_zone_axes()`. For sublattices with heavily + function ``construct_zone_axes()``. For sublattices with heavily deviating atomic columns, you may need to use sublattice.construct_zone_axes(atom_plane_tolerance=1). n : int The number of columns used at the beginning and end of each atom plane to fit a straight line. - second_fit_rigid : Bool, default True + second_fit_rigid : bool, default True Used to decide whether the first or second fitting's slope will be - rigid during fitting. With `second_fit_rigid=True`, the slope of the + rigid during fitting. With ``second_fit_rigid=True``, the slope of the second fitting will be defined as the slope as the first fitting. The y-intercept is free to move. - plot : Bool, default False + plot : bool, default False Whether to plot the atom plane data, first and second fitting, and the line constructed halfway between the two. Returns ------- x, y, u, v : lists of equal length - x, y are the original atom position coordinates `sublattice.x_position` - and `sublattice.y_position` for the coordinates included in the chosen - `axis_number`. u, v are the polarisation vector components pointing + x, y are the original atom position coordinates ``sublattice.x_position` + and ``sublattice.y_position`` for the coordinates included in the chosen + ``axis_number``. u, v are the polarisation vector components pointing towards the halfway line from the atom position coordinates. - These can be input to `plot_polarisation_vectors()` for visualisation. + These can be input to ``plot_polarisation_vectors()`` for visualisation. See Also -------- - get_xyuv_from_line_fit : uses `_fit_line_clusters` to get xyuv from arr + get_xyuv_from_line_fit : uses ``_fit_line_clusters`` to get xyuv from arr References ---------- @@ -985,8 +985,8 @@ def atom_deviation_from_straight_line_fit( >>> sublattice = dd.get_polarised_single_sublattice() >>> sublattice.construct_zone_axes(atom_plane_tolerance=1) - Choose `n`: how many atom columns should be used to fit the line on each - side of the atom planes. If `n` is too large, the fitting will appear + Choose ``n`: how many atom columns should be used to fit the line on each + side of the atom planes. If ``n`` is too large, the fitting will appear incorrect. >>> n = 5 @@ -1019,7 +1019,7 @@ def atom_deviation_from_straight_line_fit( ... plot_style='colormap', cmap='cet_coolwarm', ... overlay=True, monitor_dpi=50) - ''' + """ if sublattice.zones_axis_average_distances is None: raise Exception( @@ -1059,26 +1059,26 @@ def _truncate_colormap(cmap, minval=0.0, maxval=1.0, n=100): def full_atom_plane_deviation_from_straight_line_fit(sublattice, axis_number: int = 0, save: str = ''): - ''' + """ Fit the atoms in an atom plane to a straight line and find the deviation of each atom position from that straight line fit. - To plot all zones see `plot_atom_deviation_from_all_zone_axes()`. + To plot all zones see ``plot_atom_deviation_from_all_zone_axes()``. Parameters ---------- sublattice : Atomap Sublattice object axis_number : int, default 0 The index of the zone axis (translation symmetry) found by the Atomap - function `construct_zone_axes()`. + function ``construct_zone_axes()``. save : string, default '' - If set to `save=None`, the array will not be saved. + If set to ``save=None``, the array will not be saved. Returns ------- Four lists: x, y, u, and v where x,y are the original atom position coordinates (simply sublattice.x_position, sublattice.y_position) and u,v are the polarisation vector components pointing to the new coordinate. - These can be input to `plot_polarisation_vectors()` for visualisation. + These can be input to ``plot_polarisation_vectors()`` for visualisation. Examples -------- @@ -1096,7 +1096,7 @@ def full_atom_plane_deviation_from_straight_line_fit(sublattice, >>> ax = plot_polarisation_vectors(x, y, u, v, image=sublatticeA.image, ... unit_vector=False, save=None, monitor_dpi=50) - ''' + """ if sublattice.zones_axis_average_distances is None: raise Exception( @@ -1190,7 +1190,7 @@ def plot_atom_deviation_from_all_zone_axes( pivot='middle', angles='xy', scale_units='xy', scale=None, headwidth=3.0, headlength=5.0, headaxislength=4.5, monitor_dpi=96, no_axis_info=True, scalebar=False): - ''' + """ Plot the atom deviation from a straight line fit for all zone axes constructed by an Atomap sublattice object. @@ -1198,7 +1198,7 @@ def plot_atom_deviation_from_all_zone_axes( ---------- sublattice : Atomap Sublattice object - For all other parameters see `plot_polarisation_vectors()`. + For all other parameters see ``plot_polarisation_vectors()``. Examples -------- @@ -1212,7 +1212,7 @@ def plot_atom_deviation_from_all_zone_axes( >>> tml.plot_atom_deviation_from_all_zone_axes( ... sublatticeA, save=None) - ''' + """ if image is None: image = sublattice.image @@ -1246,7 +1246,7 @@ def combine_atom_deviations_from_zone_axes( pivot='middle', angles='xy', scale_units='xy', scale=None, headwidth=3.0, headlength=5.0, headaxislength=4.5, monitor_dpi=96, no_axis_info=True, scalebar=False): - ''' + """ Combine the atom deviations of each atom for all zone axes. Good for plotting vortexes and seeing the total deviation from a perfect structure. @@ -1255,14 +1255,14 @@ def combine_atom_deviations_from_zone_axes( ---------- sublattice : Atomap Sublattice object - For the remaining parameters see `plot_polarisation_vectors()`. + For the remaining parameters see ``plot_polarisation_vectors()``. Returns ------- Four lists: x, y, u, and v where x,y are the original atom position coordinates (simply sublattice.x_position, sublattice.y_position) and u,v are the polarisation vector components pointing to the new coordinate. - These can be input to `plot_polarisation_vectors()` for visualisation. + These can be input to ``plot_polarisation_vectors()`` for visualisation. Examples -------- @@ -1287,7 +1287,7 @@ def combine_atom_deviations_from_zone_axes( >>> ax = plot_polarisation_vectors(x, y, u, v, save=None, ... image=sublatticeA.image) - ''' + """ all_atoms_in_planes_xy = [] all_atoms_in_planes_uv = [] @@ -1372,9 +1372,9 @@ def combine_atom_deviations_from_zone_axes( def get_divide_into(sublattice, averaging_by, sampling, zone_axis_index_A, zone_axis_index_B): - ''' - Calculate the `divide_into` required to get an averaging of `averaging_by`. - `divide_into` can then be used in + """ + Calculate the ``divide_into`` required to get an averaging of ``averaging_by``. + ``divide_into`` can then be used in temul.topotem.polarisation.get_average_polarisation_in_regions. Also finds unit cell size and the number of unit cells in the (square) image along the x axis. @@ -1383,8 +1383,8 @@ def get_divide_into(sublattice, averaging_by, sampling, ---------- sublattice : Atomap Sublattice averaging_by : int or float - How many unit cells should be averaged. If `averaging_by=2`, 2x2 unit - cells will be averaged when passing `divide_into` to + How many unit cells should be averaged. If ``averaging_by=2``, 2x2 unit + cells will be averaged when passing ``divide_into`` to temul.topotem.polarisation.get_average_polarisation_in_regions. sampling : float Pixel sampling of the image for calibration. @@ -1410,7 +1410,7 @@ def get_divide_into(sublattice, averaging_by, sampling, >>> num_unit_cells = cell_info[2] >>> sublattice.plot() # You can count the unit cells to check - ''' + """ if sublattice.zones_axis_average_distances is None: raise Exception( @@ -1445,7 +1445,7 @@ def get_divide_into(sublattice, averaging_by, sampling, def get_average_polarisation_in_regions(x, y, u, v, image, divide_into=8): - ''' + """ This function splits the image into the given number of regions and averages the polarisation of each region. @@ -1498,7 +1498,7 @@ def get_average_polarisation_in_regions(x, y, u, v, image, divide_into=8): ... monitor_dpi=50, image=sublatticeA.image, save=None, color='r', ... overlay=False, title='Averaged Vector Arrows') - ''' + """ if divide_into >= np.sqrt(len(x)): raise ValueError( @@ -1547,8 +1547,8 @@ def get_average_polarisation_in_regions(x, y, u, v, image, divide_into=8): def get_average_polarisation_in_regions_square(x, y, u, v, image, divide_into=4): - ''' - Same as `get_average_polarisation_in_regions()` but works for non-square + """ + Same as ``get_average_polarisation_in_regions()`` but works for non-square (rectangular) images. Parameters @@ -1597,7 +1597,7 @@ def get_average_polarisation_in_regions_square(x, y, u, v, image, >>> ax = plot_polarisation_vectors(x_new, y_new, u_new, v_new, image=image, ... color='r', overlay=False, monitor_dpi=50, ... title='Averaged Vector Arrows', save=None) - ''' + """ if divide_into >= np.sqrt(len(x)): raise ValueError( @@ -1653,7 +1653,7 @@ def get_strain_map(sublattice, zone_axis_index, theoretical_value, sampling=None, units='pix', vmin=None, vmax=None, cmap='inferno', title='Strain Map', plot=False, filename=None, return_x_y_z=False, **kwargs): - ''' + """ Calculate the strain across a zone axis of a sublattice. Parameters @@ -1661,7 +1661,7 @@ def get_strain_map(sublattice, zone_axis_index, theoretical_value, sublattice : Atomap Sublattice object zone_axis_index : int The zone axis you wish to specify. You are indexing - `sublattice.zones_axis_average_distances[zone_axis_index]`. + ``sublattice.zones_axis_average_distances[zone_axis_index]``. theoretical_value : float The theoretical separation between the atoms across (not along) the specified zone. @@ -1675,11 +1675,11 @@ def get_strain_map(sublattice, zone_axis_index, theoretical_value, Set to true if the figure should be plotted. filename : string, optional If filename is set, the strain signal and plot will be saved. - `plot` must be set to True. - return_x_y_z : Bool, default False - If this is set to True, the `strain_signal` (map), as well as separate + ``plot`` must be set to True. + return_x_y_z : bool, default False + If this is set to True, the ``strain_signal`` (map), as well as separate lists of the x, y, and strain values. - **kwargs : Matplotlib keyword arguments passed to `imshow()`. + **kwargs : Matplotlib keyword arguments passed to ``imshow()``. Returns ------- @@ -1696,7 +1696,7 @@ def get_strain_map(sublattice, zone_axis_index, theoretical_value, >>> sublatticeA.construct_zone_axes() >>> strain_map = get_strain_map(sublatticeA, zone_axis_index=0, units='nm', ... theoretical_value=1.9, sampling=0.1) - ''' + """ zone_vector_index_list = sublattice._get_zone_vector_index_list( zone_vector_list=None) @@ -1758,7 +1758,7 @@ def rotation_of_atom_planes(sublattice, zone_axis_index, angle_offset=None, vmin=None, vmax=None, cmap='inferno', title='Rotation Map', plot=False, filename=None, return_x_y_z=False, **kwargs): - ''' + """ Calculate a map of the angles between each atom along the atom planes of a zone axis. @@ -1767,11 +1767,11 @@ def rotation_of_atom_planes(sublattice, zone_axis_index, angle_offset=None, sublattice : Atomap Sublattice object zone_axis_index : int The zone axis you wish to specify. You are indexing - `sublattice.zones_axis_average_distances[zone_axis_index]`. + ``sublattice.zones_axis_average_distances[zone_axis_index]``. angle_offset : float, default None The angle which can be considered zero degrees. Useful when the atomic planes are at an angle. - degrees : Bool, default False + degrees : bool, default False Setting to False will return angle values in radian. Setting to True will return angle values in degrees. sampling : float, default None @@ -1784,11 +1784,11 @@ def rotation_of_atom_planes(sublattice, zone_axis_index, angle_offset=None, Set to true if the figure should be plotted. filename : string, optional If filename is set, the signal and plot will be saved. - `plot` must be set to True. - return_x_y_z : Bool, default False + ``plot`` must be set to True. + return_x_y_z : bool, default False If this is set to True, the rotation_signal (map), as well as separate lists of the x, y, and angle values. - **kwargs : Matplotlib keyword arguments passed to `imshow()`. + **kwargs : Matplotlib keyword arguments passed to ``imshow()``. Returns ------- @@ -1805,7 +1805,7 @@ def rotation_of_atom_planes(sublattice, zone_axis_index, angle_offset=None, >>> sublatticeA.construct_zone_axes() >>> rotation_map = rotation_of_atom_planes(sublatticeA, 3, degrees=True) - Use `angle_offset` to effectively change the angle of the horizontal axis + Use ``angle_offset`` to effectively change the angle of the horizontal axis when calculating angles: >>> rotation_map = rotation_of_atom_planes(sublatticeA, 3, angle_offset=45, @@ -1818,7 +1818,7 @@ def rotation_of_atom_planes(sublattice, zone_axis_index, angle_offset=None, ... sublatticeA, 3, degrees=True, return_x_y_z=True) >>> mean_angle = np.mean(angles) # useful for offsetting polar. plots - ''' + """ zone_vector_index_list = sublattice._get_zone_vector_index_list( zone_vector_list=None) @@ -1897,7 +1897,7 @@ def ratio_of_lattice_spacings(sublattice, zone_axis_index_A, zone_axis_index_B, ideal_ratio_one=True, sampling=1, units='pix', vmin=None, vmax=None, cmap='inferno', title='Spacings Map', filename=None, **kwargs): - ''' + """ Create a ratio map between two zone axes. Useful to see the tetragonality or shearing of unit cells. @@ -1906,10 +1906,10 @@ def ratio_of_lattice_spacings(sublattice, zone_axis_index_A, zone_axis_index_B, sublattice : Atomap Sublattice object zone_axis_index_A, zone_axis_index_B : int The zone axes you wish to specify. You are indexing - `sublattice.zones_axis_average_distances[zone_axis_index]`. + ``sublattice.zones_axis_average_distances[zone_axis_index]``. The signal created from zone_axis_index_A will be divided by the signal created from zone_axis_index_B. - ideal_ratio_one : Bool, default True + ideal_ratio_one : bool, default True If set to true this will force negative ratio values to be positive. Useful for seeing the overall tetragonality of a lattice. sampling : float, default None @@ -1920,7 +1920,7 @@ def ratio_of_lattice_spacings(sublattice, zone_axis_index_A, zone_axis_index_B, title : string, default "Spacings Map" filename : string, optional If filename is set, the strain signal and plot will be saved. - **kwargs : Matplotlib keyword arguments passed to `imshow()`. + **kwargs : Matplotlib keyword arguments passed to ``imshow()``. Returns ------- @@ -1938,12 +1938,12 @@ def ratio_of_lattice_spacings(sublattice, zone_axis_index_A, zone_axis_index_B, >>> sublatticeA.construct_zone_axes() >>> ratio_map = ratio_of_lattice_spacings(sublatticeA, 0, 1) - Use `ideal_ratio_one=False` to view the direction of tetragonality + Use ``ideal_ratio_one=False`` to view the direction of tetragonality >>> ratio_map = ratio_of_lattice_spacings(sublatticeA, 0, 1, ... ideal_ratio_one=False) - ''' + """ zone_vector_index_list = sublattice._get_zone_vector_index_list( zone_vector_list=None) @@ -2033,7 +2033,7 @@ def angle_label(vector_rep="magnitude", units='pix', degrees=False): vector_label = "Angle (rad)" else: raise ValueError( - "`vector_rep` must be either 'magnitude' or 'angle'.") + "`vector_rep`` must be either 'magnitude' or 'angle'.") return (vector_label) @@ -2041,7 +2041,7 @@ def atom_to_atom_distance_grouped_mean(sublattice, zone_axis_index, aggregation_axis="y", slice_thickness=10, sampling=None, units="pix"): - ''' + """ Average the atom to atom distances along the chosen zone_axis_index parallel to the chosen axis ('x' or 'y'). @@ -2093,7 +2093,7 @@ def atom_to_atom_distance_grouped_mean(sublattice, zone_axis_index, plt.plot(groupings, grouped_means, 'k.') plt.show() - ''' + """ zone_vector_index_list = sublattice._get_zone_vector_index_list( zone_vector_list=None) _, zone_vector = zone_vector_index_list[zone_axis_index] From 892d432f6bd26d2b3e575b92d96d17ca0532a633 Mon Sep 17 00:00:00 2001 From: PinkShnack Date: Sun, 7 Nov 2021 19:07:06 +0100 Subject: [PATCH 2/5] docs: revert reference numbers, don't know what is wrong. --- doc/_build/doctrees/api_doc.doctree | Bin 1104931 -> 1105601 bytes doc/_build/doctrees/environment.pickle | Bin 1797718 -> 1797718 bytes doc/_build/html/api_doc.html | 16 ++++++++-------- temul/model_creation.py | 4 ++-- temul/topotem/lattice_structure_tools.py | 8 ++++---- 5 files changed, 14 insertions(+), 14 deletions(-) diff --git a/doc/_build/doctrees/api_doc.doctree 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    The slope of the first fitting will be used for the second fitting. Setting second_fit_rigid = False will reverse this @@ -256,7 +256,7 @@

    ModulesReferences

    -
    1
    +
    1

    Reference: Julie Gonnissen, Dmitry Batuk, Guillaume F. Nataf, Lewys Jones, Artem M. Abakumov, Sandra Van Aert, Dominique Schryvers, Ekhard K. H. Salje, Direct Observation of Ferroelectric @@ -1350,11 +1350,11 @@

    Modules temul.topotem.lattice_structure_tools.calculate_atom_plane_curvature(sublattice, zone_vector_index, func='strain_grad', atom_planes=None, sampling=None, units='pix', vmin=None, vmax=None, cmap='inferno', title='Curvature Map', filename=None, plot=False, return_fits=False, **kwargs)ΒΆ

    Calculates the curvature of the sublattice atom planes along the direction -given by zone_vector_index. In the case of [2]_. below, the curvature is +given by zone_vector_index. In the case of [1]_. below, the curvature is the inverse of the radius of curvature, and is effectively equal to the second derivative of the displacement direction of the atoms. Because the first derivative is negligible, the curvature can be calculated as the -strain gradient 3. +strain gradient 2. With the parameter func="strain_grad", this function calculates the strain gradient of the atom planes of a Atomap Sublattice object.

    @@ -1423,13 +1423,13 @@

    ModulesReferences

    -
    2
    +
    1

    Function adapted from a script written by Dr. Marios Hadjimichael, and used in paper_name. The original MATLAB script can be found in TEMUL/publication_examples/PTO_marios_hadj

    -
    3
    +
    2

    Landau and Lifshitz, Theory of Elasticity, Vol 7, pp 47-49, 1981

    @@ -2466,7 +2466,7 @@

    Modules[2]_

    +agrees with the simulated image in a realistic manner. See [1]_.

    Parameters

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Computes the distance of each atomic column from the line halfway between the two fitted lines, as -described in 1. This is done for every sublattice atom plane along the +described in [1]_. This is done for every sublattice atom plane along the chosen axis_number.

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