Merge remote branch: rebase onto stable with SHA pinning and test_is_zip fix

Author: Copilot

.idea/PythonCode.iml

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+ifeq ($(OS),"Windows_NT")
+	SPHINX_BUILD	=	sphinx-build.bat
+else
+	SPHINX_BUILD	=	sphinx-build
+endif
+PYTHON_SETUP	=	python setup.py
+
+BRANCH		=	`git branch | grep '*' | cut -d ' ' -f 2`
+
+clean:
+	$(MAKE) -C doc clean
+	- rm dist/*
+	- rm -rf build/*
+	- find -name '__pycache__' -exec rm -rf {} \;
+
+test:
+	pytest -n `python -c 'import os;print(min(8,os.cpu_count()))'`
+
+check:
+	prospector -E -0 --profile-path=. -P .landscape.yml Stoner > prospector-report.txt
+
+black:
+	find Stoner -name '*.py' | xargs -d "\n" black -l 119
+	find doc/samples -name '*.py' | xargs  -d "\n" black -l 80
+	find scripts -name '*.py' | xargs -d "\n" black -l 80
+
+commit: black
+	$(MAKE) -C doc readme
+	git add tests
+	git add Stoner
+	git add doc/samples
+	git commit -a
+	git push origin $(BRANCH)
+
+_build_wheel:
+	$(MAKE) -C doc readme
+	$(PYTHON_SETUP) sdist bdist_wheel --universal
+	twine upload dist/*
+
+wheel: clean test _build_wheel
+
+docbuild: FORCE
+	$(MAKE) -C doc clean
+	$(MAKE) -C doc html
+	( cd ../gh-pages; git pull )
+	rsync -rcm --perms --chmod=ugo=rwX --delete  --filter="P .git" --filter="P .nojekyll" doc/_build/html/ ../gh-pages/
+
+conda:
+	conda build --python=3.6 recipe &
+	conda build --python=3.7 recipe &
+	conda build --python 3.8 recipe &
+
+
+rtdbuild: export READTHEDOCS=1
+rtdbuild: docbuild
+
+FORCE:

.idea/modules.xml

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+.. image:: https://travis-ci.com/stonerlab/Stoner-PythonCode.svg?branch=master
+    :target: https://travis-ci.com/stonerlab/Stoner-PythonCode
+
+.. image:: https://coveralls.io/repos/github/stonerlab/Stoner-PythonCode/badge.svg?branch=master
+    :target: https://coveralls.io/github/stonerlab/Stoner-PythonCode?branch=master
+
+.. image:: https://api.codacy.com/project/badge/Grade/372f2f9227134fab9c6c2f2ba83962ba
+    :target: https://www.codacy.com/app/stonerlab/Stoner-PythonCode?utm_source=github.com&utm_medium=referral&utm_content=stonerlab/Stoner-PythonCode&utm_campaign=Badge_Grade
+
+.. image:: https://badge.fury.io/py/Stoner.svg
+   :target: https://badge.fury.io/py/Stoner
+
+.. image:: https://anaconda.org/phygbu/stoner/badges/version.svg
+   :target: https://anaconda.org/phygbu/stoner
+
+.. image:: https://readthedocs.org/projects/stoner-pythoncode/badge/?version=latest
+   :target: http://stoner-pythoncode.readthedocs.io/en/latest/?badge=latest
+   :alt: Documentation Status
+
+.. image:: https://zenodo.org/badge/10057055.svg
+   :target: https://zenodo.org/badge/latestdoi/10057055
+
+
+Introduction
+============
+
+
+The  *Stoner* Python package is a set of utility classes for writing data analysis code. It was written within
+the Condensed Matter Physics group at the University of Leeds as a shared resource for quickly writing simple
+programs to do things like fitting functions to data, extract curve parameters, churn through large numbers of
+small text data files and work with certain types of scientific image files.
+
+For a general introduction, users are referred to the Users Guide, which is part of the `online documentation`_ along with the
+API Reference guide. The `github repository`_ also contains some example scripts.
+
+Getting this Code
+==================
+
+.. image:: https://i.imgur.com/h4mWwM0.png
+    :target: https://www.youtube.com/watch?v=uZ_yKs11W18
+    :alt: Introduction and Installation Guide to Stoner Pythin Package
+    :width: 320
+
+The *Stoner* package requires h5py>=2.7.0, lmfit>=0.9.7, matplotlib>=2.0,numpy>=1.13, Pillow>=4.0,
+scikit-image>=0.13.0 & scipy>=1.0.0 and also optional depends on  filemagic, npTDMS, imreg_dft and numba.
+
+Ananconda Python (and probably other scientific Python distributions) include nearly all of the dependencies, and the remaining
+dependencies are collected together in the **phygbu** repositry on anaconda cloud. The easiest way to install the Stoner package is,
+therefore, to install the most recent Anaconda Python distribution.
+
+Compatibility
+--------------
+
+Versions 0.9.x (stable branch) are compatible with Python 2.7, 3.5, 3.6 and 3.7. The latest 0.9.6 version is also compatible with Python 3.8
+The development verstion (0.10, master branch) is compatible with Python 3.6, 3.7 and 3.8 but not 2.7.
+
+Conda packages are prepared for the stable branch and when the development branch enters beta testing. Pip wheels are prepared for selected stable releases only.
+
+Installation
+------------
+
+After installing the current Anaconda version, open a terminal (Mac/Linux) or Anaconda Prompt (Windows) an do:
+
+.. code-block:: sh
+
+    conda install -c phygbu Stoner
+
+If you are not using Anaconda python, then pip should also work:
+
+.. code-block:: sh
+
+    pip install Stoner
+
+This will install the Stoner package and any missing dependencies into your current Python environment. Since the package is under fairly
+constant updates, you might want to follow the development with git. The source code, along with example scripts
+and some sample data files can be obtained from the github repository: https://github.com/stonerlab/Stoner-PythonCode
+
+Overview
+========
+
+The main part of the **Stoner** package provides four basic top-level classes that describe:
+    - an individual file of experimental data (**Stoner.Data**),
+    - an individual experimental image (**Stoner.ImageFile**),
+    - a list (such as a directory tree on disc) of many experimental files (**Stoner.DataFolder**)
+    - a list (such as a directory tree on disc) of many image files (**Stoner.ImageFolder**).
+
+For our research, a typical single experimental data file is essentially a single 2D table of floating point
+numbers with associated metadata, usually saved in some ASCII text format. This seems to cover most experiments
+in the physical sciences, but it you need a more complex format with more dimensions of data, we suggest
+you look elsewhere.
+
+Increasingly we seem also to need process image files and so partnering the experimental measurement file classes,
+we have a parallel set of classes for interacting with image data.
+
+The general philosophy used in the package is to work with data by using methods that transform the data in place.
+Additionally, many of the analysis methods pass a copy of the data as their return value, allowing a sequence of
+operations to be chained together in one line.
+
+This is a *data-centric* approach - we have some data and we do various operations on it to get to our result. In
+contrasr, traditional functional programming thinks in terms of various functions into which you pass data.
+
+
+Data and Friends
+----------------
+
+**Stoner.Data** is the core class for representing individual experimental data sets.
+It is actually composed of several mixin classes that provide different functionality, with methods
+to examine and manipulate data, manage metadata, load and save data files, plot results and carry out various analysis tasks.
+It has a large number of sub classes - most of these are in Stoner.formats and are used to handle the loading of specific
+file formats.
+
+ImageFile
+---------
+
+**Stoner.ImageFile** is the top-level class for managing image data. It is the equivalent of **Stoner.Data** and maintains
+metadta and comes with a number of methods to manipulate image data. The image data is stored internally as a masked numpy
+array and where possible the masking is taken into account when carrying out image analysis tasks. Through some abuse of
+the Python class system, functions in the scpy.ndimage and scikit-image modules are mapped into methods of the ImageFile
+class allowing a very rich set of operations on the data sets. The default IO methods handle tiff and png images and can
+store the metadata of the ImageFile within those file formats.
+
+DataFolder
+----------
+
+**Stoner.DataFolder** is a class for assisting with the work of processing lots of files in a common directory
+structure. It provides methods to list. filter and group data according to filename patterns or metadata and then to execute
+a function on each file or group of files and then collect metadata from each file in turn. A key feature of DataFolder is
+its ability to work with the collated metadata from the individual files that are held in the DataFolder.
+In combination with its ability to walk through a complete heirarchy of groups of
+**Data** objects, the handling of the common metadata provides powerful tools for quickly writing data reduction scripts.
+
+ImageFolder
+-----------
+
+**Stoner.ImageFolder** is the equivalent of DataFolder but for images (although technically a DataFolder can contain ImageFile
+objects, the ImageFolder class offers additional Image specific functionality). There is a subclass of ImageFolder,
+**Stoner.Image.ImageStack** that uses a 3D numpy array as it's primary image store which permits faster access
+(at the expense of a larger memory footprint) than the lazy loading ordered dictionary of **ImageFolder**
+
+Other Modules and Classes
+-------------------------
+
+The **Stoner.HDF5** module provides some additional classes to manipulate *Data* and *DataFolder* objects within HDF5
+format files. HDF5 is a common chouse for storing data from large scale facilties, although providing a way to handle
+arbitary HDF5 files is beyond the scope of this package at this time - the format is much too complex and flexible to make that
+an easy task. Rather it provides a way to work with large numbers of experimental sets using just a single file which may be less
+brutal to your computer's OS than having directory trees with millions of individual files.
+
+The module also provides some classes to support loading some particular HDF5 flavoured files into **Data** and **ImageFile**
+objects.
+
+The **Stoner.Zip** module provides a similar set of classes to **Stoner.HDF5** but working with the ubiquitous zip compressed file format.
+
+Resources
+==========
+
+Included in the `github repository`_  are a (small) collection of sample scripts
+for carrying out various operations and some sample data files for testing the loading and processing of data. There is also a
+`User_Guide`_ as part of this documentation, along with a :doc:`complete API reference <Stoner>`
+
+Contact and Licensing
+=====================
+
+The lead developer for this code is `Dr Gavin Burnell`_ <[email protected]>, but many current and former members of
+the CM Physics group have contributed code, ideas and bug testing.
+
+The User Guide gives the current list of other contributors to the project.
+
+This code and the sample data are all (C) The University of Leeds 2008-2021 unless otherwise indficated in the source
+file. The contents of this package are licensed under the terms of the GNU Public License v3
+
+Recent Changes
+==============
+
+Current PyPi Version
+--------------------
+
+The current version of the package on PyPi will be the stable branch until the development branch enters beta testing, when we start
+making beta packages available.
+
+Development Version
+-------------------
+
+The current development version is hosted in the master branch of the repository and will become version 0.10.
+
+New Features in 0.10-dev include:
+
+    *   Refactor Stoner.Core.DataFile to move functionality to mixin classes
+    *   Start implementing PEP484 Type hinting
+    *   Support pathlib for paths
+    *   Switch from Tk based dialogs to Qt5 ones
+    *   Refactoring the **baseFolder** class so that sub-groups are stored in an attribute that is an instance of a custom
+        dictionary with methods to prune and filter in the virtual tree of sub-folders.
+    *   Refactoring of the **ImageArray** and **ImageFile** so that binding of external functions as methods is done at
+        class definition time rather than at runtime with overly complex __getattr__ methods. The longer term goal is to
+        depricate the use of ImageArray in favour of just using ImageFile.
+    *   Introduce interactive selection of boxes, lines and mask regions for interactive Matplotlib backends.
+
+Build Status
+~~~~~~~~~~~~
+
+Version 0.7 onwards are tested using the Travis-CI services with unit test coverage assessed by Coveralls.
+
+Version 0.9 is tested with Python 2.7, 3.5, 3.6 using the standard unittest module.
+
+The development version - which will be 0.10 is tested using **pytest** with Python 3.6, Python 3.7 and Python 3.8.
+
+
+Citing the Stoner Package
+~~~~~~~~~~~~~~~~~~~~~~~~~
+
+We maintain a digital object identifier (doi) for this package (linked to on the status bar at the top of this readme) and
+encourage any users to cite this package via that doi.
+
+Stable Versions
+---------------
+
+Online documentation for all versions can be found on the ReadTheDocs pages `online documentation`_
+
+Version 0.9 is the current stable version. This is the last version to support Python 2 and 3<3.6. Features of this release are:
+
+    *   Refactoring of the package into a more granual core, plot, formats, folders packages with submodules
+    *   Overhaul of the documentation and user guide
+    *   Dropping support for the older Stoner.Image.stack.ImageStack class
+    *   Droppping support for matplotlib<2.0
+    *   Support for Python 3.7 (and 3.8 from 0.9.6)
+    *   Unit tests now > 80% coverage across the package.
+
+Version 0.8 is the previous stable release. The main new features were:
+
+    *   Reworking of the ImageArray, ImageFile and ImageFolder with many updates and new features.
+    *   New mixin based ImageStack2 that can manipulate a large number of images in a 3D numpy array
+    *   Continued re-factoring of DataFolder using the mixin approach
+    *   Further increases to unit-test coverage, bug fixes and refactoring of some parts of the code.
+    *   _setas objects implement a more complete MutableMapping interface and also support +/- operators.
+    *   conda packages now being prepared as the preferred package format
+
+0.8.2 was the final release of the 0.8.0 branch
+
+The old stable version is 0.7.2. Features of 0.7.2 include
+
+    *   Replace older AnalyseFile and PlotFile with mixin based versions AnalysisMixin and PlotMixin
+    *   Addition of Stoner.Image package to handle image analysis
+    *   Refactor DataFolder to use Mixin classes
+    *   DataFolder now defaults to using :py:class:`Stoner.Core.Data`
+    *   DataFolder has an options to skip iterating over empty Data files
+    *   Further improvements to :py:attr:`Stoner.Core.DataFile.setas` handline.
+
+No further relases will be made to 0.7.x.
+
+0.6, 0.7 should work on Python 2.7 and 3.5
+0.8 is also tested on Python 3.6
+
+.. _online documentation: http://stoner-pythoncode.readthedocs.io/en/latest/
+.. _github repository: http://www.github.com/stonerlab/Stoner-PythonCode/
+.. _Dr Gavin Burnell: http://www.stoner.leeds.ac.uk/people/gb
+.. _User_Guide: http://stoner-pythoncode.readthedocs.io/en/latest/UserGuide/ugindex.html

.ipynb_checkpoints/Makefile-checkpoint

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+[codestyle]
+indentation = True
+edge_line = True
+edge_line_columns = 79
+
+[main]
+version = 0.2.0
+

.ipynb_checkpoints/README-checkpoint.rst

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+[encoding]
+text_encoding = utf-8
+
+[main]
+version = 0.2.0
+

.spyproject/config/backups/codestyle.ini.bak

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+[vcs]
+use_version_control = False
+version_control_system = 
+
+[main]
+version = 0.2.0
+

.spyproject/config/backups/encoding.ini.bak

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+[workspace]
+restore_data_on_startup = True
+save_data_on_exit = True
+save_history = True
+save_non_project_files = False
+project_type = 'empty-project-type'
+recent_files = ['Stoner\\folders\\methods.py', 'scripts\\VSManalysis_v2.py', 'Stoner\\tools\\widgets.py', 'tests\\stoner\\tools\\test_widgets.py', 'Stoner\\core\\base.py', 'Stoner\\analysis\\utils.py']
+
+[main]
+version = 0.2.0
+recent_files = []
+

.spyproject/config/backups/vcs.ini.bak

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+[codestyle]
+indentation = True
+edge_line = True
+edge_line_columns = 79
+
+[main]
+version = 0.2.0
+

.spyproject/config/backups/workspace.ini.bak

@@ -0,0 +1,5 @@
+[codestyle]
+indentation = True
+edge_line = True
+edge_line_columns = 79
+