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Updated CHANGELOG/README
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‎CHANGELOG.md‎

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@@ -32,12 +32,12 @@ Supported versions of Python and Qt bindings have been updated:
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PlotPy 2.0 is a major release because it also brings a lot of new features:
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* ``plot.PlotWidget``, ``plot.PlotDialog``, and ``plot.PlotWindow``: API overhaul
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* `plot.PlotWidget`, `plot.PlotDialog`, and `plot.PlotWindow`: API overhaul
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(simple, more consistent, more flexible, more extensible - see documentation
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for details)
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* ``plot.SyncPlotWindow``: new class to show multiple plots in a single window,
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* `plot.SyncPlotWindow`: new class to show multiple plots in a single window,
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in a synchronized way (zoom, pan, etc.)
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* ``widgets.selectdialog.SelectDialog``: a dialog box to select items using a
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* `widgets.selectdialog.SelectDialog`: a dialog box to select items using a
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shape tool (segment, rectangle or custom)
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* Image lookup table (LUT):
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* Initially, the LUT alpha channel was either constant (input parameter
@@ -56,56 +56,56 @@ PlotPy 2.0 is a major release because it also brings a lot of new features:
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* This is one of the benefits of porting back [guiqwt](https://pypi.org/project/guiqwt/)
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changes since the merge (i.e. between 2016 and 2023)
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* New SVG-based shapes:
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* ``items.RectangleSVGShape``: rectangle shape based on SVG data or file
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* ``items.SquareSVGShape``: square shape based on SVG data or file
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* ``items.CircleSVGShape``: circle shape based on SVG data or file
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* ``builder.PlotBuilder``:
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* Renamed ``PlotBuilder`` (originally ``guiqwt.builder.PlotItemBuilder``)
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* Builder instance is still available using ``from plotpy.builder import make``
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* `items.RectangleSVGShape`: rectangle shape based on SVG data or file
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* `items.SquareSVGShape`: square shape based on SVG data or file
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* `items.CircleSVGShape`: circle shape based on SVG data or file
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* `builder.PlotBuilder`:
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* Renamed `PlotBuilder` (originally `guiqwt.builder.PlotItemBuilder`)
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* Builder instance is still available using `from plotpy.builder import make`
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* Plot widget creation is now supported:
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* ``make.widget()`` for ``plot.PlotWidget``
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* ``make.dialog()`` for ``plot.PlotDialog``
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* ``make.window()`` for ``plot.PlotWindow``
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* `make.widget()` for `plot.PlotWidget`
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* `make.dialog()` for `plot.PlotDialog`
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* `make.window()` for `plot.PlotWindow`
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* Added support for more plot items:
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* ``make.contours()`` for generating a list of ``items.ContourItem`` objects
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* ``make.annotated_point()`` for ``items.AnnotatedPoint``
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* ``make.polygon()`` for ``items.PolygonShape``
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* ``make.svg()`` for ``items.RectangleSVGShape``, ``items.SquareSVGShape``,
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and ``items.CircleSVGShape``
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* `make.contours()` for generating a list of `items.ContourItem` objects
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* `make.annotated_point()` for `items.AnnotatedPoint`
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* `make.polygon()` for `items.PolygonShape`
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* `make.svg()` for `items.RectangleSVGShape`, `items.SquareSVGShape`,
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and `items.CircleSVGShape`
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* Added JSON serialization support for all plot items (curve, image, etc.)
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* Brand new documentation, based on Sphinx with links to other projects API, examples
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and tutorials (e.g. on development related topics).
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* Black code formatting on all Python files
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* New automated test suite:
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* Automatic execution: ``--unattended`` command line option (Qt loop is bypassed)
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* Test suite based on ``pytest``, supporting ``pytest-cov`` for coverage testing,
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``pytest-xvfb`` for headless testing, and ``pytest-qt`` for Qt testing
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* Automatic execution: `--unattended` command line option (Qt loop is bypassed)
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* Test suite based on `pytest`, supporting `pytest-cov` for coverage testing,
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`pytest-xvfb` for headless testing, and `pytest-qt` for Qt testing
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* Added support for Coverage: test coverage improved up to 70%
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* Added typing annotations on (almost) all Python files
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* Distribution: switched to ``pyproject.toml`` (still relying on ``setuptools`` and
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``setup.py`` for building Cython/C++ extensions)
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* Distribution: switched to `pyproject.toml` (still relying on `setuptools` and
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`setup.py` for building Cython/C++ extensions)
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* Added code quality configuration files:
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* ``.pylintrc``: pylint configuration file
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* ``.isort.cfg``: isort configuration file
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* ``.coveragerc``: coverage configuration file
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* `.pylintrc`: pylint configuration file
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* `.isort.cfg`: isort configuration file
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* `.coveragerc`: coverage configuration file
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* Added Visual Studio Code configuration files:
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* ``.vscode/settings.json``: Python interpreter, code formatting, etc.
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* ``.vscode/tasks.json``: build, test, etc.
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* ``.vscode/launch.json``: run current file, run tests, etc.
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* `.vscode/settings.json`: Python interpreter, code formatting, etc.
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* `.vscode/tasks.json`: build, test, etc.
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* `.vscode/launch.json`: run current file, run tests, etc.
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PlotPy 2.0 also brings a lot of bug fixes and improvements:
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* Handled all Cython/C++ extensions compilation warnings
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* Fixed all NumPy deprecation issues (e.g. ``numpy.matrix``)
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* Fixed all NumPy deprecation issues (e.g. `numpy.matrix`)
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* Fixed (annotated) circle/ellipse item creation/test
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* Fixed all documentation build warnings
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* Fixed regressions introduced by PlotPy V1 on top of guiqwt:
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* Global references for the Debian package management
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* Major aspect ratio issues:
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* When resizing the plot widget (images were downsized indefinitely)
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* When auto-scaling the plot widget (images were not displayed entirely)
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* ``TrImageItem`` rotation algorithm
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* `TrImageItem` rotation algorithm
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* Oblique cross-section test
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* About dialog, version informations
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* Ported all [guiqwt](https://pypi.org/project/guiqwt/) bug fixes since the merge
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* Optimized colormap icon caching
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* X-axis direction and auto-scale
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* Added load test (with a very large number of plot widgets)
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* Coordinates inversion in ``EllipseShape``
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* Coordinates inversion in `EllipseShape`
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* ValueError with levels histogram
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* Various fixes regarding plot item creation, cross-section features,
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PyQt5 support, DICOM support, TIFF support, etc.

‎README.md‎

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* [PythonQwt](https://pypi.python.org/pypi/PythonQwt) plotting widgets library
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* [NumPy](https://pypi.python.org/pypi/NumPy) and [SciPy](https://pypi.python.org/pypi/SciPy) scientific computing libraries
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Based on PythonQwt and on the scientific modules NumPy and SciPy, plotpy is a
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Python library providing efficient 2D data-plotting features (curve/image
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visualization and related tools) for interactive computing and signal/image
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processing application development.
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<img src="https://raw.githubusercontent.com/PlotPyStack/plotpy/master/doc/images/panorama.png">
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See [documentation](https://plotpy.readthedocs.io/en/latest/) for more details on
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* Copyright © 2023 [CEA](https://www.cea.fr), [Codra](https://codra.net/), [Pierre Raybaut](https://github.com/PierreRaybaut).
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* Licensed under the terms of the BSD 3-Clause (see [LICENSE](LICENSE)).
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### Features
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The `plotpy` library also provides the following features:
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* Ready-to-use [plot widgets and dialog boxes](https://plotpy.readthedocs.io/en/latest/features/plot/index.html)
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* [pyplot](https://plotpy.readthedocs.io/en/latest/features/pyplot.html): interactive plotting widgets, equivalent to `matplotlib.pyplot`, at
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least for the implemented functions
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* supported [plot items](https://plotpy.readthedocs.io/en/latest/features/items/index.html): curve, image, histogram, label, shape, annotation, ...
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* interactive features:
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* multiple object selection for moving objects or editing their
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properties through automatically generated dialog boxes
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* item list panel: move objects from foreground to background,
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show/hide objects, remove objects, ...
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* customizable aspect ratio for images
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* tons of ready-to-use tools: plot canvas export to image file, image
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snapshot, interval selection, image rectangular filter, etc.
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* curve fitting tool with automatic fit, manual fit with sliders, ...
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* contrast adjustment panel for images: select the LUT by moving a range selection
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object on the image levels histogram, eliminate outliers, ...
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## Features
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* X-axis and Y-axis cross-sections: support for multiple images, average
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cross-section tool on a rectangular area, ...
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The `plotpy` library also provides the following features.
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* apply any affine transform to displayed images in real-time (rotation,
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magnification, translation, horizontal/vertical flip, ...)
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General plotting features:
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* application development helpers:
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* ready-to-use [plot widgets and dialog boxes](https://plotpy.readthedocs.io/en/latest/features/plot/index.html)
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* load/save graphical objects (curves, images, shapes)
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* a lot of test scripts which demonstrate `plotpy` features (see [examples](https://plotpy.readthedocs.io/en/latest/intro/examples.html))
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## Dependencies
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### Requirements
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* Python 3.8+
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* [PyQt5](https://pypi.python.org/pypi/PyQt5) (Python Qt bindings)
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* [QtPy](https://pypi.org/project/QtPy/) (abstraction layer for Python-Qt binding libraries)
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* [PythonQwt](https://pypi.org/project/PythonQwt/) (Python wrapper for the Qwt C++ class library)
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* [guidata](https://pypi.org/project/guidata/) (Python library generating graphical user interfaces for easy dataset editing and display)
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### Build requirements
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* [setuptools](https://pypi.org/project/setuptools/) (Python packages management)
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* [wheel](https://pypi.org/project/wheel/) (Python built-package format)
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* [build](https://pypi.org/project/build/) (Python package builder)
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* [numpy](https://pypi.org/project/numpy/) (Python package for scientific computing)
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* [Cython](https://pypi.org/project/Cython/) (Python package for writing C extensions for the Python language)
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* C++ compiler (e.g. [GCC](https://gcc.gnu.org/), [MSVC](https://visualstudio.microsoft.com/vs/features/cplusplus/))
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## Installation
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### From PyPI
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Using ``pip``:
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```bash
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pip install plotpy
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```
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* Ready-to-use [plot widgets and dialog boxes](https://plotpy.readthedocs.io/en/latest/features/plot/index.html)
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* [pyplot](https://plotpy.readthedocs.io/en/latest/features/pyplot.html): interactive
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plotting widgets, equivalent to `matplotlib.pyplot`, at least for the implemented functions
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* Supported [plot items](https://plotpy.readthedocs.io/en/latest/features/items/index.html):
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curves, images, contours, histograms, labels, shapes, annotations, ...
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Interactive features (i.e. not only programmatic plotting but also with mouse/keyboard):
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* Multiple object selection for moving objects or editing their properties through
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automatically generated dialog boxes
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* Item list panel: move objects from foreground to background, show/hide objects,
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remove objects, ...
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* Customizable aspect ratio for images
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* Tons of ready-to-use tools: plot canvas export to image file, image snapshot,
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interval selection, image rectangular filter, etc.
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* Curve fitting tool with automatic fit, manual fit with sliders, ...
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* Contrast adjustment panel for images: select the LUT by moving a range selection
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object on the image levels histogram, eliminate outliers, ...
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* X-axis and Y-axis cross-sections: support for multiple images, average
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cross-section tool on a rectangular area, ...
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* Apply any affine transform to displayed images in real-time (rotation,
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magnification, translation, horizontal/vertical flip, ...)
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Application development helpers:
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### From the source package
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* Ready-to-use [plot widgets and dialog boxes](https://plotpy.readthedocs.io/en/latest/features/plot/index.html)
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* Load/save graphical objects (curves, images, shapes) into HDF5, JSON or INI files
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* A lot of test scripts which demonstrate `plotpy` features
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(see [examples](https://plotpy.readthedocs.io/en/latest/intro/examples.html))
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Using ``build``:
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## Dependencies and installation
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```bash
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python -m build
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```
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See [Installation](https://plotpy.readthedocs.io/en/latest/intro/installation.html)
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section in the documentation for more details.

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