Update dependencies and docs,, add GitHub action, and clean up · ScientificDataFormat/SDF-Python@172c7aa · GitHub
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Update dependencies and docs,, add GitHub action, and clean up
fixes #6 fixes #7 fixes #8
1 parent 08c10c1 commit 172c7aa

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.github/workflows/build.yml

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.travis.yml

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CHANGELOG.md

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DEV_README.md

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README.rst

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.. image:: https://ci.appveyor.com/api/projects/status/github/ScientificDataFormat/SDF-Python?branch=master
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Scientific Data Format for Python
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=================================
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To install the latest development version::
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python -m pip install --upgrade https://github.com/ScientificDataFormat/SDF-Python/archive/develop.zip
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python -m pip install --upgrade https://github.com/ScientificDataFormat/SDF-Python/archive/main.zip
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Tutorial
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-----------------------------
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|copyright| 2020 |Dassault Systemes|
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|copyright| 2024 |Dassault Systemes|
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.. _SDF specification: https://github.com/ScientificDataFormat/SDF
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.. _HDF5: https://www.hdfgroup.org/hdf5/

appveyor.yml

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requirements.txt

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h5py
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matplotlib
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numpy
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numpy>=2
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xlrd
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scipy

sdf/examples/interp_1d.py

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figure, axes = plt.subplots(len(methods), sharex=True)
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figure.canvas.set_window_title('Inter- and Extrapolation Methods')
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figure.set_facecolor('white')
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for ax, method in zip(axes, methods):
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yi = table.evaluate((xi,), interp=method[0], extrap=method[1])
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dyi = table.evaluate_derivative((xi,), (dxi,), interp=method[0], extrap=method[1])
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ax.set_title("interp='%s', extrap='%s'" % method)
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ax.grid(b=True, which='both', color='0.9', linestyle='-', zorder=0)
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ax.grid(True, color='0.9')
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ax.plot(x, y, 'or', label='samples', zorder=300)
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ax.plot(xi, yi, 'b', label='interpolated', zorder=100)
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ax.plot(xi, dyi, 'r', label='derivative', zorder=100)

sdf/examples/interp_2d.py

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XI, YI = np.meshgrid(xi, yi, indexing='ij')
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figure, axes = plt.subplots(ncols=2, nrows=2, sharex=True, sharey=True)
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figure.canvas.set_window_title('Inter- & Extrapolation Methods')
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figure.set_facecolor('white')
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axes = axes.flatten()
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im = NonUniformImage(ax)
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im.set_data(x, y, Z)
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im.set_extent((-3, 3, -3, 3))
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ax.images.append(im)
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ax.add_image(im)
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ax.set_xlim([-6, 6])
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ax.set_ylim([-6, 6])
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im = NonUniformImage(ax)
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im.set_data(xi, yi, ZI)
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im.set_extent((-6, 6, -6, 6))
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ax.images.append(im)
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ax.add_image(im)
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figure.tight_layout()
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plt.show()

sdf/examples/spline_1d.py

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