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Merge pull request #1208 from wright-group/3.6
3.6.0
2 parents c6341f6 + 8cf949d commit d4cce82

6 files changed

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.github/workflows/python-test.yml

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python -m pip install --upgrade pip wheel setuptools
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python -m pip install --upgrade .[dev]
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- name: Test with pytest
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env:
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MPLBACKEND: "agg"
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run: |
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pytest --color=yes
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CHANGELOG.md

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## [Unreleased]
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## [3.6.0]
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### Added
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- `Data.norm_for_each`: easier norm-by-axis syntax
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- `kit.from_list_of_objects`: convenience method for grabbing an channel/variable/axis/etc. using multiple specifiers
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### Added
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- initial release
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[Unreleased]: https://github.com/wright-group/WrightTools/-/compare/3.5.5...master
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[Unreleased]: https://github.com/wright-group/WrightTools/-/compare/3.6.0...master
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[3.6.0]: https://github.com/wright-group/WrightTools/-/compare/3.5.5...3.6.0
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[3.5.5]: https://github.com/wright-group/WrightTools/compare/3.5.3...3.5.5
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[3.5.4]: https://github.com/wright-group/WrightTools/compare/3.5.3...3.5.4
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[3.5.3]: https://github.com/wright-group/WrightTools/compare/3.5.2...3.5.3

WrightTools/VERSION

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3.5.5
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3.6.0

tests/artists/test_interact2D.py

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#! /usr/bin/env python3
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import pytest
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import numpy as np
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import WrightTools as wt
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from WrightTools import datasets
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return wt.artists.interact2D(data, xaxis=0, yaxis=1)
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@pytest.mark.xfail(reason="sometimes fails for artificial reasons")
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def test_4D():
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w1 = np.linspace(-5, 5, 31)
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w2 = w1[::2].copy()

tests/artists/test_quick2D.py

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from WrightTools import datasets
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def test_backend():
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import matplotlib
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assert matplotlib.get_backend() == "agg"
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def test_save_arguments():
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p = datasets.wt5.v1p0p0_perovskite_TA # axes w1=wm, w2, d2
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# A race condition exists where multiple tests access the same file in short order

tests/data/norm_for_each.py

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data.norm_for_each("d2", 0, new_channel={"name": "ai0_d2_norm"})
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assert np.all(data.channels[-1][:].max(axis=(0, 1)) == 1)
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data.norm_for_each("d1", 0, new_channel={"name": "ai0_d1_norm"})
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data.norm_for_each("d1", 0, new_channel=True)
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data.norm_for_each("d1", 0, new_channel={"name": "ai0_d1_norm1"})
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data.channels[0].normalize()
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assert np.all(np.isclose(data.ai0_d1_norm[:], data.channels[0][:]))
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