59 lines
2.1 KiB
YAML
Executable File
59 lines
2.1 KiB
YAML
Executable File
# Analysis environment with the rather large OpenCV package for image analysis
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name: analysis-stable
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channels:
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- conda-forge
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dependencies:
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# essentials
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- python=3.13 # keep at 3.13 beause of bitshuffle
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- pip
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- numpy>=1.26,<3 # also because of bitshuffle (perhaps not necessary and be deleted in the future)
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- scipy
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- pandas
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- numba
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- matplotlib
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- ipython
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- jupyterlab
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- ipympl
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- joblib
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- tqdm # sfdata dependency but here given explicitly
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- lmfit
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- pytest
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- bitshuffle=0.5.2 # 0.5.2 is compatible with Python 3.12–3.13 on conda-forge;
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# Python >=3.14 requires new builds, not a new version (currently not well specified enough to upgrade)
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- opencv # OpenCV package for more elaborate image analysis
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# useful development packages
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- black
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- pytest # for testing the cristallina package
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- h5py # sfdata dependency but here given explicitly
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- pint
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- line_profiler
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- loguru
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- pylint
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- ipytest # used to be taken from pip, but here we test the conda-forge version
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- sqlalchemy # X-ray transmission calculations and similar
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- xraydb # X-ray transmission calculations and similar
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- scikit-image # Image processing
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- partialjson # For processing unfinished runs
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# and extra control parts
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- fabric
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# Jupyterlab extensions
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- nb_conda_kernels # for discovery of other kernels
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# - jupyterlab-drawio
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- jupyterlab_code_formatter
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# - jupytext # needs to be tested manually
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# PSI specific modules
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- paulscherrerinstitute::sfdata
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- paulscherrerinstitute::jungfrau_utils # should be a dependency of sfdata, but not listed there explicitly
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- paulscherrerinstitute::data_api
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- pip:
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- -e /sf/cristallina/applications/cristallina # Creates a "local package" of cristallina .This shows a deprication warning and
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# should be changed to using .toml in the future.
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# If wanted, jupyterlab_hdf can be added for nicer tables
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# pip install jupyterlab_hdf
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# jupyter labextension install @jupyterlab/hdf5
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