82 lines
2.8 KiB
Python
82 lines
2.8 KiB
Python
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import os
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import shutil
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from ._registry import method_files_map
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try:
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import appdirs
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except ImportError:
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appdirs = None
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def _clear_cache(datasets, cache_dir=None, method_map=None):
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if method_map is None:
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# Use SciPy Datasets method map
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method_map = method_files_map
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if cache_dir is None:
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# Use default cache_dir path
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if appdirs is None:
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# appdirs is pooch dependency
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raise ImportError("Missing optional dependency 'pooch' required "
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"for scipy.datasets module. Please use pip or "
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"conda to install 'pooch'.")
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cache_dir = appdirs.user_cache_dir("scipy-data")
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if not os.path.exists(cache_dir):
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print(f"Cache Directory {cache_dir} doesn't exist. Nothing to clear.")
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return
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if datasets is None:
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print(f"Cleaning the cache directory {cache_dir}!")
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shutil.rmtree(cache_dir)
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else:
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if not isinstance(datasets, (list, tuple)):
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# single dataset method passed should be converted to list
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datasets = [datasets, ]
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for dataset in datasets:
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assert callable(dataset)
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dataset_name = dataset.__name__ # Name of the dataset method
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if dataset_name not in method_map:
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raise ValueError(f"Dataset method {dataset_name} doesn't "
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"exist. Please check if the passed dataset "
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"is a subset of the following dataset "
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f"methods: {list(method_map.keys())}")
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data_files = method_map[dataset_name]
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data_filepaths = [os.path.join(cache_dir, file)
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for file in data_files]
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for data_filepath in data_filepaths:
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if os.path.exists(data_filepath):
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print("Cleaning the file "
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f"{os.path.split(data_filepath)[1]} "
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f"for dataset {dataset_name}")
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os.remove(data_filepath)
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else:
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print(f"Path {data_filepath} doesn't exist. "
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"Nothing to clear.")
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def clear_cache(datasets=None):
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"""
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Cleans the scipy datasets cache directory.
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If a scipy.datasets method or a list/tuple of the same is
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provided, then clear_cache removes all the data files
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associated to the passed dataset method callable(s).
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By default, it removes all the cached data files.
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Parameters
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----------
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datasets : callable or list/tuple of callable or None
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Examples
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--------
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>>> from scipy import datasets
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>>> ascent_array = datasets.ascent()
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>>> ascent_array.shape
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(512, 512)
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>>> datasets.clear_cache([datasets.ascent])
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Cleaning the file ascent.dat for dataset ascent
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"""
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_clear_cache(datasets)
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