2023-05-04 19:16:35 +02:00
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import numpy as np
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import glob
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from datetime import date
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2023-05-04 18:32:17 +02:00
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2023-05-04 19:16:35 +02:00
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def get_mask(dataArray):
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return np.ones(dataArray.shape, dtype=bool)
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2023-05-04 18:32:17 +02:00
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2023-05-04 19:16:35 +02:00
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def remove_bad_shots(dataArray, **kwargs):
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dataArray.loc[dict(kwargs)] = np.nan
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2023-05-04 18:32:17 +02:00
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2023-05-04 19:16:35 +02:00
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def auto_rechunk(dataSet):
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kwargs = {
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key: "auto"
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2023-05-05 18:25:03 +02:00
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for key in dataSet.dims
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2023-05-04 19:16:35 +02:00
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}
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return dataSet.chunk(**kwargs)
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2023-05-04 18:32:17 +02:00
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2023-05-04 19:16:35 +02:00
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def get_h5_file_path(folderpath, maxFileNum=None, filename='*.h5',):
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filepath = np.sort(glob.glob(folderpath + filename))
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if maxFileNum is None:
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return filepath
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else:
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return filepath[:maxFileNum]
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def get_date():
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today = date.today()
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2023-05-05 18:25:03 +02:00
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return today.strftime("%y/%m/%d")
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def resolve_fit_result(fitResult):
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return
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