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a1c1de4adf
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eae8a1bde4
@ -147,11 +147,17 @@ def read_detector_data(filepath, cami_meta=None):
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# optional parameters
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# optional parameters
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if "/entry1/sample/magnetic_field" in h5f:
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if "/entry1/sample/magnetic_field" in h5f:
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scan["mf"] = h5f["/entry1/sample/magnetic_field"][:]
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scan["mf"] = h5f["/entry1/sample/magnetic_field"][:]
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# TODO: NaNs are not JSON compliant, so replace them with None
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# this is not a great solution, but makes it safe to use the array in bokeh
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scan["mf"] = np.where(np.isnan(scan["mf"]), None, scan["mf"])
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if "/entry1/sample/temperature" in h5f:
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if "/entry1/sample/temperature" in h5f:
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scan["temp"] = h5f["/entry1/sample/temperature"][:]
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scan["temp"] = h5f["/entry1/sample/temperature"][:]
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elif "/entry1/sample/Ts/value" in h5f:
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elif "/entry1/sample/Ts/value" in h5f:
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scan["temp"] = h5f["/entry1/sample/Ts/value"][:]
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scan["temp"] = h5f["/entry1/sample/Ts/value"][:]
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# TODO: NaNs are not JSON compliant, so replace them with None
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# this is not a great solution, but makes it safe to use the array in bokeh
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scan["temp"] = np.where(np.isnan(scan["temp"]), None, scan["temp"])
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# overwrite metadata from .cami
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# overwrite metadata from .cami
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if cami_meta is not None:
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if cami_meta is not None:
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