ewoksid02.utils.io.get_array_dark#

ewoksid02.utils.io.get_array_dark(filename_dark, data_signal_shape, datatype=None, binning=(1, 1), dummy=None, delta_dummy=None, filename_mask=None, dark_filter=None, dark_filter_quantil_lower=0.1, dark_filter_quantil_upper=0.9, use_cupy=False, persistent=True)[source]#

Generate the array of the dark current correction, eventually applying the mask and dummy pixel filtering and dark dataset filtering params:

  • filename_dark (str): the filename of the dark current correction

  • data_signal_shape (tuple): the shape of the data signal array, used for binning unification

  • datatype (str): format of the imported array, if None, datatype is respected

  • binning (tuple): binning of the data signal, used for binning unification

  • dummy (int): if not None, the value of the dummy pixels to filter

  • delta_dummy (float): if dummy is not None, the tolerance around the dummy value

  • filename_mask (str): the filename of the mask

  • dark_filter (str): if not None, the method to use for filtering a stack of darks into a single dark (e.g. “median” or “quantil”)

  • dark_filter_quantil_lower (float): if dark_filter is “quantil”, the lower quantile to use for filtering

  • dark_filter_quantil_upper (float): if dark_filter is “quantil”, the upper quantile to use for filtering

  • use_cupy (bool): if True, returns a cupy.asarray

  • persistent (bool): if True, the array is cached in memory and only reloaded if the file modification time changes

returns:

  • Optional[Union[numpy.ndarray, cupy.ndarray]]: the array dark current correction or None if the file does not exist

Parameters:

  • filename_dark (str)

  • data_signal_shape (tuple)

  • datatype (str)

  • binning (tuple)

  • dummy (int)

  • delta_dummy (float)

  • filename_mask (str)

  • dark_filter (str)

  • dark_filter_quantil_lower (float)

  • dark_filter_quantil_upper (float)

  • use_cupy (bool)

  • persistent (bool)

Return type:

Optional[ndarray]