Step Arguments for Non-IFU data

The outlier_detection step for non-IFU data has the following optional arguments that control the behavior of the processing:

--weight_type (string, default=’exptime’)

The type of data weighting to use during resampling; options are ‘exptime’, ‘error’, and ‘None’.

--pixfrac (float, default=1.0)

The pixel fraction used during resampling; valid values go from 0.0 to 1.0.

--kernel (string, default=’square’)

The form of the kernel function used to distribute flux onto a resampled image. Options are ‘square’, ‘turbo’, ‘point’, ‘lanczos’, and ‘tophat’.

--fillval (string, default=’INDEF’)

The value to assign to resampled image pixels that have zero weight or do not receive any flux from any input pixels during drizzling. Any floating-point value, given as a string, is valid. A value of ‘INDEF’ will use the last zero weight flux.

--nlow (integer, default=0)

The number of low values in each pixel stack to ignore when computing the median value.

--nhigh (integer, default=0)

The number of high values in each pixel stack to ignore when computing the median value.

--maskpt (float, default=0.7)

The percent of maximum weight to use as lower-limit for valid data; valid values go from 0.0 to 1.0.

--snr (string, default=’4.0 3.0’)

The signal-to-noise values to use for bad pixel identification. Valid values are a pair of floating-point values in a single string.

--scale (string, default=’0.5 0.4’)

The scaling factor applied to derivative used to identify bad pixels. Valid values are a pair of floating-point values in a single string.

--backg (float, default=0.0)

User-specified background value to apply to the median image.

--save_intermediate_results (boolean, default=False)

Specifies whether or not to save any intermediate products created during step processing.

--resample_data (boolean, default=True)

Specifies whether or not to resample the input images when performing outlier detection.

--good_bits (string, default=”~DO_NOT_USE”)

The DQ bit values from the input image DQ arrays that should be considered ‘good’ when building the weight mask. See DQ flag Parameter Specification for details.

--scale_detection (bool, default=False)

Specifies whether or not to rescale the individual input images to match total signal when doing comparisons.

--allowed_memory (float, default=None)

Specifies the fractional amount of free memory to allow when creating the resampled image. If None, the environment variable DMODEL_ALLOWED_MEMORY is used. If not defined, no check is made. If the resampled image would be larger than specified, an OutputTooLargeError exception will be generated.

For example, if set to 0.5, only resampled images that use less than half the available memory can be created.

--in_memory (boolean, default=False)

Specifies whether or not to load and create all images that are used during processing into memory. If False, input files are loaded from disk when needed and all intermediate files are stored on disk, rather than in memory.

Step Arguments for IFU data

The outlier_detection step for IFU data has the following optional arguments that control the behavior of the processing:

--kernel_size (string, default=’7 7’)

The size of the kernel to use to normalize the pixel differences. The kernel size must only contain odd values.

--threshold_percent (float, default=99.8)

The threshold (in percent) of the normalized minimum pixel difference used to identify bad pixels. Pixels with a normalized minimum pixel difference above this percentage are flagged as a outlier.

--save_intermediate_results (boolean, default=False)

Specifies whether or not to save any intermediate products created during step processing.

--in_memory (boolean, default=False)

Specifies whether or not to load and create all images that are used during processing into memory. If False, input files are loaded from disk when needed and all intermediate files are stored on disk, rather than in memory.