combine

ccdproc.combine(img_list, output_file=None, method=u'average', weights=None, scale=None, mem_limit=16000000000.0, minmax_clip=False, minmax_clip_min=None, minmax_clip_max=None, sigma_clip=False, sigma_clip_low_thresh=3, sigma_clip_high_thresh=3, sigma_clip_func=<numpy.ma.core._frommethod instance>, sigma_clip_dev_func=<numpy.ma.core._frommethod instance>, **ccdkwargs)

Convenience function for combining multiple images

Parameters:

img_list : list, ‘string’

A list of fits filenames or CCDData objects that will be combined together. Or a string of fits filenames seperated by comma ”,”.

output_file: ‘string’, optional

Optional output fits filename to which the final output can be directly written.

method: ‘string’ (default average)

Method to combine images.

‘average’ : To combine by calculating average ‘median’ : To combine by calculating median

weights: `~numpy.ndarray`, optional

Weights to be used when combining images. An array with the weight values. The dimensions should match the the dimensions of the data arrays being combined.

scale : function or array-like or None, optional

Scaling factor to be used when combining images. Images are multiplied by scaling prior to combining them. Scaling may be either a function, which will be applied to each image to determine the scaling factor, or a list or array whose length is the number of images in the Combiner. Default is None.

mem_limit : float (default 16e9)

Maximum memory which should be used while combining (in bytes).

minmax_clip : Boolean (default False)

Set to True if you want to mask all pixels that are below minmax_clip_min or above minmax_clip_max before combining.

Parameters below are valid only when minmax_clip is set to True.

minmax_clip_min: None, float

All pixels with values below minmax_clip_min will be masked.

minmax_clip_max: None or float

All pixels with values above minmax_clip_max will be masked.

sigma_clip : Boolean (default False)

Set to True if you want to reject pixels which have deviations greater than those set by the threshold values. The algorithm will first calculated a baseline value using the function specified in func and deviation based on sigma_clip_dev_func and the input data array. Any pixel with a deviation from the baseline value greater than that set by sigma_clip_high_thresh or lower than that set by sigma_clip_low_thresh will be rejected.

Parameters below are valid only when sigma_clip is set to True.

sigma_clip_low_thresh : positive float or None

Threshold for rejecting pixels that deviate below the baseline value. If negative value, then will be convert to a positive value. If None, no rejection will be done based on sigma_clip_low_thresh.

sigma_clip_high_thresh : positive float or None

Threshold for rejecting pixels that deviate above the baseline value. If None, no rejection will be done based on sigma_clip_high_thresh.

sigma_clip_func : function

Function for calculating the baseline values (i.e. mean or median). This should be a function that can handle numpy.ma.core.MaskedArray objects.

sigma_clip_dev_func : function

Function for calculating the deviation from the baseline value (i.e. std). This should be a function that can handle numpy.ma.core.MaskedArray objects.

**ccdkwargs: Other keyword arguments for CCD Object’s fits reader.

Returns:

combined_image: CCDData

CCDData object based on the combined input of CCDData objects.