ccd_process¶

ccdproc.ccd_process(ccd, oscan=None, trim=None, error=False, master_bias=None, dark_frame=None, master_flat=None, bad_pixel_mask=None, gain=None, readnoise=None, oscan_median=True, oscan_model=None, min_value=None, dark_exposure=None, data_exposure=None, exposure_key=None, exposure_unit=None, dark_scale=False, add_keyword=True)[source]¶

Perform basic processing on ccd data.

The following steps can be included:

overscan correction (subtract_overscan())
trimming of the image (trim_image())
create deviation frame (create_deviation())
gain correction (gain_correct())
add a mask to the data
subtraction of master bias (subtract_bias())
subtraction of a dark frame (subtract_dark())
correction of flat field (flat_correct())

The task returns a processed CCDData object.

Parameters:

ccd : CCDData

Frame to be reduced.

oscan : CCDData, str or None, optional

For no overscan correction, set to None. Otherwise provide a region of ccd from which the overscan is extracted, using the FITS conventions for index order and index start, or a slice from ccd that contains the overscan. Default is None.

trim : str or None, optional

For no trim correction, set to None. Otherwise provide a region of ccd from which the image should be trimmed, using the FITS conventions for index order and index start. Default is None.

error : bool, optional

If True, create an uncertainty array for ccd. Default is False.

master_bias : CCDData or None, optional

A master bias frame to be subtracted from ccd. The unit of the master bias frame should match the unit of the image after gain correction. Default is None.

dark_frame : CCDData or None, optional

A dark frame to be subtracted from the ccd. The unit of the master dark frame should match the unit of the image after gain correction. Default is None.

master_flat : CCDData or None, optional

A master flat frame to be divided into ccd. The unit of the master flat frame should match the unit of the image after gain correction. Default is None.

bad_pixel_mask : numpy.ndarray or None, optional

A bad pixel mask for the data. The bad pixel mask should be in given such that bad pixels have a value of 1 and good pixels a value of 0. Default is None.

gain : Quantity or None, optional

Gain value to multiple the image by to convert to electrons. Default is None.

readnoise : Quantity or None, optional

Read noise for the observations. The read noise should be in electrons. Default is None.

oscan_median : bool, optional

If true, takes the median of each line. Otherwise, uses the mean. Default is True.

oscan_model : Model or None, optional

Model to fit to the data. If None, returns the values calculated by the median or the mean. Default is None.

min_value : float or None, optional

Minimum value for flat field. The value can either be None and no minimum value is applied to the flat or specified by a float which will replace all values in the flat by the min_value. Default is None.

dark_exposure : Quantity or None, optional

Exposure time of the dark image; if specified, must also provided data_exposure. Default is None.

data_exposure : Quantity or None, optional

Exposure time of the science image; if specified, must also provided dark_exposure. Default is None.

exposure_key : Keyword, str or None, optional

Name of key in image metadata that contains exposure time. Default is None.

exposure_unit : Unit or None, optional

Unit of the exposure time if the value in the meta data does not include a unit. Default is None.

dark_scale : bool, optional

If True, scale the dark frame by the exposure times. Default is False.

Returns:

occd : CCDData

Reduded ccd.

Examples

To overscan, trim and gain correct a data set:

>>> import numpy as np
>>> from astropy import units as u
>>> from ccdproc import CCDData
>>> from ccdproc import ccd_process
>>> ccd = CCDData(np.ones([100, 100]), unit=u.adu)
>>> nccd = ccd_process(ccd, oscan='[1:10,1:100]',
...                    trim='[10:100, 1:100]', error=False,
...                    gain=2.0*u.electron/u.adu)

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ccd_process¶