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 * trimming of the image * create deviation frame * gain correction * add a mask to the data * subtraction of master bias * subtraction of a dark frame * correction of flat field
The task returns a processed
ccdproc.CCDData
object.Parameters: ccd: `~ccdproc.CCDData`
Frame to be reduced
oscan: None, str, or, `~ccdproc.ccddata.CCDData`
For no overscan correction, set to None. Otherwise proivde 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.
trim: None or str
For no trim correction, set to None. Otherwise proivde a region of ccd from which the image should be trimmed, using the FITS conventions for index order and index start.
error: boolean
If True, create an uncertainty array for ccd
master_bias: None or `~ccdproc.CCDData`
A master bias frame to be subtracted from ccd.
dark_frame: None or `~ccdproc.CCDData`
A dark frame to be subtracted from the ccd.
master_flat: None or `~ccdproc.CCDData`
A master flat frame to be divided into ccd.
bad_pixel_mask: None or `~numpy.ndarray`
A bad pixel mask for the data. The bad pixel mask should be in given such that bad pixels havea value of 1 and good pixels a value of 0.
gain: None or `~astropy.Quantity`
Gain value to multiple the image by to convert to electrons
readnoise: None or `~astropy.Quantity`
Read noise for the observations. The read noise should be in electrons.
oscan_median : bool, optional
If true, takes the median of each line. Otherwise, uses the mean
oscan_model :
Model
, optionalModel to fit to the data. If None, returns the values calculated by the median or the mean.
min_value : None or float
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.
dark_exposure :
Quantity
Exposure time of the dark image; if specified, must also provided
data_exposure
.data_exposure :
Quantity
Exposure time of the science image; if specified, must also provided
dark_exposure
.exposure_key : str or
Keyword
Name of key in image metadata that contains exposure time.
exposure_unit :
Unit
Unit of the exposure time if the value in the meta data does not include a unit.
dark_scale: boolean
If True, scale the dark frame by the exposure times
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)