`DispersedPRF` API Documentation

Dispersed PSF

Bases: pandoraaperture.prf.PRF

Special case where PRF is dispersed in a line

Special PRF class for making Pixel Response Functions that is dispersed across pixels.

Parameters:

Name	Description	Default
`trace_row`	Row position within the spectral trace that corresponds to each element in the flux array. Units of pixels.	required
`trace_column`	Column position within the spectral trace that corresponds to each element in the flux array. Units of pixels.	required
`flux`	Array of the flux of the PRF as a function of position. Usually normalized such that the total flux is 1.	required
`pixel_size`	True detector pixel size in dimensions of length/pixel	required
`sub_pixel_size`	PSF file pixel size in dimensions of length/pixel	required
`scale`	How much to scale the PRF by. Scale of 2 makes the PSF 2x broader. Default is 1.	`1`
`imshape`	Tuple of the shape of the true image. If using ROIs, use the shape of the image that each ROI is cut out from. Use format (row, column).	`(400, 80)`
`imcorner`	Tuple of the lower left corner of the image, i.e. it's origin. Use this to move the image around on the grid. If using a window mode, make sure to set this to the right corner. Use format (row, column).	`(0, 0)`

`evaluate(location=None, normalize=True, gradients=False)`

Parameters:

Name	Description	Default
`location`	Location of the source on the detector. Use format (row, column). If not set will default to `self._default_location` which is in the middle of the image as set by `imshape` and `imcorner`.	`None`
`normalize`	Whether to normalize the input data so that the total flux is 1.	`True`
`gradients`	Whether to return gradients. If True, will return an additional 2 arrays that contain the gradients in each axis.	`False`

Returns:

Name	Type	Description
`row_im`	`ndarray`	1D Array of integer row values at which the PRF is evaluated.
`column_im`	`ndarray`	1D Array of integer column values at which the PRF is evaluated.
`prf_im`	`ndarray`	2D Array of PRF values.
`dprf_im`	`ndarray`	2, 2D arrays of the gradient of the PRF values. Only returned if `gradients`=True.

Load a PRF object from a file.

Parameters:

Name	Type	Description	Default
`file`		Input file to use. Choose either a string path to the file or an `astropy.fits.HDUList` object	required
`pixel_resolution`		The separation between different elements in the PRF model in pixels. For example 0.25 means there will be approximately 0.25 pixels between each element.	`0.25`

Load a PRF from pandoraref.

Parameters:

Name	Type	Description	Default
`name`	`str`	Name of detector, choose from VISDA or NIRDA.	`'nirda'`
`pixel_resolution`		The separation between different elements in the PRF model in pixels. For example 0.25 means there will be approximately 0.25 pixels between each element.	`0.25`

Plots the PRF. Use this functon to visually inspect the PRF.

Parameters:

Name	Description	Default
`location`	Location of the source on the detector. Use format (row, column). If not set will default to `self._default_location` which is in the middle of the image as set by `imshape` and `imcorner`.	`None`
`normalize`	Whether to normalize the input data so that the total flux is 1.	`True`
`gradients`	Whether to return gradients. If True, will return an additional 2 arrays that contain the gradients in each axis.	`False`

Returns:

Name	Type	Description
`X`	`Sparse3D`	Sparse3D object containing the PRF at a given location.
`dX0`	`Sparse3D`	Sparse3D object containing the gradient of the PRF in axis 0 at a given location. Only returned if `gradients`=True.
`dX1`	`Sparse3D`	Sparse3D object containing the gradient of the PRF in axis 1 at a given location. Only returned if `gradients`=True.