Images

rascil.processing_components.image.gradients Module

Image operations visible to the Execution Framework as Components

Calculate image first order gradients numerically

Image operations visible to the Execution Framework as Components

`add_image`(im1, im2)	Add two images
`average_image_over_frequency`(im)	Integrate image across frequency
`create_w_term_like`(im, w[, phasecentre, ...])	Create an image with a w term phase term in it:
`create_window`(template, window_type, **kwargs)	Create a window image using one of a number of methods
`fft_image_to_griddata_with_wcs`(im)	WCS-aware FFT of a canonical image
`import_image_from_fits`(fitsfile[, fixpol])	Read an Image from fits
`pad_image`(im, shape)	Pad an image to desired shape, adding equally to all edges
`sub_image`(im, shape)	Subsection an image to desired shape, cutting equally from all edges
`polarisation_frame_from_wcs`(wcs, shape)	Convert wcs to polarisation_frame
`remove_continuum_image`(im[, degree, mask])	Fit and remove continuum visibility in place
`reproject_image`(im, newwcs[, shape])	Re-project an image to a new coordinate system
`show_components`(im, comps[, npixels, fig, ...])	Show components against an image
`show_image`(im[, fig, title, pol, chan, cm, ...])	Show an Image with coordinates using matplotlib, optionally with components
`smooth_image`(model[, width, normalise])	Smooth an image with a 2D Gaussian kernel
`scale_and_rotate_image`(im[, angle, scale, order])	Scale and then rotate and image in x, y axes
`apply_voltage_pattern_to_image`(im, vp[, ...])	Apply a voltage pattern to an image