CoordinatesMap

class astropy.visualization.wcsaxes.CoordinatesMap(axes, wcs=None, transform=None, coord_meta=None, slice=None, frame_class=<class 'astropy.visualization.wcsaxes.frame.RectangularFrame'>, previous_frame_path=None)

Bases: object

A container for coordinate helpers that represents a coordinate system.

This object can be used to access coordinate helpers by index (like a list) or by name (like a dictionary).

Parameters:

axes : WCSAxes

The axes the coordinate map belongs to.

wcs : WCS, optional

The WCS for the data. If this is specified, transform cannot be specified.

transform : Transform, optional

The transform for the data. If this is specified, wcs cannot be specified.

coord_meta : dict, optional

A dictionary providing additional metadata when transform is specified. This should include the keys type, wrap, and unit. Each of these should be a list with as many items as the dimension of the WCS. The type entries should be one of longitude, latitude, or scalar, the wrap entries should give, for the longitude, the angle at which the coordinate wraps (and None otherwise), and the unit should give the unit of the coordinates as Unit instances. This can optionally also include a format_unit entry giving the units to use for the tick labels (if not specified, this defaults to unit).

slice : tuple, optional

For WCS transformations with more than two dimensions, we need to choose which dimensions are being shown in the 2D image. The slice should contain one x entry, one y entry, and the rest of the values should be integers indicating the slice through the data. The order of the items in the slice should be the same as the order of the dimensions in the WCS, and the opposite of the order of the dimensions in Numpy. For example, (50, 'x', 'y') means that the first WCS dimension (last Numpy dimension) will be sliced at an index of 50, the second WCS and Numpy dimension will be shown on the x axis, and the final WCS dimension (first Numpy dimension) will be shown on the y-axis (and therefore the data will be plotted using data[:, :, 50].transpose())

frame_class : type, optional

The class for the frame, which should be a subclass of BaseFrame. The default is to use a RectangularFrame

previous_frame_path : Path, optional

When changing the WCS of the axes, the frame instance will change but we might want to keep re-using the same underlying matplotlib Path - in that case, this can be passed to this keyword argument.

Methods Summary

get_coord_range()
grid([draw_grid, grid_type])	Plot gridlines for both coordinates.
set_visible(visibility)

Methods Documentation

get_coord_range()

grid(draw_grid=True, grid_type=None, **kwargs)

Plot gridlines for both coordinates.

Standard matplotlib appearance options (color, alpha, etc.) can be passed as keyword arguments.

Parameters:

draw_grid : bool

Whether to show the gridlines

grid_type : { ‘lines’ | ‘contours’ }

Whether to plot the contours by determining the grid lines in world coordinates and then plotting them in world coordinates ('lines') or by determining the world coordinates at many positions in the image and then drawing contours ('contours'). The first is recommended for 2-d images, while for 3-d (or higher dimensional) cubes, the 'contours' option is recommended. By default, ‘lines’ is used if the transform has an inverse, otherwise ‘contours’ is used.

set_visible(visibility)