WCSAxes

class astropy.visualization.wcsaxes.WCSAxes(fig, rect, wcs=None, transform=None, coord_meta=None, transData=None, slices=None, frame_class=<class 'astropy.visualization.wcsaxes.frame.RectangularFrame'>, **kwargs)[source] [edit on github]

Bases: matplotlib.axes.Axes

The main axes class that can be used to show world coordinates from a WCS.

Parameters:
fig : Figure

The figure to add the axes to

rect : list

The position of the axes in the figure in relative units. Should be given as [left, bottom, width, height].

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).

transData : Transform, optional

Can be used to override the default data -> pixel mapping.

slices : 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

Methods Summary

contour(*args, **kwargs) Plot contours.
contourf(*args, **kwargs) Plot filled contours.
draw(renderer[, inframe])
draw_wcsaxes(renderer)
get_coords_overlay(frame[, coord_meta])
get_tightbbox(renderer, *args, **kwargs)
get_transform(frame) Return a transform from the specified frame to display coordinates.
get_xlabel()
get_ylabel()
grid([b, axis, which]) Plot gridlines for both coordinates.
imshow(X, *args, **kwargs) Wrapper to Matplotlib’s imshow().
plot_coord(*args, **kwargs) Plot SkyCoord or BaseCoordinateFrame objects onto the axes.
reset_wcs([wcs, slices, transform, coord_meta]) Reset the current Axes, to use a new WCS object.
set_xlabel([xlabel, labelpad])
set_ylabel([ylabel, labelpad])
tick_params([axis]) Method to set the tick and tick label parameters in the same way as the tick_params() method in Matplotlib.

Methods Documentation

contour(*args, **kwargs)[source] [edit on github]

Plot contours.

This is a custom implementation of contour() which applies the transform (if specified) to all contours in one go for performance rather than to each contour line individually. All positional and keyword arguments are the same as for contour().

contourf(*args, **kwargs)[source] [edit on github]

Plot filled contours.

This is a custom implementation of contourf() which applies the transform (if specified) to all contours in one go for performance rather than to each contour line individually. All positional and keyword arguments are the same as for contourf().

draw(renderer, inframe=False)[source] [edit on github]
draw_wcsaxes(renderer)[source] [edit on github]
get_coords_overlay(frame, coord_meta=None)[source] [edit on github]
get_tightbbox(renderer, *args, **kwargs)[source] [edit on github]
get_transform(frame)[source] [edit on github]

Return a transform from the specified frame to display coordinates.

This does not include the transData transformation

Parameters:
frame : WCS or Transform or str
The frame parameter can have several possible types:
  • WCS instance: assumed to be a transformation from pixel to world coordinates, where the world coordinates are the same as those in the WCS transformation used for this WCSAxes instance. This is used for example to show contours, since this involves plotting an array in pixel coordinates that are not the final data coordinate and have to be transformed to the common world coordinate system first.
  • Transform instance: it is assumed to be a transform to the world coordinates that are part of the WCS used to instantiate this WCSAxes instance.
  • 'pixel' or 'world': return a transformation that allows users to plot in pixel/data coordinates (essentially an identity transform) and world (the default world-to-pixel transformation used to instantiate the WCSAxes instance).
  • 'fk5' or 'galactic': return a transformation from the specified frame to the pixel/data coordinates.
  • BaseCoordinateFrame instance.
get_xlabel()[source] [edit on github]
get_ylabel()[source] [edit on github]
grid(b=None, axis='both', *, which='major', **kwargs)[source] [edit on github]

Plot gridlines for both coordinates.

Standard matplotlib appearance options (color, alpha, etc.) can be passed as keyword arguments. This behaves like matplotlib.axes.Axes except that if no arguments are specified, the grid is shown rather than toggled.

Parameters:
b : bool

Whether to show the gridlines.

imshow(X, *args, **kwargs)[source] [edit on github]

Wrapper to Matplotlib’s imshow().

If an RGB image is passed as a PIL object, it will be flipped vertically and origin will be set to lower, since WCS transformations - like FITS files - assume that the origin is the lower left pixel of the image (whereas RGB images have the origin in the top left).

All arguments are passed to imshow().

plot_coord(*args, **kwargs)[source] [edit on github]

Plot SkyCoord or BaseCoordinateFrame objects onto the axes.

The first argument to plot_coord() should be a coordinate, which will then be converted to the first two parameters to matplotlib.axes.Axes.plot. All other arguments are the same as matplotlib.axes.Axes.plot. If not specified a transform keyword argument will be created based on the coordinate.

Parameters:
coordinate : SkyCoord or BaseCoordinateFrame

The coordinate object to plot on the axes. This is converted to the first two arguments to matplotlib.axes.Axes.plot.

See also

matplotlib.axes.Axes.plot
This method is called from this function with all arguments passed to it.
reset_wcs(wcs=None, slices=None, transform=None, coord_meta=None)[source] [edit on github]

Reset the current Axes, to use a new WCS object.

set_xlabel(xlabel=None, labelpad=1, **kwargs)[source] [edit on github]
set_ylabel(ylabel=None, labelpad=1, **kwargs)[source] [edit on github]
tick_params(axis='both', **kwargs)[source] [edit on github]

Method to set the tick and tick label parameters in the same way as the tick_params() method in Matplotlib.

This is provided for convenience, but the recommended API is to use set_ticks(), set_ticklabel(), set_ticks_position(), set_ticklabel_position(), and grid().

Parameters:
axis : int or str, optional

Which axis to apply the parameters to. This defaults to ‘both’ but this can also be set to an int or str that refers to the axis to apply it to, following the valid values that can index ax.coords. Note that 'x' and 'y’ are also accepted in the case of rectangular axes.

which : {‘both’, ‘major’, ‘minor’}, optional

Which ticks to apply the settings to. By default, setting are applied to both major and minor ticks. Note that if 'minor' is specified, only the length of the ticks can be set currently.

direction : {‘in’, ‘out’}, optional

Puts ticks inside the axes, or outside the axes.

length : float, optional

Tick length in points.

width : float, optional

Tick width in points.

color : color, optional

Tick color (accepts any valid Matplotlib color)

pad : float, optional

Distance in points between tick and label.

labelsize : float or str, optional

Tick label font size in points or as a string (e.g., ‘large’).

labelcolor : color, optional

Tick label color (accepts any valid Matplotlib color)

colors : color, optional
Changes the tick color and the label color to the same value

(accepts any valid Matplotlib color).

bottom, top, left, right : bool, optional

Where to draw the ticks. Note that this can only be given if a specific coordinate is specified via the axis argument, and it will not work correctly if the frame is not rectangular.

labelbottom, labeltop, labelleft, labelright : bool, optional

Where to draw the tick labels. Note that this can only be given if a specific coordinate is specified via the axis argument, and it will not work correctly if the frame is not rectangular.

grid_color : color, optional

The color of the grid lines (accepts any valid Matplotlib color).

grid_alpha : float, optional

Transparency of grid lines: 0 (transparent) to 1 (opaque).

grid_linewidth : float, optional

Width of grid lines in points.

grid_linestyle : string, optional

The style of the grid lines (accepts any valid Matplotlib line style).