Initializing WCSAxes with custom transforms#

In Initializing axes with world coordinates, we saw how to make plots using WCS objects. However, the WCSAxes class can also be initialized with more general transformations that don’t have to be represented by the WCS class. Instead, you can initialize WCSAxes using a Matplotlib Transform object and a dictionary (coord_meta) that provides metadata on how to interpret the transformation.

The Transform should represent the conversion from pixel to world coordinates, and should have input_dims=2 and can have output_dims set to any positive integer. In addition, has_inverse should be set to True and the inverted method should be implemented.

The coord_meta dictionary should include the following keys:

name: an iterable of strings giving the names for each dimension
type: an iterable of strings that should be either 'longitude', 'latitude', or 'scalar' (for anything that isn’t a longitude or latitude).
wrap: an iterable of values which indicate for longitudes at which angle (in degrees) to wrap the coordinates. This should be None unless type is 'longitude'.
unit: an iterable of Unit objects giving the units of the world coordinates returned by the Transform.
format_unit: an iterable of Unit objects giving the units to use for the formatting of the labels. These can be set to None to default to the units given in unit, but can be set for example if the Transform returns values in degrees and you want the labels to be formatted in hours.

In addition the coord_meta can optionally include the following keys:

default_axislabel_position: an iterable of strings giving for each world coordinates the spine of the frame on which to show the axis label for the coordinate. Each string should be such that it could be used as input to set_axislabel_position().
default_ticklabel_position: an iterable of strings giving for each world coordinates the spine of the frame on which to show the tick labels for the coordinate. Each string should be such that it could be used as input to set_ticklabel_position().
default_ticks_position: an iterable of strings giving for each world coordinates the spine of the frame on which to show the ticks for the coordinate. Each string should be such that it could be used as input to set_ticks_position().

The following example illustrates a custom projection using a transform and coord_meta:

from astropy import units as u
import matplotlib.pyplot as plt
from matplotlib.transforms import Affine2D
from astropy.visualization.wcsaxes import WCSAxes

# Set up an affine transformation
transform = Affine2D()
transform.scale(0.01)
transform.translate(40, -30)
transform.rotate(0.3)  # radians

# Set up metadata dictionary
coord_meta = {}
coord_meta['name'] = 'lon', 'lat'
coord_meta['type'] = 'longitude', 'latitude'
coord_meta['wrap'] = 180 * u.deg, None
coord_meta['unit'] = u.deg, u.deg
coord_meta['format_unit'] = None, None

fig = plt.figure()
ax = WCSAxes(fig, [0.1, 0.1, 0.8, 0.8], aspect='equal',
             transform=transform, coord_meta=coord_meta)
fig.add_axes(ax)
ax.set_xlim(-0.5, 499.5)
ax.set_ylim(-0.5, 399.5)
ax.grid()
ax.coords['lon'].set_axislabel('Longitude')
ax.coords['lat'].set_axislabel('Latitude')

(png, svg, pdf)