Creating Carrington Maps#

In this example we use the reproject generate a map in heliographic Carrington coordinates from a full-disk AIA image.

You will need reproject v0.6 or higher installed.

import matplotlib.pyplot as plt

from import make_heliographic_header

We will start with using sunpy’s sample data for this example.

aia_map =

fig = plt.figure()
ax = fig.add_subplot(projection=aia_map)
AIA $193 \; \mathrm{\mathring{A}}$ 2011-06-07 06:33:07
<matplotlib.image.AxesImage object at 0x7fbf6bebda50>

Reproject works by transforming an input image to a desired World Coordinate System (WCS) projection. Here we use to create a FITS WCS header based on a heliographic Carrington reference coordinate.

shape = (720, 1440)
carr_header = make_heliographic_header(, aia_map.observer_coordinate, shape, frame='carrington')

With the new header, re-project the data into the new coordinate system. The reproject_to() defaults to using the fast reproject.reproject_interp() algorithm, but a different algorithm can be specified (e.g., reproject.reproject_adaptive()).

outmap = aia_map.reproject_to(carr_header)

Plot the result.

fig = plt.figure()
ax = fig.add_subplot(projection=outmap)
2011-06-07 06:33:07

Total running time of the script: (0 minutes 1.683 seconds)

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