How to compensate for differential rotation in the default sunpy image. This is based upon a combination of pr/452 and pr/482 my branch for which can be found here: https://github.com/Cadair/sunpy/tree/map_refactor_diff_rot

diffrot.py

# -*- coding: utf-8 -*-
"""
Created on Sat Jun 29 21:31:58 2013

@author: stuart
"""

import numpy as np
from datetime import timedelta

import matplotlib.pyplot as plt
from skimage import transform
from skimage.util import img_as_float
from astropy import units as u

import sunpy.data.sample
import sunpy.map
import sunpy.physics.transforms.differential_rotation as diffrot
from sunpy.time import parse_time

#Scikit-image needs float arrays between 0 and 1
def to_norm(arr):
    '''
    Normalises an array.
    '''
    arr = img_as_float(arr, force_copy=True)
    if arr.min() < 0:
        arr += np.abs(arr.min())
    arr /= arr.max()
    return arr

def un_norm(arr, ori):
    '''
    Un-normalises an array based in the original.
    '''
    level = 0 if ori.min() > 0 else np.abs(ori.min())
    arr *= ori.max() + level
    arr -= level
    return arr   

#Define a function that returns a new list of coordinates for each input coord.
def warp_sun(xy, smap):

    #Calculate the hpc coords
    x = np.arange(0, smap.dimensions.x.value)
    y = np.arange(0, smap.dimensions.y.value)
    xx, yy = np.meshgrid(x, y)
    hpc_coords = smap.pixel_to_data(xx * u.pix, yy * u.pix)
    
    #Do the diff rot
    rotted = diffrot.rot_hpc(hpc_coords[1], hpc_coords[0], smap.date,
                             smap.date - timedelta(days=2))
    
    #Go back to pixel coords
    x2,y2 = smap.data_to_pixel(rotted[0], rotted[1])
    
    #Restack the data to make it correct output form
    xy2 = np.column_stack([x2.value.flat,y2.value.flat])
    
    #Remove NaNs
    mask = np.isnan(xy2)
    xy2[mask] = 0.0

    return xy2
    

if __name__ == '__main__':
    data = sunpy.map.Map(sunpy.data.sample.AIA_171_IMAGE)
    #Do the warp:
    out = transform.warp(to_norm(data.data), inverse_map=warp_sun, map_args={'smap':data})
    #de norm
    out = un_norm(out, data.data)
    plt.figure()
    
    plt.subplot(121)
    plt.imshow(data.data, cmap=data.plot_settings['cmap'], origin='lower',norm=data.plot_settings['norm'])
    
    plt.subplot(122)
    plt.imshow(out, cmap=data.plot_settings['cmap'], origin='lower',norm=data.plot_settings['norm'])
    plt.show()

test_diffrot.py

import pytest
import numpy as np
from numpy.testing import assert_allclose

from sunpy.physics.transforms import diff_rot

def test_toNorm():
    array_simple = np.array([10., 20., 30., 100.])
    assert_allclose(diff_rot.to_norm(array_simple), np.array([0.1, 0.2, 0.3, 1.]))    
    array_simple_neg = np.array([-10., 0., 10., 90.])
    assert_allclose(diff_rot.to_norm(array_simple_neg), np.array([0, 0.1, 0.2, 1.]))

def test_unNorm():
    array_simple = np.array([10, 20, 30, 100.])
    assert_allclose(diff_rot.un_norm(np.array([0.1, 0.2, 0.3, 1.]), array_simple), array_simple)
    array_simple_neg = np.array([-10, 0, 10, 90])
    assert_allclose(diff_rot.un_norm(np.array([0, 0.1, 0.2, 1.]), array_simple_neg), array_simple_neg)