def test_all_pixel_indices_from_map(sub_smap):
pixel_indices = all_pixel_indices_from_map(sub_smap)
shape = sub_smap.data.shape
ny = shape[0]
nx = shape[1]
assert np.all(pixel_indices.shape == (2, ny, nx))
assert np.all(pixel_indices.unit == u.pix)
assert np.all(pixel_indices[:, 0, 0] == [0., 0.] * u.pix)
assert np.all(pixel_indices[:, 0, nx-1] == [nx-1, 0.] * u.pix)
assert np.all(pixel_indices[:, ny-1, 0] == [0., ny-1] * u.pix)
assert np.all(pixel_indices[:, ny-1, nx-1] == [nx-1, ny-1] * u.pix)
def test_all_pixel_indices_from_map(sub_smap):
pixel_indices = all_pixel_indices_from_map(sub_smap)
shape = sub_smap.data.shape
ny = shape[0]
nx = shape[1]
assert np.all(pixel_indices.shape == (2, ny, nx))
assert np.all(pixel_indices.unit == u.pix)
assert np.all(pixel_indices[:, 0, 0] == [0., 0.] * u.pix)
assert np.all(pixel_indices[:, 0, nx - 1] == [nx - 1, 0.] * u.pix)
assert np.all(pixel_indices[:, ny - 1, 0] == [0., ny - 1] * u.pix)
assert np.all(pixel_indices[:, ny - 1, nx - 1] == [nx - 1, ny - 1] * u.pix)
from sunpy.data.sample import AIA_193_IMAGE from sunpy.map.maputils import all_pixel_indices_from_map ############################################################################### # We will first create a Map using some sample data and display it. aiamap = sunpy.map.Map(AIA_193_IMAGE) plt.figure() aiamap.plot() plt.colorbar() ############################################################################### # Before we find regions of local maxima, we need to create some variables to # store pixel values for the 2D SDO/AIA data we are using. # These variables are used for plotting in 3D later on. X, Y = all_pixel_indices_from_map(aiamap) ####################################################################################### # We will only consider peaks within the AIA data that have minimum intensity # value equal to ``threshold_rel * max(Intensity)`` which is 20% of the maximum intensity. # The next step is to calculate the pixel locations of local maxima # positions where peaks are separated by at least ``min_distance = 60 pixels``. # This function comes from scikit image and the documenation is found # here `~skimage.feature.peak_local_max`. coordinates = peak_local_max(aiamap.data, min_distance=60, threshold_rel=0.2) ############################################################################### # We now check for the indices at which we get such a local maxima and plot # those positions marked red in the aiamap data.