def test_local_pixel_derivatives(spatial_wcs_2d_small_angle):
not_diag = np.logical_not(np.diag([1,1]))
# At (or close to) the reference pixel this should equal the cdelt
derivs = local_partial_pixel_derivatives(spatial_wcs_2d_small_angle, 3, 3)
np.testing.assert_allclose(np.diag(derivs), spatial_wcs_2d_small_angle.wcs.cdelt)
np.testing.assert_allclose(derivs[not_diag].flat, [0,0], atol=1e-10)
# Far away from the reference pixel this should not equal the cdelt
derivs = local_partial_pixel_derivatives(spatial_wcs_2d_small_angle, 3e4, 3e4)
assert not np.allclose(np.diag(derivs), spatial_wcs_2d_small_angle.wcs.cdelt)
# At (or close to) the reference pixel this should equal the cdelt
derivs = local_partial_pixel_derivatives(spatial_wcs_2d_small_angle, 3, 3, normalize_by_world=True)
np.testing.assert_allclose(np.diag(derivs), [1, 1])
np.testing.assert_allclose(derivs[not_diag].flat, [0,0], atol=1e-8)
def transform_coord_meta_from_wcs(wcs, frame_class, slices=None):
if slices is not None:
slices = tuple(slices)
if wcs.pixel_n_dim > 2:
if slices is None:
raise ValueError("WCS has more than 2 pixel dimensions, so "
"'slices' should be set")
elif len(slices) != wcs.pixel_n_dim:
raise ValueError("'slices' should have as many elements as WCS "
"has pixel dimensions (should be {})".format(
wcs.pixel_n_dim))
is_fits_wcs = isinstance(wcs, WCS)
coord_meta = {}
coord_meta['name'] = []
coord_meta['type'] = []
coord_meta['wrap'] = []
coord_meta['unit'] = []
coord_meta['visible'] = []
coord_meta['format_unit'] = []
for idx in range(wcs.world_n_dim):
axis_type = wcs.world_axis_physical_types[idx]
axis_unit = u.Unit(wcs.world_axis_units[idx])
coord_wrap = None
format_unit = axis_unit
coord_type = 'scalar'
if axis_type is not None:
axis_type_split = axis_type.split('.')
if "pos.helioprojective.lon" in axis_type:
coord_wrap = 180.
format_unit = u.arcsec
coord_type = "longitude"
elif "pos.helioprojective.lat" in axis_type:
format_unit = u.arcsec
coord_type = "latitude"
elif "pos.heliographic.stonyhurst.lon" in axis_type:
coord_wrap = 180.
format_unit = u.deg
coord_type = "longitude"
elif "pos.heliographic.stonyhurst.lat" in axis_type:
format_unit = u.deg
coord_type = "latitude"
elif "pos.heliographic.carrington.lon" in axis_type:
coord_wrap = 360.
format_unit = u.deg
coord_type = "longitude"
elif "pos.heliographic.carrington.lat" in axis_type:
format_unit = u.deg
coord_type = "latitude"
elif "pos" in axis_type_split:
if "lon" in axis_type_split:
coord_type = "longitude"
elif "lat" in axis_type_split:
coord_type = "latitude"
elif "ra" in axis_type_split:
coord_type = "longitude"
format_unit = u.hourangle
elif "dec" in axis_type_split:
coord_type = "latitude"
elif "alt" in axis_type_split:
coord_type = "longitude"
elif "az" in axis_type_split:
coord_type = "latitude"
elif "long" in axis_type_split:
coord_type = "longitude"
coord_meta['type'].append(coord_type)
coord_meta['wrap'].append(coord_wrap)
coord_meta['format_unit'].append(format_unit)
coord_meta['unit'].append(axis_unit)
# For FITS-WCS, for backward-compatibility, we need to make sure that we
# provide aliases based on CTYPE for the name.
if is_fits_wcs:
name = []
if isinstance(wcs, WCS):
name.append(wcs.wcs.ctype[idx].lower())
name.append(wcs.wcs.ctype[idx][:4].replace('-', '').lower())
elif isinstance(wcs, SlicedLowLevelWCS):
name.append(wcs._wcs.wcs.ctype[wcs._world_keep[idx]].lower())
name.append(
wcs._wcs.wcs.ctype[wcs._world_keep[idx]][:4].replace(
'-', '').lower())
if name[0] == name[1]:
name = name[0:1]
if axis_type:
name.insert(0, axis_type)
name = tuple(name) if len(name) > 1 else name[0]
else:
name = axis_type or ''
coord_meta['name'].append(name)
coord_meta['default_axislabel_position'] = [''] * wcs.world_n_dim
coord_meta['default_ticklabel_position'] = [''] * wcs.world_n_dim
coord_meta['default_ticks_position'] = [''] * wcs.world_n_dim
transform_wcs, invert_xy, world_map = apply_slices(wcs, slices)
transform = WCSPixel2WorldTransform(transform_wcs, invert_xy=invert_xy)
for i in range(len(coord_meta['type'])):
coord_meta['visible'].append(i in world_map)
inv_all_corr = [False] * wcs.world_n_dim
m = transform_wcs.axis_correlation_matrix.copy()
if invert_xy:
inv_all_corr = np.all(m, axis=1)
m = m[:, ::-1]
if frame_class is RectangularFrame:
for i, spine_name in enumerate('bltr'):
pos = np.nonzero(m[:, i % 2])[0]
# If all the axes we have are correlated with each other and we
# have inverted the axes, then we need to reverse the index so we
# put the 'y' on the left.
if inv_all_corr[i % 2]:
pos = pos[::-1]
if len(pos) > 0:
index = world_map[pos[0]]
coord_meta['default_axislabel_position'][index] = spine_name
coord_meta['default_ticklabel_position'][index] = spine_name
coord_meta['default_ticks_position'][index] = spine_name
m[pos[0], :] = 0
# In the special and common case where the frame is rectangular and
# we are dealing with 2-d WCS (after slicing), we show all ticks on
# all axes for backward-compatibility.
if len(world_map) == 2:
for index in world_map:
coord_meta['default_ticks_position'][index] = 'bltr'
elif frame_class is RectangularFrame1D:
derivs = np.abs(
local_partial_pixel_derivatives(transform_wcs,
*[0] * transform_wcs.pixel_n_dim,
normalize_by_world=False))[:, 0]
for i, spine_name in enumerate('bt'):
# Here we are iterating over the correlated axes in world axis order.
# We want to sort the correlated axes by their partial derivatives,
# so we put the most rapidly changing world axis on the bottom.
pos = np.nonzero(m[:, 0])[0]
order = np.argsort(derivs[pos])[::-1] # Sort largest to smallest
pos = pos[order]
if len(pos) > 0:
index = world_map[pos[0]]
coord_meta['default_axislabel_position'][index] = spine_name
coord_meta['default_ticklabel_position'][index] = spine_name
coord_meta['default_ticks_position'][index] = spine_name
m[pos[0], :] = 0
# In the special and common case where the frame is rectangular and
# we are dealing with 2-d WCS (after slicing), we show all ticks on
# all axes for backward-compatibility.
if len(world_map) == 1:
for index in world_map:
coord_meta['default_ticks_position'][index] = 'bt'
elif frame_class is EllipticalFrame:
if 'longitude' in coord_meta['type']:
lon_idx = coord_meta['type'].index('longitude')
coord_meta['default_axislabel_position'][lon_idx] = 'h'
coord_meta['default_ticklabel_position'][lon_idx] = 'h'
coord_meta['default_ticks_position'][lon_idx] = 'h'
if 'latitude' in coord_meta['type']:
lat_idx = coord_meta['type'].index('latitude')
coord_meta['default_axislabel_position'][lat_idx] = 'c'
coord_meta['default_ticklabel_position'][lat_idx] = 'c'
coord_meta['default_ticks_position'][lat_idx] = 'c'
else:
for index in range(len(coord_meta['type'])):
if index in world_map:
coord_meta['default_axislabel_position'][
index] = frame_class.spine_names
coord_meta['default_ticklabel_position'][
index] = frame_class.spine_names
coord_meta['default_ticks_position'][
index] = frame_class.spine_names
return transform, coord_meta