Source code for astropy.wcs.wcsapi.utils

# Licensed under a 3-clause BSD style license - see LICENSE.rst

import importlib
import numpy as np

__all__ = ['deserialize_class', 'wcs_info_str']


[docs]def deserialize_class(tpl, construct=True): """ Deserialize classes recursively. """ if not isinstance(tpl, tuple) or len(tpl) != 3: raise ValueError("Expected a tuple of three values") module, klass = tpl[0].rsplit('.', 1) module = importlib.import_module(module) klass = getattr(module, klass) args = tuple([deserialize_class(arg) if isinstance(arg, tuple) else arg for arg in tpl[1]]) kwargs = dict((key, deserialize_class(val)) if isinstance(val, tuple) else (key, val) for (key, val) in tpl[2].items()) if construct: return klass(*args, **kwargs) else: return klass, args, kwargs
[docs]def wcs_info_str(wcs): # Overall header s = f'{wcs.__class__.__name__} Transformation\n\n' s += ('This transformation has {} pixel and {} world dimensions\n\n' .format(wcs.pixel_n_dim, wcs.world_n_dim)) s += f'Array shape (Numpy order): {wcs.array_shape}\n\n' # Pixel dimensions table array_shape = wcs.array_shape or (0,) pixel_shape = wcs.pixel_shape or (None,) * wcs.pixel_n_dim # Find largest between header size and value length pixel_dim_width = max(9, len(str(wcs.pixel_n_dim))) pixel_nam_width = max(9, max(len(x) for x in wcs.pixel_axis_names)) pixel_siz_width = max(9, len(str(max(array_shape)))) print(pixel_nam_width) s += (('{0:' + str(pixel_dim_width) + 's}').format('Pixel Dim') + ' ' + ('{0:' + str(pixel_nam_width) + 's}').format('Axis Name') + ' ' + ('{0:' + str(pixel_siz_width) + 's}').format('Data size') + ' ' + 'Bounds\n') for ipix in range(wcs.pixel_n_dim): s += (('{0:' + str(pixel_dim_width) + 'd}').format(ipix) + ' ' + ('{0:' + str(pixel_nam_width) + 's}').format(wcs.pixel_axis_names[ipix] or 'None') + ' ' + (" " * 5 + str(None) if pixel_shape[ipix] is None else ('{0:' + str(pixel_siz_width) + 'd}').format(pixel_shape[ipix])) + ' ' + '{:s}'.format(str(None if wcs.pixel_bounds is None else wcs.pixel_bounds[ipix]) + '\n')) s += '\n' # World dimensions table # Find largest between header size and value length world_dim_width = max(9, len(str(wcs.world_n_dim))) world_nam_width = max(9, max(len(x) if x is not None else 0 for x in wcs.world_axis_names)) world_typ_width = max(13, max(len(x) if x is not None else 0 for x in wcs.world_axis_physical_types)) s += (('{0:' + str(world_dim_width) + 's}').format('World Dim') + ' ' + ('{0:' + str(world_nam_width) + 's}').format('Axis Name') + ' ' + ('{0:' + str(world_typ_width) + 's}').format('Physical Type') + ' ' + 'Units\n') for iwrl in range(wcs.world_n_dim): name = wcs.world_axis_names[iwrl] or 'None' typ = wcs.world_axis_physical_types[iwrl] or 'None' unit = wcs.world_axis_units[iwrl] or 'unknown' s += (('{0:' + str(world_dim_width) + 'd}').format(iwrl) + ' ' + ('{0:' + str(world_nam_width) + 's}').format(name) + ' ' + ('{0:' + str(world_typ_width) + 's}').format(typ) + ' ' + '{:s}'.format(unit + '\n')) s += '\n' # Axis correlation matrix pixel_dim_width = max(3, len(str(wcs.world_n_dim))) s += 'Correlation between pixel and world axes:\n\n' s += (' ' * world_dim_width + ' ' + ('{0:^' + str(wcs.pixel_n_dim * 5 - 2) + 's}').format('Pixel Dim') + '\n') s += (('{0:' + str(world_dim_width) + 's}').format('World Dim') + ''.join([' ' + ('{0:' + str(pixel_dim_width) + 'd}').format(ipix) for ipix in range(wcs.pixel_n_dim)]) + '\n') matrix = wcs.axis_correlation_matrix matrix_str = np.empty(matrix.shape, dtype='U3') matrix_str[matrix] = 'yes' matrix_str[~matrix] = 'no' for iwrl in range(wcs.world_n_dim): s += (('{0:' + str(world_dim_width) + 'd}').format(iwrl) + ''.join([' ' + ('{0:>' + str(pixel_dim_width) + 's}').format(matrix_str[iwrl, ipix]) for ipix in range(wcs.pixel_n_dim)]) + '\n') # Make sure we get rid of the extra whitespace at the end of some lines return '\n'.join([l.rstrip() for l in s.splitlines()])