# Licensed under a 3-clause BSD style license - see LICENSE.rst """ Under the hood, there are 3 separate classes that perform different parts of the transformation: - `~astropy.wcs.Wcsprm`: Is a direct wrapper of the core WCS functionality in `wcslib`_. - `~astropy.wcs.Sip`: Handles polynomial distortion as defined in the `SIP`_ convention. - `~astropy.wcs.DistortionLookupTable`: Handles `Paper IV`_ distortion lookup tables. Additionally, the class `WCS` aggregates all of these transformations together in a pipeline: - Detector to image plane correction (by a pair of `~astropy.wcs.DistortionLookupTable` objects). - `SIP`_ distortion correction (by an underlying `~astropy.wcs.Sip` object) - `Paper IV`_ table-lookup distortion correction (by a pair of `~astropy.wcs.DistortionLookupTable` objects). - `wcslib`_ WCS transformation (by a `~astropy.wcs.Wcsprm` object) """ from __future__ import absolute_import, division, print_function, unicode_literals # STDLIB import copy import io import os import textwrap import warnings # THIRD-PARTY import numpy as np # LOCAL from ..extern import six from ..io import fits from . import _docutil as __ try: from . import _wcs except ImportError: if not _ASTROPY_SETUP_: raise else: _wcs = None from ..utils import deprecated, deprecated_attribute from ..utils.compat import possible_filename from ..utils.exceptions import AstropyWarning, AstropyUserWarning, AstropyDeprecationWarning if _wcs is not None: assert _wcs._sanity_check(), \ "astropy.wcs did not pass its sanity check for your build " \ "on your platform." __all__ = ['FITSFixedWarning', 'WCS', 'find_all_wcs', 'DistortionLookupTable', 'Sip', 'Tabprm', 'Wcsprm', 'WCSBase', 'validate', 'WcsError', 'SingularMatrixError', 'InconsistentAxisTypesError', 'InvalidTransformError', 'InvalidCoordinateError', 'NoSolutionError', 'InvalidSubimageSpecificationError', 'NonseparableSubimageCoordinateSystemError', 'NoWcsKeywordsFoundError', 'InvalidTabularParametersError'] if _wcs is not None: WCSBase = _wcs._Wcs DistortionLookupTable = _wcs.DistortionLookupTable Sip = _wcs.Sip Wcsprm = _wcs.Wcsprm Tabprm = _wcs.Tabprm WcsError = _wcs.WcsError SingularMatrixError = _wcs.SingularMatrixError InconsistentAxisTypesError = _wcs.InconsistentAxisTypesError InvalidTransformError = _wcs.InvalidTransformError InvalidCoordinateError = _wcs.InvalidCoordinateError NoSolutionError = _wcs.NoSolutionError InvalidSubimageSpecificationError = _wcs.InvalidSubimageSpecificationError NonseparableSubimageCoordinateSystemError = _wcs.NonseparableSubimageCoordinateSystemError NoWcsKeywordsFoundError = _wcs.NoWcsKeywordsFoundError InvalidTabularParametersError = _wcs.InvalidTabularParametersError # Copy all the constants from the C extension into this module's namespace for key, val in _wcs.__dict__.items(): if (key.startswith('WCSSUB') or key.startswith('WCSHDR') or key.startswith('WCSHDO')): locals()[key] = val __all__.append(key) else: WCSBase = object Wcsprm = object DistortionLookupTable = object Sip = object Tabprm = object WcsError = None SingularMatrixError = None InconsistentAxisTypesError = None InvalidTransformError = None InvalidCoordinateError = None NoSolutionError = None InvalidSubimageSpecificationError = None NonseparableSubimageCoordinateSystemError = None NoWcsKeywordsFoundError = None InvalidTabularParametersError = None # Additional relax bit flags WCSHDO_SIP = 0x10000 def _parse_keysel(keysel): keysel_flags = 0 if keysel is not None: for element in keysel: if element.lower() == 'image': keysel_flags |= _wcs.WCSHDR_IMGHEAD elif element.lower() == 'binary': keysel_flags |= _wcs.WCSHDR_BIMGARR elif element.lower() == 'pixel': keysel_flags |= _wcs.WCSHDR_PIXLIST else: raise ValueError( "keysel must be a list of 'image', 'binary' " + "and/or 'pixel'") else: keysel_flags = -1 return keysel_flags class FITSFixedWarning(AstropyWarning): """ The warning raised when the contents of the FITS header have been modified to be standards compliant. """ pass class WCS(WCSBase): """ WCS objects perform standard WCS transformations, and correct for `SIP`_ and `Paper IV`_ table-lookup distortions, based on the WCS keywords and supplementary data read from a FITS file. Parameters ---------- header : astropy.io.fits header object, string, dict-like, or None, optional If *header* is not provided or None, the object will be initialized to default values. fobj : An astropy.io.fits file (hdulist) object, optional It is needed when header keywords point to a `Paper IV`_ Lookup table distortion stored in a different extension. key : str, optional The name of a particular WCS transform to use. This may be either ``' '`` or ``'A'``-``'Z'`` and corresponds to the ``\"a\"`` part of the ``CTYPEia`` cards. *key* may only be provided if *header* is also provided. minerr : float, optional The minimum value a distortion correction must have in order to be applied. If the value of ``CQERRja`` is smaller than *minerr*, the corresponding distortion is not applied. relax : bool or int, optional Degree of permissiveness: - `True` (default): Admit all recognized informal extensions of the WCS standard. - `False`: Recognize only FITS keywords defined by the published WCS standard. - `int`: a bit field selecting specific extensions to accept. See :ref:`relaxread` for details. naxis : int or sequence, optional Extracts specific coordinate axes using :meth:`~astropy.wcs.Wcsprm.sub`. If a header is provided, and *naxis* is not ``None``, *naxis* will be passed to :meth:`~astropy.wcs.Wcsprm.sub` in order to select specific axes from the header. See :meth:`~astropy.wcs.Wcsprm.sub` for more details about this parameter. keysel : sequence of flags, optional A sequence of flags used to select the keyword types considered by wcslib. When ``None``, only the standard image header keywords are considered (and the underlying wcspih() C function is called). To use binary table image array or pixel list keywords, *keysel* must be set. Each element in the list should be one of the following strings: - 'image': Image header keywords - 'binary': Binary table image array keywords - 'pixel': Pixel list keywords Keywords such as ``EQUIna`` or ``RFRQna`` that are common to binary table image arrays and pixel lists (including ``WCSNna`` and ``TWCSna``) are selected by both 'binary' and 'pixel'. colsel : sequence of int, optional A sequence of table column numbers used to restrict the WCS transformations considered to only those pertaining to the specified columns. If `None`, there is no restriction. fix : bool, optional When `True` (default), call `~astropy.wcs.Wcsprm.fix` on the resulting object to fix any non-standard uses in the header. `FITSFixedWarning` Warnings will be emitted if any changes were made. translate_units : str, optional Specify which potentially unsafe translations of non-standard unit strings to perform. By default, performs none. See `WCS.fix` for more information about this parameter. Only effective when ``fix`` is `True`. Raises ------ MemoryError Memory allocation failed. ValueError Invalid key. KeyError Key not found in FITS header. AssertionError Lookup table distortion present in the header but *fobj* was not provided. Notes ----- 1. astropy.wcs supports arbitrary *n* dimensions for the core WCS (the transformations handled by WCSLIB). However, the Paper IV lookup table and SIP distortions must be two dimensional. Therefore, if you try to create a WCS object where the core WCS has a different number of dimensions than 2 and that object also contains a Paper IV lookup table or SIP distortion, a `~.exceptions.ValueError` exception will be raised. To avoid this, consider using the *naxis* kwarg to select two dimensions from the core WCS. 2. The number of coordinate axes in the transformation is not determined directly from the ``NAXIS`` keyword but instead from the highest of: - ``NAXIS`` keyword - ``WCSAXESa`` keyword - The highest axis number in any parameterized WCS keyword. The keyvalue, as well as the keyword, must be syntactically valid otherwise it will not be considered. If none of these keyword types is present, i.e. if the header only contains auxiliary WCS keywords for a particular coordinate representation, then no coordinate description is constructed for it. The number of axes, which is set as the ``naxis`` member, may differ for different coordinate representations of the same image. 3. When the header includes duplicate keywords, in most cases the last encountered is used. 4. `~astropy.wcs.Wcsprm.set` is called immediately after construction, so any invalid keywords or transformations will be raised by the constructor, not when subsequently calling a transformation method. """ def __init__(self, header=None, fobj=None, key=' ', minerr=0.0, relax=True, naxis=None, keysel=None, colsel=None, fix=True, translate_units='', _do_set=True): close_fds = [] if header is None: if naxis is None: naxis = 2 wcsprm = _wcs.Wcsprm(header=None, key=key, relax=relax, naxis=naxis) self.naxis = wcsprm.naxis # Set some reasonable defaults. det2im = (None, None) cpdis = (None, None) sip = None else: keysel_flags = _parse_keysel(keysel) if isinstance(header, (six.text_type, six.binary_type)): try: is_path = (possible_filename(header) and os.path.exists(header)) except (IOError, ValueError): is_path = False if is_path: if fobj is not None: raise ValueError( "Can not provide both a FITS filename to " "argument 1 and a FITS file object to argument 2") fobj = fits.open(header) close_fds.append(fobj) header = fobj[0].header header_string = header.tostring() else: header_string = header elif isinstance(header, fits.Header): header_string = header.tostring() else: try: # Accept any dict-like object new_header = fits.Header() for dict_key in header.keys(): new_header[dict_key] = header[dict_key] header_string = new_header.tostring() except TypeError: raise TypeError( "header must be a string, an astropy.io.fits.Header " "object, or a dict-like object") header_string = header_string.strip() if isinstance(header_string, six.text_type): header_bytes = header_string.encode('ascii') header_string = header_string else: header_bytes = header_string header_string = header_string.decode('ascii') try: wcsprm = _wcs.Wcsprm(header=header_bytes, key=key, relax=relax, keysel=keysel_flags, colsel=colsel) except _wcs.NoWcsKeywordsFoundError: # The header may have SIP or distortions, but no core # WCS. That isn't an error -- we want a "default" # (identity) core Wcs transformation in that case. if colsel is None: wcsprm = _wcs.Wcsprm(header=None, key=key, relax=relax, keysel=keysel_flags, colsel=colsel) else: raise if naxis is not None: wcsprm = wcsprm.sub(naxis) self.naxis = wcsprm.naxis header = fits.Header.fromstring(header_string) det2im = self._read_det2im_kw(header, fobj, err=minerr) cpdis = self._read_distortion_kw( header, fobj, dist='CPDIS', err=minerr) sip = self._read_sip_kw(header) if (wcsprm.naxis != 2 and (det2im[0] or det2im[1] or cpdis[0] or cpdis[1] or sip)): raise ValueError( """ Paper IV lookup tables and SIP distortions only work in 2 dimensions. However, WCSLIB has detected {0} dimensions in the core WCS keywords. To use core WCS in conjunction with Paper IV lookup tables or SIP distortion, you must select or reduce these to 2 dimensions using the naxis kwarg. """.format(wcsprm.naxis)) header_naxis = header.get('NAXIS', None) if header_naxis is not None and header_naxis < wcsprm.naxis: warnings.warn( "The WCS transformation has more axes ({0:d}) than the " "image it is associated with ({1:d})".format( wcsprm.naxis, header_naxis), FITSFixedWarning) self._get_naxis(header) WCSBase.__init__(self, sip, cpdis, wcsprm, det2im) if fix: self.fix(translate_units=translate_units) if _do_set: self.wcs.set() for fd in close_fds: fd.close() def __copy__(self): new_copy = self.__class__() WCSBase.__init__(new_copy, self.sip, (self.cpdis1, self.cpdis2), self.wcs, (self.det2im1, self.det2im2)) new_copy.__dict__.update(self.__dict__) return new_copy def __deepcopy__(self, memo): new_copy = self.__class__() new_copy.naxis = copy.deepcopy(self.naxis, memo) WCSBase.__init__(new_copy, copy.deepcopy(self.sip, memo), (copy.deepcopy(self.cpdis1, memo), copy.deepcopy(self.cpdis2, memo)), copy.deepcopy(self.wcs, memo), (copy.deepcopy(self.det2im1, memo), copy.deepcopy(self.det2im2, memo))) for key in self.__dict__: val = self.__dict__[key] new_copy.__dict__[key] = copy.deepcopy(val, memo) return new_copy def copy(self): """ Return a shallow copy of the object. Convenience method so user doesn't have to import the :mod:`copy` stdlib module. """ return copy.copy(self) def deepcopy(self): """ Return a deep copy of the object. Convenience method so user doesn't have to import the :mod:`copy` stdlib module. """ return copy.deepcopy(self) def sub(self, axes=None): copy = self.deepcopy() copy.wcs = self.wcs.sub(axes) copy.naxis = copy.wcs.naxis return copy if _wcs is not None: sub.__doc__ = _wcs.Wcsprm.sub.__doc__ def _fix_scamp(self): """ Remove SCAMP's PVi_m distortion parameters if SIP distortion parameters are also present. Some projects (e.g., Palomar Transient Factory) convert SCAMP's distortion parameters (which abuse the PVi_m cards) to SIP. However, wcslib gets confused by the presence of both SCAMP and SIP distortion parameters. See https://github.com/astropy/astropy/issues/299. """ # Nothing to be done if no WCS attached if self.wcs is None: return # Nothing to be done if no PV parameters attached pv = self.wcs.get_pv() if not pv: return # Nothing to be done if axes don't use SIP distortion parameters if not all(ctype.endswith('-SIP') for ctype in self.wcs.ctype): return # Nothing to be done if any radial terms are present... # Loop over list to find any radial terms. # Certain values of the `j' index are used for storing # radial terms; refer to Equation (1) in # . pv = np.asarray(pv) # Loop over distinct values of `i' index for i in set(pv[:, 0]): # Get all values of `j' index for this value of `i' index js = set(pv[:, 1][pv[:, 0] == i]) # Find max value of `j' index max_j = max(js) for j in (3, 11, 23, 39): if j < max_j and j in js: return self.wcs.set_pv([]) warnings.warn("Removed redundant SCAMP distortion parameters " + "because SIP parameters are also present", FITSFixedWarning) def fix(self, translate_units='', naxis=None): """ Perform the fix operations from wcslib, and warn about any changes it has made. Parameters ---------- translate_units : str, optional Specify which potentially unsafe translations of non-standard unit strings to perform. By default, performs none. Although ``"S"`` is commonly used to represent seconds, its translation to ``"s"`` is potentially unsafe since the standard recognizes ``"S"`` formally as Siemens, however rarely that may be used. The same applies to ``"H"`` for hours (Henry), and ``"D"`` for days (Debye). This string controls what to do in such cases, and is case-insensitive. - If the string contains ``"s"``, translate ``"S"`` to ``"s"``. - If the string contains ``"h"``, translate ``"H"`` to ``"h"``. - If the string contains ``"d"``, translate ``"D"`` to ``"d"``. Thus ``''`` doesn't do any unsafe translations, whereas ``'shd'`` does all of them. naxis : int array[naxis], optional Image axis lengths. If this array is set to zero or ``None``, then `~astropy.wcs.Wcsprm.cylfix` will not be invoked. """ if self.wcs is not None: self._fix_scamp() fixes = self.wcs.fix(translate_units, naxis) for key, val in six.iteritems(fixes): if val != "No change": warnings.warn( ("'{0}' made the change '{1}'."). format(key, val), FITSFixedWarning) @deprecated("0.4", name="calcFootprint", alternative="calc_footprint") def calcFootprint(self, header=None, undistort=True, axes=None): return self.calc_footprint(header=header, undistort=undistort, axes=axes, center=True) def calc_footprint(self, header=None, undistort=True, axes=None, center=True): """ Calculates the footprint of the image on the sky. A footprint is defined as the positions of the corners of the image on the sky after all available distortions have been applied. Parameters ---------- header : `~astropy.io.fits.Header` object, optional undistort : bool, optional If `True`, take SIP and distortion lookup table into account axes : length 2 sequence ints, optional If provided, use the given sequence as the shape of the image. Otherwise, use the ``NAXIS1`` and ``NAXIS2`` keywords from the header that was used to create this `WCS` object. center : bool, optional If `True` use the center of the pixel, otherwise use the corner. Returns ------- coord : (4, 2) array of (*x*, *y*) coordinates. The order is counter-clockwise starting with the bottom left corner. """ if axes is not None: naxis1, naxis2 = axes else: if header is None: try: # classes that inherit from WCS and define naxis1/2 # do not require a header parameter naxis1 = self._naxis1 naxis2 = self._naxis2 except AttributeError: warnings.warn("Need a valid header in order to calculate footprint\n", AstropyUserWarning) return None else: naxis1 = header.get('NAXIS1', None) naxis2 = header.get('NAXIS2', None) if naxis1 is None or naxis2 is None: return None if center == True: corners = np.array([[1, 1], [1, naxis2], [naxis1, naxis2], [naxis1, 1]], dtype = np.float64) else: corners = np.array([[0.5, 0.5], [0.5, naxis2 + 0.5], [naxis1 + 0.5, naxis2 + 0.5], [naxis1 + 0.5, 0.5]], dtype = np.float64) if undistort: return self.all_pix2world(corners, 1) else: return self.wcs_pix2world(corners, 1) def _read_det2im_kw(self, header, fobj, err=0.0): """ Create a `Paper IV`_ type lookup table for detector to image plane correction. """ if fobj is None: return (None, None) if not isinstance(fobj, fits.HDUList): return (None, None) try: axiscorr = header[str('AXISCORR')] d2imdis = self._read_d2im_old_format(header, fobj, axiscorr) return d2imdis except KeyError: pass dist = 'D2IMDIS' d_kw = 'D2IM' err_kw = 'D2IMERR' tables = {} for i in range(1, self.naxis + 1): d_error = header.get(err_kw + str(i), 0.0) if d_error < err: tables[i] = None continue distortion = dist + str(i) if distortion in header: dis = header[distortion].lower() if dis == 'lookup': assert isinstance(fobj, fits.HDUList), ('An astropy.io.fits.HDUList' 'is required for Lookup table distortion.') dp = (d_kw + str(i)).strip() d_extver = header.get(dp + '.EXTVER', 1) if i == header[dp + '.AXIS.{0:d}'.format(i)]: d_data = fobj[str('D2IMARR'), d_extver].data else: d_data = (fobj[str('D2IMARR'), d_extver].data).transpose() d_header = fobj[str('D2IMARR'), d_extver].header d_crpix = (d_header.get(str('CRPIX1'), 0.0), d_header.get(str('CRPIX2'), 0.0)) d_crval = (d_header.get(str('CRVAL1'), 0.0), d_header.get(str('CRVAL2'), 0.0)) d_cdelt = (d_header.get(str('CDELT1'), 1.0), d_header.get(str('CDELT2'), 1.0)) d_lookup = DistortionLookupTable(d_data, d_crpix, d_crval, d_cdelt) tables[i] = d_lookup else: warnings.warn('Polynomial distortion is not implemented.\n', AstropyUserWarning) else: tables[i] = None if not tables: return (None, None) else: return (tables.get(1), tables.get(2)) def _read_d2im_old_format(self, header, fobj, axiscorr): warnings.warn("The use of ``AXISCORR`` for D2IM correction has been deprecated." "`~astropy.wcs` will read in files with ``AXISCORR`` but ``to_fits()`` will write " "out files without it.", AstropyDeprecationWarning) cpdis = [None, None] crpix = [0., 0.] crval = [0., 0.] cdelt = [1., 1.] try: d2im_data = fobj[(str('D2IMARR'), 1)].data except KeyError: return (None, None) except AttributeError: return (None, None) d2im_data = np.array([d2im_data]) d2im_hdr = fobj[(str('D2IMARR'), 1)].header naxis = d2im_hdr[str('NAXIS')] for i in range(1, naxis + 1): crpix[i - 1] = d2im_hdr.get(str('CRPIX') + str(i), 0.0) crval[i - 1] = d2im_hdr.get(str('CRVAL') + str(i), 0.0) cdelt[i - 1] = d2im_hdr.get(str('CDELT') + str(i), 1.0) cpdis = DistortionLookupTable(d2im_data, crpix, crval, cdelt) if axiscorr == 1: return (cpdis, None) elif axiscorr == 2: return (None, cpdis) else: warnings.warn("Expected AXISCORR to be 1 or 2", AstropyUserWarning) return (None, None) def _write_det2im(self, hdulist): """ Writes a Paper IV type lookup table to the given `astropy.io.fits.HDUList`. """ if self.det2im1 is None and self.det2im2 is None: return dist = 'D2IMDIS' d_kw = 'D2IM' err_kw = 'D2IMERR' def write_d2i(num, det2im): if det2im is None: return str('{0}{1:d}').format(dist, num), hdulist[0].header[str('{0}{1:d}').format(dist, num)] = ( 'LOOKUP', 'Detector to image correction type') hdulist[0].header[str('{0}{1:d}.EXTVER').format(d_kw, num)] = ( num, 'Version number of WCSDVARR extension') hdulist[0].header[str('{0}{1:d}.NAXES').format(d_kw, num)] = ( len(det2im.data.shape), 'Number of independent variables in d2im function') for i in range(det2im.data.ndim): hdulist[0].header[str('{0}{1:d}.AXIS.{2:d}').format(d_kw, num, i + 1)] = ( i + 1, 'Axis number of the jth independent variable in a d2im function') image = fits.ImageHDU(det2im.data, name=str('D2IMARR')) header = image.header header[str('CRPIX1')] = (det2im.crpix[0], 'Coordinate system reference pixel') header[str('CRPIX2')] = (det2im.crpix[1], 'Coordinate system reference pixel') header[str('CRVAL1')] = (det2im.crval[0], 'Coordinate system value at reference pixel') header[str('CRVAL2')] = (det2im.crval[1], 'Coordinate system value at reference pixel') header[str('CDELT1')] = (det2im.cdelt[0], 'Coordinate increment along axis') header[str('CDELT2')] = (det2im.cdelt[1], 'Coordinate increment along axis') image.update_ext_version( int(hdulist[0].header[str('{0}{1:d}.EXTVER').format(d_kw, num)])) hdulist.append(image) write_d2i(1, self.det2im1) write_d2i(2, self.det2im2) def _read_distortion_kw(self, header, fobj, dist='CPDIS', err=0.0): """ Reads `Paper IV`_ table-lookup distortion keywords and data, and returns a 2-tuple of `~astropy.wcs.DistortionLookupTable` objects. If no `Paper IV`_ distortion keywords are found, ``(None, None)`` is returned. """ if isinstance(header, (six.text_type, six.binary_type)): return (None, None) if dist == 'CPDIS': d_kw = str('DP') err_kw = str('CPERR') else: d_kw = str('DQ') err_kw = str('CQERR') tables = {} for i in range(1, self.naxis + 1): d_error = header.get(err_kw + str(i), 0.0) if d_error < err: tables[i] = None continue distortion = dist + str(i) if distortion in header: dis = header[distortion].lower() if dis == 'lookup': assert isinstance(fobj, fits.HDUList), \ 'An astropy.io.fits.HDUList is required for ' + \ 'Lookup table distortion.' dp = (d_kw + str(i)).strip() d_extver = header.get(dp + str('.EXTVER'), 1) if i == header[dp + str('.AXIS.') + str(i)]: d_data = fobj[str('WCSDVARR'), d_extver].data else: d_data = (fobj[str('WCSDVARR'), d_extver].data).transpose() d_header = fobj[str('WCSDVARR'), d_extver].header d_crpix = (d_header.get(str('CRPIX1'), 0.0), d_header.get(str('CRPIX2'), 0.0)) d_crval = (d_header.get(str('CRVAL1'), 0.0), d_header.get(str('CRVAL2'), 0.0)) d_cdelt = (d_header.get(str('CDELT1'), 1.0), d_header.get(str('CDELT2'), 1.0)) d_lookup = DistortionLookupTable(d_data, d_crpix, d_crval, d_cdelt) tables[i] = d_lookup else: warnings.warn('Polynomial distortion is not implemented.\n', AstropyUserWarning) else: tables[i] = None if not tables: return (None, None) else: return (tables.get(1), tables.get(2)) def _write_distortion_kw(self, hdulist, dist='CPDIS'): """ Write out Paper IV distortion keywords to the given `fits.HDUList`. """ if self.cpdis1 is None and self.cpdis2 is None: return if dist == 'CPDIS': d_kw = str('DP') err_kw = str('CPERR') else: d_kw = str('DQ') err_kw = str('CQERR') def write_dist(num, cpdis): if cpdis is None: return hdulist[0].header[str('{0}{1:d}').format(dist, num)] = ( 'LOOKUP', 'Prior distortion function type') hdulist[0].header[str('{0}{1:d}.EXTVER').format(d_kw, num)] = ( num, 'Version number of WCSDVARR extension') hdulist[0].header[str('{0}{1:d}.NAXES').format(d_kw, num)] = ( len(cpdis.data.shape), 'Number of independent variables in distortion function') for i in range(cpdis.data.ndim): hdulist[0].header[str('{0}{1:d}.AXIS.{2:d}').format(d_kw, num, i + 1)] = ( i + 1, 'Axis number of the jth independent variable in a distortion function') image = fits.ImageHDU(cpdis.data, name=str('WCSDVARR')) header = image.header header[str('CRPIX1')] = (cpdis.crpix[0], 'Coordinate system reference pixel') header[str('CRPIX2')] = (cpdis.crpix[1], 'Coordinate system reference pixel') header[str('CRVAL1')] = (cpdis.crval[0], 'Coordinate system value at reference pixel') header[str('CRVAL2')] = (cpdis.crval[1], 'Coordinate system value at reference pixel') header[str('CDELT1')] = (cpdis.cdelt[0], 'Coordinate increment along axis') header[str('CDELT2')] = (cpdis.cdelt[1], 'Coordinate increment along axis') image.update_ext_version( int(hdulist[0].header[str('{0}{1:d}.EXTVER').format(d_kw, num)])) hdulist.append(image) write_dist(1, self.cpdis1) write_dist(2, self.cpdis2) def _read_sip_kw(self, header): """ Reads `SIP`_ header keywords and returns a `~astropy.wcs.Sip` object. If no `SIP`_ header keywords are found, ``None`` is returned. """ if isinstance(header, (six.text_type, six.binary_type)): # TODO: Parse SIP from a string without pyfits around return None if str("A_ORDER") in header and header[str('A_ORDER')] > 1: if str("B_ORDER") not in header: raise ValueError( "A_ORDER provided without corresponding B_ORDER " "keyword for SIP distortion") m = int(header[str("A_ORDER")]) a = np.zeros((m + 1, m + 1), np.double) for i in range(m + 1): for j in range(m - i + 1): a[i, j] = header.get((str("A_{0}_{1}").format(i, j)), 0.0) m = int(header[str("B_ORDER")]) if m > 1: b = np.zeros((m + 1, m + 1), np.double) for i in range(m + 1): for j in range(m - i + 1): b[i, j] = header.get((str("B_{0}_{1}").format(i, j)), 0.0) else: a = None b = None elif str("B_ORDER") in header and header[str('B_ORDER')] > 1: raise ValueError( "B_ORDER provided without corresponding A_ORDER " + "keyword for SIP distortion") else: a = None b = None if str("AP_ORDER") in header and header[str('AP_ORDER')] > 1: if str("BP_ORDER") not in header: raise ValueError( "AP_ORDER provided without corresponding BP_ORDER " "keyword for SIP distortion") m = int(header[str("AP_ORDER")]) ap = np.zeros((m + 1, m + 1), np.double) for i in range(m + 1): for j in range(m - i + 1): ap[i, j] = header.get("AP_{0}_{1}".format(i, j), 0.0) m = int(header[str("BP_ORDER")]) if m > 1: bp = np.zeros((m + 1, m + 1), np.double) for i in range(m + 1): for j in range(m - i + 1): bp[i, j] = header.get("BP_{0}_{1}".format(i, j), 0.0) else: ap = None bp = None elif str("BP_ORDER") in header and header[str('BP_ORDER')] > 1: raise ValueError( "BP_ORDER provided without corresponding AP_ORDER " "keyword for SIP distortion") else: ap = None bp = None if a is None and b is None and ap is None and bp is None: return None if str("CRPIX1") not in header or str("CRPIX2") not in header: raise ValueError( "Header has SIP keywords without CRPIX keywords") crpix1 = header.get("CRPIX1") crpix2 = header.get("CRPIX2") return Sip(a, b, ap, bp, (crpix1, crpix2)) def _write_sip_kw(self): """ Write out SIP keywords. Returns a dictionary of key-value pairs. """ if self.sip is None: return {} keywords = {} def write_array(name, a): if a is None: return size = a.shape[0] keywords[str('{0}_ORDER').format(name)] = size - 1 for i in range(size): for j in range(size - i): if a[i, j] != 0.0: keywords[ str('{0}_{1:d}_{2:d}').format(name, i, j)] = a[i, j] write_array(str('A'), self.sip.a) write_array(str('B'), self.sip.b) write_array(str('AP'), self.sip.ap) write_array(str('BP'), self.sip.bp) return keywords def _denormalize_sky(self, sky): if self.wcs.lngtyp != 'RA': raise ValueError( "WCS does not have longitude type of 'RA', therefore " + "(ra, dec) data can not be used as input") if self.wcs.lattyp != 'DEC': raise ValueError( "WCS does not have longitude type of 'DEC', therefore " + "(ra, dec) data can not be used as input") if self.wcs.naxis == 2: if self.wcs.lng == 0 and self.wcs.lat == 1: return sky elif self.wcs.lng == 1 and self.wcs.lat == 0: # Reverse the order of the columns return sky[:, ::-1] else: raise ValueError( "WCS does not have longitude and latitude celestial " + "axes, therefore (ra, dec) data can not be used as input") else: if self.wcs.lng < 0 or self.wcs.lat < 0: raise ValueError( "WCS does not have both longitude and latitude " "celestial axes, therefore (ra, dec) data can not be " + "used as input") out = np.zeros((sky.shape[0], self.wcs.naxis)) out[:, self.wcs.lng] = sky[:, 0] out[:, self.wcs.lat] = sky[:, 1] return out def _normalize_sky(self, sky): if self.wcs.lngtyp != 'RA': raise ValueError( "WCS does not have longitude type of 'RA', therefore " + "(ra, dec) data can not be returned") if self.wcs.lattyp != 'DEC': raise ValueError( "WCS does not have longitude type of 'DEC', therefore " + "(ra, dec) data can not be returned") if self.wcs.naxis == 2: if self.wcs.lng == 0 and self.wcs.lat == 1: return sky elif self.wcs.lng == 1 and self.wcs.lat == 0: # Reverse the order of the columns return sky[:, ::-1] else: raise ValueError( "WCS does not have longitude and latitude celestial " "axes, therefore (ra, dec) data can not be returned") else: if self.wcs.lng < 0 or self.wcs.lat < 0: raise ValueError( "WCS does not have both longitude and latitude celestial " "axes, therefore (ra, dec) data can not be returned") out = np.empty((sky.shape[0], 2)) out[:, 0] = sky[:, self.wcs.lng] out[:, 1] = sky[:, self.wcs.lat] return out def _array_converter(self, func, sky, *args, **kwargs): """ A helper function to support reading either a pair of arrays or a single Nx2 array. """ ra_dec_order = kwargs.pop('ra_dec_order', False) if len(kwargs): raise TypeError("Unexpected keyword argument {0!r}".format( kwargs.keys()[0])) def _return_list_of_arrays(axes, origin): try: axes = np.broadcast_arrays(*axes) except ValueError: raise ValueError( "Coordinate arrays are not broadcastable to each other") xy = np.hstack([x.reshape((x.size, 1)) for x in axes]) if ra_dec_order and sky == 'input': xy = self._denormalize_sky(xy) output = func(xy, origin) if ra_dec_order and sky == 'output': output = self._normalize_sky(output) return (output[:, 0].reshape(axes[0].shape), output[:, 1].reshape(axes[0].shape)) return [output[:, i].reshape(axes[0].shape) for i in range(output.shape[1])] def _return_single_array(xy, origin): if xy.shape[-1] != self.naxis: raise ValueError( "When providing two arguments, the array must be " "of shape (N, {0})".format(self.naxis)) if ra_dec_order and sky == 'input': xy = self._denormalize_sky(xy) result = func(xy, origin) if ra_dec_order and sky == 'output': result = self._normalize_sky(result) return result if len(args) == 2: try: xy, origin = args xy = np.asarray(xy) origin = int(origin) except: raise TypeError( "When providing two arguments, they must be " "(coords[N][{0}], origin)".format(self.naxis)) if self.naxis == 1 and len(xy.shape) == 1: return _return_list_of_arrays([xy], origin) return _return_single_array(xy, origin) elif len(args) == self.naxis + 1: axes = args[:-1] origin = args[-1] try: axes = [np.asarray(x) for x in axes] origin = int(origin) except: raise TypeError( "When providing more than two arguments, they must be " + "a 1-D array for each axis, followed by an origin.") return _return_list_of_arrays(axes, origin) raise TypeError( "WCS projection has {0} dimensions, so expected 2 (an Nx{0} array " "and the origin argument) or {1} arguments (the position in each " "dimension, and the origin argument). Instead, {2} arguments were " "given.".format( self.naxis, self.naxis + 1, len(args))) def all_pix2world(self, *args, **kwargs): return self._array_converter( self._all_pix2world, 'output', *args, **kwargs) all_pix2world.__doc__ = """ Transforms pixel coordinates to world coordinates. Performs all of the following in order: - Detector to image plane correction (optionally) - `SIP`_ distortion correction (optionally) - `Paper IV`_ table-lookup distortion correction (optionally) - `wcslib`_ WCS transformation Parameters ---------- {0} For a transformation that is not two-dimensional, the two-argument form must be used. {1} Returns ------- {2} Notes ----- The order of the axes for the result is determined by the ``CTYPEia`` keywords in the FITS header, therefore it may not always be of the form (*ra*, *dec*). The `~astropy.wcs.Wcsprm.lat`, `~astropy.wcs.Wcsprm.lng`, `~astropy.wcs.Wcsprm.lattyp` and `~astropy.wcs.Wcsprm.lngtyp` members can be used to determine the order of the axes. Raises ------ MemoryError Memory allocation failed. SingularMatrixError Linear transformation matrix is singular. InconsistentAxisTypesError Inconsistent or unrecognized coordinate axis types. ValueError Invalid parameter value. ValueError Invalid coordinate transformation parameters. ValueError x- and y-coordinate arrays are not the same size. InvalidTransformError Invalid coordinate transformation parameters. InvalidTransformError Ill-conditioned coordinate transformation parameters. """.format(__.TWO_OR_MORE_ARGS('naxis', 8), __.RA_DEC_ORDER(8), __.RETURNS('sky coordinates, in degrees', 8)) def wcs_pix2world(self, *args, **kwargs): if self.wcs is None: raise ValueError("No basic WCS settings were created.") return self._array_converter( lambda xy, o: self.wcs.p2s(xy, o)['world'], 'output', *args, **kwargs) wcs_pix2world.__doc__ = """ Transforms pixel coordinates to world coordinates by doing only the basic `wcslib`_ transformation. No `SIP`_ or `Paper IV`_ table lookup distortion correction is applied. To perform distortion correction, see `~astropy.wcs.WCS.all_pix2world`, `~astropy.wcs.WCS.sip_pix2foc`, `~astropy.wcs.WCS.p4_pix2foc`, or `~astropy.wcs.WCS.pix2foc`. Parameters ---------- {0} For a transformation that is not two-dimensional, the two-argument form must be used. {1} Returns ------- {2} Raises ------ MemoryError Memory allocation failed. SingularMatrixError Linear transformation matrix is singular. InconsistentAxisTypesError Inconsistent or unrecognized coordinate axis types. ValueError Invalid parameter value. ValueError Invalid coordinate transformation parameters. ValueError x- and y-coordinate arrays are not the same size. InvalidTransformError Invalid coordinate transformation parameters. InvalidTransformError Ill-conditioned coordinate transformation parameters. Notes ----- The order of the axes for the result is determined by the ``CTYPEia`` keywords in the FITS header, therefore it may not always be of the form (*ra*, *dec*). The `~astropy.wcs.Wcsprm.lat`, `~astropy.wcs.Wcsprm.lng`, `~astropy.wcs.Wcsprm.lattyp` and `~astropy.wcs.Wcsprm.lngtyp` members can be used to determine the order of the axes. """.format(__.TWO_OR_MORE_ARGS('naxis', 8), __.RA_DEC_ORDER(8), __.RETURNS('world coordinates, in degrees', 8)) def _all_world2pix(self, world, origin, tolerance, **kwargs): import scipy.optimize pix = [] for i in range(len(world)): x0 = self.wcs_world2pix(np.atleast_2d(world[i]), origin, **kwargs).flatten() func = lambda pix: (self.all_pix2world(np.atleast_2d(pix), origin, **kwargs) - world[i]).flatten() # Use Broyden inverse because it is (a) present in a wide range of # Scipy version, (b) provides an option for the absolute tolerance, # and (c) is suitable for small-scale problems (i.e., a few # variables, rather than hundreds of variables). soln = scipy.optimize.broyden1(func, x0, x_tol=tolerance) pix.append(soln.flatten()) return np.asarray(pix) def all_world2pix(self, *args, **kwargs): if self.wcs is None: raise ValueError("No basic WCS settings were created.") tolerance = kwargs.pop('tolerance', 1e-6) return self._array_converter(lambda *args, **kwargs: self._all_world2pix(*args, tolerance=tolerance, **kwargs), 'input', *args, **kwargs) all_world2pix.__doc__ = """ Transforms world coordinates to pixel coordinates, using numerical iteration to invert the method `~astropy.wcs.WCS.all_pix2world` within a tolerance of 1e-6 pixels. Note that to use this function, you must have Scipy installed. Parameters ---------- {0} For a transformation that is not two-dimensional, the two-argument form must be used. {1} tolerance : float, optional Tolerance of solution. Iteration terminates when the iterative solver estimates that the true solution is within this many pixels current estimate. Default value is 1e-6 (pixels). Returns ------- {2} Notes ----- The order of the axes for the input world array is determined by the ``CTYPEia`` keywords in the FITS header, therefore it may not always be of the form (*ra*, *dec*). The `~astropy.wcs.Wcsprm.lat`, `~astropy.wcs.Wcsprm.lng`, `~astropy.wcs.Wcsprm.lattyp` and `~astropy.wcs.Wcsprm.lngtyp` members can be used to determine the order of the axes. Raises ------ MemoryError Memory allocation failed. SingularMatrixError Linear transformation matrix is singular. InconsistentAxisTypesError Inconsistent or unrecognized coordinate axis types. ValueError Invalid parameter value. ValueError Invalid coordinate transformation parameters. ValueError x- and y-coordinate arrays are not the same size. InvalidTransformError Invalid coordinate transformation parameters. InvalidTransformError Ill-conditioned coordinate transformation parameters. """.format(__.TWO_OR_MORE_ARGS('naxis', 8), __.RA_DEC_ORDER(8), __.RETURNS('pixel coordinates', 8)) def wcs_world2pix(self, *args, **kwargs): if self.wcs is None: raise ValueError("No basic WCS settings were created.") return self._array_converter( lambda xy, o: self.wcs.s2p(xy, o)['pixcrd'], 'input', *args, **kwargs) wcs_world2pix.__doc__ = """ Transforms world coordinates to pixel coordinates, using only the basic `wcslib`_ WCS transformation. No `SIP`_ or `Paper IV`_ table lookup distortion is applied. Parameters ---------- {0} For a transformation that is not two-dimensional, the two-argument form must be used. {1} Returns ------- {2} Notes ----- The order of the axes for the input world array is determined by the ``CTYPEia`` keywords in the FITS header, therefore it may not always be of the form (*ra*, *dec*). The `~astropy.wcs.Wcsprm.lat`, `~astropy.wcs.Wcsprm.lng`, `~astropy.wcs.Wcsprm.lattyp` and `~astropy.wcs.Wcsprm.lngtyp` members can be used to determine the order of the axes. Raises ------ MemoryError Memory allocation failed. SingularMatrixError Linear transformation matrix is singular. InconsistentAxisTypesError Inconsistent or unrecognized coordinate axis types. ValueError Invalid parameter value. ValueError Invalid coordinate transformation parameters. ValueError x- and y-coordinate arrays are not the same size. InvalidTransformError Invalid coordinate transformation parameters. InvalidTransformError Ill-conditioned coordinate transformation parameters. """.format(__.TWO_OR_MORE_ARGS('naxis', 8), __.RA_DEC_ORDER(8), __.RETURNS('pixel coordinates', 8)) def pix2foc(self, *args): return self._array_converter(self._pix2foc, None, *args) pix2foc.__doc__ = """ Convert pixel coordinates to focal plane coordinates using the `SIP`_ polynomial distortion convention and `Paper IV`_ table-lookup distortion correction. The output is in absolute pixel coordinates, not relative to ``CRPIX``. Parameters ---------- {0} Returns ------- {1} Raises ------ MemoryError Memory allocation failed. ValueError Invalid coordinate transformation parameters. """.format(__.TWO_OR_MORE_ARGS('2', 8), __.RETURNS('focal coordinates', 8)) def p4_pix2foc(self, *args): return self._array_converter(self._p4_pix2foc, None, *args) p4_pix2foc.__doc__ = """ Convert pixel coordinates to focal plane coordinates using `Paper IV`_ table-lookup distortion correction. The output is in absolute pixel coordinates, not relative to ``CRPIX``. Parameters ---------- {0} Returns ------- {1} Raises ------ MemoryError Memory allocation failed. ValueError Invalid coordinate transformation parameters. """.format(__.TWO_OR_MORE_ARGS('2', 8), __.RETURNS('focal coordinates', 8)) def det2im(self, *args): return self._array_converter(self._det2im, None, *args) det2im.__doc__ = """ Convert detector coordinates to image plane coordinates using `Paper IV`_ table-lookup distortion correction. The output is in absolute pixel coordinates, not relative to ``CRPIX``. Parameters ---------- {0} Returns ------- {1} Raises ------ MemoryError Memory allocation failed. ValueError Invalid coordinate transformation parameters. """.format(__.TWO_OR_MORE_ARGS('2', 8), __.RETURNS('pixel coordinates', 8)) def sip_pix2foc(self, *args): if self.sip is None: if len(args) == 2: return args[0] elif len(args) == 3: return args[:2] else: raise TypeError("Wrong number of arguments") return self._array_converter(self.sip.pix2foc, None, *args) sip_pix2foc.__doc__ = """ Convert pixel coordinates to focal plane coordinates using the `SIP`_ polynomial distortion convention. The output is in pixel coordinates, relative to ``CRPIX``. `Paper IV`_ table lookup distortion correction is not applied, even if that information existed in the FITS file that initialized this :class:`~astropy.wcs.WCS` object. To correct for that, use `~astropy.wcs.WCS.pix2foc` or `~astropy.wcs.WCS.p4_pix2foc`. Parameters ---------- {0} Returns ------- {1} Raises ------ MemoryError Memory allocation failed. ValueError Invalid coordinate transformation parameters. """.format(__.TWO_OR_MORE_ARGS('2', 8), __.RETURNS('focal coordinates', 8)) def sip_foc2pix(self, *args): if self.sip is None: if len(args) == 2: return args[0] elif len(args) == 3: return args[:2] else: raise TypeError("Wrong number of arguments") return self._array_converter(self.sip.foc2pix, None, *args) sip_foc2pix.__doc__ = """ Convert focal plane coordinates to pixel coordinates using the `SIP`_ polynomial distortion convention. `Paper IV`_ table lookup distortion correction is not applied, even if that information existed in the FITS file that initialized this `~astropy.wcs.WCS` object. Parameters ---------- {0} Returns ------- {1} Raises ------ MemoryError Memory allocation failed. ValueError Invalid coordinate transformation parameters. """.format(__.TWO_OR_MORE_ARGS('2', 8), __.RETURNS('pixel coordinates', 8)) def to_fits(self, relax=False, key=None): """ Generate an `astropy.io.fits.HDUList` object with all of the information stored in this object. This should be logically identical to the input FITS file, but it will be normalized in a number of ways. See `to_header` for some warnings about the output produced. Parameters ---------- relax : bool or int, optional Degree of permissiveness: - `False` (default): Write all extensions that are considered to be safe and recommended. - `True`: Write all recognized informal extensions of the WCS standard. - `int`: a bit field selecting specific extensions to write. See :ref:`relaxwrite` for details. key : str The name of a particular WCS transform to use. This may be either ``' '`` or ``'A'``-``'Z'`` and corresponds to the ``"a"`` part of the ``CTYPEia`` cards. Returns ------- hdulist : `astropy.io.fits.HDUList` """ header = self.to_header(relax=relax, key=key) hdu = fits.PrimaryHDU(header=header) hdulist = fits.HDUList(hdu) self._write_det2im(hdulist) self._write_distortion_kw(hdulist) return hdulist def to_header(self, relax=False, key=None): """ Generate an `astropy.io.fits.Header` object with the basic WCS and SIP information stored in this object. This should be logically identical to the input FITS file, but it will be normalized in a number of ways. .. warning:: This function does not write out Paper IV distortion information, since that requires multiple FITS header data units. To get a full representation of everything in this object, use `to_fits`. Parameters ---------- relax : bool or int, optional Degree of permissiveness: - `False` (default): Write all extensions that are considered to be safe and recommended. - `True`: Write all recognized informal extensions of the WCS standard. - `int`: a bit field selecting specific extensions to write. See :ref:`relaxwrite` for details. key : str The name of a particular WCS transform to use. This may be either ``' '`` or ``'A'``-``'Z'`` and corresponds to the ``"a"`` part of the ``CTYPEia`` cards. Returns ------- header : `astropy.io.fits.Header` Notes ----- The output header will almost certainly differ from the input in a number of respects: 1. The output header only contains WCS-related keywords. In particular, it does not contain syntactically-required keywords such as ``SIMPLE``, ``NAXIS``, ``BITPIX``, or ``END``. 2. Deprecated (e.g. ``CROTAn``) or non-standard usage will be translated to standard (this is partially dependent on whether ``fix`` was applied). 3. Quantities will be converted to the units used internally, basically SI with the addition of degrees. 4. Floating-point quantities may be given to a different decimal precision. 5. Elements of the ``PCi_j`` matrix will be written if and only if they differ from the unit matrix. Thus, if the matrix is unity then no elements will be written. 6. Additional keywords such as ``WCSAXES``, ``CUNITia``, ``LONPOLEa`` and ``LATPOLEa`` may appear. 7. The original keycomments will be lost, although `to_header` tries hard to write meaningful comments. 8. Keyword order may be changed. """ if key is not None: self.wcs.alt = key if relax not in (True, False): do_sip = relax & WCSHDO_SIP relax &= ~WCSHDO_SIP else: do_sip = relax if self.wcs is not None: header_string = self.wcs.to_header(relax) header = fits.Header.fromstring(header_string) else: header = fits.Header() if do_sip and self.sip is not None: for key, val in self._write_sip_kw().items(): header[key] = val return header def to_header_string(self, relax=False): """ Identical to `to_header`, but returns a string containing the header cards. """ return str(self.to_header(relax)) def footprint_to_file(self, filename=None, color='green', width=2): """ Writes out a `ds9`_ style regions file. It can be loaded directly by `ds9`_. Parameters ---------- filename : str, optional Output file name - default is ``'footprint.reg'`` color : str, optional Color to use when plotting the line. width : int, optional Width of the region line. """ if not filename: filename = 'footprint.reg' comments = '# Region file format: DS9 version 4.0 \n' comments += ('# global color=green font="helvetica 12 bold ' + 'select=1 highlite=1 edit=1 move=1 delete=1 ' + 'include=1 fixed=0 source\n') f = open(filename, 'a') f.write(comments) f.write('linear\n') f.write('polygon(') self.calc_footprint().tofile(f, sep=',') f.write(') # color={0}, width={1:d} \n'.format(color, width)) f.close() def _get_naxis(self, header=None): self._naxis1 = 0 self._naxis2 = 0 if (header is not None and not isinstance(header, (six.text_type, six.binary_type))): self._naxis1 = header.get('NAXIS1', 0) self._naxis2 = header.get('NAXIS2', 0) def rotateCD(self, theta): _theta = np.deg2rad(theta) _mrot = np.zeros(shape=(2, 2), dtype=np.double) _mrot[0] = (np.cos(_theta), np.sin(_theta)) _mrot[1] = (-np.sin(_theta), np.cos(_theta)) new_cd = np.dot(self.wcs.cd, _mrot) self.wcs.cd = new_cd def printwcs(self): print("WCS Keywords\n") print("Number of WCS axes: {0!r}".format(self.naxis)) sfmt = ': ' + "".join(["{"+"{0}".format(i)+"!r} " for i in range(self.naxis)]) s = 'CTYPE ' + sfmt print(s.format(*self.wcs.ctype)) s = 'CRVAL ' + sfmt print(s.format(*self.wcs.crval)) s = 'CRPIX ' + sfmt print(s.format(*self.wcs.crpix)) if hasattr(self.wcs, 'pc'): for i in range(self.naxis): s = '' for j in range(self.naxis): s += ''.join(['PC', str(i+1), '_', str(j+1), ' ']) s += sfmt print(s.format(*self.wcs.pc[i])) s = 'CDELT ' + sfmt print(s.format(*self.wcs.cdelt)) elif hasattr(self.wcs, 'cd'): for i in range(self.naxis): s = '' for j in range(self.naxis): s += "".join(['CD', str(i+1), '_', str(j+1), ' ']) s += sfmt print(s.format(*self.wcs.cd[i])) print('NAXIS : {0!r} {1!r}'.format(self._naxis1, self._naxis2)) def get_axis_types(self): """ Similar to `self.wcsprm.axis_types ` but provides the information in a more Python-friendly format. Returns ------- result : list of dicts Returns a list of dictionaries, one for each axis, each containing attributes about the type of that axis. Each dictionary has the following keys: - 'coordinate_type': - None: Non-specific coordinate type. - 'stokes': Stokes coordinate. - 'celestial': Celestial coordinate (including ``CUBEFACE``). - 'spectral': Spectral coordinate. - 'scale': - 'linear': Linear axis. - 'quantized': Quantized axis (``STOKES``, ``CUBEFACE``). - 'non-linear celestial': Non-linear celestial axis. - 'non-linear spectral': Non-linear spectral axis. - 'logarithmic': Logarithmic axis. - 'tabular': Tabular axis. - 'group' - Group number, e.g. lookup table number - 'number' - For celestial axes: - 0: Longitude coordinate. - 1: Latitude coordinate. - 2: ``CUBEFACE`` number. - For lookup tables: - the axis number in a multidimensional table. ``CTYPEia`` in ``"4-3"`` form with unrecognized algorithm code will generate an error. """ if self.wcs is None: raise AttributeError( "This WCS object does not have a wcsprm object.") coordinate_type_map = { 0: None, 1: 'stokes', 2: 'celestial', 3: 'spectral'} scale_map = { 0: 'linear', 1: 'quantized', 2: 'non-linear celestial', 3: 'non-linear spectral', 4: 'logarithmic', 5: 'tabular'} result = [] for axis_type in self.wcs.axis_types: subresult = {} coordinate_type = (axis_type // 1000) % 10 subresult['coordinate_type'] = coordinate_type_map[coordinate_type] scale = (axis_type // 100) % 10 subresult['scale'] = scale_map[scale] group = (axis_type // 10) % 10 subresult['group'] = group number = axis_type % 10 subresult['number'] = number result.append(subresult) return result def __reduce__(self): """ Support pickling of WCS objects. This is done by serializing to an in-memory FITS file and dumping that as a string. """ hdulist = self.to_fits(relax=True) buffer = io.BytesIO() hdulist.writeto(buffer) return (__WCS_unpickle__, (self.__class__, self.__dict__, buffer.getvalue(),)) def dropaxis(self, dropax): """ Remove an axis from the WCS. Parameters ---------- wcs : `~astropy.wcs.WCS` The WCS with naxis to be chopped to naxis-1 dropax : int The index of the WCS to drop, counting from 0 (i.e., python convention, not FITS convention) Returns ------- A new `~astropy.wcs.WCS` instance with one axis fewer """ inds = list(range(self.wcs.naxis)) inds.pop(dropax) # axis 0 has special meaning to sub # if wcs.wcs.ctype == ['RA','DEC','VLSR'], you want # wcs.sub([1,2]) to get 'RA','DEC' back return self.sub([i+1 for i in inds]) def swapaxes(self, ax0, ax1): """ Swap axes in a WCS. Parameters ---------- wcs: `~astropy.wcs.WCS` The WCS to have its axes swapped ax0: int ax1: int The indices of the WCS to be swapped, counting from 0 (i.e., python convention, not FITS convention) Returns ------- A new `~astropy.wcs.WCS` instance with the same number of axes, but two swapped """ inds = list(range(self.wcs.naxis)) inds[ax0],inds[ax1] = inds[ax1],inds[ax0] return self.sub([i+1 for i in inds]) def reorient_celestial_first(self): """ Reorient the WCS such that the celestial axes are first, followed by the spectral axis, followed by any others. Assumes at least celestial axes are present. """ return self.sub([WCSSUB_CELESTIAL, WCSSUB_SPECTRAL, WCSSUB_STOKES]) def slice(self, view, numpy_order=True): """ Slice a WCS instance using a Numpy slice. The order of the slice should be reversed (as for the data) compared to the natural WCS order. Parameters ---------- view : tuple A tuple containing the same number of slices as the WCS system. The ``step`` method, the third argument to a slice, is not presently supported. numpy_order : bool Use numpy order, i.e. slice the WCS so that an identical slice applied to a numpy array will slice the array and WCS in the same way. If set to `False`, the WCS will be sliced in FITS order, meaning the first slice will be applied to the *last* numpy index but the *first* WCS axis. Returns ------- wcs_new : `~astropy.wcs.WCS` A new resampled WCS axis """ if hasattr(view, '__len__') and len(view) > self.wcs.naxis: raise ValueError("Must have # of slices <= # of WCS axes") elif not hasattr(view, '__len__'): # view MUST be an iterable view = [view] if not all([isinstance(x, slice) for x in view]): raise ValueError("Cannot downsample a WCS with indexing. Use " "wcs.sub or wcs.dropaxis if you want to remove " "axes.") wcs_new = self.deepcopy() for i, iview in enumerate(view): if iview.start is not None: if numpy_order: wcs_index = self.wcs.naxis - 1 - i else: wcs_index = i if iview.step not in (None, 1): crpix = self.wcs.crpix[wcs_index] cdelt = self.wcs.cdelt[wcs_index] # equivalently (keep this comment so you can compare eqns): # wcs_new.wcs.crpix[wcs_index] = # (crpix - iview.start)*iview.step + 0.5 - iview.step/2. crp = ((crpix - iview.start - 1.)/iview.step + 0.5 + 1./iview.step/2.) wcs_new.wcs.crpix[wcs_index] = crp wcs_new.wcs.cdelt[wcs_index] = cdelt * iview.step else: wcs_new.wcs.crpix[wcs_index] -= iview.start return wcs_new def __getitem__(self, item): # "getitem" is a shortcut for self.slice; it is very limited # there is no obvious and unambiguous interpretation of wcs[1,2,3] # We COULD allow wcs[1] to link to wcs.sub([2]) # (wcs[i] -> wcs.sub([i+1]) return self.slice(item) @property def axis_type_names(self): """ World names for each coordinate axis Returns ------- A list of names along each axis """ names = list(self.wcs.cname) types = self.wcs.ctype for i in range(len(names)): if len(names[i]) > 0: continue names[i] = types[i].split('-')[0] return names def __WCS_unpickle__(cls, dct, fits_data): """ Unpickles a WCS object from a serialized FITS string. """ self = cls.__new__(cls) self.__dict__.update(dct) buffer = io.BytesIO(fits_data) hdulist = fits.open(buffer) WCS.__init__(self, hdulist[0].header, hdulist) return self def find_all_wcs(header, relax=True, keysel=None, fix=True, translate_units='', _do_set=True): """ Find all the WCS transformations in the given header. Parameters ---------- header : str or astropy.io.fits header object. relax : bool or int, optional Degree of permissiveness: - `True` (default): Admit all recognized informal extensions of the WCS standard. - `False`: Recognize only FITS keywords defined by the published WCS standard. - `int`: a bit field selecting specific extensions to accept. See :ref:`relaxread` for details. keysel : sequence of flags, optional A list of flags used to select the keyword types considered by wcslib. When ``None``, only the standard image header keywords are considered (and the underlying wcspih() C function is called). To use binary table image array or pixel list keywords, *keysel* must be set. Each element in the list should be one of the following strings: - 'image': Image header keywords - 'binary': Binary table image array keywords - 'pixel': Pixel list keywords Keywords such as ``EQUIna`` or ``RFRQna`` that are common to binary table image arrays and pixel lists (including ``WCSNna`` and ``TWCSna``) are selected by both 'binary' and 'pixel'. fix : bool, optional When `True` (default), call `~astropy.wcs.Wcsprm.fix` on the resulting objects to fix any non-standard uses in the header. `FITSFixedWarning` warnings will be emitted if any changes were made. translate_units : str, optional Specify which potentially unsafe translations of non-standard unit strings to perform. By default, performs none. See `WCS.fix` for more information about this parameter. Only effective when ``fix`` is `True`. Returns ------- wcses : list of `WCS` objects """ if isinstance(header, (six.text_type, six.binary_type)): header_string = header elif isinstance(header, fits.Header): header_string = header.tostring() else: raise TypeError( "header must be a string or astropy.io.fits.Header object") keysel_flags = _parse_keysel(keysel) if isinstance(header_string, six.text_type): header_bytes = header_string.encode('ascii') else: header_bytes = header_string wcsprms = _wcs.find_all_wcs(header_bytes, relax, keysel_flags) result = [] for wcsprm in wcsprms: subresult = WCS(fix=False, _do_set=False) subresult.wcs = wcsprm result.append(subresult) if fix: subresult.fix(translate_units) if _do_set: subresult.wcs.set() return result def validate(source): """ Prints a WCS validation report for the given FITS file. Parameters ---------- source : str path, readable file-like object or `astropy.io.fits.HDUList` object The FITS file to validate. Returns ------- results : WcsValidateResults instance The result is returned as nested lists. The first level corresponds to the HDUs in the given file. The next level has an entry for each WCS found in that header. The special subclass of list will pretty-print the results as a table when printed. """ class _WcsValidateWcsResult(list): def __init__(self, key): self._key = key def __repr__(self): result = [" WCS key '{0}':".format(self._key or ' ')] if len(self): for entry in self: for i, line in enumerate(entry.splitlines()): if i == 0: initial_indent = ' - ' else: initial_indent = ' ' result.extend( textwrap.wrap( line, initial_indent=initial_indent, subsequent_indent=' ')) else: result.append(" No issues.") return '\n'.join(result) class _WcsValidateHduResult(list): def __init__(self, hdu_index, hdu_name): self._hdu_index = hdu_index self._hdu_name = hdu_name list.__init__(self) def __repr__(self): if len(self): if self._hdu_name: hdu_name = ' ({0})'.format(self._hdu_name) else: hdu_name = '' result = ['HDU {0}{1}:'.format(self._hdu_index, hdu_name)] for wcs in self: result.append(repr(wcs)) return '\n'.join(result) return '' class _WcsValidateResults(list): def __repr__(self): result = [] for hdu in self: content = repr(hdu) if len(content): result.append(content) return '\n\n'.join(result) global __warningregistry__ if isinstance(source, fits.HDUList): hdulist = source else: hdulist = fits.open(source) results = _WcsValidateResults() for i, hdu in enumerate(hdulist): hdu_results = _WcsValidateHduResult(i, hdu.name) results.append(hdu_results) with warnings.catch_warnings(record=True) as warning_lines: wcses = find_all_wcs( hdu.header, relax=True, fix=False, _do_set=False) for wcs in wcses: wcs_results = _WcsValidateWcsResult(wcs.wcs.alt) hdu_results.append(wcs_results) try: del __warningregistry__ except NameError: pass with warnings.catch_warnings(record=True) as warning_lines: warnings.resetwarnings() warnings.simplefilter( "always", FITSFixedWarning, append=True) try: WCS(hdu.header, key=wcs.wcs.alt or ' ', relax=True, fix=True, _do_set=False) except WcsError as e: wcs_results.append(str(e)) wcs_results.extend([str(x.message) for x in warning_lines]) return results