我们从Python开源项目中，提取了以下11个代码示例，用于说明如何使用astropy.io.fits.writeto()。
def save_image(imager, grid_data, grid_norm, output_file): """Makes an image from gridded visibilities and saves it to a FITS file. Args: imager (oskar.Imager): Handle to configured imager. grid_data (numpy.ndarray): Final visibility grid. grid_norm (float): Grid normalisation to apply. output_file (str): Name of output FITS file to write. """ # Make the image (take the FFT, normalise, and apply grid correction). imager.finalise_plane(grid_data, grid_norm) grid_data = numpy.real(grid_data) # Trim the image if required. border = (imager.plane_size - imager.image_size) // 2 if border > 0: end = border + imager.image_size grid_data = grid_data[border:end, border:end] # Write the FITS file. hdr = fits.header.Header() fits.writeto(output_file, grid_data, hdr, clobber=True)
def export_image_to_fits(im: Image, fitsfile: str = 'imaging.fits'): """ Write an image to fits :param im: Image :param fitsfile: Name of output fits file """ assert isinstance(im, Image), im return fits.writeto(filename=fitsfile, data=im.data, header=im.wcs.to_header(), overwrite=True)
def ds9_arrays(**kwargs): cmd = ['ds9', '-zscale', '-zoom', '4', '-cmap', 'heat'] for name, array in kwargs.items(): # write array to fits fitsfile = 'ds9_'+name+'.fits' fits.writeto(fitsfile, np.array(array).astype(np.float32), clobber=True) # append to command cmd.append(fitsfile) #print 'cmd', cmd result = subprocess.call(cmd) ################################################################################
def savefits(cube, fitsname, **kwargs): logger = getLogger('decode.io.savefits') ### pick up kwargs dropdeg = kwargs.pop('dropdeg', False) ndim = len(cube.dims) ### load yaml FITSINFO = get_data('decode', 'data/fitsinfo.yaml') hdrdata = yaml.load(FITSINFO) ### default header if ndim == 2: header = fits.Header(hdrdata['dcube_2d']) data = cube.values.T elif ndim == 3: if dropdeg: header = fits.Header(hdrdata['dcube_2d']) data = cube.values[:, :, 0].T else: header = fits.Header(hdrdata['dcube_3d']) data = cube.values.T else: raise TypeError(ndim) ### update Header if cube.coordsys == 'AZEL': header.update({'CTYPE1': 'dAZ', 'CTYPE2': 'dEL'}) elif cube.coordsys == 'RADEC': header.update({'OBSRA': float(cube.xref), 'OBSDEC': float(cube.yref)}) else: pass header.update({'CRVAL1': float(cube.x[0]), 'CDELT1': float(cube.x[1] - cube.x[0]), 'CRVAL2': float(cube.y[0]), 'CDELT2': float(cube.y[1] - cube.y[0]), 'DATE': datetime.now(timezone('UTC')).isoformat()}) if (ndim == 3) and (not dropdeg): header.update({'CRVAL3': float(cube.kidid[0])}) fits.writeto(fitsname, data, header, **kwargs) logger.info('{} has been created.'.format(fitsname))
def saveto(self, filepath, tiff16bit=False): filepath = os.path.expanduser(filepath) lowfile = filepath.lower() # 16-bit TIFF file if tiff16bit and lowfile.endswith((".tif",".tiff")): # tiff header as uint16 words lsNX,msNX = split16(self.shape[0]) lsNY,msNY = split16(self.shape[1]) lsBYTES,msBYTES = split16(self.shape[0]*self.shape[1]*6) header = ( \ 0x4949, 42, 8, 0, # 0: TIFF header (little endian) 12, # 8: number of directory entries # (directory entry: tag,type,count,0,value/offset x 2) 256, 4, 1, 0, lsNX, msNX, # 10: ImageWidth, 1 LONG 257, 4, 1, 0, lsNY, msNY, # 22: ImageLength, 1 LONG 258, 3, 3, 0, 158, 0, # 34: BitsPerSample, 3 SHORT (-> offset!) 259, 3, 1, 0, 1, 0, # 46: Compression, 1 SHORT 262, 3, 1, 0, 2, 0, # 58: PhotometricInterpretation, 1 SHORT 273, 4, 1, 0, 180, 0, # 70: StripOffsets, 1 LONG 277, 3, 1, 0, 3, 0, # 82: SamplesPerPixel, 1 SHORT 278, 4, 1, 0, lsNY, msNY, # 94: RowsPerStrip, 1 LONG 279, 4, 1, 0, lsBYTES, msBYTES, # 106: StripByteCounts, 1 LONG 282, 5, 1, 0, 164, 0, # 118: XResolution, 1 RATIONAL (-> offset!) 283, 5, 1, 0, 172, 0, # 130: YResolution, 1 RATIONAL (-> offset!) 296, 3, 1, 0, 2, 0, # 142: ResolutionUnit, 1 SHORT 0, 0, # 154: IFD list terminator 16, 16, 16, # 158: BitsPerSample value 72, 0, 1, 0, # 164: XResolution value 72, 0, 1, 0 ) # 172: YResolution value # 180: Image data out = open(filepath, 'w') out.write(np.array(header,dtype=np.uint16).tostring()) data = self.scaledpixelarray(0,65535.99) out.write(np.flipud(np.rollaxis(data,1)).astype(np.uint16).tostring()) out.close() # standard 8-bit image file elif lowfile.endswith((".bmp",".gif",".jpg",".jpeg",".png",".tif",".tiff",".pdf")): self.ensurepil(invalidate=False) if lowfile.endswith((".jpg",".jpeg")): self.dpil.save(filepath, "JPEG", quality=80) elif lowfile.endswith((".png")): self.dpil.save(filepath, "PNG") elif lowfile.endswith((".tif",".tiff")): self.dpil.save(filepath, "TIFF") elif lowfile.endswith((".pdf")): self.dpil.save(filepath, "PDF") # FITS file elif lowfile.endswith(".fits"): self.ensurearr(invalidate=False) data = np.dstack(( self.darr[:,:,2],self.darr[:,:,1],self.darr[:,:,0] )) if os.path.exists(filepath): os.remove(filepath) # avoid message produced by fits library pyfits.writeto(filepath, data.T, clobber=True) # unsupported type else: raise ValueError("Filepath argument has unsupported filename extension") ## This function plots the image to the current axes in the current matplotlib figure. The image is # resampled to fit the axes. If \em fill is True, the image is stretched to fit the axes in both directions # changing the image aspect ratio if needed. If \em fill is False (the default), the axes aspect ratio # is adjusted so that the image aspect ratio is preserved.
def _fits_writeto(filename, data, header=None, output_verify='exception', clobber=False, checksum=False): """ Create a new FITS file using the supplied data/header. Patched version of pyfits to correctly include provided header Parameters ---------- filename : file path, file object, or file like object File to write to. If opened, must be opened in a writeable binary mode such as 'wb' or 'ab+'. data : array, record array, or groups data object data to write to the new file header : `Header` object, optional the header associated with ``data``. If `None`, a header of the appropriate type is created for the supplied data. This argument is optional. output_verify : str Output verification option. Must be one of ``"fix"``, ``"silentfix"``, ``"ignore"``, ``"warn"``, or ``"exception"``. May also be any combination of ``"fix"`` or ``"silentfix"`` with ``"+ignore"``, ``+warn``, or ``+exception" (e.g. ``"fix+warn"``). See :ref:`verify` for more info. clobber : bool, optional If `True`, and if filename already exists, it will overwrite the file. Default is `False`. checksum : bool, optional If `True`, adds both ``DATASUM`` and ``CHECKSUM`` cards to the headers of all HDU's written to the file """ hdu = pyfits.convenience._makehdu(data, header) hdu.header.update(header.cards) if hdu.is_image and not isinstance(hdu, pyfits.PrimaryHDU): hdu = pyfits.PrimaryHDU(data, header=header) hdu.writeto(filename, clobber=clobber, output_verify=output_verify, checksum=checksum)
def write(self, fname, **kwargs): """ write table into file Parameters ---------- fname: str filename to export the table into .. note:: additional keywords are forwarded to the corresponding libraries :func:`pyfits.writeto` or :func:`pyfits.append` :func:`np.savetxt` """ extension = kwargs.pop('extension', None) if extension is None: extension = fname.split('.')[-1] if (extension == 'csv'): comments = kwargs.pop('comments', '#') delimiter = kwargs.pop('delimiter', ',') commentedHeader = kwargs.pop('commentedHeader', False) hdr = _ascii_generate_header(self, comments=comments, delimiter=delimiter, commentedHeader=commentedHeader) header = kwargs.pop('header', hdr) np.savetxt(fname, self.data, delimiter=delimiter, header=header, comments='', **kwargs) elif (extension in ['txt', 'dat']): comments = kwargs.pop('comments', '#') delimiter = kwargs.pop('delimiter', ' ') commentedHeader = kwargs.pop('commentedHeader', True) hdr = _ascii_generate_header(self, comments=comments, delimiter=delimiter, commentedHeader=commentedHeader) header = kwargs.pop('header', hdr) np.savetxt(fname, self.data, delimiter=delimiter, header=header, comments='', **kwargs) elif (extension == 'fits'): hdr0 = kwargs.pop('header', None) append = kwargs.pop('append', False) hdr = _fits_generate_header(self) if hdr0 is not None: hdr.update(**hdr0) if append: _fits_append(fname, self.data, hdr, **kwargs) else: # patched version to correctly include the header _fits_writeto(fname, self.data, hdr, **kwargs) elif (extension in ('hdf', 'hdf5', 'hd5')): _hdf5_write_data(fname, self.data, header=self.header, units=self._units, comments=self._desc, aliases=self._aliases, **kwargs) else: raise Exception('Format {0:s} not handled'.format(extension))
def remove_conflictive_keywords(path, file_list): """Removes problematic keywords The blue camera has a set of keywords whose comments contain non-ascii characters, in particular the degree symbol. Those keywords are not needed in any stage of the data reduction therefore they are removed. The data will be overwritten with the keywords removed. The user will need to have backups of raw data. Notes: This function solves a problem with old data, new headers are compliant with the headers. Args: path (str): Path to the folder containing the files file_list (list): List of files to remove keywords """ log_ccd.debug('Removing conflictive keywords in Blue Camera Headers') log_ccd.warning('Files will be overwritten') for blue_file in file_list: full_path = os.path.join(path, blue_file) log_ccd.debug('Processing file {:s}'.format(blue_file)) try: data, header = fits.getdata(full_path, header=True, ignore_missing_end=True) keys_to_remove = ['PARAM0', 'PARAM61', 'PARAM62', 'PARAM63', 'NAXIS3'] if data.ndim == 3: header['NAXIS'] = 2 data = data[0] log_ccd.debug('Modified file to be 2D instead of 3D ' '(problematic)') for keyword in keys_to_remove: header.remove(keyword) log_ccd.debug('Removed conflictive keyword ' '{:s}'.format(keyword)) log_ccd.debug('Updated headers') fits.writeto(full_path, data, header, clobber=True) except KeyError as error: log_ccd.debug(error) # spectroscopy specific functions
def fits2ldac (header4ext2, data4ext3, fits_ldac_out, doSort=True): """This function converts the binary FITS table from Astrometry.net to a binary FITS_LDAC table that can be read by PSFex. [header4ext2] is what will be recorded as a single long string in the data part of the 2nd extension of the output table [fits_ldac_out], and [data4ext3] is the data part of an HDU that will define both the header and data parts of extension 3 of [fits_ldac_out]. """ # convert header to single (very) long string ext2_str = header4ext2.tostring(endcard=False, padding=False) # if the following line is not added, the very end of the data # part of extension 2 is written to a fits table such that PSFex # runs into a segmentation fault when attempting to read it (took # me ages to find out!). ext2_str += 'END END' # read into string array ext2_data = np.array([ext2_str]) # determine format string for header of extention 2 formatstr = str(len(ext2_str))+'A' # create table 1 col1 = fits.Column(name='Field Header Card', array=ext2_data, format=formatstr) cols = fits.ColDefs([col1]) ext2 = fits.BinTableHDU.from_columns(cols) # make sure these keywords are in the header ext2.header['EXTNAME'] = 'LDAC_IMHEAD' ext2.header['TDIM1'] = '(80, {0})'.format(len(ext2_str)/80) # simply create extension 3 from [data4ext3] ext3 = fits.BinTableHDU(data4ext3) # extname needs to be as follows ext3.header['EXTNAME'] = 'LDAC_OBJECTS' # sort output table by number column if needed if doSort: index_sort = np.argsort(ext3.data['NUMBER']) ext3.data = ext3.data[index_sort] # create primary HDU prihdr = fits.Header() prihdu = fits.PrimaryHDU(header=prihdr) prihdu.header['EXPTIME'] = header4ext2['EXPTIME'] prihdu.header['FILTNAME'] = header4ext2['FILTNAME'] # prihdu.header['SEEING'] = header4ext2['SEEING'] #need to calculte and add prihdu.header['BKGSIG'] = header4ext2['SEXBKDEV'] # write hdulist to output LDAC fits table hdulist = fits.HDUList([prihdu, ext2, ext3]) hdulist.writeto(fits_ldac_out, clobber=True) hdulist.close() ################################################################################
