Source code for image.image

from import fits
import numpy as np
import logging
from datetime import date

log = logging.getLogger('main')

[docs]class Image: """ Image is the basic class for raw and partially reduced CHARIS data. It must have at least the following boolean attribute references: self.destriped (default False) self.flatfielded (default False) It must have at least the following other attribute references: (default None) self.ivar (default None) self.header (default None), self.ivar, and self.header should be numpy ndarrays, which can be read from and written to a fits file with the load and write methods. If not ndarrays, they should be None. Image may be initialized with the name of the raw file to read, through a call to Image.load(). """ def __init__(self, filename='', data=None, ivar=None, chisq=None, header=fits.PrimaryHDU().header, extrahead=None, reads=None, flags=None): ''' Image initialization Parameters ---------- filename: string Name of input file data: ndarray Numpy ndarray containing your data. Can be multi-dimensional. ivar: ndarray Numpy ndarray containing the inverse variance of the data. Should be same shape as data chisq: ndarray Numpy ndarray containing chisq value for each ramp fit to the data. Should be same shape as data header: `PrimaryHDU` header Empty header instance extraheader: `PrimaryHDU` header Placeholder for header from original ramp reads: ndarray flags: ndarray ''' = data self.ivar = ivar self.chisq = chisq self.header = header self.reads = reads self.flags = flags self.filename = filename self.extrahead = extrahead if data is None and filename != '': self.load(filename)
[docs] def load(self, filename, loadbadpixmap=False): """ Image.load(outfilename) Read the first HDU with data from filename into, and HDU[0].header into self.header. If there is more than one HDU with data, attempt to read the second HDU with data into self.ivar. Parameters ---------- filename: string Name of input file loadbadpixmap: boolean When True, loads the bad pixel map at `calibrations/mask.fits` """ try: self.filename = filename hdulist = self.header = hdulist[0].header if hdulist[0].data is not None: i_data = 0 else: i_data = 1 = hdulist[i_data].data"Read data from HDU " + str(i_data) + " of " + filename) if len(hdulist) > i_data + 1: self.ivar = hdulist[i_data + 1].data if self.ivar.shape != log.error("Error: data (HDU " + str(i_data) +\ ") and inverse variance (HDU " + str(i_data +\ 1) + ") have different shapes in file " + filename) self.ivar = None else:"Read inverse variance from HDU " + str(i_data + 1) + " of " + filename) elif loadbadpixmap: self.ivar ='calibrations/mask.fits')[0].data else: self.ivar = None except: log.error("Unable to read data and header from " + filename) = None self.header = None self.ivar = None
[docs] def write(self, filename, clobber=True): """ Image.write(outfilename, clobber=True) Creates a primary HDU using and self.header, and attempts to write to outfilename. If self.ivar is not None, append self.ivar as a second HDU before writing to a file. clobber is provided as a keyword to fits.HDUList.writeto. Parameters ---------- filename: string Name of destination file clobber: boolean When True, overwrites if file already exists """ hdr = fits.PrimaryHDU().header today = yyyymmdd = '%d%02d%02d' % (today[0], today[1], today[2]) hdr['date'] = (yyyymmdd, 'File creation date (yyyymmdd)') for i, key in enumerate(self.header): hdr.append((key, self.header[i], self.header.comments[i]), end=True) out = fits.HDUList(fits.PrimaryHDU(None, hdr)) out.append(fits.PrimaryHDU(,hdr)) if self.ivar is not None: out.append(fits.PrimaryHDU(self.ivar.astype(np.float32),hdr)) if self.chisq is not None: out.append(fits.PrimaryHDU(self.chisq.astype(np.float32),hdr)) if self.flags is not None: out.append(fits.PrimaryHDU(self.flags),hdr) if self.extrahead is not None: try: out.append(fits.PrimaryHDU(None, self.extrahead)) except: log.warn("Extra header in image class must be a FITS header.") try: out.writeto(filename, clobber=clobber)"Writing data to " + filename) except: log.error("Unable to write FITS file " + filename)