def loadFitsCube(self,name_dat, name_err=None, name_var=None, xscale=1, yscale=1, hdu=0):
### Open Fits file
fits = pyfits.open(name_dat)
if hdu==0:
if fits[hdu].data is None:
hdu=1
dat = fits[hdu].data
dim = dat.shape
### Testing whether the data has 3 dimensions, if not raise error
if len(dim)==3:
### Fill all instance variables
self.dataCube = dat
self.header = fits[hdu].header
self.wDim = dim[0]
self.yDim = dim[1]
self.xDim = dim[2]
self.xScale = xscale
self.yScale = yscale
self.crval3 = [self.header['crval3']]
self.cdelt3 = [self.header['cdelt3']]
self.naxis3 = [self.header['naxis3']]
### Create the wavelength array
wave = numpy.zeros(self.wDim,dtype="float32")
for i in range(len(self.naxis3)):
if i == 0:
wave[0:self.naxis3[i]] = numpy.arange(self.naxis3[i])*self.cdelt3[i]+self.crval3[i]
elif i>0:
wave[self.naxis3[i-1]:self.naxis3[i]] = numpy.arange(self.naxis3[i])*self.cdelt3[i]+self.crval3[i]
self.wave = wave
self.empty = False
### Reading corresponding variance frame when given
if not name_err is None:
fits = pyfits.open(name_err)
err = fits[hdu].data
dim_err = err.shape
### Test whether the cube has 3 Dimensions
if len(dim)==3:
self.errCube=err
else:
raise IFUcubeIOError("The Frame is not an IFU cube!")
### Reading corresponding variance frame when given
if name_var is not None:
fits = pyfits.open(name_var)
var = fits[hdu].data
dim_var = var.shape
### Test whether the cube has 3 Dimensions
if len(dim)==3:
self.errCube=numpy.sqrt(var)
else:
raise IFUcubeIOError("The Frame is not an IFU cube")
else:
raise IFUcubeIOError("The Frame is not an IFU cube" )
def extractImageMask(self, mask, mode='sum'):
"""Extract an image from the IFU cube in the given Mask. Available modes are 'sum','median','mean'."""
if mask.shape[0]!=self.wDim:
raise IFUcubeIOError("Mask does not match wavelength dimension" )
if not self.empty:
if mode == 'sum':
image = numpy.sum(self.dataCube[mask, :, :], 0)
elif mode == 'median':
image = numpy.median(self.dataCube[mask, :, :], 0)
elif mode == 'mean':
image = numpy.mean(self.dataCube[mask, :, :],0)
return image
else:
raise IFUcubeIOError("No data in IFU cube object" )
def extractSpecMask(self, mask, mode='sum'):
if not self.empty and self.xDim == mask.shape[1] and self.yDim == mask.shape[0]:
rss = numpy.reshape(self.dataCube, (self.wDim, self.yDim*self.xDim), 'C')
ma_rss = numpy.reshape(mask, (self.yDim*self.xDim), 'c')
if mode == 'sum':
spec = numpy.sum(rss[:, ma_rss], 1)
elif mode == 'median':
spec = numpy.median(rss[:, ma_rss], 1)
elif mode == 'mean':
spec = numpy.mean(rss[:, ma_rss], 1)
return spec
elif not self.empty and (self.xDim != mask.shape[1] or self.yDim != mask.shape[0]):
raise IFUcubeIOError("Cube Operation on a wrong shape")
else:
raise IFUcubeIOError("No data in IFU cube object" )
def loadFitsVarCube(self, name_var, hdu=0):
fits = pyfits.open(name_var)
dat = numpy.sqrt(fits[hdu].data)
hdr = fits[0].header
dim = dat.shape
if dim!=(self.wDim, self.yDim, self.xDim) or [hdr['crval3']]!=self.crval3 or [hdr['cdelt3']]!=self.cdelt3:
raise IFUcubeIOError("This is not a corresponding IFU Variance cube")
else:
self.errCube = dat
def extractImage(self, start_wave, end_wave, mode='sum'):
"""Extract an image from the IFU cube in the given wavelength range. Available modes are 'sum','median','mean'."""
if not self.empty:
selectWave = numpy.logical_and(self.wave>=start_wave, self.wave<=end_wave)
if mode == 'sum':
image = numpy.sum(self.dataCube[selectWave, :, :], 0)
elif mode == 'median':
image = numpy.median(self.dataCube[selectWave, :, :], 0)
elif mode == 'mean':
image = numpy.mean(self.dataCube[selectWave, :, :], 0)
return image
else:
raise IFUcubeIOError("No data in IFU cube object" )
def writeFitsErr(self, nameErr):
if not self.emtpy and len(self.errCube.shape)==3:
hdu = pyfits.PrimaryHDU(self.errCube)
## Update header
if not self.header == []:
hdu.header = self.header
hdu.header.update('crval3', self.crval3[0])
hdu.header.update('cdelt3', self.cdelt3[0])
hdu.header.update('crval2', 0)
hdu.header.update('cdelt2', self.yScale)
hdu.header.update('crval1', 0)
hdu.header.update('cdelt1', self.xScale)
hdu.writeto(nameErr, clobber=True)
else:
raise IFUcubeIOError("The Frame is not an IFU cube" )
def writeFitsData(self, nameDat):
"""Write the current IFU data cube to a FITS file"""
if not self.empty:
hdu = pyfits.PrimaryHDU(self.dataCube)
## Update header
if not self.header == []:
hdu.header = self.header
hdu.header['crval3'] = self.crval3[0]
hdu.header['cdelt3'] = self.cdelt3[0]
hdu.header['crval2'] = 0
hdu.header['cdelt2'] = self.yScale
hdu.header['crval1'] = 0
hdu.header['cdelt1'] = self.xScale
hdu.writeto(nameDat, clobber=True)
else:
raise IFUcubeIOError("The Frame is not an IFU cube" )