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uvutil.py
498 lines (425 loc) · 17.6 KB
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uvutil.py
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"""
2014 January 31
Shane Bussmann
Varius utilities related to operations on uvfits data files.
"""
from __future__ import print_function
import numpy
from astropy.io import fits
def pcdload(visfile):
checker = visfile.find('uvfits')
if checker == -1:
uvfits = False
else:
uvfits = True
if uvfits:
# uv fits format
visdata = fits.open(visfile)
visheader = visdata[0].header
if visheader['NAXIS'] == 7:
# identify the phase center
try:
pcd_ra = visdata['AIPS SU '].data['RAEPO'][0]
pcd_dec = visdata['AIPS SU '].data['DECEPO'][0]
except:
pcd_ra = visheader['CRVAL5']
pcd_dec = visheader['CRVAL6']
if pcd_ra < 0:
pcd_ra += 360
pcd = [pcd_ra, pcd_dec]
return pcd
if visheader['NAXIS'] == 6:
# identify the channel frequency(ies):
pcd_ra = visdata[0].header['CRVAL5']
pcd_dec = visdata[0].header['CRVAL6']
if pcd_ra < 0:
pcd_ra += 360
pcd = [pcd_ra, pcd_dec]
return pcd
else:
# CASA MS
from taskinit import tb
tb.open(visfile + '/SOURCE')
pcd_ra = tb.getcol('DIRECTION')[0][0] * 180 / numpy.pi
if pcd_ra < 0:
pcd_ra += 360
pcd_dec = tb.getcol('DIRECTION')[1][0] * 180 / numpy.pi
tb.close()
pcd = [pcd_ra, pcd_dec]
return pcd
def uvload(visfile):
checker = visfile.find('uvfits')
if checker == -1:
uvfits = False
else:
uvfits = True
if uvfits:
visdata = fits.open(visfile)
visibilities = visdata[0].data
visheader = visdata[0].header
if visheader['NAXIS'] == 7:
# identify the channel frequency(ies):
visfreq = visdata[1].data
freq0 = visheader['CRVAL4']
dfreq = visheader['CDELT4']
cfreq = visheader['CRPIX4']
nvis = visibilities['DATA'][:, 0, 0, 0, 0, 0, 0].size
nspw = visibilities['DATA'][0, 0, 0, :, 0, 0, 0].size
nfreq = visibilities['DATA'][0, 0, 0, 0, :, 0, 0].size
npol = visibilities['DATA'][0, 0, 0, 0, 0, :, 0].size
if nfreq > 1:
uu = numpy.zeros([nvis, nspw, nfreq, npol])
vv = numpy.zeros([nvis, nspw, nfreq, npol])
ww = numpy.zeros([nvis, nspw, nfreq, npol])
else:
uu = numpy.zeros([nvis, nspw, npol])
vv = numpy.zeros([nvis, nspw, npol])
ww = numpy.zeros([nvis, nspw, npol])
#wgt = numpy.zeros([nvis, nspw, nfreq, npol])
for ispw in range(nspw):
if nspw > 1:
freqif = freq0 + visfreq['IF FREQ'][0][ispw]
else:
try:
freqif = freq0 + visfreq['IF FREQ'][0]
except:
freqif = freq0
#uu[:, ispw] = freqif * visibilities['UU']
#vv[:, ispw] = freqif * visibilities['VV']
for ipol in range(npol):
# then compute the spatial frequencies:
if nfreq > 1:
freq = (numpy.arange(nfreq) - cfreq + 1) * dfreq + freqif
freqvis = numpy.meshgrid(freq, visibilities['UU'])
uu[:, ispw, :, ipol] = freqvis[0] * freqvis[1]
freqvis = numpy.meshgrid(freq, visibilities['VV'])
vv[:, ispw, :, ipol] = freqvis[0] * freqvis[1]
freqvis = numpy.meshgrid(freq, visibilities['WW'])
ww[:, ispw, :, ipol] = freqvis[0] * freqvis[1]
else:
uu[:, ispw, ipol] = freqif * visibilities['UU']
vv[:, ispw, ipol] = freqif * visibilities['VV']
ww[:, ispw, ipol] = freqif * visibilities['WW']
if visheader['NAXIS'] == 6:
# identify the channel frequency(ies):
freq0 = visheader['CRVAL4']
dfreq = visheader['CDELT4']
cfreq = visheader['CRPIX4']
nvis = visibilities['DATA'][:, 0, 0, 0, 0, 0].size
nfreq = visibilities['DATA'][0, 0, 0, :, 0, 0].size
npol = visibilities['DATA'][0, 0, 0, 0, :, 0].size
if nfreq > 1:
uu = numpy.zeros([nvis, nfreq, npol])
vv = numpy.zeros([nvis, nfreq, npol])
ww = numpy.zeros([nvis, nfreq, npol])
else:
uu = numpy.zeros([nvis, npol])
vv = numpy.zeros([nvis, npol])
ww = numpy.zeros([nvis, npol])
#wgt = numpy.zeros([nvis, nspw, nfreq, npol])
freqif = freq0
#uu[:, ispw] = freqif * visibilities['UU']
#vv[:, ispw] = freqif * visibilities['VV']
for ipol in range(npol):
# then compute the spatial frequencies:
if nfreq > 1:
freq = (numpy.arange(nfreq) - cfreq + 1) * dfreq + freqif
freqvis = numpy.meshgrid(freq, visibilities['UU'])
uu[:, 0, :, ipol] = freqvis[0] * freqvis[1]
freqvis = numpy.meshgrid(freq, visibilities['VV'])
vv[:, 0, :, ipol] = freqvis[0] * freqvis[1]
freqvis = numpy.meshgrid(freq, visibilities['WW'])
ww[:, 0, :, ipol] = freqvis[0] * freqvis[1]
else:
uu[:, ipol] = freqif * visibilities['UU']
vv[:, ipol] = freqif * visibilities['VV']
ww[:, ipol] = freqif * visibilities['WW']
else:
from taskinit import tb
# read in the uvfits data
tb.open(visfile)
uvw = tb.getcol('UVW')
uvspw = tb.getcol('DATA_DESC_ID')
tb.close()
tb.open(visfile + '/SPECTRAL_WINDOW')
freq = tb.getcol('CHAN_FREQ')
tb.close()
tb.open(visfile + '/POLARIZATION')
polinfo = tb.getcol('NUM_CORR')
tb.close()
npol = polinfo[0]
nspw = len(freq[0])
for ispw in range(nspw):
ilam = 3e8 / freq[0][ispw]
indx_spw = uvspw == ispw
uvw[:, indx_spw] /= ilam
uu = []
vv = []
ww = []
for ipol in range(npol):
uu.append(uvw[0, :])
vv.append(uvw[1, :])
ww.append(uvw[2, :])
uu = numpy.array(uu)
vv = numpy.array(vv)
ww = numpy.array(ww)
if uu[:, 0].size == 1:
uu = uu.flatten()
vv = vv.flatten()
ww = ww.flatten()
return uu, vv, ww
def visload(visfile):
checker = visfile.find('uvfits')
if checker == -1:
uvfits = False
else:
uvfits = True
if uvfits:
visdata = fits.open(visfile)
# get the telescope name
visheader = visdata[0].header
#telescop = visheader['TELESCOP']
# if we are dealing with SMA data
if visheader['NAXIS'] == 6:
nfreq = visdata[0].data['DATA'][0, 0, 0, :, 0, 0].size
if nfreq > 1:
data_real = visdata[0].data['DATA'][:,0,0,:,:,0]
data_imag = visdata[0].data['DATA'][:,0,0,:,:,1]
data_wgt = visdata[0].data['DATA'][:,0,0,:,:,2]
else:
data_real = visdata[0].data['DATA'][:,0,0,0,:,0]
data_imag = visdata[0].data['DATA'][:,0,0,0,:,1]
data_wgt = visdata[0].data['DATA'][:,0,0,0,:,2]
# if we are dealing with ALMA or PdBI data
if visheader['NAXIS'] == 7:
nfreq = visdata[0].data['DATA'][0, 0, 0, 0, :, 0, 0].size
if nfreq > 1:
data_real = visdata[0].data['DATA'][:,0,0,:,:,:,0]
data_imag = visdata[0].data['DATA'][:,0,0,:,:,:,1]
data_wgt = visdata[0].data['DATA'][:,0,0,:,:,:,2]
else:
data_real = visdata[0].data['DATA'][:,0,0,:,0,:,0]
data_imag = visdata[0].data['DATA'][:,0,0,:,0,:,1]
data_wgt = visdata[0].data['DATA'][:,0,0,:,0,:,2]
data_complex = numpy.array(data_real) + \
1j * numpy.array(data_imag)
else:
from taskinit import tb
# read in the CASA MS
tb.open(visfile)
vis_complex = tb.getcol('DATA')
vis_weight = tb.getcol('WEIGHT')
tb.close()
#tb.open(visfile + '/POLARIZATION')
#polinfo = tb.getcol('NUM_CORR')
#npol = polinfo[0]
data_complex = vis_complex
data_wgt = vis_weight
wgtshape = data_wgt.shape
if len(wgtshape) == 2:
npol = wgtshape[0]
nrow = wgtshape[1]
wgtshape = (npol, 1, nrow)
data_wgt = data_wgt.reshape(wgtshape)
#data_complex = []
#data_wgt = []
#for ipol in range(npol):
# data_complex.append(vis_complex[ipol, 0, :])
# data_wgt.append(vis_weight[ipol, :])
#data_complex = numpy.array(data_complex)
#data_wgt = numpy.array(data_wgt)
return data_complex, data_wgt
def getStatWgt(real_raw, imag_raw, wgt_raw):
"""
Compute the weights as the rms scatter in the real and imaginary
visibilities.
"""
nvis = real_raw[:, 0].size
freqsize = real_raw[0, :].size
wgt_scaled = numpy.zeros([nvis, freqsize])
for i in range(nvis):
gwgt = wgt_raw[i, :] > 0
ngwgt = wgt_raw[i, gwgt].size
if ngwgt > 2:
reali = real_raw[i, gwgt]
imagi = imag_raw[i, gwgt]
rms_real = numpy.std(reali)
rms_imag = numpy.std(imagi)
rms_avg = (rms_real + rms_imag) / 2.
wgt_scaled[i, :] = 1 / rms_avg ** 2
return wgt_scaled
def statwt(visfileloc, newvisfileloc, ExcludeChannels=False):
"""
Replace the weights in 'visfile' with weights computed via getStatWgt.
"""
visfile = fits.open(visfileloc)
data_complex, data_wgt = visload(visfileloc)
data_real = numpy.real(data_complex)
data_imag = numpy.imag(data_complex)
wgt_original = data_wgt.copy()
if ExcludeChannels:
nwindows = len(ExcludeChannels) / 2
for win in range(0, nwindows * 2, 2):
chan1 = ExcludeChannels[win]
chan2 = ExcludeChannels[win + 1]
if data_real.ndim == 4:
data_wgt[:, :, chan1:chan2, :] = 0
else:
data_wgt[:, chan1:chan2, :] = 0
# get the number of visibilities, spws, frequencies, polarizations
if data_real.ndim == 4:
nvis = data_real[:, 0, 0, 0].size
nspw = data_real[0, :, 0, 0].size
nfreq = data_real[0, 0, :, 0].size
npol = data_real[0, 0, 0, :].size
wgt = numpy.zeros([nvis, nspw, nfreq, npol])
if data_real.ndim == 3:
nvis = data_real[:, 0, 0].size
nspw = 0
nfreq = data_real[0, :, 0].size
npol = data_real[0, 0, :].size
wgt = numpy.zeros([nvis, nfreq, npol])
if nspw > 0:
for ispw in range(nspw):
for ipol in range(npol):
# compute real and imaginary components of the visibilities
real_raw = data_real[:, ispw, :, ipol]
imag_raw = data_imag[:, ispw, :, ipol]
wgt_raw = data_wgt[:, ispw, :, ipol]
wgt_orig = wgt_original[:, ispw, :, ipol]
oktoreplace = wgt_orig > 0
wgt_scaled = getStatWgt(real_raw, imag_raw, wgt_raw)
wgt_temp = wgt[:, ispw, :, ipol]
wgt_temp[oktoreplace] = wgt_scaled[oktoreplace]
wgt[:, ispw, :, ipol] = wgt_temp
visfile[0].data['DATA'][:, 0, 0, :, :, :, 2] = wgt
else:
for ipol in range(npol):
# compute real and imaginary components of the visibilities
real_raw = data_real[:, :, ipol]
imag_raw = data_imag[:, :, ipol]
wgt_raw = data_wgt[:, :, ipol]
wgt_scaled = getStatWgt(real_raw, imag_raw, wgt_raw)
wgt[:, :, ipol] = wgt_scaled
visfile[0].data['DATA'][:, 0, 0, :, :, 2] = wgt
visfile.writeto(newvisfileloc)
return
def scalewt(visdataloc, newvisdataloc):
visfile = fits.open(visdataloc)
data_complex, data_wgt = visload(visdataloc)
data_real = numpy.real(data_complex)
data_imag = numpy.imag(data_complex)
# scale the weights such that:
# Sum(wgt * real^2 + wgt * imag^2) = N_visibilities
wgt_scaled = data_wgt
wgzero = wgt_scaled > 0
N_vis = 2 * wgt_scaled[wgzero].size
wgtrealimag = wgt_scaled * (data_real ** 2 + data_imag ** 2)
wgtsum = wgtrealimag[wgzero].sum()
wgtscale = N_vis / wgtsum
print("Scaling the weights by a factor of ", wgtscale)
wgt_scaled = wgt_scaled * wgtscale
# read in the uvfits data
if data_real.ndim == 4:
visfile[0].data['DATA'][:, 0, 0, :, :, :, 2] = wgt_scaled
else:
if visfile[0].header['NAXIS'] == 6:
visfile[0].data['DATA'][:, 0, 0, :, :, 2] = wgt_scaled
if visfile[0].header['NAXIS'] == 7:
visfile[0].data['DATA'][:, 0, 0, 0, :, :, 2] = wgt_scaled
visfile.writeto(newvisdataloc, clobber=True)
def zerowt(visdataloc, newvisdataloc, ExcludeChannels):
visfile = fits.open(visdataloc)
data_real, data_imag, data_wgt = visload(visfile)
nwindows = len(ExcludeChannels) / 2
for win in range(0, nwindows * 2, 2):
chan1 = ExcludeChannels[win]
chan2 = ExcludeChannels[win + 1]
if data_real.ndim == 4:
visfile[0].data['DATA'][:, 0, 0, :, chan1:chan2, :, 2] = 0.0
else:
visfile[0].data['DATA'][:, 0, 0, chan1:chan2, :, 2] = 0.0
visfile.writeto(newvisdataloc)
# AS OF 2014-02-24, spectralavg IS NON-FUNCTIONAL
def spectralavg(visdataloc, newvisdataloc, Nchannels):
# bin in frequency space to user's desired spectral resolution
vis_data = fits.open(visdataloc)
data_real, data_imag, data_wgt = visload(vis_data)
# get the number of visibilities, spws, frequencies, polarizations
if data_real.ndim == 4:
nvis = data_real[:, 0, 0, 0].size
nspw = data_real[0, :, 0, 0].size
nchan = data_real[0, 0, :, 0].size
npol = data_real[0, 0, 0, :].size
real_bin = numpy.zeros([nvis, nspw, Nchannels, npol])
imag_bin = numpy.zeros([nvis, nspw, Nchannels, npol])
wgt_bin = numpy.zeros([nvis, nspw, Nchannels, npol])
if data_real.ndim == 3:
nvis = data_real[:, 0, 0].size
nspw = 0
nchan = data_real[0, :, 0].size
npol = data_real[0, 0, :].size
real_bin = numpy.zeros([nvis, Nchannels, npol])
imag_bin = numpy.zeros([nvis, Nchannels, npol])
wgt_bin = numpy.zeros([nvis, Nchannels, npol])
chan1 = 0
dchan = nchan / Nchannels
chan2 = chan1 + dchan
if nspw > 1:
for ispw in range(nspw):
for ipol in range(npol):
for ichan in range(Nchannels):
for i in range(nvis):
gwgt = data_wgt[i, ispw, chan1:chan2, ipol] > 0
ngwgt = data_wgt[i, ispw, gwgt, ipol].size
if ngwgt == 0:
continue
value = data_real[i, ispw, gwgt, ipol].sum() / ngwgt
real_bin[i, ispw, ichan, ipol] = value
value = data_imag[i, ispw, gwgt, ipol].sum() / ngwgt
imag_bin[i, ispw, ichan, ipol] = value
value = data_wgt[i, ispw, gwgt, ipol].mean() * ngwgt
wgt_bin[i, ispw, ichan, ipol] = value
chan1 = chan2
chan2 = chan1 + dchan
newvis = numpy.zeros([nvis, 1, 1, nspw, Nchannels, npol, 3])
newvis[:, 0, 0, :, :, :, 0] = real_bin
newvis[:, 0, 0, :, :, :, 1] = imag_bin
newvis[:, 0, 0, :, :, :, 2] = wgt_bin
oldcrpix4 = vis_data[0].header['CRPIX4']
newcrpix4 = numpy.float(oldcrpix4) / nchan * Nchannels
newcrpix4 = numpy.floor(newcrpix4) + 1
vis_data[0].header['CRPIX4'] = newcrpix4
oldcdelt4 = vis_data[0].header['CDELT4']
newcdelt4 = oldcdelt4 * nchan / Nchannels
vis_data[0].header['CDELT4'] = newcdelt4
else:
for ipol in range(npol):
for ichan in range(Nchannels):
for i in range(nvis):
gwgt = data_wgt[i, chan1:chan2, ipol] > 0
ngwgt = data_wgt[i, gwgt, ipol].size
if ngwgt == 0:
continue
value = data_real[i, gwgt, ipol].sum() / ngwgt
real_bin[i, ichan, ipol] = value
value = data_imag[i, gwgt, ipol].sum() / ngwgt
imag_bin[i, ichan, ipol] = value
value = data_wgt[i, gwgt, ipol].mean() * ngwgt
wgt_bin[i, ichan, ipol] = value
chan1 = chan2
chan2 = chan1 + dchan
newvis = numpy.zeros([nvis, 1, 1, Nchannels, npol, 3])
newvis[:, 0, 0, :, :, 0] = real_bin
newvis[:, 0, 0, :, :, 1] = imag_bin
newvis[:, 0, 0, :, :, 2] = wgt_bin
oldcrpix4 = vis_data[0].header['CRPIX4']
newcrpix4 = numpy.float(oldcrpix4) / nchan * Nchannels
newcrpix4 = numpy.floor(newcrpix4) + 1
vis_data[0].header['CRPIX4'] = newcrpix4
vis_data[0].header['NAXIS4'] = Nchannels
oldcdelt4 = vis_data[0].header['CDELT4']
newcdelt4 = oldcdelt4 * nchan / Nchannels
vis_data[0].header['CDELT4'] = newcdelt4
vis_data[0].data['DATA'][:] = newvis
vis_data.writeto(newvisdataloc)