def read_files(FDF_filename, freq_filename):
"""
Read in the files needed for peak fitting. Files assumed to be the standard
outputs of RMsynth3D (and, optionally, RMclean3D). also, freq file.
"""
HDUreal = pf.open(FDF_filename.replace('_tot',
'_real').replace('_im', '_real'),
"readonly",
memmap=True)
head = HDUreal[0].header.copy()
FDFreal = HDUreal[0].data
HDUimag = pf.open(FDF_filename.replace('_tot',
'_im').replace('_real', '_im'),
"readonly",
memmap=True)
FDFimag = HDUimag[0].data
complex_cube = FDFreal + 1j * FDFimag
#Identify Faraday depth axis (assumed to be last one if not explicitly found)
Ndim, FD_axis = find_axes(head)
#Move FD axis to first place in numpy order.
if FD_axis != Ndim:
complex_cube = np.moveaxis(complex_cube, Ndim - FD_axis, 0)
#Remove degenerate axes to prevent problems with later steps.
complex_cube = complex_cube.squeeze()
lam0Sq = head['LAMSQ0']
freqArr_Hz = np.loadtxt(freq_filename, dtype=float)
lambdaSqArr_m2 = np.power(C / freqArr_Hz, 2.0)
phiArr_radm2 = fits_make_lin_axis(head, axis=FD_axis - 1)
HDUfwhm = pf.open(FDF_filename.replace(
'FDF_tot_dirty',
'RMSF_FWHM').replace('FDF_real_dirty', 'RMSF_FWHM').replace(
'FDF_im_dirty',
'RMSF_FWHM').replace('FDF_clean_tot', 'RMSF_FWHM').replace(
'FDF_clean_real', 'RMSF_FWHM').replace('FDF_clean_im',
'RMSF_FWHM'),
"readonly",
memmap=True)
fwhmRMSF = HDUfwhm[0].data.squeeze()
return complex_cube, phiArr_radm2, fwhmRMSF, lambdaSqArr_m2, lam0Sq, head
def run_rmclean(fitsFDF,
fitsRMSF,
cutoff_mJy,
maxIter=1000,
gain=0.1,
prefixOut="",
outDir="",
nBits=32):
"""Run RM-CLEAN on a FDF cube given a RMSF cube."""
# Default data types
dtFloat = "float" + str(nBits)
dtComplex = "complex" + str(2 * nBits)
# Read the FDF
HDULst = pf.open(fitsFDF, "readonly", memmap=True)
head = HDULst[0].header.copy()
FDFreal = HDULst[0].data
FDFimag = HDULst[1].data
dirtyFDF = FDFreal + 1j * FDFimag
phiArr_radm2 = fits_make_lin_axis(HDULst[0].header, axis=2, dtype=dtFloat)
# Read the RMSF
HDULst = pf.open(fitsRMSF, "readonly", memmap=True)
RMSFreal = HDULst[0].data
RMSFimag = HDULst[1].data
fwhmRMSFArr = HDULst[3].data
RMSFArr = RMSFreal + 1j * RMSFimag
phi2Arr_radm2 = fits_make_lin_axis(HDULst[0].header, axis=2, dtype=dtFloat)
startTime = time.time()
# Do the clean
cleanFDF, ccArr, iterCountArr = \
do_rmclean_hogbom(dirtyFDF = dirtyFDF * 1e3,
phiArr_radm2 = phiArr_radm2,
RMSFArr = RMSFArr,
phi2Arr_radm2 = phi2Arr_radm2,
fwhmRMSFArr = fwhmRMSFArr,
cutoff = cutoff_mJy,
maxIter = maxIter,
gain = gain,
verbose = True,
doPlots = False)
cleanFDF /= 1e3
ccArr /= 1e3
endTime = time.time()
cputime = (endTime - startTime)
print "> RM-clean completed in %.2f seconds." % cputime
print "Saving the clean FDF and ancillary FITS files"
# Save the clean FDF
fitsFileOut = outDir + "/" + prefixOut + "FDF_clean.fits"
print "> %s" % fitsFileOut
hdu0 = pf.PrimaryHDU(cleanFDF.real.astype(dtFloat), head)
hdu1 = pf.ImageHDU(cleanFDF.imag.astype(dtFloat), head)
hdu2 = pf.ImageHDU(np.abs(cleanFDF).astype(dtFloat), head)
hdu3 = pf.ImageHDU(ccArr.astype(dtFloat), head)
hduLst = pf.HDUList([hdu0, hdu1, hdu2, hdu3])
hduLst.writeto(fitsFileOut, output_verify="fix", clobber=True)
hduLst.close()
# Save the iteration count mask
fitsFileOut = outDir + "/" + prefixOut + "CLEAN_nIter.fits"
print "> %s" % fitsFileOut
head["BUNIT"] = "Iterations"
hdu0 = pf.PrimaryHDU(iterCountArr.astype(dtFloat), head)
hduLst = pf.HDUList([hdu0])
hduLst.writeto(fitsFileOut, output_verify="fix", clobber=True)
hduLst.close()
def run_rmclean(fitsFDF,
fitsRMSF,
cutoff_mJy,
maxIter=1000,
gain=0.1,
prefixOut="",
outDir="",
nBits=32,
write_separate_FDF=False,
verbose=True,
log=print):
"""Run RM-CLEAN on a FDF cube given a RMSF cube."""
# Default data types
dtFloat = "float" + str(nBits)
dtComplex = "complex" + str(2 * nBits)
# Read the FDF
dirtyFDF, head, FD_axis = read_FDF_cube(fitsFDF)
phiArr_radm2 = fits_make_lin_axis(head, axis=FD_axis - 1, dtype=dtFloat)
# Read the RMSF
RMSFArr, headRMSF, FD_axis = read_FDF_cube(fitsRMSF)
HDULst = pf.open(fitsRMSF, "readonly", memmap=True)
fwhmRMSFArr = HDULst[3].data
HDULst.close()
phi2Arr_radm2 = fits_make_lin_axis(headRMSF,
axis=FD_axis - 1,
dtype=dtFloat)
startTime = time.time()
# Do the clean
cleanFDF, ccArr, iterCountArr = \
do_rmclean_hogbom(dirtyFDF = dirtyFDF * 1e3,
phiArr_radm2 = phiArr_radm2,
RMSFArr = RMSFArr,
phi2Arr_radm2 = phi2Arr_radm2,
fwhmRMSFArr = fwhmRMSFArr,
cutoff = cutoff_mJy,
maxIter = maxIter,
gain = gain,
verbose = verbose,
doPlots = False)
cleanFDF /= 1e3
ccArr /= 1e3
endTime = time.time()
cputime = (endTime - startTime)
if (verbose): log("> RM-clean completed in %.2f seconds." % cputime)
if (verbose): log("Saving the clean FDF and ancillary FITS files")
if outDir == '': #To prevent code breaking if file is in current directory
outDir = '.'
#Move FD axis back to original position:
Ndim = head['NAXIS']
cleanFDF = np.moveaxis(cleanFDF, 0, Ndim - FD_axis)
ccArr = np.moveaxis(ccArr, 0, Ndim - FD_axis)
# Save the clean FDF
if not write_separate_FDF:
fitsFileOut = outDir + "/" + prefixOut + "FDF_clean.fits"
if (verbose): log("> %s" % fitsFileOut)
hdu0 = pf.PrimaryHDU(cleanFDF.real.astype(dtFloat), head)
hdu1 = pf.ImageHDU(cleanFDF.imag.astype(dtFloat), head)
hdu2 = pf.ImageHDU(np.abs(cleanFDF).astype(dtFloat), head)
hduLst = pf.HDUList([hdu0, hdu1, hdu2])
hduLst.writeto(fitsFileOut, output_verify="fix", overwrite=True)
hduLst.close()
else:
hdu0 = pf.PrimaryHDU(cleanFDF.real.astype(dtFloat), head)
fitsFileOut = outDir + "/" + prefixOut + "FDF_clean_real.fits"
hdu0.writeto(fitsFileOut, output_verify="fix", overwrite=True)
if (verbose): log("> %s" % fitsFileOut)
hdu1 = pf.PrimaryHDU(cleanFDF.imag.astype(dtFloat), head)
fitsFileOut = outDir + "/" + prefixOut + "FDF_clean_im.fits"
hdu1.writeto(fitsFileOut, output_verify="fix", overwrite=True)
if (verbose): log("> %s" % fitsFileOut)
hdu2 = pf.PrimaryHDU(np.abs(cleanFDF).astype(dtFloat), head)
fitsFileOut = outDir + "/" + prefixOut + "FDF_clean_tot.fits"
hdu2.writeto(fitsFileOut, output_verify="fix", overwrite=True)
if (verbose): log("> %s" % fitsFileOut)
if not write_separate_FDF:
#Save the complex clean components as another file.
fitsFileOut = outDir + "/" + prefixOut + "FDF_CC.fits"
if (verbose): log("> %s" % fitsFileOut)
hdu0 = pf.PrimaryHDU(ccArr.real.astype(dtFloat), head)
hdu1 = pf.ImageHDU(ccArr.imag.astype(dtFloat), head)
hdu2 = pf.ImageHDU(np.abs(ccArr).astype(dtFloat), head)
hduLst = pf.HDUList([hdu0, hdu1, hdu2])
hduLst.writeto(fitsFileOut, output_verify="fix", overwrite=True)
hduLst.close()
else:
hdu0 = pf.PrimaryHDU(ccArr.real.astype(dtFloat), head)
fitsFileOut = outDir + "/" + prefixOut + "FDF_CC_real.fits"
hdu0.writeto(fitsFileOut, output_verify="fix", overwrite=True)
if (verbose): log("> %s" % fitsFileOut)
hdu1 = pf.PrimaryHDU(ccArr.imag.astype(dtFloat), head)
fitsFileOut = outDir + "/" + prefixOut + "FDF_CC_im.fits"
hdu1.writeto(fitsFileOut, output_verify="fix", overwrite=True)
if (verbose): log("> %s" % fitsFileOut)
hdu2 = pf.PrimaryHDU(np.abs(ccArr).astype(dtFloat), head)
fitsFileOut = outDir + "/" + prefixOut + "FDF_CC_tot.fits"
hdu2.writeto(fitsFileOut, output_verify="fix", overwrite=True)
if (verbose): log("> %s" % fitsFileOut)
# Save the iteration count mask
fitsFileOut = outDir + "/" + prefixOut + "CLEAN_nIter.fits"
if (verbose): log("> %s" % fitsFileOut)
head["BUNIT"] = "Iterations"
hdu0 = pf.PrimaryHDU(iterCountArr.astype(dtFloat), head)
hduLst = pf.HDUList([hdu0])
hduLst.writeto(fitsFileOut, output_verify="fix", overwrite=True)
hduLst.close()
def run_rmclean(fitsFDF,
fitsRMSF,
cutoff,
maxIter=1000,
gain=0.1,
nBits=32,
pool=None,
chunksize=None,
verbose=True,
log=print):
"""Run RM-CLEAN on a 2/3D FDF cube given an RMSF cube stored as FITS.
If you want to run RM-CLEAN on arrays, just use util_RM.do_rmclean_hogbom.
Args:
fitsFDF (str): Name of FDF FITS file.
fitsRMSF (str): Name of RMSF FITS file
cutoff (float): CLEAN cutoff in flux units
Kwargs:
maxIter (int): Maximum number of CLEAN iterations per pixel.
gain (float): CLEAN loop gain.
nBits (int): Precision of floating point numbers.
pool (multiprocessing Pool): Pool function from multiprocessing
or schwimmbad
chunksize (int): Number of chunks which it submits to the process pool
as separate tasks. The (approximate) size of these chunks can be
specified by setting chunksize to a positive integer.
verbose (bool): Verbosity.
log (function): Which logging function to use.
Returns:
cleanFDF (ndarray): Cube of RMCLEANed FDFs.
ccArr (ndarray): Cube of RMCLEAN components (i.e. the model).
iterCountArr (ndarray): Cube of number of RMCLEAN iterations.
residFDF (ndarray): Cube of residual RMCLEANed FDFs.
head (fits.header): Header of FDF FITS file for template.
"""
# Default data types
dtFloat = "float" + str(nBits)
dtComplex = "complex" + str(2 * nBits)
# Read the FDF
dirtyFDF, head, FD_axis = read_FDF_cubes(fitsFDF)
phiArr_radm2 = fits_make_lin_axis(head, axis=FD_axis - 1, dtype=dtFloat)
# Read the RMSF
RMSFArr, headRMSF, FD_axis = read_FDF_cubes(fitsRMSF)
HDULst = pf.open(fitsRMSF.replace('_real', '_FWHM').replace(
'_im', '_FWHM').replace('_tot', '_FWHM'),
"readonly",
memmap=True)
fwhmRMSFArr = np.squeeze(HDULst[0].data)
HDULst.close()
phi2Arr_radm2 = fits_make_lin_axis(headRMSF,
axis=FD_axis - 1,
dtype=dtFloat)
startTime = time.time()
# Do the clean
cleanFDF, ccArr, iterCountArr, residFDF = \
do_rmclean_hogbom(dirtyFDF = dirtyFDF,
phiArr_radm2 = phiArr_radm2,
RMSFArr = RMSFArr,
phi2Arr_radm2 = phi2Arr_radm2,
fwhmRMSFArr = fwhmRMSFArr,
cutoff = cutoff,
maxIter = maxIter,
gain = gain,
verbose = verbose,
doPlots = False,
pool = pool,
chunksize = chunksize)
endTime = time.time()
cputime = (endTime - startTime)
if (verbose): log("> RM-clean completed in %.2f seconds." % cputime)
if (verbose): log("Saving the clean FDF and ancillary FITS files")
#Move FD axis back to original position:
Ndim = cleanFDF.ndim
cleanFDF = np.moveaxis(cleanFDF, 0, Ndim - FD_axis)
ccArr = np.moveaxis(ccArr, 0, Ndim - FD_axis)
return cleanFDF, ccArr, iterCountArr, residFDF, head