def test_readAndParseTbuff(self): '''flaghelper: compare the read and parse and apply tbuff''' print '' # MJD in seconds of timeranges are these # <startTime>4891227930515540000 <endTime>4891227932453838000 # <startTime>4891228473545856000 <endTime>4891228473731891000 # <startTime>4891226924455911000 <endTime>4891226927502314000 # <startTime>4891228838164987000 <endTime>4891228838418996000 # <startTime>4891228609440808000 <endTime>4891228612489617000 online = ["antenna='DV03&&*' timerange='2013/11/15/10:25:30.516~2013/11/15/10:25:32.454'", "antenna='DA44&&*' timerange='2013/11/15/10:34:33.546~2013/11/15/10:34:33.732'", "antenna='DA46&&*' timerange='2013/11/15/10:08:44.456~2013/11/15/10:08:47.502'", "antenna='DV09&&*' timerange='2013/11/15/10:18:11.798~2013/11/15/10:18:13.837'", "antenna='DV05&&*' timerange='2013/11/15/10:40:38.165~2013/11/15/10:40:38.419'"] myinput = "antenna='DV03&&*' timerange='2013/11/15/10:25:30.516~2013/11/15/10:25:32.454'\n"\ "antenna='DA44&&*' timerange='2013/11/15/10:34:33.546~2013/11/15/10:34:33.732'\n"\ "antenna='DA46&&*' timerange='2013/11/15/10:08:44.456~2013/11/15/10:08:47.502'\n"\ "antenna='DV09&&*' timerange='2013/11/15/10:18:11.798~2013/11/15/10:18:13.837'\n"\ "antenna='DV05&&*' timerange='2013/11/15/10:40:38.165~2013/11/15/10:40:38.419'" filename1 = 'flaghelperonline2.txt' create_input(myinput, filename1) # First timerange from online before padding origt = timerange='2013/11/15/10:25:30.516~2013/11/15/10:25:32.454' # Apply tbuff to timeranges timebuffer = 1.1 dlist1 = fh.readAndParse([filename1], tbuff=timebuffer) self.assertEqual(len(dlist1), 5) # Get the first padded timerange from output padt = dlist1[0]['timerange'] # Revert the tbuff application manually t0,t1 = padt.split('~',1) startTime = qa.totime(t0)['value'] startTimeSec = float((startTime * 24 * 3600) + timebuffer) startTimeSec = qa.quantity(startTimeSec, 's') paddedT0 = qa.time(startTimeSec,form='ymd',prec=9)[0] # end time endTime = qa.totime(t1)['value'] endTimeSec = float((endTime * 24 * 3600) - timebuffer) endTimeSec = qa.quantity(endTimeSec, 's') paddedT1 = qa.time(endTimeSec,form='ymd',prec=9)[0] newtimerange = paddedT0+'~'+paddedT1 # Compare with the original self.assertEqual(origt, newtimerange) # Compare with original values from Flag.xml xmlt0 = float(4891227930515540000) * 1.0E-9 xmlt1 = float(4891227932453838000) * 1.0E-9 self.assertAlmostEqual(xmlt0, startTimeSec['value'], places=3) self.assertAlmostEqual(xmlt1, endTimeSec['value'], places=3)
def time2filename(msfile, timerange='', spw=''): from astropy.time import Time tb.open(msfile) starttim = Time(tb.getcell('TIME', 0) / 24. / 3600., format='mjd') endtim = Time(tb.getcell('TIME', tb.nrows() - 1) / 24. / 3600., format='mjd') tb.close() datstr = starttim.iso[:10] ms.open(msfile) metadata = ms.metadata() observatory = metadata.observatorynames()[0] ms.close() if timerange is None or timerange == '': starttim1 = starttim endtim1 = endtim else: (tstart, tend) = timerange.split('~') if tstart[2] == ':': starttim1 = Time(datstr + 'T' + tstart) endtim1 = Time(datstr + 'T' + tend) else: starttim1 = Time(qa.quantity(tstart, 'd')['value'], format='mjd') endtim1 = Time(qa.quantity(tend, 'd')['value'], format='mjd') midtime = Time((starttim1.mjd + endtim1.mjd) / 2., format='mjd') tstr = midtime.to_datetime().strftime('{}_%Y%m%dT%H%M%S'.format(observatory)) if spw: spstr = 'spw{}'.format(spw.replace('~', '-')) filename = '.'.join([tstr, spstr]) else: filename = tstr return filename
def randomCoords(imagenames, ncoords=10): import random from taskinit import ia, qa xmin, xmax = [], [] ymin, ymax = [], [] for image in imagenames: ia.open(image) print image, ia.boundingbox() trc = ia.boundingbox()['trcf'].split(', ') blc = ia.boundingbox()['blcf'].split(', ') xmin.append(qa.convert(qa.quantity(trc[0]), 'rad')['value']) xmax.append(qa.convert(qa.quantity(blc[0]), 'rad')['value']) ymin.append(qa.convert(qa.quantity(blc[1]), 'rad')['value']) ymax.append(qa.convert(qa.quantity(trc[1]), 'rad')['value']) ia.done() randomcoords = CoordList(imagenames) for i in range(ncoords): imageid = random.randint(0, len(imagenames) - 1) x = random.uniform(xmin[imageid], xmax[imageid]) y = random.uniform(ymin[imageid], ymax[imageid]) c = Coord(x, y, 1.0) randomcoords.append(c) return randomcoords
def __axis(self, idx, unit): refpix = self.coordsys.referencepixel()['numeric'][idx] refval = self.coordsys.referencevalue()['numeric'][idx] increment = self.coordsys.increment()['numeric'][idx] _unit = self.units[idx] if _unit != unit: refval = qa.convert(qa.quantity(refval,_unit),unit)['value'] increment = qa.convert(qa.quantity(increment,_unit),unit)['value'] #return numpy.array([refval+increment*(i-refpix) for i in xrange(self.nchan)]) return (refpix, refval, increment)
def select(self, rowid=None, rasterid=None): if not ((rowid is None) ^ (rasterid is None)): raise RuntimeError('one of rowid or rasterid must be specified') if (rowid is not None) and (rowid >= self.nrow): raise IndexError('row index %s is out of range (number of rows detected: %s)'%(rowid,self.nrow)) if (rasterid is not None) and (rasterid >= self.nraster): raise IndexError('row index %s is out of range (number of rasters detected: %s)'%(rasterid,self.nraster)) with selection_manager(self.scantab, self.original_selection, types=0, ifs=self.spw, pols=self.pol) as s: alltimes = numpy.array(map(lambda x: qa.quantity(x)['value'], s.get_time(prec=16))) mean_interval = numpy.array(s.get_inttime()).mean() self.margin = 0.1 * mean_interval mjd_margin = self.margin / 86400.0 if rowid is not None: times = alltimes[self.gaplist[rowid]:self.gaplist[rowid+1]] else: times = alltimes[self.gaplist_raster[rasterid]:self.gaplist_raster[rasterid+1]] tmp_mjd_range = (times.min() - mjd_margin, times.max() + mjd_margin,) tmp_mjd_range_nomargin = (times.min(), times.max(),) casalog.post('time range: %s ~ %s'%(tmp_mjd_range_nomargin), priority='DEBUG') if rowid is not None: self.mjd_range = tmp_mjd_range self.mjd_range_nomargin = tmp_mjd_range_nomargin else: self.mjd_range_raster = tmp_mjd_range self.mjd_range_nomargin_raster = tmp_mjd_range_nomargin
def detect_gap(scantab, spw, pol): with selection_manager(scantab, scantab.get_selection(), types=0, ifs=spw, pols=pol) as s: alldir = numpy.array([s.get_directionval(i) for i in xrange(s.nrow())]).transpose() timestamp = numpy.array(map(lambda x: qa.quantity(x)['value'], s.get_time(prec=16))) row_gap = _detect_gap(timestamp) ras_gap = _detect_gap_raster(timestamp, alldir, row_gap=row_gap) return row_gap, ras_gap
def asdatestring(mjd, digit, timeonly=False): datedict = qa.splitdate(qa.quantity(mjd, 'd')) if digit > 10 : digit = 10 sstr_tmp = str(numpy.round(datedict['s'], digit)).split('.') sstr = sstr_tmp[0] + '.' + sstr_tmp[1][0:digit] if timeonly: return '%s:%s:%s'%(datedict['hour'],datedict['min'],sstr) else: return '%s/%s/%s/%s:%s:%s'%(datedict['year'],datedict['month'],datedict['monthday'],datedict['hour'],datedict['min'],sstr)
def to_velocity(self, frequency, freq_unit='GHz', restfreq=None): rest_frequency = self.coordsys.restfrequency() # user-defined rest frequency takes priority if restfreq is not None: vrf = qa.convert(qa.quantity(restfreq), freq_unit)['value'] elif rest_frequency['unit'] != freq_unit: vrf = qa.convert(rest_frequency, freq_unit)['value'] else: vrf = rest_frequency['value'] return (1.0 - (frequency / vrf)) * LightSpeed
def format_coord(x, y): col = np.argmin(np.absolute(tim - x)) row = np.argmin(np.absolute(freqghz - y)) if col >= 0 and col < ntim and row >= 0 and row < nfreq: timv = tim[col] timstr = qa.time(qa.quantity(timv, 's'), form='clean', prec=9)[0] flux = spec_plt[row, col] return 'time {0} = {1}, freq = {2:.3f} GHz, flux = {3:.2f} Jy'.format( col, timstr, y, flux) else: return 'x = {0}, y = {1:.3f}'.format(x, y)
def coordsTocl(name, flux, coords): from taskinit import cl, qa flux = qa.quantity(flux) cl.done() cl.rename(name) for coord in coords: clpars = {} clpars['flux'] = -flux['value'] clpars['fluxunit'] = flux['unit'] clpars['dir'] = ['J2000', str(coord.x) + 'rad', str(coord.y) + 'rad'] clpars['shape'] = 'point' cl.addcomponent(**clpars) cl.done()
def read_msinfo(vis=None, msinfofile=None): # read MS information # msinfo = dict.fromkeys(['vis', 'scans', 'fieldids', 'btimes', 'btimestr', \ 'inttimes', 'ras', 'decs']) ms.open(vis) scans = ms.getscansummary() scanids = sorted(scans.keys(), key=lambda x: int(x)) nscanid = len(scanids) btimes = [] btimestr = [] etimes = [] fieldids = [] inttimes = [] dirs = [] ras = [] decs = [] for i in range(nscanid): btimes.append(scans[scanids[i]]['0']['BeginTime']) etimes.append(scans[scanids[i]]['0']['EndTime']) fieldid = scans[scanids[i]]['0']['FieldId'] fieldids.append(fieldid) dir = ms.getfielddirmeas('PHASE_DIR', fieldid) dirs.append(dir) ras.append(dir['m0']) decs.append(dir['m1']) inttimes.append(scans[scanids[i]]['0']['IntegrationTime']) ms.close() btimestr = [qa.time(qa.quantity(btimes[i], 'd'), form='fits', prec=10)[0] \ for i in range(nscanid)] msinfo['vis'] = vis msinfo['scans'] = scans msinfo['fieldids'] = fieldids msinfo['btimes'] = btimes msinfo['btimestr'] = btimestr msinfo['inttimes'] = inttimes msinfo['ras'] = ras msinfo['decs'] = decs if msinfofile: np.savez(msinfofile, vis=vis, scans=scans, fieldids=fieldids, \ btimes=btimes, btimestr=btimestr, inttimes=inttimes, \ ras=ras, decs=decs) return msinfo
def parse_figsize(figsize): """ return figsize in inches """ casalog.post('parse_figsize input: {input}'.format(input=figsize), priority='DEBUG') parsed = None if figsize is not None and isinstance(figsize, str) and len(figsize) > 0: size_list = figsize.split(',') size_inch_list = [ x / 25.4 for s in size_list for x in qa.getvalue(qa.convert(qa.quantity(s), outunit='mm')) ] if len(size_inch_list) == 1: s = size_inch_list[0] parsed = (s, s) else: parsed = tuple(size_inch_list[:2]) casalog.post('parse_figsize output: {output}'.format(output=parsed), priority='DEBUG') return parsed
def parse_figsize(figsize): """ return figsize in inches """ casalog.post('parse_figsize input: {input}'.format(input=figsize), priority='DEBUG') parsed = None if figsize is not None and isinstance(figsize, str) and len(figsize) > 0: size_list = figsize.split(',') size_inch_list = [x / 25.4 for s in size_list for x in qa.getvalue(qa.convert(qa.quantity(s),outunit='mm'))] if len(size_inch_list) == 1: s = size_inch_list[0] parsed = (s, s) else: parsed = tuple(size_inch_list[:2]) casalog.post('parse_figsize output: {output}'.format(output=parsed), priority='DEBUG') return parsed
def imreg(vis=None, ephem=None, msinfo=None, imagefile=None, timerange=None, reftime=None, fitsfile=None, beamfile=None, offsetfile=None, toTb=None, scl100=None, verbose=False, p_ang=False, overwrite=True, usephacenter=True, deletehistory=False): ''' main routine to register CASA images Required Inputs: vis: STRING. CASA measurement set from which the image is derived imagefile: STRING or LIST. name of the input CASA image timerange: STRING or LIST. timerange used to generate the CASA image, must have the same length as the input images. Each element should be in CASA standard time format, e.g., '2012/03/03/12:00:00~2012/03/03/13:00:00' Optional Inputs: msinfo: DICTIONARY. CASA MS information, output from read_msinfo. If not provided, generate one from the supplied vis ephem: DICTIONARY. solar ephem, output from read_horizons. If not provided, query JPL Horizons based on time info of the vis (internet connection required) fitsfile: STRING or LIST. name of the output registered fits files reftime: STRING or LIST. Each element should be in CASA standard time format, e.g., '2012/03/03/12:00:00' offsetfile: optionally provide an offset with a series of solar x and y offsets with timestamps toTb: Bool. Convert the default Jy/beam to brightness temperature? scl100: Bool. If True, scale the image values up by 100 (to compensate VLA 20 dB attenuator) verbose: Bool. Show more diagnostic info if True. usephacenter: Bool -- if True, correct for the RA and DEC in the ms file based on solar empheris. Otherwise assume the phasecenter is correctly pointed to the solar disk center (EOVSA case) ''' ia = iatool() if deletehistory: msclearhistory(vis) if verbose: import time t0 = time.time() prtidx = 1 print('point {}: {}'.format(prtidx, time.time() - t0)) prtidx += 1 if not imagefile: raise ValueError, 'Please specify input image' if not timerange: raise ValueError, 'Please specify timerange of the input image' if type(imagefile) == str: imagefile = [imagefile] if type(timerange) == str: timerange = [timerange] if not fitsfile: fitsfile = [img + '.fits' for img in imagefile] if type(fitsfile) == str: fitsfile = [fitsfile] nimg = len(imagefile) if len(timerange) != nimg: raise ValueError, 'Number of input images does not equal to number of timeranges!' if len(fitsfile) != nimg: raise ValueError, 'Number of input images does not equal to number of output fits files!' nimg = len(imagefile) if verbose: print str(nimg) + ' images to process...' if verbose: print('point {}: {}'.format(prtidx, time.time() - t0)) prtidx += 1 if reftime: # use as reference time to find solar disk RA and DEC to register the image, but not the actual timerange associated with the image if type(reftime) == str: reftime = [reftime] * nimg if len(reftime) != nimg: raise ValueError, 'Number of reference times does not match that of input images!' helio = ephem_to_helio(vis, ephem=ephem, msinfo=msinfo, reftime=reftime, usephacenter=usephacenter) else: # use the supplied timerange to register the image helio = ephem_to_helio(vis, ephem=ephem, msinfo=msinfo, reftime=timerange, usephacenter=usephacenter) if verbose: print('point {}: {}'.format(prtidx, time.time() - t0)) prtidx += 1 for n, img in enumerate(imagefile): if verbose: print 'processing image #' + str(n) fitsf = fitsfile[n] timeran = timerange[n] # obtain duration of the image as FITS header exptime try: [tbg0, tend0] = timeran.split('~') tbg_d = qa.getvalue(qa.convert(qa.totime(tbg0), 'd'))[0] tend_d = qa.getvalue(qa.convert(qa.totime(tend0), 'd'))[0] tdur_s = (tend_d - tbg_d) * 3600. * 24. dateobs = qa.time(qa.quantity(tbg_d, 'd'), form='fits', prec=10)[0] except: print 'Error in converting the input timerange: ' + str( timeran) + '. Proceeding to the next image...' continue if verbose: print('point {}: {}'.format(prtidx, time.time() - t0)) prtidx += 1 hel = helio[n] if not os.path.exists(img): raise ValueError, 'Please specify input image' if os.path.exists(fitsf) and not overwrite: raise ValueError, 'Specified fits file already exists and overwrite is set to False. Aborting...' else: p0 = hel['p0'] ia.open(img) imr = ia.rotate(pa=str(-p0) + 'deg') imr.tofits(fitsf, history=False, overwrite=overwrite) imr.close() imsum = ia.summary() ia.close() if verbose: print('point {}: {}'.format(prtidx, time.time() - t0)) prtidx += 1 # construct the standard fits header # RA and DEC of the reference pixel crpix1 and crpix2 (imra, imdec) = (imsum['refval'][0], imsum['refval'][1]) # find out the difference of the image center to the CASA phase center # RA and DEC difference in arcseconds ddec = degrees((imdec - hel['dec_fld'])) * 3600. dra = degrees((imra - hel['ra_fld']) * cos(hel['dec_fld'])) * 3600. # Convert into image heliocentric offsets prad = -radians(hel['p0']) dx = (-dra) * cos(prad) - ddec * sin(prad) dy = (-dra) * sin(prad) + ddec * cos(prad) if offsetfile: try: offset = np.load(offsetfile) except: raise ValueError, 'The specified offsetfile does not exist!' reftimes_d = offset['reftimes_d'] xoffs = offset['xoffs'] yoffs = offset['yoffs'] timg_d = hel['reftime'] ind = bisect.bisect_left(reftimes_d, timg_d) xoff = xoffs[ind - 1] yoff = yoffs[ind - 1] else: xoff = hel['refx'] yoff = hel['refy'] if verbose: print 'offset of image phase center to visibility phase center (arcsec): ', dx, dy print 'offset of visibility phase center to solar disk center (arcsec): ', xoff, yoff (crval1, crval2) = (xoff + dx, yoff + dy) # update the fits header to heliocentric coordinates if verbose: print('point {}: {}'.format(prtidx, time.time() - t0)) prtidx += 1 hdu = pyfits.open(fitsf, mode='update') if verbose: print('point {}: {}'.format(prtidx, time.time() - t0)) prtidx += 1 header = hdu[0].header (cdelt1, cdelt2) = (-header['cdelt1'] * 3600., header['cdelt2'] * 3600. ) # Original CDELT1, 2 are for RA and DEC in degrees header['cdelt1'] = cdelt1 header['cdelt2'] = cdelt2 header['cunit1'] = 'arcsec' header['cunit2'] = 'arcsec' header['crval1'] = crval1 header['crval2'] = crval2 header['ctype1'] = 'HPLN-TAN' header['ctype2'] = 'HPLT-TAN' header['date-obs'] = dateobs # begin time of the image if not p_ang: hel['p0'] = 0 try: # this works for pyfits version of CASA 4.7.0 but not CASA 4.6.0 if tdur_s: header.set('exptime', tdur_s) else: header.set('exptime', 1.) header.set('p_angle', hel['p0']) header.set('dsun_obs', sun.sunearth_distance(Time(dateobs)).to(u.meter).value) header.set( 'rsun_obs', sun.solar_semidiameter_angular_size(Time(dateobs)).value) header.set('rsun_ref', sun.constants.radius.value) header.set('hgln_obs', 0.) header.set('hglt_obs', sun.heliographic_solar_center(Time(dateobs))[1].value) except: # this works for astropy.io.fits if tdur_s: header.append(('exptime', tdur_s)) else: header.append(('exptime', 1.)) header.append(('p_angle', hel['p0'])) header.append( ('dsun_obs', sun.sunearth_distance(Time(dateobs)).to(u.meter).value)) header.append( ('rsun_obs', sun.solar_semidiameter_angular_size(Time(dateobs)).value)) header.append(('rsun_ref', sun.constants.radius.value)) header.append(('hgln_obs', 0.)) header.append( ('hglt_obs', sun.heliographic_solar_center(Time(dateobs))[1].value)) if verbose: print('point {}: {}'.format(prtidx, time.time() - t0)) prtidx += 1 # update intensity units, i.e. to brightness temperature? if toTb: # get restoring beam info (bmajs, bmins, bpas, beamunits, bpaunits) = getbeam(imagefile=imagefile, beamfile=beamfile) bmaj = bmajs[n] bmin = bmins[n] beamunit = beamunits[n] data = hdu[ 0].data # remember the data order is reversed due to the FITS convension dim = data.ndim sz = data.shape keys = header.keys() values = header.values() # which axis is frequency? faxis = keys[values.index('FREQ')][-1] faxis_ind = dim - int(faxis) if header['BUNIT'].lower() == 'jy/beam': header['BUNIT'] = 'K' header['BTYPE'] = 'Brightness Temperature' for i in range(sz[faxis_ind]): nu = header['CRVAL' + faxis] + header['CDELT' + faxis] * ( i + 1 - header['CRPIX' + faxis]) if header['CUNIT' + faxis] == 'KHz': nu *= 1e3 if header['CUNIT' + faxis] == 'MHz': nu *= 1e6 if header['CUNIT' + faxis] == 'GHz': nu *= 1e9 if len(bmaj) > 1: # multiple (per-plane) beams bmajtmp = bmaj[i] bmintmp = bmin[i] else: # one single beam bmajtmp = bmaj[0] bmintmp = bmin[0] if beamunit == 'arcsec': bmaj0 = np.radians(bmajtmp / 3600.) bmin0 = np.radians(bmajtmp / 3600.) if beamunit == 'arcmin': bmaj0 = np.radians(bmajtmp / 60.) bmin0 = np.radians(bmintmp / 60.) if beamunit == 'deg': bmaj0 = np.radians(bmajtmp) bmin0 = np.radians(bmintmp) if beamunit == 'rad': bmaj0 = bmajtmp bmin0 = bmintmp beam_area = bmaj0 * bmin0 * np.pi / (4. * log(2.)) k_b = qa.constants('k')['value'] c_l = qa.constants('c')['value'] factor = 2. * k_b * nu**2 / c_l**2 # SI unit jy_to_si = 1e-26 # print nu/1e9, beam_area, factor factor2 = 1. if scl100: factor2 = 100. if faxis == '3': data[:, i, :, :] *= jy_to_si / beam_area / factor * factor2 if faxis == '4': data[ i, :, :, :] *= jy_to_si / beam_area / factor * factor2 if verbose: print('point {}: {}'.format(prtidx, time.time() - t0)) prtidx += 1 hdu.flush() hdu.close() if verbose: print('point {}: {}'.format(prtidx, time.time() - t0)) prtidx += 1
def subvs(vis=None, outputvis=None, timerange=None, spw=None, subtime1=None, subtime2=None, splitsel=True, reverse=False, overwrite=False): """Perform vector subtraction for visibilities Keyword arguments: vis -- Name of input visibility file (MS) default: none; example: vis='ngc5921.ms' outputvis -- Name of output uv-subtracted visibility file (MS) default: none; example: outputvis='ngc5921_src.ms' timerange -- Time range of performing the UV subtraction: default='' means all times. examples: timerange = 'YYYY/MM/DD/hh:mm:ss~YYYY/MM/DD/hh:mm:ss' timerange = 'hh:mm:ss~hh:mm:ss' spw -- Select spectral window/channel. default = '' all the spectral channels. Example: spw='0:1~20' subtime1 -- Time range 1 of the background to be subtracted from the data default='' means all times. format: timerange = 'YYYY/MM/DD/hh:mm:ss~YYYY/MM/DD/hh:mm:ss' timerange = 'hh:mm:ss~hh:mm:ss' subtime2 -- Time range 2 of the backgroud to be subtracted from the data default='' means all times. examples: timerange = 'YYYY/MM/DD/hh:mm:ss~YYYY/MM/DD/hh:mm:ss' timerange = 'hh:mm:ss~hh:mm:ss' splitsel -- True or False. default = False. If splitsel = False, then the entire input measurement set is copied as the output measurement set (outputvis), with background subtracted at selected timerange and spectral channels. If splitsel = True,then only the selected timerange and spectral channels are copied into the output measurement set (outputvis). reverse -- True or False. default = False. If reverse = False, then the times indicated by subtime1 and/or subtime2 are treated as background and subtracted; If reverse = True, then reverse the sign of the background-subtracted data. The option can be used for mapping absorptive structure. overwrite -- True or False. default = False. If overwrite = True and outputvis already exists, the selected subtime and spw in the output measurment set will be replaced with background subtracted visibilities """ #check the visbility ms if not outputvis or outputvis.isspace(): raise ValueError, 'Please specify outputvis' if os.path.exists(outputvis): if overwrite: print "The already existing output measurement set will be updated." else: raise ValueError, "Output MS %s already exists - will not overwrite." % outputvis else: if not splitsel: shutil.copytree(vis, outputvis) else: ms.open(vis, nomodify=True) ms.split(outputvis, spw=spw, time=timerange, whichcol='DATA') ms.close() #define and check the time ranges if subtime1 and (type(subtime1) == str): [bsubtime1, esubtime1] = subtime1.split('~') bsubtime1sec = qa.getvalue(qa.convert(qa.totime(bsubtime1), 's')) esubtime1sec = qa.getvalue(qa.convert(qa.totime(esubtime1), 's')) timebin1sec = esubtime1sec - bsubtime1sec if timebin1sec < 0: raise Exception, 'Negative timebin! Please check the "subtime1" parameter.' casalog.post('Selected timerange 1: ' + subtime1 + ' as background for uv subtraction.') else: raise Exception, 'Please enter at least one timerange as the background' if subtime2 and (type(subtime2) == str): [bsubtime2, esubtime2] = subtime2.split('~') bsubtime2sec = qa.getvalue(qa.convert(qa.totime(bsubtime2), 's')) esubtime2sec = qa.getvalue(qa.convert(qa.totime(esubtime2), 's')) timebin2sec = esubtime2sec - bsubtime2sec if timebin2sec < 0: raise Exception, 'Negative timebin! Please check the "subtime2" parameter.' timebin2 = str(timebin2sec) + 's' casalog.post('Selected timerange 2: ' + subtime2 + ' as background for uv subtraction.') #plus 1s is to ensure averaging over the entire timerange else: casalog.post( 'Timerange 2 not selected, using only timerange 1 as background') if timerange and (type(timerange) == str): [btimeo, etimeo] = timerange.split('~') btimeosec = qa.getvalue(qa.convert(qa.totime(btimeo), 's')) etimeosec = qa.getvalue(qa.convert(qa.totime(etimeo), 's')) timebinosec = etimeosec - btimeosec if timebinosec < 0: raise Exception, 'Negative timebin! Please check the "timerange" parameter.' casalog.post('Selected timerange: ' + timerange + ' as the time for UV subtraction.') else: casalog.post( 'Output timerange not specified, using the entire timerange') if spw and (type(spw) == str): [spwid, chanran] = spw.split(':') [bchan, echan] = chanran.split('~') else: casalog.post('spw not specified, use all frequency channels') #Select the background indicated by subtime1 ms.open(vis, nomodify=True) #Select the spw id ms.msselect({'time': subtime1}) if spw and (type(spw) == str): ms.selectinit(datadescid=int(spwid)) nchan = int(echan) - int(bchan) + 1 ms.selectchannel(nchan, int(bchan), 1, 1) rec1 = ms.getdata(['data', 'time', 'axis_info'], ifraxis=True) #print 'shape of the frequency matrix ',rec1['axis_info']['freq_axis']['chan_freq'].shape sz1 = rec1['data'].shape print 'dimension of selected background 1', rec1['data'].shape #the data shape is (n_pol,n_channel,n_baseline,n_time), no need to reshape #rec1['data']=rec1['data'].reshape(sz1[0],sz1[1],sz1[2],nspw,sz1[3]/nspw,order='F') #print 'reshaped rec1 ', rec1['data'].shape rec1avg = np.average(rec1['data'], axis=3) casalog.post('Averaging the visibilities in subtime1: ' + subtime1) ms.close() if subtime2 and (type(subtime2) == str): ms.open(vis, nomodify=True) #Select the spw id ms.msselect({'time': subtime2}) if spw and (type(spw) == str): ms.selectinit(datadescid=0) nchan = int(echan) - int(bchan) + 1 ms.selectchannel(nchan, int(bchan), 1, 1) rec2 = ms.getdata(['data', 'time', 'axis_info'], ifraxis=True) sz2 = rec2['data'].shape print 'dimension of selected background 2', rec2['data'].shape #rec2['data']=rec2['data'].reshape(sz2[0],sz2[1],sz2[2],nspw,sz2[3]/nspw,order='F') #print 'reshaped rec1 ', rec2['data'].shape rec2avg = np.average(rec2['data'], axis=3) ms.close() casalog.post('Averaged the visibilities in subtime2: ' + subtime2) #do UV subtraction, according to timerange and spw ms.open(outputvis, nomodify=False) if not splitsel: #outputvis is identical to input visibility, do the selection if timerange and (type(timerange == str)): ms.msselect({'time': timerange}) if spw and (type(spw) == str): ms.selectinit(datadescid=int(spwid)) nchan = int(echan) - int(bchan) + 1 ms.selectchannel(nchan, int(bchan), 1, 1) else: #outputvis is splitted, selections have already applied, select all the data ms.selectinit(datadescid=0) orec = ms.getdata(['data', 'time', 'axis_info'], ifraxis=True) b_rows = orec['data'].shape[2] nchan = orec['data'].shape[1] #szo=orec['data'].shape print 'dimension of output data', orec['data'].shape #orec['data']=orec['data'].reshape(szo[0],szo[1],szo[2],nspw,szo[3]/nspw,order='F') #print 'reshaped rec1 ', orec['data'].shape t_rows = orec['data'].shape[3] casalog.post('Number of baselines: ' + str(b_rows)) casalog.post('Number of spectral channels: ' + str(nchan)) casalog.post('Number of time pixels: ' + str(t_rows)) if subtime1 and (not subtime2): casalog.post( 'Only "subtime1" is defined, subtracting background defined in subtime1: ' + subtime1) t1 = (np.amax(rec1['time']) + np.amin(rec1['time'])) / 2. print 't1: ', qa.time(qa.quantity(t1, 's'), form='ymd', prec=10) for i in range(t_rows): orec['data'][:, :, :, i] -= rec1avg if reverse: orec['data'][:, :, :, i] = -orec['data'][:, :, :, i] if subtime1 and subtime2 and (type(subtime2) == str): casalog.post( 'Both subtime1 and subtime2 are specified, doing linear interpolation between "subtime1" and "subtime2"' ) t1 = (np.amax(rec1['time']) + np.amin(rec1['time'])) / 2. t2 = (np.amax(rec2['time']) + np.amin(rec2['time'])) / 2. touts = orec['time'] print 't1: ', qa.time(qa.quantity(t1, 's'), form='ymd', prec=10) print 't2: ', qa.time(qa.quantity(t2, 's'), form='ymd', prec=10) for i in range(t_rows): tout = touts[i] if tout > np.amax([t1, t2]): tout = np.amax([t1, t2]) elif tout < np.amin([t1, t2]): tout = np.amin([t1, t2]) orec['data'][:, :, :, i] -= (rec2avg - rec1avg) * (tout - t1) / (t2 - t1) + rec1avg if reverse: orec['data'][:, :, :, i] = -orec['data'][:, :, :, i] #orec['data']=orec['data'].reshape(szo[0],szo[1],szo[2],szo[3],order='F') #put the modified data back into the output visibility set del orec['time'] del orec['axis_info'] ms.putdata(orec) ms.close()
def ephem_to_helio(vis=None, ephem=None, msinfo=None, reftime=None, polyfit=None, usephacenter=False): '''1. Take a solar ms database, read the scan and field information, find out the pointings (in RA and DEC) 2. Compare with the ephemeris of the solar disk center (in RA and DEC) 3. Generate VLA pointings in heliocentric coordinates inputs: msinfo: CASA MS information, output from read_msinfo ephem: solar ephem, output from read_horizons reftime: list of reference times (e.g., used for imaging) CASA standard time format, either a single time (e.g., '2012/03/03/12:00:00' or a time range (e.g., '2012/03/03/12:00:00~2012/03/03/13:00:00'. If the latter, take the midpoint of the timerange for reference. If no date specified, take the date of the first scan polyfit: ONLY works for MS database with only one source with continously tracking; not recommanded unless scan length is too long and want to have very high accuracy usephacenter: Bool -- if True, correct for the RA and DEC in the ms file based on solar empheris. Otherwise assume the phasecenter is correctly pointed to the solar disk center (EOVSA case) return value: helio: a list of VLA pointing information reftimestr: reference time, in FITS format string reftime: reference time, in mjd format ra: actual RA of phasecenter in the ms file at the reference time (interpolated) dec: actual DEC of phasecenter in the ms file at the reference time (interpolated) # CASA uses only RA and DEC of the closest field (e.g. in clean) # ra_fld: right ascention of the CASA reference pointing direction dec_fld: declination of the CASA reference pointing direction raoff: RA offset of the phasecenter in the ms file to solar center decoff: DEC offset of the phasecenter in the ms file to solar center refx: heliocentric X offset of the phasecenter in the ms file to solar center refy: heliocentric Y offset of the phasecenter in the ms file to solar center ######## Example ######### msfile='sun_C_20140910T221952-222952.10s.cal.ms' ephemfile='horizons_sun_20140910.radecp' ephem=vla_prep.read_horizons(ephemfile=ephemfile) msinfo=vla_prep.read_msinfo(msfile=msfile) polyfit=0 reftime = '22:25:20~22:25:40' ''' if not vis or not os.path.exists(vis): raise ValueError, 'Please provide information of the MS database!' if not ephem: ephem = read_horizons(vis) if not msinfo: msinfo0 = read_msinfo(vis) else: if isinstance(msinfo, str): try: msinfo0 = np.load(msinfo) except: raise ValueError, 'The specified input msinfo file does not exist!' elif isinstance(msinfo, dict): msinfo0 = msinfo else: raise ValueError, 'msinfo should be either a numpy npz or a dictionary' print 'msinfo is derived from: ', msinfo0['vis'] scans = msinfo0['scans'] fieldids = msinfo0['fieldids'] btimes = msinfo0['btimes'] inttimes = msinfo0['inttimes'] ras = msinfo0['ras'] decs = msinfo0['decs'] ra_rads = [ra['value'] for ra in ras] dec_rads = [dec['value'] for dec in decs] # fit 2nd order polynomial fits to the RAs and DECs # if polyfit: cra = np.polyfit(btimes, ra_rads, 2) cdec = np.polyfit(btimes, dec_rads, 2) # find out phase center infomation in ms according to the input time or timerange # if not reftime: raise ValueError, 'Please specify a reference time of the image' if type(reftime) == str: reftime = [reftime] if (not isinstance(reftime, list)): print 'input "reftime" is not a valid list. Abort...' nreftime = len(reftime) helio = [] for reftime0 in reftime: helio0 = dict.fromkeys(['reftimestr', 'reftime', \ 'ra', 'dec', 'ra_fld', 'dec_fld', \ 'raoff', 'decoff', 'refx', 'refy', 'p0']) helio0['reftimestr'] = reftime0 if '~' in reftime0: # if reftime0 is specified as a timerange [tbg0, tend0] = reftime0.split('~') tbg_d = qa.getvalue(qa.convert(qa.totime(tbg0), 'd'))[0] tend_d = qa.getvalue(qa.convert(qa.totime(tend0), 'd'))[0] tdur_s = (tend_d - tbg_d) * 3600. * 24. # if no date is specified, add up the date of the first scan if tend_d < 1.: if tend_d >= tbg_d: tend_d += int(btimes[0]) else: tend_d += int(btimes[0]) + 1 if tbg_d < 1.: tbg_d += int(btimes[0]) tref_d = (tbg_d + tend_d) / 2. else: # if reftime0 is specified as a single value tref_d = qa.getvalue(qa.convert(qa.totime(reftime0), 'd')) # if no date is specified, add up the date of the first scan if tref_d < 1.: tref_d += int(btimes[0]) tbg_d = tref_d # use the intergration time ind = bisect.bisect_left(btimes, tref_d) tdur_s = inttims[ind - 1] helio0['reftime'] = tref_d helio0['date-obs'] = qa.time(qa.quantity(tbg_d, 'd'), form='fits', prec=10)[0] helio0['exptime'] = tdur_s # find out phase center RA and DEC in the measurement set according to the reference time # if polyfit, then use the 2nd order polynomial coeffs ind = bisect.bisect_left(btimes, tref_d) if ind > 1: dt = tref_d - btimes[ind - 1] if ind < len(btimes): scanlen = btimes[ind] - btimes[ind - 1] (ra_b, ra_e) = (ras[ind - 1]['value'], ras[ind]['value']) (dec_b, dec_e) = (decs[ind - 1]['value'], decs[ind]['value']) if ind >= len(btimes): scanlen = btimes[ind - 1] - btimes[ind - 2] (ra_b, ra_e) = (ras[ind - 2]['value'], ras[ind - 1]['value']) (dec_b, dec_e) = (decs[ind - 2]['value'], decs[ind - 1]['value']) if ind == 1: # only one scan exists (e.g., imported from AIPS) ra_b = ras[ind - 1]['value'] ra_e = ra_b dec_b = decs[ind - 1]['value'] dec_e = dec_b scanlen = 10. # radom value dt = 0. if ind < 1: raise ValueError, 'Reference time does not fall into the scan list!' if polyfit: ra = cra[0] * tref_d**2. + cra[1] * tref_d + cra[2] dec = cdec[0] * tref_d**2. + cdec[1] * tref_d + cdec[2] # if not, use linearly interpolated RA and DEC at the beginning of this scan and next scan else: ra = ra_b + (ra_e - ra_b) / scanlen * dt dec = dec_b + (dec_e - dec_b) / scanlen * dt if ra < 0: ra += 2. * np.pi if ra_b < 0: ra_b += 2. * np.pi # compare with ephemeris from JPL Horizons time0 = ephem['time'] ra0 = ephem['ra'] dec0 = ephem['dec'] p0 = ephem['p0'] delta0 = ephem['delta'] ind = bisect.bisect_left(time0, tref_d) dt0 = time0[ind] - time0[ind - 1] dt_ref = tref_d - time0[ind - 1] dra0 = ra0[ind] - ra0[ind - 1] ddec0 = dec0[ind] - dec0[ind - 1] dp0 = p0[ind] - p0[ind - 1] ddelta0 = delta0[ind] - delta0[ind - 1] ra0 = ra0[ind - 1] + dra0 / dt0 * dt_ref dec0 = dec0[ind - 1] + ddec0 / dt0 * dt_ref p0 = p0[ind - 1] + dp0 / dt0 * dt_ref delta0 = delta0[ind - 1] + ddelta0 / dt0 * dt_ref if ra0 < 0: ra0 += 2. * np.pi # RA and DEC offset in arcseconds decoff = degrees((dec - dec0)) * 3600. raoff = degrees((ra - ra0) * cos(dec)) * 3600. # Convert into heliocentric offsets prad = -radians(p0) refx = (-raoff) * cos(prad) - decoff * sin(prad) refy = (-raoff) * sin(prad) + decoff * cos(prad) helio0['ra'] = ra # ra of the actual pointing helio0['dec'] = dec # dec of the actual pointing helio0[ 'ra_fld'] = ra_b # ra of the field, used as the reference in e.g., clean helio0[ 'dec_fld'] = dec_b # dec of the field, used as the refenrence in e.g., clean helio0['raoff'] = raoff helio0['decoff'] = decoff if usephacenter: helio0['refx'] = refx helio0['refy'] = refy else: helio0['refx'] = 0. helio0['refy'] = 0. helio0['p0'] = p0 # helio['r_sun']=np.degrees(R_sun.value/(au.value*delta0))*3600. #in arcsecs helio.append(helio0) return helio
def test_readAndParseIrregularTbuff(self): '''flaghelper: compare the read and parse and apply of irregular tbuff''' print '' # MJD in seconds of timeranges are these # <startTime>4891227930515540000 <endTime>4891227932453838000 # <startTime>4891228473545856000 <endTime>4891228473731891000 # <startTime>4891226924455911000 <endTime>4891226927502314000 # <startTime>4891228838164987000 <endTime>4891228838418996000 # <startTime>4891228609440808000 <endTime>4891228612489617000 online = ["antenna='DV03&&*' timerange='2013/11/15/10:25:30.516~2013/11/15/10:25:32.454'", "antenna='DA44&&*' timerange='2013/11/15/10:34:33.546~2013/11/15/10:34:33.732'", "antenna='DA46&&*' timerange='2013/11/15/10:08:44.456~2013/11/15/10:08:47.502'", "antenna='DV09&&*' timerange='2013/11/15/10:18:11.798~2013/11/15/10:18:13.837'", "antenna='DV05&&*' timerange='2013/11/15/10:40:38.165~2013/11/15/10:40:38.419'"] myinput = "antenna='DV03&&*' timerange='2013/11/15/10:25:30.516~2013/11/15/10:25:32.454'\n"\ "antenna='DA44&&*' timerange='2013/11/15/10:34:33.546~2013/11/15/10:34:33.732'\n"\ "antenna='DA46&&*' timerange='2013/11/15/10:08:44.456~2013/11/15/10:08:47.502'\n"\ "antenna='DV09&&*' timerange='2013/11/15/10:18:11.798~2013/11/15/10:18:13.837'\n"\ "antenna='DV05&&*' timerange='2013/11/15/10:40:38.165~2013/11/15/10:40:38.419'" filename1 = 'flaghelperonline2.txt' create_input(myinput, filename1) # timeranges from online before padding, for comparison later timeranges=[] for cmd in online: a,b = cmd.split(' ') b = b.lstrip('timerange=') timeranges.append(b.strip("'")) # Apply 2 values of tbuff to timeranges timebuffer = [0.4, 0.7] dlist1 = fh.readAndParse([filename1], tbuff=timebuffer) self.assertEqual(len(dlist1), 5) # check the padded time ranges before and after the application n = 0 for cmd in dlist1: padt = cmd['timerange'] # padt = dlist1[0]['timerange'] # Revert the tbuff application manually t0,t1 = padt.split('~',1) startTime = qa.totime(t0)['value'] startTimeSec = float((startTime * 24 * 3600) + timebuffer[0]) startTimeSec = qa.quantity(startTimeSec, 's') paddedT0 = qa.time(startTimeSec,form='ymd',prec=9)[0] # end time endTime = qa.totime(t1)['value'] endTimeSec = float((endTime * 24 * 3600) - timebuffer[1]) endTimeSec = qa.quantity(endTimeSec, 's') paddedT1 = qa.time(endTimeSec,form='ymd',prec=9)[0] newtimerange = paddedT0+'~'+paddedT1 # Compare with the original self.assertEqual(timeranges[n], newtimerange) n += 1
def plt_dspec(specdata, pol='I', dmin=None, dmax=None, timerange=None, freqrange=None, timestr=True, movie=False, framedur=60., dtframe=10., goessav=None, goes_trange=None, savepng=True, savepdf=False): """ timerange: format: ['2012/03/10/18:00:00','2012/03/10/19:00:00'] freqrange: format: [1000.,1500.] in MHz movie: do a movie of dynamic spectrum? framedur: time range of each frame dtframe: time difference of consecutive frames goessav: provide an IDL save file from the sswidl GOES widget output goes_trange: plot only the specified time range for goes timestr: display time as strings on X-axis -- currently the times do not update themselves when zooming in """ # Set up variables import matplotlib.pyplot as plt import numpy from numpy import log10 from astropy.time import Time if pol != 'RR' and pol != 'LL' and pol != 'RRLL' and pol != 'I' and pol != 'V' and pol != 'IV': print "Please enter 'RR', 'LL', 'RRLL', 'I', 'V', 'IV' for pol" return 0 if type(specdata) is str: specdata = np.load(specdata) bl = specdata['bl'].item() try: (npol, nbl, nfreq, ntim) = specdata['spec'].shape spec = specdata['spec'] tim = specdata['tim'] tim_ = Time(tim / 3600. / 24., format='mjd') tim_plt = tim_.plot_date freq = specdata['freq'] if not 'bl' in vars(): bl = specdata['bl'] except: print('format of specdata not recognized. Check your input') return -1 if timerange: if type(timerange[0]) is str: timerange = [ qa.convert(qa.quantity(t), 's')['value'] for t in timerange ] tidx = np.where((tim >= timerange[0]) & (tim <= timerange[1]))[0] else: tidx = range(ntim) if freqrange: fidx = np.where((freq >= freqrange[0] * 1e6) & (freq <= freqrange[1] * 1e6))[0] else: fidx = range(nfreq) # setup plot parameters print 'ploting dynamic spectrum...' spec_med = np.median(np.absolute(spec)) # if not dmin: # dmin = spec_med / 20. # if not dmax: # dmax = spec_med * 5. # do the plot for b in range(nbl): if pol != 'RRLL' and pol != 'IV': if pol == 'RR': spec_plt = spec[0, b, :, :] elif pol == 'LL': spec_plt = spec[1, b, :, :] elif pol == 'I': spec_plt = (spec[0, b, :, :] + spec[1, b, :, :]) / 2. elif pol == 'V': spec_plt = (spec[0, b, :, :] - spec[1, b, :, :]) / 2. if movie: f = plt.figure(figsize=(16, 8), dpi=100) if goessav: gs = gridspec.GridSpec(2, 1, height_ratios=[2, 1]) gs.update(left=0.06, right=0.97, top=0.95, bottom=0.06) ax1 = f.add_subplot(gs[0]) ax2 = f.add_subplot(gs[1]) if os.path.exists(goessav): goes = readsav(goessav) # IDL anytim 0 sec correspond to 1979 Jan 01, convert to mjd time anytimbase = qa.convert( qa.quantity('1979/01/01/00:00:00'), 's')['value'] mjdbase = goes['utbase'] + anytimbase ts = goes['tarray'] + mjdbase lc0 = goes['yclean'][0, :] lc1 = goes['yclean'][1, :] else: ax1 = f.add_subplot(211) tstart = tim[tidx[0]] tend = tim[tidx[-1]] tstartstr = qa.time(qa.quantity(tstart, 's'))[0] tendstr = qa.time(qa.quantity(tend, 's'))[0] nfrm = int((tend - tstart) / dtframe) + 1 print 'Movie mode set. ' + str( nfrm ) + ' frames to plot from ' + tstartstr + ' to ' + tendstr for i in range(nfrm): if (i != 0) and (i % 10 == 0): print str(i) + ' frames done' timeran = [ tstart + i * dtframe, tstart + i * dtframe + framedur ] tidx1 = np.where((tim >= timeran[0]) & (tim <= timeran[1]))[0] tim1 = tim_[tidx1] freq1 = freq[fidx] / 1e9 spec_plt1 = spec_plt[fidx, :][:, tidx1] ax1.pcolormesh(tim1.plot_date, freq1, spec_plt1, cmap='jet', vmin=dmin, vmax=dmax) ax1.set_xlim(tim1[0].plot_date, tim1[-1].plot_date) ax1.set_ylim(freq1[0], freq1[-1]) ax1.set_ylabel('Frequency (GHz)') ax1.set_title('Dynamic spectrum @ bl ' + bl.split(';')[b] + ', pol ' + pol) if timestr: # date_format = mdates.DateFormatter('%H:%M:%S.%f') # ax1.xaxis_date() # ax1.xaxis.set_major_formatter(date_format) locator = AutoDateLocator() ax1.xaxis.set_major_locator(locator) ax1.xaxis.set_major_formatter( AutoDateFormatter(locator)) ax1.set_autoscale_on(False) if goessav: if goes_trange: if type(goes_trange[0]) is str: goes_trange = [ qa.convert(qa.quantity(t), 's')['value'] for t in goes_trange ] idx = np.where((ts >= goes_trange[0]) & (ts <= goes_trange[1]))[0] else: idx = range(len(ts)) ts_plt = ts[idx] lc0_plt = lc0[idx] utbase = qa.convert(qa.quantity('0001/01/01/00:00:00'), 'd')['value'] + 1 ts_plt_d = ts_plt / 3600. / 24. - utbase ax2.plot_date(ts_plt_d, lc0_plt, 'b-') ax2.axvspan(tim1[0].mjd - utbase, tim1[-1].mjd - utbase, color='red', alpha=0.5) ax2.set_yscale('log') ax2.set_title('GOES 1-8 A') tstartstr_ = tim1[0].datetime.strftime( '%Y-%m-%dT%H%M%S.%f')[:-3] tendstr_ = tim1[1].datetime.strftime('%H%M%S.%f')[:-3] timstr = tstartstr_ + '-' + tendstr_ figfile = 'dspec_t' + timstr + '.png' if not os.path.isdir('dspec'): os.makedirs('dspec') f.savefig('dspec/' + figfile) plt.cla() else: f = plt.figure(figsize=(8, 4), dpi=100) ax = f.add_subplot(111) freqghz = freq / 1e9 ax.pcolormesh(tim_plt, freqghz, spec_plt, cmap='jet', vmin=dmin, vmax=dmax) ax.set_xlim(tim_plt[tidx[0]], tim_plt[tidx[-1]]) ax.set_ylim(freqghz[fidx[0]], freqghz[fidx[-1]]) try: from sunpy import lightcurve from sunpy.time import TimeRange, parse_time t1 = tim_[tidx[0]] t2 = tim_[tidx[-1]] tr = TimeRange(t1.iso, t2.iso) goes = lightcurve.GOESLightCurve.create(tr) goes.data['xrsb'] = 2 * (np.log10(goes.data['xrsb'])) + 26 xx = [str(ll) for ll in np.array(goes.data.index)] yy = np.array(goes.data['xrsb']) ax.plot(Time(xx).mjd * 24 * 3600, yy, c='yellow') rightaxis_label_time = Time(xx[-1]).mjd * 24 * 3600 ax.text(rightaxis_label_time, 9.6, 'A', fontsize='15') ax.text(rightaxis_label_time, 11.6, 'B', fontsize='15') ax.text(rightaxis_label_time, 13.6, 'C', fontsize='15') ax.text(rightaxis_label_time, 15.6, 'M', fontsize='15') ax.text(rightaxis_label_time, 17.6, 'X', fontsize='15') except: pass def format_coord(x, y): col = np.argmin(np.absolute(tim_plt - x)) row = np.argmin(np.absolute(freqghz - y)) if col >= 0 and col < ntim and row >= 0 and row < nfreq: timstr = tim_[col].isot flux = spec_plt[row, col] return 'time {0} = {1}, freq = {2:.3f} GHz, flux = {3:.2f} Jy'.format( col, timstr, y, flux) else: return 'x = {0}, y = {1:.3f}'.format(x, y) ax.format_coord = format_coord ax.set_ylabel('Frequency (GHz)') if bl: ax.set_title('Dynamic spectrum @ bl ' + bl.split(';')[b] + ', pol ' + pol) else: ax.set_title('Medium dynamic spectrum') if timestr: # date_format = mdates.DateFormatter('%H:%M:%S.%f') # ax.xaxis_date() # ax.xaxis.set_major_formatter(date_format) locator = AutoDateLocator() ax.xaxis.set_major_locator(locator) ax.xaxis.set_major_formatter(AutoDateFormatter(locator)) ax.set_autoscale_on(False) else: f = plt.figure(figsize=(8, 6), dpi=100) R_plot = np.absolute(spec[0, b, :, :]) L_plot = np.absolute(spec[1, b, :, :]) I_plot = (R_plot + L_plot) / 2. V_plot = (R_plot - L_plot) / 2. if pol == 'RRLL': spec_plt_1 = R_plot spec_plt_2 = L_plot polstr = ['RR', 'LL'] if pol == 'IV': spec_plt_1 = I_plot spec_plt_2 = V_plot polstr = ['I', 'V'] ax1 = f.add_subplot(211) freqghz = freq / 1e9 ax1.pcolormesh(tim_plt, freqghz, spec_plt_1, cmap='jet', vmin=dmin, vmax=dmax) ax1.set_xlim(tim_plt[tidx[0]], tim_plt[tidx[-1]]) ax1.set_ylim(freqghz[fidx[0]], freqghz[fidx[-1]]) def format_coord(x, y): col = np.argmin(np.absolute(tim_plt - x)) row = np.argmin(np.absolute(freqghz - y)) if col >= 0 and col < ntim and row >= 0 and row < nfreq: timstr = tim_[col].isot flux = spec_plt[row, col] return 'time {0} = {1}, freq = {2:.3f} GHz, flux = {3:.2f} Jy'.format( col, timstr, y, flux) else: return 'x = {0}, y = {1:.3f}'.format(x, y) ax1.format_coord = format_coord ax1.set_ylabel('Frequency (GHz)') if timestr: # date_format = mdates.DateFormatter('%H:%M:%S.%f') # ax1.xaxis_date() # ax1.xaxis.set_major_formatter(date_format) locator = AutoDateLocator() ax1.xaxis.set_major_locator(locator) ax1.xaxis.set_major_formatter(AutoDateFormatter(locator)) ax1.set_title('Dynamic spectrum @ bl ' + bl.split(';')[b] + ', pol ' + polstr[0]) ax1.set_autoscale_on(False) ax2 = f.add_subplot(212) ax2.pcolormesh(tim_plt, freqghz, spec_plt_2, cmap='jet', vmin=dmin, vmax=dmax) ax2.set_xlim(tim_plt[tidx[0]], tim_plt[tidx[-1]]) ax2.set_ylim(freqghz[fidx[0]], freqghz[fidx[-1]]) if timestr: # date_format = mdates.DateFormatter('%H:%M:%S.%f') # ax2.xaxis_date() # ax2.xaxis.set_major_formatter(date_format) locator = AutoDateLocator() ax2.xaxis.set_major_locator(locator) ax2.xaxis.set_major_formatter(AutoDateFormatter(locator)) def format_coord(x, y): col = np.argmin(np.absolute(tim_plt - x)) row = np.argmin(np.absolute(freqghz - y)) if col >= 0 and col < ntim and row >= 0 and row < nfreq: timstr = tim_[col].isot flux = spec_plt[row, col] return 'time {0} = {1}, freq = {2:.3f} GHz, flux = {3:.2f} Jy'.format( col, timstr, y, flux) else: return 'x = {0}, y = {1:.3f}'.format(x, y) ax2.format_coord = format_coord ax2.set_ylabel('Frequency (GHz)') ax2.set_title('Dynamic spectrum @ bl ' + bl.split(';')[b] + ', pol ' + polstr[1]) ax2.set_autoscale_on(False)
def test_readAndParseIrregularTbuff(self): '''flaghelper: compare the read and parse and apply of irregular tbuff''' print '' # MJD in seconds of timeranges are these # <startTime>4891227930515540000 <endTime>4891227932453838000 # <startTime>4891228473545856000 <endTime>4891228473731891000 # <startTime>4891226924455911000 <endTime>4891226927502314000 # <startTime>4891228838164987000 <endTime>4891228838418996000 # <startTime>4891228609440808000 <endTime>4891228612489617000 online = [ "antenna='DV03&&*' timerange='2013/11/15/10:25:30.516~2013/11/15/10:25:32.454'", "antenna='DA44&&*' timerange='2013/11/15/10:34:33.546~2013/11/15/10:34:33.732'", "antenna='DA46&&*' timerange='2013/11/15/10:08:44.456~2013/11/15/10:08:47.502'", "antenna='DV09&&*' timerange='2013/11/15/10:18:11.798~2013/11/15/10:18:13.837'", "antenna='DV05&&*' timerange='2013/11/15/10:40:38.165~2013/11/15/10:40:38.419'" ] myinput = "antenna='DV03&&*' timerange='2013/11/15/10:25:30.516~2013/11/15/10:25:32.454'\n"\ "antenna='DA44&&*' timerange='2013/11/15/10:34:33.546~2013/11/15/10:34:33.732'\n"\ "antenna='DA46&&*' timerange='2013/11/15/10:08:44.456~2013/11/15/10:08:47.502'\n"\ "antenna='DV09&&*' timerange='2013/11/15/10:18:11.798~2013/11/15/10:18:13.837'\n"\ "antenna='DV05&&*' timerange='2013/11/15/10:40:38.165~2013/11/15/10:40:38.419'" filename1 = 'flaghelperonline2.txt' create_input(myinput, filename1) # timeranges from online before padding, for comparison later timeranges = [] for cmd in online: a, b = cmd.split(' ') b = b.lstrip('timerange=') timeranges.append(b.strip("'")) # Apply 2 values of tbuff to timeranges timebuffer = [0.4, 0.7] dlist1 = fh.readAndParse([filename1], tbuff=timebuffer) self.assertEqual(len(dlist1), 5) # check the padded time ranges before and after the application n = 0 for cmd in dlist1: padt = cmd['timerange'] # padt = dlist1[0]['timerange'] # Revert the tbuff application manually t0, t1 = padt.split('~', 1) startTime = qa.totime(t0)['value'] startTimeSec = float((startTime * 24 * 3600) + timebuffer[0]) startTimeSec = qa.quantity(startTimeSec, 's') paddedT0 = qa.time(startTimeSec, form='ymd', prec=9)[0] # end time endTime = qa.totime(t1)['value'] endTimeSec = float((endTime * 24 * 3600) - timebuffer[1]) endTimeSec = qa.quantity(endTimeSec, 's') paddedT1 = qa.time(endTimeSec, form='ymd', prec=9)[0] newtimerange = paddedT0 + '~' + paddedT1 # Compare with the original self.assertEqual(timeranges[n], newtimerange) n += 1
def test_readAndParseTbuff(self): '''flaghelper: compare the read and parse and apply tbuff''' print '' # MJD in seconds of timeranges are these # <startTime>4891227930515540000 <endTime>4891227932453838000 # <startTime>4891228473545856000 <endTime>4891228473731891000 # <startTime>4891226924455911000 <endTime>4891226927502314000 # <startTime>4891228838164987000 <endTime>4891228838418996000 # <startTime>4891228609440808000 <endTime>4891228612489617000 online = [ "antenna='DV03&&*' timerange='2013/11/15/10:25:30.516~2013/11/15/10:25:32.454'", "antenna='DA44&&*' timerange='2013/11/15/10:34:33.546~2013/11/15/10:34:33.732'", "antenna='DA46&&*' timerange='2013/11/15/10:08:44.456~2013/11/15/10:08:47.502'", "antenna='DV09&&*' timerange='2013/11/15/10:18:11.798~2013/11/15/10:18:13.837'", "antenna='DV05&&*' timerange='2013/11/15/10:40:38.165~2013/11/15/10:40:38.419'" ] myinput = "antenna='DV03&&*' timerange='2013/11/15/10:25:30.516~2013/11/15/10:25:32.454'\n"\ "antenna='DA44&&*' timerange='2013/11/15/10:34:33.546~2013/11/15/10:34:33.732'\n"\ "antenna='DA46&&*' timerange='2013/11/15/10:08:44.456~2013/11/15/10:08:47.502'\n"\ "antenna='DV09&&*' timerange='2013/11/15/10:18:11.798~2013/11/15/10:18:13.837'\n"\ "antenna='DV05&&*' timerange='2013/11/15/10:40:38.165~2013/11/15/10:40:38.419'" filename1 = 'flaghelperonline2.txt' create_input(myinput, filename1) # First timerange from online before padding origt = timerange = '2013/11/15/10:25:30.516~2013/11/15/10:25:32.454' # Apply tbuff to timeranges timebuffer = 1.1 dlist1 = fh.readAndParse([filename1], tbuff=timebuffer) self.assertEqual(len(dlist1), 5) # Get the first padded timerange from output padt = dlist1[0]['timerange'] # Revert the tbuff application manually t0, t1 = padt.split('~', 1) startTime = qa.totime(t0)['value'] startTimeSec = float((startTime * 24 * 3600) + timebuffer) startTimeSec = qa.quantity(startTimeSec, 's') paddedT0 = qa.time(startTimeSec, form='ymd', prec=9)[0] # end time endTime = qa.totime(t1)['value'] endTimeSec = float((endTime * 24 * 3600) - timebuffer) endTimeSec = qa.quantity(endTimeSec, 's') paddedT1 = qa.time(endTimeSec, form='ymd', prec=9)[0] newtimerange = paddedT0 + '~' + paddedT1 # Compare with the original self.assertEqual(origt, newtimerange) # Compare with original values from Flag.xml xmlt0 = float(4891227930515540000) * 1.0E-9 xmlt1 = float(4891227932453838000) * 1.0E-9 self.assertAlmostEqual(xmlt0, startTimeSec['value'], places=3) self.assertAlmostEqual(xmlt1, endTimeSec['value'], places=3)
def mk_diskmodel(outname='disk', bdwidth='325MHz', direction='J2000 10h00m00.0s 20d00m00.0s', reffreq='2.8GHz', flux=660000.0, eqradius='16.166arcmin', polradius='16.166arcmin', pangle='21.1deg', index=None, cell='2.0arcsec', overwrite=True): ''' Create a blank solar disk model image (or optionally a data cube) outname String to use for part of the image and fits file names (default 'disk') direction String specifying the position of the Sun in RA and Dec. Default means use the standard string "J2000 10h00m00.0s 20d00m00.0s" reffreq The reference frequency to use for the disk model (the frequency at which the flux level applies). Default is '2.8GHz'. flux The flux density, in Jy, for the entire disk. Default is 66 sfu. eqradius The equatorial radius of the disk. Default is 16 arcmin + 10" (for typical extension of the radio limb) polradius The polar radius of the disk. Default is 16 arcmin + 10" (for typical extension of the radio limb) pangle The solar P-angle (geographic position of the N-pole of the Sun) in degrees E of N. This only matters if eqradius != polradius index The spectral index to use at other frequencies. Default None means use a constant flux density for all frequencies. cell The cell size (assumed square) to use for the image. The image size is determined from a standard radius of 960" for the Sun, divided by cell size, increased to nearest power of 512 pixels. The default is '2.0arcsec', which results in an image size of 1024 x 1024. Note that the frequency increment used is '325MHz', which is the width of EOVSA bands (not the width of individual science channels) ''' diskim = outname + reffreq + '.im' if os.path.exists(diskim): if overwrite: os.system('rm -rf {}'.format(diskim)) else: return diskim ia = iatool() cl = cltool() cl.done() ia.done() try: aspect = 1.01 # Enlarge the equatorial disk by 1% eqradius = qa.quantity(eqradius) diamajor = qa.quantity(2 * aspect * eqradius['value'], eqradius['unit']) polradius = qa.quantity(polradius) diaminor = qa.quantity(2 * polradius['value'], polradius['unit']) solrad = qa.convert(polradius, 'arcsec') except: print('Radius', eqradius, polradius, 'does not have the expected format, number + unit where unit is arcmin or arcsec') return try: cell = qa.convert(qa.quantity(cell), 'arcsec') cellsize = float(cell['value']) diskpix = solrad['value'] * 2 / cellsize cell_rad = qa.convert(cell, 'rad') except: print('Cell size', cell, 'does not have the expected format, number + unit where unit is arcmin or arcsec') return # Add 90 degrees to pangle, due to angle definition in addcomponent() -- it puts the majoraxis vertical pangle = qa.add(qa.quantity(pangle), qa.quantity('90deg')) mapsize = ((int(diskpix) / 512) + 1) * 512 # Flux density is doubled because it is split between XX and YY cl.addcomponent(dir=direction, flux=flux * 2, fluxunit='Jy', freq=reffreq, shape='disk', majoraxis=diamajor, minoraxis=diaminor, positionangle=pangle) cl.setrefdirframe(0, 'J2000') ia.fromshape(diskim, [mapsize, mapsize, 1, 1], overwrite=True) cs = ia.coordsys() cs.setunits(['rad', 'rad', '', 'Hz']) cell_rad_val = cell_rad['value'] cs.setincrement([-cell_rad_val, cell_rad_val], 'direction') epoch, ra, dec = direction.split() cs.setreferencevalue([qa.convert(ra, 'rad')['value'], qa.convert(dec, 'rad')['value']], type="direction") cs.setreferencevalue(reffreq, 'spectral') cs.setincrement(bdwidth, 'spectral') ia.setcoordsys(cs.torecord()) ia.setbrightnessunit("Jy/pixel") ia.modify(cl.torecord(), subtract=False) ia.close() ia.done() # cl.close() cl.done() return diskim
def split_core(vis, outputvis, datacolumn, field, spw, width, antenna, timebin, timerange, scan, intent, array, uvrange, correlation, observation, combine, keepflags): retval = True if not outputvis or outputvis.isspace(): raise ValueError, 'Please specify outputvis' myms = mstool() mytb = None if ((type(vis)==str) & (os.path.exists(vis))): myms.open(vis, nomodify=True) else: raise ValueError, 'Visibility data set not found - please verify the name' if os.path.exists(outputvis): myms.close() raise ValueError, "Output MS %s already exists - will not overwrite." % outputvis if (os.path.exists(outputvis+".flagversions")): myms.close() raise ValueError, "The flagversions \"%s.flagversions\" for the output MS already exist. Please delete." % outputvis # No longer needed. When did it get put in? Note that the default # spw='*' in myms.split ends up as '' since the default type for a variant # is BOOLVEC. (Of course!) Therefore both split and myms.split must # work properly when spw=''. #if(spw == ''): # spw = '*' if(type(antenna) == list): antenna = ', '.join([str(ant) for ant in antenna]) ## Accept digits without units ...assume seconds timebin = qa.convert(qa.quantity(timebin), 's')['value'] timebin = str(timebin) + 's' if timebin == '0s': timebin = '-1s' # MSStateGram is picky ('CALIBRATE_WVR.REFERENCE, OBSERVE_TARGET_ON_SOURCE' # doesn't work, but 'CALIBRATE_WVR.REFERENCE,OBSERVE_TARGET_ON_SOURCE' # does), and I don't want to mess with bison now. A .upper() might be a # good idea too, but the MS def'n v.2 does not say whether OBS_MODE should # be case-insensitive. intent = intent.replace(', ', ',') if '^' in spw: casalog.post("The interpretation of ^n in split's spw strings has changed from 'average n' to 'skip n' channels!", 'WARN') casalog.post("Watch for Slicer errors", 'WARN') if type(width) == str: try: if(width.isdigit()): width=[string.atoi(width)] elif(width.count('[') == 1 and width.count(']') == 1): width = width.replace('[', '') width = width.replace(']', '') splitwidth = width.split(',') width = [] for ws in splitwidth: if(ws.isdigit()): width.append(string.atoi(ws)) else: width = [1] except: raise TypeError, 'parameter width is invalid...using 1' if type(correlation) == list: correlation = ', '.join(correlation) correlation = correlation.upper() if hasattr(combine, '__iter__'): combine = ', '.join(combine) if type(spw) == list: spw = ','.join([str(s) for s in spw]) elif type(spw) == int: spw = str(spw) do_chan_mod = spw.find('^') > -1 # '0:2~11^1' would be pointless. if not do_chan_mod: # ...look in width. if type(width) == int and width > 1: do_chan_mod = True elif hasattr(width, '__iter__'): for w in width: if w > 1: do_chan_mod = True break do_both_chan_and_time_mod = (do_chan_mod and string.atof(timebin[:-1]) > 0.0) if do_both_chan_and_time_mod: # Do channel averaging first because it might be included in the spw # string. import tempfile # We want the directory outputvis is in, not /tmp, because /tmp # might not have enough space. # outputvis is itself a directory, so strip off a trailing slash if # it is present. # I don't know if giving tempfile an absolute directory is necessary - # dir='' is effectively '.' in Ubuntu. workingdir = os.path.abspath(os.path.dirname(outputvis.rstrip('/'))) cavms = tempfile.mkdtemp(suffix=outputvis, dir=workingdir) casalog.post('Channel averaging to ' + cavms) if not myms.split(outputms=cavms, field=field, spw=spw, step=width, baseline=antenna, subarray=array, timebin='', time=timerange, whichcol=datacolumn, scan=scan, uvrange=uvrange, combine=combine, correlation=correlation, intent=intent, obs=str(observation)): myms.close() if os.path.isdir(cavms): import shutil shutil.rmtree(cavms) return False # The selection was already made, so blank them before time averaging. field = '' spw = '' width = [1] antenna = '' array = '' timerange = '' datacolumn = 'all' scan = '' intent = '' uvrange = '' observation = '' myms.close() myms.open(cavms) casalog.post('Starting time averaging') if keepflags: taqlstr = '' else: taqlstr = 'NOT (FLAG_ROW OR ALL(FLAG))' if not myms.split(outputms=outputvis, field=field, spw=spw, step=width, baseline=antenna, subarray=array, timebin=timebin, time=timerange, whichcol=datacolumn, scan=scan, uvrange=uvrange, combine=combine, correlation=correlation, taql=taqlstr, intent=intent, obs=str(observation)): myms.close() return False myms.close() if do_both_chan_and_time_mod: import shutil shutil.rmtree(cavms) # Write history to output MS, not the input ms. try: param_names = split_core.func_code.co_varnames[:split_core.func_code.co_argcount] param_vals = [eval(p) for p in param_names] retval &= write_history(myms, outputvis, 'oldsplit', param_names, param_vals, casalog) except Exception, instance: casalog.post("*** Error \'%s\' updating HISTORY" % (instance), 'WARN')
def clean_iter( tim, vis, imageprefix, imagesuffix, twidth, doreg, usephacenter, reftime, ephem, msinfo, toTb, overwrite, selectdata, field, spw, uvrange, antenna, scan, observation, intent, datacolumn, imsize, cell, phasecenter, stokes, projection, startmodel, specmode, reffreq, nchan, start, width, outframe, veltype, restfreq, interpolation, gridder, facets, chanchunks, wprojplanes, vptable, usepointing, mosweight, aterm, psterm, wbawp, conjbeams, cfcache, computepastep, rotatepastep, pblimit, normtype, deconvolver, scales, nterms, smallscalebias, restoration, restoringbeam, pbcor, outlierfile, weighting, robust, npixels, uvtaper, niter, gain, threshold, nsigma, cycleniter, cyclefactor, minpsffraction, maxpsffraction, interactive, usemask, mask, pbmask, sidelobethreshold, noisethreshold, lownoisethreshold, negativethreshold, smoothfactor, minbeamfrac, cutthreshold, growiterations, dogrowprune, minpercentchange, verbose, restart, savemodel, calcres, calcpsf, parallel, subregion, tmpdir, btidx): from tclean_cli import tclean_cli as tclean from split_cli import split_cli as split bt = btidx # 0 if bt + twidth < len(tim) - 1: et = btidx + twidth - 1 else: et = len(tim) - 1 if bt == 0: bt_d = tim[bt] - ((tim[bt + 1] - tim[bt]) / 2) else: bt_d = tim[bt] - ((tim[bt] - tim[bt - 1]) / 2) if et == (len(tim) - 1) or et == -1: et_d = tim[et] + ((tim[et] - tim[et - 1]) / 2) else: et_d = tim[et] + ((tim[et + 1] - tim[et]) / 2) timerange = qa.time(qa.quantity(bt_d, 's'), prec=9, form='ymd')[0] + '~' + \ qa.time(qa.quantity(et_d, 's'), prec=9, form='ymd')[0] btstr = qa.time(qa.quantity(bt_d, 's'), prec=9, form='fits')[0] etstr = qa.time(qa.quantity(et_d, 's'), prec=9, form='fits')[0] print('cleaning timerange: ' + timerange) image0 = btstr.replace(':', '').replace('-', '') imname = imageprefix + image0 + imagesuffix # ms_tmp = tmpdir + image0 + '.ms' # print('checkpoint 1') # # split(vis=vis, outputvis=ms_tmp, field=field, scan=scan, antenna=antenna, timerange=timerange, # # datacolumn=datacolumn) # ms.open(vis) # print('checkpoint 1-1') # ms.split(ms_tmp,field=field, scan=scan, baseline=antenna, time=timerange,whichcol=datacolumn) # print('checkpoint 1-2') # ms.close() # print('checkpoint 2') if overwrite or (len(glob.glob(imname + '*')) == 0): os.system('rm -rf {}*'.format(imname)) try: tclean(vis=vis, selectdata=selectdata, field=field, spw=spw, timerange=timerange, uvrange=uvrange, antenna=antenna, scan=scan, observation=observation, intent=intent, datacolumn=datacolumn, imagename=imname, imsize=imsize, cell=cell, phasecenter=phasecenter, stokes=stokes, projection=projection, startmodel=startmodel, specmode=specmode, reffreq=reffreq, nchan=nchan, start=start, width=width, outframe=outframe, veltype=veltype, restfreq=restfreq, interpolation=interpolation, gridder=gridder, facets=facets, chanchunks=chanchunks, wprojplanes=wprojplanes, vptable=vptable, usepointing=usepointing, mosweight=mosweight, aterm=aterm, psterm=psterm, wbawp=wbawp, conjbeams=conjbeams, cfcache=cfcache, computepastep=computepastep, rotatepastep=rotatepastep, pblimit=pblimit, normtype=normtype, deconvolver=deconvolver, scales=scales, nterms=nterms, smallscalebias=smallscalebias, restoration=restoration, restoringbeam=restoringbeam, pbcor=pbcor, outlierfile=outlierfile, weighting=weighting, robust=robust, npixels=npixels, uvtaper=uvtaper, niter=niter, gain=gain, threshold=threshold, nsigma=nsigma, cycleniter=cycleniter, cyclefactor=cyclefactor, minpsffraction=minpsffraction, maxpsffraction=maxpsffraction, interactive=interactive, usemask=usemask, mask=mask, pbmask=pbmask, sidelobethreshold=sidelobethreshold, noisethreshold=noisethreshold, lownoisethreshold=lownoisethreshold, negativethreshold=negativethreshold, smoothfactor=smoothfactor, minbeamfrac=minbeamfrac, cutthreshold=cutthreshold, growiterations=growiterations, dogrowprune=dogrowprune, minpercentchange=minpercentchange, verbose=verbose, restart=restart, savemodel=savemodel, calcres=calcres, calcpsf=calcpsf, parallel=parallel) # print('checkpoint 3') if pbcor: clnjunks = [ '.flux', '.mask', '.model', '.psf', '.residual', '.pb', '.sumwt', '.image' ] else: clnjunks = [ '.flux', '.mask', '.model', '.psf', '.residual', '.pb', '.sumwt', '.image.pbcor' ] for clnjunk in clnjunks: if os.path.exists(imname + clnjunk): shutil.rmtree(imname + clnjunk) if pbcor: os.system('mv {} {}'.format(imname + '.image.pbcor', imname + '.image')) except: print('error in cleaning image: ' + btstr) return [False, btstr, etstr, ''] else: print(imname + ' exists. Clean task aborted.') if doreg and not os.path.isfile(imname + '.fits'): # ephem.keys() # msinfo.keys() try: # check if ephemfile and msinfofile exist if not ephem: print( "ephemeris info does not exist, querying from JPL Horizons on the fly" ) ephem = hf.read_horizons(vis=vis) if not msinfo: print("ms info not provided, generating one on the fly") msinfo = hf.read_msinfo(vis) hf.imreg(vis=vis, ephem=ephem, msinfo=msinfo, timerange=timerange, reftime=reftime, imagefile=imname + '.image', fitsfile=imname + '.fits', toTb=toTb, scl100=False, usephacenter=usephacenter, subregion=subregion) if os.path.exists(imname + '.fits'): shutil.rmtree(imname + '.image') return [True, btstr, etstr, imname + '.fits'] else: return [False, btstr, etstr, ''] except: print('error in registering image: ' + btstr) return [False, btstr, etstr, imname + '.image'] else: if os.path.exists(imname + '.image'): return [True, btstr, etstr, imname + '.image'] else: return [False, btstr, etstr, '']
def predictcomp(objname=None, standard=None, epoch=None, minfreq=None, maxfreq=None, nfreqs=None, prefix=None, antennalist=None, showplot=None, savefig=None, symb=None, include0amp=None, include0bl=None, blunit=None, bl0flux=None): """ Writes a component list named clist to disk and returns a dict of {'clist': clist, 'objname': objname, 'angdiam': angular diameter in radians (if used in clist), 'standard': standard, 'epoch': epoch, 'freqs': pl.array of frequencies, in GHz, 'uvrange': pl.array of baseline lengths, in m, 'amps': pl.array of predicted visibility amplitudes, in Jy, 'savedfig': False or, if made, the filename of a plot.} or False on error. objname: An object supported by standard. standard: A standard for calculating flux densities, as in setjy. Default: 'Butler-JPL-Horizons 2010' epoch: The epoch to use for the calculations. Irrelevant for extrasolar standards. minfreq: The minimum frequency to use. Example: '342.0GHz' maxfreq: The maximum frequency to use. Default: minfreq Example: '346.0GHz' Example: '', anything <= 0, or None: use minfreq. nfreqs: The number of frequencies to use. Default: 1 if minfreq == maxfreq, 2 otherwise. prefix: The component list will be saved to prefix + '<objname>_spw0_<minfreq><epoch>.cl' Default: '' antennalist: An array configuration file as used by simdata. If given, a plot of S vs. |u| will be made. Default: '' (None, just make clist.) showplot: Whether or not to show the plot on screen. Subparameter of antennalist. Default: Necessarily False if antennalist is not specified. True otherwise. savefig: Filename for saving a plot of S vs. |u|. Subparameter of antennalist. Default: False (necessarily if antennalist is not specified) Examples: True (save to prefix + '.png') 'myplot.png' (save to myplot.png) symb: One of matplotlib's codes for plot symbols: .:,o^v<>s+xDd234hH|_ default: '.' include0amp: Force the lower limit of the amplitude axis to 0. Default: False include0bl: Force the lower limit of the baseline length axis to 0. blunit: Unit of the baseline length bl0flux: show zero baseline flux """ retval = False try: casalog.origin('predictcomp') # some parameter minimally required if objname == '': raise Exception, "Error, objname is undefined" if minfreq == '': raise Exception, "Error, minfreq is undefined" minfreqq = qa.quantity(minfreq) minfreqHz = qa.convert(minfreqq, 'Hz')['value'] try: maxfreqq = qa.quantity(maxfreq) except Exception, instance: maxfreqq = minfreqq frequnit = maxfreqq['unit'] maxfreqHz = qa.convert(maxfreqq, 'Hz')['value'] if maxfreqHz <= 0.0: maxfreqq = minfreqq maxfreqHz = minfreqHz if minfreqHz != maxfreqHz: if nfreqs < 2: nfreqs = 2 else: nfreqs = 1 freqs = pl.linspace(minfreqHz, maxfreqHz, nfreqs) myme = metool() mepoch = myme.epoch('UTC', epoch) #if not prefix: ## meanfreq = {'value': 0.5 * (minfreqHz + maxfreqHz), ## 'unit': frequnit} ## prefix = "%s%s_%.7g" % (objname, epoch.replace('/', '-'), ## minfreqq['value']) ## if minfreqHz != maxfreqHz: ## prefix += "to" + maxfreq ## else: ## prefix += minfreqq['unit'] ## prefix += "_" # prefix = '' # if not prefix: if not os.access("./", os.W_OK): casalog.post( "No write access in the current directory, trying to write cl to /tmp...", "WARN") prefix = "/tmp/" if not os.access(prefix, os.W_OK): casalog.post("No write access to /tmp to write cl file", "SEVERE") return False else: prefixdir = os.path.dirname(prefix) if prefixdir == '/' and len(prefix) > 1: prefix = prefix + '/' prefixdir = os.path.dirname(prefix) if not os.path.exists(prefixdir): prefixdirs = prefixdir.split('/') if prefixdirs[0] == "" and len(prefixdirs) > 1: rootdir = "/" + prefixdirs[1] else: rootdir = "./" if os.access(rootdir, os.W_OK): if prefixdir != '': os.makedirs(prefixdir) else: casalog.post( "No write access to " + rootdir + " to write cl file", "SEVERE") return False # Get clist myim = imtool() if hasattr(myim, 'predictcomp'): casalog.post('local im instance created', 'DEBUG1') else: casalog.post('Error creating a local im instance.', 'SEVERE') return False #print "FREQS=",freqs # output CL file name is fixed : prefix+"spw0_"+minfreq+mepoch.cl minfreqGHz = qa.convert(qa.quantity(minfreq), 'GHz')['value'] decimalfreq = minfreqGHz - int(minfreqGHz) decimalepoch = mepoch['m0']['value'] - int(mepoch['m0']['value']) if decimalfreq == 0.0: minfreqGHzStr = str(int(minfreqGHz)) + 'GHz' else: minfreqGHzStr = str(minfreqGHz) + 'GHz' if decimalepoch == 0.0: epochStr = str(int(mepoch['m0']['value'])) + 'd' else: epochStr = str(mepoch['m0']['value']) + 'd' outfilename = "spw0_" + objname + "_" + minfreqGHzStr + epochStr + '.cl' outfilename = prefix + outfilename if (os.path.exists(outfilename) and os.path.isdir(outfilename)): shutil.rmtree(outfilename) casalog.post("Removing the existing componentlist, " + outfilename) if standard == 'Butler-JPL-Horizons 2012': clist = predictSolarObjectCompList(objname, mepoch, freqs.tolist(), prefix) else: clist = myim.predictcomp(objname, standard, mepoch, freqs.tolist(), prefix) #print "created componentlist =",clist if os.path.isdir(clist): # The spw0 is useless here, but it is added by FluxStandard for the sake of setjy. casalog.post('The component list was saved to ' + clist) retval = { 'clist': clist, 'objname': objname, 'standard': standard, 'epoch': mepoch, 'freqs (GHz)': 1.0e-9 * freqs, 'antennalist': antennalist } mycl = cltool() mycl.open(clist) comp = mycl.getcomponent(0) zeroblf = comp['flux']['value'] if standard == 'Butler-JPL-Horizons 2012': f0 = comp['spectrum']['frequency']['m0']['value'] else: f0 = retval['freqs (GHz)'][0] casalog.post("Zero baseline flux %s @ %sGHz " % (zeroblf, f0), 'INFO') mycl.close(False) # False prevents the stupid warning. for k in ('shape', 'spectrum'): retval[k] = comp[k] if antennalist: retval['spectrum']['bl0flux'] = {} retval['spectrum']['bl0flux']['value'] = zeroblf[0] retval['spectrum']['bl0flux']['unit'] = 'Jy' retval['savedfig'] = savefig if not bl0flux: zeroblf = [0.0] retval.update( plotcomp(retval, showplot, wantdict=True, symb=symb, include0amp=include0amp, include0bl=include0bl, blunit=blunit, bl0flux=zeroblf[0])) else: retval['savedfig'] = None else: casalog.post("There was an error in making the component list.", 'SEVERE')
def ptclean(vis, imageprefix, ncpu, twidth, doreg, overwrite, ephemfile, msinfofile, outlierfile, field, spw, selectdata, timerange, uvrange, antenna, scan, observation, intent, mode, resmooth, gridmode, wprojplanes, facets, cfcache, rotpainc, painc, aterm, psterm, mterm, wbawp, conjbeams, epjtable, interpolation, niter, gain, threshold, psfmode, imagermode, ftmachine, mosweight, scaletype, multiscale, negcomponent, smallscalebias, interactive, mask, nchan, start, width, outframe, veltype, imsize, cell, phasecenter, restfreq, stokes, weighting, robust, uvtaper, outertaper, innertaper, modelimage, restoringbeam, pbcor, minpb, usescratch, noise, npixels, npercycle, cyclefactor, cyclespeedup, nterms, reffreq, chaniter, flatnoise, allowchunk): if not (type(ncpu) is int): casalog.post('ncpu should be an integer') ncpu = 8 if doreg: # check if ephemfile and msinfofile exist try: ephem = vla_prep.read_horizons(ephemfile=ephemfile) except ValueError: print("error in reading ephemeris file") if not os.path.isfile(msinfofile): print("msinfofile does not exist!") else: ephem = None # get number of time pixels ms.open(vis) ms.selectinit() timfreq = ms.getdata(['time', 'axis_info'], ifraxis=True) tim = timfreq['time'] # dt = tim[1]-tim[0] #need to change to median of all time intervals dt = np.median(np.diff(tim)) freq = timfreq['axis_info']['freq_axis']['chan_freq'].flatten() ms.close() if twidth < 1 or twidth > len(tim): casalog.post( 'twidth not between 1 and # of time pixels in the dataset. Change to 1' ) twidth = 1 # find out the start and end time index according to the parameter timerange # if not defined (empty string), use start and end from the entire time of the ms if not timerange: btidx = 0 etidx = len(tim) - 1 else: try: (tstart, tend) = timerange.split('~') bt_s = qa.convert(qa.quantity(tstart, 's'), 's')['value'] et_s = qa.convert(qa.quantity(tend, 's'), 's')['value'] # only time is given but not date, add the date (at 0 UT) from the first record if bt_s < 86400. or et_s < 86400.: bt_s += np.fix( qa.convert(qa.quantity(tim[0], 's'), 'd')['value']) * 86400. et_s += np.fix( qa.convert(qa.quantity(tim[0], 's'), 'd')['value']) * 86400. btidx = np.argmin(np.abs(tim - bt_s)) etidx = np.argmin(np.abs(tim - et_s)) # make the indice back to those bracket by the timerange if tim[btidx] < bt_s: btidx += 1 if tim[etidx] > et_s: etidx -= 1 if etidx <= btidx: print "ending time must be greater than starting time" print "reinitiating to the entire time range" btidx = 0 etidx = len(tim) - 1 except ValueError: print "keyword 'timerange' has a wrong format" btstr = qa.time(qa.quantity(tim[btidx], 's'), prec=9, form='fits')[0] etstr = qa.time(qa.quantity(tim[etidx], 's'), prec=9, form='fits')[0] iterable = range(btidx, etidx + 1, twidth) print 'First time pixel: ' + btstr print 'Last time pixel: ' + etstr print str(len(iterable)) + ' images to clean...' res = [] # partition clnpart = partial( clean_iter, tim, freq, vis, imageprefix, ncpu, twidth, doreg, overwrite, ephemfile, ephem, msinfofile, outlierfile, field, spw, selectdata, uvrange, antenna, scan, observation, intent, mode, resmooth, gridmode, wprojplanes, facets, cfcache, rotpainc, painc, aterm, psterm, mterm, wbawp, conjbeams, epjtable, interpolation, niter, gain, threshold, psfmode, imagermode, ftmachine, mosweight, scaletype, multiscale, negcomponent, smallscalebias, interactive, mask, nchan, start, width, outframe, veltype, imsize, cell, phasecenter, restfreq, stokes, weighting, robust, uvtaper, outertaper, innertaper, modelimage, restoringbeam, pbcor, minpb, usescratch, noise, npixels, npercycle, cyclefactor, cyclespeedup, nterms, reffreq, chaniter, flatnoise, allowchunk) timelapse = 0 t0 = time() # parallelization para = 1 if para: casalog.post('Perform clean in parallel ...') pool = mp.Pool(ncpu) # res = pool.map_async(clnpart, iterable) res = pool.map(clnpart, iterable) pool.close() pool.join() else: for i in iterable: res.append(clnpart(i)) t1 = time() timelapse = t1 - t0 print 'It took %f secs to complete' % timelapse # repackage this into a single dictionary results = {'succeeded': [], 'timestamps': [], 'imagenames': []} for r in res: results['succeeded'].append(r[0]) results['timestamps'].append(r[1]) results['imagenames'].append(r[2]) return results
def clean_iter(tim, freq, vis, imageprefix, ncpu, twidth, doreg, overwrite, ephemfile, ephem, msinfofile, outlierfile, field, spw, selectdata, uvrange, antenna, scan, observation, intent, mode, resmooth, gridmode, wprojplanes, facets, cfcache, rotpainc, painc, aterm, psterm, mterm, wbawp, conjbeams, epjtable, interpolation, niter, gain, threshold, psfmode, imagermode, ftmachine, mosweight, scaletype, multiscale, negcomponent, smallscalebias, interactive, mask, nchan, start, width, outframe, veltype, imsize, cell, phasecenter, restfreq, stokes, weighting, robust, uvtaper, outertaper, innertaper, modelimage, restoringbeam, pbcor, minpb, usescratch, noise, npixels, npercycle, cyclefactor, cyclespeedup, nterms, reffreq, chaniter, flatnoise, allowchunk, btidx): from taskinit import ms from taskinit import qa # from __casac__.quanta import quanta as qa from __main__ import default, inp from clean import clean bt = btidx # 0 if bt + twidth < len(tim) - 1: et = btidx + twidth - 1 else: et = len(tim) - 1 # tim_d = tim/3600./24.-np.fix(tim/3600./24.) if bt == 0: bt_d = tim[bt] - ((tim[bt + 1] - tim[bt]) / 2) else: bt_d = tim[bt] - ((tim[bt] - tim[bt - 1]) / 2) if et == (len(tim) - 1) or et == -1: et_d = tim[et] + ((tim[et] - tim[et - 1]) / 2) else: et_d = tim[et] + ((tim[et + 1] - tim[et]) / 2) # # bt_d=tim[bt] # et_d=tim[et]+0.005 timerange = qa.time(qa.quantity(bt_d, 's'), prec=9)[0] + '~' + \ qa.time(qa.quantity(et_d, 's'), prec=9)[0] tmid = (bt_d + et_d) / 2. btstr = qa.time(qa.quantity(bt_d, 's'), prec=9, form='fits')[0] print 'cleaning timerange: ' + timerange try: image0 = btstr.replace(':', '').replace('-', '') imname = imageprefix + image0 if overwrite or (len(glob.glob(imname + '*')) == 0): # inp(taskname = 'clean') os.system('rm -rf {}*'.format(imname)) clean(vis=vis, imagename=imname, outlierfile=outlierfile, field=field, spw=spw, selectdata=selectdata, timerange=timerange, uvrange=uvrange, antenna=antenna, scan=scan, observation=str(observation), intent=intent, mode=mode, resmooth=resmooth, gridmode=gridmode, wprojplanes=wprojplanes, facets=facets, cfcache=cfcache, rotpainc=rotpainc, painc=painc, psterm=psterm, aterm=aterm, mterm=mterm, wbawp=wbawp, conjbeams=conjbeams, epjtable=epjtable, interpolation=interpolation, niter=niter, gain=gain, threshold=threshold, psfmode=psfmode, imagermode=imagermode, ftmachine=ftmachine, mosweight=mosweight, scaletype=scaletype, multiscale=multiscale, negcomponent=negcomponent, smallscalebias=smallscalebias, interactive=interactive, mask=mask, nchan=nchan, start=start, width=width, outframe=outframe, veltype=veltype, imsize=imsize, cell=cell, phasecenter=phasecenter, restfreq=restfreq, stokes=stokes, weighting=weighting, robust=robust, uvtaper=uvtaper, outertaper=outertaper, innertaper=innertaper, modelimage=modelimage, restoringbeam=restoringbeam, pbcor=pbcor, minpb=minpb, usescratch=usescratch, noise=noise, npixels=npixels, npercycle=npercycle, cyclefactor=cyclefactor, cyclespeedup=cyclespeedup, nterms=nterms, reffreq=reffreq, chaniter=chaniter, flatnoise=flatnoise, allowchunk=False) clnjunks = ['.flux', '.mask', '.model', '.psf', '.residual'] for clnjunk in clnjunks: if os.path.exists(imname + clnjunk): shutil.rmtree(imname + clnjunk) else: print imname + ' existed. Clean task aborted.' if doreg and not os.path.isfile(imname + '.fits'): # check if ephemfile and msinfofile exist if not ephem: print("ephemeris info does not exist!") return reftime = [timerange] helio = vla_prep.ephem_to_helio(msinfo=msinfofile, ephem=ephem, reftime=reftime) imagefile = [imname + '.image'] fitsfile = [imname + '.fits'] vla_prep.imreg(imagefile=imagefile, fitsfile=fitsfile, helio=helio, toTb=False, scl100=True) if os.path.exists(imname + '.fits'): return [True, btstr, imname + '.fits'] else: return [False, btstr, ''] else: if os.path.exists(imname + '.image'): return [True, btstr, imname + '.image'] else: return [False, btstr, ''] except: print('error in processing image: ' + btstr) return [False, btstr, '']
def subvs2(vis=None, outputvis=None, timerange='', spw='', mode=None, subtime1=None, subtime2=None, smoothaxis=None, smoothtype=None, smoothwidth=None, splitsel=None, reverse=None, overwrite=None): """Perform vector subtraction for visibilities Keyword arguments: vis -- Name of input visibility file (MS) default: none; example: vis='ngc5921.ms' outputvis -- Name of output uv-subtracted visibility file (MS) default: none; example: outputvis='ngc5921_src.ms' timerange -- Time range of performing the UV subtraction: default='' means all times. examples: timerange = 'YYYY/MM/DD/hh:mm:ss~YYYY/MM/DD/hh:mm:ss' timerange = 'hh:mm:ss~hh:mm:ss' spw -- Select spectral window/channel. default = '' all the spectral channels. Example: spw='0:1~20' mode -- operation mode default 'linear' mode = 'linear': use a linear fit for the background to be subtracted mode = 'lowpass': act as a lowpass filter---smooth the data using different smooth types and window sizes. Can be performed along either time or frequency axis mode = 'highpass': act as a highpass filter---smooth the data first, and subtract the smoothed data from the original. Can be performed along either time or frequency axis mode = 'linear' expandable parameters: subtime1 -- Time range 1 of the background to be subtracted from the data default='' means all times. format: timerange = 'YYYY/MM/DD/hh:mm:ss~YYYY/MM/DD/hh:mm:ss' timerange = 'hh:mm:ss~hh:mm:ss' subtime2 -- Time range 2 of the backgroud to be subtracted from the data default='' means all times. examples: timerange = 'YYYY/MM/DD/hh:mm:ss~YYYY/MM/DD/hh:mm:ss' timerange = 'hh:mm:ss~hh:mm:ss' mode = 'lowpass' or 'highpass' expandable parameters: smoothaxis -- axis of smooth Default: 'time' smoothaxis = 'time': smooth is along the time axis smoothaxis = 'freq': smooth is along the frequency axis smoothtype -- type of the smooth depending on the convolving kernel Default: 'flat' smoothtype = 'flat': convolving kernel is a flat rectangle, equivalent to a boxcar moving smooth smoothtype = 'hanning': Hanning smooth kernel. See numpy.hanning smoothtype = 'hamming': Hamming smooth kernel. See numpy.hamming smoothtype = 'bartlett': Bartlett smooth kernel. See numpy.bartlett smoothtype = 'blackman': Blackman smooth kernel. See numpy.blackman smoothwidth -- width of the smooth kernel Default: 5 Examples: smoothwidth=5, meaning the width is 5 pixels splitsel -- True or False. default = False. If splitsel = False, then the entire input measurement set is copied as the output measurement set (outputvis), with background subtracted at selected timerange and spectral channels. If splitsel = True,then only the selected timerange and spectral channels are copied into the output measurement set (outputvis). reverse -- True or False. default = False. If reverse = False, then the times indicated by subtime1 and/or subtime2 are treated as background and subtracted; If reverse = True, then reverse the sign of the background-subtracted data. The option can be used for mapping absorptive structure. overwrite -- True or False. default = False. If overwrite = True and outputvis already exists, the selected subtime and spw in the output measurment set will be replaced with background subtracted visibilities """ # check the visbility ms casalog.post('input parameters:') casalog.post('vis: ' + vis) casalog.post('outputvis: ' + outputvis) casalog.post('smoothaxis: ' + smoothaxis) casalog.post('smoothtype: ' + smoothtype) casalog.post('smoothwidth: ' + str(smoothwidth)) if not outputvis or outputvis.isspace(): raise (ValueError, 'Please specify outputvis') if os.path.exists(outputvis): if overwrite: print( "The already existing output measurement set will be updated.") else: raise (ValueError, "Output MS %s already exists - will not overwrite." % outputvis) else: if not splitsel: shutil.copytree(vis, outputvis) else: ms.open(vis, nomodify=True) ms.split(outputvis, spw=spw, time=timerange, whichcol='DATA') ms.close() if timerange and (type(timerange) == str): [btimeo, etimeo] = timerange.split('~') btimeosec = qa.getvalue(qa.convert(qa.totime(btimeo), 's')) etimeosec = qa.getvalue(qa.convert(qa.totime(etimeo), 's')) timebinosec = etimeosec - btimeosec if timebinosec < 0: raise Exception( 'Negative timebin! Please check the "timerange" parameter.') casalog.post('Selected timerange: ' + timerange + ' as the time for UV subtraction.') else: casalog.post( 'Output timerange not specified, using the entire timerange') if spw and (type(spw) == str): spwlist = spw.split(';') else: casalog.post('spw not specified, use all frequency channels') # read the output data datams = mstool() datams.open(outputvis, nomodify=False) datamsmd = msmdtool() datamsmd.open(outputvis) spwinfod = datams.getspectralwindowinfo() spwinfok = spwinfod.keys() spwinfok.sort(key=int) spwinfol = [spwinfod[k] for k in spwinfok] for s, spi in enumerate(spwinfol): print('processing spectral window {}'.format(spi['SpectralWindowId'])) datams.selectinit(reset=True) staql = {'time': '', 'spw': ''} if not splitsel: # outputvis is identical to input visibility, do the selection if timerange and (type(timerange == str)): staql['time'] = timerange if spw and (type(spw) == str): staql['spw'] = spwlist[s] if not spw and not timerange: # data selection is not made print('selecting all spws and times') staql['spw'] = str(spi['SpectralWindowId']) else: # outputvis is splitted, selections have already applied, select all the data print('split the selected spws and times') staql['spw'] = str(spi['SpectralWindowId']) datams.msselect(staql) orec = datams.getdata(['data', 'time', 'axis_info'], ifraxis=True) npol, nchan, nbl, ntim = orec['data'].shape print('dimension of output data', orec['data'].shape) casalog.post('Number of baselines: ' + str(nbl)) casalog.post('Number of spectral channels: ' + str(nchan)) casalog.post('Number of time pixels: ' + str(ntim)) try: if mode == 'linear': # define and check the background time ranges if subtime1 and (type(subtime1) == str): [bsubtime1, esubtime1] = subtime1.split('~') bsubtime1sec = qa.getvalue( qa.convert(qa.totime(bsubtime1), 's')) esubtime1sec = qa.getvalue( qa.convert(qa.totime(esubtime1), 's')) timebin1sec = esubtime1sec - bsubtime1sec if timebin1sec < 0: raise Exception( 'Negative timebin! Please check the "subtime1" parameter.' ) casalog.post('Selected timerange 1: ' + subtime1 + ' as background for uv subtraction.') else: raise Exception( 'Please enter at least one timerange as the background' ) if subtime2 and (type(subtime2) == str): [bsubtime2, esubtime2] = subtime2.split('~') bsubtime2sec = qa.getvalue( qa.convert(qa.totime(bsubtime2), 's')) esubtime2sec = qa.getvalue( qa.convert(qa.totime(esubtime2), 's')) timebin2sec = esubtime2sec - bsubtime2sec if timebin2sec < 0: raise Exception( 'Negative timebin! Please check the "subtime2" parameter.' ) timebin2 = str(timebin2sec) + 's' casalog.post('Selected timerange 2: ' + subtime2 + ' as background for uv subtraction.') # plus 1s is to ensure averaging over the entire timerange else: casalog.post( 'Timerange 2 not selected, using only timerange 1 as background' ) # Select the background indicated by subtime1 ms.open(vis, nomodify=True) # Select the spw id # ms.msselect({'time': subtime1}) staql0 = {'time': subtime1, 'spw': ''} if spw and (type(spw) == str): staql0['spw'] = spwlist[s] else: staql0['spw'] = staql['spw'] ms.msselect(staql0) rec1 = ms.getdata(['data', 'time', 'axis_info'], ifraxis=True) # print('shape of the frequency matrix ',rec1['axis_info']['freq_axis']['chan_freq'].shape) sz1 = rec1['data'].shape print('dimension of selected background 1', rec1['data'].shape) # the data shape is (n_pol,n_channel,n_baseline,n_time), no need to reshape # rec1['data']=rec1['data'].reshape(sz1[0],sz1[1],sz1[2],nspw,sz1[3]/nspw,order='F') # print('reshaped rec1 ', rec1['data'].shape) rec1avg = np.average(rec1['data'], axis=3) casalog.post('Averaging the visibilities in subtime1: ' + subtime1) ms.close() if subtime2 and (type(subtime2) == str): ms.open(vis, nomodify=True) # Select the spw id staql0 = {'time': subtime2, 'spw': ''} if spw and (type(spw) == str): staql0['spw'] = spwlist[s] else: staql0['spw'] = staql['spw'] ms.msselect(staql0) rec2 = ms.getdata(['data', 'time', 'axis_info'], ifraxis=True) sz2 = rec2['data'].shape print('dimension of selected background 2', rec2['data'].shape) # rec2['data']=rec2['data'].reshape(sz2[0],sz2[1],sz2[2],nspw,sz2[3]/nspw,order='F') # print('reshaped rec1 ', rec2['data'].shape) rec2avg = np.average(rec2['data'], axis=3) ms.close() casalog.post('Averaged the visibilities in subtime2: ' + subtime2) if subtime1 and (not subtime2): casalog.post( 'Only "subtime1" is defined, subtracting background defined in subtime1: ' + subtime1) t1 = (np.amax(rec1['time']) + np.amin(rec1['time'])) / 2. print('t1: ', qa.time(qa.quantity(t1, 's'), form='ymd', prec=10)) for i in range(ntim): orec['data'][:, :, :, i] -= rec1avg if reverse: orec['data'][:, :, :, i] = -orec['data'][:, :, :, i] if subtime1 and subtime2 and (type(subtime2) == str): casalog.post( 'Both subtime1 and subtime2 are specified, doing linear interpolation between "subtime1" and "subtime2"' ) t1 = (np.amax(rec1['time']) + np.amin(rec1['time'])) / 2. t2 = (np.amax(rec2['time']) + np.amin(rec2['time'])) / 2. touts = orec['time'] print('t1: ', qa.time(qa.quantity(t1, 's'), form='ymd', prec=10)) print('t2: ', qa.time(qa.quantity(t2, 's'), form='ymd', prec=10)) for i in range(ntim): tout = touts[i] if tout > np.amax([t1, t2]): tout = np.amax([t1, t2]) elif tout < np.amin([t1, t2]): tout = np.amin([t1, t2]) orec['data'][:, :, :, i] -= (rec2avg - rec1avg) * ( tout - t1) / (t2 - t1) + rec1avg if reverse: orec['data'][:, :, :, i] = -orec['data'][:, :, :, i] elif mode == 'highpass': if smoothtype != 'flat' and smoothtype != 'hanning' and smoothtype != 'hamming' and smoothtype != 'bartlett' and smoothtype != 'blackman': raise Exception('Unknown smoothtype ' + str(smoothtype)) if smoothaxis == 'time': if smoothwidth <= 0 or smoothwidth >= ntim: raise Exception( 'Specified smooth width is <=0 or >= the total number of ' + smoothaxis) else: for i in range(orec['data'].shape[0]): for j in range(nchan): for k in range(nbl): orec['data'][i, j, k, :] -= signalsmooth.smooth( orec['data'][i, j, k, :], smoothwidth, smoothtype) if smoothaxis == 'freq': if smoothwidth <= 0 or smoothwidth >= nchan: raise Exception( 'Specified smooth width is <=0 or >= the total number of ' + smoothaxis) else: for i in range(orec['data'].shape[0]): for j in range(nbl): for k in range(ntim): orec['data'][i, :, j, k] -= signalsmooth.smooth( orec['data'][i, :, j, k], smoothwidth, smoothtype) elif mode == 'lowpass': if smoothtype != 'flat' and smoothtype != 'hanning' and smoothtype != 'hamming' and smoothtype != 'bartlett' and smoothtype != 'blackman': raise Exception('Unknown smoothtype ' + str(smoothtype)) if smoothaxis == 'time': if smoothwidth <= 0 or smoothwidth >= ntim: raise Exception( 'Specified smooth width is <=0 or >= the total number of ' + smoothaxis) else: for i in range(orec['data'].shape[0]): for j in range(nchan): for k in range(nbl): orec['data'][i, j, k, :] = signalsmooth.smooth( orec['data'][i, j, k, :], smoothwidth, smoothtype) if smoothaxis == 'freq': if smoothwidth <= 0 or smoothwidth >= nchan: raise Exception( 'Specified smooth width is <=0 or >= the total number of ' + smoothaxis) else: for i in range(orec['data'].shape[0]): for j in range(nbl): for k in range(ntim): orec['data'][i, :, j, k] = signalsmooth.smooth( orec['data'][i, :, j, k], smoothwidth, smoothtype) else: raise Exception('Unknown mode' + str(mode)) except Exception as instance: print('*** Error ***', instance) # orec['data']=orec['data'].reshape(szo[0],szo[1],szo[2],szo[3],order='F') # put the modified data back into the output visibility set del orec['time'] del orec['axis_info'] # ms.open(outputvis,nomodify=False) # if not splitsel: # outputvis is identical to input visibility, do the selection # if timerange and (type(timerange==str)): # datams.msselect({'time':timerange}) # if spw and (type(spw)==str): # datams.selectinit(datadescid=int(spwid)) # nchan=int(echan)-int(bchan)+1 # datams.selectchannel(nchan,int(bchan),1,1) # if not spw and not timerange: # data selection is not made # datams.selectinit(datadescid=0) # else: # outputvis is splitted, selections have already applied, select all the data # datams.selectinit(datadescid=0) datams.putdata(orec) datams.close() datamsmd.done()
def ksc_sim_gauss(projname='sim_7m_array_1GHz_gaus', antennalist='ksc-7m.cfg', dishdiam=7, imagename=None, indirection='J2000 14h26m46.0s -14d31m22.0s', incell='1arcsec', frequency='1.0GHz', inwidth='1MHz', radec_offset=[100., 100.], flux=50., majoraxis='40arcsec', minoraxis='27arcsec', positionangle='45.0deg', imsize=[512, 512]): """ Simulate observation of an input Gaussian model :param projname: project name for simobserve :param antennalist: cfg file of the array configuration :param dishdiam: diameter of each dish, in meters :param imagename: name (and path) for output clean image, psf, etc. :param indirection: phase center of the observation :param incell: pixel scale of the model/simulated image :param frequency: central frequency :param inwidth: frequency bandwidth :param radec_offset: offset of the Gaussian source from the phasecenter, in arcsec :param flux: total flux of the Gaussian source, in solar flux unit (sfu) :param majoraxis: FWHM size of the Gaussian source along the major axis :param minoraxis: FWHM size of the Gaussian source along the minor axis :param positionangle: position angle of the Gaussian source :param imsize: size of the model/simulated image, in pixels (x and y) :return: """ # set voltage patterns and primary beams for KSC 7 m. This is a placeholder for now (but required for PB correction) vp = vptool() if len(vp.getvp(telescope='KSC').keys()) == 0: vprec = vp.setpbairy(telescope='KSC', dishdiam='{0:.1f}m'.format(dishdiam), blockagediam='0.75m', maxrad='1.784deg', reffreq='1.0GHz', dopb=True) # make a Gaussian source cl = cltool() ia = iatool() cl.addcomponent(dir=indirection, flux=flux * 1e4, fluxunit='Jy', freq=frequency, shape="Gaussian", majoraxis=majoraxis, minoraxis=minoraxis, positionangle=positionangle) ia.fromshape("Gaussian.im", imsize + [1, 1], overwrite=True) cs = ia.coordsys() cs.setunits(['rad', 'rad', '', 'Hz']) cell_rad = qa.convert(qa.quantity(incell), "rad")['value'] cs.setincrement([-cell_rad, cell_rad], 'direction') ra_ref = qa.toangle(indirection.split(' ')[1]) dec_ref = qa.toangle(indirection.split(' ')[2]) ra = ra_ref['value'] - radec_offset[0] / 3600. dec = dec_ref['value'] - radec_offset[1] / 3600. cs.setreferencevalue([ qa.convert('{0:.4f}deg'.format(ra), 'rad')['value'], qa.convert('{0:.4f}deg'.format(dec), 'rad')['value'] ], type="direction") cs.setreferencevalue("1.0GHz", 'spectral') cs.setincrement('10MHz', 'spectral') ia.setcoordsys(cs.torecord()) ia.setbrightnessunit("Jy/pixel") ia.modify(cl.torecord(), subtract=False) ia.close() simobserve(project=projname, skymodel='Gaussian.im', indirection=indirection, incell=incell, incenter=frequency, inwidth=inwidth, hourangle='transit', refdate='2014/11/01', totaltime='120s', antennalist=antennalist, obsmode='int', overwrite=True) if not imagename: imagename = projname + '/tst' tclean(vis=projname + '/' + projname + '.' + antennalist.split('.')[0] + '.ms', imagename=imagename, imsize=imsize, cell=incell, phasecenter=indirection, niter=200, interactive=False) viewer(projname + '/' + projname + '.' + antennalist.split('.')[0] + '.skymodel') viewer(imagename + '.psf') viewer(imagename + '.image')
def ptclean3(vis, imageprefix, imagesuffix, ncpu, twidth, doreg, usephacenter, reftime, toTb, overwrite, selectdata, field, spw, timerange, uvrange, antenna, scan, observation, intent, datacolumn, imsize, cell, phasecenter, stokes, projection, startmodel, specmode, reffreq, nchan, start, width, outframe, veltype, restfreq, interpolation, gridder, facets, chanchunks, wprojplanes, vptable, usepointing, mosweight, aterm, psterm, wbawp, conjbeams, cfcache, computepastep, rotatepastep, pblimit, normtype, deconvolver, scales, nterms, smallscalebias, restoration, restoringbeam, pbcor, outlierfile, weighting, robust, npixels, uvtaper, niter, gain, threshold, nsigma, cycleniter, cyclefactor, minpsffraction, maxpsffraction, interactive, usemask, mask, pbmask, sidelobethreshold, noisethreshold, lownoisethreshold, negativethreshold, smoothfactor, minbeamfrac, cutthreshold, growiterations, dogrowprune, minpercentchange, verbose, restart, savemodel, calcres, calcpsf, parallel, subregion): if not (type(ncpu) is int): casalog.post('ncpu should be an integer') ncpu = 8 if doreg: # check if ephem and msinfo exist. If not, generate one on the fly try: ephem = hf.read_horizons(vis=vis) except ValueError: print("error in obtaining ephemeris") try: msinfo = hf.read_msinfo(vis) except ValueError: print("error in getting ms info") else: ephem = None msinfo = None if imageprefix: workdir = os.path.dirname(imageprefix) else: workdir = './' tmpdir = workdir + '/tmp/' if not os.path.exists(tmpdir): os.makedirs(tmpdir) # get number of time pixels ms.open(vis) ms.selectinit() timfreq = ms.getdata(['time', 'axis_info'], ifraxis=True) tim = timfreq['time'] ms.close() if twidth < 1: casalog.post('twidth less than 1. Change to 1') twidth = 1 if twidth > len(tim): casalog.post( 'twidth greater than # of time pixels in the dataset. Change to the timerange of the entire dateset' ) twidth = len(tim) # find out the start and end time index according to the parameter timerange # if not defined (empty string), use start and end from the entire time of the ms if not timerange: btidx = 0 etidx = len(tim) - 1 else: try: (tstart, tend) = timerange.split('~') bt_s = qa.convert(qa.quantity(tstart, 's'), 's')['value'] et_s = qa.convert(qa.quantity(tend, 's'), 's')['value'] # only time is given but not date, add the date (at 0 UT) from the first record if bt_s < 86400. or et_s < 86400.: bt_s += np.fix( qa.convert(qa.quantity(tim[0], 's'), 'd')['value']) * 86400. et_s += np.fix( qa.convert(qa.quantity(tim[0], 's'), 'd')['value']) * 86400. btidx = np.argmin(np.abs(tim - bt_s)) etidx = np.argmin(np.abs(tim - et_s)) # make the indice back to those bracket by the timerange if tim[btidx] < bt_s: btidx += 1 if tim[etidx] > et_s: etidx -= 1 if etidx <= btidx: print("ending time must be greater than starting time") print("reinitiating to the entire time range") btidx = 0 etidx = len(tim) - 1 except ValueError: print("keyword 'timerange' has a wrong format") btstr = qa.time(qa.quantity(tim[btidx], 's'), prec=9, form='fits')[0] etstr = qa.time(qa.quantity(tim[etidx], 's'), prec=9, form='fits')[0] iterable = range(btidx, etidx + 1, twidth) print('First time pixel: ' + btstr) print('Last time pixel: ' + etstr) print(str(len(iterable)) + ' images to clean...') res = [] # partition clnpart = partial( clean_iter, tim, vis, imageprefix, imagesuffix, twidth, doreg, usephacenter, reftime, ephem, msinfo, toTb, overwrite, selectdata, field, spw, uvrange, antenna, scan, observation, intent, datacolumn, imsize, cell, phasecenter, stokes, projection, startmodel, specmode, reffreq, nchan, start, width, outframe, veltype, restfreq, interpolation, gridder, facets, chanchunks, wprojplanes, vptable, usepointing, mosweight, aterm, psterm, wbawp, conjbeams, cfcache, computepastep, rotatepastep, pblimit, normtype, deconvolver, scales, nterms, smallscalebias, restoration, restoringbeam, pbcor, outlierfile, weighting, robust, npixels, uvtaper, niter, gain, threshold, nsigma, cycleniter, cyclefactor, minpsffraction, maxpsffraction, interactive, usemask, mask, pbmask, sidelobethreshold, noisethreshold, lownoisethreshold, negativethreshold, smoothfactor, minbeamfrac, cutthreshold, growiterations, dogrowprune, minpercentchange, verbose, restart, savemodel, calcres, calcpsf, parallel, subregion, tmpdir) timelapse = 0 t0 = time() # parallelization if ncpu > 1: import multiprocessing as mprocs casalog.post('Perform clean in parallel ...') print('Perform clean in parallel ...') pool = mprocs.Pool(ncpu) res = pool.map(clnpart, iterable) pool.close() pool.join() else: casalog.post('Perform clean in single process ...') print('Perform clean in single process ...') for i in iterable: res.append(clnpart(i)) t1 = time() timelapse = t1 - t0 print('It took %f secs to complete' % timelapse) # repackage this into a single dictionary results = { 'Succeeded': [], 'BeginTime': [], 'EndTime': [], 'ImageName': [] } for r in res: results['Succeeded'].append(r[0]) results['BeginTime'].append(r[1]) results['EndTime'].append(r[2]) results['ImageName'].append(r[3]) if os.path.exists(tmpdir): os.system('rm -rf ' + tmpdir) return results
def predictcomp(objname=None, standard=None, epoch=None, minfreq=None, maxfreq=None, nfreqs=None, prefix=None, antennalist=None, showplot=None, savefig=None, symb=None, include0amp=None, include0bl=None, blunit=None, bl0flux=None): """ Writes a component list named clist to disk and returns a dict of {'clist': clist, 'objname': objname, 'angdiam': angular diameter in radians (if used in clist), 'standard': standard, 'epoch': epoch, 'freqs': pl.array of frequencies, in GHz, 'uvrange': pl.array of baseline lengths, in m, 'amps': pl.array of predicted visibility amplitudes, in Jy, 'savedfig': False or, if made, the filename of a plot.} or False on error. objname: An object supported by standard. standard: A standard for calculating flux densities, as in setjy. Default: 'Butler-JPL-Horizons 2010' epoch: The epoch to use for the calculations. Irrelevant for extrasolar standards. minfreq: The minimum frequency to use. Example: '342.0GHz' maxfreq: The maximum frequency to use. Default: minfreq Example: '346.0GHz' Example: '', anything <= 0, or None: use minfreq. nfreqs: The number of frequencies to use. Default: 1 if minfreq == maxfreq, 2 otherwise. prefix: The component list will be saved to prefix + 'spw0_<objname>_<minfreq><epoch>.cl' Default: '' antennalist: An array configuration file as used by simdata. If given, a plot of S vs. |u| will be made. Default: '' (None, just make clist.) showplot: Whether or not to show the plot on screen. Subparameter of antennalist. Default: Necessarily False if antennalist is not specified. True otherwise. savefig: Filename for saving a plot of S vs. |u|. Subparameter of antennalist. Default: False (necessarily if antennalist is not specified) Examples: True (save to prefix + '.png') 'myplot.png' (save to myplot.png) symb: One of matplotlib's codes for plot symbols: .:,o^v<>s+xDd234hH|_ default: '.' include0amp: Force the lower limit of the amplitude axis to 0. Default: False include0bl: Force the lower limit of the baseline length axis to 0. blunit: Unit of the baseline length bl0flux: show zero baseline flux """ retval = False try: casalog.origin('predictcomp') # some parameter minimally required if objname=='': raise Exception, "Error, objname is undefined" if minfreq=='': raise Exception, "Error, minfreq is undefined" minfreqq = qa.quantity(minfreq) minfreqHz = qa.convert(minfreqq, 'Hz')['value'] try: maxfreqq = qa.quantity(maxfreq) except Exception, instance: maxfreqq = minfreqq frequnit = maxfreqq['unit'] maxfreqHz = qa.convert(maxfreqq, 'Hz')['value'] if maxfreqHz <= 0.0: maxfreqq = minfreqq maxfreqHz = minfreqHz if minfreqHz != maxfreqHz: if nfreqs < 2: nfreqs = 2 else: nfreqs = 1 freqs = pl.linspace(minfreqHz, maxfreqHz, nfreqs) myme = metool() mepoch = myme.epoch('UTC', epoch) #if not prefix: ## meanfreq = {'value': 0.5 * (minfreqHz + maxfreqHz), ## 'unit': frequnit} ## prefix = "%s%s_%.7g" % (objname, epoch.replace('/', '-'), ## minfreqq['value']) ## if minfreqHz != maxfreqHz: ## prefix += "to" + maxfreq ## else: ## prefix += minfreqq['unit'] ## prefix += "_" # prefix = '' # if not prefix: if not os.access("./",os.W_OK): casalog.post("No write access in the current directory, trying to write cl to /tmp...","WARN") prefix="/tmp/" if not os.access(prefix, os.W_OK): casalog.post("No write access to /tmp to write cl file", "SEVERE") return False else: prefixdir=os.path.dirname(prefix) if not os.path.exists(prefixdir): prefixdirs = prefixdir.split('/') if prefixdirs[0]=="": rootdir = "/" + prefixdirs[1] else: rootdir = "./" if os.access(rootdir,os.W_OK): os.makedirs(prefixdir) else: casalog.post("No write access to "+rootdir+" to write cl file", "SEVERE") return False # Get clist myim = imtool() if hasattr(myim, 'predictcomp'): casalog.post('local im instance created', 'DEBUG1') else: casalog.post('Error creating a local im instance.', 'SEVERE') return False #print "FREQS=",freqs if standard=='Butler-JPL-Horizons 2012': clist = predictSolarObjectCompList(objname, mepoch, freqs.tolist(), prefix) else: clist = myim.predictcomp(objname, standard, mepoch, freqs.tolist(), prefix) #print "created componentlist =",clist if os.path.isdir(clist): # The spw0 is useless here, but it is added by FluxStandard for the sake of setjy. casalog.post('The component list was saved to ' + clist) retval = {'clist': clist, 'objname': objname, 'standard': standard, 'epoch': mepoch, 'freqs (GHz)': 1.0e-9 * freqs, 'antennalist': antennalist} mycl = cltool() mycl.open(clist) comp = mycl.getcomponent(0) zeroblf=comp['flux']['value'] if standard=='Butler-JPL-Horizons 2012': f0=comp['spectrum']['frequency']['m0']['value'] else: f0=retval['freqs (GHz)'][0] casalog.post("Zero baseline flux %s @ %sGHz " % (zeroblf, f0),'INFO') mycl.close(False) # False prevents the stupid warning. for k in ('shape', 'spectrum'): retval[k] = comp[k] if antennalist: retval['spectrum']['bl0flux']={} retval['spectrum']['bl0flux']['value']=zeroblf[0] retval['spectrum']['bl0flux']['unit']='Jy' retval['savedfig'] = savefig if not bl0flux: zeroblf=[0.0] retval.update(plotcomp(retval, showplot, wantdict=True, symb=symb, include0amp=include0amp, include0bl=include0bl, blunit=blunit, bl0flux=zeroblf[0])) else: retval['savedfig'] = None else: casalog.post("There was an error in making the component list.", 'SEVERE')
if nspw > 1: casalog.post('Separate MS into %s spws'%nspw) config['nspw'] = nspw config['interpolation'] = interpolation if restfreq != '': config['restfreq'] = restfreq if outframe != '': config['outframe'] = outframe if phasecenter != '': config['phasecenter'] = phasecenter config['veltype'] = veltype config['preaverage'] = preaverage # Only parse timeaverage parameters when timebin > 0s if timeaverage: tb = qa.convert(qa.quantity(timebin), 's')['value'] if not tb > 0: raise Exception, "Parameter timebin must be > '0s' to do time averaging" if timeaverage: casalog.post('Parse time averaging parameters') config['timeaverage'] = True config['timebin'] = timebin config['timespan'] = timespan config['maxuvwdistance'] = maxuvwdistance if docallib: casalog.post('Parse docallib parameters') mycallib = callibrary() mycallib.read(callib) config['calibration'] = True
def read_msinfo(vis=None, msinfofile=None, use_scan_time=True): import glob # read MS information # msinfo = dict.fromkeys([ 'vis', 'scans', 'fieldids', 'btimes', 'btimestr', 'inttimes', 'ras', 'decs', 'observatory' ]) ms.open(vis) metadata = ms.metadata() observatory = metadata.observatorynames()[0] scans = ms.getscansummary() scanids = sorted(scans.keys(), key=lambda x: int(x)) nscanid = len(scanids) btimes = [] btimestr = [] etimes = [] fieldids = [] inttimes = [] dirs = [] ras = [] decs = [] ephem_file = glob.glob(vis + '/FIELD/EPHEM*SUN.tab') if ephem_file: print('Loading ephemeris info from {}'.format(ephem_file[0])) tb.open(ephem_file[0]) col_ra = tb.getcol('RA') col_dec = tb.getcol('DEC') col_mjd = tb.getcol('MJD') if use_scan_time: from scipy.interpolate import interp1d f_ra = interp1d(col_mjd, col_ra) f_dec = interp1d(col_mjd, col_dec) for idx, scanid in enumerate(scanids): btimes.append(scans[scanid]['0']['BeginTime']) etimes.append(scans[scanid]['0']['EndTime']) fieldid = scans[scanid]['0']['FieldId'] fieldids.append(fieldid) inttimes.append(scans[scanid]['0']['IntegrationTime']) ras = f_ra(np.array(btimes)) decs = f_dec(np.array(btimes)) ras = qa.convert(qa.quantity(ras, 'deg'), 'rad') decs = qa.convert(qa.quantity(decs, 'deg'), 'rad') else: ras = qa.convert(qa.quantity(col_ra, 'deg'), 'rad') decs = qa.convert(qa.quantity(col_dec, 'deg'), 'rad') else: for idx, scanid in enumerate(scanids): btimes.append(scans[scanid]['0']['BeginTime']) etimes.append(scans[scanid]['0']['EndTime']) fieldid = scans[scanid]['0']['FieldId'] fieldids.append(fieldid) inttimes.append(scans[scanid]['0']['IntegrationTime']) dir = ms.getfielddirmeas('PHASE_DIR', fieldid) dirs.append(dir) ras.append(dir['m0']) decs.append(dir['m1']) ms.close() btimestr = [ qa.time(qa.quantity(btimes[idx], 'd'), form='fits', prec=10)[0] for idx in range(nscanid) ] msinfo['vis'] = vis msinfo['scans'] = scans msinfo['fieldids'] = fieldids msinfo['btimes'] = btimes msinfo['btimestr'] = btimestr msinfo['inttimes'] = inttimes msinfo['ras'] = ras msinfo['decs'] = decs msinfo['observatory'] = observatory if msinfofile: np.savez(msinfofile, vis=vis, scans=scans, fieldids=fieldids, btimes=btimes, btimestr=btimestr, inttimes=inttimes, ras=ras, decs=decs, observatory=observatory) return msinfo
def calc_phasecenter_from_solxy(vis, timerange='', xycen=None, usemsphacenter=True): ''' return the phase center in RA and DEC of a given solar coordinates :param vis: input measurement sets file :param timerange: can be a string or astropy.time.core.Time object, or a 2-element list of string or Time object :param xycen: solar x-pos and y-pos in arcsec :param usemsphacenter: :return: phasecenter midtim: mid time of the given timerange ''' tb.open(vis + '/POINTING') tst = Time(tb.getcell('TIME_ORIGIN', 0) / 24. / 3600., format='mjd') ted = Time(tb.getcell('TIME_ORIGIN', tb.nrows() - 1) / 24. / 3600., format='mjd') tb.close() datstr = tst.iso[:10] if isinstance(timerange, Time): try: (sttim, edtim) = timerange except: sttim = timerange edtim = sttim else: if timerange == '': sttim = tst edtim = ted else: try: (tstart, tend) = timerange.split('~') if tstart[2] == ':': sttim = Time(datstr + 'T' + tstart) edtim = Time(datstr + 'T' + tend) # timerange = '{0}/{1}~{0}/{2}'.format(datstr.replace('-', '/'), tstart, tend) else: sttim = Time(qa.quantity(tstart, 'd')['value'], format='mjd') edtim = Time(qa.quantity(tend, 'd')['value'], format='mjd') except: try: if timerange[2] == ':': sttim = Time(datstr + 'T' + timerange) edtim = sttim else: sttim = Time(qa.quantity(timerange, 'd')['value'], format='mjd') edtim = sttim except ValueError: print("keyword 'timerange' in wrong format") ms.open(vis) metadata = ms.metadata() observatory = metadata.observatorynames()[0] ms.close() midtim_mjd = (sttim.mjd + edtim.mjd) / 2. midtim = Time(midtim_mjd, format='mjd') eph = read_horizons(t0=midtim) if observatory == 'EOVSA' or (not usemsphacenter): print('This is EOVSA data') # use RA and DEC from FIELD ID 0 tb.open(vis + '/FIELD') phadir = tb.getcol('PHASE_DIR').flatten() tb.close() ra0 = phadir[0] dec0 = phadir[1] else: ra0 = eph['ra'][0] dec0 = eph['dec'][0] if not xycen: # use solar disk center as default phasecenter = 'J2000 ' + str(ra0) + 'rad ' + str(dec0) + 'rad' else: x0 = np.radians(xycen[0] / 3600.) y0 = np.radians(xycen[1] / 3600.) p0 = np.radians(eph['p0'][0]) # p angle in radians raoff = -((x0) * np.cos(p0) - y0 * np.sin(p0)) / np.cos(eph['dec'][0]) decoff = (x0) * np.sin(p0) + y0 * np.cos(p0) newra = ra0 + raoff newdec = dec0 + decoff phasecenter = 'J2000 ' + str(newra) + 'rad ' + str(newdec) + 'rad' return phasecenter, midtim
def imreg(vis=None, ephem=None, msinfo=None, imagefile=None, timerange=None, reftime=None, fitsfile=None, beamfile=None, offsetfile=None, toTb=None, sclfactor=1.0, verbose=False, p_ang=False, overwrite=True, usephacenter=True, deletehistory=False, subregion=[], docompress=False): ''' main routine to register CASA images Required Inputs: vis: STRING. CASA measurement set from which the image is derived imagefile: STRING or LIST. name of the input CASA image timerange: STRING or LIST. timerange used to generate the CASA image, must have the same length as the input images. Each element should be in CASA standard time format, e.g., '2012/03/03/12:00:00~2012/03/03/13:00:00' Optional Inputs: msinfo: DICTIONARY. CASA MS information, output from read_msinfo. If not provided, generate one from the supplied vis ephem: DICTIONARY. solar ephem, output from read_horizons. If not provided, query JPL Horizons based on time info of the vis (internet connection required) fitsfile: STRING or LIST. name of the output registered fits files reftime: STRING or LIST. Each element should be in CASA standard time format, e.g., '2012/03/03/12:00:00' offsetfile: optionally provide an offset with a series of solar x and y offsets with timestamps toTb: Bool. Convert the default Jy/beam to brightness temperature? sclfactor: scale the image values up by its value (to compensate VLA 20 dB attenuator) verbose: Bool. Show more diagnostic info if True. usephacenter: Bool -- if True, correct for the RA and DEC in the ms file based on solar empheris. Otherwise assume the phasecenter is correctly pointed to the solar disk center (EOVSA case) subregion: Region selection. See 'help par.region' for details. Usage: >>> from suncasa.utils import helioimage2fits as hf >>> hf.imreg(vis='mydata.ms', imagefile='myimage.image', fitsfile='myimage.fits', timerange='2017/08/21/20:21:10~2017/08/21/20:21:18') The output fits file is 'myimage.fits' History: BC (sometime in 2014): function was first wrote, followed by a number of edits by BC and SY BC (2019-07-16): Added checks for stokes parameter. Verified that for converting from Jy/beam to brightness temperature, the convention of 2*k_b*T should always be used. I.e., for unpolarized source, stokes I, RR, LL, XX, YY, etc. in the output CASA images from (t)clean should all have same values of radio intensity (in Jy/beam) and brightness temperature (in K). ''' if deletehistory: ms_clearhistory(vis) if not imagefile: raise ValueError('Please specify input image') if not timerange: raise ValueError('Please specify timerange of the input image') if type(imagefile) == str: imagefile = [imagefile] if type(timerange) == str: timerange = [timerange] if not fitsfile: fitsfile = [img + '.fits' for img in imagefile] if type(fitsfile) == str: fitsfile = [fitsfile] nimg = len(imagefile) if len(timerange) != nimg: raise ValueError( 'Number of input images does not equal to number of timeranges!') if len(fitsfile) != nimg: raise ValueError( 'Number of input images does not equal to number of output fits files!' ) nimg = len(imagefile) if verbose: print(str(nimg) + ' images to process...') if reftime: # use as reference time to find solar disk RA and DEC to register the image, but not the actual timerange associated with the image if type(reftime) == str: reftime = [reftime] * nimg if len(reftime) != nimg: raise ValueError( 'Number of reference times does not match that of input images!' ) helio = ephem_to_helio(vis, ephem=ephem, msinfo=msinfo, reftime=reftime, usephacenter=usephacenter) else: # use the supplied timerange to register the image helio = ephem_to_helio(vis, ephem=ephem, msinfo=msinfo, reftime=timerange, usephacenter=usephacenter) if toTb: (bmajs, bmins, bpas, beamunits, bpaunits) = getbeam(imagefile=imagefile, beamfile=beamfile) for n, img in enumerate(imagefile): if verbose: print('processing image #' + str(n) + ' ' + img) fitsf = fitsfile[n] timeran = timerange[n] # obtain duration of the image as FITS header exptime try: [tbg0, tend0] = timeran.split('~') tbg_d = qa.getvalue(qa.convert(qa.totime(tbg0), 'd'))[0] tend_d = qa.getvalue(qa.convert(qa.totime(tend0), 'd'))[0] tdur_s = (tend_d - tbg_d) * 3600. * 24. dateobs = qa.time(qa.quantity(tbg_d, 'd'), form='fits', prec=10)[0] except: print('Error in converting the input timerange: ' + str(timeran) + '. Proceeding to the next image...') continue hel = helio[n] if not os.path.exists(img): warnings.warn('{} does not existed!'.format(img)) else: if os.path.exists(fitsf) and not overwrite: raise ValueError( 'Specified fits file already exists and overwrite is set to False. Aborting...' ) else: p0 = hel['p0'] tb.open(img + '/logtable', nomodify=False) nobs = tb.nrows() tb.removerows([i + 1 for i in range(nobs - 1)]) tb.close() ia.open(img) imr = ia.rotate(pa=str(-p0) + 'deg') if subregion is not []: imr = imr.subimage(region=subregion) imr.tofits(fitsf, history=False, overwrite=overwrite) imr.close() imsum = ia.summary() ia.close() ia.done() # construct the standard fits header # RA and DEC of the reference pixel crpix1 and crpix2 (imra, imdec) = (imsum['refval'][0], imsum['refval'][1]) # find out the difference of the image center to the CASA phase center # RA and DEC difference in arcseconds ddec = degrees((imdec - hel['dec_fld'])) * 3600. dra = degrees((imra - hel['ra_fld']) * cos(hel['dec_fld'])) * 3600. # Convert into image heliocentric offsets prad = -radians(hel['p0']) dx = (-dra) * cos(prad) - ddec * sin(prad) dy = (-dra) * sin(prad) + ddec * cos(prad) if offsetfile: try: offset = np.load(offsetfile) except: raise ValueError( 'The specified offsetfile does not exist!') reftimes_d = offset['reftimes_d'] xoffs = offset['xoffs'] yoffs = offset['yoffs'] timg_d = hel['reftime'] ind = bisect.bisect_left(reftimes_d, timg_d) xoff = xoffs[ind - 1] yoff = yoffs[ind - 1] else: xoff = hel['refx'] yoff = hel['refy'] if verbose: print( 'offset of image phase center to visibility phase center (arcsec): dx={0:.2f}, dy={1:.2f}' .format(dx, dy)) print( 'offset of visibility phase center to solar disk center (arcsec): dx={0:.2f}, dy={1:.2f}' .format(xoff, yoff)) (crval1, crval2) = (xoff + dx, yoff + dy) # update the fits header to heliocentric coordinates hdu = pyfits.open(fitsf, mode='update') hdu[0].verify('fix') header = hdu[0].header dshape = hdu[0].data.shape ndim = hdu[0].data.ndim (cdelt1, cdelt2) = (-header['cdelt1'] * 3600., header['cdelt2'] * 3600. ) # Original CDELT1, 2 are for RA and DEC in degrees header['cdelt1'] = cdelt1 header['cdelt2'] = cdelt2 header['cunit1'] = 'arcsec' header['cunit2'] = 'arcsec' header['crval1'] = crval1 header['crval2'] = crval2 header['ctype1'] = 'HPLN-TAN' header['ctype2'] = 'HPLT-TAN' header['date-obs'] = dateobs # begin time of the image if not p_ang: hel['p0'] = 0 try: # this works for pyfits version of CASA 4.7.0 but not CASA 4.6.0 if tdur_s: header.set('exptime', tdur_s) else: header.set('exptime', 1.) header.set('p_angle', hel['p0']) header.set('hgln_obs', 0.) header.set('rsun_ref', sun.constants.radius.value) if sunpyver <= 1: header.set( 'dsun_obs', sun.sunearth_distance(Time(dateobs)).to(u.meter).value) header.set( 'rsun_obs', sun.solar_semidiameter_angular_size( Time(dateobs)).value) header.set( 'hglt_obs', sun.heliographic_solar_center(Time(dateobs))[1].value) else: header.set( 'dsun_obs', sun.earth_distance(Time(dateobs)).to(u.meter).value) header.set('rsun_obs', sun.angular_radius(Time(dateobs)).value) header.set('hglt_obs', sun.L0(Time(dateobs)).value) except: # this works for astropy.io.fits if tdur_s: header.append(('exptime', tdur_s)) else: header.append(('exptime', 1.)) header.append(('p_angle', hel['p0'])) header.append(('hgln_obs', 0.)) header.append(('rsun_ref', sun.constants.radius.value)) if sunpyver <= 1: header.append( ('dsun_obs', sun.sunearth_distance(Time(dateobs)).to( u.meter).value)) header.append(('rsun_obs', sun.solar_semidiameter_angular_size( Time(dateobs)).value)) header.append(('hglt_obs', sun.heliographic_solar_center( Time(dateobs))[1].value)) else: header.append( ('dsun_obs', sun.earth_distance(Time(dateobs)).to(u.meter).value)) header.append( ('rsun_obs', sun.angular_radius(Time(dateobs)).value)) header.append(('hglt_obs', sun.L0(Time(dateobs)).value)) # check if stokes parameter exist exist_stokes = False stokes_mapper = { 'I': 1, 'Q': 2, 'U': 3, 'V': 4, 'RR': -1, 'LL': -2, 'RL': -3, 'LR': -4, 'XX': -5, 'YY': -6, 'XY': -7, 'YX': -8 } if 'CRVAL3' in header.keys(): if header['CTYPE3'] == 'STOKES': stokenum = header['CRVAL3'] exist_stokes = True if 'CRVAL4' in header.keys(): if header['CTYPE4'] == 'STOKES': stokenum = header['CRVAL4'] exist_stokes = True if exist_stokes: if stokenum in stokes_mapper.values(): stokesstr = list(stokes_mapper.keys())[list( stokes_mapper.values()).index(stokenum)] else: print('Stokes parameter {0:d} not recognized'.format( stokenum)) if verbose: print('This image is in Stokes ' + stokesstr) else: print( 'STOKES Information does not seem to exist! Assuming Stokes I' ) stokenum = 1 # intensity units to brightness temperature if toTb: # get restoring beam info bmaj = bmajs[n] bmin = bmins[n] beamunit = beamunits[n] data = hdu[ 0].data # remember the data order is reversed due to the FITS convension keys = list(header.keys()) values = list(header.values()) # which axis is frequency? faxis = keys[values.index('FREQ')][-1] faxis_ind = ndim - int(faxis) # find out the polarization of this image k_b = qa.constants('k')['value'] c_l = qa.constants('c')['value'] # Always use 2*kb for all polarizations const = 2. * k_b / c_l**2 if header['BUNIT'].lower() == 'jy/beam': header['BUNIT'] = 'K' header['BTYPE'] = 'Brightness Temperature' for i in range(dshape[faxis_ind]): nu = header['CRVAL' + faxis] + header['CDELT' + faxis] * ( i + 1 - header['CRPIX' + faxis]) if header['CUNIT' + faxis] == 'KHz': nu *= 1e3 if header['CUNIT' + faxis] == 'MHz': nu *= 1e6 if header['CUNIT' + faxis] == 'GHz': nu *= 1e9 if len(bmaj) > 1: # multiple (per-plane) beams bmajtmp = bmaj[i] bmintmp = bmin[i] else: # one single beam bmajtmp = bmaj[0] bmintmp = bmin[0] if beamunit == 'arcsec': bmaj0 = np.radians(bmajtmp / 3600.) bmin0 = np.radians(bmintmp / 3600.) if beamunit == 'arcmin': bmaj0 = np.radians(bmajtmp / 60.) bmin0 = np.radians(bmintmp / 60.) if beamunit == 'deg': bmaj0 = np.radians(bmajtmp) bmin0 = np.radians(bmintmp) if beamunit == 'rad': bmaj0 = bmajtmp bmin0 = bmintmp beam_area = bmaj0 * bmin0 * np.pi / (4. * log(2.)) factor = const * nu**2 # SI unit jy_to_si = 1e-26 # print(nu/1e9, beam_area, factor) factor2 = sclfactor # if sclfactor: # factor2 = 100. if faxis == '3': data[:, i, :, :] *= jy_to_si / beam_area / factor * factor2 if faxis == '4': data[ i, :, :, :] *= jy_to_si / beam_area / factor * factor2 header = fu.headerfix(header) hdu.flush() hdu.close() if ndim - np.count_nonzero(np.array(dshape) == 1) > 3: docompress = False ''' Caveat: only 1D, 2D, or 3D images are currently supported by the astropy fits compression. If a n-dimensional image data array does not have at least n-3 single-dimensional entries, force docompress to be False ''' print( 'warning: The fits data contains more than 3 non squeezable dimensions. Skipping fits compression..' ) if docompress: fitsftmp = fitsf + ".tmp.fits" os.system("mv {} {}".format(fitsf, fitsftmp)) hdu = pyfits.open(fitsftmp) hdu[0].verify('fix') header = hdu[0].header data = hdu[0].data fu.write_compressed_image_fits(fitsf, data, header, compression_type='RICE_1', quantize_level=4.0) os.system("rm -rf {}".format(fitsftmp)) if deletehistory: ms_restorehistory(vis) return fitsfile