from asap._asap import sdtable from asap import rcParams from numarray import ones,zeros import sys class scantable(sdtable): """ The ASAP container for scans """ def __init__(self, filename, average=None, unit=None): """ Create a scantable from a saved one or make a reference Parameters: filename: the name of an asap table on disk or the name of a rpfits/sdfits/ms file (integrations within scans are auto averaged and the whole file is read) or [advanced] a reference to an existing scantable average: average all integrations withinb a scan on read. The default (True) is taken from .asaprc. unit: brightness unit; must be consistent with K or Jy. Over-rides the default selected by the reader (input rpfits/sdfits/ms) or replaces the value in existing scantables """ if average is None or type(average) is not bool: average = rcParams['scantable.autoaverage'] varlist = vars() self._vb = rcParams['verbose'] self._p = None if isinstance(filename,sdtable): sdtable.__init__(self, filename) if unit is not None: self.set_fluxunit(unit) else: import os.path if not os.path.exists(filename): print "File '%s' not found." % (filename) return filename = os.path.expandvars(filename) if os.path.isdir(filename): # crude check if asap table if os.path.exists(filename+'/table.info'): sdtable.__init__(self, filename) if unit is not None: self.set_fluxunit(unit) else: print "The given file '%s'is not a valid asap table." % (filename) return else: from asap._asap import sdreader ifSel = -1 beamSel = -1 r = sdreader(filename,ifSel,beamSel) print 'Importing data...' r._read([-1]) tbl = r._getdata() if unit is not None: tbl.set_fluxunit(unit) if average: from asap._asap import average as _av print 'Auto averaging integrations...' tbl2 = _av((tbl,),(),True,'none') sdtable.__init__(self,tbl2) del tbl2 else: sdtable.__init__(self,tbl) del r,tbl self._add_history("scantable", varlist) def save(self, name=None, format=None, stokes=False, overwrite=False): """ Store the scantable on disk. This can be an asap (aips++) Table, SDFITS, Image FITS or MS2 format. Parameters: name: the name of the outputfile. For format="FITS" this is the directory file name into which all the files will be written (default is 'asap_FITS'). For format "ASCII" this is the root file name (data in 'name'.txt and header in 'name'_header.txt) format: an optional file format. Default is ASAP. Allowed are - 'ASAP' (save as ASAP [aips++] Table), 'SDFITS' (save as SDFITS file) 'FITS' (saves each row as a FITS Image) 'ASCII' (saves as ascii text file) 'MS2' (saves as an aips++ MeasurementSet V2) stokes: Convert to Stokes parameters (only available currently with FITS and ASCII formats. Default is False. overwrite: If the file should be overwritten if it exists. The default False is to return with warning without writing the output. USE WITH CARE. Example: scan.save('myscan.asap') scan.save('myscan.sdfits','SDFITS') """ from os import path if format is None: format = rcParams['scantable.save'] suffix = '.'+format.lower() if name is None or name =="": name = 'scantable'+suffix print "No filename given. Using default name %s..." % name name = path.expandvars(name) if path.isfile(name) or path.isdir(name): if not overwrite: print "File %s already exists." % name return format2 = format.upper() if format2 == 'ASAP': self._save(name) else: from asap._asap import sdwriter as _sw w = _sw(format2) w.write(self, name, stokes) return def copy(self): """ Return a copy of this scantable. Parameters: none Example: copiedscan = scan.copy() """ sd = scantable(sdtable._copy(self)) return sd def get_scan(self, scanid=None): """ Return a specific scan (by scanno) or collection of scans (by source name) in a new scantable. Parameters: scanid: a (list of) scanno or a source name, unix-style patterns are accepted for source name matching, e.g. '*_R' gets all 'ref scans Example: # get all scans containing the source '323p459' newscan = scan.get_scan('323p459') # get all 'off' scans refscans = scan.get_scan('*_R') # get a susbset of scans by scanno (as listed in scan.summary()) newscan = scan.get_scan([0,2,7,10]) """ if scanid is None: print "Please specify a scan no or name to retrieve from the scantable" try: if type(scanid) is str: s = sdtable._getsource(self,scanid) return scantable(s) elif type(scanid) is int: s = sdtable._getscan(self,[scanid]) return scantable(s) elif type(scanid) is list: s = sdtable._getscan(self,scanid) return scantable(s) else: print "Illegal scanid type, use 'int' or 'list' if ints." except RuntimeError: print "Couldn't find any match." def __str__(self): return sdtable._summary(self,True) def summary(self,filename=None, verbose=None): """ Print a summary of the contents of this scantable. Parameters: filename: the name of a file to write the putput to Default - no file output verbose: print extra info such as the frequency table The default (False) is taken from .asaprc """ info = sdtable._summary(self, verbose) if verbose is None: verbose = rcParams['scantable.verbosesummary'] if filename is not None: if filename is "": filename = 'scantable_summary.txt' from os.path import expandvars, isdir filename = expandvars(filename) if not isdir(filename): data = open(filename, 'w') data.write(info) data.close() else: print "Illegal file name '%s'." % (filename) print info def set_cursor(self, beam=0, IF=0, pol=0): """ Set the spectrum for individual operations. Parameters: beam, IF, pol: a number Example: scan.set_cursor(0,0,1) pol1sig = scan.stats(all=False) # returns std dev for beam=0 # if=0, pol=1 """ varlist = vars() self.setbeam(beam) self.setpol(pol) self.setif(IF) self._add_history("set_cursor",varlist) return def get_cursor(self): """ Return/print a the current 'cursor' into the Beam/IF/Pol cube. Parameters: none Returns: a list of values (currentBeam,currentIF,currentPol) Example: none """ i = self.getbeam() j = self.getif() k = self.getpol() if self._vb: print "--------------------------------------------------" print " Cursor position" print "--------------------------------------------------" out = 'Beam=%d IF=%d Pol=%d ' % (i,j,k) print out return i,j,k def stats(self, stat='stddev', mask=None, allaxes=None): """ Determine the specified statistic of the current beam/if/pol Takes a 'mask' as an optional parameter to specify which channels should be excluded. Parameters: stat: 'min', 'max', 'sumsq', 'sum', 'mean' 'var', 'stddev', 'avdev', 'rms', 'median' mask: an optional mask specifying where the statistic should be determined. allaxes: if True apply to all spectra. Otherwise apply only to the selected (beam/pol/if)spectra only. The default is taken from .asaprc (True if none) Example: scan.set_unit('channel') msk = scan.create_mask([100,200],[500,600]) scan.stats(stat='mean', mask=m) """ if allaxes is None: allaxes = rcParams['scantable.allaxes'] from asap._asap import stats as _stats from numarray import array,zeros,Float if mask == None: mask = ones(self.nchan()) axes = ['Beam','IF','Pol','Time'] beamSel,IFSel,polSel = (self.getbeam(),self.getif(),self.getpol()) if allaxes: n = self.nbeam()*self.nif()*self.npol()*self.nrow() shp = [self.nbeam(),self.nif(),self.npol(),self.nrow()] arr = array(zeros(n),shape=shp,type=Float) for i in range(self.nbeam()): self.setbeam(i) for j in range(self.nif()): self.setif(j) for k in range(self.npol()): self.setpol(k) arr[i,j,k,:] = _stats(self,mask,stat,-1) retval = {'axes': axes, 'data': arr, 'cursor':None} tm = [self._gettime(val) for val in range(self.nrow())] if self._vb: self._print_values(retval,stat,tm) self.setbeam(beamSel) self.setif(IFSel) self.setpol(polSel) return retval else: statval = _stats(self,mask,stat,-1) out = '' for l in range(self.nrow()): tm = self._gettime(l) out += 'Time[%s]:\n' % (tm) if self.nbeam() > 1: out += ' Beam[%d] ' % (beamSel) if self.nif() > 1: out += ' IF[%d] ' % (IFSel) if self.npol() > 1: out += ' Pol[%d] ' % (polSel) out += '= %3.3f\n' % (statval[l]) out += "--------------------------------------------------\n" if self._vb: print "--------------------------------------------------" print " ",stat print "--------------------------------------------------" print out retval = {'axes': axes, 'data': array(statval), 'cursor':(i,j,k)} return retval def stddev(self,mask=None, allaxes=None): """ Determine the standard deviation of the current beam/if/pol Takes a 'mask' as an optional parameter to specify which channels should be excluded. Parameters: mask: an optional mask specifying where the standard deviation should be determined. allaxes: optional flag to show all or a cursor selected spectrum of Beam/IF/Pol. Default is all or taken from .asaprc Example: scan.set_unit('channel') msk = scan.create_mask([100,200],[500,600]) scan.stddev(mask=m) """ if allaxes is None: allaxes = rcParams['scantable.allaxes'] return self.stats(stat='stddev',mask=mask, allaxes=allaxes); def get_tsys(self, allaxes=None): """ Return the System temperatures. Parameters: allaxes: if True apply to all spectra. Otherwise apply only to the selected (beam/pol/if)spectra only. The default is taken from .asaprc (True if none) Returns: a list of Tsys values. """ if allaxes is None: allaxes = rcParams['scantable.allaxes'] from numarray import array,zeros,Float axes = ['Beam','IF','Pol','Time'] if allaxes: n = self.nbeam()*self.nif()*self.npol()*self.nrow() shp = [self.nbeam(),self.nif(),self.npol(),self.nrow()] arr = array(zeros(n),shape=shp,type=Float) for i in range(self.nbeam()): self.setbeam(i) for j in range(self.nif()): self.setif(j) for k in range(self.npol()): self.setpol(k) arr[i,j,k,:] = self._gettsys() retval = {'axes': axes, 'data': arr, 'cursor':None} tm = [self._gettime(val) for val in range(self.nrow())] if self._vb: self._print_values(retval,'Tsys',tm) return retval else: i,j,k = (self.getbeam(),self.getif(),self.getpol()) statval = self._gettsys() out = '' for l in range(self.nrow()): tm = self._gettime(l) out += 'Time[%s]:\n' % (tm) if self.nbeam() > 1: out += ' Beam[%d] ' % (i) if self.nif() > 1: out += ' IF[%d] ' % (j) if self.npol() > 1: out += ' Pol[%d] ' % (k) out += '= %3.3f\n' % (statval[l]) out += "--------------------------------------------------\n" if self._vb: print "--------------------------------------------------" print " TSys" print "--------------------------------------------------" print out retval = {'axes': axes, 'data': array(statval), 'cursor':(i,j,k)} return retval def get_time(self, row=-1): """ Get a list of time stamps for the observations. Return a string for each integration in the scantable. Parameters: row: row no of integration. Default -1 return all rows Example: none """ out = [] if row == -1: for i in range(self.nrow()): out.append(self._gettime(i)) return out else: if row < self.nrow(): return self._gettime(row) def set_unit(self, unit='channel'): """ Set the unit for all following operations on this scantable Parameters: unit: optional unit, default is 'channel' one of '*Hz','km/s','channel', '' """ varlist = vars() if unit in ['','pixel', 'channel']: unit = '' inf = list(self._getcoordinfo()) inf[0] = unit self._setcoordinfo(inf) if self._p: self.plot() self._add_history("set_unit",varlist) def set_instrument(self, instr): """ Set the instrument for subsequent processing Parameters: instr: Select from 'ATPKSMB', 'ATPKSHOH', 'ATMOPRA', 'DSS-43' (Tid), 'CEDUNA', and 'HOBART' """ self._setInstrument(instr) self._add_history("set_instument",vars()) def set_doppler(self, doppler='RADIO'): """ Set the doppler for all following operations on this scantable. Parameters: doppler: One of 'RADIO', 'OPTICAL', 'Z', 'BETA', 'GAMMA' """ varlist = vars() inf = list(self._getcoordinfo()) inf[2] = doppler self._setcoordinfo(inf) if self._p: self.plot() self._add_history("set_doppler",vars()) def set_freqframe(self, frame=None): """ Set the frame type of the Spectral Axis. Parameters: frame: an optional frame type, default 'LSRK'. Valid frames are: 'REST','TOPO','LSRD','LSRK','BARY', 'GEO','GALACTO','LGROUP','CMB' Examples: scan.set_freqframe('BARY') """ if frame is None: frame = rcParams['scantable.freqframe'] varlist = vars() valid = ['REST','TOPO','LSRD','LSRK','BARY', \ 'GEO','GALACTO','LGROUP','CMB'] if frame in valid: inf = list(self._getcoordinfo()) inf[1] = frame self._setcoordinfo(inf) self._add_history("set_freqframe",varlist) else: print "Please specify a valid freq type. Valid types are:\n",valid def get_unit(self): """ Get the default unit set in this scantable Parameters: Returns: A unit string """ inf = self._getcoordinfo() unit = inf[0] if unit == '': unit = 'channel' return unit def get_abcissa(self, rowno=0): """ Get the abcissa in the current coordinate setup for the currently selected Beam/IF/Pol Parameters: rowno: an optional row number in the scantable. Default is the first row, i.e. rowno=0 Returns: The abcissa values and it's format string (as a dictionary) """ abc = self._getabcissa(rowno) lbl = self._getabcissalabel(rowno) return abc, lbl #return {'abcissa':abc,'label':lbl} def create_mask(self, *args, **kwargs): """ Compute and return a mask based on [min,max] windows. The specified windows are to be INCLUDED, when the mask is applied. Parameters: [min,max],[min2,max2],... Pairs of start/end points specifying the regions to be masked invert: optional argument. If specified as True, return an inverted mask, i.e. the regions specified are EXCLUDED row: create the mask using the specified row for unit conversions, default is row=0 only necessary if frequency varies over rows. Example: scan.set_unit('channel') a) msk = scan.set_mask([400,500],[800,900]) # masks everything outside 400 and 500 # and 800 and 900 in the unit 'channel' b) msk = scan.set_mask([400,500],[800,900], invert=True) # masks the regions between 400 and 500 # and 800 and 900 in the unit 'channel' """ row = 0 if kwargs.has_key("row"): row = kwargs.get("row") data = self._getabcissa(row) u = self._getcoordinfo()[0] if self._vb: if u == "": u = "channel" print "The current mask window unit is", u n = self.nchan() msk = zeros(n) for window in args: if (len(window) != 2 or window[0] > window[1] ): print "A window needs to be defined as [min,max]" return for i in range(n): if data[i] >= window[0] and data[i] < window[1]: msk[i] = 1 if kwargs.has_key('invert'): if kwargs.get('invert'): from numarray import logical_not msk = logical_not(msk) return msk def get_restfreqs(self): """ Get the restfrequency(s) stored in this scantable. The return value(s) are always of unit 'Hz' Parameters: none Returns: a list of doubles """ return list(self._getrestfreqs()) def lines(self): """ Print the list of known spectral lines """ sdtable._lines(self) def set_restfreqs(self, freqs=None, unit='Hz', lines=None, source=None, theif=None): """ Select the restfrequency for the specified source and IF OR replace for all IFs. If the 'freqs' argument holds a scalar, then that rest frequency will be applied to the selected data (and added to the list of available rest frequencies). In this way, you can set a rest frequency for each source and IF combination. If the 'freqs' argument holds a vector, then it MUST be of length the number of IFs (and the available restfrequencies will be replaced by this vector). In this case, *all* data ('source' and 'theif' are ignored) have the restfrequency set per IF according to the corresponding value you give in the 'freqs' vector. E.g. 'freqs=[1e9,2e9]' would mean IF 0 gets restfreq 1e9 and IF 1 gets restfreq 2e9. You can also specify the frequencies via known line names in the argument 'lines'. Use 'freqs' or 'lines'. 'freqs' takes precedence. See the list of known names via function scantable.lines() Parameters: freqs: list of rest frequencies unit: unit for rest frequency (default 'Hz') lines: list of known spectral lines names (alternative to freqs). See possible list via scantable.lines() source: Source name (blank means all) theif: IF (-1 means all) Example: scan.set_restfreqs(freqs=1.4e9, source='NGC253', theif=2) scan.set_restfreqs(freqs=[1.4e9,1.67e9]) """ varlist = vars() if source is None: source = "" if theif is None: theif = -1 t = type(freqs) if t is int or t is float: freqs = [freqs] if freqs is None: freqs = [] t = type(lines) if t is str: lines = [lines] if lines is None: lines = [] sdtable._setrestfreqs(self, freqs, unit, lines, source, theif) self._add_history("set_restfreqs", varlist) def flag_spectrum(self, thebeam, theif, thepol): """ This flags a selected spectrum in the scan 'for good'. USE WITH CARE - not reversible. Use masks for non-permanent exclusion of channels. Parameters: thebeam,theif,thepol: all have to be explicitly specified Example: scan.flag_spectrum(0,0,1) flags the spectrum for Beam=0, IF=0, Pol=1 """ if (thebeam < self.nbeam() and theif < self.nif() and thepol < self.npol()): sdtable.setbeam(self, thebeam) sdtable.setif(self, theif) sdtable.setpol(self, thepol) sdtable._flag(self) self._add_history("flag_spectrum", vars()) else: print "Please specify a valid (Beam/IF/Pol)" return def plot(self, what='spectrum',col='Pol', panel=None): """ Plot the spectra contained in the scan. Alternatively you can also Plot Tsys vs Time Parameters: what: a choice of 'spectrum' (default) or 'tsys' col: which out of Beams/IFs/Pols should be colour stacked panel: set up multiple panels, currently not working. """ print "Warning! Not fully functional. Use plotter.plot() instead" validcol = {'Beam':self.nbeam(),'IF':self.nif(),'Pol':self.npol()} validyax = ['spectrum','tsys'] from asap.asaplot import ASAPlot if not self._p: self._p = ASAPlot() #print "Plotting not enabled" #return if self._p.is_dead: del self._p self._p = ASAPlot() npan = 1 x = None if what == 'tsys': n = self.nrow() if n < 2: print "Only one integration. Can't plot." return self._p.hold() self._p.clear() if panel == 'Time': npan = self.nrow() self._p.set_panels(rows=npan) xlab,ylab,tlab = None,None,None self._vb = False sel = self.get_cursor() for i in range(npan): if npan > 1: self._p.subplot(i) for j in range(validcol[col]): x = None y = None m = None tlab = self._getsourcename(i) import re tlab = re.sub('_S','',tlab) if col == 'Beam': self.setbeam(j) elif col == 'IF': self.setif(j) elif col == 'Pol': self.setpol(j) if what == 'tsys': x = range(self.nrow()) xlab = 'Time [pixel]' m = list(ones(len(x))) y = [] ylab = r'$T_{sys}$' for k in range(len(x)): y.append(self._gettsys(k)) else: x,xlab = self.get_abcissa(i) y = self._getspectrum(i) ylab = r'Flux' m = self._getmask(i) llab = col+' '+str(j) self._p.set_line(label=llab) self._p.plot(x,y,m) self._p.set_axes('xlabel',xlab) self._p.set_axes('ylabel',ylab) self._p.set_axes('title',tlab) self._p.release() self.set_cursor(sel[0],sel[1],sel[2]) self._vb = rcParams['verbose'] return print out def _print_values(self, dat, label='', timestamps=[]): d = dat['data'] a = dat['axes'] shp = d.getshape() out = '' for i in range(shp[3]): out += '%s [%s]:\n' % (a[3],timestamps[i]) t = d[:,:,:,i] for j in range(shp[0]): if shp[0] > 1: out += ' %s[%d] ' % (a[0],j) for k in range(shp[1]): if shp[1] > 1: out += ' %s[%d] ' % (a[1],k) for l in range(shp[2]): if shp[2] > 1: out += ' %s[%d] ' % (a[2],l) out += '= %3.3f\n' % (t[j,k,l]) out += "-"*80 out += "\n" print "-"*80 print " ", label print "-"*80 print out def history(self): hist = list(self._gethistory()) print "-"*80 for h in hist: if h.startswith("---"): print h else: items = h.split("##") date = items[0] func = items[1] items = items[2:] print date print "Function: %s\n Parameters:" % (func) for i in items: s = i.split("=") print " %s = %s" % (s[0],s[1]) print "-"*80 return # # Maths business # def average_time(self, mask=None, scanav=False, weight='tint'): """ Return the (time) average of a scan, or apply it 'insitu'. Note: in channels only The cursor of the output scan is set to 0. Parameters: one scan or comma separated scans mask: an optional mask (only used for 'var' and 'tsys' weighting) scanav: True averages each scan separately False (default) averages all scans together, weight: Weighting scheme. 'none', 'var' (1/var(spec) weighted), 'tsys' (1/Tsys**2 weighted), 'tint' (integration time weighted) or 'tintsys' (Tint/Tsys**2). The default is 'tint' Example: # time average the scantable without using a mask newscan = scan.average_time() """ varlist = vars() if weight is None: weight = 'tint' if mask is None: mask = () from asap._asap import average as _av s = scantable(_av((self,), mask, scanav, weight)) s._add_history("average_time",varlist) return s def convert_flux(self, jyperk=None, eta=None, d=None, insitu=None, allaxes=None): """ Return a scan where all spectra are converted to either Jansky or Kelvin depending upon the flux units of the scan table. By default the function tries to look the values up internally. If it can't find them (or if you want to over-ride), you must specify EITHER jyperk OR eta (and D which it will try to look up also if you don't set it). jyperk takes precedence if you set both. Parameters: jyperk: the Jy / K conversion factor eta: the aperture efficiency d: the geomtric diameter (metres) insitu: if False a new scantable is returned. Otherwise, the scaling is done in-situ The default is taken from .asaprc (False) allaxes: if True apply to all spectra. Otherwise apply only to the selected (beam/pol/if)spectra only The default is taken from .asaprc (True if none) """ if allaxes is None: allaxes = rcParams['scantable.allaxes'] if insitu is None: insitu = rcParams['insitu'] varlist = vars() if jyperk is None: jyperk = -1.0 if d is None: d = -1.0 if eta is None: eta = -1.0 if not insitu: from asap._asap import convertflux as _convert s = scantable(_convert(self, d, eta, jyperk, allaxes)) s._add_history("convert_flux", varlist) return s else: from asap._asap import convertflux_insitu as _convert _convert(self, d, eta, jyperk, allaxes) self._add_history("convert_flux", varlist) return def gain_el(self, poly=None, filename="", method="linear", insitu=None, allaxes=None): """ Return a scan after applying a gain-elevation correction. The correction can be made via either a polynomial or a table-based interpolation (and extrapolation if necessary). You specify polynomial coefficients, an ascii table or neither. If you specify neither, then a polynomial correction will be made with built in coefficients known for certain telescopes (an error will occur if the instrument is not known). The data and Tsys are *divided* by the scaling factors. Parameters: poly: Polynomial coefficients (default None) to compute a gain-elevation correction as a function of elevation (in degrees). filename: The name of an ascii file holding correction factors. The first row of the ascii file must give the column names and these MUST include columns "ELEVATION" (degrees) and "FACTOR" (multiply data by this) somewhere. The second row must give the data type of the column. Use 'R' for Real and 'I' for Integer. An example file would be (actual factors are arbitrary) : TIME ELEVATION FACTOR R R R 0.1 0 0.8 0.2 20 0.85 0.3 40 0.9 0.4 60 0.85 0.5 80 0.8 0.6 90 0.75 method: Interpolation method when correcting from a table. Values are "nearest", "linear" (default), "cubic" and "spline" insitu: if False a new scantable is returned. Otherwise, the scaling is done in-situ The default is taken from .asaprc (False) allaxes: If True apply to all spectra. Otherwise apply only to the selected (beam/pol/if) spectra only The default is taken from .asaprc (True if none) """ if allaxes is None: allaxes = rcParams['scantable.allaxes'] if insitu is None: insitu = rcParams['insitu'] varlist = vars() if poly is None: poly = () from os.path import expandvars filename = expandvars(filename) if not insitu: from asap._asap import gainel as _gainEl s = scantable(_gainEl(self, poly, filename, method, allaxes)) s._add_history("gain_el", varlist) return s else: from asap._asap import gainel_insitu as _gainEl _gainEl(self, poly, filename, method, allaxes) self._add_history("gain_el", varlist) return def freq_align(self, reftime=None, method='cubic', perif=False, insitu=None): """ Return a scan where all rows have been aligned in frequency/velocity. The alignment frequency frame (e.g. LSRK) is that set by function set_freqframe. Parameters: reftime: reference time to align at. By default, the time of the first row of data is used. method: Interpolation method for regridding the spectra. Choose from "nearest", "linear", "cubic" (default) and "spline" perif: Generate aligners per freqID (no doppler tracking) or per IF (scan-based doppler tracking) insitu: if False a new scantable is returned. Otherwise, the scaling is done in-situ The default is taken from .asaprc (False) """ if insitu is None: insitu = rcParams['insitu'] varlist = vars() if reftime is None: reftime = '' perfreqid = not perif if not insitu: from asap._asap import freq_align as _align s = scantable(_align(self, reftime, method, perfreqid)) s._add_history("freq_align", varlist) return s else: from asap._asap import freq_align_insitu as _align _align(self, reftime, method, perfreqid) self._add_history("freq_align", varlist) return def opacity(self, tau, insitu=None, allaxes=None): """ Apply an opacity correction. The data and Tsys are multiplied by the correction factor. Parameters: tau: Opacity from which the correction factor is exp(tau*ZD) where ZD is the zenith-distance insitu: if False a new scantable is returned. Otherwise, the scaling is done in-situ The default is taken from .asaprc (False) allaxes: if True apply to all spectra. Otherwise apply only to the selected (beam/pol/if)spectra only The default is taken from .asaprc (True if none) """ if allaxes is None: allaxes = rcParams['scantable.allaxes'] if insitu is None: insitu = rcParams['insitu'] varlist = vars() if not insitu: from asap._asap import opacity as _opacity s = scantable(_opacity(self, tau, allaxes)) s._add_history("opacity", varlist) return s else: from asap._asap import opacity_insitu as _opacity _opacity(self, tau, allaxes) self._add_history("opacity", varlist) return def bin(self, width=5, insitu=None): """ Return a scan where all spectra have been binned up. width: The bin width (default=5) in pixels insitu: if False a new scantable is returned. Otherwise, the scaling is done in-situ The default is taken from .asaprc (False) """ if insitu is None: insitu = rcParams['insitu'] varlist = vars() if not insitu: from asap._asap import bin as _bin s = scantable(_bin(self, width)) s._add_history("bin",varlist) return s else: from asap._asap import bin_insitu as _bin _bin(self, width) self._add_history("bin",varlist) return def resample(self, width=5, method='cubic', insitu=None): """ Return a scan where all spectra have been binned up width: The bin width (default=5) in pixels method: Interpolation method when correcting from a table. Values are "nearest", "linear", "cubic" (default) and "spline" insitu: if False a new scantable is returned. Otherwise, the scaling is done in-situ The default is taken from .asaprc (False) """ if insitu is None: insitu = rcParams['insitu'] varlist = vars() if not insitu: from asap._asap import resample as _resample s = scantable(_resample(self, method, width)) s._add_history("resample",varlist) return s else: from asap._asap import resample_insitu as _resample _resample(self, method, width) self._add_history("resample",varlist) return def average_pol(self, mask=None, weight='none', insitu=None): """ Average the Polarisations together. The polarisation cursor of the output scan is set to 0 Parameters: mask: An optional mask defining the region, where the averaging will be applied. The output will have all specified points masked. weight: Weighting scheme. 'none' (default), 'var' (1/var(spec) weighted), or 'tsys' (1/Tsys**2 weighted) insitu: if False a new scantable is returned. Otherwise, the scaling is done in-situ The default is taken from .asaprc (False) """ if insitu is None: insitu = rcParams['insitu'] varlist = vars() if mask is None: mask = () if not insitu: from asap._asap import averagepol as _avpol s = scantable(_avpol(self, mask, weight)) s._add_history("average_pol",varlist) return s else: from asap._asap import averagepol_insitu as _avpol _avpol(self, mask, weight) self._add_history("average_pol",varlist) return def smooth(self, kernel="hanning", width=5.0, insitu=None, allaxes=None): """ Smooth the spectrum by the specified kernel (conserving flux). Parameters: scan: The input scan kernel: The type of smoothing kernel. Select from 'hanning' (default), 'gaussian' and 'boxcar'. The first three characters are sufficient. width: The width of the kernel in pixels. For hanning this is ignored otherwise it defauls to 5 pixels. For 'gaussian' it is the Full Width Half Maximum. For 'boxcar' it is the full width. insitu: if False a new scantable is returned. Otherwise, the scaling is done in-situ The default is taken from .asaprc (False) allaxes: If True (default) apply to all spectra. Otherwise apply only to the selected (beam/pol/if)spectra only The default is taken from .asaprc (True if none) Example: none """ if allaxes is None: allaxes = rcParams['scantable.allaxes'] if insitu is None: insitu = rcParams['insitu'] varlist = vars() if not insitu: from asap._asap import smooth as _smooth s = scantable(_smooth(self,kernel,width,allaxes)) s._add_history("smooth", varlist) return s else: from asap._asap import smooth_insitu as _smooth _smooth(self,kernel,width,allaxes) self._add_history("smooth", varlist) return def poly_baseline(self, mask=None, order=0, insitu=None): """ Return a scan which has been baselined (all rows) by a polynomial. Parameters: scan: a scantable mask: an optional mask order: the order of the polynomial (default is 0) insitu: if False a new scantable is returned. Otherwise, the scaling is done in-situ The default is taken from .asaprc (False) Example: # return a scan baselined by a third order polynomial, # not using a mask bscan = scan.poly_baseline(order=3) """ if insitu is None: insitu = rcParams['insitu'] varlist = vars() if mask is None: from numarray import ones mask = list(ones(self.nchan())) from asap.asapfitter import fitter f = fitter() f._verbose(True) f.set_scan(self, mask) f.set_function(poly=order) sf = f.auto_fit(insitu) if insitu: self._add_history("poly_baseline", varlist) return else: sf._add_history("poly_baseline", varlist) return sf def auto_poly_baseline(self, mask=None, edge=(0,0), order=0, threshold=3,insitu=None): """ Return a scan which has been baselined (all rows) by a polynomial. Spectral lines are detected first using linefinder and masked out to avoid them affecting the baseline solution. Parameters: scan: a scantable mask: an optional mask retreived from scantable edge: an optional number of channel to drop at the edge of spectrum. If only one value is specified, the same number will be dropped from both sides of the spectrum. Default is to keep all channels order: the order of the polynomial (default is 0) threshold: the threshold used by line finder. It is better to keep it large as only strong lines affect the baseline solution. insitu: if False a new scantable is returned. Otherwise, the scaling is done in-situ The default is taken from .asaprc (False) Example: scan2=scan.auto_poly_baseline(order=7) """ if insitu is None: insitu = rcParams['insitu'] varlist = vars() from asap.asapfitter import fitter from asap.asaplinefind import linefinder from asap import _is_sequence_or_number as _is_valid if not _is_valid(edge, int): raise RuntimeError, "Parameter 'edge' has to be an integer or a \ pair of integers specified as a tuple" # setup fitter f = fitter() f._verbose(True) f.set_function(poly=order) # setup line finder fl=linefinder() fl.set_options(threshold=threshold) if not insitu: workscan=self.copy() else: workscan=self vb=workscan._vb # remember the verbose parameter and selection workscan._vb=False sel=workscan.get_cursor() rows=range(workscan.nrow()) for i in range(workscan.nbeam()): workscan.setbeam(i) for j in range(workscan.nif()): workscan.setif(j) for k in range(workscan.npol()): workscan.setpol(k) if f._vb: print "Processing:" print 'Beam[%d], IF[%d], Pol[%d]' % (i,j,k) for iRow in rows: fl.set_scan(workscan,mask,edge) fl.find_lines(iRow) f.set_scan(workscan, fl.get_mask()) f.x=workscan._getabcissa(iRow) f.y=workscan._getspectrum(iRow) f.data=None f.fit() x=f.get_parameters() workscan._setspectrum(f.fitter.getresidual(),iRow) workscan.set_cursor(sel[0],sel[1],sel[2]) workscan._vb = vb if not insitu: return workscan def rotate_linpolphase(self, angle, allaxes=None): """ Rotate the phase of the complex polarization O=Q+iU correlation. This is always done in situ in the raw data. So if you call this function more than once then each call rotates the phase further. Parameters: angle: The angle (degrees) to rotate (add) by. allaxes: If True apply to all spectra. Otherwise apply only to the selected (beam/pol/if)spectra only. The default is taken from .asaprc (True if none) Examples: scan.rotate_linpolphase(2.3) """ if allaxes is None: allaxes = rcParams['scantable.allaxes'] varlist = vars() from asap._asap import _rotate_linpolphase as _rotate _rotate(self, angle, allaxes) self._add_history("rotate_linpolphase", varlist) return def rotate_xyphase(self, angle, allaxes=None): """ Rotate the phase of the XY correlation. This is always done in situ in the data. So if you call this function more than once then each call rotates the phase further. Parameters: angle: The angle (degrees) to rotate (add) by. allaxes: If True apply to all spectra. Otherwise apply only to the selected (beam/pol/if)spectra only. The default is taken from .asaprc (True if none) Examples: scan.rotate_xyphase(2.3) """ if allaxes is None: allaxes = rcParams['scantable.allaxes'] varlist = vars() from asap._asap import rotate_xyphase as _rotate_xyphase _rotate_xyphase(self, angle, allaxes) self._add_history("rotate_xyphase", varlist) return def add(self, offset, insitu=None, allaxes=None): """ Return a scan where all spectra have the offset added Parameters: offset: the offset insitu: if False a new scantable is returned. Otherwise, the scaling is done in-situ The default is taken from .asaprc (False) allaxes: if True apply to all spectra. Otherwise apply only to the selected (beam/pol/if)spectra only The default is taken from .asaprc (True if none) """ if allaxes is None: allaxes = rcParams['scantable.allaxes'] if insitu is None: insitu = rcParams['insitu'] varlist = vars() if not insitu: from asap._asap import add as _add s = scantable(_add(self, offset, allaxes)) s._add_history("add",varlist) return s else: from asap._asap import add_insitu as _add _add(self, offset, allaxes) self._add_history("add",varlist) return def scale(self, factor, insitu=None, allaxes=None, tsys=True): """ Return a scan where all spectra are scaled by the give 'factor' Parameters: factor: the scaling factor insitu: if False a new scantable is returned. Otherwise, the scaling is done in-situ The default is taken from .asaprc (False) allaxes: if True apply to all spectra. Otherwise apply only to the selected (beam/pol/if)spectra only. The default is taken from .asaprc (True if none) tsys: if True (default) then apply the operation to Tsys as well as the data """ if allaxes is None: allaxes = rcParams['scantable.allaxes'] if insitu is None: insitu = rcParams['insitu'] varlist = vars() if not insitu: from asap._asap import scale as _scale s = scantable(_scale(self, factor, allaxes, tsys)) s._add_history("scale",varlist) return s else: from asap._asap import scale_insitu as _scale _scale(self, factor, allaxes, tsys) self._add_history("scale",varlist) return def quotient(self, other, isreference=True, preserve=True): """ Return the quotient of a 'source' (on) scan and a 'reference' (off) scan. The reference can have just one row, even if the signal has many. Otherwise they must have the same number of rows. The cursor of the output scan is set to 0 Parameters: other: the 'other' scan isreference: if the 'other' scan is the reference (default) or source preserve: you can preserve (default) the continuum or remove it. The equations used are preserve: Output = Toff * (on/off) - Toff remove: Output = Tref * (on/off) - Ton Example: # src is a scantable for an 'on' scan, ref for an 'off' scantable q1 = src.quotient(ref) q2 = ref.quotient(src, isreference=False) # gives the same result """ from asap._asap import quotient as _quot if isreference: return scantable(_quot(self, other, preserve)) else: return scantable(_quot(other, self, preserve)) def __add__(self, other): varlist = vars() s = None if isinstance(other, scantable): from asap._asap import b_operate as _bop s = scantable(_bop(self, other, 'add', True)) elif isinstance(other, float): from asap._asap import add as _add s = scantable(_add(self, other, True)) else: print "Other input is not a scantable or float value" return s._add_history("operator +", varlist) return s def __sub__(self, other): """ implicit on all axes and on Tsys """ varlist = vars() s = None if isinstance(other, scantable): from asap._asap import b_operate as _bop s = scantable(_bop(self, other, 'sub', True)) elif isinstance(other, float): from asap._asap import add as _add s = scantable(_add(self, -other, True)) else: print "Other input is not a scantable or float value" return s._add_history("operator -", varlist) return s def __mul__(self, other): """ implicit on all axes and on Tsys """ varlist = vars() s = None if isinstance(other, scantable): from asap._asap import b_operate as _bop s = scantable(_bop(self, other, 'mul', True)) elif isinstance(other, float): if other == 0.0: print "Multiplying by zero is not recommended." return from asap._asap import scale as _sca s = scantable(_sca(self, other, True)) else: print "Other input is not a scantable or float value" return s._add_history("operator *", varlist) return s def __div__(self, other): """ implicit on all axes and on Tsys """ varlist = vars() s = None if isinstance(other, scantable): from asap._asap import b_operate as _bop s = scantable(_bop(self, other, 'div', True)) elif isinstance(other, float): if other == 0.0: print "Dividing by zero is not recommended" return from asap._asap import scale as _sca s = scantable(_sca(self, 1.0/other, True)) else: print "Other input is not a scantable or float value" return s._add_history("operator /", varlist) return s def get_fit(self, row=0): """ Print or return the stored fits for a row in the scantable Parameters: row: the row which the fit has been applied to. """ if row > self.nrow(): return from asap import asapfit fit = asapfit(self._getfit(row)) if self._vb: print fit return else: return fit.as_dict() def _add_history(self, funcname, parameters): # create date sep = "##" from datetime import datetime dstr = datetime.now().strftime('%Y/%m/%d %H:%M:%S') hist = dstr+sep hist += funcname+sep#cdate+sep if parameters.has_key('self'): del parameters['self'] for k,v in parameters.iteritems(): if type(v) is dict: for k2,v2 in v.iteritems(): hist += k2 hist += "=" if isinstance(v2,scantable): hist += 'scantable' elif k2 == 'mask': if isinstance(v2,list) or isinstance(v2,tuple): hist += str(self._zip_mask(v2)) else: hist += str(v2) else: hist += str(v2) else: hist += k hist += "=" if isinstance(v,scantable): hist += 'scantable' elif k == 'mask': if isinstance(v,list) or isinstance(v,tuple): hist += str(self._zip_mask(v)) else: hist += str(v) else: hist += str(v) hist += sep hist = hist[:-2] # remove trailing '##' self._addhistory(hist) def _zip_mask(self, mask): mask = list(mask) i = 0 segments = [] while mask[i:].count(1): i += mask[i:].index(1) if mask[i:].count(0): j = i + mask[i:].index(0) else: j = len(mask) segments.append([i,j]) i = j return segments def _get_ordinate_label(self): fu = "("+self.get_fluxunit()+")" import re lbl = "Intensity" if re.match(".K.",fu): lbl = "Brightness Temperature "+ fu elif re.match(".Jy.",fu): lbl = "Flux density "+ fu return lbl