"""This module defines the scantable class.""" import os try: from functools import wraps as wraps_dec except ImportError: from asap.compatibility import wraps as wraps_dec from asap.env import is_casapy from asap._asap import Scantable from asap._asap import filler from asap.parameters import rcParams from asap.logging import asaplog, asaplog_post_dec from asap.selector import selector from asap.linecatalog import linecatalog from asap.coordinate import coordinate from asap.utils import _n_bools, mask_not, mask_and, mask_or, page from asap.asapfitter import fitter def preserve_selection(func): @wraps_dec(func) def wrap(obj, *args, **kw): basesel = obj.get_selection() try: val = func(obj, *args, **kw) finally: obj.set_selection(basesel) return val return wrap def is_scantable(filename): """Is the given file a scantable? Parameters: filename: the name of the file/directory to test """ if ( os.path.isdir(filename) and os.path.exists(filename+'/table.info') and os.path.exists(filename+'/table.dat') ): f=open(filename+'/table.info') l=f.readline() f.close() #if ( l.find('Scantable') != -1 ): if ( l.find('Measurement Set') == -1 ): return True else: return False else: return False ## return (os.path.isdir(filename) ## and not os.path.exists(filename+'/table.f1') ## and os.path.exists(filename+'/table.info')) def is_ms(filename): """Is the given file a MeasurementSet? Parameters: filename: the name of the file/directory to test """ if ( os.path.isdir(filename) and os.path.exists(filename+'/table.info') and os.path.exists(filename+'/table.dat') ): f=open(filename+'/table.info') l=f.readline() f.close() if ( l.find('Measurement Set') != -1 ): return True else: return False else: return False class scantable(Scantable): """\ The ASAP container for scans (single-dish data). """ @asaplog_post_dec #def __init__(self, filename, average=None, unit=None, getpt=None, # antenna=None, parallactify=None): def __init__(self, filename, average=None, unit=None, parallactify=None, **args): """\ 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 filler (input rpfits/sdfits/ms) or replaces the value in existing scantables getpt: for MeasurementSet input data only: If True, all pointing data are filled. The deafult is False, which makes time to load the MS data faster in some cases. antenna: for MeasurementSet input data only: Antenna selection. integer (id) or string (name or id). parallactify: Indicate that the data had been parallatified. Default is taken from rc file. """ if average is None: average = rcParams['scantable.autoaverage'] #if getpt is None: # getpt = True #if antenna is not None: # asaplog.push("Antenna selection currently unsupported." # "Using ''") # asaplog.post('WARN') #if antenna is None: # antenna = '' #elif type(antenna) == int: # antenna = '%s' % antenna #elif type(antenna) == list: # tmpstr = '' # for i in range( len(antenna) ): # if type(antenna[i]) == int: # tmpstr = tmpstr + ('%s,'%(antenna[i])) # elif type(antenna[i]) == str: # tmpstr=tmpstr+antenna[i]+',' # else: # raise TypeError('Bad antenna selection.') # antenna = tmpstr.rstrip(',') parallactify = parallactify or rcParams['scantable.parallactify'] varlist = vars() from asap._asap import stmath self._math = stmath( rcParams['insitu'] ) if isinstance(filename, Scantable): Scantable.__init__(self, filename) else: if isinstance(filename, str): filename = os.path.expandvars(filename) filename = os.path.expanduser(filename) if not os.path.exists(filename): s = "File '%s' not found." % (filename) raise IOError(s) if is_scantable(filename): ondisk = rcParams['scantable.storage'] == 'disk' Scantable.__init__(self, filename, ondisk) if unit is not None: self.set_fluxunit(unit) # do not reset to the default freqframe #self.set_freqframe(rcParams['scantable.freqframe']) #elif os.path.isdir(filename) \ # and not os.path.exists(filename+'/table.f1'): elif is_ms(filename): # Measurement Set opts={'ms': {}} mskeys=['getpt','antenna'] for key in mskeys: if key in args.keys(): opts['ms'][key] = args[key] #self._fill([filename], unit, average, getpt, antenna) self._fill([filename], unit, average, opts) elif os.path.isfile(filename): #self._fill([filename], unit, average, getpt, antenna) self._fill([filename], unit, average) else: msg = "The given file '%s'is not a valid " \ "asap table." % (filename) raise IOError(msg) elif (isinstance(filename, list) or isinstance(filename, tuple)) \ and isinstance(filename[-1], str): #self._fill(filename, unit, average, getpt, antenna) self._fill(filename, unit, average) self.parallactify(parallactify) self._add_history("scantable", varlist) @asaplog_post_dec def save(self, name=None, format=None, overwrite=False): """\ Store the scantable on disk. This can be an asap (aips++) Table, SDFITS or MS2 format. Parameters: name: the name of the outputfile. 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) * 'ASCII' (saves as ascii text file) * 'MS2' (saves as an casacore MeasurementSet V2) * 'FITS' (save as image FITS - not readable by class) * 'CLASS' (save as FITS readable by CLASS) 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 format = format or rcParams['scantable.save'] suffix = '.'+format.lower() if name is None or name == "": name = 'scantable'+suffix msg = "No filename given. Using default name %s..." % name asaplog.push(msg) name = path.expandvars(name) if path.isfile(name) or path.isdir(name): if not overwrite: msg = "File %s exists." % name raise IOError(msg) format2 = format.upper() if format2 == 'ASAP': self._save(name) else: from asap._asap import stwriter as stw writer = stw(format2) writer.write(self, name) return def copy(self): """Return a copy of this scantable. *Note*: This makes a full (deep) copy. scan2 = scan1 makes a reference. Example:: copiedscan = scan.copy() """ sd = scantable(Scantable._copy(self)) return sd def drop_scan(self, scanid=None): """\ Return a new scantable where the specified scan number(s) has(have) been dropped. Parameters: scanid: a (list of) scan number(s) """ from asap import _is_sequence_or_number as _is_valid from asap import _to_list from asap import unique if not _is_valid(scanid): raise RuntimeError( 'Please specify a scanno to drop from the scantable' ) scanid = _to_list(scanid) allscans = unique([ self.getscan(i) for i in range(self.nrow())]) for sid in scanid: allscans.remove(sid) if len(allscans) == 0: raise ValueError("Can't remove all scans") sel = selector(scans=allscans) return self._select_copy(sel) def _select_copy(self, selection): orig = self.get_selection() self.set_selection(orig+selection) cp = self.copy() self.set_selection(orig) return cp def get_scan(self, scanid=None): """\ Return a specific scan (by scanno) or collection of scans (by source name) in a new scantable. *Note*: See scantable.drop_scan() for the inverse operation. 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: raise RuntimeError( 'Please specify a scan no or name to ' 'retrieve from the scantable' ) try: bsel = self.get_selection() sel = selector() if type(scanid) is str: sel.set_name(scanid) return self._select_copy(sel) elif type(scanid) is int: sel.set_scans([scanid]) return self._select_copy(sel) elif type(scanid) is list: sel.set_scans(scanid) return self._select_copy(sel) else: msg = "Illegal scanid type, use 'int' or 'list' if ints." raise TypeError(msg) except RuntimeError: raise def __str__(self): return Scantable._summary(self, True) def summary(self, filename=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 """ info = Scantable._summary(self, True) 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: msg = "Illegal file name '%s'." % (filename) raise IOError(msg) return page(info) def get_spectrum(self, rowno): """Return the spectrum for the current row in the scantable as a list. Parameters: rowno: the row number to retrieve the spectrum from """ return self._getspectrum(rowno) def get_mask(self, rowno): """Return the mask for the current row in the scantable as a list. Parameters: rowno: the row number to retrieve the mask from """ return self._getmask(rowno) def set_spectrum(self, spec, rowno): """Return the spectrum for the current row in the scantable as a list. Parameters: spec: the new spectrum rowno: the row number to set the spectrum for """ assert(len(spec) == self.nchan()) return self._setspectrum(spec, rowno) def get_coordinate(self, rowno): """Return the (spectral) coordinate for a a given 'rowno'. *Note*: * This coordinate is only valid until a scantable method modifies the frequency axis. * This coordinate does contain the original frequency set-up NOT the new frame. The conversions however are done using the user specified frame (e.g. LSRK/TOPO). To get the 'real' coordinate, use scantable.freq_align first. Without it there is no closure, i.e.:: c = myscan.get_coordinate(0) c.to_frequency(c.get_reference_pixel()) != c.get_reference_value() Parameters: rowno: the row number for the spectral coordinate """ return coordinate(Scantable.get_coordinate(self, rowno)) def get_selection(self): """\ Get the selection object currently set on this scantable. Example:: sel = scan.get_selection() sel.set_ifs(0) # select IF 0 scan.set_selection(sel) # apply modified selection """ return selector(self._getselection()) def set_selection(self, selection=None, **kw): """\ Select a subset of the data. All following operations on this scantable are only applied to thi selection. Parameters: selection: a selector object (default unset the selection), or any combination of "pols", "ifs", "beams", "scans", "cycles", "name", "query" Examples:: sel = selector() # create a selection object self.set_scans([0, 3]) # select SCANNO 0 and 3 scan.set_selection(sel) # set the selection scan.summary() # will only print summary of scanno 0 an 3 scan.set_selection() # unset the selection # or the equivalent scan.set_selection(scans=[0,3]) scan.summary() # will only print summary of scanno 0 an 3 scan.set_selection() # unset the selection """ if selection is None: # reset if len(kw) == 0: selection = selector() else: # try keywords for k in kw: if k not in selector.fields: raise KeyError("Invalid selection key '%s', valid keys are %s" % (k, selector.fields)) selection = selector(**kw) self._setselection(selection) def get_row(self, row=0, insitu=None): """\ Select a row in the scantable. Return a scantable with single row. Parameters: row: row no of integration, 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) """ if insitu is None: insitu = rcParams['insitu'] if not insitu: workscan = self.copy() else: workscan = self # Select a row sel=selector() sel.set_scans([workscan.getscan(row)]) sel.set_cycles([workscan.getcycle(row)]) sel.set_beams([workscan.getbeam(row)]) sel.set_ifs([workscan.getif(row)]) sel.set_polarisations([workscan.getpol(row)]) sel.set_name(workscan._getsourcename(row)) workscan.set_selection(sel) if not workscan.nrow() == 1: msg = "Cloud not identify single row. %d rows selected."%(workscan.nrow()) raise RuntimeError(msg) del sel if insitu: self._assign(workscan) else: return workscan @asaplog_post_dec def stats(self, stat='stddev', mask=None, form='3.3f', row=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', 'min_abc', 'max_abc', 'sumsq', 'sum', 'mean', 'var', 'stddev', 'avdev', 'rms', 'median' mask: an optional mask specifying where the statistic should be determined. form: format string to print statistic values row: row number of spectrum to process. (default is None: for all rows) Example: scan.set_unit('channel') msk = scan.create_mask([100, 200], [500, 600]) scan.stats(stat='mean', mask=m) """ mask = mask or [] if not self._check_ifs(): raise ValueError("Cannot apply mask as the IFs have different " "number of channels. Please use setselection() " "to select individual IFs") rtnabc = False if stat.lower().endswith('_abc'): rtnabc = True getchan = False if stat.lower().startswith('min') or stat.lower().startswith('max'): chan = self._math._minmaxchan(self, mask, stat) getchan = True statvals = [] if not rtnabc: if row == None: statvals = self._math._stats(self, mask, stat) else: statvals = self._math._statsrow(self, mask, stat, int(row)) #def cb(i): # return statvals[i] #return self._row_callback(cb, stat) label=stat #callback=cb out = "" #outvec = [] sep = '-'*50 if row == None: rows = xrange(self.nrow()) elif isinstance(row, int): rows = [ row ] for i in rows: refstr = '' statunit= '' if getchan: qx, qy = self.chan2data(rowno=i, chan=chan[i]) if rtnabc: statvals.append(qx['value']) refstr = ('(value: %'+form) % (qy['value'])+' ['+qy['unit']+'])' statunit= '['+qx['unit']+']' else: refstr = ('(@ %'+form) % (qx['value'])+' ['+qx['unit']+'])' tm = self._gettime(i) src = self._getsourcename(i) out += 'Scan[%d] (%s) ' % (self.getscan(i), src) out += 'Time[%s]:\n' % (tm) if self.nbeam(-1) > 1: out += ' Beam[%d] ' % (self.getbeam(i)) if self.nif(-1) > 1: out += ' IF[%d] ' % (self.getif(i)) if self.npol(-1) > 1: out += ' Pol[%d] ' % (self.getpol(i)) #outvec.append(callback(i)) if len(rows) > 1: # out += ('= %'+form) % (outvec[i]) +' '+refstr+'\n' out += ('= %'+form) % (statvals[i]) +' '+refstr+'\n' else: # out += ('= %'+form) % (outvec[0]) +' '+refstr+'\n' out += ('= %'+form) % (statvals[0]) +' '+refstr+'\n' out += sep+"\n" import os if os.environ.has_key( 'USER' ): usr = os.environ['USER'] else: import commands usr = commands.getoutput( 'whoami' ) tmpfile = '/tmp/tmp_'+usr+'_casapy_asap_scantable_stats' f = open(tmpfile,'w') print >> f, sep print >> f, ' %s %s' % (label, statunit) print >> f, sep print >> f, out f.close() f = open(tmpfile,'r') x = f.readlines() f.close() asaplog.push(''.join(x), False) return statvals def chan2data(self, rowno=0, chan=0): """\ Returns channel/frequency/velocity and spectral value at an arbitrary row and channel in the scantable. Parameters: rowno: a row number in the scantable. Default is the first row, i.e. rowno=0 chan: a channel in the scantable. Default is the first channel, i.e. pos=0 """ if isinstance(rowno, int) and isinstance(chan, int): qx = {'unit': self.get_unit(), 'value': self._getabcissa(rowno)[chan]} qy = {'unit': self.get_fluxunit(), 'value': self._getspectrum(rowno)[chan]} return qx, qy def stddev(self, mask=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. Example:: scan.set_unit('channel') msk = scan.create_mask([100, 200], [500, 600]) scan.stddev(mask=m) """ return self.stats(stat='stddev', mask=mask); def get_column_names(self): """\ Return a list of column names, which can be used for selection. """ return list(Scantable.get_column_names(self)) def get_tsys(self, row=-1): """\ Return the System temperatures. Parameters: row: the rowno to get the information for. (default all rows) Returns: a list of Tsys values for the current selection """ if row > -1: return self._get_column(self._gettsys, row) return self._row_callback(self._gettsys, "Tsys") def get_weather(self, row=-1): """\ Return the weather informations. Parameters: row: the rowno to get the information for. (default all rows) Returns: a dict or list of of dicts of values for the current selection """ values = self._get_column(self._get_weather, row) if row > -1: return {'temperature': values[0], 'pressure': values[1], 'humidity' : values[2], 'windspeed' : values[3], 'windaz' : values[4] } else: out = [] for r in values: out.append({'temperature': r[0], 'pressure': r[1], 'humidity' : r[2], 'windspeed' : r[3], 'windaz' : r[4] }) return out def _row_callback(self, callback, label): out = "" outvec = [] sep = '-'*50 for i in range(self.nrow()): tm = self._gettime(i) src = self._getsourcename(i) out += 'Scan[%d] (%s) ' % (self.getscan(i), src) out += 'Time[%s]:\n' % (tm) if self.nbeam(-1) > 1: out += ' Beam[%d] ' % (self.getbeam(i)) if self.nif(-1) > 1: out += ' IF[%d] ' % (self.getif(i)) if self.npol(-1) > 1: out += ' Pol[%d] ' % (self.getpol(i)) outvec.append(callback(i)) out += '= %3.3f\n' % (outvec[i]) out += sep+'\n' asaplog.push(sep) asaplog.push(" %s" % (label)) asaplog.push(sep) asaplog.push(out) asaplog.post() return outvec def _get_column(self, callback, row=-1): """ """ if row == -1: return [callback(i) for i in range(self.nrow())] else: if 0 <= row < self.nrow(): return callback(row) def get_time(self, row=-1, asdatetime=False): """\ Get a list of time stamps for the observations. Return a datetime object for each integration time stamp in the scantable. Parameters: row: row no of integration. Default -1 return all rows asdatetime: return values as datetime objects rather than strings """ from time import strptime from datetime import datetime times = self._get_column(self._gettime, row) if not asdatetime: return times format = "%Y/%m/%d/%H:%M:%S" if isinstance(times, list): return [datetime(*strptime(i, format)[:6]) for i in times] else: return datetime(*strptime(times, format)[:6]) def get_inttime(self, row=-1): """\ Get a list of integration times for the observations. Return a time in seconds for each integration in the scantable. Parameters: row: row no of integration. Default -1 return all rows. """ return self._get_column(self._getinttime, row) def get_sourcename(self, row=-1): """\ Get a list source names for the observations. Return a string for each integration in the scantable. Parameters: row: row no of integration. Default -1 return all rows. """ return self._get_column(self._getsourcename, row) def get_elevation(self, row=-1): """\ Get a list of elevations for the observations. Return a float for each integration in the scantable. Parameters: row: row no of integration. Default -1 return all rows. """ return self._get_column(self._getelevation, row) def get_azimuth(self, row=-1): """\ Get a list of azimuths for the observations. Return a float for each integration in the scantable. Parameters: row: row no of integration. Default -1 return all rows. """ return self._get_column(self._getazimuth, row) def get_parangle(self, row=-1): """\ Get a list of parallactic angles for the observations. Return a float for each integration in the scantable. Parameters: row: row no of integration. Default -1 return all rows. """ return self._get_column(self._getparangle, row) def get_direction(self, row=-1): """ Get a list of Positions on the sky (direction) for the observations. Return a string for each integration in the scantable. Parameters: row: row no of integration. Default -1 return all rows """ return self._get_column(self._getdirection, row) def get_directionval(self, row=-1): """\ Get a list of Positions on the sky (direction) for the observations. Return a float for each integration in the scantable. Parameters: row: row no of integration. Default -1 return all rows """ return self._get_column(self._getdirectionvec, row) @asaplog_post_dec def set_unit(self, unit='channel'): """\ Set the unit for all following operations on this scantable Parameters: unit: optional unit, default is 'channel'. Use one of '*Hz', 'km/s', 'channel' or equivalent '' """ varlist = vars() if unit in ['', 'pixel', 'channel']: unit = '' inf = list(self._getcoordinfo()) inf[0] = unit self._setcoordinfo(inf) self._add_history("set_unit", varlist) @asaplog_post_dec 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()) @asaplog_post_dec def set_feedtype(self, feedtype): """\ Overwrite the feed type, which might not be set correctly. Parameters: feedtype: 'linear' or 'circular' """ self._setfeedtype(feedtype) self._add_history("set_feedtype", vars()) @asaplog_post_dec 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) self._add_history("set_doppler", vars()) @asaplog_post_dec 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: 'TOPO', 'LSRD', 'LSRK', 'BARY', 'GEO', 'GALACTO', 'LGROUP', 'CMB' Example:: scan.set_freqframe('BARY') """ frame = frame or rcParams['scantable.freqframe'] varlist = vars() # "REST" is not implemented in casacore #valid = ['REST', 'TOPO', 'LSRD', 'LSRK', 'BARY', \ # 'GEO', 'GALACTO', 'LGROUP', 'CMB'] valid = ['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: msg = "Please specify a valid freq type. Valid types are:\n", valid raise TypeError(msg) @asaplog_post_dec def set_dirframe(self, frame=""): """\ Set the frame type of the Direction on the sky. Parameters: frame: an optional frame type, default ''. Valid frames are: 'J2000', 'B1950', 'GALACTIC' Example: scan.set_dirframe('GALACTIC') """ varlist = vars() Scantable.set_dirframe(self, frame) self._add_history("set_dirframe", varlist) def get_unit(self): """\ Get the default unit set in this scantable Returns: A unit string """ inf = self._getcoordinfo() unit = inf[0] if unit == '': unit = 'channel' return unit @asaplog_post_dec 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 the format string (as a dictionary) """ abc = self._getabcissa(rowno) lbl = self._getabcissalabel(rowno) return abc, lbl @asaplog_post_dec def flag(self, mask=None, unflag=False): """\ Flag the selected data using an optional channel mask. Parameters: mask: an optional channel mask, created with create_mask. Default (no mask) is all channels. unflag: if True, unflag the data """ varlist = vars() mask = mask or [] self._flag(mask, unflag) self._add_history("flag", varlist) @asaplog_post_dec def flag_row(self, rows=[], unflag=False): """\ Flag the selected data in row-based manner. Parameters: rows: list of row numbers to be flagged. Default is no row (must be explicitly specified to execute row-based flagging). unflag: if True, unflag the data. """ varlist = vars() self._flag_row(rows, unflag) self._add_history("flag_row", varlist) @asaplog_post_dec def clip(self, uthres=None, dthres=None, clipoutside=True, unflag=False): """\ Flag the selected data outside a specified range (in channel-base) Parameters: uthres: upper threshold. dthres: lower threshold clipoutside: True for flagging data outside the range [dthres:uthres]. False for glagging data inside the range. unflag: if True, unflag the data. """ varlist = vars() self._clip(uthres, dthres, clipoutside, unflag) self._add_history("clip", varlist) @asaplog_post_dec def lag_flag(self, start, end, unit="MHz", insitu=None): """\ Flag the data in 'lag' space by providing a frequency to remove. Flagged data in the scantable gets interpolated over the region. No taper is applied. Parameters: start: the start frequency (really a period within the bandwidth) or period to remove end: the end frequency or period to remove unit: the frequency unit (default "MHz") or "" for explicit lag channels *Notes*: It is recommended to flag edges of the band or strong signals beforehand. """ if insitu is None: insitu = rcParams['insitu'] self._math._setinsitu(insitu) varlist = vars() base = { "GHz": 1000000000., "MHz": 1000000., "kHz": 1000., "Hz": 1.} if not (unit == "" or base.has_key(unit)): raise ValueError("%s is not a valid unit." % unit) if unit == "": s = scantable(self._math._lag_flag(self, start, end, "lags")) else: s = scantable(self._math._lag_flag(self, start*base[unit], end*base[unit], "frequency")) s._add_history("lag_flag", varlist) if insitu: self._assign(s) else: return s @asaplog_post_dec 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 (inclusive)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. Examples:: scan.set_unit('channel') # a) msk = scan.create_mask([400, 500], [800, 900]) # masks everything outside 400 and 500 # and 800 and 900 in the unit 'channel' # b) msk = scan.create_mask([400, 500], [800, 900], invert=True) # masks the regions between 400 and 500 # and 800 and 900 in the unit 'channel' # c) #mask only channel 400 msk = scan.create_mask([400]) """ row = kwargs.get("row", 0) data = self._getabcissa(row) u = self._getcoordinfo()[0] if u == "": u = "channel" msg = "The current mask window unit is %s" % u i = self._check_ifs() if not i: msg += "\nThis mask is only valid for IF=%d" % (self.getif(i)) asaplog.push(msg) n = self.nchan() msk = _n_bools(n, False) # test if args is a 'list' or a 'normal *args - UGLY!!! ws = (isinstance(args[-1][-1], int) or isinstance(args[-1][-1], float)) \ and args or args[0] for window in ws: if len(window) == 1: window = [window[0], window[0]] if len(window) == 0 or len(window) > 2: raise ValueError("A window needs to be defined as [start(, end)]") if window[0] > window[1]: tmp = window[0] window[0] = window[1] window[1] = tmp for i in range(n): if data[i] >= window[0] and data[i] <= window[1]: msk[i] = True if kwargs.has_key('invert'): if kwargs.get('invert'): msk = mask_not(msk) return msk def get_masklist(self, mask=None, row=0, silent=False): """\ Compute and return a list of mask windows, [min, max]. Parameters: mask: channel mask, created with create_mask. row: calcutate the masklist using the specified row for unit conversions, default is row=0 only necessary if frequency varies over rows. Returns: [min, max], [min2, max2], ... Pairs of start/end points (inclusive)specifying the masked regions """ if not (isinstance(mask,list) or isinstance(mask, tuple)): raise TypeError("The mask should be list or tuple.") if len(mask) < 2: raise TypeError("The mask elements should be > 1") if self.nchan() != len(mask): msg = "Number of channels in scantable != number of mask elements" raise TypeError(msg) data = self._getabcissa(row) u = self._getcoordinfo()[0] if u == "": u = "channel" msg = "The current mask window unit is %s" % u i = self._check_ifs() if not i: msg += "\nThis mask is only valid for IF=%d" % (self.getif(i)) if not silent: asaplog.push(msg) masklist=[] ist, ien = None, None ist, ien=self.get_mask_indices(mask) if ist is not None and ien is not None: for i in xrange(len(ist)): range=[data[ist[i]],data[ien[i]]] range.sort() masklist.append([range[0],range[1]]) return masklist def get_mask_indices(self, mask=None): """\ Compute and Return lists of mask start indices and mask end indices. Parameters: mask: channel mask, created with create_mask. Returns: List of mask start indices and that of mask end indices, i.e., [istart1,istart2,....], [iend1,iend2,....]. """ if not (isinstance(mask,list) or isinstance(mask, tuple)): raise TypeError("The mask should be list or tuple.") if len(mask) < 2: raise TypeError("The mask elements should be > 1") istart=[] iend=[] if mask[0]: istart.append(0) for i in range(len(mask)-1): if not mask[i] and mask[i+1]: istart.append(i+1) elif mask[i] and not mask[i+1]: iend.append(i) if mask[len(mask)-1]: iend.append(len(mask)-1) if len(istart) != len(iend): raise RuntimeError("Numbers of mask start != mask end.") for i in range(len(istart)): if istart[i] > iend[i]: raise RuntimeError("Mask start index > mask end index") break return istart,iend # 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 get_restfreqs(self, ids=None): """\ Get the restfrequency(s) stored in this scantable. The return value(s) are always of unit 'Hz' Parameters: ids: (optional) a list of MOLECULE_ID for that restfrequency(s) to be retrieved Returns: dictionary containing ids and a list of doubles for each id """ if ids is None: rfreqs={} idlist = self.getmolnos() for i in idlist: rfreqs[i]=list(self._getrestfreqs(i)) return rfreqs else: if type(ids)==list or type(ids)==tuple: rfreqs={} for i in ids: rfreqs[i]=list(self._getrestfreqs(i)) return rfreqs else: return list(self._getrestfreqs(ids)) #return list(self._getrestfreqs(ids)) def set_restfreqs(self, freqs=None, unit='Hz'): """\ Set or replace the restfrequency specified and If the 'freqs' argument holds a scalar, then that rest frequency will be applied to all the selected data. If the 'freqs' argument holds a vector, then it MUST be of equal or smaller length than the number of IFs (and the available restfrequencies will be replaced by this vector). In this case, *all* data 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 a linecatalog. Parameters: freqs: list of rest frequency values or string idenitfiers unit: unit for rest frequency (default 'Hz') Example:: # set the given restfrequency for the all currently selected IFs scan.set_restfreqs(freqs=1.4e9) # set restfrequencies for the n IFs (n > 1) in the order of the # list, i.e # IF0 -> 1.4e9, IF1 -> 1.41e9, IF3 -> 1.42e9 # len(list_of_restfreqs) == nIF # for nIF == 1 the following will set multiple restfrequency for # that IF scan.set_restfreqs(freqs=[1.4e9, 1.41e9, 1.42e9]) # set multiple restfrequencies per IF. as a list of lists where # the outer list has nIF elements, the inner s arbitrary scan.set_restfreqs(freqs=[[1.4e9, 1.41e9], [1.67e9]]) *Note*: To do more sophisticate Restfrequency setting, e.g. on a source and IF basis, use scantable.set_selection() before using this function:: # provided your scantable is called scan selection = selector() selection.set_name("ORION*") selection.set_ifs([1]) scan.set_selection(selection) scan.set_restfreqs(freqs=86.6e9) """ varlist = vars() from asap import linecatalog # simple value if isinstance(freqs, int) or isinstance(freqs, float): self._setrestfreqs([freqs], [""], unit) # list of values elif isinstance(freqs, list) or isinstance(freqs, tuple): # list values are scalars if isinstance(freqs[-1], int) or isinstance(freqs[-1], float): if len(freqs) == 1: self._setrestfreqs(freqs, [""], unit) else: # allow the 'old' mode of setting mulitple IFs sel = selector() savesel = self._getselection() iflist = self.getifnos() if len(freqs)>len(iflist): raise ValueError("number of elements in list of list " "exeeds the current IF selections") iflist = self.getifnos() for i, fval in enumerate(freqs): sel.set_ifs(iflist[i]) self._setselection(sel) self._setrestfreqs([fval], [""], unit) self._setselection(savesel) # list values are dict, {'value'=, 'name'=) elif isinstance(freqs[-1], dict): values = [] names = [] for d in freqs: values.append(d["value"]) names.append(d["name"]) self._setrestfreqs(values, names, unit) elif isinstance(freqs[-1], list) or isinstance(freqs[-1], tuple): sel = selector() savesel = self._getselection() iflist = self.getifnos() if len(freqs)>len(iflist): raise ValueError("number of elements in list of list exeeds" " the current IF selections") for i, fval in enumerate(freqs): sel.set_ifs(iflist[i]) self._setselection(sel) self._setrestfreqs(fval, [""], unit) self._setselection(savesel) # freqs are to be taken from a linecatalog elif isinstance(freqs, linecatalog): sel = selector() savesel = self._getselection() for i in xrange(freqs.nrow()): sel.set_ifs(iflist[i]) self._setselection(sel) self._setrestfreqs([freqs.get_frequency(i)], [freqs.get_name(i)], "MHz") # ensure that we are not iterating past nIF if i == self.nif()-1: break self._setselection(savesel) else: return self._add_history("set_restfreqs", varlist) def shift_refpix(self, delta): """\ Shift the reference pixel of the Spectra Coordinate by an integer amount. Parameters: delta: the amount to shift by *Note*: Be careful using this with broadband data. """ Scantable.shift_refpix(self, delta) @asaplog_post_dec def history(self, filename=None): """\ Print the history. Optionally to a file. Parameters: filename: The name of the file to save the history to. """ hist = list(self._gethistory()) out = "-"*80 for h in hist: if h.startswith("---"): out = "\n".join([out, h]) else: items = h.split("##") date = items[0] func = items[1] items = items[2:] out += "\n"+date+"\n" out += "Function: %s\n Parameters:" % (func) for i in items: s = i.split("=") out += "\n %s = %s" % (s[0], s[1]) out = "\n".join([out, "-"*80]) if filename is not None: if filename is "": filename = 'scantable_history.txt' import os filename = os.path.expandvars(os.path.expanduser(filename)) if not os.path.isdir(filename): data = open(filename, 'w') data.write(out) data.close() else: msg = "Illegal file name '%s'." % (filename) raise IOError(msg) return page(out) # # Maths business # @asaplog_post_dec def average_time(self, mask=None, scanav=False, weight='tint', align=False): """\ Return the (time) weighted average of a scan. *Note*: in channels only - align if necessary Parameters: 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' (mean no weight) 'var' (1/var(spec) weighted) 'tsys' (1/Tsys**2 weighted) 'tint' (integration time weighted) 'tintsys' (Tint/Tsys**2) 'median' ( median averaging) The default is 'tint' align: align the spectra in velocity before averaging. It takes the time of the first spectrum as reference time. Example:: # time average the scantable without using a mask newscan = scan.average_time() """ varlist = vars() weight = weight or 'TINT' mask = mask or () scanav = (scanav and 'SCAN') or 'NONE' scan = (self, ) if align: scan = (self.freq_align(insitu=False), ) s = None if weight.upper() == 'MEDIAN': s = scantable(self._math._averagechannel(scan[0], 'MEDIAN', scanav)) else: s = scantable(self._math._average(scan, mask, weight.upper(), scanav)) s._add_history("average_time", varlist) return s @asaplog_post_dec def convert_flux(self, jyperk=None, eta=None, d=None, insitu=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) """ if insitu is None: insitu = rcParams['insitu'] self._math._setinsitu(insitu) varlist = vars() jyperk = jyperk or -1.0 d = d or -1.0 eta = eta or -1.0 s = scantable(self._math._convertflux(self, d, eta, jyperk)) s._add_history("convert_flux", varlist) if insitu: self._assign(s) else: return s @asaplog_post_dec def gain_el(self, poly=None, filename="", method="linear", insitu=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) """ if insitu is None: insitu = rcParams['insitu'] self._math._setinsitu(insitu) varlist = vars() poly = poly or () from os.path import expandvars filename = expandvars(filename) s = scantable(self._math._gainel(self, poly, filename, method)) s._add_history("gain_el", varlist) if insitu: self._assign(s) else: return s @asaplog_post_dec def freq_align(self, reftime=None, method='cubic', 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" 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"] self._math._setinsitu(insitu) varlist = vars() reftime = reftime or "" s = scantable(self._math._freq_align(self, reftime, method)) s._add_history("freq_align", varlist) if insitu: self._assign(s) else: return s @asaplog_post_dec def opacity(self, tau=None, insitu=None): """\ Apply an opacity correction. The data and Tsys are multiplied by the correction factor. Parameters: tau: (list of) opacity from which the correction factor is exp(tau*ZD) where ZD is the zenith-distance. If a list is provided, it has to be of length nIF, nIF*nPol or 1 and in order of IF/POL, e.g. [opif0pol0, opif0pol1, opif1pol0 ...] if tau is `None` the opacities are determined from a model. 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'] self._math._setinsitu(insitu) varlist = vars() if not hasattr(tau, "__len__"): tau = [tau] s = scantable(self._math._opacity(self, tau)) s._add_history("opacity", varlist) if insitu: self._assign(s) else: return s @asaplog_post_dec def bin(self, width=5, insitu=None): """\ Return a scan where all spectra have been binned up. Parameters: 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'] self._math._setinsitu(insitu) varlist = vars() s = scantable(self._math._bin(self, width)) s._add_history("bin", varlist) if insitu: self._assign(s) else: return s @asaplog_post_dec def resample(self, width=5, method='cubic', insitu=None): """\ Return a scan where all spectra have been binned up. Parameters: 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'] self._math._setinsitu(insitu) varlist = vars() s = scantable(self._math._resample(self, method, width)) s._add_history("resample", varlist) if insitu: self._assign(s) else: return s @asaplog_post_dec def average_pol(self, mask=None, weight='none'): """\ Average the Polarisations together. 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) """ varlist = vars() mask = mask or () s = scantable(self._math._averagepol(self, mask, weight.upper())) s._add_history("average_pol", varlist) return s @asaplog_post_dec def average_beam(self, mask=None, weight='none'): """\ Average the Beams together. 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) """ varlist = vars() mask = mask or () s = scantable(self._math._averagebeams(self, mask, weight.upper())) s._add_history("average_beam", varlist) return s def parallactify(self, pflag): """\ Set a flag to indicate whether this data should be treated as having been 'parallactified' (total phase == 0.0) Parameters: pflag: Bool indicating whether to turn this on (True) or off (False) """ varlist = vars() self._parallactify(pflag) self._add_history("parallactify", varlist) @asaplog_post_dec def convert_pol(self, poltype=None): """\ Convert the data to a different polarisation type. Note that you will need cross-polarisation terms for most conversions. Parameters: poltype: The new polarisation type. Valid types are: "linear", "circular", "stokes" and "linpol" """ varlist = vars() s = scantable(self._math._convertpol(self, poltype)) s._add_history("convert_pol", varlist) return s @asaplog_post_dec def smooth(self, kernel="hanning", width=5.0, order=2, plot=False, insitu=None): """\ Smooth the spectrum by the specified kernel (conserving flux). Parameters: kernel: The type of smoothing kernel. Select from 'hanning' (default), 'gaussian', 'boxcar', 'rmedian' or 'poly' 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. For 'rmedian' and 'poly' it is the half width. order: Optional parameter for 'poly' kernel (default is 2), to specify the order of the polnomial. Ignored by all other kernels. plot: plot the original and the smoothed spectra. In this each indivual fit has to be approved, by typing 'y' or 'n' 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'] self._math._setinsitu(insitu) varlist = vars() if plot: orgscan = self.copy() s = scantable(self._math._smooth(self, kernel.lower(), width, order)) s._add_history("smooth", varlist) if plot: if rcParams['plotter.gui']: from asap.asaplotgui import asaplotgui as asaplot else: from asap.asaplot import asaplot self._p=asaplot() self._p.set_panels() ylab=s._get_ordinate_label() #self._p.palette(0,["#777777","red"]) for r in xrange(s.nrow()): xsm=s._getabcissa(r) ysm=s._getspectrum(r) xorg=orgscan._getabcissa(r) yorg=orgscan._getspectrum(r) self._p.clear() self._p.hold() self._p.set_axes('ylabel',ylab) self._p.set_axes('xlabel',s._getabcissalabel(r)) self._p.set_axes('title',s._getsourcename(r)) self._p.set_line(label='Original',color="#777777") self._p.plot(xorg,yorg) self._p.set_line(label='Smoothed',color="red") self._p.plot(xsm,ysm) ### Ugly part for legend for i in [0,1]: self._p.subplots[0]['lines'].append([self._p.subplots[0]['axes'].lines[i]]) self._p.release() ### Ugly part for legend self._p.subplots[0]['lines']=[] res = raw_input("Accept smoothing ([y]/n): ") if res.upper() == 'N': s._setspectrum(yorg, r) self._p.unmap() self._p = None del orgscan if insitu: self._assign(s) else: return s @asaplog_post_dec def old_poly_baseline(self, mask=None, order=0, plot=False, uselin=False, insitu=None, rows=None): """\ Return a scan which has been baselined (all rows) by a polynomial. Parameters: mask: an optional mask order: the order of the polynomial (default is 0) plot: plot the fit and the residual. In this each indivual fit has to be approved, by typing 'y' or 'n' uselin: use linear polynomial fit insitu: if False a new scantable is returned. Otherwise, the scaling is done in-situ The default is taken from .asaprc (False) rows: row numbers of spectra to be processed. (default is None: for all rows) 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'] if not insitu: workscan = self.copy() else: workscan = self varlist = vars() if mask is None: mask = [True for i in xrange(self.nchan())] try: f = fitter() if uselin: f.set_function(lpoly=order) else: f.set_function(poly=order) if rows == None: rows = xrange(workscan.nrow()) elif isinstance(rows, int): rows = [ rows ] if len(rows) > 0: self.blpars = [] self.masklists = [] self.actualmask = [] for r in rows: f.x = workscan._getabcissa(r) f.y = workscan._getspectrum(r) f.mask = mask_and(mask, workscan._getmask(r)) # (CAS-1434) f.data = None f.fit() if plot: f.plot(residual=True) x = raw_input("Accept fit ( [y]/n ): ") if x.upper() == 'N': self.blpars.append(None) self.masklists.append(None) self.actualmask.append(None) continue workscan._setspectrum(f.fitter.getresidual(), r) self.blpars.append(f.get_parameters()) self.masklists.append(workscan.get_masklist(f.mask, row=r, silent=True)) self.actualmask.append(f.mask) if plot: f._p.unmap() f._p = None workscan._add_history("poly_baseline", varlist) if insitu: self._assign(workscan) else: return workscan except RuntimeError: msg = "The fit failed, possibly because it didn't converge." raise RuntimeError(msg) @asaplog_post_dec def poly_baseline(self, mask=None, order=0, plot=False, batch=False, insitu=None, rows=None): """\ Return a scan which has been baselined (all rows) by a polynomial. Parameters: mask: an optional mask order: the order of the polynomial (default is 0) plot: plot the fit and the residual. In this each indivual fit has to be approved, by typing 'y' or 'n'. Ignored if batch = True. batch: if True a faster algorithm is used and logs including the fit results are not output (default is False) insitu: if False a new scantable is returned. Otherwise, the scaling is done in-situ The default is taken from .asaprc (False) rows: row numbers of spectra to be processed. (default is None: for all rows) 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 insitu: workscan = self else: workscan = self.copy() nchan = workscan.nchan() if mask is None: mask = [True for i in xrange(nchan)] try: if rows == None: rows = xrange(workscan.nrow()) elif isinstance(rows, int): rows = [ rows ] if len(rows) > 0: workscan.blpars = [] workscan.masklists = [] workscan.actualmask = [] if batch: workscan._poly_baseline_batch(mask, order) elif plot: f = fitter() f.set_function(lpoly=order) for r in rows: f.x = workscan._getabcissa(r) f.y = workscan._getspectrum(r) f.mask = mask_and(mask, workscan._getmask(r)) # (CAS-1434) f.data = None f.fit() f.plot(residual=True) accept_fit = raw_input("Accept fit ( [y]/n ): ") if accept_fit.upper() == "N": self.blpars.append(None) self.masklists.append(None) self.actualmask.append(None) continue workscan._setspectrum(f.fitter.getresidual(), r) workscan.blpars.append(f.get_parameters()) workscan.masklists.append(workscan.get_masklist(f.mask, row=r)) workscan.actualmask.append(f.mask) f._p.unmap() f._p = None else: for r in rows: fitparams = workscan._poly_baseline(mask, order, r) params = fitparams.getparameters() fmtd = ", ".join(["p%d = %3.6f" % (i, v) for i, v in enumerate(params)]) errors = fitparams.geterrors() fmask = mask_and(mask, workscan._getmask(r)) workscan.blpars.append({"params":params, "fixed": fitparams.getfixedparameters(), "formatted":fmtd, "errors":errors}) workscan.masklists.append(workscan.get_masklist(fmask, r, silent=True)) workscan.actualmask.append(fmask) asaplog.push(fmtd) workscan._add_history("poly_baseline", varlist) if insitu: self._assign(workscan) else: return workscan except RuntimeError, e: msg = "The fit failed, possibly because it didn't converge." if rcParams["verbose"]: asaplog.push(str(e)) asaplog.push(str(msg)) return else: raise RuntimeError(str(e)+'\n'+msg) def auto_poly_baseline(self, mask=None, edge=(0, 0), order=0, threshold=3, chan_avg_limit=1, plot=False, insitu=None, rows=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: 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. Nested tuples represent individual edge selection for different IFs (a number of spectral channels can be different) 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. chan_avg_limit: a maximum number of consequtive spectral channels to average during the search of weak and broad lines. The default is no averaging (and no search for weak lines). If such lines can affect the fitted baseline (e.g. a high order polynomial is fitted), increase this parameter (usually values up to 8 are reasonable). Most users of this method should find the default value sufficient. plot: plot the fit and the residual. In this each indivual fit has to be approved, by typing 'y' or 'n' insitu: if False a new scantable is returned. Otherwise, the scaling is done in-situ The default is taken from .asaprc (False) rows: row numbers of spectra to be processed. (default is None: for all rows) Example:: scan2 = scan.auto_poly_baseline(order=7, insitu=False) """ if insitu is None: insitu = rcParams['insitu'] varlist = vars() from asap.asaplinefind import linefinder from asap import _is_sequence_or_number as _is_valid # check whether edge is set up for each IF individually individualedge = False; if len(edge) > 1: if isinstance(edge[0], list) or isinstance(edge[0], tuple): individualedge = True; if not _is_valid(edge, int) and not individualedge: raise ValueError, "Parameter 'edge' has to be an integer or a \ pair of integers specified as a tuple. Nested tuples are allowed \ to make individual selection for different IFs." curedge = (0, 0) if individualedge: for edgepar in edge: if not _is_valid(edgepar, int): raise ValueError, "Each element of the 'edge' tuple has \ to be a pair of integers or an integer." else: curedge = edge; if not insitu: workscan = self.copy() else: workscan = self # setup fitter f = fitter() f.set_function(lpoly=order) # setup line finder fl = linefinder() fl.set_options(threshold=threshold,avg_limit=chan_avg_limit) fl.set_scan(workscan) if mask is None: mask = _n_bools(workscan.nchan(), True) if rows is None: rows = xrange(workscan.nrow()) elif isinstance(rows, int): rows = [ rows ] # Save parameters of baseline fits & masklists as a class attribute. # NOTICE: It does not reflect changes in scantable! if len(rows) > 0: self.blpars=[] self.masklists=[] self.actualmask=[] asaplog.push("Processing:") for r in rows: msg = " Scan[%d] Beam[%d] IF[%d] Pol[%d] Cycle[%d]" % \ (workscan.getscan(r), workscan.getbeam(r), workscan.getif(r), \ workscan.getpol(r), workscan.getcycle(r)) asaplog.push(msg, False) # figure out edge parameter if individualedge: if len(edge) >= workscan.getif(r): raise RuntimeError, "Number of edge elements appear to " \ "be less than the number of IFs" curedge = edge[workscan.getif(r)] actualmask = mask_and(mask, workscan._getmask(r)) # (CAS-1434) # setup line finder fl.find_lines(r, actualmask, curedge) f.x = workscan._getabcissa(r) f.y = workscan._getspectrum(r) f.mask = fl.get_mask() f.data = None f.fit() # Show mask list masklist=workscan.get_masklist(f.mask, row=r, silent=True) msg = "mask range: "+str(masklist) asaplog.push(msg, False) if plot: f.plot(residual=True) x = raw_input("Accept fit ( [y]/n ): ") if x.upper() == 'N': self.blpars.append(None) self.masklists.append(None) self.actualmask.append(None) continue workscan._setspectrum(f.fitter.getresidual(), r) self.blpars.append(f.get_parameters()) self.masklists.append(masklist) self.actualmask.append(f.mask) if plot: f._p.unmap() f._p = None workscan._add_history("auto_poly_baseline", varlist) if insitu: self._assign(workscan) else: return workscan @asaplog_post_dec def rotate_linpolphase(self, angle): """\ 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. Example:: scan.rotate_linpolphase(2.3) """ varlist = vars() self._math._rotate_linpolphase(self, angle) self._add_history("rotate_linpolphase", varlist) return @asaplog_post_dec def rotate_xyphase(self, angle): """\ 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. Example:: scan.rotate_xyphase(2.3) """ varlist = vars() self._math._rotate_xyphase(self, angle) self._add_history("rotate_xyphase", varlist) return @asaplog_post_dec def swap_linears(self): """\ Swap the linear polarisations XX and YY, or better the first two polarisations as this also works for ciculars. """ varlist = vars() self._math._swap_linears(self) self._add_history("swap_linears", varlist) return @asaplog_post_dec def invert_phase(self): """\ Invert the phase of the complex polarisation """ varlist = vars() self._math._invert_phase(self) self._add_history("invert_phase", varlist) return @asaplog_post_dec def add(self, offset, insitu=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) """ if insitu is None: insitu = rcParams['insitu'] self._math._setinsitu(insitu) varlist = vars() s = scantable(self._math._unaryop(self, offset, "ADD", False)) s._add_history("add", varlist) if insitu: self._assign(s) else: return s @asaplog_post_dec def scale(self, factor, tsys=True, insitu=None): """\ Return a scan where all spectra are scaled by the give 'factor' Parameters: factor: the scaling factor (float or 1D float list) insitu: if False a new scantable is returned. Otherwise, the scaling is done in-situ The default is taken from .asaprc (False) tsys: if True (default) then apply the operation to Tsys as well as the data """ if insitu is None: insitu = rcParams['insitu'] self._math._setinsitu(insitu) varlist = vars() s = None import numpy if isinstance(factor, list) or isinstance(factor, numpy.ndarray): if isinstance(factor[0], list) or isinstance(factor[0], numpy.ndarray): from asapmath import _array2dOp s = _array2dOp( self.copy(), factor, "MUL", tsys ) else: s = scantable( self._math._arrayop( self.copy(), factor, "MUL", tsys ) ) else: s = scantable(self._math._unaryop(self.copy(), factor, "MUL", tsys)) s._add_history("scale", varlist) if insitu: self._assign(s) else: return s def set_sourcetype(self, match, matchtype="pattern", sourcetype="reference"): """\ Set the type of the source to be an source or reference scan using the provided pattern. Parameters: match: a Unix style pattern, regular expression or selector matchtype: 'pattern' (default) UNIX style pattern or 'regex' regular expression sourcetype: the type of the source to use (source/reference) """ varlist = vars() basesel = self.get_selection() stype = -1 if sourcetype.lower().startswith("r"): stype = 1 elif sourcetype.lower().startswith("s"): stype = 0 else: raise ValueError("Illegal sourcetype use s(ource) or r(eference)") if matchtype.lower().startswith("p"): matchtype = "pattern" elif matchtype.lower().startswith("r"): matchtype = "regex" else: raise ValueError("Illegal matchtype, use p(attern) or r(egex)") sel = selector() if isinstance(match, selector): sel = match else: sel.set_query("SRCNAME == %s('%s')" % (matchtype, match)) self.set_selection(basesel+sel) self._setsourcetype(stype) self.set_selection(basesel) self._add_history("set_sourcetype", varlist) @asaplog_post_dec @preserve_selection def auto_quotient(self, preserve=True, mode='paired', verify=False): """\ This function allows to build quotients automatically. It assumes the observation to have the same number of "ons" and "offs" Parameters: preserve: you can preserve (default) the continuum or remove it. The equations used are preserve: Output = Toff * (on/off) - Toff remove: Output = Toff * (on/off) - Ton mode: the on/off detection mode 'paired' (default) identifies 'off' scans by the trailing '_R' (Mopra/Parkes) or '_e'/'_w' (Tid) and matches on/off pairs from the observing pattern 'time' finds the closest off in time .. todo:: verify argument is not implemented """ varlist = vars() modes = ["time", "paired"] if not mode in modes: msg = "please provide valid mode. Valid modes are %s" % (modes) raise ValueError(msg) s = None if mode.lower() == "paired": sel = self.get_selection() sel.set_query("SRCTYPE==psoff") self.set_selection(sel) offs = self.copy() sel.set_query("SRCTYPE==pson") self.set_selection(sel) ons = self.copy() s = scantable(self._math._quotient(ons, offs, preserve)) elif mode.lower() == "time": s = scantable(self._math._auto_quotient(self, mode, preserve)) s._add_history("auto_quotient", varlist) return s @asaplog_post_dec def mx_quotient(self, mask = None, weight='median', preserve=True): """\ Form a quotient using "off" beams when observing in "MX" mode. Parameters: mask: an optional mask to be used when weight == 'stddev' weight: How to average the off beams. Default is 'median'. preserve: you can preserve (default) the continuum or remove it. The equations used are: preserve: Output = Toff * (on/off) - Toff remove: Output = Toff * (on/off) - Ton """ mask = mask or () varlist = vars() on = scantable(self._math._mx_extract(self, 'on')) preoff = scantable(self._math._mx_extract(self, 'off')) off = preoff.average_time(mask=mask, weight=weight, scanav=False) from asapmath import quotient q = quotient(on, off, preserve) q._add_history("mx_quotient", varlist) return q @asaplog_post_dec def freq_switch(self, insitu=None): """\ Apply frequency switching to the data. Parameters: insitu: if False a new scantable is returned. Otherwise, the swictching is done in-situ The default is taken from .asaprc (False) """ if insitu is None: insitu = rcParams['insitu'] self._math._setinsitu(insitu) varlist = vars() s = scantable(self._math._freqswitch(self)) s._add_history("freq_switch", varlist) if insitu: self._assign(s) else: return s @asaplog_post_dec def recalc_azel(self): """Recalculate the azimuth and elevation for each position.""" varlist = vars() self._recalcazel() self._add_history("recalc_azel", varlist) return @asaplog_post_dec def __add__(self, other): varlist = vars() s = None if isinstance(other, scantable): s = scantable(self._math._binaryop(self, other, "ADD")) elif isinstance(other, float): s = scantable(self._math._unaryop(self, other, "ADD", False)) else: raise TypeError("Other input is not a scantable or float value") s._add_history("operator +", varlist) return s @asaplog_post_dec def __sub__(self, other): """ implicit on all axes and on Tsys """ varlist = vars() s = None if isinstance(other, scantable): s = scantable(self._math._binaryop(self, other, "SUB")) elif isinstance(other, float): s = scantable(self._math._unaryop(self, other, "SUB", False)) else: raise TypeError("Other input is not a scantable or float value") s._add_history("operator -", varlist) return s @asaplog_post_dec def __mul__(self, other): """ implicit on all axes and on Tsys """ varlist = vars() s = None if isinstance(other, scantable): s = scantable(self._math._binaryop(self, other, "MUL")) elif isinstance(other, float): s = scantable(self._math._unaryop(self, other, "MUL", False)) else: raise TypeError("Other input is not a scantable or float value") s._add_history("operator *", varlist) return s @asaplog_post_dec def __div__(self, other): """ implicit on all axes and on Tsys """ varlist = vars() s = None if isinstance(other, scantable): s = scantable(self._math._binaryop(self, other, "DIV")) elif isinstance(other, float): if other == 0.0: raise ZeroDivisionError("Dividing by zero is not recommended") s = scantable(self._math._unaryop(self, other, "DIV", False)) else: raise TypeError("Other input is not a scantable or float value") s._add_history("operator /", varlist) return s @asaplog_post_dec 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.asapfit import asapfit fit = asapfit(self._getfit(row)) asaplog.push( '%s' %(fit) ) return fit.as_dict() def flag_nans(self): """\ Utility function to flag NaN values in the scantable. """ import numpy basesel = self.get_selection() for i in range(self.nrow()): sel = self.get_row_selector(i) self.set_selection(basesel+sel) nans = numpy.isnan(self._getspectrum(0)) if numpy.any(nans): bnans = [ bool(v) for v in nans] self.flag(bnans) self.set_selection(basesel) def get_row_selector(self, rowno): return selector(beams=self.getbeam(rowno), ifs=self.getif(rowno), pols=self.getpol(rowno), scans=self.getscan(rowno), cycles=self.getcycle(rowno)) def _add_history(self, funcname, parameters): if not rcParams['scantable.history']: return # 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 def _check_ifs(self): nchans = [self.nchan(i) for i in range(self.nif(-1))] nchans = filter(lambda t: t > 0, nchans) return (sum(nchans)/len(nchans) == nchans[0]) @asaplog_post_dec #def _fill(self, names, unit, average, getpt, antenna): def _fill(self, names, unit, average, opts={}): first = True fullnames = [] for name in names: name = os.path.expandvars(name) name = os.path.expanduser(name) if not os.path.exists(name): msg = "File '%s' does not exists" % (name) raise IOError(msg) fullnames.append(name) if average: asaplog.push('Auto averaging integrations') stype = int(rcParams['scantable.storage'].lower() == 'disk') for name in fullnames: tbl = Scantable(stype) r = filler(tbl) rx = rcParams['scantable.reference'] r.setreferenceexpr(rx) msg = "Importing %s..." % (name) asaplog.push(msg, False) #opts = {'ms': {'antenna' : antenna, 'getpt': getpt} } r.open(name, opts)# antenna, -1, -1, getpt) r.fill() if average: tbl = self._math._average((tbl, ), (), 'NONE', 'SCAN') if not first: tbl = self._math._merge([self, tbl]) Scantable.__init__(self, tbl) r.close() del r, tbl first = False #flush log asaplog.post() if unit is not None: self.set_fluxunit(unit) if not is_casapy(): self.set_freqframe(rcParams['scantable.freqframe']) def __getitem__(self, key): if key < 0: key += self.nrow() if key >= self.nrow(): raise IndexError("Row index out of range.") return self._getspectrum(key) def __setitem__(self, key, value): if key < 0: key += self.nrow() if key >= self.nrow(): raise IndexError("Row index out of range.") if not hasattr(value, "__len__") or \ len(value) > self.nchan(self.getif(key)): raise ValueError("Spectrum length doesn't match.") return self._setspectrum(value, key) def __len__(self): return self.nrow() def __iter__(self): for i in range(len(self)): yield self[i]