from asap.asaplot import ASAPlot from asap import rcParams class asapplotter: """ The ASAP plotter. By default the plotter is set up to plot polarisations 'colour stacked' and scantables across panels. Note: Currenly it only plots 'spectra' not Tsys or other variables. """ def __init__(self): self._plotter = ASAPlot() self._tdict = {'Time':'t','time':'t','t':'t','T':'t'} self._bdict = {'Beam':'b','beam':'b','b':'b','B':'b'} self._idict = {'IF':'i','if':'i','i':'i','I':'i'} self._pdict = {'Pol':'p','pol':'p','p':'p'} self._sdict = {'scan':'s','Scan':'s','s':'s','S':'s'} self._cdict = {'t':'len(self._cursor["t"])', 'b':'len(self._cursor["b"])', 'i':'len(self._cursor["i"])', 'p':'len(self._cursor["p"])', 's':'len(scans)'} self._ldict = {'b':'Beam', 'i':'IF', 'p':'Pol', 's':'Scan'} self._dicts = [self._tdict,self._bdict, self._idict,self._pdict, self._sdict] self._panelling = None self._stacking = None self.set_panelling() self.set_stacking() self._rows = None self._cols = None self._autoplot = False self._minmaxx = None self._minmaxy = None self._data = None self._lmap = None self._title = None self._ordinate = None self._abcissa = None self._abcunit = None self._cursor = {'t':None, 'b':None, 'i':None, 'p':None } def _translate(self, name): for d in self._dicts: if d.has_key(name): return d[name] return None def plot(self, *args): """ Plot a (list of) scantables. Parameters: one or more comma separated scantables Note: If a (list) of scantables was specified in a previous call to plot, no argument has to be given to 'replot' NO checking is done that the abcissas of the scantables are consistent e.g. all 'channel' or all 'velocity' etc. """ if self._plotter.is_dead: self._plotter = ASAPlot() self._plotter.hold() self._plotter.clear() if len(args) > 0: if self._data is not None: if list(args) != self._data: self._data = list(args) # reset cursor self.set_cursor(refresh=False) else: self._data = list(args) self.set_cursor(refresh=False) # ranges become invalid when unit changes if self._abcunit != self._data[0].get_unit(): self._minmaxx = None self._minmaxy = None self._abcunit = self._data[0].get_unit() if self._panelling == 't': maxrows = 25 if self._data[0].nrow() > maxrows: if self._cursor["t"] is None or \ (isinstance(self._cursor["t"],list) and \ len(self._cursor["t"]) > maxrows ): print "Scan to be plotted contains more than %d rows.\n" \ "Selecting first %d rows..." % (maxrows,maxrows) self._cursor["t"] = range(maxrows) self._plot_time(self._data[0], self._stacking) elif self._panelling == 's': self._plot_scans(self._data, self._stacking) else: self._plot_other(self._data, self._stacking) if self._minmaxy is not None: self._plotter.set_limits(ylim=self._minmaxy) self._plotter.release() return def _plot_time(self, scan, colmode): if colmode == 't': return n = len(self._cursor["t"]) cdict = {'b':'scan.setbeam(j)', 'i':'scan.setif(j)', 'p':'scan.setpol(j)'} cdict2 = {'b':'self._cursor["b"]', 'i':'self._cursor["i"]', 'p':'self._cursor["p"]'} ncol = 1 if self._stacking is not None: ncol = eval(self._cdict.get(colmode)) if n > 1: if self._rows and self._cols: n = min(n,self._rows*self._cols) self._plotter.set_panels(rows=self._rows,cols=self._cols, nplots=n) else: self._plotter.set_panels(rows=n,cols=0,nplots=n) else: self._plotter.set_panels() rows = self._cursor["t"] self._plotter.palette(0) for rowsel in rows: i = self._cursor["t"].index(rowsel) if n > 1: self._plotter.palette(0) self._plotter.subplot(i) colvals = eval(cdict2.get(colmode)) for j in colvals: polmode = "raw" jj = colvals.index(j) savej = j for k in cdict.keys(): sel = eval(cdict2.get(k)) j = sel[0] if k == "p": which = self._cursor["p"].index(j) polmode = self._polmode[which] j = which eval(cdict.get(k)) j = savej if colmode == "p": polmode = self._polmode[self._cursor["p"].index(j)] #j = jj eval(cdict.get(colmode)) x = None y = None m = None if self._title is None: tlab = scan._getsourcename(rowsel) else: if len(self._title) >= n: tlab = self._title[rowsel] else: tlab = scan._getsourcename(rowsel) x,xlab = scan.get_abcissa(rowsel) if self._abcissa: xlab = self._abcissa y = None if polmode == "stokes": y = scan._getstokesspectrum(rowsel) elif polmode == "stokes2": y = scan._getstokesspectrum(rowsel,True) elif polmode == "circular": y = scan._stokestopolspectrum(rowsel,False,-1) else: y = scan._getspectrum(rowsel) if self._ordinate: ylab = self._ordinate else: ylab = scan._get_ordinate_label() m = scan._getmask(rowsel) if self._lmap and len(self._lmap) > 0: llab = self._lmap[jj] else: if colmode == 'p': llab = self._get_pollabel(scan, polmode) else: llab = self._ldict.get(colmode)+' '+str(j) self._plotter.set_line(label=llab) if self._minmaxx is not None: s,e = self._slice_indeces(x) x = x[s:e] y = y[s:e] m = m[s:e] self._plotter.plot(x,y,m) xlim=[min(x),max(x)] if self._minmaxx is not None: xlim = self._minmaxx self._plotter.axes.set_xlim(xlim) self._plotter.set_axes('xlabel',xlab) self._plotter.set_axes('ylabel',ylab) self._plotter.set_axes('title',tlab) return def _plot_scans(self, scans, colmode): print "Plotting mode is scans across panels. Can only plot one row per scan." if colmode == 's': return cdict = {'b':'scan.setbeam(j)', 'i':'scan.setif(j)', 'p':'scan.setpol(j)'} cdict2 = {'b':'self._cursor["b"]', 'i':'self._cursor["i"]', 'p':'self._cursor["p"]'} n = len(scans) ncol = 1 if self._stacking is not None: scan = scans[0] ncol = eval(self._cdict.get(colmode)) if n > 1: if self._rows and self._cols: n = min(n,self._rows*self._cols) self._plotter.set_panels(rows=self._rows,cols=self._cols, nplots=n) else: self._plotter.set_panels(rows=n,cols=0,nplots=n) else: self._plotter.set_panels() for scan in scans: self._plotter.palette(0) if n > 1: self._plotter.subplot(scans.index(scan)) colvals = eval(cdict2.get(colmode)) rowsel = self._cursor["t"][0] for j in colvals: polmode = "raw" jj = colvals.index(j) savej = j for k in cdict.keys(): sel = eval(cdict2.get(k)) j = sel[0] eval(cdict.get(k)) if k == "p": which = self._cursor["p"].index(j) polmode = self._polmode[which] j = which j = savej if colmode == "p": polmode = self._polmode[self._cursor["p"].index(j)] #j = jj eval(cdict.get(colmode)) x = None y = None m = None tlab = self._title if not self._title: tlab = scan._getsourcename(rowsel) x,xlab = scan.get_abcissa(rowsel) if self._abcissa: xlab = self._abcissa if polmode == "stokes": y = scan._getstokesspectrum(rowsel) elif polmode == "stokes2": y = scan._getstokesspectrum(rowsel,True) elif polmode == "circular": y = scan._stokestopolspectrum(rowsel,False,-1) else: y = scan._getspectrum(rowsel) if self._ordinate: ylab = self._ordinate else: ylab = scan._get_ordinate_label() m = scan._getmask(rowsel) if self._lmap and len(self._lmap) > 0: llab = self._lmap[jj] else: if colmode == 'p': llab = self._get_pollabel(scan, polmode) else: llab = self._ldict.get(colmode)+' '+str(j) self._plotter.set_line(label=llab) if self._minmaxx is not None: s,e = self._slice_indeces(x) x = x[s:e] y = y[s:e] m = m[s:e] self._plotter.plot(x,y,m) xlim=[min(x),max(x)] if self._minmaxx is not None: xlim = self._minmaxx self._plotter.axes.set_xlim(xlim) self._plotter.set_axes('xlabel',xlab) self._plotter.set_axes('ylabel',ylab) self._plotter.set_axes('title',tlab) return def _plot_other(self,scans,colmode): if colmode == self._panelling: return cdict = {'b':'scan.setbeam(i)', 'i':'scan.setif(i)', 'p':'scan.setpol(i)'} cdict2 = {'b':'self._cursor["b"]', 'i':'self._cursor["i"]', 'p':'self._cursor["p"]', 's': 'scans', 't': 'self._cursor["t"]'} scan = scans[0] n = eval(self._cdict.get(self._panelling)) ncol=1 if self._stacking is not None: ncol = eval(self._cdict.get(colmode)) if n > 1: if self._rows and self._cols: n = min(n,self._rows*self._cols) self._plotter.set_panels(rows=self._rows,cols=self._cols, nplots=n) else: self._plotter.set_panels(rows=n,cols=0,nplots=n) else: self._plotter.set_panels() panels = self._cursor[self._panelling] for i in panels: self._plotter.palette(0) polmode = "raw" ii = self._cursor[self._panelling].index(i) if n>1: self._plotter.subplot(ii) if self._panelling == "p": polmode = self._polmode[ii] eval(cdict.get(self._panelling)) else: eval(cdict.get(self._panelling)) colvals = eval(cdict2.get(colmode)) for j in colvals: rowsel = self._cursor["t"][0] jj = colvals.index(j) savei = i for k in cdict.keys(): if k != self._panelling: sel = eval(cdict2.get(k)) i = sel[0] if k == "p": which = self._cursor["p"].index(i) polmode = self._polmode[which] i = which eval(cdict.get(k)) i = savei if colmode == 's': scan = j elif colmode == 't': rowsel = j else: savei = i if colmode == 'p': polmode = self._polmode[self._cursor["p"].index(j)] i = j eval(cdict.get(colmode)) i = savei x = None y = None m = None x,xlab = scan.get_abcissa(rowsel) if self._abcissa: xlab = self._abcissa if polmode == "stokes": y = scan._getstokesspectrum(rowsel) elif polmode == "stokes2": y = scan._getstokesspectrum(rowsel,True) elif polmode == "circular": y = scan._stokestopolspectrum(rowsel,False,-1) else: y = scan._getspectrum(rowsel) if self._ordinate: ylab = self._ordinate else: ylab = scan._get_ordinate_label() m = scan._getmask(rowsel) if colmode == 's' or colmode == 't': if self._title and len(self._title) > 0: tlab = self._title[ii] else: if self._panelling == 'p': tlab = self._get_pollabel(scan, polmode) else: tlab = self._ldict.get(self._panelling)+' '+str(i) if self._lmap and len(self._lmap) > 0: llab = self._lmap[jj] else: llab = scan._getsourcename(rowsel) else: if self._title and len(self._title) > 0: tlab = self._title[ii] else: if self._panelling == 'p': tlab = self._get_pollabel(scan, polmode) else: tlab = self._ldict.get(self._panelling)+' '+str(i) if self._lmap and len(self._lmap) > 0: llab = self._lmap[jj] else: if colmode == 'p': llab = self._get_pollabel(scan, polmode) else: llab = self._ldict.get(colmode)+' '+str(j) self._plotter.set_line(label=llab) if self._minmaxx is not None: s,e = self._slice_indeces(x) x = x[s:e] y = y[s:e] m = m[s:e] self._plotter.plot(x,y,m) xlim=[min(x),max(x)] if self._minmaxx is not None: xlim = self._minmaxx self._plotter.axes.set_xlim(xlim) self._plotter.set_axes('xlabel',xlab) self._plotter.set_axes('ylabel',ylab) self._plotter.set_axes('title',tlab) return def set_mode(self, stacking=None, panelling=None): """ Set the plots look and feel, i.e. what you want to see on the plot. Parameters: stacking: tell the plotter which variable to plot as line color overlays (default 'pol') panelling: tell the plotter which variable to plot across multiple panels (default 'scan' Note: Valid modes are: 'beam' 'Beam' 'b': Beams 'if' 'IF' 'i': IFs 'pol' 'Pol' 'p': Polarisations 'scan' 'Scan' 's': Scans 'time' 'Time' 't': Times """ if not self.set_panelling(panelling): print "Invalid mode" return if not self.set_stacking(stacking): print "Invalid mode" return if self._data: self.plot() return def set_panelling(self, what=None): mode = what if mode is None: mode = rcParams['plotter.panelling'] md = self._translate(mode) if md: self._panelling = md self._title = None return True return False def set_layout(self,rows=None,cols=None): """ Set the multi-panel layout, i.e. how many rows and columns plots are visible. Parameters: rows: The number of rows of plots cols: The number of columns of plots Note: If no argument is given, the potter reverts to its auto-plot behaviour. """ self._rows = rows self._cols = cols if self._data: self.plot() return def set_stacking(self, what=None): mode = what if mode is None: mode = rcParams['plotter.stacking'] md = self._translate(mode) if md: self._stacking = md self._lmap = None return True return False def set_range(self,xstart=None,xend=None,ystart=None,yend=None): """ Set the range of interest on the abcissa of the plot Parameters: [x,y]start,[x,y]end: The start and end points of the 'zoom' window Note: These become non-sensical when the unit changes. use plotter.set_range() without parameters to reset """ if xstart is None and xend is None: self._minmaxx = None else: self._minmaxx = [xstart,xend] if ystart is None and yend is None: self._minmaxy = None else: self._minmaxy = [ystart,yend] if self._data: self.plot() return def set_legend(self, mp=None): """ Specify a mapping for the legend instead of using the default indices: Parameters: mp: a list of 'strings'. This should have the same length as the number of elements on the legend and then maps to the indeces in order. It is possible to uses latex math expression. These have to be enclosed in r'', e.g. r'$x^{2}$' Example: If the data has two IFs/rest frequencies with index 0 and 1 for CO and SiO: plotter.set_stacking('i') plotter.set_legend(['CO','SiO']) plotter.plot() plotter.set_legend([r'$^{12}CO$', r'SiO']) """ self._lmap = mp if self._data: self.plot() return def set_title(self, title=None): """ Set the title of the plot. If multiple panels are plotted, multiple titles have to be specified. Example: # two panels are visible on the plotter plotter.set_title(["First Panel","Second Panel"]) """ self._title = title if self._data: self.plot() return def set_ordinate(self, ordinate=None): """ Set the y-axis label of the plot. If multiple panels are plotted, multiple labels have to be specified. Example: # two panels are visible on the plotter plotter.set_ordinate(["First Y-Axis","Second Y-Axis"]) """ self._ordinate = ordinate if self._data: self.plot() return def set_abcissa(self, abcissa=None): """ Set the x-axis label of the plot. If multiple panels are plotted, multiple labels have to be specified. Example: # two panels are visible on the plotter plotter.set_ordinate(["First X-Axis","Second X-Axis"]) """ self._abcissa = abcissa if self._data: self.plot() return def set_colors(self, colormap): """ Set the colors to be used. The plotter will cycle through these colors when lines are overlaid (stacking mode). Example: plotter.set_colors("red green blue") # If for example four lines are overlaid e.g I Q U V # 'I' will be 'red', 'Q' will be 'green', U will be 'blue' # and 'V' will be 'red' again. """ self._plotter.palette(0,colormap=colormap) if self._data: self.plot() def set_linestyles(self, linestyles): """ Parameters: linestyles: a list of linestyles to use. 'line', 'dashed', 'dotted', 'dashdot', 'dashdotdot' and 'dashdashdot' are possible Set the linestyles to be used. The plotter will cycle through these linestyles when lines are overlaid (stacking mode) AND only one color has been set. Example: plotter.set_colors("black") plotter.set_linestyles("line dashed dotted dashdot") # If for example four lines are overlaid e.g I Q U V # 'I' will be 'solid', 'Q' will be 'dashed', # U will be 'dotted' and 'V' will be 'dashdot'. """ self._plotter.palette(color=0,linestyle=0,linestyles=linestyles) if self._data: self.plot() def save(self, filename=None, orientation=None): """ Save the plot to a file. The know formats are 'png', 'ps', 'eps'. Parameters: filename: The name of the output file. This is optional and autodetects the image format from the file suffix. If non filename is specified a file called 'yyyymmdd_hhmmss.png' is created in the current directory. orientation: optional parameter for postscript only (not eps). 'landscape', 'portrait' or None (default) are valid. If None is choosen for 'ps' output, the plot is automatically oriented to fill the page. """ self._plotter.save(filename,orientation) return def set_cursor(self, row=None,beam=None,IF=None,pol=None, refresh=True): """ Specify a 'cursor' for plotting selected spectra. Time (rows), Beam, IF, Polarisation ranges can be specified. Parameters: Default for all paramaters is to select all available row: selects the rows (time stamps) to be plotted, this has to be a vector of row indices, e.g. row=[0,2,5] or row=[2] beam: select a range of beams IF: select a range of IFs pol: select Polarisations for plotting these can be by index (raw polarisations (default)) or by names any of: ["I", "Q", "U", "V"] or ["I", "Plinear", "Pangle", "V"] or ["XX", "YY", "Real(XY)", "Imag(XY)"] or ["RR", "LL"] Example: plotter.set_mode('pol','time') plotter.plot(myscan) # plots all raw polarisations colour stacked plotter.set_cursor(pol=["I"]) # plot "I" only for all rows # plot "I" only for two time stamps row=0 and row=2 plotter.set_cursor(row=[0,2],pol=["I"]) Note: Be careful to select only exisiting polarisations. """ if not self._data: print "Can only set cursor after a first call to plot()" return n = self._data[0].nrow() if row is None: self._cursor["t"] = range(n) else: for i in row: if i < 0 or i >= n: print "Row index '%d' out of range" % i return self._cursor["t"] = row n = self._data[0].nbeam() if beam is None: self._cursor["b"] = range(n) else: for i in beam: if i < 0 or i >= n: print "Beam index '%d' out of range" % i return self._cursor["b"] = beam n = self._data[0].nif() if IF is None: self._cursor["i"] = range(n) else: for i in IF: if i < 0 or i >= n: print "IF index '%d' out of range" %i return self._cursor["i"] = IF n = self._data[0].npol() dstokes = {"I":0,"Q":1,"U":2,"V":3} dstokes2 = {"I":0,"Plinear":1,"Pangle":2,"V":3} draw = {"XX":0, "YY":1,"Real(XY)":2, "Imag(XY)":3} dcirc = { "RR":0,"LL":1}#,"Real(RL)":2,"Imag(RL)":3} if pol is None: self._cursor["p"] = range(n) self._polmode = ["raw" for i in range(n)] else: if isinstance(pol,str): pol = pol.split() polmode = [] pols = [] for i in pol: if isinstance(i,str): if draw.has_key(i): pols.append(draw.get(i)) polmode.append("raw") elif dstokes.has_key(i): pols.append(dstokes.get(i)) polmode.append("stokes") elif dstokes2.has_key(i): pols.append(dstokes2.get(i)) polmode.append("stokes2") elif dcirc.has_key(i): pols.append(dcirc.get(i)) polmode.append("circular") else: print "Pol type '%s' not valid" %i return elif 0 > i >= n: print "Pol index '%d' out of range" %i return else: pols.append(i) polmode.append("raw") self._cursor["p"] = pols self._polmode = polmode if self._data and refresh: self.plot() def _get_pollabel(self, scan, polmode): tlab = "" if polmode == "stokes": tlab = scan._getpolarizationlabel(0,1,0) elif polmode == "stokes2": tlab = scan._getpolarizationlabel(0,1,1) elif polmode == "circular": tlab = scan._getpolarizationlabel(0,0,0) else: tlab = scan._getpolarizationlabel(1,0,0) return tlab def _slice_indeces(self, data): mn = self._minmaxx[0] mx = self._minmaxx[1] asc = data[0] < data[-1] start=0 end = len(data)-1 inc = 1 if not asc: start = len(data)-1 end = 0 inc = -1 # find min index while data[start] < mn: start+= inc # find max index while data[end] > mx: end-=inc end +=1 if start > end: return end,start return start,end if __name__ == '__main__': plotter = asapplotter()