from asap import rcParams, print_log, selector from numarray import logical_and 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, visible=None): self._visible = rcParams['plotter.gui'] if visible is not None: self._visible = visible self._plotter = self._newplotter() 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._datamask = None self._data = None self._lmap = None self._title = None self._ordinate = None self._abcissa = None self._abcunit = None self._usermask = [] self._maskselection = None self._selection = selector() self._hist = rcParams['plotter.histogram'] def _translate(self, instr): keys = "s b i p t".split() if isinstance(instr, str): for key in keys: if instr.lower().startswith(key): return key return None def _newplotter(self): if self._visible: from asap.asaplotgui import asaplotgui as asaplot else: from asap.asaplot import asaplot return asaplot() def plot(self, scan=None): """ Plot a scantable. Parameters: scan: a scantable Note: If a scantable 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 scantable are consistent e.g. all 'channel' or all 'velocity' etc. """ if self._plotter.is_dead: self._plotter = self._newplotter() self._plotter.hold() self._plotter.clear() from asap import scantable if not self._data and not scan: print "please provide a scantable to plot" if isinstance(scan, scantable): if self._data is not None: if scan != self._data: self._data = scan # reset self._reset() else: self._data = scan self._reset() # ranges become invalid when unit changes if self._abcunit and self._abcunit != self._data.get_unit(): self._minmaxx = None self._minmaxy = None self._abcunit = self._data.get_unit() self._datamask = None self._plot(self._data) if self._minmaxy is not None: self._plotter.set_limits(ylim=self._minmaxy) self._plotter.release() print_log() 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 """ msg = "Invalid mode" if not self.set_panelling(panelling) or \ not self.set_stacking(stacking): if rcParams['verbose']: print msg return else: raise TypeError(msg) if self._data: self.plot(self._data) 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(self._data) 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(self._data) 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(self._data) 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(self._data) 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. Parameters: ordinate: a list of ordinate labels. None (default) let data determine the labels 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(self._data) 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. Parameters: abcissa: a list of abcissa labels. None (default) let data determine the labels 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(self._data) 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). Parameters: colormap: a list of colour names 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. """ if isinstance(colormap,str): colormap = colormap.split() self._plotter.palette(0,colormap=colormap) if self._data: self.plot(self._data) def set_histogram(self, hist=True): """ Enable/Disable histogram-like plotting. Parameters: hist: True (default) or False. The fisrt default is taken from the .asaprc setting plotter.histogram """ self._hist = hist if self._data: self.plot(self._data) def set_linestyles(self, linestyles): """ 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. Parameters: linestyles: a list of linestyles to use. 'line', 'dashed', 'dotted', 'dashdot', 'dashdotdot' and 'dashdashdot' are possible 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'. """ if isinstance(linestyles,str): linestyles = linestyles.split() self._plotter.palette(color=0,linestyle=0,linestyles=linestyles) if self._data: self.plot(self._data) def save(self, filename=None, orientation=None, dpi=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. dpi: The dpi of the output non-ps plot """ self._plotter.save(filename,orientation,dpi) return def set_mask(self, mask=None, selection=None): """ Set a plotting mask for a specific polarization. This is useful for masking out "noise" Pangle outside a source. Parameters: mask: a mask from scantable.create_mask selection: the spectra to apply the mask to. Example: select = selector() select.setpolstrings("Pangle") plotter.set_mask(mymask, select) """ if not self._data: msg = "Can only set mask after a first call to plot()" if rcParams['verbose']: print msg return else: raise RuntimeError(msg) if len(mask): if isinstance(mask, list) or isinstance(mask, tuple): self._usermask = array(mask) else: self._usermask = mask if mask is None and selection is None: self._usermask = [] self._maskselection = None if isinstance(selection, selector): self._maskselection = {'b': selection.get_beams(), 's': selection.get_scans(), 'i': selection.get_ifs(), 'p': selection.get_pols(), 't': [] } else: self._maskselection = None self.plot(self._data) 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 def _reset(self): self._usermask = [] self._usermaskspectra = None self.set_selection(None, False) def _plot(self, scan): savesel = scan.get_selection() sel = savesel + self._selection d0 = {'s': 'SCANNO', 'b': 'BEAMNO', 'i':'IFNO', 'p': 'POLNO', 'c': 'CYCLENO', 't' : 'TIME' } order = [d0[self._panelling],d0[self._stacking]] sel.set_order(order) scan.set_selection(sel) d = {'b': scan.getbeam, 's': scan.getscan, 'i': scan.getif, 'p': scan.getpol, 't': scan._gettime } polmodes = dict(zip(self._selection.get_pols(),self._selection.get_poltypes())) n,nstack = self._get_selected_n(scan) maxpanel, maxstack = 16,8 if n > maxpanel or nstack > maxstack: from asap import asaplog msg ="Scan to be plotted contains more than %d selections.\n" \ "Selecting first %d selections..." % (maxpanel,maxpanel) asaplog.push(msg) print_log() n = min(n,maxpanel) nstack = min(nstack,maxstack) if n > 1: ganged = rcParams['plotter.ganged'] 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,ganged=ganged) else: self._plotter.set_panels(rows=n,cols=0,nplots=n,ganged=ganged) else: self._plotter.set_panels() r=0 nr = scan.nrow() a0,b0 = -1,-1 allxlim = [] allylim = [] newpanel=True panelcount,stackcount = 0,0 while r < nr: a = d[self._panelling](r) b = d[self._stacking](r) if a > a0 and panelcount < n: if n > 1: self._plotter.subplot(panelcount) self._plotter.palette(0) #title xlab = self._abcissa and self._abcissa[panelcount] \ or scan._getabcissalabel() ylab = self._ordinate and self._ordinate[panelcount] \ or scan._get_ordinate_label() self._plotter.set_axes('xlabel',xlab) self._plotter.set_axes('ylabel',ylab) lbl = self._get_label(scan, r, self._panelling, self._title) if isinstance(lbl, list) or isinstance(lbl, tuple): if 0 <= panelcount < len(lbl): lbl = lbl[panelcount] else: # get default label lbl = self._get_label(scan, r, self._panelling, None) self._plotter.set_axes('title',lbl) newpanel = True stackcount =0 panelcount += 1 if (b > b0 or newpanel) and stackcount < nstack: y = [] if len(polmodes): y = scan._getspectrum(r, polmodes[scan.getpol(r)]) else: y = scan._getspectrum(r) m = scan._getmask(r) if self._maskselection and len(self._usermask) == len(m): if d[self._stacking](r) in self._maskselection[self._stacking]: m = logical_and(m, self._usermask) x = scan._getabcissa(r) if self._minmaxx is not None: s,e = self._slice_indeces(x) x = x[s:e] y = y[s:e] m = m[s:e] if len(x) > 2048 and rcParams['plotter.decimate']: fac = len(x)/2048 x = x[::fac] m = m[::fac] y = y[::fac] llbl = self._get_label(scan, r, self._stacking, self._lmap) if isinstance(llbl, list) or isinstance(llbl, tuple): if 0 <= stackcount < len(llbl): # use user label llbl = llbl[stackcount] else: # get default label llbl = self._get_label(scan, r, self._stacking, None) self._plotter.set_line(label=llbl) plotit = self._plotter.plot if self._hist: plotit = self._plotter.hist plotit(x,y,m) xlim= self._minmaxx or [min(x),max(x)] allxlim += xlim ylim= self._minmaxy or [min(y),max(y)] allylim += ylim stackcount += 1 # last in colour stack -> autoscale x if stackcount == nstack: allxlim.sort() self._plotter.axes.set_xlim([allxlim[0],allxlim[-1]]) # clear allxlim =[] newpanel = False a0=a b0=b # ignore following rows if (panelcount == n) and (stackcount == nstack): # last panel -> autoscale y if ganged if rcParams['plotter.ganged']: allylim.sort() self._plotter.set_limits(ylim=[allylim[0],allylim[-1]]) break r+=1 # next row #reset the selector to the scantable's original scan.set_selection(savesel) def set_selection(self, selection=None, refresh=True): self._selection = isinstance(selection,selector) and selection or selector() d0 = {'s': 'SCANNO', 'b': 'BEAMNO', 'i':'IFNO', 'p': 'POLNO', 'c': 'CYCLENO', 't' : 'TIME' } order = [d0[self._panelling],d0[self._stacking]] self._selection.set_order(order) if self._data and refresh: self.plot(self._data) def _get_selected_n(self, scan): d1 = {'b': scan.nbeam, 's': scan.nscan, 'i': scan.nif, 'p': scan.npol, 't': scan.ncycle } d2 = { 'b': len(self._selection.get_beams()), 's': len(self._selection.get_scans()), 'i': len(self._selection.get_ifs()), 'p': len(self._selection.get_pols()), 't': len(self._selection.get_cycles()) } n = d2[self._panelling] or d1[self._panelling]() nstack = d2[self._stacking] or d1[self._stacking]() return n,nstack def _get_label(self, scan, row, mode, userlabel=None): pms = dict(zip(self._selection.get_pols(),self._selection.get_poltypes())) if len(pms): poleval = scan._getpollabel(scan.getpol(row),pms[scan.getpol(row)]) else: poleval = scan._getpollabel(scan.getpol(row),scan.poltype()) d = {'b': "Beam "+str(scan.getbeam(row)), 's': scan._getsourcename(row), 'i': "IF"+str(scan.getif(row)), 'p': poleval, 't': scan._gettime(row) } return userlabel or d[mode]