| [203] | 1 | from asap.asaplot import ASAPlot
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| [226] | 2 | from asap import rcParams
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| [203] | 3 |
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| 4 | class asapplotter:
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| [226] | 5 | """
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| 6 | The ASAP plotter.
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| 7 | By default the plotter is set up to plot polarisations
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| 8 | 'colour stacked' and scantables across panels.
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| 9 | Note:
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| 10 | Currenly it only plots 'spectra' not Tsys or
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| 11 | other variables.
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| 12 | """
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| [203] | 13 | def __init__(self):
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| 14 | self._plotter = ASAPlot()
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| 15 |
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| 16 | self._tdict = {'Time':'t','time':'t','t':'t','T':'t'}
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| 17 | self._bdict = {'Beam':'b','beam':'b','b':'b','B':'b'}
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| 18 | self._idict = {'IF':'i','if':'i','i':'i','I':'i'}
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| 19 | self._pdict = {'Pol':'p','pol':'p','p':'p'}
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| 20 | self._sdict = {'scan':'s','Scan':'s','s':'s','S':'s'}
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| [525] | 21 | self._cdict = {'t':'len(self._cursor["t"])',
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| 22 | 'b':'len(self._cursor["b"])',
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| 23 | 'i':'len(self._cursor["i"])',
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| 24 | 'p':'len(self._cursor["p"])',
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| [203] | 25 | 's':'len(scans)'}
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| 26 | self._ldict = {'b':'Beam',
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| 27 | 'i':'IF',
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| 28 | 'p':'Pol',
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| 29 | 's':'Scan'}
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| 30 | self._dicts = [self._tdict,self._bdict,
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| 31 | self._idict,self._pdict,
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| 32 | self._sdict]
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| [554] | 33 | self._panelling = None
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| 34 | self._stacking = None
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| 35 | self.set_panelling()
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| 36 | self.set_stacking()
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| [377] | 37 | self._rows = None
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| 38 | self._cols = None
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| [203] | 39 | self._autoplot = False
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| [525] | 40 | self._minmaxx = None
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| 41 | self._minmaxy = None
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| [203] | 42 | self._data = None
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| [605] | 43 | self._lmap = None
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| [226] | 44 | self._title = None
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| [257] | 45 | self._ordinate = None
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| 46 | self._abcissa = None
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| [525] | 47 | self._cursor = {'t':None, 'b':None,
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| 48 | 'i':None, 'p':None
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| 49 | }
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| [203] | 50 |
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| 51 | def _translate(self, name):
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| 52 | for d in self._dicts:
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| 53 | if d.has_key(name):
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| 54 | return d[name]
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| 55 | return None
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| 56 |
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| [525] | 57 | def plot(self, *args):
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| [203] | 58 | """
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| 59 | Plot a (list of) scantables.
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| 60 | Parameters:
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| 61 | one or more comma separated scantables
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| 62 | Note:
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| 63 | If a (list) of scantables was specified in a previous call
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| 64 | to plot, no argument has to be given to 'replot'
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| [525] | 65 | NO checking is done that the abcissas of the scantables
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| [203] | 66 | are consistent e.g. all 'channel' or all 'velocity' etc.
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| 67 | """
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| 68 | if self._plotter.is_dead:
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| 69 | self._plotter = ASAPlot()
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| [597] | 70 | self._plotter.hold()
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| [203] | 71 | self._plotter.clear()
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| 72 | if len(args) > 0:
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| [525] | 73 | if self._data is not None:
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| 74 | if list(args) != self._data:
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| 75 | self._data = list(args)
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| 76 | # reset cursor
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| [541] | 77 | self.set_cursor(refresh=False)
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| [525] | 78 | else:
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| 79 | self._data = list(args)
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| [541] | 80 | self.set_cursor(refresh=False)
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| [554] | 81 | if self._panelling == 't':
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| [622] | 82 | maxrows = 25
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| [541] | 83 | if self._data[0].nrow() > maxrows:
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| [601] | 84 | if self._cursor["t"] is None or \
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| 85 | (isinstance(self._cursor["t"],list) and \
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| 86 | len(self._cursor["t"]) > maxrows ):
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| 87 | print "Scan to be plotted contains more than %d rows.\n" \
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| 88 | "Selecting first %d rows..." % (maxrows,maxrows)
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| 89 | self._cursor["t"] = range(maxrows)
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| [203] | 90 | self._plot_time(self._data[0], self._stacking)
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| [554] | 91 | elif self._panelling == 's':
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| [203] | 92 | self._plot_scans(self._data, self._stacking)
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| 93 | else:
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| 94 | self._plot_other(self._data, self._stacking)
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| [525] | 95 | if self._minmaxx is not None or self._minmaxy is not None:
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| 96 | self._plotter.set_limits(xlim=self._minmaxx,ylim=self._minmaxy)
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| [203] | 97 | self._plotter.release()
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| 98 | return
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| 99 |
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| 100 | def _plot_time(self, scan, colmode):
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| 101 | if colmode == 't':
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| 102 | return
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| [525] | 103 | n = len(self._cursor["t"])
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| [203] | 104 | cdict = {'b':'scan.setbeam(j)',
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| 105 | 'i':'scan.setif(j)',
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| 106 | 'p':'scan.setpol(j)'}
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| [525] | 107 | cdict2 = {'b':'self._cursor["b"]',
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| 108 | 'i':'self._cursor["i"]',
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| 109 | 'p':'self._cursor["p"]'}
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| 110 | ncol = 1
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| [203] | 111 | if self._stacking is not None:
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| 112 | ncol = eval(self._cdict.get(colmode))
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| 113 | if n > 1:
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| [377] | 114 | if self._rows and self._cols:
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| 115 | n = min(n,self._rows*self._cols)
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| 116 | self._plotter.set_panels(rows=self._rows,cols=self._cols,
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| 117 | nplots=n)
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| 118 | else:
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| [485] | 119 | self._plotter.set_panels(rows=n,cols=0,nplots=n)
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| [597] | 120 | else:
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| 121 | self._plotter.set_panels()
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| [525] | 122 | rows = self._cursor["t"]
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| 123 | self._plotter.palette(1)
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| 124 | for rowsel in rows:
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| 125 | i = self._cursor["t"].index(rowsel)
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| [203] | 126 | if n > 1:
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| [377] | 127 | self._plotter.palette(1)
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| [203] | 128 | self._plotter.subplot(i)
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| [525] | 129 | colvals = eval(cdict2.get(colmode))
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| 130 | for j in colvals:
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| 131 | polmode = "raw"
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| 132 | jj = colvals.index(j)
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| 133 | savej = j
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| 134 | for k in cdict.keys():
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| 135 | sel = eval(cdict2.get(k))
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| 136 | j = sel[0]
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| 137 | if k == "p":
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| 138 | which = self._cursor["p"].index(j)
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| 139 | polmode = self._polmode[which]
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| 140 | j = which
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| 141 | eval(cdict.get(k))
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| 142 | j = savej
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| 143 | if colmode == "p":
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| 144 | polmode = self._polmode[self._cursor["p"].index(j)]
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| 145 | j = jj
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| [203] | 146 | eval(cdict.get(colmode))
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| 147 | x = None
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| 148 | y = None
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| 149 | m = None
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| [622] | 150 | if self._title is None:
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| [525] | 151 | tlab = scan._getsourcename(rowsel)
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| [226] | 152 | else:
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| [622] | 153 | if len(self._title) >= n:
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| [525] | 154 | tlab = self._title[rowsel]
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| [226] | 155 | else:
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| [525] | 156 | tlab = scan._getsourcename(rowsel)
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| 157 | x,xlab = scan.get_abcissa(rowsel)
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| [257] | 158 | if self._abcissa: xlab = self._abcissa
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| [525] | 159 | y = None
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| 160 | if polmode == "stokes":
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| 161 | y = scan._getstokesspectrum(rowsel)
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| 162 | elif polmode == "stokes2":
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| 163 | y = scan._getstokesspectrum(rowsel,True)
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| [541] | 164 | elif polmode == "circular":
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| 165 | y = scan._stokestopolspectrum(rowsel,False,-1)
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| [525] | 166 | else:
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| 167 | y = scan._getspectrum(rowsel)
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| [257] | 168 | if self._ordinate:
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| 169 | ylab = self._ordinate
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| 170 | else:
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| [622] | 171 | ylab = scan._get_ordinate_label()
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| [525] | 172 | m = scan._getmask(rowsel)
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| [226] | 173 | if self._lmap and len(self._lmap) > 0:
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| [525] | 174 | llab = self._lmap[jj]
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| [203] | 175 | else:
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| [525] | 176 | if colmode == 'p':
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| [601] | 177 | llab = self._get_pollabel(scan, polmode)
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| [525] | 178 | else:
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| 179 | llab = self._ldict.get(colmode)+' '+str(j)
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| [203] | 180 | self._plotter.set_line(label=llab)
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| 181 | self._plotter.plot(x,y,m)
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| 182 | xlim=[min(x),max(x)]
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| 183 | self._plotter.axes.set_xlim(xlim)
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| 184 | self._plotter.set_axes('xlabel',xlab)
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| 185 | self._plotter.set_axes('ylabel',ylab)
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| 186 | self._plotter.set_axes('title',tlab)
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| 187 | return
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| 188 |
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| [525] | 189 | def _plot_scans(self, scans, colmode):
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| 190 | print "Can only plot one row per scan."
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| [203] | 191 | if colmode == 's':
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| 192 | return
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| 193 | cdict = {'b':'scan.setbeam(j)',
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| 194 | 'i':'scan.setif(j)',
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| 195 | 'p':'scan.setpol(j)'}
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| [525] | 196 | cdict2 = {'b':'self._cursor["b"]',
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| 197 | 'i':'self._cursor["i"]',
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| 198 | 'p':'self._cursor["p"]'}
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| 199 |
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| [203] | 200 | n = len(scans)
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| [525] | 201 | ncol = 1
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| [203] | 202 | if self._stacking is not None:
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| 203 | scan = scans[0]
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| 204 | ncol = eval(self._cdict.get(colmode))
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| 205 | if n > 1:
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| [377] | 206 | if self._rows and self._cols:
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| 207 | n = min(n,self._rows*self._cols)
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| [622] | 208 | self._plotter.set_panels(rows=self._rows,cols=self._cols,
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| [377] | 209 | nplots=n)
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| 210 | else:
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| [622] | 211 | self._plotter.set_panels(rows=n,cols=0,nplots=n)
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| [597] | 212 | else:
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| 213 | self._plotter.set_panels()
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| [203] | 214 | for scan in scans:
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| [541] | 215 | self._plotter.palette(1)
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| [203] | 216 | if n > 1:
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| [525] | 217 | self._plotter.subplot(scans.index(scan))
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| [485] | 218 | self._plotter.palette(1)
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| [525] | 219 | colvals = eval(cdict2.get(colmode))
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| 220 | rowsel = self._cursor["t"][0]
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| 221 | for j in colvals:
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| 222 | polmode = "raw"
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| 223 | jj = colvals.index(j)
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| 224 | savej = j
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| 225 | for k in cdict.keys():
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| 226 | sel = eval(cdict2.get(k))
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| 227 | j = sel[0]
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| 228 | eval(cdict.get(k))
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| 229 | if k == "p":
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| 230 | which = self._cursor["p"].index(j)
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| 231 | polmode = self._polmode[which]
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| 232 | j = which
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| 233 | j = savej
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| 234 | if colmode == "p":
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| 235 | polmode = self._polmode[self._cursor["p"].index(j)]
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| 236 | j = jj
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| [203] | 237 | eval(cdict.get(colmode))
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| 238 | x = None
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| 239 | y = None
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| 240 | m = None
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| [226] | 241 | tlab = self._title
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| 242 | if not self._title:
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| [525] | 243 | tlab = scan._getsourcename(rowsel)
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| 244 | x,xlab = scan.get_abcissa(rowsel)
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| [257] | 245 | if self._abcissa: xlab = self._abcissa
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| [525] | 246 | if polmode == "stokes":
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| 247 | y = scan._getstokesspectrum(rowsel)
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| 248 | elif polmode == "stokes2":
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| 249 | y = scan._getstokesspectrum(rowsel,True)
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| [541] | 250 | elif polmode == "circular":
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| 251 | y = scan._stokestopolspectrum(rowsel,False,-1)
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| [525] | 252 | else:
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| 253 | y = scan._getspectrum(rowsel)
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| [257] | 254 | if self._ordinate:
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| 255 | ylab = self._ordinate
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| 256 | else:
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| [622] | 257 | ylab = scan._get_ordinate_label()
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| [525] | 258 | m = scan._getmask(rowsel)
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| [257] | 259 | if self._lmap and len(self._lmap) > 0:
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| [525] | 260 | llab = self._lmap[jj]
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| [203] | 261 | else:
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| [525] | 262 | if colmode == 'p':
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| [601] | 263 | llab = self._get_pollabel(scan, polmode)
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| [525] | 264 | else:
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| 265 | llab = self._ldict.get(colmode)+' '+str(j)
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| [203] | 266 | self._plotter.set_line(label=llab)
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| 267 | self._plotter.plot(x,y,m)
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| 268 | xlim=[min(x),max(x)]
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| 269 | self._plotter.axes.set_xlim(xlim)
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| 270 |
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| 271 | self._plotter.set_axes('xlabel',xlab)
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| 272 | self._plotter.set_axes('ylabel',ylab)
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| 273 | self._plotter.set_axes('title',tlab)
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| 274 | return
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| 275 |
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| 276 | def _plot_other(self,scans,colmode):
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| [554] | 277 | if colmode == self._panelling:
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| [203] | 278 | return
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| [525] | 279 | cdict = {'b':'scan.setbeam(i)',
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| 280 | 'i':'scan.setif(i)',
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| 281 | 'p':'scan.setpol(i)'}
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| 282 | cdict2 = {'b':'self._cursor["b"]',
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| 283 | 'i':'self._cursor["i"]',
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| 284 | 'p':'self._cursor["p"]',
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| 285 | 's': 'scans',
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| 286 | 't': 'self._cursor["t"]'}
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| [203] | 287 | scan = scans[0]
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| [554] | 288 | n = eval(self._cdict.get(self._panelling))
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| [525] | 289 | ncol=1
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| [203] | 290 | if self._stacking is not None:
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| 291 | ncol = eval(self._cdict.get(colmode))
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| 292 | if n > 1:
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| [377] | 293 | if self._rows and self._cols:
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| 294 | n = min(n,self._rows*self._cols)
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| 295 | self._plotter.set_panels(rows=self._rows,cols=self._cols,
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| 296 | nplots=n)
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| 297 | else:
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| [485] | 298 | self._plotter.set_panels(rows=n,cols=0,nplots=n)
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| [597] | 299 | else:
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| 300 | self._plotter.set_panels()
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| [554] | 301 | panels = self._cursor[self._panelling]
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| [525] | 302 | for i in panels:
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| [541] | 303 | self._plotter.palette(1)
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| [525] | 304 | polmode = "raw"
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| [554] | 305 | ii = self._cursor[self._panelling].index(i)
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| [203] | 306 | if n>1:
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| [525] | 307 | self._plotter.subplot(ii)
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| [554] | 308 | if self._panelling == "p":
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| [525] | 309 | polmode = self._polmode[ii]
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| [554] | 310 | eval(cdict.get(self._panelling))
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| [525] | 311 | else:
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| [554] | 312 | eval(cdict.get(self._panelling))
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| [525] | 313 | colvals = eval(cdict2.get(colmode))
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| 314 | for j in colvals:
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| 315 | rowsel = self._cursor["t"][0]
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| 316 | jj = colvals.index(j)
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| 317 | savei = i
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| 318 | for k in cdict.keys():
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| [554] | 319 | if k != self._panelling:
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| [525] | 320 | sel = eval(cdict2.get(k))
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| 321 | i = sel[0]
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| 322 | if k == "p":
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| [557] | 323 | which = self._cursor["p"].index(i)
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| [525] | 324 | polmode = self._polmode[which]
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| 325 | i = which
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| 326 | eval(cdict.get(k))
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| 327 | i = savei
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| [203] | 328 | if colmode == 's':
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| [525] | 329 | scan = j
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| [203] | 330 | elif colmode == 't':
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| [525] | 331 | rowsel = j
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| [203] | 332 | else:
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| [525] | 333 | savei = i
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| 334 | if colmode == 'p':
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| 335 | polmode = self._polmode[self._cursor["p"].index(j)]
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| 336 | i = j
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| [203] | 337 | eval(cdict.get(colmode))
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| [525] | 338 | i = savei
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| [203] | 339 | x = None
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| 340 | y = None
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| 341 | m = None
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| [525] | 342 | x,xlab = scan.get_abcissa(rowsel)
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| [257] | 343 | if self._abcissa: xlab = self._abcissa
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| [525] | 344 | if polmode == "stokes":
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| 345 | y = scan._getstokesspectrum(rowsel)
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| 346 | elif polmode == "stokes2":
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| 347 | y = scan._getstokesspectrum(rowsel,True)
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| [541] | 348 | elif polmode == "circular":
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| 349 | y = scan._stokestopolspectrum(rowsel,False,-1)
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| [525] | 350 | else:
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| 351 | y = scan._getspectrum(rowsel)
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| 352 |
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| [257] | 353 | if self._ordinate:
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| 354 | ylab = self._ordinate
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| 355 | else:
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| [622] | 356 | ylab = scan._get_ordinate_label()
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| [525] | 357 | m = scan._getmask(rowsel)
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| [203] | 358 | if colmode == 's' or colmode == 't':
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| [525] | 359 | if self._title and len(self._title) > 0:
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| 360 | tlab = self._title[ii]
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| 361 | else:
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| [554] | 362 | tlab = self._ldict.get(self._panelling)+' '+str(i)
|
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| [605] | 363 | if self._lmap and len(self._lmap) > 0:
|
|---|
| 364 | llab = self._lmap[jj]
|
|---|
| 365 | else:
|
|---|
| 366 | llab = scan._getsourcename(rowsel)
|
|---|
| [203] | 367 | else:
|
|---|
| [226] | 368 | if self._title and len(self._title) > 0:
|
|---|
| [525] | 369 | tlab = self._title[ii]
|
|---|
| [226] | 370 | else:
|
|---|
| [601] | 371 | if self._panelling == 'p':
|
|---|
| 372 | tlab = self._get_pollabel(scan, polmode)
|
|---|
| 373 | else:
|
|---|
| 374 | tlab = self._ldict.get(self._panelling)+' '+str(i)
|
|---|
| [226] | 375 | if self._lmap and len(self._lmap) > 0:
|
|---|
| [525] | 376 | llab = self._lmap[jj]
|
|---|
| [203] | 377 | else:
|
|---|
| [525] | 378 | if colmode == 'p':
|
|---|
| [601] | 379 | llab = self._get_pollabel(scan, polmode)
|
|---|
| [525] | 380 | else:
|
|---|
| 381 | llab = self._ldict.get(colmode)+' '+str(j)
|
|---|
| [203] | 382 | self._plotter.set_line(label=llab)
|
|---|
| 383 | self._plotter.plot(x,y,m)
|
|---|
| 384 | xlim=[min(x),max(x)]
|
|---|
| 385 | self._plotter.axes.set_xlim(xlim)
|
|---|
| 386 |
|
|---|
| 387 | self._plotter.set_axes('xlabel',xlab)
|
|---|
| 388 | self._plotter.set_axes('ylabel',ylab)
|
|---|
| 389 | self._plotter.set_axes('title',tlab)
|
|---|
| 390 |
|
|---|
| 391 | return
|
|---|
| 392 |
|
|---|
| 393 |
|
|---|
| [226] | 394 | def set_mode(self, stacking=None, panelling=None):
|
|---|
| [203] | 395 | """
|
|---|
| [377] | 396 | Set the plots look and feel, i.e. what you want to see on the plot.
|
|---|
| [203] | 397 | Parameters:
|
|---|
| 398 | stacking: tell the plotter which variable to plot
|
|---|
| 399 | as line colour overlays (default 'pol')
|
|---|
| 400 | panelling: tell the plotter which variable to plot
|
|---|
| 401 | across multiple panels (default 'scan'
|
|---|
| 402 | Note:
|
|---|
| 403 | Valid modes are:
|
|---|
| 404 | 'beam' 'Beam' 'b': Beams
|
|---|
| 405 | 'if' 'IF' 'i': IFs
|
|---|
| 406 | 'pol' 'Pol' 'p': Polarisations
|
|---|
| 407 | 'scan' 'Scan' 's': Scans
|
|---|
| 408 | 'time' 'Time' 't': Times
|
|---|
| 409 | """
|
|---|
| [554] | 410 | if not self.set_panelling(panelling):
|
|---|
| [203] | 411 | print "Invalid mode"
|
|---|
| [226] | 412 | return
|
|---|
| [203] | 413 | if not self.set_stacking(stacking):
|
|---|
| 414 | print "Invalid mode"
|
|---|
| [226] | 415 | return
|
|---|
| 416 | if self._data: self.plot()
|
|---|
| [203] | 417 | return
|
|---|
| 418 |
|
|---|
| [554] | 419 | def set_panelling(self, what=None):
|
|---|
| 420 | mode = what
|
|---|
| 421 | if mode is None:
|
|---|
| 422 | mode = rcParams['plotter.panelling']
|
|---|
| 423 | md = self._translate(mode)
|
|---|
| [203] | 424 | if md:
|
|---|
| [554] | 425 | self._panelling = md
|
|---|
| [226] | 426 | self._title = None
|
|---|
| [203] | 427 | return True
|
|---|
| 428 | return False
|
|---|
| 429 |
|
|---|
| [377] | 430 | def set_layout(self,rows=None,cols=None):
|
|---|
| 431 | """
|
|---|
| 432 | Set the multi-panel layout, i.e. how many rows and columns plots
|
|---|
| 433 | are visible.
|
|---|
| 434 | Parameters:
|
|---|
| 435 | rows: The number of rows of plots
|
|---|
| 436 | cols: The number of columns of plots
|
|---|
| 437 | Note:
|
|---|
| 438 | If no argument is given, the potter reverts to its auto-plot
|
|---|
| 439 | behaviour.
|
|---|
| 440 | """
|
|---|
| 441 | self._rows = rows
|
|---|
| 442 | self._cols = cols
|
|---|
| 443 | if self._data: self.plot()
|
|---|
| 444 | return
|
|---|
| 445 |
|
|---|
| [226] | 446 | def set_stacking(self, what=None):
|
|---|
| [554] | 447 | mode = what
|
|---|
| 448 | if mode is None:
|
|---|
| 449 | mode = rcParams['plotter.stacking']
|
|---|
| 450 | md = self._translate(mode)
|
|---|
| [203] | 451 | if md:
|
|---|
| 452 | self._stacking = md
|
|---|
| [226] | 453 | self._lmap = None
|
|---|
| [203] | 454 | return True
|
|---|
| 455 | return False
|
|---|
| 456 |
|
|---|
| [525] | 457 | def set_range(self,xstart=None,xend=None,ystart=None,yend=None):
|
|---|
| [203] | 458 | """
|
|---|
| 459 | Set the range of interest on the abcissa of the plot
|
|---|
| 460 | Parameters:
|
|---|
| [525] | 461 | [x,y]start,[x,y]end: The start and end points of the 'zoom' window
|
|---|
| [203] | 462 | Note:
|
|---|
| 463 | These become non-sensical when the unit changes.
|
|---|
| 464 | use plotter.set_range() without parameters to reset
|
|---|
| 465 |
|
|---|
| 466 | """
|
|---|
| [525] | 467 | if xstart is None and xend is None:
|
|---|
| 468 | self._minmaxx = None
|
|---|
| [597] | 469 | else:
|
|---|
| 470 | self._minmaxx = [xstart,xend]
|
|---|
| [525] | 471 | if ystart is None and yend is None:
|
|---|
| 472 | self._minmaxy = None
|
|---|
| [597] | 473 | else:
|
|---|
| 474 | self._minmaxy = [ystart,yend]
|
|---|
| [525] | 475 | if self._data: self.plot()
|
|---|
| [203] | 476 | return
|
|---|
| 477 |
|
|---|
| [257] | 478 | def set_legend(self, mp=None):
|
|---|
| [203] | 479 | """
|
|---|
| 480 | Specify a mapping for the legend instead of using the default
|
|---|
| 481 | indices:
|
|---|
| 482 | Parameters:
|
|---|
| 483 | mp: a list of 'strings'. This should have the same length
|
|---|
| 484 | as the number of elements on the legend and then maps
|
|---|
| 485 | to the indeces in order
|
|---|
| 486 |
|
|---|
| 487 | Example:
|
|---|
| [485] | 488 | If the data has two IFs/rest frequencies with index 0 and 1
|
|---|
| [203] | 489 | for CO and SiO:
|
|---|
| 490 | plotter.set_stacking('i')
|
|---|
| 491 | plotter.set_legend_map(['CO','SiO'])
|
|---|
| 492 | plotter.plot()
|
|---|
| 493 | """
|
|---|
| 494 | self._lmap = mp
|
|---|
| [226] | 495 | if self._data: self.plot()
|
|---|
| 496 | return
|
|---|
| 497 |
|
|---|
| 498 | def set_title(self, title=None):
|
|---|
| 499 | self._title = title
|
|---|
| 500 | if self._data: self.plot()
|
|---|
| 501 | return
|
|---|
| 502 |
|
|---|
| [257] | 503 | def set_ordinate(self, ordinate=None):
|
|---|
| 504 | self._ordinate = ordinate
|
|---|
| 505 | if self._data: self.plot()
|
|---|
| 506 | return
|
|---|
| 507 |
|
|---|
| 508 | def set_abcissa(self, abcissa=None):
|
|---|
| 509 | self._abcissa = abcissa
|
|---|
| 510 | if self._data: self.plot()
|
|---|
| 511 | return
|
|---|
| 512 |
|
|---|
| [377] | 513 | def save(self, filename=None):
|
|---|
| 514 | """
|
|---|
| 515 | Save the plot to a file. The know formats are 'png', 'ps', 'eps'.
|
|---|
| 516 | Parameters:
|
|---|
| 517 | filename: The name of the output file. This is optional
|
|---|
| 518 | and autodetects the image format from the file
|
|---|
| 519 | suffix. If non filename is specified a file
|
|---|
| 520 | called 'yyyymmdd_hhmmss.png' is created in the
|
|---|
| 521 | current directory.
|
|---|
| 522 | """
|
|---|
| 523 | self._plotter.save(filename)
|
|---|
| 524 | return
|
|---|
| [525] | 525 |
|
|---|
| [541] | 526 | def set_cursor(self, row=None,beam=None,IF=None,pol=None, refresh=True):
|
|---|
| [525] | 527 | """
|
|---|
| 528 | Specify a 'cursor' for plotting selected spectra. Time (rows),
|
|---|
| 529 | Beam, IF, Polarisation ranges can be specified.
|
|---|
| 530 | Parameters:
|
|---|
| 531 | Default for all paramaters is to select all available
|
|---|
| 532 | row: selects the rows (time stamps) to be plotted, this has
|
|---|
| 533 | to be a vector of row indices, e.g. row=[0,2,5] or row=[2]
|
|---|
| 534 | beam: select a range of beams
|
|---|
| 535 | IF: select a range of IFs
|
|---|
| 536 | pol: select Polarisations for plotting these can be by index
|
|---|
| 537 | (raw polarisations (default)) or by names any of:
|
|---|
| 538 | ["I", "Q", "U", "V"] or
|
|---|
| 539 | ["I", "Plinear", "Pangle", "V"] or
|
|---|
| [541] | 540 | ["XX", "YY", "Real(XY)", "Imag(XY)"] or
|
|---|
| 541 | ["RR", "LL"]
|
|---|
| [525] | 542 | Example:
|
|---|
| 543 | plotter.set_mode('pol','time')
|
|---|
| 544 | plotter.plot(myscan) # plots all raw polarisations colour stacked
|
|---|
| 545 | plotter.set_cursor(pol=["I"]) # plot "I" only for all rows
|
|---|
| 546 | # plot "I" only for two time stamps row=0 and row=2
|
|---|
| 547 | plotter.set_cursor(row=[0,2],pol=["I"])
|
|---|
| [257] | 548 |
|
|---|
| [525] | 549 | Note:
|
|---|
| 550 | Be careful to select only exisiting polarisations.
|
|---|
| 551 | """
|
|---|
| 552 | if not self._data:
|
|---|
| 553 | print "Can only set cursor after a first call to plot()"
|
|---|
| 554 | return
|
|---|
| 555 |
|
|---|
| 556 | n = self._data[0].nrow()
|
|---|
| 557 | if row is None:
|
|---|
| 558 | self._cursor["t"] = range(n)
|
|---|
| 559 | else:
|
|---|
| 560 | for i in row:
|
|---|
| [554] | 561 | if i < 0 or i >= n:
|
|---|
| [525] | 562 | print "Row index '%d' out of range" % i
|
|---|
| 563 | return
|
|---|
| 564 | self._cursor["t"] = row
|
|---|
| 565 |
|
|---|
| 566 | n = self._data[0].nbeam()
|
|---|
| 567 | if beam is None:
|
|---|
| 568 | self._cursor["b"] = range(n)
|
|---|
| 569 | else:
|
|---|
| 570 | for i in beam:
|
|---|
| [554] | 571 | if i < 0 or i >= n:
|
|---|
| [525] | 572 | print "Beam index '%d' out of range" % i
|
|---|
| 573 | return
|
|---|
| 574 | self._cursor["b"] = beam
|
|---|
| 575 |
|
|---|
| 576 | n = self._data[0].nif()
|
|---|
| 577 | if IF is None:
|
|---|
| 578 | self._cursor["i"] = range(n)
|
|---|
| 579 | else:
|
|---|
| 580 | for i in IF:
|
|---|
| [554] | 581 | if i < 0 or i >= n:
|
|---|
| [525] | 582 | print "IF index '%d' out of range" %i
|
|---|
| 583 | return
|
|---|
| 584 | self._cursor["i"] = IF
|
|---|
| 585 |
|
|---|
| 586 | n = self._data[0].npol()
|
|---|
| 587 | dstokes = {"I":0,"Q":1,"U":2,"V":3}
|
|---|
| 588 | dstokes2 = {"I":0,"Plinear":1,"Pangle":2,"V":3}
|
|---|
| 589 | draw = {"XX":0, "YY":1,"Real(XY)":2, "Imag(XY)":3}
|
|---|
| [541] | 590 | dcirc = { "RR":0,"LL":1}#,"Real(RL)":2,"Image(RL)":3}
|
|---|
| [525] | 591 |
|
|---|
| 592 | if pol is None:
|
|---|
| 593 | self._cursor["p"] = range(n)
|
|---|
| 594 | self._polmode = ["raw" for i in range(n)]
|
|---|
| 595 | else:
|
|---|
| 596 | if isinstance(pol,str):
|
|---|
| 597 | pol = pol.split()
|
|---|
| 598 | polmode = []
|
|---|
| 599 | pols = []
|
|---|
| 600 | for i in pol:
|
|---|
| 601 | if isinstance(i,str):
|
|---|
| 602 | if draw.has_key(i):
|
|---|
| 603 | pols.append(draw.get(i))
|
|---|
| 604 | polmode.append("raw")
|
|---|
| 605 | elif dstokes.has_key(i):
|
|---|
| 606 | pols.append(dstokes.get(i))
|
|---|
| 607 | polmode.append("stokes")
|
|---|
| 608 | elif dstokes2.has_key(i):
|
|---|
| 609 | pols.append(dstokes2.get(i))
|
|---|
| 610 | polmode.append("stokes2")
|
|---|
| 611 | elif dcirc.has_key(i):
|
|---|
| 612 | pols.append(dcirc.get(i))
|
|---|
| [541] | 613 | polmode.append("circular")
|
|---|
| [525] | 614 | else:
|
|---|
| 615 | "Pol type '%s' not valid" %i
|
|---|
| 616 | return
|
|---|
| 617 | elif 0 > i >= n:
|
|---|
| 618 | print "Pol index '%d' out of range" %i
|
|---|
| 619 | return
|
|---|
| 620 | else:
|
|---|
| 621 | pols.append(i)
|
|---|
| 622 | polmode.append("raw")
|
|---|
| 623 | self._cursor["p"] = pols
|
|---|
| 624 | self._polmode = polmode
|
|---|
| [541] | 625 | if self._data and refresh: self.plot()
|
|---|
| [525] | 626 |
|
|---|
| [601] | 627 | def _get_pollabel(self, scan, polmode):
|
|---|
| 628 | tlab = ""
|
|---|
| 629 | if polmode == "stokes":
|
|---|
| 630 | tlab = scan._getpolarizationlabel(0,1,0)
|
|---|
| 631 | elif polmode == "stokes2":
|
|---|
| 632 | tlab = scan._getpolarizationlabel(0,1,1)
|
|---|
| 633 | elif polmode == "circular":
|
|---|
| 634 | tlab = scan._getpolarizationlabel(0,0,0)
|
|---|
| 635 | else:
|
|---|
| 636 | tlab = scan._getpolarizationlabel(1,0,0)
|
|---|
| 637 | return tlab
|
|---|
| [525] | 638 |
|
|---|
| [203] | 639 | if __name__ == '__main__':
|
|---|
| 640 | plotter = asapplotter()
|
|---|
