| [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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| [607] | 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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| [672] | 47 | self._abcunit = None
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| [525] | 48 | self._cursor = {'t':None, 'b':None,
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| 49 | 'i':None, 'p':None
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| 50 | }
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| [203] | 51 |
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| 52 | def _translate(self, name):
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| 53 | for d in self._dicts:
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| 54 | if d.has_key(name):
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| 55 | return d[name]
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| 56 | return None
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| 57 |
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| [525] | 58 | def plot(self, *args):
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| [203] | 59 | """
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| 60 | Plot a (list of) scantables.
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| 61 | Parameters:
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| 62 | one or more comma separated scantables
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| 63 | Note:
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| 64 | If a (list) of scantables was specified in a previous call
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| 65 | to plot, no argument has to be given to 'replot'
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| [525] | 66 | NO checking is done that the abcissas of the scantables
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| [203] | 67 | are consistent e.g. all 'channel' or all 'velocity' etc.
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| 68 | """
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| 69 | if self._plotter.is_dead:
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| 70 | self._plotter = ASAPlot()
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| [600] | 71 | self._plotter.hold()
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| [203] | 72 | self._plotter.clear()
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| 73 | if len(args) > 0:
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| [525] | 74 | if self._data is not None:
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| 75 | if list(args) != self._data:
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| 76 | self._data = list(args)
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| 77 | # reset cursor
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| [541] | 78 | self.set_cursor(refresh=False)
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| [525] | 79 | else:
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| 80 | self._data = list(args)
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| [541] | 81 | self.set_cursor(refresh=False)
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| [672] | 82 | # ranges become invalid when unit changes
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| 83 | if self._abcunit != self._data[0].get_unit():
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| 84 | self._minmaxx = None
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| 85 | self._minmaxy = None
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| 86 | self._abcunit = self._data[0].get_unit()
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| [554] | 87 | if self._panelling == 't':
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| [626] | 88 | maxrows = 25
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| [541] | 89 | if self._data[0].nrow() > maxrows:
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| [603] | 90 | if self._cursor["t"] is None or \
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| 91 | (isinstance(self._cursor["t"],list) and \
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| 92 | len(self._cursor["t"]) > maxrows ):
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| 93 | print "Scan to be plotted contains more than %d rows.\n" \
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| 94 | "Selecting first %d rows..." % (maxrows,maxrows)
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| 95 | self._cursor["t"] = range(maxrows)
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| [203] | 96 | self._plot_time(self._data[0], self._stacking)
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| [554] | 97 | elif self._panelling == 's':
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| [203] | 98 | self._plot_scans(self._data, self._stacking)
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| 99 | else:
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| 100 | self._plot_other(self._data, self._stacking)
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| [672] | 101 | if self._minmaxy is not None:
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| 102 | self._plotter.set_limits(ylim=self._minmaxy)
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| [203] | 103 | self._plotter.release()
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| 104 | return
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| 105 |
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| 106 | def _plot_time(self, scan, colmode):
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| 107 | if colmode == 't':
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| 108 | return
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| [525] | 109 | n = len(self._cursor["t"])
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| [203] | 110 | cdict = {'b':'scan.setbeam(j)',
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| 111 | 'i':'scan.setif(j)',
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| 112 | 'p':'scan.setpol(j)'}
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| [525] | 113 | cdict2 = {'b':'self._cursor["b"]',
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| 114 | 'i':'self._cursor["i"]',
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| 115 | 'p':'self._cursor["p"]'}
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| 116 | ncol = 1
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| [203] | 117 | if self._stacking is not None:
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| 118 | ncol = eval(self._cdict.get(colmode))
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| 119 | if n > 1:
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| [377] | 120 | if self._rows and self._cols:
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| 121 | n = min(n,self._rows*self._cols)
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| 122 | self._plotter.set_panels(rows=self._rows,cols=self._cols,
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| 123 | nplots=n)
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| 124 | else:
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| [485] | 125 | self._plotter.set_panels(rows=n,cols=0,nplots=n)
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| [600] | 126 | else:
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| 127 | self._plotter.set_panels()
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| [525] | 128 | rows = self._cursor["t"]
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| [652] | 129 | self._plotter.palette(0)
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| [525] | 130 | for rowsel in rows:
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| 131 | i = self._cursor["t"].index(rowsel)
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| [203] | 132 | if n > 1:
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| [652] | 133 | self._plotter.palette(0)
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| [203] | 134 | self._plotter.subplot(i)
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| [525] | 135 | colvals = eval(cdict2.get(colmode))
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| 136 | for j in colvals:
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| 137 | polmode = "raw"
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| 138 | jj = colvals.index(j)
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| 139 | savej = j
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| 140 | for k in cdict.keys():
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| 141 | sel = eval(cdict2.get(k))
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| 142 | j = sel[0]
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| 143 | if k == "p":
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| 144 | which = self._cursor["p"].index(j)
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| 145 | polmode = self._polmode[which]
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| 146 | j = which
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| 147 | eval(cdict.get(k))
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| 148 | j = savej
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| 149 | if colmode == "p":
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| 150 | polmode = self._polmode[self._cursor["p"].index(j)]
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| [672] | 151 | #j = jj
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| [203] | 152 | eval(cdict.get(colmode))
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| 153 | x = None
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| 154 | y = None
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| 155 | m = None
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| [626] | 156 | if self._title is None:
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| [525] | 157 | tlab = scan._getsourcename(rowsel)
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| [226] | 158 | else:
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| [626] | 159 | if len(self._title) >= n:
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| [525] | 160 | tlab = self._title[rowsel]
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| [226] | 161 | else:
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| [525] | 162 | tlab = scan._getsourcename(rowsel)
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| 163 | x,xlab = scan.get_abcissa(rowsel)
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| [257] | 164 | if self._abcissa: xlab = self._abcissa
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| [525] | 165 | y = None
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| 166 | if polmode == "stokes":
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| 167 | y = scan._getstokesspectrum(rowsel)
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| 168 | elif polmode == "stokes2":
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| 169 | y = scan._getstokesspectrum(rowsel,True)
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| [541] | 170 | elif polmode == "circular":
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| 171 | y = scan._stokestopolspectrum(rowsel,False,-1)
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| [525] | 172 | else:
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| 173 | y = scan._getspectrum(rowsel)
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| [257] | 174 | if self._ordinate:
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| 175 | ylab = self._ordinate
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| 176 | else:
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| [626] | 177 | ylab = scan._get_ordinate_label()
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| [525] | 178 | m = scan._getmask(rowsel)
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| [226] | 179 | if self._lmap and len(self._lmap) > 0:
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| [525] | 180 | llab = self._lmap[jj]
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| [203] | 181 | else:
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| [525] | 182 | if colmode == 'p':
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| [603] | 183 | llab = self._get_pollabel(scan, polmode)
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| [525] | 184 | else:
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| 185 | llab = self._ldict.get(colmode)+' '+str(j)
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| [203] | 186 | self._plotter.set_line(label=llab)
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| [672] | 187 | if self._minmaxx is not None:
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| 188 | s,e = self._slice_indeces(x)
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| 189 | x = x[s:e]
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| 190 | y = y[s:e]
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| 191 | m = m[s:e]
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| [203] | 192 | self._plotter.plot(x,y,m)
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| [672] | 193 |
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| [203] | 194 | xlim=[min(x),max(x)]
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| [693] | 195 | if self._minmaxx is not None:
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| 196 | xlim = self._minmaxx
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| [203] | 197 | self._plotter.axes.set_xlim(xlim)
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| 198 | self._plotter.set_axes('xlabel',xlab)
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| 199 | self._plotter.set_axes('ylabel',ylab)
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| 200 | self._plotter.set_axes('title',tlab)
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| 201 | return
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| 202 |
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| [525] | 203 | def _plot_scans(self, scans, colmode):
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| [693] | 204 | print "Plotting mode is scans across panels. Can only plot one row per scan."
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| [203] | 205 | if colmode == 's':
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| 206 | return
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| 207 | cdict = {'b':'scan.setbeam(j)',
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| 208 | 'i':'scan.setif(j)',
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| 209 | 'p':'scan.setpol(j)'}
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| [525] | 210 | cdict2 = {'b':'self._cursor["b"]',
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| 211 | 'i':'self._cursor["i"]',
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| 212 | 'p':'self._cursor["p"]'}
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| 213 |
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| [203] | 214 | n = len(scans)
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| [525] | 215 | ncol = 1
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| [203] | 216 | if self._stacking is not None:
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| 217 | scan = scans[0]
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| 218 | ncol = eval(self._cdict.get(colmode))
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| 219 | if n > 1:
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| [377] | 220 | if self._rows and self._cols:
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| 221 | n = min(n,self._rows*self._cols)
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| [626] | 222 | self._plotter.set_panels(rows=self._rows,cols=self._cols,
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| [377] | 223 | nplots=n)
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| 224 | else:
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| [626] | 225 | self._plotter.set_panels(rows=n,cols=0,nplots=n)
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| [600] | 226 | else:
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| 227 | self._plotter.set_panels()
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| [626] | 228 |
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| [203] | 229 | for scan in scans:
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| [652] | 230 | self._plotter.palette(0)
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| [203] | 231 | if n > 1:
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| [525] | 232 | self._plotter.subplot(scans.index(scan))
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| 233 | colvals = eval(cdict2.get(colmode))
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| 234 | rowsel = self._cursor["t"][0]
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| 235 | for j in colvals:
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| 236 | polmode = "raw"
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| 237 | jj = colvals.index(j)
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| 238 | savej = j
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| 239 | for k in cdict.keys():
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| 240 | sel = eval(cdict2.get(k))
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| 241 | j = sel[0]
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| 242 | eval(cdict.get(k))
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| 243 | if k == "p":
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| 244 | which = self._cursor["p"].index(j)
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| 245 | polmode = self._polmode[which]
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| 246 | j = which
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| 247 | j = savej
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| 248 | if colmode == "p":
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| 249 | polmode = self._polmode[self._cursor["p"].index(j)]
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| [672] | 250 | #j = jj
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| [203] | 251 | eval(cdict.get(colmode))
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| 252 | x = None
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| 253 | y = None
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| 254 | m = None
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| [226] | 255 | tlab = self._title
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| 256 | if not self._title:
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| [525] | 257 | tlab = scan._getsourcename(rowsel)
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| 258 | x,xlab = scan.get_abcissa(rowsel)
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| [257] | 259 | if self._abcissa: xlab = self._abcissa
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| [525] | 260 | if polmode == "stokes":
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| 261 | y = scan._getstokesspectrum(rowsel)
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| 262 | elif polmode == "stokes2":
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| 263 | y = scan._getstokesspectrum(rowsel,True)
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| [541] | 264 | elif polmode == "circular":
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| 265 | y = scan._stokestopolspectrum(rowsel,False,-1)
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| [525] | 266 | else:
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| 267 | y = scan._getspectrum(rowsel)
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| [257] | 268 | if self._ordinate:
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| 269 | ylab = self._ordinate
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| 270 | else:
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| [626] | 271 | ylab = scan._get_ordinate_label()
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| [525] | 272 | m = scan._getmask(rowsel)
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| [257] | 273 | if self._lmap and len(self._lmap) > 0:
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| [525] | 274 | llab = self._lmap[jj]
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| [203] | 275 | else:
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| [525] | 276 | if colmode == 'p':
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| [603] | 277 | llab = self._get_pollabel(scan, polmode)
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| [525] | 278 | else:
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| 279 | llab = self._ldict.get(colmode)+' '+str(j)
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| [203] | 280 | self._plotter.set_line(label=llab)
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| [672] | 281 | if self._minmaxx is not None:
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| 282 | s,e = self._slice_indeces(x)
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| 283 | x = x[s:e]
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| 284 | y = y[s:e]
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| 285 | m = m[s:e]
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| 286 |
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| [203] | 287 | self._plotter.plot(x,y,m)
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| 288 | xlim=[min(x),max(x)]
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| [693] | 289 | if self._minmaxx is not None:
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| 290 | xlim = self._minmaxx
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| [203] | 291 | self._plotter.axes.set_xlim(xlim)
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| 292 |
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| 293 | self._plotter.set_axes('xlabel',xlab)
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| 294 | self._plotter.set_axes('ylabel',ylab)
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| 295 | self._plotter.set_axes('title',tlab)
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| 296 | return
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| 297 |
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| 298 | def _plot_other(self,scans,colmode):
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| [554] | 299 | if colmode == self._panelling:
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| [203] | 300 | return
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| [525] | 301 | cdict = {'b':'scan.setbeam(i)',
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| 302 | 'i':'scan.setif(i)',
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| 303 | 'p':'scan.setpol(i)'}
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| 304 | cdict2 = {'b':'self._cursor["b"]',
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| 305 | 'i':'self._cursor["i"]',
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| 306 | 'p':'self._cursor["p"]',
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| 307 | 's': 'scans',
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| 308 | 't': 'self._cursor["t"]'}
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| [203] | 309 | scan = scans[0]
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| [554] | 310 | n = eval(self._cdict.get(self._panelling))
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| [525] | 311 | ncol=1
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| [203] | 312 | if self._stacking is not None:
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| 313 | ncol = eval(self._cdict.get(colmode))
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| 314 | if n > 1:
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| [377] | 315 | if self._rows and self._cols:
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| 316 | n = min(n,self._rows*self._cols)
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| 317 | self._plotter.set_panels(rows=self._rows,cols=self._cols,
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| 318 | nplots=n)
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| 319 | else:
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| [485] | 320 | self._plotter.set_panels(rows=n,cols=0,nplots=n)
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| [600] | 321 | else:
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| 322 | self._plotter.set_panels()
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| [554] | 323 | panels = self._cursor[self._panelling]
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| [525] | 324 | for i in panels:
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| [652] | 325 | self._plotter.palette(0)
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| [525] | 326 | polmode = "raw"
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| [554] | 327 | ii = self._cursor[self._panelling].index(i)
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| [203] | 328 | if n>1:
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| [525] | 329 | self._plotter.subplot(ii)
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| [554] | 330 | if self._panelling == "p":
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| [525] | 331 | polmode = self._polmode[ii]
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| [554] | 332 | eval(cdict.get(self._panelling))
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| [525] | 333 | else:
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| [554] | 334 | eval(cdict.get(self._panelling))
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| [525] | 335 | colvals = eval(cdict2.get(colmode))
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| 336 | for j in colvals:
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| 337 | rowsel = self._cursor["t"][0]
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| 338 | jj = colvals.index(j)
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| 339 | savei = i
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| 340 | for k in cdict.keys():
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| [554] | 341 | if k != self._panelling:
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| [525] | 342 | sel = eval(cdict2.get(k))
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| 343 | i = sel[0]
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| 344 | if k == "p":
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| [557] | 345 | which = self._cursor["p"].index(i)
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| [525] | 346 | polmode = self._polmode[which]
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| 347 | i = which
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| 348 | eval(cdict.get(k))
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| 349 | i = savei
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| [203] | 350 | if colmode == 's':
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| [525] | 351 | scan = j
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| [203] | 352 | elif colmode == 't':
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| [525] | 353 | rowsel = j
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| [203] | 354 | else:
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| [525] | 355 | savei = i
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| 356 | if colmode == 'p':
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| 357 | polmode = self._polmode[self._cursor["p"].index(j)]
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| 358 | i = j
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| [203] | 359 | eval(cdict.get(colmode))
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| [525] | 360 | i = savei
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| [203] | 361 | x = None
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| 362 | y = None
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| 363 | m = None
|
|---|
| [525] | 364 | x,xlab = scan.get_abcissa(rowsel)
|
|---|
| [257] | 365 | if self._abcissa: xlab = self._abcissa
|
|---|
| [525] | 366 | if polmode == "stokes":
|
|---|
| 367 | y = scan._getstokesspectrum(rowsel)
|
|---|
| 368 | elif polmode == "stokes2":
|
|---|
| 369 | y = scan._getstokesspectrum(rowsel,True)
|
|---|
| [541] | 370 | elif polmode == "circular":
|
|---|
| 371 | y = scan._stokestopolspectrum(rowsel,False,-1)
|
|---|
| [525] | 372 | else:
|
|---|
| 373 | y = scan._getspectrum(rowsel)
|
|---|
| 374 |
|
|---|
| [257] | 375 | if self._ordinate:
|
|---|
| 376 | ylab = self._ordinate
|
|---|
| 377 | else:
|
|---|
| [626] | 378 | ylab = scan._get_ordinate_label()
|
|---|
| [525] | 379 | m = scan._getmask(rowsel)
|
|---|
| [203] | 380 | if colmode == 's' or colmode == 't':
|
|---|
| [525] | 381 | if self._title and len(self._title) > 0:
|
|---|
| 382 | tlab = self._title[ii]
|
|---|
| [652] | 383 | else:
|
|---|
| 384 | if self._panelling == 'p':
|
|---|
| 385 | tlab = self._get_pollabel(scan, polmode)
|
|---|
| 386 | else:
|
|---|
| 387 | tlab = self._ldict.get(self._panelling)+' '+str(i)
|
|---|
| [607] | 388 | if self._lmap and len(self._lmap) > 0:
|
|---|
| 389 | llab = self._lmap[jj]
|
|---|
| 390 | else:
|
|---|
| 391 | llab = scan._getsourcename(rowsel)
|
|---|
| [203] | 392 | else:
|
|---|
| [226] | 393 | if self._title and len(self._title) > 0:
|
|---|
| [525] | 394 | tlab = self._title[ii]
|
|---|
| [226] | 395 | else:
|
|---|
| [603] | 396 | if self._panelling == 'p':
|
|---|
| 397 | tlab = self._get_pollabel(scan, polmode)
|
|---|
| 398 | else:
|
|---|
| 399 | tlab = self._ldict.get(self._panelling)+' '+str(i)
|
|---|
| [226] | 400 | if self._lmap and len(self._lmap) > 0:
|
|---|
| [525] | 401 | llab = self._lmap[jj]
|
|---|
| [203] | 402 | else:
|
|---|
| [525] | 403 | if colmode == 'p':
|
|---|
| [603] | 404 | llab = self._get_pollabel(scan, polmode)
|
|---|
| [525] | 405 | else:
|
|---|
| 406 | llab = self._ldict.get(colmode)+' '+str(j)
|
|---|
| [203] | 407 | self._plotter.set_line(label=llab)
|
|---|
| [672] | 408 | if self._minmaxx is not None:
|
|---|
| 409 | s,e = self._slice_indeces(x)
|
|---|
| 410 | x = x[s:e]
|
|---|
| 411 | y = y[s:e]
|
|---|
| 412 | m = m[s:e]
|
|---|
| 413 |
|
|---|
| [203] | 414 | self._plotter.plot(x,y,m)
|
|---|
| 415 | xlim=[min(x),max(x)]
|
|---|
| [693] | 416 | if self._minmaxx is not None:
|
|---|
| 417 | xlim = self._minmaxx
|
|---|
| [203] | 418 | self._plotter.axes.set_xlim(xlim)
|
|---|
| 419 |
|
|---|
| 420 | self._plotter.set_axes('xlabel',xlab)
|
|---|
| 421 | self._plotter.set_axes('ylabel',ylab)
|
|---|
| 422 | self._plotter.set_axes('title',tlab)
|
|---|
| 423 |
|
|---|
| 424 | return
|
|---|
| 425 |
|
|---|
| 426 |
|
|---|
| [226] | 427 | def set_mode(self, stacking=None, panelling=None):
|
|---|
| [203] | 428 | """
|
|---|
| [377] | 429 | Set the plots look and feel, i.e. what you want to see on the plot.
|
|---|
| [203] | 430 | Parameters:
|
|---|
| 431 | stacking: tell the plotter which variable to plot
|
|---|
| [693] | 432 | as line color overlays (default 'pol')
|
|---|
| [203] | 433 | panelling: tell the plotter which variable to plot
|
|---|
| 434 | across multiple panels (default 'scan'
|
|---|
| 435 | Note:
|
|---|
| 436 | Valid modes are:
|
|---|
| 437 | 'beam' 'Beam' 'b': Beams
|
|---|
| 438 | 'if' 'IF' 'i': IFs
|
|---|
| 439 | 'pol' 'Pol' 'p': Polarisations
|
|---|
| 440 | 'scan' 'Scan' 's': Scans
|
|---|
| 441 | 'time' 'Time' 't': Times
|
|---|
| 442 | """
|
|---|
| [554] | 443 | if not self.set_panelling(panelling):
|
|---|
| [203] | 444 | print "Invalid mode"
|
|---|
| [226] | 445 | return
|
|---|
| [203] | 446 | if not self.set_stacking(stacking):
|
|---|
| 447 | print "Invalid mode"
|
|---|
| [226] | 448 | return
|
|---|
| 449 | if self._data: self.plot()
|
|---|
| [203] | 450 | return
|
|---|
| 451 |
|
|---|
| [554] | 452 | def set_panelling(self, what=None):
|
|---|
| 453 | mode = what
|
|---|
| 454 | if mode is None:
|
|---|
| 455 | mode = rcParams['plotter.panelling']
|
|---|
| 456 | md = self._translate(mode)
|
|---|
| [203] | 457 | if md:
|
|---|
| [554] | 458 | self._panelling = md
|
|---|
| [226] | 459 | self._title = None
|
|---|
| [203] | 460 | return True
|
|---|
| 461 | return False
|
|---|
| 462 |
|
|---|
| [377] | 463 | def set_layout(self,rows=None,cols=None):
|
|---|
| 464 | """
|
|---|
| 465 | Set the multi-panel layout, i.e. how many rows and columns plots
|
|---|
| 466 | are visible.
|
|---|
| 467 | Parameters:
|
|---|
| 468 | rows: The number of rows of plots
|
|---|
| 469 | cols: The number of columns of plots
|
|---|
| 470 | Note:
|
|---|
| 471 | If no argument is given, the potter reverts to its auto-plot
|
|---|
| 472 | behaviour.
|
|---|
| 473 | """
|
|---|
| 474 | self._rows = rows
|
|---|
| 475 | self._cols = cols
|
|---|
| 476 | if self._data: self.plot()
|
|---|
| 477 | return
|
|---|
| 478 |
|
|---|
| [226] | 479 | def set_stacking(self, what=None):
|
|---|
| [554] | 480 | mode = what
|
|---|
| 481 | if mode is None:
|
|---|
| 482 | mode = rcParams['plotter.stacking']
|
|---|
| 483 | md = self._translate(mode)
|
|---|
| [203] | 484 | if md:
|
|---|
| 485 | self._stacking = md
|
|---|
| [226] | 486 | self._lmap = None
|
|---|
| [203] | 487 | return True
|
|---|
| 488 | return False
|
|---|
| 489 |
|
|---|
| [525] | 490 | def set_range(self,xstart=None,xend=None,ystart=None,yend=None):
|
|---|
| [203] | 491 | """
|
|---|
| 492 | Set the range of interest on the abcissa of the plot
|
|---|
| 493 | Parameters:
|
|---|
| [525] | 494 | [x,y]start,[x,y]end: The start and end points of the 'zoom' window
|
|---|
| [203] | 495 | Note:
|
|---|
| 496 | These become non-sensical when the unit changes.
|
|---|
| 497 | use plotter.set_range() without parameters to reset
|
|---|
| 498 |
|
|---|
| 499 | """
|
|---|
| [525] | 500 | if xstart is None and xend is None:
|
|---|
| 501 | self._minmaxx = None
|
|---|
| [600] | 502 | else:
|
|---|
| 503 | self._minmaxx = [xstart,xend]
|
|---|
| [525] | 504 | if ystart is None and yend is None:
|
|---|
| 505 | self._minmaxy = None
|
|---|
| [600] | 506 | else:
|
|---|
| 507 | self._minmaxy = [ystart,yend]
|
|---|
| [525] | 508 | if self._data: self.plot()
|
|---|
| [203] | 509 | return
|
|---|
| 510 |
|
|---|
| [257] | 511 | def set_legend(self, mp=None):
|
|---|
| [203] | 512 | """
|
|---|
| 513 | Specify a mapping for the legend instead of using the default
|
|---|
| 514 | indices:
|
|---|
| 515 | Parameters:
|
|---|
| 516 | mp: a list of 'strings'. This should have the same length
|
|---|
| 517 | as the number of elements on the legend and then maps
|
|---|
| [693] | 518 | to the indeces in order. It is possible to uses latex
|
|---|
| 519 | math expression. These have to be enclosed in r'', e.g. r'$x^{2}$'
|
|---|
| [203] | 520 |
|
|---|
| 521 | Example:
|
|---|
| [485] | 522 | If the data has two IFs/rest frequencies with index 0 and 1
|
|---|
| [203] | 523 | for CO and SiO:
|
|---|
| 524 | plotter.set_stacking('i')
|
|---|
| [693] | 525 | plotter.set_legend(['CO','SiO'])
|
|---|
| [203] | 526 | plotter.plot()
|
|---|
| [693] | 527 | plotter.set_legend([r'$^{12}CO$', r'SiO'])
|
|---|
| [203] | 528 | """
|
|---|
| 529 | self._lmap = mp
|
|---|
| [226] | 530 | if self._data: self.plot()
|
|---|
| 531 | return
|
|---|
| 532 |
|
|---|
| 533 | def set_title(self, title=None):
|
|---|
| [693] | 534 | """
|
|---|
| 535 | Set the title of the plot. If multiple panels are plotted,
|
|---|
| 536 | multiple titles have to be specified.
|
|---|
| 537 | Example:
|
|---|
| 538 | # two panels are visible on the plotter
|
|---|
| 539 | plotter.set_title(["First Panel","Second Panel"])
|
|---|
| 540 | """
|
|---|
| [226] | 541 | self._title = title
|
|---|
| 542 | if self._data: self.plot()
|
|---|
| 543 | return
|
|---|
| 544 |
|
|---|
| [257] | 545 | def set_ordinate(self, ordinate=None):
|
|---|
| [693] | 546 | """
|
|---|
| 547 | Set the y-axis label of the plot. If multiple panels are plotted,
|
|---|
| 548 | multiple labels have to be specified.
|
|---|
| 549 | Example:
|
|---|
| 550 | # two panels are visible on the plotter
|
|---|
| 551 | plotter.set_ordinate(["First Y-Axis","Second Y-Axis"])
|
|---|
| 552 | """
|
|---|
| [257] | 553 | self._ordinate = ordinate
|
|---|
| 554 | if self._data: self.plot()
|
|---|
| 555 | return
|
|---|
| 556 |
|
|---|
| 557 | def set_abcissa(self, abcissa=None):
|
|---|
| [693] | 558 | """
|
|---|
| 559 | Set the x-axis label of the plot. If multiple panels are plotted,
|
|---|
| 560 | multiple labels have to be specified.
|
|---|
| 561 | Example:
|
|---|
| 562 | # two panels are visible on the plotter
|
|---|
| 563 | plotter.set_ordinate(["First X-Axis","Second X-Axis"])
|
|---|
| 564 | """
|
|---|
| [257] | 565 | self._abcissa = abcissa
|
|---|
| 566 | if self._data: self.plot()
|
|---|
| 567 | return
|
|---|
| 568 |
|
|---|
| [693] | 569 | def set_colors(self, colormap):
|
|---|
| 570 | """
|
|---|
| 571 | Set the colors to be used. The plotter will cycle through
|
|---|
| 572 | these colors when lines are overlaid (stacking mode).
|
|---|
| 573 | Example:
|
|---|
| 574 | plotter.set_colors("red green blue")
|
|---|
| 575 | # If for example four lines are overlaid e.g I Q U V
|
|---|
| 576 | # 'I' will be 'red', 'Q' will be 'green', U will be 'blue'
|
|---|
| 577 | # and 'V' will be 'red' again.
|
|---|
| 578 | """
|
|---|
| 579 | self._plotter.palette(0,colormap=colormap)
|
|---|
| 580 | if self._data: self.plot()
|
|---|
| 581 |
|
|---|
| 582 | def set_linestyles(self, linestyles):
|
|---|
| 583 | """
|
|---|
| 584 | Parameters:
|
|---|
| 585 | linestyles: a list of linestyles to use.
|
|---|
| 586 | 'line', 'dashed', 'dotted', 'dashdot',
|
|---|
| 587 | 'dashdotdot' and 'dashdashdot' are
|
|---|
| 588 | possible
|
|---|
| 589 |
|
|---|
| 590 | Set the linestyles to be used. The plotter will cycle through
|
|---|
| 591 | these linestyles when lines are overlaid (stacking mode) AND
|
|---|
| 592 | only one color has been set.
|
|---|
| 593 | Example:
|
|---|
| 594 | plotter.set_colors("black")
|
|---|
| 595 | plotter.set_linestyles("line dashed dotted dashdot")
|
|---|
| 596 | # If for example four lines are overlaid e.g I Q U V
|
|---|
| 597 | # 'I' will be 'solid', 'Q' will be 'dashed',
|
|---|
| 598 | # U will be 'dotted' and 'V' will be 'dashdot'.
|
|---|
| 599 | """
|
|---|
| 600 | self._plotter.palette(color=0,linestyle=0,linestyles=linestyles)
|
|---|
| 601 | if self._data: self.plot()
|
|---|
| 602 |
|
|---|
| [671] | 603 | def save(self, filename=None, orientation=None):
|
|---|
| [377] | 604 | """
|
|---|
| 605 | Save the plot to a file. The know formats are 'png', 'ps', 'eps'.
|
|---|
| 606 | Parameters:
|
|---|
| 607 | filename: The name of the output file. This is optional
|
|---|
| 608 | and autodetects the image format from the file
|
|---|
| 609 | suffix. If non filename is specified a file
|
|---|
| 610 | called 'yyyymmdd_hhmmss.png' is created in the
|
|---|
| 611 | current directory.
|
|---|
| [671] | 612 | orientation: optional parameter for postscript only (not eps).
|
|---|
| 613 | 'landscape', 'portrait' or None (default) are valid.
|
|---|
| 614 | If None is choosen for 'ps' output, the plot is
|
|---|
| 615 | automatically oriented to fill the page.
|
|---|
| [377] | 616 | """
|
|---|
| [652] | 617 | self._plotter.save(filename,orientation)
|
|---|
| [377] | 618 | return
|
|---|
| [525] | 619 |
|
|---|
| [541] | 620 | def set_cursor(self, row=None,beam=None,IF=None,pol=None, refresh=True):
|
|---|
| [525] | 621 | """
|
|---|
| 622 | Specify a 'cursor' for plotting selected spectra. Time (rows),
|
|---|
| 623 | Beam, IF, Polarisation ranges can be specified.
|
|---|
| 624 | Parameters:
|
|---|
| 625 | Default for all paramaters is to select all available
|
|---|
| 626 | row: selects the rows (time stamps) to be plotted, this has
|
|---|
| 627 | to be a vector of row indices, e.g. row=[0,2,5] or row=[2]
|
|---|
| 628 | beam: select a range of beams
|
|---|
| 629 | IF: select a range of IFs
|
|---|
| 630 | pol: select Polarisations for plotting these can be by index
|
|---|
| 631 | (raw polarisations (default)) or by names any of:
|
|---|
| 632 | ["I", "Q", "U", "V"] or
|
|---|
| 633 | ["I", "Plinear", "Pangle", "V"] or
|
|---|
| [541] | 634 | ["XX", "YY", "Real(XY)", "Imag(XY)"] or
|
|---|
| 635 | ["RR", "LL"]
|
|---|
| [525] | 636 | Example:
|
|---|
| 637 | plotter.set_mode('pol','time')
|
|---|
| 638 | plotter.plot(myscan) # plots all raw polarisations colour stacked
|
|---|
| 639 | plotter.set_cursor(pol=["I"]) # plot "I" only for all rows
|
|---|
| 640 | # plot "I" only for two time stamps row=0 and row=2
|
|---|
| 641 | plotter.set_cursor(row=[0,2],pol=["I"])
|
|---|
| [257] | 642 |
|
|---|
| [525] | 643 | Note:
|
|---|
| 644 | Be careful to select only exisiting polarisations.
|
|---|
| 645 | """
|
|---|
| 646 | if not self._data:
|
|---|
| 647 | print "Can only set cursor after a first call to plot()"
|
|---|
| 648 | return
|
|---|
| 649 |
|
|---|
| 650 | n = self._data[0].nrow()
|
|---|
| 651 | if row is None:
|
|---|
| 652 | self._cursor["t"] = range(n)
|
|---|
| 653 | else:
|
|---|
| 654 | for i in row:
|
|---|
| [554] | 655 | if i < 0 or i >= n:
|
|---|
| [525] | 656 | print "Row index '%d' out of range" % i
|
|---|
| 657 | return
|
|---|
| 658 | self._cursor["t"] = row
|
|---|
| 659 |
|
|---|
| 660 | n = self._data[0].nbeam()
|
|---|
| 661 | if beam is None:
|
|---|
| 662 | self._cursor["b"] = range(n)
|
|---|
| 663 | else:
|
|---|
| 664 | for i in beam:
|
|---|
| [554] | 665 | if i < 0 or i >= n:
|
|---|
| [525] | 666 | print "Beam index '%d' out of range" % i
|
|---|
| 667 | return
|
|---|
| 668 | self._cursor["b"] = beam
|
|---|
| 669 |
|
|---|
| 670 | n = self._data[0].nif()
|
|---|
| 671 | if IF is None:
|
|---|
| 672 | self._cursor["i"] = range(n)
|
|---|
| 673 | else:
|
|---|
| 674 | for i in IF:
|
|---|
| [554] | 675 | if i < 0 or i >= n:
|
|---|
| [525] | 676 | print "IF index '%d' out of range" %i
|
|---|
| 677 | return
|
|---|
| 678 | self._cursor["i"] = IF
|
|---|
| 679 |
|
|---|
| 680 | n = self._data[0].npol()
|
|---|
| 681 | dstokes = {"I":0,"Q":1,"U":2,"V":3}
|
|---|
| 682 | dstokes2 = {"I":0,"Plinear":1,"Pangle":2,"V":3}
|
|---|
| 683 | draw = {"XX":0, "YY":1,"Real(XY)":2, "Imag(XY)":3}
|
|---|
| [693] | 684 | dcirc = { "RR":0,"LL":1}#,"Real(RL)":2,"Imag(RL)":3}
|
|---|
| [525] | 685 |
|
|---|
| 686 | if pol is None:
|
|---|
| 687 | self._cursor["p"] = range(n)
|
|---|
| 688 | self._polmode = ["raw" for i in range(n)]
|
|---|
| 689 | else:
|
|---|
| 690 | if isinstance(pol,str):
|
|---|
| 691 | pol = pol.split()
|
|---|
| 692 | polmode = []
|
|---|
| 693 | pols = []
|
|---|
| 694 | for i in pol:
|
|---|
| 695 | if isinstance(i,str):
|
|---|
| 696 | if draw.has_key(i):
|
|---|
| 697 | pols.append(draw.get(i))
|
|---|
| 698 | polmode.append("raw")
|
|---|
| 699 | elif dstokes.has_key(i):
|
|---|
| 700 | pols.append(dstokes.get(i))
|
|---|
| 701 | polmode.append("stokes")
|
|---|
| 702 | elif dstokes2.has_key(i):
|
|---|
| 703 | pols.append(dstokes2.get(i))
|
|---|
| 704 | polmode.append("stokes2")
|
|---|
| 705 | elif dcirc.has_key(i):
|
|---|
| 706 | pols.append(dcirc.get(i))
|
|---|
| [541] | 707 | polmode.append("circular")
|
|---|
| [525] | 708 | else:
|
|---|
| [652] | 709 | print "Pol type '%s' not valid" %i
|
|---|
| [525] | 710 | return
|
|---|
| 711 | elif 0 > i >= n:
|
|---|
| 712 | print "Pol index '%d' out of range" %i
|
|---|
| 713 | return
|
|---|
| 714 | else:
|
|---|
| 715 | pols.append(i)
|
|---|
| 716 | polmode.append("raw")
|
|---|
| 717 | self._cursor["p"] = pols
|
|---|
| 718 | self._polmode = polmode
|
|---|
| [541] | 719 | if self._data and refresh: self.plot()
|
|---|
| [525] | 720 |
|
|---|
| [603] | 721 | def _get_pollabel(self, scan, polmode):
|
|---|
| 722 | tlab = ""
|
|---|
| 723 | if polmode == "stokes":
|
|---|
| 724 | tlab = scan._getpolarizationlabel(0,1,0)
|
|---|
| 725 | elif polmode == "stokes2":
|
|---|
| 726 | tlab = scan._getpolarizationlabel(0,1,1)
|
|---|
| 727 | elif polmode == "circular":
|
|---|
| 728 | tlab = scan._getpolarizationlabel(0,0,0)
|
|---|
| 729 | else:
|
|---|
| 730 | tlab = scan._getpolarizationlabel(1,0,0)
|
|---|
| 731 | return tlab
|
|---|
| [672] | 732 |
|
|---|
| 733 | def _slice_indeces(self, data):
|
|---|
| 734 | mn = self._minmaxx[0]
|
|---|
| 735 | mx = self._minmaxx[1]
|
|---|
| 736 | asc = data[0] < data[-1]
|
|---|
| 737 | start=0
|
|---|
| 738 | end = len(data)-1
|
|---|
| 739 | inc = 1
|
|---|
| 740 | if not asc:
|
|---|
| 741 | start = len(data)-1
|
|---|
| 742 | end = 0
|
|---|
| 743 | inc = -1
|
|---|
| 744 | # find min index
|
|---|
| 745 | while data[start] < mn:
|
|---|
| 746 | start+= inc
|
|---|
| 747 | # find max index
|
|---|
| 748 | while data[end] > mx:
|
|---|
| 749 | end-=inc
|
|---|
| 750 | end +=1
|
|---|
| 751 | if start > end:
|
|---|
| 752 | return end,start
|
|---|
| 753 | return start,end
|
|---|
| [525] | 754 |
|
|---|
| [203] | 755 | if __name__ == '__main__':
|
|---|
| 756 | plotter = asapplotter()
|
|---|
