| 1 | from asap import rcParams
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| 2 | from numarray import logical_and
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| 3 |
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| 4 | class asapplotter:
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| 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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| 13 | def __init__(self, visible=True):
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| 14 |
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| 15 | if visible:
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| 16 | from asap.asaplotgui import asaplotgui as asaplot
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| 17 | else:
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| 18 | from asap.asaplot import asaplot
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| 19 | self._plotter = asaplot()
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| 20 |
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| 21 | self._tdict = {'Time':'t','time':'t','t':'t','T':'t'}
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| 22 | self._bdict = {'Beam':'b','beam':'b','b':'b','B':'b'}
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| 23 | self._idict = {'IF':'i','if':'i','i':'i','I':'i'}
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| 24 | self._pdict = {'Pol':'p','pol':'p','p':'p'}
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| 25 | self._sdict = {'scan':'s','Scan':'s','s':'s','S':'s'}
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| 26 | self._cdict = {'t':'len(self._cursor["t"])',
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| 27 | 'b':'len(self._cursor["b"])',
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| 28 | 'i':'len(self._cursor["i"])',
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| 29 | 'p':'len(self._cursor["p"])',
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| 30 | 's':'len(scans)'}
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| 31 | self._ldict = {'b':'Beam',
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| 32 | 'i':'IF',
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| 33 | 'p':'Pol',
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| 34 | 's':'Scan'}
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| 35 | self._dicts = [self._tdict,self._bdict,
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| 36 | self._idict,self._pdict,
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| 37 | self._sdict]
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| 38 | self._panelling = None
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| 39 | self._stacking = None
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| 40 | self.set_panelling()
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| 41 | self.set_stacking()
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| 42 | self._rows = None
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| 43 | self._cols = None
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| 44 | self._autoplot = False
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| 45 | self._minmaxx = None
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| 46 | self._minmaxy = None
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| 47 | self._datamask = None
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| 48 | self._data = None
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| 49 | self._lmap = None
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| 50 | self._title = None
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| 51 | self._ordinate = None
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| 52 | self._abcissa = None
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| 53 | self._abcunit = None
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| 54 | self._cursor = {'t':None, 'b':None,
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| 55 | 'i':None, 'p':None
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| 56 | }
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| 57 |
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| 58 | def _translate(self, name):
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| 59 | for d in self._dicts:
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| 60 | if d.has_key(name):
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| 61 | return d[name]
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| 62 | return None
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| 63 |
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| 64 | def plot(self, *args):
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| 65 | """
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| 66 | Plot a (list of) scantables.
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| 67 | Parameters:
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| 68 | one or more comma separated scantables
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| 69 | Note:
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| 70 | If a (list) of scantables was specified in a previous call
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| 71 | to plot, no argument has to be given to 'replot'
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| 72 | NO checking is done that the abcissas of the scantables
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| 73 | are consistent e.g. all 'channel' or all 'velocity' etc.
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| 74 | """
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| 75 | if self._plotter.is_dead:
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| 76 | self._plotter = ASAPlot()
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| 77 | self._plotter.hold()
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| 78 | self._plotter.clear()
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| 79 | if len(args) > 0:
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| 80 | if self._data is not None:
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| 81 | if list(args) != self._data:
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| 82 | self._data = list(args)
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| 83 | # reset cursor
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| 84 | self.set_cursor(refresh=False)
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| 85 | else:
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| 86 | self._data = list(args)
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| 87 | self.set_cursor(refresh=False)
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| 88 | # ranges become invalid when unit changes
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| 89 | if self._abcunit != self._data[0].get_unit():
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| 90 | self._minmaxx = None
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| 91 | self._minmaxy = None
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| 92 | self._abcunit = self._data[0].get_unit()
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| 93 | self._datamask = None
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| 94 | if self._panelling == 't':
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| 95 | maxrows = 25
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| 96 | if self._data[0].nrow() > maxrows:
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| 97 | if self._cursor["t"] is None or \
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| 98 | (isinstance(self._cursor["t"],list) and \
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| 99 | len(self._cursor["t"]) > maxrows ):
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| 100 | print "Scan to be plotted contains more than %d rows.\n" \
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| 101 | "Selecting first %d rows..." % (maxrows,maxrows)
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| 102 | self._cursor["t"] = range(maxrows)
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| 103 | self._plot_time(self._data[0], self._stacking)
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| 104 | elif self._panelling == 's':
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| 105 | self._plot_scans(self._data, self._stacking)
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| 106 | else:
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| 107 | self._plot_other(self._data, self._stacking)
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| 108 | if self._minmaxy is not None:
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| 109 | self._plotter.set_limits(ylim=self._minmaxy)
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| 110 | self._plotter.release()
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| 111 | return
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| 112 |
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| 113 | def _plot_time(self, scan, colmode):
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| 114 | if colmode == 't':
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| 115 | return
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| 116 | n = len(self._cursor["t"])
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| 117 | cdict = {'b':'scan.setbeam(j)',
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| 118 | 'i':'scan.setif(j)',
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| 119 | 'p':'scan.setpol(j)'}
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| 120 | cdict2 = {'b':'self._cursor["b"]',
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| 121 | 'i':'self._cursor["i"]',
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| 122 | 'p':'self._cursor["p"]'}
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| 123 | ncol = 1
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| 124 | if self._stacking is not None:
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| 125 | ncol = eval(self._cdict.get(colmode))
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| 126 | if n > 1:
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| 127 | if self._rows and self._cols:
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| 128 | n = min(n,self._rows*self._cols)
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| 129 | self._plotter.set_panels(rows=self._rows,cols=self._cols,
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| 130 | nplots=n)
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| 131 | else:
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| 132 | self._plotter.set_panels(rows=n,cols=0,nplots=n)
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| 133 | else:
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| 134 | self._plotter.set_panels()
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| 135 | rows = self._cursor["t"]
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| 136 | self._plotter.palette(0)
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| 137 | for rowsel in rows:
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| 138 | i = self._cursor["t"].index(rowsel)
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| 139 | if n > 1:
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| 140 | self._plotter.palette(0)
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| 141 | self._plotter.subplot(i)
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| 142 | colvals = eval(cdict2.get(colmode))
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| 143 | for j in colvals:
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| 144 | polmode = "raw"
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| 145 | jj = colvals.index(j)
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| 146 | savej = j
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| 147 | for k in cdict.keys():
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| 148 | sel = eval(cdict2.get(k))
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| 149 | j = sel[0]
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| 150 | if k == "p":
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| 151 | which = self._cursor["p"].index(j)
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| 152 | polmode = self._polmode[which]
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| 153 | j = which
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| 154 | eval(cdict.get(k))
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| 155 | j = savej
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| 156 | if colmode == "p":
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| 157 | polmode = self._polmode[self._cursor["p"].index(j)]
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| 158 | #j = jj
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| 159 | eval(cdict.get(colmode))
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| 160 | x = None
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| 161 | y = None
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| 162 | m = None
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| 163 | if self._title is None:
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| 164 | tlab = scan._getsourcename(rowsel)
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| 165 | else:
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| 166 | if len(self._title) >= n:
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| 167 | tlab = self._title[rowsel]
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| 168 | else:
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| 169 | tlab = scan._getsourcename(rowsel)
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| 170 | x,xlab = scan.get_abcissa(rowsel)
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| 171 | if self._abcissa: xlab = self._abcissa
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| 172 | y = None
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| 173 | if polmode == "stokes":
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| 174 | y = scan._getstokesspectrum(rowsel)
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| 175 | elif polmode == "stokes2":
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| 176 | y = scan._getstokesspectrum(rowsel,True)
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| 177 | elif polmode == "circular":
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| 178 | y = scan._stokestopolspectrum(rowsel,False,-1)
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| 179 | else:
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| 180 | y = scan._getspectrum(rowsel)
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| 181 | if self._ordinate:
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| 182 | ylab = self._ordinate
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| 183 | else:
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| 184 | ylab = scan._get_ordinate_label()
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| 185 | m = scan._getmask(rowsel)
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| 186 | if self._datamask is not None:
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| 187 | if len(m) == len(self._datamask):
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| 188 | m = logical_and(m,self._datamask)
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| 189 | if self._lmap and len(self._lmap) > 0:
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| 190 | llab = self._lmap[jj]
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| 191 | else:
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| 192 | if colmode == 'p':
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| 193 | llab = self._get_pollabel(scan, polmode)
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| 194 | else:
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| 195 | llab = self._ldict.get(colmode)+' '+str(j)
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| 196 | self._plotter.set_line(label=llab)
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| 197 | if self._minmaxx is not None:
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| 198 | s,e = self._slice_indeces(x)
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| 199 | x = x[s:e]
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| 200 | y = y[s:e]
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| 201 | m = m[s:e]
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| 202 | self._plotter.plot(x,y,m)
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| 203 | xlim=[min(x),max(x)]
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| 204 | if self._minmaxx is not None:
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| 205 | xlim = self._minmaxx
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| 206 | self._plotter.axes.set_xlim(xlim)
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| 207 | self._plotter.set_axes('xlabel',xlab)
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| 208 | self._plotter.set_axes('ylabel',ylab)
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| 209 | self._plotter.set_axes('title',tlab)
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| 210 | return
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| 211 |
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| 212 | def _plot_scans(self, scans, colmode):
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| 213 | print "Can only plot one row per scan."
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| 214 | if colmode == 's':
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| 215 | return
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| 216 | cdict = {'b':'scan.setbeam(j)',
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| 217 | 'i':'scan.setif(j)',
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| 218 | 'p':'scan.setpol(j)'}
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| 219 | cdict2 = {'b':'self._cursor["b"]',
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| 220 | 'i':'self._cursor["i"]',
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| 221 | 'p':'self._cursor["p"]'}
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| 222 |
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| 223 | n = len(scans)
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| 224 | ncol = 1
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| 225 | if self._stacking is not None:
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| 226 | scan = scans[0]
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| 227 | ncol = eval(self._cdict.get(colmode))
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| 228 | if n > 1:
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| 229 | if self._rows and self._cols:
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| 230 | n = min(n,self._rows*self._cols)
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| 231 | self._plotter.set_panels(rows=self._rows,cols=self._cols,
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| 232 | nplots=n)
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| 233 | else:
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| 234 | self._plotter.set_panels(rows=n,cols=0,nplots=n)
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| 235 | else:
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| 236 | self._plotter.set_panels()
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| 237 |
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| 238 | for scan in scans:
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| 239 | self._plotter.palette(0)
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| 240 | if n > 1:
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| 241 | self._plotter.subplot(scans.index(scan))
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| 242 | colvals = eval(cdict2.get(colmode))
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| 243 | rowsel = self._cursor["t"][0]
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| 244 | for j in colvals:
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| 245 | polmode = "raw"
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| 246 | jj = colvals.index(j)
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| 247 | savej = j
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| 248 | for k in cdict.keys():
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| 249 | sel = eval(cdict2.get(k))
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| 250 | j = sel[0]
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| 251 | eval(cdict.get(k))
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| 252 | if k == "p":
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| 253 | which = self._cursor["p"].index(j)
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| 254 | polmode = self._polmode[which]
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| 255 | j = which
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| 256 | j = savej
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| 257 | if colmode == "p":
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| 258 | polmode = self._polmode[self._cursor["p"].index(j)]
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| 259 | #j = jj
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| 260 | eval(cdict.get(colmode))
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| 261 | x = None
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| 262 | y = None
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| 263 | m = None
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| 264 | tlab = self._title
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| 265 | if not self._title:
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| 266 | tlab = scan._getsourcename(rowsel)
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| 267 | x,xlab = scan.get_abcissa(rowsel)
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| 268 | if self._abcissa: xlab = self._abcissa
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| 269 | if polmode == "stokes":
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| 270 | y = scan._getstokesspectrum(rowsel)
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| 271 | elif polmode == "stokes2":
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| 272 | y = scan._getstokesspectrum(rowsel,True)
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| 273 | elif polmode == "circular":
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| 274 | y = scan._stokestopolspectrum(rowsel,False,-1)
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| 275 | else:
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| 276 | y = scan._getspectrum(rowsel)
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| 277 | if self._ordinate:
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| 278 | ylab = self._ordinate
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| 279 | else:
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| 280 | ylab = scan._get_ordinate_label()
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| 281 | m = scan._getmask(rowsel)
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| 282 | if self._datamask is not None:
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| 283 | if len(m) == len(self._datamask):
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| 284 | m = logical_and(m,self._datamask)
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| 285 | if self._lmap and len(self._lmap) > 0:
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| 286 | llab = self._lmap[jj]
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| 287 | else:
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| 288 | if colmode == 'p':
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| 289 | llab = self._get_pollabel(scan, polmode)
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| 290 | else:
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| 291 | llab = self._ldict.get(colmode)+' '+str(j)
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| 292 | self._plotter.set_line(label=llab)
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| 293 | if self._minmaxx is not None:
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| 294 | s,e = self._slice_indeces(x)
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| 295 | x = x[s:e]
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| 296 | y = y[s:e]
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| 297 | m = m[s:e]
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| 298 |
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| 299 | self._plotter.plot(x,y,m)
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| 300 | xlim=[min(x),max(x)]
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| 301 | if self._minmaxx is not None:
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| 302 | xlim = self._minmaxx
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| 303 | self._plotter.axes.set_xlim(xlim)
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| 304 |
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| 305 | self._plotter.set_axes('xlabel',xlab)
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| 306 | self._plotter.set_axes('ylabel',ylab)
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| 307 | self._plotter.set_axes('title',tlab)
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| 308 | return
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| 309 |
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| 310 | def _plot_other(self,scans,colmode):
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| 311 | if colmode == self._panelling:
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| 312 | return
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| 313 | cdict = {'b':'scan.setbeam(i)',
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| 314 | 'i':'scan.setif(i)',
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| 315 | 'p':'scan.setpol(i)'}
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| 316 | cdict2 = {'b':'self._cursor["b"]',
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| 317 | 'i':'self._cursor["i"]',
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| 318 | 'p':'self._cursor["p"]',
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| 319 | 's': 'scans',
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| 320 | 't': 'self._cursor["t"]'}
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| 321 | scan = scans[0]
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| 322 | n = eval(self._cdict.get(self._panelling))
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| 323 | ncol=1
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| 324 | if self._stacking is not None:
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| 325 | ncol = eval(self._cdict.get(colmode))
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| 326 | if n > 1:
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| 327 | if self._rows and self._cols:
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| 328 | n = min(n,self._rows*self._cols)
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| 329 | self._plotter.set_panels(rows=self._rows,cols=self._cols,
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| 330 | nplots=n)
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| 331 | else:
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| 332 | self._plotter.set_panels(rows=n,cols=0,nplots=n)
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| 333 | else:
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| 334 | self._plotter.set_panels()
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| 335 | panels = self._cursor[self._panelling]
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| 336 | for i in panels:
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| 337 | self._plotter.palette(0)
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| 338 | polmode = "raw"
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| 339 | ii = self._cursor[self._panelling].index(i)
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| 340 | if n>1:
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| 341 | self._plotter.subplot(ii)
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| 342 | if self._panelling == "p":
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| 343 | polmode = self._polmode[ii]
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| 344 | eval(cdict.get(self._panelling))
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| 345 | else:
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| 346 | eval(cdict.get(self._panelling))
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| 347 | colvals = eval(cdict2.get(colmode))
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| 348 | for j in colvals:
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| 349 | rowsel = self._cursor["t"][0]
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| 350 | jj = colvals.index(j)
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| 351 | savei = i
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| 352 | for k in cdict.keys():
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| 353 | if k != self._panelling:
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| 354 | sel = eval(cdict2.get(k))
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| 355 | i = sel[0]
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| 356 | if k == "p":
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| 357 | which = self._cursor["p"].index(i)
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| 358 | polmode = self._polmode[which]
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| 359 | i = which
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| 360 | eval(cdict.get(k))
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| 361 | i = savei
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| 362 | if colmode == 's':
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| 363 | scan = j
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| 364 | elif colmode == 't':
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| 365 | rowsel = j
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| 366 | else:
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| 367 | savei = i
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| 368 | if colmode == 'p':
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| 369 | polmode = self._polmode[self._cursor["p"].index(j)]
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| 370 | i = j
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| 371 | eval(cdict.get(colmode))
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| 372 | i = savei
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| 373 | x = None
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| 374 | y = None
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| 375 | m = None
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| 376 | x,xlab = scan.get_abcissa(rowsel)
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| 377 | if self._abcissa: xlab = self._abcissa
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| 378 | if polmode == "stokes":
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| 379 | y = scan._getstokesspectrum(rowsel)
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| 380 | elif polmode == "stokes2":
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| 381 | y = scan._getstokesspectrum(rowsel,True)
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| 382 | elif polmode == "circular":
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| 383 | y = scan._stokestopolspectrum(rowsel,False,-1)
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| 384 | else:
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| 385 | y = scan._getspectrum(rowsel)
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| 386 |
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| 387 | if self._ordinate:
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| 388 | ylab = self._ordinate
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| 389 | else:
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| 390 | ylab = scan._get_ordinate_label()
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| 391 | m = scan._getmask(rowsel)
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| 392 | if self._datamask is not None:
|
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| 393 | if len(m) == len(self._datamask):
|
|---|
| 394 | m = logical_and(m,self._datamask)
|
|---|
| 395 | if colmode == 's' or colmode == 't':
|
|---|
| 396 | if self._title and len(self._title) > 0:
|
|---|
| 397 | tlab = self._title[ii]
|
|---|
| 398 | else:
|
|---|
| 399 | if self._panelling == 'p':
|
|---|
| 400 | tlab = self._get_pollabel(scan, polmode)
|
|---|
| 401 | else:
|
|---|
| 402 | tlab = self._ldict.get(self._panelling)+' '+str(i)
|
|---|
| 403 | if self._lmap and len(self._lmap) > 0:
|
|---|
| 404 | llab = self._lmap[jj]
|
|---|
| 405 | else:
|
|---|
| 406 | llab = scan._getsourcename(rowsel)
|
|---|
| 407 | else:
|
|---|
| 408 | if self._title and len(self._title) > 0:
|
|---|
| 409 | tlab = self._title[ii]
|
|---|
| 410 | else:
|
|---|
| 411 | if self._panelling == 'p':
|
|---|
| 412 | tlab = self._get_pollabel(scan, polmode)
|
|---|
| 413 | else:
|
|---|
| 414 | tlab = self._ldict.get(self._panelling)+' '+str(i)
|
|---|
| 415 | if self._lmap and len(self._lmap) > 0:
|
|---|
| 416 | llab = self._lmap[jj]
|
|---|
| 417 | else:
|
|---|
| 418 | if colmode == 'p':
|
|---|
| 419 | llab = self._get_pollabel(scan, polmode)
|
|---|
| 420 | else:
|
|---|
| 421 | llab = self._ldict.get(colmode)+' '+str(j)
|
|---|
| 422 | self._plotter.set_line(label=llab)
|
|---|
| 423 | if self._minmaxx is not None:
|
|---|
| 424 | s,e = self._slice_indeces(x)
|
|---|
| 425 | x = x[s:e]
|
|---|
| 426 | y = y[s:e]
|
|---|
| 427 | m = m[s:e]
|
|---|
| 428 |
|
|---|
| 429 | self._plotter.plot(x,y,m)
|
|---|
| 430 | xlim=[min(x),max(x)]
|
|---|
| 431 | if self._minmaxx is not None:
|
|---|
| 432 | xlim = self._minmaxx
|
|---|
| 433 | self._plotter.axes.set_xlim(xlim)
|
|---|
| 434 |
|
|---|
| 435 | self._plotter.set_axes('xlabel',xlab)
|
|---|
| 436 | self._plotter.set_axes('ylabel',ylab)
|
|---|
| 437 | self._plotter.set_axes('title',tlab)
|
|---|
| 438 |
|
|---|
| 439 | return
|
|---|
| 440 |
|
|---|
| 441 |
|
|---|
| 442 | def set_mode(self, stacking=None, panelling=None):
|
|---|
| 443 | """
|
|---|
| 444 | Set the plots look and feel, i.e. what you want to see on the plot.
|
|---|
| 445 | Parameters:
|
|---|
| 446 | stacking: tell the plotter which variable to plot
|
|---|
| 447 | as line colour overlays (default 'pol')
|
|---|
| 448 | panelling: tell the plotter which variable to plot
|
|---|
| 449 | across multiple panels (default 'scan'
|
|---|
| 450 | Note:
|
|---|
| 451 | Valid modes are:
|
|---|
| 452 | 'beam' 'Beam' 'b': Beams
|
|---|
| 453 | 'if' 'IF' 'i': IFs
|
|---|
| 454 | 'pol' 'Pol' 'p': Polarisations
|
|---|
| 455 | 'scan' 'Scan' 's': Scans
|
|---|
| 456 | 'time' 'Time' 't': Times
|
|---|
| 457 | """
|
|---|
| 458 | if not self.set_panelling(panelling):
|
|---|
| 459 | print "Invalid mode"
|
|---|
| 460 | return
|
|---|
| 461 | if not self.set_stacking(stacking):
|
|---|
| 462 | print "Invalid mode"
|
|---|
| 463 | return
|
|---|
| 464 | if self._data: self.plot()
|
|---|
| 465 | return
|
|---|
| 466 |
|
|---|
| 467 | def set_panelling(self, what=None):
|
|---|
| 468 | mode = what
|
|---|
| 469 | if mode is None:
|
|---|
| 470 | mode = rcParams['plotter.panelling']
|
|---|
| 471 | md = self._translate(mode)
|
|---|
| 472 | if md:
|
|---|
| 473 | self._panelling = md
|
|---|
| 474 | self._title = None
|
|---|
| 475 | return True
|
|---|
| 476 | return False
|
|---|
| 477 |
|
|---|
| 478 | def set_layout(self,rows=None,cols=None):
|
|---|
| 479 | """
|
|---|
| 480 | Set the multi-panel layout, i.e. how many rows and columns plots
|
|---|
| 481 | are visible.
|
|---|
| 482 | Parameters:
|
|---|
| 483 | rows: The number of rows of plots
|
|---|
| 484 | cols: The number of columns of plots
|
|---|
| 485 | Note:
|
|---|
| 486 | If no argument is given, the potter reverts to its auto-plot
|
|---|
| 487 | behaviour.
|
|---|
| 488 | """
|
|---|
| 489 | self._rows = rows
|
|---|
| 490 | self._cols = cols
|
|---|
| 491 | if self._data: self.plot()
|
|---|
| 492 | return
|
|---|
| 493 |
|
|---|
| 494 | def set_stacking(self, what=None):
|
|---|
| 495 | mode = what
|
|---|
| 496 | if mode is None:
|
|---|
| 497 | mode = rcParams['plotter.stacking']
|
|---|
| 498 | md = self._translate(mode)
|
|---|
| 499 | if md:
|
|---|
| 500 | self._stacking = md
|
|---|
| 501 | self._lmap = None
|
|---|
| 502 | return True
|
|---|
| 503 | return False
|
|---|
| 504 |
|
|---|
| 505 | def set_range(self,xstart=None,xend=None,ystart=None,yend=None):
|
|---|
| 506 | """
|
|---|
| 507 | Set the range of interest on the abcissa of the plot
|
|---|
| 508 | Parameters:
|
|---|
| 509 | [x,y]start,[x,y]end: The start and end points of the 'zoom' window
|
|---|
| 510 | Note:
|
|---|
| 511 | These become non-sensical when the unit changes.
|
|---|
| 512 | use plotter.set_range() without parameters to reset
|
|---|
| 513 |
|
|---|
| 514 | """
|
|---|
| 515 | if xstart is None and xend is None:
|
|---|
| 516 | self._minmaxx = None
|
|---|
| 517 | else:
|
|---|
| 518 | self._minmaxx = [xstart,xend]
|
|---|
| 519 | if ystart is None and yend is None:
|
|---|
| 520 | self._minmaxy = None
|
|---|
| 521 | else:
|
|---|
| 522 | self._minmaxy = [ystart,yend]
|
|---|
| 523 | if self._data: self.plot()
|
|---|
| 524 | return
|
|---|
| 525 |
|
|---|
| 526 | def set_legend(self, mp=None):
|
|---|
| 527 | """
|
|---|
| 528 | Specify a mapping for the legend instead of using the default
|
|---|
| 529 | indices:
|
|---|
| 530 | Parameters:
|
|---|
| 531 | mp: a list of 'strings'. This should have the same length
|
|---|
| 532 | as the number of elements on the legend and then maps
|
|---|
| 533 | to the indeces in order
|
|---|
| 534 |
|
|---|
| 535 | Example:
|
|---|
| 536 | If the data has two IFs/rest frequencies with index 0 and 1
|
|---|
| 537 | for CO and SiO:
|
|---|
| 538 | plotter.set_stacking('i')
|
|---|
| 539 | plotter.set_legend_map(['CO','SiO'])
|
|---|
| 540 | plotter.plot()
|
|---|
| 541 | """
|
|---|
| 542 | self._lmap = mp
|
|---|
| 543 | if self._data: self.plot()
|
|---|
| 544 | return
|
|---|
| 545 |
|
|---|
| 546 | def set_title(self, title=None):
|
|---|
| 547 | self._title = title
|
|---|
| 548 | if self._data: self.plot()
|
|---|
| 549 | return
|
|---|
| 550 |
|
|---|
| 551 | def set_ordinate(self, ordinate=None):
|
|---|
| 552 | self._ordinate = ordinate
|
|---|
| 553 | if self._data: self.plot()
|
|---|
| 554 | return
|
|---|
| 555 |
|
|---|
| 556 | def set_abcissa(self, abcissa=None):
|
|---|
| 557 | self._abcissa = abcissa
|
|---|
| 558 | if self._data: self.plot()
|
|---|
| 559 | return
|
|---|
| 560 |
|
|---|
| 561 | def save(self, filename=None, orientation=None,dpi=None):
|
|---|
| 562 | """
|
|---|
| 563 | Save the plot to a file. The know formats are 'png', 'ps', 'eps'.
|
|---|
| 564 | Parameters:
|
|---|
| 565 | filename: The name of the output file. This is optional
|
|---|
| 566 | and autodetects the image format from the file
|
|---|
| 567 | suffix. If non filename is specified a file
|
|---|
| 568 | called 'yyyymmdd_hhmmss.png' is created in the
|
|---|
| 569 | current directory.
|
|---|
| 570 | orientation: optional parameter for postscript only (not eps).
|
|---|
| 571 | 'landscape', 'portrait' or None (default) are valid.
|
|---|
| 572 | If None is choosen for 'ps' output, the plot is
|
|---|
| 573 | automatically oriented to fill the page.
|
|---|
| 574 | """
|
|---|
| 575 | self._plotter.save(filename,orientation,dpi)
|
|---|
| 576 | return
|
|---|
| 577 |
|
|---|
| 578 | def set_cursor(self, row=None,beam=None,IF=None,pol=None, refresh=True):
|
|---|
| 579 | """
|
|---|
| 580 | Specify a 'cursor' for plotting selected spectra. Time (rows),
|
|---|
| 581 | Beam, IF, Polarisation ranges can be specified.
|
|---|
| 582 | Parameters:
|
|---|
| 583 | Default for all paramaters is to select all available
|
|---|
| 584 | row: selects the rows (time stamps) to be plotted, this has
|
|---|
| 585 | to be a vector of row indices, e.g. row=[0,2,5] or row=[2]
|
|---|
| 586 | beam: select a range of beams
|
|---|
| 587 | IF: select a range of IFs
|
|---|
| 588 | pol: select Polarisations for plotting these can be by index
|
|---|
| 589 | (raw polarisations (default)) or by names any of:
|
|---|
| 590 | ["I", "Q", "U", "V"] or
|
|---|
| 591 | ["I", "Plinear", "Pangle", "V"] or
|
|---|
| 592 | ["XX", "YY", "Real(XY)", "Imag(XY)"] or
|
|---|
| 593 | ["RR", "LL"]
|
|---|
| 594 | Example:
|
|---|
| 595 | plotter.set_mode('pol','time')
|
|---|
| 596 | plotter.plot(myscan) # plots all raw polarisations colour stacked
|
|---|
| 597 | plotter.set_cursor(pol=["I"]) # plot "I" only for all rows
|
|---|
| 598 | # plot "I" only for two time stamps row=0 and row=2
|
|---|
| 599 | plotter.set_cursor(row=[0,2],pol=["I"])
|
|---|
| 600 |
|
|---|
| 601 | Note:
|
|---|
| 602 | Be careful to select only exisiting polarisations.
|
|---|
| 603 | """
|
|---|
| 604 | if not self._data:
|
|---|
| 605 | print "Can only set cursor after a first call to plot()"
|
|---|
| 606 | return
|
|---|
| 607 |
|
|---|
| 608 | n = self._data[0].nrow()
|
|---|
| 609 | if row is None:
|
|---|
| 610 | self._cursor["t"] = range(n)
|
|---|
| 611 | else:
|
|---|
| 612 | for i in row:
|
|---|
| 613 | if i < 0 or i >= n:
|
|---|
| 614 | print "Row index '%d' out of range" % i
|
|---|
| 615 | return
|
|---|
| 616 | self._cursor["t"] = row
|
|---|
| 617 |
|
|---|
| 618 | n = self._data[0].nbeam()
|
|---|
| 619 | if beam is None:
|
|---|
| 620 | self._cursor["b"] = range(n)
|
|---|
| 621 | else:
|
|---|
| 622 | for i in beam:
|
|---|
| 623 | if i < 0 or i >= n:
|
|---|
| 624 | print "Beam index '%d' out of range" % i
|
|---|
| 625 | return
|
|---|
| 626 | self._cursor["b"] = beam
|
|---|
| 627 |
|
|---|
| 628 | n = self._data[0].nif()
|
|---|
| 629 | if IF is None:
|
|---|
| 630 | self._cursor["i"] = range(n)
|
|---|
| 631 | else:
|
|---|
| 632 | for i in IF:
|
|---|
| 633 | if i < 0 or i >= n:
|
|---|
| 634 | print "IF index '%d' out of range" %i
|
|---|
| 635 | return
|
|---|
| 636 | self._cursor["i"] = IF
|
|---|
| 637 |
|
|---|
| 638 | n = self._data[0].npol()
|
|---|
| 639 | dstokes = {"I":0,"Q":1,"U":2,"V":3}
|
|---|
| 640 | dstokes2 = {"I":0,"Plinear":1,"Pangle":2,"V":3}
|
|---|
| 641 | draw = {"XX":0, "YY":1,"Real(XY)":2, "Imag(XY)":3}
|
|---|
| 642 | dcirc = { "RR":0,"LL":1}#,"Real(RL)":2,"Image(RL)":3}
|
|---|
| 643 |
|
|---|
| 644 | if pol is None:
|
|---|
| 645 | self._cursor["p"] = range(n)
|
|---|
| 646 | self._polmode = ["raw" for i in range(n)]
|
|---|
| 647 | else:
|
|---|
| 648 | if isinstance(pol,str):
|
|---|
| 649 | pol = pol.split()
|
|---|
| 650 | polmode = []
|
|---|
| 651 | pols = []
|
|---|
| 652 | for i in pol:
|
|---|
| 653 | if isinstance(i,str):
|
|---|
| 654 | if draw.has_key(i):
|
|---|
| 655 | pols.append(draw.get(i))
|
|---|
| 656 | polmode.append("raw")
|
|---|
| 657 | elif dstokes.has_key(i):
|
|---|
| 658 | pols.append(dstokes.get(i))
|
|---|
| 659 | polmode.append("stokes")
|
|---|
| 660 | elif dstokes2.has_key(i):
|
|---|
| 661 | pols.append(dstokes2.get(i))
|
|---|
| 662 | polmode.append("stokes2")
|
|---|
| 663 | elif dcirc.has_key(i):
|
|---|
| 664 | pols.append(dcirc.get(i))
|
|---|
| 665 | polmode.append("circular")
|
|---|
| 666 | else:
|
|---|
| 667 | print "Pol type '%s' not valid" %i
|
|---|
| 668 | return
|
|---|
| 669 | elif 0 > i >= n:
|
|---|
| 670 | print "Pol index '%d' out of range" %i
|
|---|
| 671 | return
|
|---|
| 672 | else:
|
|---|
| 673 | pols.append(i)
|
|---|
| 674 | polmode.append("raw")
|
|---|
| 675 | self._cursor["p"] = pols
|
|---|
| 676 | self._polmode = polmode
|
|---|
| 677 | if self._data and refresh: self.plot()
|
|---|
| 678 |
|
|---|
| 679 | def _get_pollabel(self, scan, polmode):
|
|---|
| 680 | tlab = ""
|
|---|
| 681 | if polmode == "stokes":
|
|---|
| 682 | tlab = scan._getpolarizationlabel(0,1,0)
|
|---|
| 683 | elif polmode == "stokes2":
|
|---|
| 684 | tlab = scan._getpolarizationlabel(0,1,1)
|
|---|
| 685 | elif polmode == "circular":
|
|---|
| 686 | tlab = scan._getpolarizationlabel(0,0,0)
|
|---|
| 687 | else:
|
|---|
| 688 | tlab = scan._getpolarizationlabel(1,0,0)
|
|---|
| 689 | return tlab
|
|---|
| 690 |
|
|---|
| 691 | def _slice_indeces(self, data):
|
|---|
| 692 | mn = self._minmaxx[0]
|
|---|
| 693 | mx = self._minmaxx[1]
|
|---|
| 694 | asc = data[0] < data[-1]
|
|---|
| 695 | start=0
|
|---|
| 696 | end = len(data)-1
|
|---|
| 697 | inc = 1
|
|---|
| 698 | if not asc:
|
|---|
| 699 | start = len(data)-1
|
|---|
| 700 | end = 0
|
|---|
| 701 | inc = -1
|
|---|
| 702 | # find min index
|
|---|
| 703 | while data[start] < mn:
|
|---|
| 704 | start+= inc
|
|---|
| 705 | # find max index
|
|---|
| 706 | while data[end] > mx:
|
|---|
| 707 | end-=inc
|
|---|
| 708 | end +=1
|
|---|
| 709 | if start > end:
|
|---|
| 710 | return end,start
|
|---|
| 711 | return start,end
|
|---|
| 712 |
|
|---|
| 713 | #if __name__ == '__main__':
|
|---|
| 714 | # plotter = asapplotter()
|
|---|
