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