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