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._panels = 's' |
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34 | self._stacking = rcParams['plotter.stacking'] |
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35 | self._rows = None |
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36 | self._cols = None |
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37 | self._autoplot = False |
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38 | self._minmaxx = None |
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39 | self._minmaxy = None |
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40 | self._data = None |
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41 | self._lmap = [] |
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42 | self._title = None |
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43 | self._ordinate = None |
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44 | self._abcissa = None |
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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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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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55 | def plot(self, *args): |
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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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63 | NO checking is done that the abcissas of the scantables |
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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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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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79 | if self._panels == 't': |
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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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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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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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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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97 | n = len(self._cursor["t"]) |
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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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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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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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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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114 | self._plotter.set_panels(rows=n,cols=0,nplots=n) |
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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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119 | if n > 1: |
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120 | self._plotter.palette(1) |
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121 | self._plotter.subplot(i) |
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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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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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143 | if not self._title: |
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144 | tlab = scan._getsourcename(rowsel) |
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145 | else: |
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146 | if len(self._title) == n: |
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147 | tlab = self._title[rowsel] |
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148 | else: |
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149 | tlab = scan._getsourcename(rowsel) |
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150 | x,xlab = scan.get_abcissa(rowsel) |
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151 | if self._abcissa: xlab = self._abcissa |
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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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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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163 | m = scan._getmask(rowsel) |
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164 | if self._lmap and len(self._lmap) > 0: |
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165 | llab = self._lmap[jj] |
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166 | else: |
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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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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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185 | def _plot_scans(self, scans, colmode): |
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186 | print "Can only plot one row per scan." |
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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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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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196 | n = len(scans) |
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197 | ncol = 1 |
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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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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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208 | self._plotter.set_panels(rows=n,cols=0,nplots=n) |
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209 | self._plotter.palette(1) |
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210 | for scan in scans: |
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211 | if n > 1: |
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212 | self._plotter.subplot(scans.index(scan)) |
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213 | self._plotter.palette(1) |
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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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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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236 | tlab = self._title |
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237 | if not self._title: |
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238 | tlab = scan._getsourcename(rowsel) |
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239 | x,xlab = scan.get_abcissa(rowsel) |
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240 | if self._abcissa: xlab = self._abcissa |
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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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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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251 | m = scan._getmask(rowsel) |
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252 | if self._lmap and len(self._lmap) > 0: |
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253 | llab = self._lmap[jj] |
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254 | else: |
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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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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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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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285 | scan = scans[0] |
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286 | n = eval(self._cdict.get(self._panels)) |
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287 | ncol=1 |
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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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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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297 | self._plotter.set_panels(rows=n,cols=0,nplots=n) |
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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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303 | if n>1: |
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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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325 | if colmode == 's': |
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326 | scan = j |
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327 | elif colmode == 't': |
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328 | rowsel = j |
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329 | else: |
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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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334 | eval(cdict.get(colmode)) |
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335 | i = savei |
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336 | x = None |
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337 | y = None |
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338 | m = None |
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339 | x,xlab = scan.get_abcissa(rowsel) |
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340 | if self._abcissa: xlab = self._abcissa |
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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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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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352 | m = scan._getmask(rowsel) |
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353 | if colmode == 's' or colmode == 't': |
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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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357 | tlab = self._ldict.get(self._panels)+' '+str(i) |
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358 | llab = scan._getsourcename(rowsel) |
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359 | else: |
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360 | if self._title and len(self._title) > 0: |
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361 | tlab = self._title[ii] |
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362 | else: |
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363 | tlab = self._ldict.get(self._panels)+' '+str(i) |
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364 | if self._lmap and len(self._lmap) > 0: |
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365 | llab = self._lmap[jj] |
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366 | else: |
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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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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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395 | def set_mode(self, stacking=None, panelling=None): |
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396 | """ |
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397 | Set the plots look and feel, i.e. what you want to see on the plot. |
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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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413 | return |
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414 | if not self.set_stacking(stacking): |
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415 | print "Invalid mode" |
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416 | return |
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417 | if self._data: self.plot() |
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418 | return |
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419 | |
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420 | def set_panels(self, what=None): |
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421 | if not what: |
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422 | what = rcParams['plotter.panelling'] |
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423 | md = self._translate(what) |
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424 | if md: |
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425 | self._panels = md |
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426 | self._title = None |
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427 | return True |
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428 | return False |
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429 | |
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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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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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449 | md = self._translate(what) |
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450 | if md: |
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451 | self._stacking = md |
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452 | self._lmap = None |
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453 | return True |
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454 | return False |
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455 | |
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456 | def set_range(self,xstart=None,xend=None,ystart=None,yend=None): |
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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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460 | [x,y]start,[x,y]end: The start and end points of the 'zoom' window |
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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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466 | if xstart is None and xend is None: |
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467 | self._minmaxx = None |
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468 | if self._data: self.plot() |
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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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472 | if self._data: self.plot() |
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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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477 | return |
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478 | |
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479 | def set_legend(self, mp=None): |
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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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489 | If the data has two IFs/rest frequencies with index 0 and 1 |
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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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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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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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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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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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549 | |
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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 | |
---|
593 | if pol is None: |
---|
594 | self._cursor["p"] = range(n) |
---|
595 | self._polmode = ["raw" for i in range(n)] |
---|
596 | else: |
---|
597 | if isinstance(pol,str): |
---|
598 | pol = pol.split() |
---|
599 | polmode = [] |
---|
600 | pols = [] |
---|
601 | for i in pol: |
---|
602 | if isinstance(i,str): |
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603 | if draw.has_key(i): |
---|
604 | pols.append(draw.get(i)) |
---|
605 | polmode.append("raw") |
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606 | elif dstokes.has_key(i): |
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607 | pols.append(dstokes.get(i)) |
---|
608 | polmode.append("stokes") |
---|
609 | elif dstokes2.has_key(i): |
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610 | pols.append(dstokes2.get(i)) |
---|
611 | polmode.append("stokes2") |
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612 | elif dcirc.has_key(i): |
---|
613 | pols.append(dcirc.get(i)) |
---|
614 | polmode.append("cricular") |
---|
615 | else: |
---|
616 | "Pol type '%s' not valid" %i |
---|
617 | return |
---|
618 | elif 0 > i >= n: |
---|
619 | print "Pol index '%d' out of range" %i |
---|
620 | return |
---|
621 | else: |
---|
622 | pols.append(i) |
---|
623 | polmode.append("raw") |
---|
624 | self._cursor["p"] = pols |
---|
625 | self._polmode = polmode |
---|
626 | if self._data: self.plot() |
---|
627 | |
---|
628 | |
---|
629 | if __name__ == '__main__': |
---|
630 | plotter = asapplotter() |
---|