1 | from asap import rcParams, print_log
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2 | from numarray import logical_and
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3 |
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4 | class asapplotter:
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5 | """
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6 | The ASAP plotter.
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7 | By default the plotter is set up to plot polarisations
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8 | 'colour stacked' and scantables across panels.
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9 | Note:
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10 | Currenly it only plots 'spectra' not Tsys or
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11 | other variables.
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12 | """
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13 | def __init__(self, visible=None):
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14 | self._visible = rcParams['plotter.gui']
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15 | if visible is not None:
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16 | self._visible = visible
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17 | self._plotter = self._newplotter()
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18 |
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19 | self._tdict = {'Time':'t','time':'t','t':'t','T':'t'}
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20 | self._bdict = {'Beam':'b','beam':'b','b':'b','B':'b'}
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21 | self._idict = {'IF':'i','if':'i','i':'i','I':'i'}
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22 | self._pdict = {'Pol':'p','pol':'p','p':'p'}
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23 | self._sdict = {'scan':'s','Scan':'s','s':'s','S':'s'}
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24 | self._cdict = {'t':'len(self._cursor["t"])',
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25 | 'b':'len(self._cursor["b"])',
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26 | 'i':'len(self._cursor["i"])',
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27 | 'p':'len(self._cursor["p"])',
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28 | 's':'len(scans)'}
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29 | self._ldict = {'b':'Beam',
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30 | 'i':'IF',
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31 | 'p':'Pol',
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32 | 's':'Scan'}
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33 | self._dicts = [self._tdict,self._bdict,
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34 | self._idict,self._pdict,
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35 | self._sdict]
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36 | self._panelling = None
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37 | self._stacking = None
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38 | self.set_panelling()
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39 | self.set_stacking()
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40 | self._rows = None
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41 | self._cols = None
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42 | self._autoplot = False
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43 | self._minmaxx = None
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44 | self._minmaxy = None
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45 | self._datamask = None
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46 | self._data = None
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47 | self._lmap = None
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48 | self._title = None
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49 | self._ordinate = None
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50 | self._abcissa = None
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51 | self._abcunit = None
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52 | self._cursor = {'t':None, 'b':None,
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53 | 'i':None, 'p':None
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54 | }
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55 | self._usermask = None
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56 | self._usermaskspectra = None
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57 |
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58 | def _newplotter(self):
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59 | if self._visible:
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60 | from asap.asaplotgui import asaplotgui as asaplot
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61 | else:
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62 | from asap.asaplot import asaplot
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63 | return asaplot()
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64 |
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65 |
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66 | def _translate(self, name):
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67 | for d in self._dicts:
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68 | if d.has_key(name):
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69 | return d[name]
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70 | return None
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71 |
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72 | def plot(self, *args):
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73 | """
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74 | Plot a (list of) scantables.
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75 | Parameters:
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76 | one or more comma separated scantables
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77 | Note:
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78 | If a (list) of scantables was specified in a previous call
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79 | to plot, no argument has to be given to 'replot'
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80 | NO checking is done that the abcissas of the scantables
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81 | are consistent e.g. all 'channel' or all 'velocity' etc.
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82 | """
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83 | if self._plotter.is_dead:
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84 | self._plotter = self._newplotter()
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85 | self._plotter.hold()
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86 | self._plotter.clear()
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87 | if len(args) > 0:
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88 | if self._data is not None:
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89 | if list(args) != self._data:
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90 | self._data = list(args)
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91 | # reset
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92 | self._reset()
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93 | else:
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94 | if isinstance(args[0], list):
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95 | self._data = args[0]
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96 | else:
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97 | self._data = list(args)
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98 | self._reset()
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99 | # ranges become invalid when unit changes
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100 | if self._abcunit != self._data[0].get_unit():
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101 | self._minmaxx = None
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102 | self._minmaxy = None
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103 | self._abcunit = self._data[0].get_unit()
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104 | self._datamask = None
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105 | if self._panelling == 't':
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106 | maxrows = 25
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107 | if self._data[0].nrow() > maxrows and not (self._rows and self._cols):
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108 | if self._cursor["t"] is None or \
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109 | (isinstance(self._cursor["t"],list) and \
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110 | len(self._cursor["t"]) > maxrows ):
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111 | from asap import asaplog
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112 | msg ="Scan to be plotted contains more than %d rows.\n" \
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113 | "Selecting first %d rows..." % (maxrows,maxrows)
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114 | asaplog.push(msg)
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115 | self._cursor["t"] = range(maxrows)
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116 | self._plot_time(self._data[0], self._stacking)
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117 | elif self._panelling == 's':
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118 | self._plot_scans(self._data, self._stacking)
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119 | else:
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120 | self._plot_other(self._data, self._stacking)
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121 | if self._minmaxy is not None:
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122 | self._plotter.set_limits(ylim=self._minmaxy)
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123 | self._plotter.release()
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124 | print_log()
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125 | return
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126 |
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127 | def _plot_time(self, scan, colmode):
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128 | if colmode == 't':
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129 | return
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130 | n = len(self._cursor["t"])
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131 | cdict = {'b':'scan.setbeam(j)',
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132 | 'i':'scan.setif(j)',
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133 | 'p':'scan.setpol(j)'}
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134 | cdict2 = {'b':'self._cursor["b"]',
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135 | 'i':'self._cursor["i"]',
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136 | 'p':'self._cursor["p"]'}
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137 | ncol = 1
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138 | if self._stacking is not None:
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139 | ncol = eval(self._cdict.get(colmode))
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140 | if n > 1:
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141 | ganged = rcParams['plotter.ganged']
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142 | if self._rows and self._cols:
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143 | n = min(n,self._rows*self._cols)
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144 | self._plotter.set_panels(rows=self._rows,cols=self._cols,
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145 | nplots=n,ganged=ganged)
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146 | else:
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147 | self._plotter.set_panels(rows=n,cols=0,nplots=n,ganged=ganged)
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148 | else:
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149 | self._plotter.set_panels()
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150 | rows = self._cursor["t"]
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151 | rows = rows[:n]
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152 | self._plotter.palette(0)
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153 | for rowsel in rows:
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154 | i = self._cursor["t"].index(rowsel)
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155 | if n > 1:
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156 | self._plotter.palette(0)
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157 | self._plotter.subplot(i)
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158 | colvals = eval(cdict2.get(colmode))
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159 | for j in colvals:
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160 | polmode = "raw"
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161 | jj = colvals.index(j)
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162 | savej = j
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163 | for k in cdict.keys():
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164 | sel = eval(cdict2.get(k))
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165 | j = sel[0]
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166 | if k == "p":
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167 | which = self._cursor["p"].index(j)
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168 | polmode = self._polmode[which]
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169 | j = which
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170 | eval(cdict.get(k))
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171 | j = savej
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172 | if colmode == "p":
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173 | polmode = self._polmode[self._cursor["p"].index(j)]
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174 | #j = jj
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175 | eval(cdict.get(colmode))
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176 | x = None
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177 | y = None
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178 | m = None
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179 | if self._title is None:
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180 | tlab = scan._getsourcename(rowsel)
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181 | else:
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182 | if len(self._title) >= n:
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183 | tlab = self._title[rowsel]
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184 | else:
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185 | tlab = scan._getsourcename(rowsel)
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186 | x,xlab = scan.get_abcissa(rowsel)
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187 | if self._abcissa: xlab = self._abcissa
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188 | y = None
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189 | m = scan._getmask(rowsel)
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190 | if self._usermask and self._usermask.count(j):
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191 | m = logical_and(self._usermask, m)
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192 | if polmode == "stokes":
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193 | y = scan._getstokesspectrum(rowsel)
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194 | elif polmode == "stokes2":
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195 | y = scan._getstokesspectrum(rowsel,True)
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196 | elif polmode == "circular":
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197 | y = scan._stokestopolspectrum(rowsel,False,-1)
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198 | else:
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199 | y = scan._getspectrum(rowsel)
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200 | if self._ordinate:
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201 | ylab = self._ordinate
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202 | else:
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203 | ylab = scan._get_ordinate_label()
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204 | m = scan._getmask(rowsel)
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205 | if self._datamask is not None:
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206 | if len(m) == len(self._datamask):
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207 | m = logical_and(m,self._datamask)
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208 | if self._lmap and len(self._lmap) > 0:
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209 | llab = self._lmap[jj]
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210 | else:
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211 | if colmode == 'p':
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212 | llab = self._get_pollabel(scan, polmode)
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213 | else:
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214 | llab = self._ldict.get(colmode)+' '+str(j)
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215 | self._plotter.set_line(label=llab)
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216 | if self._minmaxx is not None:
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217 | s,e = self._slice_indeces(x)
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218 | x = x[s:e]
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219 | y = y[s:e]
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220 | m = m[s:e]
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221 | if len(x) > 1024 and rcParams['plotter.decimate']:
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222 | fac = len(x)/1024
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223 | x = x[::fac]
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224 | m = m[::fac]
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225 | y = y[::fac]
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226 | self._plotter.plot(x,y,m)
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227 | xlim=[min(x),max(x)]
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228 | if self._minmaxx is not None:
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229 | xlim = self._minmaxx
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230 | self._plotter.axes.set_xlim(xlim)
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231 | self._plotter.set_axes('xlabel',xlab)
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232 | self._plotter.set_axes('ylabel',ylab)
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233 | self._plotter.set_axes('title',tlab)
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234 | return
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235 |
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236 | def _plot_scans(self, scans, colmode):
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237 | from asap import asaplog
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238 | msg = "Plotting mode is scans across panels. Can only plot one row per scan."
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239 | asaplog.push(msg)
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240 | if colmode == 's':
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241 | return
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242 | cdict = {'b':'scan.setbeam(j)',
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243 | 'i':'scan.setif(j)',
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244 | 'p':'scan.setpol(j)'}
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245 | cdict2 = {'b':'self._cursor["b"]',
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246 | 'i':'self._cursor["i"]',
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247 | 'p':'self._cursor["p"]'}
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248 |
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249 | n = len(scans)
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250 | ncol = 1
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251 | if self._stacking is not None:
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252 | scan = scans[0]
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253 | ncol = eval(self._cdict.get(colmode))
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254 | if n > 1:
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255 | ganged = rcParams['plotter.ganged']
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256 | if self._rows and self._cols:
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257 | n = min(n,self._rows*self._cols)
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258 | self._plotter.set_panels(rows=self._rows,cols=self._cols,
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259 | nplots=n,ganged=ganged)
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260 | else:
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261 | self._plotter.set_panels(rows=n,cols=0,nplots=n,ganged=ganged)
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262 | else:
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263 | self._plotter.set_panels()
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264 |
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265 | for scan in scans:
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266 | self._plotter.palette(0)
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267 | if n > 1:
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268 | self._plotter.subplot(scans.index(scan))
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269 | colvals = eval(cdict2.get(colmode))
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270 | rowsel = self._cursor["t"][0]
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271 | for j in colvals:
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272 | polmode = "raw"
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273 | jj = colvals.index(j)
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274 | savej = j
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275 | for k in cdict.keys():
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276 | sel = eval(cdict2.get(k))
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277 | j = sel[0]
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278 | eval(cdict.get(k))
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279 | if k == "p":
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280 | which = self._cursor["p"].index(j)
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281 | polmode = self._polmode[which]
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282 | j = which
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283 | j = savej
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284 | if colmode == "p":
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285 | polmode = self._polmode[self._cursor["p"].index(j)]
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286 | #j = jj
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287 | eval(cdict.get(colmode))
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288 | x = None
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289 | y = None
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290 | m = None
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291 | tlab = self._title
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292 | if not self._title:
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293 | tlab = scan._getsourcename(rowsel)
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294 | x,xlab = scan.get_abcissa(rowsel)
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295 | if self._abcissa: xlab = self._abcissa
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296 | if polmode == "stokes":
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297 | y = scan._getstokesspectrum(rowsel)
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298 | elif polmode == "stokes2":
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299 | y = scan._getstokesspectrum(rowsel,True)
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300 | elif polmode == "circular":
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301 | y = scan._stokestopolspectrum(rowsel,False,-1)
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302 | else:
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303 | y = scan._getspectrum(rowsel)
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304 | if self._ordinate:
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305 | ylab = self._ordinate
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306 | else:
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307 | ylab = scan._get_ordinate_label()
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308 | m = scan._getmask(rowsel)
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309 | if self._usermask and self._usermask.count(j):
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310 | m = logical_and(self._usermask, m)
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311 | if self._lmap and len(self._lmap) > 0:
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312 | llab = self._lmap[jj]
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313 | else:
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314 | if colmode == 'p':
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315 | llab = self._get_pollabel(scan, polmode)
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316 | else:
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317 | llab = self._ldict.get(colmode)+' '+str(j)
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318 | self._plotter.set_line(label=llab)
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319 | if self._minmaxx is not None:
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320 | s,e = self._slice_indeces(x)
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321 | x = x[s:e]
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322 | y = y[s:e]
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323 | m = m[s:e]
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324 | if len(x) > 1024 and rcParams['plotter.decimate']:
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325 | fac = len(x)/1024
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326 | x = x[::fac]
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327 | m = m[::fac]
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328 | y = y[::fac]
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329 | self._plotter.plot(x,y,m)
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330 | xlim=[min(x),max(x)]
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331 | if self._minmaxx is not None:
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332 | xlim = self._minmaxx
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333 | self._plotter.axes.set_xlim(xlim)
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334 |
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335 | self._plotter.set_axes('xlabel',xlab)
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336 | self._plotter.set_axes('ylabel',ylab)
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337 | self._plotter.set_axes('title',tlab)
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338 | print_log()
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339 | return
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340 |
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341 | def _plot_other(self,scans,colmode):
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342 | if colmode == self._panelling:
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343 | return
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344 | cdict = {'b':'scan.setbeam(i)',
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345 | 'i':'scan.setif(i)',
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346 | 'p':'scan.setpol(i)'}
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347 | cdict2 = {'b':'self._cursor["b"]',
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348 | 'i':'self._cursor["i"]',
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349 | 'p':'self._cursor["p"]',
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350 | 's': 'scans',
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351 | 't': 'self._cursor["t"]'}
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352 | scan = scans[0]
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353 | n = eval(self._cdict.get(self._panelling))
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354 | ncol=1
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355 | if self._stacking is not None:
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356 | ncol = eval(self._cdict.get(colmode))
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357 | if n > 1:
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358 | ganged = rcParams['plotter.ganged']
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359 | if self._rows and self._cols:
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360 | n = min(n,self._rows*self._cols)
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361 | self._plotter.set_panels(rows=self._rows,cols=self._cols,
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362 | nplots=n,ganged=ganged)
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363 | else:
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364 | self._plotter.set_panels(rows=n,cols=0,nplots=n,ganged=ganged)
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365 | else:
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366 | self._plotter.set_panels()
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367 | panels = self._cursor[self._panelling]
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368 | for i in panels:
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369 | self._plotter.palette(0)
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370 | polmode = "raw"
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371 | ii = self._cursor[self._panelling].index(i)
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372 | if n>1:
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373 | self._plotter.subplot(ii)
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374 | if self._panelling == "p":
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375 | polmode = self._polmode[ii]
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376 |
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377 | eval(cdict.get(self._panelling))
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378 |
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379 | colvals = eval(cdict2.get(colmode))
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380 | for j in colvals:
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381 | rowsel = self._cursor["t"][0]
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382 | jj = colvals.index(j)
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383 | savei = i
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384 | for k in cdict.keys():
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385 | if k != self._panelling:
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386 | sel = eval(cdict2.get(k))
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387 | i = sel[0]
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388 | if k == "p":
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389 | which = self._cursor["p"].index(i)
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390 | polmode = self._polmode[which]
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391 | i = which
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392 | eval(cdict.get(k))
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393 | i = savei
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394 | if colmode == 's':
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395 | scan = j
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396 | elif colmode == 't':
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397 | rowsel = j
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398 | else:
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399 | savei = i
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400 | if colmode == 'p':
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401 | polmode = self._polmode[self._cursor["p"].index(j)]
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402 |
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403 | i = j
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404 | eval(cdict.get(colmode))
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405 | i = savei
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406 | if self._panelling == "p":
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407 | eval(cdict.get(self._panelling))
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408 | x = None
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409 | y = None
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410 | m = None
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411 | x,xlab = scan.get_abcissa(rowsel)
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412 | if self._abcissa: xlab = self._abcissa
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413 | if polmode == "stokes":
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414 | y = scan._getstokesspectrum(rowsel)
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415 | elif polmode == "stokes2":
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416 | y = scan._getstokesspectrum(rowsel,True)
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417 | elif polmode == "circular":
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418 | y = scan._stokestopolspectrum(rowsel,False,-1)
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419 | else:
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420 | y = scan._getspectrum(rowsel)
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421 |
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422 | if self._ordinate:
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423 | ylab = self._ordinate
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424 | else:
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425 | ylab = scan._get_ordinate_label()
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426 | m = scan._getmask(rowsel)
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427 | if self._usermask and self._usermask.count(j):
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428 | m = logical_and(self._usermask, m)
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429 |
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430 | if colmode == 's' or colmode == 't':
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431 | if self._title and len(self._title) > 0:
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432 | tlab = self._title[ii]
|
---|
433 | else:
|
---|
434 | if self._panelling == 'p':
|
---|
435 | tlab = self._get_pollabel(scan, polmode)
|
---|
436 | else:
|
---|
437 | tlab = self._ldict.get(self._panelling)+' '+str(i)
|
---|
438 | if self._lmap and len(self._lmap) > 0:
|
---|
439 | llab = self._lmap[jj]
|
---|
440 | else:
|
---|
441 | llab = scan._getsourcename(rowsel)
|
---|
442 | else:
|
---|
443 | if self._title and len(self._title) > 0:
|
---|
444 | tlab = self._title[ii]
|
---|
445 | else:
|
---|
446 | if self._panelling == 'p':
|
---|
447 | tlab = self._get_pollabel(scan, polmode)
|
---|
448 | else:
|
---|
449 | tlab = self._ldict.get(self._panelling)+' '+str(i)
|
---|
450 | if self._lmap and len(self._lmap) > 0:
|
---|
451 | llab = self._lmap[jj]
|
---|
452 | else:
|
---|
453 | if colmode == 'p':
|
---|
454 | llab = self._get_pollabel(scan, polmode)
|
---|
455 | else:
|
---|
456 | llab = self._ldict.get(colmode)+' '+str(j)
|
---|
457 | self._plotter.set_line(label=llab)
|
---|
458 | if self._minmaxx is not None:
|
---|
459 | s,e = self._slice_indeces(x)
|
---|
460 | x = x[s:e]
|
---|
461 | y = y[s:e]
|
---|
462 | m = m[s:e]
|
---|
463 | if len(x) > 1024 and rcParams['plotter.decimate']:
|
---|
464 | fac = len(x)/1024
|
---|
465 | x = x[::fac]
|
---|
466 | m = m[::fac]
|
---|
467 | y = y[::fac]
|
---|
468 | self._plotter.plot(x,y,m)
|
---|
469 | xlim=[min(x),max(x)]
|
---|
470 | if self._minmaxx is not None:
|
---|
471 | xlim = self._minmaxx
|
---|
472 | self._plotter.axes.set_xlim(xlim)
|
---|
473 |
|
---|
474 | self._plotter.set_axes('xlabel',xlab)
|
---|
475 | self._plotter.set_axes('ylabel',ylab)
|
---|
476 | self._plotter.set_axes('title',tlab)
|
---|
477 |
|
---|
478 | return
|
---|
479 |
|
---|
480 |
|
---|
481 | def set_mode(self, stacking=None, panelling=None):
|
---|
482 | """
|
---|
483 | Set the plots look and feel, i.e. what you want to see on the plot.
|
---|
484 | Parameters:
|
---|
485 | stacking: tell the plotter which variable to plot
|
---|
486 | as line color overlays (default 'pol')
|
---|
487 | panelling: tell the plotter which variable to plot
|
---|
488 | across multiple panels (default 'scan'
|
---|
489 | Note:
|
---|
490 | Valid modes are:
|
---|
491 | 'beam' 'Beam' 'b': Beams
|
---|
492 | 'if' 'IF' 'i': IFs
|
---|
493 | 'pol' 'Pol' 'p': Polarisations
|
---|
494 | 'scan' 'Scan' 's': Scans
|
---|
495 | 'time' 'Time' 't': Times
|
---|
496 | """
|
---|
497 | msg = "Invalid mode"
|
---|
498 | if not self.set_panelling(panelling) or \
|
---|
499 | not self.set_stacking(stacking):
|
---|
500 | if rcParams['verbose']:
|
---|
501 | print msg
|
---|
502 | return
|
---|
503 | else:
|
---|
504 | raise TypeError(msg)
|
---|
505 | if self._data: self.plot()
|
---|
506 | return
|
---|
507 |
|
---|
508 | def set_panelling(self, what=None):
|
---|
509 | mode = what
|
---|
510 | if mode is None:
|
---|
511 | mode = rcParams['plotter.panelling']
|
---|
512 | md = self._translate(mode)
|
---|
513 | if md:
|
---|
514 | self._panelling = md
|
---|
515 | self._title = None
|
---|
516 | return True
|
---|
517 | return False
|
---|
518 |
|
---|
519 | def set_layout(self,rows=None,cols=None):
|
---|
520 | """
|
---|
521 | Set the multi-panel layout, i.e. how many rows and columns plots
|
---|
522 | are visible.
|
---|
523 | Parameters:
|
---|
524 | rows: The number of rows of plots
|
---|
525 | cols: The number of columns of plots
|
---|
526 | Note:
|
---|
527 | If no argument is given, the potter reverts to its auto-plot
|
---|
528 | behaviour.
|
---|
529 | """
|
---|
530 | self._rows = rows
|
---|
531 | self._cols = cols
|
---|
532 | if self._data: self.plot()
|
---|
533 | return
|
---|
534 |
|
---|
535 | def set_stacking(self, what=None):
|
---|
536 | mode = what
|
---|
537 | if mode is None:
|
---|
538 | mode = rcParams['plotter.stacking']
|
---|
539 | md = self._translate(mode)
|
---|
540 | if md:
|
---|
541 | self._stacking = md
|
---|
542 | self._lmap = None
|
---|
543 | return True
|
---|
544 | return False
|
---|
545 |
|
---|
546 | def set_range(self,xstart=None,xend=None,ystart=None,yend=None):
|
---|
547 | """
|
---|
548 | Set the range of interest on the abcissa of the plot
|
---|
549 | Parameters:
|
---|
550 | [x,y]start,[x,y]end: The start and end points of the 'zoom' window
|
---|
551 | Note:
|
---|
552 | These become non-sensical when the unit changes.
|
---|
553 | use plotter.set_range() without parameters to reset
|
---|
554 |
|
---|
555 | """
|
---|
556 | if xstart is None and xend is None:
|
---|
557 | self._minmaxx = None
|
---|
558 | else:
|
---|
559 | self._minmaxx = [xstart,xend]
|
---|
560 | if ystart is None and yend is None:
|
---|
561 | self._minmaxy = None
|
---|
562 | else:
|
---|
563 | self._minmaxy = [ystart,yend]
|
---|
564 | if self._data: self.plot()
|
---|
565 | return
|
---|
566 |
|
---|
567 | def set_legend(self, mp=None):
|
---|
568 | """
|
---|
569 | Specify a mapping for the legend instead of using the default
|
---|
570 | indices:
|
---|
571 | Parameters:
|
---|
572 | mp: a list of 'strings'. This should have the same length
|
---|
573 | as the number of elements on the legend and then maps
|
---|
574 | to the indeces in order. It is possible to uses latex
|
---|
575 | math expression. These have to be enclosed in r'', e.g. r'$x^{2}$'
|
---|
576 |
|
---|
577 | Example:
|
---|
578 | If the data has two IFs/rest frequencies with index 0 and 1
|
---|
579 | for CO and SiO:
|
---|
580 | plotter.set_stacking('i')
|
---|
581 | plotter.set_legend(['CO','SiO'])
|
---|
582 | plotter.plot()
|
---|
583 | plotter.set_legend([r'$^{12}CO$', r'SiO'])
|
---|
584 | """
|
---|
585 | self._lmap = mp
|
---|
586 | if self._data: self.plot()
|
---|
587 | return
|
---|
588 |
|
---|
589 | def set_title(self, title=None):
|
---|
590 | """
|
---|
591 | Set the title of the plot. If multiple panels are plotted,
|
---|
592 | multiple titles have to be specified.
|
---|
593 | Example:
|
---|
594 | # two panels are visible on the plotter
|
---|
595 | plotter.set_title(["First Panel","Second Panel"])
|
---|
596 | """
|
---|
597 | self._title = title
|
---|
598 | if self._data: self.plot()
|
---|
599 | return
|
---|
600 |
|
---|
601 | def set_ordinate(self, ordinate=None):
|
---|
602 | """
|
---|
603 | Set the y-axis label of the plot. If multiple panels are plotted,
|
---|
604 | multiple labels have to be specified.
|
---|
605 | Example:
|
---|
606 | # two panels are visible on the plotter
|
---|
607 | plotter.set_ordinate(["First Y-Axis","Second Y-Axis"])
|
---|
608 | """
|
---|
609 | self._ordinate = ordinate
|
---|
610 | if self._data: self.plot()
|
---|
611 | return
|
---|
612 |
|
---|
613 | def set_abcissa(self, abcissa=None):
|
---|
614 | """
|
---|
615 | Set the x-axis label of the plot. If multiple panels are plotted,
|
---|
616 | multiple labels have to be specified.
|
---|
617 | Example:
|
---|
618 | # two panels are visible on the plotter
|
---|
619 | plotter.set_ordinate(["First X-Axis","Second X-Axis"])
|
---|
620 | """
|
---|
621 | self._abcissa = abcissa
|
---|
622 | if self._data: self.plot()
|
---|
623 | return
|
---|
624 |
|
---|
625 | def set_colors(self, colormap):
|
---|
626 | """
|
---|
627 | Set the colors to be used. The plotter will cycle through
|
---|
628 | these colors when lines are overlaid (stacking mode).
|
---|
629 | Example:
|
---|
630 | plotter.set_colors("red green blue")
|
---|
631 | # If for example four lines are overlaid e.g I Q U V
|
---|
632 | # 'I' will be 'red', 'Q' will be 'green', U will be 'blue'
|
---|
633 | # and 'V' will be 'red' again.
|
---|
634 | """
|
---|
635 | if isinstance(colormap,str):
|
---|
636 | colormap = colormap.split()
|
---|
637 | self._plotter.palette(0,colormap=colormap)
|
---|
638 | if self._data: self.plot()
|
---|
639 |
|
---|
640 | def set_linestyles(self, linestyles):
|
---|
641 | """
|
---|
642 | Set the linestyles to be used. The plotter will cycle through
|
---|
643 | these linestyles when lines are overlaid (stacking mode) AND
|
---|
644 | only one color has been set.
|
---|
645 | Parameters:
|
---|
646 | linestyles: a list of linestyles to use.
|
---|
647 | 'line', 'dashed', 'dotted', 'dashdot',
|
---|
648 | 'dashdotdot' and 'dashdashdot' are
|
---|
649 | possible
|
---|
650 |
|
---|
651 | Example:
|
---|
652 | plotter.set_colors("black")
|
---|
653 | plotter.set_linestyles("line dashed dotted dashdot")
|
---|
654 | # If for example four lines are overlaid e.g I Q U V
|
---|
655 | # 'I' will be 'solid', 'Q' will be 'dashed',
|
---|
656 | # U will be 'dotted' and 'V' will be 'dashdot'.
|
---|
657 | """
|
---|
658 | if isinstance(linestyles,str):
|
---|
659 | linestyles = linestyles.split()
|
---|
660 | self._plotter.palette(color=0,linestyle=0,linestyles=linestyles)
|
---|
661 | if self._data: self.plot()
|
---|
662 |
|
---|
663 | def save(self, filename=None, orientation=None, dpi=None):
|
---|
664 | """
|
---|
665 | Save the plot to a file. The know formats are 'png', 'ps', 'eps'.
|
---|
666 | Parameters:
|
---|
667 | filename: The name of the output file. This is optional
|
---|
668 | and autodetects the image format from the file
|
---|
669 | suffix. If non filename is specified a file
|
---|
670 | called 'yyyymmdd_hhmmss.png' is created in the
|
---|
671 | current directory.
|
---|
672 | orientation: optional parameter for postscript only (not eps).
|
---|
673 | 'landscape', 'portrait' or None (default) are valid.
|
---|
674 | If None is choosen for 'ps' output, the plot is
|
---|
675 | automatically oriented to fill the page.
|
---|
676 | dpi: The dpi of the output non-ps plot
|
---|
677 | """
|
---|
678 | self._plotter.save(filename,orientation,dpi)
|
---|
679 | return
|
---|
680 |
|
---|
681 | def set_cursor(self, row=None,beam=None,IF=None,pol=None, refresh=True):
|
---|
682 | """
|
---|
683 | Specify a 'cursor' for plotting selected spectra. Time (rows),
|
---|
684 | Beam, IF, Polarisation ranges can be specified.
|
---|
685 | Parameters:
|
---|
686 | Default for all paramaters is to select all available
|
---|
687 | row: selects the rows (time stamps) to be plotted, this has
|
---|
688 | to be a vector of row indices, e.g. row=[0,2,5] or row=[2]
|
---|
689 | beam: select a range of beams
|
---|
690 | IF: select a range of IFs
|
---|
691 | pol: select Polarisations for plotting these can be by index
|
---|
692 | (raw polarisations (default)) or by names any of:
|
---|
693 | ["I", "Q", "U", "V"] or
|
---|
694 | ["I", "Plinear", "Pangle", "V"] or
|
---|
695 | ["XX", "YY", "Real(XY)", "Imag(XY)"] or
|
---|
696 | ["RR", "LL"]
|
---|
697 | Example:
|
---|
698 | plotter.set_mode('pol','time')
|
---|
699 | plotter.plot(myscan) # plots all raw polarisations colour stacked
|
---|
700 | plotter.set_cursor(pol=["I"]) # plot "I" only for all rows
|
---|
701 | # plot "I" only for two time stamps row=0 and row=2
|
---|
702 | plotter.set_cursor(row=[0,2],pol=["I"])
|
---|
703 |
|
---|
704 | Note:
|
---|
705 | Be careful to select only exisiting polarisations.
|
---|
706 | """
|
---|
707 | if not self._data:
|
---|
708 | msg = "Can only set cursor after a first call to plot()"
|
---|
709 | if rcParams['verbose']:
|
---|
710 | print msg
|
---|
711 | return
|
---|
712 | else:
|
---|
713 | raise RuntimeError(msg)
|
---|
714 |
|
---|
715 | n = self._data[0].nrow()
|
---|
716 | if row is None:
|
---|
717 | self._cursor["t"] = range(n)
|
---|
718 | else:
|
---|
719 | for i in row:
|
---|
720 | if i < 0 or i >= n:
|
---|
721 | msg = "Row index '%d' out of range" % i
|
---|
722 | if rcParams['verbose']:
|
---|
723 | print msg
|
---|
724 | return
|
---|
725 | else:
|
---|
726 | raise IndexError(msg)
|
---|
727 | self._cursor["t"] = row
|
---|
728 |
|
---|
729 | n = self._data[0].nbeam()
|
---|
730 | if beam is None:
|
---|
731 | self._cursor["b"] = range(n)
|
---|
732 | else:
|
---|
733 | for i in beam:
|
---|
734 | if i < 0 or i >= n:
|
---|
735 | msg = "Beam index '%d' out of range" % i
|
---|
736 | if rcParams['verbose']:
|
---|
737 | print msg
|
---|
738 | return
|
---|
739 | else:
|
---|
740 | raise IndexError(msg)
|
---|
741 |
|
---|
742 | self._cursor["b"] = beam
|
---|
743 |
|
---|
744 | n = self._data[0].nif()
|
---|
745 | if IF is None:
|
---|
746 | self._cursor["i"] = range(n)
|
---|
747 | else:
|
---|
748 | for i in IF:
|
---|
749 | if i < 0 or i >= n:
|
---|
750 | msg = "IF index '%d' out of range" %i
|
---|
751 | if rcParams['verbose']:
|
---|
752 | print msg
|
---|
753 | return
|
---|
754 | else:
|
---|
755 | raise IndexError(msg)
|
---|
756 | self._cursor["i"] = IF
|
---|
757 |
|
---|
758 | n = self._data[0].npol()
|
---|
759 | dstokes = {"I":0,"Q":1,"U":2,"V":3}
|
---|
760 | dstokes2 = {"I":0,"Plinear":1,"Pangle":2,"V":3}
|
---|
761 | draw = {"XX":0, "YY":1,"Real(XY)":2, "Imag(XY)":3}
|
---|
762 | dcirc = { "RR":0,"LL":1}#,"Real(RL)":2,"Imag(RL)":3}
|
---|
763 |
|
---|
764 | if pol is None:
|
---|
765 | self._cursor["p"] = range(n)
|
---|
766 | self._polmode = ["raw" for i in range(n)]
|
---|
767 | else:
|
---|
768 | if isinstance(pol,str):
|
---|
769 | pol = pol.split()
|
---|
770 | polmode = []
|
---|
771 | pols = []
|
---|
772 | for i in pol:
|
---|
773 | if isinstance(i,str):
|
---|
774 | if draw.has_key(i):
|
---|
775 | pols.append(draw.get(i))
|
---|
776 | polmode.append("raw")
|
---|
777 | elif dstokes.has_key(i):
|
---|
778 | pols.append(dstokes.get(i))
|
---|
779 | polmode.append("stokes")
|
---|
780 | elif dstokes2.has_key(i):
|
---|
781 | pols.append(dstokes2.get(i))
|
---|
782 | polmode.append("stokes2")
|
---|
783 | elif dcirc.has_key(i):
|
---|
784 | pols.append(dcirc.get(i))
|
---|
785 | polmode.append("circular")
|
---|
786 | else:
|
---|
787 | msg = "Pol type '%s' not valid" %i
|
---|
788 | if rcParams['verbose']:
|
---|
789 | print msg
|
---|
790 | return
|
---|
791 | else:
|
---|
792 | raise TypeError(msg)
|
---|
793 | elif 0 > i >= n:
|
---|
794 | print "Pol index '%d' out of range" %i
|
---|
795 | if rcParams['verbose']:
|
---|
796 | print msg
|
---|
797 | return
|
---|
798 | else:
|
---|
799 | raise IndexError(msg)
|
---|
800 | else:
|
---|
801 | pols.append(i)
|
---|
802 | polmode.append("raw")
|
---|
803 | self._cursor["p"] = pols
|
---|
804 | self._polmode = polmode
|
---|
805 | if self._data and refresh: self.plot()
|
---|
806 |
|
---|
807 | def set_mask(self, mask=None, pol=None):
|
---|
808 | """
|
---|
809 | Set a plotting mask for a specific polarization.
|
---|
810 | This is useful for masking out "noise" Pangle outside a source.
|
---|
811 | Parameters:
|
---|
812 | mask: a mask from scantable.create_mask
|
---|
813 | pol: the polarisation to apply the mask to, e.g
|
---|
814 | "Pangle" or "XX" etc.
|
---|
815 | Example:
|
---|
816 | """
|
---|
817 | if not self._data:
|
---|
818 | msg = "Can only set cursor after a first call to plot()"
|
---|
819 | if rcParams['verbose']:
|
---|
820 | print msg
|
---|
821 | return
|
---|
822 | else:
|
---|
823 | raise RuntimeError(msg)
|
---|
824 | if isinstance(mask, array):
|
---|
825 | self._usermask = mask
|
---|
826 | if isinstance(mask, list):
|
---|
827 | self._usermask = array(mask)
|
---|
828 | if mask is None and pol is None:
|
---|
829 | self._usermask = None
|
---|
830 | self._usermaskspectra = None
|
---|
831 |
|
---|
832 | dstokes = {"I":0,"Q":1,"U":2,"V":3}
|
---|
833 | dstokes2 = {"I":0,"Plinear":1,"Pangle":2,"V":3}
|
---|
834 | draw = {"XX":0, "YY":1,"Real(XY)":2, "Imag(XY)":3}
|
---|
835 | dcirc = { "RR":0,"LL":1}#,"Real(RL)":2,"Imag(RL)":3}
|
---|
836 | if isinstance(pol, str):
|
---|
837 | pol = pol.split()
|
---|
838 | if isinstance(pol, list):
|
---|
839 | if isinstance(pol[0], str):
|
---|
840 | pass
|
---|
841 | else:
|
---|
842 | cpos = self._cursor[self._stacking]
|
---|
843 | self._usermaskspectra =filter(lambda i: filter(lambda j: j==i ,cpos),pol)
|
---|
844 | else:
|
---|
845 | return
|
---|
846 | self.plot()
|
---|
847 |
|
---|
848 | def _get_pollabel(self, scan, polmode):
|
---|
849 | tlab = ""
|
---|
850 | if polmode == "stokes":
|
---|
851 | tlab = scan._getpolarizationlabel(0,1,0)
|
---|
852 | elif polmode == "stokes2":
|
---|
853 | tlab = scan._getpolarizationlabel(0,1,1)
|
---|
854 | elif polmode == "circular":
|
---|
855 | tlab = scan._getpolarizationlabel(0,0,0)
|
---|
856 | else:
|
---|
857 | tlab = scan._getpolarizationlabel(1,0,0)
|
---|
858 | return tlab
|
---|
859 |
|
---|
860 | def _slice_indeces(self, data):
|
---|
861 | mn = self._minmaxx[0]
|
---|
862 | mx = self._minmaxx[1]
|
---|
863 | asc = data[0] < data[-1]
|
---|
864 | start=0
|
---|
865 | end = len(data)-1
|
---|
866 | inc = 1
|
---|
867 | if not asc:
|
---|
868 | start = len(data)-1
|
---|
869 | end = 0
|
---|
870 | inc = -1
|
---|
871 | # find min index
|
---|
872 | while data[start] < mn:
|
---|
873 | start+= inc
|
---|
874 | # find max index
|
---|
875 | while data[end] > mx:
|
---|
876 | end-=inc
|
---|
877 | end +=1
|
---|
878 | if start > end:
|
---|
879 | return end,start
|
---|
880 | return start,end
|
---|
881 |
|
---|
882 | def _reset(self):
|
---|
883 | self._usermask = None
|
---|
884 | self._usermaskspectra = None
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885 | self.set_cursor(refresh=False)
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