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] |
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433 | else: |
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434 | if self._panelling == 'p': |
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435 | tlab = self._get_pollabel(scan, polmode) |
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436 | else: |
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437 | tlab = self._ldict.get(self._panelling)+' '+str(i) |
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438 | if self._lmap and len(self._lmap) > 0: |
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439 | llab = self._lmap[jj] |
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440 | else: |
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441 | llab = scan._getsourcename(rowsel) |
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442 | else: |
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443 | if self._title and len(self._title) > 0: |
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444 | tlab = self._title[ii] |
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445 | else: |
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446 | if self._panelling == 'p': |
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447 | tlab = self._get_pollabel(scan, polmode) |
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448 | else: |
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449 | tlab = self._ldict.get(self._panelling)+' '+str(i) |
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450 | if self._lmap and len(self._lmap) > 0: |
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451 | llab = self._lmap[jj] |
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452 | else: |
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453 | if colmode == 'p': |
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454 | llab = self._get_pollabel(scan, polmode) |
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455 | else: |
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456 | llab = self._ldict.get(colmode)+' '+str(j) |
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457 | self._plotter.set_line(label=llab) |
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458 | if self._minmaxx is not None: |
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459 | s,e = self._slice_indeces(x) |
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460 | x = x[s:e] |
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461 | y = y[s:e] |
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462 | m = m[s:e] |
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463 | if len(x) > 1024 and rcParams['plotter.decimate']: |
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464 | fac = len(x)/1024 |
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465 | x = x[::fac] |
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466 | m = m[::fac] |
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467 | y = y[::fac] |
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468 | self._plotter.plot(x,y,m) |
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469 | xlim=[min(x),max(x)] |
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470 | if self._minmaxx is not None: |
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471 | xlim = self._minmaxx |
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472 | self._plotter.axes.set_xlim(xlim) |
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473 | |
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474 | self._plotter.set_axes('xlabel',xlab) |
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475 | self._plotter.set_axes('ylabel',ylab) |
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476 | self._plotter.set_axes('title',tlab) |
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477 | |
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478 | return |
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479 | |
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480 | |
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481 | def set_mode(self, stacking=None, panelling=None): |
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482 | """ |
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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 |
---|
885 | self.set_cursor(refresh=False) |
---|