1 | from asap.parameters import rcParams |
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2 | from asap.selector import selector |
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3 | from asap.scantable import scantable |
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4 | from asap.logging import asaplog, asaplog_post_dec |
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5 | import matplotlib.axes |
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6 | from matplotlib.font_manager import FontProperties |
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7 | from matplotlib.text import Text |
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8 | |
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9 | import re |
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10 | |
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11 | class asapplotter: |
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12 | """ |
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13 | The ASAP plotter. |
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14 | By default the plotter is set up to plot polarisations |
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15 | 'colour stacked' and scantables across panels. |
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16 | |
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17 | .. note:: |
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18 | |
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19 | Currenly it only plots 'spectra' not Tsys or |
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20 | other variables. |
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21 | |
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22 | """ |
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23 | def __init__(self, visible=None , **kwargs): |
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24 | self._visible = rcParams['plotter.gui'] |
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25 | if visible is not None: |
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26 | self._visible = visible |
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27 | self._plotter = self._newplotter(**kwargs) |
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28 | # additional tool bar |
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29 | self._plotter.figmgr.casabar=self._newcasabar() |
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30 | |
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31 | self._panelling = None |
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32 | self._stacking = None |
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33 | self.set_panelling() |
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34 | self.set_stacking() |
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35 | self._rows = None |
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36 | self._cols = None |
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37 | self._autoplot = False |
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38 | self._minmaxx = None |
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39 | self._minmaxy = None |
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40 | self._datamask = None |
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41 | self._data = None |
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42 | self._lmap = None |
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43 | self._title = None |
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44 | self._ordinate = None |
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45 | self._abcissa = None |
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46 | self._abcunit = None |
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47 | self._usermask = [] |
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48 | self._maskselection = None |
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49 | self._selection = selector() |
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50 | self._hist = rcParams['plotter.histogram'] |
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51 | self._fp = FontProperties() |
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52 | self._panellayout = self.set_panellayout(refresh=False) |
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53 | self._offset = None |
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54 | self._rowcount = 0 |
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55 | self._panelcnt = 0 |
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56 | |
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57 | def _translate(self, instr): |
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58 | keys = "s b i p t r".split() |
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59 | if isinstance(instr, str): |
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60 | for key in keys: |
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61 | if instr.lower().startswith(key): |
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62 | return key |
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63 | return None |
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64 | |
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65 | def _newplotter(self, **kwargs): |
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66 | backend=matplotlib.get_backend() |
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67 | if not self._visible: |
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68 | from asap.asaplot import asaplot |
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69 | elif backend == 'TkAgg': |
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70 | from asap.asaplotgui import asaplotgui as asaplot |
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71 | elif backend == 'Qt4Agg': |
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72 | from asap.asaplotgui_qt4 import asaplotgui as asaplot |
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73 | elif backend == 'GTkAgg': |
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74 | from asap.asaplotgui_gtk import asaplotgui as asaplot |
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75 | else: |
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76 | from asap.asaplot import asaplot |
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77 | return asaplot(**kwargs) |
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78 | |
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79 | def _newcasabar(self): |
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80 | backend=matplotlib.get_backend() |
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81 | if self._visible and backend == "TkAgg": |
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82 | from asap.casatoolbar import CustomToolbarTkAgg |
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83 | return CustomToolbarTkAgg(self) |
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84 | else: return None |
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85 | |
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86 | @asaplog_post_dec |
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87 | def plot(self, scan=None): |
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88 | """ |
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89 | Plot a scantable. |
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90 | Parameters: |
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91 | scan: a scantable |
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92 | Note: |
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93 | If a scantable was specified in a previous call |
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94 | to plot, no argument has to be given to 'replot' |
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95 | NO checking is done that the abcissas of the scantable |
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96 | are consistent e.g. all 'channel' or all 'velocity' etc. |
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97 | """ |
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98 | self._rowcount = self._panelcnt = 0 |
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99 | if self._plotter.is_dead: |
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100 | if hasattr(self._plotter.figmgr,'casabar'): |
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101 | del self._plotter.figmgr.casabar |
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102 | self._plotter = self._newplotter() |
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103 | self._plotter.figmgr.casabar=self._newcasabar() |
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104 | self._plotter.hold() |
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105 | self._plotter.clear() |
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106 | if not self._data and not scan: |
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107 | msg = "Input is not a scantable" |
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108 | raise TypeError(msg) |
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109 | if scan: |
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110 | self.set_data(scan, refresh=False) |
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111 | self._plot(self._data) |
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112 | if self._minmaxy is not None: |
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113 | self._plotter.set_limits(ylim=self._minmaxy) |
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114 | if self._plotter.figmgr.casabar: self._plotter.figmgr.casabar.enable_button() |
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115 | self._plotter.release() |
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116 | self._plotter.tidy() |
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117 | self._plotter.show(hardrefresh=False) |
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118 | return |
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119 | |
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120 | def gca(self): |
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121 | return self._plotter.figure.gca() |
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122 | |
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123 | def refresh(self): |
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124 | """Do a soft refresh""" |
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125 | self._plotter.figure.show() |
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126 | |
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127 | def create_mask(self, nwin=1, panel=0, color=None): |
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128 | """ |
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129 | Interactively define a mask.It retruns a mask that is equivalent to |
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130 | the one created manually with scantable.create_mask. |
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131 | Parameters: |
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132 | nwin: The number of mask windows to create interactively |
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133 | default is 1. |
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134 | panel: Which panel to use for mask selection. This is useful |
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135 | if different IFs are spread over panels (default 0) |
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136 | """ |
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137 | if self._data is None: |
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138 | return [] |
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139 | outmask = [] |
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140 | self._plotter.subplot(panel) |
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141 | xmin, xmax = self._plotter.axes.get_xlim() |
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142 | marg = 0.05*(xmax-xmin) |
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143 | self._plotter.axes.set_xlim(xmin-marg, xmax+marg) |
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144 | self.refresh() |
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145 | |
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146 | def cleanup(lines=False, texts=False, refresh=False): |
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147 | if lines: |
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148 | del self._plotter.axes.lines[-1] |
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149 | if texts: |
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150 | del self._plotter.axes.texts[-1] |
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151 | if refresh: |
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152 | self.refresh() |
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153 | |
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154 | for w in xrange(nwin): |
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155 | wpos = [] |
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156 | self.text(0.05,1.0, "Add start boundary", |
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157 | coords="relative", fontsize=10) |
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158 | point = self._plotter.get_point() |
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159 | cleanup(texts=True) |
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160 | if point is None: |
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161 | continue |
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162 | wpos.append(point[0]) |
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163 | self.axvline(wpos[0], color=color) |
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164 | self.text(0.05,1.0, "Add end boundary", coords="relative", fontsize=10) |
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165 | point = self._plotter.get_point() |
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166 | cleanup(texts=True, lines=True) |
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167 | if point is None: |
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168 | self.refresh() |
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169 | continue |
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170 | wpos.append(point[0]) |
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171 | self.axvspan(wpos[0], wpos[1], alpha=0.1, |
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172 | edgecolor=color, facecolor=color) |
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173 | ymin, ymax = self._plotter.axes.get_ylim() |
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174 | outmask.append(wpos) |
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175 | |
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176 | self._plotter.axes.set_xlim(xmin, xmax) |
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177 | self.refresh() |
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178 | if len(outmask) > 0: |
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179 | return self._data.create_mask(*outmask) |
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180 | return [] |
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181 | |
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182 | # forwards to matplotlib axes |
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183 | def text(self, *args, **kwargs): |
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184 | if kwargs.has_key("interactive"): |
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185 | if kwargs.pop("interactive"): |
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186 | pos = self._plotter.get_point() |
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187 | args = tuple(pos)+args |
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188 | self._axes_callback("text", *args, **kwargs) |
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189 | |
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190 | text.__doc__ = matplotlib.axes.Axes.text.__doc__ |
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191 | |
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192 | def arrow(self, *args, **kwargs): |
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193 | if kwargs.has_key("interactive"): |
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194 | if kwargs.pop("interactive"): |
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195 | pos = self._plotter.get_region() |
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196 | dpos = (pos[0][0], pos[0][1], |
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197 | pos[1][0]-pos[0][0], |
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198 | pos[1][1] - pos[0][1]) |
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199 | args = dpos + args |
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200 | self._axes_callback("arrow", *args, **kwargs) |
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201 | |
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202 | arrow.__doc__ = matplotlib.axes.Axes.arrow.__doc__ |
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203 | |
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204 | def annotate(self, text, xy=None, xytext=None, **kwargs): |
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205 | if kwargs.has_key("interactive"): |
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206 | if kwargs.pop("interactive"): |
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207 | xy = self._plotter.get_point() |
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208 | xytext = self._plotter.get_point() |
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209 | if not kwargs.has_key("arrowprops"): |
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210 | kwargs["arrowprops"] = dict(arrowstyle="->") |
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211 | self._axes_callback("annotate", text, xy, xytext, **kwargs) |
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212 | |
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213 | annotate.__doc__ = matplotlib.axes.Axes.annotate.__doc__ |
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214 | |
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215 | def axvline(self, *args, **kwargs): |
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216 | if kwargs.has_key("interactive"): |
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217 | if kwargs.pop("interactive"): |
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218 | pos = self._plotter.get_point() |
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219 | args = (pos[0],)+args |
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220 | self._axes_callback("axvline", *args, **kwargs) |
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221 | |
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222 | axvline.__doc__ = matplotlib.axes.Axes.axvline.__doc__ |
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223 | |
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224 | def axhline(self, *args, **kwargs): |
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225 | if kwargs.has_key("interactive"): |
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226 | if kwargs.pop("interactive"): |
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227 | pos = self._plotter.get_point() |
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228 | args = (pos[1],)+args |
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229 | self._axes_callback("axhline", *args, **kwargs) |
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230 | |
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231 | axhline.__doc__ = matplotlib.axes.Axes.axhline.__doc__ |
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232 | |
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233 | def axvspan(self, *args, **kwargs): |
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234 | if kwargs.has_key("interactive"): |
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235 | if kwargs.pop("interactive"): |
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236 | pos = self._plotter.get_region() |
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237 | dpos = (pos[0][0], pos[1][0]) |
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238 | args = dpos + args |
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239 | self._axes_callback("axvspan", *args, **kwargs) |
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240 | # hack to preventy mpl from redrawing the patch |
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241 | # it seem to convert the patch into lines on every draw. |
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242 | # This doesn't happen in a test script??? |
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243 | #del self._plotter.axes.patches[-1] |
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244 | |
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245 | axvspan.__doc__ = matplotlib.axes.Axes.axvspan.__doc__ |
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246 | |
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247 | def axhspan(self, *args, **kwargs): |
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248 | if kwargs.has_key("interactive"): |
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249 | if kwargs.pop("interactive"): |
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250 | pos = self._plotter.get_region() |
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251 | dpos = (pos[0][1], pos[1][1]) |
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252 | args = dpos + args |
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253 | self._axes_callback("axhspan", *args, **kwargs) |
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254 | # hack to preventy mpl from redrawing the patch |
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255 | # it seem to convert the patch into lines on every draw. |
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256 | # This doesn't happen in a test script??? |
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257 | #del self._plotter.axes.patches[-1] |
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258 | |
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259 | axhspan.__doc__ = matplotlib.axes.Axes.axhspan.__doc__ |
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260 | |
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261 | def _axes_callback(self, axesfunc, *args, **kwargs): |
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262 | panel = 0 |
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263 | if kwargs.has_key("panel"): |
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264 | panel = kwargs.pop("panel") |
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265 | coords = None |
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266 | if kwargs.has_key("coords"): |
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267 | coords = kwargs.pop("coords") |
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268 | if coords.lower() == 'world': |
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269 | kwargs["transform"] = self._plotter.axes.transData |
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270 | elif coords.lower() == 'relative': |
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271 | kwargs["transform"] = self._plotter.axes.transAxes |
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272 | self._plotter.subplot(panel) |
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273 | self._plotter.axes.set_autoscale_on(False) |
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274 | getattr(self._plotter.axes, axesfunc)(*args, **kwargs) |
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275 | self._plotter.show(False) |
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276 | self._plotter.axes.set_autoscale_on(True) |
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277 | # end matplotlib.axes fowarding functions |
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278 | |
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279 | @asaplog_post_dec |
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280 | def set_data(self, scan, refresh=True): |
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281 | """ |
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282 | Set a scantable to plot. |
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283 | Parameters: |
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284 | scan: a scantable |
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285 | refresh: True (default) or False. If True, the plot is |
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286 | replotted based on the new parameter setting(s). |
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287 | Otherwise,the parameter(s) are set without replotting. |
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288 | Note: |
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289 | The user specified masks and data selections will be reset |
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290 | if a new scantable is set. This method should be called before |
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291 | setting data selections (set_selection) and/or masks (set_mask). |
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292 | """ |
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293 | from asap import scantable |
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294 | if isinstance(scan, scantable): |
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295 | if self._data is not None: |
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296 | if scan != self._data: |
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297 | self._data = scan |
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298 | # reset |
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299 | self._reset() |
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300 | msg = "A new scantable is set to the plotter. "\ |
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301 | "The masks and data selections are reset." |
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302 | asaplog.push( msg ) |
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303 | else: |
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304 | self._data = scan |
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305 | self._reset() |
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306 | else: |
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307 | msg = "Input is not a scantable" |
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308 | raise TypeError(msg) |
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309 | |
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310 | # ranges become invalid when unit changes |
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311 | if self._abcunit and self._abcunit != self._data.get_unit(): |
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312 | self._minmaxx = None |
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313 | self._minmaxy = None |
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314 | self._abcunit = self._data.get_unit() |
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315 | self._datamask = None |
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316 | if refresh: self.plot() |
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317 | |
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318 | @asaplog_post_dec |
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319 | def set_mode(self, stacking=None, panelling=None, refresh=True): |
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320 | """ |
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321 | Set the plots look and feel, i.e. what you want to see on the plot. |
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322 | Parameters: |
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323 | stacking: tell the plotter which variable to plot |
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324 | as line colour overlays (default 'pol') |
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325 | panelling: tell the plotter which variable to plot |
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326 | across multiple panels (default 'scan' |
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327 | refresh: True (default) or False. If True, the plot is |
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328 | replotted based on the new parameter setting(s). |
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329 | Otherwise,the parameter(s) are set without replotting. |
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330 | Note: |
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331 | Valid modes are: |
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332 | 'beam' 'Beam' 'b': Beams |
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333 | 'if' 'IF' 'i': IFs |
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334 | 'pol' 'Pol' 'p': Polarisations |
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335 | 'scan' 'Scan' 's': Scans |
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336 | 'time' 'Time' 't': Times |
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337 | """ |
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338 | msg = "Invalid mode" |
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339 | if not self.set_panelling(panelling) or \ |
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340 | not self.set_stacking(stacking): |
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341 | raise TypeError(msg) |
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342 | if self._panelling == 'r': |
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343 | self._stacking = '_r' |
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344 | elif self._stacking == 'r': |
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345 | self._panelling = '_r' |
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346 | if refresh and self._data: self.plot(self._data) |
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347 | return |
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348 | |
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349 | def set_panelling(self, what=None): |
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350 | """Set the 'panelling' mode i.e. which type of spectra should be |
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351 | spread across different panels. |
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352 | """ |
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353 | |
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354 | mode = what |
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355 | if mode is None: |
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356 | mode = rcParams['plotter.panelling'] |
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357 | md = self._translate(mode) |
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358 | if md: |
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359 | self._panelling = md |
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360 | self._title = None |
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361 | if md == 'r': |
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362 | self._stacking = '_r' |
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363 | return True |
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364 | return False |
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365 | |
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366 | def set_layout(self,rows=None,cols=None,refresh=True): |
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367 | """ |
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368 | Set the multi-panel layout, i.e. how many rows and columns plots |
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369 | are visible. |
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370 | Parameters: |
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371 | rows: The number of rows of plots |
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372 | cols: The number of columns of plots |
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373 | refresh: True (default) or False. If True, the plot is |
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374 | replotted based on the new parameter setting(s). |
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375 | Otherwise,the parameter(s) are set without replotting. |
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376 | Note: |
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377 | If no argument is given, the potter reverts to its auto-plot |
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378 | behaviour. |
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379 | """ |
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380 | self._rows = rows |
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381 | self._cols = cols |
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382 | if refresh and self._data: self.plot(self._data) |
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383 | return |
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384 | |
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385 | def set_stacking(self, what=None): |
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386 | """Set the 'stacking' mode i.e. which type of spectra should be |
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387 | overlayed. |
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388 | """ |
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389 | mode = what |
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390 | if mode is None: |
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391 | mode = rcParams['plotter.stacking'] |
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392 | md = self._translate(mode) |
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393 | if md: |
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394 | self._stacking = md |
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395 | self._lmap = None |
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396 | if md == 'r': |
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397 | self._panelling = '_r' |
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398 | return True |
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399 | return False |
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400 | |
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401 | def set_range(self,xstart=None,xend=None,ystart=None,yend=None,refresh=True, offset=None): |
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402 | """ |
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403 | Set the range of interest on the abcissa of the plot |
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404 | Parameters: |
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405 | [x,y]start,[x,y]end: The start and end points of the 'zoom' window |
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406 | refresh: True (default) or False. If True, the plot is |
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407 | replotted based on the new parameter setting(s). |
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408 | Otherwise,the parameter(s) are set without replotting. |
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409 | offset: shift the abcissa by the given amount. The abcissa label will |
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410 | have '(relative)' appended to it. |
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411 | Note: |
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412 | These become non-sensical when the unit changes. |
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413 | use plotter.set_range() without parameters to reset |
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414 | |
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415 | """ |
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416 | self._offset = offset |
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417 | if xstart is None and xend is None: |
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418 | self._minmaxx = None |
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419 | else: |
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420 | self._minmaxx = [xstart,xend] |
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421 | if ystart is None and yend is None: |
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422 | self._minmaxy = None |
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423 | else: |
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424 | self._minmaxy = [ystart,yend] |
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425 | if refresh and self._data: self.plot(self._data) |
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426 | return |
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427 | |
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428 | def set_legend(self, mp=None, fontsize = None, mode = 0, refresh=True): |
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429 | """ |
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430 | Specify a mapping for the legend instead of using the default |
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431 | indices: |
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432 | Parameters: |
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433 | mp: a list of 'strings'. This should have the same length |
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434 | as the number of elements on the legend and then maps |
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435 | to the indeces in order. It is possible to uses latex |
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436 | math expression. These have to be enclosed in r'', |
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437 | e.g. r'$x^{2}$' |
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438 | fontsize: The font size of the label (default None) |
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439 | mode: where to display the legend |
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440 | Any other value for loc else disables the legend: |
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441 | 0: auto |
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442 | 1: upper right |
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443 | 2: upper left |
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444 | 3: lower left |
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445 | 4: lower right |
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446 | 5: right |
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447 | 6: center left |
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448 | 7: center right |
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449 | 8: lower center |
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450 | 9: upper center |
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451 | 10: center |
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452 | refresh: True (default) or False. If True, the plot is |
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453 | replotted based on the new parameter setting(s). |
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454 | Otherwise,the parameter(s) are set without replotting. |
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455 | |
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456 | Example: |
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457 | If the data has two IFs/rest frequencies with index 0 and 1 |
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458 | for CO and SiO: |
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459 | plotter.set_stacking('i') |
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460 | plotter.set_legend(['CO','SiO']) |
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461 | plotter.plot() |
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462 | plotter.set_legend([r'$^{12}CO$', r'SiO']) |
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463 | """ |
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464 | self._lmap = mp |
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465 | self._plotter.legend(mode) |
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466 | if isinstance(fontsize, int): |
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467 | from matplotlib import rc as rcp |
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468 | rcp('legend', fontsize=fontsize) |
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469 | if refresh and self._data: self.plot(self._data) |
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470 | return |
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471 | |
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472 | def set_title(self, title=None, fontsize=None, refresh=True): |
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473 | """ |
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474 | Set the title of the plot. If multiple panels are plotted, |
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475 | multiple titles have to be specified. |
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476 | Parameters: |
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477 | refresh: True (default) or False. If True, the plot is |
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478 | replotted based on the new parameter setting(s). |
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479 | Otherwise,the parameter(s) are set without replotting. |
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480 | Example: |
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481 | # two panels are visible on the plotter |
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482 | plotter.set_title(["First Panel","Second Panel"]) |
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483 | """ |
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484 | self._title = title |
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485 | if isinstance(fontsize, int): |
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486 | from matplotlib import rc as rcp |
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487 | rcp('axes', titlesize=fontsize) |
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488 | if refresh and self._data: self.plot(self._data) |
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489 | return |
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490 | |
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491 | def set_ordinate(self, ordinate=None, fontsize=None, refresh=True): |
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492 | """ |
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493 | Set the y-axis label of the plot. If multiple panels are plotted, |
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494 | multiple labels have to be specified. |
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495 | Parameters: |
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496 | ordinate: a list of ordinate labels. None (default) let |
---|
497 | data determine the labels |
---|
498 | refresh: True (default) or False. If True, the plot is |
---|
499 | replotted based on the new parameter setting(s). |
---|
500 | Otherwise,the parameter(s) are set without replotting. |
---|
501 | Example: |
---|
502 | # two panels are visible on the plotter |
---|
503 | plotter.set_ordinate(["First Y-Axis","Second Y-Axis"]) |
---|
504 | """ |
---|
505 | self._ordinate = ordinate |
---|
506 | if isinstance(fontsize, int): |
---|
507 | from matplotlib import rc as rcp |
---|
508 | rcp('axes', labelsize=fontsize) |
---|
509 | rcp('ytick', labelsize=fontsize) |
---|
510 | if refresh and self._data: self.plot(self._data) |
---|
511 | return |
---|
512 | |
---|
513 | def set_abcissa(self, abcissa=None, fontsize=None, refresh=True): |
---|
514 | """ |
---|
515 | Set the x-axis label of the plot. If multiple panels are plotted, |
---|
516 | multiple labels have to be specified. |
---|
517 | Parameters: |
---|
518 | abcissa: a list of abcissa labels. None (default) let |
---|
519 | data determine the labels |
---|
520 | refresh: True (default) or False. If True, the plot is |
---|
521 | replotted based on the new parameter setting(s). |
---|
522 | Otherwise,the parameter(s) are set without replotting. |
---|
523 | Example: |
---|
524 | # two panels are visible on the plotter |
---|
525 | plotter.set_ordinate(["First X-Axis","Second X-Axis"]) |
---|
526 | """ |
---|
527 | self._abcissa = abcissa |
---|
528 | if isinstance(fontsize, int): |
---|
529 | from matplotlib import rc as rcp |
---|
530 | rcp('axes', labelsize=fontsize) |
---|
531 | rcp('xtick', labelsize=fontsize) |
---|
532 | if refresh and self._data: self.plot(self._data) |
---|
533 | return |
---|
534 | |
---|
535 | def set_colors(self, colmap, refresh=True): |
---|
536 | """ |
---|
537 | Set the colours to be used. The plotter will cycle through |
---|
538 | these colours when lines are overlaid (stacking mode). |
---|
539 | Parameters: |
---|
540 | colmap: a list of colour names |
---|
541 | refresh: True (default) or False. If True, the plot is |
---|
542 | replotted based on the new parameter setting(s). |
---|
543 | Otherwise,the parameter(s) are set without replotting. |
---|
544 | Example: |
---|
545 | plotter.set_colors("red green blue") |
---|
546 | # If for example four lines are overlaid e.g I Q U V |
---|
547 | # 'I' will be 'red', 'Q' will be 'green', U will be 'blue' |
---|
548 | # and 'V' will be 'red' again. |
---|
549 | """ |
---|
550 | if isinstance(colmap,str): |
---|
551 | colmap = colmap.split() |
---|
552 | self._plotter.palette(0, colormap=colmap) |
---|
553 | if refresh and self._data: self.plot(self._data) |
---|
554 | |
---|
555 | # alias for english speakers |
---|
556 | set_colours = set_colors |
---|
557 | |
---|
558 | def set_histogram(self, hist=True, linewidth=None, refresh=True): |
---|
559 | """ |
---|
560 | Enable/Disable histogram-like plotting. |
---|
561 | Parameters: |
---|
562 | hist: True (default) or False. The fisrt default |
---|
563 | is taken from the .asaprc setting |
---|
564 | plotter.histogram |
---|
565 | refresh: True (default) or False. If True, the plot is |
---|
566 | replotted based on the new parameter setting(s). |
---|
567 | Otherwise,the parameter(s) are set without replotting. |
---|
568 | """ |
---|
569 | self._hist = hist |
---|
570 | if isinstance(linewidth, float) or isinstance(linewidth, int): |
---|
571 | from matplotlib import rc as rcp |
---|
572 | rcp('lines', linewidth=linewidth) |
---|
573 | if refresh and self._data: self.plot(self._data) |
---|
574 | |
---|
575 | def set_linestyles(self, linestyles=None, linewidth=None, refresh=True): |
---|
576 | """ |
---|
577 | Set the linestyles to be used. The plotter will cycle through |
---|
578 | these linestyles when lines are overlaid (stacking mode) AND |
---|
579 | only one color has been set. |
---|
580 | Parameters: |
---|
581 | linestyles: a list of linestyles to use. |
---|
582 | 'line', 'dashed', 'dotted', 'dashdot', |
---|
583 | 'dashdotdot' and 'dashdashdot' are |
---|
584 | possible |
---|
585 | refresh: True (default) or False. If True, the plot is |
---|
586 | replotted based on the new parameter setting(s). |
---|
587 | Otherwise,the parameter(s) are set without replotting. |
---|
588 | Example: |
---|
589 | plotter.set_colors("black") |
---|
590 | plotter.set_linestyles("line dashed dotted dashdot") |
---|
591 | # If for example four lines are overlaid e.g I Q U V |
---|
592 | # 'I' will be 'solid', 'Q' will be 'dashed', |
---|
593 | # U will be 'dotted' and 'V' will be 'dashdot'. |
---|
594 | """ |
---|
595 | if isinstance(linestyles,str): |
---|
596 | linestyles = linestyles.split() |
---|
597 | self._plotter.palette(color=0,linestyle=0,linestyles=linestyles) |
---|
598 | if isinstance(linewidth, float) or isinstance(linewidth, int): |
---|
599 | from matplotlib import rc as rcp |
---|
600 | rcp('lines', linewidth=linewidth) |
---|
601 | if refresh and self._data: self.plot(self._data) |
---|
602 | |
---|
603 | def set_font(self, refresh=True,**kwargs): |
---|
604 | """ |
---|
605 | Set font properties. |
---|
606 | Parameters: |
---|
607 | family: one of 'sans-serif', 'serif', 'cursive', 'fantasy', 'monospace' |
---|
608 | style: one of 'normal' (or 'roman'), 'italic' or 'oblique' |
---|
609 | weight: one of 'normal or 'bold' |
---|
610 | size: the 'general' font size, individual elements can be adjusted |
---|
611 | seperately |
---|
612 | refresh: True (default) or False. If True, the plot is |
---|
613 | replotted based on the new parameter setting(s). |
---|
614 | Otherwise,the parameter(s) are set without replotting. |
---|
615 | """ |
---|
616 | from matplotlib import rc as rcp |
---|
617 | fdict = {} |
---|
618 | for k,v in kwargs.iteritems(): |
---|
619 | if v: |
---|
620 | fdict[k] = v |
---|
621 | self._fp = FontProperties(**fdict) |
---|
622 | if refresh and self._data: self.plot(self._data) |
---|
623 | |
---|
624 | def set_panellayout(self,layout=[],refresh=True): |
---|
625 | """ |
---|
626 | Set the layout of subplots. |
---|
627 | Parameters: |
---|
628 | layout: a list of subplots layout in figure coordinate (0-1), |
---|
629 | i.e., fraction of the figure width or height. |
---|
630 | The order of elements should be: |
---|
631 | [left, bottom, right, top, horizontal space btw panels, |
---|
632 | vertical space btw panels]. |
---|
633 | refresh: True (default) or False. If True, the plot is |
---|
634 | replotted based on the new parameter setting(s). |
---|
635 | Otherwise,the parameter(s) are set without replotting. |
---|
636 | Note |
---|
637 | * When layout is not specified, the values are reset to the defaults |
---|
638 | of matplotlib. |
---|
639 | * If any element is set to be None, the current value is adopted. |
---|
640 | """ |
---|
641 | if layout == []: self._panellayout=self._reset_panellayout() |
---|
642 | else: |
---|
643 | self._panellayout=[None]*6 |
---|
644 | self._panellayout[0:len(layout)]=layout |
---|
645 | #print "panel layout set to ",self._panellayout |
---|
646 | if refresh and self._data: self.plot(self._data) |
---|
647 | |
---|
648 | def _reset_panellayout(self): |
---|
649 | ks=map(lambda x: 'figure.subplot.'+x, |
---|
650 | ['left','bottom','right','top','hspace','wspace']) |
---|
651 | return map(matplotlib.rcParams.get,ks) |
---|
652 | |
---|
653 | def plot_lines(self, linecat=None, doppler=0.0, deltachan=10, rotate=90.0, |
---|
654 | location=None): |
---|
655 | """ |
---|
656 | Plot a line catalog. |
---|
657 | Parameters: |
---|
658 | linecat: the linecatalog to plot |
---|
659 | doppler: the velocity shift to apply to the frequencies |
---|
660 | deltachan: the number of channels to include each side of the |
---|
661 | line to determine a local maximum/minimum |
---|
662 | rotate: the rotation (in degrees) )for the text label (default 90.0) |
---|
663 | location: the location of the line annotation from the 'top', |
---|
664 | 'bottom' or alternate (None - the default) |
---|
665 | Notes: |
---|
666 | If the spectrum is flagged no line will be drawn in that location. |
---|
667 | """ |
---|
668 | if not self._data: |
---|
669 | raise RuntimeError("No scantable has been plotted yet.") |
---|
670 | from asap._asap import linecatalog |
---|
671 | if not isinstance(linecat, linecatalog): |
---|
672 | raise ValueError("'linecat' isn't of type linecatalog.") |
---|
673 | if not self._data.get_unit().endswith("Hz"): |
---|
674 | raise RuntimeError("Can only overlay linecatalogs when data is in frequency.") |
---|
675 | from numpy import ma |
---|
676 | for j in range(len(self._plotter.subplots)): |
---|
677 | self._plotter.subplot(j) |
---|
678 | lims = self._plotter.axes.get_xlim() |
---|
679 | for row in range(linecat.nrow()): |
---|
680 | # get_frequency returns MHz |
---|
681 | base = { "GHz": 1000.0, "MHz": 1.0, "Hz": 1.0e-6 } |
---|
682 | restf = linecat.get_frequency(row)/base[self._data.get_unit()] |
---|
683 | c = 299792.458 |
---|
684 | freq = restf*(1.0-doppler/c) |
---|
685 | if lims[0] < freq < lims[1]: |
---|
686 | if location is None: |
---|
687 | loc = 'bottom' |
---|
688 | if row%2: loc='top' |
---|
689 | else: loc = location |
---|
690 | maxys = [] |
---|
691 | for line in self._plotter.axes.lines: |
---|
692 | v = line._x |
---|
693 | asc = v[0] < v[-1] |
---|
694 | |
---|
695 | idx = None |
---|
696 | if not asc: |
---|
697 | if v[len(v)-1] <= freq <= v[0]: |
---|
698 | i = len(v)-1 |
---|
699 | while i>=0 and v[i] < freq: |
---|
700 | idx = i |
---|
701 | i-=1 |
---|
702 | else: |
---|
703 | if v[0] <= freq <= v[len(v)-1]: |
---|
704 | i = 0 |
---|
705 | while i<len(v) and v[i] < freq: |
---|
706 | idx = i |
---|
707 | i+=1 |
---|
708 | if idx is not None: |
---|
709 | lower = idx - deltachan |
---|
710 | upper = idx + deltachan |
---|
711 | if lower < 0: lower = 0 |
---|
712 | if upper > len(v): upper = len(v) |
---|
713 | s = slice(lower, upper) |
---|
714 | y = line._y[s] |
---|
715 | maxy = ma.maximum(y) |
---|
716 | if isinstance( maxy, float): |
---|
717 | maxys.append(maxy) |
---|
718 | if len(maxys): |
---|
719 | peak = max(maxys) |
---|
720 | if peak > self._plotter.axes.get_ylim()[1]: |
---|
721 | loc = 'bottom' |
---|
722 | else: |
---|
723 | continue |
---|
724 | self._plotter.vline_with_label(freq, peak, |
---|
725 | linecat.get_name(row), |
---|
726 | location=loc, rotate=rotate) |
---|
727 | self._plotter.show(hardrefresh=False) |
---|
728 | |
---|
729 | |
---|
730 | def save(self, filename=None, orientation=None, dpi=None): |
---|
731 | """ |
---|
732 | Save the plot to a file. The know formats are 'png', 'ps', 'eps'. |
---|
733 | Parameters: |
---|
734 | filename: The name of the output file. This is optional |
---|
735 | and autodetects the image format from the file |
---|
736 | suffix. If non filename is specified a file |
---|
737 | called 'yyyymmdd_hhmmss.png' is created in the |
---|
738 | current directory. |
---|
739 | orientation: optional parameter for postscript only (not eps). |
---|
740 | 'landscape', 'portrait' or None (default) are valid. |
---|
741 | If None is choosen for 'ps' output, the plot is |
---|
742 | automatically oriented to fill the page. |
---|
743 | dpi: The dpi of the output non-ps plot |
---|
744 | """ |
---|
745 | self._plotter.save(filename,orientation,dpi) |
---|
746 | return |
---|
747 | |
---|
748 | @asaplog_post_dec |
---|
749 | def set_mask(self, mask=None, selection=None, refresh=True): |
---|
750 | """ |
---|
751 | Set a plotting mask for a specific polarization. |
---|
752 | This is useful for masking out "noise" Pangle outside a source. |
---|
753 | Parameters: |
---|
754 | mask: a mask from scantable.create_mask |
---|
755 | selection: the spectra to apply the mask to. |
---|
756 | refresh: True (default) or False. If True, the plot is |
---|
757 | replotted based on the new parameter setting(s). |
---|
758 | Otherwise,the parameter(s) are set without replotting. |
---|
759 | Example: |
---|
760 | select = selector() |
---|
761 | select.setpolstrings("Pangle") |
---|
762 | plotter.set_mask(mymask, select) |
---|
763 | """ |
---|
764 | if not self._data: |
---|
765 | msg = "Can only set mask after a first call to plot()" |
---|
766 | raise RuntimeError(msg) |
---|
767 | if len(mask): |
---|
768 | if isinstance(mask, list) or isinstance(mask, tuple): |
---|
769 | self._usermask = array(mask) |
---|
770 | else: |
---|
771 | self._usermask = mask |
---|
772 | if mask is None and selection is None: |
---|
773 | self._usermask = [] |
---|
774 | self._maskselection = None |
---|
775 | if isinstance(selection, selector): |
---|
776 | self._maskselection = {'b': selection.get_beams(), |
---|
777 | 's': selection.get_scans(), |
---|
778 | 'i': selection.get_ifs(), |
---|
779 | 'p': selection.get_pols(), |
---|
780 | 't': [] } |
---|
781 | else: |
---|
782 | self._maskselection = None |
---|
783 | if refresh: self.plot(self._data) |
---|
784 | |
---|
785 | def _slice_indeces(self, data): |
---|
786 | mn = self._minmaxx[0] |
---|
787 | mx = self._minmaxx[1] |
---|
788 | asc = data[0] < data[-1] |
---|
789 | start=0 |
---|
790 | end = len(data)-1 |
---|
791 | inc = 1 |
---|
792 | if not asc: |
---|
793 | start = len(data)-1 |
---|
794 | end = 0 |
---|
795 | inc = -1 |
---|
796 | # find min index |
---|
797 | #while start > 0 and data[start] < mn: |
---|
798 | # start+= inc |
---|
799 | minind=start |
---|
800 | for ind in xrange(start,end+inc,inc): |
---|
801 | if data[ind] > mn: break |
---|
802 | minind=ind |
---|
803 | # find max index |
---|
804 | #while end > 0 and data[end] > mx: |
---|
805 | # end-=inc |
---|
806 | #if end > 0: end +=1 |
---|
807 | maxind=end |
---|
808 | for ind in xrange(end,start-inc,-inc): |
---|
809 | if data[ind] < mx: break |
---|
810 | maxind=ind |
---|
811 | start=minind |
---|
812 | end=maxind |
---|
813 | if start > end: |
---|
814 | return end,start+1 |
---|
815 | elif start < end: |
---|
816 | return start,end+1 |
---|
817 | else: |
---|
818 | return start,end |
---|
819 | |
---|
820 | def _reset(self): |
---|
821 | self._usermask = [] |
---|
822 | self._usermaskspectra = None |
---|
823 | self._offset = None |
---|
824 | self.set_selection(None, False) |
---|
825 | |
---|
826 | def _plot(self, scan): |
---|
827 | savesel = scan.get_selection() |
---|
828 | sel = savesel + self._selection |
---|
829 | order = self._get_sortstring([self._panelling,self._stacking]) |
---|
830 | if order: |
---|
831 | sel.set_order(order) |
---|
832 | scan.set_selection(sel) |
---|
833 | d = {'b': scan.getbeam, 's': scan.getscan, |
---|
834 | 'i': scan.getif, 'p': scan.getpol, 't': scan._gettime, |
---|
835 | 'r': int, '_r': int} |
---|
836 | |
---|
837 | polmodes = dict(zip(self._selection.get_pols(), |
---|
838 | self._selection.get_poltypes())) |
---|
839 | # this returns either a tuple of numbers or a length (ncycles) |
---|
840 | # convert this into lengths |
---|
841 | n0,nstack0 = self._get_selected_n(scan) |
---|
842 | if isinstance(n0, int): n = n0 |
---|
843 | else: n = len(n0) |
---|
844 | if isinstance(nstack0, int): nstack = nstack0 |
---|
845 | else: nstack = len(nstack0) |
---|
846 | nptot = n |
---|
847 | maxpanel, maxstack = 16,16 |
---|
848 | if nstack > maxstack: |
---|
849 | msg ="Scan to be overlayed contains more than %d selections.\n" \ |
---|
850 | "Selecting first %d selections..." % (maxstack, maxstack) |
---|
851 | asaplog.push(msg) |
---|
852 | asaplog.post('WARN') |
---|
853 | nstack = min(nstack,maxstack) |
---|
854 | n = min(n,maxpanel) |
---|
855 | |
---|
856 | if n > 1: |
---|
857 | ganged = rcParams['plotter.ganged'] |
---|
858 | if self._panelling == 'i': |
---|
859 | ganged = False |
---|
860 | if self._rows and self._cols: |
---|
861 | n = min(n,self._rows*self._cols) |
---|
862 | self._plotter.set_panels(rows=self._rows,cols=self._cols, |
---|
863 | # nplots=n,ganged=ganged) |
---|
864 | nplots=n,layout=self._panellayout,ganged=ganged) |
---|
865 | else: |
---|
866 | # self._plotter.set_panels(rows=n,cols=0,nplots=n,ganged=ganged) |
---|
867 | self._plotter.set_panels(rows=n,cols=0,nplots=n,layout=self._panellayout,ganged=ganged) |
---|
868 | else: |
---|
869 | # self._plotter.set_panels() |
---|
870 | self._plotter.set_panels(layout=self._panellayout) |
---|
871 | #r = 0 |
---|
872 | r = self._rowcount |
---|
873 | nr = scan.nrow() |
---|
874 | a0,b0 = -1,-1 |
---|
875 | allxlim = [] |
---|
876 | allylim = [] |
---|
877 | newpanel=True |
---|
878 | panelcount,stackcount = 0,0 |
---|
879 | while r < nr: |
---|
880 | a = d[self._panelling](r) |
---|
881 | b = d[self._stacking](r) |
---|
882 | if a > a0 and panelcount < n: |
---|
883 | if n > 1: |
---|
884 | self._plotter.subplot(panelcount) |
---|
885 | self._plotter.palette(0) |
---|
886 | #title |
---|
887 | xlab = self._abcissa and self._abcissa[panelcount] \ |
---|
888 | or scan._getabcissalabel() |
---|
889 | if self._offset and not self._abcissa: |
---|
890 | xlab += " (relative)" |
---|
891 | ylab = self._ordinate and self._ordinate[panelcount] \ |
---|
892 | or scan._get_ordinate_label() |
---|
893 | self._plotter.set_axes('xlabel', xlab) |
---|
894 | self._plotter.set_axes('ylabel', ylab) |
---|
895 | lbl = self._get_label(scan, r, self._panelling, self._title) |
---|
896 | #if self._panelling == 'r': lbl = '' |
---|
897 | if isinstance(lbl, list) or isinstance(lbl, tuple): |
---|
898 | if 0 <= panelcount < len(lbl): |
---|
899 | lbl = lbl[panelcount] |
---|
900 | else: |
---|
901 | # get default label |
---|
902 | lbl = self._get_label(scan, r, self._panelling, None) |
---|
903 | self._plotter.set_axes('title',lbl) |
---|
904 | newpanel = True |
---|
905 | stackcount = 0 |
---|
906 | panelcount += 1 |
---|
907 | if (b > b0 or newpanel) and stackcount < nstack: |
---|
908 | y = [] |
---|
909 | if len(polmodes): |
---|
910 | y = scan._getspectrum(r, polmodes[scan.getpol(r)]) |
---|
911 | else: |
---|
912 | y = scan._getspectrum(r) |
---|
913 | m = scan._getmask(r) |
---|
914 | from numpy import logical_not, logical_and |
---|
915 | if self._maskselection and len(self._usermask) == len(m): |
---|
916 | if d[self._stacking](r) in self._maskselection[self._stacking]: |
---|
917 | m = logical_and(m, self._usermask) |
---|
918 | from numpy import ma, array |
---|
919 | x = array(scan._getabcissa(r)) |
---|
920 | if self._offset: |
---|
921 | x += self._offset |
---|
922 | y = ma.masked_array(y,mask=logical_not(array(m,copy=False))) |
---|
923 | if self._minmaxx is not None: |
---|
924 | s,e = self._slice_indeces(x) |
---|
925 | x = x[s:e] |
---|
926 | y = y[s:e] |
---|
927 | if len(x) > 1024 and rcParams['plotter.decimate']: |
---|
928 | fac = len(x)/1024 |
---|
929 | x = x[::fac] |
---|
930 | y = y[::fac] |
---|
931 | llbl = self._get_label(scan, r, self._stacking, self._lmap) |
---|
932 | if isinstance(llbl, list) or isinstance(llbl, tuple): |
---|
933 | if 0 <= stackcount < len(llbl): |
---|
934 | # use user label |
---|
935 | llbl = llbl[stackcount] |
---|
936 | else: |
---|
937 | # get default label |
---|
938 | llbl = self._get_label(scan, r, self._stacking, None) |
---|
939 | self._plotter.set_line(label=llbl) |
---|
940 | plotit = self._plotter.plot |
---|
941 | if self._hist: plotit = self._plotter.hist |
---|
942 | if len(x) > 0: |
---|
943 | plotit(x,y) |
---|
944 | xlim= self._minmaxx or [min(x),max(x)] |
---|
945 | allxlim += xlim |
---|
946 | ylim= self._minmaxy or [ma.minimum(y),ma.maximum(y)] |
---|
947 | allylim += ylim |
---|
948 | else: |
---|
949 | xlim = self._minmaxx or [] |
---|
950 | allxlim += xlim |
---|
951 | ylim= self._minmaxy or [] |
---|
952 | allylim += ylim |
---|
953 | stackcount += 1 |
---|
954 | # last in colour stack -> autoscale x |
---|
955 | if stackcount == nstack and len(allxlim) > 0: |
---|
956 | allxlim.sort() |
---|
957 | self._plotter.subplots[panelcount-1]['axes'].set_xlim([allxlim[0],allxlim[-1]]) |
---|
958 | # clear |
---|
959 | allxlim =[] |
---|
960 | |
---|
961 | newpanel = False |
---|
962 | a0=a |
---|
963 | b0=b |
---|
964 | # ignore following rows |
---|
965 | if (panelcount == n) and (stackcount == nstack): |
---|
966 | # last panel -> autoscale y if ganged |
---|
967 | if rcParams['plotter.ganged'] and len(allylim) > 0: |
---|
968 | allylim.sort() |
---|
969 | self._plotter.set_limits(ylim=[allylim[0],allylim[-1]]) |
---|
970 | break |
---|
971 | r+=1 # next row |
---|
972 | ###-S |
---|
973 | self._rowcount = r+1 |
---|
974 | self._panelcnt += panelcount |
---|
975 | if self._plotter.figmgr.casabar: |
---|
976 | if self._panelcnt >= nptot-1: |
---|
977 | self._plotter.figmgr.casabar.disable_next() |
---|
978 | else: |
---|
979 | self._plotter.figmgr.casabar.enable_next() |
---|
980 | #if self._panelcnt - panelcount > 0: |
---|
981 | # self._plotter.figmgr.casabar.enable_prev() |
---|
982 | #else: |
---|
983 | # self._plotter.figmgr.casabar.disable_prev() |
---|
984 | ###-E |
---|
985 | #reset the selector to the scantable's original |
---|
986 | scan.set_selection(savesel) |
---|
987 | |
---|
988 | #temporary switch-off for older matplotlib |
---|
989 | #if self._fp is not None: |
---|
990 | if self._fp is not None and getattr(self._plotter.figure,'findobj',False): |
---|
991 | for o in self._plotter.figure.findobj(Text): |
---|
992 | o.set_fontproperties(self._fp) |
---|
993 | |
---|
994 | def _get_sortstring(self, lorders): |
---|
995 | d0 = {'s': 'SCANNO', 'b': 'BEAMNO', 'i':'IFNO', |
---|
996 | 'p': 'POLNO', 'c': 'CYCLENO', 't' : 'TIME', 'r':None, '_r':None } |
---|
997 | if not (type(lorders) == list) or not (type(lorders) == tuple): |
---|
998 | return None |
---|
999 | if len(lorders) > 0: |
---|
1000 | lsorts = [] |
---|
1001 | for order in lorders: |
---|
1002 | ssort = d0[order] |
---|
1003 | if ssort: |
---|
1004 | lsorts.append(ssort) |
---|
1005 | return lsorts |
---|
1006 | return None |
---|
1007 | |
---|
1008 | def set_selection(self, selection=None, refresh=True, **kw): |
---|
1009 | """ |
---|
1010 | Parameters: |
---|
1011 | selection: a selector object (default unset the selection) |
---|
1012 | refresh: True (default) or False. If True, the plot is |
---|
1013 | replotted based on the new parameter setting(s). |
---|
1014 | Otherwise,the parameter(s) are set without replotting. |
---|
1015 | """ |
---|
1016 | if selection is None: |
---|
1017 | # reset |
---|
1018 | if len(kw) == 0: |
---|
1019 | self._selection = selector() |
---|
1020 | else: |
---|
1021 | # try keywords |
---|
1022 | for k in kw: |
---|
1023 | if k not in selector.fields: |
---|
1024 | raise KeyError("Invalid selection key '%s', valid keys are %s" % (k, selector.fields)) |
---|
1025 | self._selection = selector(**kw) |
---|
1026 | elif isinstance(selection, selector): |
---|
1027 | self._selection = selection |
---|
1028 | else: |
---|
1029 | raise TypeError("'selection' is not of type selector") |
---|
1030 | |
---|
1031 | order = self._get_sortstring([self._panelling,self._stacking]) |
---|
1032 | if order: |
---|
1033 | self._selection.set_order(order) |
---|
1034 | if refresh and self._data: self.plot(self._data) |
---|
1035 | |
---|
1036 | def _get_selected_n(self, scan): |
---|
1037 | d1 = {'b': scan.getbeamnos, 's': scan.getscannos, |
---|
1038 | 'i': scan.getifnos, 'p': scan.getpolnos, 't': scan.ncycle, |
---|
1039 | 'r': scan.nrow, '_r': False} |
---|
1040 | d2 = { 'b': self._selection.get_beams(), |
---|
1041 | 's': self._selection.get_scans(), |
---|
1042 | 'i': self._selection.get_ifs(), |
---|
1043 | 'p': self._selection.get_pols(), |
---|
1044 | 't': self._selection.get_cycles(), |
---|
1045 | 'r': False, '_r': 1} |
---|
1046 | n = d2[self._panelling] or d1[self._panelling]() |
---|
1047 | nstack = d2[self._stacking] or d1[self._stacking]() |
---|
1048 | return n,nstack |
---|
1049 | |
---|
1050 | def _get_label(self, scan, row, mode, userlabel=None): |
---|
1051 | if isinstance(userlabel, list) and len(userlabel) == 0: |
---|
1052 | userlabel = " " |
---|
1053 | pms = dict(zip(self._selection.get_pols(),self._selection.get_poltypes())) |
---|
1054 | if len(pms): |
---|
1055 | poleval = scan._getpollabel(scan.getpol(row),pms[scan.getpol(row)]) |
---|
1056 | else: |
---|
1057 | poleval = scan._getpollabel(scan.getpol(row),scan.poltype()) |
---|
1058 | d = {'b': "Beam "+str(scan.getbeam(row)), |
---|
1059 | #'s': scan._getsourcename(row), |
---|
1060 | 's': "Scan "+str(scan.getscan(row))+\ |
---|
1061 | " ("+str(scan._getsourcename(row))+")", |
---|
1062 | 'i': "IF"+str(scan.getif(row)), |
---|
1063 | 'p': poleval, |
---|
1064 | 't': str(scan.get_time(row)), |
---|
1065 | 'r': "row "+str(row), |
---|
1066 | #'_r': str(scan.get_time(row))+",\nIF"+str(scan.getif(row))+", "+poleval+", Beam"+str(scan.getbeam(row)) } |
---|
1067 | '_r': "" } |
---|
1068 | return userlabel or d[mode] |
---|
1069 | |
---|
1070 | def plotazel(self, scan=None, outfile=None): |
---|
1071 | #def plotazel(self): |
---|
1072 | """ |
---|
1073 | plot azimuth and elevation versus time of a scantable |
---|
1074 | """ |
---|
1075 | from matplotlib import pylab as PL |
---|
1076 | from matplotlib.dates import DateFormatter, timezone |
---|
1077 | from matplotlib.dates import HourLocator, MinuteLocator,SecondLocator, DayLocator |
---|
1078 | from matplotlib.ticker import MultipleLocator |
---|
1079 | from numpy import array, pi |
---|
1080 | self._data = scan |
---|
1081 | self._outfile = outfile |
---|
1082 | dates = self._data.get_time(asdatetime=True) |
---|
1083 | t = PL.date2num(dates) |
---|
1084 | tz = timezone('UTC') |
---|
1085 | PL.cla() |
---|
1086 | PL.ioff() |
---|
1087 | PL.clf() |
---|
1088 | # Adjust subplot layouts |
---|
1089 | if len(self._panellayout) !=6: self.set_panellayout(refresh=False) |
---|
1090 | lef, bot, rig, top, wsp, hsp = self._panellayout |
---|
1091 | PL.gcf().subplots_adjust(left=lef,bottom=bot,right=rig,top=top, |
---|
1092 | wspace=wsp,hspace=hsp) |
---|
1093 | |
---|
1094 | tdel = max(t) - min(t) |
---|
1095 | ax = PL.subplot(2,1,1) |
---|
1096 | el = array(self._data.get_elevation())*180./pi |
---|
1097 | PL.ylabel('El [deg.]') |
---|
1098 | dstr = dates[0].strftime('%Y/%m/%d') |
---|
1099 | if tdel > 1.0: |
---|
1100 | dstr2 = dates[len(dates)-1].strftime('%Y/%m/%d') |
---|
1101 | dstr = dstr + " - " + dstr2 |
---|
1102 | majloc = DayLocator() |
---|
1103 | minloc = HourLocator(range(0,23,12)) |
---|
1104 | timefmt = DateFormatter("%b%d") |
---|
1105 | elif tdel > 24./60.: |
---|
1106 | timefmt = DateFormatter('%H:%M') |
---|
1107 | majloc = HourLocator() |
---|
1108 | minloc = MinuteLocator(30) |
---|
1109 | else: |
---|
1110 | timefmt = DateFormatter('%H:%M') |
---|
1111 | majloc = MinuteLocator(interval=5) |
---|
1112 | minloc = SecondLocator(30) |
---|
1113 | |
---|
1114 | PL.title(dstr) |
---|
1115 | if tdel == 0.0: |
---|
1116 | th = (t - PL.floor(t))*24.0 |
---|
1117 | PL.plot(th,el,'o',markersize=2, markerfacecolor='b', markeredgecolor='b') |
---|
1118 | else: |
---|
1119 | PL.plot_date(t,el,'o', markersize=2, markerfacecolor='b', markeredgecolor='b',tz=tz) |
---|
1120 | #ax.grid(True) |
---|
1121 | ax.xaxis.set_major_formatter(timefmt) |
---|
1122 | ax.xaxis.set_major_locator(majloc) |
---|
1123 | ax.xaxis.set_minor_locator(minloc) |
---|
1124 | ax.yaxis.grid(True) |
---|
1125 | yloc = MultipleLocator(30) |
---|
1126 | ax.set_ylim(0,90) |
---|
1127 | ax.yaxis.set_major_locator(yloc) |
---|
1128 | if tdel > 1.0: |
---|
1129 | labels = ax.get_xticklabels() |
---|
1130 | # PL.setp(labels, fontsize=10, rotation=45) |
---|
1131 | PL.setp(labels, fontsize=10) |
---|
1132 | |
---|
1133 | # Az plot |
---|
1134 | az = array(self._data.get_azimuth())*180./pi |
---|
1135 | if min(az) < 0: |
---|
1136 | for irow in range(len(az)): |
---|
1137 | if az[irow] < 0: az[irow] += 360.0 |
---|
1138 | |
---|
1139 | ax2 = PL.subplot(2,1,2) |
---|
1140 | #PL.xlabel('Time (UT [hour])') |
---|
1141 | PL.ylabel('Az [deg.]') |
---|
1142 | if tdel == 0.0: |
---|
1143 | PL.plot(th,az,'o',markersize=2, markeredgecolor='b',markerfacecolor='b') |
---|
1144 | else: |
---|
1145 | PL.plot_date(t,az,'o', markersize=2,markeredgecolor='b',markerfacecolor='b',tz=tz) |
---|
1146 | ax2.xaxis.set_major_formatter(timefmt) |
---|
1147 | ax2.xaxis.set_major_locator(majloc) |
---|
1148 | ax2.xaxis.set_minor_locator(minloc) |
---|
1149 | #ax2.grid(True) |
---|
1150 | ax2.set_ylim(0,360) |
---|
1151 | ax2.yaxis.grid(True) |
---|
1152 | #hfmt = DateFormatter('%H') |
---|
1153 | #hloc = HourLocator() |
---|
1154 | yloc = MultipleLocator(60) |
---|
1155 | ax2.yaxis.set_major_locator(yloc) |
---|
1156 | if tdel > 1.0: |
---|
1157 | labels = ax2.get_xticklabels() |
---|
1158 | PL.setp(labels, fontsize=10) |
---|
1159 | PL.xlabel('Time (UT [day])') |
---|
1160 | else: |
---|
1161 | PL.xlabel('Time (UT [hour])') |
---|
1162 | |
---|
1163 | PL.ion() |
---|
1164 | PL.draw() |
---|
1165 | if (self._outfile is not None): |
---|
1166 | PL.savefig(self._outfile) |
---|
1167 | |
---|
1168 | def plotpointing(self, scan=None, outfile=None): |
---|
1169 | #def plotpointing(self): |
---|
1170 | """ |
---|
1171 | plot telescope pointings |
---|
1172 | """ |
---|
1173 | from matplotlib import pylab as PL |
---|
1174 | from numpy import array, pi |
---|
1175 | self._data = scan |
---|
1176 | self._outfile = outfile |
---|
1177 | dir = array(self._data.get_directionval()).transpose() |
---|
1178 | ra = dir[0]*180./pi |
---|
1179 | dec = dir[1]*180./pi |
---|
1180 | PL.cla() |
---|
1181 | #PL.ioff() |
---|
1182 | PL.clf() |
---|
1183 | # Adjust subplot layouts |
---|
1184 | if len(self._panellayout) !=6: self.set_panellayout(refresh=False) |
---|
1185 | lef, bot, rig, top, wsp, hsp = self._panellayout |
---|
1186 | PL.gcf().subplots_adjust(left=lef,bottom=bot,right=rig,top=top, |
---|
1187 | wspace=wsp,hspace=hsp) |
---|
1188 | ax = PL.gca() |
---|
1189 | #ax = PL.axes([0.1,0.1,0.8,0.8]) |
---|
1190 | #ax = PL.axes([0.1,0.1,0.8,0.8]) |
---|
1191 | ax.set_aspect('equal') |
---|
1192 | PL.plot(ra, dec, 'b,') |
---|
1193 | PL.xlabel('RA [deg.]') |
---|
1194 | PL.ylabel('Declination [deg.]') |
---|
1195 | PL.title('Telescope pointings') |
---|
1196 | [xmin,xmax,ymin,ymax] = PL.axis() |
---|
1197 | PL.axis([xmax,xmin,ymin,ymax]) |
---|
1198 | #PL.ion() |
---|
1199 | PL.draw() |
---|
1200 | if (self._outfile is not None): |
---|
1201 | PL.savefig(self._outfile) |
---|
1202 | |
---|
1203 | # plot total power data |
---|
1204 | # plotting in time is not yet implemented.. |
---|
1205 | @asaplog_post_dec |
---|
1206 | def plottp(self, scan=None, outfile=None): |
---|
1207 | if self._plotter.is_dead: |
---|
1208 | if hasattr(self._plotter.figmgr,'casabar'): |
---|
1209 | del self._plotter.figmgr.casabar |
---|
1210 | self._plotter = self._newplotter() |
---|
1211 | self._plotter.figmgr.casabar=self._newcasabar() |
---|
1212 | self._plotter.hold() |
---|
1213 | self._plotter.clear() |
---|
1214 | from asap import scantable |
---|
1215 | if not self._data and not scan: |
---|
1216 | msg = "Input is not a scantable" |
---|
1217 | raise TypeError(msg) |
---|
1218 | if isinstance(scan, scantable): |
---|
1219 | if self._data is not None: |
---|
1220 | if scan != self._data: |
---|
1221 | self._data = scan |
---|
1222 | # reset |
---|
1223 | self._reset() |
---|
1224 | else: |
---|
1225 | self._data = scan |
---|
1226 | self._reset() |
---|
1227 | # ranges become invalid when abcissa changes? |
---|
1228 | #if self._abcunit and self._abcunit != self._data.get_unit(): |
---|
1229 | # self._minmaxx = None |
---|
1230 | # self._minmaxy = None |
---|
1231 | # self._abcunit = self._data.get_unit() |
---|
1232 | # self._datamask = None |
---|
1233 | |
---|
1234 | # Adjust subplot layouts |
---|
1235 | if len(self._panellayout) !=6: self.set_panellayout(refresh=False) |
---|
1236 | lef, bot, rig, top, wsp, hsp = self._panellayout |
---|
1237 | self._plotter.figure.subplots_adjust( |
---|
1238 | left=lef,bottom=bot,right=rig,top=top,wspace=wsp,hspace=hsp) |
---|
1239 | if self._plotter.figmgr.casabar: self._plotter.figmgr.casabar.disable_button() |
---|
1240 | self._plottp(self._data) |
---|
1241 | if self._minmaxy is not None: |
---|
1242 | self._plotter.set_limits(ylim=self._minmaxy) |
---|
1243 | self._plotter.release() |
---|
1244 | self._plotter.tidy() |
---|
1245 | self._plotter.show(hardrefresh=False) |
---|
1246 | return |
---|
1247 | |
---|
1248 | def _plottp(self,scan): |
---|
1249 | """ |
---|
1250 | private method for plotting total power data |
---|
1251 | """ |
---|
1252 | from numpy import ma, array, arange, logical_not |
---|
1253 | r=0 |
---|
1254 | nr = scan.nrow() |
---|
1255 | a0,b0 = -1,-1 |
---|
1256 | allxlim = [] |
---|
1257 | allylim = [] |
---|
1258 | y=[] |
---|
1259 | self._plotter.set_panels() |
---|
1260 | self._plotter.palette(0) |
---|
1261 | #title |
---|
1262 | #xlab = self._abcissa and self._abcissa[panelcount] \ |
---|
1263 | # or scan._getabcissalabel() |
---|
1264 | #ylab = self._ordinate and self._ordinate[panelcount] \ |
---|
1265 | # or scan._get_ordinate_label() |
---|
1266 | xlab = self._abcissa or 'row number' #or Time |
---|
1267 | ylab = self._ordinate or scan._get_ordinate_label() |
---|
1268 | self._plotter.set_axes('xlabel',xlab) |
---|
1269 | self._plotter.set_axes('ylabel',ylab) |
---|
1270 | lbl = self._get_label(scan, r, 's', self._title) |
---|
1271 | if isinstance(lbl, list) or isinstance(lbl, tuple): |
---|
1272 | # if 0 <= panelcount < len(lbl): |
---|
1273 | # lbl = lbl[panelcount] |
---|
1274 | # else: |
---|
1275 | # get default label |
---|
1276 | lbl = self._get_label(scan, r, self._panelling, None) |
---|
1277 | self._plotter.set_axes('title',lbl) |
---|
1278 | y=array(scan._get_column(scan._getspectrum,-1)) |
---|
1279 | m = array(scan._get_column(scan._getmask,-1)) |
---|
1280 | y = ma.masked_array(y,mask=logical_not(array(m,copy=False))) |
---|
1281 | x = arange(len(y)) |
---|
1282 | # try to handle spectral data somewhat... |
---|
1283 | l,m = y.shape |
---|
1284 | if m > 1: |
---|
1285 | y=y.mean(axis=1) |
---|
1286 | plotit = self._plotter.plot |
---|
1287 | llbl = self._get_label(scan, r, self._stacking, None) |
---|
1288 | self._plotter.set_line(label=llbl) |
---|
1289 | if len(x) > 0: |
---|
1290 | plotit(x,y) |
---|
1291 | |
---|
1292 | |
---|
1293 | # forwards to matplotlib.Figure.text |
---|
1294 | def figtext(self, *args, **kwargs): |
---|
1295 | """ |
---|
1296 | Add text to figure at location x,y (relative 0-1 coords). |
---|
1297 | This method forwards *args and **kwargs to a Matplotlib method, |
---|
1298 | matplotlib.Figure.text. |
---|
1299 | See the method help for detailed information. |
---|
1300 | """ |
---|
1301 | self._plotter.text(*args, **kwargs) |
---|
1302 | # end matplotlib.Figure.text forwarding function |
---|
1303 | |
---|
1304 | |
---|
1305 | # printing header information |
---|
1306 | @asaplog_post_dec |
---|
1307 | def print_header(self, plot=True, fontsize=9, logger=False, selstr='', extrastr=''): |
---|
1308 | """ |
---|
1309 | print data (scantable) header on the plot and/or logger. |
---|
1310 | Parameters: |
---|
1311 | plot: whether or not print header info on the plot. |
---|
1312 | fontsize: header font size (valid only plot=True) |
---|
1313 | autoscale: whether or not autoscale the plot (valid only plot=True) |
---|
1314 | logger: whether or not print header info on the logger. |
---|
1315 | selstr: additional selection string (not verified) |
---|
1316 | extrastr: additional string to print (not verified) |
---|
1317 | """ |
---|
1318 | if not plot and not logger: |
---|
1319 | return |
---|
1320 | if not self._data: |
---|
1321 | raise RuntimeError("No scantable has been set yet.") |
---|
1322 | # Now header will be printed on plot and/or logger. |
---|
1323 | # Get header information and format it. |
---|
1324 | ssum=self._data.__str__() |
---|
1325 | # Print Observation header to the upper-left corner of plot |
---|
1326 | if plot: |
---|
1327 | headstr=[ssum[ssum.find('Observer:'):ssum.find('Flux Unit:')]] |
---|
1328 | headstr.append(ssum[ssum.find('Beams:'):ssum.find('Observer:')] |
---|
1329 | +ssum[ssum.find('Rest Freqs:'):ssum.find('Abcissa:')]) |
---|
1330 | if extrastr != '': headstr[0]=extrastr+'\n'+headstr[0] |
---|
1331 | #headstr[1]='Data File: '+(filestr or 'unknown')+'\n'+headstr[1] |
---|
1332 | ssel='***Selections***\n'+(selstr+self._data.get_selection().__str__() or 'none') |
---|
1333 | headstr.append(ssel) |
---|
1334 | nstcol=len(headstr) |
---|
1335 | |
---|
1336 | self._plotter.hold() |
---|
1337 | for i in range(nstcol): |
---|
1338 | self._plotter.figure.text(0.03+float(i)/nstcol,0.98, |
---|
1339 | headstr[i], |
---|
1340 | horizontalalignment='left', |
---|
1341 | verticalalignment='top', |
---|
1342 | fontsize=fontsize) |
---|
1343 | import time |
---|
1344 | self._plotter.figure.text(0.99,0.0, |
---|
1345 | time.strftime("%a %d %b %Y %H:%M:%S %Z"), |
---|
1346 | horizontalalignment='right', |
---|
1347 | verticalalignment='bottom',fontsize=8) |
---|
1348 | self._plotter.release() |
---|
1349 | del headstr, ssel |
---|
1350 | if logger: |
---|
1351 | asaplog.push("----------------\n Plot Summary\n----------------") |
---|
1352 | asaplog.push(extrastr) |
---|
1353 | asaplog.push(ssum[ssum.find('Beams:'):]) |
---|
1354 | del ssum |
---|