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 | def new_asaplot(visible=None,**kwargs):
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12 | """
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13 | Returns a new asaplot instance based on the backend settings.
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14 | """
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15 | if visible == None:
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16 | visible = rcParams['plotter.gui']
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17 |
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18 | backend=matplotlib.get_backend()
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19 | if not visible:
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20 | from asap.asaplot import asaplot
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21 | elif backend == 'TkAgg':
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22 | from asap.asaplotgui import asaplotgui as asaplot
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23 | elif backend == 'Qt4Agg':
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24 | from asap.asaplotgui_qt4 import asaplotgui as asaplot
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25 | elif backend == 'GTkAgg':
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26 | from asap.asaplotgui_gtk import asaplotgui as asaplot
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27 | else:
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28 | from asap.asaplot import asaplot
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29 | return asaplot(**kwargs)
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30 |
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31 | class asapplotter:
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32 | """
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33 | The ASAP plotter.
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34 | By default the plotter is set up to plot polarisations
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35 | 'colour stacked' and scantables across panels.
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36 |
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37 | .. note::
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38 |
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39 | Currenly it only plots 'spectra' not Tsys or
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40 | other variables.
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41 |
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42 | """
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43 | def __init__(self, visible=None , **kwargs):
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44 | self._visible = rcParams['plotter.gui']
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45 | if visible is not None:
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46 | self._visible = visible
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47 | self._plotter = self._newplotter(**kwargs)
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48 | # additional tool bar
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49 | self._plotter.figmgr.casabar=self._new_custombar()
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50 |
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51 | self._panelling = None
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52 | self._stacking = None
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53 | self.set_panelling()
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54 | self.set_stacking()
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55 | self._rows = None
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56 | self._cols = None
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57 | self._autoplot = False
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58 | self._minmaxx = None
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59 | self._minmaxy = None
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60 | self._datamask = None
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61 | self._data = None
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62 | self._lmap = None
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63 | self._title = None
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64 | self._ordinate = None
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65 | self._abcissa = None
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66 | self._abcunit = None
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67 | self._usermask = []
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68 | self._maskselection = None
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69 | self._selection = selector()
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70 | self._hist = rcParams['plotter.histogram']
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71 | self._fp = FontProperties()
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72 | self._margins = self.set_margin(refresh=False)
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73 | self._offset = None
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74 | self._startrow = 0
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75 | self._ipanel = -1
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76 | self._panelrows = []
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77 | self._headtext={'string': None, 'textobj': None}
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78 |
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79 | def _translate(self, instr):
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80 | keys = "s b i p t r".split()
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81 | if isinstance(instr, str):
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82 | for key in keys:
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83 | if instr.lower().startswith(key):
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84 | return key
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85 | return None
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86 |
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87 | def _newplotter(self, **kwargs):
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88 | return new_asaplot(self._visible,**kwargs)
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89 |
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90 | def _new_custombar(self):
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91 | backend=matplotlib.get_backend()
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92 | if not self._visible:
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93 | return None
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94 | elif backend == "TkAgg":
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95 | from asap.customgui_tkagg import CustomToolbarTkAgg
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96 | return CustomToolbarTkAgg(self)
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97 | elif backend == "Qt4Agg":
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98 | from asap.customgui_qt4agg import CustomToolbarQT4Agg
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99 | return CustomToolbarQT4Agg(self)
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100 | return None
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101 |
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102 | def casabar_exists(self):
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103 | if not hasattr(self._plotter.figmgr,'casabar'):
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104 | return False
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105 | elif self._plotter.figmgr.casabar:
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106 | return True
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107 | return False
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108 |
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109 | @asaplog_post_dec
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110 | def plot(self, scan=None):
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111 | """
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112 | Plot a scantable.
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113 | Parameters:
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114 | scan: a scantable
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115 | Note:
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116 | If a scantable was specified in a previous call
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117 | to plot, no argument has to be given to 'replot'
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118 | NO checking is done that the abcissas of the scantable
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119 | are consistent e.g. all 'channel' or all 'velocity' etc.
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120 | """
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121 | self._startrow = 0
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122 | self._ipanel = -1
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123 | self._reset_header()
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124 | if self._plotter.is_dead:
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125 | if self.casabar_exists():
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126 | del self._plotter.figmgr.casabar
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127 | self._plotter = self._newplotter()
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128 | self._plotter.figmgr.casabar=self._new_custombar()
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129 | if self.casabar_exists():
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130 | self._plotter.figmgr.casabar.set_pagecounter(1)
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131 | self._panelrows = []
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132 | self._plotter.hold()
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133 | #self._plotter.clear()
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134 | if not self._data and not scan:
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135 | msg = "Input is not a scantable"
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136 | raise TypeError(msg)
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137 | if scan:
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138 | self.set_data(scan, refresh=False)
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139 | self._plot(self._data)
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140 | if self._minmaxy is not None:
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141 | self._plotter.set_limits(ylim=self._minmaxy)
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142 | if self.casabar_exists(): self._plotter.figmgr.casabar.enable_button()
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143 | self._plotter.release()
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144 | self._plotter.tidy()
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145 | self._plotter.show(hardrefresh=False)
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146 | return
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147 |
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148 | def gca(self):
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149 | return self._plotter.figure.gca()
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150 |
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151 | def refresh(self):
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152 | """Do a soft refresh"""
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153 | self._plotter.figure.show()
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154 |
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155 | def create_mask(self, nwin=1, panel=0, color=None):
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156 | """
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157 | Interactively define a mask. It retruns a mask that is equivalent to
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158 | the one created manually with scantable.create_mask.
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159 | Parameters:
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160 | nwin: The number of mask windows to create interactively
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161 | default is 1.
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162 | panel: Which panel to use for mask selection. This is useful
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163 | if different IFs are spread over panels (default 0)
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164 | """
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165 | if self._data is None:
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166 | return []
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167 | outmask = []
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168 | self._plotter.subplot(panel)
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169 | xmin, xmax = self._plotter.axes.get_xlim()
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170 | marg = 0.05*(xmax-xmin)
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171 | self._plotter.axes.set_xlim(xmin-marg, xmax+marg)
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172 | self.refresh()
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173 |
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174 | def cleanup(lines=False, texts=False, refresh=False):
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175 | if lines:
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176 | del self._plotter.axes.lines[-1]
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177 | if texts:
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178 | del self._plotter.axes.texts[-1]
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179 | if refresh:
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180 | self.refresh()
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181 |
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182 | for w in xrange(nwin):
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183 | wpos = []
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184 | self.text(0.05,1.0, "Add start boundary",
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185 | coords="relative", fontsize=10)
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186 | point = self._plotter.get_point()
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187 | cleanup(texts=True)
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188 | if point is None:
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189 | continue
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190 | wpos.append(point[0])
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191 | self.axvline(wpos[0], color=color)
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192 | self.text(0.05,1.0, "Add end boundary", coords="relative", fontsize=10)
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193 | point = self._plotter.get_point()
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194 | cleanup(texts=True, lines=True)
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195 | if point is None:
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196 | self.refresh()
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197 | continue
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198 | wpos.append(point[0])
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199 | self.axvspan(wpos[0], wpos[1], alpha=0.1,
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200 | edgecolor=color, facecolor=color)
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201 | ymin, ymax = self._plotter.axes.get_ylim()
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202 | outmask.append(wpos)
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203 |
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204 | self._plotter.axes.set_xlim(xmin, xmax)
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205 | self.refresh()
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206 | if len(outmask) > 0:
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207 | return self._data.create_mask(*outmask)
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208 | return []
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209 |
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210 | # forwards to matplotlib axes
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211 | def text(self, *args, **kwargs):
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212 | if kwargs.has_key("interactive"):
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213 | if kwargs.pop("interactive"):
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214 | pos = self._plotter.get_point()
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215 | args = tuple(pos)+args
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216 | self._axes_callback("text", *args, **kwargs)
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217 |
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218 | text.__doc__ = matplotlib.axes.Axes.text.__doc__
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219 |
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220 | def arrow(self, *args, **kwargs):
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221 | if kwargs.has_key("interactive"):
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222 | if kwargs.pop("interactive"):
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223 | pos = self._plotter.get_region()
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224 | dpos = (pos[0][0], pos[0][1],
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225 | pos[1][0]-pos[0][0],
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226 | pos[1][1] - pos[0][1])
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227 | args = dpos + args
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228 | self._axes_callback("arrow", *args, **kwargs)
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229 |
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230 | arrow.__doc__ = matplotlib.axes.Axes.arrow.__doc__
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231 |
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232 | def annotate(self, text, xy=None, xytext=None, **kwargs):
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233 | if kwargs.has_key("interactive"):
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234 | if kwargs.pop("interactive"):
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235 | xy = self._plotter.get_point()
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236 | xytext = self._plotter.get_point()
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237 | if not kwargs.has_key("arrowprops"):
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238 | kwargs["arrowprops"] = dict(arrowstyle="->")
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239 | self._axes_callback("annotate", text, xy, xytext, **kwargs)
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240 |
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241 | annotate.__doc__ = matplotlib.axes.Axes.annotate.__doc__
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242 |
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243 | def axvline(self, *args, **kwargs):
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244 | if kwargs.has_key("interactive"):
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245 | if kwargs.pop("interactive"):
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246 | pos = self._plotter.get_point()
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247 | args = (pos[0],)+args
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248 | self._axes_callback("axvline", *args, **kwargs)
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249 |
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250 | axvline.__doc__ = matplotlib.axes.Axes.axvline.__doc__
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251 |
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252 | def axhline(self, *args, **kwargs):
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253 | if kwargs.has_key("interactive"):
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254 | if kwargs.pop("interactive"):
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255 | pos = self._plotter.get_point()
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256 | args = (pos[1],)+args
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257 | self._axes_callback("axhline", *args, **kwargs)
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258 |
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259 | axhline.__doc__ = matplotlib.axes.Axes.axhline.__doc__
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260 |
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261 | def axvspan(self, *args, **kwargs):
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262 | if kwargs.has_key("interactive"):
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263 | if kwargs.pop("interactive"):
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264 | pos = self._plotter.get_region()
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265 | dpos = (pos[0][0], pos[1][0])
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266 | args = dpos + args
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267 | self._axes_callback("axvspan", *args, **kwargs)
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268 | # hack to preventy mpl from redrawing the patch
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269 | # it seem to convert the patch into lines on every draw.
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270 | # This doesn't happen in a test script???
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271 | #del self._plotter.axes.patches[-1]
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272 |
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273 | axvspan.__doc__ = matplotlib.axes.Axes.axvspan.__doc__
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274 |
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275 | def axhspan(self, *args, **kwargs):
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276 | if kwargs.has_key("interactive"):
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277 | if kwargs.pop("interactive"):
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278 | pos = self._plotter.get_region()
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279 | dpos = (pos[0][1], pos[1][1])
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280 | args = dpos + args
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281 | self._axes_callback("axhspan", *args, **kwargs)
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282 | # hack to preventy mpl from redrawing the patch
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283 | # it seem to convert the patch into lines on every draw.
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284 | # This doesn't happen in a test script???
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285 | #del self._plotter.axes.patches[-1]
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286 |
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287 | axhspan.__doc__ = matplotlib.axes.Axes.axhspan.__doc__
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288 |
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289 | def _axes_callback(self, axesfunc, *args, **kwargs):
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290 | panel = 0
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291 | if kwargs.has_key("panel"):
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292 | panel = kwargs.pop("panel")
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293 | coords = None
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294 | if kwargs.has_key("coords"):
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295 | coords = kwargs.pop("coords")
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296 | if coords.lower() == 'world':
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297 | kwargs["transform"] = self._plotter.axes.transData
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298 | elif coords.lower() == 'relative':
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299 | kwargs["transform"] = self._plotter.axes.transAxes
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300 | self._plotter.subplot(panel)
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301 | self._plotter.axes.set_autoscale_on(False)
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302 | getattr(self._plotter.axes, axesfunc)(*args, **kwargs)
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303 | self._plotter.show(False)
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304 | self._plotter.axes.set_autoscale_on(True)
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305 | # end matplotlib.axes fowarding functions
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306 |
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307 | @asaplog_post_dec
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308 | def set_data(self, scan, refresh=True):
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309 | """
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310 | Set a scantable to plot.
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311 | Parameters:
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312 | scan: a scantable
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313 | refresh: True (default) or False. If True, the plot is
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314 | replotted based on the new parameter setting(s).
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315 | Otherwise,the parameter(s) are set without replotting.
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316 | Note:
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317 | The user specified masks and data selections will be reset
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318 | if a new scantable is set. This method should be called before
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319 | setting data selections (set_selection) and/or masks (set_mask).
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320 | """
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321 | from asap import scantable
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322 | if isinstance(scan, scantable):
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323 | if self._data is not None:
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324 | if scan != self._data:
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325 | del self._data
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326 | self._data = scan
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327 | # reset
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328 | self._reset()
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329 | msg = "A new scantable is set to the plotter. "\
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330 | "The masks and data selections are reset."
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331 | asaplog.push( msg )
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332 | else:
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333 | self._data = scan
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334 | self._reset()
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335 | else:
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336 | msg = "Input is not a scantable"
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337 | raise TypeError(msg)
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338 |
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339 | # ranges become invalid when unit changes
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340 | if self._abcunit and self._abcunit != self._data.get_unit():
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341 | self._minmaxx = None
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342 | self._minmaxy = None
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343 | self._abcunit = self._data.get_unit()
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344 | self._datamask = None
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345 | if refresh: self.plot()
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346 |
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347 | @asaplog_post_dec
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348 | def set_mode(self, stacking=None, panelling=None, refresh=True):
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349 | """
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350 | Set the plots look and feel, i.e. what you want to see on the plot.
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351 | Parameters:
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352 | stacking: tell the plotter which variable to plot
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353 | as line colour overlays (default 'pol')
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354 | panelling: tell the plotter which variable to plot
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355 | across multiple panels (default 'scan'
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356 | refresh: True (default) or False. If True, the plot is
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357 | replotted based on the new parameter setting(s).
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358 | Otherwise,the parameter(s) are set without replotting.
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359 | Note:
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360 | Valid modes are:
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361 | 'beam' 'Beam' 'b': Beams
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362 | 'if' 'IF' 'i': IFs
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363 | 'pol' 'Pol' 'p': Polarisations
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364 | 'scan' 'Scan' 's': Scans
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365 | 'time' 'Time' 't': Times
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366 | 'row' 'Row' 'r': Rows
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367 | When either 'stacking' or 'panelling' is set to 'row',
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368 | the other parameter setting is ignored.
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369 | """
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370 | msg = "Invalid mode"
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371 | if not self.set_panelling(panelling) or \
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372 | not self.set_stacking(stacking):
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373 | raise TypeError(msg)
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374 | #if self._panelling == 'r':
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375 | # self._stacking = '_r'
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376 | #if self._stacking == 'r':
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377 | # self._panelling = '_r'
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378 | if refresh and self._data: self.plot(self._data)
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379 | return
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380 |
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381 | def set_panelling(self, what=None):
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382 | """Set the 'panelling' mode i.e. which type of spectra should be
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383 | spread across different panels.
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384 | """
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385 |
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386 | mode = what
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387 | if mode is None:
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388 | mode = rcParams['plotter.panelling']
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389 | md = self._translate(mode)
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390 | if md:
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391 | self._panelling = md
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392 | self._title = None
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393 | #if md == 'r':
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394 | # self._stacking = '_r'
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395 | # you need to reset counters for multi page plotting
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396 | self._reset_counters()
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397 | return True
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398 | return False
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399 |
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400 | def set_layout(self,rows=None,cols=None,refresh=True):
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401 | """
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402 | Set the multi-panel layout, i.e. how many rows and columns plots
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403 | are visible.
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404 | Parameters:
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405 | rows: The number of rows of plots
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406 | cols: The number of columns of plots
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407 | refresh: True (default) or False. If True, the plot is
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408 | replotted based on the new parameter setting(s).
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409 | Otherwise,the parameter(s) are set without replotting.
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410 | Note:
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411 | If no argument is given, the potter reverts to its auto-plot
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412 | behaviour.
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413 | """
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414 | self._rows = rows
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415 | self._cols = cols
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416 | if refresh and self._data: self.plot(self._data)
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417 | return
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418 |
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419 | def set_stacking(self, what=None):
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420 | """Set the 'stacking' mode i.e. which type of spectra should be
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421 | overlayed.
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422 | """
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423 | mode = what
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424 | if mode is None:
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425 | mode = rcParams['plotter.stacking']
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426 | md = self._translate(mode)
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427 | if md:
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428 | self._stacking = md
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429 | self._lmap = None
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430 | #if md == 'r':
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431 | # self._panelling = '_r'
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432 | # you need to reset counters for multi page plotting
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433 | self._reset_counters()
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434 | return True
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435 | return False
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436 |
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437 | def _reset_counters(self):
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438 | self._startrow = 0
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439 | self._ipanel = -1
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440 | self._panelrows = []
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441 |
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442 | def set_range(self,xstart=None,xend=None,ystart=None,yend=None,refresh=True, offset=None):
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443 | """
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444 | Set the range of interest on the abcissa of the plot
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445 | Parameters:
|
---|
446 | [x,y]start,[x,y]end: The start and end points of the 'zoom' window
|
---|
447 | refresh: True (default) or False. If True, the plot is
|
---|
448 | replotted based on the new parameter setting(s).
|
---|
449 | Otherwise,the parameter(s) are set without replotting.
|
---|
450 | offset: shift the abcissa by the given amount. The abcissa label will
|
---|
451 | have '(relative)' appended to it.
|
---|
452 | Note:
|
---|
453 | These become non-sensical when the unit changes.
|
---|
454 | use plotter.set_range() without parameters to reset
|
---|
455 |
|
---|
456 | """
|
---|
457 | self._offset = offset
|
---|
458 | if xstart is None and xend is None:
|
---|
459 | self._minmaxx = None
|
---|
460 | else:
|
---|
461 | self._minmaxx = [xstart,xend]
|
---|
462 | if ystart is None and yend is None:
|
---|
463 | self._minmaxy = None
|
---|
464 | else:
|
---|
465 | self._minmaxy = [ystart,yend]
|
---|
466 | if refresh and self._data: self.plot(self._data)
|
---|
467 | return
|
---|
468 |
|
---|
469 | def set_legend(self, mp=None, fontsize = None, mode = 0, refresh=True):
|
---|
470 | """
|
---|
471 | Specify a mapping for the legend instead of using the default
|
---|
472 | indices:
|
---|
473 | Parameters:
|
---|
474 | mp: a list of 'strings'. This should have the same length
|
---|
475 | as the number of elements on the legend and then maps
|
---|
476 | to the indeces in order. It is possible to uses latex
|
---|
477 | math expression. These have to be enclosed in r'',
|
---|
478 | e.g. r'$x^{2}$'
|
---|
479 | fontsize: The font size of the label (default None)
|
---|
480 | mode: where to display the legend
|
---|
481 | Any other value for loc else disables the legend:
|
---|
482 | 0: auto
|
---|
483 | 1: upper right
|
---|
484 | 2: upper left
|
---|
485 | 3: lower left
|
---|
486 | 4: lower right
|
---|
487 | 5: right
|
---|
488 | 6: center left
|
---|
489 | 7: center right
|
---|
490 | 8: lower center
|
---|
491 | 9: upper center
|
---|
492 | 10: center
|
---|
493 | refresh: True (default) or False. If True, the plot is
|
---|
494 | replotted based on the new parameter setting(s).
|
---|
495 | Otherwise,the parameter(s) are set without replotting.
|
---|
496 |
|
---|
497 | Example:
|
---|
498 | If the data has two IFs/rest frequencies with index 0 and 1
|
---|
499 | for CO and SiO:
|
---|
500 | plotter.set_stacking('i')
|
---|
501 | plotter.set_legend(['CO','SiO'])
|
---|
502 | plotter.plot()
|
---|
503 | plotter.set_legend([r'$^{12}CO$', r'SiO'])
|
---|
504 | """
|
---|
505 | self._lmap = mp
|
---|
506 | self._plotter.legend(mode)
|
---|
507 | if isinstance(fontsize, int):
|
---|
508 | from matplotlib import rc as rcp
|
---|
509 | rcp('legend', fontsize=fontsize)
|
---|
510 | if refresh and self._data: self.plot(self._data)
|
---|
511 | return
|
---|
512 |
|
---|
513 | def set_title(self, title=None, fontsize=None, refresh=True):
|
---|
514 | """
|
---|
515 | Set the title of the plot. If multiple panels are plotted,
|
---|
516 | multiple titles have to be specified.
|
---|
517 | Parameters:
|
---|
518 | refresh: True (default) or False. If True, the plot is
|
---|
519 | replotted based on the new parameter setting(s).
|
---|
520 | Otherwise,the parameter(s) are set without replotting.
|
---|
521 | Example:
|
---|
522 | # two panels are visible on the plotter
|
---|
523 | plotter.set_title(["First Panel","Second Panel"])
|
---|
524 | """
|
---|
525 | self._title = title
|
---|
526 | if isinstance(fontsize, int):
|
---|
527 | from matplotlib import rc as rcp
|
---|
528 | rcp('axes', titlesize=fontsize)
|
---|
529 | if refresh and self._data: self.plot(self._data)
|
---|
530 | return
|
---|
531 |
|
---|
532 | def set_ordinate(self, ordinate=None, fontsize=None, refresh=True):
|
---|
533 | """
|
---|
534 | Set the y-axis label of the plot. If multiple panels are plotted,
|
---|
535 | multiple labels have to be specified.
|
---|
536 | Parameters:
|
---|
537 | ordinate: a list of ordinate labels. None (default) let
|
---|
538 | data determine the labels
|
---|
539 | refresh: True (default) or False. If True, the plot is
|
---|
540 | replotted based on the new parameter setting(s).
|
---|
541 | Otherwise,the parameter(s) are set without replotting.
|
---|
542 | Example:
|
---|
543 | # two panels are visible on the plotter
|
---|
544 | plotter.set_ordinate(["First Y-Axis","Second Y-Axis"])
|
---|
545 | """
|
---|
546 | self._ordinate = ordinate
|
---|
547 | if isinstance(fontsize, int):
|
---|
548 | from matplotlib import rc as rcp
|
---|
549 | rcp('axes', labelsize=fontsize)
|
---|
550 | rcp('ytick', labelsize=fontsize)
|
---|
551 | if refresh and self._data: self.plot(self._data)
|
---|
552 | return
|
---|
553 |
|
---|
554 | def set_abcissa(self, abcissa=None, fontsize=None, refresh=True):
|
---|
555 | """
|
---|
556 | Set the x-axis label of the plot. If multiple panels are plotted,
|
---|
557 | multiple labels have to be specified.
|
---|
558 | Parameters:
|
---|
559 | abcissa: a list of abcissa labels. None (default) let
|
---|
560 | data determine the labels
|
---|
561 | refresh: True (default) or False. If True, the plot is
|
---|
562 | replotted based on the new parameter setting(s).
|
---|
563 | Otherwise,the parameter(s) are set without replotting.
|
---|
564 | Example:
|
---|
565 | # two panels are visible on the plotter
|
---|
566 | plotter.set_ordinate(["First X-Axis","Second X-Axis"])
|
---|
567 | """
|
---|
568 | self._abcissa = abcissa
|
---|
569 | if isinstance(fontsize, int):
|
---|
570 | from matplotlib import rc as rcp
|
---|
571 | rcp('axes', labelsize=fontsize)
|
---|
572 | rcp('xtick', labelsize=fontsize)
|
---|
573 | if refresh and self._data: self.plot(self._data)
|
---|
574 | return
|
---|
575 |
|
---|
576 | def set_colors(self, colmap, refresh=True):
|
---|
577 | """
|
---|
578 | Set the colours to be used. The plotter will cycle through
|
---|
579 | these colours when lines are overlaid (stacking mode).
|
---|
580 | Parameters:
|
---|
581 | colmap: a list of colour names
|
---|
582 | refresh: True (default) or False. If True, the plot is
|
---|
583 | replotted based on the new parameter setting(s).
|
---|
584 | Otherwise,the parameter(s) are set without replotting.
|
---|
585 | Example:
|
---|
586 | plotter.set_colors("red green blue")
|
---|
587 | # If for example four lines are overlaid e.g I Q U V
|
---|
588 | # 'I' will be 'red', 'Q' will be 'green', U will be 'blue'
|
---|
589 | # and 'V' will be 'red' again.
|
---|
590 | """
|
---|
591 | if isinstance(colmap,str):
|
---|
592 | colmap = colmap.split()
|
---|
593 | self._plotter.palette(0, colormap=colmap)
|
---|
594 | if refresh and self._data: self.plot(self._data)
|
---|
595 |
|
---|
596 | # alias for english speakers
|
---|
597 | set_colours = set_colors
|
---|
598 |
|
---|
599 | def set_histogram(self, hist=True, linewidth=None, refresh=True):
|
---|
600 | """
|
---|
601 | Enable/Disable histogram-like plotting.
|
---|
602 | Parameters:
|
---|
603 | hist: True (default) or False. The fisrt default
|
---|
604 | is taken from the .asaprc setting
|
---|
605 | plotter.histogram
|
---|
606 | refresh: True (default) or False. If True, the plot is
|
---|
607 | replotted based on the new parameter setting(s).
|
---|
608 | Otherwise,the parameter(s) are set without replotting.
|
---|
609 | """
|
---|
610 | self._hist = hist
|
---|
611 | if isinstance(linewidth, float) or isinstance(linewidth, int):
|
---|
612 | from matplotlib import rc as rcp
|
---|
613 | rcp('lines', linewidth=linewidth)
|
---|
614 | if refresh and self._data: self.plot(self._data)
|
---|
615 |
|
---|
616 | def set_linestyles(self, linestyles=None, linewidth=None, refresh=True):
|
---|
617 | """
|
---|
618 | Set the linestyles to be used. The plotter will cycle through
|
---|
619 | these linestyles when lines are overlaid (stacking mode) AND
|
---|
620 | only one color has been set.
|
---|
621 | Parameters:
|
---|
622 | linestyles: a list of linestyles to use.
|
---|
623 | 'line', 'dashed', 'dotted', 'dashdot',
|
---|
624 | 'dashdotdot' and 'dashdashdot' are
|
---|
625 | possible
|
---|
626 | refresh: True (default) or False. If True, the plot is
|
---|
627 | replotted based on the new parameter setting(s).
|
---|
628 | Otherwise,the parameter(s) are set without replotting.
|
---|
629 | Example:
|
---|
630 | plotter.set_colors("black")
|
---|
631 | plotter.set_linestyles("line dashed dotted dashdot")
|
---|
632 | # If for example four lines are overlaid e.g I Q U V
|
---|
633 | # 'I' will be 'solid', 'Q' will be 'dashed',
|
---|
634 | # U will be 'dotted' and 'V' will be 'dashdot'.
|
---|
635 | """
|
---|
636 | if isinstance(linestyles,str):
|
---|
637 | linestyles = linestyles.split()
|
---|
638 | self._plotter.palette(color=0,linestyle=0,linestyles=linestyles)
|
---|
639 | if isinstance(linewidth, float) or isinstance(linewidth, int):
|
---|
640 | from matplotlib import rc as rcp
|
---|
641 | rcp('lines', linewidth=linewidth)
|
---|
642 | if refresh and self._data: self.plot(self._data)
|
---|
643 |
|
---|
644 | def set_font(self, refresh=True,**kwargs):
|
---|
645 | """
|
---|
646 | Set font properties.
|
---|
647 | Parameters:
|
---|
648 | family: one of 'sans-serif', 'serif', 'cursive', 'fantasy', 'monospace'
|
---|
649 | style: one of 'normal' (or 'roman'), 'italic' or 'oblique'
|
---|
650 | weight: one of 'normal or 'bold'
|
---|
651 | size: the 'general' font size, individual elements can be adjusted
|
---|
652 | seperately
|
---|
653 | refresh: True (default) or False. If True, the plot is
|
---|
654 | replotted based on the new parameter setting(s).
|
---|
655 | Otherwise,the parameter(s) are set without replotting.
|
---|
656 | """
|
---|
657 | from matplotlib import rc as rcp
|
---|
658 | fdict = {}
|
---|
659 | for k,v in kwargs.iteritems():
|
---|
660 | if v:
|
---|
661 | fdict[k] = v
|
---|
662 | self._fp = FontProperties(**fdict)
|
---|
663 | if refresh and self._data: self.plot(self._data)
|
---|
664 |
|
---|
665 | def set_margin(self,margin=[],refresh=True):
|
---|
666 | """
|
---|
667 | Set margins between subplots and plot edges.
|
---|
668 | Parameters:
|
---|
669 | margin: a list of margins in figure coordinate (0-1),
|
---|
670 | i.e., fraction of the figure width or height.
|
---|
671 | The order of elements should be:
|
---|
672 | [left, bottom, right, top, horizontal space btw panels,
|
---|
673 | vertical space btw panels].
|
---|
674 | refresh: True (default) or False. If True, the plot is
|
---|
675 | replotted based on the new parameter setting(s).
|
---|
676 | Otherwise,the parameter(s) are set without replotting.
|
---|
677 | Note
|
---|
678 | * When margin is not specified, the values are reset to the defaults
|
---|
679 | of matplotlib.
|
---|
680 | * If any element is set to be None, the current value is adopted.
|
---|
681 | """
|
---|
682 | if margin == []: self._margins=self._reset_margin()
|
---|
683 | else:
|
---|
684 | self._margins=[None]*6
|
---|
685 | self._margins[0:len(margin)]=margin
|
---|
686 | #print "panel margin set to ",self._margins
|
---|
687 | if refresh and self._data: self.plot(self._data)
|
---|
688 |
|
---|
689 | def _reset_margin(self):
|
---|
690 | ks=map(lambda x: 'figure.subplot.'+x,
|
---|
691 | ['left','bottom','right','top','hspace','wspace'])
|
---|
692 | return map(matplotlib.rcParams.get,ks)
|
---|
693 |
|
---|
694 | def plot_lines(self, linecat=None, doppler=0.0, deltachan=10, rotate=90.0,
|
---|
695 | location=None):
|
---|
696 | """
|
---|
697 | Plot a line catalog.
|
---|
698 | Parameters:
|
---|
699 | linecat: the linecatalog to plot
|
---|
700 | doppler: the velocity shift to apply to the frequencies
|
---|
701 | deltachan: the number of channels to include each side of the
|
---|
702 | line to determine a local maximum/minimum
|
---|
703 | rotate: the rotation (in degrees) for the text label (default 90.0)
|
---|
704 | location: the location of the line annotation from the 'top',
|
---|
705 | 'bottom' or alternate (None - the default)
|
---|
706 | Notes:
|
---|
707 | If the spectrum is flagged no line will be drawn in that location.
|
---|
708 | """
|
---|
709 | if not self._data:
|
---|
710 | raise RuntimeError("No scantable has been plotted yet.")
|
---|
711 | from asap._asap import linecatalog
|
---|
712 | if not isinstance(linecat, linecatalog):
|
---|
713 | raise ValueError("'linecat' isn't of type linecatalog.")
|
---|
714 | if not self._data.get_unit().endswith("Hz"):
|
---|
715 | raise RuntimeError("Can only overlay linecatalogs when data is in frequency.")
|
---|
716 | from numpy import ma
|
---|
717 | for j in range(len(self._plotter.subplots)):
|
---|
718 | self._plotter.subplot(j)
|
---|
719 | lims = self._plotter.axes.get_xlim()
|
---|
720 | for row in range(linecat.nrow()):
|
---|
721 | # get_frequency returns MHz
|
---|
722 | base = { "GHz": 1000.0, "MHz": 1.0, "Hz": 1.0e-6 }
|
---|
723 | restf = linecat.get_frequency(row)/base[self._data.get_unit()]
|
---|
724 | c = 299792.458
|
---|
725 | freq = restf*(1.0-doppler/c)
|
---|
726 | if lims[0] < freq < lims[1]:
|
---|
727 | if location is None:
|
---|
728 | loc = 'bottom'
|
---|
729 | if row%2: loc='top'
|
---|
730 | else: loc = location
|
---|
731 | maxys = []
|
---|
732 | for line in self._plotter.axes.lines:
|
---|
733 | v = line._x
|
---|
734 | asc = v[0] < v[-1]
|
---|
735 |
|
---|
736 | idx = None
|
---|
737 | if not asc:
|
---|
738 | if v[len(v)-1] <= freq <= v[0]:
|
---|
739 | i = len(v)-1
|
---|
740 | while i>=0 and v[i] < freq:
|
---|
741 | idx = i
|
---|
742 | i-=1
|
---|
743 | else:
|
---|
744 | if v[0] <= freq <= v[len(v)-1]:
|
---|
745 | i = 0
|
---|
746 | while i<len(v) and v[i] < freq:
|
---|
747 | idx = i
|
---|
748 | i+=1
|
---|
749 | if idx is not None:
|
---|
750 | lower = idx - deltachan
|
---|
751 | upper = idx + deltachan
|
---|
752 | if lower < 0: lower = 0
|
---|
753 | if upper > len(v): upper = len(v)
|
---|
754 | s = slice(lower, upper)
|
---|
755 | y = line._y[s]
|
---|
756 | maxy = ma.maximum(y)
|
---|
757 | if isinstance( maxy, float):
|
---|
758 | maxys.append(maxy)
|
---|
759 | if len(maxys):
|
---|
760 | peak = max(maxys)
|
---|
761 | if peak > self._plotter.axes.get_ylim()[1]:
|
---|
762 | loc = 'bottom'
|
---|
763 | else:
|
---|
764 | continue
|
---|
765 | self._plotter.vline_with_label(freq, peak,
|
---|
766 | linecat.get_name(row),
|
---|
767 | location=loc, rotate=rotate)
|
---|
768 | self._plotter.show(hardrefresh=False)
|
---|
769 |
|
---|
770 |
|
---|
771 | def save(self, filename=None, orientation=None, dpi=None):
|
---|
772 | """
|
---|
773 | Save the plot to a file. The known formats are 'png', 'ps', 'eps'.
|
---|
774 | Parameters:
|
---|
775 | filename: The name of the output file. This is optional
|
---|
776 | and autodetects the image format from the file
|
---|
777 | suffix. If non filename is specified a file
|
---|
778 | called 'yyyymmdd_hhmmss.png' is created in the
|
---|
779 | current directory.
|
---|
780 | orientation: optional parameter for postscript only (not eps).
|
---|
781 | 'landscape', 'portrait' or None (default) are valid.
|
---|
782 | If None is choosen for 'ps' output, the plot is
|
---|
783 | automatically oriented to fill the page.
|
---|
784 | dpi: The dpi of the output non-ps plot
|
---|
785 | """
|
---|
786 | self._plotter.save(filename,orientation,dpi)
|
---|
787 | return
|
---|
788 |
|
---|
789 | @asaplog_post_dec
|
---|
790 | def set_mask(self, mask=None, selection=None, refresh=True):
|
---|
791 | """
|
---|
792 | Set a plotting mask for a specific polarization.
|
---|
793 | This is useful for masking out "noise" Pangle outside a source.
|
---|
794 | Parameters:
|
---|
795 | mask: a mask from scantable.create_mask
|
---|
796 | selection: the spectra to apply the mask to.
|
---|
797 | refresh: True (default) or False. If True, the plot is
|
---|
798 | replotted based on the new parameter setting(s).
|
---|
799 | Otherwise,the parameter(s) are set without replotting.
|
---|
800 | Example:
|
---|
801 | select = selector()
|
---|
802 | select.setpolstrings("Pangle")
|
---|
803 | plotter.set_mask(mymask, select)
|
---|
804 | """
|
---|
805 | if not self._data:
|
---|
806 | msg = "Can only set mask after a first call to plot()"
|
---|
807 | raise RuntimeError(msg)
|
---|
808 | if len(mask):
|
---|
809 | if isinstance(mask, list) or isinstance(mask, tuple):
|
---|
810 | self._usermask = array(mask)
|
---|
811 | else:
|
---|
812 | self._usermask = mask
|
---|
813 | if mask is None and selection is None:
|
---|
814 | self._usermask = []
|
---|
815 | self._maskselection = None
|
---|
816 | if isinstance(selection, selector):
|
---|
817 | self._maskselection = {'b': selection.get_beams(),
|
---|
818 | 's': selection.get_scans(),
|
---|
819 | 'i': selection.get_ifs(),
|
---|
820 | 'p': selection.get_pols(),
|
---|
821 | 't': [] }
|
---|
822 | else:
|
---|
823 | self._maskselection = None
|
---|
824 | if refresh: self.plot(self._data)
|
---|
825 |
|
---|
826 | def _slice_indeces(self, data):
|
---|
827 | mn = self._minmaxx[0]
|
---|
828 | mx = self._minmaxx[1]
|
---|
829 | asc = data[0] < data[-1]
|
---|
830 | start=0
|
---|
831 | end = len(data)-1
|
---|
832 | inc = 1
|
---|
833 | if not asc:
|
---|
834 | start = len(data)-1
|
---|
835 | end = 0
|
---|
836 | inc = -1
|
---|
837 | # find min index
|
---|
838 | #while start > 0 and data[start] < mn:
|
---|
839 | # start+= inc
|
---|
840 | minind=start
|
---|
841 | for ind in xrange(start,end+inc,inc):
|
---|
842 | if data[ind] > mn: break
|
---|
843 | minind=ind
|
---|
844 | # find max index
|
---|
845 | #while end > 0 and data[end] > mx:
|
---|
846 | # end-=inc
|
---|
847 | #if end > 0: end +=1
|
---|
848 | maxind=end
|
---|
849 | for ind in xrange(end,start-inc,-inc):
|
---|
850 | if data[ind] < mx: break
|
---|
851 | maxind=ind
|
---|
852 | start=minind
|
---|
853 | end=maxind
|
---|
854 | if start > end:
|
---|
855 | return end,start+1
|
---|
856 | elif start < end:
|
---|
857 | return start,end+1
|
---|
858 | else:
|
---|
859 | return start,end
|
---|
860 |
|
---|
861 | def _reset(self):
|
---|
862 | self._usermask = []
|
---|
863 | self._usermaskspectra = None
|
---|
864 | self._offset = None
|
---|
865 | self.set_selection(None, False)
|
---|
866 | self._reset_header()
|
---|
867 |
|
---|
868 | def _reset_header(self):
|
---|
869 | self._headtext={'string': None, 'textobj': None}
|
---|
870 |
|
---|
871 | def _plot(self, scan):
|
---|
872 | savesel = scan.get_selection()
|
---|
873 | sel = savesel + self._selection
|
---|
874 | order = self._get_sortstring([self._panelling,self._stacking])
|
---|
875 | if order:
|
---|
876 | sel.set_order(order)
|
---|
877 | scan.set_selection(sel)
|
---|
878 | d = {'b': scan.getbeam, 's': scan.getscan,
|
---|
879 | 'i': scan.getif, 'p': scan.getpol, 't': scan.get_time,
|
---|
880 | 'r': int}#, '_r': int}
|
---|
881 |
|
---|
882 | polmodes = dict(zip(self._selection.get_pols(),
|
---|
883 | self._selection.get_poltypes()))
|
---|
884 | # this returns either a tuple of numbers or a length (ncycles)
|
---|
885 | # convert this into lengths
|
---|
886 | n0,nstack0 = self._get_selected_n(scan)
|
---|
887 | if isinstance(n0, int): n = n0
|
---|
888 | else: n = len(n0)
|
---|
889 | if isinstance(nstack0, int): nstack = nstack0
|
---|
890 | else: nstack = len(nstack0)
|
---|
891 | # In case of row stacking
|
---|
892 | rowstack = False
|
---|
893 | titlemode = self._panelling
|
---|
894 | if self._stacking == "r" and self._panelling != "r":
|
---|
895 | rowstack = True
|
---|
896 | titlemode = '_r'
|
---|
897 | nptot = n
|
---|
898 | maxpanel, maxstack = 16,16
|
---|
899 | if nstack > maxstack:
|
---|
900 | msg ="Scan to be overlayed contains more than %d selections.\n" \
|
---|
901 | "Selecting first %d selections..." % (maxstack, maxstack)
|
---|
902 | asaplog.push(msg)
|
---|
903 | asaplog.post('WARN')
|
---|
904 | nstack = min(nstack,maxstack)
|
---|
905 | #n = min(n-self._ipanel-1,maxpanel)
|
---|
906 | n = n-self._ipanel-1
|
---|
907 |
|
---|
908 | ganged = False
|
---|
909 | if n > 1:
|
---|
910 | ganged = rcParams['plotter.ganged']
|
---|
911 | if self._panelling == 'i':
|
---|
912 | ganged = False
|
---|
913 | if self._rows and self._cols:
|
---|
914 | n = min(n,self._rows*self._cols)
|
---|
915 | self._plotter.set_panels(rows=self._rows,cols=self._cols,
|
---|
916 | nplots=n,margin=self._margins,ganged=ganged)
|
---|
917 | else:
|
---|
918 | n = min(n,maxpanel)
|
---|
919 | self._plotter.set_panels(rows=n,cols=0,nplots=n,margin=self._margins,ganged=ganged)
|
---|
920 | else:
|
---|
921 | self._plotter.set_panels(margin=self._margins)
|
---|
922 | #r = 0
|
---|
923 | r = self._startrow
|
---|
924 | nr = scan.nrow()
|
---|
925 | a0,b0 = -1,-1
|
---|
926 | allxlim = []
|
---|
927 | allylim = []
|
---|
928 | #newpanel=True
|
---|
929 | newpanel=False
|
---|
930 | panelcount,stackcount = 0,0
|
---|
931 | # If this is not the first page
|
---|
932 | if r > 0:
|
---|
933 | # panelling value of the prev page
|
---|
934 | a0 = d[self._panelling](r-1)
|
---|
935 | # set the initial stackcount large not to plot
|
---|
936 | # the start row automatically
|
---|
937 | stackcount = nstack
|
---|
938 |
|
---|
939 | while r < nr:
|
---|
940 | a = d[self._panelling](r)
|
---|
941 | b = d[self._stacking](r)
|
---|
942 | if a > a0 and panelcount < n:
|
---|
943 | if n > 1:
|
---|
944 | self._plotter.subplot(panelcount)
|
---|
945 | self._plotter.palette(0)
|
---|
946 | #title
|
---|
947 | xlab = self._abcissa and self._abcissa[panelcount] \
|
---|
948 | or scan._getabcissalabel()
|
---|
949 | if self._offset and not self._abcissa:
|
---|
950 | xlab += " (relative)"
|
---|
951 | ylab = self._ordinate and self._ordinate[panelcount] \
|
---|
952 | or scan._get_ordinate_label()
|
---|
953 | self._plotter.set_axes('xlabel', xlab)
|
---|
954 | self._plotter.set_axes('ylabel', ylab)
|
---|
955 | #lbl = self._get_label(scan, r, self._panelling, self._title)
|
---|
956 | lbl = self._get_label(scan, r, titlemode, self._title)
|
---|
957 | if isinstance(lbl, list) or isinstance(lbl, tuple):
|
---|
958 | if 0 <= panelcount < len(lbl):
|
---|
959 | lbl = lbl[panelcount]
|
---|
960 | else:
|
---|
961 | # get default label
|
---|
962 | #lbl = self._get_label(scan, r, self._panelling, None)
|
---|
963 | lbl = self._get_label(scan, r, titlemode, None)
|
---|
964 | self._plotter.set_axes('title',lbl)
|
---|
965 | newpanel = True
|
---|
966 | stackcount = 0
|
---|
967 | panelcount += 1
|
---|
968 | # save the start row to plot this panel for future revisit.
|
---|
969 | if self._panelling != 'r' and \
|
---|
970 | len(self._panelrows) < self._ipanel+1+panelcount:
|
---|
971 | self._panelrows += [r]
|
---|
972 |
|
---|
973 | #if (b > b0 or newpanel) and stackcount < nstack:
|
---|
974 | if stackcount < nstack and (newpanel or rowstack or (a == a0 and b > b0)):
|
---|
975 | y = []
|
---|
976 | if len(polmodes):
|
---|
977 | y = scan._getspectrum(r, polmodes[scan.getpol(r)])
|
---|
978 | else:
|
---|
979 | y = scan._getspectrum(r)
|
---|
980 | # flag application
|
---|
981 | mr = scan._getflagrow(r)
|
---|
982 | from numpy import ma, array
|
---|
983 | if mr:
|
---|
984 | y = ma.masked_array(y,mask=mr)
|
---|
985 | else:
|
---|
986 | m = scan._getmask(r)
|
---|
987 | from numpy import logical_not, logical_and
|
---|
988 | if self._maskselection and len(self._usermask) == len(m):
|
---|
989 | if d[self._stacking](r) in self._maskselection[self._stacking]:
|
---|
990 | m = logical_and(m, self._usermask)
|
---|
991 | y = ma.masked_array(y,mask=logical_not(array(m,copy=False)))
|
---|
992 |
|
---|
993 | x = array(scan._getabcissa(r))
|
---|
994 | if self._offset:
|
---|
995 | x += self._offset
|
---|
996 | if self._minmaxx is not None:
|
---|
997 | s,e = self._slice_indeces(x)
|
---|
998 | x = x[s:e]
|
---|
999 | y = y[s:e]
|
---|
1000 | if len(x) > 1024 and rcParams['plotter.decimate']:
|
---|
1001 | fac = len(x)/1024
|
---|
1002 | x = x[::fac]
|
---|
1003 | y = y[::fac]
|
---|
1004 | llbl = self._get_label(scan, r, self._stacking, self._lmap)
|
---|
1005 | if isinstance(llbl, list) or isinstance(llbl, tuple):
|
---|
1006 | if 0 <= stackcount < len(llbl):
|
---|
1007 | # use user label
|
---|
1008 | llbl = llbl[stackcount]
|
---|
1009 | else:
|
---|
1010 | # get default label
|
---|
1011 | llbl = self._get_label(scan, r, self._stacking, None)
|
---|
1012 | self._plotter.set_line(label=llbl)
|
---|
1013 | plotit = self._plotter.plot
|
---|
1014 | if self._hist: plotit = self._plotter.hist
|
---|
1015 | if len(x) > 0 and not mr:
|
---|
1016 | plotit(x,y)
|
---|
1017 | xlim= self._minmaxx or [min(x),max(x)]
|
---|
1018 | allxlim += xlim
|
---|
1019 | ylim= self._minmaxy or [ma.minimum(y),ma.maximum(y)]
|
---|
1020 | allylim += ylim
|
---|
1021 | else:
|
---|
1022 | xlim = self._minmaxx or []
|
---|
1023 | allxlim += xlim
|
---|
1024 | ylim= self._minmaxy or []
|
---|
1025 | allylim += ylim
|
---|
1026 | stackcount += 1
|
---|
1027 | a0=a
|
---|
1028 | b0=b
|
---|
1029 | # last in colour stack -> autoscale x
|
---|
1030 | if stackcount == nstack and len(allxlim) > 0:
|
---|
1031 | allxlim.sort()
|
---|
1032 | self._plotter.subplots[panelcount-1]['axes'].set_xlim([allxlim[0],allxlim[-1]])
|
---|
1033 | if ganged:
|
---|
1034 | allxlim = [allxlim[0],allxlim[-1]]
|
---|
1035 | else:
|
---|
1036 | # clear
|
---|
1037 | allxlim =[]
|
---|
1038 |
|
---|
1039 | newpanel = False
|
---|
1040 | #a0=a
|
---|
1041 | #b0=b
|
---|
1042 | # ignore following rows
|
---|
1043 | if (panelcount == n and stackcount == nstack) or (r == nr-1):
|
---|
1044 | # last panel -> autoscale y if ganged
|
---|
1045 | #if rcParams['plotter.ganged'] and len(allylim) > 0:
|
---|
1046 | if ganged and len(allylim) > 0:
|
---|
1047 | allylim.sort()
|
---|
1048 | self._plotter.set_limits(ylim=[allylim[0],allylim[-1]])
|
---|
1049 | break
|
---|
1050 | r+=1 # next row
|
---|
1051 |
|
---|
1052 | # save the current counter for multi-page plotting
|
---|
1053 | self._startrow = r+1
|
---|
1054 | self._ipanel += panelcount
|
---|
1055 | if self.casabar_exists():
|
---|
1056 | if self._ipanel >= nptot-1:
|
---|
1057 | self._plotter.figmgr.casabar.disable_next()
|
---|
1058 | else:
|
---|
1059 | self._plotter.figmgr.casabar.enable_next()
|
---|
1060 | if self._ipanel + 1 - panelcount > 0:
|
---|
1061 | self._plotter.figmgr.casabar.enable_prev()
|
---|
1062 | else:
|
---|
1063 | self._plotter.figmgr.casabar.disable_prev()
|
---|
1064 |
|
---|
1065 | #reset the selector to the scantable's original
|
---|
1066 | scan.set_selection(savesel)
|
---|
1067 |
|
---|
1068 | #temporary switch-off for older matplotlib
|
---|
1069 | #if self._fp is not None:
|
---|
1070 | if self._fp is not None and getattr(self._plotter.figure,'findobj',False):
|
---|
1071 | for o in self._plotter.figure.findobj(Text):
|
---|
1072 | o.set_fontproperties(self._fp)
|
---|
1073 |
|
---|
1074 | def _get_sortstring(self, lorders):
|
---|
1075 | d0 = {'s': 'SCANNO', 'b': 'BEAMNO', 'i':'IFNO',
|
---|
1076 | 'p': 'POLNO', 'c': 'CYCLENO', 't' : 'TIME', 'r':None, '_r':None }
|
---|
1077 | if not (type(lorders) == list) and not (type(lorders) == tuple):
|
---|
1078 | return None
|
---|
1079 | if len(lorders) > 0:
|
---|
1080 | lsorts = []
|
---|
1081 | for order in lorders:
|
---|
1082 | if order == "r":
|
---|
1083 | # don't sort if row panelling/stacking
|
---|
1084 | return None
|
---|
1085 | ssort = d0[order]
|
---|
1086 | if ssort:
|
---|
1087 | lsorts.append(ssort)
|
---|
1088 | return lsorts
|
---|
1089 | return None
|
---|
1090 |
|
---|
1091 | def set_selection(self, selection=None, refresh=True, **kw):
|
---|
1092 | """
|
---|
1093 | Parameters:
|
---|
1094 | selection: a selector object (default unset the selection)
|
---|
1095 | refresh: True (default) or False. If True, the plot is
|
---|
1096 | replotted based on the new parameter setting(s).
|
---|
1097 | Otherwise,the parameter(s) are set without replotting.
|
---|
1098 | """
|
---|
1099 | if selection is None:
|
---|
1100 | # reset
|
---|
1101 | if len(kw) == 0:
|
---|
1102 | self._selection = selector()
|
---|
1103 | else:
|
---|
1104 | # try keywords
|
---|
1105 | for k in kw:
|
---|
1106 | if k not in selector.fields:
|
---|
1107 | raise KeyError("Invalid selection key '%s', valid keys are %s" % (k, selector.fields))
|
---|
1108 | self._selection = selector(**kw)
|
---|
1109 | elif isinstance(selection, selector):
|
---|
1110 | self._selection = selection
|
---|
1111 | else:
|
---|
1112 | raise TypeError("'selection' is not of type selector")
|
---|
1113 |
|
---|
1114 | order = self._get_sortstring([self._panelling,self._stacking])
|
---|
1115 | if order:
|
---|
1116 | self._selection.set_order(order)
|
---|
1117 | if refresh and self._data: self.plot(self._data)
|
---|
1118 |
|
---|
1119 | def _get_selected_n(self, scan):
|
---|
1120 | d1 = {'b': scan.getbeamnos, 's': scan.getscannos,
|
---|
1121 | 'i': scan.getifnos, 'p': scan.getpolnos, 't': scan.ncycle,
|
---|
1122 | 'r': scan.nrow}#, '_r': False}
|
---|
1123 | d2 = { 'b': self._selection.get_beams(),
|
---|
1124 | 's': self._selection.get_scans(),
|
---|
1125 | 'i': self._selection.get_ifs(),
|
---|
1126 | 'p': self._selection.get_pols(),
|
---|
1127 | 't': self._selection.get_cycles(),
|
---|
1128 | 'r': False}#, '_r': 1}
|
---|
1129 | n = d2[self._panelling] or d1[self._panelling]()
|
---|
1130 | nstack = d2[self._stacking] or d1[self._stacking]()
|
---|
1131 | # handle row panelling/stacking
|
---|
1132 | if self._panelling == 'r':
|
---|
1133 | nstack = 1
|
---|
1134 | elif self._stacking == 'r':
|
---|
1135 | n = 1
|
---|
1136 | return n,nstack
|
---|
1137 |
|
---|
1138 | def _get_label(self, scan, row, mode, userlabel=None):
|
---|
1139 | if isinstance(userlabel, list) and len(userlabel) == 0:
|
---|
1140 | userlabel = " "
|
---|
1141 | pms = dict(zip(self._selection.get_pols(),self._selection.get_poltypes()))
|
---|
1142 | if len(pms):
|
---|
1143 | poleval = scan._getpollabel(scan.getpol(row),pms[scan.getpol(row)])
|
---|
1144 | else:
|
---|
1145 | poleval = scan._getpollabel(scan.getpol(row),scan.poltype())
|
---|
1146 | d = {'b': "Beam "+str(scan.getbeam(row)),
|
---|
1147 | #'s': scan._getsourcename(row),
|
---|
1148 | 's': "Scan "+str(scan.getscan(row))+\
|
---|
1149 | " ("+str(scan._getsourcename(row))+")",
|
---|
1150 | 'i': "IF"+str(scan.getif(row)),
|
---|
1151 | 'p': poleval,
|
---|
1152 | 't': str(scan.get_time(row)),
|
---|
1153 | 'r': "row "+str(row),
|
---|
1154 | #'_r': str(scan.get_time(row))+",\nIF"+str(scan.getif(row))+", "+poleval+", Beam"+str(scan.getbeam(row)) }
|
---|
1155 | '_r': "" }
|
---|
1156 | return userlabel or d[mode]
|
---|
1157 |
|
---|
1158 | def plotazel(self, scan=None, outfile=None):
|
---|
1159 | """
|
---|
1160 | plot azimuth and elevation versus time of a scantable
|
---|
1161 | """
|
---|
1162 | visible = rcParams['plotter.gui']
|
---|
1163 | from matplotlib import pylab as PL
|
---|
1164 | from matplotlib.dates import DateFormatter, timezone
|
---|
1165 | from matplotlib.dates import HourLocator, MinuteLocator,SecondLocator, DayLocator
|
---|
1166 | from matplotlib.ticker import MultipleLocator
|
---|
1167 | from numpy import array, pi
|
---|
1168 | if not visible or not self._visible:
|
---|
1169 | PL.ioff()
|
---|
1170 | from matplotlib.backends.backend_agg import FigureCanvasAgg
|
---|
1171 | PL.gcf().canvas.switch_backends(FigureCanvasAgg)
|
---|
1172 | self._data = scan
|
---|
1173 | self._outfile = outfile
|
---|
1174 | dates = self._data.get_time(asdatetime=True)
|
---|
1175 | t = PL.date2num(dates)
|
---|
1176 | tz = timezone('UTC')
|
---|
1177 | PL.cla()
|
---|
1178 | PL.ioff()
|
---|
1179 | PL.clf()
|
---|
1180 | # Adjust subplot margins
|
---|
1181 | if len(self._margins) != 6:
|
---|
1182 | self.set_margin(refresh=False)
|
---|
1183 | lef, bot, rig, top, wsp, hsp = self._margins
|
---|
1184 | PL.gcf().subplots_adjust(left=lef,bottom=bot,right=rig,top=top,
|
---|
1185 | wspace=wsp,hspace=hsp)
|
---|
1186 |
|
---|
1187 | tdel = max(t) - min(t)
|
---|
1188 | ax = PL.subplot(2,1,1)
|
---|
1189 | el = array(self._data.get_elevation())*180./pi
|
---|
1190 | PL.ylabel('El [deg.]')
|
---|
1191 | dstr = dates[0].strftime('%Y/%m/%d')
|
---|
1192 | if tdel > 1.0:
|
---|
1193 | dstr2 = dates[len(dates)-1].strftime('%Y/%m/%d')
|
---|
1194 | dstr = dstr + " - " + dstr2
|
---|
1195 | majloc = DayLocator()
|
---|
1196 | minloc = HourLocator(range(0,23,12))
|
---|
1197 | timefmt = DateFormatter("%b%d")
|
---|
1198 | elif tdel > 24./60.:
|
---|
1199 | timefmt = DateFormatter('%H:%M')
|
---|
1200 | majloc = HourLocator()
|
---|
1201 | minloc = MinuteLocator(30)
|
---|
1202 | else:
|
---|
1203 | timefmt = DateFormatter('%H:%M')
|
---|
1204 | majloc = MinuteLocator(interval=5)
|
---|
1205 | minloc = SecondLocator(30)
|
---|
1206 |
|
---|
1207 | PL.title(dstr)
|
---|
1208 | if tdel == 0.0:
|
---|
1209 | th = (t - PL.floor(t))*24.0
|
---|
1210 | PL.plot(th,el,'o',markersize=2, markerfacecolor='b', markeredgecolor='b')
|
---|
1211 | else:
|
---|
1212 | PL.plot_date(t,el,'o', markersize=2, markerfacecolor='b', markeredgecolor='b',tz=tz)
|
---|
1213 | #ax.grid(True)
|
---|
1214 | ax.xaxis.set_major_formatter(timefmt)
|
---|
1215 | ax.xaxis.set_major_locator(majloc)
|
---|
1216 | ax.xaxis.set_minor_locator(minloc)
|
---|
1217 | ax.yaxis.grid(True)
|
---|
1218 | yloc = MultipleLocator(30)
|
---|
1219 | ax.set_ylim(0,90)
|
---|
1220 | ax.yaxis.set_major_locator(yloc)
|
---|
1221 | if tdel > 1.0:
|
---|
1222 | labels = ax.get_xticklabels()
|
---|
1223 | # PL.setp(labels, fontsize=10, rotation=45)
|
---|
1224 | PL.setp(labels, fontsize=10)
|
---|
1225 |
|
---|
1226 | # Az plot
|
---|
1227 | az = array(self._data.get_azimuth())*180./pi
|
---|
1228 | if min(az) < 0:
|
---|
1229 | for irow in range(len(az)):
|
---|
1230 | if az[irow] < 0: az[irow] += 360.0
|
---|
1231 |
|
---|
1232 | ax2 = PL.subplot(2,1,2)
|
---|
1233 | #PL.xlabel('Time (UT [hour])')
|
---|
1234 | PL.ylabel('Az [deg.]')
|
---|
1235 | if tdel == 0.0:
|
---|
1236 | PL.plot(th,az,'o',markersize=2, markeredgecolor='b',markerfacecolor='b')
|
---|
1237 | else:
|
---|
1238 | PL.plot_date(t,az,'o', markersize=2,markeredgecolor='b',markerfacecolor='b',tz=tz)
|
---|
1239 | ax2.xaxis.set_major_formatter(timefmt)
|
---|
1240 | ax2.xaxis.set_major_locator(majloc)
|
---|
1241 | ax2.xaxis.set_minor_locator(minloc)
|
---|
1242 | #ax2.grid(True)
|
---|
1243 | ax2.set_ylim(0,360)
|
---|
1244 | ax2.yaxis.grid(True)
|
---|
1245 | #hfmt = DateFormatter('%H')
|
---|
1246 | #hloc = HourLocator()
|
---|
1247 | yloc = MultipleLocator(60)
|
---|
1248 | ax2.yaxis.set_major_locator(yloc)
|
---|
1249 | if tdel > 1.0:
|
---|
1250 | labels = ax2.get_xticklabels()
|
---|
1251 | PL.setp(labels, fontsize=10)
|
---|
1252 | PL.xlabel('Time (UT [day])')
|
---|
1253 | else:
|
---|
1254 | PL.xlabel('Time (UT [hour])')
|
---|
1255 |
|
---|
1256 | PL.ion()
|
---|
1257 | PL.draw()
|
---|
1258 | if matplotlib.get_backend() == 'Qt4Agg': PL.gcf().show()
|
---|
1259 | if (self._outfile is not None):
|
---|
1260 | PL.savefig(self._outfile)
|
---|
1261 |
|
---|
1262 | def plotpointing(self, scan=None, outfile=None):
|
---|
1263 | """
|
---|
1264 | plot telescope pointings
|
---|
1265 | """
|
---|
1266 | visible = rcParams['plotter.gui']
|
---|
1267 | from matplotlib import pylab as PL
|
---|
1268 | from numpy import array, pi
|
---|
1269 | if not visible or not self._visible:
|
---|
1270 | PL.ioff()
|
---|
1271 | from matplotlib.backends.backend_agg import FigureCanvasAgg
|
---|
1272 | PL.gcf().canvas.switch_backends(FigureCanvasAgg)
|
---|
1273 | self._data = scan
|
---|
1274 | self._outfile = outfile
|
---|
1275 | dir = array(self._data.get_directionval()).transpose()
|
---|
1276 | ra = dir[0]*180./pi
|
---|
1277 | dec = dir[1]*180./pi
|
---|
1278 | PL.cla()
|
---|
1279 | #PL.ioff()
|
---|
1280 | PL.clf()
|
---|
1281 | # Adjust subplot margins
|
---|
1282 | if len(self._margins) != 6:
|
---|
1283 | self.set_margin(refresh=False)
|
---|
1284 | lef, bot, rig, top, wsp, hsp = self._margins
|
---|
1285 | PL.gcf().subplots_adjust(left=lef,bottom=bot,right=rig,top=top,
|
---|
1286 | wspace=wsp,hspace=hsp)
|
---|
1287 | ax = PL.gca()
|
---|
1288 | #ax = PL.axes([0.1,0.1,0.8,0.8])
|
---|
1289 | #ax = PL.axes([0.1,0.1,0.8,0.8])
|
---|
1290 | ax.set_aspect('equal')
|
---|
1291 | PL.plot(ra, dec, 'b,')
|
---|
1292 | PL.xlabel('RA [deg.]')
|
---|
1293 | PL.ylabel('Declination [deg.]')
|
---|
1294 | PL.title('Telescope pointings')
|
---|
1295 | [xmin,xmax,ymin,ymax] = PL.axis()
|
---|
1296 | PL.axis([xmax,xmin,ymin,ymax])
|
---|
1297 | PL.ion()
|
---|
1298 | PL.draw()
|
---|
1299 | if matplotlib.get_backend() == 'Qt4Agg': PL.gcf().show()
|
---|
1300 | if (self._outfile is not None):
|
---|
1301 | PL.savefig(self._outfile)
|
---|
1302 |
|
---|
1303 | # plot total power data
|
---|
1304 | # plotting in time is not yet implemented..
|
---|
1305 | @asaplog_post_dec
|
---|
1306 | def plottp(self, scan=None, outfile=None):
|
---|
1307 | if self._plotter.is_dead:
|
---|
1308 | if self.casabar_exists():
|
---|
1309 | del self._plotter.figmgr.casabar
|
---|
1310 | self._plotter = self._newplotter()
|
---|
1311 | self._plotter.figmgr.casabar=self._new_custombar()
|
---|
1312 | self._plotter.hold()
|
---|
1313 | self._plotter.clear()
|
---|
1314 | from asap import scantable
|
---|
1315 | if not self._data and not scan:
|
---|
1316 | msg = "Input is not a scantable"
|
---|
1317 | raise TypeError(msg)
|
---|
1318 | if isinstance(scan, scantable):
|
---|
1319 | if self._data is not None:
|
---|
1320 | if scan != self._data:
|
---|
1321 | self._data = scan
|
---|
1322 | # reset
|
---|
1323 | self._reset()
|
---|
1324 | else:
|
---|
1325 | self._data = scan
|
---|
1326 | self._reset()
|
---|
1327 | # ranges become invalid when abcissa changes?
|
---|
1328 | #if self._abcunit and self._abcunit != self._data.get_unit():
|
---|
1329 | # self._minmaxx = None
|
---|
1330 | # self._minmaxy = None
|
---|
1331 | # self._abcunit = self._data.get_unit()
|
---|
1332 | # self._datamask = None
|
---|
1333 |
|
---|
1334 | # Adjust subplot margins
|
---|
1335 | if len(self._margins) !=6: self.set_margin(refresh=False)
|
---|
1336 | lef, bot, rig, top, wsp, hsp = self._margins
|
---|
1337 | self._plotter.figure.subplots_adjust(
|
---|
1338 | left=lef,bottom=bot,right=rig,top=top,wspace=wsp,hspace=hsp)
|
---|
1339 | if self.casabar_exists(): self._plotter.figmgr.casabar.disable_button()
|
---|
1340 | self._plottp(self._data)
|
---|
1341 | if self._minmaxy is not None:
|
---|
1342 | self._plotter.set_limits(ylim=self._minmaxy)
|
---|
1343 | self._plotter.release()
|
---|
1344 | self._plotter.tidy()
|
---|
1345 | self._plotter.show(hardrefresh=False)
|
---|
1346 | return
|
---|
1347 |
|
---|
1348 | def _plottp(self,scan):
|
---|
1349 | """
|
---|
1350 | private method for plotting total power data
|
---|
1351 | """
|
---|
1352 | from numpy import ma, array, arange, logical_not
|
---|
1353 | r=0
|
---|
1354 | nr = scan.nrow()
|
---|
1355 | a0,b0 = -1,-1
|
---|
1356 | allxlim = []
|
---|
1357 | allylim = []
|
---|
1358 | y=[]
|
---|
1359 | self._plotter.set_panels()
|
---|
1360 | self._plotter.palette(0)
|
---|
1361 | #title
|
---|
1362 | #xlab = self._abcissa and self._abcissa[panelcount] \
|
---|
1363 | # or scan._getabcissalabel()
|
---|
1364 | #ylab = self._ordinate and self._ordinate[panelcount] \
|
---|
1365 | # or scan._get_ordinate_label()
|
---|
1366 | xlab = self._abcissa or 'row number' #or Time
|
---|
1367 | ylab = self._ordinate or scan._get_ordinate_label()
|
---|
1368 | self._plotter.set_axes('xlabel',xlab)
|
---|
1369 | self._plotter.set_axes('ylabel',ylab)
|
---|
1370 | lbl = self._get_label(scan, r, 's', self._title)
|
---|
1371 | if isinstance(lbl, list) or isinstance(lbl, tuple):
|
---|
1372 | # if 0 <= panelcount < len(lbl):
|
---|
1373 | # lbl = lbl[panelcount]
|
---|
1374 | # else:
|
---|
1375 | # get default label
|
---|
1376 | lbl = self._get_label(scan, r, self._panelling, None)
|
---|
1377 | self._plotter.set_axes('title',lbl)
|
---|
1378 | y=array(scan._get_column(scan._getspectrum,-1))
|
---|
1379 | m = array(scan._get_column(scan._getmask,-1))
|
---|
1380 | y = ma.masked_array(y,mask=logical_not(array(m,copy=False)))
|
---|
1381 | x = arange(len(y))
|
---|
1382 | # try to handle spectral data somewhat...
|
---|
1383 | l,m = y.shape
|
---|
1384 | if m > 1:
|
---|
1385 | y=y.mean(axis=1)
|
---|
1386 | plotit = self._plotter.plot
|
---|
1387 | llbl = self._get_label(scan, r, self._stacking, None)
|
---|
1388 | self._plotter.set_line(label=llbl)
|
---|
1389 | if len(x) > 0:
|
---|
1390 | plotit(x,y)
|
---|
1391 |
|
---|
1392 |
|
---|
1393 | # forwards to matplotlib.Figure.text
|
---|
1394 | def figtext(self, *args, **kwargs):
|
---|
1395 | """
|
---|
1396 | Add text to figure at location x,y (relative 0-1 coords).
|
---|
1397 | This method forwards *args and **kwargs to a Matplotlib method,
|
---|
1398 | matplotlib.Figure.text.
|
---|
1399 | See the method help for detailed information.
|
---|
1400 | """
|
---|
1401 | self._plotter.text(*args, **kwargs)
|
---|
1402 | # end matplotlib.Figure.text forwarding function
|
---|
1403 |
|
---|
1404 |
|
---|
1405 | # printing header information
|
---|
1406 | @asaplog_post_dec
|
---|
1407 | def print_header(self, plot=True, fontsize=9, logger=False, selstr='', extrastr=''):
|
---|
1408 | """
|
---|
1409 | print data (scantable) header on the plot and/or logger.
|
---|
1410 | To plot the header on the plot, this method should be called after
|
---|
1411 | plotting spectra by the method, asapplotter.plot.
|
---|
1412 | Parameters:
|
---|
1413 | plot: whether or not print header info on the plot.
|
---|
1414 | fontsize: header font size (valid only plot=True)
|
---|
1415 | logger: whether or not print header info on the logger.
|
---|
1416 | selstr: additional selection string (not verified)
|
---|
1417 | extrastr: additional string to print at the beginning (not verified)
|
---|
1418 | """
|
---|
1419 | if not plot and not logger:
|
---|
1420 | return
|
---|
1421 | if not self._data:
|
---|
1422 | raise RuntimeError("No scantable has been set yet.")
|
---|
1423 | # Now header will be printed on plot and/or logger.
|
---|
1424 | # Get header information and format it.
|
---|
1425 | ssum=self._data._list_header()
|
---|
1426 | # Print Observation header to the upper-left corner of plot
|
---|
1427 | headstr=[ssum[0:ssum.find('Obs. Type:')]]
|
---|
1428 | headstr.append(ssum[ssum.find('Obs. Type:'):ssum.find('Flux Unit:')])
|
---|
1429 | if extrastr != '':
|
---|
1430 | headstr[0]=extrastr+'\n'+headstr[0]
|
---|
1431 | self._headtext['extrastr'] = extrastr
|
---|
1432 | if selstr != '':
|
---|
1433 | selstr += '\n'
|
---|
1434 | self._headtext['selstr'] = selstr
|
---|
1435 | ssel=(selstr+self._data.get_selection().__str__()+self._selection.__str__() or 'none')
|
---|
1436 | headstr.append('***Selections***\n'+ssel)
|
---|
1437 |
|
---|
1438 | if plot:
|
---|
1439 | self._plotter.hold()
|
---|
1440 | self._header_plot(headstr,fontsize=fontsize)
|
---|
1441 | import time
|
---|
1442 | self._plotter.figure.text(0.99,0.01,
|
---|
1443 | time.strftime("%a %d %b %Y %H:%M:%S %Z"),
|
---|
1444 | horizontalalignment='right',
|
---|
1445 | verticalalignment='bottom',fontsize=8)
|
---|
1446 | self._plotter.release()
|
---|
1447 | if logger:
|
---|
1448 | selstr = "Selections: "+ssel
|
---|
1449 | asaplog.push("----------------\n Plot Summary\n----------------")
|
---|
1450 | asaplog.push(extrastr)
|
---|
1451 | asaplog.push(ssum[0:ssum.find('Selection:')]\
|
---|
1452 | + selstr)
|
---|
1453 | self._headtext['string'] = headstr
|
---|
1454 | del ssel, ssum, headstr
|
---|
1455 |
|
---|
1456 | def _header_plot(self, texts, fontsize=9):
|
---|
1457 | self._headtext['textobj']=[]
|
---|
1458 | nstcol=len(texts)
|
---|
1459 | for i in range(nstcol):
|
---|
1460 | self._headtext['textobj'].append(
|
---|
1461 | self._plotter.figure.text(0.03+float(i)/nstcol,0.98,
|
---|
1462 | texts[i],
|
---|
1463 | horizontalalignment='left',
|
---|
1464 | verticalalignment='top',
|
---|
1465 | fontsize=fontsize))
|
---|
1466 |
|
---|
1467 | def clear_header(self):
|
---|
1468 | if not self._headtext['textobj']:
|
---|
1469 | asaplog.push("No header has been plotted. Exit without any operation")
|
---|
1470 | asaplog.post("WARN")
|
---|
1471 | else:
|
---|
1472 | self._plotter.hold()
|
---|
1473 | for textobj in self._headtext['textobj']:
|
---|
1474 | #if textobj.get_text() in self._headstring:
|
---|
1475 | try:
|
---|
1476 | textobj.remove()
|
---|
1477 | except NotImplementedError:
|
---|
1478 | self._plotter.figure.texts.pop(self._plotter.figure.texts.index(textobj))
|
---|
1479 | self._plotter.release()
|
---|
1480 | self._reset_header()
|
---|