1 | from asap import rcParams, print_log, selector
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2 | import matplotlib.axes
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3 | import re
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4 |
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5 | class asapplotter:
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6 | """
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7 | The ASAP plotter.
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8 | By default the plotter is set up to plot polarisations
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9 | 'colour stacked' and scantables across panels.
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10 | Note:
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11 | Currenly it only plots 'spectra' not Tsys or
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12 | other variables.
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13 | """
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14 | def __init__(self, visible=None):
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15 | self._visible = rcParams['plotter.gui']
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16 | if visible is not None:
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17 | self._visible = visible
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18 | self._plotter = self._newplotter()
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19 |
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20 | self._panelling = None
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21 | self._stacking = None
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22 | self.set_panelling()
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23 | self.set_stacking()
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24 | self._rows = None
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25 | self._cols = None
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26 | self._autoplot = False
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27 | self._minmaxx = None
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28 | self._minmaxy = None
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29 | self._datamask = None
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30 | self._data = None
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31 | self._lmap = None
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32 | self._title = None
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33 | self._ordinate = None
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34 | self._abcissa = None
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35 | self._abcunit = None
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36 | self._usermask = []
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37 | self._maskselection = None
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38 | self._selection = selector()
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39 | self._hist = rcParams['plotter.histogram']
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40 |
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41 | def _translate(self, instr):
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42 | keys = "s b i p t".split()
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43 | if isinstance(instr, str):
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44 | for key in keys:
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45 | if instr.lower().startswith(key):
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46 | return key
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47 | return None
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48 |
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49 | def _newplotter(self):
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50 | if self._visible:
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51 | from asap.asaplotgui import asaplotgui as asaplot
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52 | else:
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53 | from asap.asaplot import asaplot
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54 | return asaplot()
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55 |
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56 |
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57 | def plot(self, scan=None):
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58 | """
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59 | Plot a scantable.
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60 | Parameters:
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61 | scan: a scantable
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62 | Note:
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63 | If a scantable was specified in a previous call
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64 | to plot, no argument has to be given to 'replot'
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65 | NO checking is done that the abcissas of the scantable
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66 | are consistent e.g. all 'channel' or all 'velocity' etc.
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67 | """
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68 | if self._plotter.is_dead:
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69 | self._plotter = self._newplotter()
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70 | self._plotter.hold()
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71 | self._plotter.clear()
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72 | from asap import scantable
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73 | if not self._data and not scan:
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74 | msg = "Input is not a scantable"
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75 | if rcParams['verbose']:
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76 | print msg
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77 | return
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78 | raise TypeError(msg)
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79 | if isinstance(scan, scantable):
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80 | if self._data is not None:
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81 | if scan != self._data:
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82 | self._data = scan
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83 | # reset
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84 | self._reset()
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85 | else:
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86 | self._data = scan
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87 | self._reset()
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88 | # ranges become invalid when unit changes
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89 | if self._abcunit and self._abcunit != self._data.get_unit():
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90 | self._minmaxx = None
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91 | self._minmaxy = None
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92 | self._abcunit = self._data.get_unit()
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93 | self._datamask = None
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94 | self._plot(self._data)
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95 | if self._minmaxy is not None:
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96 | self._plotter.set_limits(ylim=self._minmaxy)
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97 | self._plotter.release()
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98 | self._plotter.tidy()
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99 | self._plotter.show(hardrefresh=False)
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100 | print_log()
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101 | return
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102 |
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103 |
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104 | # forwards to matplotlib axes
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105 | def text(self, *args, **kwargs):
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106 | self._axes_callback("text", *args, **kwargs)
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107 | text.__doc__ = matplotlib.axes.Axes.text.__doc__
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108 | def arrow(self, *args, **kwargs):
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109 | self._axes_callback("arrow", *args, **kwargs)
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110 | arrow.__doc__ = matplotlib.axes.Axes.arrow.__doc__
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111 | def axvline(self, *args, **kwargs):
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112 | self._axes_callback("axvline", *args, **kwargs)
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113 | axvline.__doc__ = matplotlib.axes.Axes.axvline.__doc__
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114 | def axhline(self, *args, **kwargs):
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115 | self._axes_callback("axhline", *args, **kwargs)
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116 | axhline.__doc__ = matplotlib.axes.Axes.axhline.__doc__
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117 | def axvspan(self, *args, **kwargs):
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118 | self._axes_callback("axvspan", *args, **kwargs)
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119 | # hack to preventy mpl from redrawing the patch
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120 | # it seem to convert the patch into lines on every draw.
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121 | # This doesn't happen in a test script???
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122 | del self._plotter.axes.patches[-1]
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123 | axvspan.__doc__ = matplotlib.axes.Axes.axvspan.__doc__
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124 |
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125 | def axhspan(self, *args, **kwargs):
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126 | self._axes_callback("axhspan", *args, **kwargs)
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127 | # hack to preventy mpl from redrawing the patch
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128 | # it seem to convert the patch into lines on every draw.
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129 | # This doesn't happen in a test script???
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130 | del self._plotter.axes.patches[-1]
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131 | axhspan.__doc__ = matplotlib.axes.Axes.axhspan.__doc__
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132 |
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133 | def _axes_callback(self, axesfunc, *args, **kwargs):
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134 | panel = 0
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135 | if kwargs.has_key("panel"):
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136 | panel = kwargs.pop("panel")
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137 | coords = None
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138 | if kwargs.has_key("coords"):
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139 | coords = kwargs.pop("coords")
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140 | if coords.lower() == 'world':
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141 | kwargs["transform"] = self._plotter.axes.transData
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142 | elif coords.lower() == 'relative':
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143 | kwargs["transform"] = self._plotter.axes.transAxes
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144 | self._plotter.subplot(panel)
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145 | self._plotter.axes.set_autoscale_on(False)
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146 | getattr(self._plotter.axes, axesfunc)(*args, **kwargs)
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147 | self._plotter.show(False)
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148 | self._plotter.axes.set_autoscale_on(True)
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149 | # end matplotlib.axes fowarding functions
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150 |
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151 | def set_mode(self, stacking=None, panelling=None):
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152 | """
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153 | Set the plots look and feel, i.e. what you want to see on the plot.
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154 | Parameters:
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155 | stacking: tell the plotter which variable to plot
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156 | as line colour overlays (default 'pol')
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157 | panelling: tell the plotter which variable to plot
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158 | across multiple panels (default 'scan'
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159 | Note:
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160 | Valid modes are:
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161 | 'beam' 'Beam' 'b': Beams
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162 | 'if' 'IF' 'i': IFs
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163 | 'pol' 'Pol' 'p': Polarisations
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164 | 'scan' 'Scan' 's': Scans
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165 | 'time' 'Time' 't': Times
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166 | """
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167 | msg = "Invalid mode"
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168 | if not self.set_panelling(panelling) or \
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169 | not self.set_stacking(stacking):
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170 | if rcParams['verbose']:
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171 | print msg
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172 | return
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173 | else:
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174 | raise TypeError(msg)
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175 | if self._data: self.plot(self._data)
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176 | return
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177 |
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178 | def set_panelling(self, what=None):
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179 | mode = what
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180 | if mode is None:
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181 | mode = rcParams['plotter.panelling']
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182 | md = self._translate(mode)
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183 | if md:
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184 | self._panelling = md
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185 | self._title = None
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186 | return True
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187 | return False
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188 |
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189 | def set_layout(self,rows=None,cols=None):
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190 | """
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191 | Set the multi-panel layout, i.e. how many rows and columns plots
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192 | are visible.
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193 | Parameters:
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194 | rows: The number of rows of plots
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195 | cols: The number of columns of plots
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196 | Note:
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197 | If no argument is given, the potter reverts to its auto-plot
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198 | behaviour.
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199 | """
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200 | self._rows = rows
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201 | self._cols = cols
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202 | if self._data: self.plot(self._data)
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203 | return
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204 |
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205 | def set_stacking(self, what=None):
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206 | mode = what
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207 | if mode is None:
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208 | mode = rcParams['plotter.stacking']
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209 | md = self._translate(mode)
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210 | if md:
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211 | self._stacking = md
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212 | self._lmap = None
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213 | return True
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214 | return False
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215 |
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216 | def set_range(self,xstart=None,xend=None,ystart=None,yend=None):
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217 | """
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218 | Set the range of interest on the abcissa of the plot
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219 | Parameters:
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220 | [x,y]start,[x,y]end: The start and end points of the 'zoom' window
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221 | Note:
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222 | These become non-sensical when the unit changes.
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223 | use plotter.set_range() without parameters to reset
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224 |
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225 | """
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226 | if xstart is None and xend is None:
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227 | self._minmaxx = None
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228 | else:
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229 | self._minmaxx = [xstart,xend]
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230 | if ystart is None and yend is None:
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231 | self._minmaxy = None
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232 | else:
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233 | self._minmaxy = [ystart,yend]
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234 | if self._data: self.plot(self._data)
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235 | return
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236 |
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237 | def set_legend(self, mp=None, fontsize = None, mode = 0):
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238 | """
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239 | Specify a mapping for the legend instead of using the default
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240 | indices:
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241 | Parameters:
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242 | mp: a list of 'strings'. This should have the same length
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243 | as the number of elements on the legend and then maps
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244 | to the indeces in order. It is possible to uses latex
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245 | math expression. These have to be enclosed in r'',
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246 | e.g. r'$x^{2}$'
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247 | fontsize: The font size of the label (default None)
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248 | mode: where to display the legend
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249 | Any other value for loc else disables the legend:
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250 | 0: auto
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251 | 1: upper right
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252 | 2: upper left
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253 | 3: lower left
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254 | 4: lower right
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255 | 5: right
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256 | 6: center left
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257 | 7: center right
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258 | 8: lower center
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259 | 9: upper center
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260 | 10: center
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261 |
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262 | Example:
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263 | If the data has two IFs/rest frequencies with index 0 and 1
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264 | for CO and SiO:
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265 | plotter.set_stacking('i')
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266 | plotter.set_legend(['CO','SiO'])
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267 | plotter.plot()
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268 | plotter.set_legend([r'$^{12}CO$', r'SiO'])
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269 | """
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270 | self._lmap = mp
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271 | self._plotter.legend(mode)
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272 | if isinstance(fontsize, int):
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273 | from matplotlib import rc as rcp
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274 | rcp('legend', fontsize=fontsize)
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275 | if self._data:
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276 | self.plot(self._data)
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277 | return
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278 |
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279 | def set_title(self, title=None, fontsize=None):
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280 | """
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281 | Set the title of the plot. If multiple panels are plotted,
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282 | multiple titles have to be specified.
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283 | Example:
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284 | # two panels are visible on the plotter
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285 | plotter.set_title(["First Panel","Second Panel"])
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286 | """
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287 | self._title = title
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288 | if isinstance(fontsize, int):
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289 | from matplotlib import rc as rcp
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290 | rcp('axes', titlesize=fontsize)
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291 | if self._data: self.plot(self._data)
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292 | return
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293 |
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294 | def set_ordinate(self, ordinate=None, fontsize=None):
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295 | """
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296 | Set the y-axis label of the plot. If multiple panels are plotted,
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297 | multiple labels have to be specified.
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298 | Parameters:
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299 | ordinate: a list of ordinate labels. None (default) let
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300 | data determine the labels
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301 | Example:
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302 | # two panels are visible on the plotter
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303 | plotter.set_ordinate(["First Y-Axis","Second Y-Axis"])
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304 | """
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305 | self._ordinate = ordinate
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306 | if isinstance(fontsize, int):
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307 | from matplotlib import rc as rcp
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308 | rcp('axes', labelsize=fontsize)
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309 | rcp('ytick', labelsize=fontsize)
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310 | if self._data: self.plot(self._data)
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311 | return
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312 |
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313 | def set_abcissa(self, abcissa=None, fontsize=None):
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314 | """
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315 | Set the x-axis label of the plot. If multiple panels are plotted,
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316 | multiple labels have to be specified.
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317 | Parameters:
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318 | abcissa: a list of abcissa labels. None (default) let
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319 | data determine the labels
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320 | Example:
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321 | # two panels are visible on the plotter
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322 | plotter.set_ordinate(["First X-Axis","Second X-Axis"])
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323 | """
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324 | self._abcissa = abcissa
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325 | if isinstance(fontsize, int):
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326 | from matplotlib import rc as rcp
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327 | rcp('axes', labelsize=fontsize)
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328 | rcp('xtick', labelsize=fontsize)
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329 | if self._data: self.plot(self._data)
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330 | return
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331 |
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332 | def set_colors(self, colmap):
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333 | """
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334 | Set the colours to be used. The plotter will cycle through
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335 | these colours when lines are overlaid (stacking mode).
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336 | Parameters:
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337 | colmap: a list of colour names
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338 | Example:
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339 | plotter.set_colors("red green blue")
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340 | # If for example four lines are overlaid e.g I Q U V
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341 | # 'I' will be 'red', 'Q' will be 'green', U will be 'blue'
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342 | # and 'V' will be 'red' again.
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343 | """
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344 | if isinstance(colmap,str):
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345 | colmap = colmap.split()
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346 | self._plotter.palette(0, colormap=colmap)
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347 | if self._data: self.plot(self._data)
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348 |
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349 | # alias for english speakers
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350 | set_colours = set_colors
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351 |
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352 | def set_histogram(self, hist=True, linewidth=None):
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353 | """
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354 | Enable/Disable histogram-like plotting.
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355 | Parameters:
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356 | hist: True (default) or False. The fisrt default
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357 | is taken from the .asaprc setting
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358 | plotter.histogram
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359 | """
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360 | self._hist = hist
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361 | if isinstance(linewidth, float) or isinstance(linewidth, int):
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362 | from matplotlib import rc as rcp
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363 | rcp('lines', linewidth=linewidth)
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364 | if self._data: self.plot(self._data)
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365 |
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366 | def set_linestyles(self, linestyles=None, linewidth=None):
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367 | """
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368 | Set the linestyles to be used. The plotter will cycle through
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369 | these linestyles when lines are overlaid (stacking mode) AND
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370 | only one color has been set.
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371 | Parameters:
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372 | linestyles: a list of linestyles to use.
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373 | 'line', 'dashed', 'dotted', 'dashdot',
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374 | 'dashdotdot' and 'dashdashdot' are
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375 | possible
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376 |
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377 | Example:
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378 | plotter.set_colors("black")
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379 | plotter.set_linestyles("line dashed dotted dashdot")
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380 | # If for example four lines are overlaid e.g I Q U V
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381 | # 'I' will be 'solid', 'Q' will be 'dashed',
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382 | # U will be 'dotted' and 'V' will be 'dashdot'.
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383 | """
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384 | if isinstance(linestyles,str):
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385 | linestyles = linestyles.split()
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386 | self._plotter.palette(color=0,linestyle=0,linestyles=linestyles)
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387 | if isinstance(linewidth, float) or isinstance(linewidth, int):
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388 | from matplotlib import rc as rcp
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389 | rcp('lines', linewidth=linewidth)
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390 | if self._data: self.plot(self._data)
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391 |
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392 | def set_font(self, family=None, style=None, weight=None, size=None):
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393 | """
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394 | Set font properties.
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395 | Parameters:
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396 | family: one of 'sans-serif', 'serif', 'cursive', 'fantasy', 'monospace'
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397 | style: one of 'normal' (or 'roman'), 'italic' or 'oblique'
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398 | weight: one of 'normal or 'bold'
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399 | size: the 'general' font size, individual elements can be adjusted
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400 | seperately
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401 | """
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402 | from matplotlib import rc as rcp
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403 | if isinstance(family, str):
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404 | rcp('font', family=family)
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405 | if isinstance(style, str):
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406 | rcp('font', style=style)
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407 | if isinstance(weight, str):
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408 | rcp('font', weight=weight)
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409 | if isinstance(size, float) or isinstance(size, int):
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410 | rcp('font', size=size)
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411 | if self._data: self.plot(self._data)
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412 |
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413 | def plot_lines(self, linecat=None, doppler=0.0, deltachan=10, rotate=90.0,
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414 | location=None):
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415 | """
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416 | Plot a line catalog.
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417 | Parameters:
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418 | linecat: the linecatalog to plot
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419 | doppler: the velocity shift to apply to the frequencies
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420 | deltachan: the number of channels to include each side of the
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421 | line to determine a local maximum/minimum
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422 | rotate: the rotation (in degrees) )for the text label (default 90.0)
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423 | location: the location of the line annotation from the 'top',
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424 | 'bottom' or alternate (None - the default)
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425 | Notes:
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426 | If the spectrum is flagged no line will be drawn in that location.
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427 | """
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428 | if not self._data:
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429 | raise RuntimeError("No scantable has been plotted yet.")
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430 | from asap._asap import linecatalog
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431 | if not isinstance(linecat, linecatalog):
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432 | raise ValueError("'linecat' isn't of type linecatalog.")
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433 | if not self._data.get_unit().endswith("Hz"):
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434 | raise RuntimeError("Can only overlay linecatalogs when data is in frequency.")
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435 | from matplotlib.numerix import ma
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436 | for j in range(len(self._plotter.subplots)):
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437 | self._plotter.subplot(j)
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438 | lims = self._plotter.axes.get_xlim()
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439 | for row in range(linecat.nrow()):
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440 | # get_frequency returns MHz
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441 | base = { "GHz": 1000.0, "MHz": 1.0, "Hz": 1.0e-6 }
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442 | restf = linecat.get_frequency(row)/base[self._data.get_unit()]
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443 | c = 299792.458
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444 | freq = restf*(1.0-doppler/c)
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445 | if lims[0] < freq < lims[1]:
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446 | if location is None:
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447 | loc = 'bottom'
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---|
448 | if row%2: loc='top'
|
---|
449 | else: loc = location
|
---|
450 | maxys = []
|
---|
451 | for line in self._plotter.axes.lines:
|
---|
452 | v = line._x
|
---|
453 | asc = v[0] < v[-1]
|
---|
454 |
|
---|
455 | idx = None
|
---|
456 | if not asc:
|
---|
457 | if v[len(v)-1] <= freq <= v[0]:
|
---|
458 | i = len(v)-1
|
---|
459 | while i>=0 and v[i] < freq:
|
---|
460 | idx = i
|
---|
461 | i-=1
|
---|
462 | else:
|
---|
463 | if v[0] <= freq <= v[len(v)-1]:
|
---|
464 | i = 0
|
---|
465 | while i<len(v) and v[i] < freq:
|
---|
466 | idx = i
|
---|
467 | i+=1
|
---|
468 | if idx is not None:
|
---|
469 | lower = idx - deltachan
|
---|
470 | upper = idx + deltachan
|
---|
471 | if lower < 0: lower = 0
|
---|
472 | if upper > len(v): upper = len(v)
|
---|
473 | s = slice(lower, upper)
|
---|
474 | y = line._y[s]
|
---|
475 | maxy = ma.maximum(y)
|
---|
476 | if isinstance( maxy, float):
|
---|
477 | maxys.append(maxy)
|
---|
478 | if len(maxys):
|
---|
479 | peak = max(maxys)
|
---|
480 | if peak > self._plotter.axes.get_ylim()[1]:
|
---|
481 | loc = 'bottom'
|
---|
482 | else:
|
---|
483 | continue
|
---|
484 | self._plotter.vline_with_label(freq, peak,
|
---|
485 | linecat.get_name(row),
|
---|
486 | location=loc, rotate=rotate)
|
---|
487 | self._plotter.show(hardrefresh=False)
|
---|
488 |
|
---|
489 |
|
---|
490 | def save(self, filename=None, orientation=None, dpi=None):
|
---|
491 | """
|
---|
492 | Save the plot to a file. The know formats are 'png', 'ps', 'eps'.
|
---|
493 | Parameters:
|
---|
494 | filename: The name of the output file. This is optional
|
---|
495 | and autodetects the image format from the file
|
---|
496 | suffix. If non filename is specified a file
|
---|
497 | called 'yyyymmdd_hhmmss.png' is created in the
|
---|
498 | current directory.
|
---|
499 | orientation: optional parameter for postscript only (not eps).
|
---|
500 | 'landscape', 'portrait' or None (default) are valid.
|
---|
501 | If None is choosen for 'ps' output, the plot is
|
---|
502 | automatically oriented to fill the page.
|
---|
503 | dpi: The dpi of the output non-ps plot
|
---|
504 | """
|
---|
505 | self._plotter.save(filename,orientation,dpi)
|
---|
506 | return
|
---|
507 |
|
---|
508 |
|
---|
509 | def set_mask(self, mask=None, selection=None):
|
---|
510 | """
|
---|
511 | Set a plotting mask for a specific polarization.
|
---|
512 | This is useful for masking out "noise" Pangle outside a source.
|
---|
513 | Parameters:
|
---|
514 | mask: a mask from scantable.create_mask
|
---|
515 | selection: the spectra to apply the mask to.
|
---|
516 | Example:
|
---|
517 | select = selector()
|
---|
518 | select.setpolstrings("Pangle")
|
---|
519 | plotter.set_mask(mymask, select)
|
---|
520 | """
|
---|
521 | if not self._data:
|
---|
522 | msg = "Can only set mask after a first call to plot()"
|
---|
523 | if rcParams['verbose']:
|
---|
524 | print msg
|
---|
525 | return
|
---|
526 | else:
|
---|
527 | raise RuntimeError(msg)
|
---|
528 | if len(mask):
|
---|
529 | if isinstance(mask, list) or isinstance(mask, tuple):
|
---|
530 | self._usermask = array(mask)
|
---|
531 | else:
|
---|
532 | self._usermask = mask
|
---|
533 | if mask is None and selection is None:
|
---|
534 | self._usermask = []
|
---|
535 | self._maskselection = None
|
---|
536 | if isinstance(selection, selector):
|
---|
537 | self._maskselection = {'b': selection.get_beams(),
|
---|
538 | 's': selection.get_scans(),
|
---|
539 | 'i': selection.get_ifs(),
|
---|
540 | 'p': selection.get_pols(),
|
---|
541 | 't': [] }
|
---|
542 | else:
|
---|
543 | self._maskselection = None
|
---|
544 | self.plot(self._data)
|
---|
545 |
|
---|
546 | def _slice_indeces(self, data):
|
---|
547 | mn = self._minmaxx[0]
|
---|
548 | mx = self._minmaxx[1]
|
---|
549 | asc = data[0] < data[-1]
|
---|
550 | start=0
|
---|
551 | end = len(data)-1
|
---|
552 | inc = 1
|
---|
553 | if not asc:
|
---|
554 | start = len(data)-1
|
---|
555 | end = 0
|
---|
556 | inc = -1
|
---|
557 | # find min index
|
---|
558 | while start > 0 and data[start] < mn:
|
---|
559 | start+= inc
|
---|
560 | # find max index
|
---|
561 | while end > 0 and data[end] > mx:
|
---|
562 | end-=inc
|
---|
563 | if end > 0: end +=1
|
---|
564 | if start > end:
|
---|
565 | return end,start
|
---|
566 | return start,end
|
---|
567 |
|
---|
568 | def _reset(self):
|
---|
569 | self._usermask = []
|
---|
570 | self._usermaskspectra = None
|
---|
571 | self.set_selection(None, False)
|
---|
572 |
|
---|
573 | def _plot(self, scan):
|
---|
574 | savesel = scan.get_selection()
|
---|
575 | sel = savesel + self._selection
|
---|
576 | d0 = {'s': 'SCANNO', 'b': 'BEAMNO', 'i':'IFNO',
|
---|
577 | 'p': 'POLNO', 'c': 'CYCLENO', 't' : 'TIME' }
|
---|
578 | order = [d0[self._panelling],d0[self._stacking]]
|
---|
579 | sel.set_order(order)
|
---|
580 | scan.set_selection(sel)
|
---|
581 | d = {'b': scan.getbeam, 's': scan.getscan,
|
---|
582 | 'i': scan.getif, 'p': scan.getpol, 't': scan._gettime }
|
---|
583 |
|
---|
584 | polmodes = dict(zip(self._selection.get_pols(),
|
---|
585 | self._selection.get_poltypes()))
|
---|
586 | # this returns either a tuple of numbers or a length (ncycles)
|
---|
587 | # convert this into lengths
|
---|
588 | n0,nstack0 = self._get_selected_n(scan)
|
---|
589 | if isinstance(n0, int): n = n0
|
---|
590 | else: n = len(n0)
|
---|
591 | if isinstance(nstack0, int): nstack = nstack0
|
---|
592 | else: nstack = len(nstack0)
|
---|
593 | maxpanel, maxstack = 16,8
|
---|
594 | if n > maxpanel or nstack > maxstack:
|
---|
595 | from asap import asaplog
|
---|
596 | maxn = 0
|
---|
597 | if nstack > maxstack: maxn = maxstack
|
---|
598 | if n > maxpanel: maxn = maxpanel
|
---|
599 | msg ="Scan to be plotted contains more than %d selections.\n" \
|
---|
600 | "Selecting first %d selections..." % (maxn, maxn)
|
---|
601 | asaplog.push(msg)
|
---|
602 | print_log()
|
---|
603 | n = min(n,maxpanel)
|
---|
604 | nstack = min(nstack,maxstack)
|
---|
605 | if n > 1:
|
---|
606 | ganged = rcParams['plotter.ganged']
|
---|
607 | ###Start Mod: 2008.09.22 kana ###
|
---|
608 | if self._panelling == 'i':
|
---|
609 | ganged = False
|
---|
610 | ###End Mod#######################
|
---|
611 | if self._rows and self._cols:
|
---|
612 | n = min(n,self._rows*self._cols)
|
---|
613 | self._plotter.set_panels(rows=self._rows,cols=self._cols,
|
---|
614 | nplots=n,ganged=ganged)
|
---|
615 | else:
|
---|
616 | self._plotter.set_panels(rows=n,cols=0,nplots=n,ganged=ganged)
|
---|
617 | else:
|
---|
618 | self._plotter.set_panels()
|
---|
619 | r=0
|
---|
620 | nr = scan.nrow()
|
---|
621 | a0,b0 = -1,-1
|
---|
622 | allxlim = []
|
---|
623 | allylim = []
|
---|
624 | newpanel=True
|
---|
625 | panelcount,stackcount = 0,0
|
---|
626 | while r < nr:
|
---|
627 | a = d[self._panelling](r)
|
---|
628 | b = d[self._stacking](r)
|
---|
629 | if a > a0 and panelcount < n:
|
---|
630 | if n > 1:
|
---|
631 | self._plotter.subplot(panelcount)
|
---|
632 | self._plotter.palette(0)
|
---|
633 | #title
|
---|
634 | xlab = self._abcissa and self._abcissa[panelcount] \
|
---|
635 | or scan._getabcissalabel()
|
---|
636 | ylab = self._ordinate and self._ordinate[panelcount] \
|
---|
637 | or scan._get_ordinate_label()
|
---|
638 | self._plotter.set_axes('xlabel',xlab)
|
---|
639 | self._plotter.set_axes('ylabel',ylab)
|
---|
640 | lbl = self._get_label(scan, r, self._panelling, self._title)
|
---|
641 | if isinstance(lbl, list) or isinstance(lbl, tuple):
|
---|
642 | if 0 <= panelcount < len(lbl):
|
---|
643 | lbl = lbl[panelcount]
|
---|
644 | else:
|
---|
645 | # get default label
|
---|
646 | lbl = self._get_label(scan, r, self._panelling, None)
|
---|
647 | self._plotter.set_axes('title',lbl)
|
---|
648 | newpanel = True
|
---|
649 | stackcount =0
|
---|
650 | panelcount += 1
|
---|
651 | if (b > b0 or newpanel) and stackcount < nstack:
|
---|
652 | y = []
|
---|
653 | if len(polmodes):
|
---|
654 | y = scan._getspectrum(r, polmodes[scan.getpol(r)])
|
---|
655 | else:
|
---|
656 | y = scan._getspectrum(r)
|
---|
657 | m = scan._getmask(r)
|
---|
658 | from matplotlib.numerix import logical_not, logical_and
|
---|
659 | if self._maskselection and len(self._usermask) == len(m):
|
---|
660 | if d[self._stacking](r) in self._maskselection[self._stacking]:
|
---|
661 | m = logical_and(m, self._usermask)
|
---|
662 | x = scan._getabcissa(r)
|
---|
663 | from matplotlib.numerix import ma, array
|
---|
664 | y = ma.masked_array(y,mask=logical_not(array(m,copy=False)))
|
---|
665 | if self._minmaxx is not None:
|
---|
666 | s,e = self._slice_indeces(x)
|
---|
667 | x = x[s:e]
|
---|
668 | y = y[s:e]
|
---|
669 | if len(x) > 1024 and rcParams['plotter.decimate']:
|
---|
670 | fac = len(x)/1024
|
---|
671 | x = x[::fac]
|
---|
672 | y = y[::fac]
|
---|
673 | llbl = self._get_label(scan, r, self._stacking, self._lmap)
|
---|
674 | if isinstance(llbl, list) or isinstance(llbl, tuple):
|
---|
675 | if 0 <= stackcount < len(llbl):
|
---|
676 | # use user label
|
---|
677 | llbl = llbl[stackcount]
|
---|
678 | else:
|
---|
679 | # get default label
|
---|
680 | llbl = self._get_label(scan, r, self._stacking, None)
|
---|
681 | self._plotter.set_line(label=llbl)
|
---|
682 | plotit = self._plotter.plot
|
---|
683 | if self._hist: plotit = self._plotter.hist
|
---|
684 | if len(x) > 0:
|
---|
685 | plotit(x,y)
|
---|
686 | xlim= self._minmaxx or [min(x),max(x)]
|
---|
687 | allxlim += xlim
|
---|
688 | ylim= self._minmaxy or [ma.minimum(y),ma.maximum(y)]
|
---|
689 | allylim += ylim
|
---|
690 | stackcount += 1
|
---|
691 | # last in colour stack -> autoscale x
|
---|
692 | if stackcount == nstack:
|
---|
693 | allxlim.sort()
|
---|
694 | ###Start Mod: 2008.09.22 kana ###
|
---|
695 | #self._plotter.axes.set_xlim([allxlim[0],allxlim[-1]])
|
---|
696 | self._plotter.subplots[panelcount-1]['axes'].set_xlim([allxlim[0],allxlim[-1]])
|
---|
697 | ###End Mod#######################
|
---|
698 | # clear
|
---|
699 | allxlim =[]
|
---|
700 |
|
---|
701 | newpanel = False
|
---|
702 | a0=a
|
---|
703 | b0=b
|
---|
704 | # ignore following rows
|
---|
705 | if (panelcount == n) and (stackcount == nstack):
|
---|
706 | # last panel -> autoscale y if ganged
|
---|
707 | if rcParams['plotter.ganged']:
|
---|
708 | allylim.sort()
|
---|
709 | self._plotter.set_limits(ylim=[allylim[0],allylim[-1]])
|
---|
710 | break
|
---|
711 | r+=1 # next row
|
---|
712 | #reset the selector to the scantable's original
|
---|
713 | scan.set_selection(savesel)
|
---|
714 |
|
---|
715 | def set_selection(self, selection=None, refresh=True):
|
---|
716 | self._selection = isinstance(selection,selector) and selection or selector()
|
---|
717 | d0 = {'s': 'SCANNO', 'b': 'BEAMNO', 'i':'IFNO',
|
---|
718 | 'p': 'POLNO', 'c': 'CYCLENO', 't' : 'TIME' }
|
---|
719 | order = [d0[self._panelling],d0[self._stacking]]
|
---|
720 | self._selection.set_order(order)
|
---|
721 | if self._data and refresh: self.plot(self._data)
|
---|
722 |
|
---|
723 | def _get_selected_n(self, scan):
|
---|
724 | d1 = {'b': scan.getbeamnos, 's': scan.getscannos,
|
---|
725 | 'i': scan.getifnos, 'p': scan.getpolnos, 't': scan.ncycle }
|
---|
726 | d2 = { 'b': self._selection.get_beams(),
|
---|
727 | 's': self._selection.get_scans(),
|
---|
728 | 'i': self._selection.get_ifs(),
|
---|
729 | 'p': self._selection.get_pols(),
|
---|
730 | 't': self._selection.get_cycles() }
|
---|
731 | n = d2[self._panelling] or d1[self._panelling]()
|
---|
732 | nstack = d2[self._stacking] or d1[self._stacking]()
|
---|
733 | return n,nstack
|
---|
734 |
|
---|
735 | def _get_label(self, scan, row, mode, userlabel=None):
|
---|
736 | if isinstance(userlabel, list) and len(userlabel) == 0:
|
---|
737 | userlabel = " "
|
---|
738 | pms = dict(zip(self._selection.get_pols(),self._selection.get_poltypes()))
|
---|
739 | if len(pms):
|
---|
740 | poleval = scan._getpollabel(scan.getpol(row),pms[scan.getpol(row)])
|
---|
741 | else:
|
---|
742 | poleval = scan._getpollabel(scan.getpol(row),scan.poltype())
|
---|
743 | d = {'b': "Beam "+str(scan.getbeam(row)),
|
---|
744 | 's': scan._getsourcename(row),
|
---|
745 | 'i': "IF"+str(scan.getif(row)),
|
---|
746 | 'p': poleval,
|
---|
747 | 't': str(scan.get_time(row)) }
|
---|
748 | return userlabel or d[mode]
|
---|
749 |
|
---|
750 | def plotazel(self, scan=None, outfile=None):
|
---|
751 | """
|
---|
752 | plot azimuth and elevation versus time of a scantable
|
---|
753 | """
|
---|
754 | import pylab as PL
|
---|
755 | from matplotlib.dates import DateFormatter, timezone, HourLocator, MinuteLocator, DayLocator
|
---|
756 | from matplotlib.ticker import MultipleLocator
|
---|
757 | from matplotlib.numerix import array, pi
|
---|
758 | self._data = scan
|
---|
759 | self._outfile = outfile
|
---|
760 | dates = self._data.get_time(asdatetime=True)
|
---|
761 | t = PL.date2num(dates)
|
---|
762 | tz = timezone('UTC')
|
---|
763 | PL.cla()
|
---|
764 | #PL.ioff()
|
---|
765 | PL.clf()
|
---|
766 | tdel = max(t) - min(t)
|
---|
767 | ax = PL.subplot(2,1,1)
|
---|
768 | el = array(self._data.get_elevation())*180./pi
|
---|
769 | PL.ylabel('El [deg.]')
|
---|
770 | dstr = dates[0].strftime('%Y/%m/%d')
|
---|
771 | if tdel > 1.0:
|
---|
772 | dstr2 = dates[len(dates)-1].strftime('%Y/%m/%d')
|
---|
773 | dstr = dstr + " - " + dstr2
|
---|
774 | majloc = DayLocator()
|
---|
775 | minloc = HourLocator(range(0,23,12))
|
---|
776 | timefmt = DateFormatter("%b%d")
|
---|
777 | else:
|
---|
778 | timefmt = DateFormatter('%H')
|
---|
779 | majloc = HourLocator()
|
---|
780 | minloc = MinuteLocator(20)
|
---|
781 | PL.title(dstr)
|
---|
782 |
|
---|
783 | if tdel == 0.0:
|
---|
784 | th = (t - PL.floor(t))*24.0
|
---|
785 | PL.plot(th,el,'o',markersize=2, markerfacecolor='b', markeredgecolor='b')
|
---|
786 | else:
|
---|
787 | PL.plot_date(t,el,'o', markersize=2, markerfacecolor='b', markeredgecolor='b',tz=tz)
|
---|
788 | #ax.grid(True)
|
---|
789 | ax.xaxis.set_major_formatter(timefmt)
|
---|
790 | ax.xaxis.set_major_locator(majloc)
|
---|
791 | ax.xaxis.set_minor_locator(minloc)
|
---|
792 | ax.yaxis.grid(True)
|
---|
793 | yloc = MultipleLocator(30)
|
---|
794 | ax.set_ylim(0,90)
|
---|
795 | ax.yaxis.set_major_locator(yloc)
|
---|
796 | if tdel > 1.0:
|
---|
797 | labels = ax.get_xticklabels()
|
---|
798 | # PL.setp(labels, fontsize=10, rotation=45)
|
---|
799 | PL.setp(labels, fontsize=10)
|
---|
800 |
|
---|
801 | # Az plot
|
---|
802 | az = array(self._data.get_azimuth())*180./pi
|
---|
803 | if min(az) < 0:
|
---|
804 | for irow in range(len(az)):
|
---|
805 | if az[irow] < 0: az[irow] += 360.0
|
---|
806 |
|
---|
807 | ax = PL.subplot(2,1,2)
|
---|
808 | #PL.xlabel('Time (UT [hour])')
|
---|
809 | PL.ylabel('Az [deg.]')
|
---|
810 | if tdel == 0.0:
|
---|
811 | PL.plot(th,az,'o',markersize=2, markeredgecolor='b',markerfacecolor='b')
|
---|
812 | else:
|
---|
813 | PL.plot_date(t,az,'o', markersize=2,markeredgecolor='b',markerfacecolor='b',tz=tz)
|
---|
814 | ax.xaxis.set_major_formatter(timefmt)
|
---|
815 | ax.xaxis.set_major_locator(majloc)
|
---|
816 | ax.xaxis.set_minor_locator(minloc)
|
---|
817 | #ax.grid(True)
|
---|
818 | ax.set_ylim(0,360)
|
---|
819 | ax.yaxis.grid(True)
|
---|
820 | #hfmt = DateFormatter('%H')
|
---|
821 | #hloc = HourLocator()
|
---|
822 | yloc = MultipleLocator(60)
|
---|
823 | ax.yaxis.set_major_locator(yloc)
|
---|
824 | if tdel > 1.0:
|
---|
825 | labels = ax.get_xticklabels()
|
---|
826 | PL.setp(labels, fontsize=10)
|
---|
827 | PL.xlabel('Time (UT [day])')
|
---|
828 | else:
|
---|
829 | PL.xlabel('Time (UT [hour])')
|
---|
830 |
|
---|
831 | #PL.ion()
|
---|
832 | PL.draw()
|
---|
833 | if (self._outfile is not None):
|
---|
834 | PL.savefig(self._outfile)
|
---|
835 |
|
---|
836 | def plotpointing(self, scan=None, outfile=None):
|
---|
837 | """
|
---|
838 | plot telescope pointings
|
---|
839 | """
|
---|
840 | import pylab as PL
|
---|
841 | from matplotlib.dates import DateFormatter, timezone
|
---|
842 | from matplotlib.ticker import MultipleLocator
|
---|
843 | from matplotlib.numerix import array, pi, zeros
|
---|
844 | self._data = scan
|
---|
845 | self._outfile = outfile
|
---|
846 | dir = array(self._data.get_directionval()).transpose()
|
---|
847 | ra = dir[0]*180./pi
|
---|
848 | dec = dir[1]*180./pi
|
---|
849 | PL.cla()
|
---|
850 | #PL.ioff()
|
---|
851 | PL.clf()
|
---|
852 | ax = PL.axes([0.1,0.1,0.8,0.8])
|
---|
853 | ax = PL.axes([0.1,0.1,0.8,0.8])
|
---|
854 | ax.set_aspect('equal')
|
---|
855 | PL.plot(ra,dec, 'b,')
|
---|
856 | PL.xlabel('RA [deg.]')
|
---|
857 | PL.ylabel('Declination [deg.]')
|
---|
858 | PL.title('Telescope pointings')
|
---|
859 | [xmin,xmax,ymin,ymax] = PL.axis()
|
---|
860 | PL.axis([xmax,xmin,ymin,ymax])
|
---|
861 | #PL.ion()
|
---|
862 | PL.draw()
|
---|
863 | if (self._outfile is not None):
|
---|
864 | PL.savefig(self._outfile)
|
---|
865 |
|
---|
866 | # plot total power data
|
---|
867 | # plotting in time is not yet implemented..
|
---|
868 | def plottp(self, scan=None, outfile=None):
|
---|
869 | if self._plotter.is_dead:
|
---|
870 | self._plotter = self._newplotter()
|
---|
871 | self._plotter.hold()
|
---|
872 | self._plotter.clear()
|
---|
873 | from asap import scantable
|
---|
874 | if not self._data and not scan:
|
---|
875 | msg = "Input is not a scantable"
|
---|
876 | if rcParams['verbose']:
|
---|
877 | print msg
|
---|
878 | return
|
---|
879 | raise TypeError(msg)
|
---|
880 | if isinstance(scan, scantable):
|
---|
881 | if self._data is not None:
|
---|
882 | if scan != self._data:
|
---|
883 | self._data = scan
|
---|
884 | # reset
|
---|
885 | self._reset()
|
---|
886 | else:
|
---|
887 | self._data = scan
|
---|
888 | self._reset()
|
---|
889 | # ranges become invalid when abcissa changes?
|
---|
890 | #if self._abcunit and self._abcunit != self._data.get_unit():
|
---|
891 | # self._minmaxx = None
|
---|
892 | # self._minmaxy = None
|
---|
893 | # self._abcunit = self._data.get_unit()
|
---|
894 | # self._datamask = None
|
---|
895 | self._plottp(self._data)
|
---|
896 | if self._minmaxy is not None:
|
---|
897 | self._plotter.set_limits(ylim=self._minmaxy)
|
---|
898 | self._plotter.release()
|
---|
899 | self._plotter.tidy()
|
---|
900 | self._plotter.show(hardrefresh=False)
|
---|
901 | print_log()
|
---|
902 | return
|
---|
903 |
|
---|
904 | def _plottp(self,scan):
|
---|
905 | """
|
---|
906 | private method for plotting total power data
|
---|
907 | """
|
---|
908 | from matplotlib.numerix import ma, array, arange, logical_not
|
---|
909 | r=0
|
---|
910 | nr = scan.nrow()
|
---|
911 | a0,b0 = -1,-1
|
---|
912 | allxlim = []
|
---|
913 | allylim = []
|
---|
914 | y=[]
|
---|
915 | self._plotter.set_panels()
|
---|
916 | self._plotter.palette(0)
|
---|
917 | #title
|
---|
918 | #xlab = self._abcissa and self._abcissa[panelcount] \
|
---|
919 | # or scan._getabcissalabel()
|
---|
920 | #ylab = self._ordinate and self._ordinate[panelcount] \
|
---|
921 | # or scan._get_ordinate_label()
|
---|
922 | xlab = self._abcissa or 'row number' #or Time
|
---|
923 | ylab = self._ordinate or scan._get_ordinate_label()
|
---|
924 | self._plotter.set_axes('xlabel',xlab)
|
---|
925 | self._plotter.set_axes('ylabel',ylab)
|
---|
926 | lbl = self._get_label(scan, r, 's', self._title)
|
---|
927 | if isinstance(lbl, list) or isinstance(lbl, tuple):
|
---|
928 | # if 0 <= panelcount < len(lbl):
|
---|
929 | # lbl = lbl[panelcount]
|
---|
930 | # else:
|
---|
931 | # get default label
|
---|
932 | lbl = self._get_label(scan, r, self._panelling, None)
|
---|
933 | self._plotter.set_axes('title',lbl)
|
---|
934 | y=array(scan._get_column(scan._getspectrum,-1))
|
---|
935 | m = array(scan._get_column(scan._getmask,-1))
|
---|
936 | y = ma.masked_array(y,mask=logical_not(array(m,copy=False)))
|
---|
937 | x = arange(len(y))
|
---|
938 | # try to handle spectral data somewhat...
|
---|
939 | l,m = y.shape
|
---|
940 | if m > 1:
|
---|
941 | y=y.mean(axis=1)
|
---|
942 | plotit = self._plotter.plot
|
---|
943 | llbl = self._get_label(scan, r, self._stacking, None)
|
---|
944 | self._plotter.set_line(label=llbl)
|
---|
945 | if len(x) > 0:
|
---|
946 | plotit(x,y)
|
---|
947 |
|
---|
948 |
|
---|
949 | # forwards to matplotlib.Figure.text
|
---|
950 | def figtext(self, *args, **kwargs):
|
---|
951 | """
|
---|
952 | Add text to figure at location x,y (relative 0-1 coords).
|
---|
953 | This method forwards *args and **kwargs to a Matplotlib method,
|
---|
954 | matplotlib.Figure.text.
|
---|
955 | See the method help for detailed information.
|
---|
956 | """
|
---|
957 | self._plotter.text(*args, **kwargs)
|
---|
958 | # end matplotlib.Figure.text forwarding function
|
---|
959 |
|
---|