[947] | 1 | from asap import rcParams, print_log, selector |
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[1614] | 2 | from asap import asaplog |
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[1153] | 3 | import matplotlib.axes |
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[1317] | 4 | import re |
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[203] | 5 | |
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| 6 | class asapplotter: |
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[226] | 7 | """ |
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| 8 | The ASAP plotter. |
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| 9 | By default the plotter is set up to plot polarisations |
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| 10 | 'colour stacked' and scantables across panels. |
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| 11 | Note: |
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| 12 | Currenly it only plots 'spectra' not Tsys or |
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| 13 | other variables. |
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| 14 | """ |
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[734] | 15 | def __init__(self, visible=None): |
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| 16 | self._visible = rcParams['plotter.gui'] |
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| 17 | if visible is not None: |
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| 18 | self._visible = visible |
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[710] | 19 | self._plotter = self._newplotter() |
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| 20 | |
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[554] | 21 | self._panelling = None |
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| 22 | self._stacking = None |
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| 23 | self.set_panelling() |
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| 24 | self.set_stacking() |
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[377] | 25 | self._rows = None |
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| 26 | self._cols = None |
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[203] | 27 | self._autoplot = False |
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[525] | 28 | self._minmaxx = None |
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| 29 | self._minmaxy = None |
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[710] | 30 | self._datamask = None |
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[203] | 31 | self._data = None |
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[607] | 32 | self._lmap = None |
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[226] | 33 | self._title = None |
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[257] | 34 | self._ordinate = None |
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| 35 | self._abcissa = None |
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[709] | 36 | self._abcunit = None |
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[920] | 37 | self._usermask = [] |
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| 38 | self._maskselection = None |
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| 39 | self._selection = selector() |
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[1023] | 40 | self._hist = rcParams['plotter.histogram'] |
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| 41 | |
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[920] | 42 | def _translate(self, instr): |
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| 43 | keys = "s b i p t".split() |
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| 44 | if isinstance(instr, str): |
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| 45 | for key in keys: |
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| 46 | if instr.lower().startswith(key): |
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| 47 | return key |
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| 48 | return None |
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| 49 | |
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[710] | 50 | def _newplotter(self): |
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| 51 | if self._visible: |
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| 52 | from asap.asaplotgui import asaplotgui as asaplot |
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| 53 | else: |
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| 54 | from asap.asaplot import asaplot |
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| 55 | return asaplot() |
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| 56 | |
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| 57 | |
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[935] | 58 | def plot(self, scan=None): |
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[203] | 59 | """ |
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[920] | 60 | Plot a scantable. |
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[203] | 61 | Parameters: |
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[920] | 62 | scan: a scantable |
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[203] | 63 | Note: |
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[920] | 64 | If a scantable was specified in a previous call |
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[203] | 65 | to plot, no argument has to be given to 'replot' |
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[920] | 66 | NO checking is done that the abcissas of the scantable |
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[203] | 67 | are consistent e.g. all 'channel' or all 'velocity' etc. |
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| 68 | """ |
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[710] | 69 | if self._plotter.is_dead: |
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| 70 | self._plotter = self._newplotter() |
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[600] | 71 | self._plotter.hold() |
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[203] | 72 | self._plotter.clear() |
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[935] | 73 | if not self._data and not scan: |
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[1101] | 74 | msg = "Input is not a scantable" |
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| 75 | if rcParams['verbose']: |
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[1612] | 76 | #print msg |
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[1614] | 77 | asaplog.push( msg ) |
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| 78 | print_log( 'ERROR' ) |
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[1101] | 79 | return |
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| 80 | raise TypeError(msg) |
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[1698] | 81 | if scan: self.set_data(scan,refresh=False) |
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[920] | 82 | self._plot(self._data) |
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[709] | 83 | if self._minmaxy is not None: |
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| 84 | self._plotter.set_limits(ylim=self._minmaxy) |
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[203] | 85 | self._plotter.release() |
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[1153] | 86 | self._plotter.tidy() |
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| 87 | self._plotter.show(hardrefresh=False) |
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[753] | 88 | print_log() |
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[203] | 89 | return |
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| 90 | |
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[1153] | 91 | |
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| 92 | # forwards to matplotlib axes |
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| 93 | def text(self, *args, **kwargs): |
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| 94 | self._axes_callback("text", *args, **kwargs) |
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[1358] | 95 | text.__doc__ = matplotlib.axes.Axes.text.__doc__ |
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[1153] | 96 | def arrow(self, *args, **kwargs): |
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| 97 | self._axes_callback("arrow", *args, **kwargs) |
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[1358] | 98 | arrow.__doc__ = matplotlib.axes.Axes.arrow.__doc__ |
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[1153] | 99 | def axvline(self, *args, **kwargs): |
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| 100 | self._axes_callback("axvline", *args, **kwargs) |
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[1358] | 101 | axvline.__doc__ = matplotlib.axes.Axes.axvline.__doc__ |
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[1153] | 102 | def axhline(self, *args, **kwargs): |
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| 103 | self._axes_callback("axhline", *args, **kwargs) |
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[1358] | 104 | axhline.__doc__ = matplotlib.axes.Axes.axhline.__doc__ |
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[1153] | 105 | def axvspan(self, *args, **kwargs): |
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| 106 | self._axes_callback("axvspan", *args, **kwargs) |
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| 107 | # hack to preventy mpl from redrawing the patch |
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| 108 | # it seem to convert the patch into lines on every draw. |
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| 109 | # This doesn't happen in a test script??? |
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| 110 | del self._plotter.axes.patches[-1] |
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[1358] | 111 | axvspan.__doc__ = matplotlib.axes.Axes.axvspan.__doc__ |
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[1232] | 112 | |
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[1153] | 113 | def axhspan(self, *args, **kwargs): |
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[1232] | 114 | self._axes_callback("axhspan", *args, **kwargs) |
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[1153] | 115 | # hack to preventy mpl from redrawing the patch |
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| 116 | # it seem to convert the patch into lines on every draw. |
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| 117 | # This doesn't happen in a test script??? |
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| 118 | del self._plotter.axes.patches[-1] |
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[1358] | 119 | axhspan.__doc__ = matplotlib.axes.Axes.axhspan.__doc__ |
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[1153] | 120 | |
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| 121 | def _axes_callback(self, axesfunc, *args, **kwargs): |
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| 122 | panel = 0 |
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| 123 | if kwargs.has_key("panel"): |
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| 124 | panel = kwargs.pop("panel") |
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| 125 | coords = None |
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| 126 | if kwargs.has_key("coords"): |
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| 127 | coords = kwargs.pop("coords") |
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| 128 | if coords.lower() == 'world': |
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| 129 | kwargs["transform"] = self._plotter.axes.transData |
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| 130 | elif coords.lower() == 'relative': |
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| 131 | kwargs["transform"] = self._plotter.axes.transAxes |
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| 132 | self._plotter.subplot(panel) |
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| 133 | self._plotter.axes.set_autoscale_on(False) |
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| 134 | getattr(self._plotter.axes, axesfunc)(*args, **kwargs) |
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| 135 | self._plotter.show(False) |
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| 136 | self._plotter.axes.set_autoscale_on(True) |
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| 137 | # end matplotlib.axes fowarding functions |
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| 138 | |
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[1698] | 139 | def set_data(self, scan, refresh=True): |
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[203] | 140 | """ |
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[1698] | 141 | Set a scantable to plot. |
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| 142 | Parameters: |
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| 143 | scan: a scantable |
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| 144 | refresh: True (default) or False. If True, the plot is |
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| 145 | replotted based on the new parameter setting(s). |
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| 146 | Otherwise,the parameter(s) are set without replotting. |
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| 147 | """ |
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| 148 | from asap import scantable |
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| 149 | if isinstance(scan, scantable): |
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| 150 | if self._data is not None: |
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| 151 | if scan != self._data: |
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| 152 | self._data = scan |
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| 153 | # reset |
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| 154 | self._reset() |
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| 155 | else: |
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| 156 | self._data = scan |
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| 157 | self._reset() |
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| 158 | else: |
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| 159 | msg = "Input is not a scantable" |
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| 160 | if rcParams['verbose']: |
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| 161 | #print msg |
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| 162 | asaplog.push( msg ) |
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| 163 | print_log( 'ERROR' ) |
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| 164 | return |
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| 165 | raise TypeError(msg) |
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| 166 | |
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| 167 | # ranges become invalid when unit changes |
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| 168 | if self._abcunit and self._abcunit != self._data.get_unit(): |
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| 169 | self._minmaxx = None |
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| 170 | self._minmaxy = None |
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| 171 | self._abcunit = self._data.get_unit() |
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| 172 | self._datamask = None |
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| 173 | if refresh: self.plot() |
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| 174 | |
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| 175 | |
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| 176 | def set_mode(self, stacking=None, panelling=None, refresh=True): |
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| 177 | """ |
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[377] | 178 | Set the plots look and feel, i.e. what you want to see on the plot. |
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[203] | 179 | Parameters: |
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| 180 | stacking: tell the plotter which variable to plot |
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[1217] | 181 | as line colour overlays (default 'pol') |
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[203] | 182 | panelling: tell the plotter which variable to plot |
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| 183 | across multiple panels (default 'scan' |
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[1698] | 184 | refresh: True (default) or False. If True, the plot is |
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| 185 | replotted based on the new parameter setting(s). |
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| 186 | Otherwise,the parameter(s) are set without replotting. |
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[203] | 187 | Note: |
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| 188 | Valid modes are: |
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| 189 | 'beam' 'Beam' 'b': Beams |
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| 190 | 'if' 'IF' 'i': IFs |
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| 191 | 'pol' 'Pol' 'p': Polarisations |
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| 192 | 'scan' 'Scan' 's': Scans |
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| 193 | 'time' 'Time' 't': Times |
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| 194 | """ |
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[753] | 195 | msg = "Invalid mode" |
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| 196 | if not self.set_panelling(panelling) or \ |
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| 197 | not self.set_stacking(stacking): |
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| 198 | if rcParams['verbose']: |
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[1612] | 199 | #print msg |
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[1614] | 200 | asaplog.push( msg ) |
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| 201 | print_log( 'ERROR' ) |
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[753] | 202 | return |
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| 203 | else: |
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| 204 | raise TypeError(msg) |
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[1698] | 205 | if refresh and self._data: self.plot(self._data) |
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[203] | 206 | return |
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| 207 | |
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[554] | 208 | def set_panelling(self, what=None): |
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| 209 | mode = what |
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| 210 | if mode is None: |
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| 211 | mode = rcParams['plotter.panelling'] |
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| 212 | md = self._translate(mode) |
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[203] | 213 | if md: |
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[554] | 214 | self._panelling = md |
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[226] | 215 | self._title = None |
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[203] | 216 | return True |
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| 217 | return False |
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| 218 | |
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[1698] | 219 | def set_layout(self,rows=None,cols=None,refresh=True): |
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[377] | 220 | """ |
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| 221 | Set the multi-panel layout, i.e. how many rows and columns plots |
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| 222 | are visible. |
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| 223 | Parameters: |
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| 224 | rows: The number of rows of plots |
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| 225 | cols: The number of columns of plots |
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[1698] | 226 | refresh: True (default) or False. If True, the plot is |
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| 227 | replotted based on the new parameter setting(s). |
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| 228 | Otherwise,the parameter(s) are set without replotting. |
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[377] | 229 | Note: |
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| 230 | If no argument is given, the potter reverts to its auto-plot |
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| 231 | behaviour. |
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| 232 | """ |
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| 233 | self._rows = rows |
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| 234 | self._cols = cols |
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[1698] | 235 | if refresh and self._data: self.plot(self._data) |
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[377] | 236 | return |
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| 237 | |
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[709] | 238 | def set_stacking(self, what=None): |
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[554] | 239 | mode = what |
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[709] | 240 | if mode is None: |
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| 241 | mode = rcParams['plotter.stacking'] |
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[554] | 242 | md = self._translate(mode) |
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[203] | 243 | if md: |
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| 244 | self._stacking = md |
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[226] | 245 | self._lmap = None |
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[203] | 246 | return True |
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| 247 | return False |
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| 248 | |
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[1698] | 249 | def set_range(self,xstart=None,xend=None,ystart=None,yend=None,refresh=True): |
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[203] | 250 | """ |
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| 251 | Set the range of interest on the abcissa of the plot |
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| 252 | Parameters: |
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[525] | 253 | [x,y]start,[x,y]end: The start and end points of the 'zoom' window |
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[1698] | 254 | refresh: True (default) or False. If True, the plot is |
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| 255 | replotted based on the new parameter setting(s). |
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| 256 | Otherwise,the parameter(s) are set without replotting. |
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[203] | 257 | Note: |
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| 258 | These become non-sensical when the unit changes. |
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| 259 | use plotter.set_range() without parameters to reset |
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| 260 | |
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| 261 | """ |
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[525] | 262 | if xstart is None and xend is None: |
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| 263 | self._minmaxx = None |
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[600] | 264 | else: |
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| 265 | self._minmaxx = [xstart,xend] |
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[525] | 266 | if ystart is None and yend is None: |
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| 267 | self._minmaxy = None |
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[600] | 268 | else: |
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[709] | 269 | self._minmaxy = [ystart,yend] |
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[1698] | 270 | if refresh and self._data: self.plot(self._data) |
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[203] | 271 | return |
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[709] | 272 | |
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[1698] | 273 | def set_legend(self, mp=None, fontsize = None, mode = 0, refresh=True): |
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[203] | 274 | """ |
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| 275 | Specify a mapping for the legend instead of using the default |
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| 276 | indices: |
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| 277 | Parameters: |
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[1101] | 278 | mp: a list of 'strings'. This should have the same length |
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| 279 | as the number of elements on the legend and then maps |
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| 280 | to the indeces in order. It is possible to uses latex |
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| 281 | math expression. These have to be enclosed in r'', |
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| 282 | e.g. r'$x^{2}$' |
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| 283 | fontsize: The font size of the label (default None) |
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| 284 | mode: where to display the legend |
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| 285 | Any other value for loc else disables the legend: |
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[1096] | 286 | 0: auto |
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| 287 | 1: upper right |
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| 288 | 2: upper left |
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| 289 | 3: lower left |
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| 290 | 4: lower right |
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| 291 | 5: right |
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| 292 | 6: center left |
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| 293 | 7: center right |
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| 294 | 8: lower center |
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| 295 | 9: upper center |
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| 296 | 10: center |
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[1698] | 297 | refresh: True (default) or False. If True, the plot is |
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| 298 | replotted based on the new parameter setting(s). |
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| 299 | Otherwise,the parameter(s) are set without replotting. |
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[203] | 300 | |
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| 301 | Example: |
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[485] | 302 | If the data has two IFs/rest frequencies with index 0 and 1 |
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[203] | 303 | for CO and SiO: |
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| 304 | plotter.set_stacking('i') |
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[710] | 305 | plotter.set_legend(['CO','SiO']) |
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[203] | 306 | plotter.plot() |
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[710] | 307 | plotter.set_legend([r'$^{12}CO$', r'SiO']) |
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[203] | 308 | """ |
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| 309 | self._lmap = mp |
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[1096] | 310 | self._plotter.legend(mode) |
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[1101] | 311 | if isinstance(fontsize, int): |
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| 312 | from matplotlib import rc as rcp |
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| 313 | rcp('legend', fontsize=fontsize) |
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[1698] | 314 | if refresh and self._data: self.plot(self._data) |
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[226] | 315 | return |
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| 316 | |
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[1698] | 317 | def set_title(self, title=None, fontsize=None, refresh=True): |
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[710] | 318 | """ |
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| 319 | Set the title of the plot. If multiple panels are plotted, |
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| 320 | multiple titles have to be specified. |
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[1698] | 321 | Parameters: |
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| 322 | refresh: True (default) or False. If True, the plot is |
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| 323 | replotted based on the new parameter setting(s). |
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| 324 | Otherwise,the parameter(s) are set without replotting. |
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[710] | 325 | Example: |
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| 326 | # two panels are visible on the plotter |
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| 327 | plotter.set_title(["First Panel","Second Panel"]) |
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| 328 | """ |
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[226] | 329 | self._title = title |
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[1101] | 330 | if isinstance(fontsize, int): |
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| 331 | from matplotlib import rc as rcp |
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| 332 | rcp('axes', titlesize=fontsize) |
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[1698] | 333 | if refresh and self._data: self.plot(self._data) |
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[226] | 334 | return |
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| 335 | |
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[1698] | 336 | def set_ordinate(self, ordinate=None, fontsize=None, refresh=True): |
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[710] | 337 | """ |
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| 338 | Set the y-axis label of the plot. If multiple panels are plotted, |
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| 339 | multiple labels have to be specified. |
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[1021] | 340 | Parameters: |
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| 341 | ordinate: a list of ordinate labels. None (default) let |
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| 342 | data determine the labels |
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[1698] | 343 | refresh: True (default) or False. If True, the plot is |
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| 344 | replotted based on the new parameter setting(s). |
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| 345 | Otherwise,the parameter(s) are set without replotting. |
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[710] | 346 | Example: |
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| 347 | # two panels are visible on the plotter |
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| 348 | plotter.set_ordinate(["First Y-Axis","Second Y-Axis"]) |
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| 349 | """ |
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[257] | 350 | self._ordinate = ordinate |
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[1101] | 351 | if isinstance(fontsize, int): |
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| 352 | from matplotlib import rc as rcp |
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| 353 | rcp('axes', labelsize=fontsize) |
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| 354 | rcp('ytick', labelsize=fontsize) |
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[1698] | 355 | if refresh and self._data: self.plot(self._data) |
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[257] | 356 | return |
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| 357 | |
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[1698] | 358 | def set_abcissa(self, abcissa=None, fontsize=None, refresh=True): |
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[710] | 359 | """ |
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| 360 | Set the x-axis label of the plot. If multiple panels are plotted, |
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| 361 | multiple labels have to be specified. |
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[1021] | 362 | Parameters: |
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| 363 | abcissa: a list of abcissa labels. None (default) let |
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| 364 | data determine the labels |
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[1698] | 365 | refresh: True (default) or False. If True, the plot is |
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| 366 | replotted based on the new parameter setting(s). |
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| 367 | Otherwise,the parameter(s) are set without replotting. |
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[710] | 368 | Example: |
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| 369 | # two panels are visible on the plotter |
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| 370 | plotter.set_ordinate(["First X-Axis","Second X-Axis"]) |
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| 371 | """ |
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[257] | 372 | self._abcissa = abcissa |
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[1101] | 373 | if isinstance(fontsize, int): |
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| 374 | from matplotlib import rc as rcp |
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| 375 | rcp('axes', labelsize=fontsize) |
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| 376 | rcp('xtick', labelsize=fontsize) |
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[1698] | 377 | if refresh and self._data: self.plot(self._data) |
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[257] | 378 | return |
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| 379 | |
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[1698] | 380 | def set_colors(self, colmap, refresh=True): |
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[377] | 381 | """ |
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[1217] | 382 | Set the colours to be used. The plotter will cycle through |
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| 383 | these colours when lines are overlaid (stacking mode). |
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[1021] | 384 | Parameters: |
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[1217] | 385 | colmap: a list of colour names |
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[1698] | 386 | refresh: True (default) or False. If True, the plot is |
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| 387 | replotted based on the new parameter setting(s). |
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| 388 | Otherwise,the parameter(s) are set without replotting. |
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[710] | 389 | Example: |
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| 390 | plotter.set_colors("red green blue") |
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| 391 | # If for example four lines are overlaid e.g I Q U V |
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| 392 | # 'I' will be 'red', 'Q' will be 'green', U will be 'blue' |
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| 393 | # and 'V' will be 'red' again. |
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| 394 | """ |
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[1217] | 395 | if isinstance(colmap,str): |
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| 396 | colmap = colmap.split() |
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| 397 | self._plotter.palette(0, colormap=colmap) |
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[1698] | 398 | if refresh and self._data: self.plot(self._data) |
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[710] | 399 | |
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[1217] | 400 | # alias for english speakers |
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| 401 | set_colours = set_colors |
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| 402 | |
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[1698] | 403 | def set_histogram(self, hist=True, linewidth=None, refresh=True): |
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[1021] | 404 | """ |
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| 405 | Enable/Disable histogram-like plotting. |
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| 406 | Parameters: |
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| 407 | hist: True (default) or False. The fisrt default |
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| 408 | is taken from the .asaprc setting |
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| 409 | plotter.histogram |
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[1698] | 410 | refresh: True (default) or False. If True, the plot is |
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| 411 | replotted based on the new parameter setting(s). |
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| 412 | Otherwise,the parameter(s) are set without replotting. |
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[1021] | 413 | """ |
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[1023] | 414 | self._hist = hist |
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[1101] | 415 | if isinstance(linewidth, float) or isinstance(linewidth, int): |
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| 416 | from matplotlib import rc as rcp |
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| 417 | rcp('lines', linewidth=linewidth) |
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[1698] | 418 | if refresh and self._data: self.plot(self._data) |
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[1023] | 419 | |
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[1698] | 420 | def set_linestyles(self, linestyles=None, linewidth=None, refresh=True): |
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[710] | 421 | """ |
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[734] | 422 | Set the linestyles to be used. The plotter will cycle through |
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| 423 | these linestyles when lines are overlaid (stacking mode) AND |
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| 424 | only one color has been set. |
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[710] | 425 | Parameters: |
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| 426 | linestyles: a list of linestyles to use. |
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| 427 | 'line', 'dashed', 'dotted', 'dashdot', |
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| 428 | 'dashdotdot' and 'dashdashdot' are |
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| 429 | possible |
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[1698] | 430 | refresh: True (default) or False. If True, the plot is |
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| 431 | replotted based on the new parameter setting(s). |
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| 432 | Otherwise,the parameter(s) are set without replotting. |
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[710] | 433 | Example: |
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| 434 | plotter.set_colors("black") |
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| 435 | plotter.set_linestyles("line dashed dotted dashdot") |
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| 436 | # If for example four lines are overlaid e.g I Q U V |
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| 437 | # 'I' will be 'solid', 'Q' will be 'dashed', |
---|
| 438 | # U will be 'dotted' and 'V' will be 'dashdot'. |
---|
| 439 | """ |
---|
| 440 | if isinstance(linestyles,str): |
---|
| 441 | linestyles = linestyles.split() |
---|
| 442 | self._plotter.palette(color=0,linestyle=0,linestyles=linestyles) |
---|
[1101] | 443 | if isinstance(linewidth, float) or isinstance(linewidth, int): |
---|
| 444 | from matplotlib import rc as rcp |
---|
| 445 | rcp('lines', linewidth=linewidth) |
---|
[1698] | 446 | if refresh and self._data: self.plot(self._data) |
---|
[710] | 447 | |
---|
[1698] | 448 | def set_font(self, family=None, style=None, weight=None, size=None, refresh=True): |
---|
[1101] | 449 | """ |
---|
| 450 | Set font properties. |
---|
| 451 | Parameters: |
---|
| 452 | family: one of 'sans-serif', 'serif', 'cursive', 'fantasy', 'monospace' |
---|
| 453 | style: one of 'normal' (or 'roman'), 'italic' or 'oblique' |
---|
| 454 | weight: one of 'normal or 'bold' |
---|
| 455 | size: the 'general' font size, individual elements can be adjusted |
---|
| 456 | seperately |
---|
[1698] | 457 | refresh: True (default) or False. If True, the plot is |
---|
| 458 | replotted based on the new parameter setting(s). |
---|
| 459 | Otherwise,the parameter(s) are set without replotting. |
---|
[1101] | 460 | """ |
---|
| 461 | from matplotlib import rc as rcp |
---|
| 462 | if isinstance(family, str): |
---|
| 463 | rcp('font', family=family) |
---|
| 464 | if isinstance(style, str): |
---|
| 465 | rcp('font', style=style) |
---|
| 466 | if isinstance(weight, str): |
---|
| 467 | rcp('font', weight=weight) |
---|
| 468 | if isinstance(size, float) or isinstance(size, int): |
---|
| 469 | rcp('font', size=size) |
---|
[1698] | 470 | if refresh and self._data: self.plot(self._data) |
---|
[1101] | 471 | |
---|
[1259] | 472 | def plot_lines(self, linecat=None, doppler=0.0, deltachan=10, rotate=90.0, |
---|
[1146] | 473 | location=None): |
---|
| 474 | """ |
---|
[1158] | 475 | Plot a line catalog. |
---|
| 476 | Parameters: |
---|
| 477 | linecat: the linecatalog to plot |
---|
[1168] | 478 | doppler: the velocity shift to apply to the frequencies |
---|
[1158] | 479 | deltachan: the number of channels to include each side of the |
---|
| 480 | line to determine a local maximum/minimum |
---|
[1259] | 481 | rotate: the rotation (in degrees) )for the text label (default 90.0) |
---|
[1158] | 482 | location: the location of the line annotation from the 'top', |
---|
| 483 | 'bottom' or alternate (None - the default) |
---|
[1165] | 484 | Notes: |
---|
| 485 | If the spectrum is flagged no line will be drawn in that location. |
---|
[1146] | 486 | """ |
---|
[1259] | 487 | if not self._data: |
---|
| 488 | raise RuntimeError("No scantable has been plotted yet.") |
---|
[1146] | 489 | from asap._asap import linecatalog |
---|
[1259] | 490 | if not isinstance(linecat, linecatalog): |
---|
| 491 | raise ValueError("'linecat' isn't of type linecatalog.") |
---|
| 492 | if not self._data.get_unit().endswith("Hz"): |
---|
| 493 | raise RuntimeError("Can only overlay linecatalogs when data is in frequency.") |
---|
[1153] | 494 | from matplotlib.numerix import ma |
---|
[1146] | 495 | for j in range(len(self._plotter.subplots)): |
---|
| 496 | self._plotter.subplot(j) |
---|
| 497 | lims = self._plotter.axes.get_xlim() |
---|
[1153] | 498 | for row in range(linecat.nrow()): |
---|
[1259] | 499 | # get_frequency returns MHz |
---|
| 500 | base = { "GHz": 1000.0, "MHz": 1.0, "Hz": 1.0e-6 } |
---|
| 501 | restf = linecat.get_frequency(row)/base[self._data.get_unit()] |
---|
[1165] | 502 | c = 299792.458 |
---|
[1174] | 503 | freq = restf*(1.0-doppler/c) |
---|
[1146] | 504 | if lims[0] < freq < lims[1]: |
---|
| 505 | if location is None: |
---|
| 506 | loc = 'bottom' |
---|
[1153] | 507 | if row%2: loc='top' |
---|
[1146] | 508 | else: loc = location |
---|
[1153] | 509 | maxys = [] |
---|
| 510 | for line in self._plotter.axes.lines: |
---|
| 511 | v = line._x |
---|
| 512 | asc = v[0] < v[-1] |
---|
| 513 | |
---|
| 514 | idx = None |
---|
| 515 | if not asc: |
---|
| 516 | if v[len(v)-1] <= freq <= v[0]: |
---|
| 517 | i = len(v)-1 |
---|
| 518 | while i>=0 and v[i] < freq: |
---|
| 519 | idx = i |
---|
| 520 | i-=1 |
---|
| 521 | else: |
---|
| 522 | if v[0] <= freq <= v[len(v)-1]: |
---|
| 523 | i = 0 |
---|
| 524 | while i<len(v) and v[i] < freq: |
---|
| 525 | idx = i |
---|
| 526 | i+=1 |
---|
| 527 | if idx is not None: |
---|
| 528 | lower = idx - deltachan |
---|
| 529 | upper = idx + deltachan |
---|
| 530 | if lower < 0: lower = 0 |
---|
| 531 | if upper > len(v): upper = len(v) |
---|
| 532 | s = slice(lower, upper) |
---|
[1167] | 533 | y = line._y[s] |
---|
[1165] | 534 | maxy = ma.maximum(y) |
---|
| 535 | if isinstance( maxy, float): |
---|
| 536 | maxys.append(maxy) |
---|
[1164] | 537 | if len(maxys): |
---|
| 538 | peak = max(maxys) |
---|
[1165] | 539 | if peak > self._plotter.axes.get_ylim()[1]: |
---|
| 540 | loc = 'bottom' |
---|
[1164] | 541 | else: |
---|
| 542 | continue |
---|
[1157] | 543 | self._plotter.vline_with_label(freq, peak, |
---|
| 544 | linecat.get_name(row), |
---|
| 545 | location=loc, rotate=rotate) |
---|
[1153] | 546 | self._plotter.show(hardrefresh=False) |
---|
[1146] | 547 | |
---|
[1153] | 548 | |
---|
[710] | 549 | def save(self, filename=None, orientation=None, dpi=None): |
---|
| 550 | """ |
---|
[377] | 551 | Save the plot to a file. The know formats are 'png', 'ps', 'eps'. |
---|
| 552 | Parameters: |
---|
| 553 | filename: The name of the output file. This is optional |
---|
| 554 | and autodetects the image format from the file |
---|
| 555 | suffix. If non filename is specified a file |
---|
| 556 | called 'yyyymmdd_hhmmss.png' is created in the |
---|
| 557 | current directory. |
---|
[709] | 558 | orientation: optional parameter for postscript only (not eps). |
---|
| 559 | 'landscape', 'portrait' or None (default) are valid. |
---|
| 560 | If None is choosen for 'ps' output, the plot is |
---|
| 561 | automatically oriented to fill the page. |
---|
[710] | 562 | dpi: The dpi of the output non-ps plot |
---|
[377] | 563 | """ |
---|
[709] | 564 | self._plotter.save(filename,orientation,dpi) |
---|
[377] | 565 | return |
---|
[709] | 566 | |
---|
[257] | 567 | |
---|
[1698] | 568 | def set_mask(self, mask=None, selection=None, refresh=True): |
---|
[525] | 569 | """ |
---|
[734] | 570 | Set a plotting mask for a specific polarization. |
---|
| 571 | This is useful for masking out "noise" Pangle outside a source. |
---|
| 572 | Parameters: |
---|
[920] | 573 | mask: a mask from scantable.create_mask |
---|
| 574 | selection: the spectra to apply the mask to. |
---|
[1698] | 575 | refresh: True (default) or False. If True, the plot is |
---|
| 576 | replotted based on the new parameter setting(s). |
---|
| 577 | Otherwise,the parameter(s) are set without replotting. |
---|
[734] | 578 | Example: |
---|
[920] | 579 | select = selector() |
---|
| 580 | select.setpolstrings("Pangle") |
---|
| 581 | plotter.set_mask(mymask, select) |
---|
[734] | 582 | """ |
---|
[710] | 583 | if not self._data: |
---|
[920] | 584 | msg = "Can only set mask after a first call to plot()" |
---|
[753] | 585 | if rcParams['verbose']: |
---|
[1612] | 586 | #print msg |
---|
[1614] | 587 | asaplog.push( msg ) |
---|
| 588 | print_log( 'ERROR' ) |
---|
[762] | 589 | return |
---|
[753] | 590 | else: |
---|
[762] | 591 | raise RuntimeError(msg) |
---|
[920] | 592 | if len(mask): |
---|
| 593 | if isinstance(mask, list) or isinstance(mask, tuple): |
---|
| 594 | self._usermask = array(mask) |
---|
[710] | 595 | else: |
---|
[920] | 596 | self._usermask = mask |
---|
| 597 | if mask is None and selection is None: |
---|
| 598 | self._usermask = [] |
---|
| 599 | self._maskselection = None |
---|
| 600 | if isinstance(selection, selector): |
---|
[947] | 601 | self._maskselection = {'b': selection.get_beams(), |
---|
| 602 | 's': selection.get_scans(), |
---|
| 603 | 'i': selection.get_ifs(), |
---|
| 604 | 'p': selection.get_pols(), |
---|
[920] | 605 | 't': [] } |
---|
[710] | 606 | else: |
---|
[920] | 607 | self._maskselection = None |
---|
[1698] | 608 | if refresh: self.plot(self._data) |
---|
[710] | 609 | |
---|
[709] | 610 | def _slice_indeces(self, data): |
---|
| 611 | mn = self._minmaxx[0] |
---|
| 612 | mx = self._minmaxx[1] |
---|
| 613 | asc = data[0] < data[-1] |
---|
| 614 | start=0 |
---|
| 615 | end = len(data)-1 |
---|
| 616 | inc = 1 |
---|
| 617 | if not asc: |
---|
| 618 | start = len(data)-1 |
---|
| 619 | end = 0 |
---|
| 620 | inc = -1 |
---|
| 621 | # find min index |
---|
[1562] | 622 | #while start > 0 and data[start] < mn: |
---|
| 623 | # start+= inc |
---|
| 624 | minind=start |
---|
| 625 | for ind in xrange(start,end+inc,inc): |
---|
| 626 | if data[ind] > mn: break |
---|
| 627 | minind=ind |
---|
[709] | 628 | # find max index |
---|
[1562] | 629 | #while end > 0 and data[end] > mx: |
---|
| 630 | # end-=inc |
---|
| 631 | #if end > 0: end +=1 |
---|
| 632 | maxind=end |
---|
| 633 | for ind in xrange(end,start-inc,-inc): |
---|
| 634 | if data[ind] < mx: break |
---|
| 635 | maxind=ind |
---|
| 636 | start=minind |
---|
| 637 | end=maxind |
---|
[709] | 638 | if start > end: |
---|
[1562] | 639 | return end,start+1 |
---|
| 640 | elif start < end: |
---|
| 641 | return start,end+1 |
---|
| 642 | else: |
---|
| 643 | return start,end |
---|
[709] | 644 | |
---|
[710] | 645 | def _reset(self): |
---|
[920] | 646 | self._usermask = [] |
---|
[710] | 647 | self._usermaskspectra = None |
---|
[920] | 648 | self.set_selection(None, False) |
---|
| 649 | |
---|
| 650 | def _plot(self, scan): |
---|
[947] | 651 | savesel = scan.get_selection() |
---|
| 652 | sel = savesel + self._selection |
---|
| 653 | d0 = {'s': 'SCANNO', 'b': 'BEAMNO', 'i':'IFNO', |
---|
| 654 | 'p': 'POLNO', 'c': 'CYCLENO', 't' : 'TIME' } |
---|
| 655 | order = [d0[self._panelling],d0[self._stacking]] |
---|
| 656 | sel.set_order(order) |
---|
| 657 | scan.set_selection(sel) |
---|
[920] | 658 | d = {'b': scan.getbeam, 's': scan.getscan, |
---|
| 659 | 'i': scan.getif, 'p': scan.getpol, 't': scan._gettime } |
---|
| 660 | |
---|
[1148] | 661 | polmodes = dict(zip(self._selection.get_pols(), |
---|
| 662 | self._selection.get_poltypes())) |
---|
| 663 | # this returns either a tuple of numbers or a length (ncycles) |
---|
| 664 | # convert this into lengths |
---|
| 665 | n0,nstack0 = self._get_selected_n(scan) |
---|
| 666 | if isinstance(n0, int): n = n0 |
---|
[1175] | 667 | else: n = len(n0) |
---|
[1148] | 668 | if isinstance(nstack0, int): nstack = nstack0 |
---|
[1175] | 669 | else: nstack = len(nstack0) |
---|
[998] | 670 | maxpanel, maxstack = 16,8 |
---|
[920] | 671 | if n > maxpanel or nstack > maxstack: |
---|
[1148] | 672 | maxn = 0 |
---|
| 673 | if nstack > maxstack: maxn = maxstack |
---|
| 674 | if n > maxpanel: maxn = maxpanel |
---|
[920] | 675 | msg ="Scan to be plotted contains more than %d selections.\n" \ |
---|
[1148] | 676 | "Selecting first %d selections..." % (maxn, maxn) |
---|
[920] | 677 | asaplog.push(msg) |
---|
[1614] | 678 | print_log('WARN') |
---|
[920] | 679 | n = min(n,maxpanel) |
---|
[998] | 680 | nstack = min(nstack,maxstack) |
---|
[920] | 681 | if n > 1: |
---|
| 682 | ganged = rcParams['plotter.ganged'] |
---|
[1446] | 683 | if self._panelling == 'i': |
---|
| 684 | ganged = False |
---|
[920] | 685 | if self._rows and self._cols: |
---|
| 686 | n = min(n,self._rows*self._cols) |
---|
| 687 | self._plotter.set_panels(rows=self._rows,cols=self._cols, |
---|
| 688 | nplots=n,ganged=ganged) |
---|
| 689 | else: |
---|
| 690 | self._plotter.set_panels(rows=n,cols=0,nplots=n,ganged=ganged) |
---|
| 691 | else: |
---|
| 692 | self._plotter.set_panels() |
---|
| 693 | r=0 |
---|
| 694 | nr = scan.nrow() |
---|
| 695 | a0,b0 = -1,-1 |
---|
| 696 | allxlim = [] |
---|
[1018] | 697 | allylim = [] |
---|
[920] | 698 | newpanel=True |
---|
| 699 | panelcount,stackcount = 0,0 |
---|
[1002] | 700 | while r < nr: |
---|
[920] | 701 | a = d[self._panelling](r) |
---|
| 702 | b = d[self._stacking](r) |
---|
| 703 | if a > a0 and panelcount < n: |
---|
| 704 | if n > 1: |
---|
| 705 | self._plotter.subplot(panelcount) |
---|
| 706 | self._plotter.palette(0) |
---|
| 707 | #title |
---|
| 708 | xlab = self._abcissa and self._abcissa[panelcount] \ |
---|
| 709 | or scan._getabcissalabel() |
---|
| 710 | ylab = self._ordinate and self._ordinate[panelcount] \ |
---|
| 711 | or scan._get_ordinate_label() |
---|
| 712 | self._plotter.set_axes('xlabel',xlab) |
---|
| 713 | self._plotter.set_axes('ylabel',ylab) |
---|
| 714 | lbl = self._get_label(scan, r, self._panelling, self._title) |
---|
| 715 | if isinstance(lbl, list) or isinstance(lbl, tuple): |
---|
| 716 | if 0 <= panelcount < len(lbl): |
---|
| 717 | lbl = lbl[panelcount] |
---|
| 718 | else: |
---|
| 719 | # get default label |
---|
| 720 | lbl = self._get_label(scan, r, self._panelling, None) |
---|
| 721 | self._plotter.set_axes('title',lbl) |
---|
| 722 | newpanel = True |
---|
| 723 | stackcount =0 |
---|
| 724 | panelcount += 1 |
---|
| 725 | if (b > b0 or newpanel) and stackcount < nstack: |
---|
| 726 | y = [] |
---|
| 727 | if len(polmodes): |
---|
| 728 | y = scan._getspectrum(r, polmodes[scan.getpol(r)]) |
---|
| 729 | else: |
---|
| 730 | y = scan._getspectrum(r) |
---|
| 731 | m = scan._getmask(r) |
---|
[1146] | 732 | from matplotlib.numerix import logical_not, logical_and |
---|
[920] | 733 | if self._maskselection and len(self._usermask) == len(m): |
---|
| 734 | if d[self._stacking](r) in self._maskselection[self._stacking]: |
---|
| 735 | m = logical_and(m, self._usermask) |
---|
| 736 | x = scan._getabcissa(r) |
---|
[1146] | 737 | from matplotlib.numerix import ma, array |
---|
[1116] | 738 | y = ma.masked_array(y,mask=logical_not(array(m,copy=False))) |
---|
[920] | 739 | if self._minmaxx is not None: |
---|
| 740 | s,e = self._slice_indeces(x) |
---|
| 741 | x = x[s:e] |
---|
| 742 | y = y[s:e] |
---|
[1096] | 743 | if len(x) > 1024 and rcParams['plotter.decimate']: |
---|
| 744 | fac = len(x)/1024 |
---|
[920] | 745 | x = x[::fac] |
---|
| 746 | y = y[::fac] |
---|
| 747 | llbl = self._get_label(scan, r, self._stacking, self._lmap) |
---|
| 748 | if isinstance(llbl, list) or isinstance(llbl, tuple): |
---|
| 749 | if 0 <= stackcount < len(llbl): |
---|
| 750 | # use user label |
---|
| 751 | llbl = llbl[stackcount] |
---|
| 752 | else: |
---|
| 753 | # get default label |
---|
| 754 | llbl = self._get_label(scan, r, self._stacking, None) |
---|
| 755 | self._plotter.set_line(label=llbl) |
---|
[1023] | 756 | plotit = self._plotter.plot |
---|
| 757 | if self._hist: plotit = self._plotter.hist |
---|
[1146] | 758 | if len(x) > 0: |
---|
| 759 | plotit(x,y) |
---|
| 760 | xlim= self._minmaxx or [min(x),max(x)] |
---|
| 761 | allxlim += xlim |
---|
| 762 | ylim= self._minmaxy or [ma.minimum(y),ma.maximum(y)] |
---|
| 763 | allylim += ylim |
---|
[1562] | 764 | else: |
---|
| 765 | xlim = self._minmaxx or [] |
---|
| 766 | allxlim += xlim |
---|
| 767 | ylim= self._minmaxy or [] |
---|
| 768 | allylim += ylim |
---|
[920] | 769 | stackcount += 1 |
---|
| 770 | # last in colour stack -> autoscale x |
---|
[1562] | 771 | if stackcount == nstack and len(allxlim) > 0: |
---|
[920] | 772 | allxlim.sort() |
---|
[1446] | 773 | self._plotter.subplots[panelcount-1]['axes'].set_xlim([allxlim[0],allxlim[-1]]) |
---|
[920] | 774 | # clear |
---|
| 775 | allxlim =[] |
---|
| 776 | |
---|
| 777 | newpanel = False |
---|
| 778 | a0=a |
---|
| 779 | b0=b |
---|
| 780 | # ignore following rows |
---|
| 781 | if (panelcount == n) and (stackcount == nstack): |
---|
[1018] | 782 | # last panel -> autoscale y if ganged |
---|
[1562] | 783 | if rcParams['plotter.ganged'] and len(allylim) > 0: |
---|
[1018] | 784 | allylim.sort() |
---|
| 785 | self._plotter.set_limits(ylim=[allylim[0],allylim[-1]]) |
---|
[998] | 786 | break |
---|
[920] | 787 | r+=1 # next row |
---|
[947] | 788 | #reset the selector to the scantable's original |
---|
| 789 | scan.set_selection(savesel) |
---|
[920] | 790 | |
---|
| 791 | def set_selection(self, selection=None, refresh=True): |
---|
[1698] | 792 | """ |
---|
| 793 | Parameters: |
---|
| 794 | selection: a selector object (default unset the selection) |
---|
| 795 | refresh: True (default) or False. If True, the plot is |
---|
| 796 | replotted based on the new parameter setting(s). |
---|
| 797 | Otherwise,the parameter(s) are set without replotting. |
---|
| 798 | """ |
---|
[947] | 799 | self._selection = isinstance(selection,selector) and selection or selector() |
---|
[920] | 800 | d0 = {'s': 'SCANNO', 'b': 'BEAMNO', 'i':'IFNO', |
---|
| 801 | 'p': 'POLNO', 'c': 'CYCLENO', 't' : 'TIME' } |
---|
| 802 | order = [d0[self._panelling],d0[self._stacking]] |
---|
[947] | 803 | self._selection.set_order(order) |
---|
[1698] | 804 | if refresh and self._data: self.plot(self._data) |
---|
[920] | 805 | |
---|
| 806 | def _get_selected_n(self, scan): |
---|
[1148] | 807 | d1 = {'b': scan.getbeamnos, 's': scan.getscannos, |
---|
| 808 | 'i': scan.getifnos, 'p': scan.getpolnos, 't': scan.ncycle } |
---|
| 809 | d2 = { 'b': self._selection.get_beams(), |
---|
| 810 | 's': self._selection.get_scans(), |
---|
| 811 | 'i': self._selection.get_ifs(), |
---|
| 812 | 'p': self._selection.get_pols(), |
---|
| 813 | 't': self._selection.get_cycles() } |
---|
[920] | 814 | n = d2[self._panelling] or d1[self._panelling]() |
---|
| 815 | nstack = d2[self._stacking] or d1[self._stacking]() |
---|
| 816 | return n,nstack |
---|
| 817 | |
---|
| 818 | def _get_label(self, scan, row, mode, userlabel=None): |
---|
[1153] | 819 | if isinstance(userlabel, list) and len(userlabel) == 0: |
---|
| 820 | userlabel = " " |
---|
[947] | 821 | pms = dict(zip(self._selection.get_pols(),self._selection.get_poltypes())) |
---|
[920] | 822 | if len(pms): |
---|
| 823 | poleval = scan._getpollabel(scan.getpol(row),pms[scan.getpol(row)]) |
---|
| 824 | else: |
---|
| 825 | poleval = scan._getpollabel(scan.getpol(row),scan.poltype()) |
---|
| 826 | d = {'b': "Beam "+str(scan.getbeam(row)), |
---|
| 827 | 's': scan._getsourcename(row), |
---|
| 828 | 'i': "IF"+str(scan.getif(row)), |
---|
[964] | 829 | 'p': poleval, |
---|
[1175] | 830 | 't': str(scan.get_time(row)) } |
---|
[920] | 831 | return userlabel or d[mode] |
---|
[1153] | 832 | |
---|
[1446] | 833 | def plotazel(self, scan=None, outfile=None): |
---|
[1389] | 834 | """ |
---|
| 835 | plot azimuth and elevation versus time of a scantable |
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| 836 | """ |
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| 837 | import pylab as PL |
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| 838 | from matplotlib.dates import DateFormatter, timezone, HourLocator, MinuteLocator, DayLocator |
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| 839 | from matplotlib.ticker import MultipleLocator |
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| 840 | from matplotlib.numerix import array, pi |
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| 841 | self._data = scan |
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[1446] | 842 | self._outfile = outfile |
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[1457] | 843 | dates = self._data.get_time(asdatetime=True) |
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[1389] | 844 | t = PL.date2num(dates) |
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| 845 | tz = timezone('UTC') |
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| 846 | PL.cla() |
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[1446] | 847 | #PL.ioff() |
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[1389] | 848 | PL.clf() |
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| 849 | tdel = max(t) - min(t) |
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| 850 | ax = PL.subplot(2,1,1) |
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| 851 | el = array(self._data.get_elevation())*180./pi |
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| 852 | PL.ylabel('El [deg.]') |
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| 853 | dstr = dates[0].strftime('%Y/%m/%d') |
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| 854 | if tdel > 1.0: |
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| 855 | dstr2 = dates[len(dates)-1].strftime('%Y/%m/%d') |
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| 856 | dstr = dstr + " - " + dstr2 |
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| 857 | majloc = DayLocator() |
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| 858 | minloc = HourLocator(range(0,23,12)) |
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| 859 | timefmt = DateFormatter("%b%d") |
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| 860 | else: |
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| 861 | timefmt = DateFormatter('%H') |
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| 862 | majloc = HourLocator() |
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| 863 | minloc = MinuteLocator(20) |
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| 864 | PL.title(dstr) |
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[1446] | 865 | |
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| 866 | if tdel == 0.0: |
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| 867 | th = (t - PL.floor(t))*24.0 |
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| 868 | PL.plot(th,el,'o',markersize=2, markerfacecolor='b', markeredgecolor='b') |
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| 869 | else: |
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| 870 | PL.plot_date(t,el,'o', markersize=2, markerfacecolor='b', markeredgecolor='b',tz=tz) |
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| 871 | #ax.grid(True) |
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| 872 | ax.xaxis.set_major_formatter(timefmt) |
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| 873 | ax.xaxis.set_major_locator(majloc) |
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| 874 | ax.xaxis.set_minor_locator(minloc) |
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[1389] | 875 | ax.yaxis.grid(True) |
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| 876 | yloc = MultipleLocator(30) |
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| 877 | ax.set_ylim(0,90) |
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| 878 | ax.yaxis.set_major_locator(yloc) |
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| 879 | if tdel > 1.0: |
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| 880 | labels = ax.get_xticklabels() |
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| 881 | # PL.setp(labels, fontsize=10, rotation=45) |
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| 882 | PL.setp(labels, fontsize=10) |
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[1446] | 883 | |
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[1389] | 884 | # Az plot |
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| 885 | az = array(self._data.get_azimuth())*180./pi |
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| 886 | if min(az) < 0: |
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| 887 | for irow in range(len(az)): |
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| 888 | if az[irow] < 0: az[irow] += 360.0 |
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| 889 | |
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| 890 | ax = PL.subplot(2,1,2) |
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[1446] | 891 | #PL.xlabel('Time (UT [hour])') |
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[1389] | 892 | PL.ylabel('Az [deg.]') |
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[1446] | 893 | if tdel == 0.0: |
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| 894 | PL.plot(th,az,'o',markersize=2, markeredgecolor='b',markerfacecolor='b') |
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| 895 | else: |
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| 896 | PL.plot_date(t,az,'o', markersize=2,markeredgecolor='b',markerfacecolor='b',tz=tz) |
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| 897 | ax.xaxis.set_major_formatter(timefmt) |
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| 898 | ax.xaxis.set_major_locator(majloc) |
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| 899 | ax.xaxis.set_minor_locator(minloc) |
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| 900 | #ax.grid(True) |
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[1389] | 901 | ax.set_ylim(0,360) |
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| 902 | ax.yaxis.grid(True) |
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| 903 | #hfmt = DateFormatter('%H') |
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| 904 | #hloc = HourLocator() |
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| 905 | yloc = MultipleLocator(60) |
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| 906 | ax.yaxis.set_major_locator(yloc) |
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| 907 | if tdel > 1.0: |
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| 908 | labels = ax.get_xticklabels() |
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| 909 | PL.setp(labels, fontsize=10) |
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[1446] | 910 | PL.xlabel('Time (UT [day])') |
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| 911 | else: |
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| 912 | PL.xlabel('Time (UT [hour])') |
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| 913 | |
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| 914 | #PL.ion() |
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[1389] | 915 | PL.draw() |
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[1446] | 916 | if (self._outfile is not None): |
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| 917 | PL.savefig(self._outfile) |
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[1389] | 918 | |
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[1446] | 919 | def plotpointing(self, scan=None, outfile=None): |
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[1389] | 920 | """ |
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| 921 | plot telescope pointings |
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| 922 | """ |
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| 923 | import pylab as PL |
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| 924 | from matplotlib.dates import DateFormatter, timezone |
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| 925 | from matplotlib.ticker import MultipleLocator |
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| 926 | from matplotlib.numerix import array, pi, zeros |
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| 927 | self._data = scan |
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[1446] | 928 | self._outfile = outfile |
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[1389] | 929 | dir = array(self._data.get_directionval()).transpose() |
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| 930 | ra = dir[0]*180./pi |
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| 931 | dec = dir[1]*180./pi |
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| 932 | PL.cla() |
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[1446] | 933 | #PL.ioff() |
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[1389] | 934 | PL.clf() |
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| 935 | ax = PL.axes([0.1,0.1,0.8,0.8]) |
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| 936 | ax = PL.axes([0.1,0.1,0.8,0.8]) |
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| 937 | ax.set_aspect('equal') |
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| 938 | PL.plot(ra,dec, 'b,') |
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| 939 | PL.xlabel('RA [deg.]') |
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| 940 | PL.ylabel('Declination [deg.]') |
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| 941 | PL.title('Telescope pointings') |
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| 942 | [xmin,xmax,ymin,ymax] = PL.axis() |
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| 943 | PL.axis([xmax,xmin,ymin,ymax]) |
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[1446] | 944 | #PL.ion() |
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[1389] | 945 | PL.draw() |
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[1446] | 946 | if (self._outfile is not None): |
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| 947 | PL.savefig(self._outfile) |
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[1389] | 948 | |
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[1446] | 949 | # plot total power data |
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| 950 | # plotting in time is not yet implemented.. |
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| 951 | def plottp(self, scan=None, outfile=None): |
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| 952 | if self._plotter.is_dead: |
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| 953 | self._plotter = self._newplotter() |
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| 954 | self._plotter.hold() |
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| 955 | self._plotter.clear() |
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| 956 | from asap import scantable |
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| 957 | if not self._data and not scan: |
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| 958 | msg = "Input is not a scantable" |
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| 959 | if rcParams['verbose']: |
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[1612] | 960 | #print msg |
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[1614] | 961 | asaplog.push( msg ) |
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| 962 | print_log( 'ERROR' ) |
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[1446] | 963 | return |
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| 964 | raise TypeError(msg) |
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| 965 | if isinstance(scan, scantable): |
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| 966 | if self._data is not None: |
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| 967 | if scan != self._data: |
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| 968 | self._data = scan |
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| 969 | # reset |
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| 970 | self._reset() |
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| 971 | else: |
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| 972 | self._data = scan |
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| 973 | self._reset() |
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| 974 | # ranges become invalid when abcissa changes? |
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| 975 | #if self._abcunit and self._abcunit != self._data.get_unit(): |
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| 976 | # self._minmaxx = None |
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| 977 | # self._minmaxy = None |
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| 978 | # self._abcunit = self._data.get_unit() |
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| 979 | # self._datamask = None |
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| 980 | self._plottp(self._data) |
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| 981 | if self._minmaxy is not None: |
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| 982 | self._plotter.set_limits(ylim=self._minmaxy) |
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| 983 | self._plotter.release() |
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| 984 | self._plotter.tidy() |
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| 985 | self._plotter.show(hardrefresh=False) |
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| 986 | print_log() |
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| 987 | return |
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| 988 | |
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| 989 | def _plottp(self,scan): |
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| 990 | """ |
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| 991 | private method for plotting total power data |
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| 992 | """ |
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| 993 | from matplotlib.numerix import ma, array, arange, logical_not |
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| 994 | r=0 |
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| 995 | nr = scan.nrow() |
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| 996 | a0,b0 = -1,-1 |
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| 997 | allxlim = [] |
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| 998 | allylim = [] |
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| 999 | y=[] |
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| 1000 | self._plotter.set_panels() |
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| 1001 | self._plotter.palette(0) |
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| 1002 | #title |
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| 1003 | #xlab = self._abcissa and self._abcissa[panelcount] \ |
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| 1004 | # or scan._getabcissalabel() |
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| 1005 | #ylab = self._ordinate and self._ordinate[panelcount] \ |
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| 1006 | # or scan._get_ordinate_label() |
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| 1007 | xlab = self._abcissa or 'row number' #or Time |
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| 1008 | ylab = self._ordinate or scan._get_ordinate_label() |
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| 1009 | self._plotter.set_axes('xlabel',xlab) |
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| 1010 | self._plotter.set_axes('ylabel',ylab) |
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| 1011 | lbl = self._get_label(scan, r, 's', self._title) |
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| 1012 | if isinstance(lbl, list) or isinstance(lbl, tuple): |
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| 1013 | # if 0 <= panelcount < len(lbl): |
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| 1014 | # lbl = lbl[panelcount] |
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| 1015 | # else: |
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| 1016 | # get default label |
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| 1017 | lbl = self._get_label(scan, r, self._panelling, None) |
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| 1018 | self._plotter.set_axes('title',lbl) |
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| 1019 | y=array(scan._get_column(scan._getspectrum,-1)) |
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| 1020 | m = array(scan._get_column(scan._getmask,-1)) |
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| 1021 | y = ma.masked_array(y,mask=logical_not(array(m,copy=False))) |
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| 1022 | x = arange(len(y)) |
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| 1023 | # try to handle spectral data somewhat... |
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| 1024 | l,m = y.shape |
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| 1025 | if m > 1: |
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| 1026 | y=y.mean(axis=1) |
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| 1027 | plotit = self._plotter.plot |
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| 1028 | llbl = self._get_label(scan, r, self._stacking, None) |
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| 1029 | self._plotter.set_line(label=llbl) |
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| 1030 | if len(x) > 0: |
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| 1031 | plotit(x,y) |
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| 1032 | |
---|
| 1033 | |
---|
| 1034 | # forwards to matplotlib.Figure.text |
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| 1035 | def figtext(self, *args, **kwargs): |
---|
| 1036 | """ |
---|
| 1037 | Add text to figure at location x,y (relative 0-1 coords). |
---|
| 1038 | This method forwards *args and **kwargs to a Matplotlib method, |
---|
| 1039 | matplotlib.Figure.text. |
---|
| 1040 | See the method help for detailed information. |
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| 1041 | """ |
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| 1042 | self._plotter.text(*args, **kwargs) |
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| 1043 | # end matplotlib.Figure.text forwarding function |
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| 1044 | |
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