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