[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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[1724] | 20 | if self._visible and matplotlib.get_backend() == "TkAgg": |
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| 21 | from asap.casatoolbar import CustomToolbarTkAgg |
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| 22 | self._plotter.figmgr.casabar = CustomToolbarTkAgg(self) |
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[710] | 23 | |
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[554] | 24 | self._panelling = None |
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| 25 | self._stacking = None |
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| 26 | self.set_panelling() |
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| 27 | self.set_stacking() |
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[377] | 28 | self._rows = None |
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| 29 | self._cols = None |
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[203] | 30 | self._autoplot = False |
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[525] | 31 | self._minmaxx = None |
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| 32 | self._minmaxy = None |
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[710] | 33 | self._datamask = None |
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[203] | 34 | self._data = None |
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[607] | 35 | self._lmap = None |
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[226] | 36 | self._title = None |
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[257] | 37 | self._ordinate = None |
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| 38 | self._abcissa = None |
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[709] | 39 | self._abcunit = None |
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[920] | 40 | self._usermask = [] |
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| 41 | self._maskselection = None |
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| 42 | self._selection = selector() |
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[1023] | 43 | self._hist = rcParams['plotter.histogram'] |
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[1723] | 44 | self._panellayout = self.set_panellayout(refresh=False) |
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[1023] | 45 | |
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[920] | 46 | def _translate(self, instr): |
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| 47 | keys = "s b i p t".split() |
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| 48 | if isinstance(instr, str): |
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| 49 | for key in keys: |
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| 50 | if instr.lower().startswith(key): |
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| 51 | return key |
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| 52 | return None |
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| 53 | |
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[710] | 54 | def _newplotter(self): |
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[1724] | 55 | backend=matplotlib.get_backend() |
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| 56 | if not self._visible: |
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| 57 | from asap.asaplot import asaplot |
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| 58 | elif backend == 'TkAgg': |
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[710] | 59 | from asap.asaplotgui import asaplotgui as asaplot |
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[1724] | 60 | elif backend == 'Qt4Agg': |
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| 61 | from asap.asaplotgui_qt4 import asaplotgui as asaplot |
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| 62 | elif backend == 'GTkAgg': |
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| 63 | from asap.asaplotgui_gtk import asaplotgui as asaplot |
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[710] | 64 | else: |
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| 65 | from asap.asaplot import asaplot |
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| 66 | return asaplot() |
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| 67 | |
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| 68 | |
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[935] | 69 | def plot(self, scan=None): |
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[203] | 70 | """ |
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[920] | 71 | Plot a scantable. |
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[203] | 72 | Parameters: |
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[920] | 73 | scan: a scantable |
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[203] | 74 | Note: |
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[920] | 75 | If a scantable was specified in a previous call |
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[203] | 76 | to plot, no argument has to be given to 'replot' |
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[920] | 77 | NO checking is done that the abcissas of the scantable |
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[203] | 78 | are consistent e.g. all 'channel' or all 'velocity' etc. |
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| 79 | """ |
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[710] | 80 | if self._plotter.is_dead: |
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| 81 | self._plotter = self._newplotter() |
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[600] | 82 | self._plotter.hold() |
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[203] | 83 | self._plotter.clear() |
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[935] | 84 | if not self._data and not scan: |
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[1101] | 85 | msg = "Input is not a scantable" |
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| 86 | if rcParams['verbose']: |
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[1612] | 87 | #print msg |
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[1614] | 88 | asaplog.push( msg ) |
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| 89 | print_log( 'ERROR' ) |
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[1101] | 90 | return |
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| 91 | raise TypeError(msg) |
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[1698] | 92 | if scan: self.set_data(scan,refresh=False) |
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[920] | 93 | self._plot(self._data) |
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[709] | 94 | if self._minmaxy is not None: |
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| 95 | self._plotter.set_limits(ylim=self._minmaxy) |
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[1724] | 96 | if self._plotter.figmgr.casabar: self._plotter.figmgr.casabar.enable_button() |
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[203] | 97 | self._plotter.release() |
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[1153] | 98 | self._plotter.tidy() |
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| 99 | self._plotter.show(hardrefresh=False) |
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[753] | 100 | print_log() |
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[203] | 101 | return |
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| 102 | |
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[1153] | 103 | |
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| 104 | # forwards to matplotlib axes |
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| 105 | def text(self, *args, **kwargs): |
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| 106 | self._axes_callback("text", *args, **kwargs) |
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[1358] | 107 | text.__doc__ = matplotlib.axes.Axes.text.__doc__ |
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[1153] | 108 | def arrow(self, *args, **kwargs): |
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| 109 | self._axes_callback("arrow", *args, **kwargs) |
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[1358] | 110 | arrow.__doc__ = matplotlib.axes.Axes.arrow.__doc__ |
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[1153] | 111 | def axvline(self, *args, **kwargs): |
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| 112 | self._axes_callback("axvline", *args, **kwargs) |
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[1358] | 113 | axvline.__doc__ = matplotlib.axes.Axes.axvline.__doc__ |
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[1153] | 114 | def axhline(self, *args, **kwargs): |
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| 115 | self._axes_callback("axhline", *args, **kwargs) |
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[1358] | 116 | axhline.__doc__ = matplotlib.axes.Axes.axhline.__doc__ |
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[1153] | 117 | def axvspan(self, *args, **kwargs): |
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| 118 | self._axes_callback("axvspan", *args, **kwargs) |
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| 119 | # hack to preventy mpl from redrawing the patch |
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| 120 | # it seem to convert the patch into lines on every draw. |
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| 121 | # This doesn't happen in a test script??? |
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| 122 | del self._plotter.axes.patches[-1] |
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[1358] | 123 | axvspan.__doc__ = matplotlib.axes.Axes.axvspan.__doc__ |
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[1232] | 124 | |
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[1153] | 125 | def axhspan(self, *args, **kwargs): |
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[1232] | 126 | self._axes_callback("axhspan", *args, **kwargs) |
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[1153] | 127 | # hack to preventy mpl from redrawing the patch |
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| 128 | # it seem to convert the patch into lines on every draw. |
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| 129 | # This doesn't happen in a test script??? |
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| 130 | del self._plotter.axes.patches[-1] |
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[1358] | 131 | axhspan.__doc__ = matplotlib.axes.Axes.axhspan.__doc__ |
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[1153] | 132 | |
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| 133 | def _axes_callback(self, axesfunc, *args, **kwargs): |
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| 134 | panel = 0 |
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| 135 | if kwargs.has_key("panel"): |
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| 136 | panel = kwargs.pop("panel") |
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| 137 | coords = None |
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| 138 | if kwargs.has_key("coords"): |
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| 139 | coords = kwargs.pop("coords") |
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| 140 | if coords.lower() == 'world': |
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| 141 | kwargs["transform"] = self._plotter.axes.transData |
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| 142 | elif coords.lower() == 'relative': |
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| 143 | kwargs["transform"] = self._plotter.axes.transAxes |
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| 144 | self._plotter.subplot(panel) |
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| 145 | self._plotter.axes.set_autoscale_on(False) |
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| 146 | getattr(self._plotter.axes, axesfunc)(*args, **kwargs) |
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| 147 | self._plotter.show(False) |
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| 148 | self._plotter.axes.set_autoscale_on(True) |
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| 149 | # end matplotlib.axes fowarding functions |
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| 150 | |
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[1698] | 151 | def set_data(self, scan, refresh=True): |
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[203] | 152 | """ |
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[1698] | 153 | Set a scantable to plot. |
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| 154 | Parameters: |
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| 155 | scan: a scantable |
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| 156 | refresh: True (default) or False. If True, the plot is |
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| 157 | replotted based on the new parameter setting(s). |
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| 158 | Otherwise,the parameter(s) are set without replotting. |
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[1702] | 159 | Note: |
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| 160 | The user specified masks and data selections will be reset |
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| 161 | if a new scantable is set. This method should be called before |
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| 162 | setting data selections (set_selection) and/or masks (set_mask). |
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[1698] | 163 | """ |
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| 164 | from asap import scantable |
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| 165 | if isinstance(scan, scantable): |
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| 166 | if self._data is not None: |
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| 167 | if scan != self._data: |
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| 168 | self._data = scan |
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| 169 | # reset |
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| 170 | self._reset() |
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[1702] | 171 | msg = "A new scantable is set to the plotter. The masks and data selections are reset." |
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| 172 | asaplog.push( msg ) |
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| 173 | print_log( 'INFO' ) |
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[1698] | 174 | else: |
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| 175 | self._data = scan |
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| 176 | self._reset() |
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| 177 | else: |
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| 178 | msg = "Input is not a scantable" |
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| 179 | if rcParams['verbose']: |
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| 180 | #print msg |
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| 181 | asaplog.push( msg ) |
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| 182 | print_log( 'ERROR' ) |
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| 183 | return |
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| 184 | raise TypeError(msg) |
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| 185 | |
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| 186 | # ranges become invalid when unit changes |
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| 187 | if self._abcunit and self._abcunit != self._data.get_unit(): |
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| 188 | self._minmaxx = None |
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| 189 | self._minmaxy = None |
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| 190 | self._abcunit = self._data.get_unit() |
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| 191 | self._datamask = None |
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| 192 | if refresh: self.plot() |
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| 193 | |
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| 194 | |
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| 195 | def set_mode(self, stacking=None, panelling=None, refresh=True): |
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| 196 | """ |
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[377] | 197 | Set the plots look and feel, i.e. what you want to see on the plot. |
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[203] | 198 | Parameters: |
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| 199 | stacking: tell the plotter which variable to plot |
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[1217] | 200 | as line colour overlays (default 'pol') |
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[203] | 201 | panelling: tell the plotter which variable to plot |
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| 202 | across multiple panels (default 'scan' |
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[1698] | 203 | refresh: True (default) or False. If True, the plot is |
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| 204 | replotted based on the new parameter setting(s). |
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| 205 | Otherwise,the parameter(s) are set without replotting. |
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[203] | 206 | Note: |
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| 207 | Valid modes are: |
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| 208 | 'beam' 'Beam' 'b': Beams |
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| 209 | 'if' 'IF' 'i': IFs |
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| 210 | 'pol' 'Pol' 'p': Polarisations |
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| 211 | 'scan' 'Scan' 's': Scans |
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| 212 | 'time' 'Time' 't': Times |
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| 213 | """ |
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[753] | 214 | msg = "Invalid mode" |
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| 215 | if not self.set_panelling(panelling) or \ |
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| 216 | not self.set_stacking(stacking): |
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| 217 | if rcParams['verbose']: |
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[1612] | 218 | #print msg |
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[1614] | 219 | asaplog.push( msg ) |
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| 220 | print_log( 'ERROR' ) |
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[753] | 221 | return |
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| 222 | else: |
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| 223 | raise TypeError(msg) |
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[1698] | 224 | if refresh and self._data: self.plot(self._data) |
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[203] | 225 | return |
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| 226 | |
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[554] | 227 | def set_panelling(self, what=None): |
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| 228 | mode = what |
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| 229 | if mode is None: |
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| 230 | mode = rcParams['plotter.panelling'] |
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| 231 | md = self._translate(mode) |
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[203] | 232 | if md: |
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[554] | 233 | self._panelling = md |
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[226] | 234 | self._title = None |
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[203] | 235 | return True |
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| 236 | return False |
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| 237 | |
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[1698] | 238 | def set_layout(self,rows=None,cols=None,refresh=True): |
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[377] | 239 | """ |
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| 240 | Set the multi-panel layout, i.e. how many rows and columns plots |
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| 241 | are visible. |
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| 242 | Parameters: |
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| 243 | rows: The number of rows of plots |
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| 244 | cols: The number of columns of plots |
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[1698] | 245 | refresh: True (default) or False. If True, the plot is |
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| 246 | replotted based on the new parameter setting(s). |
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| 247 | Otherwise,the parameter(s) are set without replotting. |
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[377] | 248 | Note: |
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| 249 | If no argument is given, the potter reverts to its auto-plot |
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| 250 | behaviour. |
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| 251 | """ |
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| 252 | self._rows = rows |
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| 253 | self._cols = cols |
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[1698] | 254 | if refresh and self._data: self.plot(self._data) |
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[377] | 255 | return |
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| 256 | |
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[709] | 257 | def set_stacking(self, what=None): |
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[554] | 258 | mode = what |
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[709] | 259 | if mode is None: |
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| 260 | mode = rcParams['plotter.stacking'] |
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[554] | 261 | md = self._translate(mode) |
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[203] | 262 | if md: |
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| 263 | self._stacking = md |
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[226] | 264 | self._lmap = None |
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[203] | 265 | return True |
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| 266 | return False |
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| 267 | |
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[1698] | 268 | def set_range(self,xstart=None,xend=None,ystart=None,yend=None,refresh=True): |
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[203] | 269 | """ |
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| 270 | Set the range of interest on the abcissa of the plot |
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| 271 | Parameters: |
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[525] | 272 | [x,y]start,[x,y]end: The start and end points of the 'zoom' window |
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[1698] | 273 | refresh: True (default) or False. If True, the plot is |
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| 274 | replotted based on the new parameter setting(s). |
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| 275 | Otherwise,the parameter(s) are set without replotting. |
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[203] | 276 | Note: |
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| 277 | These become non-sensical when the unit changes. |
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| 278 | use plotter.set_range() without parameters to reset |
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| 279 | |
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| 280 | """ |
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[525] | 281 | if xstart is None and xend is None: |
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| 282 | self._minmaxx = None |
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[600] | 283 | else: |
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| 284 | self._minmaxx = [xstart,xend] |
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[525] | 285 | if ystart is None and yend is None: |
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| 286 | self._minmaxy = None |
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[600] | 287 | else: |
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[709] | 288 | self._minmaxy = [ystart,yend] |
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[1698] | 289 | if refresh and self._data: self.plot(self._data) |
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[203] | 290 | return |
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[709] | 291 | |
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[1698] | 292 | def set_legend(self, mp=None, fontsize = None, mode = 0, refresh=True): |
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[203] | 293 | """ |
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| 294 | Specify a mapping for the legend instead of using the default |
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| 295 | indices: |
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| 296 | Parameters: |
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[1101] | 297 | mp: a list of 'strings'. This should have the same length |
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| 298 | as the number of elements on the legend and then maps |
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| 299 | to the indeces in order. It is possible to uses latex |
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| 300 | math expression. These have to be enclosed in r'', |
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| 301 | e.g. r'$x^{2}$' |
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| 302 | fontsize: The font size of the label (default None) |
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| 303 | mode: where to display the legend |
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| 304 | Any other value for loc else disables the legend: |
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[1096] | 305 | 0: auto |
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| 306 | 1: upper right |
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| 307 | 2: upper left |
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| 308 | 3: lower left |
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| 309 | 4: lower right |
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| 310 | 5: right |
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| 311 | 6: center left |
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| 312 | 7: center right |
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| 313 | 8: lower center |
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| 314 | 9: upper center |
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| 315 | 10: center |
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[1698] | 316 | refresh: True (default) or False. If True, the plot is |
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| 317 | replotted based on the new parameter setting(s). |
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| 318 | Otherwise,the parameter(s) are set without replotting. |
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[203] | 319 | |
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| 320 | Example: |
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[485] | 321 | If the data has two IFs/rest frequencies with index 0 and 1 |
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[203] | 322 | for CO and SiO: |
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| 323 | plotter.set_stacking('i') |
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[710] | 324 | plotter.set_legend(['CO','SiO']) |
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[203] | 325 | plotter.plot() |
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[710] | 326 | plotter.set_legend([r'$^{12}CO$', r'SiO']) |
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[203] | 327 | """ |
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| 328 | self._lmap = mp |
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[1096] | 329 | self._plotter.legend(mode) |
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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('legend', fontsize=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_title(self, title=None, fontsize=None, refresh=True): |
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[710] | 337 | """ |
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| 338 | Set the title of the plot. If multiple panels are plotted, |
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| 339 | multiple titles have to be specified. |
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[1698] | 340 | Parameters: |
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| 341 | refresh: True (default) or False. If True, the plot is |
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| 342 | replotted based on the new parameter setting(s). |
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| 343 | Otherwise,the parameter(s) are set without replotting. |
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[710] | 344 | Example: |
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| 345 | # two panels are visible on the plotter |
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| 346 | plotter.set_title(["First Panel","Second Panel"]) |
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| 347 | """ |
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[226] | 348 | self._title = title |
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[1101] | 349 | if isinstance(fontsize, int): |
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| 350 | from matplotlib import rc as rcp |
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| 351 | rcp('axes', titlesize=fontsize) |
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[1698] | 352 | if refresh and self._data: self.plot(self._data) |
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[226] | 353 | return |
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| 354 | |
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[1698] | 355 | def set_ordinate(self, ordinate=None, fontsize=None, refresh=True): |
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[710] | 356 | """ |
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| 357 | Set the y-axis label of the plot. If multiple panels are plotted, |
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| 358 | multiple labels have to be specified. |
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[1021] | 359 | Parameters: |
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| 360 | ordinate: a list of ordinate labels. None (default) let |
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| 361 | data determine the labels |
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[1698] | 362 | refresh: True (default) or False. If True, the plot is |
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| 363 | replotted based on the new parameter setting(s). |
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| 364 | Otherwise,the parameter(s) are set without replotting. |
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[710] | 365 | Example: |
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| 366 | # two panels are visible on the plotter |
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| 367 | plotter.set_ordinate(["First Y-Axis","Second Y-Axis"]) |
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| 368 | """ |
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[257] | 369 | self._ordinate = ordinate |
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[1101] | 370 | if isinstance(fontsize, int): |
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| 371 | from matplotlib import rc as rcp |
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| 372 | rcp('axes', labelsize=fontsize) |
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| 373 | rcp('ytick', labelsize=fontsize) |
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[1698] | 374 | if refresh and self._data: self.plot(self._data) |
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[257] | 375 | return |
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| 376 | |
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[1698] | 377 | def set_abcissa(self, abcissa=None, fontsize=None, refresh=True): |
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[710] | 378 | """ |
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| 379 | Set the x-axis label of the plot. If multiple panels are plotted, |
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| 380 | multiple labels have to be specified. |
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[1021] | 381 | Parameters: |
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| 382 | abcissa: a list of abcissa labels. None (default) let |
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| 383 | data determine the labels |
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[1698] | 384 | refresh: True (default) or False. If True, the plot is |
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| 385 | replotted based on the new parameter setting(s). |
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| 386 | Otherwise,the parameter(s) are set without replotting. |
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[710] | 387 | Example: |
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| 388 | # two panels are visible on the plotter |
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| 389 | plotter.set_ordinate(["First X-Axis","Second X-Axis"]) |
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| 390 | """ |
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[257] | 391 | self._abcissa = abcissa |
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[1101] | 392 | if isinstance(fontsize, int): |
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| 393 | from matplotlib import rc as rcp |
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| 394 | rcp('axes', labelsize=fontsize) |
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| 395 | rcp('xtick', labelsize=fontsize) |
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[1698] | 396 | if refresh and self._data: self.plot(self._data) |
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[257] | 397 | return |
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| 398 | |
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[1698] | 399 | def set_colors(self, colmap, refresh=True): |
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[377] | 400 | """ |
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[1217] | 401 | Set the colours to be used. The plotter will cycle through |
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| 402 | these colours when lines are overlaid (stacking mode). |
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[1021] | 403 | Parameters: |
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[1217] | 404 | colmap: a list of colour names |
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[1698] | 405 | refresh: True (default) or False. If True, the plot is |
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| 406 | replotted based on the new parameter setting(s). |
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| 407 | Otherwise,the parameter(s) are set without replotting. |
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[710] | 408 | Example: |
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| 409 | plotter.set_colors("red green blue") |
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| 410 | # If for example four lines are overlaid e.g I Q U V |
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| 411 | # 'I' will be 'red', 'Q' will be 'green', U will be 'blue' |
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| 412 | # and 'V' will be 'red' again. |
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| 413 | """ |
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[1217] | 414 | if isinstance(colmap,str): |
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| 415 | colmap = colmap.split() |
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| 416 | self._plotter.palette(0, colormap=colmap) |
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[1698] | 417 | if refresh and self._data: self.plot(self._data) |
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[710] | 418 | |
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[1217] | 419 | # alias for english speakers |
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| 420 | set_colours = set_colors |
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| 421 | |
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[1698] | 422 | def set_histogram(self, hist=True, linewidth=None, refresh=True): |
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[1021] | 423 | """ |
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| 424 | Enable/Disable histogram-like plotting. |
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| 425 | Parameters: |
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| 426 | hist: True (default) or False. The fisrt default |
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| 427 | is taken from the .asaprc setting |
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| 428 | plotter.histogram |
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[1698] | 429 | refresh: True (default) or False. If True, the plot is |
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| 430 | replotted based on the new parameter setting(s). |
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| 431 | Otherwise,the parameter(s) are set without replotting. |
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[1021] | 432 | """ |
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[1023] | 433 | self._hist = hist |
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[1101] | 434 | if isinstance(linewidth, float) or isinstance(linewidth, int): |
---|
| 435 | from matplotlib import rc as rcp |
---|
| 436 | rcp('lines', linewidth=linewidth) |
---|
[1698] | 437 | if refresh and self._data: self.plot(self._data) |
---|
[1023] | 438 | |
---|
[1698] | 439 | def set_linestyles(self, linestyles=None, linewidth=None, refresh=True): |
---|
[710] | 440 | """ |
---|
[734] | 441 | Set the linestyles to be used. The plotter will cycle through |
---|
| 442 | these linestyles when lines are overlaid (stacking mode) AND |
---|
| 443 | only one color has been set. |
---|
[710] | 444 | Parameters: |
---|
| 445 | linestyles: a list of linestyles to use. |
---|
| 446 | 'line', 'dashed', 'dotted', 'dashdot', |
---|
| 447 | 'dashdotdot' and 'dashdashdot' are |
---|
| 448 | possible |
---|
[1698] | 449 | refresh: True (default) or False. If True, the plot is |
---|
| 450 | replotted based on the new parameter setting(s). |
---|
| 451 | Otherwise,the parameter(s) are set without replotting. |
---|
[710] | 452 | Example: |
---|
| 453 | plotter.set_colors("black") |
---|
| 454 | plotter.set_linestyles("line dashed dotted dashdot") |
---|
| 455 | # If for example four lines are overlaid e.g I Q U V |
---|
| 456 | # 'I' will be 'solid', 'Q' will be 'dashed', |
---|
| 457 | # U will be 'dotted' and 'V' will be 'dashdot'. |
---|
| 458 | """ |
---|
| 459 | if isinstance(linestyles,str): |
---|
| 460 | linestyles = linestyles.split() |
---|
| 461 | self._plotter.palette(color=0,linestyle=0,linestyles=linestyles) |
---|
[1101] | 462 | if isinstance(linewidth, float) or isinstance(linewidth, int): |
---|
| 463 | from matplotlib import rc as rcp |
---|
| 464 | rcp('lines', linewidth=linewidth) |
---|
[1698] | 465 | if refresh and self._data: self.plot(self._data) |
---|
[710] | 466 | |
---|
[1698] | 467 | def set_font(self, family=None, style=None, weight=None, size=None, refresh=True): |
---|
[1101] | 468 | """ |
---|
| 469 | Set font properties. |
---|
| 470 | Parameters: |
---|
| 471 | family: one of 'sans-serif', 'serif', 'cursive', 'fantasy', 'monospace' |
---|
| 472 | style: one of 'normal' (or 'roman'), 'italic' or 'oblique' |
---|
| 473 | weight: one of 'normal or 'bold' |
---|
| 474 | size: the 'general' font size, individual elements can be adjusted |
---|
| 475 | seperately |
---|
[1698] | 476 | refresh: True (default) or False. If True, the plot is |
---|
| 477 | replotted based on the new parameter setting(s). |
---|
| 478 | Otherwise,the parameter(s) are set without replotting. |
---|
[1101] | 479 | """ |
---|
| 480 | from matplotlib import rc as rcp |
---|
| 481 | if isinstance(family, str): |
---|
| 482 | rcp('font', family=family) |
---|
| 483 | if isinstance(style, str): |
---|
| 484 | rcp('font', style=style) |
---|
| 485 | if isinstance(weight, str): |
---|
| 486 | rcp('font', weight=weight) |
---|
| 487 | if isinstance(size, float) or isinstance(size, int): |
---|
| 488 | rcp('font', size=size) |
---|
[1698] | 489 | if refresh and self._data: self.plot(self._data) |
---|
[1101] | 490 | |
---|
[1723] | 491 | def set_panellayout(self,layout=[],refresh=True): |
---|
| 492 | """ |
---|
| 493 | Set the layout of subplots. |
---|
| 494 | Parameters: |
---|
| 495 | layout: a list of subplots layout in figure coordinate (0-1), |
---|
| 496 | i.e., fraction of the figure width or height. |
---|
| 497 | The order of elements should be: |
---|
| 498 | [left, bottom, right, top, horizontal space btw panels, |
---|
| 499 | vertical space btw panels]. |
---|
| 500 | refresh: True (default) or False. If True, the plot is |
---|
| 501 | replotted based on the new parameter setting(s). |
---|
| 502 | Otherwise,the parameter(s) are set without replotting. |
---|
| 503 | Note |
---|
| 504 | * When layout is not specified, the values are reset to the defaults |
---|
| 505 | of matplotlib. |
---|
| 506 | * If any element is set to be None, the current value is adopted. |
---|
| 507 | """ |
---|
| 508 | if layout == []: self._panellayout=self._reset_panellayout() |
---|
| 509 | else: |
---|
| 510 | self._panellayout=[None]*6 |
---|
| 511 | self._panellayout[0:len(layout)]=layout |
---|
| 512 | #print "panel layout set to ",self._panellayout |
---|
| 513 | if refresh and self._data: self.plot(self._data) |
---|
| 514 | |
---|
| 515 | def _reset_panellayout(self): |
---|
| 516 | ks=map(lambda x: 'figure.subplot.'+x, |
---|
| 517 | ['left','bottom','right','top','hspace','wspace']) |
---|
| 518 | return map(matplotlib.rcParams.get,ks) |
---|
| 519 | |
---|
[1259] | 520 | def plot_lines(self, linecat=None, doppler=0.0, deltachan=10, rotate=90.0, |
---|
[1146] | 521 | location=None): |
---|
| 522 | """ |
---|
[1158] | 523 | Plot a line catalog. |
---|
| 524 | Parameters: |
---|
| 525 | linecat: the linecatalog to plot |
---|
[1168] | 526 | doppler: the velocity shift to apply to the frequencies |
---|
[1158] | 527 | deltachan: the number of channels to include each side of the |
---|
| 528 | line to determine a local maximum/minimum |
---|
[1259] | 529 | rotate: the rotation (in degrees) )for the text label (default 90.0) |
---|
[1158] | 530 | location: the location of the line annotation from the 'top', |
---|
| 531 | 'bottom' or alternate (None - the default) |
---|
[1165] | 532 | Notes: |
---|
| 533 | If the spectrum is flagged no line will be drawn in that location. |
---|
[1146] | 534 | """ |
---|
[1259] | 535 | if not self._data: |
---|
| 536 | raise RuntimeError("No scantable has been plotted yet.") |
---|
[1146] | 537 | from asap._asap import linecatalog |
---|
[1259] | 538 | if not isinstance(linecat, linecatalog): |
---|
| 539 | raise ValueError("'linecat' isn't of type linecatalog.") |
---|
| 540 | if not self._data.get_unit().endswith("Hz"): |
---|
| 541 | raise RuntimeError("Can only overlay linecatalogs when data is in frequency.") |
---|
[1153] | 542 | from matplotlib.numerix import ma |
---|
[1146] | 543 | for j in range(len(self._plotter.subplots)): |
---|
| 544 | self._plotter.subplot(j) |
---|
| 545 | lims = self._plotter.axes.get_xlim() |
---|
[1153] | 546 | for row in range(linecat.nrow()): |
---|
[1259] | 547 | # get_frequency returns MHz |
---|
| 548 | base = { "GHz": 1000.0, "MHz": 1.0, "Hz": 1.0e-6 } |
---|
| 549 | restf = linecat.get_frequency(row)/base[self._data.get_unit()] |
---|
[1165] | 550 | c = 299792.458 |
---|
[1174] | 551 | freq = restf*(1.0-doppler/c) |
---|
[1146] | 552 | if lims[0] < freq < lims[1]: |
---|
| 553 | if location is None: |
---|
| 554 | loc = 'bottom' |
---|
[1153] | 555 | if row%2: loc='top' |
---|
[1146] | 556 | else: loc = location |
---|
[1153] | 557 | maxys = [] |
---|
| 558 | for line in self._plotter.axes.lines: |
---|
| 559 | v = line._x |
---|
| 560 | asc = v[0] < v[-1] |
---|
| 561 | |
---|
| 562 | idx = None |
---|
| 563 | if not asc: |
---|
| 564 | if v[len(v)-1] <= freq <= v[0]: |
---|
| 565 | i = len(v)-1 |
---|
| 566 | while i>=0 and v[i] < freq: |
---|
| 567 | idx = i |
---|
| 568 | i-=1 |
---|
| 569 | else: |
---|
| 570 | if v[0] <= freq <= v[len(v)-1]: |
---|
| 571 | i = 0 |
---|
| 572 | while i<len(v) and v[i] < freq: |
---|
| 573 | idx = i |
---|
| 574 | i+=1 |
---|
| 575 | if idx is not None: |
---|
| 576 | lower = idx - deltachan |
---|
| 577 | upper = idx + deltachan |
---|
| 578 | if lower < 0: lower = 0 |
---|
| 579 | if upper > len(v): upper = len(v) |
---|
| 580 | s = slice(lower, upper) |
---|
[1167] | 581 | y = line._y[s] |
---|
[1165] | 582 | maxy = ma.maximum(y) |
---|
| 583 | if isinstance( maxy, float): |
---|
| 584 | maxys.append(maxy) |
---|
[1164] | 585 | if len(maxys): |
---|
| 586 | peak = max(maxys) |
---|
[1165] | 587 | if peak > self._plotter.axes.get_ylim()[1]: |
---|
| 588 | loc = 'bottom' |
---|
[1164] | 589 | else: |
---|
| 590 | continue |
---|
[1157] | 591 | self._plotter.vline_with_label(freq, peak, |
---|
| 592 | linecat.get_name(row), |
---|
| 593 | location=loc, rotate=rotate) |
---|
[1153] | 594 | self._plotter.show(hardrefresh=False) |
---|
[1146] | 595 | |
---|
[1153] | 596 | |
---|
[710] | 597 | def save(self, filename=None, orientation=None, dpi=None): |
---|
| 598 | """ |
---|
[377] | 599 | Save the plot to a file. The know formats are 'png', 'ps', 'eps'. |
---|
| 600 | Parameters: |
---|
| 601 | filename: The name of the output file. This is optional |
---|
| 602 | and autodetects the image format from the file |
---|
| 603 | suffix. If non filename is specified a file |
---|
| 604 | called 'yyyymmdd_hhmmss.png' is created in the |
---|
| 605 | current directory. |
---|
[709] | 606 | orientation: optional parameter for postscript only (not eps). |
---|
| 607 | 'landscape', 'portrait' or None (default) are valid. |
---|
| 608 | If None is choosen for 'ps' output, the plot is |
---|
| 609 | automatically oriented to fill the page. |
---|
[710] | 610 | dpi: The dpi of the output non-ps plot |
---|
[377] | 611 | """ |
---|
[709] | 612 | self._plotter.save(filename,orientation,dpi) |
---|
[377] | 613 | return |
---|
[709] | 614 | |
---|
[257] | 615 | |
---|
[1698] | 616 | def set_mask(self, mask=None, selection=None, refresh=True): |
---|
[525] | 617 | """ |
---|
[734] | 618 | Set a plotting mask for a specific polarization. |
---|
| 619 | This is useful for masking out "noise" Pangle outside a source. |
---|
| 620 | Parameters: |
---|
[920] | 621 | mask: a mask from scantable.create_mask |
---|
| 622 | selection: the spectra to apply the mask to. |
---|
[1698] | 623 | refresh: True (default) or False. If True, the plot is |
---|
| 624 | replotted based on the new parameter setting(s). |
---|
| 625 | Otherwise,the parameter(s) are set without replotting. |
---|
[734] | 626 | Example: |
---|
[920] | 627 | select = selector() |
---|
| 628 | select.setpolstrings("Pangle") |
---|
| 629 | plotter.set_mask(mymask, select) |
---|
[734] | 630 | """ |
---|
[710] | 631 | if not self._data: |
---|
[920] | 632 | msg = "Can only set mask after a first call to plot()" |
---|
[753] | 633 | if rcParams['verbose']: |
---|
[1612] | 634 | #print msg |
---|
[1614] | 635 | asaplog.push( msg ) |
---|
| 636 | print_log( 'ERROR' ) |
---|
[762] | 637 | return |
---|
[753] | 638 | else: |
---|
[762] | 639 | raise RuntimeError(msg) |
---|
[920] | 640 | if len(mask): |
---|
| 641 | if isinstance(mask, list) or isinstance(mask, tuple): |
---|
| 642 | self._usermask = array(mask) |
---|
[710] | 643 | else: |
---|
[920] | 644 | self._usermask = mask |
---|
| 645 | if mask is None and selection is None: |
---|
| 646 | self._usermask = [] |
---|
| 647 | self._maskselection = None |
---|
| 648 | if isinstance(selection, selector): |
---|
[947] | 649 | self._maskselection = {'b': selection.get_beams(), |
---|
| 650 | 's': selection.get_scans(), |
---|
| 651 | 'i': selection.get_ifs(), |
---|
| 652 | 'p': selection.get_pols(), |
---|
[920] | 653 | 't': [] } |
---|
[710] | 654 | else: |
---|
[920] | 655 | self._maskselection = None |
---|
[1698] | 656 | if refresh: self.plot(self._data) |
---|
[710] | 657 | |
---|
[709] | 658 | def _slice_indeces(self, data): |
---|
| 659 | mn = self._minmaxx[0] |
---|
| 660 | mx = self._minmaxx[1] |
---|
| 661 | asc = data[0] < data[-1] |
---|
| 662 | start=0 |
---|
| 663 | end = len(data)-1 |
---|
| 664 | inc = 1 |
---|
| 665 | if not asc: |
---|
| 666 | start = len(data)-1 |
---|
| 667 | end = 0 |
---|
| 668 | inc = -1 |
---|
| 669 | # find min index |
---|
[1562] | 670 | #while start > 0 and data[start] < mn: |
---|
| 671 | # start+= inc |
---|
| 672 | minind=start |
---|
| 673 | for ind in xrange(start,end+inc,inc): |
---|
| 674 | if data[ind] > mn: break |
---|
| 675 | minind=ind |
---|
[709] | 676 | # find max index |
---|
[1562] | 677 | #while end > 0 and data[end] > mx: |
---|
| 678 | # end-=inc |
---|
| 679 | #if end > 0: end +=1 |
---|
| 680 | maxind=end |
---|
| 681 | for ind in xrange(end,start-inc,-inc): |
---|
| 682 | if data[ind] < mx: break |
---|
| 683 | maxind=ind |
---|
| 684 | start=minind |
---|
| 685 | end=maxind |
---|
[709] | 686 | if start > end: |
---|
[1562] | 687 | return end,start+1 |
---|
| 688 | elif start < end: |
---|
| 689 | return start,end+1 |
---|
| 690 | else: |
---|
| 691 | return start,end |
---|
[709] | 692 | |
---|
[710] | 693 | def _reset(self): |
---|
[920] | 694 | self._usermask = [] |
---|
[710] | 695 | self._usermaskspectra = None |
---|
[920] | 696 | self.set_selection(None, False) |
---|
| 697 | |
---|
| 698 | def _plot(self, scan): |
---|
[947] | 699 | savesel = scan.get_selection() |
---|
| 700 | sel = savesel + self._selection |
---|
| 701 | d0 = {'s': 'SCANNO', 'b': 'BEAMNO', 'i':'IFNO', |
---|
| 702 | 'p': 'POLNO', 'c': 'CYCLENO', 't' : 'TIME' } |
---|
| 703 | order = [d0[self._panelling],d0[self._stacking]] |
---|
| 704 | sel.set_order(order) |
---|
| 705 | scan.set_selection(sel) |
---|
[920] | 706 | d = {'b': scan.getbeam, 's': scan.getscan, |
---|
| 707 | 'i': scan.getif, 'p': scan.getpol, 't': scan._gettime } |
---|
| 708 | |
---|
[1148] | 709 | polmodes = dict(zip(self._selection.get_pols(), |
---|
| 710 | self._selection.get_poltypes())) |
---|
| 711 | # this returns either a tuple of numbers or a length (ncycles) |
---|
| 712 | # convert this into lengths |
---|
| 713 | n0,nstack0 = self._get_selected_n(scan) |
---|
| 714 | if isinstance(n0, int): n = n0 |
---|
[1175] | 715 | else: n = len(n0) |
---|
[1148] | 716 | if isinstance(nstack0, int): nstack = nstack0 |
---|
[1175] | 717 | else: nstack = len(nstack0) |
---|
[998] | 718 | maxpanel, maxstack = 16,8 |
---|
[920] | 719 | if n > maxpanel or nstack > maxstack: |
---|
[1148] | 720 | maxn = 0 |
---|
| 721 | if nstack > maxstack: maxn = maxstack |
---|
| 722 | if n > maxpanel: maxn = maxpanel |
---|
[920] | 723 | msg ="Scan to be plotted contains more than %d selections.\n" \ |
---|
[1148] | 724 | "Selecting first %d selections..." % (maxn, maxn) |
---|
[920] | 725 | asaplog.push(msg) |
---|
[1614] | 726 | print_log('WARN') |
---|
[920] | 727 | n = min(n,maxpanel) |
---|
[998] | 728 | nstack = min(nstack,maxstack) |
---|
[920] | 729 | if n > 1: |
---|
| 730 | ganged = rcParams['plotter.ganged'] |
---|
[1446] | 731 | if self._panelling == 'i': |
---|
| 732 | ganged = False |
---|
[920] | 733 | if self._rows and self._cols: |
---|
| 734 | n = min(n,self._rows*self._cols) |
---|
| 735 | self._plotter.set_panels(rows=self._rows,cols=self._cols, |
---|
[1723] | 736 | # nplots=n,ganged=ganged) |
---|
| 737 | nplots=n,layout=self._panellayout,ganged=ganged) |
---|
[920] | 738 | else: |
---|
[1723] | 739 | # self._plotter.set_panels(rows=n,cols=0,nplots=n,ganged=ganged) |
---|
| 740 | self._plotter.set_panels(rows=n,cols=0,nplots=n,layout=self._panellayout,ganged=ganged) |
---|
[920] | 741 | else: |
---|
[1723] | 742 | # self._plotter.set_panels() |
---|
| 743 | self._plotter.set_panels(layout=self._panellayout) |
---|
[920] | 744 | r=0 |
---|
| 745 | nr = scan.nrow() |
---|
| 746 | a0,b0 = -1,-1 |
---|
| 747 | allxlim = [] |
---|
[1018] | 748 | allylim = [] |
---|
[920] | 749 | newpanel=True |
---|
| 750 | panelcount,stackcount = 0,0 |
---|
[1002] | 751 | while r < nr: |
---|
[920] | 752 | a = d[self._panelling](r) |
---|
| 753 | b = d[self._stacking](r) |
---|
| 754 | if a > a0 and panelcount < n: |
---|
| 755 | if n > 1: |
---|
| 756 | self._plotter.subplot(panelcount) |
---|
| 757 | self._plotter.palette(0) |
---|
| 758 | #title |
---|
| 759 | xlab = self._abcissa and self._abcissa[panelcount] \ |
---|
| 760 | or scan._getabcissalabel() |
---|
| 761 | ylab = self._ordinate and self._ordinate[panelcount] \ |
---|
| 762 | or scan._get_ordinate_label() |
---|
| 763 | self._plotter.set_axes('xlabel',xlab) |
---|
| 764 | self._plotter.set_axes('ylabel',ylab) |
---|
| 765 | lbl = self._get_label(scan, r, self._panelling, self._title) |
---|
| 766 | if isinstance(lbl, list) or isinstance(lbl, tuple): |
---|
| 767 | if 0 <= panelcount < len(lbl): |
---|
| 768 | lbl = lbl[panelcount] |
---|
| 769 | else: |
---|
| 770 | # get default label |
---|
| 771 | lbl = self._get_label(scan, r, self._panelling, None) |
---|
| 772 | self._plotter.set_axes('title',lbl) |
---|
| 773 | newpanel = True |
---|
| 774 | stackcount =0 |
---|
| 775 | panelcount += 1 |
---|
| 776 | if (b > b0 or newpanel) and stackcount < nstack: |
---|
| 777 | y = [] |
---|
| 778 | if len(polmodes): |
---|
| 779 | y = scan._getspectrum(r, polmodes[scan.getpol(r)]) |
---|
| 780 | else: |
---|
| 781 | y = scan._getspectrum(r) |
---|
| 782 | m = scan._getmask(r) |
---|
[1146] | 783 | from matplotlib.numerix import logical_not, logical_and |
---|
[920] | 784 | if self._maskselection and len(self._usermask) == len(m): |
---|
| 785 | if d[self._stacking](r) in self._maskselection[self._stacking]: |
---|
| 786 | m = logical_and(m, self._usermask) |
---|
| 787 | x = scan._getabcissa(r) |
---|
[1146] | 788 | from matplotlib.numerix import ma, array |
---|
[1116] | 789 | y = ma.masked_array(y,mask=logical_not(array(m,copy=False))) |
---|
[920] | 790 | if self._minmaxx is not None: |
---|
| 791 | s,e = self._slice_indeces(x) |
---|
| 792 | x = x[s:e] |
---|
| 793 | y = y[s:e] |
---|
[1096] | 794 | if len(x) > 1024 and rcParams['plotter.decimate']: |
---|
| 795 | fac = len(x)/1024 |
---|
[920] | 796 | x = x[::fac] |
---|
| 797 | y = y[::fac] |
---|
| 798 | llbl = self._get_label(scan, r, self._stacking, self._lmap) |
---|
| 799 | if isinstance(llbl, list) or isinstance(llbl, tuple): |
---|
| 800 | if 0 <= stackcount < len(llbl): |
---|
| 801 | # use user label |
---|
| 802 | llbl = llbl[stackcount] |
---|
| 803 | else: |
---|
| 804 | # get default label |
---|
| 805 | llbl = self._get_label(scan, r, self._stacking, None) |
---|
| 806 | self._plotter.set_line(label=llbl) |
---|
[1023] | 807 | plotit = self._plotter.plot |
---|
| 808 | if self._hist: plotit = self._plotter.hist |
---|
[1146] | 809 | if len(x) > 0: |
---|
| 810 | plotit(x,y) |
---|
| 811 | xlim= self._minmaxx or [min(x),max(x)] |
---|
| 812 | allxlim += xlim |
---|
| 813 | ylim= self._minmaxy or [ma.minimum(y),ma.maximum(y)] |
---|
| 814 | allylim += ylim |
---|
[1562] | 815 | else: |
---|
| 816 | xlim = self._minmaxx or [] |
---|
| 817 | allxlim += xlim |
---|
| 818 | ylim= self._minmaxy or [] |
---|
| 819 | allylim += ylim |
---|
[920] | 820 | stackcount += 1 |
---|
| 821 | # last in colour stack -> autoscale x |
---|
[1562] | 822 | if stackcount == nstack and len(allxlim) > 0: |
---|
[920] | 823 | allxlim.sort() |
---|
[1446] | 824 | self._plotter.subplots[panelcount-1]['axes'].set_xlim([allxlim[0],allxlim[-1]]) |
---|
[920] | 825 | # clear |
---|
| 826 | allxlim =[] |
---|
| 827 | |
---|
| 828 | newpanel = False |
---|
| 829 | a0=a |
---|
| 830 | b0=b |
---|
| 831 | # ignore following rows |
---|
| 832 | if (panelcount == n) and (stackcount == nstack): |
---|
[1018] | 833 | # last panel -> autoscale y if ganged |
---|
[1562] | 834 | if rcParams['plotter.ganged'] and len(allylim) > 0: |
---|
[1018] | 835 | allylim.sort() |
---|
| 836 | self._plotter.set_limits(ylim=[allylim[0],allylim[-1]]) |
---|
[998] | 837 | break |
---|
[920] | 838 | r+=1 # next row |
---|
[947] | 839 | #reset the selector to the scantable's original |
---|
| 840 | scan.set_selection(savesel) |
---|
[920] | 841 | |
---|
| 842 | def set_selection(self, selection=None, refresh=True): |
---|
[1698] | 843 | """ |
---|
| 844 | Parameters: |
---|
| 845 | selection: a selector object (default unset the selection) |
---|
| 846 | refresh: True (default) or False. If True, the plot is |
---|
| 847 | replotted based on the new parameter setting(s). |
---|
| 848 | Otherwise,the parameter(s) are set without replotting. |
---|
| 849 | """ |
---|
[947] | 850 | self._selection = isinstance(selection,selector) and selection or selector() |
---|
[920] | 851 | d0 = {'s': 'SCANNO', 'b': 'BEAMNO', 'i':'IFNO', |
---|
| 852 | 'p': 'POLNO', 'c': 'CYCLENO', 't' : 'TIME' } |
---|
| 853 | order = [d0[self._panelling],d0[self._stacking]] |
---|
[947] | 854 | self._selection.set_order(order) |
---|
[1698] | 855 | if refresh and self._data: self.plot(self._data) |
---|
[920] | 856 | |
---|
| 857 | def _get_selected_n(self, scan): |
---|
[1148] | 858 | d1 = {'b': scan.getbeamnos, 's': scan.getscannos, |
---|
| 859 | 'i': scan.getifnos, 'p': scan.getpolnos, 't': scan.ncycle } |
---|
| 860 | d2 = { 'b': self._selection.get_beams(), |
---|
| 861 | 's': self._selection.get_scans(), |
---|
| 862 | 'i': self._selection.get_ifs(), |
---|
| 863 | 'p': self._selection.get_pols(), |
---|
| 864 | 't': self._selection.get_cycles() } |
---|
[920] | 865 | n = d2[self._panelling] or d1[self._panelling]() |
---|
| 866 | nstack = d2[self._stacking] or d1[self._stacking]() |
---|
| 867 | return n,nstack |
---|
| 868 | |
---|
| 869 | def _get_label(self, scan, row, mode, userlabel=None): |
---|
[1153] | 870 | if isinstance(userlabel, list) and len(userlabel) == 0: |
---|
| 871 | userlabel = " " |
---|
[947] | 872 | pms = dict(zip(self._selection.get_pols(),self._selection.get_poltypes())) |
---|
[920] | 873 | if len(pms): |
---|
| 874 | poleval = scan._getpollabel(scan.getpol(row),pms[scan.getpol(row)]) |
---|
| 875 | else: |
---|
| 876 | poleval = scan._getpollabel(scan.getpol(row),scan.poltype()) |
---|
| 877 | d = {'b': "Beam "+str(scan.getbeam(row)), |
---|
[1714] | 878 | #'s': scan._getsourcename(row), |
---|
| 879 | 's': "Scan "+str(scan.getscan(row))+\ |
---|
| 880 | " ("+str(scan._getsourcename(row))+")", |
---|
[920] | 881 | 'i': "IF"+str(scan.getif(row)), |
---|
[964] | 882 | 'p': poleval, |
---|
[1175] | 883 | 't': str(scan.get_time(row)) } |
---|
[920] | 884 | return userlabel or d[mode] |
---|
[1153] | 885 | |
---|
[1446] | 886 | def plotazel(self, scan=None, outfile=None): |
---|
[1389] | 887 | """ |
---|
| 888 | plot azimuth and elevation versus time of a scantable |
---|
| 889 | """ |
---|
| 890 | import pylab as PL |
---|
| 891 | from matplotlib.dates import DateFormatter, timezone, HourLocator, MinuteLocator, DayLocator |
---|
| 892 | from matplotlib.ticker import MultipleLocator |
---|
| 893 | from matplotlib.numerix import array, pi |
---|
| 894 | self._data = scan |
---|
[1446] | 895 | self._outfile = outfile |
---|
[1457] | 896 | dates = self._data.get_time(asdatetime=True) |
---|
[1389] | 897 | t = PL.date2num(dates) |
---|
| 898 | tz = timezone('UTC') |
---|
| 899 | PL.cla() |
---|
[1446] | 900 | #PL.ioff() |
---|
[1389] | 901 | PL.clf() |
---|
[1723] | 902 | # Adjust subplot layouts |
---|
| 903 | if len(self._panellayout) !=6: self.set_panellayout(refresh=False) |
---|
| 904 | lef, bot, rig, top, wsp, hsp = self._panellayout |
---|
| 905 | PL.gcf().subplots_adjust(left=lef,bottom=bot,right=rig,top=top, |
---|
| 906 | wspace=wsp,hspace=hsp) |
---|
| 907 | |
---|
[1389] | 908 | tdel = max(t) - min(t) |
---|
| 909 | ax = PL.subplot(2,1,1) |
---|
| 910 | el = array(self._data.get_elevation())*180./pi |
---|
| 911 | PL.ylabel('El [deg.]') |
---|
| 912 | dstr = dates[0].strftime('%Y/%m/%d') |
---|
| 913 | if tdel > 1.0: |
---|
| 914 | dstr2 = dates[len(dates)-1].strftime('%Y/%m/%d') |
---|
| 915 | dstr = dstr + " - " + dstr2 |
---|
| 916 | majloc = DayLocator() |
---|
| 917 | minloc = HourLocator(range(0,23,12)) |
---|
| 918 | timefmt = DateFormatter("%b%d") |
---|
| 919 | else: |
---|
| 920 | timefmt = DateFormatter('%H') |
---|
| 921 | majloc = HourLocator() |
---|
| 922 | minloc = MinuteLocator(20) |
---|
| 923 | PL.title(dstr) |
---|
[1446] | 924 | |
---|
| 925 | if tdel == 0.0: |
---|
| 926 | th = (t - PL.floor(t))*24.0 |
---|
| 927 | PL.plot(th,el,'o',markersize=2, markerfacecolor='b', markeredgecolor='b') |
---|
| 928 | else: |
---|
| 929 | PL.plot_date(t,el,'o', markersize=2, markerfacecolor='b', markeredgecolor='b',tz=tz) |
---|
| 930 | #ax.grid(True) |
---|
| 931 | ax.xaxis.set_major_formatter(timefmt) |
---|
| 932 | ax.xaxis.set_major_locator(majloc) |
---|
| 933 | ax.xaxis.set_minor_locator(minloc) |
---|
[1389] | 934 | ax.yaxis.grid(True) |
---|
| 935 | yloc = MultipleLocator(30) |
---|
| 936 | ax.set_ylim(0,90) |
---|
| 937 | ax.yaxis.set_major_locator(yloc) |
---|
| 938 | if tdel > 1.0: |
---|
| 939 | labels = ax.get_xticklabels() |
---|
| 940 | # PL.setp(labels, fontsize=10, rotation=45) |
---|
| 941 | PL.setp(labels, fontsize=10) |
---|
[1446] | 942 | |
---|
[1389] | 943 | # Az plot |
---|
| 944 | az = array(self._data.get_azimuth())*180./pi |
---|
| 945 | if min(az) < 0: |
---|
| 946 | for irow in range(len(az)): |
---|
| 947 | if az[irow] < 0: az[irow] += 360.0 |
---|
| 948 | |
---|
| 949 | ax = PL.subplot(2,1,2) |
---|
[1446] | 950 | #PL.xlabel('Time (UT [hour])') |
---|
[1389] | 951 | PL.ylabel('Az [deg.]') |
---|
[1446] | 952 | if tdel == 0.0: |
---|
| 953 | PL.plot(th,az,'o',markersize=2, markeredgecolor='b',markerfacecolor='b') |
---|
| 954 | else: |
---|
| 955 | PL.plot_date(t,az,'o', markersize=2,markeredgecolor='b',markerfacecolor='b',tz=tz) |
---|
| 956 | ax.xaxis.set_major_formatter(timefmt) |
---|
| 957 | ax.xaxis.set_major_locator(majloc) |
---|
| 958 | ax.xaxis.set_minor_locator(minloc) |
---|
| 959 | #ax.grid(True) |
---|
[1389] | 960 | ax.set_ylim(0,360) |
---|
| 961 | ax.yaxis.grid(True) |
---|
| 962 | #hfmt = DateFormatter('%H') |
---|
| 963 | #hloc = HourLocator() |
---|
| 964 | yloc = MultipleLocator(60) |
---|
| 965 | ax.yaxis.set_major_locator(yloc) |
---|
| 966 | if tdel > 1.0: |
---|
| 967 | labels = ax.get_xticklabels() |
---|
| 968 | PL.setp(labels, fontsize=10) |
---|
[1446] | 969 | PL.xlabel('Time (UT [day])') |
---|
| 970 | else: |
---|
| 971 | PL.xlabel('Time (UT [hour])') |
---|
| 972 | |
---|
| 973 | #PL.ion() |
---|
[1389] | 974 | PL.draw() |
---|
[1446] | 975 | if (self._outfile is not None): |
---|
| 976 | PL.savefig(self._outfile) |
---|
[1389] | 977 | |
---|
[1446] | 978 | def plotpointing(self, scan=None, outfile=None): |
---|
[1389] | 979 | """ |
---|
| 980 | plot telescope pointings |
---|
| 981 | """ |
---|
| 982 | import pylab as PL |
---|
| 983 | from matplotlib.dates import DateFormatter, timezone |
---|
| 984 | from matplotlib.ticker import MultipleLocator |
---|
| 985 | from matplotlib.numerix import array, pi, zeros |
---|
| 986 | self._data = scan |
---|
[1446] | 987 | self._outfile = outfile |
---|
[1389] | 988 | dir = array(self._data.get_directionval()).transpose() |
---|
| 989 | ra = dir[0]*180./pi |
---|
| 990 | dec = dir[1]*180./pi |
---|
| 991 | PL.cla() |
---|
[1446] | 992 | #PL.ioff() |
---|
[1389] | 993 | PL.clf() |
---|
[1723] | 994 | # Adjust subplot layouts |
---|
| 995 | if len(self._panellayout) !=6: self.set_panellayout(refresh=False) |
---|
| 996 | lef, bot, rig, top, wsp, hsp = self._panellayout |
---|
| 997 | PL.gcf().subplots_adjust(left=lef,bottom=bot,right=rig,top=top, |
---|
| 998 | wspace=wsp,hspace=hsp) |
---|
[1732] | 999 | ax = PL.gca() |
---|
| 1000 | #ax = PL.axes([0.1,0.1,0.8,0.8]) |
---|
| 1001 | #ax = PL.axes([0.1,0.1,0.8,0.8]) |
---|
[1389] | 1002 | ax.set_aspect('equal') |
---|
| 1003 | PL.plot(ra,dec, 'b,') |
---|
| 1004 | PL.xlabel('RA [deg.]') |
---|
| 1005 | PL.ylabel('Declination [deg.]') |
---|
| 1006 | PL.title('Telescope pointings') |
---|
| 1007 | [xmin,xmax,ymin,ymax] = PL.axis() |
---|
| 1008 | PL.axis([xmax,xmin,ymin,ymax]) |
---|
[1446] | 1009 | #PL.ion() |
---|
[1389] | 1010 | PL.draw() |
---|
[1446] | 1011 | if (self._outfile is not None): |
---|
| 1012 | PL.savefig(self._outfile) |
---|
[1389] | 1013 | |
---|
[1446] | 1014 | # plot total power data |
---|
| 1015 | # plotting in time is not yet implemented.. |
---|
| 1016 | def plottp(self, scan=None, outfile=None): |
---|
| 1017 | if self._plotter.is_dead: |
---|
| 1018 | self._plotter = self._newplotter() |
---|
| 1019 | self._plotter.hold() |
---|
| 1020 | self._plotter.clear() |
---|
| 1021 | from asap import scantable |
---|
| 1022 | if not self._data and not scan: |
---|
| 1023 | msg = "Input is not a scantable" |
---|
| 1024 | if rcParams['verbose']: |
---|
[1612] | 1025 | #print msg |
---|
[1614] | 1026 | asaplog.push( msg ) |
---|
| 1027 | print_log( 'ERROR' ) |
---|
[1446] | 1028 | return |
---|
| 1029 | raise TypeError(msg) |
---|
| 1030 | if isinstance(scan, scantable): |
---|
| 1031 | if self._data is not None: |
---|
| 1032 | if scan != self._data: |
---|
| 1033 | self._data = scan |
---|
| 1034 | # reset |
---|
| 1035 | self._reset() |
---|
| 1036 | else: |
---|
| 1037 | self._data = scan |
---|
| 1038 | self._reset() |
---|
| 1039 | # ranges become invalid when abcissa changes? |
---|
| 1040 | #if self._abcunit and self._abcunit != self._data.get_unit(): |
---|
| 1041 | # self._minmaxx = None |
---|
| 1042 | # self._minmaxy = None |
---|
| 1043 | # self._abcunit = self._data.get_unit() |
---|
| 1044 | # self._datamask = None |
---|
[1723] | 1045 | |
---|
| 1046 | # Adjust subplot layouts |
---|
| 1047 | if len(self._panellayout) !=6: self.set_panellayout(refresh=False) |
---|
| 1048 | lef, bot, rig, top, wsp, hsp = self._panellayout |
---|
| 1049 | self._plotter.figure.subplots_adjust( |
---|
| 1050 | left=lef,bottom=bot,right=rig,top=top,wspace=wsp,hspace=hsp) |
---|
[1724] | 1051 | if self._plotter.figmgr.casabar: self._plotter.figmgr.casabar.disable_button() |
---|
[1446] | 1052 | self._plottp(self._data) |
---|
| 1053 | if self._minmaxy is not None: |
---|
| 1054 | self._plotter.set_limits(ylim=self._minmaxy) |
---|
| 1055 | self._plotter.release() |
---|
| 1056 | self._plotter.tidy() |
---|
| 1057 | self._plotter.show(hardrefresh=False) |
---|
| 1058 | print_log() |
---|
| 1059 | return |
---|
| 1060 | |
---|
| 1061 | def _plottp(self,scan): |
---|
| 1062 | """ |
---|
| 1063 | private method for plotting total power data |
---|
| 1064 | """ |
---|
| 1065 | from matplotlib.numerix import ma, array, arange, logical_not |
---|
| 1066 | r=0 |
---|
| 1067 | nr = scan.nrow() |
---|
| 1068 | a0,b0 = -1,-1 |
---|
| 1069 | allxlim = [] |
---|
| 1070 | allylim = [] |
---|
| 1071 | y=[] |
---|
| 1072 | self._plotter.set_panels() |
---|
| 1073 | self._plotter.palette(0) |
---|
| 1074 | #title |
---|
| 1075 | #xlab = self._abcissa and self._abcissa[panelcount] \ |
---|
| 1076 | # or scan._getabcissalabel() |
---|
| 1077 | #ylab = self._ordinate and self._ordinate[panelcount] \ |
---|
| 1078 | # or scan._get_ordinate_label() |
---|
| 1079 | xlab = self._abcissa or 'row number' #or Time |
---|
| 1080 | ylab = self._ordinate or scan._get_ordinate_label() |
---|
| 1081 | self._plotter.set_axes('xlabel',xlab) |
---|
| 1082 | self._plotter.set_axes('ylabel',ylab) |
---|
| 1083 | lbl = self._get_label(scan, r, 's', self._title) |
---|
| 1084 | if isinstance(lbl, list) or isinstance(lbl, tuple): |
---|
| 1085 | # if 0 <= panelcount < len(lbl): |
---|
| 1086 | # lbl = lbl[panelcount] |
---|
| 1087 | # else: |
---|
| 1088 | # get default label |
---|
| 1089 | lbl = self._get_label(scan, r, self._panelling, None) |
---|
| 1090 | self._plotter.set_axes('title',lbl) |
---|
| 1091 | y=array(scan._get_column(scan._getspectrum,-1)) |
---|
| 1092 | m = array(scan._get_column(scan._getmask,-1)) |
---|
| 1093 | y = ma.masked_array(y,mask=logical_not(array(m,copy=False))) |
---|
| 1094 | x = arange(len(y)) |
---|
| 1095 | # try to handle spectral data somewhat... |
---|
| 1096 | l,m = y.shape |
---|
| 1097 | if m > 1: |
---|
| 1098 | y=y.mean(axis=1) |
---|
| 1099 | plotit = self._plotter.plot |
---|
| 1100 | llbl = self._get_label(scan, r, self._stacking, None) |
---|
| 1101 | self._plotter.set_line(label=llbl) |
---|
| 1102 | if len(x) > 0: |
---|
| 1103 | plotit(x,y) |
---|
| 1104 | |
---|
| 1105 | |
---|
| 1106 | # forwards to matplotlib.Figure.text |
---|
| 1107 | def figtext(self, *args, **kwargs): |
---|
| 1108 | """ |
---|
| 1109 | Add text to figure at location x,y (relative 0-1 coords). |
---|
| 1110 | This method forwards *args and **kwargs to a Matplotlib method, |
---|
| 1111 | matplotlib.Figure.text. |
---|
| 1112 | See the method help for detailed information. |
---|
| 1113 | """ |
---|
| 1114 | self._plotter.text(*args, **kwargs) |
---|
| 1115 | # end matplotlib.Figure.text forwarding function |
---|
| 1116 | |
---|
[1723] | 1117 | |
---|
| 1118 | # printing header information |
---|
| 1119 | def print_header(self, plot=True, fontsize=9, logger=False, selstr='', extrastr=''): |
---|
| 1120 | """ |
---|
| 1121 | print data (scantable) header on the plot and/or logger. |
---|
| 1122 | Parameters: |
---|
| 1123 | plot: whether or not print header info on the plot. |
---|
| 1124 | fontsize: header font size (valid only plot=True) |
---|
| 1125 | autoscale: whether or not autoscale the plot (valid only plot=True) |
---|
| 1126 | logger: whether or not print header info on the logger. |
---|
| 1127 | selstr: additional selection string (not verified) |
---|
| 1128 | extrastr: additional string to print (not verified) |
---|
| 1129 | """ |
---|
| 1130 | if not plot and not logger: return |
---|
| 1131 | if not self._data: raise RuntimeError("No scantable has been set yet.") |
---|
| 1132 | # Now header will be printed on plot and/or logger. |
---|
| 1133 | # Get header information and format it. |
---|
| 1134 | ssum=self._data.__str__() |
---|
| 1135 | # Print Observation header to the upper-left corner of plot |
---|
| 1136 | if plot: |
---|
| 1137 | srest=ssum[ssum.find('Rest Freqs:'):ssum.find('Abcissa:')] |
---|
| 1138 | shead=ssum[ssum.find('Beams:'):ssum.find('Flux Unit:')] |
---|
| 1139 | headstr=shead.split('\n\n') |
---|
| 1140 | if extrastr != '': headstr[1]=extrastr+'\n'+headstr[1] |
---|
| 1141 | #headstr[1]='Data File: '+(filestr or 'unknown')+'\n'+headstr[1] |
---|
| 1142 | headstr[0]=headstr[0]+'\n'+srest |
---|
| 1143 | headstr.reverse() |
---|
| 1144 | ssel='***Selections***\n'+(selstr+self._data.get_selection().__str__() or 'none') |
---|
| 1145 | headstr.append(ssel) |
---|
| 1146 | nstcol=len(headstr) |
---|
| 1147 | |
---|
| 1148 | self._plotter.hold() |
---|
| 1149 | for i in range(nstcol): |
---|
| 1150 | self._plotter.figure.text(0.03+float(i)/nstcol,0.98, |
---|
| 1151 | headstr[i], |
---|
| 1152 | horizontalalignment='left', |
---|
| 1153 | verticalalignment='top', |
---|
| 1154 | fontsize=fontsize) |
---|
| 1155 | import time |
---|
| 1156 | self._plotter.figure.text(0.99,0.0, |
---|
| 1157 | time.strftime("%a %d %b %Y %H:%M:%S %Z"), |
---|
| 1158 | horizontalalignment='right', |
---|
| 1159 | verticalalignment='bottom',fontsize=8) |
---|
| 1160 | self._plotter.release() |
---|
| 1161 | del srest, shead, headstr, ssel |
---|
| 1162 | if logger: |
---|
| 1163 | asaplog.push("----------------\n Plot Summary\n----------------") |
---|
| 1164 | asaplog.push(extrastr) |
---|
| 1165 | asaplog.push(ssum[ssum.find('Beams:'):]) |
---|
| 1166 | print_log() |
---|
| 1167 | del ssum |
---|
[1724] | 1168 | |
---|
| 1169 | |
---|