| [947] | 1 | from asap import rcParams, print_log, selector
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| [1153] | 2 | import matplotlib.axes
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| [1320] | 3 | import re
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| [203] | 4 |
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| 5 | class asapplotter:
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| [226] | 6 | """
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| 7 | The ASAP plotter.
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| 8 | By default the plotter is set up to plot polarisations
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| 9 | 'colour stacked' and scantables across panels.
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| 10 | Note:
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| 11 | Currenly it only plots 'spectra' not Tsys or
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| 12 | other variables.
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| 13 | """
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| [734] | 14 | def __init__(self, visible=None):
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| 15 | self._visible = rcParams['plotter.gui']
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| 16 | if visible is not None:
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| 17 | self._visible = visible
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| [710] | 18 | self._plotter = self._newplotter()
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| 19 |
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| [554] | 20 | self._panelling = None
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| 21 | self._stacking = None
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| 22 | self.set_panelling()
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| 23 | self.set_stacking()
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| [377] | 24 | self._rows = None
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| 25 | self._cols = None
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| [203] | 26 | self._autoplot = False
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| [525] | 27 | self._minmaxx = None
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| 28 | self._minmaxy = None
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| [710] | 29 | self._datamask = None
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| [203] | 30 | self._data = None
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| [607] | 31 | self._lmap = None
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| [226] | 32 | self._title = None
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| [257] | 33 | self._ordinate = None
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| 34 | self._abcissa = None
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| [709] | 35 | self._abcunit = None
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| [920] | 36 | self._usermask = []
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| 37 | self._maskselection = None
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| 38 | self._selection = selector()
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| [1023] | 39 | self._hist = rcParams['plotter.histogram']
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| 40 |
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| [920] | 41 | def _translate(self, instr):
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| 42 | keys = "s b i p t".split()
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| 43 | if isinstance(instr, str):
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| 44 | for key in keys:
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| 45 | if instr.lower().startswith(key):
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| 46 | return key
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| 47 | return None
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| 48 |
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| [710] | 49 | def _newplotter(self):
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| 50 | if self._visible:
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| 51 | from asap.asaplotgui import asaplotgui as asaplot
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| 52 | else:
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| 53 | from asap.asaplot import asaplot
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| 54 | return asaplot()
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| 55 |
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| 56 |
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| [935] | 57 | def plot(self, scan=None):
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| [203] | 58 | """
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| [920] | 59 | Plot a scantable.
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| [203] | 60 | Parameters:
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| [920] | 61 | scan: a scantable
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| [203] | 62 | Note:
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| [920] | 63 | If a scantable was specified in a previous call
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| [203] | 64 | to plot, no argument has to be given to 'replot'
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| [920] | 65 | NO checking is done that the abcissas of the scantable
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| [203] | 66 | are consistent e.g. all 'channel' or all 'velocity' etc.
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| 67 | """
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| [710] | 68 | if self._plotter.is_dead:
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| 69 | self._plotter = self._newplotter()
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| [600] | 70 | self._plotter.hold()
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| [203] | 71 | self._plotter.clear()
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| [920] | 72 | from asap import scantable
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| [935] | 73 | if not self._data and not scan:
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| [1101] | 74 | msg = "Input is not a scantable"
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| 75 | if rcParams['verbose']:
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| 76 | print msg
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| 77 | return
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| 78 | raise TypeError(msg)
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| [920] | 79 | if isinstance(scan, scantable):
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| [709] | 80 | if self._data is not None:
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| [920] | 81 | if scan != self._data:
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| 82 | self._data = scan
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| [710] | 83 | # reset
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| 84 | self._reset()
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| [525] | 85 | else:
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| [920] | 86 | self._data = scan
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| [710] | 87 | self._reset()
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| [709] | 88 | # ranges become invalid when unit changes
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| [935] | 89 | if self._abcunit and self._abcunit != self._data.get_unit():
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| [709] | 90 | self._minmaxx = None
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| 91 | self._minmaxy = None
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| [920] | 92 | self._abcunit = self._data.get_unit()
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| [710] | 93 | self._datamask = None
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| [920] | 94 | self._plot(self._data)
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| [709] | 95 | if self._minmaxy is not None:
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| 96 | self._plotter.set_limits(ylim=self._minmaxy)
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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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| 107 | text. __doc__ = matplotlib.axes.Axes.text.__doc__
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| 108 | def arrow(self, *args, **kwargs):
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| 109 | self._axes_callback("arrow", *args, **kwargs)
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| 110 | arrow. __doc__ = matplotlib.axes.Axes.arrow.__doc__
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| 111 | def axvline(self, *args, **kwargs):
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| 112 | self._axes_callback("axvline", *args, **kwargs)
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| 113 | axvline. __doc__ = matplotlib.axes.Axes.axvline.__doc__
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| 114 | def axhline(self, *args, **kwargs):
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| 115 | self._axes_callback("axhline", *args, **kwargs)
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| 116 | axhline. __doc__ = matplotlib.axes.Axes.axhline.__doc__
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| 117 | def axvspan(self, *args, **kwargs):
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| 118 | self._axes_callback("axvspan", *args, **kwargs)
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| 119 | # hack to preventy mpl from redrawing the patch
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| 120 | # it seem to convert the patch into lines on every draw.
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| 121 | # This doesn't happen in a test script???
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| 122 | del self._plotter.axes.patches[-1]
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| 123 | axvspan. __doc__ = matplotlib.axes.Axes.axvspan.__doc__
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| [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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| 131 | axhspan. __doc__ = matplotlib.axes.Axes.axhspan.__doc__
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| 132 |
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| 133 | def _axes_callback(self, axesfunc, *args, **kwargs):
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| 134 | panel = 0
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| 135 | if kwargs.has_key("panel"):
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| 136 | panel = kwargs.pop("panel")
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| 137 | coords = None
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| 138 | if kwargs.has_key("coords"):
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| 139 | coords = kwargs.pop("coords")
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| 140 | if coords.lower() == 'world':
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| 141 | kwargs["transform"] = self._plotter.axes.transData
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| 142 | elif coords.lower() == 'relative':
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| 143 | kwargs["transform"] = self._plotter.axes.transAxes
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| 144 | self._plotter.subplot(panel)
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| 145 | self._plotter.axes.set_autoscale_on(False)
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| 146 | getattr(self._plotter.axes, axesfunc)(*args, **kwargs)
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| 147 | self._plotter.show(False)
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| 148 | self._plotter.axes.set_autoscale_on(True)
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| 149 | # end matplotlib.axes fowarding functions
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| 150 |
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| [226] | 151 | def set_mode(self, stacking=None, panelling=None):
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| [203] | 152 | """
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| [377] | 153 | Set the plots look and feel, i.e. what you want to see on the plot.
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| [203] | 154 | Parameters:
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| 155 | stacking: tell the plotter which variable to plot
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| [1217] | 156 | as line colour overlays (default 'pol')
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| [203] | 157 | panelling: tell the plotter which variable to plot
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| 158 | across multiple panels (default 'scan'
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| 159 | Note:
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| 160 | Valid modes are:
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| 161 | 'beam' 'Beam' 'b': Beams
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| 162 | 'if' 'IF' 'i': IFs
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| 163 | 'pol' 'Pol' 'p': Polarisations
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| 164 | 'scan' 'Scan' 's': Scans
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| 165 | 'time' 'Time' 't': Times
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| 166 | """
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| [753] | 167 | msg = "Invalid mode"
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| 168 | if not self.set_panelling(panelling) or \
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| 169 | not self.set_stacking(stacking):
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| 170 | if rcParams['verbose']:
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| 171 | print msg
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| 172 | return
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| 173 | else:
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| 174 | raise TypeError(msg)
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| [920] | 175 | if self._data: self.plot(self._data)
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| [203] | 176 | return
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| 177 |
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| [554] | 178 | def set_panelling(self, what=None):
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| 179 | mode = what
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| 180 | if mode is None:
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| 181 | mode = rcParams['plotter.panelling']
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| 182 | md = self._translate(mode)
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| [203] | 183 | if md:
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| [554] | 184 | self._panelling = md
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| [226] | 185 | self._title = None
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| [203] | 186 | return True
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| 187 | return False
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| 188 |
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| [377] | 189 | def set_layout(self,rows=None,cols=None):
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| 190 | """
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| 191 | Set the multi-panel layout, i.e. how many rows and columns plots
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| 192 | are visible.
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| 193 | Parameters:
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| 194 | rows: The number of rows of plots
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| 195 | cols: The number of columns of plots
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| 196 | Note:
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| 197 | If no argument is given, the potter reverts to its auto-plot
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| 198 | behaviour.
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| 199 | """
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| 200 | self._rows = rows
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| 201 | self._cols = cols
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| [920] | 202 | if self._data: self.plot(self._data)
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| [377] | 203 | return
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| 204 |
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| [709] | 205 | def set_stacking(self, what=None):
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| [554] | 206 | mode = what
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| [709] | 207 | if mode is None:
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| 208 | mode = rcParams['plotter.stacking']
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| [554] | 209 | md = self._translate(mode)
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| [203] | 210 | if md:
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| 211 | self._stacking = md
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| [226] | 212 | self._lmap = None
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| [203] | 213 | return True
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| 214 | return False
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| 215 |
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| [525] | 216 | def set_range(self,xstart=None,xend=None,ystart=None,yend=None):
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| [203] | 217 | """
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| 218 | Set the range of interest on the abcissa of the plot
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| 219 | Parameters:
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| [525] | 220 | [x,y]start,[x,y]end: The start and end points of the 'zoom' window
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| [203] | 221 | Note:
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| 222 | These become non-sensical when the unit changes.
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| 223 | use plotter.set_range() without parameters to reset
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| 224 |
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| 225 | """
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| [525] | 226 | if xstart is None and xend is None:
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| 227 | self._minmaxx = None
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| [600] | 228 | else:
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| 229 | self._minmaxx = [xstart,xend]
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| [525] | 230 | if ystart is None and yend is None:
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| 231 | self._minmaxy = None
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| [600] | 232 | else:
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| [709] | 233 | self._minmaxy = [ystart,yend]
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| [920] | 234 | if self._data: self.plot(self._data)
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| [203] | 235 | return
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| [709] | 236 |
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| [1101] | 237 | def set_legend(self, mp=None, fontsize = None, mode = 0):
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| [203] | 238 | """
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| 239 | Specify a mapping for the legend instead of using the default
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| 240 | indices:
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| 241 | Parameters:
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| [1101] | 242 | mp: a list of 'strings'. This should have the same length
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| 243 | as the number of elements on the legend and then maps
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| 244 | to the indeces in order. It is possible to uses latex
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| 245 | math expression. These have to be enclosed in r'',
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| 246 | e.g. r'$x^{2}$'
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| 247 | fontsize: The font size of the label (default None)
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| 248 | mode: where to display the legend
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| 249 | Any other value for loc else disables the legend:
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| [1096] | 250 | 0: auto
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| 251 | 1: upper right
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| 252 | 2: upper left
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| 253 | 3: lower left
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| 254 | 4: lower right
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| 255 | 5: right
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| 256 | 6: center left
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| 257 | 7: center right
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| 258 | 8: lower center
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| 259 | 9: upper center
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| 260 | 10: center
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| [203] | 261 |
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| 262 | Example:
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| [485] | 263 | If the data has two IFs/rest frequencies with index 0 and 1
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| [203] | 264 | for CO and SiO:
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| 265 | plotter.set_stacking('i')
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| [710] | 266 | plotter.set_legend(['CO','SiO'])
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| [203] | 267 | plotter.plot()
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| [710] | 268 | plotter.set_legend([r'$^{12}CO$', r'SiO'])
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| [203] | 269 | """
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| 270 | self._lmap = mp
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| [1096] | 271 | self._plotter.legend(mode)
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| [1101] | 272 | if isinstance(fontsize, int):
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| 273 | from matplotlib import rc as rcp
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| 274 | rcp('legend', fontsize=fontsize)
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| [1096] | 275 | if self._data:
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| 276 | self.plot(self._data)
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| [226] | 277 | return
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| 278 |
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| [1101] | 279 | def set_title(self, title=None, fontsize=None):
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| [710] | 280 | """
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| 281 | Set the title of the plot. If multiple panels are plotted,
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| 282 | multiple titles have to be specified.
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| 283 | Example:
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| 284 | # two panels are visible on the plotter
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| 285 | plotter.set_title(["First Panel","Second Panel"])
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| 286 | """
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| [226] | 287 | self._title = title
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| [1101] | 288 | if isinstance(fontsize, int):
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| 289 | from matplotlib import rc as rcp
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| 290 | rcp('axes', titlesize=fontsize)
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| [920] | 291 | if self._data: self.plot(self._data)
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| [226] | 292 | return
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| 293 |
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| [1101] | 294 | def set_ordinate(self, ordinate=None, fontsize=None):
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| [710] | 295 | """
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| 296 | Set the y-axis label of the plot. If multiple panels are plotted,
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| 297 | multiple labels have to be specified.
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| [1021] | 298 | Parameters:
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| 299 | ordinate: a list of ordinate labels. None (default) let
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| 300 | data determine the labels
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| [710] | 301 | Example:
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| 302 | # two panels are visible on the plotter
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| 303 | plotter.set_ordinate(["First Y-Axis","Second Y-Axis"])
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| 304 | """
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| [257] | 305 | self._ordinate = ordinate
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| [1101] | 306 | if isinstance(fontsize, int):
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| 307 | from matplotlib import rc as rcp
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| 308 | rcp('axes', labelsize=fontsize)
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| 309 | rcp('ytick', labelsize=fontsize)
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| [920] | 310 | if self._data: self.plot(self._data)
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| [257] | 311 | return
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| 312 |
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| [1101] | 313 | def set_abcissa(self, abcissa=None, fontsize=None):
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| [710] | 314 | """
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| 315 | Set the x-axis label of the plot. If multiple panels are plotted,
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| 316 | multiple labels have to be specified.
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| [1021] | 317 | Parameters:
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| 318 | abcissa: a list of abcissa labels. None (default) let
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| 319 | data determine the labels
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| [710] | 320 | Example:
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| 321 | # two panels are visible on the plotter
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| 322 | plotter.set_ordinate(["First X-Axis","Second X-Axis"])
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| 323 | """
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| [257] | 324 | self._abcissa = abcissa
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| [1101] | 325 | if isinstance(fontsize, int):
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| 326 | from matplotlib import rc as rcp
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| 327 | rcp('axes', labelsize=fontsize)
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| 328 | rcp('xtick', labelsize=fontsize)
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| [920] | 329 | if self._data: self.plot(self._data)
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| [257] | 330 | return
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| 331 |
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| [1217] | 332 | def set_colors(self, colmap):
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| [377] | 333 | """
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| [1217] | 334 | Set the colours to be used. The plotter will cycle through
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| 335 | these colours when lines are overlaid (stacking mode).
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| [1021] | 336 | Parameters:
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| [1217] | 337 | colmap: a list of colour names
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| [710] | 338 | Example:
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| 339 | plotter.set_colors("red green blue")
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| 340 | # If for example four lines are overlaid e.g I Q U V
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| 341 | # 'I' will be 'red', 'Q' will be 'green', U will be 'blue'
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| 342 | # and 'V' will be 'red' again.
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| 343 | """
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| [1217] | 344 | if isinstance(colmap,str):
|
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| 345 | colmap = colmap.split()
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| 346 | self._plotter.palette(0, colormap=colmap)
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| [920] | 347 | if self._data: self.plot(self._data)
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| [710] | 348 |
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| [1217] | 349 | # alias for english speakers
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| 350 | set_colours = set_colors
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| 351 |
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| [1101] | 352 | def set_histogram(self, hist=True, linewidth=None):
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| [1021] | 353 | """
|
|---|
| 354 | Enable/Disable histogram-like plotting.
|
|---|
| 355 | Parameters:
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| 356 | hist: True (default) or False. The fisrt default
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| 357 | is taken from the .asaprc setting
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|---|
| 358 | plotter.histogram
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|---|
| 359 | """
|
|---|
| [1023] | 360 | self._hist = hist
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|---|
| [1101] | 361 | if isinstance(linewidth, float) or isinstance(linewidth, int):
|
|---|
| 362 | from matplotlib import rc as rcp
|
|---|
| 363 | rcp('lines', linewidth=linewidth)
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| [1021] | 364 | if self._data: self.plot(self._data)
|
|---|
| [1023] | 365 |
|
|---|
| [1101] | 366 | def set_linestyles(self, linestyles=None, linewidth=None):
|
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| [710] | 367 | """
|
|---|
| [734] | 368 | Set the linestyles to be used. The plotter will cycle through
|
|---|
| 369 | these linestyles when lines are overlaid (stacking mode) AND
|
|---|
| 370 | only one color has been set.
|
|---|
| [710] | 371 | Parameters:
|
|---|
| 372 | linestyles: a list of linestyles to use.
|
|---|
| 373 | 'line', 'dashed', 'dotted', 'dashdot',
|
|---|
| 374 | 'dashdotdot' and 'dashdashdot' are
|
|---|
| 375 | possible
|
|---|
| 376 |
|
|---|
| 377 | Example:
|
|---|
| 378 | plotter.set_colors("black")
|
|---|
| 379 | plotter.set_linestyles("line dashed dotted dashdot")
|
|---|
| 380 | # If for example four lines are overlaid e.g I Q U V
|
|---|
| 381 | # 'I' will be 'solid', 'Q' will be 'dashed',
|
|---|
| 382 | # U will be 'dotted' and 'V' will be 'dashdot'.
|
|---|
| 383 | """
|
|---|
| 384 | if isinstance(linestyles,str):
|
|---|
| 385 | linestyles = linestyles.split()
|
|---|
| 386 | self._plotter.palette(color=0,linestyle=0,linestyles=linestyles)
|
|---|
| [1101] | 387 | if isinstance(linewidth, float) or isinstance(linewidth, int):
|
|---|
| 388 | from matplotlib import rc as rcp
|
|---|
| 389 | rcp('lines', linewidth=linewidth)
|
|---|
| [920] | 390 | if self._data: self.plot(self._data)
|
|---|
| [710] | 391 |
|
|---|
| [1101] | 392 | def set_font(self, family=None, style=None, weight=None, size=None):
|
|---|
| 393 | """
|
|---|
| 394 | Set font properties.
|
|---|
| 395 | Parameters:
|
|---|
| 396 | family: one of 'sans-serif', 'serif', 'cursive', 'fantasy', 'monospace'
|
|---|
| 397 | style: one of 'normal' (or 'roman'), 'italic' or 'oblique'
|
|---|
| 398 | weight: one of 'normal or 'bold'
|
|---|
| 399 | size: the 'general' font size, individual elements can be adjusted
|
|---|
| 400 | seperately
|
|---|
| 401 | """
|
|---|
| 402 | from matplotlib import rc as rcp
|
|---|
| 403 | if isinstance(family, str):
|
|---|
| 404 | rcp('font', family=family)
|
|---|
| 405 | if isinstance(style, str):
|
|---|
| 406 | rcp('font', style=style)
|
|---|
| 407 | if isinstance(weight, str):
|
|---|
| 408 | rcp('font', weight=weight)
|
|---|
| 409 | if isinstance(size, float) or isinstance(size, int):
|
|---|
| 410 | rcp('font', size=size)
|
|---|
| 411 | if self._data: self.plot(self._data)
|
|---|
| 412 |
|
|---|
| [1259] | 413 | def plot_lines(self, linecat=None, doppler=0.0, deltachan=10, rotate=90.0,
|
|---|
| [1146] | 414 | location=None):
|
|---|
| 415 | """
|
|---|
| [1158] | 416 | Plot a line catalog.
|
|---|
| 417 | Parameters:
|
|---|
| 418 | linecat: the linecatalog to plot
|
|---|
| [1168] | 419 | doppler: the velocity shift to apply to the frequencies
|
|---|
| [1158] | 420 | deltachan: the number of channels to include each side of the
|
|---|
| 421 | line to determine a local maximum/minimum
|
|---|
| [1259] | 422 | rotate: the rotation (in degrees) )for the text label (default 90.0)
|
|---|
| [1158] | 423 | location: the location of the line annotation from the 'top',
|
|---|
| 424 | 'bottom' or alternate (None - the default)
|
|---|
| [1165] | 425 | Notes:
|
|---|
| 426 | If the spectrum is flagged no line will be drawn in that location.
|
|---|
| [1146] | 427 | """
|
|---|
| [1259] | 428 | if not self._data:
|
|---|
| 429 | raise RuntimeError("No scantable has been plotted yet.")
|
|---|
| [1146] | 430 | from asap._asap import linecatalog
|
|---|
| [1259] | 431 | if not isinstance(linecat, linecatalog):
|
|---|
| 432 | raise ValueError("'linecat' isn't of type linecatalog.")
|
|---|
| 433 | if not self._data.get_unit().endswith("Hz"):
|
|---|
| 434 | raise RuntimeError("Can only overlay linecatalogs when data is in frequency.")
|
|---|
| [1153] | 435 | from matplotlib.numerix import ma
|
|---|
| [1146] | 436 | for j in range(len(self._plotter.subplots)):
|
|---|
| 437 | self._plotter.subplot(j)
|
|---|
| 438 | lims = self._plotter.axes.get_xlim()
|
|---|
| [1153] | 439 | for row in range(linecat.nrow()):
|
|---|
| [1259] | 440 | # get_frequency returns MHz
|
|---|
| 441 | base = { "GHz": 1000.0, "MHz": 1.0, "Hz": 1.0e-6 }
|
|---|
| 442 | restf = linecat.get_frequency(row)/base[self._data.get_unit()]
|
|---|
| [1165] | 443 | c = 299792.458
|
|---|
| [1174] | 444 | freq = restf*(1.0-doppler/c)
|
|---|
| [1146] | 445 | if lims[0] < freq < lims[1]:
|
|---|
| 446 | if location is None:
|
|---|
| 447 | loc = 'bottom'
|
|---|
| [1153] | 448 | if row%2: loc='top'
|
|---|
| [1146] | 449 | else: loc = location
|
|---|
| [1153] | 450 | maxys = []
|
|---|
| 451 | for line in self._plotter.axes.lines:
|
|---|
| 452 | v = line._x
|
|---|
| 453 | asc = v[0] < v[-1]
|
|---|
| 454 |
|
|---|
| 455 | idx = None
|
|---|
| 456 | if not asc:
|
|---|
| 457 | if v[len(v)-1] <= freq <= v[0]:
|
|---|
| 458 | i = len(v)-1
|
|---|
| 459 | while i>=0 and v[i] < freq:
|
|---|
| 460 | idx = i
|
|---|
| 461 | i-=1
|
|---|
| 462 | else:
|
|---|
| 463 | if v[0] <= freq <= v[len(v)-1]:
|
|---|
| 464 | i = 0
|
|---|
| 465 | while i<len(v) and v[i] < freq:
|
|---|
| 466 | idx = i
|
|---|
| 467 | i+=1
|
|---|
| 468 | if idx is not None:
|
|---|
| 469 | lower = idx - deltachan
|
|---|
| 470 | upper = idx + deltachan
|
|---|
| 471 | if lower < 0: lower = 0
|
|---|
| 472 | if upper > len(v): upper = len(v)
|
|---|
| 473 | s = slice(lower, upper)
|
|---|
| [1167] | 474 | y = line._y[s]
|
|---|
| [1165] | 475 | maxy = ma.maximum(y)
|
|---|
| 476 | if isinstance( maxy, float):
|
|---|
| 477 | maxys.append(maxy)
|
|---|
| [1164] | 478 | if len(maxys):
|
|---|
| 479 | peak = max(maxys)
|
|---|
| [1165] | 480 | if peak > self._plotter.axes.get_ylim()[1]:
|
|---|
| 481 | loc = 'bottom'
|
|---|
| [1164] | 482 | else:
|
|---|
| 483 | continue
|
|---|
| [1157] | 484 | self._plotter.vline_with_label(freq, peak,
|
|---|
| 485 | linecat.get_name(row),
|
|---|
| 486 | location=loc, rotate=rotate)
|
|---|
| [1153] | 487 | self._plotter.show(hardrefresh=False)
|
|---|
| [1146] | 488 |
|
|---|
| [1153] | 489 |
|
|---|
| [710] | 490 | def save(self, filename=None, orientation=None, dpi=None):
|
|---|
| 491 | """
|
|---|
| [377] | 492 | Save the plot to a file. The know formats are 'png', 'ps', 'eps'.
|
|---|
| 493 | Parameters:
|
|---|
| 494 | filename: The name of the output file. This is optional
|
|---|
| 495 | and autodetects the image format from the file
|
|---|
| 496 | suffix. If non filename is specified a file
|
|---|
| 497 | called 'yyyymmdd_hhmmss.png' is created in the
|
|---|
| 498 | current directory.
|
|---|
| [709] | 499 | orientation: optional parameter for postscript only (not eps).
|
|---|
| 500 | 'landscape', 'portrait' or None (default) are valid.
|
|---|
| 501 | If None is choosen for 'ps' output, the plot is
|
|---|
| 502 | automatically oriented to fill the page.
|
|---|
| [710] | 503 | dpi: The dpi of the output non-ps plot
|
|---|
| [377] | 504 | """
|
|---|
| [709] | 505 | self._plotter.save(filename,orientation,dpi)
|
|---|
| [377] | 506 | return
|
|---|
| [709] | 507 |
|
|---|
| [257] | 508 |
|
|---|
| [920] | 509 | def set_mask(self, mask=None, selection=None):
|
|---|
| [525] | 510 | """
|
|---|
| [734] | 511 | Set a plotting mask for a specific polarization.
|
|---|
| 512 | This is useful for masking out "noise" Pangle outside a source.
|
|---|
| 513 | Parameters:
|
|---|
| [920] | 514 | mask: a mask from scantable.create_mask
|
|---|
| 515 | selection: the spectra to apply the mask to.
|
|---|
| [734] | 516 | Example:
|
|---|
| [920] | 517 | select = selector()
|
|---|
| 518 | select.setpolstrings("Pangle")
|
|---|
| 519 | plotter.set_mask(mymask, select)
|
|---|
| [734] | 520 | """
|
|---|
| [710] | 521 | if not self._data:
|
|---|
| [920] | 522 | msg = "Can only set mask after a first call to plot()"
|
|---|
| [753] | 523 | if rcParams['verbose']:
|
|---|
| 524 | print msg
|
|---|
| [762] | 525 | return
|
|---|
| [753] | 526 | else:
|
|---|
| [762] | 527 | raise RuntimeError(msg)
|
|---|
| [920] | 528 | if len(mask):
|
|---|
| 529 | if isinstance(mask, list) or isinstance(mask, tuple):
|
|---|
| 530 | self._usermask = array(mask)
|
|---|
| [710] | 531 | else:
|
|---|
| [920] | 532 | self._usermask = mask
|
|---|
| 533 | if mask is None and selection is None:
|
|---|
| 534 | self._usermask = []
|
|---|
| 535 | self._maskselection = None
|
|---|
| 536 | if isinstance(selection, selector):
|
|---|
| [947] | 537 | self._maskselection = {'b': selection.get_beams(),
|
|---|
| 538 | 's': selection.get_scans(),
|
|---|
| 539 | 'i': selection.get_ifs(),
|
|---|
| 540 | 'p': selection.get_pols(),
|
|---|
| [920] | 541 | 't': [] }
|
|---|
| [710] | 542 | else:
|
|---|
| [920] | 543 | self._maskselection = None
|
|---|
| 544 | self.plot(self._data)
|
|---|
| [710] | 545 |
|
|---|
| [709] | 546 | def _slice_indeces(self, data):
|
|---|
| 547 | mn = self._minmaxx[0]
|
|---|
| 548 | mx = self._minmaxx[1]
|
|---|
| 549 | asc = data[0] < data[-1]
|
|---|
| 550 | start=0
|
|---|
| 551 | end = len(data)-1
|
|---|
| 552 | inc = 1
|
|---|
| 553 | if not asc:
|
|---|
| 554 | start = len(data)-1
|
|---|
| 555 | end = 0
|
|---|
| 556 | inc = -1
|
|---|
| 557 | # find min index
|
|---|
| [1101] | 558 | while start > 0 and data[start] < mn:
|
|---|
| [709] | 559 | start+= inc
|
|---|
| 560 | # find max index
|
|---|
| [1101] | 561 | while end > 0 and data[end] > mx:
|
|---|
| [709] | 562 | end-=inc
|
|---|
| [1101] | 563 | if end > 0: end +=1
|
|---|
| [709] | 564 | if start > end:
|
|---|
| 565 | return end,start
|
|---|
| 566 | return start,end
|
|---|
| 567 |
|
|---|
| [710] | 568 | def _reset(self):
|
|---|
| [920] | 569 | self._usermask = []
|
|---|
| [710] | 570 | self._usermaskspectra = None
|
|---|
| [920] | 571 | self.set_selection(None, False)
|
|---|
| 572 |
|
|---|
| 573 | def _plot(self, scan):
|
|---|
| [947] | 574 | savesel = scan.get_selection()
|
|---|
| 575 | sel = savesel + self._selection
|
|---|
| 576 | d0 = {'s': 'SCANNO', 'b': 'BEAMNO', 'i':'IFNO',
|
|---|
| 577 | 'p': 'POLNO', 'c': 'CYCLENO', 't' : 'TIME' }
|
|---|
| 578 | order = [d0[self._panelling],d0[self._stacking]]
|
|---|
| 579 | sel.set_order(order)
|
|---|
| 580 | scan.set_selection(sel)
|
|---|
| [920] | 581 | d = {'b': scan.getbeam, 's': scan.getscan,
|
|---|
| 582 | 'i': scan.getif, 'p': scan.getpol, 't': scan._gettime }
|
|---|
| 583 |
|
|---|
| [1148] | 584 | polmodes = dict(zip(self._selection.get_pols(),
|
|---|
| 585 | self._selection.get_poltypes()))
|
|---|
| 586 | # this returns either a tuple of numbers or a length (ncycles)
|
|---|
| 587 | # convert this into lengths
|
|---|
| 588 | n0,nstack0 = self._get_selected_n(scan)
|
|---|
| 589 | if isinstance(n0, int): n = n0
|
|---|
| [1175] | 590 | else: n = len(n0)
|
|---|
| [1148] | 591 | if isinstance(nstack0, int): nstack = nstack0
|
|---|
| [1175] | 592 | else: nstack = len(nstack0)
|
|---|
| [998] | 593 | maxpanel, maxstack = 16,8
|
|---|
| [920] | 594 | if n > maxpanel or nstack > maxstack:
|
|---|
| 595 | from asap import asaplog
|
|---|
| [1148] | 596 | maxn = 0
|
|---|
| 597 | if nstack > maxstack: maxn = maxstack
|
|---|
| 598 | if n > maxpanel: maxn = maxpanel
|
|---|
| [920] | 599 | msg ="Scan to be plotted contains more than %d selections.\n" \
|
|---|
| [1148] | 600 | "Selecting first %d selections..." % (maxn, maxn)
|
|---|
| [920] | 601 | asaplog.push(msg)
|
|---|
| 602 | print_log()
|
|---|
| 603 | n = min(n,maxpanel)
|
|---|
| [998] | 604 | nstack = min(nstack,maxstack)
|
|---|
| [920] | 605 | if n > 1:
|
|---|
| 606 | ganged = rcParams['plotter.ganged']
|
|---|
| 607 | if self._rows and self._cols:
|
|---|
| 608 | n = min(n,self._rows*self._cols)
|
|---|
| 609 | self._plotter.set_panels(rows=self._rows,cols=self._cols,
|
|---|
| 610 | nplots=n,ganged=ganged)
|
|---|
| 611 | else:
|
|---|
| 612 | self._plotter.set_panels(rows=n,cols=0,nplots=n,ganged=ganged)
|
|---|
| 613 | else:
|
|---|
| 614 | self._plotter.set_panels()
|
|---|
| 615 | r=0
|
|---|
| 616 | nr = scan.nrow()
|
|---|
| 617 | a0,b0 = -1,-1
|
|---|
| 618 | allxlim = []
|
|---|
| [1018] | 619 | allylim = []
|
|---|
| [920] | 620 | newpanel=True
|
|---|
| 621 | panelcount,stackcount = 0,0
|
|---|
| [1002] | 622 | while r < nr:
|
|---|
| [920] | 623 | a = d[self._panelling](r)
|
|---|
| 624 | b = d[self._stacking](r)
|
|---|
| 625 | if a > a0 and panelcount < n:
|
|---|
| 626 | if n > 1:
|
|---|
| 627 | self._plotter.subplot(panelcount)
|
|---|
| 628 | self._plotter.palette(0)
|
|---|
| 629 | #title
|
|---|
| 630 | xlab = self._abcissa and self._abcissa[panelcount] \
|
|---|
| 631 | or scan._getabcissalabel()
|
|---|
| 632 | ylab = self._ordinate and self._ordinate[panelcount] \
|
|---|
| 633 | or scan._get_ordinate_label()
|
|---|
| 634 | self._plotter.set_axes('xlabel',xlab)
|
|---|
| 635 | self._plotter.set_axes('ylabel',ylab)
|
|---|
| 636 | lbl = self._get_label(scan, r, self._panelling, self._title)
|
|---|
| 637 | if isinstance(lbl, list) or isinstance(lbl, tuple):
|
|---|
| 638 | if 0 <= panelcount < len(lbl):
|
|---|
| 639 | lbl = lbl[panelcount]
|
|---|
| 640 | else:
|
|---|
| 641 | # get default label
|
|---|
| 642 | lbl = self._get_label(scan, r, self._panelling, None)
|
|---|
| 643 | self._plotter.set_axes('title',lbl)
|
|---|
| 644 | newpanel = True
|
|---|
| 645 | stackcount =0
|
|---|
| 646 | panelcount += 1
|
|---|
| 647 | if (b > b0 or newpanel) and stackcount < nstack:
|
|---|
| 648 | y = []
|
|---|
| 649 | if len(polmodes):
|
|---|
| 650 | y = scan._getspectrum(r, polmodes[scan.getpol(r)])
|
|---|
| 651 | else:
|
|---|
| 652 | y = scan._getspectrum(r)
|
|---|
| 653 | m = scan._getmask(r)
|
|---|
| [1146] | 654 | from matplotlib.numerix import logical_not, logical_and
|
|---|
| [920] | 655 | if self._maskselection and len(self._usermask) == len(m):
|
|---|
| 656 | if d[self._stacking](r) in self._maskselection[self._stacking]:
|
|---|
| 657 | m = logical_and(m, self._usermask)
|
|---|
| 658 | x = scan._getabcissa(r)
|
|---|
| [1146] | 659 | from matplotlib.numerix import ma, array
|
|---|
| [1116] | 660 | y = ma.masked_array(y,mask=logical_not(array(m,copy=False)))
|
|---|
| [920] | 661 | if self._minmaxx is not None:
|
|---|
| 662 | s,e = self._slice_indeces(x)
|
|---|
| 663 | x = x[s:e]
|
|---|
| 664 | y = y[s:e]
|
|---|
| [1096] | 665 | if len(x) > 1024 and rcParams['plotter.decimate']:
|
|---|
| 666 | fac = len(x)/1024
|
|---|
| [920] | 667 | x = x[::fac]
|
|---|
| 668 | y = y[::fac]
|
|---|
| 669 | llbl = self._get_label(scan, r, self._stacking, self._lmap)
|
|---|
| 670 | if isinstance(llbl, list) or isinstance(llbl, tuple):
|
|---|
| 671 | if 0 <= stackcount < len(llbl):
|
|---|
| 672 | # use user label
|
|---|
| 673 | llbl = llbl[stackcount]
|
|---|
| 674 | else:
|
|---|
| 675 | # get default label
|
|---|
| 676 | llbl = self._get_label(scan, r, self._stacking, None)
|
|---|
| 677 | self._plotter.set_line(label=llbl)
|
|---|
| [1023] | 678 | plotit = self._plotter.plot
|
|---|
| 679 | if self._hist: plotit = self._plotter.hist
|
|---|
| [1146] | 680 | if len(x) > 0:
|
|---|
| 681 | plotit(x,y)
|
|---|
| 682 | xlim= self._minmaxx or [min(x),max(x)]
|
|---|
| 683 | allxlim += xlim
|
|---|
| 684 | ylim= self._minmaxy or [ma.minimum(y),ma.maximum(y)]
|
|---|
| 685 | allylim += ylim
|
|---|
| [920] | 686 | stackcount += 1
|
|---|
| 687 | # last in colour stack -> autoscale x
|
|---|
| 688 | if stackcount == nstack:
|
|---|
| 689 | allxlim.sort()
|
|---|
| 690 | self._plotter.axes.set_xlim([allxlim[0],allxlim[-1]])
|
|---|
| 691 | # clear
|
|---|
| 692 | allxlim =[]
|
|---|
| 693 |
|
|---|
| 694 | newpanel = False
|
|---|
| 695 | a0=a
|
|---|
| 696 | b0=b
|
|---|
| 697 | # ignore following rows
|
|---|
| 698 | if (panelcount == n) and (stackcount == nstack):
|
|---|
| [1018] | 699 | # last panel -> autoscale y if ganged
|
|---|
| 700 | if rcParams['plotter.ganged']:
|
|---|
| 701 | allylim.sort()
|
|---|
| 702 | self._plotter.set_limits(ylim=[allylim[0],allylim[-1]])
|
|---|
| [998] | 703 | break
|
|---|
| [920] | 704 | r+=1 # next row
|
|---|
| [947] | 705 | #reset the selector to the scantable's original
|
|---|
| 706 | scan.set_selection(savesel)
|
|---|
| [920] | 707 |
|
|---|
| 708 | def set_selection(self, selection=None, refresh=True):
|
|---|
| [947] | 709 | self._selection = isinstance(selection,selector) and selection or selector()
|
|---|
| [920] | 710 | d0 = {'s': 'SCANNO', 'b': 'BEAMNO', 'i':'IFNO',
|
|---|
| 711 | 'p': 'POLNO', 'c': 'CYCLENO', 't' : 'TIME' }
|
|---|
| 712 | order = [d0[self._panelling],d0[self._stacking]]
|
|---|
| [947] | 713 | self._selection.set_order(order)
|
|---|
| [920] | 714 | if self._data and refresh: self.plot(self._data)
|
|---|
| 715 |
|
|---|
| 716 | def _get_selected_n(self, scan):
|
|---|
| [1148] | 717 | d1 = {'b': scan.getbeamnos, 's': scan.getscannos,
|
|---|
| 718 | 'i': scan.getifnos, 'p': scan.getpolnos, 't': scan.ncycle }
|
|---|
| 719 | d2 = { 'b': self._selection.get_beams(),
|
|---|
| 720 | 's': self._selection.get_scans(),
|
|---|
| 721 | 'i': self._selection.get_ifs(),
|
|---|
| 722 | 'p': self._selection.get_pols(),
|
|---|
| 723 | 't': self._selection.get_cycles() }
|
|---|
| [920] | 724 | n = d2[self._panelling] or d1[self._panelling]()
|
|---|
| 725 | nstack = d2[self._stacking] or d1[self._stacking]()
|
|---|
| 726 | return n,nstack
|
|---|
| 727 |
|
|---|
| 728 | def _get_label(self, scan, row, mode, userlabel=None):
|
|---|
| [1153] | 729 | if isinstance(userlabel, list) and len(userlabel) == 0:
|
|---|
| 730 | userlabel = " "
|
|---|
| [947] | 731 | pms = dict(zip(self._selection.get_pols(),self._selection.get_poltypes()))
|
|---|
| [920] | 732 | if len(pms):
|
|---|
| 733 | poleval = scan._getpollabel(scan.getpol(row),pms[scan.getpol(row)])
|
|---|
| 734 | else:
|
|---|
| 735 | poleval = scan._getpollabel(scan.getpol(row),scan.poltype())
|
|---|
| 736 | d = {'b': "Beam "+str(scan.getbeam(row)),
|
|---|
| 737 | 's': scan._getsourcename(row),
|
|---|
| 738 | 'i': "IF"+str(scan.getif(row)),
|
|---|
| [964] | 739 | 'p': poleval,
|
|---|
| [1175] | 740 | 't': str(scan.get_time(row)) }
|
|---|
| [920] | 741 | return userlabel or d[mode]
|
|---|
| [1153] | 742 |
|
|---|
