| [947] | 1 | from asap import rcParams, print_log, selector
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| [1146] | 2 | from asap import NUM
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| [1153] | 3 | import matplotlib.axes
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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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| 124 | def axhspan(self, *args, **kwargs):
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| 125 | self._axes_callback("ahvspan", *args, **kwargs)
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| 126 | # hack to preventy mpl from redrawing the patch
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| 127 | # it seem to convert the patch into lines on every draw.
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| 128 | # This doesn't happen in a test script???
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| 129 | del self._plotter.axes.patches[-1]
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| 130 | axhspan. __doc__ = matplotlib.axes.Axes.axhspan.__doc__
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| 131 |
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| 132 | def _axes_callback(self, axesfunc, *args, **kwargs):
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| 133 | panel = 0
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| 134 | if kwargs.has_key("panel"):
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| 135 | panel = kwargs.pop("panel")
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| 136 | coords = None
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| 137 | if kwargs.has_key("coords"):
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| 138 | coords = kwargs.pop("coords")
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| 139 | if coords.lower() == 'world':
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| 140 | kwargs["transform"] = self._plotter.axes.transData
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| 141 | elif coords.lower() == 'relative':
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| 142 | kwargs["transform"] = self._plotter.axes.transAxes
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| 143 | self._plotter.subplot(panel)
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| 144 | self._plotter.axes.set_autoscale_on(False)
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| 145 | getattr(self._plotter.axes, axesfunc)(*args, **kwargs)
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| 146 | self._plotter.show(False)
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| 147 | self._plotter.axes.set_autoscale_on(True)
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| 148 | # end matplotlib.axes fowarding functions
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| 149 |
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| [226] | 150 | def set_mode(self, stacking=None, panelling=None):
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| [203] | 151 | """
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| [377] | 152 | Set the plots look and feel, i.e. what you want to see on the plot.
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| [203] | 153 | Parameters:
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| 154 | stacking: tell the plotter which variable to plot
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| [710] | 155 | as line color overlays (default 'pol')
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| [203] | 156 | panelling: tell the plotter which variable to plot
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| 157 | across multiple panels (default 'scan'
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| 158 | Note:
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| 159 | Valid modes are:
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| 160 | 'beam' 'Beam' 'b': Beams
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| 161 | 'if' 'IF' 'i': IFs
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| 162 | 'pol' 'Pol' 'p': Polarisations
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| 163 | 'scan' 'Scan' 's': Scans
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| 164 | 'time' 'Time' 't': Times
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| 165 | """
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| [753] | 166 | msg = "Invalid mode"
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| 167 | if not self.set_panelling(panelling) or \
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| 168 | not self.set_stacking(stacking):
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| 169 | if rcParams['verbose']:
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| 170 | print msg
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| 171 | return
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| 172 | else:
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| 173 | raise TypeError(msg)
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| [920] | 174 | if self._data: self.plot(self._data)
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| [203] | 175 | return
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| 176 |
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| [554] | 177 | def set_panelling(self, what=None):
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| 178 | mode = what
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| 179 | if mode is None:
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| 180 | mode = rcParams['plotter.panelling']
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| 181 | md = self._translate(mode)
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| [203] | 182 | if md:
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| [554] | 183 | self._panelling = md
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| [226] | 184 | self._title = None
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| [203] | 185 | return True
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| 186 | return False
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| 187 |
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| [377] | 188 | def set_layout(self,rows=None,cols=None):
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| 189 | """
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| 190 | Set the multi-panel layout, i.e. how many rows and columns plots
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| 191 | are visible.
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| 192 | Parameters:
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| 193 | rows: The number of rows of plots
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| 194 | cols: The number of columns of plots
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| 195 | Note:
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| 196 | If no argument is given, the potter reverts to its auto-plot
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| 197 | behaviour.
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| 198 | """
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| 199 | self._rows = rows
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| 200 | self._cols = cols
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| [920] | 201 | if self._data: self.plot(self._data)
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| [377] | 202 | return
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| 203 |
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| [709] | 204 | def set_stacking(self, what=None):
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| [554] | 205 | mode = what
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| [709] | 206 | if mode is None:
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| 207 | mode = rcParams['plotter.stacking']
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| [554] | 208 | md = self._translate(mode)
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| [203] | 209 | if md:
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| 210 | self._stacking = md
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| [226] | 211 | self._lmap = None
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| [203] | 212 | return True
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| 213 | return False
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| 214 |
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| [525] | 215 | def set_range(self,xstart=None,xend=None,ystart=None,yend=None):
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| [203] | 216 | """
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| 217 | Set the range of interest on the abcissa of the plot
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| 218 | Parameters:
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| [525] | 219 | [x,y]start,[x,y]end: The start and end points of the 'zoom' window
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| [203] | 220 | Note:
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| 221 | These become non-sensical when the unit changes.
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| 222 | use plotter.set_range() without parameters to reset
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| 223 |
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| 224 | """
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| [525] | 225 | if xstart is None and xend is None:
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| 226 | self._minmaxx = None
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| [600] | 227 | else:
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| 228 | self._minmaxx = [xstart,xend]
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| [525] | 229 | if ystart is None and yend is None:
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| 230 | self._minmaxy = None
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| [600] | 231 | else:
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| [709] | 232 | self._minmaxy = [ystart,yend]
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| [920] | 233 | if self._data: self.plot(self._data)
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| [203] | 234 | return
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| [709] | 235 |
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| [1101] | 236 | def set_legend(self, mp=None, fontsize = None, mode = 0):
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| [203] | 237 | """
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| 238 | Specify a mapping for the legend instead of using the default
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| 239 | indices:
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| 240 | Parameters:
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| [1101] | 241 | mp: a list of 'strings'. This should have the same length
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| 242 | as the number of elements on the legend and then maps
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| 243 | to the indeces in order. It is possible to uses latex
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| 244 | math expression. These have to be enclosed in r'',
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| 245 | e.g. r'$x^{2}$'
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| 246 | fontsize: The font size of the label (default None)
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| 247 | mode: where to display the legend
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| 248 | Any other value for loc else disables the legend:
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| [1096] | 249 | 0: auto
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| 250 | 1: upper right
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| 251 | 2: upper left
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| 252 | 3: lower left
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| 253 | 4: lower right
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| 254 | 5: right
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| 255 | 6: center left
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| 256 | 7: center right
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| 257 | 8: lower center
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| 258 | 9: upper center
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| 259 | 10: center
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| [203] | 260 |
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| 261 | Example:
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| [485] | 262 | If the data has two IFs/rest frequencies with index 0 and 1
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| [203] | 263 | for CO and SiO:
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| 264 | plotter.set_stacking('i')
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| [710] | 265 | plotter.set_legend(['CO','SiO'])
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| [203] | 266 | plotter.plot()
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| [710] | 267 | plotter.set_legend([r'$^{12}CO$', r'SiO'])
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| [203] | 268 | """
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| 269 | self._lmap = mp
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| [1096] | 270 | self._plotter.legend(mode)
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| [1101] | 271 | if isinstance(fontsize, int):
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| 272 | from matplotlib import rc as rcp
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| 273 | rcp('legend', fontsize=fontsize)
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| [1096] | 274 | if self._data:
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| 275 | self.plot(self._data)
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| [226] | 276 | return
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| 277 |
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| [1101] | 278 | def set_title(self, title=None, fontsize=None):
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| [710] | 279 | """
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| 280 | Set the title of the plot. If multiple panels are plotted,
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| 281 | multiple titles have to be specified.
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| 282 | Example:
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| 283 | # two panels are visible on the plotter
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| 284 | plotter.set_title(["First Panel","Second Panel"])
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| 285 | """
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| [226] | 286 | self._title = title
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| [1101] | 287 | if isinstance(fontsize, int):
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| 288 | from matplotlib import rc as rcp
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| 289 | rcp('axes', titlesize=fontsize)
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| [920] | 290 | if self._data: self.plot(self._data)
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| [226] | 291 | return
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| 292 |
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| [1101] | 293 | def set_ordinate(self, ordinate=None, fontsize=None):
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| [710] | 294 | """
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| 295 | Set the y-axis label of the plot. If multiple panels are plotted,
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| 296 | multiple labels have to be specified.
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| [1021] | 297 | Parameters:
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| 298 | ordinate: a list of ordinate labels. None (default) let
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| 299 | data determine the labels
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| [710] | 300 | Example:
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| 301 | # two panels are visible on the plotter
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| 302 | plotter.set_ordinate(["First Y-Axis","Second Y-Axis"])
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| 303 | """
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| [257] | 304 | self._ordinate = ordinate
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| [1101] | 305 | if isinstance(fontsize, int):
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| 306 | from matplotlib import rc as rcp
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| 307 | rcp('axes', labelsize=fontsize)
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| 308 | rcp('ytick', labelsize=fontsize)
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| [920] | 309 | if self._data: self.plot(self._data)
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| [257] | 310 | return
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| 311 |
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| [1101] | 312 | def set_abcissa(self, abcissa=None, fontsize=None):
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| [710] | 313 | """
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| 314 | Set the x-axis label of the plot. If multiple panels are plotted,
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| 315 | multiple labels have to be specified.
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| [1021] | 316 | Parameters:
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| 317 | abcissa: a list of abcissa labels. None (default) let
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| 318 | data determine the labels
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| [710] | 319 | Example:
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| 320 | # two panels are visible on the plotter
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| 321 | plotter.set_ordinate(["First X-Axis","Second X-Axis"])
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| 322 | """
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| [257] | 323 | self._abcissa = abcissa
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| [1101] | 324 | if isinstance(fontsize, int):
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| 325 | from matplotlib import rc as rcp
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| 326 | rcp('axes', labelsize=fontsize)
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| 327 | rcp('xtick', labelsize=fontsize)
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| [920] | 328 | if self._data: self.plot(self._data)
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| [257] | 329 | return
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| 330 |
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| [710] | 331 | def set_colors(self, colormap):
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| [377] | 332 | """
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| [710] | 333 | Set the colors to be used. The plotter will cycle through
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| 334 | these colors when lines are overlaid (stacking mode).
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| [1021] | 335 | Parameters:
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| 336 | colormap: a list of colour names
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| [710] | 337 | Example:
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| 338 | plotter.set_colors("red green blue")
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| 339 | # If for example four lines are overlaid e.g I Q U V
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| 340 | # 'I' will be 'red', 'Q' will be 'green', U will be 'blue'
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| 341 | # and 'V' will be 'red' again.
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| 342 | """
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|---|
| 343 | if isinstance(colormap,str):
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| 344 | colormap = colormap.split()
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| 345 | self._plotter.palette(0,colormap=colormap)
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| [920] | 346 | if self._data: self.plot(self._data)
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| [710] | 347 |
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| [1101] | 348 | def set_histogram(self, hist=True, linewidth=None):
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| [1021] | 349 | """
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|---|
| 350 | Enable/Disable histogram-like plotting.
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| 351 | Parameters:
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| 352 | hist: True (default) or False. The fisrt default
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| 353 | is taken from the .asaprc setting
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| 354 | plotter.histogram
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| 355 | """
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| [1023] | 356 | self._hist = hist
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|---|
| [1101] | 357 | if isinstance(linewidth, float) or isinstance(linewidth, int):
|
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| 358 | from matplotlib import rc as rcp
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|---|
| 359 | rcp('lines', linewidth=linewidth)
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| [1021] | 360 | if self._data: self.plot(self._data)
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| [1023] | 361 |
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| [1101] | 362 | def set_linestyles(self, linestyles=None, linewidth=None):
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| [710] | 363 | """
|
|---|
| [734] | 364 | Set the linestyles to be used. The plotter will cycle through
|
|---|
| 365 | these linestyles when lines are overlaid (stacking mode) AND
|
|---|
| 366 | only one color has been set.
|
|---|
| [710] | 367 | Parameters:
|
|---|
| 368 | linestyles: a list of linestyles to use.
|
|---|
| 369 | 'line', 'dashed', 'dotted', 'dashdot',
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|---|
| 370 | 'dashdotdot' and 'dashdashdot' are
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|---|
| 371 | possible
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|---|
| 372 |
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|---|
| 373 | Example:
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|---|
| 374 | plotter.set_colors("black")
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|---|
| 375 | plotter.set_linestyles("line dashed dotted dashdot")
|
|---|
| 376 | # If for example four lines are overlaid e.g I Q U V
|
|---|
| 377 | # 'I' will be 'solid', 'Q' will be 'dashed',
|
|---|
| 378 | # U will be 'dotted' and 'V' will be 'dashdot'.
|
|---|
| 379 | """
|
|---|
| 380 | if isinstance(linestyles,str):
|
|---|
| 381 | linestyles = linestyles.split()
|
|---|
| 382 | self._plotter.palette(color=0,linestyle=0,linestyles=linestyles)
|
|---|
| [1101] | 383 | if isinstance(linewidth, float) or isinstance(linewidth, int):
|
|---|
| 384 | from matplotlib import rc as rcp
|
|---|
| 385 | rcp('lines', linewidth=linewidth)
|
|---|
| [920] | 386 | if self._data: self.plot(self._data)
|
|---|
| [710] | 387 |
|
|---|
| [1101] | 388 | def set_font(self, family=None, style=None, weight=None, size=None):
|
|---|
| 389 | """
|
|---|
| 390 | Set font properties.
|
|---|
| 391 | Parameters:
|
|---|
| 392 | family: one of 'sans-serif', 'serif', 'cursive', 'fantasy', 'monospace'
|
|---|
| 393 | style: one of 'normal' (or 'roman'), 'italic' or 'oblique'
|
|---|
| 394 | weight: one of 'normal or 'bold'
|
|---|
| 395 | size: the 'general' font size, individual elements can be adjusted
|
|---|
| 396 | seperately
|
|---|
| 397 | """
|
|---|
| 398 | from matplotlib import rc as rcp
|
|---|
| 399 | if isinstance(family, str):
|
|---|
| 400 | rcp('font', family=family)
|
|---|
| 401 | if isinstance(style, str):
|
|---|
| 402 | rcp('font', style=style)
|
|---|
| 403 | if isinstance(weight, str):
|
|---|
| 404 | rcp('font', weight=weight)
|
|---|
| 405 | if isinstance(size, float) or isinstance(size, int):
|
|---|
| 406 | rcp('font', size=size)
|
|---|
| 407 | if self._data: self.plot(self._data)
|
|---|
| 408 |
|
|---|
| [1169] | 409 | def plot_lines(self, linecat=None, doppler=0.0, deltachan=10, rotate=0.0,
|
|---|
| [1146] | 410 | location=None):
|
|---|
| 411 | """
|
|---|
| [1158] | 412 | Plot a line catalog.
|
|---|
| 413 | Parameters:
|
|---|
| 414 | linecat: the linecatalog to plot
|
|---|
| [1168] | 415 | doppler: the velocity shift to apply to the frequencies
|
|---|
| [1158] | 416 | deltachan: the number of channels to include each side of the
|
|---|
| 417 | line to determine a local maximum/minimum
|
|---|
| 418 | rotate: the rotation for the text label
|
|---|
| 419 | location: the location of the line annotation from the 'top',
|
|---|
| 420 | 'bottom' or alternate (None - the default)
|
|---|
| [1165] | 421 | Notes:
|
|---|
| 422 | If the spectrum is flagged no line will be drawn in that location.
|
|---|
| [1146] | 423 | """
|
|---|
| 424 | if not self._data: return
|
|---|
| 425 | from asap._asap import linecatalog
|
|---|
| 426 | if not isinstance(linecat, linecatalog): return
|
|---|
| 427 | if not self._data.get_unit().endswith("GHz"): return
|
|---|
| [1153] | 428 | #self._plotter.hold()
|
|---|
| 429 | from matplotlib.numerix import ma
|
|---|
| [1146] | 430 | for j in range(len(self._plotter.subplots)):
|
|---|
| 431 | self._plotter.subplot(j)
|
|---|
| 432 | lims = self._plotter.axes.get_xlim()
|
|---|
| [1153] | 433 | for row in range(linecat.nrow()):
|
|---|
| [1165] | 434 | restf = linecat.get_frequency(row)/1000.0
|
|---|
| 435 | c = 299792.458
|
|---|
| [1174] | 436 | freq = restf*(1.0-doppler/c)
|
|---|
| [1146] | 437 | if lims[0] < freq < lims[1]:
|
|---|
| 438 | if location is None:
|
|---|
| 439 | loc = 'bottom'
|
|---|
| [1153] | 440 | if row%2: loc='top'
|
|---|
| [1146] | 441 | else: loc = location
|
|---|
| [1153] | 442 | maxys = []
|
|---|
| 443 | for line in self._plotter.axes.lines:
|
|---|
| 444 | v = line._x
|
|---|
| 445 | asc = v[0] < v[-1]
|
|---|
| 446 |
|
|---|
| 447 | idx = None
|
|---|
| 448 | if not asc:
|
|---|
| 449 | if v[len(v)-1] <= freq <= v[0]:
|
|---|
| 450 | i = len(v)-1
|
|---|
| 451 | while i>=0 and v[i] < freq:
|
|---|
| 452 | idx = i
|
|---|
| 453 | i-=1
|
|---|
| 454 | else:
|
|---|
| 455 | if v[0] <= freq <= v[len(v)-1]:
|
|---|
| 456 | i = 0
|
|---|
| 457 | while i<len(v) and v[i] < freq:
|
|---|
| 458 | idx = i
|
|---|
| 459 | i+=1
|
|---|
| 460 | if idx is not None:
|
|---|
| 461 | lower = idx - deltachan
|
|---|
| 462 | upper = idx + deltachan
|
|---|
| 463 | if lower < 0: lower = 0
|
|---|
| 464 | if upper > len(v): upper = len(v)
|
|---|
| 465 | s = slice(lower, upper)
|
|---|
| [1167] | 466 | y = line._y[s]
|
|---|
| [1165] | 467 | maxy = ma.maximum(y)
|
|---|
| 468 | if isinstance( maxy, float):
|
|---|
| 469 | maxys.append(maxy)
|
|---|
| [1164] | 470 | if len(maxys):
|
|---|
| 471 | peak = max(maxys)
|
|---|
| [1165] | 472 | if peak > self._plotter.axes.get_ylim()[1]:
|
|---|
| 473 | loc = 'bottom'
|
|---|
| [1164] | 474 | else:
|
|---|
| 475 | continue
|
|---|
| [1157] | 476 | self._plotter.vline_with_label(freq, peak,
|
|---|
| 477 | linecat.get_name(row),
|
|---|
| 478 | location=loc, rotate=rotate)
|
|---|
| [1153] | 479 | # self._plotter.release()
|
|---|
| 480 | self._plotter.show(hardrefresh=False)
|
|---|
| [1146] | 481 |
|
|---|
| [1153] | 482 |
|
|---|
| [710] | 483 | def save(self, filename=None, orientation=None, dpi=None):
|
|---|
| 484 | """
|
|---|
| [377] | 485 | Save the plot to a file. The know formats are 'png', 'ps', 'eps'.
|
|---|
| 486 | Parameters:
|
|---|
| 487 | filename: The name of the output file. This is optional
|
|---|
| 488 | and autodetects the image format from the file
|
|---|
| 489 | suffix. If non filename is specified a file
|
|---|
| 490 | called 'yyyymmdd_hhmmss.png' is created in the
|
|---|
| 491 | current directory.
|
|---|
| [709] | 492 | orientation: optional parameter for postscript only (not eps).
|
|---|
| 493 | 'landscape', 'portrait' or None (default) are valid.
|
|---|
| 494 | If None is choosen for 'ps' output, the plot is
|
|---|
| 495 | automatically oriented to fill the page.
|
|---|
| [710] | 496 | dpi: The dpi of the output non-ps plot
|
|---|
| [377] | 497 | """
|
|---|
| [709] | 498 | self._plotter.save(filename,orientation,dpi)
|
|---|
| [377] | 499 | return
|
|---|
| [709] | 500 |
|
|---|
| [257] | 501 |
|
|---|
| [920] | 502 | def set_mask(self, mask=None, selection=None):
|
|---|
| [525] | 503 | """
|
|---|
| [734] | 504 | Set a plotting mask for a specific polarization.
|
|---|
| 505 | This is useful for masking out "noise" Pangle outside a source.
|
|---|
| 506 | Parameters:
|
|---|
| [920] | 507 | mask: a mask from scantable.create_mask
|
|---|
| 508 | selection: the spectra to apply the mask to.
|
|---|
| [734] | 509 | Example:
|
|---|
| [920] | 510 | select = selector()
|
|---|
| 511 | select.setpolstrings("Pangle")
|
|---|
| 512 | plotter.set_mask(mymask, select)
|
|---|
| [734] | 513 | """
|
|---|
| [710] | 514 | if not self._data:
|
|---|
| [920] | 515 | msg = "Can only set mask after a first call to plot()"
|
|---|
| [753] | 516 | if rcParams['verbose']:
|
|---|
| 517 | print msg
|
|---|
| [762] | 518 | return
|
|---|
| [753] | 519 | else:
|
|---|
| [762] | 520 | raise RuntimeError(msg)
|
|---|
| [920] | 521 | if len(mask):
|
|---|
| 522 | if isinstance(mask, list) or isinstance(mask, tuple):
|
|---|
| 523 | self._usermask = array(mask)
|
|---|
| [710] | 524 | else:
|
|---|
| [920] | 525 | self._usermask = mask
|
|---|
| 526 | if mask is None and selection is None:
|
|---|
| 527 | self._usermask = []
|
|---|
| 528 | self._maskselection = None
|
|---|
| 529 | if isinstance(selection, selector):
|
|---|
| [947] | 530 | self._maskselection = {'b': selection.get_beams(),
|
|---|
| 531 | 's': selection.get_scans(),
|
|---|
| 532 | 'i': selection.get_ifs(),
|
|---|
| 533 | 'p': selection.get_pols(),
|
|---|
| [920] | 534 | 't': [] }
|
|---|
| [710] | 535 | else:
|
|---|
| [920] | 536 | self._maskselection = None
|
|---|
| 537 | self.plot(self._data)
|
|---|
| [710] | 538 |
|
|---|
| [709] | 539 | def _slice_indeces(self, data):
|
|---|
| 540 | mn = self._minmaxx[0]
|
|---|
| 541 | mx = self._minmaxx[1]
|
|---|
| 542 | asc = data[0] < data[-1]
|
|---|
| 543 | start=0
|
|---|
| 544 | end = len(data)-1
|
|---|
| 545 | inc = 1
|
|---|
| 546 | if not asc:
|
|---|
| 547 | start = len(data)-1
|
|---|
| 548 | end = 0
|
|---|
| 549 | inc = -1
|
|---|
| 550 | # find min index
|
|---|
| [1101] | 551 | while start > 0 and data[start] < mn:
|
|---|
| [709] | 552 | start+= inc
|
|---|
| 553 | # find max index
|
|---|
| [1101] | 554 | while end > 0 and data[end] > mx:
|
|---|
| [709] | 555 | end-=inc
|
|---|
| [1101] | 556 | if end > 0: end +=1
|
|---|
| [709] | 557 | if start > end:
|
|---|
| 558 | return end,start
|
|---|
| 559 | return start,end
|
|---|
| 560 |
|
|---|
| [710] | 561 | def _reset(self):
|
|---|
| [920] | 562 | self._usermask = []
|
|---|
| [710] | 563 | self._usermaskspectra = None
|
|---|
| [920] | 564 | self.set_selection(None, False)
|
|---|
| 565 |
|
|---|
| 566 | def _plot(self, scan):
|
|---|
| [947] | 567 | savesel = scan.get_selection()
|
|---|
| 568 | sel = savesel + self._selection
|
|---|
| 569 | d0 = {'s': 'SCANNO', 'b': 'BEAMNO', 'i':'IFNO',
|
|---|
| 570 | 'p': 'POLNO', 'c': 'CYCLENO', 't' : 'TIME' }
|
|---|
| 571 | order = [d0[self._panelling],d0[self._stacking]]
|
|---|
| 572 | sel.set_order(order)
|
|---|
| 573 | scan.set_selection(sel)
|
|---|
| [920] | 574 | d = {'b': scan.getbeam, 's': scan.getscan,
|
|---|
| 575 | 'i': scan.getif, 'p': scan.getpol, 't': scan._gettime }
|
|---|
| 576 |
|
|---|
| [1148] | 577 | polmodes = dict(zip(self._selection.get_pols(),
|
|---|
| 578 | self._selection.get_poltypes()))
|
|---|
| 579 | # this returns either a tuple of numbers or a length (ncycles)
|
|---|
| 580 | # convert this into lengths
|
|---|
| 581 | n0,nstack0 = self._get_selected_n(scan)
|
|---|
| 582 | if isinstance(n0, int): n = n0
|
|---|
| [1175] | 583 | else: n = len(n0)
|
|---|
| [1148] | 584 | if isinstance(nstack0, int): nstack = nstack0
|
|---|
| [1175] | 585 | else: nstack = len(nstack0)
|
|---|
| [998] | 586 | maxpanel, maxstack = 16,8
|
|---|
| [920] | 587 | if n > maxpanel or nstack > maxstack:
|
|---|
| 588 | from asap import asaplog
|
|---|
| [1148] | 589 | maxn = 0
|
|---|
| 590 | if nstack > maxstack: maxn = maxstack
|
|---|
| 591 | if n > maxpanel: maxn = maxpanel
|
|---|
| [920] | 592 | msg ="Scan to be plotted contains more than %d selections.\n" \
|
|---|
| [1148] | 593 | "Selecting first %d selections..." % (maxn, maxn)
|
|---|
| [920] | 594 | asaplog.push(msg)
|
|---|
| 595 | print_log()
|
|---|
| 596 | n = min(n,maxpanel)
|
|---|
| [998] | 597 | nstack = min(nstack,maxstack)
|
|---|
| [920] | 598 | if n > 1:
|
|---|
| 599 | ganged = rcParams['plotter.ganged']
|
|---|
| 600 | if self._rows and self._cols:
|
|---|
| 601 | n = min(n,self._rows*self._cols)
|
|---|
| 602 | self._plotter.set_panels(rows=self._rows,cols=self._cols,
|
|---|
| 603 | nplots=n,ganged=ganged)
|
|---|
| 604 | else:
|
|---|
| 605 | self._plotter.set_panels(rows=n,cols=0,nplots=n,ganged=ganged)
|
|---|
| 606 | else:
|
|---|
| 607 | self._plotter.set_panels()
|
|---|
| 608 | r=0
|
|---|
| 609 | nr = scan.nrow()
|
|---|
| 610 | a0,b0 = -1,-1
|
|---|
| 611 | allxlim = []
|
|---|
| [1018] | 612 | allylim = []
|
|---|
| [920] | 613 | newpanel=True
|
|---|
| 614 | panelcount,stackcount = 0,0
|
|---|
| [1002] | 615 | while r < nr:
|
|---|
| [920] | 616 | a = d[self._panelling](r)
|
|---|
| 617 | b = d[self._stacking](r)
|
|---|
| 618 | if a > a0 and panelcount < n:
|
|---|
| 619 | if n > 1:
|
|---|
| 620 | self._plotter.subplot(panelcount)
|
|---|
| 621 | self._plotter.palette(0)
|
|---|
| 622 | #title
|
|---|
| 623 | xlab = self._abcissa and self._abcissa[panelcount] \
|
|---|
| 624 | or scan._getabcissalabel()
|
|---|
| 625 | ylab = self._ordinate and self._ordinate[panelcount] \
|
|---|
| 626 | or scan._get_ordinate_label()
|
|---|
| 627 | self._plotter.set_axes('xlabel',xlab)
|
|---|
| 628 | self._plotter.set_axes('ylabel',ylab)
|
|---|
| 629 | lbl = self._get_label(scan, r, self._panelling, self._title)
|
|---|
| 630 | if isinstance(lbl, list) or isinstance(lbl, tuple):
|
|---|
| 631 | if 0 <= panelcount < len(lbl):
|
|---|
| 632 | lbl = lbl[panelcount]
|
|---|
| 633 | else:
|
|---|
| 634 | # get default label
|
|---|
| 635 | lbl = self._get_label(scan, r, self._panelling, None)
|
|---|
| 636 | self._plotter.set_axes('title',lbl)
|
|---|
| 637 | newpanel = True
|
|---|
| 638 | stackcount =0
|
|---|
| 639 | panelcount += 1
|
|---|
| 640 | if (b > b0 or newpanel) and stackcount < nstack:
|
|---|
| 641 | y = []
|
|---|
| 642 | if len(polmodes):
|
|---|
| 643 | y = scan._getspectrum(r, polmodes[scan.getpol(r)])
|
|---|
| 644 | else:
|
|---|
| 645 | y = scan._getspectrum(r)
|
|---|
| 646 | m = scan._getmask(r)
|
|---|
| [1146] | 647 | from matplotlib.numerix import logical_not, logical_and
|
|---|
| [920] | 648 | if self._maskselection and len(self._usermask) == len(m):
|
|---|
| 649 | if d[self._stacking](r) in self._maskselection[self._stacking]:
|
|---|
| 650 | m = logical_and(m, self._usermask)
|
|---|
| 651 | x = scan._getabcissa(r)
|
|---|
| [1146] | 652 | from matplotlib.numerix import ma, array
|
|---|
| [1116] | 653 | y = ma.masked_array(y,mask=logical_not(array(m,copy=False)))
|
|---|
| [920] | 654 | if self._minmaxx is not None:
|
|---|
| 655 | s,e = self._slice_indeces(x)
|
|---|
| 656 | x = x[s:e]
|
|---|
| 657 | y = y[s:e]
|
|---|
| [1096] | 658 | if len(x) > 1024 and rcParams['plotter.decimate']:
|
|---|
| 659 | fac = len(x)/1024
|
|---|
| [920] | 660 | x = x[::fac]
|
|---|
| 661 | y = y[::fac]
|
|---|
| 662 | llbl = self._get_label(scan, r, self._stacking, self._lmap)
|
|---|
| 663 | if isinstance(llbl, list) or isinstance(llbl, tuple):
|
|---|
| 664 | if 0 <= stackcount < len(llbl):
|
|---|
| 665 | # use user label
|
|---|
| 666 | llbl = llbl[stackcount]
|
|---|
| 667 | else:
|
|---|
| 668 | # get default label
|
|---|
| 669 | llbl = self._get_label(scan, r, self._stacking, None)
|
|---|
| 670 | self._plotter.set_line(label=llbl)
|
|---|
| [1023] | 671 | plotit = self._plotter.plot
|
|---|
| 672 | if self._hist: plotit = self._plotter.hist
|
|---|
| [1146] | 673 | if len(x) > 0:
|
|---|
| 674 | plotit(x,y)
|
|---|
| 675 | xlim= self._minmaxx or [min(x),max(x)]
|
|---|
| 676 | allxlim += xlim
|
|---|
| 677 | ylim= self._minmaxy or [ma.minimum(y),ma.maximum(y)]
|
|---|
| 678 | allylim += ylim
|
|---|
| [920] | 679 | stackcount += 1
|
|---|
| 680 | # last in colour stack -> autoscale x
|
|---|
| 681 | if stackcount == nstack:
|
|---|
| 682 | allxlim.sort()
|
|---|
| 683 | self._plotter.axes.set_xlim([allxlim[0],allxlim[-1]])
|
|---|
| 684 | # clear
|
|---|
| 685 | allxlim =[]
|
|---|
| 686 |
|
|---|
| 687 | newpanel = False
|
|---|
| 688 | a0=a
|
|---|
| 689 | b0=b
|
|---|
| 690 | # ignore following rows
|
|---|
| 691 | if (panelcount == n) and (stackcount == nstack):
|
|---|
| [1018] | 692 | # last panel -> autoscale y if ganged
|
|---|
| 693 | if rcParams['plotter.ganged']:
|
|---|
| 694 | allylim.sort()
|
|---|
| 695 | self._plotter.set_limits(ylim=[allylim[0],allylim[-1]])
|
|---|
| [998] | 696 | break
|
|---|
| [920] | 697 | r+=1 # next row
|
|---|
| [947] | 698 | #reset the selector to the scantable's original
|
|---|
| 699 | scan.set_selection(savesel)
|
|---|
| [920] | 700 |
|
|---|
| 701 | def set_selection(self, selection=None, refresh=True):
|
|---|
| [947] | 702 | self._selection = isinstance(selection,selector) and selection or selector()
|
|---|
| [920] | 703 | d0 = {'s': 'SCANNO', 'b': 'BEAMNO', 'i':'IFNO',
|
|---|
| 704 | 'p': 'POLNO', 'c': 'CYCLENO', 't' : 'TIME' }
|
|---|
| 705 | order = [d0[self._panelling],d0[self._stacking]]
|
|---|
| [947] | 706 | self._selection.set_order(order)
|
|---|
| [920] | 707 | if self._data and refresh: self.plot(self._data)
|
|---|
| 708 |
|
|---|
| 709 | def _get_selected_n(self, scan):
|
|---|
| [1148] | 710 | d1 = {'b': scan.getbeamnos, 's': scan.getscannos,
|
|---|
| 711 | 'i': scan.getifnos, 'p': scan.getpolnos, 't': scan.ncycle }
|
|---|
| 712 | d2 = { 'b': self._selection.get_beams(),
|
|---|
| 713 | 's': self._selection.get_scans(),
|
|---|
| 714 | 'i': self._selection.get_ifs(),
|
|---|
| 715 | 'p': self._selection.get_pols(),
|
|---|
| 716 | 't': self._selection.get_cycles() }
|
|---|
| [920] | 717 | n = d2[self._panelling] or d1[self._panelling]()
|
|---|
| 718 | nstack = d2[self._stacking] or d1[self._stacking]()
|
|---|
| 719 | return n,nstack
|
|---|
| 720 |
|
|---|
| 721 | def _get_label(self, scan, row, mode, userlabel=None):
|
|---|
| [1153] | 722 | if isinstance(userlabel, list) and len(userlabel) == 0:
|
|---|
| 723 | userlabel = " "
|
|---|
| [947] | 724 | pms = dict(zip(self._selection.get_pols(),self._selection.get_poltypes()))
|
|---|
| [920] | 725 | if len(pms):
|
|---|
| 726 | poleval = scan._getpollabel(scan.getpol(row),pms[scan.getpol(row)])
|
|---|
| 727 | else:
|
|---|
| 728 | poleval = scan._getpollabel(scan.getpol(row),scan.poltype())
|
|---|
| 729 | d = {'b': "Beam "+str(scan.getbeam(row)),
|
|---|
| 730 | 's': scan._getsourcename(row),
|
|---|
| 731 | 'i': "IF"+str(scan.getif(row)),
|
|---|
| [964] | 732 | 'p': poleval,
|
|---|
| [1175] | 733 | 't': str(scan.get_time(row)) }
|
|---|
| [920] | 734 | return userlabel or d[mode]
|
|---|
| [1153] | 735 |
|
|---|
