| [1547] | 1 | from asap import rcParams, print_log, selector, scantable
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| [1153] | 2 | import matplotlib.axes
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| [1556] | 3 | from matplotlib.font_manager import FontProperties
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| 4 | from matplotlib.text import Text
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| 5 |
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| [1317] | 6 | import re
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| [203] | 7 |
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| 8 | class asapplotter:
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| [226] | 9 | """
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| 10 | The ASAP plotter.
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| 11 | By default the plotter is set up to plot polarisations
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| 12 | 'colour stacked' and scantables across panels.
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| 13 | Note:
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| 14 | Currenly it only plots 'spectra' not Tsys or
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| 15 | other variables.
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| 16 | """
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| [1563] | 17 | def __init__(self, visible=None , **kwargs):
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| [734] | 18 | self._visible = rcParams['plotter.gui']
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| 19 | if visible is not None:
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| 20 | self._visible = visible
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| [1563] | 21 | self._plotter = self._newplotter(**kwargs)
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| [710] | 22 |
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| [554] | 23 | self._panelling = None
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| 24 | self._stacking = None
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| 25 | self.set_panelling()
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| 26 | self.set_stacking()
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| [377] | 27 | self._rows = None
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| 28 | self._cols = None
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| [203] | 29 | self._autoplot = False
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| [525] | 30 | self._minmaxx = None
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| 31 | self._minmaxy = None
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| [710] | 32 | self._datamask = None
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| [203] | 33 | self._data = None
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| [607] | 34 | self._lmap = None
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| [226] | 35 | self._title = None
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| [257] | 36 | self._ordinate = None
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| 37 | self._abcissa = None
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| [709] | 38 | self._abcunit = None
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| [920] | 39 | self._usermask = []
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| 40 | self._maskselection = None
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| 41 | self._selection = selector()
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| [1023] | 42 | self._hist = rcParams['plotter.histogram']
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| [1556] | 43 | self._fp = FontProperties()
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| [1023] | 44 |
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| [920] | 45 | def _translate(self, instr):
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| 46 | keys = "s b i p t".split()
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| 47 | if isinstance(instr, str):
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| 48 | for key in keys:
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| 49 | if instr.lower().startswith(key):
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| 50 | return key
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| 51 | return None
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| 52 |
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| [1563] | 53 | def _newplotter(self, **kwargs):
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| [710] | 54 | if self._visible:
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| 55 | from asap.asaplotgui import asaplotgui as asaplot
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| 56 | else:
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| 57 | from asap.asaplot import asaplot
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| [1563] | 58 | return asaplot(**kwargs)
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| [710] | 59 |
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| 60 |
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| [935] | 61 | def plot(self, scan=None):
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| [203] | 62 | """
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| [920] | 63 | Plot a scantable.
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| [203] | 64 | Parameters:
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| [920] | 65 | scan: a scantable
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| [203] | 66 | Note:
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| [920] | 67 | If a scantable was specified in a previous call
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| [203] | 68 | to plot, no argument has to be given to 'replot'
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| [920] | 69 | NO checking is done that the abcissas of the scantable
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| [203] | 70 | are consistent e.g. all 'channel' or all 'velocity' etc.
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| 71 | """
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| [710] | 72 | if self._plotter.is_dead:
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| 73 | self._plotter = self._newplotter()
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| [600] | 74 | self._plotter.hold()
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| [203] | 75 | self._plotter.clear()
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| [920] | 76 | from asap import scantable
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| [935] | 77 | if not self._data and not scan:
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| [1101] | 78 | msg = "Input is not a scantable"
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| 79 | if rcParams['verbose']:
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| 80 | print msg
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| 81 | return
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| 82 | raise TypeError(msg)
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| [920] | 83 | if isinstance(scan, scantable):
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| [709] | 84 | if self._data is not None:
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| [920] | 85 | if scan != self._data:
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| 86 | self._data = scan
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| [710] | 87 | # reset
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| 88 | self._reset()
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| [525] | 89 | else:
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| [920] | 90 | self._data = scan
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| [710] | 91 | self._reset()
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| [709] | 92 | # ranges become invalid when unit changes
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| [935] | 93 | if self._abcunit and self._abcunit != self._data.get_unit():
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| [709] | 94 | self._minmaxx = None
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| 95 | self._minmaxy = None
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| [920] | 96 | self._abcunit = self._data.get_unit()
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| [710] | 97 | self._datamask = None
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| [920] | 98 | self._plot(self._data)
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| [709] | 99 | if self._minmaxy is not None:
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| 100 | self._plotter.set_limits(ylim=self._minmaxy)
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| [203] | 101 | self._plotter.release()
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| [1153] | 102 | self._plotter.tidy()
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| 103 | self._plotter.show(hardrefresh=False)
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| [753] | 104 | print_log()
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| [203] | 105 | return
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| 106 |
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| [1572] | 107 | def gca(self):
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| 108 | return self._plotter.figure.gca()
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| 109 |
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| [1550] | 110 | def refresh(self):
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| [1572] | 111 | """Do a soft refresh"""
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| [1550] | 112 | self._plotter.figure.show()
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| 113 |
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| [1555] | 114 | def create_mask(self, nwin=1, panel=0, color=None):
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| [1597] | 115 | """
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| 116 | Interactively define a mask.It retruns a mask that is equivalent to
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| 117 | the one created manually with scantable.create_mask.
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| 118 | Parameters:
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| 119 | nwin: The number of mask windows to create interactively
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| 120 | default is 1.
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| 121 | panel: Which panel to use for mask selection. This is useful
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| 122 | if different IFs are spread over panels (default 0)
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| 123 | """
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| [1555] | 124 | if self._data is None:
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| 125 | return []
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| [1547] | 126 | outmask = []
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| [1549] | 127 | self._plotter.subplot(panel)
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| 128 | xmin, xmax = self._plotter.axes.get_xlim()
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| [1548] | 129 | marg = 0.05*(xmax-xmin)
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| [1549] | 130 | self._plotter.axes.set_xlim(xmin-marg, xmax+marg)
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| [1550] | 131 | self.refresh()
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| 132 |
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| [1555] | 133 | def cleanup(lines=False, texts=False, refresh=False):
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| 134 | if lines:
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| 135 | del self._plotter.axes.lines[-1]
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| 136 | if texts:
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| 137 | del self._plotter.axes.texts[-1]
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| 138 | if refresh:
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| 139 | self.refresh()
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| 140 |
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| 141 | for w in xrange(nwin):
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| [1547] | 142 | wpos = []
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| [1555] | 143 | self.text(0.05,1.0, "Add start boundary",
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| 144 | coords="relative", fontsize=10)
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| 145 | point = self._plotter.get_point()
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| 146 | cleanup(texts=True)
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| 147 | if point is None:
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| 148 | continue
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| 149 | wpos.append(point[0])
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| 150 | self.axvline(wpos[0], color=color)
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| [1551] | 151 | self.text(0.05,1.0, "Add end boundary", coords="relative", fontsize=10)
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| [1555] | 152 | point = self._plotter.get_point()
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| 153 | cleanup(texts=True, lines=True)
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| 154 | if point is None:
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| 155 | self.refresh()
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| 156 | continue
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| 157 | wpos.append(point[0])
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| 158 | self.axvspan(wpos[0], wpos[1], alpha=0.1,
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| 159 | edgecolor=color, facecolor=color)
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| 160 | ymin, ymax = self._plotter.axes.get_ylim()
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| [1547] | 161 | outmask.append(wpos)
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| [1153] | 162 |
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| [1555] | 163 | self._plotter.axes.set_xlim(xmin, xmax)
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| 164 | self.refresh()
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| 165 | if len(outmask) > 0:
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| 166 | return self._data.create_mask(*outmask)
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| 167 | return []
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| 168 |
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| [1153] | 169 | # forwards to matplotlib axes
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| 170 | def text(self, *args, **kwargs):
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| [1547] | 171 | if kwargs.has_key("interactive"):
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| 172 | if kwargs.pop("interactive"):
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| 173 | pos = self._plotter.get_point()
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| 174 | args = tuple(pos)+args
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| [1153] | 175 | self._axes_callback("text", *args, **kwargs)
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| [1547] | 176 |
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| [1358] | 177 | text.__doc__ = matplotlib.axes.Axes.text.__doc__
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| [1559] | 178 |
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| [1153] | 179 | def arrow(self, *args, **kwargs):
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| [1547] | 180 | if kwargs.has_key("interactive"):
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| 181 | if kwargs.pop("interactive"):
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| 182 | pos = self._plotter.get_region()
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| 183 | dpos = (pos[0][0], pos[0][1],
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| 184 | pos[1][0]-pos[0][0],
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| 185 | pos[1][1] - pos[0][1])
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| 186 | args = dpos + args
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| [1153] | 187 | self._axes_callback("arrow", *args, **kwargs)
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| [1547] | 188 |
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| [1358] | 189 | arrow.__doc__ = matplotlib.axes.Axes.arrow.__doc__
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| [1559] | 190 |
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| 191 | def annotate(self, text, xy=None, xytext=None, **kwargs):
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| 192 | if kwargs.has_key("interactive"):
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| 193 | if kwargs.pop("interactive"):
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| 194 | xy = self._plotter.get_point()
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| 195 | xytext = self._plotter.get_point()
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| 196 | if not kwargs.has_key("arrowprops"):
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| 197 | kwargs["arrowprops"] = dict(arrowstyle="->")
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| 198 | self._axes_callback("annotate", text, xy, xytext, **kwargs)
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| 199 |
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| 200 | annotate.__doc__ = matplotlib.axes.Axes.annotate.__doc__
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| 201 |
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| [1153] | 202 | def axvline(self, *args, **kwargs):
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| [1547] | 203 | if kwargs.has_key("interactive"):
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| 204 | if kwargs.pop("interactive"):
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| 205 | pos = self._plotter.get_point()
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| 206 | args = (pos[0],)+args
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| [1153] | 207 | self._axes_callback("axvline", *args, **kwargs)
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| [1559] | 208 |
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| [1358] | 209 | axvline.__doc__ = matplotlib.axes.Axes.axvline.__doc__
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| [1547] | 210 |
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| [1153] | 211 | def axhline(self, *args, **kwargs):
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| [1547] | 212 | if kwargs.has_key("interactive"):
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| 213 | if kwargs.pop("interactive"):
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| 214 | pos = self._plotter.get_point()
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| 215 | args = (pos[1],)+args
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| [1153] | 216 | self._axes_callback("axhline", *args, **kwargs)
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| [1559] | 217 |
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| [1358] | 218 | axhline.__doc__ = matplotlib.axes.Axes.axhline.__doc__
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| [1547] | 219 |
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| [1153] | 220 | def axvspan(self, *args, **kwargs):
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| [1547] | 221 | if kwargs.has_key("interactive"):
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| 222 | if kwargs.pop("interactive"):
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| 223 | pos = self._plotter.get_region()
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| 224 | dpos = (pos[0][0], pos[1][0])
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| 225 | args = dpos + args
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| [1153] | 226 | self._axes_callback("axvspan", *args, **kwargs)
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| 227 | # hack to preventy mpl from redrawing the patch
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| 228 | # it seem to convert the patch into lines on every draw.
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| 229 | # This doesn't happen in a test script???
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| [1547] | 230 | #del self._plotter.axes.patches[-1]
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| 231 |
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| [1358] | 232 | axvspan.__doc__ = matplotlib.axes.Axes.axvspan.__doc__
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| [1232] | 233 |
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| [1153] | 234 | def axhspan(self, *args, **kwargs):
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| [1547] | 235 | if kwargs.has_key("interactive"):
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| 236 | if kwargs.pop("interactive"):
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| 237 | pos = self._plotter.get_region()
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| 238 | dpos = (pos[0][1], pos[1][1])
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| 239 | args = dpos + args
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| 240 |
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| [1232] | 241 | self._axes_callback("axhspan", *args, **kwargs)
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| [1153] | 242 | # hack to preventy mpl from redrawing the patch
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| 243 | # it seem to convert the patch into lines on every draw.
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| 244 | # This doesn't happen in a test script???
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| [1547] | 245 | #del self._plotter.axes.patches[-1]
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| [1559] | 246 |
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| [1358] | 247 | axhspan.__doc__ = matplotlib.axes.Axes.axhspan.__doc__
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| [1153] | 248 |
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| 249 | def _axes_callback(self, axesfunc, *args, **kwargs):
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| 250 | panel = 0
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| 251 | if kwargs.has_key("panel"):
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| 252 | panel = kwargs.pop("panel")
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| 253 | coords = None
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| 254 | if kwargs.has_key("coords"):
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| 255 | coords = kwargs.pop("coords")
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| 256 | if coords.lower() == 'world':
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| 257 | kwargs["transform"] = self._plotter.axes.transData
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| 258 | elif coords.lower() == 'relative':
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| 259 | kwargs["transform"] = self._plotter.axes.transAxes
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| 260 | self._plotter.subplot(panel)
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| 261 | self._plotter.axes.set_autoscale_on(False)
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| 262 | getattr(self._plotter.axes, axesfunc)(*args, **kwargs)
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| 263 | self._plotter.show(False)
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| 264 | self._plotter.axes.set_autoscale_on(True)
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| 265 | # end matplotlib.axes fowarding functions
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| 266 |
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| [1547] | 267 |
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| [226] | 268 | def set_mode(self, stacking=None, panelling=None):
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| [203] | 269 | """
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| [377] | 270 | Set the plots look and feel, i.e. what you want to see on the plot.
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| [203] | 271 | Parameters:
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| 272 | stacking: tell the plotter which variable to plot
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| [1217] | 273 | as line colour overlays (default 'pol')
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| [203] | 274 | panelling: tell the plotter which variable to plot
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| 275 | across multiple panels (default 'scan'
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| 276 | Note:
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| 277 | Valid modes are:
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| 278 | 'beam' 'Beam' 'b': Beams
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| 279 | 'if' 'IF' 'i': IFs
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| 280 | 'pol' 'Pol' 'p': Polarisations
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| 281 | 'scan' 'Scan' 's': Scans
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| 282 | 'time' 'Time' 't': Times
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| 283 | """
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| [753] | 284 | msg = "Invalid mode"
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| 285 | if not self.set_panelling(panelling) or \
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| 286 | not self.set_stacking(stacking):
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| 287 | if rcParams['verbose']:
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| 288 | print msg
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| 289 | return
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| 290 | else:
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| 291 | raise TypeError(msg)
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| [920] | 292 | if self._data: self.plot(self._data)
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| [203] | 293 | return
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| 294 |
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| [554] | 295 | def set_panelling(self, what=None):
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| 296 | mode = what
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| 297 | if mode is None:
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| 298 | mode = rcParams['plotter.panelling']
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| 299 | md = self._translate(mode)
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| [203] | 300 | if md:
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| [554] | 301 | self._panelling = md
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| [226] | 302 | self._title = None
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| [203] | 303 | return True
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| 304 | return False
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| 305 |
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| [377] | 306 | def set_layout(self,rows=None,cols=None):
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| 307 | """
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| 308 | Set the multi-panel layout, i.e. how many rows and columns plots
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| 309 | are visible.
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| 310 | Parameters:
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| 311 | rows: The number of rows of plots
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| 312 | cols: The number of columns of plots
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| 313 | Note:
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| 314 | If no argument is given, the potter reverts to its auto-plot
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| 315 | behaviour.
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| 316 | """
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| 317 | self._rows = rows
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| 318 | self._cols = cols
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| [920] | 319 | if self._data: self.plot(self._data)
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| [377] | 320 | return
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| 321 |
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| [709] | 322 | def set_stacking(self, what=None):
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| [554] | 323 | mode = what
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| [709] | 324 | if mode is None:
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| 325 | mode = rcParams['plotter.stacking']
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| [554] | 326 | md = self._translate(mode)
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| [203] | 327 | if md:
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| 328 | self._stacking = md
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| [226] | 329 | self._lmap = None
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| [203] | 330 | return True
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| 331 | return False
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| 332 |
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| [525] | 333 | def set_range(self,xstart=None,xend=None,ystart=None,yend=None):
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| [203] | 334 | """
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| 335 | Set the range of interest on the abcissa of the plot
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| 336 | Parameters:
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| [525] | 337 | [x,y]start,[x,y]end: The start and end points of the 'zoom' window
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| [203] | 338 | Note:
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| 339 | These become non-sensical when the unit changes.
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| 340 | use plotter.set_range() without parameters to reset
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| 341 |
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| 342 | """
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| [525] | 343 | if xstart is None and xend is None:
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| 344 | self._minmaxx = None
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| [600] | 345 | else:
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| 346 | self._minmaxx = [xstart,xend]
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| [525] | 347 | if ystart is None and yend is None:
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| 348 | self._minmaxy = None
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| [600] | 349 | else:
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| [709] | 350 | self._minmaxy = [ystart,yend]
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| [920] | 351 | if self._data: self.plot(self._data)
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| [203] | 352 | return
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| [709] | 353 |
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| [1101] | 354 | def set_legend(self, mp=None, fontsize = None, mode = 0):
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| [203] | 355 | """
|
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| 356 | Specify a mapping for the legend instead of using the default
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| 357 | indices:
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| 358 | Parameters:
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| [1101] | 359 | mp: a list of 'strings'. This should have the same length
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| 360 | as the number of elements on the legend and then maps
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| 361 | to the indeces in order. It is possible to uses latex
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|---|
| 362 | math expression. These have to be enclosed in r'',
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| 363 | e.g. r'$x^{2}$'
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|---|
| 364 | fontsize: The font size of the label (default None)
|
|---|
| 365 | mode: where to display the legend
|
|---|
| 366 | Any other value for loc else disables the legend:
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| [1096] | 367 | 0: auto
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| 368 | 1: upper right
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| 369 | 2: upper left
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| 370 | 3: lower left
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| 371 | 4: lower right
|
|---|
| 372 | 5: right
|
|---|
| 373 | 6: center left
|
|---|
| 374 | 7: center right
|
|---|
| 375 | 8: lower center
|
|---|
| 376 | 9: upper center
|
|---|
| 377 | 10: center
|
|---|
| [203] | 378 |
|
|---|
| 379 | Example:
|
|---|
| [485] | 380 | If the data has two IFs/rest frequencies with index 0 and 1
|
|---|
| [203] | 381 | for CO and SiO:
|
|---|
| 382 | plotter.set_stacking('i')
|
|---|
| [710] | 383 | plotter.set_legend(['CO','SiO'])
|
|---|
| [203] | 384 | plotter.plot()
|
|---|
| [710] | 385 | plotter.set_legend([r'$^{12}CO$', r'SiO'])
|
|---|
| [203] | 386 | """
|
|---|
| 387 | self._lmap = mp
|
|---|
| [1096] | 388 | self._plotter.legend(mode)
|
|---|
| [1101] | 389 | if isinstance(fontsize, int):
|
|---|
| 390 | from matplotlib import rc as rcp
|
|---|
| 391 | rcp('legend', fontsize=fontsize)
|
|---|
| [1096] | 392 | if self._data:
|
|---|
| 393 | self.plot(self._data)
|
|---|
| [226] | 394 | return
|
|---|
| 395 |
|
|---|
| [1101] | 396 | def set_title(self, title=None, fontsize=None):
|
|---|
| [710] | 397 | """
|
|---|
| 398 | Set the title of the plot. If multiple panels are plotted,
|
|---|
| 399 | multiple titles have to be specified.
|
|---|
| 400 | Example:
|
|---|
| 401 | # two panels are visible on the plotter
|
|---|
| 402 | plotter.set_title(["First Panel","Second Panel"])
|
|---|
| 403 | """
|
|---|
| [226] | 404 | self._title = title
|
|---|
| [1101] | 405 | if isinstance(fontsize, int):
|
|---|
| 406 | from matplotlib import rc as rcp
|
|---|
| 407 | rcp('axes', titlesize=fontsize)
|
|---|
| [920] | 408 | if self._data: self.plot(self._data)
|
|---|
| [226] | 409 | return
|
|---|
| 410 |
|
|---|
| [1101] | 411 | def set_ordinate(self, ordinate=None, fontsize=None):
|
|---|
| [710] | 412 | """
|
|---|
| 413 | Set the y-axis label of the plot. If multiple panels are plotted,
|
|---|
| 414 | multiple labels have to be specified.
|
|---|
| [1021] | 415 | Parameters:
|
|---|
| 416 | ordinate: a list of ordinate labels. None (default) let
|
|---|
| 417 | data determine the labels
|
|---|
| [710] | 418 | Example:
|
|---|
| 419 | # two panels are visible on the plotter
|
|---|
| 420 | plotter.set_ordinate(["First Y-Axis","Second Y-Axis"])
|
|---|
| 421 | """
|
|---|
| [257] | 422 | self._ordinate = ordinate
|
|---|
| [1101] | 423 | if isinstance(fontsize, int):
|
|---|
| 424 | from matplotlib import rc as rcp
|
|---|
| 425 | rcp('axes', labelsize=fontsize)
|
|---|
| 426 | rcp('ytick', labelsize=fontsize)
|
|---|
| [920] | 427 | if self._data: self.plot(self._data)
|
|---|
| [257] | 428 | return
|
|---|
| 429 |
|
|---|
| [1101] | 430 | def set_abcissa(self, abcissa=None, fontsize=None):
|
|---|
| [710] | 431 | """
|
|---|
| 432 | Set the x-axis label of the plot. If multiple panels are plotted,
|
|---|
| 433 | multiple labels have to be specified.
|
|---|
| [1021] | 434 | Parameters:
|
|---|
| 435 | abcissa: a list of abcissa labels. None (default) let
|
|---|
| 436 | data determine the labels
|
|---|
| [710] | 437 | Example:
|
|---|
| 438 | # two panels are visible on the plotter
|
|---|
| 439 | plotter.set_ordinate(["First X-Axis","Second X-Axis"])
|
|---|
| 440 | """
|
|---|
| [257] | 441 | self._abcissa = abcissa
|
|---|
| [1101] | 442 | if isinstance(fontsize, int):
|
|---|
| 443 | from matplotlib import rc as rcp
|
|---|
| 444 | rcp('axes', labelsize=fontsize)
|
|---|
| 445 | rcp('xtick', labelsize=fontsize)
|
|---|
| [920] | 446 | if self._data: self.plot(self._data)
|
|---|
| [257] | 447 | return
|
|---|
| 448 |
|
|---|
| [1217] | 449 | def set_colors(self, colmap):
|
|---|
| [377] | 450 | """
|
|---|
| [1217] | 451 | Set the colours to be used. The plotter will cycle through
|
|---|
| 452 | these colours when lines are overlaid (stacking mode).
|
|---|
| [1021] | 453 | Parameters:
|
|---|
| [1217] | 454 | colmap: a list of colour names
|
|---|
| [710] | 455 | Example:
|
|---|
| 456 | plotter.set_colors("red green blue")
|
|---|
| 457 | # If for example four lines are overlaid e.g I Q U V
|
|---|
| 458 | # 'I' will be 'red', 'Q' will be 'green', U will be 'blue'
|
|---|
| 459 | # and 'V' will be 'red' again.
|
|---|
| 460 | """
|
|---|
| [1217] | 461 | if isinstance(colmap,str):
|
|---|
| 462 | colmap = colmap.split()
|
|---|
| 463 | self._plotter.palette(0, colormap=colmap)
|
|---|
| [920] | 464 | if self._data: self.plot(self._data)
|
|---|
| [710] | 465 |
|
|---|
| [1217] | 466 | # alias for english speakers
|
|---|
| 467 | set_colours = set_colors
|
|---|
| 468 |
|
|---|
| [1101] | 469 | def set_histogram(self, hist=True, linewidth=None):
|
|---|
| [1021] | 470 | """
|
|---|
| 471 | Enable/Disable histogram-like plotting.
|
|---|
| 472 | Parameters:
|
|---|
| 473 | hist: True (default) or False. The fisrt default
|
|---|
| 474 | is taken from the .asaprc setting
|
|---|
| 475 | plotter.histogram
|
|---|
| 476 | """
|
|---|
| [1023] | 477 | self._hist = hist
|
|---|
| [1101] | 478 | if isinstance(linewidth, float) or isinstance(linewidth, int):
|
|---|
| 479 | from matplotlib import rc as rcp
|
|---|
| 480 | rcp('lines', linewidth=linewidth)
|
|---|
| [1021] | 481 | if self._data: self.plot(self._data)
|
|---|
| [1023] | 482 |
|
|---|
| [1101] | 483 | def set_linestyles(self, linestyles=None, linewidth=None):
|
|---|
| [710] | 484 | """
|
|---|
| [734] | 485 | Set the linestyles to be used. The plotter will cycle through
|
|---|
| 486 | these linestyles when lines are overlaid (stacking mode) AND
|
|---|
| 487 | only one color has been set.
|
|---|
| [710] | 488 | Parameters:
|
|---|
| 489 | linestyles: a list of linestyles to use.
|
|---|
| 490 | 'line', 'dashed', 'dotted', 'dashdot',
|
|---|
| 491 | 'dashdotdot' and 'dashdashdot' are
|
|---|
| 492 | possible
|
|---|
| 493 |
|
|---|
| 494 | Example:
|
|---|
| 495 | plotter.set_colors("black")
|
|---|
| 496 | plotter.set_linestyles("line dashed dotted dashdot")
|
|---|
| 497 | # If for example four lines are overlaid e.g I Q U V
|
|---|
| 498 | # 'I' will be 'solid', 'Q' will be 'dashed',
|
|---|
| 499 | # U will be 'dotted' and 'V' will be 'dashdot'.
|
|---|
| 500 | """
|
|---|
| 501 | if isinstance(linestyles,str):
|
|---|
| 502 | linestyles = linestyles.split()
|
|---|
| 503 | self._plotter.palette(color=0,linestyle=0,linestyles=linestyles)
|
|---|
| [1101] | 504 | if isinstance(linewidth, float) or isinstance(linewidth, int):
|
|---|
| 505 | from matplotlib import rc as rcp
|
|---|
| 506 | rcp('lines', linewidth=linewidth)
|
|---|
| [920] | 507 | if self._data: self.plot(self._data)
|
|---|
| [710] | 508 |
|
|---|
| [1547] | 509 | def set_font(self, **kwargs):
|
|---|
| [1101] | 510 | """
|
|---|
| 511 | Set font properties.
|
|---|
| 512 | Parameters:
|
|---|
| 513 | family: one of 'sans-serif', 'serif', 'cursive', 'fantasy', 'monospace'
|
|---|
| 514 | style: one of 'normal' (or 'roman'), 'italic' or 'oblique'
|
|---|
| 515 | weight: one of 'normal or 'bold'
|
|---|
| 516 | size: the 'general' font size, individual elements can be adjusted
|
|---|
| 517 | seperately
|
|---|
| 518 | """
|
|---|
| 519 | from matplotlib import rc as rcp
|
|---|
| [1547] | 520 | fdict = {}
|
|---|
| 521 | for k,v in kwargs.iteritems():
|
|---|
| 522 | if v:
|
|---|
| 523 | fdict[k] = v
|
|---|
| [1556] | 524 | self._fp = FontProperties(**fdict)
|
|---|
| [1547] | 525 | if self._data:
|
|---|
| [1556] | 526 | self.plot()
|
|---|
| [1101] | 527 |
|
|---|
| [1259] | 528 | def plot_lines(self, linecat=None, doppler=0.0, deltachan=10, rotate=90.0,
|
|---|
| [1146] | 529 | location=None):
|
|---|
| 530 | """
|
|---|
| [1158] | 531 | Plot a line catalog.
|
|---|
| 532 | Parameters:
|
|---|
| 533 | linecat: the linecatalog to plot
|
|---|
| [1168] | 534 | doppler: the velocity shift to apply to the frequencies
|
|---|
| [1158] | 535 | deltachan: the number of channels to include each side of the
|
|---|
| 536 | line to determine a local maximum/minimum
|
|---|
| [1259] | 537 | rotate: the rotation (in degrees) )for the text label (default 90.0)
|
|---|
| [1158] | 538 | location: the location of the line annotation from the 'top',
|
|---|
| 539 | 'bottom' or alternate (None - the default)
|
|---|
| [1165] | 540 | Notes:
|
|---|
| 541 | If the spectrum is flagged no line will be drawn in that location.
|
|---|
| [1146] | 542 | """
|
|---|
| [1259] | 543 | if not self._data:
|
|---|
| 544 | raise RuntimeError("No scantable has been plotted yet.")
|
|---|
| [1146] | 545 | from asap._asap import linecatalog
|
|---|
| [1259] | 546 | if not isinstance(linecat, linecatalog):
|
|---|
| 547 | raise ValueError("'linecat' isn't of type linecatalog.")
|
|---|
| 548 | if not self._data.get_unit().endswith("Hz"):
|
|---|
| 549 | raise RuntimeError("Can only overlay linecatalogs when data is in frequency.")
|
|---|
| [1153] | 550 | from matplotlib.numerix import ma
|
|---|
| [1146] | 551 | for j in range(len(self._plotter.subplots)):
|
|---|
| 552 | self._plotter.subplot(j)
|
|---|
| 553 | lims = self._plotter.axes.get_xlim()
|
|---|
| [1153] | 554 | for row in range(linecat.nrow()):
|
|---|
| [1259] | 555 | # get_frequency returns MHz
|
|---|
| 556 | base = { "GHz": 1000.0, "MHz": 1.0, "Hz": 1.0e-6 }
|
|---|
| 557 | restf = linecat.get_frequency(row)/base[self._data.get_unit()]
|
|---|
| [1165] | 558 | c = 299792.458
|
|---|
| [1174] | 559 | freq = restf*(1.0-doppler/c)
|
|---|
| [1146] | 560 | if lims[0] < freq < lims[1]:
|
|---|
| 561 | if location is None:
|
|---|
| 562 | loc = 'bottom'
|
|---|
| [1153] | 563 | if row%2: loc='top'
|
|---|
| [1146] | 564 | else: loc = location
|
|---|
| [1153] | 565 | maxys = []
|
|---|
| 566 | for line in self._plotter.axes.lines:
|
|---|
| 567 | v = line._x
|
|---|
| 568 | asc = v[0] < v[-1]
|
|---|
| 569 |
|
|---|
| 570 | idx = None
|
|---|
| 571 | if not asc:
|
|---|
| 572 | if v[len(v)-1] <= freq <= v[0]:
|
|---|
| 573 | i = len(v)-1
|
|---|
| 574 | while i>=0 and v[i] < freq:
|
|---|
| 575 | idx = i
|
|---|
| 576 | i-=1
|
|---|
| 577 | else:
|
|---|
| 578 | if v[0] <= freq <= v[len(v)-1]:
|
|---|
| 579 | i = 0
|
|---|
| 580 | while i<len(v) and v[i] < freq:
|
|---|
| 581 | idx = i
|
|---|
| 582 | i+=1
|
|---|
| 583 | if idx is not None:
|
|---|
| 584 | lower = idx - deltachan
|
|---|
| 585 | upper = idx + deltachan
|
|---|
| 586 | if lower < 0: lower = 0
|
|---|
| 587 | if upper > len(v): upper = len(v)
|
|---|
| 588 | s = slice(lower, upper)
|
|---|
| [1167] | 589 | y = line._y[s]
|
|---|
| [1165] | 590 | maxy = ma.maximum(y)
|
|---|
| 591 | if isinstance( maxy, float):
|
|---|
| 592 | maxys.append(maxy)
|
|---|
| [1164] | 593 | if len(maxys):
|
|---|
| 594 | peak = max(maxys)
|
|---|
| [1165] | 595 | if peak > self._plotter.axes.get_ylim()[1]:
|
|---|
| 596 | loc = 'bottom'
|
|---|
| [1164] | 597 | else:
|
|---|
| 598 | continue
|
|---|
| [1157] | 599 | self._plotter.vline_with_label(freq, peak,
|
|---|
| 600 | linecat.get_name(row),
|
|---|
| 601 | location=loc, rotate=rotate)
|
|---|
| [1153] | 602 | self._plotter.show(hardrefresh=False)
|
|---|
| [1146] | 603 |
|
|---|
| [1153] | 604 |
|
|---|
| [710] | 605 | def save(self, filename=None, orientation=None, dpi=None):
|
|---|
| 606 | """
|
|---|
| [377] | 607 | Save the plot to a file. The know formats are 'png', 'ps', 'eps'.
|
|---|
| 608 | Parameters:
|
|---|
| 609 | filename: The name of the output file. This is optional
|
|---|
| 610 | and autodetects the image format from the file
|
|---|
| 611 | suffix. If non filename is specified a file
|
|---|
| 612 | called 'yyyymmdd_hhmmss.png' is created in the
|
|---|
| 613 | current directory.
|
|---|
| [709] | 614 | orientation: optional parameter for postscript only (not eps).
|
|---|
| 615 | 'landscape', 'portrait' or None (default) are valid.
|
|---|
| 616 | If None is choosen for 'ps' output, the plot is
|
|---|
| 617 | automatically oriented to fill the page.
|
|---|
| [710] | 618 | dpi: The dpi of the output non-ps plot
|
|---|
| [377] | 619 | """
|
|---|
| [709] | 620 | self._plotter.save(filename,orientation,dpi)
|
|---|
| [377] | 621 | return
|
|---|
| [709] | 622 |
|
|---|
| [257] | 623 |
|
|---|
| [920] | 624 | def set_mask(self, mask=None, selection=None):
|
|---|
| [525] | 625 | """
|
|---|
| [734] | 626 | Set a plotting mask for a specific polarization.
|
|---|
| 627 | This is useful for masking out "noise" Pangle outside a source.
|
|---|
| 628 | Parameters:
|
|---|
| [920] | 629 | mask: a mask from scantable.create_mask
|
|---|
| 630 | selection: the spectra to apply the mask to.
|
|---|
| [734] | 631 | Example:
|
|---|
| [920] | 632 | select = selector()
|
|---|
| 633 | select.setpolstrings("Pangle")
|
|---|
| 634 | plotter.set_mask(mymask, select)
|
|---|
| [734] | 635 | """
|
|---|
| [710] | 636 | if not self._data:
|
|---|
| [920] | 637 | msg = "Can only set mask after a first call to plot()"
|
|---|
| [753] | 638 | if rcParams['verbose']:
|
|---|
| 639 | print msg
|
|---|
| [762] | 640 | return
|
|---|
| [753] | 641 | else:
|
|---|
| [762] | 642 | raise RuntimeError(msg)
|
|---|
| [920] | 643 | if len(mask):
|
|---|
| 644 | if isinstance(mask, list) or isinstance(mask, tuple):
|
|---|
| 645 | self._usermask = array(mask)
|
|---|
| [710] | 646 | else:
|
|---|
| [920] | 647 | self._usermask = mask
|
|---|
| 648 | if mask is None and selection is None:
|
|---|
| 649 | self._usermask = []
|
|---|
| 650 | self._maskselection = None
|
|---|
| 651 | if isinstance(selection, selector):
|
|---|
| [947] | 652 | self._maskselection = {'b': selection.get_beams(),
|
|---|
| 653 | 's': selection.get_scans(),
|
|---|
| 654 | 'i': selection.get_ifs(),
|
|---|
| 655 | 'p': selection.get_pols(),
|
|---|
| [920] | 656 | 't': [] }
|
|---|
| [710] | 657 | else:
|
|---|
| [920] | 658 | self._maskselection = None
|
|---|
| 659 | self.plot(self._data)
|
|---|
| [710] | 660 |
|
|---|
| [709] | 661 | def _slice_indeces(self, data):
|
|---|
| 662 | mn = self._minmaxx[0]
|
|---|
| 663 | mx = self._minmaxx[1]
|
|---|
| 664 | asc = data[0] < data[-1]
|
|---|
| 665 | start=0
|
|---|
| 666 | end = len(data)-1
|
|---|
| 667 | inc = 1
|
|---|
| 668 | if not asc:
|
|---|
| 669 | start = len(data)-1
|
|---|
| 670 | end = 0
|
|---|
| 671 | inc = -1
|
|---|
| 672 | # find min index
|
|---|
| [1101] | 673 | while start > 0 and data[start] < mn:
|
|---|
| [709] | 674 | start+= inc
|
|---|
| 675 | # find max index
|
|---|
| [1101] | 676 | while end > 0 and data[end] > mx:
|
|---|
| [709] | 677 | end-=inc
|
|---|
| [1101] | 678 | if end > 0: end +=1
|
|---|
| [709] | 679 | if start > end:
|
|---|
| 680 | return end,start
|
|---|
| 681 | return start,end
|
|---|
| 682 |
|
|---|
| [710] | 683 | def _reset(self):
|
|---|
| [920] | 684 | self._usermask = []
|
|---|
| [710] | 685 | self._usermaskspectra = None
|
|---|
| [920] | 686 | self.set_selection(None, False)
|
|---|
| 687 |
|
|---|
| 688 | def _plot(self, scan):
|
|---|
| [947] | 689 | savesel = scan.get_selection()
|
|---|
| 690 | sel = savesel + self._selection
|
|---|
| 691 | d0 = {'s': 'SCANNO', 'b': 'BEAMNO', 'i':'IFNO',
|
|---|
| 692 | 'p': 'POLNO', 'c': 'CYCLENO', 't' : 'TIME' }
|
|---|
| 693 | order = [d0[self._panelling],d0[self._stacking]]
|
|---|
| 694 | sel.set_order(order)
|
|---|
| 695 | scan.set_selection(sel)
|
|---|
| [920] | 696 | d = {'b': scan.getbeam, 's': scan.getscan,
|
|---|
| 697 | 'i': scan.getif, 'p': scan.getpol, 't': scan._gettime }
|
|---|
| 698 |
|
|---|
| [1148] | 699 | polmodes = dict(zip(self._selection.get_pols(),
|
|---|
| 700 | self._selection.get_poltypes()))
|
|---|
| 701 | # this returns either a tuple of numbers or a length (ncycles)
|
|---|
| 702 | # convert this into lengths
|
|---|
| 703 | n0,nstack0 = self._get_selected_n(scan)
|
|---|
| 704 | if isinstance(n0, int): n = n0
|
|---|
| [1175] | 705 | else: n = len(n0)
|
|---|
| [1148] | 706 | if isinstance(nstack0, int): nstack = nstack0
|
|---|
| [1175] | 707 | else: nstack = len(nstack0)
|
|---|
| [1582] | 708 | maxpanel, maxstack = 16,16
|
|---|
| [920] | 709 | if n > maxpanel or nstack > maxstack:
|
|---|
| 710 | from asap import asaplog
|
|---|
| [1148] | 711 | maxn = 0
|
|---|
| 712 | if nstack > maxstack: maxn = maxstack
|
|---|
| 713 | if n > maxpanel: maxn = maxpanel
|
|---|
| [920] | 714 | msg ="Scan to be plotted contains more than %d selections.\n" \
|
|---|
| [1148] | 715 | "Selecting first %d selections..." % (maxn, maxn)
|
|---|
| [920] | 716 | asaplog.push(msg)
|
|---|
| 717 | print_log()
|
|---|
| 718 | n = min(n,maxpanel)
|
|---|
| [998] | 719 | nstack = min(nstack,maxstack)
|
|---|
| [920] | 720 | if n > 1:
|
|---|
| 721 | ganged = rcParams['plotter.ganged']
|
|---|
| 722 | if self._rows and self._cols:
|
|---|
| 723 | n = min(n,self._rows*self._cols)
|
|---|
| 724 | self._plotter.set_panels(rows=self._rows,cols=self._cols,
|
|---|
| 725 | nplots=n,ganged=ganged)
|
|---|
| 726 | else:
|
|---|
| 727 | self._plotter.set_panels(rows=n,cols=0,nplots=n,ganged=ganged)
|
|---|
| 728 | else:
|
|---|
| 729 | self._plotter.set_panels()
|
|---|
| 730 | r=0
|
|---|
| 731 | nr = scan.nrow()
|
|---|
| 732 | a0,b0 = -1,-1
|
|---|
| 733 | allxlim = []
|
|---|
| [1018] | 734 | allylim = []
|
|---|
| [920] | 735 | newpanel=True
|
|---|
| 736 | panelcount,stackcount = 0,0
|
|---|
| [1002] | 737 | while r < nr:
|
|---|
| [920] | 738 | a = d[self._panelling](r)
|
|---|
| 739 | b = d[self._stacking](r)
|
|---|
| 740 | if a > a0 and panelcount < n:
|
|---|
| 741 | if n > 1:
|
|---|
| 742 | self._plotter.subplot(panelcount)
|
|---|
| 743 | self._plotter.palette(0)
|
|---|
| 744 | #title
|
|---|
| 745 | xlab = self._abcissa and self._abcissa[panelcount] \
|
|---|
| 746 | or scan._getabcissalabel()
|
|---|
| 747 | ylab = self._ordinate and self._ordinate[panelcount] \
|
|---|
| 748 | or scan._get_ordinate_label()
|
|---|
| [1547] | 749 | self._plotter.set_axes('xlabel', xlab)
|
|---|
| 750 | self._plotter.set_axes('ylabel', ylab)
|
|---|
| [920] | 751 | lbl = self._get_label(scan, r, self._panelling, self._title)
|
|---|
| 752 | if isinstance(lbl, list) or isinstance(lbl, tuple):
|
|---|
| 753 | if 0 <= panelcount < len(lbl):
|
|---|
| 754 | lbl = lbl[panelcount]
|
|---|
| 755 | else:
|
|---|
| 756 | # get default label
|
|---|
| 757 | lbl = self._get_label(scan, r, self._panelling, None)
|
|---|
| 758 | self._plotter.set_axes('title',lbl)
|
|---|
| 759 | newpanel = True
|
|---|
| 760 | stackcount =0
|
|---|
| 761 | panelcount += 1
|
|---|
| 762 | if (b > b0 or newpanel) and stackcount < nstack:
|
|---|
| 763 | y = []
|
|---|
| 764 | if len(polmodes):
|
|---|
| 765 | y = scan._getspectrum(r, polmodes[scan.getpol(r)])
|
|---|
| 766 | else:
|
|---|
| 767 | y = scan._getspectrum(r)
|
|---|
| 768 | m = scan._getmask(r)
|
|---|
| [1146] | 769 | from matplotlib.numerix import logical_not, logical_and
|
|---|
| [920] | 770 | if self._maskselection and len(self._usermask) == len(m):
|
|---|
| 771 | if d[self._stacking](r) in self._maskselection[self._stacking]:
|
|---|
| 772 | m = logical_and(m, self._usermask)
|
|---|
| 773 | x = scan._getabcissa(r)
|
|---|
| [1146] | 774 | from matplotlib.numerix import ma, array
|
|---|
| [1116] | 775 | y = ma.masked_array(y,mask=logical_not(array(m,copy=False)))
|
|---|
| [920] | 776 | if self._minmaxx is not None:
|
|---|
| 777 | s,e = self._slice_indeces(x)
|
|---|
| 778 | x = x[s:e]
|
|---|
| 779 | y = y[s:e]
|
|---|
| [1096] | 780 | if len(x) > 1024 and rcParams['plotter.decimate']:
|
|---|
| 781 | fac = len(x)/1024
|
|---|
| [920] | 782 | x = x[::fac]
|
|---|
| 783 | y = y[::fac]
|
|---|
| 784 | llbl = self._get_label(scan, r, self._stacking, self._lmap)
|
|---|
| 785 | if isinstance(llbl, list) or isinstance(llbl, tuple):
|
|---|
| 786 | if 0 <= stackcount < len(llbl):
|
|---|
| 787 | # use user label
|
|---|
| 788 | llbl = llbl[stackcount]
|
|---|
| 789 | else:
|
|---|
| 790 | # get default label
|
|---|
| 791 | llbl = self._get_label(scan, r, self._stacking, None)
|
|---|
| 792 | self._plotter.set_line(label=llbl)
|
|---|
| [1023] | 793 | plotit = self._plotter.plot
|
|---|
| 794 | if self._hist: plotit = self._plotter.hist
|
|---|
| [1146] | 795 | if len(x) > 0:
|
|---|
| 796 | plotit(x,y)
|
|---|
| 797 | xlim= self._minmaxx or [min(x),max(x)]
|
|---|
| 798 | allxlim += xlim
|
|---|
| 799 | ylim= self._minmaxy or [ma.minimum(y),ma.maximum(y)]
|
|---|
| 800 | allylim += ylim
|
|---|
| [920] | 801 | stackcount += 1
|
|---|
| 802 | # last in colour stack -> autoscale x
|
|---|
| 803 | if stackcount == nstack:
|
|---|
| 804 | allxlim.sort()
|
|---|
| 805 | self._plotter.axes.set_xlim([allxlim[0],allxlim[-1]])
|
|---|
| 806 | # clear
|
|---|
| 807 | allxlim =[]
|
|---|
| 808 |
|
|---|
| 809 | newpanel = False
|
|---|
| 810 | a0=a
|
|---|
| 811 | b0=b
|
|---|
| 812 | # ignore following rows
|
|---|
| 813 | if (panelcount == n) and (stackcount == nstack):
|
|---|
| [1018] | 814 | # last panel -> autoscale y if ganged
|
|---|
| 815 | if rcParams['plotter.ganged']:
|
|---|
| 816 | allylim.sort()
|
|---|
| 817 | self._plotter.set_limits(ylim=[allylim[0],allylim[-1]])
|
|---|
| [998] | 818 | break
|
|---|
| [920] | 819 | r+=1 # next row
|
|---|
| [947] | 820 | #reset the selector to the scantable's original
|
|---|
| 821 | scan.set_selection(savesel)
|
|---|
| [1556] | 822 | if self._fp is not None:
|
|---|
| 823 | for o in self._plotter.figure.findobj(Text):
|
|---|
| 824 | o.set_fontproperties(self._fp)
|
|---|
| [920] | 825 |
|
|---|
| [1556] | 826 |
|
|---|
| [1582] | 827 | def set_selection(self, selection=None, refresh=True, **kw):
|
|---|
| 828 | if selection is None:
|
|---|
| 829 | # reset
|
|---|
| 830 | if len(kw) == 0:
|
|---|
| 831 | self._selection = selector()
|
|---|
| 832 | else:
|
|---|
| 833 | # try keywords
|
|---|
| 834 | for k in kw:
|
|---|
| 835 | if k not in selector.fields:
|
|---|
| 836 | raise KeyError("Invalid selection key '%s', valid keys are %s" % (k, selector.fields))
|
|---|
| 837 | self._selection = selector(**kw)
|
|---|
| 838 | elif isinstance(selection, selector):
|
|---|
| 839 | self._selection = selection
|
|---|
| 840 | else:
|
|---|
| 841 | raise TypeError("'selection' is not of type selector")
|
|---|
| 842 |
|
|---|
| [920] | 843 | d0 = {'s': 'SCANNO', 'b': 'BEAMNO', 'i':'IFNO',
|
|---|
| 844 | 'p': 'POLNO', 'c': 'CYCLENO', 't' : 'TIME' }
|
|---|
| 845 | order = [d0[self._panelling],d0[self._stacking]]
|
|---|
| [947] | 846 | self._selection.set_order(order)
|
|---|
| [920] | 847 | if self._data and refresh: self.plot(self._data)
|
|---|
| 848 |
|
|---|
| 849 | def _get_selected_n(self, scan):
|
|---|
| [1148] | 850 | d1 = {'b': scan.getbeamnos, 's': scan.getscannos,
|
|---|
| 851 | 'i': scan.getifnos, 'p': scan.getpolnos, 't': scan.ncycle }
|
|---|
| 852 | d2 = { 'b': self._selection.get_beams(),
|
|---|
| 853 | 's': self._selection.get_scans(),
|
|---|
| 854 | 'i': self._selection.get_ifs(),
|
|---|
| 855 | 'p': self._selection.get_pols(),
|
|---|
| 856 | 't': self._selection.get_cycles() }
|
|---|
| [920] | 857 | n = d2[self._panelling] or d1[self._panelling]()
|
|---|
| 858 | nstack = d2[self._stacking] or d1[self._stacking]()
|
|---|
| 859 | return n,nstack
|
|---|
| 860 |
|
|---|
| 861 | def _get_label(self, scan, row, mode, userlabel=None):
|
|---|
| [1153] | 862 | if isinstance(userlabel, list) and len(userlabel) == 0:
|
|---|
| 863 | userlabel = " "
|
|---|
| [947] | 864 | pms = dict(zip(self._selection.get_pols(),self._selection.get_poltypes()))
|
|---|
| [920] | 865 | if len(pms):
|
|---|
| 866 | poleval = scan._getpollabel(scan.getpol(row),pms[scan.getpol(row)])
|
|---|
| 867 | else:
|
|---|
| 868 | poleval = scan._getpollabel(scan.getpol(row),scan.poltype())
|
|---|
| 869 | d = {'b': "Beam "+str(scan.getbeam(row)),
|
|---|
| 870 | 's': scan._getsourcename(row),
|
|---|
| 871 | 'i': "IF"+str(scan.getif(row)),
|
|---|
| [964] | 872 | 'p': poleval,
|
|---|
| [1175] | 873 | 't': str(scan.get_time(row)) }
|
|---|
| [920] | 874 | return userlabel or d[mode]
|
|---|
| [1153] | 875 |
|
|---|
| [1556] | 876 | def plotazel(self):
|
|---|
| [1391] | 877 | """
|
|---|
| 878 | plot azimuth and elevation versus time of a scantable
|
|---|
| 879 | """
|
|---|
| 880 | import pylab as PL
|
|---|
| 881 | from matplotlib.dates import DateFormatter, timezone, HourLocator, MinuteLocator, DayLocator
|
|---|
| 882 | from matplotlib.ticker import MultipleLocator
|
|---|
| 883 | from matplotlib.numerix import array, pi
|
|---|
| [1556] | 884 | dates = self._data.get_time(asdatetime=True)
|
|---|
| [1391] | 885 | t = PL.date2num(dates)
|
|---|
| 886 | tz = timezone('UTC')
|
|---|
| 887 | PL.cla()
|
|---|
| 888 | PL.ioff()
|
|---|
| 889 | PL.clf()
|
|---|
| 890 | tdel = max(t) - min(t)
|
|---|
| 891 | ax = PL.subplot(2,1,1)
|
|---|
| 892 | el = array(self._data.get_elevation())*180./pi
|
|---|
| 893 | PL.ylabel('El [deg.]')
|
|---|
| 894 | dstr = dates[0].strftime('%Y/%m/%d')
|
|---|
| 895 | if tdel > 1.0:
|
|---|
| 896 | dstr2 = dates[len(dates)-1].strftime('%Y/%m/%d')
|
|---|
| 897 | dstr = dstr + " - " + dstr2
|
|---|
| 898 | majloc = DayLocator()
|
|---|
| 899 | minloc = HourLocator(range(0,23,12))
|
|---|
| 900 | timefmt = DateFormatter("%b%d")
|
|---|
| 901 | else:
|
|---|
| 902 | timefmt = DateFormatter('%H')
|
|---|
| 903 | majloc = HourLocator()
|
|---|
| 904 | minloc = MinuteLocator(20)
|
|---|
| 905 | PL.title(dstr)
|
|---|
| 906 | PL.plot_date(t,el,'b,', tz=tz)
|
|---|
| 907 | #ax.grid(True)
|
|---|
| 908 | ax.yaxis.grid(True)
|
|---|
| 909 | yloc = MultipleLocator(30)
|
|---|
| 910 | ax.set_ylim(0,90)
|
|---|
| 911 | ax.xaxis.set_major_formatter(timefmt)
|
|---|
| 912 | ax.xaxis.set_major_locator(majloc)
|
|---|
| 913 | ax.xaxis.set_minor_locator(minloc)
|
|---|
| 914 | ax.yaxis.set_major_locator(yloc)
|
|---|
| 915 | if tdel > 1.0:
|
|---|
| 916 | labels = ax.get_xticklabels()
|
|---|
| 917 | # PL.setp(labels, fontsize=10, rotation=45)
|
|---|
| 918 | PL.setp(labels, fontsize=10)
|
|---|
| 919 | # Az plot
|
|---|
| 920 | az = array(self._data.get_azimuth())*180./pi
|
|---|
| 921 | if min(az) < 0:
|
|---|
| 922 | for irow in range(len(az)):
|
|---|
| 923 | if az[irow] < 0: az[irow] += 360.0
|
|---|
| 924 |
|
|---|
| 925 | ax = PL.subplot(2,1,2)
|
|---|
| 926 | PL.xlabel('Time (UT)')
|
|---|
| 927 | PL.ylabel('Az [deg.]')
|
|---|
| 928 | PL.plot_date(t,az,'b,', tz=tz)
|
|---|
| 929 | ax.set_ylim(0,360)
|
|---|
| 930 | #ax.grid(True)
|
|---|
| 931 | ax.yaxis.grid(True)
|
|---|
| 932 | #hfmt = DateFormatter('%H')
|
|---|
| 933 | #hloc = HourLocator()
|
|---|
| 934 | yloc = MultipleLocator(60)
|
|---|
| 935 | ax.xaxis.set_major_formatter(timefmt)
|
|---|
| 936 | ax.xaxis.set_major_locator(majloc)
|
|---|
| 937 | ax.xaxis.set_minor_locator(minloc)
|
|---|
| 938 | ax.yaxis.set_major_locator(yloc)
|
|---|
| 939 | if tdel > 1.0:
|
|---|
| 940 | labels = ax.get_xticklabels()
|
|---|
| 941 | PL.setp(labels, fontsize=10)
|
|---|
| 942 | PL.ion()
|
|---|
| 943 | PL.draw()
|
|---|
| 944 |
|
|---|
| [1556] | 945 | def plotpointing(self):
|
|---|
| [1391] | 946 | """
|
|---|
| 947 | plot telescope pointings
|
|---|
| 948 | """
|
|---|
| 949 | import pylab as PL
|
|---|
| 950 | from matplotlib.dates import DateFormatter, timezone
|
|---|
| 951 | from matplotlib.ticker import MultipleLocator
|
|---|
| 952 | from matplotlib.numerix import array, pi, zeros
|
|---|
| 953 | dir = array(self._data.get_directionval()).transpose()
|
|---|
| 954 | ra = dir[0]*180./pi
|
|---|
| 955 | dec = dir[1]*180./pi
|
|---|
| 956 | PL.cla()
|
|---|
| 957 | PL.ioff()
|
|---|
| 958 | PL.clf()
|
|---|
| 959 | ax = PL.axes([0.1,0.1,0.8,0.8])
|
|---|
| 960 | ax = PL.axes([0.1,0.1,0.8,0.8])
|
|---|
| 961 | ax.set_aspect('equal')
|
|---|
| 962 | PL.plot(ra,dec, 'b,')
|
|---|
| 963 | PL.xlabel('RA [deg.]')
|
|---|
| 964 | PL.ylabel('Declination [deg.]')
|
|---|
| 965 | PL.title('Telescope pointings')
|
|---|
| 966 | [xmin,xmax,ymin,ymax] = PL.axis()
|
|---|
| 967 | PL.axis([xmax,xmin,ymin,ymax])
|
|---|
| 968 | PL.ion()
|
|---|
| 969 | PL.draw()
|
|---|
| 970 |
|
|---|
