[1824] | 1 | from asap.parameters import rcParams
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| 2 | from asap.selector import selector
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| 3 | from asap.scantable import scantable
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[1862] | 4 | from asap.logging import asaplog, asaplog_post_dec
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[1153] | 5 | import matplotlib.axes
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[1556] | 6 | from matplotlib.font_manager import FontProperties
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| 7 | from matplotlib.text import Text
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| 8 |
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[1317] | 9 | import re
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[203] | 10 |
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| 11 | class asapplotter:
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[226] | 12 | """
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| 13 | The ASAP plotter.
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| 14 | By default the plotter is set up to plot polarisations
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| 15 | 'colour stacked' and scantables across panels.
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[1858] | 16 |
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| 17 | .. note::
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| 18 |
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[226] | 19 | Currenly it only plots 'spectra' not Tsys or
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| 20 | other variables.
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[1858] | 21 |
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[226] | 22 | """
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[1563] | 23 | def __init__(self, visible=None , **kwargs):
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[734] | 24 | self._visible = rcParams['plotter.gui']
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| 25 | if visible is not None:
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| 26 | self._visible = visible
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[1563] | 27 | self._plotter = self._newplotter(**kwargs)
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[1819] | 28 | # additional tool bar
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| 29 | self._plotter.figmgr.casabar=self._newcasabar()
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[710] | 30 |
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[554] | 31 | self._panelling = None
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| 32 | self._stacking = None
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| 33 | self.set_panelling()
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| 34 | self.set_stacking()
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[377] | 35 | self._rows = None
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| 36 | self._cols = None
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[203] | 37 | self._autoplot = False
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[525] | 38 | self._minmaxx = None
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| 39 | self._minmaxy = None
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[710] | 40 | self._datamask = None
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[203] | 41 | self._data = None
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[607] | 42 | self._lmap = None
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[226] | 43 | self._title = None
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[257] | 44 | self._ordinate = None
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| 45 | self._abcissa = None
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[709] | 46 | self._abcunit = None
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[920] | 47 | self._usermask = []
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| 48 | self._maskselection = None
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| 49 | self._selection = selector()
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[1023] | 50 | self._hist = rcParams['plotter.histogram']
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[1556] | 51 | self._fp = FontProperties()
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[2037] | 52 | self._margins = self.set_margin(refresh=False)
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[1897] | 53 | self._offset = None
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[1981] | 54 | self._startrow = 0
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| 55 | self._ipanel = -1
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| 56 | self._panelrows = []
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[1023] | 57 |
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[920] | 58 | def _translate(self, instr):
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[1910] | 59 | keys = "s b i p t r".split()
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[920] | 60 | if isinstance(instr, str):
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| 61 | for key in keys:
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| 62 | if instr.lower().startswith(key):
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| 63 | return key
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| 64 | return None
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| 65 |
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[1563] | 66 | def _newplotter(self, **kwargs):
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[1819] | 67 | backend=matplotlib.get_backend()
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| 68 | if not self._visible:
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| 69 | from asap.asaplot import asaplot
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| 70 | elif backend == 'TkAgg':
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[710] | 71 | from asap.asaplotgui import asaplotgui as asaplot
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[1819] | 72 | elif backend == 'Qt4Agg':
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| 73 | from asap.asaplotgui_qt4 import asaplotgui as asaplot
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| 74 | elif backend == 'GTkAgg':
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| 75 | from asap.asaplotgui_gtk import asaplotgui as asaplot
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[710] | 76 | else:
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| 77 | from asap.asaplot import asaplot
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[1563] | 78 | return asaplot(**kwargs)
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[710] | 79 |
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[1819] | 80 | def _newcasabar(self):
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| 81 | backend=matplotlib.get_backend()
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| 82 | if self._visible and backend == "TkAgg":
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| 83 | from asap.casatoolbar import CustomToolbarTkAgg
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| 84 | return CustomToolbarTkAgg(self)
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[1989] | 85 | #from asap.casatoolbar import CustomFlagToolbarTkAgg
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| 86 | #return CustomFlagToolbarTkAgg(self)
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[1995] | 87 | return None
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[1819] | 88 |
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[1862] | 89 | @asaplog_post_dec
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[935] | 90 | def plot(self, scan=None):
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[203] | 91 | """
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[920] | 92 | Plot a scantable.
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[203] | 93 | Parameters:
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[920] | 94 | scan: a scantable
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[203] | 95 | Note:
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[920] | 96 | If a scantable was specified in a previous call
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[203] | 97 | to plot, no argument has to be given to 'replot'
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[920] | 98 | NO checking is done that the abcissas of the scantable
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[203] | 99 | are consistent e.g. all 'channel' or all 'velocity' etc.
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| 100 | """
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[1981] | 101 | self._startrow = 0
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| 102 | self._ipanel = -1
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[710] | 103 | if self._plotter.is_dead:
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[1819] | 104 | if hasattr(self._plotter.figmgr,'casabar'):
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| 105 | del self._plotter.figmgr.casabar
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[710] | 106 | self._plotter = self._newplotter()
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[1819] | 107 | self._plotter.figmgr.casabar=self._newcasabar()
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[1981] | 108 | if self._plotter.figmgr.casabar:
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[1984] | 109 | self._plotter.figmgr.casabar.set_pagecounter(1)
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[1981] | 110 | self._panelrows = []
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[600] | 111 | self._plotter.hold()
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[1945] | 112 | #self._plotter.clear()
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[935] | 113 | if not self._data and not scan:
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[1101] | 114 | msg = "Input is not a scantable"
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| 115 | raise TypeError(msg)
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[1897] | 116 | if scan:
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| 117 | self.set_data(scan, refresh=False)
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[920] | 118 | self._plot(self._data)
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[709] | 119 | if self._minmaxy is not None:
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| 120 | self._plotter.set_limits(ylim=self._minmaxy)
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[1819] | 121 | if self._plotter.figmgr.casabar: self._plotter.figmgr.casabar.enable_button()
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[203] | 122 | self._plotter.release()
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[1153] | 123 | self._plotter.tidy()
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| 124 | self._plotter.show(hardrefresh=False)
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[203] | 125 | return
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| 126 |
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[1572] | 127 | def gca(self):
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| 128 | return self._plotter.figure.gca()
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| 129 |
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[1550] | 130 | def refresh(self):
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[1572] | 131 | """Do a soft refresh"""
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[1550] | 132 | self._plotter.figure.show()
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| 133 |
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[1555] | 134 | def create_mask(self, nwin=1, panel=0, color=None):
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[1597] | 135 | """
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[1927] | 136 | Interactively define a mask. It retruns a mask that is equivalent to
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[1597] | 137 | the one created manually with scantable.create_mask.
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| 138 | Parameters:
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| 139 | nwin: The number of mask windows to create interactively
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| 140 | default is 1.
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| 141 | panel: Which panel to use for mask selection. This is useful
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| 142 | if different IFs are spread over panels (default 0)
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| 143 | """
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[1555] | 144 | if self._data is None:
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| 145 | return []
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[1547] | 146 | outmask = []
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[1549] | 147 | self._plotter.subplot(panel)
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| 148 | xmin, xmax = self._plotter.axes.get_xlim()
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[1548] | 149 | marg = 0.05*(xmax-xmin)
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[1549] | 150 | self._plotter.axes.set_xlim(xmin-marg, xmax+marg)
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[1550] | 151 | self.refresh()
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[1695] | 152 |
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[1555] | 153 | def cleanup(lines=False, texts=False, refresh=False):
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| 154 | if lines:
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| 155 | del self._plotter.axes.lines[-1]
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| 156 | if texts:
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| 157 | del self._plotter.axes.texts[-1]
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| 158 | if refresh:
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| 159 | self.refresh()
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| 160 |
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| 161 | for w in xrange(nwin):
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[1547] | 162 | wpos = []
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[1695] | 163 | self.text(0.05,1.0, "Add start boundary",
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[1555] | 164 | coords="relative", fontsize=10)
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| 165 | point = self._plotter.get_point()
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| 166 | cleanup(texts=True)
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| 167 | if point is None:
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| 168 | continue
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| 169 | wpos.append(point[0])
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[1695] | 170 | self.axvline(wpos[0], color=color)
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[1551] | 171 | self.text(0.05,1.0, "Add end boundary", coords="relative", fontsize=10)
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[1555] | 172 | point = self._plotter.get_point()
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| 173 | cleanup(texts=True, lines=True)
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| 174 | if point is None:
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| 175 | self.refresh()
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| 176 | continue
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| 177 | wpos.append(point[0])
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| 178 | self.axvspan(wpos[0], wpos[1], alpha=0.1,
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| 179 | edgecolor=color, facecolor=color)
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| 180 | ymin, ymax = self._plotter.axes.get_ylim()
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[1547] | 181 | outmask.append(wpos)
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[1153] | 182 |
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[1555] | 183 | self._plotter.axes.set_xlim(xmin, xmax)
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| 184 | self.refresh()
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| 185 | if len(outmask) > 0:
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| 186 | return self._data.create_mask(*outmask)
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| 187 | return []
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| 188 |
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[1153] | 189 | # forwards to matplotlib axes
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| 190 | def text(self, *args, **kwargs):
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[1547] | 191 | if kwargs.has_key("interactive"):
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| 192 | if kwargs.pop("interactive"):
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| 193 | pos = self._plotter.get_point()
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| 194 | args = tuple(pos)+args
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[1153] | 195 | self._axes_callback("text", *args, **kwargs)
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[1547] | 196 |
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[1358] | 197 | text.__doc__ = matplotlib.axes.Axes.text.__doc__
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[1559] | 198 |
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[1153] | 199 | def arrow(self, *args, **kwargs):
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[1547] | 200 | if kwargs.has_key("interactive"):
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| 201 | if kwargs.pop("interactive"):
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| 202 | pos = self._plotter.get_region()
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| 203 | dpos = (pos[0][0], pos[0][1],
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| 204 | pos[1][0]-pos[0][0],
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| 205 | pos[1][1] - pos[0][1])
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| 206 | args = dpos + args
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[1153] | 207 | self._axes_callback("arrow", *args, **kwargs)
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[1547] | 208 |
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[1358] | 209 | arrow.__doc__ = matplotlib.axes.Axes.arrow.__doc__
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[1559] | 210 |
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| 211 | def annotate(self, text, xy=None, xytext=None, **kwargs):
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| 212 | if kwargs.has_key("interactive"):
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| 213 | if kwargs.pop("interactive"):
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| 214 | xy = self._plotter.get_point()
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| 215 | xytext = self._plotter.get_point()
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| 216 | if not kwargs.has_key("arrowprops"):
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| 217 | kwargs["arrowprops"] = dict(arrowstyle="->")
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| 218 | self._axes_callback("annotate", text, xy, xytext, **kwargs)
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| 219 |
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| 220 | annotate.__doc__ = matplotlib.axes.Axes.annotate.__doc__
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| 221 |
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[1153] | 222 | def axvline(self, *args, **kwargs):
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[1547] | 223 | if kwargs.has_key("interactive"):
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| 224 | if kwargs.pop("interactive"):
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| 225 | pos = self._plotter.get_point()
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| 226 | args = (pos[0],)+args
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[1153] | 227 | self._axes_callback("axvline", *args, **kwargs)
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[1559] | 228 |
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[1358] | 229 | axvline.__doc__ = matplotlib.axes.Axes.axvline.__doc__
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[1547] | 230 |
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[1153] | 231 | def axhline(self, *args, **kwargs):
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[1547] | 232 | if kwargs.has_key("interactive"):
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| 233 | if kwargs.pop("interactive"):
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| 234 | pos = self._plotter.get_point()
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| 235 | args = (pos[1],)+args
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[1153] | 236 | self._axes_callback("axhline", *args, **kwargs)
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[1559] | 237 |
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[1358] | 238 | axhline.__doc__ = matplotlib.axes.Axes.axhline.__doc__
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[1547] | 239 |
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[1153] | 240 | def axvspan(self, *args, **kwargs):
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[1547] | 241 | if kwargs.has_key("interactive"):
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| 242 | if kwargs.pop("interactive"):
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| 243 | pos = self._plotter.get_region()
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| 244 | dpos = (pos[0][0], pos[1][0])
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| 245 | args = dpos + args
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[1153] | 246 | self._axes_callback("axvspan", *args, **kwargs)
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| 247 | # hack to preventy mpl from redrawing the patch
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| 248 | # it seem to convert the patch into lines on every draw.
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| 249 | # This doesn't happen in a test script???
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[1547] | 250 | #del self._plotter.axes.patches[-1]
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| 251 |
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[1358] | 252 | axvspan.__doc__ = matplotlib.axes.Axes.axvspan.__doc__
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[1232] | 253 |
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[1153] | 254 | def axhspan(self, *args, **kwargs):
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[1547] | 255 | if kwargs.has_key("interactive"):
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| 256 | if kwargs.pop("interactive"):
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| 257 | pos = self._plotter.get_region()
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| 258 | dpos = (pos[0][1], pos[1][1])
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| 259 | args = dpos + args
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[1232] | 260 | self._axes_callback("axhspan", *args, **kwargs)
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[1153] | 261 | # hack to preventy mpl from redrawing the patch
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| 262 | # it seem to convert the patch into lines on every draw.
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| 263 | # This doesn't happen in a test script???
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[1547] | 264 | #del self._plotter.axes.patches[-1]
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[1559] | 265 |
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[1358] | 266 | axhspan.__doc__ = matplotlib.axes.Axes.axhspan.__doc__
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[1153] | 267 |
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| 268 | def _axes_callback(self, axesfunc, *args, **kwargs):
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| 269 | panel = 0
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| 270 | if kwargs.has_key("panel"):
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| 271 | panel = kwargs.pop("panel")
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| 272 | coords = None
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| 273 | if kwargs.has_key("coords"):
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| 274 | coords = kwargs.pop("coords")
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| 275 | if coords.lower() == 'world':
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| 276 | kwargs["transform"] = self._plotter.axes.transData
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| 277 | elif coords.lower() == 'relative':
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| 278 | kwargs["transform"] = self._plotter.axes.transAxes
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| 279 | self._plotter.subplot(panel)
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| 280 | self._plotter.axes.set_autoscale_on(False)
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| 281 | getattr(self._plotter.axes, axesfunc)(*args, **kwargs)
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| 282 | self._plotter.show(False)
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| 283 | self._plotter.axes.set_autoscale_on(True)
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| 284 | # end matplotlib.axes fowarding functions
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| 285 |
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[1862] | 286 | @asaplog_post_dec
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[1819] | 287 | def set_data(self, scan, refresh=True):
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| 288 | """
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[1824] | 289 | Set a scantable to plot.
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[1819] | 290 | Parameters:
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| 291 | scan: a scantable
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| 292 | refresh: True (default) or False. If True, the plot is
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[1824] | 293 | replotted based on the new parameter setting(s).
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[1819] | 294 | Otherwise,the parameter(s) are set without replotting.
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| 295 | Note:
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| 296 | The user specified masks and data selections will be reset
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| 297 | if a new scantable is set. This method should be called before
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[1824] | 298 | setting data selections (set_selection) and/or masks (set_mask).
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[1819] | 299 | """
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| 300 | from asap import scantable
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| 301 | if isinstance(scan, scantable):
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| 302 | if self._data is not None:
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| 303 | if scan != self._data:
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| 304 | self._data = scan
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| 305 | # reset
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| 306 | self._reset()
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[1897] | 307 | msg = "A new scantable is set to the plotter. "\
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| 308 | "The masks and data selections are reset."
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[1819] | 309 | asaplog.push( msg )
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| 310 | else:
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| 311 | self._data = scan
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| 312 | self._reset()
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| 313 | else:
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| 314 | msg = "Input is not a scantable"
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| 315 | raise TypeError(msg)
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[1547] | 316 |
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[1819] | 317 | # ranges become invalid when unit changes
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| 318 | if self._abcunit and self._abcunit != self._data.get_unit():
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| 319 | self._minmaxx = None
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| 320 | self._minmaxy = None
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| 321 | self._abcunit = self._data.get_unit()
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| 322 | self._datamask = None
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| 323 | if refresh: self.plot()
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| 324 |
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[1862] | 325 | @asaplog_post_dec
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[1819] | 326 | def set_mode(self, stacking=None, panelling=None, refresh=True):
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[203] | 327 | """
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[377] | 328 | Set the plots look and feel, i.e. what you want to see on the plot.
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[203] | 329 | Parameters:
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| 330 | stacking: tell the plotter which variable to plot
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[1217] | 331 | as line colour overlays (default 'pol')
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[203] | 332 | panelling: tell the plotter which variable to plot
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| 333 | across multiple panels (default 'scan'
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[1819] | 334 | refresh: True (default) or False. If True, the plot is
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[1824] | 335 | replotted based on the new parameter setting(s).
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[1819] | 336 | Otherwise,the parameter(s) are set without replotting.
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[203] | 337 | Note:
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| 338 | Valid modes are:
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| 339 | 'beam' 'Beam' 'b': Beams
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| 340 | 'if' 'IF' 'i': IFs
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| 341 | 'pol' 'Pol' 'p': Polarisations
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| 342 | 'scan' 'Scan' 's': Scans
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| 343 | 'time' 'Time' 't': Times
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[1989] | 344 | 'row' 'Row' 'r': Rows
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| 345 | When either 'stacking' or 'panelling' is set to 'row',
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| 346 | the other parameter setting is ignored.
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[203] | 347 | """
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[753] | 348 | msg = "Invalid mode"
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| 349 | if not self.set_panelling(panelling) or \
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| 350 | not self.set_stacking(stacking):
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[1859] | 351 | raise TypeError(msg)
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[1989] | 352 | #if self._panelling == 'r':
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| 353 | # self._stacking = '_r'
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| 354 | #if self._stacking == 'r':
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| 355 | # self._panelling = '_r'
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[1819] | 356 | if refresh and self._data: self.plot(self._data)
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[203] | 357 | return
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| 358 |
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[554] | 359 | def set_panelling(self, what=None):
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[1858] | 360 | """Set the 'panelling' mode i.e. which type of spectra should be
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| 361 | spread across different panels.
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| 362 | """
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| 363 |
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[554] | 364 | mode = what
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| 365 | if mode is None:
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| 366 | mode = rcParams['plotter.panelling']
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| 367 | md = self._translate(mode)
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[203] | 368 | if md:
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[554] | 369 | self._panelling = md
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[226] | 370 | self._title = None
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[1989] | 371 | #if md == 'r':
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| 372 | # self._stacking = '_r'
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[1981] | 373 | # you need to reset counters for multi page plotting
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| 374 | self._reset_counters()
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[203] | 375 | return True
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| 376 | return False
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| 377 |
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[1819] | 378 | def set_layout(self,rows=None,cols=None,refresh=True):
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[377] | 379 | """
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| 380 | Set the multi-panel layout, i.e. how many rows and columns plots
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| 381 | are visible.
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| 382 | Parameters:
|
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| 383 | rows: The number of rows of plots
|
---|
| 384 | cols: The number of columns of plots
|
---|
[1819] | 385 | refresh: True (default) or False. If True, the plot is
|
---|
[1824] | 386 | replotted based on the new parameter setting(s).
|
---|
[1819] | 387 | Otherwise,the parameter(s) are set without replotting.
|
---|
[377] | 388 | Note:
|
---|
| 389 | If no argument is given, the potter reverts to its auto-plot
|
---|
| 390 | behaviour.
|
---|
| 391 | """
|
---|
| 392 | self._rows = rows
|
---|
| 393 | self._cols = cols
|
---|
[1819] | 394 | if refresh and self._data: self.plot(self._data)
|
---|
[377] | 395 | return
|
---|
| 396 |
|
---|
[709] | 397 | def set_stacking(self, what=None):
|
---|
[1858] | 398 | """Set the 'stacking' mode i.e. which type of spectra should be
|
---|
| 399 | overlayed.
|
---|
| 400 | """
|
---|
[554] | 401 | mode = what
|
---|
[709] | 402 | if mode is None:
|
---|
| 403 | mode = rcParams['plotter.stacking']
|
---|
[554] | 404 | md = self._translate(mode)
|
---|
[203] | 405 | if md:
|
---|
| 406 | self._stacking = md
|
---|
[226] | 407 | self._lmap = None
|
---|
[1989] | 408 | #if md == 'r':
|
---|
| 409 | # self._panelling = '_r'
|
---|
[1981] | 410 | # you need to reset counters for multi page plotting
|
---|
| 411 | self._reset_counters()
|
---|
[203] | 412 | return True
|
---|
| 413 | return False
|
---|
| 414 |
|
---|
[1981] | 415 | def _reset_counters(self):
|
---|
| 416 | self._startrow = 0
|
---|
| 417 | self._ipanel = -1
|
---|
| 418 | self._panelrows = []
|
---|
| 419 |
|
---|
[1897] | 420 | def set_range(self,xstart=None,xend=None,ystart=None,yend=None,refresh=True, offset=None):
|
---|
[203] | 421 | """
|
---|
| 422 | Set the range of interest on the abcissa of the plot
|
---|
| 423 | Parameters:
|
---|
[525] | 424 | [x,y]start,[x,y]end: The start and end points of the 'zoom' window
|
---|
[1819] | 425 | refresh: True (default) or False. If True, the plot is
|
---|
[1824] | 426 | replotted based on the new parameter setting(s).
|
---|
[1819] | 427 | Otherwise,the parameter(s) are set without replotting.
|
---|
[1897] | 428 | offset: shift the abcissa by the given amount. The abcissa label will
|
---|
| 429 | have '(relative)' appended to it.
|
---|
[203] | 430 | Note:
|
---|
| 431 | These become non-sensical when the unit changes.
|
---|
| 432 | use plotter.set_range() without parameters to reset
|
---|
| 433 |
|
---|
| 434 | """
|
---|
[1897] | 435 | self._offset = offset
|
---|
[525] | 436 | if xstart is None and xend is None:
|
---|
| 437 | self._minmaxx = None
|
---|
[600] | 438 | else:
|
---|
| 439 | self._minmaxx = [xstart,xend]
|
---|
[525] | 440 | if ystart is None and yend is None:
|
---|
| 441 | self._minmaxy = None
|
---|
[600] | 442 | else:
|
---|
[709] | 443 | self._minmaxy = [ystart,yend]
|
---|
[1819] | 444 | if refresh and self._data: self.plot(self._data)
|
---|
[203] | 445 | return
|
---|
[709] | 446 |
|
---|
[1819] | 447 | def set_legend(self, mp=None, fontsize = None, mode = 0, refresh=True):
|
---|
[203] | 448 | """
|
---|
| 449 | Specify a mapping for the legend instead of using the default
|
---|
| 450 | indices:
|
---|
| 451 | Parameters:
|
---|
[1101] | 452 | mp: a list of 'strings'. This should have the same length
|
---|
| 453 | as the number of elements on the legend and then maps
|
---|
| 454 | to the indeces in order. It is possible to uses latex
|
---|
| 455 | math expression. These have to be enclosed in r'',
|
---|
| 456 | e.g. r'$x^{2}$'
|
---|
| 457 | fontsize: The font size of the label (default None)
|
---|
| 458 | mode: where to display the legend
|
---|
| 459 | Any other value for loc else disables the legend:
|
---|
[1096] | 460 | 0: auto
|
---|
| 461 | 1: upper right
|
---|
| 462 | 2: upper left
|
---|
| 463 | 3: lower left
|
---|
| 464 | 4: lower right
|
---|
| 465 | 5: right
|
---|
| 466 | 6: center left
|
---|
| 467 | 7: center right
|
---|
| 468 | 8: lower center
|
---|
| 469 | 9: upper center
|
---|
| 470 | 10: center
|
---|
[1819] | 471 | refresh: True (default) or False. If True, the plot is
|
---|
[1824] | 472 | replotted based on the new parameter setting(s).
|
---|
[1819] | 473 | Otherwise,the parameter(s) are set without replotting.
|
---|
[203] | 474 |
|
---|
| 475 | Example:
|
---|
[485] | 476 | If the data has two IFs/rest frequencies with index 0 and 1
|
---|
[203] | 477 | for CO and SiO:
|
---|
| 478 | plotter.set_stacking('i')
|
---|
[710] | 479 | plotter.set_legend(['CO','SiO'])
|
---|
[203] | 480 | plotter.plot()
|
---|
[710] | 481 | plotter.set_legend([r'$^{12}CO$', r'SiO'])
|
---|
[203] | 482 | """
|
---|
| 483 | self._lmap = mp
|
---|
[1096] | 484 | self._plotter.legend(mode)
|
---|
[1101] | 485 | if isinstance(fontsize, int):
|
---|
| 486 | from matplotlib import rc as rcp
|
---|
| 487 | rcp('legend', fontsize=fontsize)
|
---|
[1819] | 488 | if refresh and self._data: self.plot(self._data)
|
---|
[226] | 489 | return
|
---|
| 490 |
|
---|
[1819] | 491 | def set_title(self, title=None, fontsize=None, refresh=True):
|
---|
[710] | 492 | """
|
---|
| 493 | Set the title of the plot. If multiple panels are plotted,
|
---|
| 494 | multiple titles have to be specified.
|
---|
[1819] | 495 | Parameters:
|
---|
| 496 | refresh: True (default) or False. If True, the plot is
|
---|
[1824] | 497 | replotted based on the new parameter setting(s).
|
---|
[1819] | 498 | Otherwise,the parameter(s) are set without replotting.
|
---|
[710] | 499 | Example:
|
---|
| 500 | # two panels are visible on the plotter
|
---|
| 501 | plotter.set_title(["First Panel","Second Panel"])
|
---|
| 502 | """
|
---|
[226] | 503 | self._title = title
|
---|
[1101] | 504 | if isinstance(fontsize, int):
|
---|
| 505 | from matplotlib import rc as rcp
|
---|
| 506 | rcp('axes', titlesize=fontsize)
|
---|
[1819] | 507 | if refresh and self._data: self.plot(self._data)
|
---|
[226] | 508 | return
|
---|
| 509 |
|
---|
[1819] | 510 | def set_ordinate(self, ordinate=None, fontsize=None, refresh=True):
|
---|
[710] | 511 | """
|
---|
| 512 | Set the y-axis label of the plot. If multiple panels are plotted,
|
---|
| 513 | multiple labels have to be specified.
|
---|
[1021] | 514 | Parameters:
|
---|
| 515 | ordinate: a list of ordinate labels. None (default) let
|
---|
| 516 | data determine the labels
|
---|
[1819] | 517 | refresh: True (default) or False. If True, the plot is
|
---|
[1824] | 518 | replotted based on the new parameter setting(s).
|
---|
[1819] | 519 | Otherwise,the parameter(s) are set without replotting.
|
---|
[710] | 520 | Example:
|
---|
| 521 | # two panels are visible on the plotter
|
---|
| 522 | plotter.set_ordinate(["First Y-Axis","Second Y-Axis"])
|
---|
| 523 | """
|
---|
[257] | 524 | self._ordinate = ordinate
|
---|
[1101] | 525 | if isinstance(fontsize, int):
|
---|
| 526 | from matplotlib import rc as rcp
|
---|
| 527 | rcp('axes', labelsize=fontsize)
|
---|
| 528 | rcp('ytick', labelsize=fontsize)
|
---|
[1819] | 529 | if refresh and self._data: self.plot(self._data)
|
---|
[257] | 530 | return
|
---|
| 531 |
|
---|
[1819] | 532 | def set_abcissa(self, abcissa=None, fontsize=None, refresh=True):
|
---|
[710] | 533 | """
|
---|
| 534 | Set the x-axis label of the plot. If multiple panels are plotted,
|
---|
| 535 | multiple labels have to be specified.
|
---|
[1021] | 536 | Parameters:
|
---|
| 537 | abcissa: a list of abcissa labels. None (default) let
|
---|
| 538 | data determine the labels
|
---|
[1819] | 539 | refresh: True (default) or False. If True, the plot is
|
---|
[1824] | 540 | replotted based on the new parameter setting(s).
|
---|
[1819] | 541 | Otherwise,the parameter(s) are set without replotting.
|
---|
[710] | 542 | Example:
|
---|
| 543 | # two panels are visible on the plotter
|
---|
| 544 | plotter.set_ordinate(["First X-Axis","Second X-Axis"])
|
---|
| 545 | """
|
---|
[257] | 546 | self._abcissa = abcissa
|
---|
[1101] | 547 | if isinstance(fontsize, int):
|
---|
| 548 | from matplotlib import rc as rcp
|
---|
| 549 | rcp('axes', labelsize=fontsize)
|
---|
| 550 | rcp('xtick', labelsize=fontsize)
|
---|
[1819] | 551 | if refresh and self._data: self.plot(self._data)
|
---|
[257] | 552 | return
|
---|
| 553 |
|
---|
[1819] | 554 | def set_colors(self, colmap, refresh=True):
|
---|
[377] | 555 | """
|
---|
[1217] | 556 | Set the colours to be used. The plotter will cycle through
|
---|
| 557 | these colours when lines are overlaid (stacking mode).
|
---|
[1021] | 558 | Parameters:
|
---|
[1217] | 559 | colmap: a list of colour names
|
---|
[1819] | 560 | refresh: True (default) or False. If True, the plot is
|
---|
[1824] | 561 | replotted based on the new parameter setting(s).
|
---|
[1819] | 562 | Otherwise,the parameter(s) are set without replotting.
|
---|
[710] | 563 | Example:
|
---|
| 564 | plotter.set_colors("red green blue")
|
---|
| 565 | # If for example four lines are overlaid e.g I Q U V
|
---|
| 566 | # 'I' will be 'red', 'Q' will be 'green', U will be 'blue'
|
---|
| 567 | # and 'V' will be 'red' again.
|
---|
| 568 | """
|
---|
[1217] | 569 | if isinstance(colmap,str):
|
---|
| 570 | colmap = colmap.split()
|
---|
| 571 | self._plotter.palette(0, colormap=colmap)
|
---|
[1819] | 572 | if refresh and self._data: self.plot(self._data)
|
---|
[710] | 573 |
|
---|
[1217] | 574 | # alias for english speakers
|
---|
| 575 | set_colours = set_colors
|
---|
| 576 |
|
---|
[1819] | 577 | def set_histogram(self, hist=True, linewidth=None, refresh=True):
|
---|
[1021] | 578 | """
|
---|
| 579 | Enable/Disable histogram-like plotting.
|
---|
| 580 | Parameters:
|
---|
| 581 | hist: True (default) or False. The fisrt default
|
---|
| 582 | is taken from the .asaprc setting
|
---|
| 583 | plotter.histogram
|
---|
[1819] | 584 | refresh: True (default) or False. If True, the plot is
|
---|
[1824] | 585 | replotted based on the new parameter setting(s).
|
---|
[1819] | 586 | Otherwise,the parameter(s) are set without replotting.
|
---|
[1021] | 587 | """
|
---|
[1023] | 588 | self._hist = hist
|
---|
[1101] | 589 | if isinstance(linewidth, float) or isinstance(linewidth, int):
|
---|
| 590 | from matplotlib import rc as rcp
|
---|
| 591 | rcp('lines', linewidth=linewidth)
|
---|
[1819] | 592 | if refresh and self._data: self.plot(self._data)
|
---|
[1023] | 593 |
|
---|
[1819] | 594 | def set_linestyles(self, linestyles=None, linewidth=None, refresh=True):
|
---|
[710] | 595 | """
|
---|
[734] | 596 | Set the linestyles to be used. The plotter will cycle through
|
---|
| 597 | these linestyles when lines are overlaid (stacking mode) AND
|
---|
| 598 | only one color has been set.
|
---|
[710] | 599 | Parameters:
|
---|
| 600 | linestyles: a list of linestyles to use.
|
---|
| 601 | 'line', 'dashed', 'dotted', 'dashdot',
|
---|
| 602 | 'dashdotdot' and 'dashdashdot' are
|
---|
| 603 | possible
|
---|
[1819] | 604 | refresh: True (default) or False. If True, the plot is
|
---|
[1824] | 605 | replotted based on the new parameter setting(s).
|
---|
[1819] | 606 | Otherwise,the parameter(s) are set without replotting.
|
---|
[710] | 607 | Example:
|
---|
| 608 | plotter.set_colors("black")
|
---|
| 609 | plotter.set_linestyles("line dashed dotted dashdot")
|
---|
| 610 | # If for example four lines are overlaid e.g I Q U V
|
---|
| 611 | # 'I' will be 'solid', 'Q' will be 'dashed',
|
---|
| 612 | # U will be 'dotted' and 'V' will be 'dashdot'.
|
---|
| 613 | """
|
---|
| 614 | if isinstance(linestyles,str):
|
---|
| 615 | linestyles = linestyles.split()
|
---|
| 616 | self._plotter.palette(color=0,linestyle=0,linestyles=linestyles)
|
---|
[1101] | 617 | if isinstance(linewidth, float) or isinstance(linewidth, int):
|
---|
| 618 | from matplotlib import rc as rcp
|
---|
| 619 | rcp('lines', linewidth=linewidth)
|
---|
[1819] | 620 | if refresh and self._data: self.plot(self._data)
|
---|
[710] | 621 |
|
---|
[1819] | 622 | def set_font(self, refresh=True,**kwargs):
|
---|
[1101] | 623 | """
|
---|
| 624 | Set font properties.
|
---|
| 625 | Parameters:
|
---|
| 626 | family: one of 'sans-serif', 'serif', 'cursive', 'fantasy', 'monospace'
|
---|
| 627 | style: one of 'normal' (or 'roman'), 'italic' or 'oblique'
|
---|
| 628 | weight: one of 'normal or 'bold'
|
---|
| 629 | size: the 'general' font size, individual elements can be adjusted
|
---|
| 630 | seperately
|
---|
[1819] | 631 | refresh: True (default) or False. If True, the plot is
|
---|
[1824] | 632 | replotted based on the new parameter setting(s).
|
---|
[1819] | 633 | Otherwise,the parameter(s) are set without replotting.
|
---|
[1101] | 634 | """
|
---|
| 635 | from matplotlib import rc as rcp
|
---|
[1547] | 636 | fdict = {}
|
---|
| 637 | for k,v in kwargs.iteritems():
|
---|
| 638 | if v:
|
---|
| 639 | fdict[k] = v
|
---|
[1556] | 640 | self._fp = FontProperties(**fdict)
|
---|
[1819] | 641 | if refresh and self._data: self.plot(self._data)
|
---|
[1101] | 642 |
|
---|
[2037] | 643 | def set_margin(self,margin=[],refresh=True):
|
---|
[1819] | 644 | """
|
---|
[2037] | 645 | Set margins between subplots and plot edges.
|
---|
[1819] | 646 | Parameters:
|
---|
[2037] | 647 | margin: a list of margins in figure coordinate (0-1),
|
---|
[1824] | 648 | i.e., fraction of the figure width or height.
|
---|
[1819] | 649 | The order of elements should be:
|
---|
| 650 | [left, bottom, right, top, horizontal space btw panels,
|
---|
[1824] | 651 | vertical space btw panels].
|
---|
[1819] | 652 | refresh: True (default) or False. If True, the plot is
|
---|
[1824] | 653 | replotted based on the new parameter setting(s).
|
---|
[1819] | 654 | Otherwise,the parameter(s) are set without replotting.
|
---|
| 655 | Note
|
---|
[2037] | 656 | * When margin is not specified, the values are reset to the defaults
|
---|
[1819] | 657 | of matplotlib.
|
---|
[1824] | 658 | * If any element is set to be None, the current value is adopted.
|
---|
[1819] | 659 | """
|
---|
[2037] | 660 | if margin == []: self._margins=self._reset_margin()
|
---|
[1824] | 661 | else:
|
---|
[2037] | 662 | self._margins=[None]*6
|
---|
| 663 | self._margins[0:len(margin)]=margin
|
---|
| 664 | #print "panel margin set to ",self._margins
|
---|
[1819] | 665 | if refresh and self._data: self.plot(self._data)
|
---|
| 666 |
|
---|
[2037] | 667 | def _reset_margin(self):
|
---|
[1819] | 668 | ks=map(lambda x: 'figure.subplot.'+x,
|
---|
| 669 | ['left','bottom','right','top','hspace','wspace'])
|
---|
| 670 | return map(matplotlib.rcParams.get,ks)
|
---|
| 671 |
|
---|
[1259] | 672 | def plot_lines(self, linecat=None, doppler=0.0, deltachan=10, rotate=90.0,
|
---|
[1146] | 673 | location=None):
|
---|
| 674 | """
|
---|
[1158] | 675 | Plot a line catalog.
|
---|
| 676 | Parameters:
|
---|
| 677 | linecat: the linecatalog to plot
|
---|
[1168] | 678 | doppler: the velocity shift to apply to the frequencies
|
---|
[1158] | 679 | deltachan: the number of channels to include each side of the
|
---|
| 680 | line to determine a local maximum/minimum
|
---|
[1927] | 681 | rotate: the rotation (in degrees) for the text label (default 90.0)
|
---|
[1158] | 682 | location: the location of the line annotation from the 'top',
|
---|
| 683 | 'bottom' or alternate (None - the default)
|
---|
[1165] | 684 | Notes:
|
---|
| 685 | If the spectrum is flagged no line will be drawn in that location.
|
---|
[1146] | 686 | """
|
---|
[1259] | 687 | if not self._data:
|
---|
| 688 | raise RuntimeError("No scantable has been plotted yet.")
|
---|
[1146] | 689 | from asap._asap import linecatalog
|
---|
[1259] | 690 | if not isinstance(linecat, linecatalog):
|
---|
| 691 | raise ValueError("'linecat' isn't of type linecatalog.")
|
---|
| 692 | if not self._data.get_unit().endswith("Hz"):
|
---|
| 693 | raise RuntimeError("Can only overlay linecatalogs when data is in frequency.")
|
---|
[1739] | 694 | from numpy import ma
|
---|
[1146] | 695 | for j in range(len(self._plotter.subplots)):
|
---|
| 696 | self._plotter.subplot(j)
|
---|
| 697 | lims = self._plotter.axes.get_xlim()
|
---|
[1153] | 698 | for row in range(linecat.nrow()):
|
---|
[1259] | 699 | # get_frequency returns MHz
|
---|
| 700 | base = { "GHz": 1000.0, "MHz": 1.0, "Hz": 1.0e-6 }
|
---|
| 701 | restf = linecat.get_frequency(row)/base[self._data.get_unit()]
|
---|
[1165] | 702 | c = 299792.458
|
---|
[1174] | 703 | freq = restf*(1.0-doppler/c)
|
---|
[1146] | 704 | if lims[0] < freq < lims[1]:
|
---|
| 705 | if location is None:
|
---|
| 706 | loc = 'bottom'
|
---|
[1153] | 707 | if row%2: loc='top'
|
---|
[1146] | 708 | else: loc = location
|
---|
[1153] | 709 | maxys = []
|
---|
| 710 | for line in self._plotter.axes.lines:
|
---|
| 711 | v = line._x
|
---|
| 712 | asc = v[0] < v[-1]
|
---|
| 713 |
|
---|
| 714 | idx = None
|
---|
| 715 | if not asc:
|
---|
| 716 | if v[len(v)-1] <= freq <= v[0]:
|
---|
| 717 | i = len(v)-1
|
---|
| 718 | while i>=0 and v[i] < freq:
|
---|
| 719 | idx = i
|
---|
| 720 | i-=1
|
---|
| 721 | else:
|
---|
| 722 | if v[0] <= freq <= v[len(v)-1]:
|
---|
| 723 | i = 0
|
---|
| 724 | while i<len(v) and v[i] < freq:
|
---|
| 725 | idx = i
|
---|
| 726 | i+=1
|
---|
| 727 | if idx is not None:
|
---|
| 728 | lower = idx - deltachan
|
---|
| 729 | upper = idx + deltachan
|
---|
| 730 | if lower < 0: lower = 0
|
---|
| 731 | if upper > len(v): upper = len(v)
|
---|
| 732 | s = slice(lower, upper)
|
---|
[1167] | 733 | y = line._y[s]
|
---|
[1165] | 734 | maxy = ma.maximum(y)
|
---|
| 735 | if isinstance( maxy, float):
|
---|
| 736 | maxys.append(maxy)
|
---|
[1164] | 737 | if len(maxys):
|
---|
| 738 | peak = max(maxys)
|
---|
[1165] | 739 | if peak > self._plotter.axes.get_ylim()[1]:
|
---|
| 740 | loc = 'bottom'
|
---|
[1164] | 741 | else:
|
---|
| 742 | continue
|
---|
[1157] | 743 | self._plotter.vline_with_label(freq, peak,
|
---|
| 744 | linecat.get_name(row),
|
---|
| 745 | location=loc, rotate=rotate)
|
---|
[1153] | 746 | self._plotter.show(hardrefresh=False)
|
---|
[1146] | 747 |
|
---|
[1153] | 748 |
|
---|
[710] | 749 | def save(self, filename=None, orientation=None, dpi=None):
|
---|
| 750 | """
|
---|
[1927] | 751 | Save the plot to a file. The known formats are 'png', 'ps', 'eps'.
|
---|
[377] | 752 | Parameters:
|
---|
| 753 | filename: The name of the output file. This is optional
|
---|
| 754 | and autodetects the image format from the file
|
---|
| 755 | suffix. If non filename is specified a file
|
---|
| 756 | called 'yyyymmdd_hhmmss.png' is created in the
|
---|
| 757 | current directory.
|
---|
[709] | 758 | orientation: optional parameter for postscript only (not eps).
|
---|
| 759 | 'landscape', 'portrait' or None (default) are valid.
|
---|
| 760 | If None is choosen for 'ps' output, the plot is
|
---|
| 761 | automatically oriented to fill the page.
|
---|
[710] | 762 | dpi: The dpi of the output non-ps plot
|
---|
[377] | 763 | """
|
---|
[709] | 764 | self._plotter.save(filename,orientation,dpi)
|
---|
[377] | 765 | return
|
---|
[709] | 766 |
|
---|
[1862] | 767 | @asaplog_post_dec
|
---|
[1819] | 768 | def set_mask(self, mask=None, selection=None, refresh=True):
|
---|
[525] | 769 | """
|
---|
[734] | 770 | Set a plotting mask for a specific polarization.
|
---|
| 771 | This is useful for masking out "noise" Pangle outside a source.
|
---|
| 772 | Parameters:
|
---|
[920] | 773 | mask: a mask from scantable.create_mask
|
---|
| 774 | selection: the spectra to apply the mask to.
|
---|
[1819] | 775 | refresh: True (default) or False. If True, the plot is
|
---|
[1824] | 776 | replotted based on the new parameter setting(s).
|
---|
[1819] | 777 | Otherwise,the parameter(s) are set without replotting.
|
---|
[734] | 778 | Example:
|
---|
[920] | 779 | select = selector()
|
---|
| 780 | select.setpolstrings("Pangle")
|
---|
| 781 | plotter.set_mask(mymask, select)
|
---|
[734] | 782 | """
|
---|
[710] | 783 | if not self._data:
|
---|
[920] | 784 | msg = "Can only set mask after a first call to plot()"
|
---|
[1859] | 785 | raise RuntimeError(msg)
|
---|
[920] | 786 | if len(mask):
|
---|
| 787 | if isinstance(mask, list) or isinstance(mask, tuple):
|
---|
| 788 | self._usermask = array(mask)
|
---|
[710] | 789 | else:
|
---|
[920] | 790 | self._usermask = mask
|
---|
| 791 | if mask is None and selection is None:
|
---|
| 792 | self._usermask = []
|
---|
| 793 | self._maskselection = None
|
---|
| 794 | if isinstance(selection, selector):
|
---|
[947] | 795 | self._maskselection = {'b': selection.get_beams(),
|
---|
| 796 | 's': selection.get_scans(),
|
---|
| 797 | 'i': selection.get_ifs(),
|
---|
| 798 | 'p': selection.get_pols(),
|
---|
[920] | 799 | 't': [] }
|
---|
[710] | 800 | else:
|
---|
[920] | 801 | self._maskselection = None
|
---|
[1819] | 802 | if refresh: self.plot(self._data)
|
---|
[710] | 803 |
|
---|
[709] | 804 | def _slice_indeces(self, data):
|
---|
| 805 | mn = self._minmaxx[0]
|
---|
| 806 | mx = self._minmaxx[1]
|
---|
| 807 | asc = data[0] < data[-1]
|
---|
| 808 | start=0
|
---|
| 809 | end = len(data)-1
|
---|
| 810 | inc = 1
|
---|
| 811 | if not asc:
|
---|
| 812 | start = len(data)-1
|
---|
| 813 | end = 0
|
---|
| 814 | inc = -1
|
---|
| 815 | # find min index
|
---|
[1819] | 816 | #while start > 0 and data[start] < mn:
|
---|
| 817 | # start+= inc
|
---|
| 818 | minind=start
|
---|
| 819 | for ind in xrange(start,end+inc,inc):
|
---|
| 820 | if data[ind] > mn: break
|
---|
| 821 | minind=ind
|
---|
[709] | 822 | # find max index
|
---|
[1819] | 823 | #while end > 0 and data[end] > mx:
|
---|
| 824 | # end-=inc
|
---|
| 825 | #if end > 0: end +=1
|
---|
| 826 | maxind=end
|
---|
| 827 | for ind in xrange(end,start-inc,-inc):
|
---|
| 828 | if data[ind] < mx: break
|
---|
| 829 | maxind=ind
|
---|
| 830 | start=minind
|
---|
| 831 | end=maxind
|
---|
[709] | 832 | if start > end:
|
---|
[1819] | 833 | return end,start+1
|
---|
| 834 | elif start < end:
|
---|
| 835 | return start,end+1
|
---|
| 836 | else:
|
---|
| 837 | return start,end
|
---|
[709] | 838 |
|
---|
[710] | 839 | def _reset(self):
|
---|
[920] | 840 | self._usermask = []
|
---|
[710] | 841 | self._usermaskspectra = None
|
---|
[1897] | 842 | self._offset = None
|
---|
[920] | 843 | self.set_selection(None, False)
|
---|
| 844 |
|
---|
| 845 | def _plot(self, scan):
|
---|
[947] | 846 | savesel = scan.get_selection()
|
---|
| 847 | sel = savesel + self._selection
|
---|
[1910] | 848 | order = self._get_sortstring([self._panelling,self._stacking])
|
---|
| 849 | if order:
|
---|
| 850 | sel.set_order(order)
|
---|
[947] | 851 | scan.set_selection(sel)
|
---|
[920] | 852 | d = {'b': scan.getbeam, 's': scan.getscan,
|
---|
[1949] | 853 | 'i': scan.getif, 'p': scan.getpol, 't': scan.get_time,
|
---|
[1989] | 854 | 'r': int}#, '_r': int}
|
---|
[920] | 855 |
|
---|
[1148] | 856 | polmodes = dict(zip(self._selection.get_pols(),
|
---|
| 857 | self._selection.get_poltypes()))
|
---|
| 858 | # this returns either a tuple of numbers or a length (ncycles)
|
---|
| 859 | # convert this into lengths
|
---|
| 860 | n0,nstack0 = self._get_selected_n(scan)
|
---|
| 861 | if isinstance(n0, int): n = n0
|
---|
[1175] | 862 | else: n = len(n0)
|
---|
[1148] | 863 | if isinstance(nstack0, int): nstack = nstack0
|
---|
[1175] | 864 | else: nstack = len(nstack0)
|
---|
[1989] | 865 | # In case of row stacking
|
---|
| 866 | rowstack = False
|
---|
| 867 | titlemode = self._panelling
|
---|
| 868 | if self._stacking == "r" and self._panelling != "r":
|
---|
| 869 | rowstack = True
|
---|
| 870 | titlemode = '_r'
|
---|
[1913] | 871 | nptot = n
|
---|
[1582] | 872 | maxpanel, maxstack = 16,16
|
---|
[1913] | 873 | if nstack > maxstack:
|
---|
| 874 | msg ="Scan to be overlayed contains more than %d selections.\n" \
|
---|
| 875 | "Selecting first %d selections..." % (maxstack, maxstack)
|
---|
[920] | 876 | asaplog.push(msg)
|
---|
[1861] | 877 | asaplog.post('WARN')
|
---|
[998] | 878 | nstack = min(nstack,maxstack)
|
---|
[2038] | 879 | #n = min(n-self._ipanel-1,maxpanel)
|
---|
| 880 | n = n-self._ipanel-1
|
---|
[2011] | 881 |
|
---|
| 882 | ganged = False
|
---|
[920] | 883 | if n > 1:
|
---|
| 884 | ganged = rcParams['plotter.ganged']
|
---|
[1819] | 885 | if self._panelling == 'i':
|
---|
| 886 | ganged = False
|
---|
[920] | 887 | if self._rows and self._cols:
|
---|
| 888 | n = min(n,self._rows*self._cols)
|
---|
| 889 | self._plotter.set_panels(rows=self._rows,cols=self._cols,
|
---|
[2037] | 890 | nplots=n,margin=self._margins,ganged=ganged)
|
---|
[920] | 891 | else:
|
---|
[2038] | 892 | n = min(n,maxpanel)
|
---|
[2037] | 893 | self._plotter.set_panels(rows=n,cols=0,nplots=n,margin=self._margins,ganged=ganged)
|
---|
[920] | 894 | else:
|
---|
[2037] | 895 | self._plotter.set_panels(margin=self._margins)
|
---|
[1913] | 896 | #r = 0
|
---|
[1981] | 897 | r = self._startrow
|
---|
[920] | 898 | nr = scan.nrow()
|
---|
| 899 | a0,b0 = -1,-1
|
---|
| 900 | allxlim = []
|
---|
[1018] | 901 | allylim = []
|
---|
[1981] | 902 | #newpanel=True
|
---|
| 903 | newpanel=False
|
---|
[920] | 904 | panelcount,stackcount = 0,0
|
---|
[1981] | 905 | # If this is not the first page
|
---|
| 906 | if r > 0:
|
---|
| 907 | # panelling value of the prev page
|
---|
| 908 | a0 = d[self._panelling](r-1)
|
---|
| 909 | # set the initial stackcount large not to plot
|
---|
| 910 | # the start row automatically
|
---|
| 911 | stackcount = nstack
|
---|
| 912 |
|
---|
[1002] | 913 | while r < nr:
|
---|
[920] | 914 | a = d[self._panelling](r)
|
---|
| 915 | b = d[self._stacking](r)
|
---|
| 916 | if a > a0 and panelcount < n:
|
---|
| 917 | if n > 1:
|
---|
| 918 | self._plotter.subplot(panelcount)
|
---|
| 919 | self._plotter.palette(0)
|
---|
| 920 | #title
|
---|
| 921 | xlab = self._abcissa and self._abcissa[panelcount] \
|
---|
| 922 | or scan._getabcissalabel()
|
---|
[1897] | 923 | if self._offset and not self._abcissa:
|
---|
| 924 | xlab += " (relative)"
|
---|
[920] | 925 | ylab = self._ordinate and self._ordinate[panelcount] \
|
---|
| 926 | or scan._get_ordinate_label()
|
---|
[1547] | 927 | self._plotter.set_axes('xlabel', xlab)
|
---|
| 928 | self._plotter.set_axes('ylabel', ylab)
|
---|
[1989] | 929 | #lbl = self._get_label(scan, r, self._panelling, self._title)
|
---|
| 930 | lbl = self._get_label(scan, r, titlemode, self._title)
|
---|
[920] | 931 | if isinstance(lbl, list) or isinstance(lbl, tuple):
|
---|
| 932 | if 0 <= panelcount < len(lbl):
|
---|
| 933 | lbl = lbl[panelcount]
|
---|
| 934 | else:
|
---|
| 935 | # get default label
|
---|
[1989] | 936 | #lbl = self._get_label(scan, r, self._panelling, None)
|
---|
| 937 | lbl = self._get_label(scan, r, titlemode, None)
|
---|
[920] | 938 | self._plotter.set_axes('title',lbl)
|
---|
| 939 | newpanel = True
|
---|
[1913] | 940 | stackcount = 0
|
---|
[920] | 941 | panelcount += 1
|
---|
[1981] | 942 | # save the start row to plot this panel for future revisit.
|
---|
| 943 | if self._panelling != 'r' and \
|
---|
| 944 | len(self._panelrows) < self._ipanel+1+panelcount:
|
---|
| 945 | self._panelrows += [r]
|
---|
| 946 |
|
---|
[1944] | 947 | #if (b > b0 or newpanel) and stackcount < nstack:
|
---|
[1989] | 948 | if stackcount < nstack and (newpanel or rowstack or (a == a0 and b > b0)):
|
---|
[920] | 949 | y = []
|
---|
| 950 | if len(polmodes):
|
---|
| 951 | y = scan._getspectrum(r, polmodes[scan.getpol(r)])
|
---|
| 952 | else:
|
---|
| 953 | y = scan._getspectrum(r)
|
---|
[1995] | 954 | # flag application
|
---|
| 955 | mr = scan._getflagrow(r)
|
---|
[1739] | 956 | from numpy import ma, array
|
---|
[1995] | 957 | if mr:
|
---|
| 958 | y = ma.masked_array(y,mask=mr)
|
---|
| 959 | else:
|
---|
| 960 | m = scan._getmask(r)
|
---|
| 961 | from numpy import logical_not, logical_and
|
---|
| 962 | if self._maskselection and len(self._usermask) == len(m):
|
---|
| 963 | if d[self._stacking](r) in self._maskselection[self._stacking]:
|
---|
| 964 | m = logical_and(m, self._usermask)
|
---|
| 965 | y = ma.masked_array(y,mask=logical_not(array(m,copy=False)))
|
---|
| 966 |
|
---|
[1897] | 967 | x = array(scan._getabcissa(r))
|
---|
| 968 | if self._offset:
|
---|
| 969 | x += self._offset
|
---|
[920] | 970 | if self._minmaxx is not None:
|
---|
| 971 | s,e = self._slice_indeces(x)
|
---|
| 972 | x = x[s:e]
|
---|
| 973 | y = y[s:e]
|
---|
[1096] | 974 | if len(x) > 1024 and rcParams['plotter.decimate']:
|
---|
| 975 | fac = len(x)/1024
|
---|
[920] | 976 | x = x[::fac]
|
---|
| 977 | y = y[::fac]
|
---|
| 978 | llbl = self._get_label(scan, r, self._stacking, self._lmap)
|
---|
| 979 | if isinstance(llbl, list) or isinstance(llbl, tuple):
|
---|
| 980 | if 0 <= stackcount < len(llbl):
|
---|
| 981 | # use user label
|
---|
| 982 | llbl = llbl[stackcount]
|
---|
| 983 | else:
|
---|
| 984 | # get default label
|
---|
| 985 | llbl = self._get_label(scan, r, self._stacking, None)
|
---|
| 986 | self._plotter.set_line(label=llbl)
|
---|
[1023] | 987 | plotit = self._plotter.plot
|
---|
| 988 | if self._hist: plotit = self._plotter.hist
|
---|
[1995] | 989 | if len(x) > 0 and not mr:
|
---|
[1146] | 990 | plotit(x,y)
|
---|
| 991 | xlim= self._minmaxx or [min(x),max(x)]
|
---|
| 992 | allxlim += xlim
|
---|
| 993 | ylim= self._minmaxy or [ma.minimum(y),ma.maximum(y)]
|
---|
| 994 | allylim += ylim
|
---|
[1819] | 995 | else:
|
---|
| 996 | xlim = self._minmaxx or []
|
---|
| 997 | allxlim += xlim
|
---|
| 998 | ylim= self._minmaxy or []
|
---|
| 999 | allylim += ylim
|
---|
[920] | 1000 | stackcount += 1
|
---|
[1981] | 1001 | a0=a
|
---|
| 1002 | b0=b
|
---|
[920] | 1003 | # last in colour stack -> autoscale x
|
---|
[1819] | 1004 | if stackcount == nstack and len(allxlim) > 0:
|
---|
[920] | 1005 | allxlim.sort()
|
---|
[1819] | 1006 | self._plotter.subplots[panelcount-1]['axes'].set_xlim([allxlim[0],allxlim[-1]])
|
---|
[1989] | 1007 | if ganged:
|
---|
| 1008 | allxlim = [allxlim[0],allxlim[-1]]
|
---|
| 1009 | else:
|
---|
| 1010 | # clear
|
---|
| 1011 | allxlim =[]
|
---|
[920] | 1012 |
|
---|
| 1013 | newpanel = False
|
---|
[1981] | 1014 | #a0=a
|
---|
| 1015 | #b0=b
|
---|
[920] | 1016 | # ignore following rows
|
---|
[1981] | 1017 | if (panelcount == n and stackcount == nstack) or (r == nr-1):
|
---|
[1018] | 1018 | # last panel -> autoscale y if ganged
|
---|
[1989] | 1019 | #if rcParams['plotter.ganged'] and len(allylim) > 0:
|
---|
| 1020 | if ganged and len(allylim) > 0:
|
---|
[1018] | 1021 | allylim.sort()
|
---|
| 1022 | self._plotter.set_limits(ylim=[allylim[0],allylim[-1]])
|
---|
[998] | 1023 | break
|
---|
[920] | 1024 | r+=1 # next row
|
---|
[1981] | 1025 |
|
---|
| 1026 | # save the current counter for multi-page plotting
|
---|
| 1027 | self._startrow = r+1
|
---|
| 1028 | self._ipanel += panelcount
|
---|
[1913] | 1029 | if self._plotter.figmgr.casabar:
|
---|
[1981] | 1030 | if self._ipanel >= nptot-1:
|
---|
[1913] | 1031 | self._plotter.figmgr.casabar.disable_next()
|
---|
| 1032 | else:
|
---|
| 1033 | self._plotter.figmgr.casabar.enable_next()
|
---|
[1981] | 1034 | if self._ipanel + 1 - panelcount > 0:
|
---|
| 1035 | self._plotter.figmgr.casabar.enable_prev()
|
---|
| 1036 | else:
|
---|
| 1037 | self._plotter.figmgr.casabar.disable_prev()
|
---|
| 1038 |
|
---|
[947] | 1039 | #reset the selector to the scantable's original
|
---|
| 1040 | scan.set_selection(savesel)
|
---|
[1824] | 1041 |
|
---|
[1819] | 1042 | #temporary switch-off for older matplotlib
|
---|
| 1043 | #if self._fp is not None:
|
---|
| 1044 | if self._fp is not None and getattr(self._plotter.figure,'findobj',False):
|
---|
[1556] | 1045 | for o in self._plotter.figure.findobj(Text):
|
---|
| 1046 | o.set_fontproperties(self._fp)
|
---|
[920] | 1047 |
|
---|
[1910] | 1048 | def _get_sortstring(self, lorders):
|
---|
| 1049 | d0 = {'s': 'SCANNO', 'b': 'BEAMNO', 'i':'IFNO',
|
---|
| 1050 | 'p': 'POLNO', 'c': 'CYCLENO', 't' : 'TIME', 'r':None, '_r':None }
|
---|
[1944] | 1051 | if not (type(lorders) == list) and not (type(lorders) == tuple):
|
---|
[1910] | 1052 | return None
|
---|
| 1053 | if len(lorders) > 0:
|
---|
| 1054 | lsorts = []
|
---|
| 1055 | for order in lorders:
|
---|
[1989] | 1056 | if order == "r":
|
---|
| 1057 | # don't sort if row panelling/stacking
|
---|
| 1058 | return None
|
---|
[1910] | 1059 | ssort = d0[order]
|
---|
| 1060 | if ssort:
|
---|
| 1061 | lsorts.append(ssort)
|
---|
| 1062 | return lsorts
|
---|
| 1063 | return None
|
---|
| 1064 |
|
---|
[1582] | 1065 | def set_selection(self, selection=None, refresh=True, **kw):
|
---|
[1819] | 1066 | """
|
---|
| 1067 | Parameters:
|
---|
| 1068 | selection: a selector object (default unset the selection)
|
---|
| 1069 | refresh: True (default) or False. If True, the plot is
|
---|
[1824] | 1070 | replotted based on the new parameter setting(s).
|
---|
[1819] | 1071 | Otherwise,the parameter(s) are set without replotting.
|
---|
| 1072 | """
|
---|
[1582] | 1073 | if selection is None:
|
---|
| 1074 | # reset
|
---|
| 1075 | if len(kw) == 0:
|
---|
| 1076 | self._selection = selector()
|
---|
| 1077 | else:
|
---|
| 1078 | # try keywords
|
---|
| 1079 | for k in kw:
|
---|
| 1080 | if k not in selector.fields:
|
---|
| 1081 | raise KeyError("Invalid selection key '%s', valid keys are %s" % (k, selector.fields))
|
---|
| 1082 | self._selection = selector(**kw)
|
---|
| 1083 | elif isinstance(selection, selector):
|
---|
| 1084 | self._selection = selection
|
---|
| 1085 | else:
|
---|
| 1086 | raise TypeError("'selection' is not of type selector")
|
---|
| 1087 |
|
---|
[1910] | 1088 | order = self._get_sortstring([self._panelling,self._stacking])
|
---|
| 1089 | if order:
|
---|
| 1090 | self._selection.set_order(order)
|
---|
[1819] | 1091 | if refresh and self._data: self.plot(self._data)
|
---|
[920] | 1092 |
|
---|
| 1093 | def _get_selected_n(self, scan):
|
---|
[1148] | 1094 | d1 = {'b': scan.getbeamnos, 's': scan.getscannos,
|
---|
[1910] | 1095 | 'i': scan.getifnos, 'p': scan.getpolnos, 't': scan.ncycle,
|
---|
[1989] | 1096 | 'r': scan.nrow}#, '_r': False}
|
---|
[1148] | 1097 | d2 = { 'b': self._selection.get_beams(),
|
---|
| 1098 | 's': self._selection.get_scans(),
|
---|
| 1099 | 'i': self._selection.get_ifs(),
|
---|
| 1100 | 'p': self._selection.get_pols(),
|
---|
[1910] | 1101 | 't': self._selection.get_cycles(),
|
---|
[1989] | 1102 | 'r': False}#, '_r': 1}
|
---|
[920] | 1103 | n = d2[self._panelling] or d1[self._panelling]()
|
---|
| 1104 | nstack = d2[self._stacking] or d1[self._stacking]()
|
---|
[1989] | 1105 | # handle row panelling/stacking
|
---|
| 1106 | if self._panelling == 'r':
|
---|
| 1107 | nstack = 1
|
---|
| 1108 | elif self._stacking == 'r':
|
---|
| 1109 | n = 1
|
---|
[920] | 1110 | return n,nstack
|
---|
| 1111 |
|
---|
| 1112 | def _get_label(self, scan, row, mode, userlabel=None):
|
---|
[1153] | 1113 | if isinstance(userlabel, list) and len(userlabel) == 0:
|
---|
| 1114 | userlabel = " "
|
---|
[947] | 1115 | pms = dict(zip(self._selection.get_pols(),self._selection.get_poltypes()))
|
---|
[920] | 1116 | if len(pms):
|
---|
| 1117 | poleval = scan._getpollabel(scan.getpol(row),pms[scan.getpol(row)])
|
---|
| 1118 | else:
|
---|
| 1119 | poleval = scan._getpollabel(scan.getpol(row),scan.poltype())
|
---|
| 1120 | d = {'b': "Beam "+str(scan.getbeam(row)),
|
---|
[1819] | 1121 | #'s': scan._getsourcename(row),
|
---|
| 1122 | 's': "Scan "+str(scan.getscan(row))+\
|
---|
| 1123 | " ("+str(scan._getsourcename(row))+")",
|
---|
[920] | 1124 | 'i': "IF"+str(scan.getif(row)),
|
---|
[964] | 1125 | 'p': poleval,
|
---|
[1910] | 1126 | 't': str(scan.get_time(row)),
|
---|
| 1127 | 'r': "row "+str(row),
|
---|
[1913] | 1128 | #'_r': str(scan.get_time(row))+",\nIF"+str(scan.getif(row))+", "+poleval+", Beam"+str(scan.getbeam(row)) }
|
---|
| 1129 | '_r': "" }
|
---|
[920] | 1130 | return userlabel or d[mode]
|
---|
[1153] | 1131 |
|
---|
[1819] | 1132 | def plotazel(self, scan=None, outfile=None):
|
---|
[1391] | 1133 | """
|
---|
[1696] | 1134 | plot azimuth and elevation versus time of a scantable
|
---|
[1391] | 1135 | """
|
---|
[1923] | 1136 | visible = rcParams['plotter.gui']
|
---|
[1696] | 1137 | from matplotlib import pylab as PL
|
---|
| 1138 | from matplotlib.dates import DateFormatter, timezone
|
---|
| 1139 | from matplotlib.dates import HourLocator, MinuteLocator,SecondLocator, DayLocator
|
---|
[1391] | 1140 | from matplotlib.ticker import MultipleLocator
|
---|
[1739] | 1141 | from numpy import array, pi
|
---|
[1923] | 1142 | if not visible or not self._visible:
|
---|
| 1143 | PL.ioff()
|
---|
| 1144 | from matplotlib.backends.backend_agg import FigureCanvasAgg
|
---|
| 1145 | PL.gcf().canvas.switch_backends(FigureCanvasAgg)
|
---|
[1819] | 1146 | self._data = scan
|
---|
| 1147 | self._outfile = outfile
|
---|
[1556] | 1148 | dates = self._data.get_time(asdatetime=True)
|
---|
[1391] | 1149 | t = PL.date2num(dates)
|
---|
| 1150 | tz = timezone('UTC')
|
---|
| 1151 | PL.cla()
|
---|
| 1152 | PL.ioff()
|
---|
| 1153 | PL.clf()
|
---|
[2037] | 1154 | # Adjust subplot margins
|
---|
| 1155 | if len(self._margins) != 6:
|
---|
| 1156 | self.set_margin(refresh=False)
|
---|
| 1157 | lef, bot, rig, top, wsp, hsp = self._margins
|
---|
[1819] | 1158 | PL.gcf().subplots_adjust(left=lef,bottom=bot,right=rig,top=top,
|
---|
| 1159 | wspace=wsp,hspace=hsp)
|
---|
[1824] | 1160 |
|
---|
[1391] | 1161 | tdel = max(t) - min(t)
|
---|
| 1162 | ax = PL.subplot(2,1,1)
|
---|
| 1163 | el = array(self._data.get_elevation())*180./pi
|
---|
| 1164 | PL.ylabel('El [deg.]')
|
---|
| 1165 | dstr = dates[0].strftime('%Y/%m/%d')
|
---|
| 1166 | if tdel > 1.0:
|
---|
| 1167 | dstr2 = dates[len(dates)-1].strftime('%Y/%m/%d')
|
---|
| 1168 | dstr = dstr + " - " + dstr2
|
---|
| 1169 | majloc = DayLocator()
|
---|
| 1170 | minloc = HourLocator(range(0,23,12))
|
---|
| 1171 | timefmt = DateFormatter("%b%d")
|
---|
[1696] | 1172 | elif tdel > 24./60.:
|
---|
| 1173 | timefmt = DateFormatter('%H:%M')
|
---|
| 1174 | majloc = HourLocator()
|
---|
| 1175 | minloc = MinuteLocator(30)
|
---|
[1391] | 1176 | else:
|
---|
[1696] | 1177 | timefmt = DateFormatter('%H:%M')
|
---|
| 1178 | majloc = MinuteLocator(interval=5)
|
---|
| 1179 | minloc = SecondLocator(30)
|
---|
| 1180 |
|
---|
[1391] | 1181 | PL.title(dstr)
|
---|
[1819] | 1182 | if tdel == 0.0:
|
---|
| 1183 | th = (t - PL.floor(t))*24.0
|
---|
| 1184 | PL.plot(th,el,'o',markersize=2, markerfacecolor='b', markeredgecolor='b')
|
---|
| 1185 | else:
|
---|
| 1186 | PL.plot_date(t,el,'o', markersize=2, markerfacecolor='b', markeredgecolor='b',tz=tz)
|
---|
| 1187 | #ax.grid(True)
|
---|
| 1188 | ax.xaxis.set_major_formatter(timefmt)
|
---|
| 1189 | ax.xaxis.set_major_locator(majloc)
|
---|
| 1190 | ax.xaxis.set_minor_locator(minloc)
|
---|
[1391] | 1191 | ax.yaxis.grid(True)
|
---|
[1819] | 1192 | yloc = MultipleLocator(30)
|
---|
| 1193 | ax.set_ylim(0,90)
|
---|
| 1194 | ax.yaxis.set_major_locator(yloc)
|
---|
[1391] | 1195 | if tdel > 1.0:
|
---|
| 1196 | labels = ax.get_xticklabels()
|
---|
| 1197 | # PL.setp(labels, fontsize=10, rotation=45)
|
---|
| 1198 | PL.setp(labels, fontsize=10)
|
---|
[1819] | 1199 |
|
---|
[1391] | 1200 | # Az plot
|
---|
| 1201 | az = array(self._data.get_azimuth())*180./pi
|
---|
| 1202 | if min(az) < 0:
|
---|
| 1203 | for irow in range(len(az)):
|
---|
| 1204 | if az[irow] < 0: az[irow] += 360.0
|
---|
| 1205 |
|
---|
[1819] | 1206 | ax2 = PL.subplot(2,1,2)
|
---|
| 1207 | #PL.xlabel('Time (UT [hour])')
|
---|
| 1208 | PL.ylabel('Az [deg.]')
|
---|
| 1209 | if tdel == 0.0:
|
---|
| 1210 | PL.plot(th,az,'o',markersize=2, markeredgecolor='b',markerfacecolor='b')
|
---|
| 1211 | else:
|
---|
| 1212 | PL.plot_date(t,az,'o', markersize=2,markeredgecolor='b',markerfacecolor='b',tz=tz)
|
---|
| 1213 | ax2.xaxis.set_major_formatter(timefmt)
|
---|
| 1214 | ax2.xaxis.set_major_locator(majloc)
|
---|
| 1215 | ax2.xaxis.set_minor_locator(minloc)
|
---|
| 1216 | #ax2.grid(True)
|
---|
| 1217 | ax2.set_ylim(0,360)
|
---|
[1696] | 1218 | ax2.yaxis.grid(True)
|
---|
[1819] | 1219 | #hfmt = DateFormatter('%H')
|
---|
| 1220 | #hloc = HourLocator()
|
---|
| 1221 | yloc = MultipleLocator(60)
|
---|
| 1222 | ax2.yaxis.set_major_locator(yloc)
|
---|
| 1223 | if tdel > 1.0:
|
---|
| 1224 | labels = ax2.get_xticklabels()
|
---|
| 1225 | PL.setp(labels, fontsize=10)
|
---|
| 1226 | PL.xlabel('Time (UT [day])')
|
---|
| 1227 | else:
|
---|
| 1228 | PL.xlabel('Time (UT [hour])')
|
---|
| 1229 |
|
---|
[1391] | 1230 | PL.ion()
|
---|
| 1231 | PL.draw()
|
---|
[1819] | 1232 | if (self._outfile is not None):
|
---|
| 1233 | PL.savefig(self._outfile)
|
---|
[1391] | 1234 |
|
---|
[1819] | 1235 | def plotpointing(self, scan=None, outfile=None):
|
---|
[1391] | 1236 | """
|
---|
| 1237 | plot telescope pointings
|
---|
| 1238 | """
|
---|
[1923] | 1239 | visible = rcParams['plotter.gui']
|
---|
[1696] | 1240 | from matplotlib import pylab as PL
|
---|
[1819] | 1241 | from numpy import array, pi
|
---|
[1923] | 1242 | if not visible or not self._visible:
|
---|
| 1243 | PL.ioff()
|
---|
| 1244 | from matplotlib.backends.backend_agg import FigureCanvasAgg
|
---|
| 1245 | PL.gcf().canvas.switch_backends(FigureCanvasAgg)
|
---|
[1819] | 1246 | self._data = scan
|
---|
| 1247 | self._outfile = outfile
|
---|
[1391] | 1248 | dir = array(self._data.get_directionval()).transpose()
|
---|
| 1249 | ra = dir[0]*180./pi
|
---|
| 1250 | dec = dir[1]*180./pi
|
---|
| 1251 | PL.cla()
|
---|
[1819] | 1252 | #PL.ioff()
|
---|
[1391] | 1253 | PL.clf()
|
---|
[2037] | 1254 | # Adjust subplot margins
|
---|
| 1255 | if len(self._margins) != 6:
|
---|
| 1256 | self.set_margin(refresh=False)
|
---|
| 1257 | lef, bot, rig, top, wsp, hsp = self._margins
|
---|
[1819] | 1258 | PL.gcf().subplots_adjust(left=lef,bottom=bot,right=rig,top=top,
|
---|
| 1259 | wspace=wsp,hspace=hsp)
|
---|
| 1260 | ax = PL.gca()
|
---|
| 1261 | #ax = PL.axes([0.1,0.1,0.8,0.8])
|
---|
| 1262 | #ax = PL.axes([0.1,0.1,0.8,0.8])
|
---|
[1391] | 1263 | ax.set_aspect('equal')
|
---|
[1696] | 1264 | PL.plot(ra, dec, 'b,')
|
---|
[1391] | 1265 | PL.xlabel('RA [deg.]')
|
---|
| 1266 | PL.ylabel('Declination [deg.]')
|
---|
| 1267 | PL.title('Telescope pointings')
|
---|
| 1268 | [xmin,xmax,ymin,ymax] = PL.axis()
|
---|
| 1269 | PL.axis([xmax,xmin,ymin,ymax])
|
---|
[1819] | 1270 | #PL.ion()
|
---|
[1391] | 1271 | PL.draw()
|
---|
[1819] | 1272 | if (self._outfile is not None):
|
---|
| 1273 | PL.savefig(self._outfile)
|
---|
| 1274 |
|
---|
| 1275 | # plot total power data
|
---|
| 1276 | # plotting in time is not yet implemented..
|
---|
[1862] | 1277 | @asaplog_post_dec
|
---|
[1819] | 1278 | def plottp(self, scan=None, outfile=None):
|
---|
| 1279 | if self._plotter.is_dead:
|
---|
| 1280 | if hasattr(self._plotter.figmgr,'casabar'):
|
---|
| 1281 | del self._plotter.figmgr.casabar
|
---|
| 1282 | self._plotter = self._newplotter()
|
---|
| 1283 | self._plotter.figmgr.casabar=self._newcasabar()
|
---|
| 1284 | self._plotter.hold()
|
---|
| 1285 | self._plotter.clear()
|
---|
| 1286 | from asap import scantable
|
---|
| 1287 | if not self._data and not scan:
|
---|
| 1288 | msg = "Input is not a scantable"
|
---|
| 1289 | raise TypeError(msg)
|
---|
| 1290 | if isinstance(scan, scantable):
|
---|
| 1291 | if self._data is not None:
|
---|
| 1292 | if scan != self._data:
|
---|
| 1293 | self._data = scan
|
---|
| 1294 | # reset
|
---|
| 1295 | self._reset()
|
---|
| 1296 | else:
|
---|
| 1297 | self._data = scan
|
---|
| 1298 | self._reset()
|
---|
| 1299 | # ranges become invalid when abcissa changes?
|
---|
| 1300 | #if self._abcunit and self._abcunit != self._data.get_unit():
|
---|
| 1301 | # self._minmaxx = None
|
---|
| 1302 | # self._minmaxy = None
|
---|
| 1303 | # self._abcunit = self._data.get_unit()
|
---|
| 1304 | # self._datamask = None
|
---|
| 1305 |
|
---|
[2037] | 1306 | # Adjust subplot margins
|
---|
| 1307 | if len(self._margins) !=6: self.set_margin(refresh=False)
|
---|
| 1308 | lef, bot, rig, top, wsp, hsp = self._margins
|
---|
[1819] | 1309 | self._plotter.figure.subplots_adjust(
|
---|
| 1310 | left=lef,bottom=bot,right=rig,top=top,wspace=wsp,hspace=hsp)
|
---|
| 1311 | if self._plotter.figmgr.casabar: self._plotter.figmgr.casabar.disable_button()
|
---|
| 1312 | self._plottp(self._data)
|
---|
| 1313 | if self._minmaxy is not None:
|
---|
| 1314 | self._plotter.set_limits(ylim=self._minmaxy)
|
---|
| 1315 | self._plotter.release()
|
---|
| 1316 | self._plotter.tidy()
|
---|
| 1317 | self._plotter.show(hardrefresh=False)
|
---|
| 1318 | return
|
---|
| 1319 |
|
---|
| 1320 | def _plottp(self,scan):
|
---|
| 1321 | """
|
---|
| 1322 | private method for plotting total power data
|
---|
| 1323 | """
|
---|
| 1324 | from numpy import ma, array, arange, logical_not
|
---|
| 1325 | r=0
|
---|
| 1326 | nr = scan.nrow()
|
---|
| 1327 | a0,b0 = -1,-1
|
---|
| 1328 | allxlim = []
|
---|
| 1329 | allylim = []
|
---|
| 1330 | y=[]
|
---|
| 1331 | self._plotter.set_panels()
|
---|
| 1332 | self._plotter.palette(0)
|
---|
| 1333 | #title
|
---|
| 1334 | #xlab = self._abcissa and self._abcissa[panelcount] \
|
---|
| 1335 | # or scan._getabcissalabel()
|
---|
| 1336 | #ylab = self._ordinate and self._ordinate[panelcount] \
|
---|
| 1337 | # or scan._get_ordinate_label()
|
---|
| 1338 | xlab = self._abcissa or 'row number' #or Time
|
---|
| 1339 | ylab = self._ordinate or scan._get_ordinate_label()
|
---|
| 1340 | self._plotter.set_axes('xlabel',xlab)
|
---|
| 1341 | self._plotter.set_axes('ylabel',ylab)
|
---|
| 1342 | lbl = self._get_label(scan, r, 's', self._title)
|
---|
| 1343 | if isinstance(lbl, list) or isinstance(lbl, tuple):
|
---|
| 1344 | # if 0 <= panelcount < len(lbl):
|
---|
| 1345 | # lbl = lbl[panelcount]
|
---|
| 1346 | # else:
|
---|
| 1347 | # get default label
|
---|
| 1348 | lbl = self._get_label(scan, r, self._panelling, None)
|
---|
| 1349 | self._plotter.set_axes('title',lbl)
|
---|
| 1350 | y=array(scan._get_column(scan._getspectrum,-1))
|
---|
| 1351 | m = array(scan._get_column(scan._getmask,-1))
|
---|
| 1352 | y = ma.masked_array(y,mask=logical_not(array(m,copy=False)))
|
---|
| 1353 | x = arange(len(y))
|
---|
| 1354 | # try to handle spectral data somewhat...
|
---|
| 1355 | l,m = y.shape
|
---|
| 1356 | if m > 1:
|
---|
| 1357 | y=y.mean(axis=1)
|
---|
| 1358 | plotit = self._plotter.plot
|
---|
| 1359 | llbl = self._get_label(scan, r, self._stacking, None)
|
---|
| 1360 | self._plotter.set_line(label=llbl)
|
---|
| 1361 | if len(x) > 0:
|
---|
| 1362 | plotit(x,y)
|
---|
| 1363 |
|
---|
| 1364 |
|
---|
| 1365 | # forwards to matplotlib.Figure.text
|
---|
| 1366 | def figtext(self, *args, **kwargs):
|
---|
| 1367 | """
|
---|
| 1368 | Add text to figure at location x,y (relative 0-1 coords).
|
---|
| 1369 | This method forwards *args and **kwargs to a Matplotlib method,
|
---|
| 1370 | matplotlib.Figure.text.
|
---|
| 1371 | See the method help for detailed information.
|
---|
| 1372 | """
|
---|
| 1373 | self._plotter.text(*args, **kwargs)
|
---|
| 1374 | # end matplotlib.Figure.text forwarding function
|
---|
| 1375 |
|
---|
| 1376 |
|
---|
| 1377 | # printing header information
|
---|
[1862] | 1378 | @asaplog_post_dec
|
---|
[1819] | 1379 | def print_header(self, plot=True, fontsize=9, logger=False, selstr='', extrastr=''):
|
---|
| 1380 | """
|
---|
| 1381 | print data (scantable) header on the plot and/or logger.
|
---|
| 1382 | Parameters:
|
---|
[1824] | 1383 | plot: whether or not print header info on the plot.
|
---|
[1819] | 1384 | fontsize: header font size (valid only plot=True)
|
---|
| 1385 | logger: whether or not print header info on the logger.
|
---|
| 1386 | selstr: additional selection string (not verified)
|
---|
| 1387 | extrastr: additional string to print (not verified)
|
---|
| 1388 | """
|
---|
[1859] | 1389 | if not plot and not logger:
|
---|
| 1390 | return
|
---|
| 1391 | if not self._data:
|
---|
| 1392 | raise RuntimeError("No scantable has been set yet.")
|
---|
[1824] | 1393 | # Now header will be printed on plot and/or logger.
|
---|
| 1394 | # Get header information and format it.
|
---|
[1819] | 1395 | ssum=self._data.__str__()
|
---|
| 1396 | # Print Observation header to the upper-left corner of plot
|
---|
| 1397 | if plot:
|
---|
| 1398 | headstr=[ssum[ssum.find('Observer:'):ssum.find('Flux Unit:')]]
|
---|
| 1399 | headstr.append(ssum[ssum.find('Beams:'):ssum.find('Observer:')]
|
---|
| 1400 | +ssum[ssum.find('Rest Freqs:'):ssum.find('Abcissa:')])
|
---|
| 1401 | if extrastr != '': headstr[0]=extrastr+'\n'+headstr[0]
|
---|
| 1402 | #headstr[1]='Data File: '+(filestr or 'unknown')+'\n'+headstr[1]
|
---|
| 1403 | ssel='***Selections***\n'+(selstr+self._data.get_selection().__str__() or 'none')
|
---|
| 1404 | headstr.append(ssel)
|
---|
| 1405 | nstcol=len(headstr)
|
---|
[1824] | 1406 |
|
---|
[1819] | 1407 | self._plotter.hold()
|
---|
| 1408 | for i in range(nstcol):
|
---|
| 1409 | self._plotter.figure.text(0.03+float(i)/nstcol,0.98,
|
---|
| 1410 | headstr[i],
|
---|
| 1411 | horizontalalignment='left',
|
---|
| 1412 | verticalalignment='top',
|
---|
| 1413 | fontsize=fontsize)
|
---|
| 1414 | import time
|
---|
| 1415 | self._plotter.figure.text(0.99,0.0,
|
---|
| 1416 | time.strftime("%a %d %b %Y %H:%M:%S %Z"),
|
---|
| 1417 | horizontalalignment='right',
|
---|
| 1418 | verticalalignment='bottom',fontsize=8)
|
---|
| 1419 | self._plotter.release()
|
---|
| 1420 | del headstr, ssel
|
---|
| 1421 | if logger:
|
---|
| 1422 | asaplog.push("----------------\n Plot Summary\n----------------")
|
---|
| 1423 | asaplog.push(extrastr)
|
---|
| 1424 | asaplog.push(ssum[ssum.find('Beams:'):])
|
---|
| 1425 | del ssum
|
---|