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