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