[1824] | 1 | from asap.parameters import rcParams |
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| 2 | from asap.selector import selector |
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| 3 | from asap.scantable import scantable |
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[1862] | 4 | from asap.logging import asaplog, asaplog_post_dec |
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[1153] | 5 | import matplotlib.axes |
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[1556] | 6 | from matplotlib.font_manager import FontProperties |
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| 7 | from matplotlib.text import Text |
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| 8 | |
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[1317] | 9 | import re |
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[203] | 10 | |
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[2150] | 11 | def new_asaplot(visible=None,**kwargs): |
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| 12 | """ |
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| 13 | Returns a new asaplot instance based on the backend settings. |
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| 14 | """ |
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| 15 | if visible == None: |
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| 16 | visible = rcParams['plotter.gui'] |
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| 17 | |
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| 18 | backend=matplotlib.get_backend() |
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| 19 | if not visible: |
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| 20 | from asap.asaplot import asaplot |
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| 21 | elif backend == 'TkAgg': |
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| 22 | from asap.asaplotgui import asaplotgui as asaplot |
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| 23 | elif backend == 'Qt4Agg': |
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| 24 | from asap.asaplotgui_qt4 import asaplotgui as asaplot |
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| 25 | elif backend == 'GTkAgg': |
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| 26 | from asap.asaplotgui_gtk import asaplotgui as asaplot |
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| 27 | else: |
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| 28 | from asap.asaplot import asaplot |
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| 29 | return asaplot(**kwargs) |
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| 30 | |
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[203] | 31 | class asapplotter: |
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[226] | 32 | """ |
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| 33 | The ASAP plotter. |
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| 34 | By default the plotter is set up to plot polarisations |
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| 35 | 'colour stacked' and scantables across panels. |
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[1858] | 36 | |
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| 37 | .. note:: |
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| 38 | |
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[226] | 39 | Currenly it only plots 'spectra' not Tsys or |
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| 40 | other variables. |
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[1858] | 41 | |
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[226] | 42 | """ |
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[1563] | 43 | def __init__(self, visible=None , **kwargs): |
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[734] | 44 | self._visible = rcParams['plotter.gui'] |
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| 45 | if visible is not None: |
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| 46 | self._visible = visible |
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[1563] | 47 | self._plotter = self._newplotter(**kwargs) |
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[1819] | 48 | # additional tool bar |
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[2173] | 49 | self._plotter.figmgr.casabar=self._new_custombar() |
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[710] | 50 | |
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[554] | 51 | self._panelling = None |
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| 52 | self._stacking = None |
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| 53 | self.set_panelling() |
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| 54 | self.set_stacking() |
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[377] | 55 | self._rows = None |
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| 56 | self._cols = None |
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[203] | 57 | self._autoplot = False |
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[525] | 58 | self._minmaxx = None |
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| 59 | self._minmaxy = None |
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[710] | 60 | self._datamask = None |
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[203] | 61 | self._data = None |
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[607] | 62 | self._lmap = None |
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[226] | 63 | self._title = None |
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[257] | 64 | self._ordinate = None |
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| 65 | self._abcissa = None |
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[709] | 66 | self._abcunit = None |
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[920] | 67 | self._usermask = [] |
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| 68 | self._maskselection = None |
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| 69 | self._selection = selector() |
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[1023] | 70 | self._hist = rcParams['plotter.histogram'] |
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[1556] | 71 | self._fp = FontProperties() |
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[2037] | 72 | self._margins = self.set_margin(refresh=False) |
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[1897] | 73 | self._offset = None |
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[1981] | 74 | self._startrow = 0 |
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| 75 | self._ipanel = -1 |
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| 76 | self._panelrows = [] |
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[2053] | 77 | self._headtext={'string': None, 'textobj': None} |
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[1023] | 78 | |
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[920] | 79 | def _translate(self, instr): |
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[1910] | 80 | keys = "s b i p t r".split() |
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[920] | 81 | if isinstance(instr, str): |
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| 82 | for key in keys: |
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| 83 | if instr.lower().startswith(key): |
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| 84 | return key |
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| 85 | return None |
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| 86 | |
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[1563] | 87 | def _newplotter(self, **kwargs): |
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[2150] | 88 | return new_asaplot(self._visible,**kwargs) |
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[710] | 89 | |
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[2173] | 90 | def _new_custombar(self): |
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[1819] | 91 | backend=matplotlib.get_backend() |
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[2168] | 92 | if not self._visible: |
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| 93 | return None |
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| 94 | elif backend == "TkAgg": |
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[2155] | 95 | from asap.customgui_tkagg import CustomToolbarTkAgg |
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[1819] | 96 | return CustomToolbarTkAgg(self) |
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[2168] | 97 | elif backend == "Qt4Agg": |
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| 98 | from asap.customgui_qt4agg import CustomToolbarQT4Agg |
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| 99 | return CustomToolbarQT4Agg(self) |
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[1995] | 100 | return None |
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[1819] | 101 | |
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[2147] | 102 | def casabar_exists(self): |
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| 103 | if not hasattr(self._plotter.figmgr,'casabar'): |
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| 104 | return False |
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| 105 | elif self._plotter.figmgr.casabar: |
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| 106 | return True |
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| 107 | return False |
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| 108 | |
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[1862] | 109 | @asaplog_post_dec |
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[935] | 110 | def plot(self, scan=None): |
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[203] | 111 | """ |
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[920] | 112 | Plot a scantable. |
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[203] | 113 | Parameters: |
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[920] | 114 | scan: a scantable |
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[203] | 115 | Note: |
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[920] | 116 | If a scantable was specified in a previous call |
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[203] | 117 | to plot, no argument has to be given to 'replot' |
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[920] | 118 | NO checking is done that the abcissas of the scantable |
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[203] | 119 | are consistent e.g. all 'channel' or all 'velocity' etc. |
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| 120 | """ |
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[1981] | 121 | self._startrow = 0 |
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| 122 | self._ipanel = -1 |
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[2056] | 123 | self._reset_header() |
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[710] | 124 | if self._plotter.is_dead: |
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[2147] | 125 | if self.casabar_exists(): |
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[1819] | 126 | del self._plotter.figmgr.casabar |
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[710] | 127 | self._plotter = self._newplotter() |
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[2173] | 128 | self._plotter.figmgr.casabar=self._new_custombar() |
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[2147] | 129 | if self.casabar_exists(): |
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[1984] | 130 | self._plotter.figmgr.casabar.set_pagecounter(1) |
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[1981] | 131 | self._panelrows = [] |
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[600] | 132 | self._plotter.hold() |
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[1945] | 133 | #self._plotter.clear() |
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[935] | 134 | if not self._data and not scan: |
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[1101] | 135 | msg = "Input is not a scantable" |
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| 136 | raise TypeError(msg) |
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[1897] | 137 | if scan: |
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| 138 | self.set_data(scan, refresh=False) |
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[920] | 139 | self._plot(self._data) |
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[709] | 140 | if self._minmaxy is not None: |
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| 141 | self._plotter.set_limits(ylim=self._minmaxy) |
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[2147] | 142 | if self.casabar_exists(): self._plotter.figmgr.casabar.enable_button() |
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[203] | 143 | self._plotter.release() |
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[1153] | 144 | self._plotter.tidy() |
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| 145 | self._plotter.show(hardrefresh=False) |
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[203] | 146 | return |
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| 147 | |
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[1572] | 148 | def gca(self): |
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| 149 | return self._plotter.figure.gca() |
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| 150 | |
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[1550] | 151 | def refresh(self): |
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[1572] | 152 | """Do a soft refresh""" |
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[1550] | 153 | self._plotter.figure.show() |
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| 154 | |
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[1555] | 155 | def create_mask(self, nwin=1, panel=0, color=None): |
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[1597] | 156 | """ |
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[1927] | 157 | Interactively define a mask. It retruns a mask that is equivalent to |
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[1597] | 158 | the one created manually with scantable.create_mask. |
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| 159 | Parameters: |
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| 160 | nwin: The number of mask windows to create interactively |
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| 161 | default is 1. |
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| 162 | panel: Which panel to use for mask selection. This is useful |
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| 163 | if different IFs are spread over panels (default 0) |
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| 164 | """ |
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[1555] | 165 | if self._data is None: |
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| 166 | return [] |
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[1547] | 167 | outmask = [] |
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[1549] | 168 | self._plotter.subplot(panel) |
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| 169 | xmin, xmax = self._plotter.axes.get_xlim() |
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[1548] | 170 | marg = 0.05*(xmax-xmin) |
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[1549] | 171 | self._plotter.axes.set_xlim(xmin-marg, xmax+marg) |
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[1550] | 172 | self.refresh() |
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[1695] | 173 | |
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[1555] | 174 | def cleanup(lines=False, texts=False, refresh=False): |
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| 175 | if lines: |
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| 176 | del self._plotter.axes.lines[-1] |
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| 177 | if texts: |
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| 178 | del self._plotter.axes.texts[-1] |
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| 179 | if refresh: |
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| 180 | self.refresh() |
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| 181 | |
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| 182 | for w in xrange(nwin): |
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[1547] | 183 | wpos = [] |
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[1695] | 184 | self.text(0.05,1.0, "Add start boundary", |
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[1555] | 185 | coords="relative", fontsize=10) |
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| 186 | point = self._plotter.get_point() |
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| 187 | cleanup(texts=True) |
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| 188 | if point is None: |
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| 189 | continue |
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| 190 | wpos.append(point[0]) |
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[1695] | 191 | self.axvline(wpos[0], color=color) |
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[1551] | 192 | self.text(0.05,1.0, "Add end boundary", coords="relative", fontsize=10) |
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[1555] | 193 | point = self._plotter.get_point() |
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| 194 | cleanup(texts=True, lines=True) |
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| 195 | if point is None: |
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| 196 | self.refresh() |
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| 197 | continue |
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| 198 | wpos.append(point[0]) |
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| 199 | self.axvspan(wpos[0], wpos[1], alpha=0.1, |
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| 200 | edgecolor=color, facecolor=color) |
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| 201 | ymin, ymax = self._plotter.axes.get_ylim() |
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[1547] | 202 | outmask.append(wpos) |
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[1153] | 203 | |
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[1555] | 204 | self._plotter.axes.set_xlim(xmin, xmax) |
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| 205 | self.refresh() |
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| 206 | if len(outmask) > 0: |
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| 207 | return self._data.create_mask(*outmask) |
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| 208 | return [] |
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| 209 | |
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[1153] | 210 | # forwards to matplotlib axes |
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| 211 | def text(self, *args, **kwargs): |
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[1547] | 212 | if kwargs.has_key("interactive"): |
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| 213 | if kwargs.pop("interactive"): |
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| 214 | pos = self._plotter.get_point() |
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| 215 | args = tuple(pos)+args |
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[1153] | 216 | self._axes_callback("text", *args, **kwargs) |
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[1547] | 217 | |
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[1358] | 218 | text.__doc__ = matplotlib.axes.Axes.text.__doc__ |
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[1559] | 219 | |
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[1153] | 220 | def arrow(self, *args, **kwargs): |
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[1547] | 221 | if kwargs.has_key("interactive"): |
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| 222 | if kwargs.pop("interactive"): |
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| 223 | pos = self._plotter.get_region() |
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| 224 | dpos = (pos[0][0], pos[0][1], |
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| 225 | pos[1][0]-pos[0][0], |
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| 226 | pos[1][1] - pos[0][1]) |
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| 227 | args = dpos + args |
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[1153] | 228 | self._axes_callback("arrow", *args, **kwargs) |
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[1547] | 229 | |
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[1358] | 230 | arrow.__doc__ = matplotlib.axes.Axes.arrow.__doc__ |
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[1559] | 231 | |
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| 232 | def annotate(self, text, xy=None, xytext=None, **kwargs): |
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| 233 | if kwargs.has_key("interactive"): |
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| 234 | if kwargs.pop("interactive"): |
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| 235 | xy = self._plotter.get_point() |
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| 236 | xytext = self._plotter.get_point() |
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| 237 | if not kwargs.has_key("arrowprops"): |
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| 238 | kwargs["arrowprops"] = dict(arrowstyle="->") |
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| 239 | self._axes_callback("annotate", text, xy, xytext, **kwargs) |
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| 240 | |
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| 241 | annotate.__doc__ = matplotlib.axes.Axes.annotate.__doc__ |
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| 242 | |
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[1153] | 243 | def axvline(self, *args, **kwargs): |
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[1547] | 244 | if kwargs.has_key("interactive"): |
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| 245 | if kwargs.pop("interactive"): |
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| 246 | pos = self._plotter.get_point() |
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| 247 | args = (pos[0],)+args |
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[1153] | 248 | self._axes_callback("axvline", *args, **kwargs) |
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[1559] | 249 | |
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[1358] | 250 | axvline.__doc__ = matplotlib.axes.Axes.axvline.__doc__ |
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[1547] | 251 | |
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[1153] | 252 | def axhline(self, *args, **kwargs): |
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[1547] | 253 | if kwargs.has_key("interactive"): |
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| 254 | if kwargs.pop("interactive"): |
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| 255 | pos = self._plotter.get_point() |
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| 256 | args = (pos[1],)+args |
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[1153] | 257 | self._axes_callback("axhline", *args, **kwargs) |
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[1559] | 258 | |
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[1358] | 259 | axhline.__doc__ = matplotlib.axes.Axes.axhline.__doc__ |
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[1547] | 260 | |
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[1153] | 261 | def axvspan(self, *args, **kwargs): |
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[1547] | 262 | if kwargs.has_key("interactive"): |
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| 263 | if kwargs.pop("interactive"): |
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| 264 | pos = self._plotter.get_region() |
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| 265 | dpos = (pos[0][0], pos[1][0]) |
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| 266 | args = dpos + args |
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[1153] | 267 | self._axes_callback("axvspan", *args, **kwargs) |
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| 268 | # hack to preventy mpl from redrawing the patch |
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| 269 | # it seem to convert the patch into lines on every draw. |
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| 270 | # This doesn't happen in a test script??? |
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[1547] | 271 | #del self._plotter.axes.patches[-1] |
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| 272 | |
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[1358] | 273 | axvspan.__doc__ = matplotlib.axes.Axes.axvspan.__doc__ |
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[1232] | 274 | |
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[1153] | 275 | def axhspan(self, *args, **kwargs): |
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[1547] | 276 | if kwargs.has_key("interactive"): |
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| 277 | if kwargs.pop("interactive"): |
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| 278 | pos = self._plotter.get_region() |
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| 279 | dpos = (pos[0][1], pos[1][1]) |
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| 280 | args = dpos + args |
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[1232] | 281 | self._axes_callback("axhspan", *args, **kwargs) |
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[1153] | 282 | # hack to preventy mpl from redrawing the patch |
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| 283 | # it seem to convert the patch into lines on every draw. |
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| 284 | # This doesn't happen in a test script??? |
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[1547] | 285 | #del self._plotter.axes.patches[-1] |
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[1559] | 286 | |
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[1358] | 287 | axhspan.__doc__ = matplotlib.axes.Axes.axhspan.__doc__ |
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[1153] | 288 | |
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| 289 | def _axes_callback(self, axesfunc, *args, **kwargs): |
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| 290 | panel = 0 |
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| 291 | if kwargs.has_key("panel"): |
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| 292 | panel = kwargs.pop("panel") |
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| 293 | coords = None |
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| 294 | if kwargs.has_key("coords"): |
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| 295 | coords = kwargs.pop("coords") |
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| 296 | if coords.lower() == 'world': |
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| 297 | kwargs["transform"] = self._plotter.axes.transData |
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| 298 | elif coords.lower() == 'relative': |
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| 299 | kwargs["transform"] = self._plotter.axes.transAxes |
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| 300 | self._plotter.subplot(panel) |
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| 301 | self._plotter.axes.set_autoscale_on(False) |
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| 302 | getattr(self._plotter.axes, axesfunc)(*args, **kwargs) |
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| 303 | self._plotter.show(False) |
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| 304 | self._plotter.axes.set_autoscale_on(True) |
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| 305 | # end matplotlib.axes fowarding functions |
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| 306 | |
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[1862] | 307 | @asaplog_post_dec |
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[1819] | 308 | def set_data(self, scan, refresh=True): |
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| 309 | """ |
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[1824] | 310 | Set a scantable to plot. |
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[1819] | 311 | Parameters: |
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| 312 | scan: a scantable |
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| 313 | refresh: True (default) or False. If True, the plot is |
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[1824] | 314 | replotted based on the new parameter setting(s). |
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[1819] | 315 | Otherwise,the parameter(s) are set without replotting. |
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| 316 | Note: |
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| 317 | The user specified masks and data selections will be reset |
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| 318 | if a new scantable is set. This method should be called before |
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[1824] | 319 | setting data selections (set_selection) and/or masks (set_mask). |
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[1819] | 320 | """ |
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| 321 | from asap import scantable |
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| 322 | if isinstance(scan, scantable): |
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| 323 | if self._data is not None: |
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| 324 | if scan != self._data: |
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[2123] | 325 | del self._data |
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[1819] | 326 | self._data = scan |
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| 327 | # reset |
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| 328 | self._reset() |
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[1897] | 329 | msg = "A new scantable is set to the plotter. "\ |
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| 330 | "The masks and data selections are reset." |
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[1819] | 331 | asaplog.push( msg ) |
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| 332 | else: |
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| 333 | self._data = scan |
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| 334 | self._reset() |
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| 335 | else: |
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| 336 | msg = "Input is not a scantable" |
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| 337 | raise TypeError(msg) |
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[1547] | 338 | |
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[1819] | 339 | # ranges become invalid when unit changes |
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| 340 | if self._abcunit and self._abcunit != self._data.get_unit(): |
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| 341 | self._minmaxx = None |
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| 342 | self._minmaxy = None |
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| 343 | self._abcunit = self._data.get_unit() |
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| 344 | self._datamask = None |
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| 345 | if refresh: self.plot() |
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| 346 | |
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[1862] | 347 | @asaplog_post_dec |
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[1819] | 348 | def set_mode(self, stacking=None, panelling=None, refresh=True): |
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[203] | 349 | """ |
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[377] | 350 | Set the plots look and feel, i.e. what you want to see on the plot. |
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[203] | 351 | Parameters: |
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| 352 | stacking: tell the plotter which variable to plot |
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[1217] | 353 | as line colour overlays (default 'pol') |
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[203] | 354 | panelling: tell the plotter which variable to plot |
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| 355 | across multiple panels (default 'scan' |
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[1819] | 356 | refresh: True (default) or False. If True, the plot is |
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[1824] | 357 | replotted based on the new parameter setting(s). |
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[1819] | 358 | Otherwise,the parameter(s) are set without replotting. |
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[203] | 359 | Note: |
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| 360 | Valid modes are: |
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| 361 | 'beam' 'Beam' 'b': Beams |
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| 362 | 'if' 'IF' 'i': IFs |
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| 363 | 'pol' 'Pol' 'p': Polarisations |
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| 364 | 'scan' 'Scan' 's': Scans |
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| 365 | 'time' 'Time' 't': Times |
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[1989] | 366 | 'row' 'Row' 'r': Rows |
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| 367 | When either 'stacking' or 'panelling' is set to 'row', |
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| 368 | the other parameter setting is ignored. |
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[203] | 369 | """ |
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[753] | 370 | msg = "Invalid mode" |
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| 371 | if not self.set_panelling(panelling) or \ |
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| 372 | not self.set_stacking(stacking): |
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[1859] | 373 | raise TypeError(msg) |
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[1989] | 374 | #if self._panelling == 'r': |
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| 375 | # self._stacking = '_r' |
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| 376 | #if self._stacking == 'r': |
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| 377 | # self._panelling = '_r' |
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[1819] | 378 | if refresh and self._data: self.plot(self._data) |
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[203] | 379 | return |
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| 380 | |
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[554] | 381 | def set_panelling(self, what=None): |
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[1858] | 382 | """Set the 'panelling' mode i.e. which type of spectra should be |
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| 383 | spread across different panels. |
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| 384 | """ |
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| 385 | |
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[554] | 386 | mode = what |
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| 387 | if mode is None: |
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| 388 | mode = rcParams['plotter.panelling'] |
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| 389 | md = self._translate(mode) |
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[203] | 390 | if md: |
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[554] | 391 | self._panelling = md |
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[226] | 392 | self._title = None |
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[1989] | 393 | #if md == 'r': |
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| 394 | # self._stacking = '_r' |
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[1981] | 395 | # you need to reset counters for multi page plotting |
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| 396 | self._reset_counters() |
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[203] | 397 | return True |
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| 398 | return False |
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| 399 | |
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[1819] | 400 | def set_layout(self,rows=None,cols=None,refresh=True): |
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[377] | 401 | """ |
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| 402 | Set the multi-panel layout, i.e. how many rows and columns plots |
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| 403 | are visible. |
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| 404 | Parameters: |
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| 405 | rows: The number of rows of plots |
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| 406 | cols: The number of columns of plots |
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[1819] | 407 | refresh: True (default) or False. If True, the plot is |
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[1824] | 408 | replotted based on the new parameter setting(s). |
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[1819] | 409 | Otherwise,the parameter(s) are set without replotting. |
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[377] | 410 | Note: |
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| 411 | If no argument is given, the potter reverts to its auto-plot |
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| 412 | behaviour. |
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| 413 | """ |
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| 414 | self._rows = rows |
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| 415 | self._cols = cols |
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[1819] | 416 | if refresh and self._data: self.plot(self._data) |
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[377] | 417 | return |
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| 418 | |
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[709] | 419 | def set_stacking(self, what=None): |
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[1858] | 420 | """Set the 'stacking' mode i.e. which type of spectra should be |
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| 421 | overlayed. |
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| 422 | """ |
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[554] | 423 | mode = what |
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[709] | 424 | if mode is None: |
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| 425 | mode = rcParams['plotter.stacking'] |
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[554] | 426 | md = self._translate(mode) |
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[203] | 427 | if md: |
---|
| 428 | self._stacking = md |
---|
[226] | 429 | self._lmap = None |
---|
[1989] | 430 | #if md == 'r': |
---|
| 431 | # self._panelling = '_r' |
---|
[1981] | 432 | # you need to reset counters for multi page plotting |
---|
| 433 | self._reset_counters() |
---|
[203] | 434 | return True |
---|
| 435 | return False |
---|
| 436 | |
---|
[1981] | 437 | def _reset_counters(self): |
---|
| 438 | self._startrow = 0 |
---|
| 439 | self._ipanel = -1 |
---|
| 440 | self._panelrows = [] |
---|
| 441 | |
---|
[1897] | 442 | def set_range(self,xstart=None,xend=None,ystart=None,yend=None,refresh=True, offset=None): |
---|
[203] | 443 | """ |
---|
| 444 | Set the range of interest on the abcissa of the plot |
---|
| 445 | Parameters: |
---|
[525] | 446 | [x,y]start,[x,y]end: The start and end points of the 'zoom' window |
---|
[1819] | 447 | refresh: True (default) or False. If True, the plot is |
---|
[1824] | 448 | replotted based on the new parameter setting(s). |
---|
[1819] | 449 | Otherwise,the parameter(s) are set without replotting. |
---|
[1897] | 450 | offset: shift the abcissa by the given amount. The abcissa label will |
---|
| 451 | have '(relative)' appended to it. |
---|
[203] | 452 | Note: |
---|
| 453 | These become non-sensical when the unit changes. |
---|
| 454 | use plotter.set_range() without parameters to reset |
---|
| 455 | |
---|
| 456 | """ |
---|
[1897] | 457 | self._offset = offset |
---|
[525] | 458 | if xstart is None and xend is None: |
---|
| 459 | self._minmaxx = None |
---|
[600] | 460 | else: |
---|
| 461 | self._minmaxx = [xstart,xend] |
---|
[525] | 462 | if ystart is None and yend is None: |
---|
| 463 | self._minmaxy = None |
---|
[600] | 464 | else: |
---|
[709] | 465 | self._minmaxy = [ystart,yend] |
---|
[1819] | 466 | if refresh and self._data: self.plot(self._data) |
---|
[203] | 467 | return |
---|
[709] | 468 | |
---|
[1819] | 469 | def set_legend(self, mp=None, fontsize = None, mode = 0, refresh=True): |
---|
[203] | 470 | """ |
---|
| 471 | Specify a mapping for the legend instead of using the default |
---|
| 472 | indices: |
---|
| 473 | Parameters: |
---|
[1101] | 474 | mp: a list of 'strings'. This should have the same length |
---|
| 475 | as the number of elements on the legend and then maps |
---|
| 476 | to the indeces in order. It is possible to uses latex |
---|
| 477 | math expression. These have to be enclosed in r'', |
---|
| 478 | e.g. r'$x^{2}$' |
---|
| 479 | fontsize: The font size of the label (default None) |
---|
| 480 | mode: where to display the legend |
---|
| 481 | Any other value for loc else disables the legend: |
---|
[1096] | 482 | 0: auto |
---|
| 483 | 1: upper right |
---|
| 484 | 2: upper left |
---|
| 485 | 3: lower left |
---|
| 486 | 4: lower right |
---|
| 487 | 5: right |
---|
| 488 | 6: center left |
---|
| 489 | 7: center right |
---|
| 490 | 8: lower center |
---|
| 491 | 9: upper center |
---|
| 492 | 10: center |
---|
[1819] | 493 | refresh: True (default) or False. If True, the plot is |
---|
[1824] | 494 | replotted based on the new parameter setting(s). |
---|
[1819] | 495 | Otherwise,the parameter(s) are set without replotting. |
---|
[203] | 496 | |
---|
| 497 | Example: |
---|
[485] | 498 | If the data has two IFs/rest frequencies with index 0 and 1 |
---|
[203] | 499 | for CO and SiO: |
---|
| 500 | plotter.set_stacking('i') |
---|
[710] | 501 | plotter.set_legend(['CO','SiO']) |
---|
[203] | 502 | plotter.plot() |
---|
[710] | 503 | plotter.set_legend([r'$^{12}CO$', r'SiO']) |
---|
[203] | 504 | """ |
---|
| 505 | self._lmap = mp |
---|
[1096] | 506 | self._plotter.legend(mode) |
---|
[1101] | 507 | if isinstance(fontsize, int): |
---|
| 508 | from matplotlib import rc as rcp |
---|
| 509 | rcp('legend', fontsize=fontsize) |
---|
[1819] | 510 | if refresh and self._data: self.plot(self._data) |
---|
[226] | 511 | return |
---|
| 512 | |
---|
[1819] | 513 | def set_title(self, title=None, fontsize=None, refresh=True): |
---|
[710] | 514 | """ |
---|
| 515 | Set the title of the plot. If multiple panels are plotted, |
---|
| 516 | multiple titles have to be specified. |
---|
[1819] | 517 | Parameters: |
---|
| 518 | refresh: True (default) or False. If True, the plot is |
---|
[1824] | 519 | replotted based on the new parameter setting(s). |
---|
[1819] | 520 | Otherwise,the parameter(s) are set without replotting. |
---|
[710] | 521 | Example: |
---|
| 522 | # two panels are visible on the plotter |
---|
| 523 | plotter.set_title(["First Panel","Second Panel"]) |
---|
| 524 | """ |
---|
[226] | 525 | self._title = title |
---|
[1101] | 526 | if isinstance(fontsize, int): |
---|
| 527 | from matplotlib import rc as rcp |
---|
| 528 | rcp('axes', titlesize=fontsize) |
---|
[1819] | 529 | if refresh and self._data: self.plot(self._data) |
---|
[226] | 530 | return |
---|
| 531 | |
---|
[1819] | 532 | def set_ordinate(self, ordinate=None, fontsize=None, refresh=True): |
---|
[710] | 533 | """ |
---|
| 534 | Set the y-axis label of the plot. If multiple panels are plotted, |
---|
| 535 | multiple labels have to be specified. |
---|
[1021] | 536 | Parameters: |
---|
| 537 | ordinate: a list of ordinate labels. None (default) let |
---|
| 538 | data determine the labels |
---|
[1819] | 539 | refresh: True (default) or False. If True, the plot is |
---|
[1824] | 540 | replotted based on the new parameter setting(s). |
---|
[1819] | 541 | Otherwise,the parameter(s) are set without replotting. |
---|
[710] | 542 | Example: |
---|
| 543 | # two panels are visible on the plotter |
---|
| 544 | plotter.set_ordinate(["First Y-Axis","Second Y-Axis"]) |
---|
| 545 | """ |
---|
[257] | 546 | self._ordinate = ordinate |
---|
[1101] | 547 | if isinstance(fontsize, int): |
---|
| 548 | from matplotlib import rc as rcp |
---|
| 549 | rcp('axes', labelsize=fontsize) |
---|
| 550 | rcp('ytick', labelsize=fontsize) |
---|
[1819] | 551 | if refresh and self._data: self.plot(self._data) |
---|
[257] | 552 | return |
---|
| 553 | |
---|
[1819] | 554 | def set_abcissa(self, abcissa=None, fontsize=None, refresh=True): |
---|
[710] | 555 | """ |
---|
| 556 | Set the x-axis label of the plot. If multiple panels are plotted, |
---|
| 557 | multiple labels have to be specified. |
---|
[1021] | 558 | Parameters: |
---|
| 559 | abcissa: a list of abcissa labels. None (default) let |
---|
| 560 | data determine the labels |
---|
[1819] | 561 | refresh: True (default) or False. If True, the plot is |
---|
[1824] | 562 | replotted based on the new parameter setting(s). |
---|
[1819] | 563 | Otherwise,the parameter(s) are set without replotting. |
---|
[710] | 564 | Example: |
---|
| 565 | # two panels are visible on the plotter |
---|
| 566 | plotter.set_ordinate(["First X-Axis","Second X-Axis"]) |
---|
| 567 | """ |
---|
[257] | 568 | self._abcissa = abcissa |
---|
[1101] | 569 | if isinstance(fontsize, int): |
---|
| 570 | from matplotlib import rc as rcp |
---|
| 571 | rcp('axes', labelsize=fontsize) |
---|
| 572 | rcp('xtick', labelsize=fontsize) |
---|
[1819] | 573 | if refresh and self._data: self.plot(self._data) |
---|
[257] | 574 | return |
---|
| 575 | |
---|
[1819] | 576 | def set_colors(self, colmap, refresh=True): |
---|
[377] | 577 | """ |
---|
[1217] | 578 | Set the colours to be used. The plotter will cycle through |
---|
| 579 | these colours when lines are overlaid (stacking mode). |
---|
[1021] | 580 | Parameters: |
---|
[1217] | 581 | colmap: a list of colour names |
---|
[1819] | 582 | refresh: True (default) or False. If True, the plot is |
---|
[1824] | 583 | replotted based on the new parameter setting(s). |
---|
[1819] | 584 | Otherwise,the parameter(s) are set without replotting. |
---|
[710] | 585 | Example: |
---|
| 586 | plotter.set_colors("red green blue") |
---|
| 587 | # If for example four lines are overlaid e.g I Q U V |
---|
| 588 | # 'I' will be 'red', 'Q' will be 'green', U will be 'blue' |
---|
| 589 | # and 'V' will be 'red' again. |
---|
| 590 | """ |
---|
[1217] | 591 | if isinstance(colmap,str): |
---|
| 592 | colmap = colmap.split() |
---|
| 593 | self._plotter.palette(0, colormap=colmap) |
---|
[1819] | 594 | if refresh and self._data: self.plot(self._data) |
---|
[710] | 595 | |
---|
[1217] | 596 | # alias for english speakers |
---|
| 597 | set_colours = set_colors |
---|
| 598 | |
---|
[1819] | 599 | def set_histogram(self, hist=True, linewidth=None, refresh=True): |
---|
[1021] | 600 | """ |
---|
| 601 | Enable/Disable histogram-like plotting. |
---|
| 602 | Parameters: |
---|
| 603 | hist: True (default) or False. The fisrt default |
---|
| 604 | is taken from the .asaprc setting |
---|
| 605 | plotter.histogram |
---|
[1819] | 606 | refresh: True (default) or False. If True, the plot is |
---|
[1824] | 607 | replotted based on the new parameter setting(s). |
---|
[1819] | 608 | Otherwise,the parameter(s) are set without replotting. |
---|
[1021] | 609 | """ |
---|
[1023] | 610 | self._hist = hist |
---|
[1101] | 611 | if isinstance(linewidth, float) or isinstance(linewidth, int): |
---|
| 612 | from matplotlib import rc as rcp |
---|
| 613 | rcp('lines', linewidth=linewidth) |
---|
[1819] | 614 | if refresh and self._data: self.plot(self._data) |
---|
[1023] | 615 | |
---|
[1819] | 616 | def set_linestyles(self, linestyles=None, linewidth=None, refresh=True): |
---|
[710] | 617 | """ |
---|
[734] | 618 | Set the linestyles to be used. The plotter will cycle through |
---|
| 619 | these linestyles when lines are overlaid (stacking mode) AND |
---|
| 620 | only one color has been set. |
---|
[710] | 621 | Parameters: |
---|
| 622 | linestyles: a list of linestyles to use. |
---|
| 623 | 'line', 'dashed', 'dotted', 'dashdot', |
---|
| 624 | 'dashdotdot' and 'dashdashdot' are |
---|
| 625 | possible |
---|
[1819] | 626 | refresh: True (default) or False. If True, the plot is |
---|
[1824] | 627 | replotted based on the new parameter setting(s). |
---|
[1819] | 628 | Otherwise,the parameter(s) are set without replotting. |
---|
[710] | 629 | Example: |
---|
| 630 | plotter.set_colors("black") |
---|
| 631 | plotter.set_linestyles("line dashed dotted dashdot") |
---|
| 632 | # If for example four lines are overlaid e.g I Q U V |
---|
| 633 | # 'I' will be 'solid', 'Q' will be 'dashed', |
---|
| 634 | # U will be 'dotted' and 'V' will be 'dashdot'. |
---|
| 635 | """ |
---|
| 636 | if isinstance(linestyles,str): |
---|
| 637 | linestyles = linestyles.split() |
---|
| 638 | self._plotter.palette(color=0,linestyle=0,linestyles=linestyles) |
---|
[1101] | 639 | if isinstance(linewidth, float) or isinstance(linewidth, int): |
---|
| 640 | from matplotlib import rc as rcp |
---|
| 641 | rcp('lines', linewidth=linewidth) |
---|
[1819] | 642 | if refresh and self._data: self.plot(self._data) |
---|
[710] | 643 | |
---|
[1819] | 644 | def set_font(self, refresh=True,**kwargs): |
---|
[1101] | 645 | """ |
---|
| 646 | Set font properties. |
---|
| 647 | Parameters: |
---|
| 648 | family: one of 'sans-serif', 'serif', 'cursive', 'fantasy', 'monospace' |
---|
| 649 | style: one of 'normal' (or 'roman'), 'italic' or 'oblique' |
---|
| 650 | weight: one of 'normal or 'bold' |
---|
| 651 | size: the 'general' font size, individual elements can be adjusted |
---|
| 652 | seperately |
---|
[1819] | 653 | refresh: True (default) or False. If True, the plot is |
---|
[1824] | 654 | replotted based on the new parameter setting(s). |
---|
[1819] | 655 | Otherwise,the parameter(s) are set without replotting. |
---|
[1101] | 656 | """ |
---|
| 657 | from matplotlib import rc as rcp |
---|
[1547] | 658 | fdict = {} |
---|
| 659 | for k,v in kwargs.iteritems(): |
---|
| 660 | if v: |
---|
| 661 | fdict[k] = v |
---|
[1556] | 662 | self._fp = FontProperties(**fdict) |
---|
[1819] | 663 | if refresh and self._data: self.plot(self._data) |
---|
[1101] | 664 | |
---|
[2037] | 665 | def set_margin(self,margin=[],refresh=True): |
---|
[1819] | 666 | """ |
---|
[2037] | 667 | Set margins between subplots and plot edges. |
---|
[1819] | 668 | Parameters: |
---|
[2037] | 669 | margin: a list of margins in figure coordinate (0-1), |
---|
[1824] | 670 | i.e., fraction of the figure width or height. |
---|
[1819] | 671 | The order of elements should be: |
---|
| 672 | [left, bottom, right, top, horizontal space btw panels, |
---|
[1824] | 673 | vertical space btw panels]. |
---|
[1819] | 674 | refresh: True (default) or False. If True, the plot is |
---|
[1824] | 675 | replotted based on the new parameter setting(s). |
---|
[1819] | 676 | Otherwise,the parameter(s) are set without replotting. |
---|
| 677 | Note |
---|
[2037] | 678 | * When margin is not specified, the values are reset to the defaults |
---|
[1819] | 679 | of matplotlib. |
---|
[1824] | 680 | * If any element is set to be None, the current value is adopted. |
---|
[1819] | 681 | """ |
---|
[2037] | 682 | if margin == []: self._margins=self._reset_margin() |
---|
[1824] | 683 | else: |
---|
[2037] | 684 | self._margins=[None]*6 |
---|
| 685 | self._margins[0:len(margin)]=margin |
---|
| 686 | #print "panel margin set to ",self._margins |
---|
[1819] | 687 | if refresh and self._data: self.plot(self._data) |
---|
| 688 | |
---|
[2037] | 689 | def _reset_margin(self): |
---|
[1819] | 690 | ks=map(lambda x: 'figure.subplot.'+x, |
---|
| 691 | ['left','bottom','right','top','hspace','wspace']) |
---|
| 692 | return map(matplotlib.rcParams.get,ks) |
---|
| 693 | |
---|
[1259] | 694 | def plot_lines(self, linecat=None, doppler=0.0, deltachan=10, rotate=90.0, |
---|
[1146] | 695 | location=None): |
---|
| 696 | """ |
---|
[1158] | 697 | Plot a line catalog. |
---|
| 698 | Parameters: |
---|
| 699 | linecat: the linecatalog to plot |
---|
[1168] | 700 | doppler: the velocity shift to apply to the frequencies |
---|
[1158] | 701 | deltachan: the number of channels to include each side of the |
---|
| 702 | line to determine a local maximum/minimum |
---|
[1927] | 703 | rotate: the rotation (in degrees) for the text label (default 90.0) |
---|
[1158] | 704 | location: the location of the line annotation from the 'top', |
---|
| 705 | 'bottom' or alternate (None - the default) |
---|
[1165] | 706 | Notes: |
---|
| 707 | If the spectrum is flagged no line will be drawn in that location. |
---|
[1146] | 708 | """ |
---|
[1259] | 709 | if not self._data: |
---|
| 710 | raise RuntimeError("No scantable has been plotted yet.") |
---|
[1146] | 711 | from asap._asap import linecatalog |
---|
[1259] | 712 | if not isinstance(linecat, linecatalog): |
---|
| 713 | raise ValueError("'linecat' isn't of type linecatalog.") |
---|
| 714 | if not self._data.get_unit().endswith("Hz"): |
---|
| 715 | raise RuntimeError("Can only overlay linecatalogs when data is in frequency.") |
---|
[1739] | 716 | from numpy import ma |
---|
[1146] | 717 | for j in range(len(self._plotter.subplots)): |
---|
| 718 | self._plotter.subplot(j) |
---|
| 719 | lims = self._plotter.axes.get_xlim() |
---|
[1153] | 720 | for row in range(linecat.nrow()): |
---|
[1259] | 721 | # get_frequency returns MHz |
---|
| 722 | base = { "GHz": 1000.0, "MHz": 1.0, "Hz": 1.0e-6 } |
---|
| 723 | restf = linecat.get_frequency(row)/base[self._data.get_unit()] |
---|
[1165] | 724 | c = 299792.458 |
---|
[1174] | 725 | freq = restf*(1.0-doppler/c) |
---|
[1146] | 726 | if lims[0] < freq < lims[1]: |
---|
| 727 | if location is None: |
---|
| 728 | loc = 'bottom' |
---|
[1153] | 729 | if row%2: loc='top' |
---|
[1146] | 730 | else: loc = location |
---|
[1153] | 731 | maxys = [] |
---|
| 732 | for line in self._plotter.axes.lines: |
---|
| 733 | v = line._x |
---|
| 734 | asc = v[0] < v[-1] |
---|
| 735 | |
---|
| 736 | idx = None |
---|
| 737 | if not asc: |
---|
| 738 | if v[len(v)-1] <= freq <= v[0]: |
---|
| 739 | i = len(v)-1 |
---|
| 740 | while i>=0 and v[i] < freq: |
---|
| 741 | idx = i |
---|
| 742 | i-=1 |
---|
| 743 | else: |
---|
| 744 | if v[0] <= freq <= v[len(v)-1]: |
---|
| 745 | i = 0 |
---|
| 746 | while i<len(v) and v[i] < freq: |
---|
| 747 | idx = i |
---|
| 748 | i+=1 |
---|
| 749 | if idx is not None: |
---|
| 750 | lower = idx - deltachan |
---|
| 751 | upper = idx + deltachan |
---|
| 752 | if lower < 0: lower = 0 |
---|
| 753 | if upper > len(v): upper = len(v) |
---|
| 754 | s = slice(lower, upper) |
---|
[1167] | 755 | y = line._y[s] |
---|
[1165] | 756 | maxy = ma.maximum(y) |
---|
| 757 | if isinstance( maxy, float): |
---|
| 758 | maxys.append(maxy) |
---|
[1164] | 759 | if len(maxys): |
---|
| 760 | peak = max(maxys) |
---|
[1165] | 761 | if peak > self._plotter.axes.get_ylim()[1]: |
---|
| 762 | loc = 'bottom' |
---|
[1164] | 763 | else: |
---|
| 764 | continue |
---|
[1157] | 765 | self._plotter.vline_with_label(freq, peak, |
---|
| 766 | linecat.get_name(row), |
---|
| 767 | location=loc, rotate=rotate) |
---|
[1153] | 768 | self._plotter.show(hardrefresh=False) |
---|
[1146] | 769 | |
---|
[1153] | 770 | |
---|
[710] | 771 | def save(self, filename=None, orientation=None, dpi=None): |
---|
| 772 | """ |
---|
[1927] | 773 | Save the plot to a file. The known formats are 'png', 'ps', 'eps'. |
---|
[377] | 774 | Parameters: |
---|
| 775 | filename: The name of the output file. This is optional |
---|
| 776 | and autodetects the image format from the file |
---|
| 777 | suffix. If non filename is specified a file |
---|
| 778 | called 'yyyymmdd_hhmmss.png' is created in the |
---|
| 779 | current directory. |
---|
[709] | 780 | orientation: optional parameter for postscript only (not eps). |
---|
| 781 | 'landscape', 'portrait' or None (default) are valid. |
---|
| 782 | If None is choosen for 'ps' output, the plot is |
---|
| 783 | automatically oriented to fill the page. |
---|
[710] | 784 | dpi: The dpi of the output non-ps plot |
---|
[377] | 785 | """ |
---|
[709] | 786 | self._plotter.save(filename,orientation,dpi) |
---|
[377] | 787 | return |
---|
[709] | 788 | |
---|
[1862] | 789 | @asaplog_post_dec |
---|
[1819] | 790 | def set_mask(self, mask=None, selection=None, refresh=True): |
---|
[525] | 791 | """ |
---|
[734] | 792 | Set a plotting mask for a specific polarization. |
---|
| 793 | This is useful for masking out "noise" Pangle outside a source. |
---|
| 794 | Parameters: |
---|
[920] | 795 | mask: a mask from scantable.create_mask |
---|
| 796 | selection: the spectra to apply the mask to. |
---|
[1819] | 797 | refresh: True (default) or False. If True, the plot is |
---|
[1824] | 798 | replotted based on the new parameter setting(s). |
---|
[1819] | 799 | Otherwise,the parameter(s) are set without replotting. |
---|
[734] | 800 | Example: |
---|
[920] | 801 | select = selector() |
---|
| 802 | select.setpolstrings("Pangle") |
---|
| 803 | plotter.set_mask(mymask, select) |
---|
[734] | 804 | """ |
---|
[710] | 805 | if not self._data: |
---|
[920] | 806 | msg = "Can only set mask after a first call to plot()" |
---|
[1859] | 807 | raise RuntimeError(msg) |
---|
[920] | 808 | if len(mask): |
---|
| 809 | if isinstance(mask, list) or isinstance(mask, tuple): |
---|
| 810 | self._usermask = array(mask) |
---|
[710] | 811 | else: |
---|
[920] | 812 | self._usermask = mask |
---|
| 813 | if mask is None and selection is None: |
---|
| 814 | self._usermask = [] |
---|
| 815 | self._maskselection = None |
---|
| 816 | if isinstance(selection, selector): |
---|
[947] | 817 | self._maskselection = {'b': selection.get_beams(), |
---|
| 818 | 's': selection.get_scans(), |
---|
| 819 | 'i': selection.get_ifs(), |
---|
| 820 | 'p': selection.get_pols(), |
---|
[920] | 821 | 't': [] } |
---|
[710] | 822 | else: |
---|
[920] | 823 | self._maskselection = None |
---|
[1819] | 824 | if refresh: self.plot(self._data) |
---|
[710] | 825 | |
---|
[709] | 826 | def _slice_indeces(self, data): |
---|
| 827 | mn = self._minmaxx[0] |
---|
| 828 | mx = self._minmaxx[1] |
---|
| 829 | asc = data[0] < data[-1] |
---|
| 830 | start=0 |
---|
| 831 | end = len(data)-1 |
---|
| 832 | inc = 1 |
---|
| 833 | if not asc: |
---|
| 834 | start = len(data)-1 |
---|
| 835 | end = 0 |
---|
| 836 | inc = -1 |
---|
| 837 | # find min index |
---|
[1819] | 838 | #while start > 0 and data[start] < mn: |
---|
| 839 | # start+= inc |
---|
| 840 | minind=start |
---|
| 841 | for ind in xrange(start,end+inc,inc): |
---|
| 842 | if data[ind] > mn: break |
---|
| 843 | minind=ind |
---|
[709] | 844 | # find max index |
---|
[1819] | 845 | #while end > 0 and data[end] > mx: |
---|
| 846 | # end-=inc |
---|
| 847 | #if end > 0: end +=1 |
---|
| 848 | maxind=end |
---|
| 849 | for ind in xrange(end,start-inc,-inc): |
---|
| 850 | if data[ind] < mx: break |
---|
| 851 | maxind=ind |
---|
| 852 | start=minind |
---|
| 853 | end=maxind |
---|
[709] | 854 | if start > end: |
---|
[1819] | 855 | return end,start+1 |
---|
| 856 | elif start < end: |
---|
| 857 | return start,end+1 |
---|
| 858 | else: |
---|
| 859 | return start,end |
---|
[709] | 860 | |
---|
[710] | 861 | def _reset(self): |
---|
[920] | 862 | self._usermask = [] |
---|
[710] | 863 | self._usermaskspectra = None |
---|
[1897] | 864 | self._offset = None |
---|
[920] | 865 | self.set_selection(None, False) |
---|
[2051] | 866 | self._reset_header() |
---|
[920] | 867 | |
---|
[2051] | 868 | def _reset_header(self): |
---|
[2053] | 869 | self._headtext={'string': None, 'textobj': None} |
---|
[2051] | 870 | |
---|
[920] | 871 | def _plot(self, scan): |
---|
[947] | 872 | savesel = scan.get_selection() |
---|
| 873 | sel = savesel + self._selection |
---|
[1910] | 874 | order = self._get_sortstring([self._panelling,self._stacking]) |
---|
| 875 | if order: |
---|
| 876 | sel.set_order(order) |
---|
[947] | 877 | scan.set_selection(sel) |
---|
[920] | 878 | d = {'b': scan.getbeam, 's': scan.getscan, |
---|
[1949] | 879 | 'i': scan.getif, 'p': scan.getpol, 't': scan.get_time, |
---|
[1989] | 880 | 'r': int}#, '_r': int} |
---|
[920] | 881 | |
---|
[1148] | 882 | polmodes = dict(zip(self._selection.get_pols(), |
---|
| 883 | self._selection.get_poltypes())) |
---|
| 884 | # this returns either a tuple of numbers or a length (ncycles) |
---|
| 885 | # convert this into lengths |
---|
| 886 | n0,nstack0 = self._get_selected_n(scan) |
---|
| 887 | if isinstance(n0, int): n = n0 |
---|
[1175] | 888 | else: n = len(n0) |
---|
[1148] | 889 | if isinstance(nstack0, int): nstack = nstack0 |
---|
[1175] | 890 | else: nstack = len(nstack0) |
---|
[1989] | 891 | # In case of row stacking |
---|
| 892 | rowstack = False |
---|
| 893 | titlemode = self._panelling |
---|
| 894 | if self._stacking == "r" and self._panelling != "r": |
---|
| 895 | rowstack = True |
---|
| 896 | titlemode = '_r' |
---|
[1913] | 897 | nptot = n |
---|
[1582] | 898 | maxpanel, maxstack = 16,16 |
---|
[1913] | 899 | if nstack > maxstack: |
---|
| 900 | msg ="Scan to be overlayed contains more than %d selections.\n" \ |
---|
| 901 | "Selecting first %d selections..." % (maxstack, maxstack) |
---|
[920] | 902 | asaplog.push(msg) |
---|
[1861] | 903 | asaplog.post('WARN') |
---|
[998] | 904 | nstack = min(nstack,maxstack) |
---|
[2038] | 905 | #n = min(n-self._ipanel-1,maxpanel) |
---|
| 906 | n = n-self._ipanel-1 |
---|
[2011] | 907 | |
---|
| 908 | ganged = False |
---|
[920] | 909 | if n > 1: |
---|
| 910 | ganged = rcParams['plotter.ganged'] |
---|
[1819] | 911 | if self._panelling == 'i': |
---|
| 912 | ganged = False |
---|
[920] | 913 | if self._rows and self._cols: |
---|
| 914 | n = min(n,self._rows*self._cols) |
---|
| 915 | self._plotter.set_panels(rows=self._rows,cols=self._cols, |
---|
[2277] | 916 | nplots=n,margin=self._margins,ganged=ganged) |
---|
[920] | 917 | else: |
---|
[2038] | 918 | n = min(n,maxpanel) |
---|
[2277] | 919 | self._plotter.set_panels(rows=n,cols=0,nplots=n,margin=self._margins,ganged=ganged) |
---|
[920] | 920 | else: |
---|
[2037] | 921 | self._plotter.set_panels(margin=self._margins) |
---|
[1913] | 922 | #r = 0 |
---|
[1981] | 923 | r = self._startrow |
---|
[920] | 924 | nr = scan.nrow() |
---|
| 925 | a0,b0 = -1,-1 |
---|
| 926 | allxlim = [] |
---|
[1018] | 927 | allylim = [] |
---|
[1981] | 928 | #newpanel=True |
---|
| 929 | newpanel=False |
---|
[920] | 930 | panelcount,stackcount = 0,0 |
---|
[1981] | 931 | # If this is not the first page |
---|
| 932 | if r > 0: |
---|
| 933 | # panelling value of the prev page |
---|
| 934 | a0 = d[self._panelling](r-1) |
---|
| 935 | # set the initial stackcount large not to plot |
---|
| 936 | # the start row automatically |
---|
| 937 | stackcount = nstack |
---|
| 938 | |
---|
[1002] | 939 | while r < nr: |
---|
[920] | 940 | a = d[self._panelling](r) |
---|
| 941 | b = d[self._stacking](r) |
---|
| 942 | if a > a0 and panelcount < n: |
---|
| 943 | if n > 1: |
---|
| 944 | self._plotter.subplot(panelcount) |
---|
| 945 | self._plotter.palette(0) |
---|
| 946 | #title |
---|
| 947 | xlab = self._abcissa and self._abcissa[panelcount] \ |
---|
| 948 | or scan._getabcissalabel() |
---|
[1897] | 949 | if self._offset and not self._abcissa: |
---|
| 950 | xlab += " (relative)" |
---|
[920] | 951 | ylab = self._ordinate and self._ordinate[panelcount] \ |
---|
| 952 | or scan._get_ordinate_label() |
---|
[1547] | 953 | self._plotter.set_axes('xlabel', xlab) |
---|
| 954 | self._plotter.set_axes('ylabel', ylab) |
---|
[1989] | 955 | #lbl = self._get_label(scan, r, self._panelling, self._title) |
---|
| 956 | lbl = self._get_label(scan, r, titlemode, self._title) |
---|
[920] | 957 | if isinstance(lbl, list) or isinstance(lbl, tuple): |
---|
| 958 | if 0 <= panelcount < len(lbl): |
---|
| 959 | lbl = lbl[panelcount] |
---|
| 960 | else: |
---|
| 961 | # get default label |
---|
[1989] | 962 | #lbl = self._get_label(scan, r, self._panelling, None) |
---|
| 963 | lbl = self._get_label(scan, r, titlemode, None) |
---|
[920] | 964 | self._plotter.set_axes('title',lbl) |
---|
| 965 | newpanel = True |
---|
[1913] | 966 | stackcount = 0 |
---|
[920] | 967 | panelcount += 1 |
---|
[1981] | 968 | # save the start row to plot this panel for future revisit. |
---|
| 969 | if self._panelling != 'r' and \ |
---|
| 970 | len(self._panelrows) < self._ipanel+1+panelcount: |
---|
| 971 | self._panelrows += [r] |
---|
| 972 | |
---|
[1944] | 973 | #if (b > b0 or newpanel) and stackcount < nstack: |
---|
[2277] | 974 | if stackcount < nstack and (newpanel or rowstack or (a == a0 and b > b0)): |
---|
[920] | 975 | y = [] |
---|
| 976 | if len(polmodes): |
---|
| 977 | y = scan._getspectrum(r, polmodes[scan.getpol(r)]) |
---|
| 978 | else: |
---|
| 979 | y = scan._getspectrum(r) |
---|
[1995] | 980 | # flag application |
---|
| 981 | mr = scan._getflagrow(r) |
---|
[1739] | 982 | from numpy import ma, array |
---|
[1995] | 983 | if mr: |
---|
| 984 | y = ma.masked_array(y,mask=mr) |
---|
| 985 | else: |
---|
| 986 | m = scan._getmask(r) |
---|
| 987 | from numpy import logical_not, logical_and |
---|
| 988 | if self._maskselection and len(self._usermask) == len(m): |
---|
[2277] | 989 | if d[self._stacking](r) in self._maskselection[self._stacking]: |
---|
[1995] | 990 | m = logical_and(m, self._usermask) |
---|
[2277] | 991 | y = ma.masked_array(y,mask=logical_not(array(m,copy=False))) |
---|
[1995] | 992 | |
---|
[1897] | 993 | x = array(scan._getabcissa(r)) |
---|
| 994 | if self._offset: |
---|
| 995 | x += self._offset |
---|
[920] | 996 | if self._minmaxx is not None: |
---|
| 997 | s,e = self._slice_indeces(x) |
---|
| 998 | x = x[s:e] |
---|
| 999 | y = y[s:e] |
---|
[1096] | 1000 | if len(x) > 1024 and rcParams['plotter.decimate']: |
---|
| 1001 | fac = len(x)/1024 |
---|
[920] | 1002 | x = x[::fac] |
---|
| 1003 | y = y[::fac] |
---|
| 1004 | llbl = self._get_label(scan, r, self._stacking, self._lmap) |
---|
| 1005 | if isinstance(llbl, list) or isinstance(llbl, tuple): |
---|
| 1006 | if 0 <= stackcount < len(llbl): |
---|
| 1007 | # use user label |
---|
| 1008 | llbl = llbl[stackcount] |
---|
| 1009 | else: |
---|
| 1010 | # get default label |
---|
| 1011 | llbl = self._get_label(scan, r, self._stacking, None) |
---|
| 1012 | self._plotter.set_line(label=llbl) |
---|
[1023] | 1013 | plotit = self._plotter.plot |
---|
| 1014 | if self._hist: plotit = self._plotter.hist |
---|
[1995] | 1015 | if len(x) > 0 and not mr: |
---|
[1146] | 1016 | plotit(x,y) |
---|
| 1017 | xlim= self._minmaxx or [min(x),max(x)] |
---|
| 1018 | allxlim += xlim |
---|
| 1019 | ylim= self._minmaxy or [ma.minimum(y),ma.maximum(y)] |
---|
| 1020 | allylim += ylim |
---|
[1819] | 1021 | else: |
---|
| 1022 | xlim = self._minmaxx or [] |
---|
| 1023 | allxlim += xlim |
---|
| 1024 | ylim= self._minmaxy or [] |
---|
| 1025 | allylim += ylim |
---|
[920] | 1026 | stackcount += 1 |
---|
[1981] | 1027 | a0=a |
---|
| 1028 | b0=b |
---|
[920] | 1029 | # last in colour stack -> autoscale x |
---|
[1819] | 1030 | if stackcount == nstack and len(allxlim) > 0: |
---|
[920] | 1031 | allxlim.sort() |
---|
[1819] | 1032 | self._plotter.subplots[panelcount-1]['axes'].set_xlim([allxlim[0],allxlim[-1]]) |
---|
[1989] | 1033 | if ganged: |
---|
| 1034 | allxlim = [allxlim[0],allxlim[-1]] |
---|
| 1035 | else: |
---|
| 1036 | # clear |
---|
| 1037 | allxlim =[] |
---|
[920] | 1038 | |
---|
| 1039 | newpanel = False |
---|
[1981] | 1040 | #a0=a |
---|
| 1041 | #b0=b |
---|
[920] | 1042 | # ignore following rows |
---|
[1981] | 1043 | if (panelcount == n and stackcount == nstack) or (r == nr-1): |
---|
[1018] | 1044 | # last panel -> autoscale y if ganged |
---|
[1989] | 1045 | #if rcParams['plotter.ganged'] and len(allylim) > 0: |
---|
| 1046 | if ganged and len(allylim) > 0: |
---|
[1018] | 1047 | allylim.sort() |
---|
| 1048 | self._plotter.set_limits(ylim=[allylim[0],allylim[-1]]) |
---|
[998] | 1049 | break |
---|
[920] | 1050 | r+=1 # next row |
---|
[1981] | 1051 | |
---|
| 1052 | # save the current counter for multi-page plotting |
---|
| 1053 | self._startrow = r+1 |
---|
| 1054 | self._ipanel += panelcount |
---|
[2147] | 1055 | if self.casabar_exists(): |
---|
[1981] | 1056 | if self._ipanel >= nptot-1: |
---|
[1913] | 1057 | self._plotter.figmgr.casabar.disable_next() |
---|
| 1058 | else: |
---|
| 1059 | self._plotter.figmgr.casabar.enable_next() |
---|
[1981] | 1060 | if self._ipanel + 1 - panelcount > 0: |
---|
| 1061 | self._plotter.figmgr.casabar.enable_prev() |
---|
| 1062 | else: |
---|
| 1063 | self._plotter.figmgr.casabar.disable_prev() |
---|
| 1064 | |
---|
[947] | 1065 | #reset the selector to the scantable's original |
---|
| 1066 | scan.set_selection(savesel) |
---|
[1824] | 1067 | |
---|
[1819] | 1068 | #temporary switch-off for older matplotlib |
---|
| 1069 | #if self._fp is not None: |
---|
| 1070 | if self._fp is not None and getattr(self._plotter.figure,'findobj',False): |
---|
[1556] | 1071 | for o in self._plotter.figure.findobj(Text): |
---|
| 1072 | o.set_fontproperties(self._fp) |
---|
[920] | 1073 | |
---|
[1910] | 1074 | def _get_sortstring(self, lorders): |
---|
| 1075 | d0 = {'s': 'SCANNO', 'b': 'BEAMNO', 'i':'IFNO', |
---|
| 1076 | 'p': 'POLNO', 'c': 'CYCLENO', 't' : 'TIME', 'r':None, '_r':None } |
---|
[1944] | 1077 | if not (type(lorders) == list) and not (type(lorders) == tuple): |
---|
[1910] | 1078 | return None |
---|
| 1079 | if len(lorders) > 0: |
---|
| 1080 | lsorts = [] |
---|
| 1081 | for order in lorders: |
---|
[1989] | 1082 | if order == "r": |
---|
| 1083 | # don't sort if row panelling/stacking |
---|
| 1084 | return None |
---|
[1910] | 1085 | ssort = d0[order] |
---|
| 1086 | if ssort: |
---|
| 1087 | lsorts.append(ssort) |
---|
| 1088 | return lsorts |
---|
| 1089 | return None |
---|
| 1090 | |
---|
[1582] | 1091 | def set_selection(self, selection=None, refresh=True, **kw): |
---|
[1819] | 1092 | """ |
---|
| 1093 | Parameters: |
---|
| 1094 | selection: a selector object (default unset the selection) |
---|
| 1095 | refresh: True (default) or False. If True, the plot is |
---|
[1824] | 1096 | replotted based on the new parameter setting(s). |
---|
[1819] | 1097 | Otherwise,the parameter(s) are set without replotting. |
---|
| 1098 | """ |
---|
[1582] | 1099 | if selection is None: |
---|
| 1100 | # reset |
---|
| 1101 | if len(kw) == 0: |
---|
| 1102 | self._selection = selector() |
---|
| 1103 | else: |
---|
| 1104 | # try keywords |
---|
| 1105 | for k in kw: |
---|
| 1106 | if k not in selector.fields: |
---|
| 1107 | raise KeyError("Invalid selection key '%s', valid keys are %s" % (k, selector.fields)) |
---|
| 1108 | self._selection = selector(**kw) |
---|
| 1109 | elif isinstance(selection, selector): |
---|
| 1110 | self._selection = selection |
---|
| 1111 | else: |
---|
| 1112 | raise TypeError("'selection' is not of type selector") |
---|
| 1113 | |
---|
[1910] | 1114 | order = self._get_sortstring([self._panelling,self._stacking]) |
---|
| 1115 | if order: |
---|
| 1116 | self._selection.set_order(order) |
---|
[1819] | 1117 | if refresh and self._data: self.plot(self._data) |
---|
[920] | 1118 | |
---|
| 1119 | def _get_selected_n(self, scan): |
---|
[1148] | 1120 | d1 = {'b': scan.getbeamnos, 's': scan.getscannos, |
---|
[1910] | 1121 | 'i': scan.getifnos, 'p': scan.getpolnos, 't': scan.ncycle, |
---|
[1989] | 1122 | 'r': scan.nrow}#, '_r': False} |
---|
[1148] | 1123 | d2 = { 'b': self._selection.get_beams(), |
---|
| 1124 | 's': self._selection.get_scans(), |
---|
| 1125 | 'i': self._selection.get_ifs(), |
---|
| 1126 | 'p': self._selection.get_pols(), |
---|
[1910] | 1127 | 't': self._selection.get_cycles(), |
---|
[1989] | 1128 | 'r': False}#, '_r': 1} |
---|
[920] | 1129 | n = d2[self._panelling] or d1[self._panelling]() |
---|
| 1130 | nstack = d2[self._stacking] or d1[self._stacking]() |
---|
[1989] | 1131 | # handle row panelling/stacking |
---|
| 1132 | if self._panelling == 'r': |
---|
| 1133 | nstack = 1 |
---|
| 1134 | elif self._stacking == 'r': |
---|
| 1135 | n = 1 |
---|
[920] | 1136 | return n,nstack |
---|
| 1137 | |
---|
| 1138 | def _get_label(self, scan, row, mode, userlabel=None): |
---|
[1153] | 1139 | if isinstance(userlabel, list) and len(userlabel) == 0: |
---|
| 1140 | userlabel = " " |
---|
[947] | 1141 | pms = dict(zip(self._selection.get_pols(),self._selection.get_poltypes())) |
---|
[920] | 1142 | if len(pms): |
---|
| 1143 | poleval = scan._getpollabel(scan.getpol(row),pms[scan.getpol(row)]) |
---|
| 1144 | else: |
---|
| 1145 | poleval = scan._getpollabel(scan.getpol(row),scan.poltype()) |
---|
| 1146 | d = {'b': "Beam "+str(scan.getbeam(row)), |
---|
[1819] | 1147 | #'s': scan._getsourcename(row), |
---|
| 1148 | 's': "Scan "+str(scan.getscan(row))+\ |
---|
| 1149 | " ("+str(scan._getsourcename(row))+")", |
---|
[920] | 1150 | 'i': "IF"+str(scan.getif(row)), |
---|
[964] | 1151 | 'p': poleval, |
---|
[1910] | 1152 | 't': str(scan.get_time(row)), |
---|
| 1153 | 'r': "row "+str(row), |
---|
[1913] | 1154 | #'_r': str(scan.get_time(row))+",\nIF"+str(scan.getif(row))+", "+poleval+", Beam"+str(scan.getbeam(row)) } |
---|
| 1155 | '_r': "" } |
---|
[920] | 1156 | return userlabel or d[mode] |
---|
[1153] | 1157 | |
---|
[1819] | 1158 | def plotazel(self, scan=None, outfile=None): |
---|
[1391] | 1159 | """ |
---|
[1696] | 1160 | plot azimuth and elevation versus time of a scantable |
---|
[1391] | 1161 | """ |
---|
[1923] | 1162 | visible = rcParams['plotter.gui'] |
---|
[1696] | 1163 | from matplotlib import pylab as PL |
---|
| 1164 | from matplotlib.dates import DateFormatter, timezone |
---|
| 1165 | from matplotlib.dates import HourLocator, MinuteLocator,SecondLocator, DayLocator |
---|
[1391] | 1166 | from matplotlib.ticker import MultipleLocator |
---|
[1739] | 1167 | from numpy import array, pi |
---|
[1923] | 1168 | if not visible or not self._visible: |
---|
| 1169 | PL.ioff() |
---|
| 1170 | from matplotlib.backends.backend_agg import FigureCanvasAgg |
---|
| 1171 | PL.gcf().canvas.switch_backends(FigureCanvasAgg) |
---|
[1819] | 1172 | self._data = scan |
---|
| 1173 | self._outfile = outfile |
---|
[1556] | 1174 | dates = self._data.get_time(asdatetime=True) |
---|
[1391] | 1175 | t = PL.date2num(dates) |
---|
| 1176 | tz = timezone('UTC') |
---|
| 1177 | PL.cla() |
---|
| 1178 | PL.ioff() |
---|
| 1179 | PL.clf() |
---|
[2037] | 1180 | # Adjust subplot margins |
---|
| 1181 | if len(self._margins) != 6: |
---|
| 1182 | self.set_margin(refresh=False) |
---|
| 1183 | lef, bot, rig, top, wsp, hsp = self._margins |
---|
[1819] | 1184 | PL.gcf().subplots_adjust(left=lef,bottom=bot,right=rig,top=top, |
---|
| 1185 | wspace=wsp,hspace=hsp) |
---|
[1824] | 1186 | |
---|
[1391] | 1187 | tdel = max(t) - min(t) |
---|
| 1188 | ax = PL.subplot(2,1,1) |
---|
| 1189 | el = array(self._data.get_elevation())*180./pi |
---|
| 1190 | PL.ylabel('El [deg.]') |
---|
| 1191 | dstr = dates[0].strftime('%Y/%m/%d') |
---|
| 1192 | if tdel > 1.0: |
---|
| 1193 | dstr2 = dates[len(dates)-1].strftime('%Y/%m/%d') |
---|
| 1194 | dstr = dstr + " - " + dstr2 |
---|
| 1195 | majloc = DayLocator() |
---|
| 1196 | minloc = HourLocator(range(0,23,12)) |
---|
| 1197 | timefmt = DateFormatter("%b%d") |
---|
[1696] | 1198 | elif tdel > 24./60.: |
---|
| 1199 | timefmt = DateFormatter('%H:%M') |
---|
| 1200 | majloc = HourLocator() |
---|
| 1201 | minloc = MinuteLocator(30) |
---|
[1391] | 1202 | else: |
---|
[1696] | 1203 | timefmt = DateFormatter('%H:%M') |
---|
| 1204 | majloc = MinuteLocator(interval=5) |
---|
| 1205 | minloc = SecondLocator(30) |
---|
| 1206 | |
---|
[1391] | 1207 | PL.title(dstr) |
---|
[1819] | 1208 | if tdel == 0.0: |
---|
| 1209 | th = (t - PL.floor(t))*24.0 |
---|
| 1210 | PL.plot(th,el,'o',markersize=2, markerfacecolor='b', markeredgecolor='b') |
---|
| 1211 | else: |
---|
| 1212 | PL.plot_date(t,el,'o', markersize=2, markerfacecolor='b', markeredgecolor='b',tz=tz) |
---|
| 1213 | #ax.grid(True) |
---|
| 1214 | ax.xaxis.set_major_formatter(timefmt) |
---|
| 1215 | ax.xaxis.set_major_locator(majloc) |
---|
| 1216 | ax.xaxis.set_minor_locator(minloc) |
---|
[1391] | 1217 | ax.yaxis.grid(True) |
---|
[1819] | 1218 | yloc = MultipleLocator(30) |
---|
| 1219 | ax.set_ylim(0,90) |
---|
| 1220 | ax.yaxis.set_major_locator(yloc) |
---|
[1391] | 1221 | if tdel > 1.0: |
---|
| 1222 | labels = ax.get_xticklabels() |
---|
| 1223 | # PL.setp(labels, fontsize=10, rotation=45) |
---|
| 1224 | PL.setp(labels, fontsize=10) |
---|
[1819] | 1225 | |
---|
[1391] | 1226 | # Az plot |
---|
| 1227 | az = array(self._data.get_azimuth())*180./pi |
---|
| 1228 | if min(az) < 0: |
---|
| 1229 | for irow in range(len(az)): |
---|
| 1230 | if az[irow] < 0: az[irow] += 360.0 |
---|
| 1231 | |
---|
[1819] | 1232 | ax2 = PL.subplot(2,1,2) |
---|
| 1233 | #PL.xlabel('Time (UT [hour])') |
---|
| 1234 | PL.ylabel('Az [deg.]') |
---|
| 1235 | if tdel == 0.0: |
---|
| 1236 | PL.plot(th,az,'o',markersize=2, markeredgecolor='b',markerfacecolor='b') |
---|
| 1237 | else: |
---|
| 1238 | PL.plot_date(t,az,'o', markersize=2,markeredgecolor='b',markerfacecolor='b',tz=tz) |
---|
| 1239 | ax2.xaxis.set_major_formatter(timefmt) |
---|
| 1240 | ax2.xaxis.set_major_locator(majloc) |
---|
| 1241 | ax2.xaxis.set_minor_locator(minloc) |
---|
| 1242 | #ax2.grid(True) |
---|
| 1243 | ax2.set_ylim(0,360) |
---|
[1696] | 1244 | ax2.yaxis.grid(True) |
---|
[1819] | 1245 | #hfmt = DateFormatter('%H') |
---|
| 1246 | #hloc = HourLocator() |
---|
| 1247 | yloc = MultipleLocator(60) |
---|
| 1248 | ax2.yaxis.set_major_locator(yloc) |
---|
| 1249 | if tdel > 1.0: |
---|
| 1250 | labels = ax2.get_xticklabels() |
---|
| 1251 | PL.setp(labels, fontsize=10) |
---|
| 1252 | PL.xlabel('Time (UT [day])') |
---|
| 1253 | else: |
---|
| 1254 | PL.xlabel('Time (UT [hour])') |
---|
| 1255 | |
---|
[1391] | 1256 | PL.ion() |
---|
| 1257 | PL.draw() |
---|
[2155] | 1258 | PL.gcf().show() |
---|
[1819] | 1259 | if (self._outfile is not None): |
---|
| 1260 | PL.savefig(self._outfile) |
---|
[1391] | 1261 | |
---|
[1819] | 1262 | def plotpointing(self, scan=None, outfile=None): |
---|
[1391] | 1263 | """ |
---|
| 1264 | plot telescope pointings |
---|
| 1265 | """ |
---|
[1923] | 1266 | visible = rcParams['plotter.gui'] |
---|
[1696] | 1267 | from matplotlib import pylab as PL |
---|
[1819] | 1268 | from numpy import array, pi |
---|
[1923] | 1269 | if not visible or not self._visible: |
---|
| 1270 | PL.ioff() |
---|
| 1271 | from matplotlib.backends.backend_agg import FigureCanvasAgg |
---|
| 1272 | PL.gcf().canvas.switch_backends(FigureCanvasAgg) |
---|
[1819] | 1273 | self._data = scan |
---|
| 1274 | self._outfile = outfile |
---|
[1391] | 1275 | dir = array(self._data.get_directionval()).transpose() |
---|
| 1276 | ra = dir[0]*180./pi |
---|
| 1277 | dec = dir[1]*180./pi |
---|
| 1278 | PL.cla() |
---|
[1819] | 1279 | #PL.ioff() |
---|
[1391] | 1280 | PL.clf() |
---|
[2037] | 1281 | # Adjust subplot margins |
---|
| 1282 | if len(self._margins) != 6: |
---|
| 1283 | self.set_margin(refresh=False) |
---|
| 1284 | lef, bot, rig, top, wsp, hsp = self._margins |
---|
[1819] | 1285 | PL.gcf().subplots_adjust(left=lef,bottom=bot,right=rig,top=top, |
---|
| 1286 | wspace=wsp,hspace=hsp) |
---|
| 1287 | ax = PL.gca() |
---|
| 1288 | #ax = PL.axes([0.1,0.1,0.8,0.8]) |
---|
| 1289 | #ax = PL.axes([0.1,0.1,0.8,0.8]) |
---|
[1391] | 1290 | ax.set_aspect('equal') |
---|
[1696] | 1291 | PL.plot(ra, dec, 'b,') |
---|
[1391] | 1292 | PL.xlabel('RA [deg.]') |
---|
| 1293 | PL.ylabel('Declination [deg.]') |
---|
| 1294 | PL.title('Telescope pointings') |
---|
| 1295 | [xmin,xmax,ymin,ymax] = PL.axis() |
---|
| 1296 | PL.axis([xmax,xmin,ymin,ymax]) |
---|
[1819] | 1297 | #PL.ion() |
---|
[1391] | 1298 | PL.draw() |
---|
[2155] | 1299 | PL.gcf().show() |
---|
[1819] | 1300 | if (self._outfile is not None): |
---|
| 1301 | PL.savefig(self._outfile) |
---|
| 1302 | |
---|
| 1303 | # plot total power data |
---|
| 1304 | # plotting in time is not yet implemented.. |
---|
[1862] | 1305 | @asaplog_post_dec |
---|
[1819] | 1306 | def plottp(self, scan=None, outfile=None): |
---|
| 1307 | if self._plotter.is_dead: |
---|
[2147] | 1308 | if self.casabar_exists(): |
---|
[1819] | 1309 | del self._plotter.figmgr.casabar |
---|
| 1310 | self._plotter = self._newplotter() |
---|
[2173] | 1311 | self._plotter.figmgr.casabar=self._new_custombar() |
---|
[1819] | 1312 | self._plotter.hold() |
---|
| 1313 | self._plotter.clear() |
---|
| 1314 | from asap import scantable |
---|
| 1315 | if not self._data and not scan: |
---|
| 1316 | msg = "Input is not a scantable" |
---|
| 1317 | raise TypeError(msg) |
---|
| 1318 | if isinstance(scan, scantable): |
---|
| 1319 | if self._data is not None: |
---|
| 1320 | if scan != self._data: |
---|
| 1321 | self._data = scan |
---|
| 1322 | # reset |
---|
| 1323 | self._reset() |
---|
| 1324 | else: |
---|
| 1325 | self._data = scan |
---|
| 1326 | self._reset() |
---|
| 1327 | # ranges become invalid when abcissa changes? |
---|
| 1328 | #if self._abcunit and self._abcunit != self._data.get_unit(): |
---|
| 1329 | # self._minmaxx = None |
---|
| 1330 | # self._minmaxy = None |
---|
| 1331 | # self._abcunit = self._data.get_unit() |
---|
| 1332 | # self._datamask = None |
---|
| 1333 | |
---|
[2037] | 1334 | # Adjust subplot margins |
---|
| 1335 | if len(self._margins) !=6: self.set_margin(refresh=False) |
---|
| 1336 | lef, bot, rig, top, wsp, hsp = self._margins |
---|
[1819] | 1337 | self._plotter.figure.subplots_adjust( |
---|
| 1338 | left=lef,bottom=bot,right=rig,top=top,wspace=wsp,hspace=hsp) |
---|
[2147] | 1339 | if self.casabar_exists(): self._plotter.figmgr.casabar.disable_button() |
---|
[1819] | 1340 | self._plottp(self._data) |
---|
| 1341 | if self._minmaxy is not None: |
---|
| 1342 | self._plotter.set_limits(ylim=self._minmaxy) |
---|
| 1343 | self._plotter.release() |
---|
| 1344 | self._plotter.tidy() |
---|
| 1345 | self._plotter.show(hardrefresh=False) |
---|
| 1346 | return |
---|
| 1347 | |
---|
| 1348 | def _plottp(self,scan): |
---|
| 1349 | """ |
---|
| 1350 | private method for plotting total power data |
---|
| 1351 | """ |
---|
| 1352 | from numpy import ma, array, arange, logical_not |
---|
| 1353 | r=0 |
---|
| 1354 | nr = scan.nrow() |
---|
| 1355 | a0,b0 = -1,-1 |
---|
| 1356 | allxlim = [] |
---|
| 1357 | allylim = [] |
---|
| 1358 | y=[] |
---|
| 1359 | self._plotter.set_panels() |
---|
| 1360 | self._plotter.palette(0) |
---|
| 1361 | #title |
---|
| 1362 | #xlab = self._abcissa and self._abcissa[panelcount] \ |
---|
| 1363 | # or scan._getabcissalabel() |
---|
| 1364 | #ylab = self._ordinate and self._ordinate[panelcount] \ |
---|
| 1365 | # or scan._get_ordinate_label() |
---|
| 1366 | xlab = self._abcissa or 'row number' #or Time |
---|
| 1367 | ylab = self._ordinate or scan._get_ordinate_label() |
---|
| 1368 | self._plotter.set_axes('xlabel',xlab) |
---|
| 1369 | self._plotter.set_axes('ylabel',ylab) |
---|
| 1370 | lbl = self._get_label(scan, r, 's', self._title) |
---|
| 1371 | if isinstance(lbl, list) or isinstance(lbl, tuple): |
---|
| 1372 | # if 0 <= panelcount < len(lbl): |
---|
| 1373 | # lbl = lbl[panelcount] |
---|
| 1374 | # else: |
---|
| 1375 | # get default label |
---|
| 1376 | lbl = self._get_label(scan, r, self._panelling, None) |
---|
| 1377 | self._plotter.set_axes('title',lbl) |
---|
| 1378 | y=array(scan._get_column(scan._getspectrum,-1)) |
---|
| 1379 | m = array(scan._get_column(scan._getmask,-1)) |
---|
| 1380 | y = ma.masked_array(y,mask=logical_not(array(m,copy=False))) |
---|
| 1381 | x = arange(len(y)) |
---|
| 1382 | # try to handle spectral data somewhat... |
---|
| 1383 | l,m = y.shape |
---|
| 1384 | if m > 1: |
---|
| 1385 | y=y.mean(axis=1) |
---|
| 1386 | plotit = self._plotter.plot |
---|
| 1387 | llbl = self._get_label(scan, r, self._stacking, None) |
---|
| 1388 | self._plotter.set_line(label=llbl) |
---|
| 1389 | if len(x) > 0: |
---|
| 1390 | plotit(x,y) |
---|
| 1391 | |
---|
| 1392 | |
---|
| 1393 | # forwards to matplotlib.Figure.text |
---|
| 1394 | def figtext(self, *args, **kwargs): |
---|
| 1395 | """ |
---|
| 1396 | Add text to figure at location x,y (relative 0-1 coords). |
---|
| 1397 | This method forwards *args and **kwargs to a Matplotlib method, |
---|
| 1398 | matplotlib.Figure.text. |
---|
| 1399 | See the method help for detailed information. |
---|
| 1400 | """ |
---|
| 1401 | self._plotter.text(*args, **kwargs) |
---|
| 1402 | # end matplotlib.Figure.text forwarding function |
---|
| 1403 | |
---|
| 1404 | |
---|
| 1405 | # printing header information |
---|
[1862] | 1406 | @asaplog_post_dec |
---|
[2053] | 1407 | def print_header(self, plot=True, fontsize=9, logger=False, selstr='', extrastr=''): |
---|
[1819] | 1408 | """ |
---|
| 1409 | print data (scantable) header on the plot and/or logger. |
---|
[2056] | 1410 | To plot the header on the plot, this method should be called after |
---|
| 1411 | plotting spectra by the method, asapplotter.plot. |
---|
[1819] | 1412 | Parameters: |
---|
[1824] | 1413 | plot: whether or not print header info on the plot. |
---|
[2053] | 1414 | fontsize: header font size (valid only plot=True) |
---|
[1819] | 1415 | logger: whether or not print header info on the logger. |
---|
| 1416 | selstr: additional selection string (not verified) |
---|
[2053] | 1417 | extrastr: additional string to print at the beginning (not verified) |
---|
[1819] | 1418 | """ |
---|
[1859] | 1419 | if not plot and not logger: |
---|
| 1420 | return |
---|
| 1421 | if not self._data: |
---|
| 1422 | raise RuntimeError("No scantable has been set yet.") |
---|
[1824] | 1423 | # Now header will be printed on plot and/or logger. |
---|
| 1424 | # Get header information and format it. |
---|
[2112] | 1425 | ssum=self._data._list_header() |
---|
[1819] | 1426 | # Print Observation header to the upper-left corner of plot |
---|
[2290] | 1427 | headstr=[ssum[0:ssum.find('Obs. Type:')]] |
---|
| 1428 | headstr.append(ssum[ssum.find('Obs. Type:'):ssum.find('Flux Unit:')]) |
---|
[2053] | 1429 | if extrastr != '': |
---|
| 1430 | headstr[0]=extrastr+'\n'+headstr[0] |
---|
| 1431 | self._headtext['extrastr'] = extrastr |
---|
[2112] | 1432 | if selstr != '': |
---|
| 1433 | selstr += '\n' |
---|
| 1434 | self._headtext['selstr'] = selstr |
---|
[2056] | 1435 | ssel=(selstr+self._data.get_selection().__str__()+self._selection.__str__() or 'none') |
---|
[2053] | 1436 | headstr.append('***Selections***\n'+ssel) |
---|
[1824] | 1437 | |
---|
[2051] | 1438 | if plot: |
---|
[1819] | 1439 | self._plotter.hold() |
---|
[2053] | 1440 | self._header_plot(headstr,fontsize=fontsize) |
---|
[1819] | 1441 | import time |
---|
[2106] | 1442 | self._plotter.figure.text(0.99,0.01, |
---|
[1819] | 1443 | time.strftime("%a %d %b %Y %H:%M:%S %Z"), |
---|
| 1444 | horizontalalignment='right', |
---|
| 1445 | verticalalignment='bottom',fontsize=8) |
---|
| 1446 | self._plotter.release() |
---|
| 1447 | if logger: |
---|
[2053] | 1448 | selstr = "Selections: "+ssel |
---|
[1819] | 1449 | asaplog.push("----------------\n Plot Summary\n----------------") |
---|
[2053] | 1450 | asaplog.push(extrastr) |
---|
[2290] | 1451 | asaplog.push(ssum[0:ssum.find('Selection:')]\ |
---|
[2112] | 1452 | + selstr) |
---|
[2053] | 1453 | self._headtext['string'] = headstr |
---|
| 1454 | del ssel, ssum, headstr |
---|
[2051] | 1455 | |
---|
[2053] | 1456 | def _header_plot(self, texts, fontsize=9): |
---|
| 1457 | self._headtext['textobj']=[] |
---|
| 1458 | nstcol=len(texts) |
---|
| 1459 | for i in range(nstcol): |
---|
| 1460 | self._headtext['textobj'].append( |
---|
| 1461 | self._plotter.figure.text(0.03+float(i)/nstcol,0.98, |
---|
| 1462 | texts[i], |
---|
| 1463 | horizontalalignment='left', |
---|
| 1464 | verticalalignment='top', |
---|
| 1465 | fontsize=fontsize)) |
---|
| 1466 | |
---|
| 1467 | def clear_header(self): |
---|
| 1468 | if not self._headtext['textobj']: |
---|
| 1469 | asaplog.push("No header has been plotted. Exit without any operation") |
---|
| 1470 | asaplog.post("WARN") |
---|
| 1471 | else: |
---|
| 1472 | self._plotter.hold() |
---|
| 1473 | for textobj in self._headtext['textobj']: |
---|
| 1474 | #if textobj.get_text() in self._headstring: |
---|
| 1475 | try: |
---|
| 1476 | textobj.remove() |
---|
| 1477 | except NotImplementedError: |
---|
| 1478 | self._plotter.figure.texts.pop(self._plotter.figure.texts.index(textobj)) |
---|
| 1479 | self._plotter.release() |
---|
| 1480 | self._reset_header() |
---|