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