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