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