##// END OF EJS Templates
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1 1 # Copyright (c) 2012-2021 Jicamarca Radio Observatory
2 2 # All rights reserved.
3 3 #
4 4 # Distributed under the terms of the BSD 3-clause license.
5 5 """Classes to plot Spectra data
6 6
7 7 """
8 8
9 9 import os
10 10 import numpy
11 11
12 12 from schainpy.model.graphics.jroplot_base import Plot, plt, log
13 13
14 14
15 15 class SpectraPlot(Plot):
16 16 '''
17 17 Plot for Spectra data
18 18 '''
19 19
20 20 CODE = 'spc'
21 21 colormap = 'jet'
22 22 plot_type = 'pcolor'
23 23 buffering = False
24 24
25 25 def setup(self):
26 26
27 27 self.nplots = len(self.data.channels)
28 28 self.ncols = int(numpy.sqrt(self.nplots) + 0.9)
29 29 self.nrows = int((1.0 * self.nplots / self.ncols) + 0.9)
30 30 self.height = 2.6 * self.nrows
31 31 self.cb_label = 'dB'
32 32 if self.showprofile:
33 33 self.width = 4 * self.ncols
34 34 else:
35 35 self.width = 3.5 * self.ncols
36 36 self.plots_adjust.update({'wspace': 0.8, 'hspace':0.2, 'left': 0.2, 'right': 0.9, 'bottom': 0.18})
37 37 self.ylabel = 'Range [km]'
38 38
39 39 def update(self, dataOut):
40 40
41 41 data = {}
42 42 meta = {}
43 43 spc = 10 * numpy.log10(dataOut.data_spc / dataOut.normFactor)
44 44 data['spc'] = spc
45 45 data['rti'] = dataOut.getPower()
46 46 data['noise'] = 10 * numpy.log10(dataOut.getNoise() / dataOut.normFactor)
47 47 extrapoints = spc.shape[1] % dataOut.nFFTPoints
48 extrapoints=1
48 49 meta['xrange'] = (dataOut.getFreqRange(extrapoints) / 1000., dataOut.getAcfRange(extrapoints), dataOut.getVelRange(extrapoints))
49 50 if self.CODE == 'spc_moments':
50 51 data['moments'] = dataOut.moments
51 52 if self.CODE == 'gaussian_fit':
52 53 data['gaussfit'] = dataOut.DGauFitParams
53 54
54 55 return data, meta
55 56
56 57 def plot(self):
57 58
58 59 if self.xaxis == "frequency":
59 60 x = self.data.xrange[0]
60 61 self.xlabel = "Frequency (kHz)"
61 62 elif self.xaxis == "time":
62 63 x = self.data.xrange[1]
63 64 self.xlabel = "Time (ms)"
64 65 else:
65 66 x = self.data.xrange[2]
66 67 self.xlabel = "Velocity (m/s)"
67 68
68 69 if (self.CODE == 'spc_moments') | (self.CODE == 'gaussian_fit'):
69 70 x = self.data.xrange[2]
70 71 self.xlabel = "Velocity (m/s)"
71 72
72 73 self.titles = []
73 74
74 75 y = self.data.yrange
75 76 self.y = y
76 77
77 78 data = self.data[-1]
78 79 z = data['spc']
79 80
80 81 for n, ax in enumerate(self.axes):
81 82 noise = data['noise'][n]
82 83
83 84 if self.CODE == 'spc_moments':
84 85 mean = data['moments'][n, 1]
85 86 if self.CODE == 'gaussian_fit':
86 87 gau0 = data['gaussfit'][n][2,:,0]
87 88 gau1 = data['gaussfit'][n][2,:,1]
88 89 if ax.firsttime:
89 90 self.xmax = self.xmax if self.xmax else numpy.nanmax(x)
90 91 self.xmin = self.xmin if self.xmin else -self.xmax
91 92 self.zmin = self.zmin if self.zmin else numpy.nanmin(z)
92 93 self.zmax = self.zmax if self.zmax else numpy.nanmax(z)
93 94 ax.plt = ax.pcolormesh(x, y, z[n].T,
94 95 vmin=self.zmin,
95 96 vmax=self.zmax,
96 97 cmap=plt.get_cmap(self.colormap)
97 98 )
98 99
99 100 if self.showprofile:
100 101 ax.plt_profile = self.pf_axes[n].plot(
101 102 data['rti'][n], y)[0]
102 103 ax.plt_noise = self.pf_axes[n].plot(numpy.repeat(noise, len(y)), y,
103 104 color="k", linestyle="dashed", lw=1)[0]
104 105 if self.CODE == 'spc_moments':
105 106 ax.plt_mean = ax.plot(mean, y, color='k', lw=1)[0]
106 107 if self.CODE == 'gaussian_fit':
107 108 ax.plt_gau0 = ax.plot(gau0, y, color='r', lw=1)[0]
108 109 ax.plt_gau1 = ax.plot(gau1, y, color='y', lw=1)[0]
109 110 else:
110 111 ax.plt.set_array(z[n].T.ravel())
111 112 if self.showprofile:
112 113 ax.plt_profile.set_data(data['rti'][n], y)
113 114 ax.plt_noise.set_data(numpy.repeat(noise, len(y)), y)
114 115 if self.CODE == 'spc_moments':
115 116 ax.plt_mean.set_data(mean, y)
116 117 if self.CODE == 'gaussian_fit':
117 118 ax.plt_gau0.set_data(gau0, y)
118 119 ax.plt_gau1.set_data(gau1, y)
119 120 self.titles.append('CH {}: {:3.2f}dB'.format(n, noise))
120 121
121 122 class SpectraObliquePlot(Plot):
122 123 '''
123 124 Plot for Spectra data
124 125 '''
125 126
126 127 CODE = 'spc_oblique'
127 128 colormap = 'jet'
128 129 plot_type = 'pcolor'
129 130
130 131 def setup(self):
131 132 self.xaxis = "oblique"
132 133 self.nplots = len(self.data.channels)
133 134 self.ncols = int(numpy.sqrt(self.nplots) + 0.9)
134 135 self.nrows = int((1.0 * self.nplots / self.ncols) + 0.9)
135 136 self.height = 2.6 * self.nrows
136 137 self.cb_label = 'dB'
137 138 if self.showprofile:
138 139 self.width = 4 * self.ncols
139 140 else:
140 141 self.width = 3.5 * self.ncols
141 142 self.plots_adjust.update({'wspace': 0.8, 'hspace':0.2, 'left': 0.2, 'right': 0.9, 'bottom': 0.18})
142 143 self.ylabel = 'Range [km]'
143 144
144 145 def update(self, dataOut):
145 146
146 147 data = {}
147 148 meta = {}
148 149 spc = 10*numpy.log10(dataOut.data_spc/dataOut.normFactor)
149 150 data['spc'] = spc
150 151 data['rti'] = dataOut.getPower()
151 152 data['noise'] = 10*numpy.log10(dataOut.getNoise()/dataOut.normFactor)
152 153 meta['xrange'] = (dataOut.getFreqRange(1)/1000., dataOut.getAcfRange(1), dataOut.getVelRange(1))
153 154
154 155 data['shift1'] = dataOut.Oblique_params[0][1]
155 156 data['shift2'] = dataOut.Oblique_params[0][4]
156 157 data['shift1_error'] = dataOut.Oblique_param_errors[0][1]
157 158 data['shift2_error'] = dataOut.Oblique_param_errors[0][4]
158 159
159 160 return data, meta
160 161
161 162 def plot(self):
162 163
163 164 if self.xaxis == "frequency":
164 165 x = self.data.xrange[0]
165 166 self.xlabel = "Frequency (kHz)"
166 167 elif self.xaxis == "time":
167 168 x = self.data.xrange[1]
168 169 self.xlabel = "Time (ms)"
169 170 else:
170 171 x = self.data.xrange[2]
171 172 self.xlabel = "Velocity (m/s)"
172 173
173 174 self.titles = []
174 175
175 176 y = self.data.yrange
176 177 self.y = y
177 178 z = self.data['spc']
178 179
179 180 for n, ax in enumerate(self.axes):
180 181 noise = self.data['noise'][n][-1]
181 182 shift1 = self.data['shift1']
182 183 shift2 = self.data['shift2']
183 184 err1 = self.data['shift1_error']
184 185 err2 = self.data['shift2_error']
185 186 if ax.firsttime:
186 187 self.xmax = self.xmax if self.xmax else numpy.nanmax(x)
187 188 self.xmin = self.xmin if self.xmin else -self.xmax
188 189 self.zmin = self.zmin if self.zmin else numpy.nanmin(z)
189 190 self.zmax = self.zmax if self.zmax else numpy.nanmax(z)
190 191 ax.plt = ax.pcolormesh(x, y, z[n].T,
191 192 vmin=self.zmin,
192 193 vmax=self.zmax,
193 194 cmap=plt.get_cmap(self.colormap)
194 195 )
195 196
196 197 if self.showprofile:
197 198 ax.plt_profile = self.pf_axes[n].plot(
198 199 self.data['rti'][n][-1], y)[0]
199 200 ax.plt_noise = self.pf_axes[n].plot(numpy.repeat(noise, len(y)), y,
200 201 color="k", linestyle="dashed", lw=1)[0]
201 202
202 203 self.ploterr1 = ax.errorbar(shift1, y, xerr=err1, fmt='k^', elinewidth=0.2, marker='x', linestyle='None',markersize=0.5,capsize=0.3,markeredgewidth=0.2)
203 204 self.ploterr2 = ax.errorbar(shift2, y, xerr=err2, fmt='m^',elinewidth=0.2,marker='x',linestyle='None',markersize=0.5,capsize=0.3,markeredgewidth=0.2)
204 205 else:
205 206 self.ploterr1.remove()
206 207 self.ploterr2.remove()
207 208 ax.plt.set_array(z[n].T.ravel())
208 209 if self.showprofile:
209 210 ax.plt_profile.set_data(self.data['rti'][n][-1], y)
210 211 ax.plt_noise.set_data(numpy.repeat(noise, len(y)), y)
211 212 self.ploterr1 = ax.errorbar(shift1, y, xerr=err1, fmt='k^',elinewidth=0.2,marker='x',linestyle='None',markersize=0.5,capsize=0.3,markeredgewidth=0.2)
212 213 self.ploterr2 = ax.errorbar(shift2, y, xerr=err2, fmt='m^',elinewidth=0.2,marker='x',linestyle='None',markersize=0.5,capsize=0.3,markeredgewidth=0.2)
213 214
214 215 self.titles.append('CH {}: {:3.2f}dB'.format(n, noise))
215 216
216 217
217 218 class CrossSpectraPlot(Plot):
218 219
219 220 CODE = 'cspc'
220 221 colormap = 'jet'
221 222 plot_type = 'pcolor'
222 223 zmin_coh = None
223 224 zmax_coh = None
224 225 zmin_phase = None
225 226 zmax_phase = None
226 227
227 228 def setup(self):
228 229
229 230 self.ncols = 4
230 231 self.nplots = len(self.data.pairs) * 2
231 232 self.nrows = int((1.0 * self.nplots / self.ncols) + 0.9)
232 233 self.width = 3.1 * self.ncols
233 234 self.height = 5 * self.nrows
234 235 self.ylabel = 'Range [km]'
235 236 self.showprofile = False
236 237 self.plots_adjust.update({'left': 0.08, 'right': 0.92, 'wspace': 0.5, 'hspace':0.4, 'top':0.95, 'bottom': 0.08})
237 238
238 239 def update(self, dataOut):
239 240
240 241 data = {}
241 242 meta = {}
242 243
243 244 spc = dataOut.data_spc
244 245 cspc = dataOut.data_cspc
245 246 extrapoints = spc.shape[1] % dataOut.nFFTPoints
246 247 meta['xrange'] = (dataOut.getFreqRange(extrapoints) / 1000., dataOut.getAcfRange(extrapoints), dataOut.getVelRange(extrapoints))
247 248 meta['pairs'] = dataOut.pairsList
248 249
249 250 tmp = []
250 251
251 252 for n, pair in enumerate(meta['pairs']):
252 253 out = cspc[n] / numpy.sqrt(spc[pair[0]] * spc[pair[1]])
253 254 coh = numpy.abs(out)
254 255 phase = numpy.arctan2(out.imag, out.real) * 180 / numpy.pi
255 256 tmp.append(coh)
256 257 tmp.append(phase)
257 258
258 259 data['cspc'] = numpy.array(tmp)
259 260
260 261 return data, meta
261 262
262 263 def plot(self):
263 264
264 265 if self.xaxis == "frequency":
265 266 x = self.data.xrange[0]
266 267 self.xlabel = "Frequency (kHz)"
267 268 elif self.xaxis == "time":
268 269 x = self.data.xrange[1]
269 270 self.xlabel = "Time (ms)"
270 271 else:
271 272 x = self.data.xrange[2]
272 273 self.xlabel = "Velocity (m/s)"
273 274
274 275 self.titles = []
275 276
276 277 y = self.data.yrange
277 278 self.y = y
278 279
279 280 data = self.data[-1]
280 281 cspc = data['cspc']
281 282
282 283 for n in range(len(self.data.pairs)):
283 284 pair = self.data.pairs[n]
284 285 coh = cspc[n * 2]
285 286 phase = cspc[n * 2 + 1]
286 287 ax = self.axes[2 * n]
287 288 if ax.firsttime:
288 289 ax.plt = ax.pcolormesh(x, y, coh.T,
289 290 vmin=0,
290 291 vmax=1,
291 292 cmap=plt.get_cmap(self.colormap_coh)
292 293 )
293 294 else:
294 295 ax.plt.set_array(coh.T.ravel())
295 296 self.titles.append(
296 297 'Coherence Ch{} * Ch{}'.format(pair[0], pair[1]))
297 298
298 299 ax = self.axes[2 * n + 1]
299 300 if ax.firsttime:
300 301 ax.plt = ax.pcolormesh(x, y, phase.T,
301 302 vmin=-180,
302 303 vmax=180,
303 304 cmap=plt.get_cmap(self.colormap_phase)
304 305 )
305 306 else:
306 307 ax.plt.set_array(phase.T.ravel())
307 308 self.titles.append('Phase CH{} * CH{}'.format(pair[0], pair[1]))
308 309
309 310
310 311 class CrossSpectra4Plot(Plot):
311 312
312 313 CODE = 'cspc'
313 314 colormap = 'jet'
314 315 plot_type = 'pcolor'
315 316 zmin_coh = None
316 317 zmax_coh = None
317 318 zmin_phase = None
318 319 zmax_phase = None
319 320
320 321 def setup(self):
321 322
322 323 self.ncols = 4
323 324 self.nrows = len(self.data.pairs)
324 325 self.nplots = self.nrows * 4
325 326 self.width = 3.1 * self.ncols
326 327 self.height = 5 * self.nrows
327 328 self.ylabel = 'Range [km]'
328 329 self.showprofile = False
329 330 self.plots_adjust.update({'left': 0.08, 'right': 0.92, 'wspace': 0.5, 'hspace':0.4, 'top':0.95, 'bottom': 0.08})
330 331
331 332 def plot(self):
332 333
333 334 if self.xaxis == "frequency":
334 335 x = self.data.xrange[0]
335 336 self.xlabel = "Frequency (kHz)"
336 337 elif self.xaxis == "time":
337 338 x = self.data.xrange[1]
338 339 self.xlabel = "Time (ms)"
339 340 else:
340 341 x = self.data.xrange[2]
341 342 self.xlabel = "Velocity (m/s)"
342 343
343 344 self.titles = []
344 345
345 346
346 347 y = self.data.heights
347 348 self.y = y
348 349 nspc = self.data['spc']
349 350 #print(numpy.shape(self.data['spc']))
350 351 spc = self.data['cspc'][0]
351 352 #print(numpy.shape(nspc))
352 353 #exit()
353 354 #nspc[1,:,:] = numpy.flip(nspc[1,:,:],axis=0)
354 355 #print(numpy.shape(spc))
355 356 #exit()
356 357 cspc = self.data['cspc'][1]
357 358
358 359 #xflip=numpy.flip(x)
359 360 #print(numpy.shape(cspc))
360 361 #exit()
361 362
362 363 for n in range(self.nrows):
363 364 noise = self.data['noise'][:,-1]
364 365 pair = self.data.pairs[n]
365 366 #print(pair)
366 367 #exit()
367 368 ax = self.axes[4 * n]
368 369 if ax.firsttime:
369 370 self.xmax = self.xmax if self.xmax else numpy.nanmax(x)
370 371 self.xmin = self.xmin if self.xmin else -self.xmax
371 372 self.zmin = self.zmin if self.zmin else numpy.nanmin(nspc)
372 373 self.zmax = self.zmax if self.zmax else numpy.nanmax(nspc)
373 374 ax.plt = ax.pcolormesh(x , y , nspc[pair[0]].T,
374 375 vmin=self.zmin,
375 376 vmax=self.zmax,
376 377 cmap=plt.get_cmap(self.colormap)
377 378 )
378 379 else:
379 380 #print(numpy.shape(nspc[pair[0]].T))
380 381 #exit()
381 382 ax.plt.set_array(nspc[pair[0]].T.ravel())
382 383 self.titles.append('CH {}: {:3.2f}dB'.format(pair[0], noise[pair[0]]))
383 384
384 385 ax = self.axes[4 * n + 1]
385 386
386 387 if ax.firsttime:
387 388 ax.plt = ax.pcolormesh(x , y, numpy.flip(nspc[pair[1]],axis=0).T,
388 389 vmin=self.zmin,
389 390 vmax=self.zmax,
390 391 cmap=plt.get_cmap(self.colormap)
391 392 )
392 393 else:
393 394
394 395 ax.plt.set_array(numpy.flip(nspc[pair[1]],axis=0).T.ravel())
395 396 self.titles.append('CH {}: {:3.2f}dB'.format(pair[1], noise[pair[1]]))
396 397
397 398 out = cspc[n] / numpy.sqrt(spc[pair[0]] * spc[pair[1]])
398 399 coh = numpy.abs(out)
399 400 phase = numpy.arctan2(out.imag, out.real) * 180 / numpy.pi
400 401
401 402 ax = self.axes[4 * n + 2]
402 403 if ax.firsttime:
403 404 ax.plt = ax.pcolormesh(x, y, numpy.flip(coh,axis=0).T,
404 405 vmin=0,
405 406 vmax=1,
406 407 cmap=plt.get_cmap(self.colormap_coh)
407 408 )
408 409 else:
409 410 ax.plt.set_array(numpy.flip(coh,axis=0).T.ravel())
410 411 self.titles.append(
411 412 'Coherence Ch{} * Ch{}'.format(pair[0], pair[1]))
412 413
413 414 ax = self.axes[4 * n + 3]
414 415 if ax.firsttime:
415 416 ax.plt = ax.pcolormesh(x, y, numpy.flip(phase,axis=0).T,
416 417 vmin=-180,
417 418 vmax=180,
418 419 cmap=plt.get_cmap(self.colormap_phase)
419 420 )
420 421 else:
421 422 ax.plt.set_array(numpy.flip(phase,axis=0).T.ravel())
422 423 self.titles.append('Phase CH{} * CH{}'.format(pair[0], pair[1]))
423 424
424 425
425 426 class CrossSpectra2Plot(Plot):
426 427
427 428 CODE = 'cspc'
428 429 colormap = 'jet'
429 430 plot_type = 'pcolor'
430 431 zmin_coh = None
431 432 zmax_coh = None
432 433 zmin_phase = None
433 434 zmax_phase = None
434 435
435 436 def setup(self):
436 437
437 438 self.ncols = 1
438 439 self.nrows = len(self.data.pairs)
439 440 self.nplots = self.nrows * 1
440 441 self.width = 3.1 * self.ncols
441 442 self.height = 5 * self.nrows
442 443 self.ylabel = 'Range [km]'
443 444 self.showprofile = False
444 445 self.plots_adjust.update({'left': 0.22, 'right': .90, 'wspace': 0.5, 'hspace':0.4, 'top':0.95, 'bottom': 0.08})
445 446
446 447 def plot(self):
447 448
448 449 if self.xaxis == "frequency":
449 450 x = self.data.xrange[0]
450 451 self.xlabel = "Frequency (kHz)"
451 452 elif self.xaxis == "time":
452 453 x = self.data.xrange[1]
453 454 self.xlabel = "Time (ms)"
454 455 else:
455 456 x = self.data.xrange[2]
456 457 self.xlabel = "Velocity (m/s)"
457 458
458 459 self.titles = []
459 460
460 461
461 462 y = self.data.heights
462 463 self.y = y
463 464 #nspc = self.data['spc']
464 465 #print(numpy.shape(self.data['spc']))
465 466 #spc = self.data['cspc'][0]
466 467 #print(numpy.shape(spc))
467 468 #exit()
468 469 cspc = self.data['cspc'][1]
469 470 #print(numpy.shape(cspc))
470 471 #exit()
471 472
472 473 for n in range(self.nrows):
473 474 noise = self.data['noise'][:,-1]
474 475 pair = self.data.pairs[n]
475 476 #print(pair) #exit()
476 477
477 478
478 479
479 480 out = cspc[n]# / numpy.sqrt(spc[pair[0]] * spc[pair[1]])
480 481
481 482 #print(out[:,53])
482 483 #exit()
483 484 cross = numpy.abs(out)
484 485 z = cross/self.data.nFactor
485 486 #print("here")
486 487 #print(dataOut.data_spc[0,0,0])
487 488 #exit()
488 489
489 490 cross = 10*numpy.log10(z)
490 491 #print(numpy.shape(cross))
491 492 #print(cross[0,:])
492 493 #print(self.data.nFactor)
493 494 #exit()
494 495 #phase = numpy.arctan2(out.imag, out.real) * 180 / numpy.pi
495 496
496 497 ax = self.axes[1 * n]
497 498 if ax.firsttime:
498 499 self.xmax = self.xmax if self.xmax else numpy.nanmax(x)
499 500 self.xmin = self.xmin if self.xmin else -self.xmax
500 501 self.zmin = self.zmin if self.zmin else numpy.nanmin(cross)
501 502 self.zmax = self.zmax if self.zmax else numpy.nanmax(cross)
502 503 ax.plt = ax.pcolormesh(x, y, cross.T,
503 504 vmin=self.zmin,
504 505 vmax=self.zmax,
505 506 cmap=plt.get_cmap(self.colormap)
506 507 )
507 508 else:
508 509 ax.plt.set_array(cross.T.ravel())
509 510 self.titles.append(
510 511 'Cross Spectra Power Ch{} * Ch{}'.format(pair[0], pair[1]))
511 512
512 513
513 514 class CrossSpectra3Plot(Plot):
514 515
515 516 CODE = 'cspc'
516 517 colormap = 'jet'
517 518 plot_type = 'pcolor'
518 519 zmin_coh = None
519 520 zmax_coh = None
520 521 zmin_phase = None
521 522 zmax_phase = None
522 523
523 524 def setup(self):
524 525
525 526 self.ncols = 3
526 527 self.nrows = len(self.data.pairs)
527 528 self.nplots = self.nrows * 3
528 529 self.width = 3.1 * self.ncols
529 530 self.height = 5 * self.nrows
530 531 self.ylabel = 'Range [km]'
531 532 self.showprofile = False
532 533 self.plots_adjust.update({'left': 0.22, 'right': .90, 'wspace': 0.5, 'hspace':0.4, 'top':0.95, 'bottom': 0.08})
533 534
534 535 def plot(self):
535 536
536 537 if self.xaxis == "frequency":
537 538 x = self.data.xrange[0]
538 539 self.xlabel = "Frequency (kHz)"
539 540 elif self.xaxis == "time":
540 541 x = self.data.xrange[1]
541 542 self.xlabel = "Time (ms)"
542 543 else:
543 544 x = self.data.xrange[2]
544 545 self.xlabel = "Velocity (m/s)"
545 546
546 547 self.titles = []
547 548
548 549
549 550 y = self.data.heights
550 551 self.y = y
551 552 #nspc = self.data['spc']
552 553 #print(numpy.shape(self.data['spc']))
553 554 #spc = self.data['cspc'][0]
554 555 #print(numpy.shape(spc))
555 556 #exit()
556 557 cspc = self.data['cspc'][1]
557 558 #print(numpy.shape(cspc))
558 559 #exit()
559 560
560 561 for n in range(self.nrows):
561 562 noise = self.data['noise'][:,-1]
562 563 pair = self.data.pairs[n]
563 564 #print(pair) #exit()
564 565
565 566
566 567
567 568 out = cspc[n]# / numpy.sqrt(spc[pair[0]] * spc[pair[1]])
568 569
569 570 #print(out[:,53])
570 571 #exit()
571 572 cross = numpy.abs(out)
572 573 z = cross/self.data.nFactor
573 574 cross = 10*numpy.log10(z)
574 575
575 576 out_r= out.real/self.data.nFactor
576 577 #out_r = 10*numpy.log10(out_r)
577 578
578 579 out_i= out.imag/self.data.nFactor
579 580 #out_i = 10*numpy.log10(out_i)
580 581 #print(numpy.shape(cross))
581 582 #print(cross[0,:])
582 583 #print(self.data.nFactor)
583 584 #exit()
584 585 #phase = numpy.arctan2(out.imag, out.real) * 180 / numpy.pi
585 586
586 587 ax = self.axes[3 * n]
587 588 if ax.firsttime:
588 589 self.xmax = self.xmax if self.xmax else numpy.nanmax(x)
589 590 self.xmin = self.xmin if self.xmin else -self.xmax
590 591 self.zmin = self.zmin if self.zmin else numpy.nanmin(cross)
591 592 self.zmax = self.zmax if self.zmax else numpy.nanmax(cross)
592 593 ax.plt = ax.pcolormesh(x, y, cross.T,
593 594 vmin=self.zmin,
594 595 vmax=self.zmax,
595 596 cmap=plt.get_cmap(self.colormap)
596 597 )
597 598 else:
598 599 ax.plt.set_array(cross.T.ravel())
599 600 self.titles.append(
600 601 'Cross Spectra Power Ch{} * Ch{}'.format(pair[0], pair[1]))
601 602
602 603 ax = self.axes[3 * n + 1]
603 604 if ax.firsttime:
604 605 self.xmax = self.xmax if self.xmax else numpy.nanmax(x)
605 606 self.xmin = self.xmin if self.xmin else -self.xmax
606 607 self.zmin = self.zmin if self.zmin else numpy.nanmin(cross)
607 608 self.zmax = self.zmax if self.zmax else numpy.nanmax(cross)
608 609 ax.plt = ax.pcolormesh(x, y, out_r.T,
609 610 vmin=-1.e6,
610 611 vmax=0,
611 612 cmap=plt.get_cmap(self.colormap)
612 613 )
613 614 else:
614 615 ax.plt.set_array(out_r.T.ravel())
615 616 self.titles.append(
616 617 'Cross Spectra Real Ch{} * Ch{}'.format(pair[0], pair[1]))
617 618
618 619 ax = self.axes[3 * n + 2]
619 620
620 621
621 622 if ax.firsttime:
622 623 self.xmax = self.xmax if self.xmax else numpy.nanmax(x)
623 624 self.xmin = self.xmin if self.xmin else -self.xmax
624 625 self.zmin = self.zmin if self.zmin else numpy.nanmin(cross)
625 626 self.zmax = self.zmax if self.zmax else numpy.nanmax(cross)
626 627 ax.plt = ax.pcolormesh(x, y, out_i.T,
627 628 vmin=-1.e6,
628 629 vmax=1.e6,
629 630 cmap=plt.get_cmap(self.colormap)
630 631 )
631 632 else:
632 633 ax.plt.set_array(out_i.T.ravel())
633 634 self.titles.append(
634 635 'Cross Spectra Imag Ch{} * Ch{}'.format(pair[0], pair[1]))
635 636
636 637 class RTIPlot(Plot):
637 638 '''
638 639 Plot for RTI data
639 640 '''
640 641
641 642 CODE = 'rti'
642 643 colormap = 'jet'
643 644 plot_type = 'pcolorbuffer'
644 645
645 646 def setup(self):
646 647 self.xaxis = 'time'
647 648 self.ncols = 1
648 649 self.nrows = len(self.data.channels)
649 650 self.nplots = len(self.data.channels)
650 651 self.ylabel = 'Range [km]'
651 652 self.xlabel = 'Time'
652 653 self.cb_label = 'dB'
653 654 self.plots_adjust.update({'hspace':0.8, 'left': 0.1, 'bottom': 0.1, 'right':0.95})
654 655 self.titles = ['{} Channel {}'.format(
655 656 self.CODE.upper(), x) for x in range(self.nrows)]
656 657
657 658 def update(self, dataOut):
658 659
659 660 data = {}
660 661 meta = {}
661 662 data['rti'] = dataOut.getPower()
662 663 data['noise'] = 10 * numpy.log10(dataOut.getNoise() / dataOut.normFactor)
663 664
664 665 return data, meta
665 666
666 667 def plot(self):
667 668 self.x = self.data.times
668 669 self.y = self.data.yrange
669 670 self.z = self.data[self.CODE]
670 671
671 672 self.z = numpy.ma.masked_invalid(self.z)
672 673
673 674 if self.decimation is None:
674 675 x, y, z = self.fill_gaps(self.x, self.y, self.z)
675 676 else:
676 677 x, y, z = self.fill_gaps(*self.decimate())
677 678
678 679 for n, ax in enumerate(self.axes):
679 680 self.zmin = self.zmin if self.zmin else numpy.min(self.z)
680 681 self.zmax = self.zmax if self.zmax else numpy.max(self.z)
681 682 if ax.firsttime:
682 683 ax.plt = ax.pcolormesh(x, y, z[n].T,
683 684 vmin=self.zmin,
684 685 vmax=self.zmax,
685 686 cmap=plt.get_cmap(self.colormap)
686 687 )
687 688 if self.showprofile:
688 689 ax.plot_profile = self.pf_axes[n].plot(
689 690 self.data['rti'][n][-1], self.y)[0]
690 691 ax.plot_noise = self.pf_axes[n].plot(numpy.repeat(self.data['noise'][n][-1], len(self.y)), self.y,
691 692 color="k", linestyle="dashed", lw=1)[0]
692 693 else:
693 694 ax.plt.remove()
694 695 ax.plt = ax.pcolormesh(x, y, z[n].T,
695 696 vmin=self.zmin,
696 697 vmax=self.zmax,
697 698 cmap=plt.get_cmap(self.colormap)
698 699 )
699 700 if self.showprofile:
700 701 ax.plot_profile.set_data(self.data['rti'][n][-1], self.y)
701 702 ax.plot_noise.set_data(numpy.repeat(
702 703 self.data['noise'][n][-1], len(self.y)), self.y)
703 704
704 705
705 706 class SpectrogramPlot(Plot):
706 707 '''
707 708 Plot for Spectrogram data
708 709 '''
709 710
710 711 CODE = 'spectrogram'
711 712 colormap = 'binary'
712 713 plot_type = 'pcolorbuffer'
713 714
714 715 def setup(self):
715 716 self.xaxis = 'time'
716 717 self.ncols = 1
717 718 self.nrows = len(self.data.channels)
718 719 self.nplots = len(self.data.channels)
719 720 self.xlabel = 'Time'
720 721 self.cb_label = 'dB'
721 722 self.plots_adjust.update({'hspace':1.2, 'left': 0.1, 'bottom': 0.12, 'right':0.95})
722 723 self.titles = ['{} Channel {} \n H = {} km ({} - {})'.format(
723 724 self.CODE.upper(), x, self.data.heightList[self.data.hei], self.data.heightList[self.data.hei],self.data.heightList[self.data.hei]+(self.data.DH*self.data.nProfiles)) for x in range(self.nrows)]
724 725
725 726 def plot(self):
726 727
727 728 self.x = self.data.times
728 729 self.z = self.data[self.CODE]
729 730 self.y = self.data.xrange[0]
730 731
731 732 self.ylabel = "Frequency (kHz)"
732 733
733 734 self.z = numpy.ma.masked_invalid(self.z)
734 735
735 736 if self.decimation is None:
736 737 x, y, z = self.fill_gaps(self.x, self.y, self.z)
737 738 else:
738 739 x, y, z = self.fill_gaps(*self.decimate())
739 740
740 741 for n, ax in enumerate(self.axes):
741 742 self.zmin = self.zmin if self.zmin else numpy.min(self.z)
742 743 self.zmax = self.zmax if self.zmax else numpy.max(self.z)
743 744 data = self.data[-1]
744 745 if ax.firsttime:
745 746 ax.plt = ax.pcolormesh(x, y, z[n].T,
746 747 vmin=self.zmin,
747 748 vmax=self.zmax,
748 749 cmap=plt.get_cmap(self.colormap)
749 750 )
750 751 if self.showprofile:
751 752 ax.plot_profile = self.pf_axes[n].plot(
752 753 data['rti'][n], self.y)[0]
753 754 ax.plot_noise = self.pf_axes[n].plot(numpy.repeat(data['noise'][n], len(self.y)), self.y,
754 755 color="k", linestyle="dashed", lw=1)[0]
755 756 else:
756 757 ax.plt.remove()
757 758 ax.plt = ax.pcolormesh(x, y, z[n].T,
758 759 vmin=self.zmin,
759 760 vmax=self.zmax,
760 761 cmap=plt.get_cmap(self.colormap)
761 762 )
762 763 if self.showprofile:
763 764 ax.plot_profile.set_data(data['rti'][n], self.y)
764 765 ax.plot_noise.set_data(numpy.repeat(
765 766 data['noise'][n], len(self.y)), self.y)
766 767
767 768
768 769 class CoherencePlot(RTIPlot):
769 770 '''
770 771 Plot for Coherence data
771 772 '''
772 773
773 774 CODE = 'coh'
774 775
775 776 def setup(self):
776 777 self.xaxis = 'time'
777 778 self.ncols = 1
778 779 self.nrows = len(self.data.pairs)
779 780 self.nplots = len(self.data.pairs)
780 781 self.ylabel = 'Range [km]'
781 782 self.xlabel = 'Time'
782 783 self.plots_adjust.update({'hspace':0.6, 'left': 0.1, 'bottom': 0.1, 'right':0.95})
783 784 if self.CODE == 'coh':
784 785 self.cb_label = ''
785 786 self.titles = [
786 787 'Coherence Map Ch{} * Ch{}'.format(x[0], x[1]) for x in self.data.pairs]
787 788 else:
788 789 self.cb_label = 'Degrees'
789 790 self.titles = [
790 791 'Phase Map Ch{} * Ch{}'.format(x[0], x[1]) for x in self.data.pairs]
791 792
792 793 def update(self, dataOut):
793 794
794 795 data = {}
795 796 meta = {}
796 797 data['coh'] = dataOut.getCoherence()
797 798 meta['pairs'] = dataOut.pairsList
798 799
799 800 return data, meta
800 801
801 802 class PhasePlot(CoherencePlot):
802 803 '''
803 804 Plot for Phase map data
804 805 '''
805 806
806 807 CODE = 'phase'
807 808 colormap = 'seismic'
808 809
809 810 def update(self, dataOut):
810 811
811 812 data = {}
812 813 meta = {}
813 814 data['phase'] = dataOut.getCoherence(phase=True)
814 815 meta['pairs'] = dataOut.pairsList
815 816
816 817 return data, meta
817 818
818 819 class NoisePlot(Plot):
819 820 '''
820 821 Plot for noise
821 822 '''
822 823
823 824 CODE = 'noise'
824 825 plot_type = 'scatterbuffer'
825 826
826 827 def setup(self):
827 828 self.xaxis = 'time'
828 829 self.ncols = 1
829 830 self.nrows = 1
830 831 self.nplots = 1
831 832 self.ylabel = 'Intensity [dB]'
832 833 self.xlabel = 'Time'
833 834 self.titles = ['Noise']
834 835 self.colorbar = False
835 836 self.plots_adjust.update({'right': 0.85 })
836 837
837 838 def update(self, dataOut):
838 839
839 840 data = {}
840 841 meta = {}
841 842 data['noise'] = 10 * numpy.log10(dataOut.getNoise() / dataOut.normFactor).reshape(dataOut.nChannels, 1)
842 843 meta['yrange'] = numpy.array([])
843 844
844 845 return data, meta
845 846
846 847 def plot(self):
847 848
848 849 x = self.data.times
849 850 xmin = self.data.min_time
850 851 xmax = xmin + self.xrange * 60 * 60
851 852 Y = self.data['noise']
852 853
853 854 if self.axes[0].firsttime:
854 855 self.ymin = numpy.nanmin(Y) - 5
855 856 self.ymax = numpy.nanmax(Y) + 5
856 857 for ch in self.data.channels:
857 858 y = Y[ch]
858 859 self.axes[0].plot(x, y, lw=1, label='Ch{}'.format(ch))
859 860 plt.legend(bbox_to_anchor=(1.18, 1.0))
860 861 else:
861 862 for ch in self.data.channels:
862 863 y = Y[ch]
863 864 self.axes[0].lines[ch].set_data(x, y)
864 865
865 866 self.ymin = numpy.nanmin(Y) - 5
866 867 self.ymax = numpy.nanmax(Y) + 10
867 868
868 869
869 870 class PowerProfilePlot(Plot):
870 871
871 872 CODE = 'pow_profile'
872 873 plot_type = 'scatter'
873 874
874 875 def setup(self):
875 876
876 877 self.ncols = 1
877 878 self.nrows = 1
878 879 self.nplots = 1
879 880 self.height = 4
880 881 self.width = 3
881 882 self.ylabel = 'Range [km]'
882 883 self.xlabel = 'Intensity [dB]'
883 884 self.titles = ['Power Profile']
884 885 self.colorbar = False
885 886
886 887 def update(self, dataOut):
887 888
888 889 data = {}
889 890 meta = {}
890 891 data[self.CODE] = dataOut.getPower()
891 892
892 893 return data, meta
893 894
894 895 def plot(self):
895 896
896 897 y = self.data.yrange
897 898 self.y = y
898 899
899 900 x = self.data[-1][self.CODE]
900 901
901 902 if self.xmin is None: self.xmin = numpy.nanmin(x) * 0.9
902 903 if self.xmax is None: self.xmax = numpy.nanmax(x) * 1.1
903 904
904 905 if self.axes[0].firsttime:
905 906 for ch in self.data.channels:
906 907 self.axes[0].plot(x[ch], y, lw=1, label='Ch{}'.format(ch))
907 908 plt.legend()
908 909 else:
909 910 for ch in self.data.channels:
910 911 self.axes[0].lines[ch].set_data(x[ch], y)
911 912
912 913
913 914 class SpectraCutPlot(Plot):
914 915
915 916 CODE = 'spc_cut'
916 917 plot_type = 'scatter'
917 918 buffering = False
918 919
919 920 def setup(self):
920 921
921 922 self.nplots = len(self.data.channels)
922 923 self.ncols = int(numpy.sqrt(self.nplots) + 0.9)
923 924 self.nrows = int((1.0 * self.nplots / self.ncols) + 0.9)
924 925 self.width = 3.4 * self.ncols + 1.5
925 926 self.height = 3 * self.nrows
926 927 self.ylabel = 'Power [dB]'
927 928 self.colorbar = False
928 929 self.plots_adjust.update({'left':0.1, 'hspace':0.3, 'right': 0.75, 'bottom':0.08})
929 930
930 931 def update(self, dataOut):
931 932
932 933 data = {}
933 934 meta = {}
934 935 spc = 10 * numpy.log10(dataOut.data_pre[0] / dataOut.normFactor)
935 936 data['spc'] = spc
936 937 meta['xrange'] = (dataOut.getFreqRange(1) / 1000., dataOut.getAcfRange(1), dataOut.getVelRange(1))
937 938 if self.CODE == 'cut_gaussian_fit':
938 939 data['gauss_fit0'] = 10 * numpy.log10(dataOut.GaussFit0 / dataOut.normFactor)
939 940 data['gauss_fit1'] = 10 * numpy.log10(dataOut.GaussFit1 / dataOut.normFactor)
940 941 return data, meta
941 942
942 943 def plot(self):
943 944 if self.xaxis == "frequency":
944 945 x = self.data.xrange[0][1:]
945 946 self.xlabel = "Frequency (kHz)"
946 947 elif self.xaxis == "time":
947 948 x = self.data.xrange[1]
948 949 self.xlabel = "Time (ms)"
949 950 else:
950 951 x = self.data.xrange[2][:-1]
951 952 self.xlabel = "Velocity (m/s)"
952 953
953 954 if self.CODE == 'cut_gaussian_fit':
954 955 x = self.data.xrange[2][:-1]
955 956 self.xlabel = "Velocity (m/s)"
956 957
957 958 self.titles = []
958 959
959 960 y = self.data.yrange
960 961 data = self.data[-1]
961 962 z = data['spc']
962 963
963 964 if self.height_index:
964 965 index = numpy.array(self.height_index)
965 966 else:
966 967 index = numpy.arange(0, len(y), int((len(y)) / 9))
967 968
968 969 for n, ax in enumerate(self.axes):
969 970 if self.CODE == 'cut_gaussian_fit':
970 971 gau0 = data['gauss_fit0']
971 972 gau1 = data['gauss_fit1']
972 973 if ax.firsttime:
973 974 self.xmax = self.xmax if self.xmax else numpy.nanmax(x)
974 975 self.xmin = self.xmin if self.xmin else -self.xmax
975 976 self.ymin = self.ymin if self.ymin else numpy.nanmin(z)
976 977 self.ymax = self.ymax if self.ymax else numpy.nanmax(z)
977 978 ax.plt = ax.plot(x, z[n, :, index].T, lw=0.25)
978 979 if self.CODE == 'cut_gaussian_fit':
979 980 ax.plt_gau0 = ax.plot(x, gau0[n, :, index].T, lw=1, linestyle='-.')
980 981 for i, line in enumerate(ax.plt_gau0):
981 982 line.set_color(ax.plt[i].get_color())
982 983 ax.plt_gau1 = ax.plot(x, gau1[n, :, index].T, lw=1, linestyle='--')
983 984 for i, line in enumerate(ax.plt_gau1):
984 985 line.set_color(ax.plt[i].get_color())
985 986 labels = ['Range = {:2.1f}km'.format(y[i]) for i in index]
986 987 self.figures[0].legend(ax.plt, labels, loc='center right')
987 988 else:
988 989 for i, line in enumerate(ax.plt):
989 990 line.set_data(x, z[n, :, index[i]].T)
990 991 for i, line in enumerate(ax.plt_gau0):
991 992 line.set_data(x, gau0[n, :, index[i]].T)
992 993 line.set_color(ax.plt[i].get_color())
993 994 for i, line in enumerate(ax.plt_gau1):
994 995 line.set_data(x, gau1[n, :, index[i]].T)
995 996 line.set_color(ax.plt[i].get_color())
996 997 self.titles.append('CH {}'.format(n))
997 998
998 999
999 1000 class BeaconPhase(Plot):
1000 1001
1001 1002 __isConfig = None
1002 1003 __nsubplots = None
1003 1004
1004 1005 PREFIX = 'beacon_phase'
1005 1006
1006 1007 def __init__(self):
1007 1008 Plot.__init__(self)
1008 1009 self.timerange = 24 * 60 * 60
1009 1010 self.isConfig = False
1010 1011 self.__nsubplots = 1
1011 1012 self.counter_imagwr = 0
1012 1013 self.WIDTH = 800
1013 1014 self.HEIGHT = 400
1014 1015 self.WIDTHPROF = 120
1015 1016 self.HEIGHTPROF = 0
1016 1017 self.xdata = None
1017 1018 self.ydata = None
1018 1019
1019 1020 self.PLOT_CODE = BEACON_CODE
1020 1021
1021 1022 self.FTP_WEI = None
1022 1023 self.EXP_CODE = None
1023 1024 self.SUB_EXP_CODE = None
1024 1025 self.PLOT_POS = None
1025 1026
1026 1027 self.filename_phase = None
1027 1028
1028 1029 self.figfile = None
1029 1030
1030 1031 self.xmin = None
1031 1032 self.xmax = None
1032 1033
1033 1034 def getSubplots(self):
1034 1035
1035 1036 ncol = 1
1036 1037 nrow = 1
1037 1038
1038 1039 return nrow, ncol
1039 1040
1040 1041 def setup(self, id, nplots, wintitle, showprofile=True, show=True):
1041 1042
1042 1043 self.__showprofile = showprofile
1043 1044 self.nplots = nplots
1044 1045
1045 1046 ncolspan = 7
1046 1047 colspan = 6
1047 1048 self.__nsubplots = 2
1048 1049
1049 1050 self.createFigure(id=id,
1050 1051 wintitle=wintitle,
1051 1052 widthplot=self.WIDTH + self.WIDTHPROF,
1052 1053 heightplot=self.HEIGHT + self.HEIGHTPROF,
1053 1054 show=show)
1054 1055
1055 1056 nrow, ncol = self.getSubplots()
1056 1057
1057 1058 self.addAxes(nrow, ncol * ncolspan, 0, 0, colspan, 1)
1058 1059
1059 1060 def save_phase(self, filename_phase):
1060 1061 f = open(filename_phase, 'w+')
1061 1062 f.write('\n\n')
1062 1063 f.write('JICAMARCA RADIO OBSERVATORY - Beacon Phase \n')
1063 1064 f.write('DD MM YYYY HH MM SS pair(2,0) pair(2,1) pair(2,3) pair(2,4)\n\n')
1064 1065 f.close()
1065 1066
1066 1067 def save_data(self, filename_phase, data, data_datetime):
1067 1068 f = open(filename_phase, 'a')
1068 1069 timetuple_data = data_datetime.timetuple()
1069 1070 day = str(timetuple_data.tm_mday)
1070 1071 month = str(timetuple_data.tm_mon)
1071 1072 year = str(timetuple_data.tm_year)
1072 1073 hour = str(timetuple_data.tm_hour)
1073 1074 minute = str(timetuple_data.tm_min)
1074 1075 second = str(timetuple_data.tm_sec)
1075 1076 f.write(day + ' ' + month + ' ' + year + ' ' + hour + ' ' + minute + ' ' + second + ' ' + str(data[0]) + ' ' + str(data[1]) + ' ' + str(data[2]) + ' ' + str(data[3]) + '\n')
1076 1077 f.close()
1077 1078
1078 1079 def plot(self):
1079 1080 log.warning('TODO: Not yet implemented...')
1080 1081
1081 1082 def run(self, dataOut, id, wintitle="", pairsList=None, showprofile='True',
1082 1083 xmin=None, xmax=None, ymin=None, ymax=None, hmin=None, hmax=None,
1083 1084 timerange=None,
1084 1085 save=False, figpath='./', figfile=None, show=True, ftp=False, wr_period=1,
1085 1086 server=None, folder=None, username=None, password=None,
1086 1087 ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0):
1087 1088
1088 1089 if dataOut.flagNoData:
1089 1090 return dataOut
1090 1091
1091 1092 if not isTimeInHourRange(dataOut.datatime, xmin, xmax):
1092 1093 return
1093 1094
1094 1095 if pairsList == None:
1095 1096 pairsIndexList = dataOut.pairsIndexList[:10]
1096 1097 else:
1097 1098 pairsIndexList = []
1098 1099 for pair in pairsList:
1099 1100 if pair not in dataOut.pairsList:
1100 1101 raise ValueError("Pair %s is not in dataOut.pairsList" % (pair))
1101 1102 pairsIndexList.append(dataOut.pairsList.index(pair))
1102 1103
1103 1104 if pairsIndexList == []:
1104 1105 return
1105 1106
1106 1107 # if len(pairsIndexList) > 4:
1107 1108 # pairsIndexList = pairsIndexList[0:4]
1108 1109
1109 1110 hmin_index = None
1110 1111 hmax_index = None
1111 1112
1112 1113 if hmin != None and hmax != None:
1113 1114 indexes = numpy.arange(dataOut.nHeights)
1114 1115 hmin_list = indexes[dataOut.heightList >= hmin]
1115 1116 hmax_list = indexes[dataOut.heightList <= hmax]
1116 1117
1117 1118 if hmin_list.any():
1118 1119 hmin_index = hmin_list[0]
1119 1120
1120 1121 if hmax_list.any():
1121 1122 hmax_index = hmax_list[-1] + 1
1122 1123
1123 1124 x = dataOut.getTimeRange()
1124 1125
1125 1126 thisDatetime = dataOut.datatime
1126 1127
1127 1128 title = wintitle + " Signal Phase" # : %s" %(thisDatetime.strftime("%d-%b-%Y"))
1128 1129 xlabel = "Local Time"
1129 1130 ylabel = "Phase (degrees)"
1130 1131
1131 1132 update_figfile = False
1132 1133
1133 1134 nplots = len(pairsIndexList)
1134 1135 # phase = numpy.zeros((len(pairsIndexList),len(dataOut.beacon_heiIndexList)))
1135 1136 phase_beacon = numpy.zeros(len(pairsIndexList))
1136 1137 for i in range(nplots):
1137 1138 pair = dataOut.pairsList[pairsIndexList[i]]
1138 1139 ccf = numpy.average(dataOut.data_cspc[pairsIndexList[i], :, hmin_index:hmax_index], axis=0)
1139 1140 powa = numpy.average(dataOut.data_spc[pair[0], :, hmin_index:hmax_index], axis=0)
1140 1141 powb = numpy.average(dataOut.data_spc[pair[1], :, hmin_index:hmax_index], axis=0)
1141 1142 avgcoherenceComplex = ccf / numpy.sqrt(powa * powb)
1142 1143 phase = numpy.arctan2(avgcoherenceComplex.imag, avgcoherenceComplex.real) * 180 / numpy.pi
1143 1144
1144 1145 if dataOut.beacon_heiIndexList:
1145 1146 phase_beacon[i] = numpy.average(phase[dataOut.beacon_heiIndexList])
1146 1147 else:
1147 1148 phase_beacon[i] = numpy.average(phase)
1148 1149
1149 1150 if not self.isConfig:
1150 1151
1151 1152 nplots = len(pairsIndexList)
1152 1153
1153 1154 self.setup(id=id,
1154 1155 nplots=nplots,
1155 1156 wintitle=wintitle,
1156 1157 showprofile=showprofile,
1157 1158 show=show)
1158 1159
1159 1160 if timerange != None:
1160 1161 self.timerange = timerange
1161 1162
1162 1163 self.xmin, self.xmax = self.getTimeLim(x, xmin, xmax, timerange)
1163 1164
1164 1165 if ymin == None: ymin = 0
1165 1166 if ymax == None: ymax = 360
1166 1167
1167 1168 self.FTP_WEI = ftp_wei
1168 1169 self.EXP_CODE = exp_code
1169 1170 self.SUB_EXP_CODE = sub_exp_code
1170 1171 self.PLOT_POS = plot_pos
1171 1172
1172 1173 self.name = thisDatetime.strftime("%Y%m%d_%H%M%S")
1173 1174 self.isConfig = True
1174 1175 self.figfile = figfile
1175 1176 self.xdata = numpy.array([])
1176 1177 self.ydata = numpy.array([])
1177 1178
1178 1179 update_figfile = True
1179 1180
1180 1181 # open file beacon phase
1181 1182 path = '%s%03d' % (self.PREFIX, self.id)
1182 1183 beacon_file = os.path.join(path, '%s.txt' % self.name)
1183 1184 self.filename_phase = os.path.join(figpath, beacon_file)
1184 1185 # self.save_phase(self.filename_phase)
1185 1186
1186 1187
1187 1188 # store data beacon phase
1188 1189 # self.save_data(self.filename_phase, phase_beacon, thisDatetime)
1189 1190
1190 1191 self.setWinTitle(title)
1191 1192
1192 1193
1193 1194 title = "Phase Plot %s" % (thisDatetime.strftime("%Y/%m/%d %H:%M:%S"))
1194 1195
1195 1196 legendlabels = ["Pair (%d,%d)" % (pair[0], pair[1]) for pair in dataOut.pairsList]
1196 1197
1197 1198 axes = self.axesList[0]
1198 1199
1199 1200 self.xdata = numpy.hstack((self.xdata, x[0:1]))
1200 1201
1201 1202 if len(self.ydata) == 0:
1202 1203 self.ydata = phase_beacon.reshape(-1, 1)
1203 1204 else:
1204 1205 self.ydata = numpy.hstack((self.ydata, phase_beacon.reshape(-1, 1)))
1205 1206
1206 1207
1207 1208 axes.pmultilineyaxis(x=self.xdata, y=self.ydata,
1208 1209 xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax,
1209 1210 xlabel=xlabel, ylabel=ylabel, title=title, legendlabels=legendlabels, marker='x', markersize=8, linestyle="solid",
1210 1211 XAxisAsTime=True, grid='both'
1211 1212 )
1212 1213
1213 1214 self.draw()
1214 1215
1215 1216 if dataOut.ltctime >= self.xmax:
1216 1217 self.counter_imagwr = wr_period
1217 1218 self.isConfig = False
1218 1219 update_figfile = True
1219 1220
1220 1221 self.save(figpath=figpath,
1221 1222 figfile=figfile,
1222 1223 save=save,
1223 1224 ftp=ftp,
1224 1225 wr_period=wr_period,
1225 1226 thisDatetime=thisDatetime,
1226 1227 update_figfile=update_figfile)
1227 1228
1228 1229 return dataOut
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