| @@ -21,12 +21,14 class SpectraPlot(Plot): | |||
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21 | 21 | colormap = 'jet' |
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22 | 22 | plot_type = 'pcolor' |
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23 | 23 | buffering = False |
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24 | channelList = None | |
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24 | 25 | |
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25 | 26 | def setup(self): |
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26 | 27 | self.nplots = len(self.data.channels) |
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27 | 28 | self.ncols = int(numpy.sqrt(self.nplots) + 0.9) |
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28 | 29 | self.nrows = int((1.0 * self.nplots / self.ncols) + 0.9) |
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29 | 30 | self.height = 2.6 * self.nrows |
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31 | ||
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30 | 32 | self.cb_label = 'dB' |
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31 | 33 | if self.showprofile: |
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32 | 34 | self.width = 4 * self.ncols |
| @@ -36,7 +38,8 class SpectraPlot(Plot): | |||
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36 | 38 | self.ylabel = 'Range [km]' |
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37 | 39 | |
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38 | 40 | def update(self, dataOut): |
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39 | ||
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41 | if self.channelList == None: | |
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42 | self.channelList = dataOut.channelList | |
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40 | 43 | data = {} |
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41 | 44 | meta = {} |
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42 | 45 | spc = 10*numpy.log10(dataOut.data_spc/dataOut.normFactor) |
| @@ -46,9 +49,9 class SpectraPlot(Plot): | |||
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46 | 49 | meta['xrange'] = (dataOut.getFreqRange(1)/1000., dataOut.getAcfRange(1), dataOut.getVelRange(1)) |
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47 | 50 | if self.CODE == 'spc_moments': |
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48 | 51 | data['moments'] = dataOut.moments |
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49 | ||
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50 |
return data, meta |
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51 | ||
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52 | ||
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53 | return data, meta | |
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54 | ||
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52 | 55 | def plot(self): |
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53 | 56 | if self.xaxis == "frequency": |
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54 | 57 | x = self.data.xrange[0] |
| @@ -101,7 +104,7 class SpectraPlot(Plot): | |||
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101 | 104 | ax.plt_noise.set_data(numpy.repeat(noise, len(y)), y) |
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102 | 105 | if self.CODE == 'spc_moments': |
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103 | 106 | ax.plt_mean.set_data(mean, y) |
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104 | self.titles.append('CH {}: {:3.2f}dB'.format(n, noise)) | |
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107 | self.titles.append('CH {}: {:3.2f}dB'.format(self.channelList[n], noise)) | |
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105 | 108 | |
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106 | 109 | |
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107 | 110 | class CrossSpectraPlot(Plot): |
| @@ -146,8 +149,8 class CrossSpectraPlot(Plot): | |||
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146 | 149 | |
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147 | 150 | data['cspc'] = numpy.array(tmp) |
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148 | 151 | |
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149 |
return data, meta |
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150 | ||
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152 | return data, meta | |
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153 | ||
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151 | 154 | def plot(self): |
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152 | 155 | |
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153 | 156 | if self.xaxis == "frequency": |
| @@ -159,7 +162,7 class CrossSpectraPlot(Plot): | |||
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159 | 162 | else: |
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160 | 163 | x = self.data.xrange[2] |
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161 | 164 | self.xlabel = "Velocity (m/s)" |
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162 | ||
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165 | ||
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163 | 166 | self.titles = [] |
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164 | 167 | |
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165 | 168 | y = self.data.yrange |
| @@ -183,13 +186,13 class CrossSpectraPlot(Plot): | |||
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183 | 186 | ax.plt.set_array(coh.T.ravel()) |
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184 | 187 | self.titles.append( |
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185 | 188 | 'Coherence Ch{} * Ch{}'.format(pair[0], pair[1])) |
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186 | ||
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189 | ||
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187 | 190 | ax = self.axes[2 * n + 1] |
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188 | 191 | if ax.firsttime: |
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189 | 192 | ax.plt = ax.pcolormesh(x, y, phase.T, |
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190 | 193 | vmin=-180, |
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191 | 194 | vmax=180, |
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192 |
cmap=plt.get_cmap(self.colormap_phase) |
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195 | cmap=plt.get_cmap(self.colormap_phase) | |
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193 | 196 | ) |
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194 | 197 | else: |
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195 | 198 | ax.plt.set_array(phase.T.ravel()) |
| @@ -204,6 +207,8 class RTIPlot(Plot): | |||
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204 | 207 | CODE = 'rti' |
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205 | 208 | colormap = 'jet' |
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206 | 209 | plot_type = 'pcolorbuffer' |
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210 | titles = None | |
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211 | channelList = None | |
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207 | 212 | |
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208 | 213 | def setup(self): |
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209 | 214 | self.xaxis = 'time' |
| @@ -215,10 +220,11 class RTIPlot(Plot): | |||
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215 | 220 | self.cb_label = 'dB' |
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216 | 221 | self.plots_adjust.update({'hspace':0.8, 'left': 0.1, 'bottom': 0.08, 'right':0.95}) |
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217 | 222 | self.titles = ['{} Channel {}'.format( |
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218 |
self.CODE.upper(), x) for x in range(self.n |
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223 | self.CODE.upper(), x) for x in range(self.nplots)] | |
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219 | 224 | |
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220 | 225 | def update(self, dataOut): |
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221 | ||
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226 | if self.channelList == None: | |
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227 | self.channelList = dataOut.channelList | |
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222 | 228 | data = {} |
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223 | 229 | meta = {} |
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224 | 230 | data['rti'] = dataOut.getPower() |
| @@ -231,6 +237,9 class RTIPlot(Plot): | |||
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231 | 237 | self.y = self.data.yrange |
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232 | 238 | self.z = self.data[self.CODE] |
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233 | 239 | self.z = numpy.ma.masked_invalid(self.z) |
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240 | if self.channelList != None: | |
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241 | self.titles = ['{} Channel {}'.format( | |
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242 | self.CODE.upper(), x) for x in self.channelList] | |
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234 | 243 | |
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235 | 244 | if self.decimation is None: |
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236 | 245 | x, y, z = self.fill_gaps(self.x, self.y, self.z) |
| @@ -317,7 +326,7 class PhasePlot(CoherencePlot): | |||
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317 | 326 | |
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318 | 327 | class NoisePlot(Plot): |
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319 | 328 | ''' |
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320 |
Plot for noise |
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329 | Plot for noise | |
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321 | 330 | ''' |
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322 | 331 | |
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323 | 332 | CODE = 'noise' |
| @@ -362,7 +371,7 class NoisePlot(Plot): | |||
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362 | 371 | y = Y[ch] |
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363 | 372 | self.axes[0].lines[ch].set_data(x, y) |
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364 | 373 | |
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365 | ||
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374 | ||
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366 | 375 | class PowerProfilePlot(Plot): |
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367 | 376 | |
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368 | 377 | CODE = 'pow_profile' |
| @@ -394,10 +403,10 class PowerProfilePlot(Plot): | |||
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394 | 403 | self.y = y |
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395 | 404 | |
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396 | 405 | x = self.data[-1][self.CODE] |
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397 | ||
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406 | ||
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398 | 407 | if self.xmin is None: self.xmin = numpy.nanmin(x)*0.9 |
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399 | 408 | if self.xmax is None: self.xmax = numpy.nanmax(x)*1.1 |
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400 | ||
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409 | ||
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401 | 410 | if self.axes[0].firsttime: |
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402 | 411 | for ch in self.data.channels: |
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403 | 412 | self.axes[0].plot(x[ch], y, lw=1, label='Ch{}'.format(ch)) |
| @@ -559,7 +568,7 class BeaconPhase(Plot): | |||
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559 | 568 | server=None, folder=None, username=None, password=None, |
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560 | 569 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0): |
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561 | 570 | |
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562 |
if dataOut.flagNoData: |
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571 | if dataOut.flagNoData: | |
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563 | 572 | return dataOut |
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564 | 573 | |
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565 | 574 | if not isTimeInHourRange(dataOut.datatime, xmin, xmax): |
| @@ -699,4 +708,4 class BeaconPhase(Plot): | |||
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699 | 708 | thisDatetime=thisDatetime, |
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700 | 709 | update_figfile=update_figfile) |
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701 | 710 | |
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702 | return dataOut No newline at end of file | |
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711 | return dataOut | |
| @@ -507,8 +507,7 class CleanRayleigh(Operation): | |||
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507 | 507 | self.buffer = 0 |
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508 | 508 | self.buffer2 = 0 |
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509 | 509 | self.buffer3 = 0 |
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510 | #self.min_hei = None | |
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511 | #self.max_hei = None | |
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510 | ||
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512 | 511 | |
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513 | 512 | def setup(self,dataOut,min_hei,max_hei,n, timeInterval,factor_stdv): |
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514 | 513 | |
| @@ -545,8 +544,7 class CleanRayleigh(Operation): | |||
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545 | 544 | self.currentTime = self.__initime |
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546 | 545 | self.pairsArray = numpy.array(dataOut.pairsList) |
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547 | 546 | self.factor_stdv = factor_stdv |
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548 | ||
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549 | ||
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547 | print("CHANNELS: ",[x for x in self.channels]) | |
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550 | 548 | |
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551 | 549 | if n != None : |
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552 | 550 | self.byProfiles = True |
| @@ -678,7 +676,7 class CleanRayleigh(Operation): | |||
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678 | 676 | dataOut.data_dc = self.buffer3 |
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679 | 677 | dataOut.nIncohInt *= self.nIntProfiles |
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680 | 678 | dataOut.utctime = self.currentTime #tiempo promediado |
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681 | print("Time: ",time.localtime(dataOut.utctime)) | |
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679 | #print("Time: ",time.localtime(dataOut.utctime)) | |
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682 | 680 | # dataOut.data_spc = sat_spectra |
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683 | 681 | # dataOut.data_cspc = sat_cspectra |
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684 | 682 | self.buffer = 0 |
| @@ -763,26 +761,27 class CleanRayleigh(Operation): | |||
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763 | 761 | if len(noval[0]) > 0: #forma de array (N,) es igual a longitud (N) |
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764 | 762 | novall = ((func2clean - mode) >= (factor_stdv*stdv)).nonzero() |
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765 | 763 | #print(novall) |
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766 | #print(" ") | |
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764 | #print(" ",self.pairsArray[ii]) | |
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767 | 765 | cross_pairs = self.pairsArray[ii] |
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768 | 766 | #Getting coherent echoes which are removed. |
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769 | if len(novall[0]) > 0: | |
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770 | ||
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771 | val_spc[novall[0],cross_pairs[0],ifreq,ih] = 1 | |
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772 | val_spc[novall[0],cross_pairs[1],ifreq,ih] = 1 | |
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773 | val_cspc[novall[0],ii,ifreq,ih] = 1 | |
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767 | # if len(novall[0]) > 0: | |
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768 | # | |
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769 | # val_spc[novall[0],cross_pairs[0],ifreq,ih] = 1 | |
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770 | # val_spc[novall[0],cross_pairs[1],ifreq,ih] = 1 | |
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771 | # val_cspc[novall[0],ii,ifreq,ih] = 1 | |
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774 | 772 | #print("OUT NOVALL 1") |
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775 | 773 | #Removing coherent from ISR data |
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774 | chA = self.channels.index(cross_pairs[0]) | |
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775 | chB = self.channels.index(cross_pairs[1]) | |
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776 | 776 | |
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777 | #print(spectra[:,ii,ifreq,ih]) | |
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778 | 777 | new_a = numpy.delete(cspectra[:,ii,ifreq,ih], noval[0]) |
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779 | 778 | mean_cspc = numpy.mean(new_a) |
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780 |
new_b = numpy.delete(spectra[:,c |
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779 | new_b = numpy.delete(spectra[:,chA,ifreq,ih], noval[0]) | |
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781 | 780 | mean_spc0 = numpy.mean(new_b) |
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782 |
new_c = numpy.delete(spectra[:,c |
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781 | new_c = numpy.delete(spectra[:,chB,ifreq,ih], noval[0]) | |
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783 | 782 | mean_spc1 = numpy.mean(new_c) |
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784 |
spectra[noval,c |
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785 |
spectra[noval,c |
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783 | spectra[noval,chA,ifreq,ih] = mean_spc0 | |
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784 | spectra[noval,chB,ifreq,ih] = mean_spc1 | |
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786 | 785 | cspectra[noval,ii,ifreq,ih] = mean_cspc |
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787 | 786 | |
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788 | 787 | ''' |
| @@ -112,7 +112,7 class selectChannels(Operation): | |||
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112 | 112 | self.dataOut.data_dc = data_dc |
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113 | 113 | |
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114 | 114 | # self.dataOut.channelList = [self.dataOut.channelList[i] for i in channelIndexList] |
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115 |
self.dataOut.channelList = |
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115 | self.dataOut.channelList = channelIndexList | |
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116 | 116 | self.__selectPairsByChannel(channelIndexList) |
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117 | 117 | |
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118 | 118 | return 1 |
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