Mercurial > public > atmospheric_lidar / file comparison
comparison: generic.py
generic.py
- changeset 15
- a0b073b1f684
- parent 14
- a267a7564570
- child 17
- 74449200826c
equal
deleted
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replaced
| 14:a267a7564570 | 15:a0b073b1f684 |
|---|---|
| 170 ''' | 170 ''' |
| 171 | 171 |
| 172 self.info['Temperature'] = 10.0 | 172 self.info['Temperature'] = 10.0 |
| 173 self.info['Pressure'] = 930.0 | 173 self.info['Pressure'] = 930.0 |
| 174 | 174 |
| 175 | 175 def subtract_dark(self): |
| 176 | |
| 177 if not self.dark_measurement: | |
| 178 raise IOError('No dark measurements have been imported yet.') | |
| 179 | |
| 180 for (channel_name, dark_channel) in self.dark_measurement.channels.iteritems(): | |
| 181 dark_profile = dark_channel.average_profile() | |
| 182 channel = self.channels[channel_name] | |
| 183 | |
| 184 for measurement_time, data in channel.data.iteritems(): | |
| 185 channel.data[measurement_time] = data - dark_profile | |
| 186 | |
| 187 channel.update() | |
| 188 | |
| 176 def save_as_netcdf(self, filename): | 189 def save_as_netcdf(self, filename): |
| 177 """Saves the measurement in the netcdf format as required by the SCC. | 190 """Saves the measurement in the netcdf format as required by the SCC. |
| 178 Input: filename | 191 Input: filename |
| 179 """ | 192 """ |
| 180 params = self.extra_netcdf_parameters | 193 params = self.extra_netcdf_parameters |
| 448 condition = (tim >= starttime) & (tim <= endtime) | 461 condition = (tim >= starttime) & (tim <= endtime) |
| 449 sl = data[condition, :] | 462 sl = data[condition, :] |
| 450 t = tim[condition] | 463 t = tim[condition] |
| 451 return sl,t | 464 return sl,t |
| 452 | 465 |
| 453 def av_profile(self, tim, duration = datetime.timedelta(seconds = 0), signal_type = 'rc'): | 466 def profile_for_duration(self, tim, duration = datetime.timedelta(seconds = 0), signal_type = 'rc'): |
| 467 """ Calculates the profile around a specific time (tim). """ | |
| 454 starttime = tim - duration/2 | 468 starttime = tim - duration/2 |
| 455 endtime = tim + duration/2 | 469 endtime = tim + duration/2 |
| 456 d,t = self.get_slice(starttime, endtime, signal_type = signal_type) | 470 d,t = self.get_slice(starttime, endtime, signal_type = signal_type) |
| 457 prof = np.mean(d, axis = 0) | 471 prof = np.mean(d, axis = 0) |
| 458 tmin = min(t) | 472 tmin = min(t) |
| 459 tmax = max(t) | 473 tmax = max(t) |
| 460 tav = tmin + (tmax-tmin)/2 | 474 tav = tmin + (tmax-tmin)/2 |
| 461 return prof,(tav, tmin,tmax) | 475 return prof,(tav, tmin,tmax) |
| 462 | 476 |
| 477 def average_profile(self): | |
| 478 """ Return the average profile (NOT range corrected) for all the duration of the measurement. """ | |
| 479 prof = np.mean(self.matrix, axis = 0) | |
| 480 return prof | |
| 481 | |
| 463 def plot(self, signal_type = 'rc', filename = None, zoom = [0,12000,0,-1], show_plot = True, cmap = plt.cm.jet): | 482 def plot(self, signal_type = 'rc', filename = None, zoom = [0,12000,0,-1], show_plot = True, cmap = plt.cm.jet): |
| 464 #if filename is not None: | 483 #if filename is not None: |
| 465 # matplotlib.use('Agg') | 484 # matplotlib.use('Agg') |
| 466 | 485 |
| 467 fig = plt.figure() | 486 fig = plt.figure() |
