@@ -231,7 +231,6 class Plot(Operation): | |||
|
231 | 231 | self.attr_time = kwargs.get('attr_time', 'utctime') |
|
232 | 232 | self.attr_data = kwargs.get('attr_data', 'data_param') |
|
233 | 233 | self.decimation = kwargs.get('decimation', None) |
|
234 | self.showSNR = kwargs.get('showSNR', False) | |
|
235 | 234 | self.oneFigure = kwargs.get('oneFigure', True) |
|
236 | 235 | self.width = kwargs.get('width', None) |
|
237 | 236 | self.height = kwargs.get('height', None) |
@@ -262,6 +261,9 class Plot(Operation): | |||
|
262 | 261 | self.name |
|
263 | 262 | ) |
|
264 | 263 | |
|
264 | if isinstance(self.attr_data, str): | |
|
265 | self.attr_data = [self.attr_data] | |
|
266 | ||
|
265 | 267 | def __setup_plot(self): |
|
266 | 268 | ''' |
|
267 | 269 | Common setup for all figures, here figures and axes are created |
@@ -322,6 +324,7 class Plot(Operation): | |||
|
322 | 324 | self.pf_axes.append(cax) |
|
323 | 325 | |
|
324 | 326 | for n in range(self.nrows): |
|
327 | print(self.nrows) | |
|
325 | 328 | if self.colormaps is not None: |
|
326 | 329 | cmap = plt.get_cmap(self.colormaps[n]) |
|
327 | 330 | else: |
@@ -503,33 +506,33 class Plot(Operation): | |||
|
503 | 506 | |
|
504 | 507 | fig = self.figures[n] |
|
505 | 508 | |
|
506 | figname = os.path.join( | |
|
507 | self.save, | |
|
508 | self.save_code, | |
|
509 | '{}_{}.png'.format( | |
|
510 | self.save_code, | |
|
511 | self.getDateTime(self.data.max_time).strftime( | |
|
512 | '%Y%m%d_%H%M%S' | |
|
513 | ), | |
|
514 | ) | |
|
515 | ) | |
|
516 | log.log('Saving figure: {}'.format(figname), self.name) | |
|
517 | if not os.path.isdir(os.path.dirname(figname)): | |
|
518 | os.makedirs(os.path.dirname(figname)) | |
|
519 | fig.savefig(figname) | |
|
520 | ||
|
521 | 509 | if self.throttle == 0: |
|
522 | 510 | figname = os.path.join( |
|
523 | 511 | self.save, |
|
524 | '{}_{}.png'.format( | |
|
512 | self.save_code, | |
|
513 | '{}_{}.png'.format( | |
|
525 | 514 | self.save_code, |
|
526 |
self.getDateTime(self.data.m |
|
|
527 | '%Y%m%d' | |
|
515 | self.getDateTime(self.data.max_time).strftime( | |
|
516 | '%Y%m%d_%H%M%S' | |
|
528 | 517 | ), |
|
529 | 518 | ) |
|
530 | 519 | ) |
|
520 | log.log('Saving figure: {}'.format(figname), self.name) | |
|
521 | if not os.path.isdir(os.path.dirname(figname)): | |
|
522 | os.makedirs(os.path.dirname(figname)) | |
|
531 | 523 | fig.savefig(figname) |
|
532 | 524 | |
|
525 | figname = os.path.join( | |
|
526 | self.save, | |
|
527 | '{}_{}.png'.format( | |
|
528 | self.save_code, | |
|
529 | self.getDateTime(self.data.min_time).strftime( | |
|
530 | '%Y%m%d' | |
|
531 | ), | |
|
532 | ) | |
|
533 | ) | |
|
534 | fig.savefig(figname) | |
|
535 | ||
|
533 | 536 | def send_to_server(self): |
|
534 | 537 | ''' |
|
535 | 538 | ''' |
@@ -176,7 +176,7 class GenericRTIPlot(Plot): | |||
|
176 | 176 | def setup(self): |
|
177 | 177 | self.xaxis = 'time' |
|
178 | 178 | self.ncols = 1 |
|
179 |
self.nrows = self.data.shape( |
|
|
179 | self.nrows = self.data.shape('param')[0] | |
|
180 | 180 | self.nplots = self.nrows |
|
181 | 181 | self.plots_adjust.update({'hspace':0.8, 'left': 0.1, 'bottom': 0.08, 'right':0.95, 'top': 0.95}) |
|
182 | 182 | |
@@ -185,13 +185,12 class GenericRTIPlot(Plot): | |||
|
185 | 185 | |
|
186 | 186 | self.ylabel = 'Range [km]' |
|
187 | 187 | if not self.titles: |
|
188 | self.titles = self.data.parameters \ | |
|
189 | if self.data.parameters else ['Param {}'.format(x) for x in range(self.nrows)] | |
|
188 | self.titles = ['Param {}'.format(x) for x in range(self.nrows)] | |
|
190 | 189 | |
|
191 | 190 | def update(self, dataOut): |
|
192 | 191 | |
|
193 | 192 | data = { |
|
194 |
|
|
|
193 | 'param' : numpy.concatenate([getattr(dataOut, attr) for attr in self.attr_data], axis=0) | |
|
195 | 194 | } |
|
196 | 195 | |
|
197 | 196 | meta = {} |
@@ -202,7 +201,7 class GenericRTIPlot(Plot): | |||
|
202 | 201 | # self.data.normalize_heights() |
|
203 | 202 | self.x = self.data.times |
|
204 | 203 | self.y = self.data.yrange |
|
205 |
self.z = self.data[ |
|
|
204 | self.z = self.data['param'] | |
|
206 | 205 | |
|
207 | 206 | self.z = numpy.ma.masked_invalid(self.z) |
|
208 | 207 |
@@ -1,16 +1,8 | |||
|
1 | 1 | import os |
|
2 | 2 | import sys |
|
3 | 3 | import glob |
|
4 | import fnmatch | |
|
5 | import datetime | |
|
6 | import time | |
|
7 | import re | |
|
8 | import h5py | |
|
9 | 4 | import numpy |
|
10 | 5 | |
|
11 | import pylab as plb | |
|
12 | from scipy.optimize import curve_fit | |
|
13 | from scipy import asarray as ar, exp | |
|
14 | 6 | |
|
15 | 7 | SPEED_OF_LIGHT = 299792458 |
|
16 | 8 | SPEED_OF_LIGHT = 3e8 |
@@ -19,9 +11,9 from .utils import folder_in_range | |||
|
19 | 11 | |
|
20 | 12 | import schainpy.admin |
|
21 | 13 | from schainpy.model.data.jrodata import Spectra |
|
22 |
from schainpy.model.proc.jroproc_base import ProcessingUnit |
|
|
14 | from schainpy.model.proc.jroproc_base import ProcessingUnit | |
|
23 | 15 | from schainpy.utils import log |
|
24 | from schainpy.model.io.jroIO_base import JRODataReader | |
|
16 | ||
|
25 | 17 | |
|
26 | 18 | def pol2cart(rho, phi): |
|
27 | 19 | x = rho * numpy.cos(phi) |
@@ -423,7 +415,6 class BLTRSpectraReader (ProcessingUnit): | |||
|
423 | 415 | copy = self.data_block.copy() |
|
424 | 416 | spc = copy * numpy.conjugate(copy) |
|
425 | 417 | self.data_spc = numpy.absolute(spc) # valor absoluto o magnitud |
|
426 | self.dataOut.data_spc = self.data_spc | |
|
427 | 418 | |
|
428 | 419 | cspc = self.data_block.copy() |
|
429 | 420 | self.data_cspc = self.data_block.copy() |
@@ -196,11 +196,11 class HDFReader(Reader, ProcessingUnit): | |||
|
196 | 196 | |
|
197 | 197 | if self.description: |
|
198 | 198 | for key, value in self.description['Metadata'].items(): |
|
199 |
meta[key] = self.fp[value] |
|
|
199 | meta[key] = self.fp[value][()] | |
|
200 | 200 | else: |
|
201 | 201 | grp = self.fp['Metadata'] |
|
202 | 202 | for name in grp: |
|
203 |
meta[name] = grp[name] |
|
|
203 | meta[name] = grp[name][()] | |
|
204 | 204 | |
|
205 | 205 | if self.extras: |
|
206 | 206 | for key, value in self.extras.items(): |
@@ -217,26 +217,26 class HDFReader(Reader, ProcessingUnit): | |||
|
217 | 217 | for key, value in self.description['Data'].items(): |
|
218 | 218 | if isinstance(value, str): |
|
219 | 219 | if isinstance(self.fp[value], h5py.Dataset): |
|
220 |
data[key] = self.fp[value] |
|
|
220 | data[key] = self.fp[value][()] | |
|
221 | 221 | elif isinstance(self.fp[value], h5py.Group): |
|
222 | 222 | array = [] |
|
223 | 223 | for ch in self.fp[value]: |
|
224 |
array.append(self.fp[value][ch] |
|
|
224 | array.append(self.fp[value][ch][()]) | |
|
225 | 225 | data[key] = numpy.array(array) |
|
226 | 226 | elif isinstance(value, list): |
|
227 | 227 | array = [] |
|
228 | 228 | for ch in value: |
|
229 |
array.append(self.fp[ch] |
|
|
229 | array.append(self.fp[ch][()]) | |
|
230 | 230 | data[key] = numpy.array(array) |
|
231 | 231 | else: |
|
232 | 232 | grp = self.fp['Data'] |
|
233 | 233 | for name in grp: |
|
234 | 234 | if isinstance(grp[name], h5py.Dataset): |
|
235 |
array = grp[name] |
|
|
235 | array = grp[name][()] | |
|
236 | 236 | elif isinstance(grp[name], h5py.Group): |
|
237 | 237 | array = [] |
|
238 | 238 | for ch in grp[name]: |
|
239 |
array.append(grp[name][ch] |
|
|
239 | array.append(grp[name][ch][()]) | |
|
240 | 240 | array = numpy.array(array) |
|
241 | 241 | else: |
|
242 | 242 | log.warning('Unknown type: {}'.format(name)) |
@@ -5,14 +5,10 Created on Oct 24, 2016 | |||
|
5 | 5 | ''' |
|
6 | 6 | |
|
7 | 7 | import numpy |
|
8 | import copy | |
|
9 | 8 | import datetime |
|
10 | 9 | import time |
|
11 | from time import gmtime | |
|
12 | 10 | |
|
13 | from numpy import transpose | |
|
14 | ||
|
15 | from schainpy.model.proc.jroproc_base import ProcessingUnit, Operation, MPDecorator | |
|
11 | from schainpy.model.proc.jroproc_base import ProcessingUnit, Operation | |
|
16 | 12 | from schainpy.model.data.jrodata import Parameters |
|
17 | 13 | |
|
18 | 14 | |
@@ -68,23 +64,14 class BLTRParametersProc(ProcessingUnit): | |||
|
68 | 64 | self.dataOut.data_param = self.dataOut.data[mode] |
|
69 | 65 | self.dataOut.heightList = self.dataOut.height[0] |
|
70 | 66 | self.dataOut.data_snr = self.dataOut.data_snr[mode] |
|
71 | ||
|
72 | data_param = numpy.zeros([4, len(self.dataOut.heightList)]) | |
|
73 | ||
|
74 | 67 | SNRavg = numpy.average(self.dataOut.data_snr, axis=0) |
|
75 | 68 | SNRavgdB = 10*numpy.log10(SNRavg) |
|
69 | self.dataOut.data_snr_avg_db = SNRavgdB.reshape(1, *SNRavgdB.shape) | |
|
70 | ||
|
76 | 71 | # Censoring Data |
|
77 | 72 | if snr_threshold is not None: |
|
78 | 73 | for i in range(3): |
|
79 | 74 | self.dataOut.data_param[i][SNRavgdB <= snr_threshold] = numpy.nan |
|
80 | # Including AvgSNR in data_param | |
|
81 | for i in range(data_param.shape[0]): | |
|
82 | if i == 3: | |
|
83 | data_param[i] = SNRavgdB | |
|
84 | else: | |
|
85 | data_param[i] = self.dataOut.data_param[i] | |
|
86 | ||
|
87 | self.dataOut.data_param = data_param | |
|
88 | 75 | |
|
89 | 76 | # TODO |
|
90 | 77 |
General Comments 0
You need to be logged in to leave comments.
Login now