schain Commit - r1362:036afbeb089e · Jicamarca Repository

Merge branch 'master' of http://jro-dev.igp.gob.pe/rhodecode/schain

Danny Scipión -

r1362:036afbeb089e

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r1362:036afbeb089e

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schainpy/model/graphics/jroplot_base.py +5 -2

                     self.attr_time = kwargs.get('attr_time', 'utctime')
                     self.attr_data = kwargs.get('attr_data', 'data_param')
                     self.decimation = kwargs.get('decimation', None)
-                    self.showSNR = kwargs.get('showSNR', False)
                     self.oneFigure = kwargs.get('oneFigure', True)
                     self.width = kwargs.get('width', None)
                     self.height = kwargs.get('height', None)
                             self.name
                         )
+                    if isinstance(self.attr_data, str):
+                        self.attr_data = [self.attr_data]
                 def __setup_plot(self):
                     '''
                     Common setup for all figures, here figures and axes are created
                                 self.pf_axes.append(cax)
                     for n in range(self.nrows):
+                        print(self.nrows)
                         if self.colormaps is not None:
                             cmap = plt.get_cmap(self.colormaps[n])
                         else:
                     fig = self.figures[n]
+                    if self.throttle == 0:
                         figname = os.path.join(
                             self.save,
                             self.save_code,
                             os.makedirs(os.path.dirname(figname))
                         fig.savefig(figname)
-                    if self.throttle == 0:
                     figname = os.path.join(
                         self.save,
                         '{}_{}.png'.format(

schainpy/model/graphics/jroplot_parameters.py +4 -5

                 def setup(self):
                     self.xaxis = 'time'
                     self.ncols = 1
-                    self.nrows = self.data.shape(self.attr_data)[0]
+                    self.nrows = self.data.shape('param')[0]
                     self.nplots = self.nrows
                     self.plots_adjust.update({'hspace':0.8, 'left': 0.1, 'bottom': 0.08, 'right':0.95, 'top': 0.95})
                     self.ylabel = 'Range [km]'
                     if not self.titles:
-                        self.titles = self.data.parameters \
+                        self.titles = ['Param {}'.format(x) for x in range(self.nrows)]
-                            if self.data.parameters else ['Param {}'.format(x) for x in range(self.nrows)]
                 def update(self, dataOut):
                     data = {
-                        self.attr_data : getattr(dataOut, self.attr_data)
+                        'param' : numpy.concatenate([getattr(dataOut, attr) for attr in self.attr_data], axis=0)
                     }
                     meta = {}
                     # self.data.normalize_heights()
                     self.x = self.data.times
                     self.y = self.data.yrange
-                    self.z = self.data[self.attr_data]
+                    self.z = self.data['param']
                     self.z = numpy.ma.masked_invalid(self.z)

schainpy/model/io/bltrIO_spectra.py +2 -11

             import os
             import sys
             import glob
-            import fnmatch
-            import datetime
-            import time
-            import re
-            import h5py
             import numpy
-            import pylab as plb
-            from scipy.optimize import curve_fit
-            from scipy import asarray as ar, exp
             SPEED_OF_LIGHT = 299792458
             SPEED_OF_LIGHT = 3e8
             import schainpy.admin
             from schainpy.model.data.jrodata import Spectra
-            from schainpy.model.proc.jroproc_base import ProcessingUnit, Operation, MPDecorator
+            from schainpy.model.proc.jroproc_base import ProcessingUnit
             from schainpy.utils import log
-            from schainpy.model.io.jroIO_base import JRODataReader
             def pol2cart(rho, phi):
                 x = rho * numpy.cos(phi)
                     copy = self.data_block.copy()
                     spc = copy * numpy.conjugate(copy)
                     self.data_spc = numpy.absolute(spc)  # valor absoluto o magnitud
-                    self.dataOut.data_spc = self.data_spc
                     cspc = self.data_block.copy()
                     self.data_cspc = self.data_block.copy()

schainpy/model/io/jroIO_param.py +7 -7

                     if self.description:
                         for key, value in self.description['Metadata'].items():
-                            meta[key] = self.fp[value].value
+                            meta[key] = self.fp[value][()]
                     else:
                         grp = self.fp['Metadata']
                         for name in grp:
-                            meta[name] = grp[name].value
+                            meta[name] = grp[name][()]
                     if self.extras:
                         for key, value in self.extras.items():
                         for key, value in self.description['Data'].items():
                             if isinstance(value, str):
                                 if isinstance(self.fp[value], h5py.Dataset):
-                                    data[key] = self.fp[value].value
+                                    data[key] = self.fp[value][()]
                                 elif isinstance(self.fp[value], h5py.Group):
                                     array = []
                                     for ch in self.fp[value]:
-                                        array.append(self.fp[value][ch].value)
+                                        array.append(self.fp[value][ch][()])
                                     data[key] = numpy.array(array)
                             elif isinstance(value, list):
                                 array = []
                                 for ch in value:
-                                    array.append(self.fp[ch].value)
+                                    array.append(self.fp[ch][()])
                                 data[key] = numpy.array(array)
                     else:
                         grp = self.fp['Data']
                         for name in grp:
                             if isinstance(grp[name], h5py.Dataset):
-                                array = grp[name].value
+                                array = grp[name][()]
                             elif isinstance(grp[name], h5py.Group):
                                 array = []
                                 for ch in grp[name]:
-                                    array.append(grp[name][ch].value)
+                                    array.append(grp[name][ch][()])
                                 array = numpy.array(array)
                             else:
                                 log.warning('Unknown type: {}'.format(name))

schainpy/model/proc/bltrproc_parameters.py +3 -16

             '''
             import numpy
-            import copy
             import datetime
             import time
-            from time import gmtime
-            from numpy import transpose
+            from schainpy.model.proc.jroproc_base import ProcessingUnit, Operation
-            from schainpy.model.proc.jroproc_base import ProcessingUnit, Operation, MPDecorator
             from schainpy.model.data.jrodata import Parameters
                     self.dataOut.data_param = self.dataOut.data[mode]
                     self.dataOut.heightList = self.dataOut.height[0]
                     self.dataOut.data_snr = self.dataOut.data_snr[mode]
-                    data_param = numpy.zeros([4, len(self.dataOut.heightList)])
                     SNRavg = numpy.average(self.dataOut.data_snr, axis=0)
                     SNRavgdB = 10*numpy.log10(SNRavg)
+                    self.dataOut.data_snr_avg_db = SNRavgdB.reshape(1, *SNRavgdB.shape)
                     # Censoring Data
                     if snr_threshold is not None:
                         for i in range(3):
                             self.dataOut.data_param[i][SNRavgdB <= snr_threshold] = numpy.nan
-                    # Including AvgSNR in data_param
-                    for i in range(data_param.shape[0]):
-                        if i == 3:
-                            data_param[i] = SNRavgdB
-                        else:
-                            data_param[i] = self.dataOut.data_param[i]
-                    self.dataOut.data_param = data_param
             # TODO

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