schain Commit - r1452:d596eb625435 · Jicamarca Repository

Now we can merge ProcUnits for Double Pulse Experiments

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schainpy/controller.py +4 -1

             # Copyright (c) 2012-2020 Jicamarca Radio Observatory
             # All rights reserved.
             #
             # Distributed under the terms of the BSD 3-clause license.
             """API to create signal chain projects
             The API is provide through class: Project
             """
             import re
             import sys
             import ast
             import datetime
             import traceback
             import time
             import multiprocessing
             from multiprocessing import Process, Queue
             from threading import Thread
             from xml.etree.ElementTree import ElementTree, Element, SubElement
             from schainpy.admin import Alarm, SchainWarning
             from schainpy.model import *
             from schainpy.utils import log
             if 'darwin' in sys.platform and sys.version_info[0] == 3 and sys.version_info[1] > 7:
                 multiprocessing.set_start_method('fork')
             class ConfBase():
                 def __init__(self):
                     self.id = '0'
                     self.name = None
                     self.priority = None
                     self.parameters = {}
                     self.object = None
                     self.operations = []
                 def getId(self):
                     return self.id
                 def getNewId(self):
                     return int(self.id) * 10 + len(self.operations) + 1
                 def updateId(self, new_id):
                     self.id = str(new_id)
                     n = 1
                     for conf in self.operations:
                         conf_id = str(int(new_id) * 10 + n)
                         conf.updateId(conf_id)
                         n += 1
                 def getKwargs(self):
                     params = {}
                     for key, value in self.parameters.items():
                         if value not in (None, '', ' '):
                             params[key] = value
                     return params
                 def update(self, **kwargs):
                     if 'format' not in kwargs:
                         kwargs['format'] = None
                     for key, value, fmt in kwargs.items():
                         self.addParameter(name=key, value=value, format=fmt)
                 def addParameter(self, name, value, format=None):
                     '''
                     '''
                     if format is not None:
                         self.parameters[name] = eval(format)(value)
                     elif isinstance(value, str) and re.search(r'(\d+/\d+/\d+)', value):
                         self.parameters[name] = datetime.date(*[int(x) for x in value.split('/')])
                     elif isinstance(value, str) and re.search(r'(\d+:\d+:\d+)', value):
                         self.parameters[name] = datetime.time(*[int(x) for x in value.split(':')])
                     else:
                         try:
                             self.parameters[name] = ast.literal_eval(value)
                         except:
                             if isinstance(value, str) and ',' in value:
                                 self.parameters[name] = value.split(',')
                             else:
                                 self.parameters[name] = value
                 def getParameters(self):
                     params = {}
                     for key, value in self.parameters.items():
                         s = type(value).__name__
                         if s == 'date':
                             params[key] = value.strftime('%Y/%m/%d')
                         elif s == 'time':
                             params[key] = value.strftime('%H:%M:%S')
                         else:
                             params[key] = str(value)
                     return params
                 def makeXml(self, element):
                     xml = SubElement(element, self.ELEMENTNAME)
                     for label in self.xml_labels:
                         xml.set(label, str(getattr(self, label)))
                     for key, value in self.getParameters().items():
                         xml_param = SubElement(xml, 'Parameter')
                         xml_param.set('name', key)
                         xml_param.set('value', value)
                     for conf in self.operations:
                         conf.makeXml(xml)
                 def __str__(self):
                     if self.ELEMENTNAME == 'Operation':
                         s = '  {}[id={}]\n'.format(self.name, self.id)
                     else:
                         s = '{}[id={}, inputId={}]\n'.format(self.name, self.id, self.inputId)
                     for key, value in self.parameters.items():
                         if self.ELEMENTNAME == 'Operation':
                             s += '    {}: {}\n'.format(key, value)
                         else:
                             s += '  {}: {}\n'.format(key, value)
                     for conf in self.operations:
                         s += str(conf)
                     return s
             class OperationConf(ConfBase):
                 ELEMENTNAME = 'Operation'
                 xml_labels = ['id', 'name']
                 def setup(self, id, name, priority, project_id, err_queue):
                     self.id = str(id)
                     self.project_id = project_id
                     self.name = name
                     self.type = 'other'
                     self.err_queue = err_queue
                 def readXml(self, element, project_id, err_queue):
                     self.id = element.get('id')
                     self.name = element.get('name')
                     self.type = 'other'
                     self.project_id = str(project_id)
                     self.err_queue = err_queue
                     for elm in element.iter('Parameter'):
                         self.addParameter(elm.get('name'), elm.get('value'))
                 def createObject(self):
                     className = eval(self.name)
                     if 'Plot' in self.name or 'Writer' in self.name or 'Send' in self.name or 'print' in self.name:
                         kwargs = self.getKwargs()
                         opObj = className(self.id, self.id, self.project_id, self.err_queue, **kwargs)
                         opObj.start()
                         self.type = 'external'
                     else:
                         opObj = className()
                     self.object = opObj
                     return opObj
             class ProcUnitConf(ConfBase):
                 ELEMENTNAME = 'ProcUnit'
                 xml_labels = ['id', 'inputId', 'name']
                 def setup(self, project_id, id, name, datatype, inputId, err_queue):
                     '''
                     '''
                     if datatype == None and name == None:
                         raise ValueError('datatype or name should be defined')
                     if name == None:
                         if 'Proc' in datatype:
                             name = datatype
                         else:
                             name = '%sProc' % (datatype)
                     if datatype == None:
                         datatype = name.replace('Proc', '')
                     self.id = str(id)
                     self.project_id = project_id
                     self.name = name
                     self.datatype = datatype
                     self.inputId = inputId
                     self.err_queue = err_queue
                     self.operations = []
                     self.parameters = {}
                 def removeOperation(self, id):
                     i = [1 if x.id==id else 0 for x in self.operations]
                     self.operations.pop(i.index(1))
                 def getOperation(self, id):
                     for conf in self.operations:
                         if conf.id == id:
                             return conf
                 def addOperation(self, name, optype='self'):
                     '''
                     '''
                     id = self.getNewId()
                     conf = OperationConf()
                     conf.setup(id, name=name, priority='0', project_id=self.project_id, err_queue=self.err_queue)
                     self.operations.append(conf)
                     return conf
                 def readXml(self, element, project_id, err_queue):
                     self.id = element.get('id')
                     self.name = element.get('name')
                     self.inputId = None if element.get('inputId') == 'None' else element.get('inputId')
                     self.datatype = element.get('datatype', self.name.replace(self.ELEMENTNAME.replace('Unit', ''), ''))
                     self.project_id = str(project_id)
                     self.err_queue = err_queue
                     self.operations = []
                     self.parameters = {}
                     for elm in element:
                         if elm.tag == 'Parameter':
                             self.addParameter(elm.get('name'), elm.get('value'))
                         elif elm.tag == 'Operation':
                             conf = OperationConf()
                             conf.readXml(elm, project_id, err_queue)
                             self.operations.append(conf)
                 def createObjects(self):
                     '''
                     Instancia de unidades de procesamiento.
                     '''
                     className = eval(self.name)
                     kwargs = self.getKwargs()
                     procUnitObj = className()
                     procUnitObj.name = self.name
                     log.success('creating process...', self.name)
                     for conf in self.operations:
                         opObj = conf.createObject()
                         log.success('adding operation: {}, type:{}'.format(
                             conf.name,
                             conf.type), self.name)
                         procUnitObj.addOperation(conf, opObj)
                     self.object = procUnitObj
                 def run(self):
                     '''
                     '''
                     return self.object.call(**self.getKwargs())
             class ReadUnitConf(ProcUnitConf):
                 ELEMENTNAME = 'ReadUnit'
                 def __init__(self):
                     self.id = None
                     self.datatype = None
                     self.name = None
                     self.inputId = None
                     self.operations = []
                     self.parameters = {}
                 def setup(self, project_id, id, name, datatype, err_queue, path='', startDate='', endDate='',
                           startTime='', endTime='', server=None, **kwargs):
                     if datatype == None and name == None:
                         raise ValueError('datatype or name should be defined')
                     if name == None:
                         if 'Reader' in datatype:
                             name = datatype
                             datatype = name.replace('Reader','')
                         else:
                             name = '{}Reader'.format(datatype)
                     if datatype == None:
                         if 'Reader' in name:
                             datatype = name.replace('Reader','')
                         else:
                             datatype = name
                             name = '{}Reader'.format(name)
                     self.id = id
                     self.project_id = project_id
                     self.name = name
                     self.datatype = datatype
                     self.err_queue = err_queue
                     self.addParameter(name='path', value=path, format='str')
                     self.addParameter(name='startDate', value=startDate)
                     self.addParameter(name='endDate', value=endDate)
                     self.addParameter(name='startTime', value=startTime)
                     self.addParameter(name='endTime', value=endTime)
                     for key, value in kwargs.items():
                         self.addParameter(name=key, value=value)
             class Project(Process):
                 """API to create signal chain projects"""
                 ELEMENTNAME = 'Project'
                 def __init__(self, name=''):
                     Process.__init__(self)
                     self.id = '1'
                     if name:
                         self.name = '{} ({})'.format(Process.__name__, name)
                     self.filename = None
                     self.description = None
                     self.email = None
                     self.alarm = []
                     self.configurations = {}
                     # self.err_queue = Queue()
                     self.err_queue = None
                     self.started = False
                 def getNewId(self):
                     idList = list(self.configurations.keys())
                     id = int(self.id) * 10
                     while True:
                         id += 1
                         if str(id) in idList:
                             continue
                         break
                     return str(id)
                 def updateId(self, new_id):
                     self.id = str(new_id)
                     keyList = list(self.configurations.keys())
                     keyList.sort()
                     n = 1
                     new_confs = {}
                     for procKey in keyList:
                         conf = self.configurations[procKey]
                         idProcUnit = str(int(self.id) * 10 + n)
                         conf.updateId(idProcUnit)
                         new_confs[idProcUnit] = conf
                         n += 1
                     self.configurations = new_confs
                 def setup(self, id=1, name='', description='', email=None, alarm=[]):
                     self.id = str(id)
                     self.description = description
                     self.email = email
                     self.alarm = alarm
                     if name:
                         self.name = '{} ({})'.format(Process.__name__, name)
                 def update(self, **kwargs):
                     for key, value in kwargs.items():
                         setattr(self, key, value)
                 def clone(self):
                     p = Project()
                     p.id = self.id
                     p.name = self.name
                     p.description = self.description
                     p.configurations = self.configurations.copy()
                     return p
                 def addReadUnit(self, id=None, datatype=None, name=None, **kwargs):
                     '''
                     '''
                     if id is None:
                         idReadUnit = self.getNewId()
                     else:
                         idReadUnit = str(id)
                     conf = ReadUnitConf()
                     conf.setup(self.id, idReadUnit, name, datatype, self.err_queue, **kwargs)
                     self.configurations[conf.id] = conf
                     return conf
                 def addProcUnit(self, id=None, inputId='0', datatype=None, name=None):
                     '''
                     '''
                     if id is None:
                         idProcUnit = self.getNewId()
                     else:
                         idProcUnit = id
                     conf = ProcUnitConf()
                     conf.setup(self.id, idProcUnit, name, datatype, inputId, self.err_queue)
                     self.configurations[conf.id] = conf
                     return conf
                 def removeProcUnit(self, id):
                     if id in self.configurations:
                         self.configurations.pop(id)
                 def getReadUnit(self):
                     for obj in list(self.configurations.values()):
                         if obj.ELEMENTNAME == 'ReadUnit':
                             return obj
                     return None
                 def getProcUnit(self, id):
                     return self.configurations[id]
                 def getUnits(self):
                     keys = list(self.configurations)
                     keys.sort()
                     for key in keys:
                         yield self.configurations[key]
                 def updateUnit(self, id, **kwargs):
                     conf = self.configurations[id].update(**kwargs)
                 def makeXml(self):
                     xml = Element('Project')
                     xml.set('id', str(self.id))
                     xml.set('name', self.name)
                     xml.set('description', self.description)
                     for conf in self.configurations.values():
                         conf.makeXml(xml)
                     self.xml = xml
                 def writeXml(self, filename=None):
                     if filename == None:
                         if self.filename:
                             filename = self.filename
                         else:
                             filename = 'schain.xml'
                     if not filename:
                         print('filename has not been defined. Use setFilename(filename) for do it.')
                         return 0
                     abs_file = os.path.abspath(filename)
                     if not os.access(os.path.dirname(abs_file), os.W_OK):
                         print('No write permission on %s' % os.path.dirname(abs_file))
                         return 0
                     if os.path.isfile(abs_file) and not(os.access(abs_file, os.W_OK)):
                         print('File %s already exists and it could not be overwriten' % abs_file)
                         return 0
                     self.makeXml()
                     ElementTree(self.xml).write(abs_file, method='xml')
                     self.filename = abs_file
                     return 1
                 def readXml(self, filename):
                     abs_file = os.path.abspath(filename)
                     self.configurations = {}
                     try:
                         self.xml = ElementTree().parse(abs_file)
                     except:
                         log.error('Error reading %s, verify file format' % filename)
                         return 0
                     self.id = self.xml.get('id')
                     self.name = self.xml.get('name')
                     self.description = self.xml.get('description')
                     for element in self.xml:
                         if element.tag == 'ReadUnit':
                             conf = ReadUnitConf()
                             conf.readXml(element, self.id, self.err_queue)
                             self.configurations[conf.id] = conf
                         elif element.tag == 'ProcUnit':
                             conf = ProcUnitConf()
                             input_proc = self.configurations[element.get('inputId')]
                             conf.readXml(element, self.id, self.err_queue)
                             self.configurations[conf.id] = conf
                     self.filename = abs_file
                     return 1
                 def __str__(self):
                     text = '\nProject[id=%s, name=%s, description=%s]\n\n' % (
                         self.id,
                         self.name,
                         self.description,
                         )
                     for conf in self.configurations.values():
                         text += '{}'.format(conf)
                     return text
                 def createObjects(self):
                     keys = list(self.configurations.keys())
                     keys.sort()
                     for key in keys:
                         conf = self.configurations[key]
                         conf.createObjects()
                         if conf.inputId is not None:
-                            conf.object.setInput(self.configurations[conf.inputId].object)
+                            if isinstance(conf.inputId, list):
+                                conf.object.setInput([self.configurations[x].object for x in conf.inputId])
+                            else:
+                                conf.object.setInput([self.configurations[conf.inputId].object])
                 def monitor(self):
                     t = Thread(target=self._monitor, args=(self.err_queue, self.ctx))
                     t.start()
                 def _monitor(self, queue, ctx):
                     import socket
                     procs = 0
                     err_msg = ''
                     while True:
                         msg = queue.get()
                         if '#_start_#' in msg:
                             procs += 1
                         elif '#_end_#' in msg:
                             procs -=1
                         else:
                             err_msg = msg
                         if procs == 0 or 'Traceback' in err_msg:
                             break
                         time.sleep(0.1)
                     if '|' in err_msg:
                         name, err = err_msg.split('|')
                         if 'SchainWarning' in err:
                             log.warning(err.split('SchainWarning:')[-1].split('\n')[0].strip(), name)
                         elif 'SchainError' in err:
                             log.error(err.split('SchainError:')[-1].split('\n')[0].strip(), name)
                         else:
                             log.error(err, name)
                     else:
                         name, err = self.name, err_msg
                     time.sleep(1)
                     ctx.term()
                     message = ''.join(err)
                     if err_msg:
                         subject = 'SChain v%s: Error running %s\n' % (
                             schainpy.__version__, self.name)
                         subtitle = 'Hostname: %s\n' % socket.gethostbyname(
                             socket.gethostname())
                         subtitle += 'Working directory: %s\n' % os.path.abspath('./')
                         subtitle += 'Configuration file: %s\n' % self.filename
                         subtitle += 'Time: %s\n' % str(datetime.datetime.now())
                         readUnitConfObj = self.getReadUnit()
                         if readUnitConfObj:
                             subtitle += '\nInput parameters:\n'
                             subtitle += '[Data path = %s]\n' % readUnitConfObj.parameters['path']
                             subtitle += '[Start date = %s]\n' % readUnitConfObj.parameters['startDate']
                             subtitle += '[End date = %s]\n' % readUnitConfObj.parameters['endDate']
                             subtitle += '[Start time = %s]\n' % readUnitConfObj.parameters['startTime']
                             subtitle += '[End time = %s]\n' % readUnitConfObj.parameters['endTime']
                         a = Alarm(
                             modes=self.alarm,
                             email=self.email,
                             message=message,
                             subject=subject,
                             subtitle=subtitle,
                             filename=self.filename
                         )
                         a.start()
                 def setFilename(self, filename):
                     self.filename = filename
                 def runProcs(self):
                     err = False
                     n = len(self.configurations)
                     while not err:
                         for conf in self.getUnits():
                             ok = conf.run()
                             if ok == 'Error':
                                 n -= 1
                                 continue
                             elif not ok:
                                 break
                         if n == 0:
                             err = True
                 def run(self):
                     log.success('\nStarting Project {} [id={}]'.format(self.name, self.id), tag='')
                     self.started = True
                     self.start_time = time.time()
                     self.createObjects()
                     self.runProcs()
                     log.success('{} Done (Time: {:4.2f}s)'.format(
                         self.name,
                         time.time()-self.start_time), '')

schainpy/model/graphics/jroplot_parameters.py +2 -2

             import os
             import datetime
             import numpy
             from mpl_toolkits.axisartist.grid_finder import FixedLocator, DictFormatter
             from schainpy.model.graphics.jroplot_base import Plot, plt
             from schainpy.model.graphics.jroplot_spectra import SpectraPlot, RTIPlot, CoherencePlot, SpectraCutPlot
             from schainpy.utils import log
             # libreria wradlib
             import wradlib as wrl
             EARTH_RADIUS = 6.3710e3
             def ll2xy(lat1, lon1, lat2, lon2):
                 p = 0.017453292519943295
                 a = 0.5 - numpy.cos((lat2 - lat1) * p)/2 + numpy.cos(lat1 * p) * \
                     numpy.cos(lat2 * p) * (1 - numpy.cos((lon2 - lon1) * p)) / 2
                 r = 12742 * numpy.arcsin(numpy.sqrt(a))
                 theta = numpy.arctan2(numpy.sin((lon2-lon1)*p)*numpy.cos(lat2*p), numpy.cos(lat1*p)
                                       * numpy.sin(lat2*p)-numpy.sin(lat1*p)*numpy.cos(lat2*p)*numpy.cos((lon2-lon1)*p))
                 theta = -theta + numpy.pi/2
                 return r*numpy.cos(theta), r*numpy.sin(theta)
             def km2deg(km):
                 '''
                 Convert distance in km to degrees
                 '''
                 return numpy.rad2deg(km/EARTH_RADIUS)
             class SpectralMomentsPlot(SpectraPlot):
                 '''
                 Plot for Spectral Moments
                 '''
                 CODE = 'spc_moments'
                 # colormap = 'jet'
                 # plot_type = 'pcolor'
             class DobleGaussianPlot(SpectraPlot):
                 '''
                 Plot for Double Gaussian Plot
                 '''
                 CODE = 'gaussian_fit'
                 # colormap = 'jet'
                 # plot_type = 'pcolor'
             class DoubleGaussianSpectraCutPlot(SpectraCutPlot):
                 '''
                 Plot SpectraCut with Double Gaussian Fit
                 '''
                 CODE = 'cut_gaussian_fit'
             class SnrPlot(RTIPlot):
                 '''
                 Plot for SNR Data
                 '''
                 CODE = 'snr'
                 colormap = 'jet'
                 def update(self, dataOut):
                     data = {
                         'snr': 10*numpy.log10(dataOut.data_snr)
                     }
                     return data, {}
             class DopplerPlot(RTIPlot):
                 '''
                 Plot for DOPPLER Data (1st moment)
                 '''
                 CODE = 'dop'
                 colormap = 'jet'
                 def update(self, dataOut):
                     data = {
                         'dop': 10*numpy.log10(dataOut.data_dop)
                     }
                     return data, {}
             class PowerPlot(RTIPlot):
                 '''
                 Plot for Power Data (0 moment)
                 '''
                 CODE = 'pow'
                 colormap = 'jet'
                 def update(self, dataOut):
                     data = {
                         'pow': 10*numpy.log10(dataOut.data_pow/dataOut.normFactor)
                     }
                     return data, {}
             class SpectralWidthPlot(RTIPlot):
                 '''
                 Plot for Spectral Width Data (2nd moment)
                 '''
                 CODE = 'width'
                 colormap = 'jet'
                 def update(self, dataOut):
                     data = {
                         'width': dataOut.data_width
                     }
                     return data, {}
             class SkyMapPlot(Plot):
                 '''
                 Plot for meteors detection data
                 '''
                 CODE = 'param'
                 def setup(self):
                     self.ncols = 1
                     self.nrows = 1
                     self.width = 7.2
                     self.height = 7.2
                     self.nplots = 1
                     self.xlabel = 'Zonal Zenith Angle (deg)'
                     self.ylabel = 'Meridional Zenith Angle (deg)'
                     self.polar = True
                     self.ymin = -180
                     self.ymax = 180
                     self.colorbar = False
                 def plot(self):
                     arrayParameters = numpy.concatenate(self.data['param'])
                     error = arrayParameters[:, -1]
                     indValid = numpy.where(error == 0)[0]
                     finalMeteor = arrayParameters[indValid, :]
                     finalAzimuth = finalMeteor[:, 3]
                     finalZenith = finalMeteor[:, 4]
                     x = finalAzimuth * numpy.pi / 180
                     y = finalZenith
                     ax = self.axes[0]
                     if ax.firsttime:
                         ax.plot = ax.plot(x, y, 'bo', markersize=5)[0]
                     else:
                         ax.plot.set_data(x, y)
                     dt1 = self.getDateTime(self.data.min_time).strftime('%y/%m/%d %H:%M:%S')
                     dt2 = self.getDateTime(self.data.max_time).strftime('%y/%m/%d %H:%M:%S')
                     title = 'Meteor Detection Sky Map\n %s - %s \n Number of events: %5.0f\n' % (dt1,
                                                                                                  dt2,
                                                                                                  len(x))
                     self.titles[0] = title
             class GenericRTIPlot(Plot):
                 '''
                 Plot for data_xxxx object
                 '''
                 CODE = 'param'
                 colormap = 'viridis'
                 plot_type = 'pcolorbuffer'
                 def setup(self):
                     self.xaxis = 'time'
                     self.ncols = 1
                     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})
                     if not self.xlabel:
                         self.xlabel = 'Time'
                     self.ylabel = 'Range [km]'
                     if not self.titles:
                         self.titles = ['Param {}'.format(x) for x in range(self.nrows)]
                 def update(self, dataOut):
                     data = {
                         'param' : numpy.concatenate([getattr(dataOut, attr) for attr in self.attr_data], axis=0)
                     }
                     meta = {}
                     return data, meta
                 def plot(self):
                     # self.data.normalize_heights()
                     self.x = self.data.times
                     self.y = self.data.yrange
                     self.z = self.data['param']
                     self.z = 10*numpy.log10(self.z)
                     self.z = numpy.ma.masked_invalid(self.z)
                     if self.decimation is None:
                         x, y, z = self.fill_gaps(self.x, self.y, self.z)
                     else:
                         x, y, z = self.fill_gaps(*self.decimate())
                     for n, ax in enumerate(self.axes):
                         self.zmax = self.zmax if self.zmax is not None else numpy.max(
                             self.z[n])
                         self.zmin = self.zmin if self.zmin is not None else numpy.min(
                             self.z[n])
                         if ax.firsttime:
                             if self.zlimits is not None:
                                 self.zmin, self.zmax = self.zlimits[n]
                             ax.plt = ax.pcolormesh(x, y, z[n].T * self.factors[n],
                                                    vmin=self.zmin,
                                                    vmax=self.zmax,
                                                    cmap=self.cmaps[n]
                                                    )
                         else:
                             if self.zlimits is not None:
                                 self.zmin, self.zmax = self.zlimits[n]
                             ax.collections.remove(ax.collections[0])
                             ax.plt = ax.pcolormesh(x, y, z[n].T * self.factors[n],
                                                    vmin=self.zmin,
                                                    vmax=self.zmax,
                                                    cmap=self.cmaps[n]
                                                    )
             class PolarMapPlot(Plot):
                 '''
                 Plot for weather radar
                 '''
                 CODE = 'param'
                 colormap = 'seismic'
                 def setup(self):
                     self.ncols = 1
                     self.nrows = 1
                     self.width = 9
                     self.height = 8
                     self.mode = self.data.meta['mode']
                     if self.channels is not None:
                         self.nplots = len(self.channels)
                         self.nrows = len(self.channels)
                     else:
                         self.nplots = self.data.shape(self.CODE)[0]
                         self.nrows = self.nplots
                         self.channels = list(range(self.nplots))
                     if self.mode == 'E':
                         self.xlabel = 'Longitude'
                         self.ylabel = 'Latitude'
                     else:
                         self.xlabel = 'Range (km)'
                         self.ylabel = 'Height (km)'
                     self.bgcolor = 'white'
                     self.cb_labels = self.data.meta['units']
                     self.lat = self.data.meta['latitude']
                     self.lon = self.data.meta['longitude']
                     self.xmin, self.xmax = float(
                         km2deg(self.xmin) + self.lon), float(km2deg(self.xmax) + self.lon)
                     self.ymin, self.ymax = float(
                         km2deg(self.ymin) + self.lat), float(km2deg(self.ymax) + self.lat)
                     #  self.polar = True
                 def plot(self):
                     for n, ax in enumerate(self.axes):
                         data = self.data['param'][self.channels[n]]
                         zeniths = numpy.linspace(
 , self.data.meta['max_range'], data.shape[1])
                         if self.mode == 'E':
                             azimuths = -numpy.radians(self.data.yrange)+numpy.pi/2
                             r, theta = numpy.meshgrid(zeniths, azimuths)
                             x, y = r*numpy.cos(theta)*numpy.cos(numpy.radians(self.data.meta['elevation'])), r*numpy.sin(
                                 theta)*numpy.cos(numpy.radians(self.data.meta['elevation']))
                             x = km2deg(x) + self.lon
                             y = km2deg(y) + self.lat
                         else:
                             azimuths = numpy.radians(self.data.yrange)
                             r, theta = numpy.meshgrid(zeniths, azimuths)
                             x, y = r*numpy.cos(theta), r*numpy.sin(theta)
                         self.y = zeniths
                         if ax.firsttime:
                             if self.zlimits is not None:
                                 self.zmin, self.zmax = self.zlimits[n]
                             ax.plt = ax.pcolormesh(  # r, theta, numpy.ma.array(data, mask=numpy.isnan(data)),
                                 x, y, numpy.ma.array(data, mask=numpy.isnan(data)),
                                 vmin=self.zmin,
                                 vmax=self.zmax,
                                 cmap=self.cmaps[n])
                         else:
                             if self.zlimits is not None:
                                 self.zmin, self.zmax = self.zlimits[n]
                             ax.collections.remove(ax.collections[0])
                             ax.plt = ax.pcolormesh(  # r, theta, numpy.ma.array(data, mask=numpy.isnan(data)),
                                 x, y, numpy.ma.array(data, mask=numpy.isnan(data)),
                                 vmin=self.zmin,
                                 vmax=self.zmax,
                                 cmap=self.cmaps[n])
                         if self.mode == 'A':
                             continue
                         # plot district names
                         f = open('/data/workspace/schain_scripts/distrito.csv')
                         for line in f:
                             label, lon, lat = [s.strip() for s in line.split(',') if s]
                             lat = float(lat)
                             lon = float(lon)
                             # ax.plot(lon, lat, '.b', ms=2)
                             ax.text(lon, lat, label.decode('utf8'), ha='center',
                                     va='bottom', size='8', color='black')
                         # plot limites
                         limites = []
                         tmp = []
                         for line in open('/data/workspace/schain_scripts/lima.csv'):
                             if '#' in line:
                                 if tmp:
                                     limites.append(tmp)
                                 tmp = []
                                 continue
                             values = line.strip().split(',')
                             tmp.append((float(values[0]), float(values[1])))
                         for points in limites:
                             ax.add_patch(
                                 Polygon(points, ec='k', fc='none', ls='--', lw=0.5))
                         # plot Cuencas
                         for cuenca in ('rimac', 'lurin', 'mala', 'chillon', 'chilca', 'chancay-huaral'):
                             f = open('/data/workspace/schain_scripts/{}.csv'.format(cuenca))
                             values = [line.strip().split(',') for line in f]
                             points = [(float(s[0]), float(s[1])) for s in values]
                             ax.add_patch(Polygon(points, ec='b', fc='none'))
                         # plot grid
                         for r in (15, 30, 45, 60):
                             ax.add_artist(plt.Circle((self.lon, self.lat),
                                                      km2deg(r), color='0.6', fill=False, lw=0.2))
                             ax.text(
                                 self.lon + (km2deg(r))*numpy.cos(60*numpy.pi/180),
                                 self.lat + (km2deg(r))*numpy.sin(60*numpy.pi/180),
                                 '{}km'.format(r),
                                 ha='center', va='bottom', size='8', color='0.6', weight='heavy')
                     if self.mode == 'E':
                         title = 'El={}$^\circ$'.format(self.data.meta['elevation'])
                         label = 'E{:02d}'.format(int(self.data.meta['elevation']))
                     else:
                         title = 'Az={}$^\circ$'.format(self.data.meta['azimuth'])
                         label = 'A{:02d}'.format(int(self.data.meta['azimuth']))
                     self.save_labels = ['{}-{}'.format(lbl, label) for lbl in self.labels]
                     self.titles = ['{} {}'.format(
                         self.data.parameters[x], title) for x in self.channels]
             class WeatherPlot(Plot):
                 CODE = 'weather'
                 plot_name = 'weather'
                 plot_type = 'ppistyle'
                 buffering = False
                 def setup(self):
                     self.ncols = 1
                     self.nrows = 1
                     self.width   =8
                     self.height  =8
                     self.nplots= 1
                     self.ylabel= 'Range [Km]'
                     self.titles= ['Weather']
                     self.colorbar=False
                     self.ini     =0
                     self.len_azi =0
                     self.buffer_ini  = None
                     self.buffer_azi   = None
                     self.plots_adjust.update({'wspace': 0.4, 'hspace':0.4, 'left': 0.1, 'right': 0.9, 'bottom': 0.08})
                     self.flag    =0
                     self.indicador= 0
                     self.last_data_azi = None
                     self.val_mean      = None
                 def update(self, dataOut):
                     data = {}
                     meta = {}
                     if hasattr(dataOut, 'dataPP_POWER'):
                         factor = 1
                     if hasattr(dataOut, 'nFFTPoints'):
                         factor = dataOut.normFactor
                     #print("DIME EL SHAPE PORFAVOR",dataOut.data_360.shape)
                     data['weather'] = 10*numpy.log10(dataOut.data_360[1]/(factor))
                     data['azi']     = dataOut.data_azi
                     data['ele']     = dataOut.data_ele
                     return data, meta
                 def get2List(self,angulos):
                     list1=[]
                     list2=[]
                     for i in reversed(range(len(angulos))):
                         diff_ = angulos[i]-angulos[i-1]
                         if diff_ >1.5:
                             list1.append(i-1)
                             list2.append(diff_)
                     return list(reversed(list1)),list(reversed(list2))
                 def fixData360(self,list_,ang_):
                     if list_[0]==-1:
                         vec = numpy.where(ang_<ang_[0])
                         ang_[vec] = ang_[vec]+360
                         return ang_
                     return ang_
                 def fixData360HL(self,angulos):
                     vec = numpy.where(angulos>=360)
                     angulos[vec]=angulos[vec]-360
                     return angulos
                 def search_pos(self,pos,list_):
                     for i in range(len(list_)):
                         if pos == list_[i]:
                             return True,i
                     i=None
                     return False,i
                 def fixDataComp(self,ang_,list1_,list2_):
                     size  = len(ang_)
                     size2 = 0
                     for i in range(len(list2_)):
                         size2=size2+round(list2_[i])-1
                     new_size= size+size2
                     ang_new = numpy.zeros(new_size)
                     ang_new2 = numpy.zeros(new_size)
                     tmp = 0
                     c   = 0
                     for i in range(len(ang_)):
                         ang_new[tmp +c] = ang_[i]
                         ang_new2[tmp+c] = ang_[i]
                         condition , value = self.search_pos(i,list1_)
                         if condition:
                             pos = tmp + c + 1
                             for k in range(round(list2_[value])-1):
                                 ang_new[pos+k]  = ang_new[pos+k-1]+1
                                 ang_new2[pos+k] = numpy.nan
                             tmp = pos +k
                             c   = 0
                         c=c+1
                     return ang_new,ang_new2
                 def globalCheckPED(self,angulos):
                     l1,l2 = self.get2List(angulos)
                     if len(l1)>0:
                         angulos2 = self.fixData360(list_=l1,ang_=angulos)
                         l1,l2 = self.get2List(angulos2)
                         ang1_,ang2_ = self.fixDataComp(ang_=angulos2,list1_=l1,list2_=l2)
                         ang1_ = self.fixData360HL(ang1_)
                         ang2_ = self.fixData360HL(ang2_)
                     else:
                         ang1_= angulos
                         ang2_= angulos
                     return ang1_,ang2_
                 def analizeDATA(self,data_azi):
                     list1 = []
                     list2 = []
                     dat   = data_azi
                     for i in reversed(range(1,len(dat))):
                         if dat[i]>dat[i-1]:
                             diff = int(dat[i])-int(dat[i-1])
                         else:
                             diff = 360+int(dat[i])-int(dat[i-1])
                         if diff > 1:
                             list1.append(i-1)
                             list2.append(diff-1)
                     return list1,list2
                 def fixDATANEW(self,data_azi,data_weather):
                     list1,list2 = self.analizeDATA(data_azi)
                     if len(list1)== 0:
                         return data_azi,data_weather
                     else:
                         resize = 0
                         for i in range(len(list2)):
                             resize=  resize + list2[i]
                         new_data_azi = numpy.resize(data_azi,resize)
                         new_data_weather= numpy.resize(date_weather,resize)
                         for i in range(len(list2)):
                             j=0
                             position=list1[i]+1
                             for j in range(list2[i]):
                                 new_data_azi[position+j]=new_data_azi[position+j-1]+1
                     return new_data_azi
                 def fixDATA(self,data_azi):
                     data=data_azi
                     for i in range(len(data)):
                         if numpy.isnan(data[i]):
                            data[i]=data[i-1]+1
                     return data
                 def replaceNAN(self,data_weather,data_azi,val):
                     data= data_azi
                     data_T= data_weather
                     if data.shape[0]> data_T.shape[0]:
                         data_N = numpy.ones( [data.shape[0],data_T.shape[1]])
                         c      = 0
                         for i in range(len(data)):
                             if numpy.isnan(data[i]):
                                 data_N[i,:]=numpy.ones(data_T.shape[1])*numpy.nan
                             else:
                                 data_N[i,:]=data_T[c,:]
                                 c=c+1
                         return data_N
                     else:
                         for i in range(len(data)):
                             if numpy.isnan(data[i]):
                                data_T[i,:]=numpy.ones(data_T.shape[1])*numpy.nan
                         return data_T
                 def const_ploteo(self,data_weather,data_azi,step,res):
                     if self.ini==0:
                         #-------
                         n     = (360/res)-len(data_azi)
                         #--------------------- new -------------------------
                         data_azi_new ,data_azi_old= self.globalCheckPED(data_azi)
                         #------------------------
                         start = data_azi_new[-1] + res
                         end   = data_azi_new[0]  - res
                         #------ new
                         self.last_data_azi = end
                         if start>end:
                             end        = end + 360
                         azi_vacia = numpy.linspace(start,end,int(n))
                         azi_vacia = numpy.where(azi_vacia>360,azi_vacia-360,azi_vacia)
                         data_azi  = numpy.hstack((data_azi_new,azi_vacia))
                         # RADAR
                         val_mean         = numpy.mean(data_weather[:,-1])
                         self.val_mean    = val_mean
                         data_weather_cmp = numpy.ones([(360-data_weather.shape[0]),data_weather.shape[1]])*val_mean
                         data_weather     = self.replaceNAN(data_weather=data_weather,data_azi=data_azi_old,val=self.val_mean)
                         data_weather     = numpy.vstack((data_weather,data_weather_cmp))
                     else:
                         # azimuth
                         flag=0
                         start_azi = self.res_azi[0]
                         #-----------new------------
                         data_azi ,data_azi_old= self.globalCheckPED(data_azi)
                         data_weather = self.replaceNAN(data_weather=data_weather,data_azi=data_azi_old,val=self.val_mean)
                         #--------------------------
                         start = data_azi[0]
                         end   = data_azi[-1]
                         self.last_data_azi= end
                         if start< start_azi:
                             start = start +360
                         if end <start_azi:
                             end  = end +360
                         pos_ini = int((start-start_azi)/res)
                         len_azi = len(data_azi)
                         if (360-pos_ini)<len_azi:
                             if pos_ini+1==360:
                                 pos_ini=0
                             else:
                                 flag=1
                                 dif= 360-pos_ini
                                 comp= len_azi-dif
                         #-----------------
                         if flag==0:
                             # AZIMUTH
                             self.res_azi[pos_ini:pos_ini+len_azi] = data_azi
                             # RADAR
                             self.res_weather[pos_ini:pos_ini+len_azi,:] = data_weather
                         else:
                             # AZIMUTH
                             self.res_azi[pos_ini:pos_ini+dif] = data_azi[0:dif]
                             self.res_azi[0:comp]              = data_azi[dif:]
                             # RADAR
                             self.res_weather[pos_ini:pos_ini+dif,:] = data_weather[0:dif,:]
                             self.res_weather[0:comp,:]              = data_weather[dif:,:]
                             flag=0
                         data_azi                                    = self.res_azi
                         data_weather                                = self.res_weather
                     return data_weather,data_azi
                 def plot(self):
                     thisDatetime = datetime.datetime.utcfromtimestamp(self.data.times[-1]).strftime('%Y-%m-%d %H:%M:%S')
                     data         = self.data[-1]
                     r            = self.data.yrange
                     delta_height = r[1]-r[0]
                     r_mask       = numpy.where(r>=0)[0]
                     r            = numpy.arange(len(r_mask))*delta_height
                     self.y       = 2*r
                     # RADAR
                     #data_weather = data['weather']
                     # PEDESTAL
                     #data_azi  = data['azi']
                     res          = 1
                     # STEP
                     step         = (360/(res*data['weather'].shape[0]))
                     self.res_weather, self.res_azi = self.const_ploteo(data_weather=data['weather'][:,r_mask],data_azi=data['azi'],step=step,res=res)
                     self.res_ele = numpy.mean(data['ele'])
                     #################    PLOTEO           ###################
                     for i,ax in enumerate(self.axes):
                         self.zmin = self.zmin if self.zmin else 20
                         self.zmax = self.zmax if self.zmax else 80
                         if ax.firsttime:
                             plt.clf()
                             cgax, pm = wrl.vis.plot_ppi(self.res_weather,r=r,az=self.res_azi,fig=self.figures[0], proj='cg', vmin=self.zmin, vmax=self.zmax)
                         else:
                             plt.clf()
                             cgax, pm = wrl.vis.plot_ppi(self.res_weather,r=r,az=self.res_azi,fig=self.figures[0], proj='cg', vmin=self.zmin, vmax=self.zmax)
                     caax = cgax.parasites[0]
                     paax = cgax.parasites[1]
                     cbar = plt.gcf().colorbar(pm, pad=0.075)
                     caax.set_xlabel('x_range [km]')
                     caax.set_ylabel('y_range [km]')
                     plt.text(1.0, 1.05, 'Azimuth '+str(thisDatetime)+"  Step   "+str(self.ini)+ " EL: "+str(round(self.res_ele, 1)), transform=caax.transAxes, va='bottom',ha='right')
                     self.ini= self.ini+1
             class WeatherRHIPlot(Plot):
                 CODE = 'weather'
                 plot_name = 'weather'
                 plot_type = 'rhistyle'
                 buffering = False
                 data_ele_tmp = None
                 def setup(self):
                     print("********************")
                     print("********************")
                     print("********************")
                     print("SETUP WEATHER PLOT")
                     self.ncols = 1
                     self.nrows = 1
                     self.nplots= 1
                     self.ylabel= 'Range [Km]'
                     self.titles= ['Weather']
                     if self.channels is not None:
                         self.nplots = len(self.channels)
                         self.nrows = len(self.channels)
                     else:
                         self.nplots = self.data.shape(self.CODE)[0]
                         self.nrows = self.nplots
                         self.channels = list(range(self.nplots))
                     print("channels",self.channels)
                     print("que saldra", self.data.shape(self.CODE)[0])
                     self.titles = ['{} Channel {}'.format(self.CODE.upper(), x) for x in range(self.nrows)]
                     print("self.titles",self.titles)
                     self.colorbar=False
                     self.width   =12
                     self.height  =8
                     self.ini     =0
                     self.len_azi =0
                     self.buffer_ini  = None
                     self.buffer_ele   = None
                     self.plots_adjust.update({'wspace': 0.4, 'hspace':0.4, 'left': 0.1, 'right': 0.9, 'bottom': 0.08})
                     self.flag    =0
                     self.indicador= 0
                     self.last_data_ele = None
                     self.val_mean      = None
                 def update(self, dataOut):
                     data = {}
                     meta = {}
                     if hasattr(dataOut, 'dataPP_POWER'):
                         factor = 1
                     if hasattr(dataOut, 'nFFTPoints'):
                         factor = dataOut.normFactor
                     print("dataOut",dataOut.data_360.shape)
                     #
                     data['weather'] = 10*numpy.log10(dataOut.data_360/(factor))
                     #
                     #data['weather'] = 10*numpy.log10(dataOut.data_360[1]/(factor))
                     data['azi']     = dataOut.data_azi
                     data['ele']     = dataOut.data_ele
                     #print("UPDATE")
                     #print("data[weather]",data['weather'].shape)
                     #print("data[azi]",data['azi'])
                     return data, meta
                 def get2List(self,angulos):
                     list1=[]
                     list2=[]
                     for i in reversed(range(len(angulos))):
                         if not i==0:#el caso de i=0 evalula el primero de la lista con el ultimo y no es relevante
                             diff_ = angulos[i]-angulos[i-1]
                             if abs(diff_) >1.5:
                                 list1.append(i-1)
                                 list2.append(diff_)
                     return list(reversed(list1)),list(reversed(list2))
                 def fixData90(self,list_,ang_):
                     if list_[0]==-1:
                         vec = numpy.where(ang_<ang_[0])
                         ang_[vec] = ang_[vec]+90
                         return ang_
                     return ang_
                 def fixData90HL(self,angulos):
                     vec = numpy.where(angulos>=90)
                     angulos[vec]=angulos[vec]-90
                     return angulos
                 def search_pos(self,pos,list_):
                     for i in range(len(list_)):
                         if pos == list_[i]:
                             return True,i
                     i=None
                     return False,i
                 def fixDataComp(self,ang_,list1_,list2_,tipo_case):
                     size  = len(ang_)
                     size2 = 0
                     for i in range(len(list2_)):
                         size2=size2+round(abs(list2_[i]))-1
                     new_size= size+size2
                     ang_new = numpy.zeros(new_size)
                     ang_new2 = numpy.zeros(new_size)
                     tmp = 0
                     c   = 0
                     for i in range(len(ang_)):
                         ang_new[tmp +c] = ang_[i]
                         ang_new2[tmp+c] = ang_[i]
                         condition , value = self.search_pos(i,list1_)
                         if condition:
                             pos = tmp + c + 1
                             for k in range(round(abs(list2_[value]))-1):
                                 if tipo_case==0 or tipo_case==3:#subida
                                     ang_new[pos+k]  = ang_new[pos+k-1]+1
                                     ang_new2[pos+k] = numpy.nan
                                 elif tipo_case==1 or tipo_case==2:#bajada
                                     ang_new[pos+k]  = ang_new[pos+k-1]-1
                                     ang_new2[pos+k] = numpy.nan
                             tmp = pos +k
                             c   = 0
                         c=c+1
                     return ang_new,ang_new2
                 def globalCheckPED(self,angulos,tipo_case):
                     l1,l2 = self.get2List(angulos)
                     ##print("l1",l1)
                     ##print("l2",l2)
                     if len(l1)>0:
                         #angulos2 = self.fixData90(list_=l1,ang_=angulos)
                         #l1,l2 = self.get2List(angulos2)
                         ang1_,ang2_ = self.fixDataComp(ang_=angulos,list1_=l1,list2_=l2,tipo_case=tipo_case)
                         #ang1_ = self.fixData90HL(ang1_)
                         #ang2_ = self.fixData90HL(ang2_)
                     else:
                         ang1_= angulos
                         ang2_= angulos
                     return ang1_,ang2_
                 def replaceNAN(self,data_weather,data_ele,val):
                     data= data_ele
                     data_T= data_weather
                     if data.shape[0]> data_T.shape[0]:
                         data_N = numpy.ones( [data.shape[0],data_T.shape[1]])
                         c      = 0
                         for i in range(len(data)):
                             if numpy.isnan(data[i]):
                                 data_N[i,:]=numpy.ones(data_T.shape[1])*numpy.nan
                             else:
                                 data_N[i,:]=data_T[c,:]
                                 c=c+1
                         return data_N
                     else:
                         for i in range(len(data)):
                             if numpy.isnan(data[i]):
                                data_T[i,:]=numpy.ones(data_T.shape[1])*numpy.nan
                         return data_T
                 def check_case(self,data_ele,ang_max,ang_min):
                     start  = data_ele[0]
                     end    = data_ele[-1]
                     number = (end-start)
                     len_ang=len(data_ele)
                     print("start",start)
                     print("end",end)
                     print("number",number)
                     print("len_ang",len_ang)
                     #exit(1)
                     if start<end and (round(abs(number)+1)>=len_ang or (numpy.argmin(data_ele)==0)):#caso subida
                         return 0
                     #elif start>end and (round(abs(number)+1)>=len_ang or(numpy.argmax(data_ele)==0)):#caso bajada
                     #    return 1
                     elif round(abs(number)+1)>=len_ang and (start>end or(numpy.argmax(data_ele)==0)):#caso bajada
                         return 1
                     elif round(abs(number)+1)<len_ang and data_ele[-2]>data_ele[-1]:# caso BAJADA CAMBIO ANG MAX
                         return 2
                     elif round(abs(number)+1)<len_ang and data_ele[-2]<data_ele[-1] :# caso SUBIDA CAMBIO ANG MIN
                         return 3
                 def const_ploteo(self,val_ch,data_weather,data_ele,step,res,ang_max,ang_min):
                     ang_max= ang_max
                     ang_min= ang_min
                     data_weather=data_weather
                     val_ch=val_ch
                     ##print("*********************DATA WEATHER**************************************")
                     ##print(data_weather)
                     if self.ini==0:
                         '''
                         print("**********************************************")
                         print("**********************************************")
                         print("***************ini**************")
                         print("**********************************************")
                         print("**********************************************")
                         '''
                         #print("data_ele",data_ele)
                         #----------------------------------------------------------
                         tipo_case = self.check_case(data_ele,ang_max,ang_min)
                         print("check_case",tipo_case)
                         #exit(1)
                         #--------------------- new -------------------------
                         data_ele_new ,data_ele_old= self.globalCheckPED(data_ele,tipo_case)
                         #-------------------------CAMBIOS RHI---------------------------------
                         start= ang_min
                         end  = ang_max
                         n= (ang_max-ang_min)/res
                         #------ new
                         self.start_data_ele = data_ele_new[0]
                         self.end_data_ele  = data_ele_new[-1]
                         if tipo_case==0  or tipo_case==3: # SUBIDA
                             n1= round(self.start_data_ele)- start
                             n2= end - round(self.end_data_ele)
                             print(self.start_data_ele)
                             print(self.end_data_ele)
                             if n1>0:
                                 ele1= numpy.linspace(ang_min+1,self.start_data_ele-1,n1)
                                 ele1_nan= numpy.ones(n1)*numpy.nan
                                 data_ele = numpy.hstack((ele1,data_ele_new))
                                 print("ele1_nan",ele1_nan.shape)
                                 print("data_ele_old",data_ele_old.shape)
                                 data_ele_old = numpy.hstack((ele1_nan,data_ele_old))
                             if n2>0:
                                 ele2= numpy.linspace(self.end_data_ele+1,end,n2)
                                 ele2_nan= numpy.ones(n2)*numpy.nan
                                 data_ele = numpy.hstack((data_ele,ele2))
                                 print("ele2_nan",ele2_nan.shape)
                                 print("data_ele_old",data_ele_old.shape)
                                 data_ele_old = numpy.hstack((data_ele_old,ele2_nan))
                         if tipo_case==1  or tipo_case==2: # BAJADA
                             data_ele_new       = data_ele_new[::-1] #  reversa
                             data_ele_old   = data_ele_old[::-1]# reversa
                             data_weather   = data_weather[::-1,:]# reversa
                             vec= numpy.where(data_ele_new<ang_max)
                             data_ele_new = data_ele_new[vec]
                             data_ele_old = data_ele_old[vec]
                             data_weather  = data_weather[vec[0]]
                             vec2= numpy.where(0<data_ele_new)
                             data_ele_new = data_ele_new[vec2]
                             data_ele_old = data_ele_old[vec2]
                             data_weather  = data_weather[vec2[0]]
                             self.start_data_ele = data_ele_new[0]
                             self.end_data_ele  = data_ele_new[-1]
                             n1= round(self.start_data_ele)- start
                             n2= end - round(self.end_data_ele)-1
                             print(self.start_data_ele)
                             print(self.end_data_ele)
                             if n1>0:
                                 ele1= numpy.linspace(ang_min+1,self.start_data_ele-1,n1)
                                 ele1_nan= numpy.ones(n1)*numpy.nan
                                 data_ele = numpy.hstack((ele1,data_ele_new))
                                 data_ele_old = numpy.hstack((ele1_nan,data_ele_old))
                             if n2>0:
                                 ele2= numpy.linspace(self.end_data_ele+1,end,n2)
                                 ele2_nan= numpy.ones(n2)*numpy.nan
                                 data_ele = numpy.hstack((data_ele,ele2))
                                 data_ele_old = numpy.hstack((data_ele_old,ele2_nan))
                         # RADAR
                         # NOTA data_ele y data_weather es la variable que retorna
                         val_mean         = numpy.mean(data_weather[:,-1])
                         self.val_mean    = val_mean
                         data_weather     = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean)
                         self.data_ele_tmp[val_ch]= data_ele_old
                     else:
                         #print("**********************************************")
                         #print("****************VARIABLE**********************")
                         #-------------------------CAMBIOS RHI---------------------------------
                         #---------------------------------------------------------------------
                         ##print("INPUT data_ele",data_ele)
                         flag=0
                         start_ele = self.res_ele[0]
                         tipo_case = self.check_case(data_ele,ang_max,ang_min)
                         #print("TIPO DE DATA",tipo_case)
                         #-----------new------------
                         data_ele ,data_ele_old = self.globalCheckPED(data_ele,tipo_case)
                         data_weather           = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean)
                         #-------------------------------NEW RHI ITERATIVO-------------------------
                         if tipo_case==0 : # SUBIDA
                             vec = numpy.where(data_ele<ang_max)
                             data_ele = data_ele[vec]
                             data_ele_old = data_ele_old[vec]
                             data_weather  = data_weather[vec[0]]
                             vec2 = numpy.where(0<data_ele)
                             data_ele= data_ele[vec2]
                             data_ele_old= data_ele_old[vec2]
                             ##print(data_ele_new)
                             data_weather= data_weather[vec2[0]]
                             new_i_ele  = int(round(data_ele[0]))
                             new_f_ele  = int(round(data_ele[-1]))
                             #print(new_i_ele)
                             #print(new_f_ele)
                             #print(data_ele,len(data_ele))
                             #print(data_ele_old,len(data_ele_old))
                             if new_i_ele< 2:
                                 self.data_ele_tmp[val_ch] = numpy.ones(ang_max-ang_min)*numpy.nan
                                 self.res_weather[val_ch]  = self.replaceNAN(data_weather=self.res_weather[val_ch],data_ele=self.data_ele_tmp[val_ch],val=self.val_mean)
                             self.data_ele_tmp[val_ch][new_i_ele:new_i_ele+len(data_ele)]=data_ele_old
                             self.res_ele[new_i_ele:new_i_ele+len(data_ele)]= data_ele
                             self.res_weather[val_ch][new_i_ele:new_i_ele+len(data_ele),:]= data_weather
                             data_ele                                    = self.res_ele
                             data_weather                                = self.res_weather[val_ch]
                         elif tipo_case==1 : #BAJADA
                             data_ele       = data_ele[::-1] #  reversa
                             data_ele_old   = data_ele_old[::-1]# reversa
                             data_weather   = data_weather[::-1,:]# reversa
                             vec= numpy.where(data_ele<ang_max)
                             data_ele = data_ele[vec]
                             data_ele_old = data_ele_old[vec]
                             data_weather  = data_weather[vec[0]]
                             vec2= numpy.where(0<data_ele)
                             data_ele = data_ele[vec2]
                             data_ele_old = data_ele_old[vec2]
                             data_weather  = data_weather[vec2[0]]
                             new_i_ele  = int(round(data_ele[0]))
                             new_f_ele  = int(round(data_ele[-1]))
                             #print(data_ele)
                             #print(ang_max)
                             #print(data_ele_old)
                             if new_i_ele <= 1:
                                 new_i_ele = 1
                             if round(data_ele[-1])>=ang_max-1:
                                 self.data_ele_tmp[val_ch] = numpy.ones(ang_max-ang_min)*numpy.nan
                                 self.res_weather[val_ch]  = self.replaceNAN(data_weather=self.res_weather[val_ch],data_ele=self.data_ele_tmp[val_ch],val=self.val_mean)
                             self.data_ele_tmp[val_ch][new_i_ele-1:new_i_ele+len(data_ele)-1]=data_ele_old
                             self.res_ele[new_i_ele-1:new_i_ele+len(data_ele)-1]= data_ele
                             self.res_weather[val_ch][new_i_ele-1:new_i_ele+len(data_ele)-1,:]= data_weather
                             data_ele     = self.res_ele
                             data_weather = self.res_weather[val_ch]
                         elif tipo_case==2:  #bajada
                             vec = numpy.where(data_ele<ang_max)
                             data_ele = data_ele[vec]
                             data_weather= data_weather[vec[0]]
                             len_vec = len(vec)
                             data_ele_new     = data_ele[::-1] #  reversa
                             data_weather =  data_weather[::-1,:]
                             new_i_ele  = int(data_ele_new[0])
                             new_f_ele  = int(data_ele_new[-1])
                             n1= new_i_ele- ang_min
                             n2= ang_max - new_f_ele-1
                             if n1>0:
                                 ele1= numpy.linspace(ang_min+1,new_i_ele-1,n1)
                                 ele1_nan= numpy.ones(n1)*numpy.nan
                                 data_ele = numpy.hstack((ele1,data_ele_new))
                                 data_ele_old = numpy.hstack((ele1_nan,data_ele_new))
                             if n2>0:
                                 ele2= numpy.linspace(new_f_ele+1,ang_max,n2)
                                 ele2_nan= numpy.ones(n2)*numpy.nan
                                 data_ele = numpy.hstack((data_ele,ele2))
                                 data_ele_old = numpy.hstack((data_ele_old,ele2_nan))
                             self.data_ele_tmp[val_ch] = data_ele_old
                             self.res_ele      = data_ele
                             self.res_weather[val_ch]  = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean)
                             data_ele                                    = self.res_ele
                             data_weather                                = self.res_weather[val_ch]
                         elif tipo_case==3:#subida
                             vec = numpy.where(0<data_ele)
                             data_ele= data_ele[vec]
                             data_ele_new = data_ele
                             data_ele_old= data_ele_old[vec]
                             data_weather= data_weather[vec[0]]
                             pos_ini = numpy.argmin(data_ele)
                             if pos_ini>0:
                                 len_vec= len(data_ele)
                                 vec3  = numpy.linspace(pos_ini,len_vec-1,len_vec-pos_ini).astype(int)
                                 #print(vec3)
                                 data_ele= data_ele[vec3]
                                 data_ele_new = data_ele
                                 data_ele_old= data_ele_old[vec3]
                                 data_weather= data_weather[vec3]
                             new_i_ele  = int(data_ele_new[0])
                             new_f_ele  = int(data_ele_new[-1])
                             n1= new_i_ele- ang_min
                             n2= ang_max - new_f_ele-1
                             if n1>0:
                                 ele1= numpy.linspace(ang_min+1,new_i_ele-1,n1)
                                 ele1_nan= numpy.ones(n1)*numpy.nan
                                 data_ele = numpy.hstack((ele1,data_ele_new))
                                 data_ele_old = numpy.hstack((ele1_nan,data_ele_new))
                             if n2>0:
                                 ele2= numpy.linspace(new_f_ele+1,ang_max,n2)
                                 ele2_nan= numpy.ones(n2)*numpy.nan
                                 data_ele = numpy.hstack((data_ele,ele2))
                                 data_ele_old = numpy.hstack((data_ele_old,ele2_nan))
                             self.data_ele_tmp[val_ch] = data_ele_old
                             self.res_ele      = data_ele
                             self.res_weather[val_ch]  = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean)
                             data_ele                                    = self.res_ele
                             data_weather                                = self.res_weather[val_ch]
                     #print("self.data_ele_tmp",self.data_ele_tmp)
                     return data_weather,data_ele
                 def plot(self):
                     thisDatetime = datetime.datetime.utcfromtimestamp(self.data.times[-1]).strftime('%Y-%m-%d %H:%M:%S')
                     data         = self.data[-1]
                     r            = self.data.yrange
                     delta_height = r[1]-r[0]
                     r_mask       = numpy.where(r>=0)[0]
                     ##print("delta_height",delta_height)
                     #print("r_mask",r_mask,len(r_mask))
                     r            = numpy.arange(len(r_mask))*delta_height
                     self.y       = 2*r
                     res          = 1
                     ###print("data['weather'].shape[0]",data['weather'].shape[0])
                     ang_max = self.ang_max
                     ang_min = self.ang_min
                     var_ang      =ang_max -  ang_min
                     step         = (int(var_ang)/(res*data['weather'].shape[0]))
                     ###print("step",step)
                     #--------------------------------------------------------
                     ##print('weather',data['weather'].shape)
                     ##print('ele',data['ele'].shape)
                     ###self.res_weather, self.res_ele = self.const_ploteo(data_weather=data['weather'][:,r_mask],data_ele=data['ele'],step=step,res=res,ang_max=ang_max,ang_min=ang_min)
                     ###self.res_azi                   = numpy.mean(data['azi'])
                     ###print("self.res_ele",self.res_ele)
                     plt.clf()
                     subplots = [121, 122]
                     cg={'angular_spacing': 20.}
                     if self.ini==0:
                         self.data_ele_tmp = numpy.ones([self.nplots,int(var_ang)])*numpy.nan
                         self.res_weather= numpy.ones([self.nplots,int(var_ang),len(r_mask)])*numpy.nan
                         print("SHAPE",self.data_ele_tmp.shape)
                     for i,ax in enumerate(self.axes):
                         self.res_weather[i], self.res_ele = self.const_ploteo(val_ch=i, data_weather=data['weather'][i][:,r_mask],data_ele=data['ele'],step=step,res=res,ang_max=ang_max,ang_min=ang_min)
                         self.res_azi                   = numpy.mean(data['azi'])
                         if i==0:
                             print("*****************************************************************************to plot**************************",self.res_weather[i].shape)
                         self.zmin = self.zmin if self.zmin else 20
                         self.zmax = self.zmax if self.zmax else 80
                         if ax.firsttime:
                             #plt.clf()
                             cgax, pm = wrl.vis.plot_rhi(self.res_weather[i],r=r,th=self.res_ele,ax=subplots[i], proj=cg,vmin=self.zmin, vmax=self.zmax)
                             #fig=self.figures[0]
                         else:
                             #plt.clf()
                             if i==0:
                                 print(self.res_weather[i])
                                 print(self.res_ele)
                             cgax, pm = wrl.vis.plot_rhi(self.res_weather[i],r=r,th=self.res_ele,ax=subplots[i], proj=cg,vmin=self.zmin, vmax=self.zmax)
                         caax = cgax.parasites[0]
                         paax = cgax.parasites[1]
                         cbar = plt.gcf().colorbar(pm, pad=0.075)
                         caax.set_xlabel('x_range [km]')
                         caax.set_ylabel('y_range [km]')
                         plt.text(1.0, 1.05, 'Elevacion '+str(thisDatetime)+"  Step   "+str(self.ini)+ " Azi: "+str(round(self.res_azi,2)), transform=caax.transAxes, va='bottom',ha='right')
                     print("***************************self.ini****************************",self.ini)
                     self.ini= self.ini+1
             class Weather_vRF_Plot(Plot):
                 CODE = 'PPI'
                 plot_name = 'PPI'
                 #plot_type = 'ppistyle'
                 buffering = False
                 def setup(self):
                     self.ncols = 1
                     self.nrows = 1
                     self.width   =8
                     self.height  =8
                     self.nplots= 1
                     self.ylabel= 'Range [Km]'
                     self.xlabel= 'Range [Km]'
                     self.titles= ['PPI']
                     self.polar = True
                     if self.channels is not None:
                         self.nplots = len(self.channels)
                         self.nrows = len(self.channels)
                     else:
                         self.nplots = self.data.shape(self.CODE)[0]
                         self.nrows = self.nplots
                         self.channels = list(range(self.nplots))
                     if self.CODE == 'POWER':
                         self.cb_label = r'Power (dB)'
                     elif self.CODE == 'DOPPLER':
                         self.cb_label = r'Velocity (m/s)'
                     self.colorbar=True
                     self.width  = 9
                     self.height  =8
                     self.ini  =0
                     self.len_azi =0
                     self.buffer_ini  = None
                     self.buffer_ele   = None
                     self.plots_adjust.update({'wspace': 0.4, 'hspace':0.4, 'left': 0.15, 'right': 0.9, 'bottom': 0.08})
                     self.flag    =0
                     self.indicador= 0
                     self.last_data_ele = None
                     self.val_mean      = None
                 def update(self, dataOut):
                     data = {}
                     meta = {}
                     if hasattr(dataOut, 'dataPP_POWER'):
                         factor = 1
                     if hasattr(dataOut, 'nFFTPoints'):
                         factor = dataOut.normFactor
                     if 'pow' in self.attr_data[0].lower():
                         data['data'] = 10*numpy.log10(getattr(dataOut, self.attr_data[0])/(factor))
                     else:
                         data['data'] = getattr(dataOut, self.attr_data[0])/(factor)
                     data['azi']     = dataOut.data_azi
                     data['ele']     = dataOut.data_ele
                     return data, meta
                 def plot(self):
                     data         = self.data[-1]
                     r            = self.data.yrange
                     delta_height = r[1]-r[0]
                     r_mask       = numpy.where(r>=0)[0]
                     self.r_mask = r_mask
                     r            = numpy.arange(len(r_mask))*delta_height
                     self.y       = 2*r
                     z = data['data'][self.channels[0]][:,r_mask]
                     self.titles = []
                     self.ymax = self.ymax if self.ymax else numpy.nanmax(r)
                     self.ymin = self.ymin if self.ymin else numpy.nanmin(r)
                     self.zmax = self.zmax if self.zmax else numpy.nanmax(z)
                     self.zmin = self.zmin if self.zmin else numpy.nanmin(z)
                     self.ang_min = self.ang_min if self.ang_min else 0
                     self.ang_max = self.ang_max if self.ang_max else 360
                     r, theta = numpy.meshgrid(r, numpy.radians(data['azi']) )
                     for i,ax in enumerate(self.axes):
                         if ax.firsttime:
                             ax.set_xlim(numpy.radians(self.ang_min),numpy.radians(self.ang_max))
                             ax.plt = ax.pcolormesh(theta, r, z, cmap=self.colormap, vmin=self.zmin, vmax=self.zmax)
                         else:
                             ax.set_xlim(numpy.radians(self.ang_min),numpy.radians(self.ang_max))
                             ax.plt = ax.pcolormesh(theta, r, z, cmap=self.colormap, vmin=self.zmin, vmax=self.zmax)
                         ax.grid(True)
                         if len(self.channels) !=1:
                             self.titles = ['PPI {} at EL: {} Channel {}'.format(self.self.labels[x], str(round(numpy.mean(data['ele']),1)), x) for x in range(self.nrows)]
                         else:
                             self.titles = ['PPI {} at EL: {} Channel {}'.format(self.labels[0], str(round(numpy.mean(data['ele']),1)), self.channels[0])]
             class WeatherRHI_vRF2_Plot(Plot):
                 CODE = 'weather'
                 plot_name = 'weather'
                 plot_type = 'rhistyle'
                 buffering = False
                 data_ele_tmp = None
                 def setup(self):
                     print("********************")
                     print("********************")
                     print("********************")
                     print("SETUP WEATHER PLOT")
                     self.ncols = 1
                     self.nrows = 1
                     self.nplots= 1
                     self.ylabel= 'Range [Km]'
                     self.titles= ['Weather']
                     if self.channels is not None:
                         self.nplots = len(self.channels)
                         self.nrows = len(self.channels)
                     else:
                         self.nplots = self.data.shape(self.CODE)[0]
                         self.nrows = self.nplots
                         self.channels = list(range(self.nplots))
                     print("channels",self.channels)
                     print("que saldra", self.data.shape(self.CODE)[0])
                     self.titles = ['{} Channel {}'.format(self.CODE.upper(), x) for x in range(self.nrows)]
                     print("self.titles",self.titles)
                     self.colorbar=False
                     self.width   =8
                     self.height  =8
                     self.ini     =0
                     self.len_azi =0
                     self.buffer_ini  = None
                     self.buffer_ele   = None
                     self.plots_adjust.update({'wspace': 0.4, 'hspace':0.4, 'left': 0.1, 'right': 0.9, 'bottom': 0.08})
                     self.flag    =0
                     self.indicador= 0
                     self.last_data_ele = None
                     self.val_mean      = None
                 def update(self, dataOut):
                     data = {}
                     meta = {}
                     if hasattr(dataOut, 'dataPP_POWER'):
                         factor = 1
                     if hasattr(dataOut, 'nFFTPoints'):
                         factor = dataOut.normFactor
                     print("dataOut",dataOut.data_360.shape)
                     #
                     data['weather'] = 10*numpy.log10(dataOut.data_360/(factor))
                     #
                     #data['weather'] = 10*numpy.log10(dataOut.data_360[1]/(factor))
                     data['azi']     = dataOut.data_azi
                     data['ele']     = dataOut.data_ele
                     data['case_flag']     = dataOut.case_flag
                     #print("UPDATE")
                     #print("data[weather]",data['weather'].shape)
                     #print("data[azi]",data['azi'])
                     return data, meta
                 def get2List(self,angulos):
                     list1=[]
                     list2=[]
                     for i in reversed(range(len(angulos))):
                         if not i==0:#el caso de i=0 evalula el primero de la lista con el ultimo y no es relevante
                             diff_ = angulos[i]-angulos[i-1]
                             if abs(diff_) >1.5:
                                 list1.append(i-1)
                                 list2.append(diff_)
                     return list(reversed(list1)),list(reversed(list2))
                 def fixData90(self,list_,ang_):
                     if list_[0]==-1:
                         vec = numpy.where(ang_<ang_[0])
                         ang_[vec] = ang_[vec]+90
                         return ang_
                     return ang_
                 def fixData90HL(self,angulos):
                     vec = numpy.where(angulos>=90)
                     angulos[vec]=angulos[vec]-90
                     return angulos
                 def search_pos(self,pos,list_):
                     for i in range(len(list_)):
                         if pos == list_[i]:
                             return True,i
                     i=None
                     return False,i
                 def fixDataComp(self,ang_,list1_,list2_,tipo_case):
                     size  = len(ang_)
                     size2 = 0
                     for i in range(len(list2_)):
                         size2=size2+round(abs(list2_[i]))-1
                     new_size= size+size2
                     ang_new = numpy.zeros(new_size)
                     ang_new2 = numpy.zeros(new_size)
                     tmp = 0
                     c   = 0
                     for i in range(len(ang_)):
                         ang_new[tmp +c] = ang_[i]
                         ang_new2[tmp+c] = ang_[i]
                         condition , value = self.search_pos(i,list1_)
                         if condition:
                             pos = tmp + c + 1
                             for k in range(round(abs(list2_[value]))-1):
                                 if tipo_case==0 or tipo_case==3:#subida
                                     ang_new[pos+k]  = ang_new[pos+k-1]+1
                                     ang_new2[pos+k] = numpy.nan
                                 elif tipo_case==1 or tipo_case==2:#bajada
                                     ang_new[pos+k]  = ang_new[pos+k-1]-1
                                     ang_new2[pos+k] = numpy.nan
                             tmp = pos +k
                             c   = 0
                         c=c+1
                     return ang_new,ang_new2
                 def globalCheckPED(self,angulos,tipo_case):
                     l1,l2 = self.get2List(angulos)
                     ##print("l1",l1)
                     ##print("l2",l2)
                     if len(l1)>0:
                         #angulos2 = self.fixData90(list_=l1,ang_=angulos)
                         #l1,l2 = self.get2List(angulos2)
                         ang1_,ang2_ = self.fixDataComp(ang_=angulos,list1_=l1,list2_=l2,tipo_case=tipo_case)
                         #ang1_ = self.fixData90HL(ang1_)
                         #ang2_ = self.fixData90HL(ang2_)
                     else:
                         ang1_= angulos
                         ang2_= angulos
                     return ang1_,ang2_
                 def replaceNAN(self,data_weather,data_ele,val):
                     data= data_ele
                     data_T= data_weather
                     if data.shape[0]> data_T.shape[0]:
                         data_N = numpy.ones( [data.shape[0],data_T.shape[1]])
                         c      = 0
                         for i in range(len(data)):
                             if numpy.isnan(data[i]):
                                 data_N[i,:]=numpy.ones(data_T.shape[1])*numpy.nan
                             else:
                                 data_N[i,:]=data_T[c,:]
                                 c=c+1
                         return data_N
                     else:
                         for i in range(len(data)):
                             if numpy.isnan(data[i]):
                                data_T[i,:]=numpy.ones(data_T.shape[1])*numpy.nan
                         return data_T
                 def check_case(self,data_ele,ang_max,ang_min):
                     start  = data_ele[0]
                     end    = data_ele[-1]
                     number = (end-start)
                     len_ang=len(data_ele)
                     print("start",start)
                     print("end",end)
                     print("number",number)
                     print("len_ang",len_ang)
                     #exit(1)
                     if start<end and (round(abs(number)+1)>=len_ang or (numpy.argmin(data_ele)==0)):#caso subida
                         return 0
                     #elif start>end and (round(abs(number)+1)>=len_ang or(numpy.argmax(data_ele)==0)):#caso bajada
                     #    return 1
                     elif round(abs(number)+1)>=len_ang and (start>end or(numpy.argmax(data_ele)==0)):#caso bajada
                         return 1
                     elif round(abs(number)+1)<len_ang and data_ele[-2]>data_ele[-1]:# caso BAJADA CAMBIO ANG MAX
                         return 2
                     elif round(abs(number)+1)<len_ang and data_ele[-2]<data_ele[-1] :# caso SUBIDA CAMBIO ANG MIN
                         return 3
                 def const_ploteo(self,val_ch,data_weather,data_ele,step,res,ang_max,ang_min,case_flag):
                     ang_max= ang_max
                     ang_min= ang_min
                     data_weather=data_weather
                     val_ch=val_ch
                     ##print("*********************DATA WEATHER**************************************")
                     ##print(data_weather)
                     if self.ini==0:
                         '''
                         print("**********************************************")
                         print("**********************************************")
                         print("***************ini**************")
                         print("**********************************************")
                         print("**********************************************")
                         '''
                         #print("data_ele",data_ele)
                         #----------------------------------------------------------
                         tipo_case = case_flag[-1]
                         #tipo_case = self.check_case(data_ele,ang_max,ang_min)
                         print("check_case",tipo_case)
                         #exit(1)
                         #--------------------- new -------------------------
                         data_ele_new ,data_ele_old= self.globalCheckPED(data_ele,tipo_case)
                         #-------------------------CAMBIOS RHI---------------------------------
                         start= ang_min
                         end  = ang_max
                         n= (ang_max-ang_min)/res
                         #------ new
                         self.start_data_ele = data_ele_new[0]
                         self.end_data_ele  = data_ele_new[-1]
                         if tipo_case==0  or tipo_case==3: # SUBIDA
                             n1= round(self.start_data_ele)- start
                             n2= end - round(self.end_data_ele)
                             print(self.start_data_ele)
                             print(self.end_data_ele)
                             if n1>0:
                                 ele1= numpy.linspace(ang_min+1,self.start_data_ele-1,n1)
                                 ele1_nan= numpy.ones(n1)*numpy.nan
                                 data_ele = numpy.hstack((ele1,data_ele_new))
                                 print("ele1_nan",ele1_nan.shape)
                                 print("data_ele_old",data_ele_old.shape)
                                 data_ele_old = numpy.hstack((ele1_nan,data_ele_old))
                             if n2>0:
                                 ele2= numpy.linspace(self.end_data_ele+1,end,n2)
                                 ele2_nan= numpy.ones(n2)*numpy.nan
                                 data_ele = numpy.hstack((data_ele,ele2))
                                 print("ele2_nan",ele2_nan.shape)
                                 print("data_ele_old",data_ele_old.shape)
                                 data_ele_old = numpy.hstack((data_ele_old,ele2_nan))
                         if tipo_case==1  or tipo_case==2: # BAJADA
                             data_ele_new       = data_ele_new[::-1] #  reversa
                             data_ele_old   = data_ele_old[::-1]# reversa
                             data_weather   = data_weather[::-1,:]# reversa
                             vec= numpy.where(data_ele_new<ang_max)
                             data_ele_new = data_ele_new[vec]
                             data_ele_old = data_ele_old[vec]
                             data_weather  = data_weather[vec[0]]
                             vec2= numpy.where(0<data_ele_new)
                             data_ele_new = data_ele_new[vec2]
                             data_ele_old = data_ele_old[vec2]
                             data_weather  = data_weather[vec2[0]]
                             self.start_data_ele = data_ele_new[0]
                             self.end_data_ele  = data_ele_new[-1]
                             n1= round(self.start_data_ele)- start
                             n2= end - round(self.end_data_ele)-1
                             print(self.start_data_ele)
                             print(self.end_data_ele)
                             if n1>0:
                                 ele1= numpy.linspace(ang_min+1,self.start_data_ele-1,n1)
                                 ele1_nan= numpy.ones(n1)*numpy.nan
                                 data_ele = numpy.hstack((ele1,data_ele_new))
                                 data_ele_old = numpy.hstack((ele1_nan,data_ele_old))
                             if n2>0:
                                 ele2= numpy.linspace(self.end_data_ele+1,end,n2)
                                 ele2_nan= numpy.ones(n2)*numpy.nan
                                 data_ele = numpy.hstack((data_ele,ele2))
                                 data_ele_old = numpy.hstack((data_ele_old,ele2_nan))
                         # RADAR
                         # NOTA data_ele y data_weather es la variable que retorna
                         val_mean         = numpy.mean(data_weather[:,-1])
                         self.val_mean    = val_mean
                         data_weather     = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean)
                         print("eleold",data_ele_old)
                         print(self.data_ele_tmp[val_ch])
                         print(data_ele_old.shape[0])
                         print(self.data_ele_tmp[val_ch].shape[0])
                         if (data_ele_old.shape[0]==91 or self.data_ele_tmp[val_ch].shape[0]==91):
                             import sys
                             print("EXIT",self.ini)
                             sys.exit(1)
                         self.data_ele_tmp[val_ch]= data_ele_old
                     else:
                         #print("**********************************************")
                         #print("****************VARIABLE**********************")
                         #-------------------------CAMBIOS RHI---------------------------------
                         #---------------------------------------------------------------------
                         ##print("INPUT data_ele",data_ele)
                         flag=0
                         start_ele = self.res_ele[0]
                         #tipo_case = self.check_case(data_ele,ang_max,ang_min)
                         tipo_case = case_flag[-1]
                         #print("TIPO DE DATA",tipo_case)
                         #-----------new------------
                         data_ele ,data_ele_old = self.globalCheckPED(data_ele,tipo_case)
                         data_weather           = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean)
                         #-------------------------------NEW RHI ITERATIVO-------------------------
                         if tipo_case==0 : # SUBIDA
                             vec = numpy.where(data_ele<ang_max)
                             data_ele = data_ele[vec]
                             data_ele_old = data_ele_old[vec]
                             data_weather  = data_weather[vec[0]]
                             vec2 = numpy.where(0<data_ele)
                             data_ele= data_ele[vec2]
                             data_ele_old= data_ele_old[vec2]
                             ##print(data_ele_new)
                             data_weather= data_weather[vec2[0]]
                             new_i_ele  = int(round(data_ele[0]))
                             new_f_ele  = int(round(data_ele[-1]))
                             #print(new_i_ele)
                             #print(new_f_ele)
                             #print(data_ele,len(data_ele))
                             #print(data_ele_old,len(data_ele_old))
                             if new_i_ele< 2:
                                 self.data_ele_tmp[val_ch] = numpy.ones(ang_max-ang_min)*numpy.nan
                                 self.res_weather[val_ch]  = self.replaceNAN(data_weather=self.res_weather[val_ch],data_ele=self.data_ele_tmp[val_ch],val=self.val_mean)
                             self.data_ele_tmp[val_ch][new_i_ele:new_i_ele+len(data_ele)]=data_ele_old
                             self.res_ele[new_i_ele:new_i_ele+len(data_ele)]= data_ele
                             self.res_weather[val_ch][new_i_ele:new_i_ele+len(data_ele),:]= data_weather
                             data_ele                                    = self.res_ele
                             data_weather                                = self.res_weather[val_ch]
                         elif tipo_case==1 : #BAJADA
                             data_ele       = data_ele[::-1] #  reversa
                             data_ele_old   = data_ele_old[::-1]# reversa
                             data_weather   = data_weather[::-1,:]# reversa
                             vec= numpy.where(data_ele<ang_max)
                             data_ele = data_ele[vec]
                             data_ele_old = data_ele_old[vec]
                             data_weather  = data_weather[vec[0]]
                             vec2= numpy.where(0<data_ele)
                             data_ele = data_ele[vec2]
                             data_ele_old = data_ele_old[vec2]
                             data_weather  = data_weather[vec2[0]]
                             new_i_ele  = int(round(data_ele[0]))
                             new_f_ele  = int(round(data_ele[-1]))
                             #print(data_ele)
                             #print(ang_max)
                             #print(data_ele_old)
                             if new_i_ele <= 1:
                                 new_i_ele = 1
                             if round(data_ele[-1])>=ang_max-1:
                                 self.data_ele_tmp[val_ch] = numpy.ones(ang_max-ang_min)*numpy.nan
                                 self.res_weather[val_ch]  = self.replaceNAN(data_weather=self.res_weather[val_ch],data_ele=self.data_ele_tmp[val_ch],val=self.val_mean)
                             self.data_ele_tmp[val_ch][new_i_ele-1:new_i_ele+len(data_ele)-1]=data_ele_old
                             self.res_ele[new_i_ele-1:new_i_ele+len(data_ele)-1]= data_ele
                             self.res_weather[val_ch][new_i_ele-1:new_i_ele+len(data_ele)-1,:]= data_weather
                             data_ele     = self.res_ele
                             data_weather = self.res_weather[val_ch]
                         elif tipo_case==2:  #bajada
                             vec = numpy.where(data_ele<ang_max)
                             data_ele = data_ele[vec]
                             data_weather= data_weather[vec[0]]
                             len_vec = len(vec)
                             data_ele_new     = data_ele[::-1] #  reversa
                             data_weather =  data_weather[::-1,:]
                             new_i_ele  = int(data_ele_new[0])
                             new_f_ele  = int(data_ele_new[-1])
                             n1= new_i_ele- ang_min
                             n2= ang_max - new_f_ele-1
                             if n1>0:
                                 ele1= numpy.linspace(ang_min+1,new_i_ele-1,n1)
                                 ele1_nan= numpy.ones(n1)*numpy.nan
                                 data_ele = numpy.hstack((ele1,data_ele_new))
                                 data_ele_old = numpy.hstack((ele1_nan,data_ele_new))
                             if n2>0:
                                 ele2= numpy.linspace(new_f_ele+1,ang_max,n2)
                                 ele2_nan= numpy.ones(n2)*numpy.nan
                                 data_ele = numpy.hstack((data_ele,ele2))
                                 data_ele_old = numpy.hstack((data_ele_old,ele2_nan))
                             self.data_ele_tmp[val_ch] = data_ele_old
                             self.res_ele      = data_ele
                             self.res_weather[val_ch]  = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean)
                             data_ele                                    = self.res_ele
                             data_weather                                = self.res_weather[val_ch]
                         elif tipo_case==3:#subida
                             vec = numpy.where(0<data_ele)
                             data_ele= data_ele[vec]
                             data_ele_new = data_ele
                             data_ele_old= data_ele_old[vec]
                             data_weather= data_weather[vec[0]]
                             pos_ini = numpy.argmin(data_ele)
                             if pos_ini>0:
                                 len_vec= len(data_ele)
                                 vec3  = numpy.linspace(pos_ini,len_vec-1,len_vec-pos_ini).astype(int)
                                 #print(vec3)
                                 data_ele= data_ele[vec3]
                                 data_ele_new = data_ele
                                 data_ele_old= data_ele_old[vec3]
                                 data_weather= data_weather[vec3]
                             new_i_ele  = int(data_ele_new[0])
                             new_f_ele  = int(data_ele_new[-1])
                             n1= new_i_ele- ang_min
                             n2= ang_max - new_f_ele-1
                             if n1>0:
                                 ele1= numpy.linspace(ang_min+1,new_i_ele-1,n1)
                                 ele1_nan= numpy.ones(n1)*numpy.nan
                                 data_ele = numpy.hstack((ele1,data_ele_new))
                                 data_ele_old = numpy.hstack((ele1_nan,data_ele_new))
                             if n2>0:
                                 ele2= numpy.linspace(new_f_ele+1,ang_max,n2)
                                 ele2_nan= numpy.ones(n2)*numpy.nan
                                 data_ele = numpy.hstack((data_ele,ele2))
                                 data_ele_old = numpy.hstack((data_ele_old,ele2_nan))
                             self.data_ele_tmp[val_ch] = data_ele_old
                             self.res_ele      = data_ele
                             self.res_weather[val_ch]  = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean)
                             data_ele                                    = self.res_ele
                             data_weather                                = self.res_weather[val_ch]
                     #print("self.data_ele_tmp",self.data_ele_tmp)
                     return data_weather,data_ele
                 def plot(self):
                     thisDatetime = datetime.datetime.utcfromtimestamp(self.data.times[-1]).strftime('%Y-%m-%d %H:%M:%S')
                     data         = self.data[-1]
                     r            = self.data.yrange
                     delta_height = r[1]-r[0]
                     r_mask       = numpy.where(r>=0)[0]
                     ##print("delta_height",delta_height)
                     #print("r_mask",r_mask,len(r_mask))
                     r            = numpy.arange(len(r_mask))*delta_height
                     self.y       = 2*r
                     res          = 1
                     ###print("data['weather'].shape[0]",data['weather'].shape[0])
                     ang_max = self.ang_max
                     ang_min = self.ang_min
                     var_ang      =ang_max -  ang_min
                     step         = (int(var_ang)/(res*data['weather'].shape[0]))
                     ###print("step",step)
                     #--------------------------------------------------------
                     ##print('weather',data['weather'].shape)
                     ##print('ele',data['ele'].shape)
                     ###self.res_weather, self.res_ele = self.const_ploteo(data_weather=data['weather'][:,r_mask],data_ele=data['ele'],step=step,res=res,ang_max=ang_max,ang_min=ang_min)
                     ###self.res_azi                   = numpy.mean(data['azi'])
                     ###print("self.res_ele",self.res_ele)
                     plt.clf()
                     subplots = [121, 122]
                     try:
                         if self.data[-2]['ele'].max()<data['ele'].max():
                             self.ini=0
                     except:
                         pass
                     if self.ini==0:
                         self.data_ele_tmp = numpy.ones([self.nplots,int(var_ang)])*numpy.nan
                         self.res_weather= numpy.ones([self.nplots,int(var_ang),len(r_mask)])*numpy.nan
                         print("SHAPE",self.data_ele_tmp.shape)
                     for i,ax in enumerate(self.axes):
                         self.res_weather[i], self.res_ele = self.const_ploteo(val_ch=i, data_weather=data['weather'][i][:,r_mask],data_ele=data['ele'],step=step,res=res,ang_max=ang_max,ang_min=ang_min,case_flag=self.data['case_flag'])
                         self.res_azi                   = numpy.mean(data['azi'])
                         if ax.firsttime:
                             #plt.clf()
                             print("Frist Plot")
                             cgax, pm = wrl.vis.plot_rhi(self.res_weather[i],r=r,th=self.res_ele,ax=subplots[i], proj='cg',vmin=20, vmax=80)
                             #fig=self.figures[0]
                         else:
                             #plt.clf()
                             print("ELSE PLOT")
                             cgax, pm = wrl.vis.plot_rhi(self.res_weather[i],r=r,th=self.res_ele,ax=subplots[i], proj='cg',vmin=20, vmax=80)
                         caax = cgax.parasites[0]
                         paax = cgax.parasites[1]
                         cbar = plt.gcf().colorbar(pm, pad=0.075)
                         caax.set_xlabel('x_range [km]')
                         caax.set_ylabel('y_range [km]')
                         plt.text(1.0, 1.05, 'Elevacion '+str(thisDatetime)+"  Step   "+str(self.ini)+ " Azi: "+str(round(self.res_azi,2)), transform=caax.transAxes, va='bottom',ha='right')
                     print("***************************self.ini****************************",self.ini)
                     self.ini= self.ini+1
             class WeatherRHI_vRF4_Plot(Plot):
                 CODE = 'RHI'
                 plot_name = 'RHI'
                 #plot_type = 'rhistyle'
                 buffering = False
                 def setup(self):
                     self.ncols = 1
                     self.nrows = 1
                     self.nplots= 1
                     self.ylabel= 'Range [Km]'
                     self.xlabel= 'Range [Km]'
                     self.titles= ['RHI']
                     self.polar = True
                     self.grid = True
                     if self.channels is not None:
                         self.nplots = len(self.channels)
                         self.nrows = len(self.channels)
                     else:
                         self.nplots = self.data.shape(self.CODE)[0]
                         self.nrows = self.nplots
                         self.channels = list(range(self.nplots))
                     if self.CODE == 'Power':
                         self.cb_label = r'Power (dB)'
                     elif self.CODE == 'Doppler':
                         self.cb_label = r'Velocity (m/s)'
                     self.colorbar=True
                     self.width   =8
                     self.height  =8
                     self.ini     =0
                     self.len_azi =0
                     self.buffer_ini  = None
                     self.buffer_ele   = None
                     self.plots_adjust.update({'wspace': 0.4, 'hspace':0.4, 'left': 0.1, 'right': 0.9, 'bottom': 0.08})
                     self.flag    =0
                     self.indicador= 0
                     self.last_data_ele = None
                     self.val_mean      = None
                 def update(self, dataOut):
                     data = {}
                     meta = {}
                     if hasattr(dataOut, 'dataPP_POWER'):
                         factor = 1
                     if hasattr(dataOut, 'nFFTPoints'):
                         factor = dataOut.normFactor
                     if 'pow' in self.attr_data[0].lower():
                         data['data'] = 10*numpy.log10(getattr(dataOut, self.attr_data[0])/(factor))
                     else:
                         data['data'] = getattr(dataOut, self.attr_data[0])/(factor)
                     data['azi']     = dataOut.data_azi
                     data['ele']     = dataOut.data_ele
                     return data, meta
                 def plot(self):
                     data         = self.data[-1]
                     r            = self.data.yrange
                     delta_height = r[1]-r[0]
                     r_mask       = numpy.where(r>=0)[0]
                     self.r_mask =r_mask
                     r            = numpy.arange(len(r_mask))*delta_height
                     self.y       = 2*r
                     z = data['data'][self.channels[0]][:,r_mask]
                     self.titles = []
                     self.ymax = self.ymax if self.ymax else numpy.nanmax(r)
                     self.ymin = self.ymin if self.ymin else numpy.nanmin(r)
                     self.zmax = self.zmax if self.zmax else numpy.nanmax(z)
                     self.zmin = self.zmin if self.zmin else numpy.nanmin(z)
                     self.ang_min = self.ang_min if self.ang_min else 0
                     self.ang_max = self.ang_max if self.ang_max else 90
                     r, theta = numpy.meshgrid(r, numpy.radians(data['ele']) )
                     for i,ax in enumerate(self.axes):
                         if ax.firsttime:
                             ax.set_xlim(numpy.radians(self.ang_min),numpy.radians(self.ang_max))
                             ax.plt = ax.pcolormesh(theta, r, z, cmap=self.colormap, vmin=self.zmin, vmax=self.zmax)
                         else:
                             ax.set_xlim(numpy.radians(self.ang_min),numpy.radians(self.ang_max))
                             ax.plt = ax.pcolormesh(theta, r, z, cmap=self.colormap, vmin=self.zmin, vmax=self.zmax)
                         ax.grid(True)
                         if len(self.channels) !=1:
                             self.titles = ['RHI {} at AZ: {} Channel {}'.format(self.labels[x], str(round(numpy.mean(data['azi']),1)), x) for x in range(self.nrows)]
                         else:
                             self.titles = ['RHI {} at AZ: {} Channel {}'.format(self.labels[0], str(round(numpy.mean(data['azi']),1)), self.channels[0])]

schainpy/model/proc/jroproc_base.py +20 -2

             '''
             Base clases to create Processing units and operations, the MPDecorator
             must be used in plotting and writing operations to allow to run as an
             external process.
             '''
             import os
             import inspect
             import zmq
             import time
             import pickle
             import traceback
             from threading import Thread
             from multiprocessing import Process, Queue
             from schainpy.utils import log
             QUEUE_SIZE = int(os.environ.get('QUEUE_MAX_SIZE', '10'))
             class ProcessingUnit(object):
                 '''
                 Base class to create Signal Chain Units
                 '''
                 proc_type = 'processing'
                 def __init__(self):
                     self.dataIn = None
                     self.dataOut = None
                     self.isConfig = False
                     self.operations = []
+                    self.name = 'Test'
+                    self.inputs = []
                 def setInput(self, unit):
-                    self.dataIn = unit.dataOut
+                    attr = 'dataIn'
+                    for i, u in enumerate(unit):
+                        if i==0:
+                            self.dataIn = u.dataOut
+                            self.inputs.append('dataIn')
+                        else:
+                            setattr(self, 'dataIn{}'.format(i), u.dataOut)
+                            self.inputs.append('dataIn{}'.format(i))
                 def getAllowedArgs(self):
                     if hasattr(self, '__attrs__'):
                         return self.__attrs__
                     else:
                         return inspect.getargspec(self.run).args
                 def addOperation(self, conf, operation):
                     '''
                     '''
                     self.operations.append((operation, conf.type, conf.getKwargs()))
                 def getOperationObj(self, objId):
                     if objId not in list(self.operations.keys()):
                         return None
                     return self.operations[objId]
                 def call(self, **kwargs):
                     '''
                     '''
                     try:
                         if self.dataIn is not None and self.dataIn.flagNoData and not self.dataIn.error:
                             return self.dataIn.isReady()
                         elif self.dataIn is None or not self.dataIn.error:
                             self.run(**kwargs)
                         elif self.dataIn.error:
                             self.dataOut.error = self.dataIn.error
                             self.dataOut.flagNoData = True
                     except:
                         err = traceback.format_exc()
                         if 'SchainWarning' in err:
                             log.warning(err.split('SchainWarning:')[-1].split('\n')[0].strip(), self.name)
                         elif 'SchainError' in err:
                             log.error(err.split('SchainError:')[-1].split('\n')[0].strip(), self.name)
                         else:
                             log.error(err, self.name)
                         self.dataOut.error = True
                     ##### correcion de la declaracion Out
                     for op, optype, opkwargs in self.operations:
                         aux = self.dataOut.copy()
                         if optype == 'other' and not self.dataOut.flagNoData:
                             self.dataOut = op.run(self.dataOut, **opkwargs)
                         elif optype == 'external' and not self.dataOut.flagNoData:
                             #op.queue.put(self.dataOut)
                             op.queue.put(aux)
                         elif optype == 'external' and self.dataOut.error:
                             #op.queue.put(self.dataOut)
                             op.queue.put(aux)
-                    return 'Error' if self.dataOut.error else self.dataOut.isReady()
+                    try:
+                        if self.dataOut.runNextUnit:
+                            runNextUnit = self.dataOut.runNextUnit
+                        else:
+                            runNextUnit = self.dataOut.isReady()
+                    except:
+                        runNextUnit = self.dataOut.isReady()
+                    return 'Error' if self.dataOut.error else runNextUnit
                 def setup(self):
                     raise NotImplementedError
                 def run(self):
                     raise NotImplementedError
                 def close(self):
                     return
             class Operation(object):
                 '''
                 '''
                 proc_type = 'operation'
                 def __init__(self):
                     self.id = None
                     self.isConfig = False
                     if not hasattr(self, 'name'):
                         self.name = self.__class__.__name__
                 def getAllowedArgs(self):
                     if hasattr(self, '__attrs__'):
                         return self.__attrs__
                     else:
                         return inspect.getargspec(self.run).args
                 def setup(self):
                     self.isConfig = True
                     raise NotImplementedError
                 def run(self, dataIn, **kwargs):
                     """
                     Realiza las operaciones necesarias sobre la dataIn.data y actualiza los
                     atributos del objeto dataIn.
                     Input:
                         dataIn    :    objeto del tipo JROData
                     Return:
                         None
                     Affected:
                         __buffer    :    buffer de recepcion de datos.
                     """
                     if not self.isConfig:
                         self.setup(**kwargs)
                     raise NotImplementedError
                 def close(self):
                     return
             def MPDecorator(BaseClass):
                 """
                 Multiprocessing class decorator
                 This function add multiprocessing features to a BaseClass.
                 """
                 class MPClass(BaseClass, Process):
                     def __init__(self, *args, **kwargs):
                         super(MPClass, self).__init__()
                         Process.__init__(self)
                         self.args = args
                         self.kwargs = kwargs
                         self.t = time.time()
                         self.op_type = 'external'
                         self.name = BaseClass.__name__
                         self.__doc__ = BaseClass.__doc__
                         if 'plot' in self.name.lower() and not self.name.endswith('_'):
                             self.name = '{}{}'.format(self.CODE.upper(), 'Plot')
                         self.start_time = time.time()
                         self.err_queue = args[3]
                         self.queue = Queue(maxsize=QUEUE_SIZE)
                         self.myrun = BaseClass.run
                     def run(self):
                         while True:
                             dataOut = self.queue.get()
                             if not dataOut.error:
                                 try:
                                     BaseClass.run(self, dataOut, **self.kwargs)
                                 except:
                                     err = traceback.format_exc()
                                     log.error(err, self.name)
                             else:
                                 break
                         self.close()
                     def close(self):
                         BaseClass.close(self)
                         log.success('Done...(Time:{:4.2f} secs)'.format(time.time()-self.start_time), self.name)
                 return MPClass

schainpy/model/proc/jroproc_parameters.py 0 0

	1	NO CONTENT: modified file			NO CONTENT: modified file
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schainpy/model/proc/jroproc_voltage.py +5 -7

             import sys
             import numpy,math
             from scipy import interpolate
             from schainpy.model.proc.jroproc_base import ProcessingUnit, Operation, MPDecorator
             from schainpy.model.data.jrodata import Voltage,hildebrand_sekhon
             from schainpy.utils import log
             from time import time
             class VoltageProc(ProcessingUnit):
                 def __init__(self):
                     ProcessingUnit.__init__(self)
                     self.dataOut = Voltage()
                     self.flip = 1
                     self.setupReq = False
                 def run(self):
                     if self.dataIn.type == 'AMISR':
                         self.__updateObjFromAmisrInput()
                     if self.dataIn.type == 'Voltage':
                         self.dataOut.copy(self.dataIn)
                 def __updateObjFromAmisrInput(self):
                     self.dataOut.timeZone = self.dataIn.timeZone
                     self.dataOut.dstFlag = self.dataIn.dstFlag
                     self.dataOut.errorCount = self.dataIn.errorCount
                     self.dataOut.useLocalTime = self.dataIn.useLocalTime
                     self.dataOut.flagNoData = self.dataIn.flagNoData
                     self.dataOut.data = self.dataIn.data
                     self.dataOut.utctime = self.dataIn.utctime
                     self.dataOut.channelList = self.dataIn.channelList
                     #self.dataOut.timeInterval = self.dataIn.timeInterval
                     self.dataOut.heightList = self.dataIn.heightList
                     self.dataOut.nProfiles = self.dataIn.nProfiles
                     self.dataOut.nCohInt = self.dataIn.nCohInt
                     self.dataOut.ippSeconds = self.dataIn.ippSeconds
                     self.dataOut.frequency = self.dataIn.frequency
                     self.dataOut.azimuth = self.dataIn.azimuth
                     self.dataOut.zenith = self.dataIn.zenith
                     self.dataOut.beam.codeList = self.dataIn.beam.codeList
                     self.dataOut.beam.azimuthList = self.dataIn.beam.azimuthList
                     self.dataOut.beam.zenithList = self.dataIn.beam.zenithList
             class selectChannels(Operation):
                 def run(self, dataOut, channelList):
                     channelIndexList = []
                     self.dataOut = dataOut
                     for channel in channelList:
                         if channel not in self.dataOut.channelList:
                             raise ValueError("Channel %d is not in %s" %(channel, str(self.dataOut.channelList)))
                         index = self.dataOut.channelList.index(channel)
                         channelIndexList.append(index)
                     self.selectChannelsByIndex(channelIndexList)
                     return self.dataOut
                 def selectChannelsByIndex(self, channelIndexList):
                     """
                     Selecciona un bloque de datos en base a canales segun el channelIndexList
                     Input:
                         channelIndexList    :    lista sencilla de canales a seleccionar por ej. [2,3,7]
                     Affected:
                         self.dataOut.data
                         self.dataOut.channelIndexList
                         self.dataOut.nChannels
                         self.dataOut.m_ProcessingHeader.totalSpectra
                         self.dataOut.systemHeaderObj.numChannels
                         self.dataOut.m_ProcessingHeader.blockSize
                     Return:
                         None
                     """
                     for channelIndex in channelIndexList:
                         if channelIndex not in self.dataOut.channelIndexList:
                             raise ValueError("The value %d in channelIndexList is not valid" %channelIndex)
                     if self.dataOut.type == 'Voltage':
                         if self.dataOut.flagDataAsBlock:
                             """
                             Si la data es obtenida por bloques, dimension = [nChannels, nProfiles, nHeis]
                             """
                             data = self.dataOut.data[channelIndexList,:,:]
                         else:
                             data = self.dataOut.data[channelIndexList,:]
                         self.dataOut.data = data
                         # self.dataOut.channelList = [self.dataOut.channelList[i] for i in channelIndexList]
                         self.dataOut.channelList = range(len(channelIndexList))
                     elif self.dataOut.type == 'Spectra':
                         data_spc = self.dataOut.data_spc[channelIndexList, :]
                         data_dc = self.dataOut.data_dc[channelIndexList, :]
                         self.dataOut.data_spc = data_spc
                         self.dataOut.data_dc = data_dc
                         # self.dataOut.channelList = [self.dataOut.channelList[i] for i in channelIndexList]
                         self.dataOut.channelList = range(len(channelIndexList))
                         self.__selectPairsByChannel(channelIndexList)
                     return 1
                 def __selectPairsByChannel(self, channelList=None):
                     if channelList == None:
                         return
                     pairsIndexListSelected = []
                     for pairIndex in self.dataOut.pairsIndexList:
                         # First pair
                         if self.dataOut.pairsList[pairIndex][0] not in channelList:
                             continue
                         # Second pair
                         if self.dataOut.pairsList[pairIndex][1] not in channelList:
                             continue
                         pairsIndexListSelected.append(pairIndex)
                     if not pairsIndexListSelected:
                         self.dataOut.data_cspc = None
                         self.dataOut.pairsList = []
                         return
                     self.dataOut.data_cspc = self.dataOut.data_cspc[pairsIndexListSelected]
                     self.dataOut.pairsList = [self.dataOut.pairsList[i]
                                               for i in pairsIndexListSelected]
                     return
             class selectHeights(Operation):
                 def run(self, dataOut, minHei=None, maxHei=None, minIndex=None, maxIndex=None):
                     """
                     Selecciona un bloque de datos en base a un grupo de valores de alturas segun el rango
                     minHei <= height <= maxHei
                     Input:
                         minHei    :    valor minimo de altura a considerar
                         maxHei    :    valor maximo de altura a considerar
                     Affected:
                         Indirectamente son cambiados varios valores a travez del metodo selectHeightsByIndex
                     Return:
 si el metodo se ejecuto con exito caso contrario devuelve 0
                     """
                     self.dataOut = dataOut
                     if minHei and maxHei:
                         if (minHei < self.dataOut.heightList[0]):
                             minHei = self.dataOut.heightList[0]
                         if (maxHei > self.dataOut.heightList[-1]):
                             maxHei = self.dataOut.heightList[-1]
                         minIndex = 0
                         maxIndex = 0
                         heights = self.dataOut.heightList
                         inda = numpy.where(heights >= minHei)
                         indb = numpy.where(heights <= maxHei)
                         try:
                             minIndex = inda[0][0]
                         except:
                             minIndex = 0
                         try:
                             maxIndex = indb[0][-1]
                         except:
                             maxIndex = len(heights)
                     self.selectHeightsByIndex(minIndex, maxIndex)
                     return self.dataOut
                 def selectHeightsByIndex(self, minIndex, maxIndex):
                     """
                     Selecciona un bloque de datos en base a un grupo indices de alturas segun el rango
                     minIndex <= index <= maxIndex
                     Input:
                         minIndex    :    valor de indice minimo de altura a considerar
                         maxIndex    :    valor de indice maximo de altura a considerar
                     Affected:
                         self.dataOut.data
                         self.dataOut.heightList
                     Return:
 si el metodo se ejecuto con exito caso contrario devuelve 0
                     """
                     if self.dataOut.type == 'Voltage':
                         if (minIndex < 0) or (minIndex > maxIndex):
                             raise ValueError("Height index range (%d,%d) is not valid" % (minIndex, maxIndex))
                         if (maxIndex >= self.dataOut.nHeights):
                             maxIndex = self.dataOut.nHeights
                         #print("shapeeee",self.dataOut.data.shape)
                         #voltage
                         if self.dataOut.flagDataAsBlock:
                             """
                             Si la data es obtenida por bloques, dimension = [nChannels, nProfiles, nHeis]
                             """
                             data = self.dataOut.data[:,:, minIndex:maxIndex]
                         else:
                             data = self.dataOut.data[:, minIndex:maxIndex]
                         #         firstHeight = self.dataOut.heightList[minIndex]
                         self.dataOut.data = data
                         self.dataOut.heightList = self.dataOut.heightList[minIndex:maxIndex]
                         if self.dataOut.nHeights <= 1:
                             raise ValueError("selectHeights: Too few heights. Current number of heights is %d" %(self.dataOut.nHeights))
                     elif self.dataOut.type == 'Spectra':
                         if (minIndex < 0) or (minIndex > maxIndex):
                             raise ValueError("Error selecting heights: Index range (%d,%d) is not valid" % (
                                 minIndex, maxIndex))
                         if (maxIndex >= self.dataOut.nHeights):
                             maxIndex = self.dataOut.nHeights - 1
                         # Spectra
                         data_spc = self.dataOut.data_spc[:, :, minIndex:maxIndex + 1]
                         data_cspc = None
                         if self.dataOut.data_cspc is not None:
                             data_cspc = self.dataOut.data_cspc[:, :, minIndex:maxIndex + 1]
                         data_dc = None
                         if self.dataOut.data_dc is not None:
                             data_dc = self.dataOut.data_dc[:, minIndex:maxIndex + 1]
                         self.dataOut.data_spc = data_spc
                         self.dataOut.data_cspc = data_cspc
                         self.dataOut.data_dc = data_dc
                         self.dataOut.heightList = self.dataOut.heightList[minIndex:maxIndex + 1]
                     return 1
             class filterByHeights(Operation):
                 def run(self, dataOut, window):
                     deltaHeight = dataOut.heightList[1] - dataOut.heightList[0]
                     if window == None:
                         window = (dataOut.radarControllerHeaderObj.txA/dataOut.radarControllerHeaderObj.nBaud) / deltaHeight
                     newdelta = deltaHeight * window
                     r = dataOut.nHeights % window
                     newheights = (dataOut.nHeights-r)/window
                     if newheights <= 1:
                         raise ValueError("filterByHeights: Too few heights. Current number of heights is %d and window is %d" %(dataOut.nHeights, window))
                     if dataOut.flagDataAsBlock:
                         """
                         Si la data es obtenida por bloques, dimension = [nChannels, nProfiles, nHeis]
                         """
                         buffer = dataOut.data[:, :, 0:int(dataOut.nHeights-r)]
                         buffer = buffer.reshape(dataOut.nChannels, dataOut.nProfiles, int(dataOut.nHeights/window), window)
                         buffer = numpy.sum(buffer,3)
                     else:
                         buffer = dataOut.data[:,0:int(dataOut.nHeights-r)]
                         buffer = buffer.reshape(dataOut.nChannels,int(dataOut.nHeights/window),int(window))
                         buffer = numpy.sum(buffer,2)
                     dataOut.data = buffer
                     dataOut.heightList = dataOut.heightList[0] + numpy.arange( newheights )*newdelta
                     dataOut.windowOfFilter = window
                     return dataOut
             class setH0(Operation):
                 def run(self, dataOut, h0, deltaHeight = None):
                     if not deltaHeight:
                         deltaHeight = dataOut.heightList[1] - dataOut.heightList[0]
                     nHeights = dataOut.nHeights
                     newHeiRange = h0 + numpy.arange(nHeights)*deltaHeight
                     dataOut.heightList = newHeiRange
                     return dataOut
             class deFlip(Operation):
                 def run(self, dataOut, channelList = []):
                     data = dataOut.data.copy()
                     if dataOut.flagDataAsBlock:
                         flip = self.flip
                         profileList = list(range(dataOut.nProfiles))
                         if not channelList:
                             for thisProfile in profileList:
                                 data[:,thisProfile,:] = data[:,thisProfile,:]*flip
                                 flip *= -1.0
                         else:
                             for thisChannel in channelList:
                                 if thisChannel not in dataOut.channelList:
                                     continue
                                 for thisProfile in profileList:
                                     data[thisChannel,thisProfile,:] = data[thisChannel,thisProfile,:]*flip
                                     flip *= -1.0
                         self.flip = flip
                     else:
                         if not channelList:
                             data[:,:] = data[:,:]*self.flip
                         else:
                             for thisChannel in channelList:
                                 if thisChannel not in dataOut.channelList:
                                     continue
                                 data[thisChannel,:] = data[thisChannel,:]*self.flip
                         self.flip *= -1.
                     dataOut.data = data
                     return dataOut
             class setAttribute(Operation):
                 '''
                 Set an arbitrary attribute(s) to dataOut
                 '''
                 def __init__(self):
                     Operation.__init__(self)
                     self._ready = False
                 def run(self, dataOut, **kwargs):
                     for key, value in kwargs.items():
                         setattr(dataOut, key, value)
                     return dataOut
             @MPDecorator
             class printAttribute(Operation):
                 '''
                 Print an arbitrary attribute of dataOut
                 '''
                 def __init__(self):
                     Operation.__init__(self)
                 def run(self, dataOut, attributes):
                     if isinstance(attributes, str):
                         attributes = [attributes]
                     for attr in attributes:
                         if hasattr(dataOut, attr):
                             log.log(getattr(dataOut, attr), attr)
             class interpolateHeights(Operation):
                 def run(self, dataOut, topLim, botLim):
                     #69 al 72 para julia
                     #82-84 para meteoros
                     if len(numpy.shape(dataOut.data))==2:
                         sampInterp = (dataOut.data[:,botLim-1] + dataOut.data[:,topLim+1])/2
                         sampInterp = numpy.transpose(numpy.tile(sampInterp,(topLim-botLim + 1,1)))
                         #dataOut.data[:,botLim:limSup+1] = sampInterp
                         dataOut.data[:,botLim:topLim+1] = sampInterp
                     else:
                         nHeights = dataOut.data.shape[2]
                         x = numpy.hstack((numpy.arange(botLim),numpy.arange(topLim+1,nHeights)))
                         y = dataOut.data[:,:,list(range(botLim))+list(range(topLim+1,nHeights))]
                         f = interpolate.interp1d(x, y, axis = 2)
                         xnew = numpy.arange(botLim,topLim+1)
                         ynew = f(xnew)
                         dataOut.data[:,:,botLim:topLim+1]  = ynew
                     return dataOut
             class CohInt(Operation):
                 isConfig = False
                 __profIndex = 0
                 __byTime = False
                 __initime = None
                 __lastdatatime = None
                 __integrationtime = None
                 __buffer = None
                 __bufferStride = []
                 __dataReady = False
                 __profIndexStride = 0
                 __dataToPutStride = False
                 n = None
                 def __init__(self, **kwargs):
                     Operation.__init__(self, **kwargs)
                 def setup(self, n=None, timeInterval=None, stride=None, overlapping=False, byblock=False):
                     """
                     Set the parameters of the integration class.
                     Inputs:
                         n               :    Number of coherent integrations
                         timeInterval    :    Time of integration. If the parameter "n" is selected this one does not work
                         overlapping     :
                     """
                     self.__initime = None
                     self.__lastdatatime = 0
                     self.__buffer = None
                     self.__dataReady = False
                     self.byblock = byblock
                     self.stride = stride
                     if n == None and timeInterval == None:
                         raise ValueError("n or timeInterval should be specified ...")
                     if n != None:
                         self.n = n
                         self.__byTime = False
                     else:
                         self.__integrationtime = timeInterval #* 60. #if (type(timeInterval)!=integer) -> change this line
                         self.n = 9999
                         self.__byTime = True
                     if overlapping:
                         self.__withOverlapping = True
                         self.__buffer = None
                     else:
                         self.__withOverlapping = False
                         self.__buffer = 0
                     self.__profIndex = 0
                 def putData(self, data):
                     """
                     Add a profile to the __buffer and increase in one the __profileIndex
                     """
                     if not self.__withOverlapping:
                         self.__buffer += data.copy()
                         self.__profIndex += 1
                         return
                     #Overlapping data
                     nChannels, nHeis = data.shape
                     data = numpy.reshape(data, (1, nChannels, nHeis))
                     #If the buffer is empty then it takes the data value
                     if self.__buffer is None:
                         self.__buffer = data
                         self.__profIndex += 1
                         return
                     #If the buffer length is lower than n then stakcing the data value
                     if self.__profIndex < self.n:
                         self.__buffer = numpy.vstack((self.__buffer, data))
                         self.__profIndex += 1
                         return
                     #If the buffer length is equal to n then replacing the last buffer value with the data value
                     self.__buffer = numpy.roll(self.__buffer, -1, axis=0)
                     self.__buffer[self.n-1] = data
                     self.__profIndex = self.n
                     return
                 def pushData(self):
                     """
                     Return the sum of the last profiles and the profiles used in the sum.
                     Affected:
                     self.__profileIndex
                     """
                     if not self.__withOverlapping:
                         data = self.__buffer
                         n = self.__profIndex
                         self.__buffer = 0
                         self.__profIndex = 0
                         return data, n
                     #Integration with Overlapping
                     data = numpy.sum(self.__buffer, axis=0)
                     # print data
                     # raise
                     n = self.__profIndex
                     return data, n
                 def byProfiles(self, data):
                     self.__dataReady = False
                     avgdata = None
                     #         n = None
                     # print data
                     # raise
                     self.putData(data)
                     if self.__profIndex == self.n:
                         avgdata, n = self.pushData()
                         self.__dataReady = True
                     return avgdata
                 def byTime(self, data, datatime):
                     self.__dataReady = False
                     avgdata = None
                     n = None
                     self.putData(data)
                     if (datatime - self.__initime) >= self.__integrationtime:
                         avgdata, n = self.pushData()
                         self.n = n
                         self.__dataReady = True
                     return avgdata
                 def integrateByStride(self, data, datatime):
                     # print data
                     if self.__profIndex == 0:
                         self.__buffer = [[data.copy(), datatime]]
                     else:
                         self.__buffer.append([data.copy(),datatime])
                     self.__profIndex += 1
                     self.__dataReady = False
                     if self.__profIndex == self.n * self.stride :
                         self.__dataToPutStride = True
                         self.__profIndexStride = 0
                         self.__profIndex = 0
                         self.__bufferStride = []
                         for i in range(self.stride):
                             current = self.__buffer[i::self.stride]
                             data = numpy.sum([t[0] for t in current], axis=0)
                             avgdatatime = numpy.average([t[1] for t in current])
                             # print data
                             self.__bufferStride.append((data, avgdatatime))
                     if self.__dataToPutStride:
                         self.__dataReady = True
                         self.__profIndexStride += 1
                         if self.__profIndexStride == self.stride:
                             self.__dataToPutStride = False
                         # print self.__bufferStride[self.__profIndexStride - 1]
                         # raise
                         return self.__bufferStride[self.__profIndexStride - 1]
                     return None, None
                 def integrate(self, data, datatime=None):
                     if self.__initime == None:
                         self.__initime = datatime
                     if self.__byTime:
                         avgdata = self.byTime(data, datatime)
                     else:
                         avgdata = self.byProfiles(data)
                     self.__lastdatatime = datatime
                     if avgdata is None:
                         return None, None
                     avgdatatime = self.__initime
                     deltatime = datatime - self.__lastdatatime
                     if not self.__withOverlapping:
                         self.__initime = datatime
                     else:
                         self.__initime += deltatime
                     return avgdata, avgdatatime
                 def integrateByBlock(self, dataOut):
                     times = int(dataOut.data.shape[1]/self.n)
                     avgdata = numpy.zeros((dataOut.nChannels, times, dataOut.nHeights), dtype=numpy.complex)
                     id_min = 0
                     id_max = self.n
                     for i in range(times):
                         junk = dataOut.data[:,id_min:id_max,:]
                         avgdata[:,i,:] = junk.sum(axis=1)
                         id_min += self.n
                         id_max += self.n
                     timeInterval = dataOut.ippSeconds*self.n
                     avgdatatime = (times - 1) * timeInterval + dataOut.utctime
                     self.__dataReady = True
                     return avgdata, avgdatatime
                 def run(self, dataOut, n=None, timeInterval=None, stride=None, overlapping=False, byblock=False, **kwargs):
                     if not self.isConfig:
                         self.setup(n=n, stride=stride, timeInterval=timeInterval, overlapping=overlapping, byblock=byblock, **kwargs)
                         self.isConfig = True
                     if dataOut.flagDataAsBlock:
                         """
                         Si la data es leida por bloques, dimension = [nChannels, nProfiles, nHeis]
                         """
                         avgdata, avgdatatime = self.integrateByBlock(dataOut)
                         dataOut.nProfiles /= self.n
                     else:
                         if stride is None:
                             avgdata, avgdatatime = self.integrate(dataOut.data, dataOut.utctime)
                         else:
                             avgdata, avgdatatime = self.integrateByStride(dataOut.data, dataOut.utctime)
                     #   dataOut.timeInterval *= n
                     dataOut.flagNoData = True
                     if self.__dataReady:
                         dataOut.data = avgdata
                         if not dataOut.flagCohInt:
                             dataOut.nCohInt *= self.n
                             dataOut.flagCohInt = True
                         dataOut.utctime = avgdatatime
                         # print avgdata, avgdatatime
                         # raise
                         #   dataOut.timeInterval = dataOut.ippSeconds * dataOut.nCohInt
                         dataOut.flagNoData = False
                     return dataOut
             class Decoder(Operation):
                 isConfig = False
                 __profIndex = 0
                 code = None
                 nCode = None
                 nBaud = None
                 def __init__(self, **kwargs):
                     Operation.__init__(self, **kwargs)
                     self.times = None
                     self.osamp = None
                 #         self.__setValues = False
                     self.isConfig = False
                     self.setupReq = False
                 def setup(self, code, osamp, dataOut):
                     self.__profIndex = 0
                     self.code = code
                     self.nCode = len(code)
                     self.nBaud = len(code[0])
                     if (osamp != None) and (osamp >1):
                         self.osamp = osamp
                         self.code = numpy.repeat(code, repeats=self.osamp, axis=1)
                         self.nBaud = self.nBaud*self.osamp
                     self.__nChannels = dataOut.nChannels
                     self.__nProfiles = dataOut.nProfiles
                     self.__nHeis = dataOut.nHeights
                     if self.__nHeis < self.nBaud:
                         raise ValueError('Number of heights (%d) should be greater than number of bauds (%d)' %(self.__nHeis, self.nBaud))
                     #Frequency
                     __codeBuffer = numpy.zeros((self.nCode, self.__nHeis), dtype=numpy.complex)
                     __codeBuffer[:,0:self.nBaud] = self.code
                     self.fft_code = numpy.conj(numpy.fft.fft(__codeBuffer, axis=1))
                     if dataOut.flagDataAsBlock:
                         self.ndatadec = self.__nHeis #- self.nBaud + 1
                         self.datadecTime = numpy.zeros((self.__nChannels, self.__nProfiles, self.ndatadec), dtype=numpy.complex)
                     else:
                         #Time
                         self.ndatadec = self.__nHeis #- self.nBaud + 1
                         self.datadecTime = numpy.zeros((self.__nChannels, self.ndatadec), dtype=numpy.complex)
                 def __convolutionInFreq(self, data):
                     fft_code = self.fft_code[self.__profIndex].reshape(1,-1)
                     fft_data = numpy.fft.fft(data, axis=1)
                     conv = fft_data*fft_code
                     data = numpy.fft.ifft(conv,axis=1)
                     return data
                 def __convolutionInFreqOpt(self, data):
                     raise NotImplementedError
                 def __convolutionInTime(self, data):
                     code = self.code[self.__profIndex]
                     for i in range(self.__nChannels):
                         self.datadecTime[i,:] = numpy.correlate(data[i,:], code, mode='full')[self.nBaud-1:]
                     return self.datadecTime
                 def __convolutionByBlockInTime(self, data):
                     repetitions = int(self.__nProfiles / self.nCode)
                     junk = numpy.lib.stride_tricks.as_strided(self.code, (repetitions, self.code.size), (0, self.code.itemsize))
                     junk = junk.flatten()
                     code_block = numpy.reshape(junk, (self.nCode*repetitions, self.nBaud))
                     profilesList = range(self.__nProfiles)
                     for i in range(self.__nChannels):
                         for j in profilesList:
                             self.datadecTime[i,j,:] = numpy.correlate(data[i,j,:], code_block[j,:], mode='full')[self.nBaud-1:]
                     return self.datadecTime
                 def __convolutionByBlockInFreq(self, data):
                     raise NotImplementedError("Decoder by frequency fro Blocks not implemented")
                     fft_code = self.fft_code[self.__profIndex].reshape(1,-1)
                     fft_data = numpy.fft.fft(data, axis=2)
                     conv = fft_data*fft_code
                     data = numpy.fft.ifft(conv,axis=2)
                     return data
                 def run(self, dataOut, code=None, nCode=None, nBaud=None, mode = 0, osamp=None, times=None):
                     if dataOut.flagDecodeData:
                         print("This data is already decoded, recoding again ...")
                     if not self.isConfig:
                         if code is None:
                             if dataOut.code is None:
                                 raise ValueError("Code could not be read from %s instance. Enter a value in Code parameter" %dataOut.type)
                             code = dataOut.code
                         else:
                             code = numpy.array(code).reshape(nCode,nBaud)
                         self.setup(code, osamp, dataOut)
                         self.isConfig = True
                         if mode == 3:
                             sys.stderr.write("Decoder Warning: mode=%d is not valid, using mode=0\n" %mode)
                         if times != None:
                             sys.stderr.write("Decoder Warning: Argument 'times' in not used anymore\n")
                     if self.code is None:
                         print("Fail decoding: Code is not defined.")
                         return
                     self.__nProfiles = dataOut.nProfiles
                     datadec = None
                     if mode == 3:
                         mode = 0
                     if dataOut.flagDataAsBlock:
                         """
                         Decoding when data have been read as block,
                         """
                         if mode == 0:
                             datadec = self.__convolutionByBlockInTime(dataOut.data)
                         if mode == 1:
                             datadec = self.__convolutionByBlockInFreq(dataOut.data)
                     else:
                         """
                         Decoding when data have been read profile by profile
                         """
                         if mode == 0:
                             datadec = self.__convolutionInTime(dataOut.data)
                         if mode == 1:
                             datadec = self.__convolutionInFreq(dataOut.data)
                         if mode == 2:
                             datadec = self.__convolutionInFreqOpt(dataOut.data)
                     if datadec is None:
                         raise ValueError("Codification mode selected is not valid: mode=%d. Try selecting 0 or 1" %mode)
                     dataOut.code = self.code
                     dataOut.nCode = self.nCode
                     dataOut.nBaud = self.nBaud
                     dataOut.data = datadec
                     dataOut.heightList = dataOut.heightList[0:datadec.shape[-1]]
                     dataOut.flagDecodeData = True #asumo q la data esta decodificada
                     if self.__profIndex == self.nCode-1:
                         self.__profIndex = 0
                         return dataOut
                     self.__profIndex += 1
                     return dataOut
                 #        dataOut.flagDeflipData = True #asumo q la data no esta sin flip
             class ProfileConcat(Operation):
                 isConfig = False
                 buffer = None
                 def __init__(self, **kwargs):
                     Operation.__init__(self, **kwargs)
                     self.profileIndex = 0
                 def reset(self):
                     self.buffer = numpy.zeros_like(self.buffer)
                     self.start_index = 0
                     self.times = 1
                 def setup(self, data, m, n=1):
                     self.buffer = numpy.zeros((data.shape[0],data.shape[1]*m),dtype=type(data[0,0]))
                     self.nHeights = data.shape[1]#.nHeights
                     self.start_index = 0
                     self.times = 1
                 def concat(self, data):
                     self.buffer[:,self.start_index:self.nHeights*self.times] = data.copy()
                     self.start_index = self.start_index + self.nHeights
                 def run(self, dataOut, m):
                     dataOut.flagNoData = True
                     if not self.isConfig:
                         self.setup(dataOut.data, m, 1)
                         self.isConfig = True
                     if dataOut.flagDataAsBlock:
                         raise ValueError("ProfileConcat can only be used when voltage have been read profile by profile, getBlock = False")
                     else:
                         self.concat(dataOut.data)
                         self.times += 1
                         if self.times > m:
                             dataOut.data = self.buffer
                             self.reset()
                             dataOut.flagNoData = False
                             # se deben actualizar mas propiedades del header y del objeto dataOut, por ejemplo, las alturas
                             deltaHeight = dataOut.heightList[1] - dataOut.heightList[0]
                             xf = dataOut.heightList[0] + dataOut.nHeights * deltaHeight * m
                             dataOut.heightList = numpy.arange(dataOut.heightList[0], xf, deltaHeight)
                             dataOut.ippSeconds *= m
                     return dataOut
             class ProfileSelector(Operation):
                 profileIndex = None
                 # Tamanho total de los perfiles
                 nProfiles = None
                 def __init__(self, **kwargs):
                     Operation.__init__(self, **kwargs)
                     self.profileIndex = 0
                 def incProfileIndex(self):
                     self.profileIndex += 1
                     if self.profileIndex >= self.nProfiles:
                         self.profileIndex = 0
                 def isThisProfileInRange(self, profileIndex, minIndex, maxIndex):
                     if profileIndex < minIndex:
                         return False
                     if profileIndex > maxIndex:
                         return False
                     return True
                 def isThisProfileInList(self, profileIndex, profileList):
                     if profileIndex not in profileList:
                         return False
                     return True
                 def run(self, dataOut, profileList=None, profileRangeList=None, beam=None, byblock=False, rangeList = None, nProfiles=None):
+                    #print("before",dataOut.data.shape)
                     """
                     ProfileSelector:
                     Inputs:
                         profileList        :    Index of profiles selected. Example: profileList = (0,1,2,7,8)
                         profileRangeList    :    Minimum and maximum profile indexes. Example: profileRangeList = (4, 30)
                         rangeList            :    List of profile ranges. Example: rangeList = ((4, 30), (32, 64), (128, 256))
                     """
                     if rangeList is not None:
                         if type(rangeList[0]) not in (tuple, list):
                             rangeList = [rangeList]
                     dataOut.flagNoData = True
                     if dataOut.flagDataAsBlock:
                         """
                         data dimension  = [nChannels, nProfiles, nHeis]
                         """
                         if profileList != None:
                             dataOut.data = dataOut.data[:,profileList,:]
                         if profileRangeList != None:
                             minIndex = profileRangeList[0]
                             maxIndex = profileRangeList[1]
                             profileList = list(range(minIndex, maxIndex+1))
                             dataOut.data = dataOut.data[:,minIndex:maxIndex+1,:]
                         if rangeList != None:
                             profileList = []
                             for thisRange in rangeList:
                                 minIndex = thisRange[0]
                                 maxIndex = thisRange[1]
                                 profileList.extend(list(range(minIndex, maxIndex+1)))
                             dataOut.data = dataOut.data[:,profileList,:]
                         dataOut.nProfiles = len(profileList)
                         dataOut.profileIndex = dataOut.nProfiles - 1
                         dataOut.flagNoData = False
+                        #print(dataOut.data.shape)
                         return dataOut
                     """
                     data dimension  = [nChannels, nHeis]
                     """
                     if profileList != None:
                         if self.isThisProfileInList(dataOut.profileIndex, profileList):
                             self.nProfiles = len(profileList)
                             dataOut.nProfiles = self.nProfiles
                             dataOut.profileIndex = self.profileIndex
                             dataOut.flagNoData = False
                             self.incProfileIndex()
                         return dataOut
                     if profileRangeList != None:
                         minIndex = profileRangeList[0]
                         maxIndex = profileRangeList[1]
                         if self.isThisProfileInRange(dataOut.profileIndex, minIndex, maxIndex):
                             self.nProfiles = maxIndex - minIndex + 1
                             dataOut.nProfiles = self.nProfiles
                             dataOut.profileIndex = self.profileIndex
                             dataOut.flagNoData = False
                             self.incProfileIndex()
                         return dataOut
                     if rangeList != None:
                         nProfiles = 0
                         for thisRange in rangeList:
                             minIndex = thisRange[0]
                             maxIndex = thisRange[1]
                             nProfiles += maxIndex - minIndex + 1
                         for thisRange in rangeList:
                             minIndex = thisRange[0]
                             maxIndex = thisRange[1]
                             if self.isThisProfileInRange(dataOut.profileIndex, minIndex, maxIndex):
                                 self.nProfiles = nProfiles
                                 dataOut.nProfiles = self.nProfiles
                                 dataOut.profileIndex = self.profileIndex
                                 dataOut.flagNoData = False
                                 self.incProfileIndex()
                                 break
                         return dataOut
                     if beam != None: #beam is only for AMISR data
                         if self.isThisProfileInList(dataOut.profileIndex, dataOut.beamRangeDict[beam]):
                             dataOut.flagNoData = False
                             dataOut.profileIndex = self.profileIndex
                             self.incProfileIndex()
                         return dataOut
                     raise ValueError("ProfileSelector needs profileList, profileRangeList or rangeList parameter")
             class Reshaper(Operation):
                 def __init__(self, **kwargs):
                     Operation.__init__(self, **kwargs)
                     self.__buffer = None
                     self.__nitems = 0
                 def __appendProfile(self, dataOut, nTxs):
                     if self.__buffer is None:
                         shape = (dataOut.nChannels, int(dataOut.nHeights/nTxs) )
                         self.__buffer = numpy.empty(shape, dtype = dataOut.data.dtype)
                     ini = dataOut.nHeights * self.__nitems
                     end = ini + dataOut.nHeights
                     self.__buffer[:, ini:end] = dataOut.data
                     self.__nitems += 1
                     return int(self.__nitems*nTxs)
                 def __getBuffer(self):
                     if self.__nitems == int(1./self.__nTxs):
                         self.__nitems = 0
                         return self.__buffer.copy()
                     return None
                 def __checkInputs(self, dataOut, shape, nTxs):
                     if shape is None and nTxs is None:
                         raise ValueError("Reshaper: shape of factor should be defined")
                     if nTxs:
                         if nTxs < 0:
                             raise ValueError("nTxs should be greater than 0")
                         if nTxs < 1 and dataOut.nProfiles % (1./nTxs) != 0:
                             raise ValueError("nProfiles= %d is not divisibled by (1./nTxs) = %f" %(dataOut.nProfiles, (1./nTxs)))
                         shape = [dataOut.nChannels, dataOut.nProfiles*nTxs, dataOut.nHeights/nTxs]
                         return shape, nTxs
                     if len(shape) != 2 and len(shape) !=  3:
                         raise ValueError("shape dimension should be equal to 2 or 3. shape = (nProfiles, nHeis) or (nChannels, nProfiles, nHeis). Actually shape = (%d, %d, %d)" %(dataOut.nChannels, dataOut.nProfiles, dataOut.nHeights))
                     if len(shape) == 2:
                         shape_tuple = [dataOut.nChannels]
                         shape_tuple.extend(shape)
                     else:
                         shape_tuple = list(shape)
                     nTxs = 1.0*shape_tuple[1]/dataOut.nProfiles
                     return shape_tuple, nTxs
                 def run(self, dataOut, shape=None, nTxs=None):
                     shape_tuple, self.__nTxs = self.__checkInputs(dataOut, shape, nTxs)
                     dataOut.flagNoData = True
                     profileIndex = None
                     if dataOut.flagDataAsBlock:
                         dataOut.data = numpy.reshape(dataOut.data, shape_tuple)
                         dataOut.flagNoData = False
                         profileIndex = int(dataOut.nProfiles*self.__nTxs) - 1
                     else:
                         if self.__nTxs < 1:
                             self.__appendProfile(dataOut, self.__nTxs)
                             new_data = self.__getBuffer()
                             if new_data is not None:
                                 dataOut.data = new_data
                                 dataOut.flagNoData = False
                                 profileIndex = dataOut.profileIndex*nTxs
                         else:
                             raise ValueError("nTxs should be greater than 0 and lower than 1, or use VoltageReader(..., getblock=True)")
                     deltaHeight = dataOut.heightList[1] - dataOut.heightList[0]
                     dataOut.heightList = numpy.arange(dataOut.nHeights/self.__nTxs) * deltaHeight + dataOut.heightList[0]
                     dataOut.nProfiles = int(dataOut.nProfiles*self.__nTxs)
                     dataOut.profileIndex = profileIndex
                     dataOut.ippSeconds /= self.__nTxs
                     return dataOut
             class SplitProfiles(Operation):
                 def __init__(self, **kwargs):
                     Operation.__init__(self, **kwargs)
                 def run(self, dataOut, n):
                     dataOut.flagNoData = True
                     profileIndex = None
                     if dataOut.flagDataAsBlock:
                         #nchannels, nprofiles, nsamples
                         shape = dataOut.data.shape
                         if shape[2] % n != 0:
                             raise ValueError("Could not split the data, n=%d has to be multiple of %d" %(n, shape[2]))
                         new_shape = shape[0], shape[1]*n, int(shape[2]/n)
                         dataOut.data = numpy.reshape(dataOut.data, new_shape)
                         dataOut.flagNoData = False
                         profileIndex = int(dataOut.nProfiles/n) - 1
                     else:
                         raise ValueError("Could not split the data when is read Profile by Profile. Use VoltageReader(..., getblock=True)")
                     deltaHeight = dataOut.heightList[1] - dataOut.heightList[0]
                     dataOut.heightList = numpy.arange(dataOut.nHeights/n) * deltaHeight + dataOut.heightList[0]
                     dataOut.nProfiles = int(dataOut.nProfiles*n)
                     dataOut.profileIndex = profileIndex
                     dataOut.ippSeconds /= n
                     return dataOut
             class CombineProfiles(Operation):
                 def __init__(self, **kwargs):
                     Operation.__init__(self, **kwargs)
                     self.__remData = None
                     self.__profileIndex = 0
                 def run(self, dataOut, n):
                     dataOut.flagNoData = True
                     profileIndex = None
                     if dataOut.flagDataAsBlock:
                         #nchannels, nprofiles, nsamples
                         shape = dataOut.data.shape
                         new_shape = shape[0], shape[1]/n, shape[2]*n
                         if shape[1] % n != 0:
                             raise ValueError("Could not split the data, n=%d has to be multiple of %d" %(n, shape[1]))
                         dataOut.data = numpy.reshape(dataOut.data, new_shape)
                         dataOut.flagNoData = False
                         profileIndex = int(dataOut.nProfiles*n) - 1
                     else:
                         #nchannels, nsamples
                         if self.__remData is None:
                             newData = dataOut.data
                         else:
                             newData = numpy.concatenate((self.__remData, dataOut.data), axis=1)
                         self.__profileIndex += 1
                         if self.__profileIndex < n:
                             self.__remData = newData
                             #continue
                             return
                         self.__profileIndex = 0
                         self.__remData = None
                         dataOut.data = newData
                         dataOut.flagNoData = False
                         profileIndex = dataOut.profileIndex/n
                     deltaHeight = dataOut.heightList[1] - dataOut.heightList[0]
                     dataOut.heightList = numpy.arange(dataOut.nHeights*n) * deltaHeight + dataOut.heightList[0]
                     dataOut.nProfiles = int(dataOut.nProfiles/n)
                     dataOut.profileIndex = profileIndex
                     dataOut.ippSeconds *= n
                     return dataOut
             class PulsePair(Operation):
                 '''
                 Function PulsePair(Signal Power, Velocity)
                 The real component of Lag[0] provides Intensity Information
                 The imag component of Lag[1] Phase provides Velocity Information
                 Configuration Parameters:
                 nPRF = Number of Several PRF
                 theta = Degree Azimuth angel Boundaries
                 Input:
                       self.dataOut
                       lag[N]
                 Affected:
                       self.dataOut.spc
                 '''
                 isConfig       = False
                 __profIndex    = 0
                 __initime      = None
                 __lastdatatime = None
                 __buffer       = None
                 noise          = None
                 __dataReady    = False
                 n              = None
                 __nch          = 0
                 __nHeis        = 0
                 removeDC       = False
                 ipp            = None
                 lambda_        = 0
                 def __init__(self,**kwargs):
                     Operation.__init__(self,**kwargs)
                 def setup(self, dataOut, n = None, removeDC=False):
                     '''
                     n= Numero de PRF's de entrada
                     '''
                     self.__initime        = None
                     ####print("[INICIO]-setup  del METODO PULSE PAIR")
                     self.__lastdatatime   = 0
                     self.__dataReady      = False
                     self.__buffer         = 0
                     self.__profIndex      = 0
                     self.noise            = None
                     self.__nch            = dataOut.nChannels
                     self.__nHeis          = dataOut.nHeights
                     self.removeDC         = removeDC
                     self.lambda_          = 3.0e8/(9345.0e6)
                     self.ippSec           = dataOut.ippSeconds
                     self.nCohInt          = dataOut.nCohInt
                     ####print("IPPseconds",dataOut.ippSeconds)
                     ####print("ELVALOR DE n es:", n)
                     if n == None:
                         raise ValueError("n should be specified.")
                     if n != None:
                         if n<2:
                             raise ValueError("n should be greater than 2")
                     self.n       = n
                     self.__nProf = n
                     self.__buffer = numpy.zeros((dataOut.nChannels,
                                                        n,
                                                        dataOut.nHeights),
                                                       dtype='complex')
                 def putData(self,data):
                     '''
                     Add a profile to he __buffer and increase in one the __profiel Index
                     '''
                     self.__buffer[:,self.__profIndex,:]= data
                     self.__profIndex      += 1
                     return
                 def pushData(self,dataOut):
                     '''
                     Return the PULSEPAIR and the profiles used in the operation
                     Affected :  self.__profileIndex
                     '''
                     #----------------- Remove DC-----------------------------------
                     if self.removeDC==True:
                         mean    = numpy.mean(self.__buffer,1)
                         tmp     = mean.reshape(self.__nch,1,self.__nHeis)
                         dc= numpy.tile(tmp,[1,self.__nProf,1])
                         self.__buffer = self.__buffer -  dc
                     #------------------Calculo de Potencia ------------------------
                     pair0       = self.__buffer*numpy.conj(self.__buffer)
                     pair0       = pair0.real
                     lag_0       = numpy.sum(pair0,1)
                     #-----------------Calculo de Cscp------------------------------ New
                     cspc_pair01 = self.__buffer[0]*self.__buffer[1]
                     #------------------Calculo de Ruido x canal--------------------
                     self.noise  = numpy.zeros(self.__nch)
                     for i in range(self.__nch):
                         daux         = numpy.sort(pair0[i,:,:],axis= None)
                         self.noise[i]=hildebrand_sekhon( daux ,self.nCohInt)
                     self.noise       = self.noise.reshape(self.__nch,1)
                     self.noise       = numpy.tile(self.noise,[1,self.__nHeis])
                     noise_buffer     = self.noise.reshape(self.__nch,1,self.__nHeis)
                     noise_buffer     = numpy.tile(noise_buffer,[1,self.__nProf,1])
                     #------------------ Potencia recibida= P , Potencia senal = S , Ruido= N--
                     #------------------   P= S+N  ,P=lag_0/N ---------------------------------
                     #-------------------- Power --------------------------------------------------
                     data_power       = lag_0/(self.n*self.nCohInt)
                     #--------------------CCF------------------------------------------------------
                     data_ccf         =numpy.sum(cspc_pair01,axis=0)/(self.n*self.nCohInt)
                     #------------------  Senal  --------------------------------------------------
                     data_intensity   = pair0 - noise_buffer
                     data_intensity   = numpy.sum(data_intensity,axis=1)*(self.n*self.nCohInt)#*self.nCohInt)
                     #data_intensity   = (lag_0-self.noise*self.n)*(self.n*self.nCohInt)
                     for i in range(self.__nch):
                         for j in range(self.__nHeis):
                             if data_intensity[i][j]  < 0:
                                 data_intensity[i][j] = numpy.min(numpy.absolute(data_intensity[i][j]))
                     #----------------- Calculo de Frecuencia y Velocidad doppler--------
                     pair1            = self.__buffer[:,:-1,:]*numpy.conjugate(self.__buffer[:,1:,:])
                     lag_1            = numpy.sum(pair1,1)
                     data_freq        = (-1/(2.0*math.pi*self.ippSec*self.nCohInt))*numpy.angle(lag_1)
                     data_velocity    = (self.lambda_/2.0)*data_freq
                     #---------------- Potencia promedio estimada de la Senal-----------
                     lag_0            = lag_0/self.n
                     S                = lag_0-self.noise
                     #---------------- Frecuencia Doppler promedio ---------------------
                     lag_1            = lag_1/(self.n-1)
                     R1               = numpy.abs(lag_1)
                     #---------------- Calculo del SNR----------------------------------
                     data_snrPP       = S/self.noise
                     for i in range(self.__nch):
                         for j in range(self.__nHeis):
                             if data_snrPP[i][j]  < 1.e-20:
                                 data_snrPP[i][j] = 1.e-20
                     #----------------- Calculo del ancho espectral ----------------------
                     L                = S/R1
                     L                = numpy.where(L<0,1,L)
                     L                = numpy.log(L)
                     tmp              = numpy.sqrt(numpy.absolute(L))
                     data_specwidth   = (self.lambda_/(2*math.sqrt(2)*math.pi*self.ippSec*self.nCohInt))*tmp*numpy.sign(L)
                     n                = self.__profIndex
                     self.__buffer    = numpy.zeros((self.__nch, self.__nProf,self.__nHeis),  dtype='complex')
                     self.__profIndex = 0
                     return data_power,data_intensity,data_velocity,data_snrPP,data_specwidth,data_ccf,n
                 def pulsePairbyProfiles(self,dataOut):
                     self.__dataReady     =  False
                     data_power           =  None
                     data_intensity       =  None
                     data_velocity        =  None
                     data_specwidth       =  None
                     data_snrPP           =  None
                     data_ccf             =  None
                     self.putData(data=dataOut.data)
                     if self.__profIndex  == self.n:
                         data_power,data_intensity, data_velocity,data_snrPP,data_specwidth,data_ccf, n   = self.pushData(dataOut=dataOut)
                         self.__dataReady                   = True
                     return data_power, data_intensity, data_velocity, data_snrPP,data_specwidth,data_ccf
                 def pulsePairOp(self, dataOut, datatime= None):
                     if self.__initime == None:
                         self.__initime = datatime
                     data_power, data_intensity, data_velocity, data_snrPP,data_specwidth,data_ccf = self.pulsePairbyProfiles(dataOut)
                     self.__lastdatatime           = datatime
                     if data_power is None:
                         return None, None, None,None,None,None,None
                     avgdatatime    = self.__initime
                     deltatime      = datatime - self.__lastdatatime
                     self.__initime = datatime
                     return data_power, data_intensity, data_velocity, data_snrPP,data_specwidth,data_ccf, avgdatatime
                 def run(self, dataOut,n = None,removeDC= False, overlapping= False,**kwargs):
                     #print("hey")
                     #print(dataOut.data.shape)
                     #exit(1)
                     #print(self.__profIndex)
                     if not self.isConfig:
                         self.setup(dataOut = dataOut, n    = n , removeDC=removeDC , **kwargs)
                         self.isConfig   = True
                     data_power, data_intensity, data_velocity,data_snrPP,data_specwidth,data_ccf, avgdatatime = self.pulsePairOp(dataOut, dataOut.utctime)
                     dataOut.flagNoData                         = True
                     if self.__dataReady:
                         ###print("READY ----------------------------------")
                         dataOut.nCohInt        *= self.n
                         dataOut.dataPP_POW      = data_intensity # S
                         dataOut.dataPP_POWER    = data_power     # P valor que corresponde a POTENCIA MOMENTO
                         dataOut.dataPP_DOP      = data_velocity
                         dataOut.dataPP_SNR      = data_snrPP
                         dataOut.dataPP_WIDTH    = data_specwidth
                         dataOut.dataPP_CCF      = data_ccf
                         dataOut.PRFbyAngle      = self.n         #numero de PRF*cada angulo rotado que equivale a un tiempo.
                         dataOut.nProfiles       = int(dataOut.nProfiles/n)
                         dataOut.utctime         = avgdatatime
                         dataOut.flagNoData      = False
                     return dataOut
             class PulsePair_vRF(Operation):
                 '''
                 Function PulsePair(Signal Power, Velocity)
                 The real component of Lag[0] provides Intensity Information
                 The imag component of Lag[1] Phase provides Velocity Information
                 Configuration Parameters:
                 nPRF = Number of Several PRF
                 theta = Degree Azimuth angel Boundaries
                 Input:
                       self.dataOut
                       lag[N]
                 Affected:
                       self.dataOut.spc
                 '''
                 isConfig       = False
                 __profIndex    = 0
                 __initime      = None
                 __lastdatatime = None
                 __buffer       = None
                 noise          = None
                 __dataReady    = False
                 n              = None
                 __nch          = 0
                 __nHeis        = 0
                 removeDC       = False
                 ipp            = None
                 lambda_        = 0
                 def __init__(self,**kwargs):
                     Operation.__init__(self,**kwargs)
                 def setup(self, dataOut, n = None, removeDC=False):
                     '''
                     n= Numero de PRF's de entrada
                     '''
                     self.__initime        = None
                     ####print("[INICIO]-setup  del METODO PULSE PAIR")
                     self.__lastdatatime   = 0
                     self.__dataReady      = False
                     self.__buffer         = 0
                     self.__profIndex      = 0
                     self.noise            = None
                     self.__nch            = dataOut.nChannels
                     self.__nHeis          = dataOut.nHeights
                     self.removeDC         = removeDC
                     self.lambda_          = 3.0e8/(9345.0e6)
                     self.ippSec           = dataOut.ippSeconds
                     self.nCohInt          = dataOut.nCohInt
                     ####print("IPPseconds",dataOut.ippSeconds)
                     ####print("ELVALOR DE n es:", n)
                     if n == None:
                         raise ValueError("n should be specified.")
                     if n != None:
                         if n<2:
                             raise ValueError("n should be greater than 2")
                     self.n       = n
                     self.__nProf = n
                     self.__buffer = numpy.zeros((dataOut.nChannels,
                                                        n,
                                                        dataOut.nHeights),
                                                       dtype='complex')
                 def putData(self,data):
                     '''
                     Add a profile to he __buffer and increase in one the __profiel Index
                     '''
                     self.__buffer[:,self.__profIndex,:]= data
                     self.__profIndex      += 1
                     return
                 def putDataByBlock(self,data,n):
                     '''
                     Add a profile to he __buffer and increase in one the __profiel Index
                     '''
                     self.__buffer[:]= data
                     self.__profIndex      = n
                     return
                 def pushData(self,dataOut):
                     '''
                     Return the PULSEPAIR and the profiles used in the operation
                     Affected :  self.__profileIndex
                     '''
                     #----------------- Remove DC-----------------------------------
                     if self.removeDC==True:
                         mean    = numpy.mean(self.__buffer,1)
                         tmp     = mean.reshape(self.__nch,1,self.__nHeis)
                         dc= numpy.tile(tmp,[1,self.__nProf,1])
                         self.__buffer = self.__buffer -  dc
                     #------------------Calculo de Potencia ------------------------
                     pair0       = self.__buffer*numpy.conj(self.__buffer)
                     pair0       = pair0.real
                     lag_0       = numpy.sum(pair0,1)
                     #-----------------Calculo de Cscp------------------------------ New
                     cspc_pair01 = self.__buffer[0]*self.__buffer[1]
                     #------------------Calculo de Ruido x canal--------------------
                     self.noise  = numpy.zeros(self.__nch)
                     for i in range(self.__nch):
                         daux         = numpy.sort(pair0[i,:,:],axis= None)
                         self.noise[i]=hildebrand_sekhon( daux ,self.nCohInt)
                     self.noise       = self.noise.reshape(self.__nch,1)
                     self.noise       = numpy.tile(self.noise,[1,self.__nHeis])
                     noise_buffer     = self.noise.reshape(self.__nch,1,self.__nHeis)
                     noise_buffer     = numpy.tile(noise_buffer,[1,self.__nProf,1])
                     #------------------ Potencia recibida= P , Potencia senal = S , Ruido= N--
                     #------------------   P= S+N  ,P=lag_0/N ---------------------------------
                     #-------------------- Power --------------------------------------------------
                     data_power       = lag_0/(self.n*self.nCohInt)
                     #--------------------CCF------------------------------------------------------
                     data_ccf         =numpy.sum(cspc_pair01,axis=0)/(self.n*self.nCohInt)
                     #------------------  Senal  --------------------------------------------------
                     data_intensity   = pair0 - noise_buffer
                     data_intensity   = numpy.sum(data_intensity,axis=1)*(self.n*self.nCohInt)#*self.nCohInt)
                     #data_intensity   = (lag_0-self.noise*self.n)*(self.n*self.nCohInt)
                     for i in range(self.__nch):
                         for j in range(self.__nHeis):
                             if data_intensity[i][j]  < 0:
                                 data_intensity[i][j] = numpy.min(numpy.absolute(data_intensity[i][j]))
                     #----------------- Calculo de Frecuencia y Velocidad doppler--------
                     pair1            = self.__buffer[:,:-1,:]*numpy.conjugate(self.__buffer[:,1:,:])
                     lag_1            = numpy.sum(pair1,1)
                     data_freq        = (-1/(2.0*math.pi*self.ippSec*self.nCohInt))*numpy.angle(lag_1)
                     data_velocity    = (self.lambda_/2.0)*data_freq
                     #---------------- Potencia promedio estimada de la Senal-----------
                     lag_0            = lag_0/self.n
                     S                = lag_0-self.noise
                     #---------------- Frecuencia Doppler promedio ---------------------
                     lag_1            = lag_1/(self.n-1)
                     R1               = numpy.abs(lag_1)
                     #---------------- Calculo del SNR----------------------------------
                     data_snrPP       = S/self.noise
                     for i in range(self.__nch):
                         for j in range(self.__nHeis):
                             if data_snrPP[i][j]  < 1.e-20:
                                 data_snrPP[i][j] = 1.e-20
                     #----------------- Calculo del ancho espectral ----------------------
                     L                = S/R1
                     L                = numpy.where(L<0,1,L)
                     L                = numpy.log(L)
                     tmp              = numpy.sqrt(numpy.absolute(L))
                     data_specwidth   = (self.lambda_/(2*math.sqrt(2)*math.pi*self.ippSec*self.nCohInt))*tmp*numpy.sign(L)
                     n                = self.__profIndex
                     self.__buffer    = numpy.zeros((self.__nch, self.__nProf,self.__nHeis),  dtype='complex')
                     self.__profIndex = 0
                     return data_power,data_intensity,data_velocity,data_snrPP,data_specwidth,data_ccf,n
                 def pulsePairbyProfiles(self,dataOut,n):
                     self.__dataReady     =  False
                     data_power           =  None
                     data_intensity       =  None
                     data_velocity        =  None
                     data_specwidth       =  None
                     data_snrPP           =  None
                     data_ccf             =  None
                     if dataOut.flagDataAsBlock:
                         self.putDataByBlock(data=dataOut.data,n=n)
                     else:
                         self.putData(data=dataOut.data)
                     if self.__profIndex  == self.n:
                         data_power,data_intensity, data_velocity,data_snrPP,data_specwidth,data_ccf, n   = self.pushData(dataOut=dataOut)
                         self.__dataReady                   = True
                     return data_power, data_intensity, data_velocity, data_snrPP,data_specwidth,data_ccf
                 def pulsePairOp(self, dataOut, n, datatime= None):
                     if self.__initime == None:
                         self.__initime = datatime
                     data_power, data_intensity, data_velocity, data_snrPP,data_specwidth,data_ccf = self.pulsePairbyProfiles(dataOut,n)
                     self.__lastdatatime           = datatime
                     if data_power is None:
                         return None, None, None,None,None,None,None
                     avgdatatime    = self.__initime
                     deltatime      = datatime - self.__lastdatatime
                     self.__initime = datatime
                     return data_power, data_intensity, data_velocity, data_snrPP,data_specwidth,data_ccf, avgdatatime
                 def run(self, dataOut,n = None,removeDC= False, overlapping= False,**kwargs):
-                    #print("hey")
-                    #print(dataOut.data.shape)
-                    #exit(1)
                     if dataOut.flagDataAsBlock:
-                        n = dataOut.nProfileBlocks
+                        n = dataOut.nProfiles
-                    #print(self.__profIndex)
                     if not self.isConfig:
                         self.setup(dataOut = dataOut, n    = n , removeDC=removeDC , **kwargs)
                         self.isConfig   = True
                     data_power, data_intensity, data_velocity,data_snrPP,data_specwidth,data_ccf, avgdatatime = self.pulsePairOp(dataOut, n, dataOut.utctime)
                     dataOut.flagNoData                         = True
                     if self.__dataReady:
                         ###print("READY ----------------------------------")
                         dataOut.nCohInt        *= self.n
                         dataOut.dataPP_POW      = data_intensity # S
                         dataOut.dataPP_POWER    = data_power     # P valor que corresponde a POTENCIA MOMENTO
                         dataOut.dataPP_DOP      = data_velocity
                         dataOut.dataPP_SNR      = data_snrPP
                         dataOut.dataPP_WIDTH    = data_specwidth
                         dataOut.dataPP_CCF      = data_ccf
                         dataOut.PRFbyAngle      = self.n         #numero de PRF*cada angulo rotado que equivale a un tiempo.
                         dataOut.nProfiles       = int(dataOut.nProfiles/n)
                         dataOut.utctime         = avgdatatime
                         dataOut.flagNoData      = False
                     return dataOut
             # import collections
             # from scipy.stats import mode
             #
             # class Synchronize(Operation):
             #
             #     isConfig = False
             #     __profIndex = 0
             #
             #     def __init__(self, **kwargs):
             #
             #         Operation.__init__(self, **kwargs)
             # #         self.isConfig = False
             #         self.__powBuffer = None
             #         self.__startIndex = 0
             #         self.__pulseFound = False
             #
             #     def __findTxPulse(self, dataOut, channel=0, pulse_with = None):
             #
             #         #Read data
             #
             #         powerdB = dataOut.getPower(channel = channel)
             #         noisedB = dataOut.getNoise(channel = channel)[0]
             #
             #         self.__powBuffer.extend(powerdB.flatten())
             #
             #         dataArray = numpy.array(self.__powBuffer)
             #
             #         filteredPower = numpy.correlate(dataArray, dataArray[0:self.__nSamples], "same")
             #
             #         maxValue = numpy.nanmax(filteredPower)
             #
             #         if maxValue < noisedB + 10:
             #             #No se encuentra ningun pulso de transmision
             #             return None
             #
             #         maxValuesIndex = numpy.where(filteredPower > maxValue - 0.1*abs(maxValue))[0]
             #
             #         if len(maxValuesIndex) < 2:
             #             #Solo se encontro un solo pulso de transmision de un baudio, esperando por el siguiente TX
             #             return None
             #
             #         phasedMaxValuesIndex = maxValuesIndex - self.__nSamples
             #
             #         #Seleccionar solo valores con un espaciamiento de nSamples
             #         pulseIndex = numpy.intersect1d(maxValuesIndex, phasedMaxValuesIndex)
             #
             #         if len(pulseIndex) < 2:
             #             #Solo se encontro un pulso de transmision con ancho mayor a 1
             #             return None
             #
             #         spacing = pulseIndex[1:] - pulseIndex[:-1]
             #
             #         #remover senales que se distancien menos de 10 unidades o muestras
             #         #(No deberian existir IPP menor a 10 unidades)
             #
             #         realIndex = numpy.where(spacing > 10 )[0]
             #
             #         if len(realIndex) < 2:
             #             #Solo se encontro un pulso de transmision con ancho mayor a 1
             #             return None
             #
             #         #Eliminar pulsos anchos (deja solo la diferencia entre IPPs)
             #         realPulseIndex = pulseIndex[realIndex]
             #
             #         period = mode(realPulseIndex[1:] - realPulseIndex[:-1])[0][0]
             #
             #         print "IPP = %d samples" %period
             #
             #         self.__newNSamples = dataOut.nHeights #int(period)
             #         self.__startIndex = int(realPulseIndex[0])
             #
             #         return 1
             #
             #
             #     def setup(self, nSamples, nChannels, buffer_size = 4):
             #
             #         self.__powBuffer = collections.deque(numpy.zeros( buffer_size*nSamples,dtype=numpy.float),
             #                                           maxlen = buffer_size*nSamples)
             #
             #         bufferList = []
             #
             #         for i in range(nChannels):
             #             bufferByChannel = collections.deque(numpy.zeros( buffer_size*nSamples, dtype=numpy.complex) +  numpy.NAN,
             #                                           maxlen = buffer_size*nSamples)
             #
             #             bufferList.append(bufferByChannel)
             #
             #         self.__nSamples = nSamples
             #         self.__nChannels = nChannels
             #         self.__bufferList = bufferList
             #
             #     def run(self, dataOut, channel = 0):
             #
             #         if not self.isConfig:
             #             nSamples = dataOut.nHeights
             #             nChannels = dataOut.nChannels
             #             self.setup(nSamples, nChannels)
             #             self.isConfig = True
             #
             #         #Append new data to internal buffer
             #         for thisChannel in range(self.__nChannels):
             #             bufferByChannel = self.__bufferList[thisChannel]
             #             bufferByChannel.extend(dataOut.data[thisChannel])
             #
             #         if self.__pulseFound:
             #             self.__startIndex -= self.__nSamples
             #
             #         #Finding Tx Pulse
             #         if not self.__pulseFound:
             #             indexFound = self.__findTxPulse(dataOut, channel)
             #
             #             if indexFound == None:
             #                 dataOut.flagNoData = True
             #                 return
             #
             #             self.__arrayBuffer = numpy.zeros((self.__nChannels, self.__newNSamples), dtype = numpy.complex)
             #             self.__pulseFound = True
             #             self.__startIndex = indexFound
             #
             #         #If pulse was found ...
             #         for thisChannel in range(self.__nChannels):
             #             bufferByChannel = self.__bufferList[thisChannel]
             #             #print self.__startIndex
             #             x = numpy.array(bufferByChannel)
             #             self.__arrayBuffer[thisChannel] = x[self.__startIndex:self.__startIndex+self.__newNSamples]
             #
             #         deltaHeight = dataOut.heightList[1] - dataOut.heightList[0]
             #         dataOut.heightList = numpy.arange(self.__newNSamples)*deltaHeight
             # #             dataOut.ippSeconds = (self.__newNSamples / deltaHeight)/1e6
             #
             #         dataOut.data = self.__arrayBuffer
             #
             #         self.__startIndex += self.__newNSamples
             #
             #         return

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