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'''
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'''
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$Author: dsuarez $
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$Author: dsuarez $
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$Id: Processor.py 1 2012-11-12 18:56:07Z dsuarez $
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$Id: Processor.py 1 2012-11-12 18:56:07Z dsuarez $
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'''
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'''
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import os
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import os
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import numpy
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import numpy
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import datetime
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import datetime
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import time
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import time
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import math
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import math
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from jrodata import *
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from jrodata import *
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from jrodataIO import *
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from jrodataIO import *
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from jroplot import *
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from jroplot import *
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try:
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try:
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import cfunctions
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import cfunctions
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except:
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except:
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pass
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pass
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class ProcessingUnit:
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class ProcessingUnit:
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"""
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"""
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Esta es la clase base para el procesamiento de datos.
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Esta es la clase base para el procesamiento de datos.
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Contiene el metodo "call" para llamar operaciones. Las operaciones pueden ser:
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Contiene el metodo "call" para llamar operaciones. Las operaciones pueden ser:
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- Metodos internos (callMethod)
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- Metodos internos (callMethod)
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- Objetos del tipo Operation (callObject). Antes de ser llamados, estos objetos
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- Objetos del tipo Operation (callObject). Antes de ser llamados, estos objetos
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tienen que ser agreagados con el metodo "add".
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tienen que ser agreagados con el metodo "add".
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"""
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"""
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# objeto de datos de entrada (Voltage, Spectra o Correlation)
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# objeto de datos de entrada (Voltage, Spectra o Correlation)
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dataIn = None
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dataIn = None
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# objeto de datos de entrada (Voltage, Spectra o Correlation)
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# objeto de datos de entrada (Voltage, Spectra o Correlation)
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dataOut = None
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dataOut = None
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objectDict = None
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objectDict = None
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def __init__(self):
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def __init__(self):
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self.objectDict = {}
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self.objectDict = {}
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def init(self):
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def init(self):
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raise ValueError, "Not implemented"
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raise ValueError, "Not implemented"
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def addOperation(self, object, objId):
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def addOperation(self, object, objId):
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"""
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"""
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Agrega el objeto "object" a la lista de objetos "self.objectList" y retorna el
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Agrega el objeto "object" a la lista de objetos "self.objectList" y retorna el
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identificador asociado a este objeto.
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identificador asociado a este objeto.
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Input:
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Input:
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object : objeto de la clase "Operation"
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object : objeto de la clase "Operation"
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Return:
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Return:
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objId : identificador del objeto, necesario para ejecutar la operacion
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objId : identificador del objeto, necesario para ejecutar la operacion
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"""
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"""
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self.objectDict[objId] = object
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self.objectDict[objId] = object
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return objId
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return objId
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def operation(self, **kwargs):
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def operation(self, **kwargs):
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"""
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"""
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Operacion directa sobre la data (dataOut.data). Es necesario actualizar los valores de los
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Operacion directa sobre la data (dataOut.data). Es necesario actualizar los valores de los
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atributos del objeto dataOut
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atributos del objeto dataOut
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Input:
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Input:
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**kwargs : Diccionario de argumentos de la funcion a ejecutar
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**kwargs : Diccionario de argumentos de la funcion a ejecutar
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"""
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"""
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raise ValueError, "ImplementedError"
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raise ValueError, "ImplementedError"
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def callMethod(self, name, **kwargs):
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def callMethod(self, name, **kwargs):
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"""
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"""
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Ejecuta el metodo con el nombre "name" y con argumentos **kwargs de la propia clase.
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Ejecuta el metodo con el nombre "name" y con argumentos **kwargs de la propia clase.
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Input:
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Input:
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name : nombre del metodo a ejecutar
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name : nombre del metodo a ejecutar
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**kwargs : diccionario con los nombres y valores de la funcion a ejecutar.
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**kwargs : diccionario con los nombres y valores de la funcion a ejecutar.
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"""
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"""
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if name != 'run':
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if name != 'run':
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if name == 'init' and self.dataIn.isEmpty():
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if name == 'init' and self.dataIn.isEmpty():
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self.dataOut.flagNoData = True
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self.dataOut.flagNoData = True
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return False
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return False
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if name != 'init' and self.dataOut.isEmpty():
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if name != 'init' and self.dataOut.isEmpty():
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return False
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return False
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methodToCall = getattr(self, name)
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methodToCall = getattr(self, name)
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methodToCall(**kwargs)
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methodToCall(**kwargs)
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if name != 'run':
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if name != 'run':
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return True
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return True
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if self.dataOut.isEmpty():
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if self.dataOut.isEmpty():
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return False
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return False
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return True
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return True
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def callObject(self, objId, **kwargs):
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def callObject(self, objId, **kwargs):
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"""
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"""
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Ejecuta la operacion asociada al identificador del objeto "objId"
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Ejecuta la operacion asociada al identificador del objeto "objId"
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Input:
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Input:
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objId : identificador del objeto a ejecutar
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objId : identificador del objeto a ejecutar
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**kwargs : diccionario con los nombres y valores de la funcion a ejecutar.
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**kwargs : diccionario con los nombres y valores de la funcion a ejecutar.
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Return:
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Return:
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None
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None
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"""
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"""
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if self.dataOut.isEmpty():
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if self.dataOut.isEmpty():
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return False
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return False
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object = self.objectDict[objId]
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object = self.objectDict[objId]
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object.run(self.dataOut, **kwargs)
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object.run(self.dataOut, **kwargs)
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return True
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return True
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def call(self, operationConf, **kwargs):
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def call(self, operationConf, **kwargs):
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"""
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"""
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Return True si ejecuta la operacion "operationConf.name" con los
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Return True si ejecuta la operacion "operationConf.name" con los
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argumentos "**kwargs". False si la operacion no se ha ejecutado.
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argumentos "**kwargs". False si la operacion no se ha ejecutado.
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La operacion puede ser de dos tipos:
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La operacion puede ser de dos tipos:
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1. Un metodo propio de esta clase:
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1. Un metodo propio de esta clase:
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operation.type = "self"
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operation.type = "self"
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2. El metodo "run" de un objeto del tipo Operation o de un derivado de ella:
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2. El metodo "run" de un objeto del tipo Operation o de un derivado de ella:
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operation.type = "other".
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operation.type = "other".
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Este objeto de tipo Operation debe de haber sido agregado antes con el metodo:
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Este objeto de tipo Operation debe de haber sido agregado antes con el metodo:
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"addOperation" e identificado con el operation.id
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"addOperation" e identificado con el operation.id
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con el id de la operacion.
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con el id de la operacion.
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Input:
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Input:
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Operation : Objeto del tipo operacion con los atributos: name, type y id.
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Operation : Objeto del tipo operacion con los atributos: name, type y id.
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"""
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"""
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if operationConf.type == 'self':
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if operationConf.type == 'self':
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sts = self.callMethod(operationConf.name, **kwargs)
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sts = self.callMethod(operationConf.name, **kwargs)
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if operationConf.type == 'other':
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if operationConf.type == 'other':
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sts = self.callObject(operationConf.id, **kwargs)
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sts = self.callObject(operationConf.id, **kwargs)
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return sts
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return sts
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def setInput(self, dataIn):
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def setInput(self, dataIn):
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self.dataIn = dataIn
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self.dataIn = dataIn
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def getOutput(self):
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def getOutput(self):
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return self.dataOut
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return self.dataOut
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class Operation():
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class Operation():
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"""
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"""
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Clase base para definir las operaciones adicionales que se pueden agregar a la clase ProcessingUnit
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Clase base para definir las operaciones adicionales que se pueden agregar a la clase ProcessingUnit
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y necesiten acumular informacion previa de los datos a procesar. De preferencia usar un buffer de
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y necesiten acumular informacion previa de los datos a procesar. De preferencia usar un buffer de
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acumulacion dentro de esta clase
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acumulacion dentro de esta clase
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Ejemplo: Integraciones coherentes, necesita la informacion previa de los n perfiles anteriores (bufffer)
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Ejemplo: Integraciones coherentes, necesita la informacion previa de los n perfiles anteriores (bufffer)
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"""
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"""
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__buffer = None
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__buffer = None
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__isConfig = False
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__isConfig = False
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def __init__(self):
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def __init__(self):
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pass
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pass
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def run(self, dataIn, **kwargs):
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def run(self, dataIn, **kwargs):
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"""
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"""
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Realiza las operaciones necesarias sobre la dataIn.data y actualiza los atributos del objeto dataIn.
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Realiza las operaciones necesarias sobre la dataIn.data y actualiza los atributos del objeto dataIn.
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Input:
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Input:
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dataIn : objeto del tipo JROData
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dataIn : objeto del tipo JROData
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205
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205
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206
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Return:
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206
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Return:
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207
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207
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208
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None
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208
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None
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209
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209
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210
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Affected:
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210
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Affected:
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211
|
__buffer : buffer de recepcion de datos.
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211
|
__buffer : buffer de recepcion de datos.
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212
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212
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213
|
"""
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213
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"""
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214
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214
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215
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raise ValueError, "ImplementedError"
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215
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raise ValueError, "ImplementedError"
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216
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216
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217
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class VoltageProc(ProcessingUnit):
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217
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class VoltageProc(ProcessingUnit):
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218
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218
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219
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219
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220
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def __init__(self):
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220
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def __init__(self):
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221
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221
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222
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self.objectDict = {}
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222
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self.objectDict = {}
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223
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self.dataOut = Voltage()
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223
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self.dataOut = Voltage()
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224
|
self.flip = 1
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224
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self.flip = 1
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225
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225
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226
|
def __updateObjFromAmisrInput(self):
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226
|
def __updateObjFromAmisrInput(self):
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227
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227
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228
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self.dataOut.timeZone = self.dataIn.timeZone
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228
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self.dataOut.timeZone = self.dataIn.timeZone
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229
|
self.dataOut.dstFlag = self.dataIn.dstFlag
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229
|
self.dataOut.dstFlag = self.dataIn.dstFlag
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230
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self.dataOut.errorCount = self.dataIn.errorCount
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230
|
self.dataOut.errorCount = self.dataIn.errorCount
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231
|
self.dataOut.useLocalTime = self.dataIn.useLocalTime
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231
|
self.dataOut.useLocalTime = self.dataIn.useLocalTime
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232
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232
|
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233
|
self.dataOut.flagNoData = self.dataIn.flagNoData
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233
|
self.dataOut.flagNoData = self.dataIn.flagNoData
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234
|
self.dataOut.data = self.dataIn.data
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234
|
self.dataOut.data = self.dataIn.data
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235
|
self.dataOut.utctime = self.dataIn.utctime
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235
|
self.dataOut.utctime = self.dataIn.utctime
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|
236
|
self.dataOut.channelList = self.dataIn.channelList
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236
|
self.dataOut.channelList = self.dataIn.channelList
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237
|
self.dataOut.timeInterval = self.dataIn.timeInterval
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237
|
self.dataOut.timeInterval = self.dataIn.timeInterval
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238
|
self.dataOut.heightList = self.dataIn.heightList
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238
|
self.dataOut.heightList = self.dataIn.heightList
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|
239
|
self.dataOut.nProfiles = self.dataIn.nProfiles
|
|
239
|
self.dataOut.nProfiles = self.dataIn.nProfiles
|
|
|
240
|
|
|
240
|
|
|
|
241
|
self.dataOut.nCohInt = self.dataIn.nCohInt
|
|
241
|
self.dataOut.nCohInt = self.dataIn.nCohInt
|
|
|
242
|
self.dataOut.ippSeconds = self.dataIn.ippSeconds
|
|
242
|
self.dataOut.ippSeconds = self.dataIn.ippSeconds
|
|
|
243
|
self.dataOut.frequency = self.dataIn.frequency
|
|
243
|
self.dataOut.frequency = self.dataIn.frequency
|
|
|
244
|
|
|
244
|
|
|
|
245
|
pass
|
|
245
|
pass
|
|
|
246
|
|
|
246
|
|
|
|
247
|
def init(self):
|
|
247
|
def init(self):
|
|
|
248
|
|
|
248
|
|
|
|
249
|
|
|
249
|
|
|
|
250
|
if self.dataIn.type == 'AMISR':
|
|
250
|
if self.dataIn.type == 'AMISR':
|
|
|
251
|
self.__updateObjFromAmisrInput()
|
|
251
|
self.__updateObjFromAmisrInput()
|
|
|
252
|
|
|
252
|
|
|
|
253
|
if self.dataIn.type == 'Voltage':
|
|
253
|
if self.dataIn.type == 'Voltage':
|
|
|
254
|
self.dataOut.copy(self.dataIn)
|
|
254
|
self.dataOut.copy(self.dataIn)
|
|
|
255
|
# No necesita copiar en cada init() los atributos de dataIn
|
|
255
|
# No necesita copiar en cada init() los atributos de dataIn
|
|
|
256
|
# la copia deberia hacerse por cada nuevo bloque de datos
|
|
256
|
# la copia deberia hacerse por cada nuevo bloque de datos
|
|
|
257
|
|
|
257
|
|
|
|
258
|
def selectChannels(self, channelList):
|
|
258
|
def selectChannels(self, channelList):
|
|
|
259
|
|
|
259
|
|
|
|
260
|
channelIndexList = []
|
|
260
|
channelIndexList = []
|
|
|
261
|
|
|
261
|
|
|
|
262
|
for channel in channelList:
|
|
262
|
for channel in channelList:
|
|
|
263
|
index = self.dataOut.channelList.index(channel)
|
|
263
|
index = self.dataOut.channelList.index(channel)
|
|
|
264
|
channelIndexList.append(index)
|
|
264
|
channelIndexList.append(index)
|
|
|
265
|
|
|
265
|
|
|
|
266
|
self.selectChannelsByIndex(channelIndexList)
|
|
266
|
self.selectChannelsByIndex(channelIndexList)
|
|
|
267
|
|
|
267
|
|
|
|
268
|
def selectChannelsByIndex(self, channelIndexList):
|
|
268
|
def selectChannelsByIndex(self, channelIndexList):
|
|
|
269
|
"""
|
|
269
|
"""
|
|
|
270
|
Selecciona un bloque de datos en base a canales segun el channelIndexList
|
|
270
|
Selecciona un bloque de datos en base a canales segun el channelIndexList
|
|
|
271
|
|
|
271
|
|
|
|
272
|
Input:
|
|
272
|
Input:
|
|
|
273
|
channelIndexList : lista sencilla de canales a seleccionar por ej. [2,3,7]
|
|
273
|
channelIndexList : lista sencilla de canales a seleccionar por ej. [2,3,7]
|
|
|
274
|
|
|
274
|
|
|
|
275
|
Affected:
|
|
275
|
Affected:
|
|
|
276
|
self.dataOut.data
|
|
276
|
self.dataOut.data
|
|
|
277
|
self.dataOut.channelIndexList
|
|
277
|
self.dataOut.channelIndexList
|
|
|
278
|
self.dataOut.nChannels
|
|
278
|
self.dataOut.nChannels
|
|
|
279
|
self.dataOut.m_ProcessingHeader.totalSpectra
|
|
279
|
self.dataOut.m_ProcessingHeader.totalSpectra
|
|
|
280
|
self.dataOut.systemHeaderObj.numChannels
|
|
280
|
self.dataOut.systemHeaderObj.numChannels
|
|
|
281
|
self.dataOut.m_ProcessingHeader.blockSize
|
|
281
|
self.dataOut.m_ProcessingHeader.blockSize
|
|
|
282
|
|
|
282
|
|
|
|
283
|
Return:
|
|
283
|
Return:
|
|
|
284
|
None
|
|
284
|
None
|
|
|
285
|
"""
|
|
285
|
"""
|
|
|
286
|
|
|
286
|
|
|
|
287
|
for channelIndex in channelIndexList:
|
|
287
|
for channelIndex in channelIndexList:
|
|
|
288
|
if channelIndex not in self.dataOut.channelIndexList:
|
|
288
|
if channelIndex not in self.dataOut.channelIndexList:
|
|
|
289
|
print channelIndexList
|
|
289
|
print channelIndexList
|
|
|
290
|
raise ValueError, "The value %d in channelIndexList is not valid" %channelIndex
|
|
290
|
raise ValueError, "The value %d in channelIndexList is not valid" %channelIndex
|
|
|
291
|
|
|
291
|
|
|
|
292
|
nChannels = len(channelIndexList)
|
|
292
|
nChannels = len(channelIndexList)
|
|
|
293
|
|
|
293
|
|
|
|
294
|
data = self.dataOut.data[channelIndexList,:]
|
|
294
|
data = self.dataOut.data[channelIndexList,:]
|
|
|
295
|
|
|
295
|
|
|
|
296
|
self.dataOut.data = data
|
|
296
|
self.dataOut.data = data
|
|
|
297
|
self.dataOut.channelList = [self.dataOut.channelList[i] for i in channelIndexList]
|
|
297
|
self.dataOut.channelList = [self.dataOut.channelList[i] for i in channelIndexList]
|
|
|
298
|
# self.dataOut.nChannels = nChannels
|
|
298
|
# self.dataOut.nChannels = nChannels
|
|
|
299
|
|
|
299
|
|
|
|
300
|
return 1
|
|
300
|
return 1
|
|
|
301
|
|
|
301
|
|
|
|
302
|
def selectHeights(self, minHei=None, maxHei=None):
|
|
302
|
def selectHeights(self, minHei=None, maxHei=None):
|
|
|
303
|
"""
|
|
303
|
"""
|
|
|
304
|
Selecciona un bloque de datos en base a un grupo de valores de alturas segun el rango
|
|
304
|
Selecciona un bloque de datos en base a un grupo de valores de alturas segun el rango
|
|
|
305
|
minHei <= height <= maxHei
|
|
305
|
minHei <= height <= maxHei
|
|
|
306
|
|
|
306
|
|
|
|
307
|
Input:
|
|
307
|
Input:
|
|
|
308
|
minHei : valor minimo de altura a considerar
|
|
308
|
minHei : valor minimo de altura a considerar
|
|
|
309
|
maxHei : valor maximo de altura a considerar
|
|
309
|
maxHei : valor maximo de altura a considerar
|
|
|
310
|
|
|
310
|
|
|
|
311
|
Affected:
|
|
311
|
Affected:
|
|
|
312
|
Indirectamente son cambiados varios valores a travez del metodo selectHeightsByIndex
|
|
312
|
Indirectamente son cambiados varios valores a travez del metodo selectHeightsByIndex
|
|
|
313
|
|
|
313
|
|
|
|
314
|
Return:
|
|
314
|
Return:
|
|
|
315
|
1 si el metodo se ejecuto con exito caso contrario devuelve 0
|
|
315
|
1 si el metodo se ejecuto con exito caso contrario devuelve 0
|
|
|
316
|
"""
|
|
316
|
"""
|
|
|
317
|
|
|
317
|
|
|
|
318
|
if minHei == None:
|
|
318
|
if minHei == None:
|
|
|
319
|
minHei = self.dataOut.heightList[0]
|
|
319
|
minHei = self.dataOut.heightList[0]
|
|
|
320
|
|
|
320
|
|
|
|
321
|
if maxHei == None:
|
|
321
|
if maxHei == None:
|
|
|
322
|
maxHei = self.dataOut.heightList[-1]
|
|
322
|
maxHei = self.dataOut.heightList[-1]
|
|
|
323
|
|
|
323
|
|
|
|
324
|
if (minHei < self.dataOut.heightList[0]) or (minHei > maxHei):
|
|
324
|
if (minHei < self.dataOut.heightList[0]) or (minHei > maxHei):
|
|
|
325
|
raise ValueError, "some value in (%d,%d) is not valid" % (minHei, maxHei)
|
|
325
|
raise ValueError, "some value in (%d,%d) is not valid" % (minHei, maxHei)
|
|
|
326
|
|
|
326
|
|
|
|
327
|
|
|
327
|
|
|
|
328
|
if (maxHei > self.dataOut.heightList[-1]):
|
|
328
|
if (maxHei > self.dataOut.heightList[-1]):
|
|
|
329
|
maxHei = self.dataOut.heightList[-1]
|
|
329
|
maxHei = self.dataOut.heightList[-1]
|
|
|
330
|
# raise ValueError, "some value in (%d,%d) is not valid" % (minHei, maxHei)
|
|
330
|
# raise ValueError, "some value in (%d,%d) is not valid" % (minHei, maxHei)
|
|
|
331
|
|
|
331
|
|
|
|
332
|
minIndex = 0
|
|
332
|
minIndex = 0
|
|
|
333
|
maxIndex = 0
|
|
333
|
maxIndex = 0
|
|
|
334
|
heights = self.dataOut.heightList
|
|
334
|
heights = self.dataOut.heightList
|
|
|
335
|
|
|
335
|
|
|
|
336
|
inda = numpy.where(heights >= minHei)
|
|
336
|
inda = numpy.where(heights >= minHei)
|
|
|
337
|
indb = numpy.where(heights <= maxHei)
|
|
337
|
indb = numpy.where(heights <= maxHei)
|
|
|
338
|
|
|
338
|
|
|
|
339
|
try:
|
|
339
|
try:
|
|
|
340
|
minIndex = inda[0][0]
|
|
340
|
minIndex = inda[0][0]
|
|
|
341
|
except:
|
|
341
|
except:
|
|
|
342
|
minIndex = 0
|
|
342
|
minIndex = 0
|
|
|
343
|
|
|
343
|
|
|
|
344
|
try:
|
|
344
|
try:
|
|
|
345
|
maxIndex = indb[0][-1]
|
|
345
|
maxIndex = indb[0][-1]
|
|
|
346
|
except:
|
|
346
|
except:
|
|
|
347
|
maxIndex = len(heights)
|
|
347
|
maxIndex = len(heights)
|
|
|
348
|
|
|
348
|
|
|
|
349
|
self.selectHeightsByIndex(minIndex, maxIndex)
|
|
349
|
self.selectHeightsByIndex(minIndex, maxIndex)
|
|
|
350
|
|
|
350
|
|
|
|
351
|
return 1
|
|
351
|
return 1
|
|
|
352
|
|
|
352
|
|
|
|
353
|
|
|
353
|
|
|
|
354
|
def selectHeightsByIndex(self, minIndex, maxIndex):
|
|
354
|
def selectHeightsByIndex(self, minIndex, maxIndex):
|
|
|
355
|
"""
|
|
355
|
"""
|
|
|
356
|
Selecciona un bloque de datos en base a un grupo indices de alturas segun el rango
|
|
356
|
Selecciona un bloque de datos en base a un grupo indices de alturas segun el rango
|
|
|
357
|
minIndex <= index <= maxIndex
|
|
357
|
minIndex <= index <= maxIndex
|
|
|
358
|
|
|
358
|
|
|
|
359
|
Input:
|
|
359
|
Input:
|
|
|
360
|
minIndex : valor de indice minimo de altura a considerar
|
|
360
|
minIndex : valor de indice minimo de altura a considerar
|
|
|
361
|
maxIndex : valor de indice maximo de altura a considerar
|
|
361
|
maxIndex : valor de indice maximo de altura a considerar
|
|
|
362
|
|
|
362
|
|
|
|
363
|
Affected:
|
|
363
|
Affected:
|
|
|
364
|
self.dataOut.data
|
|
364
|
self.dataOut.data
|
|
|
365
|
self.dataOut.heightList
|
|
365
|
self.dataOut.heightList
|
|
|
366
|
|
|
366
|
|
|
|
367
|
Return:
|
|
367
|
Return:
|
|
|
368
|
1 si el metodo se ejecuto con exito caso contrario devuelve 0
|
|
368
|
1 si el metodo se ejecuto con exito caso contrario devuelve 0
|
|
|
369
|
"""
|
|
369
|
"""
|
|
|
370
|
|
|
370
|
|
|
|
371
|
if (minIndex < 0) or (minIndex > maxIndex):
|
|
371
|
if (minIndex < 0) or (minIndex > maxIndex):
|
|
|
372
|
raise ValueError, "some value in (%d,%d) is not valid" % (minIndex, maxIndex)
|
|
372
|
raise ValueError, "some value in (%d,%d) is not valid" % (minIndex, maxIndex)
|
|
|
373
|
|
|
373
|
|
|
|
374
|
if (maxIndex >= self.dataOut.nHeights):
|
|
374
|
if (maxIndex >= self.dataOut.nHeights):
|
|
|
375
|
maxIndex = self.dataOut.nHeights-1
|
|
375
|
maxIndex = self.dataOut.nHeights-1
|
|
|
376
|
# raise ValueError, "some value in (%d,%d) is not valid" % (minIndex, maxIndex)
|
|
376
|
# raise ValueError, "some value in (%d,%d) is not valid" % (minIndex, maxIndex)
|
|
|
377
|
|
|
377
|
|
|
|
378
|
nHeights = maxIndex - minIndex + 1
|
|
378
|
nHeights = maxIndex - minIndex + 1
|
|
|
379
|
|
|
379
|
|
|
|
380
|
#voltage
|
|
380
|
#voltage
|
|
|
381
|
data = self.dataOut.data[:,minIndex:maxIndex+1]
|
|
381
|
data = self.dataOut.data[:,minIndex:maxIndex+1]
|
|
|
382
|
|
|
382
|
|
|
|
383
|
firstHeight = self.dataOut.heightList[minIndex]
|
|
383
|
firstHeight = self.dataOut.heightList[minIndex]
|
|
|
384
|
|
|
384
|
|
|
|
385
|
self.dataOut.data = data
|
|
385
|
self.dataOut.data = data
|
|
|
386
|
self.dataOut.heightList = self.dataOut.heightList[minIndex:maxIndex+1]
|
|
386
|
self.dataOut.heightList = self.dataOut.heightList[minIndex:maxIndex+1]
|
|
|
387
|
|
|
387
|
|
|
|
388
|
return 1
|
|
388
|
return 1
|
|
|
389
|
|
|
389
|
|
|
|
390
|
|
|
390
|
|
|
|
391
|
def filterByHeights(self, window):
|
|
391
|
def filterByHeights(self, window):
|
|
|
392
|
deltaHeight = self.dataOut.heightList[1] - self.dataOut.heightList[0]
|
|
392
|
deltaHeight = self.dataOut.heightList[1] - self.dataOut.heightList[0]
|
|
|
393
|
|
|
393
|
|
|
|
394
|
if window == None:
|
|
394
|
if window == None:
|
|
|
395
|
window = (self.dataOut.radarControllerHeaderObj.txA/self.dataOut.radarControllerHeaderObj.nBaud) / deltaHeight
|
|
395
|
window = (self.dataOut.radarControllerHeaderObj.txA/self.dataOut.radarControllerHeaderObj.nBaud) / deltaHeight
|
|
|
396
|
|
|
396
|
|
|
|
397
|
newdelta = deltaHeight * window
|
|
397
|
newdelta = deltaHeight * window
|
|
|
398
|
r = self.dataOut.data.shape[1] % window
|
|
398
|
r = self.dataOut.data.shape[1] % window
|
|
|
399
|
buffer = self.dataOut.data[:,0:self.dataOut.data.shape[1]-r]
|
|
399
|
buffer = self.dataOut.data[:,0:self.dataOut.data.shape[1]-r]
|
|
|
400
|
buffer = buffer.reshape(self.dataOut.data.shape[0],self.dataOut.data.shape[1]/window,window)
|
|
400
|
buffer = buffer.reshape(self.dataOut.data.shape[0],self.dataOut.data.shape[1]/window,window)
|
|
|
401
|
buffer = numpy.sum(buffer,2)
|
|
401
|
buffer = numpy.sum(buffer,2)
|
|
|
402
|
self.dataOut.data = buffer
|
|
402
|
self.dataOut.data = buffer
|
|
|
403
|
self.dataOut.heightList = numpy.arange(self.dataOut.heightList[0],newdelta*(self.dataOut.nHeights-r)/window,newdelta)
|
|
403
|
self.dataOut.heightList = numpy.arange(self.dataOut.heightList[0],newdelta*(self.dataOut.nHeights-r)/window,newdelta)
|
|
|
404
|
self.dataOut.windowOfFilter = window
|
|
404
|
self.dataOut.windowOfFilter = window
|
|
|
405
|
|
|
405
|
|
|
|
406
|
def deFlip(self):
|
|
406
|
def deFlip(self):
|
|
|
407
|
self.dataOut.data *= self.flip
|
|
407
|
self.dataOut.data *= self.flip
|
|
|
408
|
self.flip *= -1.
|
|
408
|
self.flip *= -1.
|
|
|
409
|
|
|
409
|
|
|
|
410
|
def setRadarFrequency(self, frequency=None):
|
|
410
|
def setRadarFrequency(self, frequency=None):
|
|
|
411
|
if frequency != None:
|
|
411
|
if frequency != None:
|
|
|
412
|
self.dataOut.frequency = frequency
|
|
412
|
self.dataOut.frequency = frequency
|
|
|
413
|
|
|
413
|
|
|
|
414
|
return 1
|
|
414
|
return 1
|
|
|
415
|
|
|
415
|
|
|
|
416
|
class CohInt(Operation):
|
|
416
|
class CohInt(Operation):
|
|
|
417
|
|
|
417
|
|
|
|
418
|
__isConfig = False
|
|
418
|
__isConfig = False
|
|
|
419
|
|
|
419
|
|
|
|
420
|
__profIndex = 0
|
|
420
|
__profIndex = 0
|
|
|
421
|
__withOverapping = False
|
|
421
|
__withOverapping = False
|
|
|
422
|
|
|
422
|
|
|
|
423
|
__byTime = False
|
|
423
|
__byTime = False
|
|
|
424
|
__initime = None
|
|
424
|
__initime = None
|
|
|
425
|
__lastdatatime = None
|
|
425
|
__lastdatatime = None
|
|
|
426
|
__integrationtime = None
|
|
426
|
__integrationtime = None
|
|
|
427
|
|
|
427
|
|
|
|
428
|
__buffer = None
|
|
428
|
__buffer = None
|
|
|
429
|
|
|
429
|
|
|
|
430
|
__dataReady = False
|
|
430
|
__dataReady = False
|
|
|
431
|
|
|
431
|
|
|
|
432
|
n = None
|
|
432
|
n = None
|
|
|
433
|
|
|
433
|
|
|
|
434
|
|
|
434
|
|
|
|
435
|
def __init__(self):
|
|
435
|
def __init__(self):
|
|
|
436
|
|
|
436
|
|
|
|
437
|
self.__isConfig = False
|
|
437
|
self.__isConfig = False
|
|
|
438
|
|
|
438
|
|
|
|
439
|
def setup(self, n=None, timeInterval=None, overlapping=False):
|
|
439
|
def setup(self, n=None, timeInterval=None, overlapping=False):
|
|
|
440
|
"""
|
|
440
|
"""
|
|
|
441
|
Set the parameters of the integration class.
|
|
441
|
Set the parameters of the integration class.
|
|
|
442
|
|
|
442
|
|
|
|
443
|
Inputs:
|
|
443
|
Inputs:
|
|
|
444
|
|
|
444
|
|
|
|
445
|
n : Number of coherent integrations
|
|
445
|
n : Number of coherent integrations
|
|
|
446
|
timeInterval : Time of integration. If the parameter "n" is selected this one does not work
|
|
446
|
timeInterval : Time of integration. If the parameter "n" is selected this one does not work
|
|
|
447
|
overlapping :
|
|
447
|
overlapping :
|
|
|
448
|
|
|
448
|
|
|
|
449
|
"""
|
|
449
|
"""
|
|
|
450
|
|
|
450
|
|
|
|
451
|
self.__initime = None
|
|
451
|
self.__initime = None
|
|
|
452
|
self.__lastdatatime = 0
|
|
452
|
self.__lastdatatime = 0
|
|
|
453
|
self.__buffer = None
|
|
453
|
self.__buffer = None
|
|
|
454
|
self.__dataReady = False
|
|
454
|
self.__dataReady = False
|
|
|
455
|
|
|
455
|
|
|
|
456
|
|
|
456
|
|
|
|
457
|
if n == None and timeInterval == None:
|
|
457
|
if n == None and timeInterval == None:
|
|
|
458
|
raise ValueError, "n or timeInterval should be specified ..."
|
|
458
|
raise ValueError, "n or timeInterval should be specified ..."
|
|
|
459
|
|
|
459
|
|
|
|
460
|
if n != None:
|
|
460
|
if n != None:
|
|
|
461
|
self.n = n
|
|
461
|
self.n = n
|
|
|
462
|
self.__byTime = False
|
|
462
|
self.__byTime = False
|
|
|
463
|
else:
|
|
463
|
else:
|
|
|
464
|
self.__integrationtime = timeInterval * 60. #if (type(timeInterval)!=integer) -> change this line
|
|
464
|
self.__integrationtime = timeInterval * 60. #if (type(timeInterval)!=integer) -> change this line
|
|
|
465
|
self.n = 9999
|
|
465
|
self.n = 9999
|
|
|
466
|
self.__byTime = True
|
|
466
|
self.__byTime = True
|
|
|
467
|
|
|
467
|
|
|
|
468
|
if overlapping:
|
|
468
|
if overlapping:
|
|
|
469
|
self.__withOverapping = True
|
|
469
|
self.__withOverapping = True
|
|
|
470
|
self.__buffer = None
|
|
470
|
self.__buffer = None
|
|
|
471
|
else:
|
|
471
|
else:
|
|
|
472
|
self.__withOverapping = False
|
|
472
|
self.__withOverapping = False
|
|
|
473
|
self.__buffer = 0
|
|
473
|
self.__buffer = 0
|
|
|
474
|
|
|
474
|
|
|
|
475
|
self.__profIndex = 0
|
|
475
|
self.__profIndex = 0
|
|
|
476
|
|
|
476
|
|
|
|
477
|
def putData(self, data):
|
|
477
|
def putData(self, data):
|
|
|
478
|
|
|
478
|
|
|
|
479
|
"""
|
|
479
|
"""
|
|
|
480
|
Add a profile to the __buffer and increase in one the __profileIndex
|
|
480
|
Add a profile to the __buffer and increase in one the __profileIndex
|
|
|
481
|
|
|
481
|
|
|
|
482
|
"""
|
|
482
|
"""
|
|
|
483
|
|
|
483
|
|
|
|
484
|
if not self.__withOverapping:
|
|
484
|
if not self.__withOverapping:
|
|
|
485
|
self.__buffer += data.copy()
|
|
485
|
self.__buffer += data.copy()
|
|
|
486
|
self.__profIndex += 1
|
|
486
|
self.__profIndex += 1
|
|
|
487
|
return
|
|
487
|
return
|
|
|
488
|
|
|
488
|
|
|
|
489
|
#Overlapping data
|
|
489
|
#Overlapping data
|
|
|
490
|
nChannels, nHeis = data.shape
|
|
490
|
nChannels, nHeis = data.shape
|
|
|
491
|
data = numpy.reshape(data, (1, nChannels, nHeis))
|
|
491
|
data = numpy.reshape(data, (1, nChannels, nHeis))
|
|
|
492
|
|
|
492
|
|
|
|
493
|
#If the buffer is empty then it takes the data value
|
|
493
|
#If the buffer is empty then it takes the data value
|
|
|
494
|
if self.__buffer == None:
|
|
494
|
if self.__buffer == None:
|
|
|
495
|
self.__buffer = data
|
|
495
|
self.__buffer = data
|
|
|
496
|
self.__profIndex += 1
|
|
496
|
self.__profIndex += 1
|
|
|
497
|
return
|
|
497
|
return
|
|
|
498
|
|
|
498
|
|
|
|
499
|
#If the buffer length is lower than n then stakcing the data value
|
|
499
|
#If the buffer length is lower than n then stakcing the data value
|
|
|
500
|
if self.__profIndex < self.n:
|
|
500
|
if self.__profIndex < self.n:
|
|
|
501
|
self.__buffer = numpy.vstack((self.__buffer, data))
|
|
501
|
self.__buffer = numpy.vstack((self.__buffer, data))
|
|
|
502
|
self.__profIndex += 1
|
|
502
|
self.__profIndex += 1
|
|
|
503
|
return
|
|
503
|
return
|
|
|
504
|
|
|
504
|
|
|
|
505
|
#If the buffer length is equal to n then replacing the last buffer value with the data value
|
|
505
|
#If the buffer length is equal to n then replacing the last buffer value with the data value
|
|
|
506
|
self.__buffer = numpy.roll(self.__buffer, -1, axis=0)
|
|
506
|
self.__buffer = numpy.roll(self.__buffer, -1, axis=0)
|
|
|
507
|
self.__buffer[self.n-1] = data
|
|
507
|
self.__buffer[self.n-1] = data
|
|
|
508
|
self.__profIndex = self.n
|
|
508
|
self.__profIndex = self.n
|
|
|
509
|
return
|
|
509
|
return
|
|
|
510
|
|
|
510
|
|
|
|
511
|
|
|
511
|
|
|
|
512
|
def pushData(self):
|
|
512
|
def pushData(self):
|
|
|
513
|
"""
|
|
513
|
"""
|
|
|
514
|
Return the sum of the last profiles and the profiles used in the sum.
|
|
514
|
Return the sum of the last profiles and the profiles used in the sum.
|
|
|
515
|
|
|
515
|
|
|
|
516
|
Affected:
|
|
516
|
Affected:
|
|
|
517
|
|
|
517
|
|
|
|
518
|
self.__profileIndex
|
|
518
|
self.__profileIndex
|
|
|
519
|
|
|
519
|
|
|
|
520
|
"""
|
|
520
|
"""
|
|
|
521
|
|
|
521
|
|
|
|
522
|
if not self.__withOverapping:
|
|
522
|
if not self.__withOverapping:
|
|
|
523
|
data = self.__buffer
|
|
523
|
data = self.__buffer
|
|
|
524
|
n = self.__profIndex
|
|
524
|
n = self.__profIndex
|
|
|
525
|
|
|
525
|
|
|
|
526
|
self.__buffer = 0
|
|
526
|
self.__buffer = 0
|
|
|
527
|
self.__profIndex = 0
|
|
527
|
self.__profIndex = 0
|
|
|
528
|
|
|
528
|
|
|
|
529
|
return data, n
|
|
529
|
return data, n
|
|
|
530
|
|
|
530
|
|
|
|
531
|
#Integration with Overlapping
|
|
531
|
#Integration with Overlapping
|
|
|
532
|
data = numpy.sum(self.__buffer, axis=0)
|
|
532
|
data = numpy.sum(self.__buffer, axis=0)
|
|
|
533
|
n = self.__profIndex
|
|
533
|
n = self.__profIndex
|
|
|
534
|
|
|
534
|
|
|
|
535
|
return data, n
|
|
535
|
return data, n
|
|
|
536
|
|
|
536
|
|
|
|
537
|
def byProfiles(self, data):
|
|
537
|
def byProfiles(self, data):
|
|
|
538
|
|
|
538
|
|
|
|
539
|
self.__dataReady = False
|
|
539
|
self.__dataReady = False
|
|
|
540
|
avgdata = None
|
|
540
|
avgdata = None
|
|
|
541
|
n = None
|
|
541
|
n = None
|
|
|
542
|
|
|
542
|
|
|
|
543
|
self.putData(data)
|
|
543
|
self.putData(data)
|
|
|
544
|
|
|
544
|
|
|
|
545
|
if self.__profIndex == self.n:
|
|
545
|
if self.__profIndex == self.n:
|
|
|
546
|
|
|
546
|
|
|
|
547
|
avgdata, n = self.pushData()
|
|
547
|
avgdata, n = self.pushData()
|
|
|
548
|
self.__dataReady = True
|
|
548
|
self.__dataReady = True
|
|
|
549
|
|
|
549
|
|
|
|
550
|
return avgdata
|
|
550
|
return avgdata
|
|
|
551
|
|
|
551
|
|
|
|
552
|
def byTime(self, data, datatime):
|
|
552
|
def byTime(self, data, datatime):
|
|
|
553
|
|
|
553
|
|
|
|
554
|
self.__dataReady = False
|
|
554
|
self.__dataReady = False
|
|
|
555
|
avgdata = None
|
|
555
|
avgdata = None
|
|
|
556
|
n = None
|
|
556
|
n = None
|
|
|
557
|
|
|
557
|
|
|
|
558
|
self.putData(data)
|
|
558
|
self.putData(data)
|
|
|
559
|
|
|
559
|
|
|
|
560
|
if (datatime - self.__initime) >= self.__integrationtime:
|
|
560
|
if (datatime - self.__initime) >= self.__integrationtime:
|
|
|
561
|
avgdata, n = self.pushData()
|
|
561
|
avgdata, n = self.pushData()
|
|
|
562
|
self.n = n
|
|
562
|
self.n = n
|
|
|
563
|
self.__dataReady = True
|
|
563
|
self.__dataReady = True
|
|
|
564
|
|
|
564
|
|
|
|
565
|
return avgdata
|
|
565
|
return avgdata
|
|
|
566
|
|
|
566
|
|
|
|
567
|
def integrate(self, data, datatime=None):
|
|
567
|
def integrate(self, data, datatime=None):
|
|
|
568
|
|
|
568
|
|
|
|
569
|
if self.__initime == None:
|
|
569
|
if self.__initime == None:
|
|
|
570
|
self.__initime = datatime
|
|
570
|
self.__initime = datatime
|
|
|
571
|
|
|
571
|
|
|
|
572
|
if self.__byTime:
|
|
572
|
if self.__byTime:
|
|
|
573
|
avgdata = self.byTime(data, datatime)
|
|
573
|
avgdata = self.byTime(data, datatime)
|
|
|
574
|
else:
|
|
574
|
else:
|
|
|
575
|
avgdata = self.byProfiles(data)
|
|
575
|
avgdata = self.byProfiles(data)
|
|
|
576
|
|
|
576
|
|
|
|
577
|
|
|
577
|
|
|
|
578
|
self.__lastdatatime = datatime
|
|
578
|
self.__lastdatatime = datatime
|
|
|
579
|
|
|
579
|
|
|
|
580
|
if avgdata == None:
|
|
580
|
if avgdata == None:
|
|
|
581
|
return None, None
|
|
581
|
return None, None
|
|
|
582
|
|
|
582
|
|
|
|
583
|
avgdatatime = self.__initime
|
|
583
|
avgdatatime = self.__initime
|
|
|
584
|
|
|
584
|
|
|
|
585
|
deltatime = datatime -self.__lastdatatime
|
|
585
|
deltatime = datatime -self.__lastdatatime
|
|
|
586
|
|
|
586
|
|
|
|
587
|
if not self.__withOverapping:
|
|
587
|
if not self.__withOverapping:
|
|
|
588
|
self.__initime = datatime
|
|
588
|
self.__initime = datatime
|
|
|
589
|
else:
|
|
589
|
else:
|
|
|
590
|
self.__initime += deltatime
|
|
590
|
self.__initime += deltatime
|
|
|
591
|
|
|
591
|
|
|
|
592
|
return avgdata, avgdatatime
|
|
592
|
return avgdata, avgdatatime
|
|
|
593
|
|
|
593
|
|
|
|
594
|
def run(self, dataOut, **kwargs):
|
|
594
|
def run(self, dataOut, **kwargs):
|
|
|
595
|
|
|
595
|
|
|
|
596
|
if not self.__isConfig:
|
|
596
|
if not self.__isConfig:
|
|
|
597
|
self.setup(**kwargs)
|
|
597
|
self.setup(**kwargs)
|
|
|
598
|
self.__isConfig = True
|
|
598
|
self.__isConfig = True
|
|
|
599
|
|
|
599
|
|
|
|
600
|
avgdata, avgdatatime = self.integrate(dataOut.data, dataOut.utctime)
|
|
600
|
avgdata, avgdatatime = self.integrate(dataOut.data, dataOut.utctime)
|
|
|
601
|
|
|
601
|
|
|
|
602
|
# dataOut.timeInterval *= n
|
|
602
|
# dataOut.timeInterval *= n
|
|
|
603
|
dataOut.flagNoData = True
|
|
603
|
dataOut.flagNoData = True
|
|
|
604
|
|
|
604
|
|
|
|
605
|
if self.__dataReady:
|
|
605
|
if self.__dataReady:
|
|
|
606
|
dataOut.data = avgdata
|
|
606
|
dataOut.data = avgdata
|
|
|
607
|
dataOut.nCohInt *= self.n
|
|
607
|
dataOut.nCohInt *= self.n
|
|
|
608
|
dataOut.utctime = avgdatatime
|
|
608
|
dataOut.utctime = avgdatatime
|
|
|
609
|
dataOut.timeInterval = dataOut.ippSeconds * dataOut.nCohInt
|
|
609
|
dataOut.timeInterval = dataOut.ippSeconds * dataOut.nCohInt
|
|
|
610
|
dataOut.flagNoData = False
|
|
610
|
dataOut.flagNoData = False
|
|
|
611
|
|
|
611
|
|
|
|
612
|
|
|
612
|
|
|
|
613
|
class Decoder(Operation):
|
|
613
|
class Decoder(Operation):
|
|
|
614
|
|
|
614
|
|
|
|
615
|
__isConfig = False
|
|
615
|
__isConfig = False
|
|
|
616
|
__profIndex = 0
|
|
616
|
__profIndex = 0
|
|
|
617
|
|
|
617
|
|
|
|
618
|
code = None
|
|
618
|
code = None
|
|
|
619
|
|
|
619
|
|
|
|
620
|
nCode = None
|
|
620
|
nCode = None
|
|
|
621
|
nBaud = None
|
|
621
|
nBaud = None
|
|
|
622
|
|
|
622
|
|
|
|
623
|
def __init__(self):
|
|
623
|
def __init__(self):
|
|
|
624
|
|
|
624
|
|
|
|
625
|
self.__isConfig = False
|
|
625
|
self.__isConfig = False
|
|
|
626
|
|
|
626
|
|
|
|
627
|
def setup(self, code, shape):
|
|
627
|
def setup(self, code, shape):
|
|
|
628
|
|
|
628
|
|
|
|
629
|
self.__profIndex = 0
|
|
629
|
self.__profIndex = 0
|
|
|
630
|
|
|
630
|
|
|
|
631
|
self.code = code
|
|
631
|
self.code = code
|
|
|
632
|
|
|
632
|
|
|
|
633
|
self.nCode = len(code)
|
|
633
|
self.nCode = len(code)
|
|
|
634
|
self.nBaud = len(code[0])
|
|
634
|
self.nBaud = len(code[0])
|
|
|
635
|
|
|
635
|
|
|
|
636
|
self.__nChannels, self.__nHeis = shape
|
|
636
|
self.__nChannels, self.__nHeis = shape
|
|
|
637
|
|
|
637
|
|
|
|
638
|
__codeBuffer = numpy.zeros((self.nCode, self.__nHeis), dtype=numpy.complex)
|
|
638
|
__codeBuffer = numpy.zeros((self.nCode, self.__nHeis), dtype=numpy.complex)
|
|
|
639
|
|
|
639
|
|
|
|
640
|
__codeBuffer[:,0:self.nBaud] = self.code
|
|
640
|
__codeBuffer[:,0:self.nBaud] = self.code
|
|
|
641
|
|
|
641
|
|
|
|
642
|
self.fft_code = numpy.conj(numpy.fft.fft(__codeBuffer, axis=1))
|
|
642
|
self.fft_code = numpy.conj(numpy.fft.fft(__codeBuffer, axis=1))
|
|
|
643
|
|
|
643
|
|
|
|
644
|
self.ndatadec = self.__nHeis - self.nBaud + 1
|
|
644
|
self.ndatadec = self.__nHeis - self.nBaud + 1
|
|
|
645
|
|
|
645
|
|
|
|
646
|
self.datadecTime = numpy.zeros((self.__nChannels, self.ndatadec), dtype=numpy.complex)
|
|
646
|
self.datadecTime = numpy.zeros((self.__nChannels, self.ndatadec), dtype=numpy.complex)
|
|
|
647
|
|
|
647
|
|
|
|
648
|
def convolutionInFreq(self, data):
|
|
648
|
def convolutionInFreq(self, data):
|
|
|
649
|
|
|
649
|
|
|
|
650
|
fft_code = self.fft_code[self.__profIndex].reshape(1,-1)
|
|
650
|
fft_code = self.fft_code[self.__profIndex].reshape(1,-1)
|
|
|
651
|
|
|
651
|
|
|
|
652
|
fft_data = numpy.fft.fft(data, axis=1)
|
|
652
|
fft_data = numpy.fft.fft(data, axis=1)
|
|
|
653
|
|
|
653
|
|
|
|
654
|
conv = fft_data*fft_code
|
|
654
|
conv = fft_data*fft_code
|
|
|
655
|
|
|
655
|
|
|
|
656
|
data = numpy.fft.ifft(conv,axis=1)
|
|
656
|
data = numpy.fft.ifft(conv,axis=1)
|
|
|
657
|
|
|
657
|
|
|
|
658
|
datadec = data[:,:-self.nBaud+1]
|
|
658
|
datadec = data[:,:-self.nBaud+1]
|
|
|
659
|
|
|
659
|
|
|
|
660
|
return datadec
|
|
660
|
return datadec
|
|
|
661
|
|
|
661
|
|
|
|
662
|
def convolutionInFreqOpt(self, data):
|
|
662
|
def convolutionInFreqOpt(self, data):
|
|
|
663
|
|
|
663
|
|
|
|
664
|
fft_code = self.fft_code[self.__profIndex].reshape(1,-1)
|
|
664
|
fft_code = self.fft_code[self.__profIndex].reshape(1,-1)
|
|
|
665
|
|
|
665
|
|
|
|
666
|
data = cfunctions.decoder(fft_code, data)
|
|
666
|
data = cfunctions.decoder(fft_code, data)
|
|
|
667
|
|
|
667
|
|
|
|
668
|
datadec = data[:,:-self.nBaud+1]
|
|
668
|
datadec = data[:,:-self.nBaud+1]
|
|
|
669
|
|
|
669
|
|
|
|
670
|
return datadec
|
|
670
|
return datadec
|
|
|
671
|
|
|
671
|
|
|
|
672
|
def convolutionInTime(self, data):
|
|
672
|
def convolutionInTime(self, data):
|
|
|
673
|
|
|
673
|
|
|
|
674
|
code = self.code[self.__profIndex]
|
|
674
|
code = self.code[self.__profIndex]
|
|
|
675
|
|
|
675
|
|
|
|
676
|
for i in range(self.__nChannels):
|
|
676
|
for i in range(self.__nChannels):
|
|
|
677
|
self.datadecTime[i,:] = numpy.correlate(data[i,:], code, mode='valid')
|
|
677
|
self.datadecTime[i,:] = numpy.correlate(data[i,:], code, mode='valid')
|
|
|
678
|
|
|
678
|
|
|
|
679
|
return self.datadecTime
|
|
679
|
return self.datadecTime
|
|
|
680
|
|
|
680
|
|
|
|
681
|
def run(self, dataOut, code=None, nCode=None, nBaud=None, mode = 0):
|
|
681
|
def run(self, dataOut, code=None, nCode=None, nBaud=None, mode = 0):
|
|
|
682
|
|
|
682
|
|
|
|
683
|
if code == None:
|
|
683
|
if code == None:
|
|
|
684
|
code = dataOut.code
|
|
684
|
code = dataOut.code
|
|
|
685
|
else:
|
|
685
|
else:
|
|
|
686
|
code = numpy.array(code).reshape(nCode,nBaud)
|
|
686
|
code = numpy.array(code).reshape(nCode,nBaud)
|
|
|
687
|
dataOut.code = code
|
|
687
|
dataOut.code = code
|
|
|
688
|
dataOut.nCode = nCode
|
|
688
|
dataOut.nCode = nCode
|
|
|
689
|
dataOut.nBaud = nBaud
|
|
689
|
dataOut.nBaud = nBaud
|
|
|
690
|
dataOut.radarControllerHeaderObj.code = code
|
|
690
|
dataOut.radarControllerHeaderObj.code = code
|
|
|
691
|
dataOut.radarControllerHeaderObj.nCode = nCode
|
|
691
|
dataOut.radarControllerHeaderObj.nCode = nCode
|
|
|
692
|
dataOut.radarControllerHeaderObj.nBaud = nBaud
|
|
692
|
dataOut.radarControllerHeaderObj.nBaud = nBaud
|
|
|
693
|
|
|
693
|
|
|
|
694
|
|
|
694
|
|
|
|
695
|
if not self.__isConfig:
|
|
695
|
if not self.__isConfig:
|
|
|
696
|
|
|
696
|
|
|
|
697
|
self.setup(code, dataOut.data.shape)
|
|
697
|
self.setup(code, dataOut.data.shape)
|
|
|
698
|
self.__isConfig = True
|
|
698
|
self.__isConfig = True
|
|
|
699
|
|
|
699
|
|
|
|
700
|
if mode == 0:
|
|
700
|
if mode == 0:
|
|
|
701
|
datadec = self.convolutionInTime(dataOut.data)
|
|
701
|
datadec = self.convolutionInTime(dataOut.data)
|
|
|
702
|
|
|
702
|
|
|
|
703
|
if mode == 1:
|
|
703
|
if mode == 1:
|
|
|
704
|
datadec = self.convolutionInFreq(dataOut.data)
|
|
704
|
datadec = self.convolutionInFreq(dataOut.data)
|
|
|
705
|
|
|
705
|
|
|
|
706
|
if mode == 2:
|
|
706
|
if mode == 2:
|
|
|
707
|
datadec = self.convolutionInFreqOpt(dataOut.data)
|
|
707
|
datadec = self.convolutionInFreqOpt(dataOut.data)
|
|
|
708
|
|
|
708
|
|
|
|
709
|
dataOut.data = datadec
|
|
709
|
dataOut.data = datadec
|
|
|
710
|
|
|
710
|
|
|
|
711
|
dataOut.heightList = dataOut.heightList[0:self.ndatadec]
|
|
711
|
dataOut.heightList = dataOut.heightList[0:self.ndatadec]
|
|
|
712
|
|
|
712
|
|
|
|
713
|
dataOut.flagDecodeData = True #asumo q la data no esta decodificada
|
|
713
|
dataOut.flagDecodeData = True #asumo q la data no esta decodificada
|
|
|
714
|
|
|
714
|
|
|
|
715
|
if self.__profIndex == self.nCode-1:
|
|
715
|
if self.__profIndex == self.nCode-1:
|
|
|
716
|
self.__profIndex = 0
|
|
716
|
self.__profIndex = 0
|
|
|
717
|
return 1
|
|
717
|
return 1
|
|
|
718
|
|
|
718
|
|
|
|
719
|
self.__profIndex += 1
|
|
719
|
self.__profIndex += 1
|
|
|
720
|
|
|
720
|
|
|
|
721
|
return 1
|
|
721
|
return 1
|
|
|
722
|
# dataOut.flagDeflipData = True #asumo q la data no esta sin flip
|
|
722
|
# dataOut.flagDeflipData = True #asumo q la data no esta sin flip
|
|
|
723
|
|
|
723
|
|
|
|
724
|
|
|
724
|
|
|
|
725
|
|
|
725
|
|
|
|
726
|
class SpectraProc(ProcessingUnit):
|
|
726
|
class SpectraProc(ProcessingUnit):
|
|
|
727
|
|
|
727
|
|
|
|
728
|
def __init__(self):
|
|
728
|
def __init__(self):
|
|
|
729
|
|
|
729
|
|
|
|
730
|
self.objectDict = {}
|
|
730
|
self.objectDict = {}
|
|
|
731
|
self.buffer = None
|
|
731
|
self.buffer = None
|
|
|
732
|
self.firstdatatime = None
|
|
732
|
self.firstdatatime = None
|
|
|
733
|
self.profIndex = 0
|
|
733
|
self.profIndex = 0
|
|
|
734
|
self.dataOut = Spectra()
|
|
734
|
self.dataOut = Spectra()
|
|
|
735
|
|
|
735
|
|
|
|
736
|
def __updateObjFromInput(self):
|
|
736
|
def __updateObjFromInput(self):
|
|
|
737
|
|
|
737
|
|
|
|
738
|
self.dataOut.timeZone = self.dataIn.timeZone
|
|
738
|
self.dataOut.timeZone = self.dataIn.timeZone
|
|
|
739
|
self.dataOut.dstFlag = self.dataIn.dstFlag
|
|
739
|
self.dataOut.dstFlag = self.dataIn.dstFlag
|
|
|
740
|
self.dataOut.errorCount = self.dataIn.errorCount
|
|
740
|
self.dataOut.errorCount = self.dataIn.errorCount
|
|
|
741
|
self.dataOut.useLocalTime = self.dataIn.useLocalTime
|
|
741
|
self.dataOut.useLocalTime = self.dataIn.useLocalTime
|
|
|
742
|
|
|
742
|
|
|
|
743
|
self.dataOut.radarControllerHeaderObj = self.dataIn.radarControllerHeaderObj.copy()
|
|
743
|
self.dataOut.radarControllerHeaderObj = self.dataIn.radarControllerHeaderObj.copy()
|
|
|
744
|
self.dataOut.systemHeaderObj = self.dataIn.systemHeaderObj.copy()
|
|
744
|
self.dataOut.systemHeaderObj = self.dataIn.systemHeaderObj.copy()
|
|
|
745
|
self.dataOut.channelList = self.dataIn.channelList
|
|
745
|
self.dataOut.channelList = self.dataIn.channelList
|
|
|
746
|
self.dataOut.heightList = self.dataIn.heightList
|
|
746
|
self.dataOut.heightList = self.dataIn.heightList
|
|
|
747
|
self.dataOut.dtype = numpy.dtype([('real','<f4'),('imag','<f4')])
|
|
747
|
self.dataOut.dtype = numpy.dtype([('real','<f4'),('imag','<f4')])
|
|
|
748
|
# self.dataOut.nHeights = self.dataIn.nHeights
|
|
748
|
# self.dataOut.nHeights = self.dataIn.nHeights
|
|
|
749
|
# self.dataOut.nChannels = self.dataIn.nChannels
|
|
749
|
# self.dataOut.nChannels = self.dataIn.nChannels
|
|
|
750
|
self.dataOut.nBaud = self.dataIn.nBaud
|
|
750
|
self.dataOut.nBaud = self.dataIn.nBaud
|
|
|
751
|
self.dataOut.nCode = self.dataIn.nCode
|
|
751
|
self.dataOut.nCode = self.dataIn.nCode
|
|
|
752
|
self.dataOut.code = self.dataIn.code
|
|
752
|
self.dataOut.code = self.dataIn.code
|
|
|
753
|
self.dataOut.nProfiles = self.dataOut.nFFTPoints
|
|
753
|
self.dataOut.nProfiles = self.dataOut.nFFTPoints
|
|
|
754
|
# self.dataOut.channelIndexList = self.dataIn.channelIndexList
|
|
754
|
# self.dataOut.channelIndexList = self.dataIn.channelIndexList
|
|
|
755
|
self.dataOut.flagTimeBlock = self.dataIn.flagTimeBlock
|
|
755
|
self.dataOut.flagTimeBlock = self.dataIn.flagTimeBlock
|
|
|
756
|
self.dataOut.utctime = self.firstdatatime
|
|
756
|
self.dataOut.utctime = self.firstdatatime
|
|
|
757
|
self.dataOut.flagDecodeData = self.dataIn.flagDecodeData #asumo q la data esta decodificada
|
|
757
|
self.dataOut.flagDecodeData = self.dataIn.flagDecodeData #asumo q la data esta decodificada
|
|
|
758
|
self.dataOut.flagDeflipData = self.dataIn.flagDeflipData #asumo q la data esta sin flip
|
|
758
|
self.dataOut.flagDeflipData = self.dataIn.flagDeflipData #asumo q la data esta sin flip
|
|
|
759
|
# self.dataOut.flagShiftFFT = self.dataIn.flagShiftFFT
|
|
759
|
# self.dataOut.flagShiftFFT = self.dataIn.flagShiftFFT
|
|
|
760
|
self.dataOut.nCohInt = self.dataIn.nCohInt
|
|
760
|
self.dataOut.nCohInt = self.dataIn.nCohInt
|
|
|
761
|
self.dataOut.nIncohInt = 1
|
|
761
|
self.dataOut.nIncohInt = 1
|
|
|
762
|
self.dataOut.ippSeconds = self.dataIn.ippSeconds
|
|
762
|
self.dataOut.ippSeconds = self.dataIn.ippSeconds
|
|
|
763
|
self.dataOut.windowOfFilter = self.dataIn.windowOfFilter
|
|
763
|
self.dataOut.windowOfFilter = self.dataIn.windowOfFilter
|
|
|
764
|
|
|
764
|
|
|
|
765
|
self.dataOut.timeInterval = self.dataIn.timeInterval*self.dataOut.nFFTPoints*self.dataOut.nIncohInt
|
|
765
|
self.dataOut.timeInterval = self.dataIn.timeInterval*self.dataOut.nFFTPoints*self.dataOut.nIncohInt
|
|
|
766
|
self.dataOut.frequency = self.dataIn.frequency
|
|
766
|
self.dataOut.frequency = self.dataIn.frequency
|
|
|
767
|
self.dataOut.realtime = self.dataIn.realtime
|
|
767
|
self.dataOut.realtime = self.dataIn.realtime
|
|
|
768
|
|
|
768
|
|
|
|
769
|
def __getFft(self):
|
|
769
|
def __getFft(self):
|
|
|
770
|
"""
|
|
770
|
"""
|
|
|
771
|
Convierte valores de Voltaje a Spectra
|
|
771
|
Convierte valores de Voltaje a Spectra
|
|
|
772
|
|
|
772
|
|
|
|
773
|
Affected:
|
|
773
|
Affected:
|
|
|
774
|
self.dataOut.data_spc
|
|
774
|
self.dataOut.data_spc
|
|
|
775
|
self.dataOut.data_cspc
|
|
775
|
self.dataOut.data_cspc
|
|
|
776
|
self.dataOut.data_dc
|
|
776
|
self.dataOut.data_dc
|
|
|
777
|
self.dataOut.heightList
|
|
777
|
self.dataOut.heightList
|
|
|
778
|
self.profIndex
|
|
778
|
self.profIndex
|
|
|
779
|
self.buffer
|
|
779
|
self.buffer
|
|
|
780
|
self.dataOut.flagNoData
|
|
780
|
self.dataOut.flagNoData
|
|
|
781
|
"""
|
|
781
|
"""
|
|
|
782
|
fft_volt = numpy.fft.fft(self.buffer,n=self.dataOut.nFFTPoints,axis=1)
|
|
782
|
fft_volt = numpy.fft.fft(self.buffer,n=self.dataOut.nFFTPoints,axis=1)
|
|
|
783
|
fft_volt = fft_volt.astype(numpy.dtype('complex'))
|
|
783
|
fft_volt = fft_volt.astype(numpy.dtype('complex'))
|
|
|
784
|
dc = fft_volt[:,0,:]
|
|
784
|
dc = fft_volt[:,0,:]
|
|
|
785
|
|
|
785
|
|
|
|
786
|
#calculo de self-spectra
|
|
786
|
#calculo de self-spectra
|
|
|
787
|
fft_volt = numpy.fft.fftshift(fft_volt,axes=(1,))
|
|
787
|
fft_volt = numpy.fft.fftshift(fft_volt,axes=(1,))
|
|
|
788
|
spc = fft_volt * numpy.conjugate(fft_volt)
|
|
788
|
spc = fft_volt * numpy.conjugate(fft_volt)
|
|
|
789
|
spc = spc.real
|
|
789
|
spc = spc.real
|
|
|
790
|
|
|
790
|
|
|
|
791
|
blocksize = 0
|
|
791
|
blocksize = 0
|
|
|
792
|
blocksize += dc.size
|
|
792
|
blocksize += dc.size
|
|
|
793
|
blocksize += spc.size
|
|
793
|
blocksize += spc.size
|
|
|
794
|
|
|
794
|
|
|
|
795
|
cspc = None
|
|
795
|
cspc = None
|
|
|
796
|
pairIndex = 0
|
|
796
|
pairIndex = 0
|
|
|
797
|
if self.dataOut.pairsList != None:
|
|
797
|
if self.dataOut.pairsList != None:
|
|
|
798
|
#calculo de cross-spectra
|
|
798
|
#calculo de cross-spectra
|
|
|
799
|
cspc = numpy.zeros((self.dataOut.nPairs, self.dataOut.nFFTPoints, self.dataOut.nHeights), dtype='complex')
|
|
799
|
cspc = numpy.zeros((self.dataOut.nPairs, self.dataOut.nFFTPoints, self.dataOut.nHeights), dtype='complex')
|
|
|
800
|
for pair in self.dataOut.pairsList:
|
|
800
|
for pair in self.dataOut.pairsList:
|
|
|
801
|
cspc[pairIndex,:,:] = fft_volt[pair[0],:,:] * numpy.conjugate(fft_volt[pair[1],:,:])
|
|
801
|
cspc[pairIndex,:,:] = fft_volt[pair[0],:,:] * numpy.conjugate(fft_volt[pair[1],:,:])
|
|
|
802
|
pairIndex += 1
|
|
802
|
pairIndex += 1
|
|
|
803
|
blocksize += cspc.size
|
|
803
|
blocksize += cspc.size
|
|
|
804
|
|
|
804
|
|
|
|
805
|
self.dataOut.data_spc = spc
|
|
805
|
self.dataOut.data_spc = spc
|
|
|
806
|
self.dataOut.data_cspc = cspc
|
|
806
|
self.dataOut.data_cspc = cspc
|
|
|
807
|
self.dataOut.data_dc = dc
|
|
807
|
self.dataOut.data_dc = dc
|
|
|
808
|
self.dataOut.blockSize = blocksize
|
|
808
|
self.dataOut.blockSize = blocksize
|
|
|
809
|
self.dataOut.flagShiftFFT = False
|
|
809
|
self.dataOut.flagShiftFFT = False
|
|
|
810
|
|
|
810
|
|
|
|
811
|
def init(self, nProfiles=None, nFFTPoints=None, pairsList=None, ippFactor=None):
|
|
811
|
def init(self, nProfiles=None, nFFTPoints=None, pairsList=None, ippFactor=None):
|
|
|
812
|
|
|
812
|
|
|
|
813
|
self.dataOut.flagNoData = True
|
|
813
|
self.dataOut.flagNoData = True
|
|
|
814
|
|
|
814
|
|
|
|
815
|
if self.dataIn.type == "Spectra":
|
|
815
|
if self.dataIn.type == "Spectra":
|
|
|
816
|
self.dataOut.copy(self.dataIn)
|
|
816
|
self.dataOut.copy(self.dataIn)
|
|
|
817
|
return
|
|
817
|
return
|
|
|
818
|
|
|
818
|
|
|
|
819
|
if self.dataIn.type == "Voltage":
|
|
819
|
if self.dataIn.type == "Voltage":
|
|
|
820
|
|
|
820
|
|
|
|
821
|
if nFFTPoints == None:
|
|
821
|
if nFFTPoints == None:
|
|
|
822
|
raise ValueError, "This SpectraProc.init() need nFFTPoints input variable"
|
|
822
|
raise ValueError, "This SpectraProc.init() need nFFTPoints input variable"
|
|
|
823
|
|
|
823
|
|
|
|
824
|
if pairsList == None:
|
|
824
|
if pairsList == None:
|
|
|
825
|
nPairs = 0
|
|
825
|
nPairs = 0
|
|
|
826
|
else:
|
|
826
|
else:
|
|
|
827
|
nPairs = len(pairsList)
|
|
827
|
nPairs = len(pairsList)
|
|
|
828
|
|
|
828
|
|
|
|
829
|
if ippFactor == None:
|
|
829
|
if ippFactor == None:
|
|
|
830
|
ippFactor = 1
|
|
830
|
ippFactor = 1
|
|
|
831
|
self.dataOut.ippFactor = ippFactor
|
|
831
|
self.dataOut.ippFactor = ippFactor
|
|
|
832
|
|
|
832
|
|
|
|
833
|
self.dataOut.nFFTPoints = nFFTPoints
|
|
833
|
self.dataOut.nFFTPoints = nFFTPoints
|
|
|
834
|
self.dataOut.pairsList = pairsList
|
|
834
|
self.dataOut.pairsList = pairsList
|
|
|
835
|
self.dataOut.nPairs = nPairs
|
|
835
|
self.dataOut.nPairs = nPairs
|
|
|
836
|
|
|
836
|
|
|
|
837
|
if self.buffer == None:
|
|
837
|
if self.buffer == None:
|
|
|
838
|
self.buffer = numpy.zeros((self.dataIn.nChannels,
|
|
838
|
self.buffer = numpy.zeros((self.dataIn.nChannels,
|
|
|
839
|
nProfiles,
|
|
839
|
nProfiles,
|
|
|
840
|
self.dataIn.nHeights),
|
|
840
|
self.dataIn.nHeights),
|
|
|
841
|
dtype='complex')
|
|
841
|
dtype='complex')
|
|
|
842
|
|
|
842
|
|
|
|
843
|
|
|
843
|
|
|
|
844
|
self.buffer[:,self.profIndex,:] = self.dataIn.data.copy()
|
|
844
|
self.buffer[:,self.profIndex,:] = self.dataIn.data.copy()
|
|
|
845
|
self.profIndex += 1
|
|
845
|
self.profIndex += 1
|
|
|
846
|
|
|
846
|
|
|
|
847
|
if self.firstdatatime == None:
|
|
847
|
if self.firstdatatime == None:
|
|
|
848
|
self.firstdatatime = self.dataIn.utctime
|
|
848
|
self.firstdatatime = self.dataIn.utctime
|
|
|
849
|
|
|
849
|
|
|
|
850
|
if self.profIndex == nProfiles:
|
|
850
|
if self.profIndex == nProfiles:
|
|
|
851
|
self.__updateObjFromInput()
|
|
851
|
self.__updateObjFromInput()
|
|
|
852
|
self.__getFft()
|
|
852
|
self.__getFft()
|
|
|
853
|
|
|
853
|
|
|
|
854
|
self.dataOut.flagNoData = False
|
|
854
|
self.dataOut.flagNoData = False
|
|
|
855
|
|
|
855
|
|
|
|
856
|
self.buffer = None
|
|
856
|
self.buffer = None
|
|
|
857
|
self.firstdatatime = None
|
|
857
|
self.firstdatatime = None
|
|
|
858
|
self.profIndex = 0
|
|
858
|
self.profIndex = 0
|
|
|
859
|
|
|
859
|
|
|
|
860
|
return
|
|
860
|
return
|
|
|
861
|
|
|
861
|
|
|
|
862
|
raise ValueError, "The type object %s is not valid"%(self.dataIn.type)
|
|
862
|
raise ValueError, "The type object %s is not valid"%(self.dataIn.type)
|
|
|
863
|
|
|
863
|
|
|
|
864
|
def selectChannels(self, channelList):
|
|
864
|
def selectChannels(self, channelList):
|
|
|
865
|
|
|
865
|
|
|
|
866
|
channelIndexList = []
|
|
866
|
channelIndexList = []
|
|
|
867
|
|
|
867
|
|
|
|
868
|
for channel in channelList:
|
|
868
|
for channel in channelList:
|
|
|
869
|
index = self.dataOut.channelList.index(channel)
|
|
869
|
index = self.dataOut.channelList.index(channel)
|
|
|
870
|
channelIndexList.append(index)
|
|
870
|
channelIndexList.append(index)
|
|
|
871
|
|
|
871
|
|
|
|
872
|
self.selectChannelsByIndex(channelIndexList)
|
|
872
|
self.selectChannelsByIndex(channelIndexList)
|
|
|
873
|
|
|
873
|
|
|
|
874
|
def selectChannelsByIndex(self, channelIndexList):
|
|
874
|
def selectChannelsByIndex(self, channelIndexList):
|
|
|
875
|
"""
|
|
875
|
"""
|
|
|
876
|
Selecciona un bloque de datos en base a canales segun el channelIndexList
|
|
876
|
Selecciona un bloque de datos en base a canales segun el channelIndexList
|
|
|
877
|
|
|
877
|
|
|
|
878
|
Input:
|
|
878
|
Input:
|
|
|
879
|
channelIndexList : lista sencilla de canales a seleccionar por ej. [2,3,7]
|
|
879
|
channelIndexList : lista sencilla de canales a seleccionar por ej. [2,3,7]
|
|
|
880
|
|
|
880
|
|
|
|
881
|
Affected:
|
|
881
|
Affected:
|
|
|
882
|
self.dataOut.data_spc
|
|
882
|
self.dataOut.data_spc
|
|
|
883
|
self.dataOut.channelIndexList
|
|
883
|
self.dataOut.channelIndexList
|
|
|
884
|
self.dataOut.nChannels
|
|
884
|
self.dataOut.nChannels
|
|
|
885
|
|
|
885
|
|
|
|
886
|
Return:
|
|
886
|
Return:
|
|
|
887
|
None
|
|
887
|
None
|
|
|
888
|
"""
|
|
888
|
"""
|
|
|
889
|
|
|
889
|
|
|
|
890
|
for channelIndex in channelIndexList:
|
|
890
|
for channelIndex in channelIndexList:
|
|
|
891
|
if channelIndex not in self.dataOut.channelIndexList:
|
|
891
|
if channelIndex not in self.dataOut.channelIndexList:
|
|
|
892
|
print channelIndexList
|
|
892
|
print channelIndexList
|
|
|
893
|
raise ValueError, "The value %d in channelIndexList is not valid" %channelIndex
|
|
893
|
raise ValueError, "The value %d in channelIndexList is not valid" %channelIndex
|
|
|
894
|
|
|
894
|
|
|
|
895
|
nChannels = len(channelIndexList)
|
|
895
|
nChannels = len(channelIndexList)
|
|
|
896
|
|
|
896
|
|
|
|
897
|
data_spc = self.dataOut.data_spc[channelIndexList,:]
|
|
897
|
data_spc = self.dataOut.data_spc[channelIndexList,:]
|
|
|
898
|
|
|
898
|
|
|
|
899
|
self.dataOut.data_spc = data_spc
|
|
899
|
self.dataOut.data_spc = data_spc
|
|
|
900
|
self.dataOut.channelList = [self.dataOut.channelList[i] for i in channelIndexList]
|
|
900
|
self.dataOut.channelList = [self.dataOut.channelList[i] for i in channelIndexList]
|
|
|
901
|
# self.dataOut.nChannels = nChannels
|
|
901
|
# self.dataOut.nChannels = nChannels
|
|
|
902
|
|
|
902
|
|
|
|
903
|
return 1
|
|
903
|
return 1
|
|
|
904
|
|
|
904
|
|
|
|
905
|
def selectHeights(self, minHei, maxHei):
|
|
905
|
def selectHeights(self, minHei, maxHei):
|
|
|
906
|
"""
|
|
906
|
"""
|
|
|
907
|
Selecciona un bloque de datos en base a un grupo de valores de alturas segun el rango
|
|
907
|
Selecciona un bloque de datos en base a un grupo de valores de alturas segun el rango
|
|
|
908
|
minHei <= height <= maxHei
|
|
908
|
minHei <= height <= maxHei
|
|
|
909
|
|
|
909
|
|
|
|
910
|
Input:
|
|
910
|
Input:
|
|
|
911
|
minHei : valor minimo de altura a considerar
|
|
911
|
minHei : valor minimo de altura a considerar
|
|
|
912
|
maxHei : valor maximo de altura a considerar
|
|
912
|
maxHei : valor maximo de altura a considerar
|
|
|
913
|
|
|
913
|
|
|
|
914
|
Affected:
|
|
914
|
Affected:
|
|
|
915
|
Indirectamente son cambiados varios valores a travez del metodo selectHeightsByIndex
|
|
915
|
Indirectamente son cambiados varios valores a travez del metodo selectHeightsByIndex
|
|
|
916
|
|
|
916
|
|
|
|
917
|
Return:
|
|
917
|
Return:
|
|
|
918
|
1 si el metodo se ejecuto con exito caso contrario devuelve 0
|
|
918
|
1 si el metodo se ejecuto con exito caso contrario devuelve 0
|
|
|
919
|
"""
|
|
919
|
"""
|
|
|
920
|
if (minHei < self.dataOut.heightList[0]) or (minHei > maxHei):
|
|
920
|
if (minHei < self.dataOut.heightList[0]) or (minHei > maxHei):
|
|
|
921
|
raise ValueError, "some value in (%d,%d) is not valid" % (minHei, maxHei)
|
|
921
|
raise ValueError, "some value in (%d,%d) is not valid" % (minHei, maxHei)
|
|
|
922
|
|
|
922
|
|
|
|
923
|
if (maxHei > self.dataOut.heightList[-1]):
|
|
923
|
if (maxHei > self.dataOut.heightList[-1]):
|
|
|
924
|
maxHei = self.dataOut.heightList[-1]
|
|
924
|
maxHei = self.dataOut.heightList[-1]
|
|
|
925
|
# raise ValueError, "some value in (%d,%d) is not valid" % (minHei, maxHei)
|
|
925
|
# raise ValueError, "some value in (%d,%d) is not valid" % (minHei, maxHei)
|
|
|
926
|
|
|
926
|
|
|
|
927
|
minIndex = 0
|
|
927
|
minIndex = 0
|
|
|
928
|
maxIndex = 0
|
|
928
|
maxIndex = 0
|
|
|
929
|
heights = self.dataOut.heightList
|
|
929
|
heights = self.dataOut.heightList
|
|
|
930
|
|
|
930
|
|
|
|
931
|
inda = numpy.where(heights >= minHei)
|
|
931
|
inda = numpy.where(heights >= minHei)
|
|
|
932
|
indb = numpy.where(heights <= maxHei)
|
|
932
|
indb = numpy.where(heights <= maxHei)
|
|
|
933
|
|
|
933
|
|
|
|
934
|
try:
|
|
934
|
try:
|
|
|
935
|
minIndex = inda[0][0]
|
|
935
|
minIndex = inda[0][0]
|
|
|
936
|
except:
|
|
936
|
except:
|
|
|
937
|
minIndex = 0
|
|
937
|
minIndex = 0
|
|
|
938
|
|
|
938
|
|
|
|
939
|
try:
|
|
939
|
try:
|
|
|
940
|
maxIndex = indb[0][-1]
|
|
940
|
maxIndex = indb[0][-1]
|
|
|
941
|
except:
|
|
941
|
except:
|
|
|
942
|
maxIndex = len(heights)
|
|
942
|
maxIndex = len(heights)
|
|
|
943
|
|
|
943
|
|
|
|
944
|
self.selectHeightsByIndex(minIndex, maxIndex)
|
|
944
|
self.selectHeightsByIndex(minIndex, maxIndex)
|
|
|
945
|
|
|
945
|
|
|
|
946
|
return 1
|
|
946
|
return 1
|
|
|
947
|
|
|
947
|
|
|
|
948
|
def getBeaconSignal(self, tauindex = 0, channelindex = 0, hei_ref=None):
|
|
948
|
def getBeaconSignal(self, tauindex = 0, channelindex = 0, hei_ref=None):
|
|
|
949
|
newheis = numpy.where(self.dataOut.heightList>self.dataOut.radarControllerHeaderObj.Taus[tauindex])
|
|
949
|
newheis = numpy.where(self.dataOut.heightList>self.dataOut.radarControllerHeaderObj.Taus[tauindex])
|
|
|
950
|
|
|
950
|
|
|
|
951
|
if hei_ref != None:
|
|
951
|
if hei_ref != None:
|
|
|
952
|
newheis = numpy.where(self.dataOut.heightList>hei_ref)
|
|
952
|
newheis = numpy.where(self.dataOut.heightList>hei_ref)
|
|
|
953
|
|
|
953
|
|
|
|
954
|
minIndex = min(newheis[0])
|
|
954
|
minIndex = min(newheis[0])
|
|
|
955
|
maxIndex = max(newheis[0])
|
|
955
|
maxIndex = max(newheis[0])
|
|
|
956
|
data_spc = self.dataOut.data_spc[:,:,minIndex:maxIndex+1]
|
|
956
|
data_spc = self.dataOut.data_spc[:,:,minIndex:maxIndex+1]
|
|
|
957
|
heightList = self.dataOut.heightList[minIndex:maxIndex+1]
|
|
957
|
heightList = self.dataOut.heightList[minIndex:maxIndex+1]
|
|
|
958
|
|
|
958
|
|
|
|
959
|
# determina indices
|
|
959
|
# determina indices
|
|
|
960
|
nheis = int(self.dataOut.radarControllerHeaderObj.txB/(self.dataOut.heightList[1]-self.dataOut.heightList[0]))
|
|
960
|
nheis = int(self.dataOut.radarControllerHeaderObj.txB/(self.dataOut.heightList[1]-self.dataOut.heightList[0]))
|
|
|
961
|
avg_dB = 10*numpy.log10(numpy.sum(data_spc[channelindex,:,:],axis=0))
|
|
961
|
avg_dB = 10*numpy.log10(numpy.sum(data_spc[channelindex,:,:],axis=0))
|
|
|
962
|
beacon_dB = numpy.sort(avg_dB)[-nheis:]
|
|
962
|
beacon_dB = numpy.sort(avg_dB)[-nheis:]
|
|
|
963
|
beacon_heiIndexList = []
|
|
963
|
beacon_heiIndexList = []
|
|
|
964
|
for val in avg_dB.tolist():
|
|
964
|
for val in avg_dB.tolist():
|
|
|
965
|
if val >= beacon_dB[0]:
|
|
965
|
if val >= beacon_dB[0]:
|
|
|
966
|
beacon_heiIndexList.append(avg_dB.tolist().index(val))
|
|
966
|
beacon_heiIndexList.append(avg_dB.tolist().index(val))
|
|
|
967
|
|
|
967
|
|
|
|
968
|
#data_spc = data_spc[:,:,beacon_heiIndexList]
|
|
968
|
#data_spc = data_spc[:,:,beacon_heiIndexList]
|
|
|
969
|
data_cspc = None
|
|
969
|
data_cspc = None
|
|
|
970
|
if self.dataOut.data_cspc != None:
|
|
970
|
if self.dataOut.data_cspc != None:
|
|
|
971
|
data_cspc = self.dataOut.data_cspc[:,:,minIndex:maxIndex+1]
|
|
971
|
data_cspc = self.dataOut.data_cspc[:,:,minIndex:maxIndex+1]
|
|
|
972
|
#data_cspc = data_cspc[:,:,beacon_heiIndexList]
|
|
972
|
#data_cspc = data_cspc[:,:,beacon_heiIndexList]
|
|
|
973
|
|
|
973
|
|
|
|
974
|
data_dc = None
|
|
974
|
data_dc = None
|
|
|
975
|
if self.dataOut.data_dc != None:
|
|
975
|
if self.dataOut.data_dc != None:
|
|
|
976
|
data_dc = self.dataOut.data_dc[:,minIndex:maxIndex+1]
|
|
976
|
data_dc = self.dataOut.data_dc[:,minIndex:maxIndex+1]
|
|
|
977
|
#data_dc = data_dc[:,beacon_heiIndexList]
|
|
977
|
#data_dc = data_dc[:,beacon_heiIndexList]
|
|
|
978
|
|
|
978
|
|
|
|
979
|
self.dataOut.data_spc = data_spc
|
|
979
|
self.dataOut.data_spc = data_spc
|
|
|
980
|
self.dataOut.data_cspc = data_cspc
|
|
980
|
self.dataOut.data_cspc = data_cspc
|
|
|
981
|
self.dataOut.data_dc = data_dc
|
|
981
|
self.dataOut.data_dc = data_dc
|
|
|
982
|
self.dataOut.heightList = heightList
|
|
982
|
self.dataOut.heightList = heightList
|
|
|
983
|
self.dataOut.beacon_heiIndexList = beacon_heiIndexList
|
|
983
|
self.dataOut.beacon_heiIndexList = beacon_heiIndexList
|
|
|
984
|
|
|
984
|
|
|
|
985
|
return 1
|
|
985
|
return 1
|
|
|
986
|
|
|
986
|
|
|
|
987
|
|
|
987
|
|
|
|
988
|
def selectHeightsByIndex(self, minIndex, maxIndex):
|
|
988
|
def selectHeightsByIndex(self, minIndex, maxIndex):
|
|
|
989
|
"""
|
|
989
|
"""
|
|
|
990
|
Selecciona un bloque de datos en base a un grupo indices de alturas segun el rango
|
|
990
|
Selecciona un bloque de datos en base a un grupo indices de alturas segun el rango
|
|
|
991
|
minIndex <= index <= maxIndex
|
|
991
|
minIndex <= index <= maxIndex
|
|
|
992
|
|
|
992
|
|
|
|
993
|
Input:
|
|
993
|
Input:
|
|
|
994
|
minIndex : valor de indice minimo de altura a considerar
|
|
994
|
minIndex : valor de indice minimo de altura a considerar
|
|
|
995
|
maxIndex : valor de indice maximo de altura a considerar
|
|
995
|
maxIndex : valor de indice maximo de altura a considerar
|
|
|
996
|
|
|
996
|
|
|
|
997
|
Affected:
|
|
997
|
Affected:
|
|
|
998
|
self.dataOut.data_spc
|
|
998
|
self.dataOut.data_spc
|
|
|
999
|
self.dataOut.data_cspc
|
|
999
|
self.dataOut.data_cspc
|
|
|
1000
|
self.dataOut.data_dc
|
|
1000
|
self.dataOut.data_dc
|
|
|
1001
|
self.dataOut.heightList
|
|
1001
|
self.dataOut.heightList
|
|
|
1002
|
|
|
1002
|
|
|
|
1003
|
Return:
|
|
1003
|
Return:
|
|
|
1004
|
1 si el metodo se ejecuto con exito caso contrario devuelve 0
|
|
1004
|
1 si el metodo se ejecuto con exito caso contrario devuelve 0
|
|
|
1005
|
"""
|
|
1005
|
"""
|
|
|
1006
|
|
|
1006
|
|
|
|
1007
|
if (minIndex < 0) or (minIndex > maxIndex):
|
|
1007
|
if (minIndex < 0) or (minIndex > maxIndex):
|
|
|
1008
|
raise ValueError, "some value in (%d,%d) is not valid" % (minIndex, maxIndex)
|
|
1008
|
raise ValueError, "some value in (%d,%d) is not valid" % (minIndex, maxIndex)
|
|
|
1009
|
|
|
1009
|
|
|
|
1010
|
if (maxIndex >= self.dataOut.nHeights):
|
|
1010
|
if (maxIndex >= self.dataOut.nHeights):
|
|
|
1011
|
maxIndex = self.dataOut.nHeights-1
|
|
1011
|
maxIndex = self.dataOut.nHeights-1
|
|
|
1012
|
# raise ValueError, "some value in (%d,%d) is not valid" % (minIndex, maxIndex)
|
|
1012
|
# raise ValueError, "some value in (%d,%d) is not valid" % (minIndex, maxIndex)
|
|
|
1013
|
|
|
1013
|
|
|
|
1014
|
nHeights = maxIndex - minIndex + 1
|
|
1014
|
nHeights = maxIndex - minIndex + 1
|
|
|
1015
|
|
|
1015
|
|
|
|
1016
|
#Spectra
|
|
1016
|
#Spectra
|
|
|
1017
|
data_spc = self.dataOut.data_spc[:,:,minIndex:maxIndex+1]
|
|
1017
|
data_spc = self.dataOut.data_spc[:,:,minIndex:maxIndex+1]
|
|
|
1018
|
|
|
1018
|
|
|
|
1019
|
data_cspc = None
|
|
1019
|
data_cspc = None
|
|
|
1020
|
if self.dataOut.data_cspc != None:
|
|
1020
|
if self.dataOut.data_cspc != None:
|
|
|
1021
|
data_cspc = self.dataOut.data_cspc[:,:,minIndex:maxIndex+1]
|
|
1021
|
data_cspc = self.dataOut.data_cspc[:,:,minIndex:maxIndex+1]
|
|
|
1022
|
|
|
1022
|
|
|
|
1023
|
data_dc = None
|
|
1023
|
data_dc = None
|
|
|
1024
|
if self.dataOut.data_dc != None:
|
|
1024
|
if self.dataOut.data_dc != None:
|
|
|
1025
|
data_dc = self.dataOut.data_dc[:,minIndex:maxIndex+1]
|
|
1025
|
data_dc = self.dataOut.data_dc[:,minIndex:maxIndex+1]
|
|
|
1026
|
|
|
1026
|
|
|
|
1027
|
self.dataOut.data_spc = data_spc
|
|
1027
|
self.dataOut.data_spc = data_spc
|
|
|
1028
|
self.dataOut.data_cspc = data_cspc
|
|
1028
|
self.dataOut.data_cspc = data_cspc
|
|
|
1029
|
self.dataOut.data_dc = data_dc
|
|
1029
|
self.dataOut.data_dc = data_dc
|
|
|
1030
|
|
|
1030
|
|
|
|
1031
|
self.dataOut.heightList = self.dataOut.heightList[minIndex:maxIndex+1]
|
|
1031
|
self.dataOut.heightList = self.dataOut.heightList[minIndex:maxIndex+1]
|
|
|
1032
|
|
|
1032
|
|
|
|
1033
|
return 1
|
|
1033
|
return 1
|
|
|
1034
|
|
|
1034
|
|
|
|
1035
|
def removeDC(self, mode = 2):
|
|
1035
|
def removeDC(self, mode = 2):
|
|
|
1036
|
jspectra = self.dataOut.data_spc
|
|
1036
|
jspectra = self.dataOut.data_spc
|
|
|
1037
|
jcspectra = self.dataOut.data_cspc
|
|
1037
|
jcspectra = self.dataOut.data_cspc
|
|
|
1038
|
|
|
1038
|
|
|
|
1039
|
|
|
1039
|
|
|
|
1040
|
num_chan = jspectra.shape[0]
|
|
1040
|
num_chan = jspectra.shape[0]
|
|
|
1041
|
num_hei = jspectra.shape[2]
|
|
1041
|
num_hei = jspectra.shape[2]
|
|
|
1042
|
|
|
1042
|
|
|
|
1043
|
if jcspectra != None:
|
|
1043
|
if jcspectra != None:
|
|
|
1044
|
jcspectraExist = True
|
|
1044
|
jcspectraExist = True
|
|
|
1045
|
num_pairs = jcspectra.shape[0]
|
|
1045
|
num_pairs = jcspectra.shape[0]
|
|
|
1046
|
else: jcspectraExist = False
|
|
1046
|
else: jcspectraExist = False
|
|
|
1047
|
|
|
1047
|
|
|
|
1048
|
freq_dc = jspectra.shape[1]/2
|
|
1048
|
freq_dc = jspectra.shape[1]/2
|
|
|
1049
|
ind_vel = numpy.array([-2,-1,1,2]) + freq_dc
|
|
1049
|
ind_vel = numpy.array([-2,-1,1,2]) + freq_dc
|
|
|
1050
|
|
|
1050
|
|
|
|
1051
|
if ind_vel[0]<0:
|
|
1051
|
if ind_vel[0]<0:
|
|
|
1052
|
ind_vel[range(0,1)] = ind_vel[range(0,1)] + self.num_prof
|
|
1052
|
ind_vel[range(0,1)] = ind_vel[range(0,1)] + self.num_prof
|
|
|
1053
|
|
|
1053
|
|
|
|
1054
|
if mode == 1:
|
|
1054
|
if mode == 1:
|
|
|
1055
|
jspectra[:,freq_dc,:] = (jspectra[:,ind_vel[1],:] + jspectra[:,ind_vel[2],:])/2 #CORRECCION
|
|
1055
|
jspectra[:,freq_dc,:] = (jspectra[:,ind_vel[1],:] + jspectra[:,ind_vel[2],:])/2 #CORRECCION
|
|
|
1056
|
|
|
1056
|
|
|
|
1057
|
if jcspectraExist:
|
|
1057
|
if jcspectraExist:
|
|
|
1058
|
jcspectra[:,freq_dc,:] = (jcspectra[:,ind_vel[1],:] + jcspectra[:,ind_vel[2],:])/2
|
|
1058
|
jcspectra[:,freq_dc,:] = (jcspectra[:,ind_vel[1],:] + jcspectra[:,ind_vel[2],:])/2
|
|
|
1059
|
|
|
1059
|
|
|
|
1060
|
if mode == 2:
|
|
1060
|
if mode == 2:
|
|
|
1061
|
|
|
1061
|
|
|
|
1062
|
vel = numpy.array([-2,-1,1,2])
|
|
1062
|
vel = numpy.array([-2,-1,1,2])
|
|
|
1063
|
xx = numpy.zeros([4,4])
|
|
1063
|
xx = numpy.zeros([4,4])
|
|
|
1064
|
|
|
1064
|
|
|
|
1065
|
for fil in range(4):
|
|
1065
|
for fil in range(4):
|
|
|
1066
|
xx[fil,:] = vel[fil]**numpy.asarray(range(4))
|
|
1066
|
xx[fil,:] = vel[fil]**numpy.asarray(range(4))
|
|
|
1067
|
|
|
1067
|
|
|
|
1068
|
xx_inv = numpy.linalg.inv(xx)
|
|
1068
|
xx_inv = numpy.linalg.inv(xx)
|
|
|
1069
|
xx_aux = xx_inv[0,:]
|
|
1069
|
xx_aux = xx_inv[0,:]
|
|
|
1070
|
|
|
1070
|
|
|
|
1071
|
for ich in range(num_chan):
|
|
1071
|
for ich in range(num_chan):
|
|
|
1072
|
yy = jspectra[ich,ind_vel,:]
|
|
1072
|
yy = jspectra[ich,ind_vel,:]
|
|
|
1073
|
jspectra[ich,freq_dc,:] = numpy.dot(xx_aux,yy)
|
|
1073
|
jspectra[ich,freq_dc,:] = numpy.dot(xx_aux,yy)
|
|
|
1074
|
|
|
1074
|
|
|
|
1075
|
junkid = jspectra[ich,freq_dc,:]<=0
|
|
1075
|
junkid = jspectra[ich,freq_dc,:]<=0
|
|
|
1076
|
cjunkid = sum(junkid)
|
|
1076
|
cjunkid = sum(junkid)
|
|
|
1077
|
|
|
1077
|
|
|
|
1078
|
if cjunkid.any():
|
|
1078
|
if cjunkid.any():
|
|
|
1079
|
jspectra[ich,freq_dc,junkid.nonzero()] = (jspectra[ich,ind_vel[1],junkid] + jspectra[ich,ind_vel[2],junkid])/2
|
|
1079
|
jspectra[ich,freq_dc,junkid.nonzero()] = (jspectra[ich,ind_vel[1],junkid] + jspectra[ich,ind_vel[2],junkid])/2
|
|
|
1080
|
|
|
1080
|
|
|
|
1081
|
if jcspectraExist:
|
|
1081
|
if jcspectraExist:
|
|
|
1082
|
for ip in range(num_pairs):
|
|
1082
|
for ip in range(num_pairs):
|
|
|
1083
|
yy = jcspectra[ip,ind_vel,:]
|
|
1083
|
yy = jcspectra[ip,ind_vel,:]
|
|
|
1084
|
jcspectra[ip,freq_dc,:] = numpy.dot(xx_aux,yy)
|
|
1084
|
jcspectra[ip,freq_dc,:] = numpy.dot(xx_aux,yy)
|
|
|
1085
|
|
|
1085
|
|
|
|
1086
|
|
|
1086
|
|
|
|
1087
|
self.dataOut.data_spc = jspectra
|
|
1087
|
self.dataOut.data_spc = jspectra
|
|
|
1088
|
self.dataOut.data_cspc = jcspectra
|
|
1088
|
self.dataOut.data_cspc = jcspectra
|
|
|
1089
|
|
|
1089
|
|
|
|
1090
|
return 1
|
|
1090
|
return 1
|
|
|
1091
|
|
|
1091
|
|
|
|
1092
|
def removeInterference(self, interf = 2,hei_interf = None, nhei_interf = None, offhei_interf = None):
|
|
1092
|
def removeInterference(self, interf = 2,hei_interf = None, nhei_interf = None, offhei_interf = None):
|
|
|
1093
|
|
|
1093
|
|
|
|
1094
|
jspectra = self.dataOut.data_spc
|
|
1094
|
jspectra = self.dataOut.data_spc
|
|
|
1095
|
jcspectra = self.dataOut.data_cspc
|
|
1095
|
jcspectra = self.dataOut.data_cspc
|
|
|
1096
|
jnoise = self.dataOut.getNoise()
|
|
1096
|
jnoise = self.dataOut.getNoise()
|
|
|
1097
|
num_incoh = self.dataOut.nIncohInt
|
|
1097
|
num_incoh = self.dataOut.nIncohInt
|
|
|
1098
|
|
|
1098
|
|
|
|
1099
|
num_channel = jspectra.shape[0]
|
|
1099
|
num_channel = jspectra.shape[0]
|
|
|
1100
|
num_prof = jspectra.shape[1]
|
|
1100
|
num_prof = jspectra.shape[1]
|
|
|
1101
|
num_hei = jspectra.shape[2]
|
|
1101
|
num_hei = jspectra.shape[2]
|
|
|
1102
|
|
|
1102
|
|
|
|
1103
|
#hei_interf
|
|
1103
|
#hei_interf
|
|
|
1104
|
if hei_interf == None:
|
|
1104
|
if hei_interf == None:
|
|
|
1105
|
count_hei = num_hei/2 #Como es entero no importa
|
|
1105
|
count_hei = num_hei/2 #Como es entero no importa
|
|
|
1106
|
hei_interf = numpy.asmatrix(range(count_hei)) + num_hei - count_hei
|
|
1106
|
hei_interf = numpy.asmatrix(range(count_hei)) + num_hei - count_hei
|
|
|
1107
|
hei_interf = numpy.asarray(hei_interf)[0]
|
|
1107
|
hei_interf = numpy.asarray(hei_interf)[0]
|
|
|
1108
|
#nhei_interf
|
|
1108
|
#nhei_interf
|
|
|
1109
|
if (nhei_interf == None):
|
|
1109
|
if (nhei_interf == None):
|
|
|
1110
|
nhei_interf = 5
|
|
1110
|
nhei_interf = 5
|
|
|
1111
|
if (nhei_interf < 1):
|
|
1111
|
if (nhei_interf < 1):
|
|
|
1112
|
nhei_interf = 1
|
|
1112
|
nhei_interf = 1
|
|
|
1113
|
if (nhei_interf > count_hei):
|
|
1113
|
if (nhei_interf > count_hei):
|
|
|
1114
|
nhei_interf = count_hei
|
|
1114
|
nhei_interf = count_hei
|
|
|
1115
|
if (offhei_interf == None):
|
|
1115
|
if (offhei_interf == None):
|
|
|
1116
|
offhei_interf = 0
|
|
1116
|
offhei_interf = 0
|
|
|
1117
|
|
|
1117
|
|
|
|
1118
|
ind_hei = range(num_hei)
|
|
1118
|
ind_hei = range(num_hei)
|
|
|
1119
|
# mask_prof = numpy.asarray(range(num_prof - 2)) + 1
|
|
1119
|
# mask_prof = numpy.asarray(range(num_prof - 2)) + 1
|
|
|
1120
|
# mask_prof[range(num_prof/2 - 1,len(mask_prof))] += 1
|
|
1120
|
# mask_prof[range(num_prof/2 - 1,len(mask_prof))] += 1
|
|
|
1121
|
mask_prof = numpy.asarray(range(num_prof))
|
|
1121
|
mask_prof = numpy.asarray(range(num_prof))
|
|
|
1122
|
num_mask_prof = mask_prof.size
|
|
1122
|
num_mask_prof = mask_prof.size
|
|
|
1123
|
comp_mask_prof = [0, num_prof/2]
|
|
1123
|
comp_mask_prof = [0, num_prof/2]
|
|
|
1124
|
|
|
1124
|
|
|
|
1125
|
|
|
1125
|
|
|
|
1126
|
#noise_exist: Determina si la variable jnoise ha sido definida y contiene la informacion del ruido de cada canal
|
|
1126
|
#noise_exist: Determina si la variable jnoise ha sido definida y contiene la informacion del ruido de cada canal
|
|
|
1127
|
if (jnoise.size < num_channel or numpy.isnan(jnoise).any()):
|
|
1127
|
if (jnoise.size < num_channel or numpy.isnan(jnoise).any()):
|
|
|
1128
|
jnoise = numpy.nan
|
|
1128
|
jnoise = numpy.nan
|
|
|
1129
|
noise_exist = jnoise[0] < numpy.Inf
|
|
1129
|
noise_exist = jnoise[0] < numpy.Inf
|
|
|
1130
|
|
|
1130
|
|
|
|
1131
|
#Subrutina de Remocion de la Interferencia
|
|
1131
|
#Subrutina de Remocion de la Interferencia
|
|
|
1132
|
for ich in range(num_channel):
|
|
1132
|
for ich in range(num_channel):
|
|
|
1133
|
#Se ordena los espectros segun su potencia (menor a mayor)
|
|
1133
|
#Se ordena los espectros segun su potencia (menor a mayor)
|
|
|
1134
|
power = jspectra[ich,mask_prof,:]
|
|
1134
|
power = jspectra[ich,mask_prof,:]
|
|
|
1135
|
power = power[:,hei_interf]
|
|
1135
|
power = power[:,hei_interf]
|
|
|
1136
|
power = power.sum(axis = 0)
|
|
1136
|
power = power.sum(axis = 0)
|
|
|
1137
|
psort = power.ravel().argsort()
|
|
1137
|
psort = power.ravel().argsort()
|
|
|
1138
|
|
|
1138
|
|
|
|
1139
|
#Se estima la interferencia promedio en los Espectros de Potencia empleando
|
|
1139
|
#Se estima la interferencia promedio en los Espectros de Potencia empleando
|
|
|
1140
|
junkspc_interf = jspectra[ich,:,hei_interf[psort[range(offhei_interf, nhei_interf + offhei_interf)]]]
|
|
1140
|
junkspc_interf = jspectra[ich,:,hei_interf[psort[range(offhei_interf, nhei_interf + offhei_interf)]]]
|
|
|
1141
|
|
|
1141
|
|
|
|
1142
|
if noise_exist:
|
|
1142
|
if noise_exist:
|
|
|
1143
|
# tmp_noise = jnoise[ich] / num_prof
|
|
1143
|
# tmp_noise = jnoise[ich] / num_prof
|
|
|
1144
|
tmp_noise = jnoise[ich]
|
|
1144
|
tmp_noise = jnoise[ich]
|
|
|
1145
|
junkspc_interf = junkspc_interf - tmp_noise
|
|
1145
|
junkspc_interf = junkspc_interf - tmp_noise
|
|
|
1146
|
#junkspc_interf[:,comp_mask_prof] = 0
|
|
1146
|
#junkspc_interf[:,comp_mask_prof] = 0
|
|
|
1147
|
|
|
1147
|
|
|
|
1148
|
jspc_interf = junkspc_interf.sum(axis = 0) / nhei_interf
|
|
1148
|
jspc_interf = junkspc_interf.sum(axis = 0) / nhei_interf
|
|
|
1149
|
jspc_interf = jspc_interf.transpose()
|
|
1149
|
jspc_interf = jspc_interf.transpose()
|
|
|
1150
|
#Calculando el espectro de interferencia promedio
|
|
1150
|
#Calculando el espectro de interferencia promedio
|
|
|
1151
|
noiseid = numpy.where(jspc_interf <= tmp_noise/ math.sqrt(num_incoh))
|
|
1151
|
noiseid = numpy.where(jspc_interf <= tmp_noise/ math.sqrt(num_incoh))
|
|
|
1152
|
noiseid = noiseid[0]
|
|
1152
|
noiseid = noiseid[0]
|
|
|
1153
|
cnoiseid = noiseid.size
|
|
1153
|
cnoiseid = noiseid.size
|
|
|
1154
|
interfid = numpy.where(jspc_interf > tmp_noise/ math.sqrt(num_incoh))
|
|
1154
|
interfid = numpy.where(jspc_interf > tmp_noise/ math.sqrt(num_incoh))
|
|
|
1155
|
interfid = interfid[0]
|
|
1155
|
interfid = interfid[0]
|
|
|
1156
|
cinterfid = interfid.size
|
|
1156
|
cinterfid = interfid.size
|
|
|
1157
|
|
|
1157
|
|
|
|
1158
|
if (cnoiseid > 0): jspc_interf[noiseid] = 0
|
|
1158
|
if (cnoiseid > 0): jspc_interf[noiseid] = 0
|
|
|
1159
|
|
|
1159
|
|
|
|
1160
|
#Expandiendo los perfiles a limpiar
|
|
1160
|
#Expandiendo los perfiles a limpiar
|
|
|
1161
|
if (cinterfid > 0):
|
|
1161
|
if (cinterfid > 0):
|
|
|
1162
|
new_interfid = (numpy.r_[interfid - 1, interfid, interfid + 1] + num_prof)%num_prof
|
|
1162
|
new_interfid = (numpy.r_[interfid - 1, interfid, interfid + 1] + num_prof)%num_prof
|
|
|
1163
|
new_interfid = numpy.asarray(new_interfid)
|
|
1163
|
new_interfid = numpy.asarray(new_interfid)
|
|
|
1164
|
new_interfid = {x for x in new_interfid}
|
|
1164
|
new_interfid = {x for x in new_interfid}
|
|
|
1165
|
new_interfid = numpy.array(list(new_interfid))
|
|
1165
|
new_interfid = numpy.array(list(new_interfid))
|
|
|
1166
|
new_cinterfid = new_interfid.size
|
|
1166
|
new_cinterfid = new_interfid.size
|
|
|
1167
|
else: new_cinterfid = 0
|
|
1167
|
else: new_cinterfid = 0
|
|
|
1168
|
|
|
1168
|
|
|
|
1169
|
for ip in range(new_cinterfid):
|
|
1169
|
for ip in range(new_cinterfid):
|
|
|
1170
|
ind = junkspc_interf[:,new_interfid[ip]].ravel().argsort()
|
|
1170
|
ind = junkspc_interf[:,new_interfid[ip]].ravel().argsort()
|
|
|
1171
|
jspc_interf[new_interfid[ip]] = junkspc_interf[ind[nhei_interf/2],new_interfid[ip]]
|
|
1171
|
jspc_interf[new_interfid[ip]] = junkspc_interf[ind[nhei_interf/2],new_interfid[ip]]
|
|
|
1172
|
|
|
1172
|
|
|
|
1173
|
|
|
1173
|
|
|
|
1174
|
jspectra[ich,:,ind_hei] = jspectra[ich,:,ind_hei] - jspc_interf #Corregir indices
|
|
1174
|
jspectra[ich,:,ind_hei] = jspectra[ich,:,ind_hei] - jspc_interf #Corregir indices
|
|
|
1175
|
|
|
1175
|
|
|
|
1176
|
#Removiendo la interferencia del punto de mayor interferencia
|
|
1176
|
#Removiendo la interferencia del punto de mayor interferencia
|
|
|
1177
|
ListAux = jspc_interf[mask_prof].tolist()
|
|
1177
|
ListAux = jspc_interf[mask_prof].tolist()
|
|
|
1178
|
maxid = ListAux.index(max(ListAux))
|
|
1178
|
maxid = ListAux.index(max(ListAux))
|
|
|
1179
|
|
|
1179
|
|
|
|
1180
|
|
|
1180
|
|
|
|
1181
|
if cinterfid > 0:
|
|
1181
|
if cinterfid > 0:
|
|
|
1182
|
for ip in range(cinterfid*(interf == 2) - 1):
|
|
1182
|
for ip in range(cinterfid*(interf == 2) - 1):
|
|
|
1183
|
ind = (jspectra[ich,interfid[ip],:] < tmp_noise*(1 + 1/math.sqrt(num_incoh))).nonzero()
|
|
1183
|
ind = (jspectra[ich,interfid[ip],:] < tmp_noise*(1 + 1/math.sqrt(num_incoh))).nonzero()
|
|
|
1184
|
cind = len(ind)
|
|
1184
|
cind = len(ind)
|
|
|
1185
|
|
|
1185
|
|
|
|
1186
|
if (cind > 0):
|
|
1186
|
if (cind > 0):
|
|
|
1187
|
jspectra[ich,interfid[ip],ind] = tmp_noise*(1 + (numpy.random.uniform(cind) - 0.5)/math.sqrt(num_incoh))
|
|
1187
|
jspectra[ich,interfid[ip],ind] = tmp_noise*(1 + (numpy.random.uniform(cind) - 0.5)/math.sqrt(num_incoh))
|
|
|
1188
|
|
|
1188
|
|
|
|
1189
|
ind = numpy.array([-2,-1,1,2])
|
|
1189
|
ind = numpy.array([-2,-1,1,2])
|
|
|
1190
|
xx = numpy.zeros([4,4])
|
|
1190
|
xx = numpy.zeros([4,4])
|
|
|
1191
|
|
|
1191
|
|
|
|
1192
|
for id1 in range(4):
|
|
1192
|
for id1 in range(4):
|
|
|
1193
|
xx[:,id1] = ind[id1]**numpy.asarray(range(4))
|
|
1193
|
xx[:,id1] = ind[id1]**numpy.asarray(range(4))
|
|
|
1194
|
|
|
1194
|
|
|
|
1195
|
xx_inv = numpy.linalg.inv(xx)
|
|
1195
|
xx_inv = numpy.linalg.inv(xx)
|
|
|
1196
|
xx = xx_inv[:,0]
|
|
1196
|
xx = xx_inv[:,0]
|
|
|
1197
|
ind = (ind + maxid + num_mask_prof)%num_mask_prof
|
|
1197
|
ind = (ind + maxid + num_mask_prof)%num_mask_prof
|
|
|
1198
|
yy = jspectra[ich,mask_prof[ind],:]
|
|
1198
|
yy = jspectra[ich,mask_prof[ind],:]
|
|
|
1199
|
jspectra[ich,mask_prof[maxid],:] = numpy.dot(yy.transpose(),xx)
|
|
1199
|
jspectra[ich,mask_prof[maxid],:] = numpy.dot(yy.transpose(),xx)
|
|
|
1200
|
|
|
1200
|
|
|
|
1201
|
|
|
1201
|
|
|
|
1202
|
indAux = (jspectra[ich,:,:] < tmp_noise*(1-1/math.sqrt(num_incoh))).nonzero()
|
|
1202
|
indAux = (jspectra[ich,:,:] < tmp_noise*(1-1/math.sqrt(num_incoh))).nonzero()
|
|
|
1203
|
jspectra[ich,indAux[0],indAux[1]] = tmp_noise * (1 - 1/math.sqrt(num_incoh))
|
|
1203
|
jspectra[ich,indAux[0],indAux[1]] = tmp_noise * (1 - 1/math.sqrt(num_incoh))
|
|
|
1204
|
|
|
1204
|
|
|
|
1205
|
#Remocion de Interferencia en el Cross Spectra
|
|
1205
|
#Remocion de Interferencia en el Cross Spectra
|
|
|
1206
|
if jcspectra == None: return jspectra, jcspectra
|
|
1206
|
if jcspectra == None: return jspectra, jcspectra
|
|
|
1207
|
num_pairs = jcspectra.size/(num_prof*num_hei)
|
|
1207
|
num_pairs = jcspectra.size/(num_prof*num_hei)
|
|
|
1208
|
jcspectra = jcspectra.reshape(num_pairs, num_prof, num_hei)
|
|
1208
|
jcspectra = jcspectra.reshape(num_pairs, num_prof, num_hei)
|
|
|
1209
|
|
|
1209
|
|
|
|
1210
|
for ip in range(num_pairs):
|
|
1210
|
for ip in range(num_pairs):
|
|
|
1211
|
|
|
1211
|
|
|
|
1212
|
#-------------------------------------------
|
|
1212
|
#-------------------------------------------
|
|
|
1213
|
|
|
1213
|
|
|
|
1214
|
cspower = numpy.abs(jcspectra[ip,mask_prof,:])
|
|
1214
|
cspower = numpy.abs(jcspectra[ip,mask_prof,:])
|
|
|
1215
|
cspower = cspower[:,hei_interf]
|
|
1215
|
cspower = cspower[:,hei_interf]
|
|
|
1216
|
cspower = cspower.sum(axis = 0)
|
|
1216
|
cspower = cspower.sum(axis = 0)
|
|
|
1217
|
|
|
1217
|
|
|
|
1218
|
cspsort = cspower.ravel().argsort()
|
|
1218
|
cspsort = cspower.ravel().argsort()
|
|
|
1219
|
junkcspc_interf = jcspectra[ip,:,hei_interf[cspsort[range(offhei_interf, nhei_interf + offhei_interf)]]]
|
|
1219
|
junkcspc_interf = jcspectra[ip,:,hei_interf[cspsort[range(offhei_interf, nhei_interf + offhei_interf)]]]
|
|
|
1220
|
junkcspc_interf = junkcspc_interf.transpose()
|
|
1220
|
junkcspc_interf = junkcspc_interf.transpose()
|
|
|
1221
|
jcspc_interf = junkcspc_interf.sum(axis = 1)/nhei_interf
|
|
1221
|
jcspc_interf = junkcspc_interf.sum(axis = 1)/nhei_interf
|
|
|
1222
|
|
|
1222
|
|
|
|
1223
|
ind = numpy.abs(jcspc_interf[mask_prof]).ravel().argsort()
|
|
1223
|
ind = numpy.abs(jcspc_interf[mask_prof]).ravel().argsort()
|
|
|
1224
|
|
|
1224
|
|
|
|
1225
|
median_real = numpy.median(numpy.real(junkcspc_interf[mask_prof[ind[range(3*num_prof/4)]],:]))
|
|
1225
|
median_real = numpy.median(numpy.real(junkcspc_interf[mask_prof[ind[range(3*num_prof/4)]],:]))
|
|
|
1226
|
median_imag = numpy.median(numpy.imag(junkcspc_interf[mask_prof[ind[range(3*num_prof/4)]],:]))
|
|
1226
|
median_imag = numpy.median(numpy.imag(junkcspc_interf[mask_prof[ind[range(3*num_prof/4)]],:]))
|
|
|
1227
|
junkcspc_interf[comp_mask_prof,:] = numpy.complex(median_real, median_imag)
|
|
1227
|
junkcspc_interf[comp_mask_prof,:] = numpy.complex(median_real, median_imag)
|
|
|
1228
|
|
|
1228
|
|
|
|
1229
|
for iprof in range(num_prof):
|
|
1229
|
for iprof in range(num_prof):
|
|
|
1230
|
ind = numpy.abs(junkcspc_interf[iprof,:]).ravel().argsort()
|
|
1230
|
ind = numpy.abs(junkcspc_interf[iprof,:]).ravel().argsort()
|
|
|
1231
|
jcspc_interf[iprof] = junkcspc_interf[iprof, ind[nhei_interf/2]]
|
|
1231
|
jcspc_interf[iprof] = junkcspc_interf[iprof, ind[nhei_interf/2]]
|
|
|
1232
|
|
|
1232
|
|
|
|
1233
|
#Removiendo la Interferencia
|
|
1233
|
#Removiendo la Interferencia
|
|
|
1234
|
jcspectra[ip,:,ind_hei] = jcspectra[ip,:,ind_hei] - jcspc_interf
|
|
1234
|
jcspectra[ip,:,ind_hei] = jcspectra[ip,:,ind_hei] - jcspc_interf
|
|
|
1235
|
|
|
1235
|
|
|
|
1236
|
ListAux = numpy.abs(jcspc_interf[mask_prof]).tolist()
|
|
1236
|
ListAux = numpy.abs(jcspc_interf[mask_prof]).tolist()
|
|
|
1237
|
maxid = ListAux.index(max(ListAux))
|
|
1237
|
maxid = ListAux.index(max(ListAux))
|
|
|
1238
|
|
|
1238
|
|
|
|
1239
|
ind = numpy.array([-2,-1,1,2])
|
|
1239
|
ind = numpy.array([-2,-1,1,2])
|
|
|
1240
|
xx = numpy.zeros([4,4])
|
|
1240
|
xx = numpy.zeros([4,4])
|
|
|
1241
|
|
|
1241
|
|
|
|
1242
|
for id1 in range(4):
|
|
1242
|
for id1 in range(4):
|
|
|
1243
|
xx[:,id1] = ind[id1]**numpy.asarray(range(4))
|
|
1243
|
xx[:,id1] = ind[id1]**numpy.asarray(range(4))
|
|
|
1244
|
|
|
1244
|
|
|
|
1245
|
xx_inv = numpy.linalg.inv(xx)
|
|
1245
|
xx_inv = numpy.linalg.inv(xx)
|
|
|
1246
|
xx = xx_inv[:,0]
|
|
1246
|
xx = xx_inv[:,0]
|
|
|
1247
|
|
|
1247
|
|
|
|
1248
|
ind = (ind + maxid + num_mask_prof)%num_mask_prof
|
|
1248
|
ind = (ind + maxid + num_mask_prof)%num_mask_prof
|
|
|
1249
|
yy = jcspectra[ip,mask_prof[ind],:]
|
|
1249
|
yy = jcspectra[ip,mask_prof[ind],:]
|
|
|
1250
|
jcspectra[ip,mask_prof[maxid],:] = numpy.dot(yy.transpose(),xx)
|
|
1250
|
jcspectra[ip,mask_prof[maxid],:] = numpy.dot(yy.transpose(),xx)
|
|
|
1251
|
|
|
1251
|
|
|
|
1252
|
#Guardar Resultados
|
|
1252
|
#Guardar Resultados
|
|
|
1253
|
self.dataOut.data_spc = jspectra
|
|
1253
|
self.dataOut.data_spc = jspectra
|
|
|
1254
|
self.dataOut.data_cspc = jcspectra
|
|
1254
|
self.dataOut.data_cspc = jcspectra
|
|
|
1255
|
|
|
1255
|
|
|
|
1256
|
return 1
|
|
1256
|
return 1
|
|
|
1257
|
|
|
1257
|
|
|
|
1258
|
def setRadarFrequency(self, frequency=None):
|
|
1258
|
def setRadarFrequency(self, frequency=None):
|
|
|
1259
|
if frequency != None:
|
|
1259
|
if frequency != None:
|
|
|
1260
|
self.dataOut.frequency = frequency
|
|
1260
|
self.dataOut.frequency = frequency
|
|
|
1261
|
|
|
1261
|
|
|
|
1262
|
return 1
|
|
1262
|
return 1
|
|
|
1263
|
|
|
1263
|
|
|
|
1264
|
def getNoise(self, minHei=None, maxHei=None, minVel=None, maxVel=None):
|
|
1264
|
def getNoise(self, minHei=None, maxHei=None, minVel=None, maxVel=None):
|
|
|
1265
|
#validacion de rango
|
|
1265
|
#validacion de rango
|
|
|
1266
|
if minHei == None:
|
|
1266
|
if minHei == None:
|
|
|
1267
|
minHei = self.dataOut.heightList[0]
|
|
1267
|
minHei = self.dataOut.heightList[0]
|
|
|
1268
|
|
|
1268
|
|
|
|
1269
|
if maxHei == None:
|
|
1269
|
if maxHei == None:
|
|
|
1270
|
maxHei = self.dataOut.heightList[-1]
|
|
1270
|
maxHei = self.dataOut.heightList[-1]
|
|
|
1271
|
|
|
1271
|
|
|
|
1272
|
if (minHei < self.dataOut.heightList[0]) or (minHei > maxHei):
|
|
1272
|
if (minHei < self.dataOut.heightList[0]) or (minHei > maxHei):
|
|
|
1273
|
print 'minHei: %.2f is out of the heights range'%(minHei)
|
|
1273
|
print 'minHei: %.2f is out of the heights range'%(minHei)
|
|
|
1274
|
print 'minHei is setting to %.2f'%(self.dataOut.heightList[0])
|
|
1274
|
print 'minHei is setting to %.2f'%(self.dataOut.heightList[0])
|
|
|
1275
|
minHei = self.dataOut.heightList[0]
|
|
1275
|
minHei = self.dataOut.heightList[0]
|
|
|
1276
|
|
|
1276
|
|
|
|
1277
|
if (maxHei > self.dataOut.heightList[-1]) or (maxHei < minHei):
|
|
1277
|
if (maxHei > self.dataOut.heightList[-1]) or (maxHei < minHei):
|
|
|
1278
|
print 'maxHei: %.2f is out of the heights range'%(maxHei)
|
|
1278
|
print 'maxHei: %.2f is out of the heights range'%(maxHei)
|
|
|
1279
|
print 'maxHei is setting to %.2f'%(self.dataOut.heightList[-1])
|
|
1279
|
print 'maxHei is setting to %.2f'%(self.dataOut.heightList[-1])
|
|
|
1280
|
maxHei = self.dataOut.heightList[-1]
|
|
1280
|
maxHei = self.dataOut.heightList[-1]
|
|
|
1281
|
|
|
1281
|
|
|
|
1282
|
# validacion de velocidades
|
|
1282
|
# validacion de velocidades
|
|
|
1283
|
velrange = self.dataOut.getVelRange(1)
|
|
1283
|
velrange = self.dataOut.getVelRange(1)
|
|
|
1284
|
|
|
1284
|
|
|
|
1285
|
if minVel == None:
|
|
1285
|
if minVel == None:
|
|
|
1286
|
minVel = velrange[0]
|
|
1286
|
minVel = velrange[0]
|
|
|
1287
|
|
|
1287
|
|
|
|
1288
|
if maxVel == None:
|
|
1288
|
if maxVel == None:
|
|
|
1289
|
maxVel = velrange[-1]
|
|
1289
|
maxVel = velrange[-1]
|
|
|
1290
|
|
|
1290
|
|
|
|
1291
|
if (minVel < velrange[0]) or (minVel > maxVel):
|
|
1291
|
if (minVel < velrange[0]) or (minVel > maxVel):
|
|
|
1292
|
print 'minVel: %.2f is out of the velocity range'%(minVel)
|
|
1292
|
print 'minVel: %.2f is out of the velocity range'%(minVel)
|
|
|
1293
|
print 'minVel is setting to %.2f'%(velrange[0])
|
|
1293
|
print 'minVel is setting to %.2f'%(velrange[0])
|
|
|
1294
|
minVel = velrange[0]
|
|
1294
|
minVel = velrange[0]
|
|
|
1295
|
|
|
1295
|
|
|
|
1296
|
if (maxVel > velrange[-1]) or (maxVel < minVel):
|
|
1296
|
if (maxVel > velrange[-1]) or (maxVel < minVel):
|
|
|
1297
|
print 'maxVel: %.2f is out of the velocity range'%(maxVel)
|
|
1297
|
print 'maxVel: %.2f is out of the velocity range'%(maxVel)
|
|
|
1298
|
print 'maxVel is setting to %.2f'%(velrange[-1])
|
|
1298
|
print 'maxVel is setting to %.2f'%(velrange[-1])
|
|
|
1299
|
maxVel = velrange[-1]
|
|
1299
|
maxVel = velrange[-1]
|
|
|
1300
|
|
|
1300
|
|
|
|
1301
|
# seleccion de indices para rango
|
|
1301
|
# seleccion de indices para rango
|
|
|
1302
|
minIndex = 0
|
|
1302
|
minIndex = 0
|
|
|
1303
|
maxIndex = 0
|
|
1303
|
maxIndex = 0
|
|
|
1304
|
heights = self.dataOut.heightList
|
|
1304
|
heights = self.dataOut.heightList
|
|
|
1305
|
|
|
1305
|
|
|
|
1306
|
inda = numpy.where(heights >= minHei)
|
|
1306
|
inda = numpy.where(heights >= minHei)
|
|
|
1307
|
indb = numpy.where(heights <= maxHei)
|
|
1307
|
indb = numpy.where(heights <= maxHei)
|
|
|
1308
|
|
|
1308
|
|
|
|
1309
|
try:
|
|
1309
|
try:
|
|
|
1310
|
minIndex = inda[0][0]
|
|
1310
|
minIndex = inda[0][0]
|
|
|
1311
|
except:
|
|
1311
|
except:
|
|
|
1312
|
minIndex = 0
|
|
1312
|
minIndex = 0
|
|
|
1313
|
|
|
1313
|
|
|
|
1314
|
try:
|
|
1314
|
try:
|
|
|
1315
|
maxIndex = indb[0][-1]
|
|
1315
|
maxIndex = indb[0][-1]
|
|
|
1316
|
except:
|
|
1316
|
except:
|
|
|
1317
|
maxIndex = len(heights)
|
|
1317
|
maxIndex = len(heights)
|
|
|
1318
|
|
|
1318
|
|
|
|
1319
|
if (minIndex < 0) or (minIndex > maxIndex):
|
|
1319
|
if (minIndex < 0) or (minIndex > maxIndex):
|
|
|
1320
|
raise ValueError, "some value in (%d,%d) is not valid" % (minIndex, maxIndex)
|
|
1320
|
raise ValueError, "some value in (%d,%d) is not valid" % (minIndex, maxIndex)
|
|
|
1321
|
|
|
1321
|
|
|
|
1322
|
if (maxIndex >= self.dataOut.nHeights):
|
|
1322
|
if (maxIndex >= self.dataOut.nHeights):
|
|
|
1323
|
maxIndex = self.dataOut.nHeights-1
|
|
1323
|
maxIndex = self.dataOut.nHeights-1
|
|
|
1324
|
|
|
1324
|
|
|
|
1325
|
# seleccion de indices para velocidades
|
|
1325
|
# seleccion de indices para velocidades
|
|
|
1326
|
indminvel = numpy.where(velrange >= minVel)
|
|
1326
|
indminvel = numpy.where(velrange >= minVel)
|
|
|
1327
|
indmaxvel = numpy.where(velrange <= maxVel)
|
|
1327
|
indmaxvel = numpy.where(velrange <= maxVel)
|
|
|
1328
|
try:
|
|
1328
|
try:
|
|
|
1329
|
minIndexVel = indminvel[0][0]
|
|
1329
|
minIndexVel = indminvel[0][0]
|
|
|
1330
|
except:
|
|
1330
|
except:
|
|
|
1331
|
minIndexVel = 0
|
|
1331
|
minIndexVel = 0
|
|
|
1332
|
|
|
1332
|
|
|
|
1333
|
try:
|
|
1333
|
try:
|
|
|
1334
|
maxIndexVel = indmaxvel[0][-1]
|
|
1334
|
maxIndexVel = indmaxvel[0][-1]
|
|
|
1335
|
except:
|
|
1335
|
except:
|
|
|
1336
|
maxIndexVel = len(velrange)
|
|
1336
|
maxIndexVel = len(velrange)
|
|
|
1337
|
|
|
1337
|
|
|
|
1338
|
#seleccion del espectro
|
|
1338
|
#seleccion del espectro
|
|
|
1339
|
data_spc = self.dataOut.data_spc[:,minIndexVel:maxIndexVel+1,minIndex:maxIndex+1]
|
|
1339
|
data_spc = self.dataOut.data_spc[:,minIndexVel:maxIndexVel+1,minIndex:maxIndex+1]
|
|
|
1340
|
#estimacion de ruido
|
|
1340
|
#estimacion de ruido
|
|
|
1341
|
noise = numpy.zeros(self.dataOut.nChannels)
|
|
1341
|
noise = numpy.zeros(self.dataOut.nChannels)
|
|
|
1342
|
|
|
1342
|
|
|
|
1343
|
for channel in range(self.dataOut.nChannels):
|
|
1343
|
for channel in range(self.dataOut.nChannels):
|
|
|
1344
|
daux = data_spc[channel,:,:]
|
|
1344
|
daux = data_spc[channel,:,:]
|
|
|
1345
|
noise[channel] = hildebrand_sekhon(daux, self.dataOut.nIncohInt)
|
|
1345
|
noise[channel] = hildebrand_sekhon(daux, self.dataOut.nIncohInt)
|
|
|
1346
|
|
|
1346
|
|
|
|
1347
|
self.dataOut.noise = noise.copy()
|
|
1347
|
self.dataOut.noise = noise.copy()
|
|
|
1348
|
|
|
1348
|
|
|
|
1349
|
return 1
|
|
1349
|
return 1
|
|
|
1350
|
|
|
1350
|
|
|
|
1351
|
|
|
1351
|
|
|
|
1352
|
class IncohInt(Operation):
|
|
1352
|
class IncohInt(Operation):
|
|
|
1353
|
|
|
1353
|
|
|
|
1354
|
|
|
1354
|
|
|
|
1355
|
__profIndex = 0
|
|
1355
|
__profIndex = 0
|
|
|
1356
|
__withOverapping = False
|
|
1356
|
__withOverapping = False
|
|
|
1357
|
|
|
1357
|
|
|
|
1358
|
__byTime = False
|
|
1358
|
__byTime = False
|
|
|
1359
|
__initime = None
|
|
1359
|
__initime = None
|
|
|
1360
|
__lastdatatime = None
|
|
1360
|
__lastdatatime = None
|
|
|
1361
|
__integrationtime = None
|
|
1361
|
__integrationtime = None
|
|
|
1362
|
|
|
1362
|
|
|
|
1363
|
__buffer_spc = None
|
|
1363
|
__buffer_spc = None
|
|
|
1364
|
__buffer_cspc = None
|
|
1364
|
__buffer_cspc = None
|
|
|
1365
|
__buffer_dc = None
|
|
1365
|
__buffer_dc = None
|
|
|
1366
|
|
|
1366
|
|
|
|
1367
|
__dataReady = False
|
|
1367
|
__dataReady = False
|
|
|
1368
|
|
|
1368
|
|
|
|
1369
|
__timeInterval = None
|
|
1369
|
__timeInterval = None
|
|
|
1370
|
|
|
1370
|
|
|
|
1371
|
n = None
|
|
1371
|
n = None
|
|
|
1372
|
|
|
1372
|
|
|
|
1373
|
|
|
1373
|
|
|
|
1374
|
|
|
1374
|
|
|
|
1375
|
def __init__(self):
|
|
1375
|
def __init__(self):
|
|
|
1376
|
|
|
1376
|
|
|
|
1377
|
self.__isConfig = False
|
|
1377
|
self.__isConfig = False
|
|
|
1378
|
|
|
1378
|
|
|
|
1379
|
def setup(self, n=None, timeInterval=None, overlapping=False):
|
|
1379
|
def setup(self, n=None, timeInterval=None, overlapping=False):
|
|
|
1380
|
"""
|
|
1380
|
"""
|
|
|
1381
|
Set the parameters of the integration class.
|
|
1381
|
Set the parameters of the integration class.
|
|
|
1382
|
|
|
1382
|
|
|
|
1383
|
Inputs:
|
|
1383
|
Inputs:
|
|
|
1384
|
|
|
1384
|
|
|
|
1385
|
n : Number of coherent integrations
|
|
1385
|
n : Number of coherent integrations
|
|
|
1386
|
timeInterval : Time of integration. If the parameter "n" is selected this one does not work
|
|
1386
|
timeInterval : Time of integration. If the parameter "n" is selected this one does not work
|
|
|
1387
|
overlapping :
|
|
1387
|
overlapping :
|
|
|
1388
|
|
|
1388
|
|
|
|
1389
|
"""
|
|
1389
|
"""
|
|
|
1390
|
|
|
1390
|
|
|
|
1391
|
self.__initime = None
|
|
1391
|
self.__initime = None
|
|
|
1392
|
self.__lastdatatime = 0
|
|
1392
|
self.__lastdatatime = 0
|
|
|
1393
|
self.__buffer_spc = None
|
|
1393
|
self.__buffer_spc = None
|
|
|
1394
|
self.__buffer_cspc = None
|
|
1394
|
self.__buffer_cspc = None
|
|
|
1395
|
self.__buffer_dc = None
|
|
1395
|
self.__buffer_dc = None
|
|
|
1396
|
self.__dataReady = False
|
|
1396
|
self.__dataReady = False
|
|
|
1397
|
|
|
1397
|
|
|
|
1398
|
|
|
1398
|
|
|
|
1399
|
if n == None and timeInterval == None:
|
|
1399
|
if n == None and timeInterval == None:
|
|
|
1400
|
raise ValueError, "n or timeInterval should be specified ..."
|
|
1400
|
raise ValueError, "n or timeInterval should be specified ..."
|
|
|
1401
|
|
|
1401
|
|
|
|
1402
|
if n != None:
|
|
1402
|
if n != None:
|
|
|
1403
|
self.n = n
|
|
1403
|
self.n = n
|
|
|
1404
|
self.__byTime = False
|
|
1404
|
self.__byTime = False
|
|
|
1405
|
else:
|
|
1405
|
else:
|
|
|
1406
|
self.__integrationtime = timeInterval #if (type(timeInterval)!=integer) -> change this line
|
|
1406
|
self.__integrationtime = timeInterval #if (type(timeInterval)!=integer) -> change this line
|
|
|
1407
|
self.n = 9999
|
|
1407
|
self.n = 9999
|
|
|
1408
|
self.__byTime = True
|
|
1408
|
self.__byTime = True
|
|
|
1409
|
|
|
1409
|
|
|
|
1410
|
if overlapping:
|
|
1410
|
if overlapping:
|
|
|
1411
|
self.__withOverapping = True
|
|
1411
|
self.__withOverapping = True
|
|
|
1412
|
else:
|
|
1412
|
else:
|
|
|
1413
|
self.__withOverapping = False
|
|
1413
|
self.__withOverapping = False
|
|
|
1414
|
self.__buffer_spc = 0
|
|
1414
|
self.__buffer_spc = 0
|
|
|
1415
|
self.__buffer_cspc = 0
|
|
1415
|
self.__buffer_cspc = 0
|
|
|
1416
|
self.__buffer_dc = 0
|
|
1416
|
self.__buffer_dc = 0
|
|
|
1417
|
|
|
1417
|
|
|
|
1418
|
self.__profIndex = 0
|
|
1418
|
self.__profIndex = 0
|
|
|
1419
|
|
|
1419
|
|
|
|
1420
|
def putData(self, data_spc, data_cspc, data_dc):
|
|
1420
|
def putData(self, data_spc, data_cspc, data_dc):
|
|
|
1421
|
|
|
1421
|
|
|
|
1422
|
"""
|
|
1422
|
"""
|
|
|
1423
|
Add a profile to the __buffer_spc and increase in one the __profileIndex
|
|
1423
|
Add a profile to the __buffer_spc and increase in one the __profileIndex
|
|
|
1424
|
|
|
1424
|
|
|
|
1425
|
"""
|
|
1425
|
"""
|
|
|
1426
|
|
|
1426
|
|
|
|
1427
|
if not self.__withOverapping:
|
|
1427
|
if not self.__withOverapping:
|
|
|
1428
|
self.__buffer_spc += data_spc
|
|
1428
|
self.__buffer_spc += data_spc
|
|
|
1429
|
|
|
1429
|
|
|
|
1430
|
if data_cspc == None:
|
|
1430
|
if data_cspc == None:
|
|
|
1431
|
self.__buffer_cspc = None
|
|
1431
|
self.__buffer_cspc = None
|
|
|
1432
|
else:
|
|
1432
|
else:
|
|
|
1433
|
self.__buffer_cspc += data_cspc
|
|
1433
|
self.__buffer_cspc += data_cspc
|
|
|
1434
|
|
|
1434
|
|
|
|
1435
|
if data_dc == None:
|
|
1435
|
if data_dc == None:
|
|
|
1436
|
self.__buffer_dc = None
|
|
1436
|
self.__buffer_dc = None
|
|
|
1437
|
else:
|
|
1437
|
else:
|
|
|
1438
|
self.__buffer_dc += data_dc
|
|
1438
|
self.__buffer_dc += data_dc
|
|
|
1439
|
|
|
1439
|
|
|
|
1440
|
self.__profIndex += 1
|
|
1440
|
self.__profIndex += 1
|
|
|
1441
|
return
|
|
1441
|
return
|
|
|
1442
|
|
|
1442
|
|
|
|
1443
|
#Overlapping data
|
|
1443
|
#Overlapping data
|
|
|
1444
|
nChannels, nFFTPoints, nHeis = data_spc.shape
|
|
1444
|
nChannels, nFFTPoints, nHeis = data_spc.shape
|
|
|
1445
|
data_spc = numpy.reshape(data_spc, (1, nChannels, nFFTPoints, nHeis))
|
|
1445
|
data_spc = numpy.reshape(data_spc, (1, nChannels, nFFTPoints, nHeis))
|
|
|
1446
|
if data_cspc != None:
|
|
1446
|
if data_cspc != None:
|
|
|
1447
|
data_cspc = numpy.reshape(data_cspc, (1, -1, nFFTPoints, nHeis))
|
|
1447
|
data_cspc = numpy.reshape(data_cspc, (1, -1, nFFTPoints, nHeis))
|
|
|
1448
|
if data_dc != None:
|
|
1448
|
if data_dc != None:
|
|
|
1449
|
data_dc = numpy.reshape(data_dc, (1, -1, nHeis))
|
|
1449
|
data_dc = numpy.reshape(data_dc, (1, -1, nHeis))
|
|
|
1450
|
|
|
1450
|
|
|
|
1451
|
#If the buffer is empty then it takes the data value
|
|
1451
|
#If the buffer is empty then it takes the data value
|
|
|
1452
|
if self.__buffer_spc == None:
|
|
1452
|
if self.__buffer_spc == None:
|
|
|
1453
|
self.__buffer_spc = data_spc
|
|
1453
|
self.__buffer_spc = data_spc
|
|
|
1454
|
|
|
1454
|
|
|
|
1455
|
if data_cspc == None:
|
|
1455
|
if data_cspc == None:
|
|
|
1456
|
self.__buffer_cspc = None
|
|
1456
|
self.__buffer_cspc = None
|
|
|
1457
|
else:
|
|
1457
|
else:
|
|
|
1458
|
self.__buffer_cspc += data_cspc
|
|
1458
|
self.__buffer_cspc += data_cspc
|
|
|
1459
|
|
|
1459
|
|
|
|
1460
|
if data_dc == None:
|
|
1460
|
if data_dc == None:
|
|
|
1461
|
self.__buffer_dc = None
|
|
1461
|
self.__buffer_dc = None
|
|
|
1462
|
else:
|
|
1462
|
else:
|
|
|
1463
|
self.__buffer_dc += data_dc
|
|
1463
|
self.__buffer_dc += data_dc
|
|
|
1464
|
|
|
1464
|
|
|
|
1465
|
self.__profIndex += 1
|
|
1465
|
self.__profIndex += 1
|
|
|
1466
|
return
|
|
1466
|
return
|
|
|
1467
|
|
|
1467
|
|
|
|
1468
|
#If the buffer length is lower than n then stakcing the data value
|
|
1468
|
#If the buffer length is lower than n then stakcing the data value
|
|
|
1469
|
if self.__profIndex < self.n:
|
|
1469
|
if self.__profIndex < self.n:
|
|
|
1470
|
self.__buffer_spc = numpy.vstack((self.__buffer_spc, data_spc))
|
|
1470
|
self.__buffer_spc = numpy.vstack((self.__buffer_spc, data_spc))
|
|
|
1471
|
|
|
1471
|
|
|
|
1472
|
if data_cspc != None:
|
|
1472
|
if data_cspc != None:
|
|
|
1473
|
self.__buffer_cspc = numpy.vstack((self.__buffer_cspc, data_cspc))
|
|
1473
|
self.__buffer_cspc = numpy.vstack((self.__buffer_cspc, data_cspc))
|
|
|
1474
|
|
|
1474
|
|
|
|
1475
|
if data_dc != None:
|
|
1475
|
if data_dc != None:
|
|
|
1476
|
self.__buffer_dc = numpy.vstack((self.__buffer_dc, data_dc))
|
|
1476
|
self.__buffer_dc = numpy.vstack((self.__buffer_dc, data_dc))
|
|
|
1477
|
|
|
1477
|
|
|
|
1478
|
self.__profIndex += 1
|
|
1478
|
self.__profIndex += 1
|
|
|
1479
|
return
|
|
1479
|
return
|
|
|
1480
|
|
|
1480
|
|
|
|
1481
|
#If the buffer length is equal to n then replacing the last buffer value with the data value
|
|
1481
|
#If the buffer length is equal to n then replacing the last buffer value with the data value
|
|
|
1482
|
self.__buffer_spc = numpy.roll(self.__buffer_spc, -1, axis=0)
|
|
1482
|
self.__buffer_spc = numpy.roll(self.__buffer_spc, -1, axis=0)
|
|
|
1483
|
self.__buffer_spc[self.n-1] = data_spc
|
|
1483
|
self.__buffer_spc[self.n-1] = data_spc
|
|
|
1484
|
|
|
1484
|
|
|
|
1485
|
if data_cspc != None:
|
|
1485
|
if data_cspc != None:
|
|
|
1486
|
self.__buffer_cspc = numpy.roll(self.__buffer_cspc, -1, axis=0)
|
|
1486
|
self.__buffer_cspc = numpy.roll(self.__buffer_cspc, -1, axis=0)
|
|
|
1487
|
self.__buffer_cspc[self.n-1] = data_cspc
|
|
1487
|
self.__buffer_cspc[self.n-1] = data_cspc
|
|
|
1488
|
|
|
1488
|
|
|
|
1489
|
if data_dc != None:
|
|
1489
|
if data_dc != None:
|
|
|
1490
|
self.__buffer_dc = numpy.roll(self.__buffer_dc, -1, axis=0)
|
|
1490
|
self.__buffer_dc = numpy.roll(self.__buffer_dc, -1, axis=0)
|
|
|
1491
|
self.__buffer_dc[self.n-1] = data_dc
|
|
1491
|
self.__buffer_dc[self.n-1] = data_dc
|
|
|
1492
|
|
|
1492
|
|
|
|
1493
|
self.__profIndex = self.n
|
|
1493
|
self.__profIndex = self.n
|
|
|
1494
|
return
|
|
1494
|
return
|
|
|
1495
|
|
|
1495
|
|
|
|
1496
|
|
|
1496
|
|
|
|
1497
|
def pushData(self):
|
|
1497
|
def pushData(self):
|
|
|
1498
|
"""
|
|
1498
|
"""
|
|
|
1499
|
Return the sum of the last profiles and the profiles used in the sum.
|
|
1499
|
Return the sum of the last profiles and the profiles used in the sum.
|
|
|
1500
|
|
|
1500
|
|
|
|
1501
|
Affected:
|
|
1501
|
Affected:
|
|
|
1502
|
|
|
1502
|
|
|
|
1503
|
self.__profileIndex
|
|
1503
|
self.__profileIndex
|
|
|
1504
|
|
|
1504
|
|
|
|
1505
|
"""
|
|
1505
|
"""
|
|
|
1506
|
data_spc = None
|
|
1506
|
data_spc = None
|
|
|
1507
|
data_cspc = None
|
|
1507
|
data_cspc = None
|
|
|
1508
|
data_dc = None
|
|
1508
|
data_dc = None
|
|
|
1509
|
|
|
1509
|
|
|
|
1510
|
if not self.__withOverapping:
|
|
1510
|
if not self.__withOverapping:
|
|
|
1511
|
data_spc = self.__buffer_spc
|
|
1511
|
data_spc = self.__buffer_spc
|
|
|
1512
|
data_cspc = self.__buffer_cspc
|
|
1512
|
data_cspc = self.__buffer_cspc
|
|
|
1513
|
data_dc = self.__buffer_dc
|
|
1513
|
data_dc = self.__buffer_dc
|
|
|
1514
|
|
|
1514
|
|
|
|
1515
|
n = self.__profIndex
|
|
1515
|
n = self.__profIndex
|
|
|
1516
|
|
|
1516
|
|
|
|
1517
|
self.__buffer_spc = 0
|
|
1517
|
self.__buffer_spc = 0
|
|
|
1518
|
self.__buffer_cspc = 0
|
|
1518
|
self.__buffer_cspc = 0
|
|
|
1519
|
self.__buffer_dc = 0
|
|
1519
|
self.__buffer_dc = 0
|
|
|
1520
|
self.__profIndex = 0
|
|
1520
|
self.__profIndex = 0
|
|
|
1521
|
|
|
1521
|
|
|
|
1522
|
return data_spc, data_cspc, data_dc, n
|
|
1522
|
return data_spc, data_cspc, data_dc, n
|
|
|
1523
|
|
|
1523
|
|
|
|
1524
|
#Integration with Overlapping
|
|
1524
|
#Integration with Overlapping
|
|
|
1525
|
data_spc = numpy.sum(self.__buffer_spc, axis=0)
|
|
1525
|
data_spc = numpy.sum(self.__buffer_spc, axis=0)
|
|
|
1526
|
|
|
1526
|
|
|
|
1527
|
if self.__buffer_cspc != None:
|
|
1527
|
if self.__buffer_cspc != None:
|
|
|
1528
|
data_cspc = numpy.sum(self.__buffer_cspc, axis=0)
|
|
1528
|
data_cspc = numpy.sum(self.__buffer_cspc, axis=0)
|
|
|
1529
|
|
|
1529
|
|
|
|
1530
|
if self.__buffer_dc != None:
|
|
1530
|
if self.__buffer_dc != None:
|
|
|
1531
|
data_dc = numpy.sum(self.__buffer_dc, axis=0)
|
|
1531
|
data_dc = numpy.sum(self.__buffer_dc, axis=0)
|
|
|
1532
|
|
|
1532
|
|
|
|
1533
|
n = self.__profIndex
|
|
1533
|
n = self.__profIndex
|
|
|
1534
|
|
|
1534
|
|
|
|
1535
|
return data_spc, data_cspc, data_dc, n
|
|
1535
|
return data_spc, data_cspc, data_dc, n
|
|
|
1536
|
|
|
1536
|
|
|
|
1537
|
def byProfiles(self, *args):
|
|
1537
|
def byProfiles(self, *args):
|
|
|
1538
|
|
|
1538
|
|
|
|
1539
|
self.__dataReady = False
|
|
1539
|
self.__dataReady = False
|
|
|
1540
|
avgdata_spc = None
|
|
1540
|
avgdata_spc = None
|
|
|
1541
|
avgdata_cspc = None
|
|
1541
|
avgdata_cspc = None
|
|
|
1542
|
avgdata_dc = None
|
|
1542
|
avgdata_dc = None
|
|
|
1543
|
n = None
|
|
1543
|
n = None
|
|
|
1544
|
|
|
1544
|
|
|
|
1545
|
self.putData(*args)
|
|
1545
|
self.putData(*args)
|
|
|
1546
|
|
|
1546
|
|
|
|
1547
|
if self.__profIndex == self.n:
|
|
1547
|
if self.__profIndex == self.n:
|
|
|
1548
|
|
|
1548
|
|
|
|
1549
|
avgdata_spc, avgdata_cspc, avgdata_dc, n = self.pushData()
|
|
1549
|
avgdata_spc, avgdata_cspc, avgdata_dc, n = self.pushData()
|
|
|
1550
|
self.__dataReady = True
|
|
1550
|
self.__dataReady = True
|
|
|
1551
|
|
|
1551
|
|
|
|
1552
|
return avgdata_spc, avgdata_cspc, avgdata_dc
|
|
1552
|
return avgdata_spc, avgdata_cspc, avgdata_dc
|
|
|
1553
|
|
|
1553
|
|
|
|
1554
|
def byTime(self, datatime, *args):
|
|
1554
|
def byTime(self, datatime, *args):
|
|
|
1555
|
|
|
1555
|
|
|
|
1556
|
self.__dataReady = False
|
|
1556
|
self.__dataReady = False
|
|
|
1557
|
avgdata_spc = None
|
|
1557
|
avgdata_spc = None
|
|
|
1558
|
avgdata_cspc = None
|
|
1558
|
avgdata_cspc = None
|
|
|
1559
|
avgdata_dc = None
|
|
1559
|
avgdata_dc = None
|
|
|
1560
|
n = None
|
|
1560
|
n = None
|
|
|
1561
|
|
|
1561
|
|
|
|
1562
|
self.putData(*args)
|
|
1562
|
self.putData(*args)
|
|
|
1563
|
|
|
1563
|
|
|
|
1564
|
if (datatime - self.__initime) >= self.__integrationtime:
|
|
1564
|
if (datatime - self.__initime) >= self.__integrationtime:
|
|
|
1565
|
avgdata_spc, avgdata_cspc, avgdata_dc, n = self.pushData()
|
|
1565
|
avgdata_spc, avgdata_cspc, avgdata_dc, n = self.pushData()
|
|
|
1566
|
self.n = n
|
|
1566
|
self.n = n
|
|
|
1567
|
self.__dataReady = True
|
|
1567
|
self.__dataReady = True
|
|
|
1568
|
|
|
1568
|
|
|
|
1569
|
return avgdata_spc, avgdata_cspc, avgdata_dc
|
|
1569
|
return avgdata_spc, avgdata_cspc, avgdata_dc
|
|
|
1570
|
|
|
1570
|
|
|
|
1571
|
def integrate(self, datatime, *args):
|
|
1571
|
def integrate(self, datatime, *args):
|
|
|
1572
|
|
|
1572
|
|
|
|
1573
|
if self.__initime == None:
|
|
1573
|
if self.__initime == None:
|
|
|
1574
|
self.__initime = datatime
|
|
1574
|
self.__initime = datatime
|
|
|
1575
|
|
|
1575
|
|
|
|
1576
|
if self.__byTime:
|
|
1576
|
if self.__byTime:
|
|
|
1577
|
avgdata_spc, avgdata_cspc, avgdata_dc = self.byTime(datatime, *args)
|
|
1577
|
avgdata_spc, avgdata_cspc, avgdata_dc = self.byTime(datatime, *args)
|
|
|
1578
|
else:
|
|
1578
|
else:
|
|
|
1579
|
avgdata_spc, avgdata_cspc, avgdata_dc = self.byProfiles(*args)
|
|
1579
|
avgdata_spc, avgdata_cspc, avgdata_dc = self.byProfiles(*args)
|
|
|
1580
|
|
|
1580
|
|
|
|
1581
|
self.__lastdatatime = datatime
|
|
1581
|
self.__lastdatatime = datatime
|
|
|
1582
|
|
|
1582
|
|
|
|
1583
|
if avgdata_spc == None:
|
|
1583
|
if avgdata_spc == None:
|
|
|
1584
|
return None, None, None, None
|
|
1584
|
return None, None, None, None
|
|
|
1585
|
|
|
1585
|
|
|
|
1586
|
avgdatatime = self.__initime
|
|
1586
|
avgdatatime = self.__initime
|
|
|
1587
|
try:
|
|
1587
|
try:
|
|
|
1588
|
self.__timeInterval = (self.__lastdatatime - self.__initime)/(self.n - 1)
|
|
1588
|
self.__timeInterval = (self.__lastdatatime - self.__initime)/(self.n - 1)
|
|
|
1589
|
except:
|
|
1589
|
except:
|
|
|
1590
|
self.__timeInterval = self.__lastdatatime - self.__initime
|
|
1590
|
self.__timeInterval = self.__lastdatatime - self.__initime
|
|
|
1591
|
|
|
1591
|
|
|
|
1592
|
deltatime = datatime -self.__lastdatatime
|
|
1592
|
deltatime = datatime -self.__lastdatatime
|
|
|
1593
|
|
|
1593
|
|
|
|
1594
|
if not self.__withOverapping:
|
|
1594
|
if not self.__withOverapping:
|
|
|
1595
|
self.__initime = datatime
|
|
1595
|
self.__initime = datatime
|
|
|
1596
|
else:
|
|
1596
|
else:
|
|
|
1597
|
self.__initime += deltatime
|
|
1597
|
self.__initime += deltatime
|
|
|
1598
|
|
|
1598
|
|
|
|
1599
|
return avgdatatime, avgdata_spc, avgdata_cspc, avgdata_dc
|
|
1599
|
return avgdatatime, avgdata_spc, avgdata_cspc, avgdata_dc
|
|
|
1600
|
|
|
1600
|
|
|
|
1601
|
def run(self, dataOut, n=None, timeInterval=None, overlapping=False):
|
|
1601
|
def run(self, dataOut, n=None, timeInterval=None, overlapping=False):
|
|
|
1602
|
|
|
1602
|
|
|
|
1603
|
if n==1:
|
|
1603
|
if n==1:
|
|
|
1604
|
dataOut.flagNoData = False
|
|
1604
|
dataOut.flagNoData = False
|
|
|
1605
|
return
|
|
1605
|
return
|
|
|
1606
|
|
|
1606
|
|
|
|
1607
|
if not self.__isConfig:
|
|
1607
|
if not self.__isConfig:
|
|
|
1608
|
self.setup(n, timeInterval, overlapping)
|
|
1608
|
self.setup(n, timeInterval, overlapping)
|
|
|
1609
|
self.__isConfig = True
|
|
1609
|
self.__isConfig = True
|
|
|
1610
|
|
|
1610
|
|
|
|
1611
|
avgdatatime, avgdata_spc, avgdata_cspc, avgdata_dc = self.integrate(dataOut.utctime,
|
|
1611
|
avgdatatime, avgdata_spc, avgdata_cspc, avgdata_dc = self.integrate(dataOut.utctime,
|
|
|
1612
|
dataOut.data_spc,
|
|
1612
|
dataOut.data_spc,
|
|
|
1613
|
dataOut.data_cspc,
|
|
1613
|
dataOut.data_cspc,
|
|
|
1614
|
dataOut.data_dc)
|
|
1614
|
dataOut.data_dc)
|
|
|
1615
|
|
|
1615
|
|
|
|
1616
|
# dataOut.timeInterval *= n
|
|
1616
|
# dataOut.timeInterval *= n
|
|
|
1617
|
dataOut.flagNoData = True
|
|
1617
|
dataOut.flagNoData = True
|
|
|
1618
|
|
|
1618
|
|
|
|
1619
|
if self.__dataReady:
|
|
1619
|
if self.__dataReady:
|
|
|
1620
|
|
|
1620
|
|
|
|
1621
|
dataOut.data_spc = avgdata_spc
|
|
1621
|
dataOut.data_spc = avgdata_spc
|
|
|
1622
|
dataOut.data_cspc = avgdata_cspc
|
|
1622
|
dataOut.data_cspc = avgdata_cspc
|
|
|
1623
|
dataOut.data_dc = avgdata_dc
|
|
1623
|
dataOut.data_dc = avgdata_dc
|
|
|
1624
|
|
|
1624
|
|
|
|
1625
|
dataOut.nIncohInt *= self.n
|
|
1625
|
dataOut.nIncohInt *= self.n
|
|
|
1626
|
dataOut.utctime = avgdatatime
|
|
1626
|
dataOut.utctime = avgdatatime
|
|
|
1627
|
#dataOut.timeInterval = dataOut.ippSeconds * dataOut.nCohInt * dataOut.nIncohInt * dataOut.nFFTPoints
|
|
1627
|
#dataOut.timeInterval = dataOut.ippSeconds * dataOut.nCohInt * dataOut.nIncohInt * dataOut.nFFTPoints
|
|
|
1628
|
dataOut.timeInterval = self.__timeInterval*self.n
|
|
1628
|
dataOut.timeInterval = self.__timeInterval*self.n
|
|
|
1629
|
dataOut.flagNoData = False
|
|
1629
|
dataOut.flagNoData = False
|
|
|
1630
|
|
|
1630
|
|
|
|
1631
|
class ProfileConcat(Operation):
|
|
1631
|
class ProfileConcat(Operation):
|
|
|
1632
|
|
|
1632
|
|
|
|
1633
|
__isConfig = False
|
|
1633
|
__isConfig = False
|
|
|
1634
|
buffer = None
|
|
1634
|
buffer = None
|
|
|
1635
|
|
|
1635
|
|
|
|
1636
|
def __init__(self):
|
|
1636
|
def __init__(self):
|
|
|
1637
|
|
|
1637
|
|
|
|
1638
|
self.profileIndex = 0
|
|
1638
|
self.profileIndex = 0
|
|
|
1639
|
|
|
1639
|
|
|
|
1640
|
def reset(self):
|
|
1640
|
def reset(self):
|
|
|
1641
|
self.buffer = numpy.zeros_like(self.buffer)
|
|
1641
|
self.buffer = numpy.zeros_like(self.buffer)
|
|
|
1642
|
self.start_index = 0
|
|
1642
|
self.start_index = 0
|
|
|
1643
|
self.times = 1
|
|
1643
|
self.times = 1
|
|
|
1644
|
|
|
1644
|
|
|
|
1645
|
def setup(self, data, m, n=1):
|
|
1645
|
def setup(self, data, m, n=1):
|
|
|
1646
|
self.buffer = numpy.zeros((data.shape[0],data.shape[1]*m),dtype=type(data[0,0]))
|
|
1646
|
self.buffer = numpy.zeros((data.shape[0],data.shape[1]*m),dtype=type(data[0,0]))
|
|
|
1647
|
self.profiles = data.shape[1]
|
|
1647
|
self.profiles = data.shape[1]
|
|
|
1648
|
self.start_index = 0
|
|
1648
|
self.start_index = 0
|
|
|
1649
|
self.times = 1
|
|
1649
|
self.times = 1
|
|
|
1650
|
|
|
1650
|
|
|
|
1651
|
def concat(self, data):
|
|
1651
|
def concat(self, data):
|
|
|
1652
|
|
|
1652
|
|
|
|
1653
|
self.buffer[:,self.start_index:self.profiles*self.times] = data.copy()
|
|
1653
|
self.buffer[:,self.start_index:self.profiles*self.times] = data.copy()
|
|
|
1654
|
self.start_index = self.start_index + self.profiles
|
|
1654
|
self.start_index = self.start_index + self.profiles
|
|
|
1655
|
|
|
1655
|
|
|
|
1656
|
def run(self, dataOut, m):
|
|
1656
|
def run(self, dataOut, m):
|
|
|
1657
|
|
|
1657
|
|
|
|
1658
|
dataOut.flagNoData = True
|
|
1658
|
dataOut.flagNoData = True
|
|
|
1659
|
|
|
1659
|
|
|
|
1660
|
if not self.__isConfig:
|
|
1660
|
if not self.__isConfig:
|
|
|
1661
|
self.setup(dataOut.data, m, 1)
|
|
1661
|
self.setup(dataOut.data, m, 1)
|
|
|
1662
|
self.__isConfig = True
|
|
1662
|
self.__isConfig = True
|
|
|
1663
|
|
|
1663
|
|
|
|
1664
|
self.concat(dataOut.data)
|
|
1664
|
self.concat(dataOut.data)
|
|
|
1665
|
self.times += 1
|
|
1665
|
self.times += 1
|
|
|
1666
|
if self.times > m:
|
|
1666
|
if self.times > m:
|
|
|
1667
|
dataOut.data = self.buffer
|
|
1667
|
dataOut.data = self.buffer
|
|
|
1668
|
self.reset()
|
|
1668
|
self.reset()
|
|
|
1669
|
dataOut.flagNoData = False
|
|
1669
|
dataOut.flagNoData = False
|
|
|
1670
|
# se deben actualizar mas propiedades del header y del objeto dataOut, por ejemplo, las alturas
|
|
1670
|
# se deben actualizar mas propiedades del header y del objeto dataOut, por ejemplo, las alturas
|
|
|
1671
|
deltaHeight = dataOut.heightList[1] - dataOut.heightList[0]
|
|
1671
|
deltaHeight = dataOut.heightList[1] - dataOut.heightList[0]
|
|
|
1672
|
xf = dataOut.heightList[0] + dataOut.nHeights * deltaHeight * 5
|
|
1672
|
xf = dataOut.heightList[0] + dataOut.nHeights * deltaHeight * 5
|
|
|
1673
|
dataOut.heightList = numpy.arange(dataOut.heightList[0], xf, deltaHeight)
|
|
1673
|
dataOut.heightList = numpy.arange(dataOut.heightList[0], xf, deltaHeight)
|
|
|
1674
|
|
|
1674
|
|
|
|
1675
|
|
|
1675
|
|
|
|
1676
|
|
|
1676
|
|
|
|
1677
|
class ProfileSelector(Operation):
|
|
1677
|
class ProfileSelector(Operation):
|
|
|
1678
|
|
|
1678
|
|
|
|
1679
|
profileIndex = None
|
|
1679
|
profileIndex = None
|
|
|
1680
|
# Tamanho total de los perfiles
|
|
1680
|
# Tamanho total de los perfiles
|
|
|
1681
|
nProfiles = None
|
|
1681
|
nProfiles = None
|
|
|
1682
|
|
|
1682
|
|
|
|
1683
|
def __init__(self):
|
|
1683
|
def __init__(self):
|
|
|
1684
|
|
|
1684
|
|
|
|
1685
|
self.profileIndex = 0
|
|
1685
|
self.profileIndex = 0
|
|
|
1686
|
|
|
1686
|
|
|
|
1687
|
def incIndex(self):
|
|
1687
|
def incIndex(self):
|
|
|
1688
|
self.profileIndex += 1
|
|
1688
|
self.profileIndex += 1
|
|
|
1689
|
|
|
1689
|
|
|
|
1690
|
if self.profileIndex >= self.nProfiles:
|
|
1690
|
if self.profileIndex >= self.nProfiles:
|
|
|
1691
|
self.profileIndex = 0
|
|
1691
|
self.profileIndex = 0
|
|
|
1692
|
|
|
1692
|
|
|
|
1693
|
def isProfileInRange(self, minIndex, maxIndex):
|
|
1693
|
def isProfileInRange(self, minIndex, maxIndex):
|
|
|
1694
|
|
|
1694
|
|
|
|
1695
|
if self.profileIndex < minIndex:
|
|
1695
|
if self.profileIndex < minIndex:
|
|
|
1696
|
return False
|
|
1696
|
return False
|
|
|
1697
|
|
|
1697
|
|
|
|
1698
|
if self.profileIndex > maxIndex:
|
|
1698
|
if self.profileIndex > maxIndex:
|
|
|
1699
|
return False
|
|
1699
|
return False
|
|
|
1700
|
|
|
1700
|
|
|
|
1701
|
return True
|
|
1701
|
return True
|
|
|
1702
|
|
|
1702
|
|
|
|
1703
|
def isProfileInList(self, profileList):
|
|
1703
|
def isProfileInList(self, profileList):
|
|
|
1704
|
|
|
1704
|
|
|
|
1705
|
if self.profileIndex not in profileList:
|
|
1705
|
if self.profileIndex not in profileList:
|
|
|
1706
|
return False
|
|
1706
|
return False
|
|
|
1707
|
|
|
1707
|
|
|
|
1708
|
return True
|
|
1708
|
return True
|
|
|
1709
|
|
|
1709
|
|
|
|
1710
|
def run(self, dataOut, profileList=None, profileRangeList=None):
|
|
1710
|
def run(self, dataOut, profileList=None, profileRangeList=None, beam=None):
|
|
|
1711
|
|
|
1711
|
|
|
|
1712
|
dataOut.flagNoData = True
|
|
1712
|
dataOut.flagNoData = True
|
|
|
1713
|
self.nProfiles = dataOut.nProfiles
|
|
1713
|
self.nProfiles = dataOut.nProfiles
|
|
|
1714
|
|
|
1714
|
|
|
|
1715
|
if profileList != None:
|
|
1715
|
if profileList != None:
|
|
|
1716
|
if self.isProfileInList(profileList):
|
|
1716
|
if self.isProfileInList(profileList):
|
|
|
1717
|
dataOut.flagNoData = False
|
|
1717
|
dataOut.flagNoData = False
|
|
|
1718
|
|
|
1718
|
|
|
|
1719
|
self.incIndex()
|
|
1719
|
self.incIndex()
|
|
|
1720
|
return 1
|
|
1720
|
return 1
|
|
|
1721
|
|
|
1721
|
|
|
|
1722
|
|
|
1722
|
|
|
|
1723
|
elif profileRangeList != None:
|
|
1723
|
elif profileRangeList != None:
|
|
|
1724
|
minIndex = profileRangeList[0]
|
|
1724
|
minIndex = profileRangeList[0]
|
|
|
1725
|
maxIndex = profileRangeList[1]
|
|
1725
|
maxIndex = profileRangeList[1]
|
|
|
1726
|
if self.isProfileInRange(minIndex, maxIndex):
|
|
1726
|
if self.isProfileInRange(minIndex, maxIndex):
|
|
|
1727
|
dataOut.flagNoData = False
|
|
1727
|
dataOut.flagNoData = False
|
|
|
1728
|
|
|
1728
|
|
|
|
1729
|
self.incIndex()
|
|
1729
|
self.incIndex()
|
|
|
1730
|
return 1
|
|
1730
|
return 1
|
|
|
|
|
|
1731
|
elif beam != None:
|
|
|
|
|
|
1732
|
if self.isProfileInList(dataOut.beamRangeDict[beam]):
|
|
|
|
|
|
1733
|
dataOut.flagNoData = False
|
|
|
|
|
|
1734
|
|
|
|
|
|
|
1735
|
self.incIndex()
|
|
|
|
|
|
1736
|
return 1
|
|
|
1731
|
|
|
1737
|
|
|
|
1732
|
else:
|
|
1738
|
else:
|
|
|
1733
|
raise ValueError, "ProfileSelector needs profileList or profileRangeList"
|
|
1739
|
raise ValueError, "ProfileSelector needs profileList or profileRangeList"
|
|
|
1734
|
|
|
1740
|
|
|
|
1735
|
return 0
|
|
1741
|
return 0
|
|
|
1736
|
|
|
1742
|
|
|
|
1737
|
class SpectraHeisProc(ProcessingUnit):
|
|
1743
|
class SpectraHeisProc(ProcessingUnit):
|
|
|
1738
|
def __init__(self):
|
|
1744
|
def __init__(self):
|
|
|
1739
|
self.objectDict = {}
|
|
1745
|
self.objectDict = {}
|
|
|
1740
|
# self.buffer = None
|
|
1746
|
# self.buffer = None
|
|
|
1741
|
# self.firstdatatime = None
|
|
1747
|
# self.firstdatatime = None
|
|
|
1742
|
# self.profIndex = 0
|
|
1748
|
# self.profIndex = 0
|
|
|
1743
|
self.dataOut = SpectraHeis()
|
|
1749
|
self.dataOut = SpectraHeis()
|
|
|
1744
|
|
|
1750
|
|
|
|
1745
|
def __updateObjFromInput(self):
|
|
1751
|
def __updateObjFromInput(self):
|
|
|
1746
|
self.dataOut.timeZone = self.dataIn.timeZone
|
|
1752
|
self.dataOut.timeZone = self.dataIn.timeZone
|
|
|
1747
|
self.dataOut.dstFlag = self.dataIn.dstFlag
|
|
1753
|
self.dataOut.dstFlag = self.dataIn.dstFlag
|
|
|
1748
|
self.dataOut.errorCount = self.dataIn.errorCount
|
|
1754
|
self.dataOut.errorCount = self.dataIn.errorCount
|
|
|
1749
|
self.dataOut.useLocalTime = self.dataIn.useLocalTime
|
|
1755
|
self.dataOut.useLocalTime = self.dataIn.useLocalTime
|
|
|
1750
|
|
|
1756
|
|
|
|
1751
|
self.dataOut.radarControllerHeaderObj = self.dataIn.radarControllerHeaderObj.copy()#
|
|
1757
|
self.dataOut.radarControllerHeaderObj = self.dataIn.radarControllerHeaderObj.copy()#
|
|
|
1752
|
self.dataOut.systemHeaderObj = self.dataIn.systemHeaderObj.copy()#
|
|
1758
|
self.dataOut.systemHeaderObj = self.dataIn.systemHeaderObj.copy()#
|
|
|
1753
|
self.dataOut.channelList = self.dataIn.channelList
|
|
1759
|
self.dataOut.channelList = self.dataIn.channelList
|
|
|
1754
|
self.dataOut.heightList = self.dataIn.heightList
|
|
1760
|
self.dataOut.heightList = self.dataIn.heightList
|
|
|
1755
|
# self.dataOut.dtype = self.dataIn.dtype
|
|
1761
|
# self.dataOut.dtype = self.dataIn.dtype
|
|
|
1756
|
self.dataOut.dtype = numpy.dtype([('real','<f4'),('imag','<f4')])
|
|
1762
|
self.dataOut.dtype = numpy.dtype([('real','<f4'),('imag','<f4')])
|
|
|
1757
|
# self.dataOut.nHeights = self.dataIn.nHeights
|
|
1763
|
# self.dataOut.nHeights = self.dataIn.nHeights
|
|
|
1758
|
# self.dataOut.nChannels = self.dataIn.nChannels
|
|
1764
|
# self.dataOut.nChannels = self.dataIn.nChannels
|
|
|
1759
|
self.dataOut.nBaud = self.dataIn.nBaud
|
|
1765
|
self.dataOut.nBaud = self.dataIn.nBaud
|
|
|
1760
|
self.dataOut.nCode = self.dataIn.nCode
|
|
1766
|
self.dataOut.nCode = self.dataIn.nCode
|
|
|
1761
|
self.dataOut.code = self.dataIn.code
|
|
1767
|
self.dataOut.code = self.dataIn.code
|
|
|
1762
|
# self.dataOut.nProfiles = 1
|
|
1768
|
# self.dataOut.nProfiles = 1
|
|
|
1763
|
# self.dataOut.nProfiles = self.dataOut.nFFTPoints
|
|
1769
|
# self.dataOut.nProfiles = self.dataOut.nFFTPoints
|
|
|
1764
|
self.dataOut.nFFTPoints = self.dataIn.nHeights
|
|
1770
|
self.dataOut.nFFTPoints = self.dataIn.nHeights
|
|
|
1765
|
# self.dataOut.channelIndexList = self.dataIn.channelIndexList
|
|
1771
|
# self.dataOut.channelIndexList = self.dataIn.channelIndexList
|
|
|
1766
|
# self.dataOut.flagNoData = self.dataIn.flagNoData
|
|
1772
|
# self.dataOut.flagNoData = self.dataIn.flagNoData
|
|
|
1767
|
self.dataOut.flagTimeBlock = self.dataIn.flagTimeBlock
|
|
1773
|
self.dataOut.flagTimeBlock = self.dataIn.flagTimeBlock
|
|
|
1768
|
self.dataOut.utctime = self.dataIn.utctime
|
|
1774
|
self.dataOut.utctime = self.dataIn.utctime
|
|
|
1769
|
# self.dataOut.utctime = self.firstdatatime
|
|
1775
|
# self.dataOut.utctime = self.firstdatatime
|
|
|
1770
|
self.dataOut.flagDecodeData = self.dataIn.flagDecodeData #asumo q la data esta decodificada
|
|
1776
|
self.dataOut.flagDecodeData = self.dataIn.flagDecodeData #asumo q la data esta decodificada
|
|
|
1771
|
self.dataOut.flagDeflipData = self.dataIn.flagDeflipData #asumo q la data esta sin flip
|
|
1777
|
self.dataOut.flagDeflipData = self.dataIn.flagDeflipData #asumo q la data esta sin flip
|
|
|
1772
|
# self.dataOut.flagShiftFFT = self.dataIn.flagShiftFFT
|
|
1778
|
# self.dataOut.flagShiftFFT = self.dataIn.flagShiftFFT
|
|
|
1773
|
self.dataOut.nCohInt = self.dataIn.nCohInt
|
|
1779
|
self.dataOut.nCohInt = self.dataIn.nCohInt
|
|
|
1774
|
self.dataOut.nIncohInt = 1
|
|
1780
|
self.dataOut.nIncohInt = 1
|
|
|
1775
|
self.dataOut.ippSeconds= self.dataIn.ippSeconds
|
|
1781
|
self.dataOut.ippSeconds= self.dataIn.ippSeconds
|
|
|
1776
|
self.dataOut.windowOfFilter = self.dataIn.windowOfFilter
|
|
1782
|
self.dataOut.windowOfFilter = self.dataIn.windowOfFilter
|
|
|
1777
|
|
|
1783
|
|
|
|
1778
|
self.dataOut.timeInterval = self.dataIn.timeInterval*self.dataOut.nIncohInt
|
|
1784
|
self.dataOut.timeInterval = self.dataIn.timeInterval*self.dataOut.nIncohInt
|
|
|
1779
|
# self.dataOut.set=self.dataIn.set
|
|
1785
|
# self.dataOut.set=self.dataIn.set
|
|
|
1780
|
# self.dataOut.deltaHeight=self.dataIn.deltaHeight
|
|
1786
|
# self.dataOut.deltaHeight=self.dataIn.deltaHeight
|
|
|
1781
|
|
|
1787
|
|
|
|
1782
|
|
|
1788
|
|
|
|
1783
|
def __updateObjFromFits(self):
|
|
1789
|
def __updateObjFromFits(self):
|
|
|
1784
|
self.dataOut.utctime = self.dataIn.utctime
|
|
1790
|
self.dataOut.utctime = self.dataIn.utctime
|
|
|
1785
|
self.dataOut.channelIndexList = self.dataIn.channelIndexList
|
|
1791
|
self.dataOut.channelIndexList = self.dataIn.channelIndexList
|
|
|
1786
|
|
|
1792
|
|
|
|
1787
|
self.dataOut.channelList = self.dataIn.channelList
|
|
1793
|
self.dataOut.channelList = self.dataIn.channelList
|
|
|
1788
|
self.dataOut.heightList = self.dataIn.heightList
|
|
1794
|
self.dataOut.heightList = self.dataIn.heightList
|
|
|
1789
|
self.dataOut.data_spc = self.dataIn.data
|
|
1795
|
self.dataOut.data_spc = self.dataIn.data
|
|
|
1790
|
self.dataOut.timeInterval = self.dataIn.timeInterval
|
|
1796
|
self.dataOut.timeInterval = self.dataIn.timeInterval
|
|
|
1791
|
self.dataOut.timeZone = self.dataIn.timeZone
|
|
1797
|
self.dataOut.timeZone = self.dataIn.timeZone
|
|
|
1792
|
self.dataOut.useLocalTime = True
|
|
1798
|
self.dataOut.useLocalTime = True
|
|
|
1793
|
# self.dataOut.
|
|
1799
|
# self.dataOut.
|
|
|
1794
|
# self.dataOut.
|
|
1800
|
# self.dataOut.
|
|
|
1795
|
|
|
1801
|
|
|
|
1796
|
def __getFft(self):
|
|
1802
|
def __getFft(self):
|
|
|
1797
|
|
|
1803
|
|
|
|
1798
|
fft_volt = numpy.fft.fft(self.dataIn.data, axis=1)
|
|
1804
|
fft_volt = numpy.fft.fft(self.dataIn.data, axis=1)
|
|
|
1799
|
fft_volt = numpy.fft.fftshift(fft_volt,axes=(1,))
|
|
1805
|
fft_volt = numpy.fft.fftshift(fft_volt,axes=(1,))
|
|
|
1800
|
spc = numpy.abs(fft_volt * numpy.conjugate(fft_volt))/(self.dataOut.nFFTPoints)
|
|
1806
|
spc = numpy.abs(fft_volt * numpy.conjugate(fft_volt))/(self.dataOut.nFFTPoints)
|
|
|
1801
|
self.dataOut.data_spc = spc
|
|
1807
|
self.dataOut.data_spc = spc
|
|
|
1802
|
|
|
1808
|
|
|
|
1803
|
def init(self):
|
|
1809
|
def init(self):
|
|
|
1804
|
|
|
1810
|
|
|
|
1805
|
self.dataOut.flagNoData = True
|
|
1811
|
self.dataOut.flagNoData = True
|
|
|
1806
|
|
|
1812
|
|
|
|
1807
|
if self.dataIn.type == "Fits":
|
|
1813
|
if self.dataIn.type == "Fits":
|
|
|
1808
|
self.__updateObjFromFits()
|
|
1814
|
self.__updateObjFromFits()
|
|
|
1809
|
self.dataOut.flagNoData = False
|
|
1815
|
self.dataOut.flagNoData = False
|
|
|
1810
|
return
|
|
1816
|
return
|
|
|
1811
|
|
|
1817
|
|
|
|
1812
|
if self.dataIn.type == "SpectraHeis":
|
|
1818
|
if self.dataIn.type == "SpectraHeis":
|
|
|
1813
|
self.dataOut.copy(self.dataIn)
|
|
1819
|
self.dataOut.copy(self.dataIn)
|
|
|
1814
|
return
|
|
1820
|
return
|
|
|
1815
|
|
|
1821
|
|
|
|
1816
|
if self.dataIn.type == "Voltage":
|
|
1822
|
if self.dataIn.type == "Voltage":
|
|
|
1817
|
self.__updateObjFromInput()
|
|
1823
|
self.__updateObjFromInput()
|
|
|
1818
|
self.__getFft()
|
|
1824
|
self.__getFft()
|
|
|
1819
|
self.dataOut.flagNoData = False
|
|
1825
|
self.dataOut.flagNoData = False
|
|
|
1820
|
|
|
1826
|
|
|
|
1821
|
return
|
|
1827
|
return
|
|
|
1822
|
|
|
1828
|
|
|
|
1823
|
raise ValueError, "The type object %s is not valid"%(self.dataIn.type)
|
|
1829
|
raise ValueError, "The type object %s is not valid"%(self.dataIn.type)
|
|
|
1824
|
|
|
1830
|
|
|
|
1825
|
|
|
1831
|
|
|
|
1826
|
def selectChannels(self, channelList):
|
|
1832
|
def selectChannels(self, channelList):
|
|
|
1827
|
|
|
1833
|
|
|
|
1828
|
channelIndexList = []
|
|
1834
|
channelIndexList = []
|
|
|
1829
|
|
|
1835
|
|
|
|
1830
|
for channel in channelList:
|
|
1836
|
for channel in channelList:
|
|
|
1831
|
index = self.dataOut.channelList.index(channel)
|
|
1837
|
index = self.dataOut.channelList.index(channel)
|
|
|
1832
|
channelIndexList.append(index)
|
|
1838
|
channelIndexList.append(index)
|
|
|
1833
|
|
|
1839
|
|
|
|
1834
|
self.selectChannelsByIndex(channelIndexList)
|
|
1840
|
self.selectChannelsByIndex(channelIndexList)
|
|
|
1835
|
|
|
1841
|
|
|
|
1836
|
def selectChannelsByIndex(self, channelIndexList):
|
|
1842
|
def selectChannelsByIndex(self, channelIndexList):
|
|
|
1837
|
"""
|
|
1843
|
"""
|
|
|
1838
|
Selecciona un bloque de datos en base a canales segun el channelIndexList
|
|
1844
|
Selecciona un bloque de datos en base a canales segun el channelIndexList
|
|
|
1839
|
|
|
1845
|
|
|
|
1840
|
Input:
|
|
1846
|
Input:
|
|
|
1841
|
channelIndexList : lista sencilla de canales a seleccionar por ej. [2,3,7]
|
|
1847
|
channelIndexList : lista sencilla de canales a seleccionar por ej. [2,3,7]
|
|
|
1842
|
|
|
1848
|
|
|
|
1843
|
Affected:
|
|
1849
|
Affected:
|
|
|
1844
|
self.dataOut.data
|
|
1850
|
self.dataOut.data
|
|
|
1845
|
self.dataOut.channelIndexList
|
|
1851
|
self.dataOut.channelIndexList
|
|
|
1846
|
self.dataOut.nChannels
|
|
1852
|
self.dataOut.nChannels
|
|
|
1847
|
self.dataOut.m_ProcessingHeader.totalSpectra
|
|
1853
|
self.dataOut.m_ProcessingHeader.totalSpectra
|
|
|
1848
|
self.dataOut.systemHeaderObj.numChannels
|
|
1854
|
self.dataOut.systemHeaderObj.numChannels
|
|
|
1849
|
self.dataOut.m_ProcessingHeader.blockSize
|
|
1855
|
self.dataOut.m_ProcessingHeader.blockSize
|
|
|
1850
|
|
|
1856
|
|
|
|
1851
|
Return:
|
|
1857
|
Return:
|
|
|
1852
|
None
|
|
1858
|
None
|
|
|
1853
|
"""
|
|
1859
|
"""
|
|
|
1854
|
|
|
1860
|
|
|
|
1855
|
for channelIndex in channelIndexList:
|
|
1861
|
for channelIndex in channelIndexList:
|
|
|
1856
|
if channelIndex not in self.dataOut.channelIndexList:
|
|
1862
|
if channelIndex not in self.dataOut.channelIndexList:
|
|
|
1857
|
print channelIndexList
|
|
1863
|
print channelIndexList
|
|
|
1858
|
raise ValueError, "The value %d in channelIndexList is not valid" %channelIndex
|
|
1864
|
raise ValueError, "The value %d in channelIndexList is not valid" %channelIndex
|
|
|
1859
|
|
|
1865
|
|
|
|
1860
|
nChannels = len(channelIndexList)
|
|
1866
|
nChannels = len(channelIndexList)
|
|
|
1861
|
|
|
1867
|
|
|
|
1862
|
data_spc = self.dataOut.data_spc[channelIndexList,:]
|
|
1868
|
data_spc = self.dataOut.data_spc[channelIndexList,:]
|
|
|
1863
|
|
|
1869
|
|
|
|
1864
|
self.dataOut.data_spc = data_spc
|
|
1870
|
self.dataOut.data_spc = data_spc
|
|
|
1865
|
self.dataOut.channelList = [self.dataOut.channelList[i] for i in channelIndexList]
|
|
1871
|
self.dataOut.channelList = [self.dataOut.channelList[i] for i in channelIndexList]
|
|
|
1866
|
|
|
1872
|
|
|
|
1867
|
return 1
|
|
1873
|
return 1
|
|
|
1868
|
|
|
1874
|
|
|
|
1869
|
class IncohInt4SpectraHeis(Operation):
|
|
1875
|
class IncohInt4SpectraHeis(Operation):
|
|
|
1870
|
|
|
1876
|
|
|
|
1871
|
__isConfig = False
|
|
1877
|
__isConfig = False
|
|
|
1872
|
|
|
1878
|
|
|
|
1873
|
__profIndex = 0
|
|
1879
|
__profIndex = 0
|
|
|
1874
|
__withOverapping = False
|
|
1880
|
__withOverapping = False
|
|
|
1875
|
|
|
1881
|
|
|
|
1876
|
__byTime = False
|
|
1882
|
__byTime = False
|
|
|
1877
|
__initime = None
|
|
1883
|
__initime = None
|
|
|
1878
|
__lastdatatime = None
|
|
1884
|
__lastdatatime = None
|
|
|
1879
|
__integrationtime = None
|
|
1885
|
__integrationtime = None
|
|
|
1880
|
|
|
1886
|
|
|
|
1881
|
__buffer = None
|
|
1887
|
__buffer = None
|
|
|
1882
|
|
|
1888
|
|
|
|
1883
|
__dataReady = False
|
|
1889
|
__dataReady = False
|
|
|
1884
|
|
|
1890
|
|
|
|
1885
|
n = None
|
|
1891
|
n = None
|
|
|
1886
|
|
|
1892
|
|
|
|
1887
|
|
|
1893
|
|
|
|
1888
|
def __init__(self):
|
|
1894
|
def __init__(self):
|
|
|
1889
|
|
|
1895
|
|
|
|
1890
|
self.__isConfig = False
|
|
1896
|
self.__isConfig = False
|
|
|
1891
|
|
|
1897
|
|
|
|
1892
|
def setup(self, n=None, timeInterval=None, overlapping=False):
|
|
1898
|
def setup(self, n=None, timeInterval=None, overlapping=False):
|
|
|
1893
|
"""
|
|
1899
|
"""
|
|
|
1894
|
Set the parameters of the integration class.
|
|
1900
|
Set the parameters of the integration class.
|
|
|
1895
|
|
|
1901
|
|
|
|
1896
|
Inputs:
|
|
1902
|
Inputs:
|
|
|
1897
|
|
|
1903
|
|
|
|
1898
|
n : Number of coherent integrations
|
|
1904
|
n : Number of coherent integrations
|
|
|
1899
|
timeInterval : Time of integration. If the parameter "n" is selected this one does not work
|
|
1905
|
timeInterval : Time of integration. If the parameter "n" is selected this one does not work
|
|
|
1900
|
overlapping :
|
|
1906
|
overlapping :
|
|
|
1901
|
|
|
1907
|
|
|
|
1902
|
"""
|
|
1908
|
"""
|
|
|
1903
|
|
|
1909
|
|
|
|
1904
|
self.__initime = None
|
|
1910
|
self.__initime = None
|
|
|
1905
|
self.__lastdatatime = 0
|
|
1911
|
self.__lastdatatime = 0
|
|
|
1906
|
self.__buffer = None
|
|
1912
|
self.__buffer = None
|
|
|
1907
|
self.__dataReady = False
|
|
1913
|
self.__dataReady = False
|
|
|
1908
|
|
|
1914
|
|
|
|
1909
|
|
|
1915
|
|
|
|
1910
|
if n == None and timeInterval == None:
|
|
1916
|
if n == None and timeInterval == None:
|
|
|
1911
|
raise ValueError, "n or timeInterval should be specified ..."
|
|
1917
|
raise ValueError, "n or timeInterval should be specified ..."
|
|
|
1912
|
|
|
1918
|
|
|
|
1913
|
if n != None:
|
|
1919
|
if n != None:
|
|
|
1914
|
self.n = n
|
|
1920
|
self.n = n
|
|
|
1915
|
self.__byTime = False
|
|
1921
|
self.__byTime = False
|
|
|
1916
|
else:
|
|
1922
|
else:
|
|
|
1917
|
self.__integrationtime = timeInterval #* 60. #if (type(timeInterval)!=integer) -> change this line
|
|
1923
|
self.__integrationtime = timeInterval #* 60. #if (type(timeInterval)!=integer) -> change this line
|
|
|
1918
|
self.n = 9999
|
|
1924
|
self.n = 9999
|
|
|
1919
|
self.__byTime = True
|
|
1925
|
self.__byTime = True
|
|
|
1920
|
|
|
1926
|
|
|
|
1921
|
if overlapping:
|
|
1927
|
if overlapping:
|
|
|
1922
|
self.__withOverapping = True
|
|
1928
|
self.__withOverapping = True
|
|
|
1923
|
self.__buffer = None
|
|
1929
|
self.__buffer = None
|
|
|
1924
|
else:
|
|
1930
|
else:
|
|
|
1925
|
self.__withOverapping = False
|
|
1931
|
self.__withOverapping = False
|
|
|
1926
|
self.__buffer = 0
|
|
1932
|
self.__buffer = 0
|
|
|
1927
|
|
|
1933
|
|
|
|
1928
|
self.__profIndex = 0
|
|
1934
|
self.__profIndex = 0
|
|
|
1929
|
|
|
1935
|
|
|
|
1930
|
def putData(self, data):
|
|
1936
|
def putData(self, data):
|
|
|
1931
|
|
|
1937
|
|
|
|
1932
|
"""
|
|
1938
|
"""
|
|
|
1933
|
Add a profile to the __buffer and increase in one the __profileIndex
|
|
1939
|
Add a profile to the __buffer and increase in one the __profileIndex
|
|
|
1934
|
|
|
1940
|
|
|
|
1935
|
"""
|
|
1941
|
"""
|
|
|
1936
|
|
|
1942
|
|
|
|
1937
|
if not self.__withOverapping:
|
|
1943
|
if not self.__withOverapping:
|
|
|
1938
|
self.__buffer += data.copy()
|
|
1944
|
self.__buffer += data.copy()
|
|
|
1939
|
self.__profIndex += 1
|
|
1945
|
self.__profIndex += 1
|
|
|
1940
|
return
|
|
1946
|
return
|
|
|
1941
|
|
|
1947
|
|
|
|
1942
|
#Overlapping data
|
|
1948
|
#Overlapping data
|
|
|
1943
|
nChannels, nHeis = data.shape
|
|
1949
|
nChannels, nHeis = data.shape
|
|
|
1944
|
data = numpy.reshape(data, (1, nChannels, nHeis))
|
|
1950
|
data = numpy.reshape(data, (1, nChannels, nHeis))
|
|
|
1945
|
|
|
1951
|
|
|
|
1946
|
#If the buffer is empty then it takes the data value
|
|
1952
|
#If the buffer is empty then it takes the data value
|
|
|
1947
|
if self.__buffer == None:
|
|
1953
|
if self.__buffer == None:
|
|
|
1948
|
self.__buffer = data
|
|
1954
|
self.__buffer = data
|
|
|
1949
|
self.__profIndex += 1
|
|
1955
|
self.__profIndex += 1
|
|
|
1950
|
return
|
|
1956
|
return
|
|
|
1951
|
|
|
1957
|
|
|
|
1952
|
#If the buffer length is lower than n then stakcing the data value
|
|
1958
|
#If the buffer length is lower than n then stakcing the data value
|
|
|
1953
|
if self.__profIndex < self.n:
|
|
1959
|
if self.__profIndex < self.n:
|
|
|
1954
|
self.__buffer = numpy.vstack((self.__buffer, data))
|
|
1960
|
self.__buffer = numpy.vstack((self.__buffer, data))
|
|
|
1955
|
self.__profIndex += 1
|
|
1961
|
self.__profIndex += 1
|
|
|
1956
|
return
|
|
1962
|
return
|
|
|
1957
|
|
|
1963
|
|
|
|
1958
|
#If the buffer length is equal to n then replacing the last buffer value with the data value
|
|
1964
|
#If the buffer length is equal to n then replacing the last buffer value with the data value
|
|
|
1959
|
self.__buffer = numpy.roll(self.__buffer, -1, axis=0)
|
|
1965
|
self.__buffer = numpy.roll(self.__buffer, -1, axis=0)
|
|
|
1960
|
self.__buffer[self.n-1] = data
|
|
1966
|
self.__buffer[self.n-1] = data
|
|
|
1961
|
self.__profIndex = self.n
|
|
1967
|
self.__profIndex = self.n
|
|
|
1962
|
return
|
|
1968
|
return
|
|
|
1963
|
|
|
1969
|
|
|
|
1964
|
|
|
1970
|
|
|
|
1965
|
def pushData(self):
|
|
1971
|
def pushData(self):
|
|
|
1966
|
"""
|
|
1972
|
"""
|
|
|
1967
|
Return the sum of the last profiles and the profiles used in the sum.
|
|
1973
|
Return the sum of the last profiles and the profiles used in the sum.
|
|
|
1968
|
|
|
1974
|
|
|
|
1969
|
Affected:
|
|
1975
|
Affected:
|
|
|
1970
|
|
|
1976
|
|
|
|
1971
|
self.__profileIndex
|
|
1977
|
self.__profileIndex
|
|
|
1972
|
|
|
1978
|
|
|
|
1973
|
"""
|
|
1979
|
"""
|
|
|
1974
|
|
|
1980
|
|
|
|
1975
|
if not self.__withOverapping:
|
|
1981
|
if not self.__withOverapping:
|
|
|
1976
|
data = self.__buffer
|
|
1982
|
data = self.__buffer
|
|
|
1977
|
n = self.__profIndex
|
|
1983
|
n = self.__profIndex
|
|
|
1978
|
|
|
1984
|
|
|
|
1979
|
self.__buffer = 0
|
|
1985
|
self.__buffer = 0
|
|
|
1980
|
self.__profIndex = 0
|
|
1986
|
self.__profIndex = 0
|
|
|
1981
|
|
|
1987
|
|
|
|
1982
|
return data, n
|
|
1988
|
return data, n
|
|
|
1983
|
|
|
1989
|
|
|
|
1984
|
#Integration with Overlapping
|
|
1990
|
#Integration with Overlapping
|
|
|
1985
|
data = numpy.sum(self.__buffer, axis=0)
|
|
1991
|
data = numpy.sum(self.__buffer, axis=0)
|
|
|
1986
|
n = self.__profIndex
|
|
1992
|
n = self.__profIndex
|
|
|
1987
|
|
|
1993
|
|
|
|
1988
|
return data, n
|
|
1994
|
return data, n
|
|
|
1989
|
|
|
1995
|
|
|
|
1990
|
def byProfiles(self, data):
|
|
1996
|
def byProfiles(self, data):
|
|
|
1991
|
|
|
1997
|
|
|
|
1992
|
self.__dataReady = False
|
|
1998
|
self.__dataReady = False
|
|
|
1993
|
avgdata = None
|
|
1999
|
avgdata = None
|
|
|
1994
|
n = None
|
|
2000
|
n = None
|
|
|
1995
|
|
|
2001
|
|
|
|
1996
|
self.putData(data)
|
|
2002
|
self.putData(data)
|
|
|
1997
|
|
|
2003
|
|
|
|
1998
|
if self.__profIndex == self.n:
|
|
2004
|
if self.__profIndex == self.n:
|
|
|
1999
|
|
|
2005
|
|
|
|
2000
|
avgdata, n = self.pushData()
|
|
2006
|
avgdata, n = self.pushData()
|
|
|
2001
|
self.__dataReady = True
|
|
2007
|
self.__dataReady = True
|
|
|
2002
|
|
|
2008
|
|
|
|
2003
|
return avgdata
|
|
2009
|
return avgdata
|
|
|
2004
|
|
|
2010
|
|
|
|
2005
|
def byTime(self, data, datatime):
|
|
2011
|
def byTime(self, data, datatime):
|
|
|
2006
|
|
|
2012
|
|
|
|
2007
|
self.__dataReady = False
|
|
2013
|
self.__dataReady = False
|
|
|
2008
|
avgdata = None
|
|
2014
|
avgdata = None
|
|
|
2009
|
n = None
|
|
2015
|
n = None
|
|
|
2010
|
|
|
2016
|
|
|
|
2011
|
self.putData(data)
|
|
2017
|
self.putData(data)
|
|
|
2012
|
|
|
2018
|
|
|
|
2013
|
if (datatime - self.__initime) >= self.__integrationtime:
|
|
2019
|
if (datatime - self.__initime) >= self.__integrationtime:
|
|
|
2014
|
avgdata, n = self.pushData()
|
|
2020
|
avgdata, n = self.pushData()
|
|
|
2015
|
self.n = n
|
|
2021
|
self.n = n
|
|
|
2016
|
self.__dataReady = True
|
|
2022
|
self.__dataReady = True
|
|
|
2017
|
|
|
2023
|
|
|
|
2018
|
return avgdata
|
|
2024
|
return avgdata
|
|
|
2019
|
|
|
2025
|
|
|
|
2020
|
def integrate(self, data, datatime=None):
|
|
2026
|
def integrate(self, data, datatime=None):
|
|
|
2021
|
|
|
2027
|
|
|
|
2022
|
if self.__initime == None:
|
|
2028
|
if self.__initime == None:
|
|
|
2023
|
self.__initime = datatime
|
|
2029
|
self.__initime = datatime
|
|
|
2024
|
|
|
2030
|
|
|
|
2025
|
if self.__byTime:
|
|
2031
|
if self.__byTime:
|
|
|
2026
|
avgdata = self.byTime(data, datatime)
|
|
2032
|
avgdata = self.byTime(data, datatime)
|
|
|
2027
|
else:
|
|
2033
|
else:
|
|
|
2028
|
avgdata = self.byProfiles(data)
|
|
2034
|
avgdata = self.byProfiles(data)
|
|
|
2029
|
|
|
2035
|
|
|
|
2030
|
|
|
2036
|
|
|
|
2031
|
self.__lastdatatime = datatime
|
|
2037
|
self.__lastdatatime = datatime
|
|
|
2032
|
|
|
2038
|
|
|
|
2033
|
if avgdata == None:
|
|
2039
|
if avgdata == None:
|
|
|
2034
|
return None, None
|
|
2040
|
return None, None
|
|
|
2035
|
|
|
2041
|
|
|
|
2036
|
avgdatatime = self.__initime
|
|
2042
|
avgdatatime = self.__initime
|
|
|
2037
|
|
|
2043
|
|
|
|
2038
|
deltatime = datatime -self.__lastdatatime
|
|
2044
|
deltatime = datatime -self.__lastdatatime
|
|
|
2039
|
|
|
2045
|
|
|
|
2040
|
if not self.__withOverapping:
|
|
2046
|
if not self.__withOverapping:
|
|
|
2041
|
self.__initime = datatime
|
|
2047
|
self.__initime = datatime
|
|
|
2042
|
else:
|
|
2048
|
else:
|
|
|
2043
|
self.__initime += deltatime
|
|
2049
|
self.__initime += deltatime
|
|
|
2044
|
|
|
2050
|
|
|
|
2045
|
return avgdata, avgdatatime
|
|
2051
|
return avgdata, avgdatatime
|
|
|
2046
|
|
|
2052
|
|
|
|
2047
|
def run(self, dataOut, **kwargs):
|
|
2053
|
def run(self, dataOut, **kwargs):
|
|
|
2048
|
|
|
2054
|
|
|
|
2049
|
if not self.__isConfig:
|
|
2055
|
if not self.__isConfig:
|
|
|
2050
|
self.setup(**kwargs)
|
|
2056
|
self.setup(**kwargs)
|
|
|
2051
|
self.__isConfig = True
|
|
2057
|
self.__isConfig = True
|
|
|
2052
|
|
|
2058
|
|
|
|
2053
|
avgdata, avgdatatime = self.integrate(dataOut.data_spc, dataOut.utctime)
|
|
2059
|
avgdata, avgdatatime = self.integrate(dataOut.data_spc, dataOut.utctime)
|
|
|
2054
|
|
|
2060
|
|
|
|
2055
|
# dataOut.timeInterval *= n
|
|
2061
|
# dataOut.timeInterval *= n
|
|
|
2056
|
dataOut.flagNoData = True
|
|
2062
|
dataOut.flagNoData = True
|
|
|
2057
|
|
|
2063
|
|
|
|
2058
|
if self.__dataReady:
|
|
2064
|
if self.__dataReady:
|
|
|
2059
|
dataOut.data_spc = avgdata
|
|
2065
|
dataOut.data_spc = avgdata
|
|
|
2060
|
dataOut.nIncohInt *= self.n
|
|
2066
|
dataOut.nIncohInt *= self.n
|
|
|
2061
|
# dataOut.nCohInt *= self.n
|
|
2067
|
# dataOut.nCohInt *= self.n
|
|
|
2062
|
dataOut.utctime = avgdatatime
|
|
2068
|
dataOut.utctime = avgdatatime
|
|
|
2063
|
dataOut.timeInterval = dataOut.ippSeconds * dataOut.nIncohInt
|
|
2069
|
dataOut.timeInterval = dataOut.ippSeconds * dataOut.nIncohInt
|
|
|
2064
|
# dataOut.timeInterval = self.__timeInterval*self.n
|
|
2070
|
# dataOut.timeInterval = self.__timeInterval*self.n
|
|
|
2065
|
dataOut.flagNoData = False
|
|
2071
|
dataOut.flagNoData = False
|
|
|
2066
|
|
|
2072
|
|
|
|
2067
|
|
|
2073
|
|
|
|
2068
|
|
|
2074
|
|
|
|
2069
|
|
|
2075
|
|
|
|
2070
|
No newline at end of file
|
|
2076
|
class AMISRProc(ProcessingUnit):
|
|
|
|
|
|
2077
|
def __init__(self):
|
|
|
|
|
|
2078
|
self.objectDict = {}
|
|
|
|
|
|
2079
|
self.dataOut = AMISR()
|
|
|
|
|
|
2080
|
|
|
|
|
|
|
2081
|
def init(self):
|
|
|
|
|
|
2082
|
if self.dataIn.type == 'AMISR':
|
|
|
|
|
|
2083
|
self.dataOut.copy(self.dataIn)
|
|
|
|
|
|
2084
|
|
|
|
|
|
|
2085
|
class BeamSelector(Operation):
|
|
|
|
|
|
2086
|
profileIndex = None
|
|
|
|
|
|
2087
|
# Tamanho total de los perfiles
|
|
|
|
|
|
2088
|
nProfiles = None
|
|
|
|
|
|
2089
|
|
|
|
|
|
|
2090
|
def __init__(self):
|
|
|
|
|
|
2091
|
|
|
|
|
|
|
2092
|
self.profileIndex = 0
|
|
|
|
|
|
2093
|
|
|
|
|
|
|
2094
|
def incIndex(self):
|
|
|
|
|
|
2095
|
self.profileIndex += 1
|
|
|
|
|
|
2096
|
|
|
|
|
|
|
2097
|
if self.profileIndex >= self.nProfiles:
|
|
|
|
|
|
2098
|
self.profileIndex = 0
|
|
|
|
|
|
2099
|
|
|
|
|
|
|
2100
|
def isProfileInRange(self, minIndex, maxIndex):
|
|
|
|
|
|
2101
|
|
|
|
|
|
|
2102
|
if self.profileIndex < minIndex:
|
|
|
|
|
|
2103
|
return False
|
|
|
|
|
|
2104
|
|
|
|
|
|
|
2105
|
if self.profileIndex > maxIndex:
|
|
|
|
|
|
2106
|
return False
|
|
|
|
|
|
2107
|
|
|
|
|
|
|
2108
|
return True
|
|
|
|
|
|
2109
|
|
|
|
|
|
|
2110
|
def isProfileInList(self, profileList):
|
|
|
|
|
|
2111
|
|
|
|
|
|
|
2112
|
if self.profileIndex not in profileList:
|
|
|
|
|
|
2113
|
return False
|
|
|
|
|
|
2114
|
|
|
|
|
|
|
2115
|
return True
|
|
|
|
|
|
2116
|
|
|
|
|
|
|
2117
|
def run(self, dataOut, beam=None):
|
|
|
|
|
|
2118
|
|
|
|
|
|
|
2119
|
dataOut.flagNoData = True
|
|
|
|
|
|
2120
|
self.nProfiles = dataOut.nProfiles
|
|
|
|
|
|
2121
|
|
|
|
|
|
|
2122
|
if beam != None:
|
|
|
|
|
|
2123
|
if self.isProfileInList(dataOut.beamRangeDict[beam]):
|
|
|
|
|
|
2124
|
dataOut.flagNoData = False
|
|
|
|
|
|
2125
|
|
|
|
|
|
|
2126
|
self.incIndex()
|
|
|
|
|
|
2127
|
return 1
|
|
|
|
|
|
2128
|
|
|
|
|
|
|
2129
|
else:
|
|
|
|
|
|
2130
|
raise ValueError, "BeamSelector needs beam value"
|
|
|
|
|
|
2131
|
|
|
|
|
|
|
2132
|
return 0
No newline at end of file
|
