jroprocessing.py
2043 lines
| 64.6 KiB
| text/x-python
|
PythonLexer
Miguel Valdez
|
r174 | ''' | |
| $Author: dsuarez $ | |||
| $Id: Processor.py 1 2012-11-12 18:56:07Z dsuarez $ | |||
| ''' | |||
| import os | |||
| import numpy | |||
| import datetime | |||
| import time | |||
Daniel Valdez
|
r447 | import math | |
|
Miguel Valdez
|
r178 | from jrodata import * | |
| from jrodataIO import * | |||
| from jroplot import * | |||
|
Miguel Valdez
|
r174 | ||
|
Miguel Valdez
|
r301 | try: | |
| import cfunctions | |||
| except: | |||
| pass | |||
|
Miguel Valdez
|
r174 | class ProcessingUnit: | |
| """ | |||
| Esta es la clase base para el procesamiento de datos. | |||
| Contiene el metodo "call" para llamar operaciones. Las operaciones pueden ser: | |||
| - Metodos internos (callMethod) | |||
| - Objetos del tipo Operation (callObject). Antes de ser llamados, estos objetos | |||
| tienen que ser agreagados con el metodo "add". | |||
| """ | |||
| # objeto de datos de entrada (Voltage, Spectra o Correlation) | |||
| dataIn = None | |||
| # objeto de datos de entrada (Voltage, Spectra o Correlation) | |||
| dataOut = None | |||
| objectDict = None | |||
| def __init__(self): | |||
| self.objectDict = {} | |||
|
Miguel Valdez
|
r197 | def init(self): | |
| raise ValueError, "Not implemented" | |||
|
Miguel Valdez
|
r174 | def addOperation(self, object, objId): | |
| """ | |||
| Agrega el objeto "object" a la lista de objetos "self.objectList" y retorna el | |||
| identificador asociado a este objeto. | |||
| Input: | |||
| object : objeto de la clase "Operation" | |||
| Return: | |||
| objId : identificador del objeto, necesario para ejecutar la operacion | |||
| """ | |||
|
Daniel Valdez
|
r179 | self.objectDict[objId] = object | |
|
Miguel Valdez
|
r174 | ||
| return objId | |||
| def operation(self, **kwargs): | |||
| """ | |||
|
Miguel Valdez
|
r232 | Operacion directa sobre la data (dataOut.data). Es necesario actualizar los valores de los | |
|
Miguel Valdez
|
r174 | atributos del objeto dataOut | |
| Input: | |||
| **kwargs : Diccionario de argumentos de la funcion a ejecutar | |||
| """ | |||
| raise ValueError, "ImplementedError" | |||
| def callMethod(self, name, **kwargs): | |||
| """ | |||
| Ejecuta el metodo con el nombre "name" y con argumentos **kwargs de la propia clase. | |||
| Input: | |||
| name : nombre del metodo a ejecutar | |||
| **kwargs : diccionario con los nombres y valores de la funcion a ejecutar. | |||
| """ | |||
|
Miguel Valdez
|
r197 | if name != 'run': | |
| if name == 'init' and self.dataIn.isEmpty(): | |||
|
Miguel Valdez
|
r199 | self.dataOut.flagNoData = True | |
| return False | |||
|
Miguel Valdez
|
r197 | ||
| if name != 'init' and self.dataOut.isEmpty(): | |||
|
Miguel Valdez
|
r199 | return False | |
|
Miguel Valdez
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r174 | ||
| methodToCall = getattr(self, name) | |||
| methodToCall(**kwargs) | |||
|
Miguel Valdez
|
r199 | if name != 'run': | |
| return True | |||
| if self.dataOut.isEmpty(): | |||
| return False | |||
| return True | |||
|
Miguel Valdez
|
r174 | def callObject(self, objId, **kwargs): | |
| """ | |||
| Ejecuta la operacion asociada al identificador del objeto "objId" | |||
| Input: | |||
| objId : identificador del objeto a ejecutar | |||
| **kwargs : diccionario con los nombres y valores de la funcion a ejecutar. | |||
| Return: | |||
| None | |||
| """ | |||
|
Miguel Valdez
|
r197 | if self.dataOut.isEmpty(): | |
|
Miguel Valdez
|
r199 | return False | |
|
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r197 | ||
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r189 | object = self.objectDict[objId] | |
|
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r174 | ||
| object.run(self.dataOut, **kwargs) | |||
|
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r199 | ||
| return True | |||
|
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r174 | ||
|
Miguel Valdez
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r188 | def call(self, operationConf, **kwargs): | |
|
Miguel Valdez
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r174 | ||
| """ | |||
|
Miguel Valdez
|
r199 | Return True si ejecuta la operacion "operationConf.name" con los | |
| argumentos "**kwargs". False si la operacion no se ha ejecutado. | |||
| La operacion puede ser de dos tipos: | |||
|
Miguel Valdez
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r174 | ||
| 1. Un metodo propio de esta clase: | |||
| operation.type = "self" | |||
| 2. El metodo "run" de un objeto del tipo Operation o de un derivado de ella: | |||
| operation.type = "other". | |||
| Este objeto de tipo Operation debe de haber sido agregado antes con el metodo: | |||
| "addOperation" e identificado con el operation.id | |||
| con el id de la operacion. | |||
|
Miguel Valdez
|
r188 | ||
| Input: | |||
| Operation : Objeto del tipo operacion con los atributos: name, type y id. | |||
|
Miguel Valdez
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r174 | """ | |
|
Miguel Valdez
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r188 | if operationConf.type == 'self': | |
|
Miguel Valdez
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r199 | sts = self.callMethod(operationConf.name, **kwargs) | |
|
Miguel Valdez
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r174 | ||
|
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r188 | if operationConf.type == 'other': | |
|
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r199 | sts = self.callObject(operationConf.id, **kwargs) | |
| return sts | |||
|
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r191 | ||
| def setInput(self, dataIn): | |||
| self.dataIn = dataIn | |||
| def getOutput(self): | |||
| return self.dataOut | |||
|
Miguel Valdez
|
r174 | ||
| class Operation(): | |||
| """ | |||
| Clase base para definir las operaciones adicionales que se pueden agregar a la clase ProcessingUnit | |||
|
Daniel Valdez
|
r179 | y necesiten acumular informacion previa de los datos a procesar. De preferencia usar un buffer de | |
|
Miguel Valdez
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r174 | acumulacion dentro de esta clase | |
|
Daniel Valdez
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r179 | Ejemplo: Integraciones coherentes, necesita la informacion previa de los n perfiles anteriores (bufffer) | |
|
Miguel Valdez
|
r174 | ||
| """ | |||
| __buffer = None | |||
|
Miguel Valdez
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r175 | __isConfig = False | |
|
Miguel Valdez
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r174 | ||
| def __init__(self): | |||
| pass | |||
| def run(self, dataIn, **kwargs): | |||
| """ | |||
| Realiza las operaciones necesarias sobre la dataIn.data y actualiza los atributos del objeto dataIn. | |||
| Input: | |||
| dataIn : objeto del tipo JROData | |||
| Return: | |||
| None | |||
| Affected: | |||
| __buffer : buffer de recepcion de datos. | |||
| """ | |||
| raise ValueError, "ImplementedError" | |||
| class VoltageProc(ProcessingUnit): | |||
| def __init__(self): | |||
|
Miguel Valdez
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r188 | ||
|
Daniel Valdez
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r179 | self.objectDict = {} | |
|
Miguel Valdez
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r188 | self.dataOut = Voltage() | |
|
Daniel Valdez
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r239 | self.flip = 1 | |
|
Miguel Valdez
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r174 | ||
| def init(self): | |||
|
Daniel Valdez
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r179 | self.dataOut.copy(self.dataIn) | |
| # No necesita copiar en cada init() los atributos de dataIn | |||
|
Miguel Valdez
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r174 | # la copia deberia hacerse por cada nuevo bloque de datos | |
| def selectChannels(self, channelList): | |||
|
Miguel Valdez
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r200 | channelIndexList = [] | |
| for channel in channelList: | |||
| index = self.dataOut.channelList.index(channel) | |||
| channelIndexList.append(index) | |||
| self.selectChannelsByIndex(channelIndexList) | |||
|
Miguel Valdez
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r174 | ||
| def selectChannelsByIndex(self, channelIndexList): | |||
| """ | |||
| Selecciona un bloque de datos en base a canales segun el channelIndexList | |||
| Input: | |||
| channelIndexList : lista sencilla de canales a seleccionar por ej. [2,3,7] | |||
| Affected: | |||
|
Daniel Valdez
|
r179 | self.dataOut.data | |
| self.dataOut.channelIndexList | |||
| self.dataOut.nChannels | |||
| self.dataOut.m_ProcessingHeader.totalSpectra | |||
| self.dataOut.systemHeaderObj.numChannels | |||
| self.dataOut.m_ProcessingHeader.blockSize | |||
|
Miguel Valdez
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r174 | ||
| Return: | |||
| None | |||
| """ | |||
|
Miguel Valdez
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r200 | for channelIndex in channelIndexList: | |
| if channelIndex not in self.dataOut.channelIndexList: | |||
|
Miguel Valdez
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r197 | print channelIndexList | |
|
Miguel Valdez
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r200 | raise ValueError, "The value %d in channelIndexList is not valid" %channelIndex | |
|
Miguel Valdez
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r174 | ||
| nChannels = len(channelIndexList) | |||
|
Daniel Valdez
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r179 | data = self.dataOut.data[channelIndexList,:] | |
|
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r174 | ||
|
Daniel Valdez
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r179 | self.dataOut.data = data | |
| self.dataOut.channelList = [self.dataOut.channelList[i] for i in channelIndexList] | |||
|
Miguel Valdez
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r200 | # self.dataOut.nChannels = nChannels | |
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Miguel Valdez
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r174 | ||
| return 1 | |||
|
Miguel Valdez
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r219 | ||
|
Daniel Valdez
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r392 | def selectHeights(self, minHei=None, maxHei=None): | |
|
Miguel Valdez
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r219 | """ | |
| Selecciona un bloque de datos en base a un grupo de valores de alturas segun el rango | |||
| minHei <= height <= maxHei | |||
| Input: | |||
| minHei : valor minimo de altura a considerar | |||
| maxHei : valor maximo de altura a considerar | |||
| Affected: | |||
| Indirectamente son cambiados varios valores a travez del metodo selectHeightsByIndex | |||
| Return: | |||
| 1 si el metodo se ejecuto con exito caso contrario devuelve 0 | |||
| """ | |||
|
Daniel Valdez
|
r392 | ||
| if minHei == None: | |||
| minHei = self.dataOut.heightList[0] | |||
| if maxHei == None: | |||
| maxHei = self.dataOut.heightList[-1] | |||
|
Miguel Valdez
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r219 | if (minHei < self.dataOut.heightList[0]) or (minHei > maxHei): | |
| raise ValueError, "some value in (%d,%d) is not valid" % (minHei, maxHei) | |||
|
Daniel Valdez
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r392 | ||
|
Miguel Valdez
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r219 | if (maxHei > self.dataOut.heightList[-1]): | |
| maxHei = self.dataOut.heightList[-1] | |||
| # raise ValueError, "some value in (%d,%d) is not valid" % (minHei, maxHei) | |||
| minIndex = 0 | |||
| maxIndex = 0 | |||
|
Miguel Valdez
|
r242 | heights = self.dataOut.heightList | |
| inda = numpy.where(heights >= minHei) | |||
| indb = numpy.where(heights <= maxHei) | |||
| try: | |||
| minIndex = inda[0][0] | |||
| except: | |||
| minIndex = 0 | |||
| try: | |||
| maxIndex = indb[0][-1] | |||
| except: | |||
| maxIndex = len(heights) | |||
|
Miguel Valdez
|
r219 | ||
| self.selectHeightsByIndex(minIndex, maxIndex) | |||
| return 1 | |||
| def selectHeightsByIndex(self, minIndex, maxIndex): | |||
| """ | |||
| Selecciona un bloque de datos en base a un grupo indices de alturas segun el rango | |||
| minIndex <= index <= maxIndex | |||
| Input: | |||
| minIndex : valor de indice minimo de altura a considerar | |||
| maxIndex : valor de indice maximo de altura a considerar | |||
| Affected: | |||
| self.dataOut.data | |||
| self.dataOut.heightList | |||
| Return: | |||
| 1 si el metodo se ejecuto con exito caso contrario devuelve 0 | |||
| """ | |||
| if (minIndex < 0) or (minIndex > maxIndex): | |||
| raise ValueError, "some value in (%d,%d) is not valid" % (minIndex, maxIndex) | |||
| if (maxIndex >= self.dataOut.nHeights): | |||
| maxIndex = self.dataOut.nHeights-1 | |||
| # raise ValueError, "some value in (%d,%d) is not valid" % (minIndex, maxIndex) | |||
| nHeights = maxIndex - minIndex + 1 | |||
| #voltage | |||
| data = self.dataOut.data[:,minIndex:maxIndex+1] | |||
| firstHeight = self.dataOut.heightList[minIndex] | |||
| self.dataOut.data = data | |||
| self.dataOut.heightList = self.dataOut.heightList[minIndex:maxIndex+1] | |||
| return 1 | |||
|
Daniel Valdez
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r233 | ||
| def filterByHeights(self, window): | |||
| deltaHeight = self.dataOut.heightList[1] - self.dataOut.heightList[0] | |||
| if window == None: | |||
|
Daniel Valdez
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r392 | window = (self.dataOut.radarControllerHeaderObj.txA/self.dataOut.radarControllerHeaderObj.nBaud) / deltaHeight | |
|
Daniel Valdez
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r233 | ||
| newdelta = deltaHeight * window | |||
| r = self.dataOut.data.shape[1] % window | |||
| buffer = self.dataOut.data[:,0:self.dataOut.data.shape[1]-r] | |||
| buffer = buffer.reshape(self.dataOut.data.shape[0],self.dataOut.data.shape[1]/window,window) | |||
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Daniel Valdez
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r245 | buffer = numpy.sum(buffer,2) | |
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Daniel Valdez
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r233 | self.dataOut.data = buffer | |
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Daniel Valdez
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r392 | self.dataOut.heightList = numpy.arange(self.dataOut.heightList[0],newdelta*(self.dataOut.nHeights-r)/window,newdelta) | |
|
Daniel Valdez
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r245 | self.dataOut.windowOfFilter = window | |
|
Daniel Valdez
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r233 | ||
|
Daniel Valdez
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r239 | def deFlip(self): | |
| self.dataOut.data *= self.flip | |||
| self.flip *= -1. | |||
|
Daniel Valdez
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r233 | ||
|
Daniel Valdez
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r402 | def setRadarFrequency(self, frequency=None): | |
| if frequency != None: | |||
| self.dataOut.frequency = frequency | |||
| return 1 | |||
|
Miguel Valdez
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r174 | class CohInt(Operation): | |
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Miguel Valdez
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r232 | __isConfig = False | |
|
Miguel Valdez
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r174 | __profIndex = 0 | |
| __withOverapping = False | |||
| __byTime = False | |||
| __initime = None | |||
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Miguel Valdez
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r175 | __lastdatatime = None | |
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Miguel Valdez
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r174 | __integrationtime = None | |
| __buffer = None | |||
| __dataReady = False | |||
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Miguel Valdez
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r201 | n = None | |
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Miguel Valdez
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r174 | ||
| def __init__(self): | |||
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Miguel Valdez
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r175 | self.__isConfig = False | |
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Miguel Valdez
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r174 | ||
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Miguel Valdez
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r201 | def setup(self, n=None, timeInterval=None, overlapping=False): | |
|
Miguel Valdez
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r174 | """ | |
| Set the parameters of the integration class. | |||
| Inputs: | |||
|
Miguel Valdez
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r201 | n : Number of coherent integrations | |
| timeInterval : Time of integration. If the parameter "n" is selected this one does not work | |||
|
Miguel Valdez
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r174 | overlapping : | |
| """ | |||
| self.__initime = None | |||
|
Miguel Valdez
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r175 | self.__lastdatatime = 0 | |
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Miguel Valdez
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r174 | self.__buffer = None | |
| self.__dataReady = False | |||
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Miguel Valdez
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r201 | if n == None and timeInterval == None: | |
| raise ValueError, "n or timeInterval should be specified ..." | |||
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r174 | ||
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Miguel Valdez
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r201 | if n != None: | |
| self.n = n | |||
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Miguel Valdez
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r174 | self.__byTime = False | |
| else: | |||
| self.__integrationtime = timeInterval * 60. #if (type(timeInterval)!=integer) -> change this line | |||
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Miguel Valdez
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r201 | self.n = 9999 | |
|
Miguel Valdez
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r174 | self.__byTime = True | |
| if overlapping: | |||
| self.__withOverapping = True | |||
| self.__buffer = None | |||
| else: | |||
| self.__withOverapping = False | |||
| self.__buffer = 0 | |||
| self.__profIndex = 0 | |||
| def putData(self, data): | |||
| """ | |||
| Add a profile to the __buffer and increase in one the __profileIndex | |||
| """ | |||
| if not self.__withOverapping: | |||
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r201 | self.__buffer += data.copy() | |
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r174 | self.__profIndex += 1 | |
| return | |||
| #Overlapping data | |||
| nChannels, nHeis = data.shape | |||
| data = numpy.reshape(data, (1, nChannels, nHeis)) | |||
| #If the buffer is empty then it takes the data value | |||
| if self.__buffer == None: | |||
| self.__buffer = data | |||
| self.__profIndex += 1 | |||
| return | |||
|
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r201 | #If the buffer length is lower than n then stakcing the data value | |
| if self.__profIndex < self.n: | |||
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Miguel Valdez
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r174 | self.__buffer = numpy.vstack((self.__buffer, data)) | |
| self.__profIndex += 1 | |||
| return | |||
|
Miguel Valdez
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r201 | #If the buffer length is equal to n then replacing the last buffer value with the data value | |
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Miguel Valdez
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r174 | self.__buffer = numpy.roll(self.__buffer, -1, axis=0) | |
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Miguel Valdez
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r201 | self.__buffer[self.n-1] = data | |
| self.__profIndex = self.n | |||
|
Miguel Valdez
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r174 | return | |
| def pushData(self): | |||
| """ | |||
| Return the sum of the last profiles and the profiles used in the sum. | |||
| Affected: | |||
| self.__profileIndex | |||
| """ | |||
| if not self.__withOverapping: | |||
| data = self.__buffer | |||
|
Miguel Valdez
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r201 | n = self.__profIndex | |
|
Miguel Valdez
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r174 | ||
| self.__buffer = 0 | |||
| self.__profIndex = 0 | |||
|
Miguel Valdez
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r201 | return data, n | |
|
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r174 | ||
| #Integration with Overlapping | |||
| data = numpy.sum(self.__buffer, axis=0) | |||
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Miguel Valdez
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r201 | n = self.__profIndex | |
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r174 | ||
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Miguel Valdez
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r201 | return data, n | |
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Miguel Valdez
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r174 | ||
| def byProfiles(self, data): | |||
| self.__dataReady = False | |||
|
Daniel Valdez
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r189 | avgdata = None | |
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Miguel Valdez
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r201 | n = None | |
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Miguel Valdez
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r174 | ||
| self.putData(data) | |||
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Miguel Valdez
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r201 | if self.__profIndex == self.n: | |
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r174 | ||
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r201 | avgdata, n = self.pushData() | |
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r174 | self.__dataReady = True | |
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Daniel Valdez
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r189 | return avgdata | |
|
Miguel Valdez
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r174 | ||
| def byTime(self, data, datatime): | |||
| self.__dataReady = False | |||
|
Daniel Valdez
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r189 | avgdata = None | |
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Miguel Valdez
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r201 | n = None | |
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r175 | ||
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Miguel Valdez
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r174 | self.putData(data) | |
| if (datatime - self.__initime) >= self.__integrationtime: | |||
|
Miguel Valdez
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r201 | avgdata, n = self.pushData() | |
| self.n = n | |||
|
Miguel Valdez
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r174 | self.__dataReady = True | |
|
Daniel Valdez
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r189 | return avgdata | |
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Miguel Valdez
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r174 | ||
| def integrate(self, data, datatime=None): | |||
|
Miguel Valdez
|
r175 | if self.__initime == None: | |
| self.__initime = datatime | |||
| if self.__byTime: | |||
| avgdata = self.byTime(data, datatime) | |||
|
Miguel Valdez
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r174 | else: | |
|
Miguel Valdez
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r175 | avgdata = self.byProfiles(data) | |
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Miguel Valdez
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r174 | ||
|
Miguel Valdez
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r175 | self.__lastdatatime = datatime | |
| if avgdata == None: | |||
|
Daniel Valdez
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r189 | return None, None | |
|
Miguel Valdez
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r175 | ||
| avgdatatime = self.__initime | |||
| deltatime = datatime -self.__lastdatatime | |||
| if not self.__withOverapping: | |||
| self.__initime = datatime | |||
| else: | |||
| self.__initime += deltatime | |||
|
Daniel Valdez
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r179 | return avgdata, avgdatatime | |
|
Miguel Valdez
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r174 | ||
|
Miguel Valdez
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r232 | def run(self, dataOut, **kwargs): | |
|
Miguel Valdez
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r174 | ||
|
Miguel Valdez
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r175 | if not self.__isConfig: | |
|
Miguel Valdez
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r232 | self.setup(**kwargs) | |
|
Miguel Valdez
|
r175 | self.__isConfig = True | |
| avgdata, avgdatatime = self.integrate(dataOut.data, dataOut.utctime) | |||
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Miguel Valdez
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r174 | ||
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Miguel Valdez
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r201 | # dataOut.timeInterval *= n | |
|
Daniel Valdez
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r189 | dataOut.flagNoData = True | |
|
Miguel Valdez
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r174 | ||
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Miguel Valdez
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r175 | if self.__dataReady: | |
|
Daniel Valdez
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r179 | dataOut.data = avgdata | |
|
Miguel Valdez
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r201 | dataOut.nCohInt *= self.n | |
|
Daniel Valdez
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r179 | dataOut.utctime = avgdatatime | |
|
Miguel Valdez
|
r201 | dataOut.timeInterval = dataOut.ippSeconds * dataOut.nCohInt | |
|
Daniel Valdez
|
r192 | dataOut.flagNoData = False | |
|
Miguel Valdez
|
r232 | ||
|
Daniel Valdez
|
r233 | ||
|
Miguel Valdez
|
r232 | class Decoder(Operation): | |
| __isConfig = False | |||
| __profIndex = 0 | |||
| code = None | |||
| nCode = None | |||
| nBaud = None | |||
| def __init__(self): | |||
| self.__isConfig = False | |||
|
Miguel Valdez
|
r298 | def setup(self, code, shape): | |
|
Miguel Valdez
|
r232 | ||
| self.__profIndex = 0 | |||
| self.code = code | |||
| self.nCode = len(code) | |||
| self.nBaud = len(code[0]) | |||
|
Miguel Valdez
|
r298 | self.__nChannels, self.__nHeis = shape | |
|
Miguel Valdez
|
r325 | __codeBuffer = numpy.zeros((self.nCode, self.__nHeis), dtype=numpy.complex) | |
|
Miguel Valdez
|
r298 | ||
|
Miguel Valdez
|
r308 | __codeBuffer[:,0:self.nBaud] = self.code | |
|
Miguel Valdez
|
r298 | ||
|
Miguel Valdez
|
r308 | self.fft_code = numpy.conj(numpy.fft.fft(__codeBuffer, axis=1)) | |
|
Miguel Valdez
|
r298 | ||
|
Miguel Valdez
|
r310 | self.ndatadec = self.__nHeis - self.nBaud + 1 | |
|
Miguel Valdez
|
r308 | ||
| self.datadecTime = numpy.zeros((self.__nChannels, self.ndatadec), dtype=numpy.complex) | |||
|
Miguel Valdez
|
r298 | ||
|
Miguel Valdez
|
r232 | def convolutionInFreq(self, data): | |
|
Miguel Valdez
|
r298 | fft_code = self.fft_code[self.__profIndex].reshape(1,-1) | |
|
Miguel Valdez
|
r232 | ||
| fft_data = numpy.fft.fft(data, axis=1) | |||
|
Miguel Valdez
|
r298 | ||
|
Miguel Valdez
|
r232 | conv = fft_data*fft_code | |
|
Miguel Valdez
|
r312 | ||
|
Miguel Valdez
|
r232 | data = numpy.fft.ifft(conv,axis=1) | |
| datadec = data[:,:-self.nBaud+1] | |||
|
Miguel Valdez
|
r308 | return datadec | |
|
Miguel Valdez
|
r232 | ||
|
Miguel Valdez
|
r301 | def convolutionInFreqOpt(self, data): | |
|
Miguel Valdez
|
r307 | ||
|
Miguel Valdez
|
r301 | fft_code = self.fft_code[self.__profIndex].reshape(1,-1) | |
| data = cfunctions.decoder(fft_code, data) | |||
|
Miguel Valdez
|
r232 | ||
|
Miguel Valdez
|
r301 | datadec = data[:,:-self.nBaud+1] | |
|
Miguel Valdez
|
r308 | return datadec | |
|
Miguel Valdez
|
r301 | ||
|
Miguel Valdez
|
r232 | def convolutionInTime(self, data): | |
|
Miguel Valdez
|
r315 | code = self.code[self.__profIndex] | |
|
Miguel Valdez
|
r232 | ||
|
Miguel Valdez
|
r311 | for i in range(self.__nChannels): | |
|
Miguel Valdez
|
r308 | self.datadecTime[i,:] = numpy.correlate(data[i,:], code, mode='valid') | |
|
Miguel Valdez
|
r232 | ||
|
Miguel Valdez
|
r308 | return self.datadecTime | |
|
Miguel Valdez
|
r232 | ||
|
Daniel Valdez
|
r269 | def run(self, dataOut, code=None, nCode=None, nBaud=None, mode = 0): | |
|
Miguel Valdez
|
r316 | ||
|
Daniel Valdez
|
r464 | if code == None: | |
| code = dataOut.code | |||
| else: | |||
| code = numpy.array(code).reshape(nCode,nBaud) | |||
| dataOut.code = code | |||
| dataOut.nCode = nCode | |||
| dataOut.nBaud = nBaud | |||
| dataOut.radarControllerHeaderObj.code = code | |||
| dataOut.radarControllerHeaderObj.nCode = nCode | |||
| dataOut.radarControllerHeaderObj.nBaud = nBaud | |||
|
Daniel Valdez
|
r284 | ||
|
Daniel Valdez
|
r464 | ||
| if not self.__isConfig: | |||
|
Daniel Valdez
|
r284 | ||
|
Miguel Valdez
|
r299 | self.setup(code, dataOut.data.shape) | |
|
Miguel Valdez
|
r232 | self.__isConfig = True | |
| if mode == 0: | |||
|
Miguel Valdez
|
r316 | datadec = self.convolutionInTime(dataOut.data) | |
|
Miguel Valdez
|
r232 | ||
| if mode == 1: | |||
|
Miguel Valdez
|
r316 | datadec = self.convolutionInFreq(dataOut.data) | |
|
Miguel Valdez
|
r303 | ||
|
Miguel Valdez
|
r305 | if mode == 2: | |
|
Miguel Valdez
|
r309 | datadec = self.convolutionInFreqOpt(dataOut.data) | |
|
Miguel Valdez
|
r308 | ||
|
Miguel Valdez
|
r232 | dataOut.data = datadec | |
|
Miguel Valdez
|
r309 | dataOut.heightList = dataOut.heightList[0:self.ndatadec] | |
|
Miguel Valdez
|
r232 | ||
| dataOut.flagDecodeData = True #asumo q la data no esta decodificada | |||
|
Miguel Valdez
|
r308 | ||
| if self.__profIndex == self.nCode-1: | |||
| self.__profIndex = 0 | |||
| return 1 | |||
| self.__profIndex += 1 | |||
|
Miguel Valdez
|
r232 | ||
|
Miguel Valdez
|
r308 | return 1 | |
| # dataOut.flagDeflipData = True #asumo q la data no esta sin flip | |||
|
Daniel Valdez
|
r192 | ||
| class SpectraProc(ProcessingUnit): | |||
| def __init__(self): | |||
|
Miguel Valdez
|
r199 | ||
|
Daniel Valdez
|
r192 | self.objectDict = {} | |
| self.buffer = None | |||
| self.firstdatatime = None | |||
| self.profIndex = 0 | |||
| self.dataOut = Spectra() | |||
| def __updateObjFromInput(self): | |||
|
Miguel Valdez
|
r344 | self.dataOut.timeZone = self.dataIn.timeZone | |
| self.dataOut.dstFlag = self.dataIn.dstFlag | |||
| self.dataOut.errorCount = self.dataIn.errorCount | |||
| self.dataOut.useLocalTime = self.dataIn.useLocalTime | |||
|
Daniel Valdez
|
r192 | self.dataOut.radarControllerHeaderObj = self.dataIn.radarControllerHeaderObj.copy() | |
| self.dataOut.systemHeaderObj = self.dataIn.systemHeaderObj.copy() | |||
| self.dataOut.channelList = self.dataIn.channelList | |||
| self.dataOut.heightList = self.dataIn.heightList | |||
|
Daniel Valdez
|
r276 | self.dataOut.dtype = numpy.dtype([('real','<f4'),('imag','<f4')]) | |
|
Daniel Valdez
|
r207 | # self.dataOut.nHeights = self.dataIn.nHeights | |
|
Miguel Valdez
|
r200 | # self.dataOut.nChannels = self.dataIn.nChannels | |
|
Daniel Valdez
|
r192 | self.dataOut.nBaud = self.dataIn.nBaud | |
| self.dataOut.nCode = self.dataIn.nCode | |||
| self.dataOut.code = self.dataIn.code | |||
| self.dataOut.nProfiles = self.dataOut.nFFTPoints | |||
|
Miguel Valdez
|
r200 | # self.dataOut.channelIndexList = self.dataIn.channelIndexList | |
|
Daniel Valdez
|
r192 | self.dataOut.flagTimeBlock = self.dataIn.flagTimeBlock | |
| self.dataOut.utctime = self.firstdatatime | |||
| self.dataOut.flagDecodeData = self.dataIn.flagDecodeData #asumo q la data esta decodificada | |||
| self.dataOut.flagDeflipData = self.dataIn.flagDeflipData #asumo q la data esta sin flip | |||
|
Daniel Valdez
|
r357 | # self.dataOut.flagShiftFFT = self.dataIn.flagShiftFFT | |
|
Daniel Valdez
|
r192 | self.dataOut.nCohInt = self.dataIn.nCohInt | |
| self.dataOut.nIncohInt = 1 | |||
| self.dataOut.ippSeconds = self.dataIn.ippSeconds | |||
|
Daniel Valdez
|
r245 | self.dataOut.windowOfFilter = self.dataIn.windowOfFilter | |
|
Miguel Valdez
|
r219 | ||
|
Miguel Valdez
|
r220 | self.dataOut.timeInterval = self.dataIn.timeInterval*self.dataOut.nFFTPoints*self.dataOut.nIncohInt | |
|
Daniel Valdez
|
r402 | self.dataOut.frequency = self.dataIn.frequency | |
|
Daniel Valdez
|
r408 | self.dataOut.realtime = self.dataIn.realtime | |
|
Miguel Valdez
|
r219 | ||
|
Daniel Valdez
|
r192 | def __getFft(self): | |
| """ | |||
| Convierte valores de Voltaje a Spectra | |||
| Affected: | |||
| self.dataOut.data_spc | |||
| self.dataOut.data_cspc | |||
| self.dataOut.data_dc | |||
| self.dataOut.heightList | |||
| self.profIndex | |||
| self.buffer | |||
| self.dataOut.flagNoData | |||
| """ | |||
|
Daniel Valdez
|
r404 | fft_volt = numpy.fft.fft(self.buffer,n=self.dataOut.nFFTPoints,axis=1) | |
|
Daniel Valdez
|
r276 | fft_volt = fft_volt.astype(numpy.dtype('complex')) | |
|
Daniel Valdez
|
r192 | dc = fft_volt[:,0,:] | |
| #calculo de self-spectra | |||
| fft_volt = numpy.fft.fftshift(fft_volt,axes=(1,)) | |||
| spc = fft_volt * numpy.conjugate(fft_volt) | |||
| spc = spc.real | |||
| blocksize = 0 | |||
| blocksize += dc.size | |||
| blocksize += spc.size | |||
| cspc = None | |||
| pairIndex = 0 | |||
| if self.dataOut.pairsList != None: | |||
| #calculo de cross-spectra | |||
| cspc = numpy.zeros((self.dataOut.nPairs, self.dataOut.nFFTPoints, self.dataOut.nHeights), dtype='complex') | |||
| for pair in self.dataOut.pairsList: | |||
|
Miguel Valdez
|
r227 | cspc[pairIndex,:,:] = fft_volt[pair[0],:,:] * numpy.conjugate(fft_volt[pair[1],:,:]) | |
|
Daniel Valdez
|
r192 | pairIndex += 1 | |
| blocksize += cspc.size | |||
| self.dataOut.data_spc = spc | |||
| self.dataOut.data_cspc = cspc | |||
| self.dataOut.data_dc = dc | |||
| self.dataOut.blockSize = blocksize | |||
|
Daniel Valdez
|
r357 | self.dataOut.flagShiftFFT = False | |
|
Miguel Valdez
|
r199 | ||
|
Daniel Valdez
|
r445 | def init(self, nProfiles=None, nFFTPoints=None, pairsList=None, ippFactor=None): | |
|
Miguel Valdez
|
r199 | ||
|
Miguel Valdez
|
r232 | self.dataOut.flagNoData = True | |
|
Miguel Valdez
|
r199 | if self.dataIn.type == "Spectra": | |
| self.dataOut.copy(self.dataIn) | |||
| return | |||
| if self.dataIn.type == "Voltage": | |||
| if nFFTPoints == None: | |||
|
Miguel Valdez
|
r217 | raise ValueError, "This SpectraProc.init() need nFFTPoints input variable" | |
|
Miguel Valdez
|
r199 | ||
| if pairsList == None: | |||
| nPairs = 0 | |||
| else: | |||
| nPairs = len(pairsList) | |||
|
Daniel Valdez
|
r445 | if ippFactor == None: | |
| ippFactor = 1 | |||
| self.dataOut.ippFactor = ippFactor | |||
|
Miguel Valdez
|
r199 | self.dataOut.nFFTPoints = nFFTPoints | |
| self.dataOut.pairsList = pairsList | |||
| self.dataOut.nPairs = nPairs | |||
| if self.buffer == None: | |||
| self.buffer = numpy.zeros((self.dataIn.nChannels, | |||
|
Daniel Valdez
|
r404 | nProfiles, | |
|
Miguel Valdez
|
r199 | self.dataIn.nHeights), | |
| dtype='complex') | |||
|
Miguel Valdez
|
r232 | self.buffer[:,self.profIndex,:] = self.dataIn.data.copy() | |
|
Miguel Valdez
|
r199 | self.profIndex += 1 | |
| if self.firstdatatime == None: | |||
| self.firstdatatime = self.dataIn.utctime | |||
|
Daniel Valdez
|
r421 | if self.profIndex == nProfiles: | |
|
Miguel Valdez
|
r199 | self.__updateObjFromInput() | |
| self.__getFft() | |||
| self.dataOut.flagNoData = False | |||
| self.buffer = None | |||
| self.firstdatatime = None | |||
| self.profIndex = 0 | |||
| return | |||
|
Daniel Valdez
|
r445 | raise ValueError, "The type object %s is not valid"%(self.dataIn.type) | |
|
Miguel Valdez
|
r199 | ||
| def selectChannels(self, channelList): | |||
|
Miguel Valdez
|
r200 | channelIndexList = [] | |
| for channel in channelList: | |||
| index = self.dataOut.channelList.index(channel) | |||
| channelIndexList.append(index) | |||
| self.selectChannelsByIndex(channelIndexList) | |||
|
Miguel Valdez
|
r199 | ||
| def selectChannelsByIndex(self, channelIndexList): | |||
| """ | |||
| Selecciona un bloque de datos en base a canales segun el channelIndexList | |||
| Input: | |||
| channelIndexList : lista sencilla de canales a seleccionar por ej. [2,3,7] | |||
| Affected: | |||
|
Miguel Valdez
|
r201 | self.dataOut.data_spc | |
|
Miguel Valdez
|
r199 | self.dataOut.channelIndexList | |
| self.dataOut.nChannels | |||
| Return: | |||
| None | |||
| """ | |||
|
Miguel Valdez
|
r200 | for channelIndex in channelIndexList: | |
| if channelIndex not in self.dataOut.channelIndexList: | |||
|
Miguel Valdez
|
r199 | print channelIndexList | |
|
Miguel Valdez
|
r200 | raise ValueError, "The value %d in channelIndexList is not valid" %channelIndex | |
|
Miguel Valdez
|
r199 | ||
| nChannels = len(channelIndexList) | |||
|
Miguel Valdez
|
r201 | data_spc = self.dataOut.data_spc[channelIndexList,:] | |
|
Miguel Valdez
|
r199 | ||
|
Miguel Valdez
|
r201 | self.dataOut.data_spc = data_spc | |
|
Miguel Valdez
|
r199 | self.dataOut.channelList = [self.dataOut.channelList[i] for i in channelIndexList] | |
|
Miguel Valdez
|
r200 | # self.dataOut.nChannels = nChannels | |
|
Miguel Valdez
|
r199 | ||
| return 1 | |||
|
Daniel Valdez
|
r192 | ||
|
Miguel Valdez
|
r266 | def selectHeights(self, minHei, maxHei): | |
| """ | |||
| Selecciona un bloque de datos en base a un grupo de valores de alturas segun el rango | |||
| minHei <= height <= maxHei | |||
| Input: | |||
| minHei : valor minimo de altura a considerar | |||
| maxHei : valor maximo de altura a considerar | |||
| Affected: | |||
| Indirectamente son cambiados varios valores a travez del metodo selectHeightsByIndex | |||
| Return: | |||
| 1 si el metodo se ejecuto con exito caso contrario devuelve 0 | |||
| """ | |||
| if (minHei < self.dataOut.heightList[0]) or (minHei > maxHei): | |||
| raise ValueError, "some value in (%d,%d) is not valid" % (minHei, maxHei) | |||
| if (maxHei > self.dataOut.heightList[-1]): | |||
| maxHei = self.dataOut.heightList[-1] | |||
| # raise ValueError, "some value in (%d,%d) is not valid" % (minHei, maxHei) | |||
| minIndex = 0 | |||
| maxIndex = 0 | |||
| heights = self.dataOut.heightList | |||
| inda = numpy.where(heights >= minHei) | |||
| indb = numpy.where(heights <= maxHei) | |||
| try: | |||
| minIndex = inda[0][0] | |||
| except: | |||
| minIndex = 0 | |||
| try: | |||
| maxIndex = indb[0][-1] | |||
| except: | |||
| maxIndex = len(heights) | |||
|
Daniel Valdez
|
r192 | ||
|
Miguel Valdez
|
r266 | self.selectHeightsByIndex(minIndex, maxIndex) | |
| return 1 | |||
|
Daniel Valdez
|
r471 | def getBeaconSignal(self, tauindex = 0, channelindex = 0, hei_ref=None): | |
|
Daniel Valdez
|
r453 | newheis = numpy.where(self.dataOut.heightList>self.dataOut.radarControllerHeaderObj.Taus[tauindex]) | |
|
Daniel Valdez
|
r471 | ||
| if hei_ref != None: | |||
| newheis = numpy.where(self.dataOut.heightList>hei_ref) | |||
|
Daniel Valdez
|
r453 | minIndex = min(newheis[0]) | |
| maxIndex = max(newheis[0]) | |||
| data_spc = self.dataOut.data_spc[:,:,minIndex:maxIndex+1] | |||
| heightList = self.dataOut.heightList[minIndex:maxIndex+1] | |||
| # determina indices | |||
| nheis = int(self.dataOut.radarControllerHeaderObj.txB/(self.dataOut.heightList[1]-self.dataOut.heightList[0])) | |||
| avg_dB = 10*numpy.log10(numpy.sum(data_spc[channelindex,:,:],axis=0)) | |||
| beacon_dB = numpy.sort(avg_dB)[-nheis:] | |||
| beacon_heiIndexList = [] | |||
| for val in avg_dB.tolist(): | |||
| if val >= beacon_dB[0]: | |||
| beacon_heiIndexList.append(avg_dB.tolist().index(val)) | |||
| #data_spc = data_spc[:,:,beacon_heiIndexList] | |||
| data_cspc = None | |||
| if self.dataOut.data_cspc != None: | |||
| data_cspc = self.dataOut.data_cspc[:,:,minIndex:maxIndex+1] | |||
| #data_cspc = data_cspc[:,:,beacon_heiIndexList] | |||
| data_dc = None | |||
| if self.dataOut.data_dc != None: | |||
| data_dc = self.dataOut.data_dc[:,minIndex:maxIndex+1] | |||
| #data_dc = data_dc[:,beacon_heiIndexList] | |||
| self.dataOut.data_spc = data_spc | |||
| self.dataOut.data_cspc = data_cspc | |||
| self.dataOut.data_dc = data_dc | |||
| self.dataOut.heightList = heightList | |||
| self.dataOut.beacon_heiIndexList = beacon_heiIndexList | |||
| return 1 | |||
|
Miguel Valdez
|
r266 | ||
| def selectHeightsByIndex(self, minIndex, maxIndex): | |||
| """ | |||
| Selecciona un bloque de datos en base a un grupo indices de alturas segun el rango | |||
| minIndex <= index <= maxIndex | |||
| Input: | |||
| minIndex : valor de indice minimo de altura a considerar | |||
| maxIndex : valor de indice maximo de altura a considerar | |||
| Affected: | |||
| self.dataOut.data_spc | |||
| self.dataOut.data_cspc | |||
| self.dataOut.data_dc | |||
| self.dataOut.heightList | |||
| Return: | |||
| 1 si el metodo se ejecuto con exito caso contrario devuelve 0 | |||
| """ | |||
| if (minIndex < 0) or (minIndex > maxIndex): | |||
| raise ValueError, "some value in (%d,%d) is not valid" % (minIndex, maxIndex) | |||
| if (maxIndex >= self.dataOut.nHeights): | |||
| maxIndex = self.dataOut.nHeights-1 | |||
| # raise ValueError, "some value in (%d,%d) is not valid" % (minIndex, maxIndex) | |||
| nHeights = maxIndex - minIndex + 1 | |||
| #Spectra | |||
| data_spc = self.dataOut.data_spc[:,:,minIndex:maxIndex+1] | |||
| data_cspc = None | |||
| if self.dataOut.data_cspc != None: | |||
| data_cspc = self.dataOut.data_cspc[:,:,minIndex:maxIndex+1] | |||
| data_dc = None | |||
| if self.dataOut.data_dc != None: | |||
|
Miguel Valdez
|
r291 | data_dc = self.dataOut.data_dc[:,minIndex:maxIndex+1] | |
|
Miguel Valdez
|
r266 | ||
| self.dataOut.data_spc = data_spc | |||
| self.dataOut.data_cspc = data_cspc | |||
| self.dataOut.data_dc = data_dc | |||
| self.dataOut.heightList = self.dataOut.heightList[minIndex:maxIndex+1] | |||
| return 1 | |||
|
Daniel Valdez
|
r445 | def removeDC(self, mode = 2): | |
| jspectra = self.dataOut.data_spc | |||
| jcspectra = self.dataOut.data_cspc | |||
|
Miguel Valdez
|
r266 | ||
|
Daniel Valdez
|
r445 | ||
| num_chan = jspectra.shape[0] | |||
| num_hei = jspectra.shape[2] | |||
| if jcspectra != None: | |||
| jcspectraExist = True | |||
| num_pairs = jcspectra.shape[0] | |||
| else: jcspectraExist = False | |||
| freq_dc = jspectra.shape[1]/2 | |||
| ind_vel = numpy.array([-2,-1,1,2]) + freq_dc | |||
| if ind_vel[0]<0: | |||
| ind_vel[range(0,1)] = ind_vel[range(0,1)] + self.num_prof | |||
| if mode == 1: | |||
|
Daniel Valdez
|
r447 | jspectra[:,freq_dc,:] = (jspectra[:,ind_vel[1],:] + jspectra[:,ind_vel[2],:])/2 #CORRECCION | |
|
Daniel Valdez
|
r445 | ||
| if jcspectraExist: | |||
|
Daniel Valdez
|
r447 | jcspectra[:,freq_dc,:] = (jcspectra[:,ind_vel[1],:] + jcspectra[:,ind_vel[2],:])/2 | |
|
Miguel Valdez
|
r266 | ||
|
Daniel Valdez
|
r445 | if mode == 2: | |
|
Miguel Valdez
|
r266 | ||
|
Daniel Valdez
|
r445 | vel = numpy.array([-2,-1,1,2]) | |
| xx = numpy.zeros([4,4]) | |||
| for fil in range(4): | |||
| xx[fil,:] = vel[fil]**numpy.asarray(range(4)) | |||
| xx_inv = numpy.linalg.inv(xx) | |||
| xx_aux = xx_inv[0,:] | |||
| for ich in range(num_chan): | |||
| yy = jspectra[ich,ind_vel,:] | |||
| jspectra[ich,freq_dc,:] = numpy.dot(xx_aux,yy) | |||
| junkid = jspectra[ich,freq_dc,:]<=0 | |||
| cjunkid = sum(junkid) | |||
| if cjunkid.any(): | |||
| jspectra[ich,freq_dc,junkid.nonzero()] = (jspectra[ich,ind_vel[1],junkid] + jspectra[ich,ind_vel[2],junkid])/2 | |||
| if jcspectraExist: | |||
| for ip in range(num_pairs): | |||
| yy = jcspectra[ip,ind_vel,:] | |||
| jcspectra[ip,freq_dc,:] = numpy.dot(xx_aux,yy) | |||
|
Miguel Valdez
|
r266 | ||
|
Daniel Valdez
|
r445 | self.dataOut.data_spc = jspectra | |
| self.dataOut.data_cspc = jcspectra | |||
| return 1 | |||
|
Miguel Valdez
|
r266 | ||
|
Daniel Valdez
|
r445 | def removeInterference(self, interf = 2,hei_interf = None, nhei_interf = None, offhei_interf = None): | |
| jspectra = self.dataOut.data_spc | |||
| jcspectra = self.dataOut.data_cspc | |||
| jnoise = self.dataOut.getNoise() | |||
| num_incoh = self.dataOut.nIncohInt | |||
| num_channel = jspectra.shape[0] | |||
| num_prof = jspectra.shape[1] | |||
| num_hei = jspectra.shape[2] | |||
| #hei_interf | |||
| if hei_interf == None: | |||
| count_hei = num_hei/2 #Como es entero no importa | |||
| hei_interf = numpy.asmatrix(range(count_hei)) + num_hei - count_hei | |||
| hei_interf = numpy.asarray(hei_interf)[0] | |||
| #nhei_interf | |||
| if (nhei_interf == None): | |||
| nhei_interf = 5 | |||
| if (nhei_interf < 1): | |||
| nhei_interf = 1 | |||
| if (nhei_interf > count_hei): | |||
| nhei_interf = count_hei | |||
| if (offhei_interf == None): | |||
| offhei_interf = 0 | |||
| ind_hei = range(num_hei) | |||
| # mask_prof = numpy.asarray(range(num_prof - 2)) + 1 | |||
| # mask_prof[range(num_prof/2 - 1,len(mask_prof))] += 1 | |||
| mask_prof = numpy.asarray(range(num_prof)) | |||
| num_mask_prof = mask_prof.size | |||
| comp_mask_prof = [0, num_prof/2] | |||
| #noise_exist: Determina si la variable jnoise ha sido definida y contiene la informacion del ruido de cada canal | |||
| if (jnoise.size < num_channel or numpy.isnan(jnoise).any()): | |||
| jnoise = numpy.nan | |||
| noise_exist = jnoise[0] < numpy.Inf | |||
| #Subrutina de Remocion de la Interferencia | |||
| for ich in range(num_channel): | |||
| #Se ordena los espectros segun su potencia (menor a mayor) | |||
| power = jspectra[ich,mask_prof,:] | |||
| power = power[:,hei_interf] | |||
| power = power.sum(axis = 0) | |||
| psort = power.ravel().argsort() | |||
| #Se estima la interferencia promedio en los Espectros de Potencia empleando | |||
| junkspc_interf = jspectra[ich,:,hei_interf[psort[range(offhei_interf, nhei_interf + offhei_interf)]]] | |||
| if noise_exist: | |||
| # tmp_noise = jnoise[ich] / num_prof | |||
| tmp_noise = jnoise[ich] | |||
| junkspc_interf = junkspc_interf - tmp_noise | |||
| #junkspc_interf[:,comp_mask_prof] = 0 | |||
| jspc_interf = junkspc_interf.sum(axis = 0) / nhei_interf | |||
| jspc_interf = jspc_interf.transpose() | |||
| #Calculando el espectro de interferencia promedio | |||
| noiseid = numpy.where(jspc_interf <= tmp_noise/ math.sqrt(num_incoh)) | |||
| noiseid = noiseid[0] | |||
| cnoiseid = noiseid.size | |||
| interfid = numpy.where(jspc_interf > tmp_noise/ math.sqrt(num_incoh)) | |||
| interfid = interfid[0] | |||
| cinterfid = interfid.size | |||
| if (cnoiseid > 0): jspc_interf[noiseid] = 0 | |||
| #Expandiendo los perfiles a limpiar | |||
| if (cinterfid > 0): | |||
| new_interfid = (numpy.r_[interfid - 1, interfid, interfid + 1] + num_prof)%num_prof | |||
| new_interfid = numpy.asarray(new_interfid) | |||
| new_interfid = {x for x in new_interfid} | |||
| new_interfid = numpy.array(list(new_interfid)) | |||
| new_cinterfid = new_interfid.size | |||
| else: new_cinterfid = 0 | |||
| for ip in range(new_cinterfid): | |||
| ind = junkspc_interf[:,new_interfid[ip]].ravel().argsort() | |||
| jspc_interf[new_interfid[ip]] = junkspc_interf[ind[nhei_interf/2],new_interfid[ip]] | |||
| jspectra[ich,:,ind_hei] = jspectra[ich,:,ind_hei] - jspc_interf #Corregir indices | |||
| #Removiendo la interferencia del punto de mayor interferencia | |||
| ListAux = jspc_interf[mask_prof].tolist() | |||
| maxid = ListAux.index(max(ListAux)) | |||
| if cinterfid > 0: | |||
| for ip in range(cinterfid*(interf == 2) - 1): | |||
| ind = (jspectra[ich,interfid[ip],:] < tmp_noise*(1 + 1/math.sqrt(num_incoh))).nonzero() | |||
| cind = len(ind) | |||
| if (cind > 0): | |||
| jspectra[ich,interfid[ip],ind] = tmp_noise*(1 + (numpy.random.uniform(cind) - 0.5)/math.sqrt(num_incoh)) | |||
| ind = numpy.array([-2,-1,1,2]) | |||
| xx = numpy.zeros([4,4]) | |||
| for id1 in range(4): | |||
| xx[:,id1] = ind[id1]**numpy.asarray(range(4)) | |||
| xx_inv = numpy.linalg.inv(xx) | |||
| xx = xx_inv[:,0] | |||
| ind = (ind + maxid + num_mask_prof)%num_mask_prof | |||
| yy = jspectra[ich,mask_prof[ind],:] | |||
| jspectra[ich,mask_prof[maxid],:] = numpy.dot(yy.transpose(),xx) | |||
| indAux = (jspectra[ich,:,:] < tmp_noise*(1-1/math.sqrt(num_incoh))).nonzero() | |||
| jspectra[ich,indAux[0],indAux[1]] = tmp_noise * (1 - 1/math.sqrt(num_incoh)) | |||
| #Remocion de Interferencia en el Cross Spectra | |||
| if jcspectra == None: return jspectra, jcspectra | |||
| num_pairs = jcspectra.size/(num_prof*num_hei) | |||
| jcspectra = jcspectra.reshape(num_pairs, num_prof, num_hei) | |||
|
Miguel Valdez
|
r266 | ||
|
Daniel Valdez
|
r445 | for ip in range(num_pairs): | |
| #------------------------------------------- | |||
| cspower = numpy.abs(jcspectra[ip,mask_prof,:]) | |||
| cspower = cspower[:,hei_interf] | |||
| cspower = cspower.sum(axis = 0) | |||
| cspsort = cspower.ravel().argsort() | |||
| junkcspc_interf = jcspectra[ip,:,hei_interf[cspsort[range(offhei_interf, nhei_interf + offhei_interf)]]] | |||
| junkcspc_interf = junkcspc_interf.transpose() | |||
| jcspc_interf = junkcspc_interf.sum(axis = 1)/nhei_interf | |||
| ind = numpy.abs(jcspc_interf[mask_prof]).ravel().argsort() | |||
| median_real = numpy.median(numpy.real(junkcspc_interf[mask_prof[ind[range(3*num_prof/4)]],:])) | |||
| median_imag = numpy.median(numpy.imag(junkcspc_interf[mask_prof[ind[range(3*num_prof/4)]],:])) | |||
| junkcspc_interf[comp_mask_prof,:] = numpy.complex(median_real, median_imag) | |||
| for iprof in range(num_prof): | |||
| ind = numpy.abs(junkcspc_interf[iprof,:]).ravel().argsort() | |||
| jcspc_interf[iprof] = junkcspc_interf[iprof, ind[nhei_interf/2]] | |||
| #Removiendo la Interferencia | |||
| jcspectra[ip,:,ind_hei] = jcspectra[ip,:,ind_hei] - jcspc_interf | |||
| ListAux = numpy.abs(jcspc_interf[mask_prof]).tolist() | |||
| maxid = ListAux.index(max(ListAux)) | |||
| ind = numpy.array([-2,-1,1,2]) | |||
| xx = numpy.zeros([4,4]) | |||
| for id1 in range(4): | |||
| xx[:,id1] = ind[id1]**numpy.asarray(range(4)) | |||
| xx_inv = numpy.linalg.inv(xx) | |||
| xx = xx_inv[:,0] | |||
| ind = (ind + maxid + num_mask_prof)%num_mask_prof | |||
| yy = jcspectra[ip,mask_prof[ind],:] | |||
| jcspectra[ip,mask_prof[maxid],:] = numpy.dot(yy.transpose(),xx) | |||
| #Guardar Resultados | |||
| self.dataOut.data_spc = jspectra | |||
| self.dataOut.data_cspc = jcspectra | |||
| return 1 | |||
|
Daniel Valdez
|
r402 | ||
| def setRadarFrequency(self, frequency=None): | |||
| if frequency != None: | |||
| self.dataOut.frequency = frequency | |||
| return 1 | |||
|
Daniel Valdez
|
r448 | ||
|
Daniel Valdez
|
r450 | def getNoise(self, minHei=None, maxHei=None, minVel=None, maxVel=None): | |
| #validacion de rango | |||
| if minHei == None: | |||
| minHei = self.dataOut.heightList[0] | |||
|
Daniel Valdez
|
r448 | ||
|
Daniel Valdez
|
r450 | if maxHei == None: | |
| maxHei = self.dataOut.heightList[-1] | |||
|
Daniel Valdez
|
r448 | if (minHei < self.dataOut.heightList[0]) or (minHei > maxHei): | |
|
Daniel Valdez
|
r450 | print 'minHei: %.2f is out of the heights range'%(minHei) | |
| print 'minHei is setting to %.2f'%(self.dataOut.heightList[0]) | |||
| minHei = self.dataOut.heightList[0] | |||
|
Daniel Valdez
|
r448 | ||
|
Daniel Valdez
|
r450 | if (maxHei > self.dataOut.heightList[-1]) or (maxHei < minHei): | |
| print 'maxHei: %.2f is out of the heights range'%(maxHei) | |||
| print 'maxHei is setting to %.2f'%(self.dataOut.heightList[-1]) | |||
|
Daniel Valdez
|
r448 | maxHei = self.dataOut.heightList[-1] | |
|
Daniel Valdez
|
r450 | ||
| # validacion de velocidades | |||
| velrange = self.dataOut.getVelRange(1) | |||
| if minVel == None: | |||
| minVel = velrange[0] | |||
| if maxVel == None: | |||
| maxVel = velrange[-1] | |||
| if (minVel < velrange[0]) or (minVel > maxVel): | |||
| print 'minVel: %.2f is out of the velocity range'%(minVel) | |||
| print 'minVel is setting to %.2f'%(velrange[0]) | |||
| minVel = velrange[0] | |||
| if (maxVel > velrange[-1]) or (maxVel < minVel): | |||
| print 'maxVel: %.2f is out of the velocity range'%(maxVel) | |||
| print 'maxVel is setting to %.2f'%(velrange[-1]) | |||
| maxVel = velrange[-1] | |||
| # seleccion de indices para rango | |||
|
Daniel Valdez
|
r448 | minIndex = 0 | |
| maxIndex = 0 | |||
| heights = self.dataOut.heightList | |||
| inda = numpy.where(heights >= minHei) | |||
| indb = numpy.where(heights <= maxHei) | |||
| try: | |||
| minIndex = inda[0][0] | |||
| except: | |||
| minIndex = 0 | |||
| try: | |||
| maxIndex = indb[0][-1] | |||
| except: | |||
| maxIndex = len(heights) | |||
| if (minIndex < 0) or (minIndex > maxIndex): | |||
| raise ValueError, "some value in (%d,%d) is not valid" % (minIndex, maxIndex) | |||
| if (maxIndex >= self.dataOut.nHeights): | |||
| maxIndex = self.dataOut.nHeights-1 | |||
|
Daniel Valdez
|
r450 | # seleccion de indices para velocidades | |
| indminvel = numpy.where(velrange >= minVel) | |||
| indmaxvel = numpy.where(velrange <= maxVel) | |||
| try: | |||
| minIndexVel = indminvel[0][0] | |||
| except: | |||
| minIndexVel = 0 | |||
| try: | |||
| maxIndexVel = indmaxvel[0][-1] | |||
| except: | |||
| maxIndexVel = len(velrange) | |||
|
Daniel Valdez
|
r448 | ||
|
Daniel Valdez
|
r450 | #seleccion del espectro | |
| data_spc = self.dataOut.data_spc[:,minIndexVel:maxIndexVel+1,minIndex:maxIndex+1] | |||
| #estimacion de ruido | |||
|
Daniel Valdez
|
r448 | noise = numpy.zeros(self.dataOut.nChannels) | |
| for channel in range(self.dataOut.nChannels): | |||
| daux = data_spc[channel,:,:] | |||
| noise[channel] = hildebrand_sekhon(daux, self.dataOut.nIncohInt) | |||
| self.dataOut.noise = noise.copy() | |||
| return 1 | |||
|
Miguel Valdez
|
r266 | ||
|
Daniel Valdez
|
r192 | class IncohInt(Operation): | |
|
Miguel Valdez
|
r201 | ||
| __profIndex = 0 | |||
| __withOverapping = False | |||
| __byTime = False | |||
| __initime = None | |||
| __lastdatatime = None | |||
| __integrationtime = None | |||
|
Miguel Valdez
|
r212 | __buffer_spc = None | |
| __buffer_cspc = None | |||
| __buffer_dc = None | |||
|
Miguel Valdez
|
r201 | ||
| __dataReady = False | |||
|
Daniel Valdez
|
r280 | __timeInterval = None | |
|
Miguel Valdez
|
r201 | n = None | |
|
Daniel Valdez
|
r280 | ||
|
Miguel Valdez
|
r201 | def __init__(self): | |
| self.__isConfig = False | |||
| def setup(self, n=None, timeInterval=None, overlapping=False): | |||
| """ | |||
| Set the parameters of the integration class. | |||
| Inputs: | |||
| n : Number of coherent integrations | |||
| timeInterval : Time of integration. If the parameter "n" is selected this one does not work | |||
| overlapping : | |||
| """ | |||
| self.__initime = None | |||
| self.__lastdatatime = 0 | |||
|
Miguel Valdez
|
r212 | self.__buffer_spc = None | |
| self.__buffer_cspc = None | |||
| self.__buffer_dc = None | |||
|
Miguel Valdez
|
r201 | self.__dataReady = False | |
| if n == None and timeInterval == None: | |||
| raise ValueError, "n or timeInterval should be specified ..." | |||
| if n != None: | |||
| self.n = n | |||
| self.__byTime = False | |||
| else: | |||
|
Daniel Valdez
|
r415 | self.__integrationtime = timeInterval #if (type(timeInterval)!=integer) -> change this line | |
|
Miguel Valdez
|
r201 | self.n = 9999 | |
| self.__byTime = True | |||
| if overlapping: | |||
| self.__withOverapping = True | |||
| else: | |||
| self.__withOverapping = False | |||
|
Miguel Valdez
|
r212 | self.__buffer_spc = 0 | |
| self.__buffer_cspc = 0 | |||
| self.__buffer_dc = 0 | |||
|
Miguel Valdez
|
r201 | ||
| self.__profIndex = 0 | |||
|
Miguel Valdez
|
r212 | def putData(self, data_spc, data_cspc, data_dc): | |
|
Miguel Valdez
|
r201 | ||
| """ | |||
|
Miguel Valdez
|
r212 | Add a profile to the __buffer_spc and increase in one the __profileIndex | |
|
Miguel Valdez
|
r201 | ||
| """ | |||
| if not self.__withOverapping: | |||
|
Miguel Valdez
|
r212 | self.__buffer_spc += data_spc | |
| if data_cspc == None: | |||
| self.__buffer_cspc = None | |||
| else: | |||
| self.__buffer_cspc += data_cspc | |||
| if data_dc == None: | |||
| self.__buffer_dc = None | |||
| else: | |||
| self.__buffer_dc += data_dc | |||
|
Miguel Valdez
|
r201 | self.__profIndex += 1 | |
| return | |||
| #Overlapping data | |||
|
Miguel Valdez
|
r212 | nChannels, nFFTPoints, nHeis = data_spc.shape | |
| data_spc = numpy.reshape(data_spc, (1, nChannels, nFFTPoints, nHeis)) | |||
|
Miguel Valdez
|
r222 | if data_cspc != None: | |
| data_cspc = numpy.reshape(data_cspc, (1, -1, nFFTPoints, nHeis)) | |||
| if data_dc != None: | |||
| data_dc = numpy.reshape(data_dc, (1, -1, nHeis)) | |||
|
Miguel Valdez
|
r201 | ||
| #If the buffer is empty then it takes the data value | |||
|
Miguel Valdez
|
r212 | if self.__buffer_spc == None: | |
|
Miguel Valdez
|
r222 | self.__buffer_spc = data_spc | |
|
Miguel Valdez
|
r212 | ||
| if data_cspc == None: | |||
| self.__buffer_cspc = None | |||
| else: | |||
|
Miguel Valdez
|
r222 | self.__buffer_cspc += data_cspc | |
|
Miguel Valdez
|
r212 | ||
| if data_dc == None: | |||
| self.__buffer_dc = None | |||
| else: | |||
|
Miguel Valdez
|
r222 | self.__buffer_dc += data_dc | |
|
Miguel Valdez
|
r212 | ||
|
Miguel Valdez
|
r201 | self.__profIndex += 1 | |
| return | |||
| #If the buffer length is lower than n then stakcing the data value | |||
| if self.__profIndex < self.n: | |||
|
Miguel Valdez
|
r212 | self.__buffer_spc = numpy.vstack((self.__buffer_spc, data_spc)) | |
|
Miguel Valdez
|
r222 | if data_cspc != None: | |
|
Miguel Valdez
|
r212 | self.__buffer_cspc = numpy.vstack((self.__buffer_cspc, data_cspc)) | |
|
Miguel Valdez
|
r222 | if data_dc != None: | |
|
Miguel Valdez
|
r212 | self.__buffer_dc = numpy.vstack((self.__buffer_dc, data_dc)) | |
|
Miguel Valdez
|
r201 | self.__profIndex += 1 | |
| return | |||
| #If the buffer length is equal to n then replacing the last buffer value with the data value | |||
|
Miguel Valdez
|
r212 | self.__buffer_spc = numpy.roll(self.__buffer_spc, -1, axis=0) | |
| self.__buffer_spc[self.n-1] = data_spc | |||
|
Miguel Valdez
|
r222 | if data_cspc != None: | |
| self.__buffer_cspc = numpy.roll(self.__buffer_cspc, -1, axis=0) | |||
| self.__buffer_cspc[self.n-1] = data_cspc | |||
|
Miguel Valdez
|
r212 | ||
|
Miguel Valdez
|
r222 | if data_dc != None: | |
| self.__buffer_dc = numpy.roll(self.__buffer_dc, -1, axis=0) | |||
| self.__buffer_dc[self.n-1] = data_dc | |||
|
Miguel Valdez
|
r212 | ||
|
Miguel Valdez
|
r201 | self.__profIndex = self.n | |
| return | |||
| def pushData(self): | |||
| """ | |||
| Return the sum of the last profiles and the profiles used in the sum. | |||
| Affected: | |||
| self.__profileIndex | |||
| """ | |||
|
Miguel Valdez
|
r212 | data_spc = None | |
| data_cspc = None | |||
| data_dc = None | |||
|
Miguel Valdez
|
r201 | ||
| if not self.__withOverapping: | |||
|
Miguel Valdez
|
r212 | data_spc = self.__buffer_spc | |
| data_cspc = self.__buffer_cspc | |||
| data_dc = self.__buffer_dc | |||
|
Miguel Valdez
|
r201 | n = self.__profIndex | |
|
Miguel Valdez
|
r212 | self.__buffer_spc = 0 | |
| self.__buffer_cspc = 0 | |||
| self.__buffer_dc = 0 | |||
|
Miguel Valdez
|
r201 | self.__profIndex = 0 | |
|
Miguel Valdez
|
r212 | return data_spc, data_cspc, data_dc, n | |
|
Miguel Valdez
|
r201 | ||
| #Integration with Overlapping | |||
|
Miguel Valdez
|
r212 | data_spc = numpy.sum(self.__buffer_spc, axis=0) | |
| if self.__buffer_cspc != None: | |||
| data_cspc = numpy.sum(self.__buffer_cspc, axis=0) | |||
| if self.__buffer_dc != None: | |||
| data_dc = numpy.sum(self.__buffer_dc, axis=0) | |||
|
Miguel Valdez
|
r201 | n = self.__profIndex | |
|
Miguel Valdez
|
r212 | return data_spc, data_cspc, data_dc, n | |
|
Miguel Valdez
|
r201 | ||
|
Miguel Valdez
|
r212 | def byProfiles(self, *args): | |
|
Miguel Valdez
|
r201 | ||
| self.__dataReady = False | |||
|
Miguel Valdez
|
r212 | avgdata_spc = None | |
| avgdata_cspc = None | |||
| avgdata_dc = None | |||
|
Miguel Valdez
|
r201 | n = None | |
|
Miguel Valdez
|
r212 | self.putData(*args) | |
|
Miguel Valdez
|
r201 | ||
| if self.__profIndex == self.n: | |||
|
Miguel Valdez
|
r212 | avgdata_spc, avgdata_cspc, avgdata_dc, n = self.pushData() | |
|
Miguel Valdez
|
r201 | self.__dataReady = True | |
|
Miguel Valdez
|
r212 | return avgdata_spc, avgdata_cspc, avgdata_dc | |
|
Miguel Valdez
|
r201 | ||
|
Miguel Valdez
|
r212 | def byTime(self, datatime, *args): | |
|
Miguel Valdez
|
r201 | ||
| self.__dataReady = False | |||
|
Miguel Valdez
|
r212 | avgdata_spc = None | |
| avgdata_cspc = None | |||
| avgdata_dc = None | |||
|
Miguel Valdez
|
r201 | n = None | |
|
Miguel Valdez
|
r212 | self.putData(*args) | |
|
Miguel Valdez
|
r201 | ||
| if (datatime - self.__initime) >= self.__integrationtime: | |||
|
Miguel Valdez
|
r212 | avgdata_spc, avgdata_cspc, avgdata_dc, n = self.pushData() | |
|
Miguel Valdez
|
r201 | self.n = n | |
| self.__dataReady = True | |||
|
Miguel Valdez
|
r212 | return avgdata_spc, avgdata_cspc, avgdata_dc | |
|
Miguel Valdez
|
r201 | ||
|
Miguel Valdez
|
r212 | def integrate(self, datatime, *args): | |
|
Miguel Valdez
|
r201 | ||
| if self.__initime == None: | |||
| self.__initime = datatime | |||
| if self.__byTime: | |||
|
Miguel Valdez
|
r212 | avgdata_spc, avgdata_cspc, avgdata_dc = self.byTime(datatime, *args) | |
|
Miguel Valdez
|
r201 | else: | |
|
Miguel Valdez
|
r212 | avgdata_spc, avgdata_cspc, avgdata_dc = self.byProfiles(*args) | |
|
Miguel Valdez
|
r201 | ||
| self.__lastdatatime = datatime | |||
|
Miguel Valdez
|
r212 | if avgdata_spc == None: | |
| return None, None, None, None | |||
|
Miguel Valdez
|
r201 | ||
| avgdatatime = self.__initime | |||
|
Daniel Valdez
|
r389 | try: | |
| self.__timeInterval = (self.__lastdatatime - self.__initime)/(self.n - 1) | |||
| except: | |||
| self.__timeInterval = self.__lastdatatime - self.__initime | |||
|
Miguel Valdez
|
r201 | deltatime = datatime -self.__lastdatatime | |
| if not self.__withOverapping: | |||
| self.__initime = datatime | |||
| else: | |||
| self.__initime += deltatime | |||
|
Miguel Valdez
|
r212 | return avgdatatime, avgdata_spc, avgdata_cspc, avgdata_dc | |
|
Miguel Valdez
|
r201 | ||
| def run(self, dataOut, n=None, timeInterval=None, overlapping=False): | |||
|
Miguel Valdez
|
r325 | if n==1: | |
| dataOut.flagNoData = False | |||
| return | |||
|
Miguel Valdez
|
r201 | if not self.__isConfig: | |
| self.setup(n, timeInterval, overlapping) | |||
| self.__isConfig = True | |||
|
Miguel Valdez
|
r212 | avgdatatime, avgdata_spc, avgdata_cspc, avgdata_dc = self.integrate(dataOut.utctime, | |
| dataOut.data_spc, | |||
| dataOut.data_cspc, | |||
| dataOut.data_dc) | |||
|
Miguel Valdez
|
r201 | ||
| # dataOut.timeInterval *= n | |||
| dataOut.flagNoData = True | |||
| if self.__dataReady: | |||
|
Miguel Valdez
|
r234 | ||
|
Daniel Valdez
|
r245 | dataOut.data_spc = avgdata_spc | |
| dataOut.data_cspc = avgdata_cspc | |||
| dataOut.data_dc = avgdata_dc | |||
|
Miguel Valdez
|
r212 | ||
|
Miguel Valdez
|
r201 | dataOut.nIncohInt *= self.n | |
| dataOut.utctime = avgdatatime | |||
|
Daniel Valdez
|
r280 | #dataOut.timeInterval = dataOut.ippSeconds * dataOut.nCohInt * dataOut.nIncohInt * dataOut.nFFTPoints | |
| dataOut.timeInterval = self.__timeInterval*self.n | |||
|
Miguel Valdez
|
r201 | dataOut.flagNoData = False | |
|
Daniel Valdez
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r233 | ||
|
Daniel Valdez
|
r430 | class ProfileConcat(Operation): | |
| __isConfig = False | |||
| buffer = None | |||
| def __init__(self): | |||
| self.profileIndex = 0 | |||
| def reset(self): | |||
| self.buffer = numpy.zeros_like(self.buffer) | |||
| self.start_index = 0 | |||
| self.times = 1 | |||
| def setup(self, data, m, n=1): | |||
| self.buffer = numpy.zeros((data.shape[0],data.shape[1]*m),dtype=type(data[0,0])) | |||
| self.profiles = data.shape[1] | |||
| self.start_index = 0 | |||
| self.times = 1 | |||
| def concat(self, data): | |||
| self.buffer[:,self.start_index:self.profiles*self.times] = data.copy() | |||
| self.start_index = self.start_index + self.profiles | |||
| def run(self, dataOut, m): | |||
| dataOut.flagNoData = True | |||
| if not self.__isConfig: | |||
| self.setup(dataOut.data, m, 1) | |||
| self.__isConfig = True | |||
| self.concat(dataOut.data) | |||
| self.times += 1 | |||
| if self.times > m: | |||
| dataOut.data = self.buffer | |||
| self.reset() | |||
| dataOut.flagNoData = False | |||
| # se deben actualizar mas propiedades del header y del objeto dataOut, por ejemplo, las alturas | |||
| deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] | |||
| xf = dataOut.heightList[0] + dataOut.nHeights * deltaHeight * 5 | |||
| dataOut.heightList = numpy.arange(dataOut.heightList[0], xf, deltaHeight) | |||
|
Daniel Valdez
|
r233 | class ProfileSelector(Operation): | |
| profileIndex = None | |||
| # Tamanho total de los perfiles | |||
| nProfiles = None | |||
| def __init__(self): | |||
| self.profileIndex = 0 | |||
| def incIndex(self): | |||
| self.profileIndex += 1 | |||
| if self.profileIndex >= self.nProfiles: | |||
| self.profileIndex = 0 | |||
| def isProfileInRange(self, minIndex, maxIndex): | |||
| if self.profileIndex < minIndex: | |||
| return False | |||
| if self.profileIndex > maxIndex: | |||
| return False | |||
| return True | |||
| def isProfileInList(self, profileList): | |||
| if self.profileIndex not in profileList: | |||
| return False | |||
| return True | |||
| def run(self, dataOut, profileList=None, profileRangeList=None): | |||
|
Miguel Valdez
|
r234 | dataOut.flagNoData = True | |
|
Daniel Valdez
|
r233 | self.nProfiles = dataOut.nProfiles | |
| if profileList != None: | |||
|
Miguel Valdez
|
r234 | if self.isProfileInList(profileList): | |
|
Daniel Valdez
|
r233 | dataOut.flagNoData = False | |
|
Miguel Valdez
|
r234 | ||
|
Daniel Valdez
|
r233 | self.incIndex() | |
| return 1 | |||
| elif profileRangeList != None: | |||
| minIndex = profileRangeList[0] | |||
| maxIndex = profileRangeList[1] | |||
|
Miguel Valdez
|
r234 | if self.isProfileInRange(minIndex, maxIndex): | |
|
Daniel Valdez
|
r233 | dataOut.flagNoData = False | |
|
Miguel Valdez
|
r234 | ||
|
Daniel Valdez
|
r233 | self.incIndex() | |
| return 1 | |||
|
Miguel Valdez
|
r234 | ||
|
Daniel Valdez
|
r233 | else: | |
| raise ValueError, "ProfileSelector needs profileList or profileRangeList" | |||
| return 0 | |||
|
Daniel Valdez
|
r334 | class SpectraHeisProc(ProcessingUnit): | |
| def __init__(self): | |||
| self.objectDict = {} | |||
| # self.buffer = None | |||
| # self.firstdatatime = None | |||
| # self.profIndex = 0 | |||
| self.dataOut = SpectraHeis() | |||
| def __updateObjFromInput(self): | |||
|
Daniel Valdez
|
r359 | self.dataOut.timeZone = self.dataIn.timeZone | |
| self.dataOut.dstFlag = self.dataIn.dstFlag | |||
| self.dataOut.errorCount = self.dataIn.errorCount | |||
| self.dataOut.useLocalTime = self.dataIn.useLocalTime | |||
|
Daniel Valdez
|
r334 | self.dataOut.radarControllerHeaderObj = self.dataIn.radarControllerHeaderObj.copy()# | |
| self.dataOut.systemHeaderObj = self.dataIn.systemHeaderObj.copy()# | |||
| self.dataOut.channelList = self.dataIn.channelList | |||
| self.dataOut.heightList = self.dataIn.heightList | |||
| # self.dataOut.dtype = self.dataIn.dtype | |||
| self.dataOut.dtype = numpy.dtype([('real','<f4'),('imag','<f4')]) | |||
| # self.dataOut.nHeights = self.dataIn.nHeights | |||
| # self.dataOut.nChannels = self.dataIn.nChannels | |||
| self.dataOut.nBaud = self.dataIn.nBaud | |||
| self.dataOut.nCode = self.dataIn.nCode | |||
| self.dataOut.code = self.dataIn.code | |||
| # self.dataOut.nProfiles = 1 | |||
| # self.dataOut.nProfiles = self.dataOut.nFFTPoints | |||
| self.dataOut.nFFTPoints = self.dataIn.nHeights | |||
| # self.dataOut.channelIndexList = self.dataIn.channelIndexList | |||
| # self.dataOut.flagNoData = self.dataIn.flagNoData | |||
| self.dataOut.flagTimeBlock = self.dataIn.flagTimeBlock | |||
| self.dataOut.utctime = self.dataIn.utctime | |||
| # self.dataOut.utctime = self.firstdatatime | |||
| self.dataOut.flagDecodeData = self.dataIn.flagDecodeData #asumo q la data esta decodificada | |||
| self.dataOut.flagDeflipData = self.dataIn.flagDeflipData #asumo q la data esta sin flip | |||
|
Daniel Valdez
|
r357 | # self.dataOut.flagShiftFFT = self.dataIn.flagShiftFFT | |
|
Daniel Valdez
|
r334 | self.dataOut.nCohInt = self.dataIn.nCohInt | |
| self.dataOut.nIncohInt = 1 | |||
| self.dataOut.ippSeconds= self.dataIn.ippSeconds | |||
| self.dataOut.windowOfFilter = self.dataIn.windowOfFilter | |||
| self.dataOut.timeInterval = self.dataIn.timeInterval*self.dataOut.nIncohInt | |||
| # self.dataOut.set=self.dataIn.set | |||
| # self.dataOut.deltaHeight=self.dataIn.deltaHeight | |||
|
Daniel Valdez
|
r439 | def __updateObjFromFits(self): | |
| self.dataOut.utctime = self.dataIn.utctime | |||
| self.dataOut.channelIndexList = self.dataIn.channelIndexList | |||
| self.dataOut.channelList = self.dataIn.channelList | |||
| self.dataOut.heightList = self.dataIn.heightList | |||
| self.dataOut.data_spc = self.dataIn.data | |||
| self.dataOut.timeInterval = self.dataIn.timeInterval | |||
| self.dataOut.timeZone = self.dataIn.timeZone | |||
| self.dataOut.useLocalTime = True | |||
| # self.dataOut. | |||
| # self.dataOut. | |||
|
Daniel Valdez
|
r334 | def __getFft(self): | |
| fft_volt = numpy.fft.fft(self.dataIn.data, axis=1) | |||
| fft_volt = numpy.fft.fftshift(fft_volt,axes=(1,)) | |||
| spc = numpy.abs(fft_volt * numpy.conjugate(fft_volt))/(self.dataOut.nFFTPoints) | |||
| self.dataOut.data_spc = spc | |||
| def init(self): | |||
| self.dataOut.flagNoData = True | |||
|
Daniel Valdez
|
r439 | if self.dataIn.type == "Fits": | |
| self.__updateObjFromFits() | |||
| self.dataOut.flagNoData = False | |||
| return | |||
|
Daniel Valdez
|
r334 | if self.dataIn.type == "SpectraHeis": | |
| self.dataOut.copy(self.dataIn) | |||
| return | |||
| if self.dataIn.type == "Voltage": | |||
| self.__updateObjFromInput() | |||
| self.__getFft() | |||
| self.dataOut.flagNoData = False | |||
| return | |||
|
Daniel Valdez
|
r445 | raise ValueError, "The type object %s is not valid"%(self.dataIn.type) | |
|
Daniel Valdez
|
r334 | ||
| def selectChannels(self, channelList): | |||
| channelIndexList = [] | |||
| for channel in channelList: | |||
| index = self.dataOut.channelList.index(channel) | |||
| channelIndexList.append(index) | |||
| self.selectChannelsByIndex(channelIndexList) | |||
| def selectChannelsByIndex(self, channelIndexList): | |||
| """ | |||
| Selecciona un bloque de datos en base a canales segun el channelIndexList | |||
| Input: | |||
| channelIndexList : lista sencilla de canales a seleccionar por ej. [2,3,7] | |||
| Affected: | |||
| self.dataOut.data | |||
| self.dataOut.channelIndexList | |||
| self.dataOut.nChannels | |||
| self.dataOut.m_ProcessingHeader.totalSpectra | |||
| self.dataOut.systemHeaderObj.numChannels | |||
| self.dataOut.m_ProcessingHeader.blockSize | |||
| Return: | |||
| None | |||
| """ | |||
| for channelIndex in channelIndexList: | |||
| if channelIndex not in self.dataOut.channelIndexList: | |||
| print channelIndexList | |||
| raise ValueError, "The value %d in channelIndexList is not valid" %channelIndex | |||
| nChannels = len(channelIndexList) | |||
| data_spc = self.dataOut.data_spc[channelIndexList,:] | |||
| self.dataOut.data_spc = data_spc | |||
| self.dataOut.channelList = [self.dataOut.channelList[i] for i in channelIndexList] | |||
| return 1 | |||
| class IncohInt4SpectraHeis(Operation): | |||
| __isConfig = False | |||
| __profIndex = 0 | |||
| __withOverapping = False | |||
| __byTime = False | |||
| __initime = None | |||
| __lastdatatime = None | |||
| __integrationtime = None | |||
| __buffer = None | |||
| __dataReady = False | |||
| n = None | |||
| def __init__(self): | |||
| self.__isConfig = False | |||
| def setup(self, n=None, timeInterval=None, overlapping=False): | |||
| """ | |||
| Set the parameters of the integration class. | |||
| Inputs: | |||
| n : Number of coherent integrations | |||
| timeInterval : Time of integration. If the parameter "n" is selected this one does not work | |||
| overlapping : | |||
| """ | |||
| self.__initime = None | |||
| self.__lastdatatime = 0 | |||
| self.__buffer = None | |||
| self.__dataReady = False | |||
| if n == None and timeInterval == None: | |||
| raise ValueError, "n or timeInterval should be specified ..." | |||
| if n != None: | |||
| self.n = n | |||
| self.__byTime = False | |||
| else: | |||
| self.__integrationtime = timeInterval #* 60. #if (type(timeInterval)!=integer) -> change this line | |||
| self.n = 9999 | |||
| self.__byTime = True | |||
| if overlapping: | |||
| self.__withOverapping = True | |||
| self.__buffer = None | |||
| else: | |||
| self.__withOverapping = False | |||
| self.__buffer = 0 | |||
| self.__profIndex = 0 | |||
| def putData(self, data): | |||
| """ | |||
| Add a profile to the __buffer and increase in one the __profileIndex | |||
| """ | |||
| if not self.__withOverapping: | |||
| self.__buffer += data.copy() | |||
| self.__profIndex += 1 | |||
| return | |||
| #Overlapping data | |||
| nChannels, nHeis = data.shape | |||
| data = numpy.reshape(data, (1, nChannels, nHeis)) | |||
| #If the buffer is empty then it takes the data value | |||
| if self.__buffer == None: | |||
| self.__buffer = data | |||
| self.__profIndex += 1 | |||
| return | |||
| #If the buffer length is lower than n then stakcing the data value | |||
| if self.__profIndex < self.n: | |||
| self.__buffer = numpy.vstack((self.__buffer, data)) | |||
| self.__profIndex += 1 | |||
| return | |||
| #If the buffer length is equal to n then replacing the last buffer value with the data value | |||
| self.__buffer = numpy.roll(self.__buffer, -1, axis=0) | |||
| self.__buffer[self.n-1] = data | |||
| self.__profIndex = self.n | |||
| return | |||
| def pushData(self): | |||
| """ | |||
| Return the sum of the last profiles and the profiles used in the sum. | |||
| Affected: | |||
| self.__profileIndex | |||
| """ | |||
| if not self.__withOverapping: | |||
| data = self.__buffer | |||
| n = self.__profIndex | |||
| self.__buffer = 0 | |||
| self.__profIndex = 0 | |||
| return data, n | |||
| #Integration with Overlapping | |||
| data = numpy.sum(self.__buffer, axis=0) | |||
| n = self.__profIndex | |||
| return data, n | |||
| def byProfiles(self, data): | |||
| self.__dataReady = False | |||
| avgdata = None | |||
| n = None | |||
| self.putData(data) | |||
| if self.__profIndex == self.n: | |||
| avgdata, n = self.pushData() | |||
| self.__dataReady = True | |||
| return avgdata | |||
| def byTime(self, data, datatime): | |||
| self.__dataReady = False | |||
| avgdata = None | |||
| n = None | |||
| self.putData(data) | |||
| if (datatime - self.__initime) >= self.__integrationtime: | |||
| avgdata, n = self.pushData() | |||
| self.n = n | |||
| self.__dataReady = True | |||
| return avgdata | |||
| def integrate(self, data, datatime=None): | |||
| if self.__initime == None: | |||
| self.__initime = datatime | |||
| if self.__byTime: | |||
| avgdata = self.byTime(data, datatime) | |||
| else: | |||
| avgdata = self.byProfiles(data) | |||
| self.__lastdatatime = datatime | |||
| if avgdata == None: | |||
| return None, None | |||
| avgdatatime = self.__initime | |||
| deltatime = datatime -self.__lastdatatime | |||
| if not self.__withOverapping: | |||
| self.__initime = datatime | |||
| else: | |||
| self.__initime += deltatime | |||
| return avgdata, avgdatatime | |||
| def run(self, dataOut, **kwargs): | |||
| if not self.__isConfig: | |||
| self.setup(**kwargs) | |||
| self.__isConfig = True | |||
| avgdata, avgdatatime = self.integrate(dataOut.data_spc, dataOut.utctime) | |||
| # dataOut.timeInterval *= n | |||
| dataOut.flagNoData = True | |||
| if self.__dataReady: | |||
| dataOut.data_spc = avgdata | |||
| dataOut.nIncohInt *= self.n | |||
| # dataOut.nCohInt *= self.n | |||
| dataOut.utctime = avgdatatime | |||
| dataOut.timeInterval = dataOut.ippSeconds * dataOut.nIncohInt | |||
| # dataOut.timeInterval = self.__timeInterval*self.n | |||
|
Daniel Valdez
|
r340 | dataOut.flagNoData = False | |