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import numpy
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from Model.JROHeader import *
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from Model.Voltage import Voltage
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def hildebrand_sekhon(Data, navg=1 ):
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"""
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This method is for the objective determination of de noise level in Doppler spectra. This
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implementation technique is based on the fact that the standard deviation of the spectral
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densities is equal to the mean spectral density for white Gaussian noise
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Inputs:
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Data : heights
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navg : numbers of averages
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Return:
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-1 : any error
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anoise : noise's level
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"""
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divisor = 8
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ratio = 7 / divisor
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data = Data.reshape(-1)
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npts = data.size #numbers of points of the data
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if npts < 32:
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print "error in noise - requires at least 32 points"
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return -1.0
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# data sorted in ascending order
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nmin = int(npts/divisor + ratio);
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s = 0.0
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s2 = 0.0
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data2 = data[:npts]
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data2.sort()
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for i in range(nmin):
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s += data2[i]
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s2 += data2[i]**2;
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icount = nmin
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iflag = 0
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for i in range(nmin, npts):
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s += data2[i];
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s2 += data2[i]**2
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icount=icount+1;
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p = s / float(icount);
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p2 = p**2;
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q = s2 / float(icount) - p2;
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leftc = p2;
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rightc = q * float(navg);
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if leftc > rightc:
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iflag = 1; #No weather signal
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# Signal detect: R2 < 1 (R2 = leftc/rightc)
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if(leftc < rightc):
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if iflag:
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break
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anoise = 0.0;
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for j in range(i):
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anoise += data2[j];
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anoise = anoise / float(i);
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return anoise;
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class Noise():
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"""
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Clase que implementa los metodos necesarios para deternimar el nivel de ruido en un Spectro Doppler
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"""
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m_DataObj = None
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def __init__(self, m_Voltage=None):
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"""
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Inicializador de la clase Noise para la la determinacion del nivel de ruido en un Spectro Doppler.
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Affected:
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self.m_DataObj
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Return:
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None
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"""
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# if m_Voltage == None:
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# m_Voltage = Voltage()
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#
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# if not(isinstance(m_Voltage, Voltage)):
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# raise ValueError, "in Noise class, m_Voltage must be an Voltage class object"
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self.m_DataObj = m_Voltage
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def getNoiseLevelByHildebrandSekhon(self):
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"""
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Determino el nivel de ruido usando el metodo Hildebrand-Sekhon
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Return:
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noise level
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"""
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data = self.m_DataObj.data # heights x perfiles
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#heights = numpy.transpose( Data, (2,0,1) ) # channel x profile x height
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#data = Data[0,0,:]
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noiselevel = hildebrand_sekhon(data)
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print noiselevel
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