schain Commit - r1508:6520a1ac8270 · Jicamarca Repository

1255

1256

'''

1256

'''

1257

1258

def run(self, dataOut):

1258

def run(self, dataOut,wradar=False):

1259

1260

data = dataOut.data_pre[0]

1260

data = dataOut.data_pre[0]

1261

absc = dataOut.abscissaList[:-1]

1261

absc = dataOut.abscissaList[:-1]

1264

data_param = numpy.zeros((nChannel, 4, data.shape[2]))

1264

data_param = numpy.zeros((nChannel, 4, data.shape[2]))

1265

1266

for ind in range(nChannel):

1266

for ind in range(nChannel):

1267

data_param[ind,:,:] = self.__calculateMoments( data[ind,:,:] , absc , noise[ind] )

1267

data_param[ind,:,:] = self.__calculateMoments( data[ind,:,:] , absc , noise[ind],wradar=wradar )

1268

1269

dataOut.moments = data_param[:,1:,:]

1269

dataOut.moments = data_param[:,1:,:]

1270

dataOut.data_snr = data_param[:,0]

1270

dataOut.data_snr = data_param[:,0]

1274

return dataOut

1274

return dataOut

1275

1276

def __calculateMoments(self, oldspec, oldfreq, n0,

1276

def __calculateMoments(self, oldspec, oldfreq, n0,

1277

nicoh = None, graph = None, smooth = None, type1 = None, fwindow = None, snrth = None, dc = None, aliasing = None, oldfd = None, wwauto = None):

1277

nicoh = None, graph = None, smooth = None, type1 = None, fwindow = None, snrth = None, dc = None, aliasing = None, oldfd = None, wwauto = None,wradar=None):

1278

1279

if (nicoh is None): nicoh = 1

1279

if (nicoh is None): nicoh = 1

1280

if (graph is None): graph = 0

1280

if (graph is None): graph = 0

1347

snr = 1.e-20

1347

snr = 1.e-20

1348

1349

# vec_power[ind] = power #D. Scipión replaced with the line below

1349

# vec_power[ind] = power #D. Scipión replaced with the line below

1350

vec_power[ind] = total_power

1350

if wradar ==False:

1351

vec_power[ind] = total_power

1352

else:

1353

vec_power[ind] = signal_power

1354

1351

vec_fd[ind] = fd

1355

vec_fd[ind] = fd

1352

vec_w[ind] = w

1356

vec_w[ind] = w

1353

vec_snr[ind] = snr

1357

vec_snr[ind] = snr

1354

1355

return numpy.vstack((vec_snr, vec_power, vec_fd, vec_w))

1358

return numpy.vstack((vec_snr, vec_power, vec_fd, vec_w))

1356

1359

1357

#------------------ Get SA Parameters --------------------------

1360

#------------------ Get SA Parameters --------------------------

3973

data_param[:,3,:] = dataOut.dataPP_SNR

3976

data_param[:,3,:] = dataOut.dataPP_SNR

3974

if type == "Spectra":

3977

if type == "Spectra":

3975

factor = dataOut.normFactor

3978

factor = dataOut.normFactor

3976

data_param[:,0,:] = dataOut.data_~~POW~~/(factor)

3979

data_param[:,0,:] = dataOut.data_pow/(factor)

3977

data_param[:,1,:] = dataOut.data_~~DOP~~

3980

data_param[:,1,:] = dataOut.data_dop

3978

data_param[:,2,:] = dataOut.data_~~WIDTH~~

3981

data_param[:,2,:] = dataOut.data_width

3979

data_param[:,3,:] = dataOut.data_~~SNR~~

3982

data_param[:,3,:] = dataOut.data_snr

3980

3981

return data_param

3983

return data_param

3982

3984

3983

def getCoeficienteCorrelacionROhv_R(self,dataOut):

3985

def getCoeficienteCorrelacionROhv_R(self,dataOut):

3985

nHeis = dataOut.nHeights

3987

nHeis = dataOut.nHeights

3986

data_RhoHV_R = numpy.zeros((nHeis))

3988

data_RhoHV_R = numpy.zeros((nHeis))

3987

if type == "Voltage":

3989

if type == "Voltage":

3988

powa = dataOut.data~~PP_POWER~~[0]

3990

powa = dataOut.data_param[0,0,:]

3989

powb = dataOut.data~~PP_POWER~~[1]

3991

powb = dataOut.data_param[1,0,:]

3990

ccf = dataOut.dataPP_CCF

3992

ccf = dataOut.dataPP_CCF

3991

avgcoherenceComplex = ccf / numpy.sqrt(powa * powb)

3993

avgcoherenceComplex = ccf / numpy.sqrt(powa * powb)

3992

data_RhoHV_R = numpy.abs(avgcoherenceComplex)

3994

data_RhoHV_R = numpy.abs(avgcoherenceComplex)

4000

nHeis = dataOut.nHeights

4002

nHeis = dataOut.nHeights

4001

data_PhiD_P = numpy.zeros((nHeis))

4003

data_PhiD_P = numpy.zeros((nHeis))

4002

if type == "Voltage":

4004

if type == "Voltage":

4003

powa = dataOut.data~~PP_POWER~~[0]

4005

powa = dataOut.data_param[0,0,:]

4004

powb = dataOut.data~~PP_POWER~~[1]

4006

powb = dataOut.data_param[1,0,:]

4005

ccf = dataOut.dataPP_CCF

4007

ccf = dataOut.dataPP_CCF

4006

avgcoherenceComplex = ccf / numpy.sqrt(powa * powb)

4008

avgcoherenceComplex = ccf / numpy.sqrt(powa * powb)

4007

if phase:

4009

if phase:

4041

#print("Pr last10",10*numpy.log10(Pr[0,-20:]))

4043

#print("Pr last10",10*numpy.log10(Pr[0,-20:]))

4042

#print("LCTE",10*numpy.log10(self.lambda_**4/( numpy.pi**5 * self.Km**2)))

4044

#print("LCTE",10*numpy.log10(self.lambda_**4/( numpy.pi**5 * self.Km**2)))

4043

if self.Pt<0.3:

4045

if self.Pt<0.3:

4044

factor=-31

4046

factor=10.072

4045

else:

4047

else:

4046

factor=-18

4048

factor=23.072

4047

4049

4048

dBZeh = 10*numpy.log10(Zeh) + factor

4050

dBZeh = 10*numpy.log10(Zeh) + factor

4049

if type=='N':

4051

if type=='N':

	Site-wide shortcuts
/	Use quick search box
g h	Goto home page
g g	Goto my private gists page
g G	Goto my public gists page
g 0-9	Goto bookmarked items from 0-9
n r	New repository page
n g	New gist page

	Repositories
g s	Goto summary page
g c	Goto changelog page
g f	Goto files page
g F	Goto files page with file search activated
g p	Goto pull requests page
g o	Goto repository settings
g O	Goto repository access permissions settings
t s	Toggle sidebar on some pages

                 '''
-                def run(self, dataOut):
+                def run(self, dataOut,wradar=False):
                     data = dataOut.data_pre[0]
                     absc = dataOut.abscissaList[:-1]
                     data_param = numpy.zeros((nChannel, 4, data.shape[2]))
                     for ind in range(nChannel):
-                        data_param[ind,:,:] = self.__calculateMoments( data[ind,:,:] , absc , noise[ind] )
+                        data_param[ind,:,:] = self.__calculateMoments( data[ind,:,:] , absc , noise[ind],wradar=wradar )
                     dataOut.moments = data_param[:,1:,:]
                     dataOut.data_snr = data_param[:,0]
                     return dataOut
                 def __calculateMoments(self, oldspec, oldfreq, n0,
-                                       nicoh = None, graph = None, smooth = None, type1 = None, fwindow = None, snrth = None, dc = None, aliasing = None, oldfd = None, wwauto = None):
+                                       nicoh = None, graph = None, smooth = None, type1 = None, fwindow = None, snrth = None, dc = None, aliasing = None, oldfd = None, wwauto = None,wradar=None):
                     if (nicoh is None): nicoh = 1
                     if (graph is None): graph = 0
                             snr = 1.e-20
                         # vec_power[ind] = power    #D. Scipión replaced with the line below
-                        vec_power[ind] = total_power
+                        if wradar ==False:
+                            vec_power[ind] = total_power
+                        else:
+                            vec_power[ind] = signal_power
                         vec_fd[ind] = fd
-                        vec_w[ind] = w
+                        vec_w[ind]  =  w
                         vec_snr[ind] = snr
                     return numpy.vstack((vec_snr, vec_power, vec_fd, vec_w))
                 #------------------    Get SA Parameters    --------------------------
                         data_param[:,3,:] = dataOut.dataPP_SNR
                     if type == "Spectra":
                         factor = dataOut.normFactor
-                        data_param[:,0,:] = dataOut.data_POW/(factor)
+                        data_param[:,0,:] = dataOut.data_pow/(factor)
-                        data_param[:,1,:] = dataOut.data_DOP
+                        data_param[:,1,:] = dataOut.data_dop
-                        data_param[:,2,:] = dataOut.data_WIDTH
+                        data_param[:,2,:] = dataOut.data_width
-                        data_param[:,3,:] = dataOut.data_SNR
+                        data_param[:,3,:] = dataOut.data_snr
                     return data_param
                 def getCoeficienteCorrelacionROhv_R(self,dataOut):
                     nHeis = dataOut.nHeights
                     data_RhoHV_R = numpy.zeros((nHeis))
                     if type == "Voltage":
-                        powa  = dataOut.dataPP_POWER[0]
+                        powa  = dataOut.data_param[0,0,:]
-                        powb = dataOut.dataPP_POWER[1]
+                        powb  = dataOut.data_param[1,0,:]
                         ccf   = dataOut.dataPP_CCF
                         avgcoherenceComplex = ccf / numpy.sqrt(powa * powb)
                         data_RhoHV_R = numpy.abs(avgcoherenceComplex)
                     nHeis = dataOut.nHeights
                     data_PhiD_P = numpy.zeros((nHeis))
                     if type == "Voltage":
-                        powa  = dataOut.dataPP_POWER[0]
+                        powa  = dataOut.data_param[0,0,:]
-                        powb = dataOut.dataPP_POWER[1]
+                        powb  = dataOut.data_param[1,0,:]
                         ccf   = dataOut.dataPP_CCF
                         avgcoherenceComplex = ccf / numpy.sqrt(powa * powb)
                         if phase:
                     #print("Pr last10",10*numpy.log10(Pr[0,-20:]))
                     #print("LCTE",10*numpy.log10(self.lambda_**4/( numpy.pi**5 * self.Km**2)))
                     if self.Pt<0.3:
-                        factor=-31
+                        factor=10.072
                     else:
-                        factor=-18
+                        factor=23.072
                     dBZeh = 10*numpy.log10(Zeh) + factor
                     if type=='N':