From af752b8a14b4fe64c21301ed63ef29f43cd46112 2022-07-19 13:21:56
From: joabAM <joab.apaza32@gmail.com>
Date: 2022-07-19 13:21:56
Subject: [PATCH] pc amisr

---

diff --git a/schainpy/model/proc/jroproc_spectra.py b/schainpy/model/proc/jroproc_spectra.py
index 821c1fd..2a6d9fb 100644
--- a/schainpy/model/proc/jroproc_spectra.py
+++ b/schainpy/model/proc/jroproc_spectra.py
@@ -705,7 +705,7 @@ class getNoiseB(Operation):
         #print("2: ",10*numpy.log10(self.dataOut.noise_estimation/64))
 
         #print(self.dataOut.flagNoData)
-        print("getNoise Done")
+        print("getNoise Done", noise)
         return self.dataOut
 
     def getNoiseByMean(self,data):
diff --git a/schainpy/model/proc/jroproc_voltage.py b/schainpy/model/proc/jroproc_voltage.py
index 22f413d..bb026d6 100644
--- a/schainpy/model/proc/jroproc_voltage.py
+++ b/schainpy/model/proc/jroproc_voltage.py
@@ -6,7 +6,7 @@ from schainpy.model.data.jrodata import Voltage,hildebrand_sekhon
 from schainpy.utils import log
 from schainpy.model.io.utils import getHei_index
 from time import time
-#import datetime
+
 import numpy
 #import copy
 from schainpy.model.data import _noise
@@ -1890,9 +1890,6 @@ class SSheightProfiles2(Operation):
 
 
 
-#import skimage.color
-#import skimage.io
-#import matplotlib.pyplot as plt
 
 class removeProfileByFaradayHS(Operation):
     '''
@@ -2024,14 +2021,16 @@ class removeProfileByFaradayHS(Operation):
         return data
 
     def cleanOutliersByBlock(self):
+        import matplotlib.pyplot as plt
+        import datetime
         #print(self.__buffer_data[0].shape)
         data = self.__buffer_data#.copy()
-        #print("cleaning shape inpt: ",data.shape)
-        '''
+        print("cleaning shape inpt: ",data.shape)
+
         self.__buffer_data = []
 
-        spectrum = numpy.fft.fft2(data, axes=(0,2))
-        #print("spc : ",spectrum.shape)
+        spectrum = numpy.fft.fft2(data[:,:,self.minHei_idx:], axes=(0,2))
+        print("spc : ",spectrum.shape)
         (nch,nsamples, nh) = spectrum.shape
         data2 = None
         #print(data.shape)
@@ -2048,41 +2047,48 @@ class removeProfileByFaradayHS(Operation):
 
             x, y = numpy.meshgrid(numpy.sort(freqh),numpy.sort(freqv))
             z = numpy.abs(spectrum[ch,:,:])
+            phase = numpy.angle(spectrum[ch,:,:])
             # Find all peaks higher than the 98th percentile
-            peaks = z < numpy.percentile(z, 98)
+            peaks = z < numpy.percentile(z, 99)
             #print(peaks)
             # Set those peak coefficients to zero
             spectrum2 = spectrum2 * peaks.astype(int)
-            data2 = numpy.fft.ifft2(spectrum2)
+            data2 = numpy.fft.ifft2(spectrum2,axes=(0,2))
 
             dat = numpy.log10(z.T)
-            dat2 = numpy.log10(spectrum2.T)
-
-            # m = numpy.mean(dat)
-            # o = numpy.std(dat)
-            # fig, ax = plt.subplots(2,1,figsize=(8, 6))
-            #
-            # c = ax[0].pcolormesh(x, y, dat, cmap ='YlGnBu', vmin = (m-2*o), vmax = (m+2*o))
-            # #c = ax.pcolor( z.T , cmap ='gray', vmin = (m-2*o), vmax = (m+2*o))
-            # date_time = datetime.datetime.fromtimestamp(self.__buffer_times[0]).strftime('%Y-%m-%d %H:%M:%S.%f')
-            # #strftime('%Y-%m-%d %H:%M:%S')
-            # ax[0].set_title('Spectrum magnitude '+date_time)
-            # fig.canvas.set_window_title('Spectrum magnitude {} '.format(self.n)+date_time)
-            #
-            #
-            # c = ax[1].pcolormesh(x, y, dat, cmap ='YlGnBu', vmin = (m-2*o), vmax = (m+2*o))
-            # fig.colorbar(c)
-            # plt.show()
+            pdat = numpy.log10(phase.T)
+            dat2 = numpy.log10(numpy.abs(spectrum2.T))
+
+            m = numpy.mean(dat)
+            o = numpy.std(dat)
+            fig, ax = plt.subplots(1,2,figsize=(12, 6))
+
+            colormap = 'jet'
+            #c = ax[0].pcolormesh(x, y, dat, cmap =colormap, vmin = (m-2*o)/2, vmax = (m+2*o))
+            c = ax[0].pcolormesh(x, y, dat, cmap =colormap, vmin = 4.2, vmax = 5.0)
+            fig.colorbar(c, ax=ax[0])
+            #print("aqui estoy", dat.shape)
+            #c = ax.pcolor( z.T , cmap ='gray', vmin = (m-2*o), vmax = (m+2*o))
+            date_time = datetime.datetime.fromtimestamp(self.__buffer_times[0]).strftime('%Y-%m-%d %H:%M:%S.%f')
+            #strftime('%Y-%m-%d %H:%M:%S')
+            #ax[0].set_title('Spectrum magnitude '+date_time)
+            fig.canvas.set_window_title('Spectrum magnitude {} '.format(self.n)+date_time)
+            #print("aqui estoy2",dat2[:,:,0].shape)
+            c = ax[1].pcolormesh(x, y, pdat, cmap =colormap, vmin = -0.0, vmax = 0.5)
+            #c = ax[1].pcolormesh(x, y, dat2[:,:,0], cmap =colormap, vmin = (m-2*o)/2, vmax = (m+2*o)-1)
+            #print("aqui estoy3")
+            fig.colorbar(c, ax=ax[1])
+            plt.show()
 
         #print(data2.shape)
 
-        data = data2
+        #data = data2
+
+        #cleanBlock = numpy.fft.ifft2(data, axes=(0,2)).reshape()
 
-        #cleanBlock = numpy.fft.ifft2(spectrum, axes=(0,2)).reshape()
-        '''
         #print("cleanOutliersByBlock Done")
 
-        return self.filterSatsProfiles()
+        return data
 
 
 
@@ -2094,7 +2100,7 @@ class removeProfileByFaradayHS(Operation):
         else:
             self.__buffer_data = numpy.concatenate((self.__buffer_data,data), axis=1)#en perfiles
         self.__profIndex += 1
-        #self.__buffer_times.append(datatime)
+        self.__buffer_times.append(datatime)
 
     def getData(self, data, datatime=None):