In [1]:

    

%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
import scipy.signal

framesize = 1024


    

In [2]:

    

a = np.fromfile('symbols_before_eclipse.f32', dtype = 'float32')[1000:20000] # 2020-03-25 before eclipse
b = np.fromfile('symbols_after_eclipse.f32', dtype = 'float32')[305000:] # 2020-03-25 after eclipse
c = np.fromfile('symbols_20200329.f32', dtype = 'float32')[2000:90000] # 2020-03-29 before eclipse


    

In [3]:

    

for x in [a, b, c]:
    plt.figure(figsize = (8,4), facecolor = 'w')
    plt.plot(x, ',')
    plt.ylim((-3,3))
    plt.title('BPSK symbols')
    plt.xlabel('Symbol')
    plt.ylabel('Amplitude');


    

In [4]:

    

a_diff = np.sign(-a[1:]*a[:-1])
b_diff = np.sign(-b[1:]*b[:-1])
c_diff = np.sign(-c[1:]*c[:-1])
corr = np.fft.ifft(np.fft.fft(a_diff[:framesize])*np.conj(np.fft.fft(b_diff[:framesize])))
corr2 = np.fft.ifft(np.fft.fft(a_diff[:framesize])*np.conj(np.fft.fft(c_diff[:framesize])))


    

In [5]:

    

plt.plot(corr.real)


    

    
Out[5]:





[<matplotlib.lines.Line2D at 0x7f61292e1b00>]






    

In [6]:

    

plt.plot(corr2.real)


    

    
Out[6]:





[<matplotlib.lines.Line2D at 0x7f61292c9978>]






    

In [7]:

    

shift = np.argmax(corr.real)
shift


    

    
Out[7]:





819

In [8]:

    

shift2 = np.argmax(corr2.real)
shift2


    

    
Out[8]:





702

In [9]:

    

x = np.concatenate((a_diff, np.zeros(1024*3 + 1 + shift - a.size % 1024), b_diff))
x = np.concatenate((x, np.zeros(1024*10 + shift2 - x.size % 1024), c_diff))


    

In [10]:

    

pad_diff = 0
x_pad_diff = np.concatenate((np.zeros(pad_diff), x))#np.sign(-x[1:]*x[:-1])))
x_pad_diff = np.concatenate((x_pad_diff, np.zeros(framesize - x_pad_diff.size % framesize)))
data = x_pad_diff.reshape((-1,framesize))
plt.figure(figsize = (14,10), facecolor = 'w')
plt.imshow(data, aspect = 5)
plt.title('Bitstream by frames (differentially decoded)');


    

In [11]:

    

for off in range(0,1024,128):
    plt.figure(figsize = (14,10), facecolor = 'w')
    plt.imshow(data[:,off:off+128], aspect = 0.3)
    plt.title(f'Frame bits {off} to {off+128-1}')


    

In [12]:

    

plt.imshow(data[:,49:55], aspect = 0.1)


    

    
Out[12]:





<matplotlib.image.AxesImage at 0x7f61287bc828>






    

In [13]:

    

bits = data[:,49:55]
bits = ((bits[np.all(bits != 0, axis = 1)] + 1)/2).astype('int')
plt.plot([np.packbits(b)[0] >> 2 for b in bits], '.-')


    

    
Out[13]:





[<matplotlib.lines.Line2D at 0x7f612878e908>]






    

In [14]:

    

plt.imshow(data[:,191:199], aspect = 0.1)


    

    
Out[14]:





<matplotlib.image.AxesImage at 0x7f61286efb70>






    

In [15]:

    

bits = data[:,191:199]
bits = ((bits[np.all(bits != 0, axis = 1)] + 1)/2).astype('int')
plt.plot([np.packbits(b).view('uint8') for b in bits], '.-')


    

    
Out[15]:





[<matplotlib.lines.Line2D at 0x7f61286c6c50>]






    

In [16]:

    

plt.imshow(data[:,703:708], aspect = 0.1)


    

    
Out[16]:





<matplotlib.image.AxesImage at 0x7f612844f438>






    

In [17]:

    

bits = data[:, 703:708]
bits = ((bits[np.all(bits != 0, axis = 1)] + 1)/2).astype('int')
plt.plot([np.packbits(b).view('uint8') >> 3 for b in bits], '.-')


    

    
Out[17]:





[<matplotlib.lines.Line2D at 0x7f6128426518>]






    

In [18]:

    

plt.imshow(data[:,865:871], aspect = 0.1)


    

    
Out[18]:





<matplotlib.image.AxesImage at 0x7f61291d5160>






    

In [19]:

    

bits = data[:, 865:871]
bits = ((bits[np.all(bits != 0, axis = 1)] + 1)/2).astype('int')
plt.plot([np.packbits(b).view('uint8')>>2 for b in bits], '.-')


    

    
Out[19]:





[<matplotlib.lines.Line2D at 0x7f61287da550>]