

In [2]:

    
%matplotlib inline
%load_ext autoreload
%autoreload 2

import sys
sys.path.append("..")
import splitwavepy as sw

import scipy
import numpy as np
import matplotlib.pyplot as plt









    



The autoreload extension is already loaded. To reload it, use:
  %reload_ext autoreload

Method:

1) Split wave using set parameters, lots of noise, and variable polarisation.

2) Try to recover the splitting parameters by error surface stacking.



In [3]:

    
# 1. Generate Synthetic Data

noise_level = 0.1
fast = 0.
lag = 2.
delta = 0.1

listM = [ sw.EigenM(pol=np.random.randint(360),
                    noise=noise_level,
                    split = (fast, lag),
                    delta = delta,
                    lags=(4,)) for _ in range(40) ]

# 2. Collect in Stack

S = sw.measure.Stack(listM)



In [4]:

    
# 3. Plot

cax = plt.contourf(S.lags,S.degs,S.stack(),26,cmap='magma')
plt.colorbar(cax)
plt.show()



In [5]:

    
cax = plt.contourf(S.lags,S.degs,S.stackpdf(),26,cmap='magma')
plt.colorbar(cax)
plt.show()



In [6]:

    
cax = plt.contourf(S.lags,S.degs,S.wolfe_silver(),26,cmap='magma_r')
plt.colorbar(cax)
plt.show()



In [7]:

    
cax = plt.contourf(S.lags,S.degs,S.restivo_helffrich(),26,cmap='magma_r')
plt.colorbar(cax)
plt.show()









    



---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-7-242ab16a22ca> in <module>()
----> 1 cax = plt.contourf(S.lags,S.degs,S.restivo_helffrich(),26,cmap='magma_r')
      2 plt.colorbar(cax)
      3 plt.show()

/Users/glyjw/Applications/splitwavepy/splitwavepy/measure/stack.py in restivo_helffrich(self, **kwargs)
     79 
     80         # weight by signal to noise ratio
---> 81         weights = np.asarray([ M.data.snrRH() for M in self.listM ])
     82 
     83         # should apply sigmoid (?) function to weights with min to max ranging from 1 to 21 to be consistent with original paper.  Note: sheba does not bother with this.

/Users/glyjw/Applications/splitwavepy/splitwavepy/measure/stack.py in <listcomp>(.0)
     79 
     80         # weight by signal to noise ratio
---> 81         weights = np.asarray([ M.data.snrRH() for M in self.listM ])
     82 
     83         # should apply sigmoid (?) function to weights with min to max ranging from 1 to 21 to be consistent with original paper.  Note: sheba does not bother with this.

AttributeError: 'Pair' object has no attribute 'snrRH'



In [ ]:

    
# 1. Generate Synthetic Data with variable noise

# noise_level = 0.1
fast = 0.
lag = 2.
delta = 0.1

listM = [ sw.EigenM(pol=np.random.randint(360),
                    noise=0.2*np.random.rand(1),
                    split = (fast,lag),
                    delta = delta,
                    lags=(4,)) for _ in range(40) ]

# 2. Collect in Stack

S = sw.eigval.Stack(listM)



In [ ]:

    
# 3. Plot

cax = plt.contourf(S.lags,S.degs,S.stack(),26,cmap='magma')
plt.colorbar(cax)
plt.show()



In [ ]:

    
cax = plt.contourf(S.lags,S.degs,S.stackpdf(),26,cmap='magma')
plt.colorbar(cax)
plt.show()



In [ ]:

    
cax = plt.contourf(S.lags,S.degs,S.wolfe_silver(),26,cmap='magma_r')
plt.colorbar(cax)
plt.show()



In [ ]:

    
cax=plt.contourf(S.lags,S.degs,S.restivo_helffrich(),26,cmap='magma_r')
plt.colorbar(cax)
plt.show()



In [ ]:

    
def sigmoid (x): return 1/(1 + np.exp(-x))



In [ ]:

    
x = np.linspace(0,22,300)
plt.plot(x,sigmoid(2*x-10))



In [ ]:

    
a = sw.Pair()
b = a.copy()
b.rotateto(b.pol())
b.chop()



In [ ]:

    
a.snrRH()



In [ ]:

    
a.rotateto(a.pol())



In [ ]:

    
dat



In [ ]: