def _get_mutual_inf_KNN(a):
"""
Gets mutual information using EQQ algorithm for given data.
"""
i, j, ph1, ph2 = a
return i, j, MI.knn_mutual_information(ph1, ph2, k = 32, dualtree = True)
def _process_matrix(self, jobq, resq):
while True:
a = jobq.get() # get queued input
if a is None: # if it is None, we are finished, put poison pill to resq
break # break infinity cycle
else:
i, j, ph1, ph2, method = a # compute stuff
if method == "MPC":
# get phase diff
diff = ph1 - ph2
# compute mean phase coherence
coh = np.power(np.mean(np.cos(diff)), 2) + np.power(np.mean(np.sin(diff)), 2)
resq.put((i, j, coh))
elif method == "MIEQQ":
resq.put((i, j, MI.mutual_information(ph1, ph2, algorithm = 'EQQ2', bins = 4, log2 = False)))
elif method == "MIKNN":
resq.put((i, j, MI.knn_mutual_information(ph1, ph2, k = 32, dualtree = True)))
elif method == "MIGAU":
corr = np.corrcoef([ph1, ph2])[0, 1]
mi = -0.5 * np.log(1 - np.power(corr, 2)) if corr < 1. else 0
resq.put((i, j, mi))
elif method == "COV":
resq.put((i, j, np.cov(ph1, ph2, ddof = 1)[0,1]))
elif method == "CORR":
resq.put((i, j, st.pearsonr(ph1, ph2)[0]))
elif method == "WCOH":
# input field must be wave from wavelet!!!!
w1 = np.complex(0, 0)
w2 = w1; w3 = w1
for t in range(0, self.time.shape[0]):
w1 += ph1[t] * np.conjugate(ph2[t])
w2 += ph1[t] * np.conjugate(ph1[t])
w3 += ph2[t] * np.conjugate(ph2[t])
w1 /= np.sqrt(np.abs(w2) * np.abs(w3))
resq.put((i, j, np.abs(w1)))
elif method[0] == 'L':
p = int(method[1])
res = 0
for t in range(ph1.shape[0]):
res += np.power(np.abs(ph1[t] - ph2[t]), p)
resq.put((i, j, np.power(res, 1./p)))
