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Diffstat (limited to 'pyspike/directionality/cython/cython_directionality.pyx')
| -rw-r--r-- | pyspike/directionality/cython/cython_directionality.pyx | 223 |
1 files changed, 0 insertions, 223 deletions
diff --git a/pyspike/directionality/cython/cython_directionality.pyx b/pyspike/directionality/cython/cython_directionality.pyx deleted file mode 100644 index e1f63c4..0000000 --- a/pyspike/directionality/cython/cython_directionality.pyx +++ /dev/null @@ -1,223 +0,0 @@ -#cython: boundscheck=False -#cython: wraparound=False -#cython: cdivision=True - -""" -cython_directionality.pyx - -cython implementation of the spike delay asymmetry measures - -Copyright 2015, Mario Mulansky <mario.mulansky@gmx.net> - -Distributed under the BSD License - -""" - -""" -To test whether things can be optimized: remove all yellow stuff -in the html output:: - - cython -a cython_directionality.pyx - -which gives:: - - cython_directionality.html - -""" - -import numpy as np -cimport numpy as np - -from libc.math cimport fabs -from libc.math cimport fmax -from libc.math cimport fmin - -# from pyspike.cython.cython_distances cimport get_tau - -DTYPE = np.float -ctypedef np.float_t DTYPE_t - - -############################################################ -# get_tau -############################################################ -cdef inline double get_tau(double[:] spikes1, double[:] spikes2, - int i, int j, double interval, double max_tau): - cdef double m = interval # use interval length as initial tau - cdef int N1 = spikes1.shape[0]-1 # len(spikes1)-1 - cdef int N2 = spikes2.shape[0]-1 # len(spikes2)-1 - if i < N1 and i > -1: - m = fmin(m, spikes1[i+1]-spikes1[i]) - if j < N2 and j > -1: - m = fmin(m, spikes2[j+1]-spikes2[j]) - if i > 0: - m = fmin(m, spikes1[i]-spikes1[i-1]) - if j > 0: - m = fmin(m, spikes2[j]-spikes2[j-1]) - m *= 0.5 - if max_tau > 0.0: - m = fmin(m, max_tau) - return m - - -############################################################ -# spike_train_order_profile_cython -############################################################ -def spike_train_order_profile_cython(double[:] spikes1, double[:] spikes2, - double t_start, double t_end, - double max_tau): - - cdef int N1 = len(spikes1) - cdef int N2 = len(spikes2) - cdef int i = -1 - cdef int j = -1 - cdef int n = 0 - cdef double[:] st = np.zeros(N1 + N2 + 2) # spike times - cdef double[:] a = np.zeros(N1 + N2 + 2) # asymmetry values - cdef double[:] mp = np.ones(N1 + N2 + 2) # multiplicity - cdef double interval = t_end - t_start - cdef double tau - while i + j < N1 + N2 - 2: - if (i < N1-1) and (j == N2-1 or spikes1[i+1] < spikes2[j+1]): - i += 1 - n += 1 - tau = get_tau(spikes1, spikes2, i, j, interval, max_tau) - st[n] = spikes1[i] - if j > -1 and spikes1[i]-spikes2[j] < tau: - # coincidence between the current spike and the previous spike - # spike from spike train 1 after spike train 2 - # both get marked with -1 - a[n] = -1 - a[n-1] = -1 - elif (j < N2-1) and (i == N1-1 or spikes1[i+1] > spikes2[j+1]): - j += 1 - n += 1 - tau = get_tau(spikes1, spikes2, i, j, interval, max_tau) - st[n] = spikes2[j] - if i > -1 and spikes2[j]-spikes1[i] < tau: - # coincidence between the current spike and the previous spike - # spike from spike train 1 before spike train 2 - # both get marked with 1 - a[n] = 1 - a[n-1] = 1 - else: # spikes1[i+1] = spikes2[j+1] - # advance in both spike trains - j += 1 - i += 1 - n += 1 - # add only one event with zero asymmetry value and multiplicity 2 - st[n] = spikes1[i] - a[n] = 0 - mp[n] = 2 - - st = st[:n+2] - a = a[:n+2] - mp = mp[:n+2] - - st[0] = t_start - st[len(st)-1] = t_end - if N1 + N2 > 0: - a[0] = a[1] - a[len(a)-1] = a[len(a)-2] - mp[0] = mp[1] - mp[len(mp)-1] = mp[len(mp)-2] - else: - a[0] = 1 - a[1] = 1 - - return st, a, mp - - - -############################################################ -# spike_order_values_cython -############################################################ -def spike_order_values_cython(double[:] spikes1, - double[:] spikes2, - double t_start, double t_end, - double max_tau): - - cdef int N1 = len(spikes1) - cdef int N2 = len(spikes2) - cdef int i = -1 - cdef int j = -1 - cdef double[:] a1 = np.zeros(N1) # asymmetry values - cdef double[:] a2 = np.zeros(N2) # asymmetry values - cdef double interval = t_end - t_start - cdef double tau - while i + j < N1 + N2 - 2: - if (i < N1-1) and (j == N2-1 or spikes1[i+1] < spikes2[j+1]): - i += 1 - tau = get_tau(spikes1, spikes2, i, j, interval, max_tau) - if j > -1 and spikes1[i]-spikes2[j] < tau: - # coincidence between the current spike and the previous spike - # spike from spike train 1 after spike train 2 - # leading spike gets +1, following spike -1 - a1[i] = -1 - a2[j] = +1 - elif (j < N2-1) and (i == N1-1 or spikes1[i+1] > spikes2[j+1]): - j += 1 - tau = get_tau(spikes1, spikes2, i, j, interval, max_tau) - if i > -1 and spikes2[j]-spikes1[i] < tau: - # coincidence between the current spike and the previous spike - # spike from spike train 1 before spike train 2 - # leading spike gets +1, following spike -1 - a1[i] = +1 - a2[j] = -1 - else: # spikes1[i+1] = spikes2[j+1] - # advance in both spike trains - j += 1 - i += 1 - # equal spike times: zero asymmetry value - a1[i] = 0 - a2[j] = 0 - - return a1, a2 - - -############################################################ -# spike_train_order_cython -############################################################ -def spike_train_order_cython(double[:] spikes1, double[:] spikes2, - double t_start, double t_end, double max_tau): - - cdef int N1 = len(spikes1) - cdef int N2 = len(spikes2) - cdef int i = -1 - cdef int j = -1 - cdef int asym = 0 - cdef int mp = 0 - cdef double interval = t_end - t_start - cdef double tau - while i + j < N1 + N2 - 2: - if (i < N1-1) and (j == N2-1 or spikes1[i+1] < spikes2[j+1]): - i += 1 - mp += 1 - tau = get_tau(spikes1, spikes2, i, j, interval, max_tau) - if j > -1 and spikes1[i]-spikes2[j] < tau: - # coincidence between the current spike and the previous spike - # spike in spike train 2 appeared before spike in spike train 1 - # mark with -1 - asym -= 2 - elif (j < N2-1) and (i == N1-1 or spikes1[i+1] > spikes2[j+1]): - j += 1 - mp += 1 - tau = get_tau(spikes1, spikes2, i, j, interval, max_tau) - if i > -1 and spikes2[j]-spikes1[i] < tau: - # coincidence between the current spike and the previous spike - # spike in spike train 1 appeared before spike in spike train 2 - # mark with +1 - asym += 2 - else: # spikes1[i+1] = spikes2[j+1] - # advance in both spike trains - j += 1 - i += 1 - # add only one event with multiplicity 2, but no asymmetry counting - mp += 2 - - if asym == 0 and mp == 0: - # empty spike trains -> spike sync = 1 by definition - asym = 1 - mp = 1 - - return asym, mp |