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| author | Mario Mulansky <mario.mulansky@gmx.net> | 2016-03-29 14:14:39 +0200 |
|---|---|---|
| committer | Mario Mulansky <mario.mulansky@gmx.net> | 2016-03-29 14:14:39 +0200 |
| commit | 177c97bd11c4b8dca87ca70e8a44857e14b6d87c (patch) | |
| tree | 0837780a4959822f595d60e739017a500d66aa59 | |
| parent | 78f1404168447b3173302fa98817a0d964d8f290 (diff) | |
python3 fixes
| -rw-r--r-- | pyspike/spike_directionality.py | 21 | ||||
| -rw-r--r-- | pyspike/spike_sync.py | 2 |
2 files changed, 12 insertions, 11 deletions
diff --git a/pyspike/spike_directionality.py b/pyspike/spike_directionality.py index e1f5f16..cd2bf04 100644 --- a/pyspike/spike_directionality.py +++ b/pyspike/spike_directionality.py @@ -3,8 +3,9 @@ # Copyright 2015, Mario Mulansky <mario.mulansky@gmx.net> # Distributed under the BSD License +from __future__ import absolute_import + import numpy as np -from math import exp import pyspike from pyspike import DiscreteFunc from functools import partial @@ -22,7 +23,7 @@ def spike_directionality(spike_train1, spike_train2, normalize=True, # distance over the whole interval is requested: use specific function # for optimal performance try: - from cython.cython_directionality import \ + from .cython.cython_directionality import \ spike_directionality_cython as spike_directionality_impl if max_tau is None: max_tau = 0.0 @@ -95,7 +96,7 @@ def spike_directionality_profiles(spike_trains, indices=None, # cython implementation try: - from cython.cython_directionality import \ + from .cython.cython_directionality import \ spike_directionality_profiles_cython as profile_impl except ImportError: if not(pyspike.disable_backend_warning): @@ -103,7 +104,7 @@ def spike_directionality_profiles(spike_trains, indices=None, PySpike is installed by running\n 'python setup.py build_ext --inplace'!\n \ Falling back to slow python backend.") # use python backend - from cython.directionality_python_backend import \ + from .cython.directionality_python_backend import \ spike_directionality_profile_python as profile_impl if max_tau is None: @@ -143,7 +144,7 @@ def spike_train_order_profile(spike_train1, spike_train2, max_tau=None): # cython implementation try: - from cython.cython_directionality import \ + from .cython.cython_directionality import \ spike_train_order_profile_cython as \ spike_train_order_profile_impl except ImportError: @@ -153,7 +154,7 @@ def spike_train_order_profile(spike_train1, spike_train2, max_tau=None): PySpike is installed by running\n 'python setup.py build_ext --inplace'!\n \ Falling back to slow python backend.") # use python backend - from cython.directionality_python_backend import \ + from .cython.directionality_python_backend import \ spike_train_order_profile_python as spike_train_order_profile_impl if max_tau is None: @@ -180,7 +181,7 @@ def spike_train_order(spike_train1, spike_train2, normalize=True, # distance over the whole interval is requested: use specific function # for optimal performance try: - from cython.cython_directionality import \ + from .cython.cython_directionality import \ spike_train_order_cython as spike_train_order_impl if max_tau is None: max_tau = 0.0 @@ -246,7 +247,7 @@ def optimal_spike_train_order_from_matrix(D, full_output=False): T_end = 1E-5 * T_start # final temperature alpha = 0.9 # cooling factor - from cython.cython_simulated_annealing import sim_ann_cython as sim_ann + from .cython.cython_simulated_annealing import sim_ann_cython as sim_ann p, A, total_iter = sim_ann(D, T_start, T_end, alpha) @@ -305,8 +306,8 @@ def permutate_matrix(D, p): """ N = len(D) D_p = np.empty_like(D) - for n in xrange(N): - for m in xrange(N): + for n in range(N): + for m in range(N): D_p[n, m] = D[p[n], p[m]] return D_p diff --git a/pyspike/spike_sync.py b/pyspike/spike_sync.py index 28e252c..32e6bf4 100644 --- a/pyspike/spike_sync.py +++ b/pyspike/spike_sync.py @@ -323,7 +323,7 @@ Falling back to slow python backend.") for i, st in enumerate(spike_trains): coincidences = np.zeros_like(st) - for j in xrange(N): + for j in range(N): if i == j: continue coincidences += coincidence_impl(st.spikes, spike_trains[j].spikes, |