From 7989b2d337a0e5d2e0223d7fdec73833ff47c7bb Mon Sep 17 00:00:00 2001 From: Mario Mulansky Date: Tue, 3 Feb 2015 16:40:55 +0100 Subject: first version of psth profile --- pyspike/psth.py | 27 +++++++++++++++++++++++++++ 1 file changed, 27 insertions(+) create mode 100644 pyspike/psth.py (limited to 'pyspike/psth.py') diff --git a/pyspike/psth.py b/pyspike/psth.py new file mode 100644 index 0000000..8516460 --- /dev/null +++ b/pyspike/psth.py @@ -0,0 +1,27 @@ +""" + +Module containing functions to compute the PSTH profile + +Copyright 2015, Mario Mulansky + +Distributed under the BSD License +""" + +import numpy as np +from pyspike import PieceWiseConstFunc + + +# Computes the Peristimulus time histogram of a set of spike trains +def psth(spike_trains, bin_size): + + bins = int((spike_trains[0][-1] - spike_trains[0][0]) / bin_size) + + N = len(spike_trains) + combined_spike_train = spike_trains[0][1:-1] + for i in xrange(1, len(spike_trains)): + combined_spike_train = np.append(combined_spike_train, + spike_trains[i][1:-1]) + + vals, edges = np.histogram(combined_spike_train, bins, density=False) + bin_size = edges[1]-edges[0] + return PieceWiseConstFunc(edges, vals/(N*bin_size)) -- cgit v1.2.3 From 2336f1fcf28efeb23e8450f407a008b8032edd5e Mon Sep 17 00:00:00 2001 From: Mario Mulansky Date: Mon, 27 Apr 2015 18:16:12 +0200 Subject: adjusted PSTH, added to doc index --- doc/pyspike.rst | 8 ++++++++ examples/spike_sync.py | 2 +- pyspike/psth.py | 39 +++++++++++++++++++++++---------------- 3 files changed, 32 insertions(+), 17 deletions(-) (limited to 'pyspike/psth.py') diff --git a/doc/pyspike.rst b/doc/pyspike.rst index a6dc1a0..74ab439 100644 --- a/doc/pyspike.rst +++ b/doc/pyspike.rst @@ -57,6 +57,14 @@ SPIKE-synchronization :undoc-members: :show-inheritance: +PSTH +........................................ +.. automodule:: pyspike.psth + :members: + :undoc-members: + :show-inheritance: + + Helper functions ........................................ .. automodule:: pyspike.spikes diff --git a/examples/spike_sync.py b/examples/spike_sync.py index 9e81536..37dbff4 100644 --- a/examples/spike_sync.py +++ b/examples/spike_sync.py @@ -40,7 +40,7 @@ plt.plot(x1, y1, '-k', lw=2.5, label="averaged SPIKE-Sync profile") plt.subplot(212) -f_psth = spk.psth(spike_trains, bin_size=5.0) +f_psth = spk.psth(spike_trains, bin_size=50.0) x, y = f_psth.get_plottable_data() plt.plot(x, y, '-k', alpha=1.0, label="PSTH") diff --git a/pyspike/psth.py b/pyspike/psth.py index 8516460..4027215 100644 --- a/pyspike/psth.py +++ b/pyspike/psth.py @@ -1,27 +1,34 @@ -""" - -Module containing functions to compute the PSTH profile - -Copyright 2015, Mario Mulansky - -Distributed under the BSD License -""" +# Module containing functions to compute the PSTH profile +# Copyright 2015, Mario Mulansky +# Distributed under the BSD License import numpy as np from pyspike import PieceWiseConstFunc -# Computes the Peristimulus time histogram of a set of spike trains +# Computes the peri-stimulus time histogram of a set of spike trains def psth(spike_trains, bin_size): - - bins = int((spike_trains[0][-1] - spike_trains[0][0]) / bin_size) - - N = len(spike_trains) - combined_spike_train = spike_trains[0][1:-1] + """ Computes the peri-stimulus time histogram of a set of + :class:`.SpikeTrain`. The PSTH is simply the histogram of merged spike + events. The :code:`bin_size` defines the width of the histogram bins. + + :param spike_trains: list of :class:`.SpikeTrain` + :param bin_size: width of the histogram bins. + :return: The PSTH as a :class:`.PieceWiseConstFunc` + """ + + bin_count = int((spike_trains[0].t_end - spike_trains[0].t_start) / + bin_size) + bins = np.linspace(spike_trains[0].t_start, spike_trains[0].t_end, + bin_count+1) + + # N = len(spike_trains) + combined_spike_train = spike_trains[0].spikes for i in xrange(1, len(spike_trains)): combined_spike_train = np.append(combined_spike_train, - spike_trains[i][1:-1]) + spike_trains[i].spikes) vals, edges = np.histogram(combined_spike_train, bins, density=False) + bin_size = edges[1]-edges[0] - return PieceWiseConstFunc(edges, vals/(N*bin_size)) + return PieceWiseConstFunc(edges, vals) # /(N*bin_size)) -- cgit v1.2.3 From 2c42e59e5097d3b9745e6eae2bee8f1ff27f7e09 Mon Sep 17 00:00:00 2001 From: Igor Gnatenko Date: Sun, 13 Dec 2015 10:57:12 +0100 Subject: py3: xrange() -> range() Signed-off-by: Igor Gnatenko --- examples/multivariate.py | 2 +- examples/performance.py | 2 +- pyspike/DiscreteFunc.py | 4 ++-- pyspike/directionality/spike_train_order.py | 4 ++-- pyspike/generic.py | 4 ++-- pyspike/psth.py | 2 +- test/test_distance.py | 6 +++--- 7 files changed, 12 insertions(+), 12 deletions(-) (limited to 'pyspike/psth.py') diff --git a/examples/multivariate.py b/examples/multivariate.py index 9a44758..93f8516 100644 --- a/examples/multivariate.py +++ b/examples/multivariate.py @@ -24,7 +24,7 @@ t_loading = time.clock() print("Number of spike trains: %d" % len(spike_trains)) num_of_spikes = sum([len(spike_trains[i]) - for i in xrange(len(spike_trains))]) + for i in range(len(spike_trains))]) print("Number of spikes: %d" % num_of_spikes) # calculate the multivariate spike distance diff --git a/examples/performance.py b/examples/performance.py index d0c3b91..ec6c830 100644 --- a/examples/performance.py +++ b/examples/performance.py @@ -26,7 +26,7 @@ print("%d spike trains with %d spikes" % (M, int(r*T))) spike_trains = [] t_start = datetime.now() -for i in xrange(M): +for i in range(M): spike_trains.append(spk.generate_poisson_spikes(r, T)) t_end = datetime.now() runtime = (t_end-t_start).total_seconds() diff --git a/pyspike/DiscreteFunc.py b/pyspike/DiscreteFunc.py index 55c0bc8..fe97bc2 100644 --- a/pyspike/DiscreteFunc.py +++ b/pyspike/DiscreteFunc.py @@ -80,7 +80,7 @@ class DiscreteFunc(object): expected_mp = (averaging_window_size+1) * int(self.mp[0]) y_plot = np.zeros_like(self.y) # compute the values in a loop, could be done in cython if required - for i in xrange(len(y_plot)): + for i in range(len(y_plot)): if self.mp[i] >= expected_mp: # the current value contains already all the wanted @@ -244,7 +244,7 @@ def average_profile(profiles): assert len(profiles) > 1 avrg_profile = profiles[0].copy() - for i in xrange(1, len(profiles)): + for i in range(1, len(profiles)): avrg_profile.add(profiles[i]) avrg_profile.mul_scalar(1.0/len(profiles)) # normalize diff --git a/pyspike/directionality/spike_train_order.py b/pyspike/directionality/spike_train_order.py index 44d931d..e6c9830 100644 --- a/pyspike/directionality/spike_train_order.py +++ b/pyspike/directionality/spike_train_order.py @@ -260,7 +260,7 @@ def optimal_spike_train_order(spike_trains, indices=None, interval=None, 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/generic.py b/pyspike/generic.py index 904c3c2..81ae660 100644 --- a/pyspike/generic.py +++ b/pyspike/generic.py @@ -137,8 +137,8 @@ def _generic_distance_matrix(spike_trains, dist_function, assert (indices < len(spike_trains)).all() and (indices >= 0).all(), \ "Invalid index list." # generate a list of possible index pairs - pairs = [(i, j) for i in xrange(len(indices)) - for j in xrange(i+1, len(indices))] + pairs = [(i, j) for i in range(len(indices)) + for j in range(i+1, len(indices))] distance_matrix = np.zeros((len(indices), len(indices))) for i, j in pairs: diff --git a/pyspike/psth.py b/pyspike/psth.py index 4027215..7cf1140 100644 --- a/pyspike/psth.py +++ b/pyspike/psth.py @@ -24,7 +24,7 @@ def psth(spike_trains, bin_size): # N = len(spike_trains) combined_spike_train = spike_trains[0].spikes - for i in xrange(1, len(spike_trains)): + for i in range(1, len(spike_trains)): combined_spike_train = np.append(combined_spike_train, spike_trains[i].spikes) diff --git a/test/test_distance.py b/test/test_distance.py index e45ac16..d5bce30 100644 --- a/test/test_distance.py +++ b/test/test_distance.py @@ -309,10 +309,10 @@ def check_dist_matrix(dist_func, dist_matrix_func): f_matrix = dist_matrix_func(spike_trains) # check zero diagonal - for i in xrange(4): + for i in range(4): assert_equal(0.0, f_matrix[i, i]) - for i in xrange(4): - for j in xrange(i+1, 4): + for i in range(4): + for j in range(i+1, 4): assert_equal(f_matrix[i, j], f_matrix[j, i]) assert_equal(f12, f_matrix[1, 0]) assert_equal(f13, f_matrix[2, 0]) -- cgit v1.2.3