From e85e6a72662d30b677dd4c9ded6d2b1520ba63ec Mon Sep 17 00:00:00 2001 From: Mario Mulansky Date: Mon, 20 Oct 2014 18:13:23 +0200 Subject: +multivariate example, docs for spike profile --- examples/multivariate.py | 50 ++++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 50 insertions(+) create mode 100644 examples/multivariate.py (limited to 'examples/multivariate.py') diff --git a/examples/multivariate.py b/examples/multivariate.py new file mode 100644 index 0000000..260b217 --- /dev/null +++ b/examples/multivariate.py @@ -0,0 +1,50 @@ +""" Example for the multivariate spike distance + +Copyright 2014, Mario Mulansky + +""" +from __future__ import print_function +import time +import pyspike as spk + + +def time_diff_in_ms(start, end): + """ Returns the time difference end-start in ms. + """ + return (end-start)*1000 + + +t_start = time.clock() + +# load the data +time_loading = time.clock() +spike_trains = spk.load_spike_trains_from_txt("PySpike_testdata.txt", + time_interval=(0, 4000)) +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))]) +print("Number of spikes: %d" % num_of_spikes) + +# calculate the multivariate spike distance +f = spk.spike_profile_multi(spike_trains) + +t_spike = time.clock() + +# print the average +avrg = f.avrg() +print("Spike distance from average: %.8f" % avrg) + +t_avrg = time.clock() + +# compute average distance directly, should give the same result as above +spike_dist = spk.spike_distance_multi(spike_trains) +print("Spike distance directly: %.8f" % spike_dist) + +t_dist = time.clock() + +print("Loading: %9.1f ms" % time_diff_in_ms(t_start, t_loading)) +print("Computing profile: %9.1f ms" % time_diff_in_ms(t_loading, t_spike)) +print("Averaging: %9.1f ms" % time_diff_in_ms(t_spike, t_avrg)) +print("Computing distance: %9.1f ms" % time_diff_in_ms(t_avrg, t_dist)) +print("Total: %9.1f ms" % time_diff_in_ms(t_start, t_dist)) -- cgit v1.2.3 From ecc7898a0b6cd5bc353fd246f3ad549934c82229 Mon Sep 17 00:00:00 2001 From: Mario Mulansky Date: Mon, 27 Apr 2015 17:35:36 +0200 Subject: adjustments of examples --- examples/PySpike_testdata.txt | 0 examples/merge.py | 11 ++++++----- examples/multivariate.py | 5 +++-- examples/plot.py | 6 +++--- examples/spike_sync.py | 3 +-- 5 files changed, 13 insertions(+), 12 deletions(-) mode change 100755 => 100644 examples/PySpike_testdata.txt (limited to 'examples/multivariate.py') diff --git a/examples/PySpike_testdata.txt b/examples/PySpike_testdata.txt old mode 100755 new mode 100644 diff --git a/examples/merge.py b/examples/merge.py index 2550cdb..2ea96ea 100644 --- a/examples/merge.py +++ b/examples/merge.py @@ -17,12 +17,13 @@ import pyspike as spk # first load the data, ending time = 4000 spike_trains = spk.load_spike_trains_from_txt("PySpike_testdata.txt", 4000) -spikes = spk.merge_spike_trains([spike_trains[0], spike_trains[1]]) +merged_spike_train = spk.merge_spike_trains([spike_trains[0], spike_trains[1]]) -print(spikes) +print(merged_spike_train.spikes) -plt.plot(spike_trains[0], np.ones_like(spike_trains[0]), 'o') -plt.plot(spike_trains[1], np.ones_like(spike_trains[1]), 'x') -plt.plot(spikes, 2*np.ones_like(spikes), 'o') +plt.plot(spike_trains[0].spikes, np.ones_like(spike_trains[0].spikes), 'o') +plt.plot(spike_trains[1].spikes, np.ones_like(spike_trains[1].spikes), 'x') +plt.plot(merged_spike_train.spikes, + 2*np.ones_like(merged_spike_train.spikes), 'o') plt.show() diff --git a/examples/multivariate.py b/examples/multivariate.py index 260b217..53dbf0f 100644 --- a/examples/multivariate.py +++ b/examples/multivariate.py @@ -19,11 +19,12 @@ t_start = time.clock() # load the data time_loading = time.clock() spike_trains = spk.load_spike_trains_from_txt("PySpike_testdata.txt", - time_interval=(0, 4000)) + edges=(0, 4000)) 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))]) +num_of_spikes = sum([len(spike_trains[i].spikes) + for i in xrange(len(spike_trains))]) print("Number of spikes: %d" % num_of_spikes) # calculate the multivariate spike distance diff --git a/examples/plot.py b/examples/plot.py index d32c464..9670286 100644 --- a/examples/plot.py +++ b/examples/plot.py @@ -17,11 +17,11 @@ import matplotlib.pyplot as plt import pyspike as spk spike_trains = spk.load_spike_trains_from_txt("PySpike_testdata.txt", - time_interval=(0, 4000)) + edges=(0, 4000)) # plot the spike time -for (i, spikes) in enumerate(spike_trains): - plt.plot(spikes, i*np.ones_like(spikes), 'o') +for (i, spike_train) in enumerate(spike_trains): + plt.plot(spike_train.spikes, i*np.ones_like(spike_train.spikes), 'o') f = spk.isi_profile(spike_trains[0], spike_trains[1]) x, y = f.get_plottable_data() diff --git a/examples/spike_sync.py b/examples/spike_sync.py index 9c5f75c..9e81536 100644 --- a/examples/spike_sync.py +++ b/examples/spike_sync.py @@ -1,12 +1,11 @@ from __future__ import print_function -import numpy as np import matplotlib.pyplot as plt import pyspike as spk spike_trains = spk.load_spike_trains_from_txt("../test/SPIKE_Sync_Test.txt", - time_interval=(0, 4000)) + edges=(0, 4000)) plt.figure() -- cgit v1.2.3 From 7984d32e767e5833f1aaee06b6aeda8cc3f4500d Mon Sep 17 00:00:00 2001 From: Mario Mulansky Date: Fri, 12 Jun 2015 14:57:50 +0200 Subject: update example to use new SpikeTrain capability Make use of __getitem__ and __len__ of SpikeTrains in some examples. --- examples/multivariate.py | 2 +- examples/plot.py | 4 ++-- 2 files changed, 3 insertions(+), 3 deletions(-) (limited to 'examples/multivariate.py') diff --git a/examples/multivariate.py b/examples/multivariate.py index 53dbf0f..9a44758 100644 --- a/examples/multivariate.py +++ b/examples/multivariate.py @@ -23,7 +23,7 @@ spike_trains = spk.load_spike_trains_from_txt("PySpike_testdata.txt", t_loading = time.clock() print("Number of spike trains: %d" % len(spike_trains)) -num_of_spikes = sum([len(spike_trains[i].spikes) +num_of_spikes = sum([len(spike_trains[i]) for i in xrange(len(spike_trains))]) print("Number of spikes: %d" % num_of_spikes) diff --git a/examples/plot.py b/examples/plot.py index 9670286..5841baf 100644 --- a/examples/plot.py +++ b/examples/plot.py @@ -19,9 +19,9 @@ import pyspike as spk spike_trains = spk.load_spike_trains_from_txt("PySpike_testdata.txt", edges=(0, 4000)) -# plot the spike time +# plot the spike times for (i, spike_train) in enumerate(spike_trains): - plt.plot(spike_train.spikes, i*np.ones_like(spike_train.spikes), 'o') + plt.plot(spike_train, i*np.ones_like(spike_train), 'o') f = spk.isi_profile(spike_trains[0], spike_trains[1]) x, y = f.get_plottable_data() -- 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 'examples/multivariate.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 From ee0e980b72c299eed12b7a3afc542fc470dd6d98 Mon Sep 17 00:00:00 2001 From: Mario Mulansky Date: Wed, 9 Mar 2016 12:30:35 +0100 Subject: updated examples to use new unified interface removed all occasions of *multi functions from examples as they are considered deprecated now. Uses unified interface everywhere. --- examples/averages.py | 2 +- examples/merge.py | 6 +++--- examples/multivariate.py | 4 ++-- examples/performance.py | 27 +++++++++++++++------------ examples/plot.py | 5 +++-- examples/profiles.py | 4 ++-- examples/spike_sync.py | 2 +- 7 files changed, 27 insertions(+), 23 deletions(-) (limited to 'examples/multivariate.py') diff --git a/examples/averages.py b/examples/averages.py index c3e81e2..8b405d0 100644 --- a/examples/averages.py +++ b/examples/averages.py @@ -12,7 +12,7 @@ from __future__ import print_function import pyspike as spk spike_trains = spk.load_spike_trains_from_txt("PySpike_testdata.txt", - time_interval=(0, 4000)) + edges=(0, 4000)) f = spk.isi_profile(spike_trains[0], spike_trains[1]) diff --git a/examples/merge.py b/examples/merge.py index 2ea96ea..b4437a3 100644 --- a/examples/merge.py +++ b/examples/merge.py @@ -21,9 +21,9 @@ merged_spike_train = spk.merge_spike_trains([spike_trains[0], spike_trains[1]]) print(merged_spike_train.spikes) -plt.plot(spike_trains[0].spikes, np.ones_like(spike_trains[0].spikes), 'o') -plt.plot(spike_trains[1].spikes, np.ones_like(spike_trains[1].spikes), 'x') +plt.plot(spike_trains[0], np.ones_like(spike_trains[0]), 'o') +plt.plot(spike_trains[1], np.ones_like(spike_trains[1]), 'x') plt.plot(merged_spike_train.spikes, - 2*np.ones_like(merged_spike_train.spikes), 'o') + 2*np.ones_like(merged_spike_train), 'o') plt.show() diff --git a/examples/multivariate.py b/examples/multivariate.py index 93f8516..e9579a5 100644 --- a/examples/multivariate.py +++ b/examples/multivariate.py @@ -28,7 +28,7 @@ num_of_spikes = sum([len(spike_trains[i]) print("Number of spikes: %d" % num_of_spikes) # calculate the multivariate spike distance -f = spk.spike_profile_multi(spike_trains) +f = spk.spike_profile(spike_trains) t_spike = time.clock() @@ -39,7 +39,7 @@ print("Spike distance from average: %.8f" % avrg) t_avrg = time.clock() # compute average distance directly, should give the same result as above -spike_dist = spk.spike_distance_multi(spike_trains) +spike_dist = spk.spike_distance(spike_trains) print("Spike distance directly: %.8f" % spike_dist) t_dist = time.clock() diff --git a/examples/performance.py b/examples/performance.py index ec6c830..30691f8 100644 --- a/examples/performance.py +++ b/examples/performance.py @@ -31,38 +31,41 @@ for i in range(M): t_end = datetime.now() runtime = (t_end-t_start).total_seconds() +sort_by = 'tottime' +# sort_by = 'cumtime' + print("Spike generation runtime: %.3fs" % runtime) print() print("================ ISI COMPUTATIONS ================") print(" MULTIVARIATE DISTANCE") -cProfile.run('spk.isi_distance_multi(spike_trains)', 'performance.stat') +cProfile.run('spk.isi_distance(spike_trains)', 'performance.stat') p = pstats.Stats('performance.stat') -p.strip_dirs().sort_stats('tottime').print_stats(5) +p.strip_dirs().sort_stats(sort_by).print_stats(5) print(" MULTIVARIATE PROFILE") -cProfile.run('spk.isi_profile_multi(spike_trains)', 'performance.stat') +cProfile.run('spk.isi_profile(spike_trains)', 'performance.stat') p = pstats.Stats('performance.stat') -p.strip_dirs().sort_stats('tottime').print_stats(5) +p.strip_dirs().sort_stats(sort_by).print_stats(5) print("================ SPIKE COMPUTATIONS ================") print(" MULTIVARIATE DISTANCE") -cProfile.run('spk.spike_distance_multi(spike_trains)', 'performance.stat') +cProfile.run('spk.spike_distance(spike_trains)', 'performance.stat') p = pstats.Stats('performance.stat') -p.strip_dirs().sort_stats('tottime').print_stats(5) +p.strip_dirs().sort_stats(sort_by).print_stats(5) print(" MULTIVARIATE PROFILE") -cProfile.run('spk.spike_profile_multi(spike_trains)', 'performance.stat') +cProfile.run('spk.spike_profile(spike_trains)', 'performance.stat') p = pstats.Stats('performance.stat') -p.strip_dirs().sort_stats('tottime').print_stats(5) +p.strip_dirs().sort_stats(sort_by).print_stats(5) print("================ SPIKE-SYNC COMPUTATIONS ================") print(" MULTIVARIATE DISTANCE") -cProfile.run('spk.spike_sync_multi(spike_trains)', 'performance.stat') +cProfile.run('spk.spike_sync(spike_trains)', 'performance.stat') p = pstats.Stats('performance.stat') -p.strip_dirs().sort_stats('tottime').print_stats(5) +p.strip_dirs().sort_stats(sort_by).print_stats(5) print(" MULTIVARIATE PROFILE") -cProfile.run('spk.spike_sync_profile_multi(spike_trains)', 'performance.stat') +cProfile.run('spk.spike_sync_profile(spike_trains)', 'performance.stat') p = pstats.Stats('performance.stat') -p.strip_dirs().sort_stats('tottime').print_stats(5) +p.strip_dirs().sort_stats(sort_by).print_stats(5) diff --git a/examples/plot.py b/examples/plot.py index 1922939..a0e04da 100644 --- a/examples/plot.py +++ b/examples/plot.py @@ -24,7 +24,8 @@ spike_trains = spk.load_spike_trains_from_txt("PySpike_testdata.txt", for (i, spike_train) in enumerate(spike_trains): plt.scatter(spike_train, i*np.ones_like(spike_train), marker='|') -f = spk.isi_profile(spike_trains[0], spike_trains[1]) +# profile of the first two spike trains +f = spk.isi_profile(spike_trains, indices=[0, 1]) x, y = f.get_plottable_data() plt.figure() @@ -32,7 +33,7 @@ plt.plot(x, np.abs(y), '--k', label="ISI-profile") print("ISI-distance: %.8f" % f.avrg()) -f = spk.spike_profile(spike_trains[0], spike_trains[1]) +f = spk.spike_profile(spike_trains, indices=[0, 1]) x, y = f.get_plottable_data() plt.plot(x, y, '-b', label="SPIKE-profile") diff --git a/examples/profiles.py b/examples/profiles.py index 05494bd..8412ffb 100644 --- a/examples/profiles.py +++ b/examples/profiles.py @@ -29,7 +29,7 @@ print("Average ISI distance:", f.avrg()) print() # compute the multivariate ISI profile -f = spk.isi_profile_multi(spike_trains) +f = spk.isi_profile(spike_trains) t = 1200 print("Multivariate ISI value at t =", t, ":", f(t)) @@ -56,7 +56,7 @@ print("Average SPIKE distance:", f.avrg()) print() # compute the multivariate SPIKE profile -f = spk.spike_profile_multi(spike_trains) +f = spk.spike_profile(spike_trains) # SPIKE values at certain points t = 1200 diff --git a/examples/spike_sync.py b/examples/spike_sync.py index 37dbff4..13ca0ce 100644 --- a/examples/spike_sync.py +++ b/examples/spike_sync.py @@ -31,7 +31,7 @@ plt.figure() plt.subplot(211) -f = spk.spike_sync_profile_multi(spike_trains) +f = spk.spike_sync_profile(spike_trains) x, y = f.get_plottable_data() plt.plot(x, y, '-b', alpha=0.7, label="SPIKE-Sync profile") -- cgit v1.2.3