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(-) 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