From 52a0028775c6dd167795a15bb452c67739084ec1 Mon Sep 17 00:00:00 2001 From: Gard Spreemann Date: Thu, 30 Dec 2021 17:48:11 +0100 Subject: New upstream version --- ...allclose-instead-of-assert_equal-in-tests.patch | 675 --------------------- 1 file changed, 675 deletions(-) delete mode 100644 debian/patches/0001-Use-assert_allclose-instead-of-assert_equal-in-tests.patch (limited to 'debian/patches/0001-Use-assert_allclose-instead-of-assert_equal-in-tests.patch') diff --git a/debian/patches/0001-Use-assert_allclose-instead-of-assert_equal-in-tests.patch b/debian/patches/0001-Use-assert_allclose-instead-of-assert_equal-in-tests.patch deleted file mode 100644 index b03409d..0000000 --- a/debian/patches/0001-Use-assert_allclose-instead-of-assert_equal-in-tests.patch +++ /dev/null @@ -1,675 +0,0 @@ -From: Gard Spreemann -Date: Sat, 7 Mar 2020 18:51:42 +0100 -Subject: Use assert_allclose instead of assert_equal in tests. - ---- - test/test_distance.py | 70 +++++++++++++++--------------- - test/test_empty.py | 36 +++++++-------- - test/test_function.py | 52 +++++++++++----------- - test/test_generic_interfaces.py | 18 ++++---- - test/test_regression/test_regression_15.py | 20 ++++----- - test/test_spikes.py | 10 ++--- - test/test_sync_filter.py | 32 +++++++------- - 7 files changed, 119 insertions(+), 119 deletions(-) - -diff --git a/test/test_distance.py b/test/test_distance.py -index fe09f34..7ec3a72 100644 ---- a/test/test_distance.py -+++ b/test/test_distance.py -@@ -11,7 +11,7 @@ Distributed under the BSD License - from __future__ import print_function - import numpy as np - from copy import copy --from numpy.testing import assert_equal, assert_almost_equal, \ -+from numpy.testing import assert_allclose, assert_almost_equal, \ - assert_array_almost_equal - - import pyspike as spk -@@ -41,10 +41,10 @@ def test_isi(): - # print("ISI: ", f.y) - print("ISI value:", expected_isi_val) - -- assert_equal(f.x, expected_times) -+ assert_allclose(f.x, expected_times) - assert_array_almost_equal(f.y, expected_isi, decimal=15) -- assert_equal(f.avrg(), expected_isi_val) -- assert_equal(spk.isi_distance(t1, t2), expected_isi_val) -+ assert_allclose(f.avrg(), expected_isi_val) -+ assert_allclose(spk.isi_distance(t1, t2), expected_isi_val) - - # check with some equal spike times - t1 = SpikeTrain([0.2, 0.4, 0.6], [0.0, 1.0]) -@@ -60,10 +60,10 @@ def test_isi(): - - f = spk.isi_profile(t1, t2) - -- assert_equal(f.x, expected_times) -+ assert_allclose(f.x, expected_times) - assert_array_almost_equal(f.y, expected_isi, decimal=15) -- assert_equal(f.avrg(), expected_isi_val) -- assert_equal(spk.isi_distance(t1, t2), expected_isi_val) -+ assert_allclose(f.avrg(), expected_isi_val) -+ assert_allclose(spk.isi_distance(t1, t2), expected_isi_val) - - - def test_spike(): -@@ -75,7 +75,7 @@ def test_spike(): - - f = spk.spike_profile(t1, t2) - -- assert_equal(f.x, expected_times) -+ assert_allclose(f.x, expected_times) - - # from SPIKY: - y_all = np.array([0.000000000000000000, 0.555555555555555580, -@@ -89,7 +89,7 @@ def test_spike(): - assert_array_almost_equal(f.y2, y_all[1::2]) - - assert_almost_equal(f.avrg(), 0.186309523809523814, decimal=15) -- assert_equal(spk.spike_distance(t1, t2), f.avrg()) -+ assert_allclose(spk.spike_distance(t1, t2), f.avrg()) - - t1 = SpikeTrain([0.2, 0.4, 0.6, 0.7], 1.0) - t2 = SpikeTrain([0.3, 0.45, 0.8, 0.9, 0.95], 1.0) -@@ -118,7 +118,7 @@ def test_spike(): - - f = spk.spike_profile(t1, t2) - -- assert_equal(f.x, expected_times) -+ assert_allclose(f.x, expected_times) - assert_array_almost_equal(f.y1, expected_y1, decimal=15) - assert_array_almost_equal(f.y2, expected_y2, decimal=15) - assert_almost_equal(f.avrg(), expected_spike_val, decimal=15) -@@ -157,7 +157,7 @@ def test_spike(): - - f = spk.spike_profile(t1, t2) - -- assert_equal(f.x, expected_times) -+ assert_allclose(f.x, expected_times) - assert_array_almost_equal(f.y1, expected_y1, decimal=14) - assert_array_almost_equal(f.y2, expected_y2, decimal=14) - assert_almost_equal(f.avrg(), expected_spike_val, decimal=16) -@@ -236,8 +236,8 @@ def test_spike_sync(): - f.add(f2) - i12 = f.integral() - -- assert_equal(i1[0]+i2[0], i12[0]) -- assert_equal(i1[1]+i2[1], i12[1]) -+ assert_allclose(i1[0]+i2[0], i12[0]) -+ assert_allclose(i1[1]+i2[1], i12[1]) - - - def check_multi_profile(profile_func, profile_func_multi, dist_func_multi): -@@ -258,7 +258,7 @@ def check_multi_profile(profile_func, profile_func_multi, dist_func_multi): - f_multi = profile_func_multi(spike_trains, [0, 1]) - assert f_multi.almost_equal(f12, decimal=14) - d = dist_func_multi(spike_trains, [0, 1]) -- assert_equal(f_multi.avrg(), d) -+ assert_allclose(f_multi.avrg(), d) - - f_multi1 = profile_func_multi(spike_trains, [1, 2, 3]) - f_multi2 = profile_func_multi(spike_trains[1:]) -@@ -329,11 +329,11 @@ def test_multi_spike_sync(): - - f = spk.spike_sync_profile_multi(spike_trains) - -- assert_equal(spike_times, f.x[1:-1]) -- assert_equal(len(f.x), len(f.y)) -+ assert_allclose(spike_times, f.x[1:-1]) -+ assert_allclose(len(f.x), len(f.y)) - -- assert_equal(np.sum(f.y[1:-1]), 39932) -- assert_equal(np.sum(f.mp[1:-1]), 85554) -+ assert_allclose(np.sum(f.y[1:-1]), 39932) -+ assert_allclose(np.sum(f.mp[1:-1]), 85554) - - # example with 2 empty spike trains - sts = [] -@@ -365,16 +365,16 @@ def check_dist_matrix(dist_func, dist_matrix_func): - f_matrix = dist_matrix_func(spike_trains) - # check zero diagonal - for i in range(4): -- assert_equal(0.0, f_matrix[i, i]) -+ assert_allclose(0.0, f_matrix[i, i]) - 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]) -- assert_equal(f14, f_matrix[3, 0]) -- assert_equal(f23, f_matrix[2, 1]) -- assert_equal(f24, f_matrix[3, 1]) -- assert_equal(f34, f_matrix[3, 2]) -+ assert_allclose(f_matrix[i, j], f_matrix[j, i]) -+ assert_allclose(f12, f_matrix[1, 0]) -+ assert_allclose(f13, f_matrix[2, 0]) -+ assert_allclose(f14, f_matrix[3, 0]) -+ assert_allclose(f23, f_matrix[2, 1]) -+ assert_allclose(f24, f_matrix[3, 1]) -+ assert_allclose(f34, f_matrix[3, 2]) - - - def test_isi_matrix(): -@@ -397,13 +397,13 @@ def test_regression_spiky(): - isi_dist = spk.isi_distance(st1, st2) - assert_almost_equal(isi_dist, 9.0909090909090939e-02, decimal=15) - isi_profile = spk.isi_profile(st1, st2) -- assert_equal(isi_profile.y, 0.1/1.1 * np.ones_like(isi_profile.y)) -+ assert_allclose(isi_profile.y, 0.1/1.1 * np.ones_like(isi_profile.y)) - - spike_dist = spk.spike_distance(st1, st2) -- assert_equal(spike_dist, 0.211058782487353908) -+ assert_allclose(spike_dist, 0.211058782487353908) - - spike_sync = spk.spike_sync(st1, st2) -- assert_equal(spike_sync, 8.6956521739130432e-01) -+ assert_allclose(spike_sync, 8.6956521739130432e-01) - - # multivariate check - -@@ -414,7 +414,7 @@ def test_regression_spiky(): - assert_almost_equal(isi_dist, 0.17051816816999129656, decimal=15) - - spike_profile = spk.spike_profile_multi(spike_trains) -- assert_equal(len(spike_profile.y1)+len(spike_profile.y2), 1252) -+ assert_allclose(len(spike_profile.y1)+len(spike_profile.y2), 1252) - - spike_dist = spk.spike_distance_multi(spike_trains) - # get the full precision from SPIKY -@@ -422,7 +422,7 @@ def test_regression_spiky(): - - spike_sync = spk.spike_sync_multi(spike_trains) - # get the full precision from SPIKY -- assert_equal(spike_sync, 0.7183531505298066) -+ assert_allclose(spike_sync, 0.7183531505298066) - - # Eero's edge correction example - st1 = SpikeTrain([0.5, 1.5, 2.5], 6.0) -@@ -439,7 +439,7 @@ def test_regression_spiky(): - expected_y1 = y_all[::2] - expected_y2 = y_all[1::2] - -- assert_equal(f.x, expected_times) -+ assert_allclose(f.x, expected_times) - assert_array_almost_equal(f.y1, expected_y1, decimal=14) - assert_array_almost_equal(f.y2, expected_y2, decimal=14) - -@@ -452,15 +452,15 @@ def test_multi_variate_subsets(): - - v1 = spk.isi_distance_multi(spike_trains_sub_set) - v2 = spk.isi_distance_multi(spike_trains, sub_set) -- assert_equal(v1, v2) -+ assert_allclose(v1, v2) - - v1 = spk.spike_distance_multi(spike_trains_sub_set) - v2 = spk.spike_distance_multi(spike_trains, sub_set) -- assert_equal(v1, v2) -+ assert_allclose(v1, v2) - - v1 = spk.spike_sync_multi(spike_trains_sub_set) - v2 = spk.spike_sync_multi(spike_trains, sub_set) -- assert_equal(v1, v2) -+ assert_allclose(v1, v2) - - - if __name__ == "__main__": -diff --git a/test/test_empty.py b/test/test_empty.py -index 4d0a5cf..93fd2c1 100644 ---- a/test/test_empty.py -+++ b/test/test_empty.py -@@ -10,7 +10,7 @@ Distributed under the BSD License - - from __future__ import print_function - import numpy as np --from numpy.testing import assert_equal, assert_almost_equal, \ -+from numpy.testing import assert_allclose, assert_almost_equal, \ - assert_array_equal, assert_array_almost_equal - - import pyspike as spk -@@ -33,18 +33,18 @@ def test_isi_empty(): - st1 = SpikeTrain([], edges=(0.0, 1.0)) - st2 = SpikeTrain([], edges=(0.0, 1.0)) - d = spk.isi_distance(st1, st2) -- assert_equal(d, 0.0) -+ assert_allclose(d, 0.0) - prof = spk.isi_profile(st1, st2) -- assert_equal(d, prof.avrg()) -+ assert_allclose(d, prof.avrg()) - assert_array_equal(prof.x, [0.0, 1.0]) - assert_array_equal(prof.y, [0.0, ]) - - st1 = SpikeTrain([], edges=(0.0, 1.0)) - st2 = SpikeTrain([0.4, ], edges=(0.0, 1.0)) - d = spk.isi_distance(st1, st2) -- assert_equal(d, 0.6*0.4+0.4*0.6) -+ assert_allclose(d, 0.6*0.4+0.4*0.6) - prof = spk.isi_profile(st1, st2) -- assert_equal(d, prof.avrg()) -+ assert_allclose(d, prof.avrg()) - assert_array_equal(prof.x, [0.0, 0.4, 1.0]) - assert_array_equal(prof.y, [0.6, 0.4]) - -@@ -53,7 +53,7 @@ def test_isi_empty(): - d = spk.isi_distance(st1, st2) - assert_almost_equal(d, 0.2/0.6*0.4 + 0.0 + 0.2/0.6*0.4, decimal=15) - prof = spk.isi_profile(st1, st2) -- assert_equal(d, prof.avrg()) -+ assert_allclose(d, prof.avrg()) - assert_array_almost_equal(prof.x, [0.0, 0.4, 0.6, 1.0], decimal=15) - assert_array_almost_equal(prof.y, [0.2/0.6, 0.0, 0.2/0.6], decimal=15) - -@@ -62,9 +62,9 @@ def test_spike_empty(): - st1 = SpikeTrain([], edges=(0.0, 1.0)) - st2 = SpikeTrain([], edges=(0.0, 1.0)) - d = spk.spike_distance(st1, st2) -- assert_equal(d, 0.0) -+ assert_allclose(d, 0.0) - prof = spk.spike_profile(st1, st2) -- assert_equal(d, prof.avrg()) -+ assert_allclose(d, prof.avrg()) - assert_array_equal(prof.x, [0.0, 1.0]) - assert_array_equal(prof.y1, [0.0, ]) - assert_array_equal(prof.y2, [0.0, ]) -@@ -75,7 +75,7 @@ def test_spike_empty(): - d_expect = 2*0.4*0.4*1.0/(0.4+1.0)**2 + 2*0.6*0.4*1.0/(0.6+1.0)**2 - assert_almost_equal(d, d_expect, decimal=15) - prof = spk.spike_profile(st1, st2) -- assert_equal(d, prof.avrg()) -+ assert_allclose(d, prof.avrg()) - assert_array_equal(prof.x, [0.0, 0.4, 1.0]) - assert_array_almost_equal(prof.y1, [2*0.4*1.0/(0.4+1.0)**2, - 2*0.4*1.0/(0.6+1.0)**2], -@@ -100,7 +100,7 @@ def test_spike_empty(): - - assert_almost_equal(d, expected_spike_val, decimal=15) - prof = spk.spike_profile(st1, st2) -- assert_equal(d, prof.avrg()) -+ assert_allclose(d, prof.avrg()) - assert_array_almost_equal(prof.x, [0.0, 0.4, 0.6, 1.0], decimal=15) - assert_array_almost_equal(prof.y1, expected_y1, decimal=15) - assert_array_almost_equal(prof.y2, expected_y2, decimal=15) -@@ -110,18 +110,18 @@ def test_spike_sync_empty(): - st1 = SpikeTrain([], edges=(0.0, 1.0)) - st2 = SpikeTrain([], edges=(0.0, 1.0)) - d = spk.spike_sync(st1, st2) -- assert_equal(d, 1.0) -+ assert_allclose(d, 1.0) - prof = spk.spike_sync_profile(st1, st2) -- assert_equal(d, prof.avrg()) -+ assert_allclose(d, prof.avrg()) - assert_array_equal(prof.x, [0.0, 1.0]) - assert_array_equal(prof.y, [1.0, 1.0]) - - st1 = SpikeTrain([], edges=(0.0, 1.0)) - st2 = SpikeTrain([0.4, ], edges=(0.0, 1.0)) - d = spk.spike_sync(st1, st2) -- assert_equal(d, 0.0) -+ assert_allclose(d, 0.0) - prof = spk.spike_sync_profile(st1, st2) -- assert_equal(d, prof.avrg()) -+ assert_allclose(d, prof.avrg()) - assert_array_equal(prof.x, [0.0, 0.4, 1.0]) - assert_array_equal(prof.y, [0.0, 0.0, 0.0]) - -@@ -130,7 +130,7 @@ def test_spike_sync_empty(): - d = spk.spike_sync(st1, st2) - assert_almost_equal(d, 1.0, decimal=15) - prof = spk.spike_sync_profile(st1, st2) -- assert_equal(d, prof.avrg()) -+ assert_allclose(d, prof.avrg()) - assert_array_almost_equal(prof.x, [0.0, 0.4, 0.6, 1.0], decimal=15) - assert_array_almost_equal(prof.y, [1.0, 1.0, 1.0, 1.0], decimal=15) - -@@ -139,7 +139,7 @@ def test_spike_sync_empty(): - d = spk.spike_sync(st1, st2) - assert_almost_equal(d, 0.0, decimal=15) - prof = spk.spike_sync_profile(st1, st2) -- assert_equal(d, prof.avrg()) -+ assert_allclose(d, prof.avrg()) - assert_array_almost_equal(prof.x, [0.0, 0.2, 0.8, 1.0], decimal=15) - assert_array_almost_equal(prof.y, [0.0, 0.0, 0.0, 0.0], decimal=15) - -@@ -148,9 +148,9 @@ def test_spike_sync_empty(): - st2 = SpikeTrain([2.1, 7.0], [0, 10.0]) - st3 = SpikeTrain([5.1, 6.0], [0, 10.0]) - res = spk.spike_sync_profile(st1, st2).avrg(interval=[3.0, 4.0]) -- assert_equal(res, 1.0) -+ assert_allclose(res, 1.0) - res = spk.spike_sync(st1, st2, interval=[3.0, 4.0]) -- assert_equal(res, 1.0) -+ assert_allclose(res, 1.0) - - sync_matrix = spk.spike_sync_matrix([st1, st2, st3], interval=[3.0, 4.0]) - assert_array_equal(sync_matrix, np.ones((3, 3)) - np.diag(np.ones(3))) -diff --git a/test/test_function.py b/test/test_function.py -index 6c04839..ba10ae7 100644 ---- a/test/test_function.py -+++ b/test/test_function.py -@@ -11,7 +11,7 @@ from __future__ import print_function - import numpy as np - from copy import copy - from nose.tools import raises --from numpy.testing import assert_equal, assert_almost_equal, \ -+from numpy.testing import assert_allclose, assert_almost_equal, \ - assert_array_equal, assert_array_almost_equal - - import pyspike as spk -@@ -24,14 +24,14 @@ def test_pwc(): - f = spk.PieceWiseConstFunc(x, y) - - # function values -- assert_equal(f(0.0), 1.0) -- assert_equal(f(0.5), 1.0) -- assert_equal(f(1.0), 0.25) -- assert_equal(f(2.0), 0.5) -- assert_equal(f(2.25), 1.5) -- assert_equal(f(2.5), 2.25/2) -- assert_equal(f(3.5), 0.75) -- assert_equal(f(4.0), 0.75) -+ assert_allclose(f(0.0), 1.0) -+ assert_allclose(f(0.5), 1.0) -+ assert_allclose(f(1.0), 0.25) -+ assert_allclose(f(2.0), 0.5) -+ assert_allclose(f(2.25), 1.5) -+ assert_allclose(f(2.5), 2.25/2) -+ assert_allclose(f(3.5), 0.75) -+ assert_allclose(f(4.0), 0.75) - - assert_array_equal(f([0.0, 0.5, 1.0, 2.0, 2.25, 2.5, 3.5, 4.0]), - [1.0, 1.0, 0.25, 0.5, 1.5, 2.25/2, 0.75, 0.75]) -@@ -131,21 +131,21 @@ def test_pwc_integral(): - - # test full interval - full = 1.0*1.0 + 1.0*-0.5 + 0.5*1.5 + 1.5*0.75; -- assert_equal(f1.integral(), full) -- assert_equal(f1.integral((np.min(x),np.max(x))), full) -+ assert_allclose(f1.integral(), full) -+ assert_allclose(f1.integral((np.min(x),np.max(x))), full) - # test part interval, spanning an edge -- assert_equal(f1.integral((0.5,1.5)), 0.5*1.0 + 0.5*-0.5) -+ assert_allclose(f1.integral((0.5,1.5)), 0.5*1.0 + 0.5*-0.5) - # test part interval, just over two edges - assert_almost_equal(f1.integral((1.0-1e-16,2+1e-16)), 1.0*-0.5, decimal=14) - # test part interval, between two edges -- assert_equal(f1.integral((1.0,2.0)), 1.0*-0.5) -- assert_equal(f1.integral((1.2,1.7)), (1.7-1.2)*-0.5) -+ assert_allclose(f1.integral((1.0,2.0)), 1.0*-0.5) -+ assert_allclose(f1.integral((1.2,1.7)), (1.7-1.2)*-0.5) - # test part interval, start to before and after edge -- assert_equal(f1.integral((0.0,0.7)), 0.7*1.0) -- assert_equal(f1.integral((0.0,1.1)), 1.0*1.0+0.1*-0.5) -+ assert_allclose(f1.integral((0.0,0.7)), 0.7*1.0) -+ assert_allclose(f1.integral((0.0,1.1)), 1.0*1.0+0.1*-0.5) - # test part interval, before and after edge till end -- assert_equal(f1.integral((2.6,4.0)), (4.0-2.6)*0.75) -- assert_equal(f1.integral((2.4,4.0)), (2.5-2.4)*1.5+(4-2.5)*0.75) -+ assert_allclose(f1.integral((2.6,4.0)), (4.0-2.6)*0.75) -+ assert_allclose(f1.integral((2.4,4.0)), (2.5-2.4)*1.5+(4-2.5)*0.75) - - @raises(ValueError) - def test_pwc_integral_bad_bounds_inv(): -@@ -178,14 +178,14 @@ def test_pwl(): - f = spk.PieceWiseLinFunc(x, y1, y2) - - # function values -- assert_equal(f(0.0), 1.0) -- assert_equal(f(0.5), 1.25) -- assert_equal(f(1.0), 0.5) -- assert_equal(f(2.0), 1.1/2) -- assert_equal(f(2.25), 1.5) -- assert_equal(f(2.5), 2.25/2) -- assert_equal(f(3.5), 0.75-0.5*1.0/1.5) -- assert_equal(f(4.0), 0.25) -+ assert_allclose(f(0.0), 1.0) -+ assert_allclose(f(0.5), 1.25) -+ assert_allclose(f(1.0), 0.5) -+ assert_allclose(f(2.0), 1.1/2) -+ assert_allclose(f(2.25), 1.5) -+ assert_allclose(f(2.5), 2.25/2) -+ assert_allclose(f(3.5), 0.75-0.5*1.0/1.5) -+ assert_allclose(f(4.0), 0.25) - - assert_array_equal(f([0.0, 0.5, 1.0, 2.0, 2.25, 2.5, 3.5, 4.0]), - [1.0, 1.25, 0.5, 0.55, 1.5, 2.25/2, 0.75-0.5/1.5, 0.25]) -diff --git a/test/test_generic_interfaces.py b/test/test_generic_interfaces.py -index 7f08067..553f3f4 100644 ---- a/test/test_generic_interfaces.py -+++ b/test/test_generic_interfaces.py -@@ -9,7 +9,7 @@ Distributed under the BSD License - """ - - from __future__ import print_function --from numpy.testing import assert_equal -+from numpy.testing import assert_allclose - - import pyspike as spk - from pyspike import SpikeTrain -@@ -43,33 +43,33 @@ def check_func(dist_func): - - isi12 = dist_func(t1, t2) - isi12_ = dist_func([t1, t2]) -- assert_equal(isi12, isi12_) -+ assert_allclose(isi12, isi12_) - - isi12_ = dist_func(spike_trains, indices=[0, 1]) -- assert_equal(isi12, isi12_) -+ assert_allclose(isi12, isi12_) - - isi123 = dist_func(t1, t2, t3) - isi123_ = dist_func([t1, t2, t3]) -- assert_equal(isi123, isi123_) -+ assert_allclose(isi123, isi123_) - - isi123_ = dist_func(spike_trains, indices=[0, 1, 2]) -- assert_equal(isi123, isi123_) -+ assert_allclose(isi123, isi123_) - - # run the same test with an additional interval parameter - - isi12 = dist_func(t1, t2, interval=[0.0, 0.5]) - isi12_ = dist_func([t1, t2], interval=[0.0, 0.5]) -- assert_equal(isi12, isi12_) -+ assert_allclose(isi12, isi12_) - - isi12_ = dist_func(spike_trains, indices=[0, 1], interval=[0.0, 0.5]) -- assert_equal(isi12, isi12_) -+ assert_allclose(isi12, isi12_) - - isi123 = dist_func(t1, t2, t3, interval=[0.0, 0.5]) - isi123_ = dist_func([t1, t2, t3], interval=[0.0, 0.5]) -- assert_equal(isi123, isi123_) -+ assert_allclose(isi123, isi123_) - - isi123_ = dist_func(spike_trains, indices=[0, 1, 2], interval=[0.0, 0.5]) -- assert_equal(isi123, isi123_) -+ assert_allclose(isi123, isi123_) - - - def test_isi_profile(): -diff --git a/test/test_regression/test_regression_15.py b/test/test_regression/test_regression_15.py -index 54adf23..81b5bb0 100644 ---- a/test/test_regression/test_regression_15.py -+++ b/test/test_regression/test_regression_15.py -@@ -11,7 +11,7 @@ Distributed under the BSD License - from __future__ import division - - import numpy as np --from numpy.testing import assert_equal, assert_almost_equal, \ -+from numpy.testing import assert_allclose, assert_almost_equal, \ - assert_array_almost_equal - - import pyspike as spk -@@ -28,15 +28,15 @@ def test_regression_15_isi(): - N = len(spike_trains) - - dist_mat = spk.isi_distance_matrix(spike_trains) -- assert_equal(dist_mat.shape, (N, N)) -+ assert_allclose(dist_mat.shape, (N, N)) - - ind = np.arange(N//2) - dist_mat = spk.isi_distance_matrix(spike_trains, ind) -- assert_equal(dist_mat.shape, (N//2, N//2)) -+ assert_allclose(dist_mat.shape, (N//2, N//2)) - - ind = np.arange(N//2, N) - dist_mat = spk.isi_distance_matrix(spike_trains, ind) -- assert_equal(dist_mat.shape, (N//2, N//2)) -+ assert_allclose(dist_mat.shape, (N//2, N//2)) - - - def test_regression_15_spike(): -@@ -46,15 +46,15 @@ def test_regression_15_spike(): - N = len(spike_trains) - - dist_mat = spk.spike_distance_matrix(spike_trains) -- assert_equal(dist_mat.shape, (N, N)) -+ assert_allclose(dist_mat.shape, (N, N)) - - ind = np.arange(N//2) - dist_mat = spk.spike_distance_matrix(spike_trains, ind) -- assert_equal(dist_mat.shape, (N//2, N//2)) -+ assert_allclose(dist_mat.shape, (N//2, N//2)) - - ind = np.arange(N//2, N) - dist_mat = spk.spike_distance_matrix(spike_trains, ind) -- assert_equal(dist_mat.shape, (N//2, N//2)) -+ assert_allclose(dist_mat.shape, (N//2, N//2)) - - - def test_regression_15_sync(): -@@ -64,15 +64,15 @@ def test_regression_15_sync(): - N = len(spike_trains) - - dist_mat = spk.spike_sync_matrix(spike_trains) -- assert_equal(dist_mat.shape, (N, N)) -+ assert_allclose(dist_mat.shape, (N, N)) - - ind = np.arange(N//2) - dist_mat = spk.spike_sync_matrix(spike_trains, ind) -- assert_equal(dist_mat.shape, (N//2, N//2)) -+ assert_allclose(dist_mat.shape, (N//2, N//2)) - - ind = np.arange(N//2, N) - dist_mat = spk.spike_sync_matrix(spike_trains, ind) -- assert_equal(dist_mat.shape, (N//2, N//2)) -+ assert_allclose(dist_mat.shape, (N//2, N//2)) - - - if __name__ == "__main__": -diff --git a/test/test_spikes.py b/test/test_spikes.py -index ee505b5..579f8e1 100644 ---- a/test/test_spikes.py -+++ b/test/test_spikes.py -@@ -9,7 +9,7 @@ Distributed under the BSD License - - from __future__ import print_function - import numpy as np --from numpy.testing import assert_equal -+from numpy.testing import assert_allclose - - import pyspike as spk - -@@ -29,7 +29,7 @@ def test_load_from_txt(): - spike_times = [64.886, 305.81, 696, 937.77, 1059.7, 1322.2, 1576.1, - 1808.1, 2121.5, 2381.1, 2728.6, 2966.9, 3223.7, 3473.7, - 3644.3, 3936.3] -- assert_equal(spike_times, spike_trains[0].spikes) -+ assert_allclose(spike_times, spike_trains[0].spikes) - - # check auxiliary spikes - for spike_train in spike_trains: -@@ -47,9 +47,9 @@ def test_load_time_series(): - - # check spike trains - for n in range(len(spike_trains)): -- assert_equal(spike_trains[n].spikes, spike_trains_check[n].spikes) -- assert_equal(spike_trains[n].t_start, 0) -- assert_equal(spike_trains[n].t_end, 4000) -+ assert_allclose(spike_trains[n].spikes, spike_trains_check[n].spikes) -+ assert_allclose(spike_trains[n].t_start, 0) -+ assert_allclose(spike_trains[n].t_end, 4000) - - - def check_merged_spikes(merged_spikes, spike_trains): -diff --git a/test/test_sync_filter.py b/test/test_sync_filter.py -index e259903..0b915db 100644 ---- a/test/test_sync_filter.py -+++ b/test/test_sync_filter.py -@@ -10,7 +10,7 @@ Distributed under the BSD License - - from __future__ import print_function - import numpy as np --from numpy.testing import assert_equal, assert_almost_equal, \ -+from numpy.testing import assert_allclose, assert_almost_equal, \ - assert_array_almost_equal - - import pyspike as spk -@@ -36,21 +36,21 @@ def test_single_prof(): - coincidences = np.array(coincidence_impl(st1, st2, 0, 5.0, 0.0)) - print(coincidences) - for i, t in enumerate(st1): -- assert_equal(coincidences[i], sync_prof.y[sync_prof.x == t], -- "At index %d" % i) -+ assert_allclose(coincidences[i], sync_prof.y[sync_prof.x == t], -+ err_msg="At index %d" % i) - - coincidences = np.array(coincidence_impl(st2, st1, 0, 5.0, 0.0)) - for i, t in enumerate(st2): -- assert_equal(coincidences[i], sync_prof.y[sync_prof.x == t], -- "At index %d" % i) -+ assert_allclose(coincidences[i], sync_prof.y[sync_prof.x == t], -+ err_msg="At index %d" % i) - - sync_prof = spk.spike_sync_profile(SpikeTrain(st1, 5.0), - SpikeTrain(st3, 5.0)) - - coincidences = np.array(coincidence_impl(st1, st3, 0, 5.0, 0.0)) - for i, t in enumerate(st1): -- assert_equal(coincidences[i], sync_prof.y[sync_prof.x == t], -- "At index %d" % i) -+ assert_allclose(coincidences[i], sync_prof.y[sync_prof.x == t], -+ err_msg="At index %d" % i) - - st1 = np.array([1.0, 2.0, 3.0, 4.0]) - st2 = np.array([1.0, 2.0, 4.0]) -@@ -61,8 +61,8 @@ def test_single_prof(): - coincidences = np.array(coincidence_impl(st1, st2, 0, 5.0, 0.0)) - for i, t in enumerate(st1): - expected = sync_prof.y[sync_prof.x == t]/sync_prof.mp[sync_prof.x == t] -- assert_equal(coincidences[i], expected, -- "At index %d" % i) -+ assert_allclose(coincidences[i], expected, -+ err_msg="At index %d" % i) - - - def test_filter(): -@@ -72,22 +72,22 @@ def test_filter(): - - # filtered_spike_trains = spk.filter_by_spike_sync([st1, st2], 0.5) - -- # assert_equal(filtered_spike_trains[0].spikes, [1.0, 2.0, 4.0]) -- # assert_equal(filtered_spike_trains[1].spikes, [1.1, 2.1, 3.8]) -+ # assert_allclose(filtered_spike_trains[0].spikes, [1.0, 2.0, 4.0]) -+ # assert_allclose(filtered_spike_trains[1].spikes, [1.1, 2.1, 3.8]) - - # filtered_spike_trains = spk.filter_by_spike_sync([st2, st1], 0.5) - -- # assert_equal(filtered_spike_trains[0].spikes, [1.1, 2.1, 3.8]) -- # assert_equal(filtered_spike_trains[1].spikes, [1.0, 2.0, 4.0]) -+ # assert_allclose(filtered_spike_trains[0].spikes, [1.1, 2.1, 3.8]) -+ # assert_allclose(filtered_spike_trains[1].spikes, [1.0, 2.0, 4.0]) - - filtered_spike_trains = spk.filter_by_spike_sync([st1, st2, st3], 0.75) - - for st in filtered_spike_trains: - print(st.spikes) - -- assert_equal(filtered_spike_trains[0].spikes, [1.0, 4.0]) -- assert_equal(filtered_spike_trains[1].spikes, [1.1, 3.8]) -- assert_equal(filtered_spike_trains[2].spikes, [0.9, 4.1]) -+ assert_allclose(filtered_spike_trains[0].spikes, [1.0, 4.0]) -+ assert_allclose(filtered_spike_trains[1].spikes, [1.1, 3.8]) -+ assert_allclose(filtered_spike_trains[2].spikes, [0.9, 4.1]) - - - if __name__ == "main": -- cgit v1.2.3