From 8d89279046fd24c58d617cf8fc3d5788a907c87c Mon Sep 17 00:00:00 2001 From: Gard Spreemann Date: Sat, 7 Mar 2020 18:52:56 +0100 Subject: Add patch to allow floating point behavior differences in tests. --- ...allclose-instead-of-assert_equal-in-tests.patch | 675 +++++++++++++++++++++ debian/patches/series | 1 + 2 files changed, 676 insertions(+) create mode 100644 debian/patches/0001-Use-assert_allclose-instead-of-assert_equal-in-tests.patch create mode 100644 debian/patches/series (limited to 'debian/patches') 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 new file mode 100644 index 0000000..b03409d --- /dev/null +++ b/debian/patches/0001-Use-assert_allclose-instead-of-assert_equal-in-tests.patch @@ -0,0 +1,675 @@ +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": diff --git a/debian/patches/series b/debian/patches/series new file mode 100644 index 0000000..e2a97f9 --- /dev/null +++ b/debian/patches/series @@ -0,0 +1 @@ +0001-Use-assert_allclose-instead-of-assert_equal-in-tests.patch -- cgit v1.2.3