def test_gen_sample_by_factors():
test_GUMP_SCENES_IDS = [26, 36, 25, 38]
g1=gen_sample_by_factors(test_GUMP_SCENES_IDS, factor_grid, False)
f3=list(g1[0].values())[0]
r3=(np.array([128, 129, 130, 131, 132, 133, 134, 135, 136, 137]),
np.array([138, 139, 140, 141, 142, 143, 144, 145, 146, 147]))
f4=g1[1]
r4=[25]
assert_almost_equal(f3,r3)
assert_almost_equal(f4,r4)
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 66, 66, 66, 66, 66, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 66, 66, 66, 66, 66, 66, 66, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 66, 66, 66])
assert_almost_equal(f2,r2)
test_GUMP_SCENES_IDS = [26, 36, 25, 38]
samp_gump, miss_gump = gen_sample_by_factors(test_GUMP_SCENES_IDS, factor_grid, False)
def test_gen_sample_by_factors():
test_GUMP_SCENES_IDS = [26, 36, 25, 38]
g1=gen_sample_by_factors(test_GUMP_SCENES_IDS, factor_grid, False)
f3=list(g1[0].values())[0]
r3=(np.array([128, 129, 130, 131, 132, 133, 134, 135, 136, 137]),
np.array([138, 139, 140, 141, 142, 143, 144, 145, 146, 147]))
f4=g1[1]
r4=[25]
assert_almost_equal(f3,r3)
assert_almost_equal(f4,r4)
def test_get_training_samples():
r5 = np.array([128, 129, 130, 131, 132, 133, 134, 135, 136, 137])
f5= list(get_training_samples(samp_gump).values())[0]
