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7de9f6c72d
This allows (and changes the current examples) to exit with status 99 to
skip a test instead of outputting a special string ("NumPy missing").
This also fixes the eigen test, which currently fails when eigen
headers are available but NumPy is not, to skip instead of failing when
NumPy isn't available.
72 lines
2.9 KiB
Python
72 lines
2.9 KiB
Python
#!/usr/bin/env python
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from __future__ import print_function
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import sys
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sys.path.append('.')
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from example import fixed_r, fixed_c
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from example import fixed_passthrough_r, fixed_passthrough_c
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from example import dense_r, dense_c
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from example import dense_passthrough_r, dense_passthrough_c
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from example import sparse_r, sparse_c
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from example import sparse_passthrough_r, sparse_passthrough_c
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from example import double_row, double_col
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from example import double_mat_cm, double_mat_rm
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try:
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import numpy as np
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except ImportError:
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# NumPy missing: skip test
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exit(99)
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ref = np.array(
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[[0, 3, 0, 0, 0, 11],
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[22, 0, 0, 0, 17, 11],
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[7, 5, 0, 1, 0, 11],
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[0, 0, 0, 0, 0, 11],
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[0, 0, 14, 0, 8, 11]])
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def check(mat):
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return 'OK' if np.sum(abs(mat - ref)) == 0 else 'NOT OK'
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print("should_give_NOT_OK = %s" % check(ref[:, ::-1]))
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print("fixed_r = %s" % check(fixed_r()))
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print("fixed_c = %s" % check(fixed_c()))
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print("pt_r(fixed_r) = %s" % check(fixed_passthrough_r(fixed_r())))
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print("pt_c(fixed_c) = %s" % check(fixed_passthrough_c(fixed_c())))
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print("pt_r(fixed_c) = %s" % check(fixed_passthrough_r(fixed_c())))
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print("pt_c(fixed_r) = %s" % check(fixed_passthrough_c(fixed_r())))
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print("dense_r = %s" % check(dense_r()))
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print("dense_c = %s" % check(dense_c()))
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print("pt_r(dense_r) = %s" % check(dense_passthrough_r(dense_r())))
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print("pt_c(dense_c) = %s" % check(dense_passthrough_c(dense_c())))
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print("pt_r(dense_c) = %s" % check(dense_passthrough_r(dense_c())))
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print("pt_c(dense_r) = %s" % check(dense_passthrough_c(dense_r())))
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print("sparse_r = %s" % check(sparse_r()))
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print("sparse_c = %s" % check(sparse_c()))
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print("pt_r(sparse_r) = %s" % check(sparse_passthrough_r(sparse_r())))
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print("pt_c(sparse_c) = %s" % check(sparse_passthrough_c(sparse_c())))
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print("pt_r(sparse_c) = %s" % check(sparse_passthrough_r(sparse_c())))
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print("pt_c(sparse_r) = %s" % check(sparse_passthrough_c(sparse_r())))
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def check_got_vs_ref(got_x, ref_x):
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return 'OK' if np.array_equal(got_x, ref_x) else 'NOT OK'
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counting_mat = np.arange(9.0, dtype=np.float32).reshape((3, 3))
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first_row = counting_mat[0, :]
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first_col = counting_mat[:, 0]
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print("double_row(first_row) = %s" % check_got_vs_ref(double_row(first_row), 2.0 * first_row))
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print("double_col(first_row) = %s" % check_got_vs_ref(double_col(first_row), 2.0 * first_row))
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print("double_row(first_col) = %s" % check_got_vs_ref(double_row(first_col), 2.0 * first_col))
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print("double_col(first_col) = %s" % check_got_vs_ref(double_col(first_col), 2.0 * first_col))
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counting_3d = np.arange(27.0, dtype=np.float32).reshape((3, 3, 3))
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slices = [counting_3d[0, :, :], counting_3d[:, 0, :], counting_3d[:, :, 0]]
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for slice_idx, ref_mat in enumerate(slices):
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print("double_mat_cm(%d) = %s" % (slice_idx, check_got_vs_ref(double_mat_cm(ref_mat), 2.0 * ref_mat)))
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print("double_mat_rm(%d) = %s" % (slice_idx, check_got_vs_ref(double_mat_rm(ref_mat), 2.0 * ref_mat)))
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