pybind11/example/eigen.py
Jason Rhinelander 7de9f6c72d Tests can skip by exiting with 99; fix eigen test failure
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.
2016-07-09 14:33:10 -04:00

72 lines
2.9 KiB
Python

#!/usr/bin/env python
from __future__ import print_function
import sys
sys.path.append('.')
from example import fixed_r, fixed_c
from example import fixed_passthrough_r, fixed_passthrough_c
from example import dense_r, dense_c
from example import dense_passthrough_r, dense_passthrough_c
from example import sparse_r, sparse_c
from example import sparse_passthrough_r, sparse_passthrough_c
from example import double_row, double_col
from example import double_mat_cm, double_mat_rm
try:
import numpy as np
except ImportError:
# NumPy missing: skip test
exit(99)
ref = np.array(
[[0, 3, 0, 0, 0, 11],
[22, 0, 0, 0, 17, 11],
[7, 5, 0, 1, 0, 11],
[0, 0, 0, 0, 0, 11],
[0, 0, 14, 0, 8, 11]])
def check(mat):
return 'OK' if np.sum(abs(mat - ref)) == 0 else 'NOT OK'
print("should_give_NOT_OK = %s" % check(ref[:, ::-1]))
print("fixed_r = %s" % check(fixed_r()))
print("fixed_c = %s" % check(fixed_c()))
print("pt_r(fixed_r) = %s" % check(fixed_passthrough_r(fixed_r())))
print("pt_c(fixed_c) = %s" % check(fixed_passthrough_c(fixed_c())))
print("pt_r(fixed_c) = %s" % check(fixed_passthrough_r(fixed_c())))
print("pt_c(fixed_r) = %s" % check(fixed_passthrough_c(fixed_r())))
print("dense_r = %s" % check(dense_r()))
print("dense_c = %s" % check(dense_c()))
print("pt_r(dense_r) = %s" % check(dense_passthrough_r(dense_r())))
print("pt_c(dense_c) = %s" % check(dense_passthrough_c(dense_c())))
print("pt_r(dense_c) = %s" % check(dense_passthrough_r(dense_c())))
print("pt_c(dense_r) = %s" % check(dense_passthrough_c(dense_r())))
print("sparse_r = %s" % check(sparse_r()))
print("sparse_c = %s" % check(sparse_c()))
print("pt_r(sparse_r) = %s" % check(sparse_passthrough_r(sparse_r())))
print("pt_c(sparse_c) = %s" % check(sparse_passthrough_c(sparse_c())))
print("pt_r(sparse_c) = %s" % check(sparse_passthrough_r(sparse_c())))
print("pt_c(sparse_r) = %s" % check(sparse_passthrough_c(sparse_r())))
def check_got_vs_ref(got_x, ref_x):
return 'OK' if np.array_equal(got_x, ref_x) else 'NOT OK'
counting_mat = np.arange(9.0, dtype=np.float32).reshape((3, 3))
first_row = counting_mat[0, :]
first_col = counting_mat[:, 0]
print("double_row(first_row) = %s" % check_got_vs_ref(double_row(first_row), 2.0 * first_row))
print("double_col(first_row) = %s" % check_got_vs_ref(double_col(first_row), 2.0 * first_row))
print("double_row(first_col) = %s" % check_got_vs_ref(double_row(first_col), 2.0 * first_col))
print("double_col(first_col) = %s" % check_got_vs_ref(double_col(first_col), 2.0 * first_col))
counting_3d = np.arange(27.0, dtype=np.float32).reshape((3, 3, 3))
slices = [counting_3d[0, :, :], counting_3d[:, 0, :], counting_3d[:, :, 0]]
for slice_idx, ref_mat in enumerate(slices):
print("double_mat_cm(%d) = %s" % (slice_idx, check_got_vs_ref(double_mat_cm(ref_mat), 2.0 * ref_mat)))
print("double_mat_rm(%d) = %s" % (slice_idx, check_got_vs_ref(double_mat_rm(ref_mat), 2.0 * ref_mat)))