1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
|
### pyhegp --- Homomorphic encryption of genotypes and phenotypes
### Copyright © 2026 Arun Isaac <arunisaac@systemreboot.net>
###
### This file is part of pyhegp.
###
### pyhegp is free software: you can redistribute it and/or modify it
### under the terms of the GNU General Public License as published by
### the Free Software Foundation, either version 3 of the License, or
### (at your option) any later version.
###
### pyhegp is distributed in the hope that it will be useful, but
### WITHOUT ANY WARRANTY; without even the implied warranty of
### MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
### General Public License for more details.
###
### You should have received a copy of the GNU General Public License
### along with pyhegp. If not, see <https://www.gnu.org/licenses/>.
from hypothesis import given, strategies as st
from hypothesis.extra.numpy import arrays
import numpy as np
from pytest import approx
from pyhegp.linalg import BlockDiagonalMatrix
@st.composite
def block_diagonal_matrices(draw, max_block_size=10, max_number_of_blocks=None):
return BlockDiagonalMatrix(
[draw(arrays("float64", (n, n),
elements=st.floats(min_value=-10,
max_value=10,
allow_nan=False,
allow_infinity=False)))
for n in draw(st.lists(st.integers(min_value=1,
max_value=max_block_size),
min_size=1,
max_size=max_number_of_blocks))])
@given(block_diagonal_matrices(max_number_of_blocks=10))
def test_block_diagonal_matrix_transpose(block_diagonal_matrix):
assert (np.transpose(block_diagonal_matrix).__array__()
== approx(np.transpose(block_diagonal_matrix.__array__())))
@st.composite
def block_diagonal_matrix_product_multiplicands(draw):
block_diagonal_matrix = draw(block_diagonal_matrices())
return (block_diagonal_matrix,
draw(arrays("float64",
# Either a vector or a matrix
(len(block_diagonal_matrix),
*draw(st.one_of(
st.just(()),
st.builds(lambda x: (x,),
st.integers(min_value=1,
max_value=100))))),
elements=st.floats(min_value=-10,
max_value=10,
allow_nan=False,
allow_infinity=False))))
@given(block_diagonal_matrix_product_multiplicands())
def test_block_diagonal_matrix_product(multiplicands):
block_diagonal_matrix, multiplier = multiplicands
assert ((block_diagonal_matrix @ multiplier)
== approx(block_diagonal_matrix.__array__() @ multiplier))
|
