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#############################################################################
#
# ViSP, open source Visual Servoing Platform software.
# Copyright (C) 2005 - 2025 by Inria. All rights reserved.
#
# This software 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 2 of the License, or
# (at your option) any later version.
# See the file LICENSE.txt at the root directory of this source
# distribution for additional information about the GNU GPL.
#
# For using ViSP with software that can not be combined with the GNU
# GPL, please contact Inria about acquiring a ViSP Professional
# Edition License.
#
# See https://visp.inria.fr for more information.
#
# This software was developed at:
# Inria Rennes - Bretagne Atlantique
# Campus Universitaire de Beaulieu
# 35042 Rennes Cedex
# France
#
# If you have questions regarding the use of this file, please contact
# Inria at visp@inria.fr
#
# This file is provided AS IS with NO WARRANTY OF ANY KIND, INCLUDING THE
# WARRANTY OF DESIGN, MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE.
#
# Description:
# ViSP Python bindings test
#
#############################################################################
import visp
from visp.core import ArrayDouble2D, RotationMatrix, Matrix, HomogeneousMatrix, PoseVector, ColVector, RowVector
import numpy as np
import pytest
def test_np_array_modifies_vp_array():
# Test that numpy is a view of array and that writing to numpy array modifies vpArray
array = ArrayDouble2D(5, 5, 1.0)
assert array.getRows() == array.getCols() == 5
array_np = np.array(array, copy=False)
assert array_np.shape == (5, 5)
assert np.all(array_np == 1.0)
array_np[0:2, 0:2] = 2
assert array.getMinValue() == 1 and array.getMaxValue() == 2
def test_visp_view_of_np_array():
a = np.zeros((5, 5))
with pytest.raises(RuntimeError):
ColVector.view(a)
with pytest.raises(RuntimeError):
RowVector.view(a)
m = Matrix.view(a)
m[0, 0] = 1
assert a[0, 0] == 1
assert m.getRows() == a.shape[0] and m.getCols() == a.shape[1]
a = np.zeros(10)
with pytest.raises(RuntimeError):
Matrix.view(a)
v = ColVector.view(a)
v[0] = 1
assert a[0] == 1
assert v.getRows() == a.shape[0]
a = np.zeros(10)
v = RowVector.view(a)
v[0] = 1
assert a[0] == 1
assert v.getCols() == a.shape[0]
def fn_test_not_writable_2d(R):
R_np = np.array(R, copy=False)
with pytest.raises(ValueError):
R_np[0, 0] = 1
with pytest.raises(ValueError):
R.numpy()[:1] = 0
with pytest.raises(ValueError):
row = R[0]
row[0] = 1
with pytest.raises(ValueError):
sub = R[:2, :2]
sub[0, :] = 1
def test_rotation_matrix_not_writable():
R = RotationMatrix()
fn_test_not_writable_2d(R)
def test_homogeneous_matrix_not_writable():
T = HomogeneousMatrix()
fn_test_not_writable_2d(T)
def test_numpy_constructor():
n_invalid = np.array([1, 2, 3])
with pytest.raises(RuntimeError):
a = ArrayDouble2D(n_invalid)
n_valid = np.array([[1, 2, 3], [4, 5, 6]])
a = ArrayDouble2D(n_valid)
assert np.all(np.equal(a.numpy(), n_valid))
def test_numpy_constructor_interpreted_as_1d_vector():
n_1d = np.array([1, 2, 3])
with pytest.raises(RuntimeError):
a = ArrayDouble2D(n_1d) # R = 0, c = 0
ar = ArrayDouble2D(n_1d, r=len(n_1d))
ac = ArrayDouble2D(n_1d, c=len(n_1d))
def test_numpy_conversion_and_back():
a = ArrayDouble2D(10, 10, 2.0)
a_np = a.numpy().copy()
a2 = ArrayDouble2D(a_np)
mat = Matrix(a_np)
for i in range(a.getRows()):
for j in range(a.getCols()):
assert a[i, j] == a_np[i, j]
assert a[i, j] == a2[i, j]
assert mat[i, j] == a[i, j]
def test_indexing_array2D():
a_np = np.asarray([[i for _ in range(10)] for i in range(10)])
a = ArrayDouble2D(a_np)
col = list(range(10))
for i in range(a.getRows()):
assert np.all(a[i] == float(i))
assert np.all(a[-i - 1] == float(a.getRows() - i - 1))
assert np.all(a[:, i] == col)
assert np.all(a[:, -i - 1] == col)
def test_index_row_not_copy():
a = ArrayDouble2D(5, 5, 1.0)
first_row_view = a[0]
first_row_view[0] = 0.0
assert a[0, 0] == 0.0
def test_index_slice_not_copy():
a = ArrayDouble2D(5, 5, 1.0)
sub_matrix = a[1:3]
sub_matrix[0] = 0.0
for i in range(a.getCols()):
assert a[1, i] == 0.0
def test_index_tuple_not_copy():
a = ArrayDouble2D(5, 5, 1.0)
col = a[:, -1]
col[0] = 0.0
assert a[0, -1] == 0.0
sub = a[0:2, 0:2]
sub[:, :] = 0.0
for i in range(2):
for j in range(2):
assert a[i, j] == 0.0
def test_setitem_2D_array():
h,w = 50, 50
a = ArrayDouble2D(h, w, 5)
# 2D indexing (basic)
a[0, 0] = 5
assert a[0, 0] == 5
a[0, 0] = 20
assert a[0, 0] == 20
# Replace a row
a[1] = 20
for i in range(a.getCols()):
assert a[1, i] == 20
# Replace a row
a[:] = 20
for i in range(a.getRows()):
for j in range(a.getCols()):
assert a[i, j] == 20
# Replace rows with a slice
a[:] = 5
a[::2] = 20
for i in range(a.getRows()):
v = 5 if i % 2 == 1 else 20
for j in range(a.getCols()):
assert a[i, j] == v
a[:] = 5
a[2:-2:2] = 20
for i in range(a.getRows()):
v = 5 if i % 2 == 1 or i >= a.getRows() - 2 or i < 2 else 20
for j in range(a.getCols()):
assert a[i, j] == v
a[:, :] = 5
for i in range(a.getRows()):
for j in range(a.getCols()):
assert a[i, j] == 5
# Indexing with two slices
a[2:-2:2, 3:-3] = 20
for i in range(a.getRows()):
is_v = i >= 2 and i % 2 == 0 and i < a.getRows() - 2
for j in range(a.getCols()):
is_vj = is_v and j >= 3 and j < a.getCols() - 3
v = 20 if is_vj else 5
assert a[i, j] == v
# Negative step not supported
with pytest.raises(RuntimeError):
a[::-1] = 20
with pytest.raises(RuntimeError):
a[:, ::-1] = 20
# Wrong start and end values
with pytest.raises(RuntimeError):
a[2:1] = 20
with pytest.raises(RuntimeError):
a[:, 3:2] = 20
a = ArrayDouble2D(h, w, 0.0)
single_row = np.ones((w, ), dtype=np.double) * 20
a[2] = single_row
assert not np.any(np.equal(a.numpy()[list(set(range(h)) - {2})], single_row))
assert np.all(np.equal(a.numpy()[2], single_row))
a[:] = 0
a[1:-2] = single_row
assert np.all(np.equal(a.numpy()[list(set(range(h)) - {0, h - 2, h - 1})], single_row))
assert np.all(np.equal(a.numpy()[[0, h - 2, h - 1]], 0))
multi_rows = np.asarray([[i * w + j for j in range(w)] for i in range(h - 5)])
a[:-5] = multi_rows
assert np.all(np.equal(a.numpy()[:-5], multi_rows))
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