#############################################################################
#
# 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
#
#############################################################################

from pytest import approx
from visp.core import Math, ImagePoint, ColVector, ThetaUVector, Point
def test_tuple_return_basic_values_only_output():
  '''
  Test that a function that was with signature
  double lineFitting(const std::vector<...>& imPts, double& a, double& b, double& c)
  is now (with custom configuration) with a signature lineFitting(imPts) -> tuple[double * 4]

  all the reference parameters are used as outputs but not as inputs

  '''
  a = 45.0
  b = 52.0
  points = [
    ImagePoint(a*i+b, i) for i in range(3)
  ]
  res =  Math.lineFitting(points)
  print(res)
  values = (res[0], -res[1] / res[2], res[3] / res[2])
  expected = (0, a, b)
  for i, (val, exp) in enumerate(zip(values, expected)):
    print(i)
    assert val == approx(exp, 0.0001)

def test_tuple_return_basic_values_only_output_2():
  theta = 3.14
  vec = [0.0, 0.0, 1.0]
  thetau = ThetaUVector(*[v * theta for v in vec])
  theta_out, vec_out = thetau.extract()
  assert theta_out == theta
  assert vec_out == ColVector(vec)

def test_pass_by_ref():
  values = [0, 1, 2]
  p = Point(values)
  vec_ref = ColVector()
  p.getWorldCoordinates(vec_ref)
  assert vec_ref == p.getWorldCoordinates()

def test_tuple_return_basic_values_mixed():
  pass