Test failures

[opoplawski]

Describe the bug
The Fedora pyswarms package is failing tests

==================================== ERRORS ====================================
_ ERROR at setup of TestGeneralOptimizer.test_train_history[optimizer_history0-cost_history-expected_shape0] _

self = <tests.optimizers.test_general_optimizer.TestGeneralOptimizer object at 0x7fbc9210e510>
request = <SubRequest 'optimizer_history' for <Function test_train_history[optimizer_history0-cost_history-expected_shape0]>>
options = {'c1': 0.3, 'c2': 0.7, 'k': 2, 'p': 2, ...}

    @pytest.fixture(params=topologies)
    def optimizer_history(self, request, options):
        opt = GeneralOptimizerPSO(
            n_particles=10,
            dimensions=2,
            options=options,
            topology=request.param,
        )
>       opt.optimize(sphere, 1000)

tests/optimizers/test_general_optimizer.py:51: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
pyswarms/single/general_optimizer.py:252: in optimize
    self.swarm.best_pos, self.swarm.best_cost = self.top.compute_gbest(
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

self = <pyswarms.backend.topology.pyramid.Pyramid object at 0x7fbc9230ba90>
swarm = Swarm(position=array([[0.99029359, 0.76531587],
       [0.6685371 , 0.85310907],
       [0.36142089, 0.14341208],
    ...6, 1.17473693, 0.15119209, 0.54211531, 0.53914621,
       0.4226627 , 1.00655433, 0.39733392, 1.45670983, 0.97363041]))
kwargs = {'c1': 0.3, 'c2': 0.7, 'k': 2, 'p': 2, ...}
pyramid = <scipy.spatial._qhull.Delaunay object at 0x7fbc91f3d350>

    def compute_gbest(self, swarm, **kwargs):
        """Update the global best using a pyramid neighborhood approach
    
        This topology uses the :code:`Delaunay` class from :code:`scipy`. To
        prevent precision errors in the Delaunay class, custom
        :code:`qhull_options` were added. Namely, :code:`QJ0.001 Qbb Qc Qx`.
        The meaning of those options is explained in [qhull]. This method is
        used to triangulate N-dimensional space into simplices. The vertices of
        the simplicies consist of swarm particles. This method is adapted from
        the work of Lane et al.[SIS2008]
    
        [SIS2008] J. Lane, A. Engelbrecht and J. Gain, "Particle swarm optimization with spatially
        meaningful neighbours," 2008 IEEE Swarm Intelligence Symposium, St. Louis, MO, 2008,
        pp. 1-8. doi: 10.1109/SIS.2008.4668281
        [qhull] http://www.qhull.org/html/qh-optq.htm
    
        Parameters
        ----------
        swarm : pyswarms.backend.swarms.Swarm
            a Swarm instance
    
        Returns
        -------
        numpy.ndarray
            Best position of shape :code:`(n_dimensions, )`
        float
            Best cost
        """
        try:
            # If there are less than (swarm.dimensions + 1) particles they are all connected
            if swarm.n_particles < swarm.dimensions + 1:
                self.neighbor_idx = np.tile(
                    np.arange(swarm.n_particles), (swarm.n_particles, 1)
                )
                best_pos = swarm.pbest_pos[np.argmin(swarm.pbest_cost)]
                best_cost = np.min(swarm.pbest_cost)
            else:
                # Check if the topology is static or dynamic and assign neighbors
                if (
                    self.static and self.neighbor_idx is None
                ) or not self.static:
                    pyramid = Delaunay(
                        swarm.position, qhull_options="QJ0.001 Qbb Qc Qx"
                    )
                    indices, index_pointer = pyramid.vertex_neighbor_vertices
                    # Insert all the neighbors for each particle in the idx array
>                   self.neighbor_idx = np.array(
                        [
                            index_pointer[indices[i] : indices[i + 1]]
                            for i in range(swarm.n_particles)
                        ]
                    )
E                   ValueError: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (10,) + inhomogeneous part.

pyswarms/backend/topology/pyramid.py:81: ValueError
---------------------------- Captured stderr setup -----------------------------
2023-06-25 10:55:09,612 - pyswarms.single.general_optimizer - INFO - Optimize for 1000 iters with {'c1': 0.3, 'c2': 0.7, 'w': 0.9, 'k': 2, 'p': 2, 'r': 1}
pyswarms.single.general_optimizer:   0%|          |0/1000

Most errors seem to be identical to this. Full log:
build.log.gz

=========================== short test summary info ============================
FAILED tests/backend/topology/test_pyramid.py::TestPyramidTopology::test_neighbor_idx[True]
FAILED tests/backend/topology/test_pyramid.py::TestPyramidTopology::test_neighbor_idx[False]
FAILED tests/backend/topology/test_pyramid.py::TestPyramidTopology::test_compute_gbest_return_values[True]
FAILED tests/backend/topology/test_pyramid.py::TestPyramidTopology::test_compute_gbest_return_values[False]
FAILED tests/backend/topology/test_random.py::TestRandomTopology::test_neighbor_idx[1-True]
FAILED tests/backend/topology/test_random.py::TestRandomTopology::test_neighbor_idx[1-False]
FAILED tests/backend/topology/test_random.py::TestRandomTopology::test_neighbor_idx[2-True]
FAILED tests/backend/topology/test_random.py::TestRandomTopology::test_neighbor_idx[2-False]
FAILED tests/backend/topology/test_random.py::TestRandomTopology::test_neighbor_idx[3-True]
FAILED tests/backend/topology/test_random.py::TestRandomTopology::test_neighbor_idx[3-False]
FAILED tests/backend/topology/test_random.py::TestRandomTopology::test_compute_gbest_return_values[1-1-True]
FAILED tests/backend/topology/test_random.py::TestRandomTopology::test_compute_gbest_return_values[1-1-False]
FAILED tests/backend/topology/test_random.py::TestRandomTopology::test_compute_gbest_return_values[1-2-True]
FAILED tests/backend/topology/test_random.py::TestRandomTopology::test_compute_gbest_return_values[1-2-False]
FAILED tests/backend/topology/test_random.py::TestRandomTopology::test_compute_gbest_return_values[2-1-True]
FAILED tests/backend/topology/test_random.py::TestRandomTopology::test_compute_gbest_return_values[2-1-False]
FAILED tests/backend/topology/test_random.py::TestRandomTopology::test_compute_gbest_return_values[2-2-True]
FAILED tests/backend/topology/test_random.py::TestRandomTopology::test_compute_gbest_return_values[2-2-False]
FAILED tests/backend/topology/test_random.py::TestRandomTopology::test_compute_gbest_return_values[3-1-True]
FAILED tests/backend/topology/test_random.py::TestRandomTopology::test_compute_gbest_return_values[3-1-False]
FAILED tests/backend/topology/test_random.py::TestRandomTopology::test_compute_gbest_return_values[3-2-True]
FAILED tests/backend/topology/test_random.py::TestRandomTopology::test_compute_gbest_return_values[3-2-False]
FAILED tests/optimizers/test_general_optimizer.py::TestGeneralOptimizer::test_ftol_effect[optimizer0]
FAILED tests/optimizers/test_general_optimizer.py::TestGeneralOptimizer::test_ftol_effect[optimizer1]
FAILED tests/optimizers/test_general_optimizer.py::TestGeneralOptimizer::test_parallel_evaluation[optimizer0]
FAILED tests/optimizers/test_general_optimizer.py::TestGeneralOptimizer::test_parallel_evaluation[optimizer1]
FAILED tests/optimizers/test_general_optimizer.py::TestGeneralOptimizer::test_general_correct_pos[optimizer0]
FAILED tests/optimizers/test_general_optimizer.py::TestGeneralOptimizer::test_general_correct_pos[optimizer1]
FAILED tests/optimizers/test_general_optimizer.py::TestGeneralOptimizer::test_ftol_iter_effect[optimizer0]
FAILED tests/optimizers/test_general_optimizer.py::TestGeneralOptimizer::test_ftol_iter_effect[optimizer1]
ERROR tests/optimizers/test_general_optimizer.py::TestGeneralOptimizer::test_train_history[optimizer_history0-cost_history-expected_shape0]
ERROR tests/optimizers/test_general_optimizer.py::TestGeneralOptimizer::test_train_history[optimizer_history0-mean_pbest_history-expected_shape1]
ERROR tests/optimizers/test_general_optimizer.py::TestGeneralOptimizer::test_train_history[optimizer_history0-mean_neighbor_history-expected_shape2]
ERROR tests/optimizers/test_general_optimizer.py::TestGeneralOptimizer::test_train_history[optimizer_history0-pos_history-expected_shape3]
ERROR tests/optimizers/test_general_optimizer.py::TestGeneralOptimizer::test_train_history[optimizer_history0-velocity_history-expected_shape4]
ERROR tests/optimizers/test_general_optimizer.py::TestGeneralOptimizer::test_train_history[optimizer_history1-cost_history-expected_shape0]
ERROR tests/optimizers/test_general_optimizer.py::TestGeneralOptimizer::test_train_history[optimizer_history1-mean_pbest_history-expected_shape1]
ERROR tests/optimizers/test_general_optimizer.py::TestGeneralOptimizer::test_train_history[optimizer_history1-mean_neighbor_history-expected_shape2]
ERROR tests/optimizers/test_general_optimizer.py::TestGeneralOptimizer::test_train_history[optimizer_history1-pos_history-expected_shape3]
ERROR tests/optimizers/test_general_optimizer.py::TestGeneralOptimizer::test_train_history[optimizer_history1-velocity_history-expected_shape4]
ERROR tests/optimizers/test_general_optimizer.py::TestGeneralOptimizer::test_reset_default_values[optimizer_reset0]
ERROR tests/optimizers/test_general_optimizer.py::TestGeneralOptimizer::test_reset_default_values[optimizer_reset1]
====== 30 failed, 414 passed, 12 skipped, 2 warnings, 12 errors in 33.26s ======
Exception ignored in: <function Pool.__del__ at 0x7fbc91580680>
Traceback (most recent call last):
  File "/usr/lib64/python3.11/multiprocessing/pool.py", line 271, in __del__
    self._change_notifier.put(None)
  File "/usr/lib64/python3.11/multiprocessing/queues.py", line 377, in put
    self._writer.send_bytes(obj)
  File "/usr/lib64/python3.11/multiprocessing/connection.py", line 199, in send_bytes
    self._send_bytes(m[offset:offset + size])
  File "/usr/lib64/python3.11/multiprocessing/connection.py", line 410, in _send_bytes
    self._send(header + buf)
  File "/usr/lib64/python3.11/multiprocessing/connection.py", line 367, in _send
    n = write(self._handle, buf)
        ^^^^^^^^^^^^^^^^^^^^^^^^
OSError: [Errno 9] Bad file descriptor

To Reproduce

+ /usr/bin/pytest
============================= test session starts ==============================
platform linux -- Python 3.11.4, pytest-7.3.2, pluggy-1.0.0
rootdir: /builddir/build/BUILD/pyswarms-1.3.0
collected 468 items

Environment (please complete the following information):

• OS: Fedora rawhide
• PySwarms Version 1.3.0
• Python Version 3.11.4