Support with NumPy 1.24+

[mwtoews]

Tests currently fail with recent NumPy releases. For instance:

pytest tests/test_algorithms.py::TestAlgorithms::test_padds

With current numpy (1.24.4):

self = <test_algorithms.TestAlgorithms testMethod=test_padds>

    def test_padds(self):
        sampler = spotpy.algorithms.padds(
            spot_setup_hymod(self.multi_obj_func),
            parallel=self.parallel,
            dbname="Rosen",
            dbformat=self.dbformat,
            sim_timeout=self.timeout,
        )
>       sampler.sample(int(self.rep * 0.5), metric="ones")

tests/test_algorithms.py:216: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
src/spotpy/algorithms/padds.py:259: in sample
    ) = self.calculate_initial_parameterset(
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

self = padds(), repetitions = 493, initial_objs = array([], dtype=float64), initial_params = array([], dtype=float64)

    def calculate_initial_parameterset(self, repetitions, initial_objs, initial_params):
        self.obj_func_current = np.array([0.0])
        self.parameter_current = np.array([0.0] * self.number_of_parameters)
        self.parameter_range = (
            self.best_value.parameters.maxbound - self.best_value.parameters.minbound
        )
>       self.pareto_front = np.array(
            [[np.array([]), np.array([0] * self.number_of_parameters)]]
        )
E       ValueError: setting an array element with a sequence. The requested array has an inhomogeneous shape after 2 dimensions. The detected shape was (1, 2) + inhomogeneous part.

src/spotpy/algorithms/padds.py:172: ValueError

With previous numpy (1.23.5) the test passes, but shows a VisibleDeprecationWarning:

/path/to/spotpy/src/spotpy/algorithms/padds.py:173: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray.
self.pareto_front = np.array(

where it created array([[array([], dtype=float64), array([0, 0, 0, 0, 0])]], dtype=object)

[lotruheawea]

Another issue is that np.int was deprecated
See

  File "/perm/cyrs/conda/envs/calibrate_ecland/lib/python3.11/site-packages/spotpy/algorithms/dds.py", line 281, in sample
    initial_iterations = np.int(np.max([5, round(0.005 * repetitions)]))
                         ^^^^^^
  File "/perm/cyrs/conda/envs/calibrate_ecland/lib/python3.11/site-packages/numpy/__init__.py", line 324, in __getattr__
    raise AttributeError(__former_attrs__[attr])
AttributeError: module 'numpy' has no attribute 'int'.
`np.int` was a deprecated alias for the builtin `int`. To avoid this error in existing code, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.
The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:
    https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'inf'?