mindscience.data.HyperCube

class mindscience.data.HyperCube(name, dim, coord_min, coord_max, dtype=numpy.float32, sampling_config=None)[source]

Definition of HyperCube object.

Parameters

  • name (str) – Name of the hyper cube.

  • dim (int) – Number of dimensions.

  • coord_min (Union[int, float, tuple, list, numpy.ndarray]) – Minimal coordinate of the hyper cube. If the parameter type is tuple or list, each element should be of type int or float, and its length must be consistent with the dim parameter.

  • coord_max (Union[int, float, tuple, list, numpy.ndarray]) – Maximal coordinate of the hyper cube. If the parameter type is tuple or list, each element should be of type int or float, and its length must be consistent with the dim parameter.

  • dtype (numpy.dtype) – Data type of sampled point data type. Default: numpy.float32.

  • sampling_config (SamplingConfig) – Sampling configuration. Default: None.

Raises

TypeError – sampling_config is not instance of class SamplingConfig.

Examples

>>> from mindscience.data import generate_sampling_config, HyperCube
>>> hypercube_random = dict({
...      'domain': dict({
...          'random_sampling': True,
...          'size': 1000,
...          'sampler': 'uniform'
...         }),
...      'BC': dict({
...          'random_sampling': True,
...          'size': 200,
...          'sampler': 'uniform',
...          'with_normal': False,
...      }),
...  })
>>> sampling_config = generate_sampling_config(hypercube_random)
>>> hypercube = HyperCube("HyperCube", 3, [-1, 2, 1], [0, 3, 2], sampling_config=sampling_config)
>>> domain = hypercube.sampling(geom_type="domain")
>>> bc = hypercube.sampling(geom_type="BC")
>>> print(domain.shape)
(1000, 3)
sampling(geom_type='domain')[source]

Sampling points.

Parameters

geom_type (str) –

Geometry type: can be 'domain' or 'BC'. Default: 'domain'.

  • 'domain', feasible domain of the problem.

  • 'BC', boundary of the problem.

Returns

Numpy.ndarray, if the with_normal property of boundary configuration is true, returns 2D numpy array with

boundary normal vectors. Otherwise, returns 2D numpy array without boundary normal vectors.

Raises

  • KeyError – If geom_type is 'domain' but self.sampling_config.domain is None.

  • KeyError – If geom_type is 'BC' but self.sampling_config.bc is None.

  • ValueError – If geom_type is neither 'BC' nor 'domain'.