mindflow.geometry.PartSamplingConfig
- class mindflow.geometry.PartSamplingConfig(size, random_sampling=True, sampler='uniform', random_merge=True, with_normal=False, with_sdf=False)[source]
Definition of partial sampling configuration.
- Parameters
size (Union[int, tuple[int], list[int]]) – number of sampling points.
random_sampling (bool) – Whether randomly sampling points. Default:
True
.sampler (str) – method for random sampling. Default:
"uniform"
.random_merge (bool) – Specifies whether randomly merge coordinates of different dimensions. Default:
True
.with_normal (bool) – Specifies whether generating the normal vectors of the boundary. Default:
False
.with_sdf (bool) – Specifies whether return the sign-distance-function result of the inner domain points. Default:
False
.
- Raises
TypeError – size is not int number when random sampling.
- Supported Platforms:
Ascend
GPU
Examples
>>> from mindflow.geometry import PartSamplingConfig >>> partsampling = PartSamplingConfig(100, True, "uniform", True, True)