:py:mod:`synthpic2.recipe.synth_chain.feature_generation_steps.agglomeration.utilities`
=======================================================================================

.. py:module:: synthpic2.recipe.synth_chain.feature_generation_steps.agglomeration.utilities

.. autoapi-nested-parse::

   Module for agglomeration utilities.



Module Contents
---------------


Functions
~~~~~~~~~

.. autoapisummary::

   synthpic2.recipe.synth_chain.feature_generation_steps.agglomeration.utilities.validate_3d_vector
   synthpic2.recipe.synth_chain.feature_generation_steps.agglomeration.utilities.sample_random_mass_points_in_mesh
   synthpic2.recipe.synth_chain.feature_generation_steps.agglomeration.utilities.normalize_vector
   synthpic2.recipe.synth_chain.feature_generation_steps.agglomeration.utilities.get_random_direction
   synthpic2.recipe.synth_chain.feature_generation_steps.agglomeration.utilities.flatten_list



.. py:function:: validate_3d_vector(vector: numpy.ndarray | list | tuple) -> numpy.ndarray

   Validate 3d vector.

   Args:
       vector (np.ndarray | list | tuple): vector in different data types

   Raises:
       ValueError: If vector has not exactly 3 elements.

   Returns:
       np.ndarray: vector as numpy array


.. py:function:: sample_random_mass_points_in_mesh(mesh: trimesh.Trimesh, count: int) -> tuple[numpy.ndarray, numpy.ndarray]

   Sample random points inside of a mesh. The specified `count` is not matched
       exactly.

   Args:
       mesh (trimesh.Trimesh): Mesh to sample from.
       count (int): Approximate number of points

   Returns:
       tuple[np.ndarray, np.ndarray]: Number of points and associated weights.


.. py:function:: normalize_vector(vector: numpy.ndarray) -> numpy.ndarray


.. py:function:: get_random_direction() -> numpy.ndarray


.. py:function:: flatten_list(l: list[list]) -> list