geo3d.pdal.filters
==================

.. py:module:: geo3d.pdal.filters


Attributes
----------

.. autoapisummary::

   geo3d.pdal.filters.FILTER_TYPES


Functions
---------

.. autoapisummary::

   geo3d.pdal.filters.range
   geo3d.pdal.filters.cluster
   geo3d.pdal.filters.assign
   geo3d.pdal.filters.merge
   geo3d.pdal.filters.stats
   geo3d.pdal.filters.expression
   geo3d.pdal.filters.crop
   geo3d.pdal.filters.info
   geo3d.pdal.filters.nndistance
   geo3d.pdal.filters.outlier
   geo3d.pdal.filters.groupby


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

.. py:data:: FILTER_TYPES

.. py:function:: range(limits: str) -> Dict[str, str]

   Create the `filters.range`'s stage.

   :param limits: A list of limits as defined in pdal. 'Z[0:100],Classification[2:2]' for example.
   :type limits: str

   :returns: The Filter's stage dictionary.
   :rtype: Dict


.. py:function:: cluster(min_points: int, tolerance: float) -> Dict[str, str]

   Create the `filters.cluster`'s stage.

   :param min_points: The minimum size of a cluster.
   :type min_points: int
   :param tolerance: The maximum distance to a cluster.
   :type tolerance: float

   :returns: The Filter's stage dictionary.
   :rtype: dict


.. py:function:: assign(value: str) -> Dict[str, str]

   Create `filters.assign`'s stage.

   :param value: A list of assignment expressions. See pdal documentation.
   :type value: str

   .. rubric:: Examples

   value='Dimension = ValueExpression [WHERE ConditionalExpression]'.

   :returns: The Filter's stage dictionary.
   :rtype: dict


.. py:function:: merge() -> Dict

   Create `filters.merge`'s stage.

   :returns: The Filter's stage dictionary.
   :rtype: dict


.. py:function:: stats(dimensions: str, enumerate: Optional[str] = None, count: Optional[str] = None) -> Dict[str, Any]

   Create `filters.stats`'s stage.

   :param dimensions: The dimensions on whose to compute statistics.
   :type dimensions: str
   :param enumerate: The dimensions whose values should be enumerated.
   :type enumerate: str
   :param count: Provide the count of the number of points of each enumerated category.
   :type count: str

   :returns: The Stats' stage dictionary.
   :rtype: dict


.. py:function:: expression(expression: str) -> Dict[str, str]

   Create `filters.expression`'s stage.

   :param expression: An expression that limits points passed to a filter. For example, 'Classification == 3'.
   :type expression: str

   :returns: The Expression' stage dictionary.
   :rtype: dict


.. py:function:: crop(bounds: str) -> Dict[str, str]

   Create `filters.crop`'s stage.

   :param bounds: The bounding box to crop on. It can be in the format '([xmin, xmax], [ymin, ymax])'.
   :type bounds: str

   :returns: The Crop's stage dictionary.
   :rtype: dict


.. py:function:: info() -> Dict

   Create `filters.info`'s stage.

   :returns: the Info's stage dictionary.
   :rtype: dict


.. py:function:: nndistance(mode: str, k: int) -> Dict[str, Any]

   Create `filters.nndistance`'s stage.

   :param mode: The mode of operation.
   :type mode: str
   :param k: The number of nearest neighbors.
   :type k: int

   :returns: the nndistance's stage dictionary.
   :rtype: dict


.. py:function:: outlier(classification: int, method: str, min_k: int, radius: float, mean_k: int, multiplier: float) -> Dict[str, Any]

   Create `filters.outlier`'s stage.

   :param classification: The class value to assign to outliers.
   :type classification: int
   :param method: The outlier removal method. 'statistical' or 'radius'.
   :type method: str
   :param min_k: Minimum number of neighbors in radius. Applicable to radius method only.
   :type min_k: int
   :param radius: The value of radius of the ball of neighbors.
   :type radius: float
   :param mean_k: The number of k nearest neighbors. Applicable to statistical method only.
   :type mean_k: int
   :param multiplier: The multiplier to use in computing the threshold.
   :type multiplier: float

   :returns: the outlier's stage dictionary.
   :rtype: dict


.. py:function:: groupby(dimension: str) -> Dict[str, Any]

   Create `filters.groupby`'s stage.

   :param dimension: The dimension to be used in grouping the data.
   :type dimension: str

   :returns: the Info's stage dictionary.
   :rtype: dict