Data Sampler (Implementation) [0%]#
- class KDTreeKNNDataSampler(*args: 'Any', **kwargs: 'Any')[source]#
Bases:
ResultDataSampler
- query(self, queries, size) data_points [source]#
- DescriptionReturns a tuple of
size
queries andsize
results in the area of the requested queries.- Parameters:
queries (NDArray) – A list of queries
size (Number) – The preferred sample size
- Returns:
A tuple of queries and their associated results
- Return type:
Tuple[NDArray,`NDArray <https://numpy.org/doc/stable/reference/arrays.ndarray.html>`_]
- query_constrain(self) QueryConstrain [source]#
- DescriptionReturns the
QueryConstrain
of the object.Not implemented here.
- result_constrain(self) ResultConstrain [source]#
- DescriptionReturns the
ResultConstrain
of the object.Not implemented here.
- result_update(self, subscription) None [source]#
- DescriptionTries to update the given
subscription
.- Parameters:
subscription (Subscribable) – The subscription to be updated
- sample_size_data_fraction: int = 6#
- sample_size_max: int = 80#
- sample_size_min: int = 5#
- class KDTreeRegionDataSampler(*args: 'Any', **kwargs: 'Any')[source]#
Bases:
ResultDataSampler
- query(self, queries, size) data_points [source]#
- DescriptionReturns a tuple of
size
queries andsize
results in the area of the requested queries.- Parameters:
queries – A list of queries
size (Number) – The preferred sample size
- Returns:
A tuple of queries and their associated results
- Return type:
Tuple[NDArray,`NDArray <https://numpy.org/doc/stable/reference/arrays.ndarray.html>`_]
- query_constrain(self) QueryConstrain [source]#
- DescriptionReturns the
QueryConstrain
of the object.Not implemented here.
- region_size: float = 0.1#
- result_constrain(self) ResultConstrain [source]#
- DescriptionReturns the
ResultConstrain
of the object.Not implemented here.
- result_update(self, subscription) None [source]#
- DescriptionTries to update the given
subscription
.- Parameters:
subscription (Subscribable) – The subscription to be updated