smqtk.algorithms.SmqtkAlgorithm
Here we list and briefly describe the high level algorithm interfaces which SMQTK provides. There is at least one implementation available for each interface. Some implementations will require additional dependencies that cannot be packaged with SMQTK.
This interface represents algorithms that classify DescriptorElement instances into discrete labels or label confidences.
smqtk.algorithms.classifier.Classifier
smqtk.algorithms.classifier.get_classifier_impls
This interface represents algorithms that generate whole-content descriptor vectors for a single given input DataElement instance. The input DataElement must be of a content type that the DescriptorGenerator supports, referenced against the DescriptorGenerator.valid_content_types method.
The compute_descriptor method also requires a DescriptorElementFactory instance to tell the algorithm how to generate the DescriptorElement it should return. The returned DescriptorElement instance will have a type equal to the name of the DescriptorGenerator class that generated it, and a UUID that is the same as the input DataElement instance.
If a DescriptorElement implementation that supports persistant storage is generated, and there is already a descriptor associated with the given type name and UUID values, the descriptor is returned without re-computation.
If the overwrite parameter is True, the DescriptorGenerator instance will re-compute a descriptor for the input DataElement, setting it to the generated DescriptorElement. This will overwrite descriptor data in persistant storage if the DescriptorElement type used supports it.
This interface supports a high-level, implementation agnostic asynchronous descriptor computation method. This is given an iterable of DataElement instances, a single DescriptorElementFactory that is used to produce all descriptor
smqtk.algorithms.descriptor_generator.DescriptorGenerator
smqtk.algorithms.descriptor_generator.get_descriptor_generator_impls
This interface describes specialized NearestNeighborsIndex implementations designed to index hash codes (bit vectors) via the hamming distance function. Implementations of this interface are primarily used with the LSHNearestNeighborIndex implementation.
Unlike the NearestNeighborsIndex interface from which this interface descends, HashIndex instances are build with an iterable of numpy.ndarray and nn returns a numpy.ndarray.
smqtk.algorithms.nn_index.hash_index.HashIndex
smqtk.algorithms.nn_index.hash_index.get_hash_index_impls
Implementations of this interface define the generation of a locality-sensitive hash code for a given DescriptorElement. These are used in LSHNearestNeighborIndex instances.
smqtk.algorithms.nn_index.lsh.functors.LshFunctor
smqtk.algorithms.nn_index.lsh.functors.get_lsh_functor_impls
This interface defines a method to build an index from a set of DescriptorElement instances (NearestNeighborsIndex.build_index) and a nearest-neighbors query function for getting a number of near neighbors to e query DescriptorElement (NearestNeighborsIndex.nn).
Building an index requires that some non-zero number of DescriptorElement instances be passed into the build_index method. Subsequent calls to this method should rebuild the index model, not add to it. If an implementation supports persistant storage of the index, it should overwrite the configured index.
The nn method uses a single DescriptorElement to query the current index for a specified number of nearest neighbors. Thus, the NearestNeighborsIndex instance must have a non-empty index loaded for this method to function. If the provided query DescriptorElement does not have a set vector, this method will also fail with an exception.
This interface additionally requires that implementations define a count method, which returns the number of distinct DescriptorElement instances are in the index.
smqtk.algorithms.nn_index.NearestNeighborsIndex
smqtk.algorithms.nn_index.get_nn_index_impls
This interface defines two methods: build_index and rank. The build_index method is, like a NearestNeighborsIndex, used to build an index of DescriptorElement instances. The rank method takes examples of relevant and not-relevant DescriptorElement examples with which the algorithm uses to rank (think sort) the indexed DescriptorElement instances by relevancy (on a [0, 1] scale).
smqtk.algorithms.relevancy_index.RelevancyIndex
smqtk.algorithms.relevancy_index.get_relevancy_index_impls