.. ****************************************************************************** .. * Copyright 2019 Intel Corporation .. * .. * Licensed under the Apache License, Version 2.0 (the "License"); .. * you may not use this file except in compliance with the License. .. * You may obtain a copy of the License at .. * .. * http://www.apache.org/licenses/LICENSE-2.0 .. * .. * Unless required by applicable law or agreed to in writing, software .. * distributed under the License is distributed on an "AS IS" BASIS, .. * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. .. * See the License for the specific language governing permissions and .. * limitations under the License. .. *******************************************************************************/ Essential Interfaces for Algorithms =================================== In addition to Generic Interfaces, more methods enable interfacing numeric tables with algorithms. The getDataLayout method provides information about the data layout: +-----------------------------------+-----------------------------------+ | Data Layout | Description | +===================================+===================================+ | soa | Structure-Of-Arrays (SOA). Values | | | of individual data features are | | | stored in contiguous memory | | | blocks. | +-----------------------------------+-----------------------------------+ | aos | Array-Of-Structures (AOS). | | | Feature vectors are stored in | | | contiguous memory block. | +-----------------------------------+-----------------------------------+ | csr_Array | Condensed-Sparse-Row (CSR). | +-----------------------------------+-----------------------------------+ | lowerPackedSymetricMatrix | Lower packed symmetric matrix | +-----------------------------------+-----------------------------------+ | lowerPackedTriangularMatrix | Lower packed triangular matrix | +-----------------------------------+-----------------------------------+ | upperPackedSymetricMatrix | Upper packed symmetric matrix | +-----------------------------------+-----------------------------------+ | upperPackedTriangularMatrix | Upper packed triangular matrix | +-----------------------------------+-----------------------------------+ | unknown | No information about data layout | | | or unsupported layout. | +-----------------------------------+-----------------------------------+ Rather than access the entire in-memory data set, it is often more efficient to process it by blocks. The key methods that |product| algorithms use for per-block data access are ``getBlockOfRows()`` and ``getBlockOfColumnValues()``. The ``getBlockOfRows()`` method accesses a block of feature vectors, while the ``getBlockOfColumnValues()`` method accesses a block of values for a given feature. A particular algorithm uses ``getBlockOfRows()``, ``getBlockOfColumnValues()``, or both methods to access the data. The efficiency of data access highly depends on the data layout and on whether the data type of the feature is natively supported by the algorithm without type conversions. Refer to the Performance Considerations section in the description of a particular algorithm for a discussion of the optimal data layout and natively supported data types. When the data layout fits the per-block data access pattern and the algorithm requests the data type that corresponds to the actual data type, the ``getBlockOfRows()`` and ``getBlockOfColumnValues()`` methods avoid data copying and type conversion. However, when the layout does not fit the data access pattern or when type conversion is required, both methods automatically re-pack and convert data as required. When dealing with custom or unsupported data layouts, you must implement NumericTableIface, DenseNumericTableIface interfaces, and optionally CSRNumericTableIface or PackedNumericTableIface interfaces. Some algorithms, such as Moments of Low Order, compute basic statistics (minimums, maximums, and so on). The other algorithms, such as Correlation and Variance-Covariance Matrices or Principal Component Analysis, require some basic statistics on input. To avoid duplicated computation of basic statistics, |product| provides methods to store and retrieve basic statistics associated with a given numeric table: ``basicStatistics.set()`` and ``basicStatistics.get()``. The following basic statistics are computed for each numeric table: - minimum - minimum - maximum - maximum - sum - sum - sumSquares - sum of squares .. note:: The default data type of basic statistics is float. **Special Interfaces for the HomogenNumericTable and Matrix Classes** - Use the assign method to initialize elements of a dense homogeneous numeric table with a certain value, that is, to set all elements of the matrix to zero. - Use the operator [] method to access rows of a homogeneous dense numeric table. **Special Interfaces for the PackedTriangularMatrix and PackedSymmetricMatrix Classes** - While you can use generic ``getArray()`` and ``setArray()`` methods to access the data in a packed format, in algorithms that have specific implementations for a packed data layout, you can use more specific ``getPackedValues()`` and ``releasePackedValues()`` methods. **Special Interfaces for the CSRNumericTable Class** - To access three CSR arrays (values , columns, and rowIndex), use ``getArrays()`` and ``setArrays()`` methods instead of generic ``getArray()`` and ``setArray()`` methods. For details of the arrays, see CSR data layout. - Similarly, in algorithms that have specific implementations for the CSR data layout, you can use more specific ``getBlockOfCSRValues()`` and ``releaseBlockOfCSRValues()`` methods. **Special Interfaces for the MergedNumericTable Class** - To add a new array to the object of the MergedNumericTable class, use the ``addNumericTable()`` method.