.. ****************************************************************************** .. * Copyright 2020-2021 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. .. *******************************************************************************/ Pivoted QR Decomposition ======================== Given the matrix :math:`X` of size :math:`n \times p`, the problem is to compute the QR decomposition with column pivoting :math:`XP = QR`, where - :math:`Q` is an orthogonal matrix of size :math:`n \times n` - :math:`R` is a rectangular upper triangular matrix of size :math:`n \times p` - :math:`P` is a permutation matrix of size :math:`n \times n` The library requires :math:`n > p`. In this case: .. math:: XP = QR = [Q_1, Q_2] \cdot \begin{bmatrix} R_1 \\ 0 \end{bmatrix} = Q_1 R_1 where the matrix :math:`Q_1` has the size :math:`n \times p` and :math:`R_1` has the size :math:`p \times p`. Batch Processing **************** Algorithm Input --------------- Pivoted QR decomposition accepts the input described below. Pass the ``Input ID`` as a parameter to the methods that provide input for your algorithm. For more details, see :ref:`algorithms`. .. tabularcolumns:: |\Y{0.2}|\Y{0.8}| .. list-table:: Algorithm Input for Pivoted QR Decomposition (Batch Processing) :widths: 10 60 :header-rows: 1 * - Input ID - Input * - ``data`` - Pointer to the numeric table that represents the :math:`n \times p` matrix :math:`X` to be factorized. The input can be an object of any class derived from ``NumericTable``. Algorithm Parameters -------------------- Pivoted QR decomposition has the following parameters: .. tabularcolumns:: |\Y{0.15}|\Y{0.15}|\Y{0.7}| .. list-table:: Algorithm Parameters for Pivoted QR Decomposition (Batch Processing) :header-rows: 1 :widths: 10 10 60 :align: left :class: longtable * - Parameter - Default Value - Description * - ``algorithmFPType`` - ``float`` - The floating-point type that the algorithm uses for intermediate computations. Can be ``float`` or ``double``. * - ``method`` - ``defaultDense`` - Performance-oriented computation method, the only method supported by the algorithm. * - ``permutedColumns`` - Not applicable - Pointer to the numeric table with the :math:`1 \times p` matrix with the information for the permutation: - If the :math:`i`-th element is zero, the :math:`i`-th column of the input matrix is a free column and may be permuted with any other free column during the computation. - If the :math:`i`-th element is non-zero, the :math:`i`-th column of the input matrix is moved to the beginning of XP before the computation and remains in its place during the computation. .. note:: By default, this parameter is an object of the ``HomogenNumericTable`` class, filled by zeros. However, you can define this parameter as an object of any class derived from ``NumericTable`` except the ``PackedSymmetricMatrix`` class, ``CSRNumericTable`` class, and ``PackedTriangularMatrix`` class with the ``lowerPackedTriangularMatrix`` layout. Algorithm Output ---------------- Pivoted QR decomposition calculates the results described below. Pass the ``Result ID`` as a parameter to the methods that access the results of your algorithm. For more details, see :ref:`algorithms`. .. tabularcolumns:: |\Y{0.2}|\Y{0.8}| .. list-table:: Algorithm Output for Pivoted QR Decomposition (Batch Processing) :widths: 10 60 :header-rows: 1 :class: longtable * - Result ID - Result * - ``matrixQ`` - Pointer to the numeric table with the :math:`n \times p` matrix :math:`Q_1`. .. note:: By default, this result is an object of the ``HomogenNumericTable`` class, but you can define the result as an object of any class derived from ``NumericTable`` except ``PackedSymmetricMatrix``, ``PackedTriangularMatrix``, and ``CSRNumericTable``. * - ``matrixR`` - Pointer to the numeric table with the :math:`p \times p` upper triangular matrix :math:`R_1`. .. note:: By default, this result is an object of the ``HomogenNumericTable`` class, but you can define the result as an object of any class derived from ``NumericTable`` except the ``PackedSymmetricMatrix`` class, ``CSRNumericTable`` class, and ``PackedTriangularMatrix`` class with the ``lowerPackedTriangularMatrix`` layout. * - ``permutationMatrix`` - Pointer to the numeric table with the :math:`1 \times p` matrix such that :math:`\text{permutationMatrix}(i) = k` if the column :math:`k` of the full matrix :math:`X` is permuted into the position :math:`i` in :math:`XP`. .. note:: By default, this result is an object of the ``HomogenNumericTable`` class, but you can define the result as an object of any class derived from ``NumericTable`` except the ``PackedSymmetricMatrix`` class, ``CSRNumericTable`` class, and ``PackedTriangularMatrix`` class with the ``lowerPackedTriangularMatrix`` layout. Examples ******** .. tabs:: .. tab:: C++ (CPU) Batch Processing: - :cpp_example:`pivoted_qr_dense_batch.cpp ` .. tab:: Java* .. note:: There is no support for Java on GPU. Batch Processing: - :java_example:`PivotedQRDenseBatch.java ` .. tab:: Python* Batch Processing: - :daal4py_example:`pivoted_qr_batch.py`