Deprecation Notice: With the introduction of daal4py, a package that supersedes PyDAAL, Intel is deprecating PyDAAL and will discontinue support starting with Intel® DAAL 2021 and Intel® Distribution for Python 2021. Until then Intel will continue to provide compatible pyDAAL pip and conda packages for newer releases of Intel DAAL and make it available in open source. However, Intel will not add the new features of Intel DAAL to pyDAAL. Intel recommends developers switch to and use daal4py.

Note: To find daal4py examples, refer to daal4py documentation or browse github repository.

 # file:
 # Copyright 2014-2019 Intel Corporation.
 # This software and the related documents are Intel copyrighted  materials,  and
 # your use of  them is  governed by the  express license  under which  they were
 # provided to you (License).  Unless the License provides otherwise, you may not
 # use, modify, copy, publish, distribute,  disclose or transmit this software or
 # the related documents without Intel's prior written permission.
 # This software and the related documents  are provided as  is,  with no express
 # or implied  warranties,  other  than those  that are  expressly stated  in the
 # License.
 ## @example
 import os
 import sys
 import numpy as np
 from daal.data_management import features, AOSNumericTable, BlockDescriptor, readOnly, readWrite
 utils_folder = os.path.realpath(os.path.abspath(os.path.dirname(os.path.dirname(__file__))))
 if utils_folder not in sys.path:
     sys.path.insert(0, utils_folder)
 from utils import printArray
 if __name__ == "__main__":
     print("Array of structures (AOS) numeric table example\n")
     points = np.array([(0.5, -1.3, 1, 100.1),
                        (2.5, -3.3, 2, 200.2),
                        (4.5, -5.3, 2, 350.3),
                        (6.5, -7.3, 0, 470.4),
                        (8.5, -9.3, 1, 270.5)],
                       dtype=[('x','f4'), ('y','f4'), ('categ','i4'), ('value','f8')])
     nObservations = len(points)
     nFeatures = len(points[0])
     # Construct AOS numericTable for a data array with nFeatures fields and nObservations elements
     # Dictionary will be initialized with type information from ndarray
     dataTable = AOSNumericTable(points)
     #  Get the dictionary and update it with additional information about data
     dict = dataTable.getDictionary()
     #  Add a feature type to the dictionary
     dict[0].featureType = features.DAAL_CONTINUOUS
     dict[1].featureType = features.DAAL_CONTINUOUS
     dict[2].featureType = features.DAAL_CATEGORICAL
     dict[3].featureType = features.DAAL_CONTINUOUS
     #  Set the number of categories for a categorical feature
     dict[2].categoryNumber = 3
     #  Read a block of rows
     firstReadRow = 0
     doubleBlock = BlockDescriptor()
     dataTable.getBlockOfRows(firstReadRow, nObservations, readWrite, doubleBlock)
         doubleBlock.getArray(), nFeatures, doubleBlock.getNumberOfRows(),
         doubleBlock.getNumberOfColumns(),"Print AOS data structures as double:"
     #  Read a feature (column)
     readFeatureIdx = 2
     intBlock = BlockDescriptor(ntype=np.intc)
     dataTable.getBlockOfColumnValues(readFeatureIdx, firstReadRow, nObservations, readOnly, intBlock)
         intBlock.getArray(), 1, intBlock.getNumberOfRows(), intBlock.getNumberOfColumns(),
         "Print the third feature of AOS:", flt64=False
For more complete information about compiler optimizations, see our Optimization Notice.
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