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.
 # !  Content:
 # !    Python example of bernoulli distribution
 # !
 # !*****************************************************************************
 ## \example
 import os
 import sys
 import daal.algorithms.distributions as distributions
 import daal.algorithms.distributions.bernoulli as bernoulli
 from daal.algorithms.engines.mt19937 import Batch_Float64DefaultDense_create as create
 from daal.data_management import HomogenNumericTable, NumericTableIface
 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 printNumericTable
 if __name__ == "__main__":
     # Create input table to fill with random numbers
     dataTable = HomogenNumericTable(1, 10, NumericTableIface.doAllocate)
     # Create the algorithm
     bernoulli = bernoulli.Batch(0.5)
     # Set the algorithm input
     bernoulli.input.set(distributions.tableToFill, dataTable)
     # Set the Mersenne Twister engine to the distribution
     bernoulli.parameter.engine = create(777)
     # Perform computations
     # Print the results
     printNumericTable(dataTable, "Bernoulli distribution output:")
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