# file: normal_dense_batch.py
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#
# !  Content:
# !    Python example of normal distribution
# !
# !*****************************************************************************

#
## <a name="DAAL-EXAMPLE-PY-NORMAL_DENSE_BATCH"></a>
## \example normal_dense_batch.py
#

import os
import sys

import daal.algorithms.distributions as distributions
import daal.algorithms.distributions.normal as normal
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
    normal = normal.Batch()

    # Set the algorithm input
    normal.input.set(distributions.tableToFill, dataTable)

    # Set the Mersenne Twister engine to the distribution
    normal.parameter.engine = create(777)

    # Perform computations
    normal.compute()

    # Print the results
    printNumericTable(dataTable, "Normal distribution output:")
