#===============================================================================
# Copyright 2014-2017 Intel Corporation
# All Rights Reserved.
#
# If this  software was obtained  under the  Intel Simplified  Software License,
# the following terms apply:
#
# The source code,  information  and material  ("Material") contained  herein is
# owned by Intel Corporation or its  suppliers or licensors,  and  title to such
# Material remains with Intel  Corporation or its  suppliers or  licensors.  The
# Material  contains  proprietary  information  of  Intel or  its suppliers  and
# licensors.  The Material is protected by  worldwide copyright  laws and treaty
# provisions.  No part  of  the  Material   may  be  used,  copied,  reproduced,
# modified, published,  uploaded, posted, transmitted,  distributed or disclosed
# in any way without Intel's prior express written permission.  No license under
# any patent,  copyright or other  intellectual property rights  in the Material
# is granted to  or  conferred  upon  you,  either   expressly,  by implication,
# inducement,  estoppel  or  otherwise.  Any  license   under such  intellectual
# property rights must be express and approved by Intel in writing.
#
# Unless otherwise agreed by Intel in writing,  you may not remove or alter this
# notice or  any  other  notice   embedded  in  Materials  by  Intel  or Intel's
# suppliers or licensors in any way.
#
#
# If this  software  was obtained  under the  Apache License,  Version  2.0 (the
# "License"), the following terms apply:
#
# 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.
#===============================================================================

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

import os

import daal.algorithms.kmeans as kmeans
import daal.algorithms.kmeans.init as init
from daal.data_management import FileDataSource, DataSourceIface
from daal.services import Environment

# Input data set parameters
datasetFileName = os.path.join('..', 'data', 'batch', 'kmeans_dense.csv')

# K-Means algorithm parameters
nClusters = 20
nIterations = 5
nThreads = 2
nThreadsInit = None
nThreadsNew = None

if __name__ == "__main__":

    # Get the number of threads that is used by the library by default
    nThreadsInit = Environment.getInstance().getNumberOfThreads()

    # Set the maximum number of threads to be used by the library
    Environment.getInstance().setNumberOfThreads(nThreads)

    # Get the number of threads that is used by the library after changing
    nThreadsNew = Environment.getInstance().getNumberOfThreads()

    # Initialize FileDataSource to retrieve the input data from a .csv file
    dataSource = FileDataSource(
        datasetFileName, DataSourceIface.doAllocateNumericTable,
        DataSourceIface.doDictionaryFromContext
    )

    # Retrieve the data from the input file
    dataSource.loadDataBlock()

    # Get initial clusters for the K-Means algorithm
    initAlg = init.Batch(nClusters)

    initAlg.input.set(init.data, dataSource.getNumericTable())
    res = initAlg.compute()
    centroids = res.get(init.centroids)

    # Create an algorithm object for the K-Means algorithm
    algorithm = kmeans.Batch(nClusters, nIterations)

    algorithm.input.set(kmeans.data, dataSource.getNumericTable())
    algorithm.input.set(kmeans.inputCentroids, centroids)

    # Run computations
    unused_result = algorithm.compute()

    print("Initial number of threads:        {}".format(nThreadsInit))
    print("Number of threads to set:         {}".format(nThreads))
    print("Number of threads after setting:  {}".format(nThreadsNew))
