Python* API Reference for Intel® Data Analytics Acceleration Library 2018 Update 3

uniform_dense_batch.py

1 # file: uniform_dense_batch.py
2 #===============================================================================
3 # Copyright 2014-2018 Intel Corporation.
4 #
5 # This software and the related documents are Intel copyrighted materials, and
6 # your use of them is governed by the express license under which they were
7 # provided to you (License). Unless the License provides otherwise, you may not
8 # use, modify, copy, publish, distribute, disclose or transmit this software or
9 # the related documents without Intel's prior written permission.
10 #
11 # This software and the related documents are provided as is, with no express
12 # or implied warranties, other than those that are expressly stated in the
13 # License.
14 #===============================================================================
15 
16 #
17 # ! Content:
18 # ! Python example of uniform distribution
19 # !
20 # !*****************************************************************************
21 
22 #
23 
24 
25 #
26 
27 import os
28 import sys
29 
30 import daal.algorithms.distributions as distributions
31 import daal.algorithms.distributions.uniform as uniform
32 from daal.algorithms.engines.mt19937 import Batch_Float64DefaultDense_create as create
33 from daal.data_management import HomogenNumericTable, NumericTableIface
34 
35 utils_folder = os.path.realpath(os.path.abspath(os.path.dirname(os.path.dirname(__file__))))
36 if utils_folder not in sys.path:
37  sys.path.insert(0, utils_folder)
38 from utils import printNumericTable
39 
40 if __name__ == "__main__":
41  # Create input table to fill with random numbers
42  dataTable = HomogenNumericTable(1, 10, NumericTableIface.doAllocate)
43 
44  # Create the algorithm
45  uniform = uniform.Batch()
46 
47  # Set the algorithm input
48  uniform.input.set(distributions.tableToFill, dataTable)
49 
50  # Set the Mersenne Twister engine to the distribution
51  uniform.parameter.engine = create(777)
52 
53  # Perform computations
54  uniform.compute()
55 
56  # Print the results
57  printNumericTable(dataTable, "Uniform distribution output:")

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