Python* API Reference for Intel® Data Analytics Acceleration Library 2019 Update 4

datastructures_matrix.py

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.

1 # file: datastructures_matrix.py
2 #===============================================================================
3 # Copyright 2014-2019 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 using matrix data structures
19 # !*****************************************************************************
20 
21 #
22 ## <a name="DAAL-EXAMPLE-PY-DATASTRUCTURES_MATRIX">
23 ## \example datastructures_matrix.py
24 #
25 
26 import sys, os
27 import numpy as np
28 from daal.data_management import Matrix, BlockDescriptor, readOnly
29 
30 utils_folder = os.path.realpath(os.path.abspath(os.path.dirname(os.path.dirname(__file__))))
31 if utils_folder not in sys.path:
32  sys.path.insert(0, utils_folder)
33 from utils import printArray
34 
35 if __name__ == "__main__":
36 
37  print("Matrix numeric table example\n")
38 
39  nObservations = 10
40  nFeatures = 11
41  firstReadRow = 0
42  nRead = 5
43 
44  #Example of using a matrix
45  data = np.array([(0.0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1),
46  (1.0, 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 2),
47  (2.0, 2.1, 2.2, 2.3, 2.4, 2.5, 2.6, 2.7, 2.8, 2.9, 3),
48  (3.0, 3.1, 3.2, 3.3, 3.4, 3.5, 3.6, 3.7, 3.8, 3.9, 4),
49  (4.0, 4.1, 4.2, 4.3, 4.4, 4.5, 4.6, 4.7, 4.8, 4.9, 5),
50  (5.0, 5.1, 5.2, 5.3, 5.4, 5.5, 5.6, 5.7, 5.8, 5.9, 1),
51  (6.0, 6.1, 6.2, 6.3, 6.4, 6.5, 6.6, 6.7, 6.8, 6.9, 2),
52  (7.0, 7.1, 7.2, 7.3, 7.4, 7.5, 7.6, 7.7, 7.8, 7.9, 3),
53  (8.0, 8.1, 8.2, 8.3, 8.4, 8.5, 8.6, 8.7, 8.8, 8.9, 4),
54  (9.0, 9.1, 9.2, 9.3, 9.4, 9.5, 9.6, 9.7, 9.8, 9.9, 5)], dtype=np.float32)
55 
56  dataTable = Matrix(data, ntype=np.float32)
57 
58  block = BlockDescriptor()
59 
60  # Read a block of rows
61  dataTable.getBlockOfRows(firstReadRow, nRead, readOnly, block)
62  print(str(block.getNumberOfRows()) + " rows are read")
63  printArray(block.getArray(), nFeatures, nRead, block.getNumberOfColumns(), "Print 5 rows from matrix data array as float:")
64  dataTable.releaseBlockOfRows(block)
65 
66  readFeatureIdx = 2
67 
68  # Set new values in Matrix
69  npdt = dataTable.getArray()
70  npdt[firstReadRow, readFeatureIdx] = -1
71  npdt[firstReadRow + 1, readFeatureIdx] = -2
72  npdt[firstReadRow + 2, readFeatureIdx] = -3
73 
74  # Read a feature(column) and print it
75  dataTable.getBlockOfColumnValues(readFeatureIdx, firstReadRow, nObservations, readOnly, block)
76  printArray(block.getArray(), 1, block.getNumberOfRows(), block.getNumberOfColumns(), "Print the third feature of matrix data:")
77  dataTable.releaseBlockOfColumnValues(block)

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