Python* API Reference for Intel® Data Analytics Acceleration Library 2018 Update 2

datastructures_matrix.py

1 # file: datastructures_matrix.py
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40 #===============================================================================
41 
42 #
43 # ! Content:
44 # ! Python example of using matrix data structures
45 # !*****************************************************************************
46 
47 #
48 
49 
50 #
51 
52 import sys, os
53 import numpy as np
54 from daal.data_management import Matrix, BlockDescriptor, readOnly
55 
56 utils_folder = os.path.realpath(os.path.abspath(os.path.dirname(os.path.dirname(__file__))))
57 if utils_folder not in sys.path:
58  sys.path.insert(0, utils_folder)
59 from utils import printArray
60 
61 if __name__ == "__main__":
62 
63  print("Matrix numeric table example\n")
64 
65  nObservations = 10
66  nFeatures = 11
67  firstReadRow = 0
68  nRead = 5
69 
70  #Example of using a matrix
71  data = np.array([(0.0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1),
72  (1.0, 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 2),
73  (2.0, 2.1, 2.2, 2.3, 2.4, 2.5, 2.6, 2.7, 2.8, 2.9, 3),
74  (3.0, 3.1, 3.2, 3.3, 3.4, 3.5, 3.6, 3.7, 3.8, 3.9, 4),
75  (4.0, 4.1, 4.2, 4.3, 4.4, 4.5, 4.6, 4.7, 4.8, 4.9, 5),
76  (5.0, 5.1, 5.2, 5.3, 5.4, 5.5, 5.6, 5.7, 5.8, 5.9, 1),
77  (6.0, 6.1, 6.2, 6.3, 6.4, 6.5, 6.6, 6.7, 6.8, 6.9, 2),
78  (7.0, 7.1, 7.2, 7.3, 7.4, 7.5, 7.6, 7.7, 7.8, 7.9, 3),
79  (8.0, 8.1, 8.2, 8.3, 8.4, 8.5, 8.6, 8.7, 8.8, 8.9, 4),
80  (9.0, 9.1, 9.2, 9.3, 9.4, 9.5, 9.6, 9.7, 9.8, 9.9, 5)], dtype=np.float32)
81 
82  dataTable = Matrix(data, ntype=np.float32)
83 
84  block = BlockDescriptor()
85 
86  # Read a block of rows
87  dataTable.getBlockOfRows(firstReadRow, nRead, readOnly, block)
88  print(str(block.getNumberOfRows()) + " rows are read")
89  printArray(block.getArray(), nFeatures, nRead, block.getNumberOfColumns(), "Print 5 rows from matrix data array as float:")
90  dataTable.releaseBlockOfRows(block)
91 
92  readFeatureIdx = 2
93 
94  # Set new values in Matrix
95  npdt = dataTable.getArray()
96  npdt[firstReadRow, readFeatureIdx] = -1
97  npdt[firstReadRow + 1, readFeatureIdx] = -2
98  npdt[firstReadRow + 2, readFeatureIdx] = -3
99 
100  # Read a feature(column) and print it
101  dataTable.getBlockOfColumnValues(readFeatureIdx, firstReadRow, nObservations, readOnly, block)
102  printArray(block.getArray(), 1, block.getNumberOfRows(), block.getNumberOfColumns(), "Print the third feature of matrix data:")
103  dataTable.releaseBlockOfColumnValues(block)

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