Python* API Reference for Intel® Data Analytics Acceleration Library 2019 Update 5

custom_csv_feature_modifiers.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: custom_csv_feature_modifiers.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 # ! Content:
17 # ! Python example of modifiers usage with file data source
18 # !*****************************************************************************
19 
20 #
21 ## <a name="DAAL-EXAMPLE-PY-DATASOURCE_CUSTOM_CSV_FEATURE_MODIFIERS">
22 ## \example custom_csv_feature_modifiers.py
23 #
24 
25 from daal.data_management import FileDataSource, CsvDataSourceOptions, modifiers
26 from daal.data_management.modifiers.csv import FeatureModifier
27 
28 import os, sys
29 utils_folder = os.path.realpath(os.path.abspath(os.path.dirname(os.path.dirname(__file__))))
30 if utils_folder not in sys.path:
31  sys.path.insert(0, utils_folder)
32 from utils import printNumericTable
33 
34 # User-defined feature modifier that computes a square for every feature
35 class MySquaringModifier(FeatureModifier):
36  def apply(self, tokens):
37  return [[float(x)*float(x) for x in t] for t in tokens]
38 
39 
40 # User-defined feature modifier that selects max element among all features
41 class MyMaxFeatureModifier(FeatureModifier):
42  def __init__(self):
43  super(MyMaxFeatureModifier, self).__init__(1,4)
44 
45  # This method is called for every row in CSV file
46  def apply(self, tokens):
47  return [[float(max(t))] for t in tokens]
48 
49 
50 if __name__ == "__main__":
51  # Path to the CSV to be read
52  csvFileName = "../data/batch/mixed_text_and_numbers.csv"
53 
54  # Define options for CSV data source
55  csvOptions = CsvDataSourceOptions(CsvDataSourceOptions.allocateNumericTable | CsvDataSourceOptions.createDictionaryFromContext | CsvDataSourceOptions.parseHeader)
56 
57  # Define CSV file data source
58  ds = FileDataSource(csvFileName, csvOptions)
59 
60  # Configure format of output numeric table by applying modifiers.
61  # Output numeric table will have the following format:
62  # | Numeric1 | Numeric2 ^ 2 | Numeric5 ^ 2 | max(Numeric0, Numeric5) |
63  fm = ds.getFeatureManager()
64  fm.addModifier(["Numeric1"], modifiers.csv.continuous())
65  fm.addModifier(["Numeric2", "Numeric5"], MySquaringModifier())
66  fm.addModifier(["Numeric0", "Numeric5"], MyMaxFeatureModifier())
67 
68  # Load and parse CSV file
69  ds.loadDataBlock()
70  printNumericTable(ds.getNumericTable(), "Loaded numeric table:")

For more complete information about compiler optimizations, see our Optimization Notice.