Coverage for biobb_ml/utils/dummy_variables.py: 78%
59 statements
« prev ^ index » next coverage.py v7.6.1, created at 2024-10-03 14:57 +0000
« prev ^ index » next coverage.py v7.6.1, created at 2024-10-03 14:57 +0000
1#!/usr/bin/env python3
3"""Module containing the DummyVariables class and the command line interface."""
4import argparse
5import pandas as pd
6from biobb_common.generic.biobb_object import BiobbObject
7from biobb_common.configuration import settings
8from biobb_common.tools import file_utils as fu
9from biobb_common.tools.file_utils import launchlogger
10from biobb_ml.utils.common import check_input_path, check_output_path, getHeader, getTargetsList, getIndependentVarsList
13class DummyVariables(BiobbObject):
14 """
15 | biobb_ml DummyVariables
16 | Converts categorical variables into dummy/indicator variables (binaries).
18 Args:
19 input_dataset_path (str): Path to the input dataset. File type: input. `Sample file <https://github.com/bioexcel/biobb_ml/raw/master/biobb_ml/test/data/utils/dataset_dummy_variables.csv>`_. Accepted formats: csv (edam:format_3752).
20 output_dataset_path (str): Path to the output dataset. File type: output. `Sample file <https://github.com/bioexcel/biobb_ml/raw/master/biobb_ml/test/reference/utils/ref_output_dataset_dummy_variables.csv>`_. Accepted formats: csv (edam:format_3752).
21 properties (dic):
22 * **targets** (*dict*) - ({}) Independent variables or columns from your dataset you want to drop. If None given, all the columns will be taken. You can specify either a list of columns names from your input dataset, a list of columns indexes or a range of columns indexes. Formats: { "columns": ["column1", "column2"] } or { "indexes": [0, 2, 3, 10, 11, 17] } or { "range": [[0, 20], [50, 102]] }. In case of mulitple formats, the first one will be picked.
23 * **remove_tmp** (*bool*) - (True) [WF property] Remove temporal files.
24 * **restart** (*bool*) - (False) [WF property] Do not execute if output files exist.
25 * **sandbox_path** (*str*) - ("./") [WF property] Parent path to the sandbox directory.
27 Examples:
28 This is a use example of how to use the building block from Python::
30 from biobb_ml.utils.dummy_variables import dummy_variables
31 prop = {
32 'targets': {
33 'columns': [ 'column1', 'column2', 'column3' ]
34 }
35 }
36 dummy_variables(input_dataset_path='/path/to/myDataset.csv',
37 output_dataset_path='/path/to/newDataset.csv',
38 properties=prop)
40 Info:
41 * wrapped_software:
42 * name: In house
43 * license: Apache-2.0
44 * ontology:
45 * name: EDAM
46 * schema: http://edamontology.org/EDAM.owl
48 """
50 def __init__(self, input_dataset_path, output_dataset_path,
51 properties=None, **kwargs) -> None:
52 properties = properties or {}
54 # Call parent class constructor
55 super().__init__(properties)
56 self.locals_var_dict = locals().copy()
58 # Input/Output files
59 self.io_dict = {
60 "in": {"input_dataset_path": input_dataset_path},
61 "out": {"output_dataset_path": output_dataset_path}
62 }
64 # Properties specific for BB
65 self.targets = properties.get('targets', {})
66 self.properties = properties
68 # Check the properties
69 self.check_properties(properties)
70 self.check_arguments()
72 def check_data_params(self, out_log, err_log):
73 """ Checks all the input/output paths and parameters """
74 self.io_dict["in"]["input_dataset_path"] = check_input_path(self.io_dict["in"]["input_dataset_path"], "input_dataset_path", out_log, self.__class__.__name__)
75 self.io_dict["out"]["output_dataset_path"] = check_output_path(self.io_dict["out"]["output_dataset_path"], "output_dataset_path", False, out_log, self.__class__.__name__)
77 @launchlogger
78 def launch(self) -> int:
79 """Execute the :class:`DummyVariables <utils.dummy_variables.DummyVariables>` utils.dummy_variables.DummyVariables object."""
81 # check input/output paths and parameters
82 self.check_data_params(self.out_log, self.err_log)
84 # Setup Biobb
85 if self.check_restart():
86 return 0
87 self.stage_files()
89 # load dataset
90 fu.log('Getting dataset from %s' % self.io_dict["in"]["input_dataset_path"], self.out_log, self.global_log)
91 if 'columns' in self.targets:
92 labels = getHeader(self.io_dict["in"]["input_dataset_path"])
93 skiprows = 1
94 else:
95 labels = None
96 skiprows = None
97 data = pd.read_csv(self.io_dict["in"]["input_dataset_path"], header=None, sep="\\s+|;|:|,|\t", engine="python", skiprows=skiprows, names=labels)
99 # map dummy variables
100 fu.log('Dummying up [%s] columns of the dataset' % getIndependentVarsList(self.targets), self.out_log, self.global_log)
101 cols = None
102 if self.targets is not None:
103 cols = getTargetsList(self.targets, 'dummy', self.out_log, self.__class__.__name__)
105 data = pd.get_dummies(data, drop_first=True, columns=cols)
107 # save to csv
108 fu.log('Saving results to %s\n' % self.io_dict["out"]["output_dataset_path"], self.out_log, self.global_log)
109 data.to_csv(self.io_dict["out"]["output_dataset_path"], index=False, header=True, float_format='%.3f')
111 # Copy files to host
112 self.copy_to_host()
114 self.tmp_files.extend([
115 self.stage_io_dict.get("unique_dir")
116 ])
117 self.remove_tmp_files()
119 self.check_arguments(output_files_created=True, raise_exception=False)
121 return 0
124def dummy_variables(input_dataset_path: str, output_dataset_path: str, properties: dict = None, **kwargs) -> int:
125 """Execute the :class:`DummyVariables <utils.dummy_variables.DummyVariables>` class and
126 execute the :meth:`launch() <utils.dummy_variables.DummyVariables.launch>` method."""
128 return DummyVariables(input_dataset_path=input_dataset_path,
129 output_dataset_path=output_dataset_path,
130 properties=properties, **kwargs).launch()
133def main():
134 """Command line execution of this building block. Please check the command line documentation."""
135 parser = argparse.ArgumentParser(description="Maps dummy variables from a given dataset.", formatter_class=lambda prog: argparse.RawTextHelpFormatter(prog, width=99999))
136 parser.add_argument('--config', required=False, help='Configuration file')
138 # Specific args of each building block
139 required_args = parser.add_argument_group('required arguments')
140 required_args.add_argument('--input_dataset_path', required=True, help='Path to the input dataset. Accepted formats: csv.')
141 required_args.add_argument('--output_dataset_path', required=True, help='Path to the output dataset. Accepted formats: csv.')
143 args = parser.parse_args()
144 args.config = args.config or "{}"
145 properties = settings.ConfReader(config=args.config).get_prop_dic()
147 # Specific call of each building block
148 dummy_variables(input_dataset_path=args.input_dataset_path,
149 output_dataset_path=args.output_dataset_path,
150 properties=properties)
153if __name__ == '__main__':
154 main()