#!/usr/bin/env python3
"""Module containing the DummyVariables class and the command line interface."""
import argparse
import pandas as pd
from biobb_common.generic.biobb_object import BiobbObject
from biobb_common.configuration import settings
from biobb_common.tools import file_utils as fu
from biobb_common.tools.file_utils import launchlogger
from biobb_ml.utils.common import check_input_path, check_output_path, getHeader, getTargetsList, getIndependentVarsList
[docs]class DummyVariables(BiobbObject):
"""
| biobb_ml DummyVariables
| Converts categorical variables into dummy/indicator variables (binaries).
Args:
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).
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).
properties (dic):
* **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.
* **remove_tmp** (*bool*) - (True) [WF property] Remove temporal files.
* **restart** (*bool*) - (False) [WF property] Do not execute if output files exist.
Examples:
This is a use example of how to use the building block from Python::
from biobb_ml.utils.dummy_variables import dummy_variables
prop = {
'targets': {
'columns': [ 'column1', 'column2', 'column3' ]
}
}
dummy_variables(input_dataset_path='/path/to/myDataset.csv',
output_dataset_path='/path/to/newDataset.csv',
properties=prop)
Info:
* wrapped_software:
* name: In house
* license: Apache-2.0
* ontology:
* name: EDAM
* schema: http://edamontology.org/EDAM.owl
"""
def __init__(self, input_dataset_path, output_dataset_path,
properties=None, **kwargs) -> None:
properties = properties or {}
# Call parent class constructor
super().__init__(properties)
self.locals_var_dict = locals().copy()
# Input/Output files
self.io_dict = {
"in": {"input_dataset_path": input_dataset_path},
"out": {"output_dataset_path": output_dataset_path}
}
# Properties specific for BB
self.targets = properties.get('targets', {})
self.properties = properties
# Check the properties
self.check_properties(properties)
self.check_arguments()
[docs] def check_data_params(self, out_log, err_log):
""" Checks all the input/output paths and parameters """
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__)
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__)
[docs] @launchlogger
def launch(self) -> int:
"""Execute the :class:`DummyVariables <utils.dummy_variables.DummyVariables>` utils.dummy_variables.DummyVariables object."""
# check input/output paths and parameters
self.check_data_params(self.out_log, self.err_log)
# Setup Biobb
if self.check_restart():
return 0
self.stage_files()
# load dataset
fu.log('Getting dataset from %s' % self.io_dict["in"]["input_dataset_path"], self.out_log, self.global_log)
if 'columns' in self.targets:
labels = getHeader(self.io_dict["in"]["input_dataset_path"])
skiprows = 1
else:
labels = None
skiprows = None
data = pd.read_csv(self.io_dict["in"]["input_dataset_path"], header=None, sep="\\s+|;|:|,|\t", engine="python", skiprows=skiprows, names=labels)
# map dummy variables
fu.log('Dummying up [%s] columns of the dataset' % getIndependentVarsList(self.targets), self.out_log, self.global_log)
cols = None
if self.targets is not None:
cols = getTargetsList(self.targets, 'dummy', self.out_log, self.__class__.__name__)
data = pd.get_dummies(data, drop_first=True, columns=cols)
# save to csv
fu.log('Saving results to %s\n' % self.io_dict["out"]["output_dataset_path"], self.out_log, self.global_log)
data.to_csv(self.io_dict["out"]["output_dataset_path"], index=False, header=True, float_format='%.3f')
# Copy files to host
self.copy_to_host()
self.tmp_files.extend([
self.stage_io_dict.get("unique_dir")
])
self.remove_tmp_files()
self.check_arguments(output_files_created=True, raise_exception=False)
return 0
[docs]def dummy_variables(input_dataset_path: str, output_dataset_path: str, properties: dict = None, **kwargs) -> int:
"""Execute the :class:`DummyVariables <utils.dummy_variables.DummyVariables>` class and
execute the :meth:`launch() <utils.dummy_variables.DummyVariables.launch>` method."""
return DummyVariables(input_dataset_path=input_dataset_path,
output_dataset_path=output_dataset_path,
properties=properties, **kwargs).launch()
[docs]def main():
"""Command line execution of this building block. Please check the command line documentation."""
parser = argparse.ArgumentParser(description="Maps dummy variables from a given dataset.", formatter_class=lambda prog: argparse.RawTextHelpFormatter(prog, width=99999))
parser.add_argument('--config', required=False, help='Configuration file')
# Specific args of each building block
required_args = parser.add_argument_group('required arguments')
required_args.add_argument('--input_dataset_path', required=True, help='Path to the input dataset. Accepted formats: csv.')
required_args.add_argument('--output_dataset_path', required=True, help='Path to the output dataset. Accepted formats: csv.')
args = parser.parse_args()
args.config = args.config or "{}"
properties = settings.ConfReader(config=args.config).get_prop_dic()
# Specific call of each building block
dummy_variables(input_dataset_path=args.input_dataset_path,
output_dataset_path=args.output_dataset_path,
properties=properties)
if __name__ == '__main__':
main()