Coverage for biobb_ml/utils/drop_columns.py: 77%

1#!/usr/bin/env python3 

2 

3"""Module containing the DropColumns 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 

11 

12 

13class DropColumns(BiobbObject): 

14 """ 

15 | biobb_ml DropColumns 

16 | Drops columns from a given dataset. 

17 

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_drop.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_drop.csv>`_. Accepted formats: csv (edam:format_3752). 

21 properties (dic): 

22 * **targets** (*dict*) - ({}) Independent variables or columns from your dataset you want to drop. 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. 

26 

27 Examples: 

28 This is a use example of how to use the building block from Python:: 

29 

30 from biobb_ml.utils.drop_columns import drop_columns 

31 prop = { 

32 'targets': { 

33 'columns': [ 'column1', 'column2', 'column3' ] 

34 } 

35 } 

36 drop_columns(input_dataset_path='/path/to/myDataset.csv', 

37 output_dataset_path='/path/to/newDataset.csv', 

38 properties=prop) 

39 

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 

47 

48 """ 

49 

50 def __init__(self, input_dataset_path, output_dataset_path, 

51 properties=None, **kwargs) -> None: 

52 properties = properties or {} 

53 

54 # Call parent class constructor 

55 super().__init__(properties) 

56 self.locals_var_dict = locals().copy() 

57 

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 } 

63 

64 # Properties specific for BB 

65 self.targets = properties.get('targets', {}) 

66 self.properties = properties 

67 

68 # Check the properties 

69 self.check_properties(properties) 

70 self.check_arguments() 

71 

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__) 

76 

77 @launchlogger 

78 def launch(self) -> int: 

79 """Execute the :class:`DropColumns <utils.drop_columns.DropColumns>` utils.drop_columns.DropColumns object.""" 

80 

81 # check input/output paths and parameters 

82 self.check_data_params(self.out_log, self.err_log) 

83 

84 # Setup Biobb 

85 if self.check_restart(): 

86 return 0 

87 self.stage_files() 

88 

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 header = 0 

95 else: 

96 labels = None 

97 skiprows = None 

98 header = None 

99 data = pd.read_csv(self.io_dict["in"]["input_dataset_path"], header=None, sep="\\s+|;|:|,|\t", engine="python", skiprows=skiprows, names=labels) 

100 

101 targets = getTargetsList(self.targets, 'drop', self.out_log, self.__class__.__name__) 

102 

103 fu.log('Dropping [%s] columns from dataset' % getIndependentVarsList(self.targets), self.out_log, self.global_log) 

104 data = data.drop(targets, axis=1) 

105 

106 hdr = False 

107 if header == 0: 

108 hdr = True 

109 fu.log('Saving dataset to %s' % self.io_dict["out"]["output_dataset_path"], self.out_log, self.global_log) 

110 data.to_csv(self.io_dict["out"]["output_dataset_path"], index=False, header=hdr) 

111 

112 # Copy files to host 

113 self.copy_to_host() 

114 

115 self.tmp_files.extend([ 

116 self.stage_io_dict.get("unique_dir") 

117 ]) 

118 self.remove_tmp_files() 

119 

120 self.check_arguments(output_files_created=True, raise_exception=False) 

121 

122 return 0 

123 

124 

125def drop_columns(input_dataset_path: str, output_dataset_path: str, properties: dict = None, **kwargs) -> int: 

126 """Execute the :class:`DropColumns <utils.drop_columns.DropColumns>` class and 

127 execute the :meth:`launch() <utils.drop_columns.DropColumns.launch>` method.""" 

128 

129 return DropColumns(input_dataset_path=input_dataset_path, 

130 output_dataset_path=output_dataset_path, 

131 properties=properties, **kwargs).launch() 

132 

133 

134def main(): 

135 """Command line execution of this building block. Please check the command line documentation.""" 

136 parser = argparse.ArgumentParser(description="Drops columns from a given dataset.", formatter_class=lambda prog: argparse.RawTextHelpFormatter(prog, width=99999)) 

137 parser.add_argument('--config', required=False, help='Configuration file') 

138 

139 # Specific args of each building block 

140 required_args = parser.add_argument_group('required arguments') 

141 required_args.add_argument('--input_dataset_path', required=True, help='Path to the input dataset. Accepted formats: csv.') 

142 required_args.add_argument('--output_dataset_path', required=True, help='Path to the output dataset. Accepted formats: csv.') 

143 

144 args = parser.parse_args() 

145 args.config = args.config or "{}" 

146 properties = settings.ConfReader(config=args.config).get_prop_dic() 

147 

148 # Specific call of each building block 

149 drop_columns(input_dataset_path=args.input_dataset_path, 

150 output_dataset_path=args.output_dataset_path, 

151 properties=properties) 

152 

153 

154if __name__ == '__main__': 

155 main()