Coverage for biobb_dna / dna / dna_averages.py: 81%
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« prev ^ index » next coverage.py v7.13.0, created at 2025-12-15 18:49 +0000
1#!/usr/bin/env python3
3"""Module containing the HelParAverages class and the command line interface."""
5from pathlib import Path
6from typing import Optional
8import matplotlib.pyplot as plt
9import pandas as pd
10from biobb_common.generic.biobb_object import BiobbObject
11from biobb_common.tools.file_utils import launchlogger
13from biobb_dna.utils import constants
14from biobb_dna.utils.common import _from_string_to_list
15from biobb_dna.utils.loader import read_series
18class HelParAverages(BiobbObject):
19 """
20 | biobb_dna HelParAverages
21 | Load .ser file for a given helical parameter and read each column corresponding to a base calculating average over each one.
22 | Calculate average values for each base pair and save them in a .csv file.
24 Args:
25 input_ser_path (str): Path to .ser file for helical parameter. File is expected to be a table, with the first column being an index and the rest the helical parameter values for each base/basepair. File type: input. `Sample file <https://raw.githubusercontent.com/bioexcel/biobb_dna/master/biobb_dna/test/data/dna/canal_output_shift.ser>`_. Accepted formats: ser (edam:format_2330).
26 output_csv_path (str): Path to .csv file where output is saved. File type: output. `Sample file <https://raw.githubusercontent.com/bioexcel/biobb_dna/master/biobb_dna/test/reference/dna/shift_avg.csv>`_. Accepted formats: csv (edam:format_3752).
27 output_jpg_path (str): Path to .jpg file where output is saved. File type: output. `Sample file <https://raw.githubusercontent.com/bioexcel/biobb_dna/master/biobb_dna/test/reference/dna/shift_avg.jpg>`_. Accepted formats: jpg (edam:format_3579).
28 properties (dict):
29 * **sequence** (*str*) - (None) Nucleic acid sequence corresponding to the input .ser file. Length of sequence is expected to be the same as the total number of columns in the .ser file, minus the index column (even if later on a subset of columns is selected with the *seqpos* option).
30 * **helpar_name** (*str*) - (Optional) helical parameter name.
31 * **stride** (*int*) - (1000) granularity of the number of snapshots for plotting time series.
32 * **seqpos** (*list*) - (None) list of sequence positions (columns indices starting by 0) to analyze. If not specified it will analyse the complete sequence.
33 * **remove_tmp** (*bool*) - (True) [WF property] Remove temporal files.
34 * **restart** (*bool*) - (False) [WF property] Do not execute if output files exist.
35 * **sandbox_path** (*str*) - ("./") [WF property] Parent path to the sandbox directory.
36 Examples:
37 This is a use example of how to use the building block from Python::
39 from biobb_dna.dna.dna_averages import dna_averages
41 prop = {
42 'helpar_name': 'twist',
43 'seqpos': [1,2],
44 'sequence': 'GCAT'
45 }
46 dna_averages(
47 input_ser_path='/path/to/twist.ser',
48 output_csv_path='/path/to/table/output.csv',
49 output_jpg_path='/path/to/table/output.jpg',
50 properties=prop)
52 Info:
53 * wrapped_software:
54 * name: In house
55 * license: Apache-2.0
56 * ontology:
57 * name: EDAM
58 * schema: http://edamontology.org/EDAM.owl
60 """
62 def __init__(
63 self,
64 input_ser_path,
65 output_csv_path,
66 output_jpg_path,
67 properties=None,
68 **kwargs,
69 ) -> None:
70 properties = properties or {}
72 # Call parent class constructor
73 super().__init__(properties)
74 self.locals_var_dict = locals().copy()
76 # Input/Output files
77 self.io_dict = {
78 "in": {
79 "input_ser_path": input_ser_path,
80 },
81 "out": {
82 "output_csv_path": output_csv_path,
83 "output_jpg_path": output_jpg_path,
84 },
85 }
87 # Properties specific for BB
88 self.properties = properties
89 self.sequence = properties.get("sequence", None)
90 self.stride = properties.get("stride", 1000)
91 self.seqpos = [
92 int(elem) for elem in _from_string_to_list(properties.get("seqpos", None))
93 ]
94 self.helpar_name = properties.get("helpar_name", None)
96 # Check the properties
97 self.check_properties(properties)
98 self.check_arguments()
100 @launchlogger
101 def launch(self) -> int:
102 """Execute the :class:`HelParAverages <dna.averages.HelParAverages>` object."""
104 # Setup Biobb
105 if self.check_restart():
106 return 0
107 self.stage_files()
109 # check sequence
110 if self.sequence is None or len(self.sequence) < 2:
111 raise ValueError("sequence is null or too short!")
113 # get helical parameter from filename if not specified
114 if self.helpar_name is None:
115 for hp in constants.helical_parameters:
116 ser_name = Path(self.stage_io_dict["in"]["input_ser_path"]).name.lower()
117 if hp.lower() in ser_name:
118 self.helpar_name = hp
119 if self.helpar_name is None:
120 raise ValueError(
121 "Helical parameter name can't be inferred from file, "
122 "so it must be specified!"
123 )
124 else:
125 if self.helpar_name not in constants.helical_parameters:
126 raise ValueError(
127 "Helical parameter name is invalid! "
128 f"Options: {constants.helical_parameters}"
129 )
131 # get base length and unit from helical parameter name
132 if self.helpar_name.lower() in constants.hp_basepairs:
133 self.baselen = 1
134 elif self.helpar_name.lower() in constants.hp_singlebases:
135 self.baselen = 0
136 if self.helpar_name in constants.hp_angular:
137 self.hp_unit = "Degrees"
138 else:
139 self.hp_unit = "Angstroms"
141 # check seqpos
142 if self.seqpos:
143 if (max(self.seqpos) > len(self.sequence) - 2) or (min(self.seqpos) < 1):
144 raise ValueError(
145 f"seqpos values must be between 1 and {len(self.sequence) - 2}"
146 )
147 if not (isinstance(self.seqpos, list) and len(self.seqpos) > 1):
148 raise ValueError("seqpos must be a list of at least two integers")
149 else:
150 self.seqpos = None # type: ignore
152 # read input .ser file
153 ser_data = read_series(
154 self.stage_io_dict["in"]["input_ser_path"], usecols=self.seqpos
155 )
156 if not self.seqpos:
157 ser_data = ser_data[ser_data.columns[1:-1]]
158 # discard first and last base(pairs) from sequence
159 sequence = self.sequence[1:]
160 xlabels = [
161 f"{sequence[i:i+1+self.baselen]}"
162 for i in range(len(ser_data.columns) - self.baselen)
163 ]
164 else:
165 sequence = self.sequence
166 xlabels = [f"{sequence[i:i+1+self.baselen]}" for i in self.seqpos]
168 # rename duplicated subunits
169 while any(pd.Index(ser_data.columns).duplicated()):
170 ser_data.columns = [
171 name if not duplicated else name + "_dup"
172 for duplicated, name in zip(
173 pd.Index(ser_data.columns).duplicated(), ser_data.columns
174 )
175 ]
177 # write output files for all selected bases
178 means = ser_data.mean(axis=0).iloc[: len(xlabels)]
179 stds = ser_data.std(axis=0).iloc[: len(xlabels)]
181 # save plot
182 fig, axs = plt.subplots(1, 1, dpi=300, tight_layout=True)
183 axs.errorbar(
184 means.index, means.to_numpy(), yerr=stds.to_numpy(), marker="o", capsize=5
185 )
186 axs.set_xticks(means.index)
187 axs.set_xticklabels(xlabels, rotation=90)
188 axs.set_xlabel("Sequence Base Pair " f"{'Step' if self.baselen == 1 else ''}")
189 axs.set_ylabel(f"{self.helpar_name.capitalize()} ({self.hp_unit})")
190 axs.set_title(
191 "Base Pair "
192 f"{'Step' if self.baselen == 1 else ''} "
193 f"Helical Parameter: {self.helpar_name.capitalize()}"
194 )
195 fig.savefig(self.stage_io_dict["out"]["output_jpg_path"], format="jpg")
197 # save table
198 dataset = pd.DataFrame(
199 {
200 f"Base Pair {'Step' if self.baselen == 1 else ''}": xlabels,
201 "mean": means.to_numpy(),
202 "std": stds.to_numpy(),
203 }
204 )
205 dataset.to_csv(self.stage_io_dict["out"]["output_csv_path"], index=False)
207 plt.close()
209 # Copy files to host
210 self.copy_to_host()
212 # Remove temporary file(s)
213 self.remove_tmp_files()
215 self.check_arguments(output_files_created=True, raise_exception=False)
217 return 0
220def dna_averages(
221 input_ser_path: str,
222 output_csv_path: str,
223 output_jpg_path: str,
224 properties: Optional[dict] = None,
225 **kwargs,
226) -> int:
227 """Create :class:`HelParAverages <dna.dna_averages.HelParAverages>` class and
228 execute the :meth:`launch() <dna.dna_averages.HelParAverages.launch>` method."""
229 return HelParAverages(**dict(locals())).launch()
232dna_averages.__doc__ = HelParAverages.__doc__
233main = HelParAverages.get_main(dna_averages, "Load helical parameter file and calculate average values for each base pair.")
235if __name__ == '__main__':
236 main()