Feature

src/parameter_parser.py

+"""Module containing functionalities to store run parameters.
+
+Class:
+    ParamParse: Take as input a file containing the parameters
+    and stores them in its attributes.
+"""
+import logging
+from pathlib import Path
+
+LOG = logging.getLogger(__name__)
+
+
+class ParamParse:
+    """Class holding the parameters of the run.
+
+    Args:
+        param_file: Path to file with parameter values.
+
+    Attributes:
+        param_file: File with parameter values.
+        transcripts_file: File with transcript abundances.
+        genome_ref_file: Reference genome file.
+        annotations_file: Transcripts annotations.
+        output_path: Output folder.
+        n_reads: Number of reads to be simulated.
+        n_cells: Number of cells to be simulated.
+        rna_avg_length: average RNA fragment length.
+        rna_sd_length: RNA fragment length standard deviation.
+        read_length: Read length.
+        intron_rate: Constant probability of retaining an intron.
+        add_poly_a: Boolean option to add a poly A tail.
+        poly_a_func: Function to add a poly_a tail.
+        primer_seq: Sequence of the primer.
+        priming_func: Function that evaluates internal priming.
+    """
+
+    def __init__(self, param_file: Path) -> None:
+        """Class constructor."""
+        self.param_file: Path = Path(param_file)
+        with open(param_file) as f:
+            LOG.info("Loading parameters...")
+            for line in f:
+                s = line.split(':')
+                if s[0] == 'Csv transcripts file':
+                    self.transcripts_file: Path = Path(s[1].strip())
+                elif s[0] == 'Reference genome file':
+                    self.genome_ref_file: Path = Path(s[1].strip())
+                elif s[0] == 'Transcripts annotation file':
+                    self.annotations_file: Path = Path(s[1].strip())
+                elif s[0] == 'Output folder':
+                    self.output_path: Path = Path(s[1].strip())
+                elif s[0] == 'Number of reads':
+                    self.n_reads: int = int(s[1].strip())
+                elif s[0] == 'Number of cells':
+                    self.n_cells: int = int(s[1].strip())
+                elif s[0] == 'Average RNA fragments length':
+                    self.rna_avg: float = float(s[1].strip())
+                elif s[0] == 'RNA fragment length standard deviation':
+                    self.rna_sd_length: float = float(s[1].strip())
+                elif s[0] == 'Reads length':
+                    self.read_length: int = int(s[1].strip())
+                elif s[0] == 'Intron retaining probability':
+                    self.intron_rate: float = float(s[1].strip())
+                elif s[0] == 'Add poly A tail':
+                    self.add_poly_a: bool = bool(s[1].strip())
+                elif s[0] == 'Function to add poly A tail':
+                    self.poly_a_func: str = str(s[1].strip())
+                elif s[0] == 'Primer sequence':
+                    self.primer_seq: str = str(s[1].strip())
+                elif s[0] == 'Function to evaluate internal priming':
+                    self.priming_func: str = str(s[1].strip())
+        LOG.info("Parameters loaded.")