import warnings
from collections import Counter
from pathlib import Path
import pandas as pd
import plotly.express as px
from immuneML.data_model.dataset.RepertoireDataset import RepertoireDataset
from immuneML.data_model.repertoire.Repertoire import Repertoire
from immuneML.reports.ReportOutput import ReportOutput
from immuneML.reports.ReportResult import ReportResult
from immuneML.reports.data_reports.DataReport import DataReport
from immuneML.util.PathBuilder import PathBuilder
[docs]class SequenceLengthDistribution(DataReport):
"""
Generates a histogram of the lengths of the sequences in a RepertoireDataset.
YAML specification:
.. indent with spaces
.. code-block:: yaml
my_sld_report: SequenceLengthDistribution
"""
[docs] @classmethod
def build_object(cls, **kwargs):
return SequenceLengthDistribution(**kwargs)
def __init__(self, dataset: RepertoireDataset = None, batch_size: int = 1, result_path: Path = None, name: str = None):
super().__init__(dataset=dataset, result_path=result_path, name=name)
self.batch_size = batch_size
[docs] def check_prerequisites(self):
if isinstance(self.dataset, RepertoireDataset):
return True
else:
warnings.warn("SequenceLengthDistribution: report can be generated only from RepertoireDataset. Skipping this report...")
return False
def _generate(self) -> ReportResult:
sequence_lengths = self._get_sequence_lengths()
report_output_fig = self._plot(sequence_lengths=sequence_lengths)
output_figures = None if report_output_fig is None else [report_output_fig]
return ReportResult(type(self).__name__, output_figures=output_figures)
def _get_sequence_lengths(self) -> Counter:
sequence_lenghts = Counter()
for repertoire in self.dataset.get_data(self.batch_size):
seq_lengths = self._count_in_repertoire(repertoire)
sequence_lenghts += seq_lengths
return sequence_lenghts
def _count_in_repertoire(self, repertoire: Repertoire) -> Counter:
c = Counter([len(sequence.get_sequence()) for sequence in repertoire.sequences])
return c
def _plot(self, sequence_lengths: Counter):
df = pd.DataFrame({"counts": list(sequence_lengths.values()), 'sequence_lengths': list(sequence_lengths.keys())})
figure = px.bar(df, x="sequence_lengths", y="counts")
figure.update_layout(xaxis=dict(tickmode='array', tickvals=df["sequence_lengths"]), yaxis=dict(tickmode='array', tickvals=df["counts"]),
title="Sequence length distribution", template="plotly_white")
figure.update_traces(marker_color=px.colors.diverging.Tealrose[0])
PathBuilder.build(self.result_path)
file_path = self.result_path / "sequence_length_distribution.html"
figure.write_html(str(file_path))
return ReportOutput(path=file_path, name="sequence length distribution plot")