#!/usr/bin/env python3
#
# project.py
"""
Comparison between projects.
"""
#
# Copyright © 2024 Dominic Davis-Foster <dominic@davis-foster.co.uk>
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in all
# copies or substantial portions of the Software.
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# EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
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#
# 3rd party
import numpy
import pandas # type: ignore[import-untyped]
from pyms.DPA.Alignment import Alignment
# this package
from libgunshotmatch.project import Project
from libgunshotmatch.utils import create_alignment
# this package
from ._utils import _get_padded_peak_list, _PaddedPeakList
__all__ = ("filter_alignment_to_consolidate", "get_padded_peak_list")
[docs]def filter_alignment_to_consolidate(project: Project) -> Alignment:
"""
Filter peaks from a project's ``alignment`` to only those which survived the ``consolidate`` process.
:param project:
"""
assert project.consolidated_peaks is not None
# Sort expr_code and peakpos into order from datafile_data
desired_order = list(project.datafile_data)[::-1]
sort_map = [project.alignment.expr_code.index(code) for code in desired_order]
expr_code = [project.alignment.expr_code[idx] for idx in sort_map]
peakpos = [project.alignment.peakpos[idx] for idx in sort_map]
assert desired_order == expr_code
consolidated_peak_retention_times = []
for cp in project.consolidated_peaks:
consolidated_peak_retention_times.append([None if numpy.isnan(rt) else rt for rt in cp.rt_list])
aligned_peaks_surviving_consolidate = []
for aligned_peaks in zip(*peakpos):
aprt = [None if p is None else p.rt for p in reversed(aligned_peaks)]
if aprt in consolidated_peak_retention_times:
aligned_peaks_surviving_consolidate.append(aligned_peaks)
alignment_surviving_consolidate = list(zip(*aligned_peaks_surviving_consolidate))
# Sanity check
for c_expr_peaks, expr_peaks in zip(alignment_surviving_consolidate, peakpos):
for peak in c_expr_peaks:
assert peak in expr_peaks
# Create new Alignment object
return create_alignment(alignment_surviving_consolidate, expr_code)
[docs]def get_padded_peak_list(project: Project, alignment_rts: pandas.DataFrame) -> _PaddedPeakList:
"""
Returns a list of consolidated peaks for the project, based on the between-project alignment.
:param project:
:param alignment_rts: Pandas DataFrame giving retention times for the peak alignment.
The output of :meth:`~pyms.DPA.Alignment.Alignment.get_peak_alignment`.
"""
rts = [numpy.mean(row[1:]) for row in alignment_rts[list(project.datafile_data)].itertuples()]
return _get_padded_peak_list(project, rts)