Mercurial > repos > dfornika > mob_suite
comparison distance_matrix_phylip.py @ 19:115b462224cf draft
planemo upload for repository https://github.com/phac-nml/mob-suite commit 8898f2229ec13917b7d96e20725f3871d9d93e90-dirty
| author | dfornika |
|---|---|
| date | Fri, 28 Jun 2019 22:17:09 -0400 |
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| children |
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| 18:dce4f8d7b19f | 19:115b462224cf |
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| 1 #!/usr/bin/env python | |
| 2 | |
| 3 import argparse | |
| 4 import sys | |
| 5 import csv | |
| 6 import numpy as np | |
| 7 | |
| 8 from Bio.Phylo.TreeConstruction import DistanceMatrix, DistanceTreeConstructor | |
| 9 | |
| 10 | |
| 11 def process_input_matrix(input_matrix): | |
| 12 """ Converts an array-of-arrays containting sample IDs and distances | |
| 13 into a BioPython DistanceMatrix object | |
| 14 """ | |
| 15 input_matrix.pop(0) | |
| 16 sample_names = [row[0] for row in input_matrix] | |
| 17 for row in input_matrix: | |
| 18 row.pop(0) | |
| 19 distance_matrix = [] | |
| 20 for input_matrix_row in input_matrix: | |
| 21 distance_matrix.append([float(i) for i in input_matrix_row]) | |
| 22 """ np.tril() converts a matrix like this: [[0 1 2] | |
| 23 [1 0 1] | |
| 24 [2 1 0]] | |
| 25 ...into this: [[0 0 0] | |
| 26 [1 0 0] | |
| 27 [2 1 0]] | |
| 28 ...but what we need to pass to DistanceMatrix() is this: [[0] | |
| 29 [1 0] | |
| 30 [2 1 0]] | |
| 31 ...so that's what the (somewhat cryptic) code below does. | |
| 32 """ | |
| 33 distance_matrix = np.tril(np.array(distance_matrix)) | |
| 34 num_rows = distance_matrix.shape[0] | |
| 35 """ masking the distance matrix with tril_indices gives a linearized | |
| 36 distance matrix [0 1 0 2 1 0] that we need to re-construct | |
| 37 into [[0], [1, 0], [2, 1, 0]] | |
| 38 """ | |
| 39 lower_triangular_idx_mask = np.tril_indices(num_rows) | |
| 40 linear_distance_matrix = distance_matrix[lower_triangular_idx_mask] | |
| 41 distance_matrix = [] | |
| 42 min = 0 | |
| 43 max = 1 | |
| 44 for i in range(num_rows): | |
| 45 distance_matrix.append(linear_distance_matrix[min:max].tolist()) | |
| 46 min = max | |
| 47 max = max + (i + 2) | |
| 48 | |
| 49 distance_matrix = DistanceMatrix(names=sample_names, matrix=distance_matrix) | |
| 50 | |
| 51 return distance_matrix | |
| 52 | |
| 53 def main(): | |
| 54 parser = argparse.ArgumentParser() | |
| 55 parser.add_argument("--input", dest="input", help="") | |
| 56 args = parser.parse_args() | |
| 57 | |
| 58 reader = csv.reader(open(args.input, "r"), delimiter="\t") | |
| 59 input_matrix = list(reader) | |
| 60 # Don't build a tree with fewer than 3 samples, just produce an empty file | |
| 61 if len(input_matrix) < 4: | |
| 62 print('();') | |
| 63 sys.exit(0) | |
| 64 distance_matrix = process_input_matrix(input_matrix) | |
| 65 distance_matrix.format_phylip(sys.stdout) | |
| 66 | |
| 67 | |
| 68 if __name__ == '__main__': | |
| 69 main() |
