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Diffstat (limited to 'src/python/example/rips_complex_diagram_persistence_from_correlation_matrix_file_example.py')
-rwxr-xr-x | src/python/example/rips_complex_diagram_persistence_from_correlation_matrix_file_example.py | 87 |
1 files changed, 87 insertions, 0 deletions
diff --git a/src/python/example/rips_complex_diagram_persistence_from_correlation_matrix_file_example.py b/src/python/example/rips_complex_diagram_persistence_from_correlation_matrix_file_example.py new file mode 100755 index 00000000..3571580b --- /dev/null +++ b/src/python/example/rips_complex_diagram_persistence_from_correlation_matrix_file_example.py @@ -0,0 +1,87 @@ +#!/usr/bin/env python + +import gudhi +import sys +import argparse + +""" This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT. + See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details. + Author(s): Vincent Rouvreau + + Copyright (C) 2017 Inria + + Modification(s): + - YYYY/MM Author: Description of the modification +""" + +__author__ = "Vincent Rouvreau" +__copyright__ = "Copyright (C) 2017 Inria" +__license__ = "MIT" + +parser = argparse.ArgumentParser( + description="RipsComplex creation from " "a correlation matrix read in a csv file.", + epilog="Example: " + "example/rips_complex_diagram_persistence_from_correlation_matrix_file_example.py " + "-f ../data/correlation_matrix/lower_triangular_correlation_matrix.csv -e 12.0 -d 3" + "- Constructs a Rips complex with the " + "correlation matrix from the given csv file.", +) +parser.add_argument("-f", "--file", type=str, required=True) +parser.add_argument("-c", "--min_edge_correlation", type=float, default=0.5) +parser.add_argument("-d", "--max_dimension", type=int, default=1) +parser.add_argument("-b", "--band", type=float, default=0.0) +parser.add_argument( + "--no-diagram", + default=False, + action="store_true", + help="Flag for not to display the diagrams", +) + +args = parser.parse_args() + +if not (-1.0 < args.min_edge_correlation < 1.0): + print("Wrong value of the treshold corelation (should be between -1 and 1).") + sys.exit(1) + +print("#####################################################################") +print("Caution: as persistence diagrams points will be under the diagonal,") +print("bottleneck distance and persistence graphical tool will not work") +print("properly, this is a known issue.") + +print("#####################################################################") +print("RipsComplex creation from correlation matrix read in a csv file") + +message = "RipsComplex with min_edge_correlation=" + repr(args.min_edge_correlation) +print(message) + +correlation_matrix = gudhi.read_lower_triangular_matrix_from_csv_file( + csv_file=args.file +) +# Given a correlation matrix M, we compute component-wise M'[i,j] = 1-M[i,j] to get a distance matrix: +distance_matrix = [ + [1.0 - correlation_matrix[i][j] for j in range(len(correlation_matrix[i]))] + for i in range(len(correlation_matrix)) +] + +rips_complex = gudhi.RipsComplex( + distance_matrix=distance_matrix, max_edge_length=1.0 - args.min_edge_correlation +) +simplex_tree = rips_complex.create_simplex_tree(max_dimension=args.max_dimension) + +message = "Number of simplices=" + repr(simplex_tree.num_simplices()) +print(message) + +diag = simplex_tree.persistence() + +print("betti_numbers()=") +print(simplex_tree.betti_numbers()) + +# invert the persistence diagram +invert_diag = [ + (diag[pers][0], (1.0 - diag[pers][1][0], 1.0 - diag[pers][1][1])) + for pers in range(len(diag)) +] + +if args.no_diagram == False: + pplot = gudhi.plot_persistence_diagram(invert_diag, band=args.band) + pplot.show() |