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Diffstat (limited to 'cython/cython/reader_utils.pyx')
-rw-r--r-- | cython/cython/reader_utils.pyx | 95 |
1 files changed, 95 insertions, 0 deletions
diff --git a/cython/cython/reader_utils.pyx b/cython/cython/reader_utils.pyx new file mode 100644 index 00000000..3a17c5a0 --- /dev/null +++ b/cython/cython/reader_utils.pyx @@ -0,0 +1,95 @@ +from cython cimport numeric +from libcpp.vector cimport vector +from libcpp.string cimport string +from libcpp.map cimport map +from libcpp.pair cimport pair +import os + +"""This file is part of the Gudhi Library. The Gudhi library + (Geometric Understanding in Higher Dimensions) is a generic C++ + library for computational topology. + + Author(s): Vincent Rouvreau + + Copyright (C) 2017 INRIA + + This program is free software: you can redistribute it and/or modify + it under the terms of the GNU General Public License as published by + the Free Software Foundation, either version 3 of the License, or + (at your option) any later version. + + This program is distributed in the hope that it will be useful, + but WITHOUT ANY WARRANTY; without even the implied warranty of + MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the + GNU General Public License for more details. + + You should have received a copy of the GNU General Public License + along with this program. If not, see <http://www.gnu.org/licenses/>. +""" + +__author__ = "Vincent Rouvreau" +__copyright__ = "Copyright (C) 2017 INRIA" +__license__ = "GPL v3" + +cdef extern from "Reader_utils_interface.h" namespace "Gudhi": + vector[vector[double]] read_matrix_from_csv_file(string off_file, char separator) + map[int, vector[pair[double, double]]] read_pers_intervals_grouped_by_dimension(string filename) + vector[pair[double, double]] read_pers_intervals_in_dimension(string filename, int only_this_dim) + +def read_lower_triangular_matrix_from_csv_file(csv_file='', separator=';'): + """Read lower triangular matrix from a CSV style file. + + :param csv_file: A CSV file style name. + :type csv_file: string + :param separator: The value separator in the CSV file. Default value is ';' + :type separator: char + + :returns: The lower triangular matrix. + :rtype: vector[vector[double]] + """ + if csv_file is not '': + if os.path.isfile(csv_file): + return read_matrix_from_csv_file(str.encode(csv_file), ord(separator[0])) + print("file " + csv_file + " not set or not found.") + return [] + +def read_persistence_intervals_grouped_by_dimension(persistence_file=''): + """Reads a file containing persistence intervals. + Each line might contain 2, 3 or 4 values: [[field] dimension] birth death + The return value is an `map[dim, vector[pair[birth, death]]]` + where `dim` is an `int`, `birth` a `double`, and `death` a `double`. + Note: the function does not check that birth <= death. + + :param persistence_file: A persistence file style name. + :type persistence_file: string + + :returns: The persistence pairs grouped by dimension. + :rtype: map[int, vector[pair[double, double]]] + """ + if persistence_file is not '': + if os.path.isfile(persistence_file): + return read_pers_intervals_grouped_by_dimension(str.encode(persistence_file)) + print("file " + persistence_file + " not set or not found.") + return [] + +def read_persistence_intervals_in_dimension(persistence_file='', only_this_dim=-1): + """Reads a file containing persistence intervals. + Each line might contain 2, 3 or 4 values: [[field] dimension] birth death + If `only_this_dim` = -1, dimension is ignored and all lines are returned. + If `only_this_dim` is >= 0, only the lines where dimension = `only_this_dim` + (or where dimension is not specified) are returned. + The return value is an `vector[pair[birth, death]]` + where `birth` a `double`, and `death` a `double`. + Note: the function does not check that birth <= death. + + :param persistence_file: A persistence file style name. + :type persistence_file: string + + :returns: The persistence pairs grouped by dimension. + :rtype: map[int, vector[pair[double, double]]] + """ + if persistence_file is not '': + if os.path.isfile(persistence_file): + return read_pers_intervals_in_dimension(str.encode(persistence_file), only_this_dim) + print("file " + persistence_file + " not set or not found.") + return [] |