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Diffstat (limited to 'cython/cython/reader_utils.pyx')
| -rw-r--r-- | cython/cython/reader_utils.pyx | 95 |
1 files changed, 0 insertions, 95 deletions
diff --git a/cython/cython/reader_utils.pyx b/cython/cython/reader_utils.pyx deleted file mode 100644 index e4572db0..00000000 --- a/cython/cython/reader_utils.pyx +++ /dev/null @@ -1,95 +0,0 @@ -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 [] |