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from cython cimport numeric
from libcpp.vector cimport vector
from libcpp.string cimport string
from libcpp.map cimport map
from libcpp.pair cimport pair
from os import path
from numpy import array as np_array
"""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) 2019 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 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 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 of persistence_file might contain 2, 3 or 4 values:
[[field] dimension] birth death
Note: the function does not check that birth <= death.
:param persistence_file: A persistence file style name.
:type persistence_file: string
:param only_this_dim: The specific dimension. Default value is -1.
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.
:type only_this_dim: int.
:returns: The persistence intervals.
:rtype: numpy array of dimension 2
"""
if persistence_file is not '':
if path.isfile(persistence_file):
return np_array(read_pers_intervals_in_dimension(str.encode(
persistence_file), only_this_dim))
print("file " + persistence_file + " not set or not found.")
return []
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