diff options
Diffstat (limited to 'src/Persistence_representations/include/gudhi/Persistence_landscape_on_grid.h')
-rw-r--r-- | src/Persistence_representations/include/gudhi/Persistence_landscape_on_grid.h | 192 |
1 files changed, 54 insertions, 138 deletions
diff --git a/src/Persistence_representations/include/gudhi/Persistence_landscape_on_grid.h b/src/Persistence_representations/include/gudhi/Persistence_landscape_on_grid.h index 5703163a..d663b543 100644 --- a/src/Persistence_representations/include/gudhi/Persistence_landscape_on_grid.h +++ b/src/Persistence_representations/include/gudhi/Persistence_landscape_on_grid.h @@ -4,7 +4,7 @@ * * Author(s): Pawel Dlotko * - * Copyright (C) 2015 INRIA (France) + * Copyright (C) 2017 INRIA (France) * * 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 @@ -21,8 +21,8 @@ * along with this program. If not, see <http://www.gnu.org/licenses/>. **/ -#ifndef Persistence_landscape_on_grid_H_ -#define Persistence_landscape_on_grid_H_ +#ifndef PERSISTENCE_LANDSCAPE_ON_GRID_H_ +#define PERSISTENCE_LANDSCAPE_ON_GRID_H_ //standard include @@ -50,16 +50,25 @@ namespace Gudhi namespace Persistence_representations { -//predeclaration +// pre declaration class Persistence_landscape_on_grid; template < typename operation > Persistence_landscape_on_grid operation_on_pair_of_landscapes_on_grid( const Persistence_landscape_on_grid& land1 , const Persistence_landscape_on_grid& land2 ); /** - * A clas implementing persistence landascpes by approximating them on a collection of grid points. * Persistence landscapes on grid allow vertorization, computations of distances, computations - * of projections to Real, computations of averages and scalar products. Therefore they implement suitable interfaces. - * It implements the following concepts: Vectorized_topological_data, Topological_data_with_distances, Real_valued_topological_data, Topological_data_with_averages, Topological_data_with_scalar_product - * Note that at the moment, due to roundoff errors during the construction of persistence landscapes on a grid, elements which are different by 0.000005 are considered the same. If the scale in your persistence diagrams + * \class Persistence_landscape_on_grid Persistence_landscape_on_grid.h gudhi/Persistence_landscape_on_grid.h + * \brief A class implementing persistence landscapes by approximating them on a collection of grid points. + * + * \ingroup Persistence_representations + * + * \details + * Persistence landscapes on grid allows vectorization, computations of distances, computations of projections to Real, + * computations of averages and scalar products. Therefore they implement suitable interfaces. + * It implements the following concepts: Vectorized_topological_data, Topological_data_with_distances, + * Real_valued_topological_data, Topological_data_with_averages, Topological_data_with_scalar_product + * + * Note that at the moment, due to rounding errors during the construction of persistence landscapes on a grid, + * elements which are different by 0.000005 are considered the same. If the scale in your persistence diagrams * is comparable to this value, please rescale them before use this code. **/ @@ -89,14 +98,14 @@ public: /** * Constructor that reads persistence intervals from file and creates persistence landscape. The format of the input file is the following: in each line we put birth-death pair. Last line is assumed - * to be empty. Even if the points within a line are not ordered, they will be ordered while the input is read. The additional parameters of this procedure are: ranges of grid, resoltion of a grid + * to be empty. Even if the points within a line are not ordered, they will be ordered while the input is read. The additional parameters of this procedure are: ranges of grid, resolution of a grid * number of landscape functions to be created and the dimension of intervals that are need to be read from a file (in case of Gudhi format files). **/ Persistence_landscape_on_grid(const char* filename , double grid_min_, double grid_max_ , size_t number_of_points_ , unsigned number_of_levels_of_landscape , unsigned short dimension_ = std::numeric_limits<unsigned short>::max() ); /** * Constructor that reads persistence intervals from file and creates persistence landscape. The format of the input file is the following: in each line we put birth-death pair. Last line is assumed - * to be empty. Even if the points within a line are not ordered, they will be ordered while the input is read. The additional parameters of this procedure are: ranges of grid, resoltion of a grid + * to be empty. Even if the points within a line are not ordered, they will be ordered while the input is read. The additional parameters of this procedure are: ranges of grid, resolution of a grid * and the dimension of intervals that are need to be read from a file (in case of Gudhi format files). **/ Persistence_landscape_on_grid(const char* filename , double grid_min_, double grid_max_ , size_t number_of_points_ , unsigned short dimension_ = std::numeric_limits<unsigned short>::max() ); @@ -104,16 +113,16 @@ public: /** * Constructor that reads persistence intervals from file and creates persistence landscape. The format of the input file is the following: in each line we put birth-death pair. Last line is assumed - * to be empty. Even if the points within a line are not ordered, they will be ordered while the input is read. The additional parameter is the resoution of a grid and the number of landscape - * functions to be created. The remaning parameters are calculated based on data. + * to be empty. Even if the points within a line are not ordered, they will be ordered while the input is read. The additional parameter is the resolution of a grid and the number of landscape + * functions to be created. The remaining parameters are calculated based on data. **/ Persistence_landscape_on_grid(const char* filename , size_t number_of_points , unsigned number_of_levels_of_landscape , unsigned short dimension = std::numeric_limits<unsigned short>::max() ); /** * Constructor that reads persistence intervals from file and creates persistence landscape. The format of the input file is the following: in each line we put birth-death pair. Last line is assumed - * to be empty. Even if the points within a line are not ordered, they will be ordered while the input is read. The additional parameter is the resoution of a grid. The last parameter is the dimension + * to be empty. Even if the points within a line are not ordered, they will be ordered while the input is read. The additional parameter is the resolution of a grid. The last parameter is the dimension * of a persistence to read from the file. If your file contains only persistence pair in a single dimension, please set it up to std::numeric_limits<unsigned>::max(). - * The remaning parameters are calculated based on data. + * The remaining parameters are calculated based on data. **/ Persistence_landscape_on_grid(const char* filename , size_t number_of_points , unsigned short dimension = std::numeric_limits<unsigned short>::max() ); @@ -258,7 +267,7 @@ public: if ( dbg ) { std::cerr << "Increasing result by : " << value_to_add << std::endl; - std::cerr << "restult : " << result << std::endl; + std::cerr << "result : " << result << std::endl; getchar(); } previous_x = current_x; @@ -311,9 +320,9 @@ public: std::cerr << "This is a procedure compute_value_at_a_given_point \n"; std::cerr << "level : " << level << std::endl; std::cerr << "x : " << x << std::endl; - std::cerr << "psoition : " << position << std::endl; + std::cerr << "position : " << position << std::endl; } - //check if we are not exacly in the grid point: + //check if we are not exactly in the grid point: if ( almost_equal( position*dx+ this->grid_min , x) ) { if ( this->values_of_landscapes[position].size() < level ) @@ -389,7 +398,7 @@ public: } /** - * An operator * that allows multipilication of a landscape by a real number. + * An operator * that allows multiplication of a landscape by a real number. **/ friend Persistence_landscape_on_grid operator*( const Persistence_landscape_on_grid& first , double con ) { @@ -397,7 +406,7 @@ public: } /** - * An operator * that allows multipilication of a landscape by a real number (order of parameters swapped). + * An operator * that allows multiplication of a landscape by a real number (order of parameters swapped). **/ friend Persistence_landscape_on_grid operator*( double con , const Persistence_landscape_on_grid& first ) { @@ -413,7 +422,7 @@ public: } /** - * Operator +=. The second parameter is persistnece landwscape. + * Operator +=. The second parameter is persistence landscape. **/ Persistence_landscape_on_grid operator += ( const Persistence_landscape_on_grid& rhs ) { @@ -422,7 +431,7 @@ public: } /** - * Operator -=. The second parameter is persistnece landwscape. + * Operator -=. The second parameter is persistence landscape. **/ Persistence_landscape_on_grid operator -= ( const Persistence_landscape_on_grid& rhs ) { @@ -458,7 +467,7 @@ public: bool dbg = true; if ( this->values_of_landscapes.size() != rhs.values_of_landscapes.size() ) { - if (dbg) std::cerr << "values_of_landscapes of incompatable sizes\n"; + if (dbg) std::cerr << "values_of_landscapes of incompatible sizes\n"; return false; } if ( !almost_equal( this->grid_min , rhs.grid_min ) ) @@ -546,28 +555,6 @@ public: std::pair< double , double > get_x_range( size_t level = 0 )const { return std::make_pair( this->grid_min , this->grid_max ); - //std::pair< double , double > result; - //if ( level < this->land.size() ) - //{ - // double dx = (this->grid_max - this->grid_min)/(double)this->values_of_landscapes.size(); - // size_t first_nonzero = 0; - // while ( (first_nonzero != this->values_of_landscapes.size()) && (this->values_of_landscapes[level][first_nonzero] == 0) )++first_nonzero; - // - // if ( first_nonzero == 0 ) - // { - // return std::make_pair( 0,0 );//this landscape is empty. - // } - // - // size_t last_nonzero = 0; - // while ( (last_nonzero != 0) && (this->values_of_landscapes[level][last_nonzero] == 0) )--last_nonzero; - // - // result = std::make_pair( this->grid_min +first_nonzero*dx , this->grid_max - last_nonzero*dx ); - //} - //else - //{ - // result = std::make_pair( 0,0 ); - //} - //return result; } /** @@ -577,16 +564,6 @@ public: std::pair< double , double > get_y_range( size_t level = 0 )const { return this->compute_minimum_maximum(); - //std::pair< double , double > result; - //if ( level < this->land.size() ) - //{ - // result = this->compute_minimum_maximum() - //} - //else - //{ - // result = std::make_pair( 0,0 ); - //} - //return result; } /** @@ -629,13 +606,11 @@ public: * Computations of \f$L^{\infty}\f$ distance between two landscapes. **/ friend double compute_max_norm_distance_of_landscapes( const Persistence_landscape_on_grid& first, const Persistence_landscape_on_grid& second ); - //friend double compute_max_norm_distance_of_landscapes( const Persistence_landscape_on_grid& first, const Persistence_landscape_on_grid& second , unsigned& nrOfLand , double&x , double& y1, double& y2 ); - /** - * Function to compute absolute value of a PL function. The representation of persistence landscapes allow to store general PL-function. When computing distance betwen two landscapes, we compute difference between + * Function to compute absolute value of a PL function. The representation of persistence landscapes allow to store general PL-function. When computing distance between two landscapes, we compute difference between * them. In this case, a general PL-function with negative value can appear as a result. Then in order to compute distance, we need to take its absolute value. This is the purpose of this procedure. **/ void abs() @@ -655,7 +630,7 @@ public: size_t size()const{return this->number_of_nonzero_levels(); } /** - * Computate maximal value of lambda-level landscape. + * Compute maximal value of lambda-level landscape. **/ double find_max( unsigned lambda )const { @@ -742,14 +717,14 @@ public: } //now, to compute the inner product in this interval we need to compute the integral of (ax+b)(cx+d) = acx^2 + (ad+bc)x + bd in the interval from previous_x to current_x: - //The integal is ac/3*x^3 + (ac+bd)/2*x^2 + bd*x + //The integral is ac/3*x^3 + (ac+bd)/2*x^2 + bd*x double added_value = (a*c/3*current_x*current_x*current_x + (a*d+b*c)/2*current_x*current_x + b*d*current_x)- (a*c/3*previous_x*previous_x*previous_x + (a*d+b*c)/2*previous_x*previous_x + b*d*previous_x); if ( dbg ) { - std::cerr << "Value of the integral on the left end ie : " << previous_x << " is : " << a*c/3*previous_x*previous_x*previous_x + (a*d+b*c)/2*previous_x*previous_x + b*d*previous_x << std::endl; + std::cerr << "Value of the integral on the left end i.e. : " << previous_x << " is : " << a*c/3*previous_x*previous_x*previous_x + (a*d+b*c)/2*previous_x*previous_x + b*d*previous_x << std::endl; std::cerr << "Value of the integral on the right end i.e. : " << current_x << " is " << a*c/3*current_x*current_x*current_x + (a*d+b*c)/2*current_x*current_x + b*d*current_x << std::endl; } @@ -775,7 +750,7 @@ public: /** * Computations of \f$L^{p}\f$ distance between two landscapes on a grid. p is the parameter of the procedure. * FIXME: Note that, due to the grid representation, the method below may give non--accurate results in case when the landscape P and Q the difference of which we want to compute - * are interxsecting. This is a consequence of a general way they are computed. In the future, an integral of absolute value of a difference of P and Q will be given as a separated + * are intersecting. This is a consequence of a general way they are computed. In the future, an integral of absolute value of a difference of P and Q will be given as a separated * function to fix that inaccuracy. **/ friend double compute_distance_of_landscapes_on_grid( const Persistence_landscape_on_grid& first, const Persistence_landscape_on_grid& second , double p ) @@ -819,7 +794,7 @@ public: else { result = lan.compute_integral_of_landscape(); - if (dbg){std::cerr << "integral, wihtout power : " << result << std::endl;getchar();} + if (dbg){std::cerr << "integral, without power : " << result << std::endl;getchar();} } //(\int_{- \infty}^{+\infty}| first-second |^p)^(1/p) return pow( result , 1/(double)p ); @@ -830,45 +805,14 @@ public: return lan.compute_maximum(); } } - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - //Functions that are needed for that class to implement the concept. /** * The number of projections to R is defined to the number of nonzero landscape functions. I-th projection is an integral of i-th landscape function over whole R. * This function is required by the Real_valued_topological_data concept. - * At the moment this function is not tested, since it is quite likelly to be changed in the future. Given this, when using it, keep in mind that it - * will be most likelly changed in the next versions. + * At the moment this function is not tested, since it is quite likely to be changed in the future. Given this, when using it, keep in mind that it + * will be most likely changed in the next versions. **/ double project_to_R( int number_of_function )const { @@ -884,8 +828,6 @@ public: } - - /** * This function produce a vector of doubles based on a landscape. It is required in a concept Vectorized_topological_data */ @@ -909,16 +851,13 @@ public: } /** - * This function return the number of functions that allows vectorization of persistence laandscape. It is required in a concept Vectorized_topological_data. + * This function return the number of functions that allows vectorization of persistence landscape. It is required in a concept Vectorized_topological_data. **/ size_t number_of_vectorize_functions()const { return number_of_functions_for_vectorization; } - - - /** * A function to compute averaged persistence landscape on a grid, based on vector of persistence landscapes on grid. @@ -932,7 +871,7 @@ public: this->values_of_landscapes .clear(); this->grid_min = this->grid_max = 0; - //if there is nothing to averate, then the average is a zero landscape. + //if there is nothing to average, then the average is a zero landscape. if ( to_average.size() == 0 )return; //now we need to check if the grids in all objects of to_average are the same: @@ -968,7 +907,7 @@ public: std::cerr << "We are considering the point : " << grid_point << " of the grid. In this point, there are at most : " << maximal_size_of_vector << " nonzero landscape functions \n"; } - //and compute an arythmetic average: + //and compute an arithmetic average: for ( size_t land_no = 0 ; land_no != to_average.size() ; ++land_no ) { //summing: @@ -989,7 +928,7 @@ public: /** * A function to compute distance between persistence landscape on a grid. - * The parameter of this functionis a Persistence_landscape_on_grid. + * The parameter of this function is a Persistence_landscape_on_grid. * This function is required in Topological_data_with_distances concept. * For max norm distance, set power to std::numeric_limits<double>::max() **/ @@ -1007,7 +946,7 @@ public: /** * A function to compute scalar product of persistence landscape on a grid. - * The parameter of this functionis a Persistence_landscape_on_grid. + * The parameter of this function is a Persistence_landscape_on_grid. * This function is required in Topological_data_with_scalar_product concept. **/ double compute_scalar_product( const Persistence_landscape_on_grid& second ) @@ -1016,28 +955,9 @@ public: } //end of implementation of functions needed for concepts. - - - - - - - - - - - - - - - - - - - /** - * A function that returns values of landsapes. It can be used for vizualization + * A function that returns values of landscapes. It can be used for visualization **/ std::vector< std::vector< double > > output_for_visualization()const { @@ -1046,7 +966,7 @@ public: /** * function used to create a gnuplot script for visualization of landscapes. Over here we need to specify which landscapes do we want to plot. - * In addition, the user may specify the range (min and max) where landscape is plot. The fefault values for min and max are std::numeric_limits<double>::max(). If the procedure detect those + * In addition, the user may specify the range (min and max) where landscape is plot. The default values for min and max are std::numeric_limits<double>::max(). If the procedure detect those * values, it will determine the range so that the whole landscape is supported there. If at least one min or max value is different from std::numeric_limits<double>::max(), then the values * provided by the user will be used. **/ @@ -1123,7 +1043,7 @@ void Persistence_landscape_on_grid::set_up_values_of_landscapes( const std::vect if ( grid_max_ <= grid_min_ ) { - throw "Wrong parameters of grid_min and grid_max given to the procedure. THe grid have negative, or zero size. The program will now terminate.\n"; + throw "Wrong parameters of grid_min and grid_max given to the procedure. The grid have negative, or zero size. The program will now terminate.\n"; } double dx = ( grid_max_ - grid_min_ )/(double)(number_of_points_); @@ -1174,7 +1094,7 @@ void Persistence_landscape_on_grid::set_up_values_of_landscapes( const std::vect if ( this->values_of_landscapes[i].size() == number_of_levels-1 ) { //this->values_of_landscapes[i].size() == number_of_levels - //in this case we need to create the heep. + //in this case we need to create the heap. std::make_heap (this->values_of_landscapes[i].begin(),this->values_of_landscapes[i].end()); } } @@ -1212,7 +1132,7 @@ void Persistence_landscape_on_grid::set_up_values_of_landscapes( const std::vect if ( this->values_of_landscapes[i].size() == number_of_levels-1 ) { //this->values_of_landscapes[i].size() == number_of_levels - //in this case we need to create the heep. + //in this case we need to create the heap. std::make_heap (this->values_of_landscapes[i].begin(),this->values_of_landscapes[i].end()); } } @@ -1225,7 +1145,7 @@ void Persistence_landscape_on_grid::set_up_values_of_landscapes( const std::vect if ( dbg ) { - std::cerr << "AAdding landscape value (going down) for a point : " << i << " equal : " << landscape_value << std::endl; + std::cerr << "Adding landscape value (going down) for a point : " << i << " equal : " << landscape_value << std::endl; } } landscape_value -= dx; @@ -1235,11 +1155,10 @@ void Persistence_landscape_on_grid::set_up_values_of_landscapes( const std::vect if ( number_of_levels != std::numeric_limits< unsigned >::max() ) { //in this case, vectors are used as heaps. And, since we want to have the smallest element at the top of - //each heap, we store mminus distances. To get if right at the end, we need to multiply each value + //each heap, we store minus distances. To get if right at the end, we need to multiply each value //in the heap by -1 to get real vector of distances. for ( size_t pt = 0 ; pt != this->values_of_landscapes.size() ; ++pt ) { - //std::cerr << this->values_of_landscapes[pt].size() <<std::endl; for ( size_t j = 0 ; j != this->values_of_landscapes[pt].size() ; ++j ) { this->values_of_landscapes[pt][j] *= -1; @@ -1362,7 +1281,6 @@ void Persistence_landscape_on_grid::load_landscape_from_file( const char* filena //read a line of a file and convert it to a vector. std::vector< double > vv; std::getline(in, line); - //std::cerr << "Reading line : " << line << std::endl;getchar(); std::istringstream stream(line); while (stream >> number) { @@ -1485,7 +1403,7 @@ Persistence_landscape_on_grid operation_on_pair_of_landscapes_on_grid ( const Pe result.grid_min = land1.grid_min; result.grid_max = land1.grid_max; - //now we perorm the operations: + //now we perform the operations: for ( size_t grid_point = 0 ; grid_point != land1.values_of_landscapes.size() ; ++grid_point ) { result.values_of_landscapes[grid_point] = std::vector< double >( std::max( land1.values_of_landscapes[grid_point].size() , land2.values_of_landscapes[grid_point].size() ) ); @@ -1555,9 +1473,7 @@ double compute_max_norm_distance_of_landscapes( const Persistence_landscape_on_g return result; } - - -}//namespace Gudhi_stat +}//namespace Persistence_representations }//namespace Gudhi -#endif +#endif // PERSISTENCE_LANDSCAPE_ON_GRID_H_ |