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-rw-r--r--src/Persistence_representations/example/persistence_landscape_on_grid.cpp22
1 files changed, 11 insertions, 11 deletions
diff --git a/src/Persistence_representations/example/persistence_landscape_on_grid.cpp b/src/Persistence_representations/example/persistence_landscape_on_grid.cpp
index 16a58e1d..6d58e167 100644
--- a/src/Persistence_representations/example/persistence_landscape_on_grid.cpp
+++ b/src/Persistence_representations/example/persistence_landscape_on_grid.cpp
@@ -37,31 +37,31 @@ int main(int argc, char** argv) {
Persistence_landscape_on_grid l2(persistence2, 0, 11, 20);
// This is how to compute integral of landscapes:
- std::cout << "Integral of the first landscape : " << l1.compute_integral_of_landscape() << std::endl;
- std::cout << "Integral of the second landscape : " << l2.compute_integral_of_landscape() << std::endl;
+ std::clog << "Integral of the first landscape : " << l1.compute_integral_of_landscape() << std::endl;
+ std::clog << "Integral of the second landscape : " << l2.compute_integral_of_landscape() << std::endl;
// And here how to write landscapes to stream:
- std::cout << "l1 : " << l1 << std::endl;
- std::cout << "l2 : " << l2 << std::endl;
+ std::clog << "l1 : " << l1 << std::endl;
+ std::clog << "l2 : " << l2 << std::endl;
// here are the maxima of the functions:
- std::cout << "Maximum of l1 : " << l1.compute_maximum() << std::endl;
- std::cout << "Maximum of l2 : " << l2.compute_maximum() << std::endl;
+ std::clog << "Maximum of l1 : " << l1.compute_maximum() << std::endl;
+ std::clog << "Maximum of l2 : " << l2.compute_maximum() << std::endl;
// here are the norms of landscapes:
- std::cout << "L^1 Norm of l1 : " << l1.compute_norm_of_landscape(1.) << std::endl;
- std::cout << "L^1 Norm of l2 : " << l2.compute_norm_of_landscape(1.) << std::endl;
+ std::clog << "L^1 Norm of l1 : " << l1.compute_norm_of_landscape(1.) << std::endl;
+ std::clog << "L^1 Norm of l2 : " << l2.compute_norm_of_landscape(1.) << std::endl;
// here is the average of landscapes:
Persistence_landscape_on_grid average;
average.compute_average({&l1, &l2});
- std::cout << "average : " << average << std::endl;
+ std::clog << "average : " << average << std::endl;
// here is the distance of landscapes:
- std::cout << "Distance : " << l1.distance(l2) << std::endl;
+ std::clog << "Distance : " << l1.distance(l2) << std::endl;
// here is the scalar product of landscapes:
- std::cout << "Scalar product : " << l1.compute_scalar_product(l2) << std::endl;
+ std::clog << "Scalar product : " << l1.compute_scalar_product(l2) << std::endl;
// here is how to create a file which is suitable for visualization via gnuplot:
average.plot("average_landscape");