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/* This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT.
* See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details.
* Author(s): Marc Glisse
*
* Copyright (C) 2020 Inria
*
* Modification(s):
* - YYYY/MM Author: Description of the modification
*/
#include <pybind11/pybind11.h>
#include <pybind11/numpy.h>
#include <boost/range/counting_range.hpp>
#include <boost/range/adaptor/transformed.hpp>
#include <wasserstein.h> // Hera
#include <utility>
namespace py = pybind11;
typedef py::array_t<double> Dgm;
// Get m[i,0] and m[i,1] as a pair
static auto pairify(void* p, ssize_t h, ssize_t w) {
return [=](ssize_t i){
char* birth = (char*)p + i * h;
char* death = birth + w;
return std::make_pair(*(double*)birth, *(double*)death);
};
}
inline auto numpy_to_range_of_pairs(py::array_t<double> dgm) {
py::buffer_info buf = dgm.request();
// shape (n,2) or (0) for empty
if((buf.ndim!=2 || buf.shape[1]!=2) && (buf.ndim!=1 || buf.shape[0]!=0))
throw std::runtime_error("Diagram must be an array of size n x 2");
// In the case of shape (0), avoid reading non-existing strides[1] even if we won't use it.
ssize_t stride1 = buf.ndim == 2 ? buf.strides[1] : 0;
auto cnt = boost::counting_range<ssize_t>(0, buf.shape[0]);
return boost::adaptors::transform(cnt, pairify(buf.ptr, buf.strides[0], stride1));
// Be careful that the returned range cannot contain references to dead temporaries.
}
double wasserstein_distance(
Dgm d1, Dgm d2,
double wasserstein_power, double internal_p,
double delta)
{
// I *think* the call to request() has to be before releasing the GIL.
auto diag1 = numpy_to_range_of_pairs(d1);
auto diag2 = numpy_to_range_of_pairs(d2);
py::gil_scoped_release release;
hera::AuctionParams<double> params;
params.wasserstein_power = wasserstein_power;
// hera encodes infinity as -1...
if(std::isinf(internal_p)) internal_p = hera::get_infinity<double>();
params.internal_p = internal_p;
params.delta = delta;
// The extra parameters are purposedly not exposed for now.
return hera::wasserstein_dist(diag1, diag2, params);
}
PYBIND11_MODULE(hera, m) {
m.def("wasserstein_distance", &wasserstein_distance,
py::arg("X"), py::arg("Y"),
py::arg("order") = 1,
py::arg("internal_p") = std::numeric_limits<double>::infinity(),
py::arg("delta") = .01,
R"pbdoc(
Compute the Wasserstein distance between two diagrams.
Points at infinity are supported.
Parameters:
X (n x 2 numpy array): First diagram
Y (n x 2 numpy array): Second diagram
order (float): Wasserstein exponent W_q
internal_p (float): Internal Minkowski norm L^p in R^2
delta (float): Relative error 1+delta
Returns:
float: Approximate Wasserstein distance W_q(X,Y)
)pbdoc");
}
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