3 files changed, 123 insertions, 0 deletions
diff --git a/src/python/gudhi/hera/__init__.py b/src/python/gudhi/hera/__init__.py
new file mode 100644
index 00000000..f70b92b9
--- /dev/null
+++ b/src/python/gudhi/hera/__init__.py
@@ -0,0 +1,7 @@
+from .wasserstein import wasserstein_distance
+from .bottleneck import bottleneck_distance
+
+
+__author__ = "Marc Glisse"
+__copyright__ = "Copyright (C) 2020 Inria"
+__license__ = "MIT"
diff --git a/src/python/gudhi/hera/bottleneck.cc b/src/python/gudhi/hera/bottleneck.cc
new file mode 100644
index 00000000..ec461f7c
--- /dev/null
+++ b/src/python/gudhi/hera/bottleneck.cc
@@ -0,0 +1,54 @@
+/*    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_diagram_utils.h>
+
+#ifdef _MSC_VER
+// https://github.com/grey-narn/hera/issues/3
+// ssize_t is a non-standard type (well, posix)
+using py::ssize_t;
+#endif
+
+#include <hera/bottleneck.h> // Hera
+
+double bottleneck_distance(Dgm d1, Dgm d2, 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;
+
+  if (delta == 0)
+    return hera::bottleneckDistExact(diag1, diag2);
+  else
+    return hera::bottleneckDistApprox(diag1, diag2, delta);
+}
+
+PYBIND11_MODULE(bottleneck, m) {
+      m.def("bottleneck_distance", &bottleneck_distance,
+          py::arg("X"), py::arg("Y"),
+          py::arg("delta") = .01,
+          R"pbdoc(
+        Compute the Bottleneck distance between two diagrams.
+        Points at infinity are supported.
+
+        .. note::
+           Points on the diagonal are not supported and must be filtered out before calling this function.
+
+        Parameters:
+            X (n x 2 numpy array): First diagram
+            Y (n x 2 numpy array): Second diagram
+            delta (float): Relative error 1+delta
+
+        Returns:
+            float: (approximate) bottleneck distance d_B(X,Y)
+    )pbdoc");
+}
diff --git a/src/python/gudhi/hera/wasserstein.cc b/src/python/gudhi/hera/wasserstein.cc
new file mode 100644
index 00000000..3516352e
--- /dev/null
+++ b/src/python/gudhi/hera/wasserstein.cc
@@ -0,0 +1,62 @@
+/*    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_diagram_utils.h>
+
+#ifdef _MSC_VER
+// https://github.com/grey-narn/hera/issues/3
+// ssize_t is a non-standard type (well, posix)
+using py::ssize_t;
+#endif
+
+#include <hera/wasserstein.h> // Hera
+
+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 purposely not exposed for now.
+  return hera::wasserstein_dist(diag1, diag2, params);
+}
+
+PYBIND11_MODULE(wasserstein, 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");
+}