[clustering] type dispatching via explicit specialization

deeptime-ml · Oct 15, 2019 · 1a4327c · 1a4327c
1 parent 385c4b7
commit 1a4327c
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Showing 3 changed files with 6 additions and 4 deletions.
diff --git a/CMakeLists.txt b/CMakeLists.txt
@@ -1,6 +1,6 @@
 cmake_minimum_required(VERSION 3.9)
 
-set(CMAKE_CXX_STANDARD 17)
+set(CMAKE_CXX_STANDARD 14)
 
 if(DEFINED PROJECT_NAME)
     set(SKTIME_IS_SUBPROJECT ON)

diff --git a/sktime/clustering/include/bits/metric_base_bits.h b/sktime/clustering/include/bits/metric_base_bits.h
@@ -10,6 +10,11 @@
 #include <omp.h>
 #endif
 
+template<>
+inline float Metric::compute<float>(const float* xs, const float* ys, std::size_t dim) const {
+    return this->compute_f(xs, ys, dim);
+}
+
 template<typename T>
 inline py::array_t<int> assign_chunk_to_centers(const np_array<T>& chunk,
                                                 const np_array<T>& centers,

diff --git a/sktime/clustering/include/metric.h b/sktime/clustering/include/metric.h
@@ -24,9 +24,6 @@ class Metric {
     T compute(const T* xs, const T* ys, std::size_t dim) const {
         return compute_d(xs, ys, dim);
     }
-	float compute(const float* xs, const float* ys, std::size_t dim) const {
-		return compute_f(xs, ys, dim);
-	}
 };
 
 class EuclideanMetric : public Metric {