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authorUlrich Bauer <mail@ulrich-bauer.org>2019-08-19 12:42:19 +0200
committerUlrich Bauer <mail@ulrich-bauer.org>2019-08-19 12:42:19 +0200
commit3fd98444e764f490752aac427011180c19e69e31 (patch)
tree257190b386c8974ba71e5a545503cce452e1121d
parenta304cb663b2e7e7680c15f8acf5aa36ad9bb9f15 (diff)
fixed size_t / index_t conversion warnings
-rw-r--r--ripser.cpp21
1 files changed, 10 insertions, 11 deletions
diff --git a/ripser.cpp b/ripser.cpp
index c1d4fb3..9418141 100644
--- a/ripser.cpp
+++ b/ripser.cpp
@@ -60,7 +60,6 @@ template <class Key, class T, class H, class E>
class hash_map : public google::dense_hash_map<Key, T, H, E> {
public:
explicit hash_map() : google::dense_hash_map<Key, T, H, E>() { this->set_empty_key(-1); }
-
inline void reserve(size_t hint) { this->resize(hint); }
};
#else
@@ -221,8 +220,8 @@ template <compressed_matrix_layout Layout> struct compressed_distance_matrix {
: distances(mat.size() * (mat.size() - 1) / 2), rows(mat.size()) {
init_rows();
- for (index_t i = 1; i < size(); ++i)
- for (index_t j = 0; j < i; ++j) rows[i][j] = mat(i, j);
+ for (size_t i = 1; i < size(); ++i)
+ for (size_t j = 0; j < i; ++j) rows[i][j] = mat(i, j);
}
value_t operator()(const index_t i, const index_t j) const;
@@ -235,7 +234,7 @@ typedef compressed_distance_matrix<UPPER_TRIANGULAR> compressed_upper_distance_m
template <> void compressed_lower_distance_matrix::init_rows() {
value_t* pointer = &distances[0];
- for (index_t i = 1; i < size(); ++i) {
+ for (size_t i = 1; i < size(); ++i) {
rows[i] = pointer;
pointer += i;
}
@@ -243,7 +242,7 @@ template <> void compressed_lower_distance_matrix::init_rows() {
template <> void compressed_upper_distance_matrix::init_rows() {
value_t* pointer = &distances[0] - 1;
- for (index_t i = 0; i < size() - 1; ++i) {
+ for (size_t i = 0; i < size() - 1; ++i) {
rows[i] = pointer;
pointer += size() - i - 2;
}
@@ -275,8 +274,8 @@ struct sparse_distance_matrix {
sparse_distance_matrix(const DistanceMatrix& mat, const value_t threshold)
: neighbors(mat.size()), num_edges(0) {
- for (index_t i = 0; i < size(); ++i)
- for (index_t j = 0; j < size(); ++j)
+ for (size_t i = 0; i < size(); ++i)
+ for (size_t j = 0; j < size(); ++j)
if (i != j && mat(i, j) <= threshold) {
++num_edges;
neighbors[i].push_back({j, mat(i, j)});
@@ -608,7 +607,7 @@ public:
#ifdef INDICATE_PROGRESS
std::chrono::steady_clock::time_point next = std::chrono::steady_clock::now() + time_step;
#endif
- for (index_t index_column_to_reduce = 0; index_column_to_reduce < columns_to_reduce.size();
+ for (size_t index_column_to_reduce = 0; index_column_to_reduce < columns_to_reduce.size();
++index_column_to_reduce) {
diameter_entry_t column_to_reduce(columns_to_reduce[index_column_to_reduce], 1);
@@ -889,7 +888,7 @@ sparse_distance_matrix read_sparse_distance_matrix(std::istream& input_stream) {
}
}
- for (index_t i = 0; i < neighbors.size(); ++i)
+ for (size_t i = 0; i < neighbors.size(); ++i)
std::sort(neighbors[i].begin(), neighbors[i].end());
return sparse_distance_matrix(std::move(neighbors), num_edges);
@@ -1097,9 +1096,9 @@ int main(int argc, char** argv) {
if (threshold == std::numeric_limits<value_t>::max()) {
value_t enclosing_radius = std::numeric_limits<value_t>::infinity();
- for (index_t i = 0; i < dist.size(); ++i) {
+ for (size_t i = 0; i < dist.size(); ++i) {
value_t r_i = -std::numeric_limits<value_t>::infinity();
- for (index_t j = 0; j < dist.size(); ++j) r_i = std::max(r_i, dist(i, j));
+ for (size_t j = 0; j < dist.size(); ++j) r_i = std::max(r_i, dist(i, j));
enclosing_radius = std::min(enclosing_radius, r_i);
}
threshold = enclosing_radius;