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Stabilize feature order in overzoom (#210)

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* Stabilize feature order in overzoom

* I want my sorts to be stable, please

* Revert "[ci] test in debug mode (#202)"

This reverts commit 853ada87b5.

* No need to reinitialize here
This commit is contained in:
Erica Fischer
2024-02-29 10:39:10 -08:00
committed by GitHub
parent d9a5c2eed7
commit 312e1560a3
14 changed files with 33 additions and 26 deletions
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tile.cpp
+8 -8
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@@ -426,7 +426,7 @@ static std::vector<serial_feature> disassemble_multiplier_clusters(std::vector<s
// sort the other features by their drop sequence, for consistency across zoom levels
if (cluster.size() > 1) {
std::sort(cluster.begin() + 1, cluster.end(), drop_sequence_cmp());
std::stable_sort(cluster.begin() + 1, cluster.end(), drop_sequence_cmp());
}
for (auto const &feature : cluster) {
@@ -814,7 +814,7 @@ static unsigned long long choose_mingap(std::vector<unsigned long long> const &i
// If there are no higher extents available, the tile has already been reduced as much as possible
// and tippecanoe will exit with an error.
static long long choose_minextent(std::vector<long long> &extents, double f, long long existing_extent) {
std::sort(extents.begin(), extents.end());
std::stable_sort(extents.begin(), extents.end());
size_t ix = (extents.size() - 1) * (1 - f);
while (ix + 1 < extents.size() && extents[ix] == existing_extent) {
@@ -829,7 +829,7 @@ static unsigned long long choose_mindrop_sequence(std::vector<unsigned long long
return ULLONG_MAX;
}
std::sort(drop_sequences.begin(), drop_sequences.end());
std::stable_sort(drop_sequences.begin(), drop_sequences.end());
size_t ix = (drop_sequences.size() - 1) * (1 - f);
while (ix + 1 < drop_sequences.size() && drop_sequences[ix] == existing_drop_sequence) {
@@ -2009,7 +2009,7 @@ long long write_tile(decompressor *geoms, std::atomic<long long> *geompos_in, ch
// Reorder and coalesce.
// Sort back into input order or by attribute value
std::sort(shared_nodes.begin(), shared_nodes.end());
std::stable_sort(shared_nodes.begin(), shared_nodes.end());
for (auto &kv : layers) {
std::string const &layername = kv.first;
@@ -2031,7 +2031,7 @@ long long write_tile(decompressor *geoms, std::atomic<long long> *geompos_in, ch
// these will be smaller numbers, and avoid the problem of the
// original sequence number varying based on how many reader threads
// there were reading the input
std::sort(feature_sequences.begin(), feature_sequences.end());
std::stable_sort(feature_sequences.begin(), feature_sequences.end());
for (size_t i = 0; i < feature_sequences.size(); i++) {
size_t j = feature_sequences[i].second;
serial_val sv(mvt_double, std::to_string(i));
@@ -2151,7 +2151,7 @@ long long write_tile(decompressor *geoms, std::atomic<long long> *geompos_in, ch
std::vector<serial_feature> &layer_features = features;
if (additional[A_REORDER]) {
std::sort(layer_features.begin(), layer_features.end(), coalindexcmp_comparator());
std::stable_sort(layer_features.begin(), layer_features.end(), coalindexcmp_comparator());
}
if (additional[A_COALESCE]) {
@@ -2215,13 +2215,13 @@ long long write_tile(decompressor *geoms, std::atomic<long long> *geompos_in, ch
if (prevent[P_INPUT_ORDER]) {
auto clustered = assemble_multiplier_clusters(layer_features);
std::sort(clustered.begin(), clustered.end(), preservecmp);
std::stable_sort(clustered.begin(), clustered.end(), preservecmp);
layer_features = disassemble_multiplier_clusters(clustered);
}
if (order_by.size() != 0) {
auto clustered = assemble_multiplier_clusters(layer_features);
std::sort(clustered.begin(), clustered.end(), ordercmp());
std::stable_sort(clustered.begin(), clustered.end(), ordercmp());
layer_features = disassemble_multiplier_clusters(clustered);
}