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Make feature ordering cooperate with --retain-points-multiplier (#188)

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* Make feature ordering cooperate with --retain-points-multiplier

* Forgot to check in the actual code changes???

* Sort within each multiplier cluster as well as between clusters

* Correct description of behavior in changelog

* Drag original feature sequence along in megatiles for post-filter sort

* Plumb the preserve-input-order flag through overzoom

* Sort in overzoom if requested

* Use within-tile input sequence numbers, not global sequence numbers

* Documentation

* Reverse direction of search to prevent accidental skipping

* Add some comments about converting between attribute representations
This commit is contained in:
Erica Fischer
2024-01-21 12:09:05 -08:00
committed by GitHub
parent 5d92a17193
commit 679a0d62f2
23 changed files with 41781 additions and 41134 deletions
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tile.cpp
+108 -3
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@@ -111,7 +111,11 @@ struct coalesce {
}
};
struct preservecmp {
static struct preservecmp {
bool operator()(const std::vector<struct coalesce> &a, const std::vector<struct coalesce> &b) {
return operator()(a[0], b[0]);
}
bool operator()(const struct coalesce &a, const struct coalesce &b) {
return a.original_seq < b.original_seq;
}
@@ -303,6 +307,10 @@ static mvt_value coerce_double(mvt_value v) {
}
struct ordercmp {
bool operator()(const std::vector<struct coalesce> &a, const std::vector<struct coalesce> &b) {
return operator()(a[0], b[0]);
}
bool operator()(const struct coalesce &a, const struct coalesce &b) {
for (size_t i = 0; i < order_by.size(); i++) {
mvt_value v1 = coerce_double(find_attribute_value(&a, order_by[i].name));
@@ -331,6 +339,66 @@ struct ordercmp {
}
} ordercmp;
std::vector<std::vector<coalesce>> assemble_multiplier_clusters(std::vector<coalesce> &features) {
std::vector<std::vector<coalesce>> clusters;
if (retain_points_multiplier == 1) {
for (auto const &feature : features) {
std::vector<coalesce> cluster;
cluster.push_back(feature);
clusters.push_back(cluster);
}
} else {
for (auto const &feature : features) {
bool is_cluster_start = false;
for (size_t i = 0; i < feature.full_keys.size(); i++) {
if (feature.full_keys[i] == "tippecanoe:retain_points_multiplier_first") {
is_cluster_start = true;
break;
}
}
if (is_cluster_start) {
clusters.push_back(std::vector<coalesce>());
}
clusters.back().push_back(feature);
}
}
return clusters;
}
std::vector<coalesce> disassemble_multiplier_clusters(std::vector<std::vector<coalesce>> &clusters) {
std::vector<coalesce> out;
for (auto &cluster : clusters) {
// fix up the attributes so the first feature of the multiplier cluster
// gets the marker attribute
for (size_t i = 0; i < cluster.size(); i++) {
for (size_t j = 0; j < cluster[i].full_keys.size(); j++) {
if (cluster[i].full_keys[j] == "tippecanoe:retain_points_multiplier_first") {
cluster[0].full_keys.push_back(cluster[i].full_keys[j]);
cluster[0].full_values.push_back(cluster[i].full_values[j]);
cluster[i].full_keys.erase(cluster[i].full_keys.begin() + j);
cluster[i].full_values.erase(cluster[i].full_values.begin() + j);
i = cluster.size(); // break outer
break;
}
}
}
for (auto const &feature : cluster) {
out.push_back(feature);
}
}
return out;
}
void rewrite(drawvec &geom, int z, int nextzoom, int maxzoom, long long *bbox, unsigned tx, unsigned ty, int buffer, int *within, std::atomic<long long> *geompos, compressor **geomfile, const char *fname, signed char t, int layer, signed char feature_minzoom, int child_shards, int max_zoom_increment, long long seq, int tippecanoe_minzoom, int tippecanoe_maxzoom, int segment, unsigned *initial_x, unsigned *initial_y, std::vector<long long> &metakeys, std::vector<long long> &metavals, bool has_id, unsigned long long id, unsigned long long index, unsigned long long label_point, long long extent) {
if (geom.size() > 0 && (nextzoom <= maxzoom || additional[A_EXTEND_ZOOMS] || extend_zooms_max > 0)) {
int xo, yo;
@@ -2379,6 +2447,33 @@ long long write_tile(decompressor *geoms, std::atomic<long long> *geompos_in, ch
coalesced_area = 0;
}
if (retain_points_multiplier > 1) {
// mapping from input sequence to current sequence within this tile
std::vector<std::pair<size_t, size_t>> feature_sequences;
for (size_t i = 0; i < partials.size(); i++) {
feature_sequences.emplace_back(partials[i].original_seq, i);
}
// tag each feature with its sequence number within the tile
// if the tile were sorted by input order
//
// 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());
for (size_t i = 0; i < feature_sequences.size(); i++) {
size_t j = feature_sequences[i].second;
serial_val val;
val.type = mvt_double;
val.s = std::to_string(i);
partials[j].full_keys.push_back("tippecanoe:retain_points_multiplier_sequence");
partials[j].full_values.push_back(val);
}
}
std::sort(shared_nodes.begin(), shared_nodes.end());
for (size_t i = 0; i < partials.size(); i++) {
@@ -2629,11 +2724,21 @@ long long write_tile(decompressor *geoms, std::atomic<long long> *geompos_in, ch
}
if (prevent[P_INPUT_ORDER]) {
std::sort(layer_features.begin(), layer_features.end(), preservecmp);
auto clustered = assemble_multiplier_clusters(layer_features);
for (auto &c : clustered) {
std::sort(c.begin(), c.end());
}
std::sort(clustered.begin(), clustered.end(), preservecmp);
layer_features = disassemble_multiplier_clusters(clustered);
}
if (order_by.size() != 0) {
std::sort(layer_features.begin(), layer_features.end(), ordercmp);
auto clustered = assemble_multiplier_clusters(layer_features);
for (auto &c : clustered) {
std::sort(c.begin(), c.end());
}
std::sort(clustered.begin(), clustered.end(), ordercmp);
layer_features = disassemble_multiplier_clusters(clustered);
}
if (z == maxzoom && limit_tile_feature_count_at_maxzoom != 0) {