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Improve maxzoom guessing for tightly-clustered point data sources (#4)
* Improve maxzoom guessing for tightly-clustered point data sources * Go back to the old distance estimate, since it is less mysterious * Update changelog and version
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@@ -1,3 +1,7 @@
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## 2.4.0
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* Change maxzoom guessing to take into account the standard deviation of the distances between features, so data with tight clusters will choose a higher maxzoom
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## 2.3.2
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## 2.3.2
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* Add --smallest-maximum-zoom-guess to guess maxzoom starting at some minimum
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* Add --smallest-maximum-zoom-guess to guess maxzoom starting at some minimum
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@@ -2005,15 +2005,44 @@ int read_input(std::vector<source> &sources, char *fname, int maxzoom, int minzo
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bool fix_dropping = false;
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bool fix_dropping = false;
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if (guess_maxzoom) {
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if (guess_maxzoom) {
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double sum = 0;
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double mean = 0;
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size_t count = 0;
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size_t count = 0;
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double m2 = 0;
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long long progress = -1;
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long long progress = -1;
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long long ip;
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long long ip;
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for (ip = 1; ip < indices; ip++) {
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for (ip = 1; ip < indices; ip++) {
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if (map[ip].ix != map[ip - 1].ix) {
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if (map[ip].ix != map[ip - 1].ix) {
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#if 0
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// This #ifdef block provides data to empirically determine the relationship
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// between a difference in quadkey index and a ground distance in feet:
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//
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// $ ./tippecanoe --no-tile-size-limit -zg -f -o foo.mbtiles ne_10m_populated_places.json > /tmp/points
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// gnuplot> stats "/tmp/points" using (log($2)):(log($3))
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unsigned wx1, wy1, wx2, wy2;
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decode_quadkey(map[ip - 1].ix, &wx1, &wy1);
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decode_quadkey(map[ip].ix, &wx2, &wy2);
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double x1, y1, x2, y2;
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x1 = (wx1 * 360.0 / UINT_MAX - 180.0) / .00000274;
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y1 = (wy1 * 360.0 / UINT_MAX - 180.0) / .00000274;
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x2 = (wx2 * 360.0 / UINT_MAX - 180.0) / .00000274;
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y2 = (wy2 * 360.0 / UINT_MAX - 180.0) / .00000274;
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double dx = x1 - x2;
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double dy = y1 - y2;
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double d = sqrt(dx * dx + dy * dy);
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printf("%llu %llu %0.2f\n", map[ip].ix, map[ip].ix - map[ip - 1].ix, d);
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#endif
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// https://en.wikipedia.org/wiki/Algorithms_for_calculating_variance#Welford's_online_algorithm
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double newValue = log(map[ip].ix - map[ip - 1].ix);
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count++;
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count++;
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sum += log(map[ip].ix - map[ip - 1].ix);
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double delta = newValue - mean;
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mean += delta / count;
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double delta2 = newValue - mean;
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m2 += delta * delta2;
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}
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}
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long long nprogress = 100 * ip / indices;
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long long nprogress = 100 * ip / indices;
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@@ -2034,14 +2063,21 @@ int read_input(std::vector<source> &sources, char *fname, int maxzoom, int minzo
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}
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}
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if (count > 0) {
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if (count > 0) {
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// Geometric mean is appropriate because distances between features
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double stddev = sqrt(m2 / count);
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// are typically lognormally distributed
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double avg = exp(sum / count);
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// Convert approximately from tile units to feet
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// Geometric mean is appropriate because distances between features
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// are typically lognormally distributed. Two standard deviations
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// below the mean should be enough to distinguish most features.
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double avg = exp(mean);
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double nearby = exp(mean - 2 * stddev);
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// Convert approximately from tile units to feet.
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// See empirical data above for source
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double dist_ft = sqrt(avg) / 33;
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double dist_ft = sqrt(avg) / 33;
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// Factor of 8 (3 zooms) beyond minimum required to distinguish features
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double nearby_ft = sqrt(nearby) / 33;
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double want = dist_ft / 8;
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// Go one zoom level beyond what is strictly necessary for nearby features.
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double want = nearby_ft / 2;
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maxzoom = ceil(log(360 / (.00000274 * want)) / log(2) - full_detail);
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maxzoom = ceil(log(360 / (.00000274 * want)) / log(2) - full_detail);
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if (maxzoom < 0) {
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if (maxzoom < 0) {
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@@ -2055,7 +2091,12 @@ int read_input(std::vector<source> &sources, char *fname, int maxzoom, int minzo
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}
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}
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if (!quiet) {
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if (!quiet) {
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fprintf(stderr, "Choosing a maxzoom of -z%d for features about %d feet (%d meters) apart\n", maxzoom, (int) ceil(dist_ft), (int) ceil(dist_ft / 3.28084));
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fprintf(stderr,
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"Choosing a maxzoom of -z%d for features typically %d feet (%d meters) apart, ",
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maxzoom,
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(int) ceil(dist_ft), (int) ceil(dist_ft / 3.28084));
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fprintf(stderr, "and at least %d feet (%d meters) apart\n",
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(int) ceil(nearby_ft), (int) ceil(nearby_ft / 3.28084));
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}
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}
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bool changed = false;
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bool changed = false;
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@@ -2074,6 +2115,7 @@ int read_input(std::vector<source> &sources, char *fname, int maxzoom, int minzo
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}
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}
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if (dist_count != 0) {
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if (dist_count != 0) {
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// no conversion to pseudo-feet here because that already happened within each feature
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double want2 = exp(dist_sum / dist_count) / 8;
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double want2 = exp(dist_sum / dist_count) / 8;
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int mz = ceil(log(360 / (.00000274 * want2)) / log(2) - full_detail);
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int mz = ceil(log(360 / (.00000274 * want2)) / log(2) - full_detail);
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@@ -480,6 +480,7 @@ int serialize_feature(struct serialization_state *sst, serial_feature &sf) {
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if (n > 0) {
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if (n > 0) {
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double avg = exp(sum / n);
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double avg = exp(sum / n);
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// Convert approximately from tile units to feet
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// Convert approximately from tile units to feet
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// See comment about empirical data in main.cpp
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double dist_ft = sqrt(avg) / 33;
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double dist_ft = sqrt(avg) / 33;
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*(sst->dist_sum) += log(dist_ft) * n;
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*(sst->dist_sum) += log(dist_ft) * n;
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+1
-1
@@ -1,6 +1,6 @@
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#ifndef VERSION_HPP
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#ifndef VERSION_HPP
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#define VERSION_HPP
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#define VERSION_HPP
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#define VERSION "v2.3.2"
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#define VERSION "v2.4.0"
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#endif
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#endif
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