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Make clusters look better by averaging locations of clustered points
This commit is contained in:
Eric Fischer
parent
61cbc3eca0
commit
18e345efb0
@ -1,3 +1,7 @@
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## 1.27.9
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* Make clusters look better by averaging locations of clustered points
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## 1.27.8
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* Add --accumulate-attribute to keep attributes of dropped, coalesced,
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@ -218,7 +218,7 @@ tippecanoe -z5 -o filtered.mbtiles -j '{ "ne_10m_admin_0_countries": [ "all", [
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compensate for the larger marker, or `-Bf`*number* to allow at most *number* features in the densest tile.
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* `-al` or `--drop-lines`: Let "dot" dropping at lower zooms apply to lines too
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* `-ap` or `--drop-polygons`: Let "dot" dropping at lower zooms apply to polygons too
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* `-K` _distance_ or `--cluster-distance=`_distance_: Cluster points (as with `--cluster-densest-as-needed`, but without the experimental discovery process) that are approximately within _distance_ of each other. The units are tile coordinates within a nominally 256-pixel tile, so the maximum value of 255 allows only one feature per tile. Values around 20 are probably appropriate for typical marker sizes.
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* `-K` _distance_ or `--cluster-distance=`_distance_: Cluster points (as with `--cluster-densest-as-needed`, but without the experimental discovery process) that are approximately within _distance_ of each other. The units are tile coordinates within a nominally 256-pixel tile, so the maximum value of 255 allows only one feature per tile. Values around 10 are probably appropriate for typical marker sizes. See `--cluster-densest-as-needed` below for behavior.
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### Dropping a fraction of features to keep under tile size limits
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@ -229,7 +229,7 @@ tippecanoe -z5 -o filtered.mbtiles -j '{ "ne_10m_admin_0_countries": [ "all", [
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* `-aD` or `--coalesce-densest-as-needed`: Dynamically combine the densest features from each zoom level into other nearby features to keep large tiles under the 500K size limit. (Again, mostly useful for polygons.)
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* `-aS` or `--coalesce-fraction-as-needed`: Dynamically combine a fraction of features from each zoom level into other nearby features to keep large tiles under the 500K size limit. (Again, mostly useful for polygons.)
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* `-pd` or `--force-feature-limit`: Dynamically drop some fraction of features from large tiles to keep them under the 500K size limit. It will probably look ugly at the tile boundaries. (This is like `-ad` but applies to each tile individually, not to the entire zoom level.) You probably don't want to use this.
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* `-aC` or `--cluster-densest-as-needed`: If a tile is too large, try to reduce its size by increasing the minimum spacing between features, and leaving one placeholder feature from each group. The remaining feature will be given a `"cluster": true` attribute to indicate that it represents a cluster, a `"point_count"` attribute to indicate the number of features that were clustered into it, and a `"sqrt_point_count"` attribute to indicate the relative width of a feature to represent the cluster.
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* `-aC` or `--cluster-densest-as-needed`: If a tile is too large, try to reduce its size by increasing the minimum spacing between features, and leaving one placeholder feature from each group. The remaining feature will be given a `"cluster": true` attribute to indicate that it represents a cluster, a `"point_count"` attribute to indicate the number of features that were clustered into it, and a `"sqrt_point_count"` attribute to indicate the relative width of a feature to represent the cluster. If the features being clustered are points, the representative feature will be located at the average of the original points' locations; otherwise, one of the original features will be left as the representative.
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### Dropping tightly overlapping features
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@ -309,7 +309,7 @@ The postfilter receives the features at tile resolution, after simplification, c
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The layer name is provided as part of the `tippecanoe` element of the feature and must be passed through
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to keep the feature in its correct layer. In the case of the prefilter, the `tippecanoe` element may also
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contain `index`, `sequence`, and `extent` elements, which must be passed through for internal operations like
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contain `index`, `sequence`, `extent`, and `dropped`, elements, which must be passed through for internal operations like
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`--drop-densest-as-needed`, `--drop-smallest-as-needed`, and `--preserve-input-order` to work.
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#### Examples:
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@ -3,6 +3,8 @@
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Builds vector tilesets \[la]https://www.mapbox.com/developers/vector-tiles/\[ra] from large (or small) collections of GeoJSON \[la]http://geojson.org/\[ra], Geobuf \[la]https://github.com/mapbox/geobuf\[ra], or CSV \[la]https://en.wikipedia.org/wiki/Comma-separated_values\[ra] features,
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like these \[la]MADE_WITH.md\[ra]\&.
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.PP
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[Mapbox Tippecanoe](\[la]https://user-images.githubusercontent.com/1951835/36568734-ede27ec0-17df-11e8-8c22-ffaaebb8daf4.JPG\[ra])
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.PP
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[Build Status](https://travis\-ci.org/mapbox/tippecanoe.svg) \[la]https://travis-ci.org/mapbox/tippecanoe\[ra]
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[Coverage Status](https://coveralls.io/repos/mapbox/tippecanoe/badge.svg?branch=master&service=github) \[la]https://coveralls.io/github/mapbox/tippecanoe?branch=master\[ra]
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.SH Intent
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@ -212,7 +214,8 @@ If the type is \fB\fCfloat\fR or \fB\fCint\fR and the original attribute was non
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If the type is \fB\fCint\fR and the original attribute was floating\-point, it is rounded to the nearest integer.
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.IP \(bu 2
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\fB\fC\-E\fR\fIattribute\fP\fB\fC:\fR\fIoperation\fP or \fB\fC\-\-accumulate\-attribute=\fR\fIattribute\fP\fB\fC:\fR\fIoperation\fP: Preserve the named \fIattribute\fP from features
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that are dropped, coalesced\-as\-needed, or clustered. The \fIoperation\fP may be \fB\fCsum\fR, \fB\fCproduct\fR, \fB\fCmean\fR, \fB\fCconcat\fR, or \fB\fCcomma\fR
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that are dropped, coalesced\-as\-needed, or clustered. The \fIoperation\fP may be
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\fB\fCsum\fR, \fB\fCproduct\fR, \fB\fCmean\fR, \fB\fCmax\fR, \fB\fCmin\fR, \fB\fCconcat\fR, or \fB\fCcomma\fR
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to specify how the named \fIattribute\fP is accumulated onto the attribute of the same name in a feature that does survive.
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.RE
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.SS Filtering features by attributes
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@ -247,7 +250,7 @@ compensate for the larger marker, or \fB\fC\-Bf\fR\fInumber\fP to allow at most
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.IP \(bu 2
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\fB\fC\-ap\fR or \fB\fC\-\-drop\-polygons\fR: Let "dot" dropping at lower zooms apply to polygons too
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.IP \(bu 2
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\fB\fC\-K\fR \fIdistance\fP or \fB\fC\-\-cluster\-distance=\fR\fIdistance\fP: Cluster points (as with \fB\fC\-\-cluster\-densest\-as\-needed\fR, but without the experimental discovery process) that are approximately within \fIdistance\fP of each other. The units are tile coordinates within a nominally 256\-pixel tile, so the maximum value of 255 allows only one feature per tile. Values around 20 are probably appropriate for typical marker sizes.
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\fB\fC\-K\fR \fIdistance\fP or \fB\fC\-\-cluster\-distance=\fR\fIdistance\fP: Cluster points (as with \fB\fC\-\-cluster\-densest\-as\-needed\fR, but without the experimental discovery process) that are approximately within \fIdistance\fP of each other. The units are tile coordinates within a nominally 256\-pixel tile, so the maximum value of 255 allows only one feature per tile. Values around 10 are probably appropriate for typical marker sizes. See \fB\fC\-\-cluster\-densest\-as\-needed\fR below for behavior.
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.RE
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.SS Dropping a fraction of features to keep under tile size limits
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.RS
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@ -266,7 +269,7 @@ compensate for the larger marker, or \fB\fC\-Bf\fR\fInumber\fP to allow at most
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.IP \(bu 2
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\fB\fC\-pd\fR or \fB\fC\-\-force\-feature\-limit\fR: Dynamically drop some fraction of features from large tiles to keep them under the 500K size limit. It will probably look ugly at the tile boundaries. (This is like \fB\fC\-ad\fR but applies to each tile individually, not to the entire zoom level.) You probably don't want to use this.
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.IP \(bu 2
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\fB\fC\-aC\fR or \fB\fC\-\-cluster\-densest\-as\-needed\fR: If a tile is too large, try to reduce its size by increasing the minimum spacing between features, and leaving one placeholder feature from each group. The remaining feature will be given a \fB\fC"cluster": true\fR attribute to indicate that it represents a cluster, a \fB\fC"point_count"\fR attribute to indicate the number of features that were clustered into it, and a \fB\fC"sqrt_point_count"\fR attribute to indicate the relative width of a feature to represent the cluster.
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\fB\fC\-aC\fR or \fB\fC\-\-cluster\-densest\-as\-needed\fR: If a tile is too large, try to reduce its size by increasing the minimum spacing between features, and leaving one placeholder feature from each group. The remaining feature will be given a \fB\fC"cluster": true\fR attribute to indicate that it represents a cluster, a \fB\fC"point_count"\fR attribute to indicate the number of features that were clustered into it, and a \fB\fC"sqrt_point_count"\fR attribute to indicate the relative width of a feature to represent the cluster. If the features being clustered are points, the representative feature will be located at the average of the original points' locations; otherwise, one of the original features will be left as the representative.
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.RE
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.SS Dropping tightly overlapping features
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.RS
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@ -376,7 +379,7 @@ The postfilter receives the features at tile resolution, after simplification, c
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.PP
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The layer name is provided as part of the \fB\fCtippecanoe\fR element of the feature and must be passed through
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to keep the feature in its correct layer. In the case of the prefilter, the \fB\fCtippecanoe\fR element may also
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contain \fB\fCindex\fR, \fB\fCsequence\fR, and \fB\fCextent\fR elements, which must be passed through for internal operations like
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contain \fB\fCindex\fR, \fB\fCsequence\fR, \fB\fCextent\fR, and \fB\fCdropped\fR, elements, which must be passed through for internal operations like
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\fB\fC\-\-drop\-densest\-as\-needed\fR, \fB\fC\-\-drop\-smallest\-as\-needed\fR, and \fB\fC\-\-preserve\-input\-order\fR to work.
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.SS Examples:
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.RS
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@ -12,17 +12,17 @@
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}, "features": [
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{ "type": "FeatureCollection", "properties": { "zoom": 0, "x": 0, "y": 0 }, "features": [
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{ "type": "FeatureCollection", "properties": { "layer": "in", "version": 2, "extent": 4096 }, "features": [
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{ "type": "Feature", "properties": { "thesum": 669, "themax": 94, "themin": 3, "theproduct": 1.50635366827988e+21, "themean": 47.785714285714288, "theconcat": "31478286774655129484515737", "thecomma": "3,14,78,28,67,74,65,5,12,94,84,51,57,37", "clustered": true, "point_count": 14, "sqrt_point_count": 3.74 }, "geometry": { "type": "Point", "coordinates": [ -147.392578, 84.786525 ] } }
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{ "type": "Feature", "properties": { "thesum": 669, "themax": 94, "themin": 3, "theproduct": 1.50635366827988e+21, "themean": 47.785714285714288, "theconcat": "31478286774655129484515737", "thecomma": "3,14,78,28,67,74,65,5,12,94,84,51,57,37", "clustered": true, "point_count": 14, "sqrt_point_count": 3.74 }, "geometry": { "type": "Point", "coordinates": [ -131.308594, 60.283408 ] } }
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,
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{ "type": "Feature", "properties": { "thesum": 960, "themax": 99, "themin": 9, "theproduct": 3.663431746147758e+29, "themean": 49.41935483870968, "theconcat": "97539299902113384943547193275237229", "thecomma": "97,53,92,99,90,21,13,38,49,43,54,71,9,32,75,23,72,29", "clustered": true, "point_count": 18, "sqrt_point_count": 4.24 }, "geometry": { "type": "Point", "coordinates": [ -19.160156, 85.013073 ] } }
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{ "type": "Feature", "properties": { "thesum": 960, "themax": 99, "themin": 9, "theproduct": 3.663431746147758e+29, "themean": 49.41935483870968, "theconcat": "97539299902113384943547193275237229", "thecomma": "97,53,92,99,90,21,13,38,49,43,54,71,9,32,75,23,72,29", "clustered": true, "point_count": 18, "sqrt_point_count": 4.24 }, "geometry": { "type": "Point", "coordinates": [ -113.115234, -2.986927 ] } }
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,
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{ "type": "Feature", "properties": { "thesum": 625, "themax": 100, "themin": 19, "theproduct": 256866214501512000, "themean": 52.45, "theconcat": "594210066226395738619", "thecomma": "59,42,100,66,22,63,95,73,86,19", "clustered": true, "point_count": 10, "sqrt_point_count": 3.16 }, "geometry": { "type": "Point", "coordinates": [ -146.953125, -72.893802 ] } }
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{ "type": "Feature", "properties": { "thesum": 625, "themax": 100, "themin": 19, "theproduct": 256866214501512000, "themean": 52.45, "theconcat": "594210066226395738619", "thecomma": "59,42,100,66,22,63,95,73,86,19", "clustered": true, "point_count": 10, "sqrt_point_count": 3.16 }, "geometry": { "type": "Point", "coordinates": [ -71.367188, -53.696706 ] } }
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,
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{ "type": "Feature", "properties": { "thesum": 397, "themax": 91, "themin": 2, "theproduct": 8357260912000, "themean": 51.75, "theconcat": "11216822689255591", "thecomma": "11,2,16,82,26,89,25,55,91", "clustered": true, "point_count": 9, "sqrt_point_count": 3 }, "geometry": { "type": "Point", "coordinates": [ 30.849609, 80.193694 ] } }
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{ "type": "Feature", "properties": { "thesum": 397, "themax": 91, "themin": 2, "theproduct": 8357260912000, "themean": 51.75, "theconcat": "11216822689255591", "thecomma": "11,2,16,82,26,89,25,55,91", "clustered": true, "point_count": 9, "sqrt_point_count": 3 }, "geometry": { "type": "Point", "coordinates": [ 48.164062, 66.583217 ] } }
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,
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{ "type": "Feature", "properties": { "thesum": 793, "themax": 93, "themin": 7, "theproduct": 3.649478722049509e+25, "themean": 51.492063492063497, "theconcat": "3317626981793467648183915808524", "thecomma": "33,17,62,69,81,7,93,46,76,48,18,39,15,80,85,24", "clustered": true, "point_count": 16, "sqrt_point_count": 4 }, "geometry": { "type": "Point", "coordinates": [ 177.363281, 76.393312 ] } }
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{ "type": "Feature", "properties": { "thesum": 793, "themax": 93, "themin": 7, "theproduct": 3.649478722049509e+25, "themean": 51.492063492063497, "theconcat": "3317626981793467648183915808524", "thecomma": "33,17,62,69,81,7,93,46,76,48,18,39,15,80,85,24", "clustered": true, "point_count": 16, "sqrt_point_count": 4 }, "geometry": { "type": "Point", "coordinates": [ 71.279297, -22.268764 ] } }
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,
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{ "type": "Feature", "properties": { "thesum": 821, "themax": 96, "themin": 1, "theproduct": 3.7235827383082715e+25, "themean": 50.40506329113924, "theconcat": "8310357913170648446526136879658", "thecomma": "83,10,35,79,1,31,70,64,8,44,6,52,61,36,87,96,58", "clustered": true, "point_count": 17, "sqrt_point_count": 4.12 }, "geometry": { "type": "Point", "coordinates": [ 43.330078, -79.981891 ] } }
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{ "type": "Feature", "properties": { "thesum": 821, "themax": 96, "themin": 1, "theproduct": 3.7235827383082715e+25, "themean": 50.40506329113924, "theconcat": "8310357913170648446526136879658", "thecomma": "83,10,35,79,1,31,70,64,8,44,6,52,61,36,87,96,58", "clustered": true, "point_count": 17, "sqrt_point_count": 4.12 }, "geometry": { "type": "Point", "coordinates": [ 129.990234, -69.472969 ] } }
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] }
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] }
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,
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@ -30,27 +30,27 @@
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||||
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|
||||
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|
||||
,
|
||||
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|
||||
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|
||||
,
|
||||
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|
||||
{ "type": "Feature", "properties": { "thesum": 251, "themax": 74, "themin": 5, "theproduct": 541413600, "themean": 39.75, "theconcat": "28677465512", "thecomma": "28,67,74,65,5,12", "clustered": true, "point_count": 6, "sqrt_point_count": 2.45 }, "geometry": { "type": "Point", "coordinates": [ -151.831055, 34.125448 ] } }
|
||||
,
|
||||
{ "type": "Feature", "properties": { "thesum": 323, "themax": 94, "themin": 37, "theproduct": 849285864, "themean": 45.583333333333339, "theconcat": "9484515737", "thecomma": "94,84,51,57,37", "clustered": true, "point_count": 5, "sqrt_point_count": 2.24 }, "geometry": { "type": "Point", "coordinates": [ -132.539062, 18.104087 ] } }
|
||||
{ "type": "Feature", "properties": { "thesum": 323, "themax": 94, "themin": 37, "theproduct": 849285864, "themean": 45.583333333333339, "theconcat": "9484515737", "thecomma": "94,84,51,57,37", "clustered": true, "point_count": 5, "sqrt_point_count": 2.24 }, "geometry": { "type": "Point", "coordinates": [ -101.381836, 58.608334 ] } }
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,
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|
||||
{ "type": "Feature", "properties": { "thesum": 83, "themax": 83, "themin": 83, "theproduct": 83, "themean": 83, "theconcat": 83, "thecomma": 83 }, "geometry": { "type": "Point", "coordinates": [ 43.352051, -79.993351 ] } }
|
||||
] }
|
||||
@ -400,7 +400,7 @@
|
||||
,
|
||||
{ "type": "FeatureCollection", "properties": { "zoom": 3, "x": 4, "y": 5 }, "features": [
|
||||
{ "type": "FeatureCollection", "properties": { "layer": "in", "version": 2, "extent": 4096 }, "features": [
|
||||
{ "type": "Feature", "properties": { "thesum": 105, "themax": 48, "themin": 18, "theproduct": 33696, "themean": 35, "theconcat": "481839", "thecomma": "48,18,39", "clustered": true, "point_count": 3, "sqrt_point_count": 1.73 }, "geometry": { "type": "Point", "coordinates": [ 3.757324, -46.950262 ] } }
|
||||
{ "type": "Feature", "properties": { "thesum": 105, "themax": 48, "themin": 18, "theproduct": 33696, "themean": 35, "theconcat": "481839", "thecomma": "48,18,39", "clustered": true, "point_count": 3, "sqrt_point_count": 1.73 }, "geometry": { "type": "Point", "coordinates": [ 10.228271, -45.567910 ] } }
|
||||
,
|
||||
{ "type": "Feature", "properties": { "thesum": 15, "themax": 15, "themin": 15, "theproduct": 15, "themean": 15, "theconcat": 15, "thecomma": 15 }, "geometry": { "type": "Point", "coordinates": [ 14.655762, -65.252108 ] } }
|
||||
] }
|
||||
@ -410,7 +410,7 @@
|
||||
{ "type": "FeatureCollection", "properties": { "layer": "in", "version": 2, "extent": 4096 }, "features": [
|
||||
{ "type": "Feature", "properties": { "thesum": 86, "themax": 86, "themin": 86, "theproduct": 86, "themean": 86, "theconcat": 86, "thecomma": 86 }, "geometry": { "type": "Point", "coordinates": [ -0.263672, -32.685620 ] } }
|
||||
,
|
||||
{ "type": "Feature", "properties": { "thesum": 122, "themax": 76, "themin": 46, "theproduct": 3496, "themean": 61, "theconcat": "4676", "thecomma": "46,76", "clustered": true, "point_count": 2, "sqrt_point_count": 1.41 }, "geometry": { "type": "Point", "coordinates": [ 37.770996, -9.253936 ] } }
|
||||
{ "type": "Feature", "properties": { "thesum": 122, "themax": 76, "themin": 46, "theproduct": 3496, "themean": 61, "theconcat": "4676", "thecomma": "46,76", "clustered": true, "point_count": 2, "sqrt_point_count": 1.41 }, "geometry": { "type": "Point", "coordinates": [ 36.606445, -15.485445 ] } }
|
||||
] }
|
||||
] }
|
||||
,
|
||||
@ -422,7 +422,7 @@
|
||||
,
|
||||
{ "type": "FeatureCollection", "properties": { "zoom": 3, "x": 4, "y": 2 }, "features": [
|
||||
{ "type": "FeatureCollection", "properties": { "layer": "in", "version": 2, "extent": 4096 }, "features": [
|
||||
{ "type": "Feature", "properties": { "thesum": 18, "themax": 16, "themin": 2, "theproduct": 32, "themean": 9, "theconcat": "216", "thecomma": "2,16", "clustered": true, "point_count": 2, "sqrt_point_count": 1.41 }, "geometry": { "type": "Point", "coordinates": [ 14.051514, 46.732331 ] } }
|
||||
{ "type": "Feature", "properties": { "thesum": 18, "themax": 16, "themin": 2, "theproduct": 32, "themean": 9, "theconcat": "216", "thecomma": "2,16", "clustered": true, "point_count": 2, "sqrt_point_count": 1.41 }, "geometry": { "type": "Point", "coordinates": [ 19.346924, 54.065836 ] } }
|
||||
,
|
||||
{ "type": "Feature", "properties": { "thesum": 82, "themax": 82, "themin": 82, "theproduct": 82, "themean": 82, "theconcat": 82, "thecomma": 82 }, "geometry": { "type": "Point", "coordinates": [ 31.959229, 55.596971 ] } }
|
||||
,
|
||||
@ -438,7 +438,7 @@
|
||||
,
|
||||
{ "type": "FeatureCollection", "properties": { "zoom": 3, "x": 5, "y": 7 }, "features": [
|
||||
{ "type": "FeatureCollection", "properties": { "layer": "in", "version": 2, "extent": 4096 }, "features": [
|
||||
{ "type": "Feature", "properties": { "thesum": 114, "themax": 79, "themin": 35, "theproduct": 2765, "themean": 57, "theconcat": "3579", "thecomma": "35,79", "clustered": true, "point_count": 2, "sqrt_point_count": 1.41 }, "geometry": { "type": "Point", "coordinates": [ 57.952881, -82.229086 ] } }
|
||||
{ "type": "Feature", "properties": { "thesum": 114, "themax": 79, "themin": 35, "theproduct": 2765, "themean": 57, "theconcat": "3579", "thecomma": "35,79", "clustered": true, "point_count": 2, "sqrt_point_count": 1.41 }, "geometry": { "type": "Point", "coordinates": [ 55.667725, -83.244185 ] } }
|
||||
] }
|
||||
] }
|
||||
,
|
||||
@ -478,7 +478,7 @@
|
||||
,
|
||||
{ "type": "Feature", "properties": { "thesum": 62, "themax": 62, "themin": 62, "theproduct": 62, "themean": 62, "theconcat": 62, "thecomma": 62 }, "geometry": { "type": "Point", "coordinates": [ 120.717773, 34.052659 ] } }
|
||||
,
|
||||
{ "type": "Feature", "properties": { "thesum": 150, "themax": 81, "themin": 69, "theproduct": 5589, "themean": 75, "theconcat": "6981", "thecomma": "69,81", "clustered": true, "point_count": 2, "sqrt_point_count": 1.41 }, "geometry": { "type": "Point", "coordinates": [ 113.609619, 13.848747 ] } }
|
||||
{ "type": "Feature", "properties": { "thesum": 150, "themax": 81, "themin": 69, "theproduct": 5589, "themean": 75, "theconcat": "6981", "thecomma": "69,81", "clustered": true, "point_count": 2, "sqrt_point_count": 1.41 }, "geometry": { "type": "Point", "coordinates": [ 119.443359, 16.088042 ] } }
|
||||
,
|
||||
{ "type": "Feature", "properties": { "thesum": 7, "themax": 7, "themin": 7, "theproduct": 7, "themean": 7, "theconcat": 7, "thecomma": 7 }, "geometry": { "type": "Point", "coordinates": [ 126.595459, 8.733077 ] } }
|
||||
] }
|
||||
@ -500,7 +500,7 @@
|
||||
,
|
||||
{ "type": "FeatureCollection", "properties": { "zoom": 3, "x": 7, "y": 6 }, "features": [
|
||||
{ "type": "FeatureCollection", "properties": { "layer": "in", "version": 2, "extent": 4096 }, "features": [
|
||||
{ "type": "Feature", "properties": { "thesum": 97, "themax": 61, "themin": 36, "theproduct": 2196, "themean": 48.5, "theconcat": "6136", "thecomma": "61,36", "clustered": true, "point_count": 2, "sqrt_point_count": 1.41 }, "geometry": { "type": "Point", "coordinates": [ 146.239014, -77.413467 ] } }
|
||||
{ "type": "Feature", "properties": { "thesum": 97, "themax": 61, "themin": 36, "theproduct": 2196, "themean": 48.5, "theconcat": "6136", "thecomma": "61,36", "clustered": true, "point_count": 2, "sqrt_point_count": 1.41 }, "geometry": { "type": "Point", "coordinates": [ 149.490967, -77.911068 ] } }
|
||||
,
|
||||
{ "type": "Feature", "properties": { "thesum": 87, "themax": 87, "themin": 87, "theproduct": 87, "themean": 87, "theconcat": 87, "thecomma": 87 }, "geometry": { "type": "Point", "coordinates": [ 165.520020, -69.862328 ] } }
|
||||
,
|
||||
@ -522,7 +522,7 @@
|
||||
,
|
||||
{ "type": "FeatureCollection", "properties": { "zoom": 3, "x": 7, "y": 4 }, "features": [
|
||||
{ "type": "FeatureCollection", "properties": { "layer": "in", "version": 2, "extent": 4096 }, "features": [
|
||||
{ "type": "Feature", "properties": { "thesum": 101, "themax": 70, "themin": 31, "theproduct": 2170, "themean": 50.5, "theconcat": "3170", "thecomma": "31,70", "clustered": true, "point_count": 2, "sqrt_point_count": 1.41 }, "geometry": { "type": "Point", "coordinates": [ 151.424561, -2.043024 ] } }
|
||||
{ "type": "Feature", "properties": { "thesum": 101, "themax": 70, "themin": 31, "theproduct": 2170, "themean": 50.5, "theconcat": "3170", "thecomma": "31,70", "clustered": true, "point_count": 2, "sqrt_point_count": 1.41 }, "geometry": { "type": "Point", "coordinates": [ 149.227295, -12.007085 ] } }
|
||||
,
|
||||
{ "type": "Feature", "properties": { "thesum": 64, "themax": 64, "themin": 64, "theproduct": 64, "themean": 64, "theconcat": 64, "thecomma": 64 }, "geometry": { "type": "Point", "coordinates": [ 159.675293, -17.130292 ] } }
|
||||
,
|
||||
|
||||
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
13
tile.cpp
13
tile.cpp
@ -1758,6 +1758,19 @@ long long write_tile(FILE *geoms, long long *geompos_in, char *metabase, char *s
|
||||
indices.push_back(sf.index);
|
||||
if ((sf.index < merge_previndex || sf.index - merge_previndex < mingap) && find_partial(partials, sf, which_partial, layer_unmaps)) {
|
||||
partials[which_partial].clustered++;
|
||||
|
||||
if (partials[which_partial].t == VT_POINT &&
|
||||
partials[which_partial].geoms.size() == 1 &&
|
||||
partials[which_partial].geoms[0].size() == 1 &&
|
||||
sf.geometry.size() == 1) {
|
||||
double x = (double) partials[which_partial].geoms[0][0].x * partials[which_partial].clustered;
|
||||
double y = (double) partials[which_partial].geoms[0][0].y * partials[which_partial].clustered;
|
||||
x += sf.geometry[0].x;
|
||||
y += sf.geometry[0].y;
|
||||
partials[which_partial].geoms[0][0].x = x / (partials[which_partial].clustered + 1);
|
||||
partials[which_partial].geoms[0][0].y = y / (partials[which_partial].clustered + 1);
|
||||
}
|
||||
|
||||
preserve_attributes(arg->attribute_accum, attribute_accum_state, sf, stringpool, pool_off, partials[which_partial]);
|
||||
continue;
|
||||
}
|
||||
|
||||
@ -1,6 +1,6 @@
|
||||
#ifndef VERSION_HPP
|
||||
#define VERSION_HPP
|
||||
|
||||
#define VERSION "tippecanoe v1.27.8\n"
|
||||
#define VERSION "tippecanoe v1.27.9\n"
|
||||
|
||||
#endif
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user