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point-cluster Build Statusexperimental

Point clustering for 2D spatial indexing. Incorporates optimized quad-tree data structure.

Maintained by Plotly
constcluster=require('point-cluster')letids=cluster(points)// get point ids in the indicated rangeletselectedIds=ids.range([10,10,20,20])// get levels of details: list of ids subranges for rendering purposesletlod=ids.range([10,10,20,20],{lod: true})

API

ids = cluster(points, options?)

Create index for the set of 2d points based on options.

  • points is an array of [x,y, x,y, ...] or [[x,y], [x,y], ...] coordinates.
  • ids is Uint32Array with point ids sorted by zoom levels, suitable for WebGL buffer, subranging or alike.
  • options
OptionDefaultDescription
bounds'auto'Data range, if different from points bounds, eg. in case of subdata.
depth256Max number of levels. Points below the indicated level are grouped into single level.
output'array'Output data array or data format. For available formats see dtype.

result = ids.range(box?, options?)

Get point ids from the indicated range.

  • box can be any rectangle object, eg. [l, t, r, b], see parse-rect.
  • options
OptionDefaultDescription
lodfalseMakes result a list of level details instead of ids, useful for obtaining subranges to render.
px0Min pixel size in data dimension (number or [width, height] couple) to search for, to ignore lower levels.
levelnullMax level to limit search.
letlevels=ids.range([0,0,100,100],{lod: true,d: dataRange/canvas.width})levels.forEach([from,to]=>{// offset and count point to range in `ids` arrayrender(ids.subarray(from,to))})

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License

© 2017 Dmitry Yv. MIT License

Development supported by plot.ly.

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2d point clustering for datavis purposes.

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var __re = new RegExp('^' + "github\\.com" + '
GitHub - plotly/point-cluster: 2d point clustering for datavis purposes. · GitHub
Skip to content
BranchesTags
Repository files navigation
point-cluster Build Statusexperimental
Point clustering for 2D spatial indexing. Incorporates optimized quad-tree data structure.
Maintained by Plotly
constcluster=require('point-cluster')letids=cluster(points)// get point ids in the indicated rangeletselectedIds=ids.range([10,10,20,20])// get levels of details: list of ids subranges for rendering purposesletlod=ids.range([10,10,20,20],{lod: true})
API
ids = cluster(points, options?)
Create index for the set of 2d points based on options.
  • points is an array of [x,y, x,y, ...] or [[x,y], [x,y], ...] coordinates.
  • ids is Uint32Array with point ids sorted by zoom levels, suitable for WebGL buffer, subranging or alike.
  • options
OptionDefaultDescription
bounds'auto'Data range, if different from points bounds, eg. in case of subdata.
depth256Max number of levels. Points below the indicated level are grouped into single level.
output'array'Output data array or data format. For available formats see dtype.
result = ids.range(box?, options?)
Get point ids from the indicated range.
  • box can be any rectangle object, eg. [l, t, r, b], see parse-rect.
  • options
OptionDefaultDescription
lodfalseMakes result a list of level details instead of ids, useful for obtaining subranges to render.
px0Min pixel size in data dimension (number or [width, height] couple) to search for, to ignore lower levels.
levelnullMax level to limit search.
letlevels=ids.range([0,0,100,100],{lod: true,d: dataRange/canvas.width})levels.forEach([from,to]=>{// offset and count point to range in `ids` arrayrender(ids.subarray(from,to))})
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License
© 2017 Dmitry Yv. MIT License
Development supported by plot.ly.
About
2d point clustering for datavis purposes.
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GitHub - plotly/point-cluster: 2d point clustering for datavis purposes. · GitHub
Skip to content
BranchesTags
Repository files navigation
point-cluster Build Statusexperimental
Point clustering for 2D spatial indexing. Incorporates optimized quad-tree data structure.
Maintained by Plotly
constcluster=require('point-cluster')letids=cluster(points)// get point ids in the indicated rangeletselectedIds=ids.range([10,10,20,20])// get levels of details: list of ids subranges for rendering purposesletlod=ids.range([10,10,20,20],{lod: true})
API
ids = cluster(points, options?)
Create index for the set of 2d points based on options.
  • points is an array of [x,y, x,y, ...] or [[x,y], [x,y], ...] coordinates.
  • ids is Uint32Array with point ids sorted by zoom levels, suitable for WebGL buffer, subranging or alike.
  • options
OptionDefaultDescription
bounds'auto'Data range, if different from points bounds, eg. in case of subdata.
depth256Max number of levels. Points below the indicated level are grouped into single level.
output'array'Output data array or data format. For available formats see dtype.
result = ids.range(box?, options?)
Get point ids from the indicated range.
  • box can be any rectangle object, eg. [l, t, r, b], see parse-rect.
  • options
OptionDefaultDescription
lodfalseMakes result a list of level details instead of ids, useful for obtaining subranges to render.
px0Min pixel size in data dimension (number or [width, height] couple) to search for, to ignore lower levels.
levelnullMax level to limit search.
letlevels=ids.range([0,0,100,100],{lod: true,d: dataRange/canvas.width})levels.forEach([from,to]=>{// offset and count point to range in `ids` arrayrender(ids.subarray(from,to))})
Related
License
© 2017 Dmitry Yv. MIT License
Development supported by plot.ly.
About
2d point clustering for datavis purposes.
Resources
Readme
MIT license
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(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
GitHub - plotly/point-cluster: 2d point clustering for datavis purposes. · GitHub
Skip to content
BranchesTags
Repository files navigation
point-cluster Build Statusexperimental
Point clustering for 2D spatial indexing. Incorporates optimized quad-tree data structure.
Maintained by Plotly
constcluster=require('point-cluster')letids=cluster(points)// get point ids in the indicated rangeletselectedIds=ids.range([10,10,20,20])// get levels of details: list of ids subranges for rendering purposesletlod=ids.range([10,10,20,20],{lod: true})
API
ids = cluster(points, options?)
Create index for the set of 2d points based on options.
  • points is an array of [x,y, x,y, ...] or [[x,y], [x,y], ...] coordinates.
  • ids is Uint32Array with point ids sorted by zoom levels, suitable for WebGL buffer, subranging or alike.
  • options
OptionDefaultDescription
bounds'auto'Data range, if different from points bounds, eg. in case of subdata.
depth256Max number of levels. Points below the indicated level are grouped into single level.
output'array'Output data array or data format. For available formats see dtype.
result = ids.range(box?, options?)
Get point ids from the indicated range.
  • box can be any rectangle object, eg. [l, t, r, b], see parse-rect.
  • options
OptionDefaultDescription
lodfalseMakes result a list of level details instead of ids, useful for obtaining subranges to render.
px0Min pixel size in data dimension (number or [width, height] couple) to search for, to ignore lower levels.
levelnullMax level to limit search.
letlevels=ids.range([0,0,100,100],{lod: true,d: dataRange/canvas.width})levels.forEach([from,to]=>{// offset and count point to range in `ids` arrayrender(ids.subarray(from,to))})
Related
License
© 2017 Dmitry Yv. MIT License
Development supported by plot.ly.
About
2d point clustering for datavis purposes.
Resources
Readme
MIT license
Activity
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1 star
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5 forks
Report repository
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(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '
GitHub - plotly/point-cluster: 2d point clustering for datavis purposes. · GitHub
Skip to content
BranchesTags
Repository files navigation
point-cluster Build Statusexperimental
Point clustering for 2D spatial indexing. Incorporates optimized quad-tree data structure.
Maintained by Plotly
constcluster=require('point-cluster')letids=cluster(points)// get point ids in the indicated rangeletselectedIds=ids.range([10,10,20,20])// get levels of details: list of ids subranges for rendering purposesletlod=ids.range([10,10,20,20],{lod: true})
API
ids = cluster(points, options?)
Create index for the set of 2d points based on options.
  • points is an array of [x,y, x,y, ...] or [[x,y], [x,y], ...] coordinates.
  • ids is Uint32Array with point ids sorted by zoom levels, suitable for WebGL buffer, subranging or alike.
  • options
OptionDefaultDescription
bounds'auto'Data range, if different from points bounds, eg. in case of subdata.
depth256Max number of levels. Points below the indicated level are grouped into single level.
output'array'Output data array or data format. For available formats see dtype.
result = ids.range(box?, options?)
Get point ids from the indicated range.
  • box can be any rectangle object, eg. [l, t, r, b], see parse-rect.
  • options
OptionDefaultDescription
lodfalseMakes result a list of level details instead of ids, useful for obtaining subranges to render.
px0Min pixel size in data dimension (number or [width, height] couple) to search for, to ignore lower levels.
levelnullMax level to limit search.
letlevels=ids.range([0,0,100,100],{lod: true,d: dataRange/canvas.width})levels.forEach([from,to]=>{// offset and count point to range in `ids` arrayrender(ids.subarray(from,to))})
Related
License
© 2017 Dmitry Yv. MIT License
Development supported by plot.ly.
About
2d point clustering for datavis purposes.
Resources
Readme
MIT license
Activity
Custom properties
Stars
1 star
Watchers
0 watching
Forks
5 forks
Report repository
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, 'i');
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(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
GitHub - plotly/point-cluster: 2d point clustering for datavis purposes. · GitHub
Skip to content
BranchesTags
Repository files navigation
point-cluster Build Statusexperimental
Point clustering for 2D spatial indexing. Incorporates optimized quad-tree data structure.
Maintained by Plotly
constcluster=require('point-cluster')letids=cluster(points)// get point ids in the indicated rangeletselectedIds=ids.range([10,10,20,20])// get levels of details: list of ids subranges for rendering purposesletlod=ids.range([10,10,20,20],{lod: true})
API
ids = cluster(points, options?)
Create index for the set of 2d points based on options.
  • points is an array of [x,y, x,y, ...] or [[x,y], [x,y], ...] coordinates.
  • ids is Uint32Array with point ids sorted by zoom levels, suitable for WebGL buffer, subranging or alike.
  • options
OptionDefaultDescription
bounds'auto'Data range, if different from points bounds, eg. in case of subdata.
depth256Max number of levels. Points below the indicated level are grouped into single level.
output'array'Output data array or data format. For available formats see dtype.
result = ids.range(box?, options?)
Get point ids from the indicated range.
  • box can be any rectangle object, eg. [l, t, r, b], see parse-rect.
  • options
OptionDefaultDescription
lodfalseMakes result a list of level details instead of ids, useful for obtaining subranges to render.
px0Min pixel size in data dimension (number or [width, height] couple) to search for, to ignore lower levels.
levelnullMax level to limit search.
letlevels=ids.range([0,0,100,100],{lod: true,d: dataRange/canvas.width})levels.forEach([from,to]=>{// offset and count point to range in `ids` arrayrender(ids.subarray(from,to))})
Related
License
© 2017 Dmitry Yv. MIT License
Development supported by plot.ly.
About
2d point clustering for datavis purposes.
Resources
Readme
MIT license
Activity
Custom properties
Stars
1 star
Watchers
0 watching
Forks
5 forks
Report repository
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, 'i');
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(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
GitHub - plotly/point-cluster: 2d point clustering for datavis purposes. · GitHub
Skip to content
BranchesTags
Repository files navigation
point-cluster Build Statusexperimental
Point clustering for 2D spatial indexing. Incorporates optimized quad-tree data structure.
Maintained by Plotly
constcluster=require('point-cluster')letids=cluster(points)// get point ids in the indicated rangeletselectedIds=ids.range([10,10,20,20])// get levels of details: list of ids subranges for rendering purposesletlod=ids.range([10,10,20,20],{lod: true})
API
ids = cluster(points, options?)
Create index for the set of 2d points based on options.
  • points is an array of [x,y, x,y, ...] or [[x,y], [x,y], ...] coordinates.
  • ids is Uint32Array with point ids sorted by zoom levels, suitable for WebGL buffer, subranging or alike.
  • options
OptionDefaultDescription
bounds'auto'Data range, if different from points bounds, eg. in case of subdata.
depth256Max number of levels. Points below the indicated level are grouped into single level.
output'array'Output data array or data format. For available formats see dtype.
result = ids.range(box?, options?)
Get point ids from the indicated range.
  • box can be any rectangle object, eg. [l, t, r, b], see parse-rect.
  • options
OptionDefaultDescription
lodfalseMakes result a list of level details instead of ids, useful for obtaining subranges to render.
px0Min pixel size in data dimension (number or [width, height] couple) to search for, to ignore lower levels.
levelnullMax level to limit search.
letlevels=ids.range([0,0,100,100],{lod: true,d: dataRange/canvas.width})levels.forEach([from,to]=>{// offset and count point to range in `ids` arrayrender(ids.subarray(from,to))})
Related
License
© 2017 Dmitry Yv. MIT License
Development supported by plot.ly.
About
2d point clustering for datavis purposes.
Resources
Readme
MIT license
Activity
Custom properties
Stars
1 star
Watchers
0 watching
Forks
5 forks
Report repository
Releases
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observer.observe(document.head, { childList: true });
console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');
})();
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();
GitHub - plotly/point-cluster: 2d point clustering for datavis purposes. · GitHub
Skip to content
BranchesTags
Repository files navigation
point-cluster Build Statusexperimental
Point clustering for 2D spatial indexing. Incorporates optimized quad-tree data structure.
Maintained by Plotly
constcluster=require('point-cluster')letids=cluster(points)// get point ids in the indicated rangeletselectedIds=ids.range([10,10,20,20])// get levels of details: list of ids subranges for rendering purposesletlod=ids.range([10,10,20,20],{lod: true})
API
ids = cluster(points, options?)
Create index for the set of 2d points based on options.
  • points is an array of [x,y, x,y, ...] or [[x,y], [x,y], ...] coordinates.
  • ids is Uint32Array with point ids sorted by zoom levels, suitable for WebGL buffer, subranging or alike.
  • options
OptionDefaultDescription
bounds'auto'Data range, if different from points bounds, eg. in case of subdata.
depth256Max number of levels. Points below the indicated level are grouped into single level.
output'array'Output data array or data format. For available formats see dtype.
result = ids.range(box?, options?)
Get point ids from the indicated range.
  • box can be any rectangle object, eg. [l, t, r, b], see parse-rect.
  • options
OptionDefaultDescription
lodfalseMakes result a list of level details instead of ids, useful for obtaining subranges to render.
px0Min pixel size in data dimension (number or [width, height] couple) to search for, to ignore lower levels.
levelnullMax level to limit search.
letlevels=ids.range([0,0,100,100],{lod: true,d: dataRange/canvas.width})levels.forEach([from,to]=>{// offset and count point to range in `ids` arrayrender(ids.subarray(from,to))})
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© 2017 Dmitry Yv. MIT License
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2d point clustering for datavis purposes.
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