flux_gen.go

// DO NOT EDIT: This file is autogenerated via the builtin command.

package geo

import (
	ast "github.com/influxdata/flux/ast"
	runtime "github.com/influxdata/flux/runtime"
)

func init() {
	runtime.RegisterPackage(pkgAST)
}

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				Source: "package geo\n\nimport \"experimental\"\nimport \"influxdata/influxdb/v1\"\n\n// Units\noption units = {\n  distance: \"km\"\n}\n\n//\n// Builtin GIS functions\n//\n\n// Returns boolean whether the region contains specified geometry.\nbuiltin stContains : (region: A, geometry: B, units: {distance: string}) => bool where A: Record, B: Record\n\n// Returns distance from given region to specified geometry.\nbuiltin stDistance : (region: A, geometry: B, units: {distance: string}) => float where A: Record, B: Record\n\n// Returns length of a curve.\nbuiltin stLength : (geometry: A, units: {distance: string}) => float where A: Record\n\n//\n// Flux GIS ST functions\n//\n\nST_Contains = (region, geometry, units=units) =>\n  stContains(region: region, geometry: geometry, units: units)\n\nST_Distance = (region, geometry, units=units) =>\n  stDistance(region: region, geometry: geometry, units: units)\n\nST_DWithin = (region, geometry, distance, units=units) =>\n  stDistance(region: region, geometry: geometry, units: units) <= distance\n\nST_Intersects = (region, geometry, units=units) =>\n  stDistance(region: region, geometry: geometry, units: units) <= 0.0\n\nST_Length = (geometry, units=units) =>\n  stLength(geometry: geometry, units: units)\n\n// Non-standard\nST_LineString = (tables=<-) =>\n  tables\n    |> reduce(fn: (r, accumulator) => ({\n        __linestring: accumulator.__linestring + (if accumulator.__count > 0 then \", \" else \"\") + string(v: r.lon) + \" \" + string(v: r.lat),\n        __count: accumulator.__count + 1\n      }), identity: {\n        __linestring: \"\",\n        __count: 0\n      }\n    )\n    |> drop(columns: [\"__count\"])\n    |> rename(columns: {__linestring: \"st_linestring\"})\n\n//\n// None of the following builtin functions are intended to be used by end users.\n//\n\n// Calculates grid (set of cell ID tokens) for given region and according to options.\nbuiltin getGrid : (region: T, ?minSize: int, ?maxSize: int, ?level: int, ?maxLevel: int, units: {distance: string}) => {level: int , set: [string]} where T: Record\n\n// Returns level of specified cell ID token.\nbuiltin getLevel : (token: string) => int\n\n// Returns cell ID token for given cell or lat/lon point at specified level.\nbuiltin s2CellIDToken : (?token: string, ?point: {lat: float , lon: float}, level: int) => string\n\n// Returns lat/lon coordinates of given cell ID token.\nbuiltin s2CellLatLon : (token: string) => {lat: float , lon: float}\n\n//\n// Flux functions\n//\n\n// Gets level of cell ID tag `s2cellID` from the first record from the first table in the stream.\n_detectLevel = (tables=<-) => {\n  _r0 =\n    tables\n      |> tableFind(fn: (key) => exists key.s2_cell_id)\n      |> getRecord(idx: 0)\n  _level =\n    if exists _r0 then\n      getLevel(token: _r0.s2_cell_id)\n    else\n       666\n  return _level\n}\n\n//\n// Convenience functions\n//\n\n// Pivots values to row-wise sets.\ntoRows = (tables=<-) =>\n  tables\n    |> v1.fieldsAsCols()\n\n// Shapes data to meet the requirements of the geo package.\n// Renames fields containing latitude and longitude values to lat and lon.\n// Pivots values to row-wise sets.\n// Generates an s2_cell_id tag for each reach using lat and lon values.\n// Adds the s2_cell_id column to the group key.\nshapeData = (tables=<-, latField, lonField, level) =>\n  tables\n    |> map(fn: (r) => ({ r with\n        _field:\n          if r._field == latField then \"lat\"\n          else if r._field == lonField then \"lon\"\n          else r._field\n      })\n    )\n    |> toRows()\n    |> map(fn: (r) => ({ r with\n        s2_cell_id: s2CellIDToken(point: {lat: r.lat, lon: r.lon}, level: level)\n      })\n    )\n    |> experimental.group(\n      columns: [\"s2_cell_id\"],\n      mode: \"extend\"\n    )\n\n//\n// Filtering functions\n//\n\n// Filters records by a box, a circle or a polygon area using S2 cell ID tag.\n// It is a coarse filter, as the grid always overlays the region, the result will likely contain records\n// with lat/lon outside the specified region.\ngridFilter = (tables=<-, region, minSize=24, maxSize=-1, level=-1, s2cellIDLevel=-1, units=units) => {\n  _s2cellIDLevel =\n    if s2cellIDLevel == -1 then\n      tables\n        |> _detectLevel()\n    else\n      s2cellIDLevel\n  _grid = getGrid(region: region, minSize: minSize, maxSize: maxSize, level: level, maxLevel: _s2cellIDLevel, units: units)\n  return\n    tables\n      |> filter(fn: (r) =>\n        if _grid.level == _s2cellIDLevel then\n          contains(value: r.s2_cell_id, set: _grid.set)\n        else\n          contains(value: s2CellIDToken(token: r.s2_cell_id, level: _grid.level), set: _grid.set)\n      )\n}\n\n// Filters records by specified region.\n// It is an exact filter and must be used after `toRows()` because it requires `lat` and `lon` columns in input row sets.\nstrictFilter = (tables=<-, region) =>\n  tables\n    |> filter(fn: (r) =>\n      ST_Contains(region: region, geometry: {lat: r.lat, lon: r.lon})\n    )\n\n// Two-phase filtering by specified region.\n// Checks to see if data is already pivoted and contains a lat column.\n// Returns pivoted data.\nfilterRows = (tables=<-, region, minSize=24, maxSize=-1, level=-1, s2cellIDLevel=-1, strict=true) => {\n  _columns =\n    tables\n      |> columns(column: \"_value\")\n      |> tableFind(fn: (key) => true )\n      |> getColumn(column: \"_value\")\n  _rows =\n    if contains(value: \"lat\", set: _columns) then\n      tables\n        |> gridFilter(region: region, minSize: minSize, maxSize: maxSize, level: level, s2cellIDLevel: s2cellIDLevel)\n    else\n      tables\n        |> gridFilter(region: region, minSize: minSize, maxSize: maxSize, level: level, s2cellIDLevel: s2cellIDLevel)\n        |> toRows()\n  _result =\n    if strict then\n      _rows\n        |> strictFilter(region)\n    else\n      _rows\n  return _result\n}\n\n//\n// Grouping functions\n//\n// intended to be used row-wise sets (i.e after `toRows()`)\n\n// Groups data by area of size specified by level. Result is grouped by `newColumn`.\n// Grouping levels: https://s2geometry.io/resources/s2cell_statistics.html\ngroupByArea = (tables=<-, newColumn, level, s2cellIDLevel=-1) => {\n  _s2cellIDLevel =\n    if s2cellIDLevel == -1 then\n      tables\n        |> _detectLevel()\n    else\n      s2cellIDLevel\n  _prepared =\n    if level == _s2cellIDLevel then\n      tables\n\t    |> duplicate(column: \"s2_cell_id\", as: newColumn)\n    else\n      tables\n        |> map(fn: (r) => ({\n             r with\n               _s2_cell_id_xxx: s2CellIDToken(point: {lat: r.lat, lon: r.lon}, level: level)\n           }))\n        |> rename(columns: { _s2_cell_id_xxx: newColumn })\n  return\n    _prepared\n      |> group(columns: [newColumn])\n}\n\n// Groups rows into tracks.\nasTracks = (tables=<-, groupBy=[\"id\",\"tid\"], orderBy=[\"_time\"]) =>\n  tables\n    |> group(columns: groupBy)\n    |> sort(columns: orderBy)",
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