diff --git a/dev/index.html b/dev/index.html index ab9a775..04cef34 100644 --- a/dev/index.html +++ b/dev/index.html @@ -1,2 +1,2 @@ -Home · OSMToolset.jl
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OSMToolset.jl

Documentation for OSMToolset.jl

For details please go to the Reference section.

Aknowledgments

<sup>This research was funded in whole or in part by [National Science Centre, Poland][2021/41/B/HS4/03349]. </sup>

+Home · OSMToolset.jl
Edit on GitHub

OSMToolset.jl

Documentation for OSMToolset.jl

For details please go to the Reference section.

Aknowledgments

<sup>This research was funded in whole or in part by [National Science Centre, Poland][2021/41/B/HS4/03349]. </sup>

diff --git a/dev/reference/index.html b/dev/reference/index.html index 145024f..40a78ad 100644 --- a/dev/reference/index.html +++ b/dev/reference/index.html @@ -1,6 +1,6 @@ -Reference · OSMToolset.jl
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Reference

Measuring Attractiveness Spatial Index

OSMToolset.find_poi — Method
find_poi(filename::AbstractString; attract_config::AttractivenessConfig=__builtin_attract)

Generates a DataFrame with points of interests and their attractivenss from a given XML filename.

This DataFrame can be later used with AttractivenessSpatIndex to build an attractivenss spatial index.

The attractiveness values for the index will be used ones from the attract_config file. By default builtin_attract_path will be used but you can define your own index.

source
OSMToolset.AttractivenessConfig — Type
Represents the configuration of the data scraping process from OSM XML.

Only those pieces of data will be scraped that are defined here.

The configuration is defined in a DataFrame with the following columns: class, key, values, points, range. Instead of the DataFrame a paths to a CSV file can be provided.

  • Constructors *
  • AttractivenessConfig() - default inbuilt configuration for data scraping. Note that the default configuration can change with library updates
  • AttractivenessConfig(filename::AbstractString) - use a CSV file with configuration
  • AttractivenessConfig(df::DataFrame) - use a DataFrame
source
OSMToolset.AttractivenessSpatIndex — Type
AttractivenessSpatIndex(filename::AbstractString)
-AttractivenessSpatIndex(df::AbstractDataFrame)

Builds an attractivness spatial index basing on data in some CSV file o a DataFrame

The CSV file or DataFrame should have the following columns: - class - data class in attractiveness index, each class name creates attractiveness dimension - key - key in the XML file <tag> - values - values in the <tag> (a star "*" catches all values) - points - number of influance points - range - maximum influence range in meters

When a DataFrame is provided the additional parameter refLLA can be provided for the reference LLA coordinates in the spatial index. The spatial index works in the ENU coordinate system.

source
OSMToolset.attractiveness — Method
attractiveness(sindex::AttractivenessSpatIndex, enu::ENU, aggregator::Function=+; explain::Bool=false)

Returns the multidimensional attractiveness measure for the given spatial index sindex and enu cooridanates. Note that the enu coordinates must use sindex.refLLA as the reference point. If explain is set to true the result will additionally contain details about objects used to calculate the attractiveness.

Attractiveness will be aggregagated in a way defined by the aggregator paramterr

source
Missing docstring.

Missing docstring for attractiveness(::AttractivenessSpatIndex, ::Float64; ::Float64). Check Documenter's build log for details.

Tiling OSM file

OSMToolset.calc_tiling — Method
calc_tiling(filename::AbstractString, latTileSize::Float64, lonTileSize::Float64)

Calculates recommended bounds, number of rows and columns for a given filename and size of tile latTileSize x lonTileSize.

source
OSMToolset.calc_tiling — Method
calc_tiling(bounds::Bounds, latTileSize::Float64, lonTileSize::Float64)

Calculates recommended bounds, number of rows and columns for a given bounds and size of tile latTileSize x lonTileSize.

source
OSMToolset.tile_osm_file — Method
tile_osm_file(filename::AbstractString, [bounds::Bounds]; nrow::Integer, ncol::Integer, [out_dir::AbstractString]

Provide the tiling functionality for maps. A filename will be open for processing and the tiling will be done around given bounds. If bounds are not given they will be calculated using getbounds function. The tiling will be performed with a matrix having nrow rows and ncol columns. The output will be written to the folder name out_dir. If none out_dir is given than as the output is written to where filename is located.

source

Helper functions

OSMToolset.FloatLon — Type
This is an AbstractFloat type representing geographic longitude as the values may wrap around
source
OSMToolset.Node — Type
Node
+Reference · OSMToolset.jl
Edit on GitHub
Reference
Measuring Attractiveness Spatial Index
OSMToolset.find_poi — Method
find_poi(filename::AbstractString; attract_config::AttractivenessConfig=__builtin_attract)
Generates a DataFrame with points of interests and their attractivenss from a given XML filename.
This DataFrame can be later used with AttractivenessSpatIndex to build an attractivenss spatial index.
The attractiveness values for the index will be used ones from the attract_config file. By default builtin_attract_path will be used but you can define your own index.
source
OSMToolset.AttractivenessConfig — Type
Represents the configuration of the data scraping process from OSM XML.
Only those pieces of data will be scraped that are defined here.
The configuration is defined in a DataFrame with the following columns: class, key, values, points, range. Instead of the DataFrame a paths to a CSV file can be provided.
  • Constructors *
  • AttractivenessConfig() - default inbuilt configuration for data scraping.   Note that the default configuration can change with library updates
  • AttractivenessConfig(filename::AbstractString) - use a CSV file with configuration
  • AttractivenessConfig(df::DataFrame) - use a DataFrame
source
OSMToolset.AttractivenessSpatIndex — Type
AttractivenessSpatIndex(filename::AbstractString)
+AttractivenessSpatIndex(df::AbstractDataFrame)
Builds an attractivness spatial index basing on data in some CSV file o a DataFrame
The CSV file or DataFrame should have the following columns:     - class - data class in attractiveness index, each class name creates attractiveness dimension     - key - key in the XML file <tag>     - values - values in the <tag> (a star "*" catches all values)     - points - number of influance points      - range - maximum influence range in meters 
When a DataFrame is provided the additional parameter refLLA can be provided for the reference  LLA coordinates in the spatial index. The spatial index works in the ENU coordinate system.
source
OSMToolset.attractiveness — Method
attractiveness(sindex::AttractivenessSpatIndex, enu::ENU, aggregator::Function=+; explain::Bool=false)
Returns the multidimensional attractiveness measure for the given spatial index sindex and enu cooridanates. Note that the enu coordinates must use sindex.refLLA as the reference point. If explain is set to true the result will additionally contain details  about objects used to calculate the attractiveness.
Attractiveness will be aggregagated in a way defined by the aggregator function.
source
OSMToolset.attractiveness — Method
attractiveness(sindex::AttractivenessSpatIndex, latitude::Float64, longitude::Float64, aggregator::Function=+; explain::Bool=false)
Returns the multidimensional attractiveness measure for the given spatial index sindex and lattitude and longitude If explain is set to true the result will additionally contain details  about objects used to calculate the attractiveness
source
Missing docstring.
Missing docstring for attractiveness(::AttractivenessSpatIndex, ::LLA; ::Function; ::Bool). Check Documenter's build log for details.
Tiling OSM file
OSMToolset.calc_tiling — Method
calc_tiling(filename::AbstractString, latTileSize::Float64, lonTileSize::Float64)
Calculates recommended bounds, number of rows and columns for a given filename and size of tile latTileSize x lonTileSize.
source
OSMToolset.calc_tiling — Method
calc_tiling(bounds::Bounds, latTileSize::Float64, lonTileSize::Float64)
Calculates recommended bounds, number of rows and columns for a given bounds and size of tile latTileSize x lonTileSize.
source
OSMToolset.tile_osm_file — Method
tile_osm_file(filename::AbstractString, [bounds::Bounds]; nrow::Integer, ncol::Integer, [out_dir::AbstractString]
Provide the tiling functionality for maps. A filename will be open for processing and the tiling will be done around given bounds. If bounds are not given they will be calculated using getbounds function. The tiling will be performed with a matrix having nrow rows and ncol columns. The output will be written to the folder name out_dir.   If none out_dir is given than as the output is written to where filename is located.
source
Helper functions
OSMToolset.FloatLon — Type
This is an AbstractFloat type representing geographic longitude as the values may wrap around
source
OSMToolset.Node — Type
Node
 
 A node is a point in the map. It has an id, a latitude and a longitude.
-All nodes need to be stored in memory in this format.
source

+All nodes need to be stored in memory in this format.
source
diff --git a/dev/search/index.html b/dev/search/index.html index f1db6aa..46e3dbc 100644 --- a/dev/search/index.html +++ b/dev/search/index.html @@ -1,2 +1,2 @@ -Search · OSMToolset.jl

Loading search...

    +Search · OSMToolset.jl

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