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sensors4plumes (version 0.9.3)

Test and Optimise Sampling Designs Based on Plume Simulations

Description

Test sampling designs by several flexible cost functions, usually based on the simulations, and optimise sampling designs using different optimisation algorithms; load plume simulations (on lattice or points) even if they do not fit into memory.

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Version

Install

install.packages('sensors4plumes')

Monthly Downloads

10

Version

0.9.3

License

GPL-3

Maintainer

Kristina Helle

Last Published

May 7th, 2018

Functions in sensors4plumes (0.9.3)

optimiseSD_manual

Plot cost map for interactive adding and deleting of sensors
interpolationErrorFunctions

Compare original and interpolated maps point-wise
optimiseSD_global

Derive one or all globally optimal sampling designs for plume detection
spatialSpread

Cost function based on sensor locations only
optimiseSD_ssa

Spatial Simulated Annealing optimisation algorithm
subsetSDF.SpatialPolygridDataFrame

Subsetting objects of class SpatialPolygridDataFrame
plotSD

Plot sampling designs and related cost maps
optimiseSD_greedy

Greedy optimisation algorithm
spplotLog

Plot methods for spatial data with logarithmic scale
subsetSDF

Subsetting objects of class SpatialDataFrame
optimalSD

Optimised sampling designs
subsetSDF.SpatialIndexDataFrame

Subsetting objects of class SpatialIndexDataFrame
simulationsApply

Apply functions value-wise, location-wise, or plume-wise to Simulations
spatialSpreadFunctions

Cost functions dependent only on sensor locations
plot.Simulations

Plot overview of simulations.
interpolate

Interpolate many maps at once -- even if they do not fit into memory
optimisationCurve

Plot Optimisation Curve
subset.Simulations

Subsetting Simulations
radioactivePlumes

Simulations of radioactive plumes
optimiseSD

(Spatial) optimisation of sampling designs
replaceDefault

Replace default values in functions and check parameter list
points2polygrid

Turn points (and data) into a SpatialPolygridDataFrame
similaritySD

Determine (spatial) similarity between sampling designs
polygrid2grid

Coerce SpatialPolygridDataFrame into SpatialGridDataFrame and geoTiff file
summaryLocations

Summarise values of Simulations by locations
summaryPlumes

Summarise values of Simulations by plumes
sensors4plumes-package

Test and optimise sampling designs based on plume simulations
optimiseSD_genetic

Optimisation of sensor locations by a binary genetic algorithm
areaSDF

Areas of elements of SpatialDataFrame objects
cbindSimulations

Combine plumes of Simulations objects with coinciding parameters
SDF2simulations

Turn a SpatialDataFrame into Simulations.
SpatialPolygridDataFrame-class

Class "SpatialPolygridDataFrame"
SpatialDataFrame-class

Class "SpatialDataFrame"
testDataArtificial

Small artificial test data
SpatialIndexDataFrame-class

Class "SpatialIndexDataFrame"
SDLonLat

Transform locations of simulations into longitude latitude coordinates
mesurementsResultFunctions

Cost functions by plume-wise summary of values at locations
copySimulations

Copy Simulations (including raster files)
SimulationsSmall

Artificial, small test data.
Simulations-class

Class "Simulations"
extractSpatialDataFrame

Extract some values of Simulations to a SpatialDataFrame with the same spatial properties.
changeSimulationsPath

Reset file paths in Simulations objects
interpolationError

Interpolate many maps at once, compare them to the original and determine a global error
measurementsResult

General cost function by plume-wise summary of values at locations
medianVariogram

Variogram of radioactivePlumes
loadSimulations

Load values from raster or text files into Simulations objects