explore_mobloc: Explore the visualize propagation, prior, connection...

In MobilePhoneESSnetBigData/mobvis: Visualization of mobile phone location algorithm results

Explore the visualize propagation, prior, connection likelihood and location posterior probabilities per raster tile

Description

Explore the visualize propagation, prior, connection likelihood and location posterior probabilities per raster tile. When the raster is large (say larger than 30 by 30 kilometers), we recommend to specify the filter arguemnt.

Usage

explore_mobloc(
  cp,
  raster,
  strength,
  priorlist,
  llhlist,
  param,
  filter = NULL,
  coverage_map_dBm = NULL,
  coverage_map_s = NULL,
  best_server_map = NULL,
  settings = mobvis_settings_interactive(),
  height = 600
)

Arguments

cp	cellplan, validated with validate_cellplan
raster	raster object that contains the raster tile index numbers (e.g. created with create_raster)
strength	a signal strength model object, which is the result of compute_sig_strength
priorlist	list of priors
llhlist	list of likelihoods
param	parameter list created with mobloc_param
filter	bounding box of the filter of the visualized raster. If not specified, the whole raster is shown, which could be very slow. Therefore, we recommand to use a filter when the raster covers a large area (say 30 by 30 kilometers).
coverage_map_dBm	coverage map, created with create_coverage_map (with type = "dBm"). If not specified, it will be created (which takes some time).
coverage_map_s	coverage map, created with create_coverage_map (with type = "s"). If not specified, it will be created (which takes some time).
best_server_map	best server map, created with create_best_server_map. If not specified, it will be created (which takes some time).
settings	mobvis settings, see mobvis_settings
height	height of the map in pixels

Note

Note that duo to the reprojection of the raster to the web mercator projection (for interactive maps), the visualized raster does not correspond exactly to the output raster.

See Also

vignette("mobloc")

Examples

## Not run: 

require(mobloc)

# set parameters
ZL_param <- mobloc_param()

# load data
data("ZL_cellplan", "ZL_muni", "ZL_elevation", "ZL_landuse")

# create environment layer (needed to calculate path loss exponent (ple))
ZL_envir <- combine_raster_layers(ZL_landuse, weights = c(1, 1, 1, 0, 0))

# validate cellplan
ZL_cellplan <- validate_cellplan(ZL_cellplan, param = ZL_param, region = ZL_muni,
    envir = ZL_envir, elevation = ZL_elevation)

# create raster
ZL_bbox <- sf::st_bbox(c(xmin = 4012000, ymin = 3077000, xmax = 4048000, ymax = 3117000),
    crs = sf::st_crs(3035))
ZL_raster <- create_raster(ZL_bbox)

# compute the signal strength model
ZL_strength <- compute_sig_strength(cp = ZL_cellplan, raster = ZL_raster,
    elevation = ZL_elevation, param = ZL_param)

# create likelihoods
ZL_strength_llh <- create_strength_llh(ZL_strength, param = ZL_param)
ZL_voronoi_llh <- create_voronoi_llh(ZL_cellplan, ZL_raster)

# create priors
ZL_uniform_prior <- create_uniform_prior(ZL_raster)
ZL_network_prior <- create_network_prior(ZL_strength, ZL_raster)
ZL_landuse_prior <- create_prior(ZL_landuse, weights = c(1, 1, .1, 0, .5))

# explore the results
explore_mobloc(ZL_cellplan, ZL_raster, ZL_strength,
  list(landuse = ZL_landuse_prior, network = ZL_network_prior, uniform = ZL_uniform_prior),
       list(Strength = ZL_strength_llh, Voronoi = ZL_voronoi_llh),
      param = ZL_param)

## End(Not run)

MobilePhoneESSnetBigData/mobvis documentation built on Feb. 3, 2024, 2:49 p.m.