Search over all networks using a keyword, a custom query or a spatial object
If the query is a character string, then all character columns in the table
are searched and the entries for which at least one
partial match was found are returned.
Alternatively, a named list can be used to look for an exact match in a specific column (see Details section)
Arguments
- query
either a character string including a single keyword or a named list containing a custom query (see details section below), or a spatial object (see the description of
query_sf). Note that if an empty character string is passed, then all datasets available are returned.- verbose
a
logical. Should extra information be reported on progress?- ...
further arguments to be passed to
httr::GET().- query_sf
a spatial object of class
sfused to search in a specific geographical area.
Value
An object of class mgSearchNetworks, which is a data.frame object with all networks informations
Details
Names of the list should match one of the column names within the table.
For the networks table, those are
id: unique identifier of the network;
all_interactions: false interaction can be considered as real false interaction
dataset_id: the identifier of the dataset;
public: network publicly available;
Note that for lists with more than one element, only the first element is used, the others are ignored. An example is provided below.
Functions
search_networks_sf(): Search networks within a spatial object passed as an argument. Note thatsfmust be installed to use this function.
Examples
# \donttest{
mg_insect <- search_networks(query = "insect%")
#> Data retrieval 100%
#>
#> Found 14 networks
# Retrieve the search results
nets_insect <- get_collection(mg_insect)
#> Processing id: 18 1/1
#>
#> Data retrieval 100%
#>
#> Data retrieval 100%
#>
#> Processing id: 4 1/1
#>
#> Processing id: 4 1/1
#>
#> Processing id: 909 1/1
#>
#> Data retrieval 50%
#> Data retrieval 100%
#>
#> Data retrieval 33.3%
#> Data retrieval 66.7%
#> Data retrieval 100%
#>
#> Processing id: 9 1/1
#>
#> Processing id: 9 1/1
#>
#> Processing id: 948 1/1
#>
#> Data retrieval 20%
#> Data retrieval 40%
#> Data retrieval 60%
#> Data retrieval 80%
#> Data retrieval 100%
#>
#> Data retrieval 11.1%
#> Data retrieval 22.2%
#> Data retrieval 33.3%
#> Data retrieval 44.4%
#> Data retrieval 55.6%
#> Data retrieval 66.7%
#> Data retrieval 77.8%
#> Data retrieval 88.9%
#> Data retrieval 100%
#>
#> Processing id: 66 1/1
#>
#> Processing id: 65 1/1
#>
#> Processing id: 1460 1/1
#>
#> Data retrieval 100%
#>
#> Data retrieval 100%
#>
#> Processing id: 91 1/1
#>
#> Processing id: 90 1/1
#>
#> Processing id: 1461 1/1
#>
#> Data retrieval 100%
#>
#> Data retrieval 50%
#> Data retrieval 100%
#>
#> Processing id: 91 1/1
#>
#> Processing id: 90 1/1
#>
#> Processing id: 1471 1/1
#>
#> Data retrieval 100%
#>
#> Data retrieval 100%
#>
#> Processing id: 99 1/1
#>
#> Processing id: 98 1/1
#>
#> Processing id: 1493 1/1
#>
#> Data retrieval 100%
#>
#> Data retrieval 100%
#>
#> Processing id: 114 1/1
#>
#> Processing id: 113 1/1
#>
#> Processing id: 1501 1/1
#>
#> Data retrieval 100%
#>
#> Data retrieval 100%
#>
#> Processing id: 118 1/1
#>
#> Processing id: 117 1/1
#>
#> Processing id: 1500 1/1
#>
#> Data retrieval 100%
#>
#> Data retrieval 100%
#>
#> Processing id: 118 1/1
#>
#> Processing id: 117 1/1
#>
#> Processing id: 1502 1/1
#>
#> Data retrieval 100%
#>
#> Data retrieval 100%
#>
#> Processing id: 119 1/1
#>
#> Processing id: 118 1/1
#>
#> Processing id: 1507 1/1
#>
#> Data retrieval 100%
#>
#> Data retrieval 100%
#>
#> Processing id: 124 1/1
#>
#> Processing id: 123 1/1
#>
#> Processing id: 1508 1/1
#>
#> Data retrieval 100%
#>
#> Data retrieval 50%
#> Data retrieval 100%
#>
#> Processing id: 124 1/1
#>
#> Processing id: 123 1/1
#>
#> Processing id: 1510 1/1
#>
#> Data retrieval 100%
#>
#> Data retrieval 100%
#>
#> Processing id: 126 1/1
#>
#> Processing id: 125 1/1
#>
#> Processing id: 1566 1/1
#>
#> Data retrieval 100%
#>
#> Data retrieval 100%
#>
#> Processing id: 154 1/1
#>
#> Processing id: 151 1/1
#>
# Spatial query
if (requireNamespace("sf", quietly = TRUE)) {
area <- sf::st_read(system.file("shape/nc.shp", package="sf"))
networks_in_area <- search_networks_sf(area, verbose = FALSE)
plot(networks_in_area)
} else warning("Package sf is missing")
#> Reading layer `nc' from data source
#> `/github/home/R/x86_64-pc-linux-gnu-library/4.5/sf/shape/nc.shp'
#> using driver `ESRI Shapefile'
#> Simple feature collection with 100 features and 14 fields
#> Geometry type: MULTIPOLYGON
#> Dimension: XY
#> Bounding box: xmin: -84.32385 ymin: 33.88199 xmax: -75.45698 ymax: 36.58965
#> Geodetic CRS: NAD27
# Retrieve network ID 5013
net_5013 <- search_networks(query = list(id = 5013))
#> Data retrieval 100%
#>
#> Found 1 networks
# Network(s) of dataset ID 19
mg_19 <- search_networks(list(dataset_id = 19))
#> Data retrieval 100%
#>
#> Found 1 networks
# }