Geospatial
geo distancegeo distancegeo distancegeo bearinggeo destinationgeo midpointgeo containsgeo polygongeo nearestgeo geohashgeo geohash_decodegeo utmgeo idwgeo idwgeo variogramgeo variogramgeo kriginggeo kriginggeo morans_igeo morans_igeo gearys_cgeo gearys_cgeo lisageo lisageo hotspotsgeo hotspotsgeo ripley_kgeo ripley_kgeo nnigeo nnigeo dbscangeo buffergeo buffergeo convex_hullgeo simplifygeo lengthgeo bboxgeo intersectsgeo projectgeo unprojectgeo kdegeo kdegeo gridgeo geojsongeo spatial_laggeo spatial_lag
geo distance <lat1> <lon1> <lat2> <lon2>
Description
Great-circle distance (haversine) in km
Great-circle distance (haversine) in km
Parameters
lat1: Latitude 1 - Number - required
lon1: Longitude 1 - Number - required
lat2: Latitude 2 - Number - required
lon2: Longitude 2 - Number - required
lat1: Latitude 1 - Number - required
lon1: Longitude 1 - Number - required
lat2: Latitude 2 - Number - required
lon2: Longitude 2 - Number - required
admin
geo distance 48.8566 2.3522 51.5074 -0.1278
mentdb
343.5565348808832
geo distance <lat1> <lon1> <lat2> <lon2> <unit>
Description
Distance in a unit: m, km, mi (miles), nm (nautical miles)
Distance in a unit: m, km, mi (miles), nm (nautical miles)
Parameters
lat1: Latitude 1 - Number - required
lon1: Longitude 1 - Number - required
lat2: Latitude 2 - Number - required
lon2: Longitude 2 - Number - required
unit: m, km, mi or nm - String - required
lat1: Latitude 1 - Number - required
lon1: Longitude 1 - Number - required
lat2: Latitude 2 - Number - required
lon2: Longitude 2 - Number - required
unit: m, km, mi or nm - String - required
admin
geo distance -20.8789 55.4481 -21.3393 55.4781 "nm"
mentdb
27.69368983431146
geo distance <lat1> <lon1> <lat2> <lon2> <unit> <method>
Description
Distance with a method: haversine (sphere) or vincenty (WGS84 ellipsoid, millimetre accuracy)
Distance with a method: haversine (sphere) or vincenty (WGS84 ellipsoid, millimetre accuracy)
Parameters
lat1: Latitude 1 - Number - required
lon1: Longitude 1 - Number - required
lat2: Latitude 2 - Number - required
lon2: Longitude 2 - Number - required
unit: The unit - String - required
method: haversine or vincenty - String - required
lat1: Latitude 1 - Number - required
lon1: Longitude 1 - Number - required
lat2: Latitude 2 - Number - required
lon2: Longitude 2 - Number - required
unit: The unit - String - required
method: haversine or vincenty - String - required
admin
geo distance -37.95103342 144.42486789 -37.65282114 143.92649554 "m" "vincenty"
mentdb
54972.2705048579
geo bearing <lat1> <lon1> <lat2> <lon2>
Description
Initial bearing (degrees from the north, clockwise) from point 1 to point 2
Initial bearing (degrees from the north, clockwise) from point 1 to point 2
Parameters
lat1: Latitude 1 - Number - required
lon1: Longitude 1 - Number - required
lat2: Latitude 2 - Number - required
lon2: Longitude 2 - Number - required
lat1: Latitude 1 - Number - required
lon1: Longitude 1 - Number - required
lat2: Latitude 2 - Number - required
lon2: Longitude 2 - Number - required
admin
geo bearing 48.8566 2.3522 51.5074 -0.1278
mentdb
330.02109285606355
geo destination <lat> <lon> <bearing> <distance_km>
Description
The point reached from a start with an initial bearing and a distance in km
The point reached from a start with an initial bearing and a distance in km
Parameters
lat: Latitude - Number - required
lon: Longitude - Number - required
bearing: The bearing in degrees - Number - required
distance_km: The distance in km - Number - required
lat: Latitude - Number - required
lon: Longitude - Number - required
bearing: The bearing in degrees - Number - required
distance_km: The distance in km - Number - required
admin
geo destination 48.8566 2.3522 330.02 343.56
mentdb
[51.50739535, -0.1279068]
geo midpoint <lat1> <lon1> <lat2> <lon2>
Description
Middle of the great circle between two points
Middle of the great circle between two points
Parameters
lat1: Latitude 1 - Number - required
lon1: Longitude 1 - Number - required
lat2: Latitude 2 - Number - required
lon2: Longitude 2 - Number - required
lat1: Latitude 1 - Number - required
lon1: Longitude 1 - Number - required
lat2: Latitude 2 - Number - required
lon2: Longitude 2 - Number - required
admin
geo midpoint 48.8566 2.3522 51.5074 -0.1278
mentdb
[50.18859488, 1.14661763]
geo contains <json_polygon> <json_points>
Description
Is a point (or are points) inside a polygon: 1 or 0 (the border counts as inside)
Is a point (or are points) inside a polygon: 1 or 0 (the border counts as inside)
Parameters
json_polygon: The polygon [[lat, lon], ...] - String - required
json_points: A point [lat, lon] or points - String - required
json_polygon: The polygon [[lat, lon], ...] - String - required
json_points: A point [lat, lon] or points - String - required
admin
geo contains "[[-20.87, 55.45], [-20.93, 55.66], [-21.1, 55.82], [-21.37, 55.8], [-21.39, 55.53], [-21.26, 55.32], [-21.04, 55.21], [-20.9, 55.29]]" "[[-20.8789, 55.4481], [-20.16, 57.50]]"
mentdb
[1, 0]
geo polygon <json_polygon>
Description
Area (m2, km2, ha, on the ellipsoid authalic sphere), perimeter in km and centroid of a polygon
Area (m2, km2, ha, on the ellipsoid authalic sphere), perimeter in km and centroid of a polygon
Parameters
json_polygon: The polygon [[lat, lon], ...] - String - required
json_polygon: The polygon [[lat, lon], ...] - String - required
admin
geo polygon "[[-20.87, 55.45], [-20.93, 55.66], [-21.1, 55.82], [-21.37, 55.8], [-21.39, 55.53], [-21.26, 55.32], [-21.04, 55.21], [-20.9, 55.29]]"
mentdb
{"area_m2": 2.669268321482069E9, "area_km2": 2669.268321482069, "area_ha": 266926.8321482069, "perimeter_km": 193.82131417533924, "centroid": [-21.13113775, 55.53068193], "vertices": 8}
geo nearest <json_points> <json_target> <k>
Description
The k nearest points to a target with their index and distance in km
The k nearest points to a target with their index and distance in km
Parameters
json_points: The points [[lat, lon], ...] - String - required
json_target: The target [lat, lon] - String - required
k: The number of points - Number - required
json_points: The points [[lat, lon], ...] - String - required
json_target: The target [lat, lon] - String - required
k: The number of points - Number - required
admin
geo nearest "[[-20.88, 55.45], [-21.00, 55.27], [-21.33, 55.47], [-21.13, 55.55]]" "[-21.05, 55.40]" 2
mentdb
[{"index": 1, "distance_km": 14.593537786540201}, {"index": 3, "distance_km": 17.92507563331795}]
geo geohash <lat> <lon> <precision>
Description
Geohash of a point (precision 1 to 12 characters): a short code where the nearby points share the prefix
Geohash of a point (precision 1 to 12 characters): a short code where the nearby points share the prefix
Parameters
lat: Latitude - Number - required
lon: Longitude - Number - required
precision: The number of characters - Number - required
lat: Latitude - Number - required
lon: Longitude - Number - required
precision: The number of characters - Number - required
admin
geo geohash 57.64911 10.40744 11
mentdb
u4pruydqqvj
geo geohash_decode <geohash>
Description
Centre, error and bounding box of a geohash
Centre, error and bounding box of a geohash
Parameters
geohash: The geohash - String - required
geohash: The geohash - String - required
admin
geo geohash_decode "u4pruydqqvj"
mentdb
{"lat": 57.64911063015461, "lon": 10.407439693808556, "lat_error": 6.705522537231445E-7, "lon_error": 6.705522537231445E-7, "bbox": [57.649109959602356, 10.407439023256302, 57.64911130070686, 10.40744036436081]}
geo utm <lat> <lon>
Description
UTM coordinates (WGS84): zone, latitude band, hemisphere, easting and northing in metres
UTM coordinates (WGS84): zone, latitude band, hemisphere, easting and northing in metres
Parameters
lat: Latitude - Number - required
lon: Longitude - Number - required
lat: Latitude - Number - required
lon: Longitude - Number - required
admin
geo utm 48.8566 2.3522
mentdb
{"zone": 31, "band": "U", "hemisphere": "N", "easting": 452482.53, "northing": 5411717.18}
Saint-Denis, Reunion
admin
geo utm -20.8789 55.4481
mentdb
{"zone": 40, "band": "K", "hemisphere": "S", "easting": 338568.32, "northing": 7690475.44}
geo idw <json_known> <json_targets>
Description
Inverse distance weighting: the value at each target from the measured points [lat, lon, value], weights 1 / distance^2
Inverse distance weighting: the value at each target from the measured points [lat, lon, value], weights 1 / distance^2
Parameters
json_known: The measures [[lat, lon, value], ...] - String - required
json_targets: The targets [[lat, lon], ...] - String - required
json_known: The measures [[lat, lon, value], ...] - String - required
json_targets: The targets [[lat, lon], ...] - String - required
admin
geo idw "[[-20.88, 55.45, 26.1], [-21.0, 55.27, 25.4], [-21.33, 55.47, 24.8], [-21.13, 55.55, 17.2], [-20.95, 55.65, 25.6], [-21.26, 55.33, 23.9], [-21.07, 55.36, 20.1], [-21.2, 55.62, 22.4], [-21.38, 55.62, 24.2], [-20.92, 55.33, 25.9]]" "[[-21.05, 55.40], [-21.25, 55.55]]"
mentdb
[21.277462108794847, 22.467337037366836]
geo idw <json_known> <json_targets> <json_params>
Description
IDW with parameters: power (2), neighbors (0 = all), radius_km (0 = no limit)
IDW with parameters: power (2), neighbors (0 = all), radius_km (0 = no limit)
Parameters
json_known: The measures - String - required
json_targets: The targets - String - required
json_params: The parameters - String - required
json_known: The measures - String - required
json_targets: The targets - String - required
json_params: The parameters - String - required
admin
geo idw "[[-20.88, 55.45, 26.1], [-21.0, 55.27, 25.4], [-21.33, 55.47, 24.8], [-21.13, 55.55, 17.2], [-20.95, 55.65, 25.6], [-21.26, 55.33, 23.9], [-21.07, 55.36, 20.1], [-21.2, 55.62, 22.4], [-21.38, 55.62, 24.2], [-20.92, 55.33, 25.9]]" "[[-21.05, 55.40]]" "{\"power\": 3, \"neighbors\": 4}"
mentdb
[20.34942459324603]
Used in use cases (2 recipes)
Agronomist › Area of a field and soil map
Climate & environment scientist › Temperature between weather stations
Agronomist › Area of a field and soil map
Climate & environment scientist › Temperature between weather stations
geo variogram <json_known>
Description
Empirical semivariogram of measures (bins of distance up to half the maximum distance) and the fitted model: nugget, sill, range in km
Empirical semivariogram of measures (bins of distance up to half the maximum distance) and the fitted model: nugget, sill, range in km
Parameters
json_known: The measures [[lat, lon, value], ...] - String - required
json_known: The measures [[lat, lon, value], ...] - String - required
admin
geo variogram "[[-20.88, 55.45, 26.1], [-21.0, 55.27, 25.4], [-21.33, 55.47, 24.8], [-21.13, 55.55, 17.2], [-20.95, 55.65, 25.6], [-21.26, 55.33, 23.9], [-21.07, 55.36, 20.1], [-21.2, 55.62, 22.4], [-21.38, 55.62, 24.2], [-20.92, 55.33, 25.9]]"
mentdb
{"model": "spherical", "nugget": 9.278736958917958E-22, "sill": 25.10133333304355, "range_km": 75.34333788215689, "empirical": [{"distance_km": 10.75166747811554, "semivariance": 6.822499999999998, "pairs": 2}, {"distance_km": 12.696944864971885, "semivariance": 7.0324999999999935, "pairs": 2}, {"distance_km": 16.642521317933056, "semivariance": 5.801666666666662, "pairs": 3}, {"distance_km": 20.01511444203574, "semivariance": 1.6200000000000012, "pairs": 1}, {"distance_km": 22.0269293920428, "semivariance": 9.707857142857145, "pairs": 7}, {"distance_km": 23.73456001660908, "semivariance": 28.88000000000001, "pairs": 1}, {"distance_km": 28.319550125798465, "semivariance": 13.297500000000001, "pairs": 4}]}
geo variogram <json_known> <json_params>
Description
Variogram with parameters: model (spherical, exponential, gaussian), bins
Variogram with parameters: model (spherical, exponential, gaussian), bins
Parameters
json_known: The measures - String - required
json_params: The parameters - String - required
json_known: The measures - String - required
json_params: The parameters - String - required
admin
geo variogram "[[-20.88, 55.45, 26.1], [-21.0, 55.27, 25.4], [-21.33, 55.47, 24.8], [-21.13, 55.55, 17.2], [-20.95, 55.65, 25.6], [-21.26, 55.33, 23.9], [-21.07, 55.36, 20.1], [-21.2, 55.62, 22.4], [-21.38, 55.62, 24.2], [-20.92, 55.33, 25.9]]" "{\"model\": \"exponential\", \"bins\": 6}"
mentdb
{"model": "exponential", "nugget": 4.4307876205388516E-21, "sill": 25.101333333333333, "range_km": 118.67196109218135, "empirical": [{"distance_km": 11.724306171543711, "semivariance": 6.927499999999996, "pairs": 4}, {"distance_km": 16.642521317933056, "semivariance": 5.801666666666662, "pairs": 3}, {"distance_km": 21.99313113366049, "semivariance": 10.939444444444447, "pairs": 9}, {"distance_km": 28.319550125798465, "semivariance": 13.297500000000001, "pairs": 4}]}
geo kriging <json_known> <json_targets>
Description
Ordinary kriging: the best linear unbiased prediction at each target with its variance, from a variogram fitted on the measures (up to 1500 points)
Ordinary kriging: the best linear unbiased prediction at each target with its variance, from a variogram fitted on the measures (up to 1500 points)
Parameters
json_known: The measures [[lat, lon, value], ...] - String - required
json_targets: The targets [[lat, lon], ...] - String - required
json_known: The measures [[lat, lon, value], ...] - String - required
json_targets: The targets [[lat, lon], ...] - String - required
admin
geo kriging "[[-20.88, 55.45, 26.1], [-21.0, 55.27, 25.4], [-21.33, 55.47, 24.8], [-21.13, 55.55, 17.2], [-20.95, 55.65, 25.6], [-21.26, 55.33, 23.9], [-21.07, 55.36, 20.1], [-21.2, 55.62, 22.4], [-21.38, 55.62, 24.2], [-20.92, 55.33, 25.9]]" "[[-21.05, 55.40], [-21.25, 55.55]]"
mentdb
{"variogram": {"model": "spherical", "nugget": 9.278736958917958E-22, "sill": 25.10133333304355, "range_km": 75.34333788215689}, "predictions": [{"prediction": 20.49957613494371, "variance": 3.6141285975346307, "sd": 1.9010861625751292}, {"prediction": 22.119957641851624, "variance": 4.85855430366677, "sd": 2.2042128535299783}]}
geo kriging <json_known> <json_targets> <json_params>
Description
Kriging with parameters: model, bins, or a given variogram (nugget, sill, range_km)
Kriging with parameters: model, bins, or a given variogram (nugget, sill, range_km)
Parameters
json_known: The measures - String - required
json_targets: The targets - String - required
json_params: The parameters - String - required
json_known: The measures - String - required
json_targets: The targets - String - required
json_params: The parameters - String - required
admin
geo kriging "[[-20.88, 55.45, 26.1], [-21.0, 55.27, 25.4], [-21.33, 55.47, 24.8], [-21.13, 55.55, 17.2], [-20.95, 55.65, 25.6], [-21.26, 55.33, 23.9], [-21.07, 55.36, 20.1], [-21.2, 55.62, 22.4], [-21.38, 55.62, 24.2], [-20.92, 55.33, 25.9]]" "[[-21.05, 55.40]]" "{\"model\": \"exponential\", \"nugget\": 0.5, \"sill\": 8, \"range_km\": 30}"
mentdb
{"variogram": {"model": "exponential", "nugget": 0.5, "sill": 8, "range_km": 30}, "predictions": [{"prediction": 21.592056471922913, "variance": 5.141665715480597, "sd": 2.2675241377944793}]}
geo morans_i <json_points>
Description
Global Moran's I of spatial autocorrelation of values at [lat, lon, value] points (k nearest neighbors, row-standardized), permutation p-value
Global Moran's I of spatial autocorrelation of values at [lat, lon, value] points (k nearest neighbors, row-standardized), permutation p-value
Parameters
json_points: The points [[lat, lon, value], ...] - String - required
json_points: The points [[lat, lon, value], ...] - String - required
admin
geo morans_i "[[-21.132, 55.3016, 11.9], [-21.2167, 55.4508, 11.02], [-20.791, 55.6502, 19.25], [-20.9817, 55.3883, 14.66], [-21.1637, 55.3031, 12.23], [-20.8355, 55.6533, 20.52], [-20.8498, 55.3467, 17.49], [-20.8841, 55.6773, 18.63], [-20.81, 55.2934, 17.63], [-20.997, 55.3389, 14.14], [-21.0132, 55.2947, 16.57], [-20.9762, 55.4001, 14.68], [-20.7956, 55.5362, 20.52], [-20.9958, 55.457, 13.78], [-20.9505, 55.4655, 16.44], [-20.8437, 55.2716, 18.85], [-21.2268, 55.5632, 10.23], [-21.0144, 55.4214, 15.93], [-20.7514, 55.3478, 19.4], [-20.9337, 55.3882, 16.68]]"
mentdb
{"n": 20, "i": 0.5647620604622158, "expected": -0.05263157894736842, "z": 5.751601751367616, "p_value": 0.001, "permutations": 999, "interpretation": "positive autocorrelation (similar neighbors)"}
geo morans_i <json_points> <json_params>
Description
Moran's I with parameters: k (5 neighbors) or band_km (distance band), permutations (999), seed
Moran's I with parameters: k (5 neighbors) or band_km (distance band), permutations (999), seed
Parameters
json_points: The points - String - required
json_params: The parameters - String - required
json_points: The points - String - required
json_params: The parameters - String - required
admin
geo morans_i "[[-21.132, 55.3016, 11.9], [-21.2167, 55.4508, 11.02], [-20.791, 55.6502, 19.25], [-20.9817, 55.3883, 14.66], [-21.1637, 55.3031, 12.23], [-20.8355, 55.6533, 20.52], [-20.8498, 55.3467, 17.49], [-20.8841, 55.6773, 18.63], [-20.81, 55.2934, 17.63], [-20.997, 55.3389, 14.14], [-21.0132, 55.2947, 16.57], [-20.9762, 55.4001, 14.68], [-20.7956, 55.5362, 20.52], [-20.9958, 55.457, 13.78], [-20.9505, 55.4655, 16.44], [-20.8437, 55.2716, 18.85], [-21.2268, 55.5632, 10.23], [-21.0144, 55.4214, 15.93], [-20.7514, 55.3478, 19.4], [-20.9337, 55.3882, 16.68]]" "{\"band_km\": 15}"
mentdb
{"n": 20, "i": 0.8541539326084242, "expected": -0.05263157894736842, "z": 4.806601407622025, "p_value": 0.001, "permutations": 999, "interpretation": "positive autocorrelation (similar neighbors)"}
Used in use cases (1 recipe)
Epidemiologist › Dengue incidence by town: spatial autocorrelation and hot spots
Epidemiologist › Dengue incidence by town: spatial autocorrelation and hot spots
geo gearys_c <json_points>
Description
Geary's C (local differences): < 1 positive autocorrelation, > 1 negative, permutation p-value
Geary's C (local differences): < 1 positive autocorrelation, > 1 negative, permutation p-value
Parameters
json_points: The points - String - required
json_points: The points - String - required
admin
geo gearys_c "[[-21.132, 55.3016, 11.9], [-21.2167, 55.4508, 11.02], [-20.791, 55.6502, 19.25], [-20.9817, 55.3883, 14.66], [-21.1637, 55.3031, 12.23], [-20.8355, 55.6533, 20.52], [-20.8498, 55.3467, 17.49], [-20.8841, 55.6773, 18.63], [-20.81, 55.2934, 17.63], [-20.997, 55.3389, 14.14], [-21.0132, 55.2947, 16.57], [-20.9762, 55.4001, 14.68], [-20.7956, 55.5362, 20.52], [-20.9958, 55.457, 13.78], [-20.9505, 55.4655, 16.44], [-20.8437, 55.2716, 18.85], [-21.2268, 55.5632, 10.23], [-21.0144, 55.4214, 15.93], [-20.7514, 55.3478, 19.4], [-20.9337, 55.3882, 16.68]]"
mentdb
{"n": 20, "c": 0.34235858605153313, "expected": 1, "z": -6.146282043626115, "p_value": 0.001, "permutations": 999, "interpretation": "positive autocorrelation (similar neighbors)"}
geo gearys_c <json_points> <json_params>
Description
Geary's C with parameters: k, band_km, permutations, seed
Geary's C with parameters: k, band_km, permutations, seed
Parameters
json_points: The points - String - required
json_params: The parameters - String - required
json_points: The points - String - required
json_params: The parameters - String - required
admin
geo gearys_c "[[-21.132, 55.3016, 11.9], [-21.2167, 55.4508, 11.02], [-20.791, 55.6502, 19.25], [-20.9817, 55.3883, 14.66], [-21.1637, 55.3031, 12.23], [-20.8355, 55.6533, 20.52], [-20.8498, 55.3467, 17.49], [-20.8841, 55.6773, 18.63], [-20.81, 55.2934, 17.63], [-20.997, 55.3389, 14.14], [-21.0132, 55.2947, 16.57], [-20.9762, 55.4001, 14.68], [-20.7956, 55.5362, 20.52], [-20.9958, 55.457, 13.78], [-20.9505, 55.4655, 16.44], [-20.8437, 55.2716, 18.85], [-21.2268, 55.5632, 10.23], [-21.0144, 55.4214, 15.93], [-20.7514, 55.3478, 19.4], [-20.9337, 55.3882, 16.68]]" "{\"k\": 4}"
mentdb
{"n": 20, "c": 0.2550951856347974, "expected": 1, "z": -5.985235817452607, "p_value": 0.001, "permutations": 999, "interpretation": "positive autocorrelation (similar neighbors)"}
geo lisa <json_points>
Description
Local Moran (LISA): the local index and the cluster of each point (high-high, low-low, high-low, low-high, not significant) by conditional permutations
Local Moran (LISA): the local index and the cluster of each point (high-high, low-low, high-low, low-high, not significant) by conditional permutations
Parameters
json_points: The points - String - required
json_points: The points - String - required
admin
geo lisa "[[-21.132, 55.3016, 11.9], [-21.2167, 55.4508, 11.02], [-20.791, 55.6502, 19.25], [-20.9817, 55.3883, 14.66], [-21.1637, 55.3031, 12.23], [-20.8355, 55.6533, 20.52], [-20.8498, 55.3467, 17.49], [-20.8841, 55.6773, 18.63], [-20.81, 55.2934, 17.63], [-20.997, 55.3389, 14.14], [-21.0132, 55.2947, 16.57], [-20.9762, 55.4001, 14.68]]"
mentdb
{"n": 12, "level": 0.95, "points": [{"index": 0, "lat": -21.132, "lon": 55.3016, "value": 11.9, "local_i": 0.805874299684997, "p_value": 0.028, "cluster": "low-low"}, {"index": 1, "lat": -21.2167, "lon": 55.4508, "value": 11.02, "local_i": 1.185493490807285, "p_value": 0.028, "cluster": "low-low"}, {"index": 2, "lat": -20.791, "lon": 55.6502, "value": 19.25, "local_i": 0.591448397724972, "p_value": 0.168, "cluster": "not significant"}, {"index": 3, "lat": -20.9817, "lon": 55.3883, "value": 14.66, "local_i": -0.011817008772340293, "p_value": 0.195, "cluster": "not significant"}, {"index": 4, "lat": -21.1637, "lon": 55.3031, "value": 12.23, "local_i": 0.8263947431390234, "p_value": 0.045, "cluster": "low-low"}, {"index": 5, "lat": -20.8355, "lon": 55.6533, "value": 20.52, "local_i": 0.6655425660138327, "p_value": 0.262, "cluster": "not significant"}, {"index": 6, "lat": -20.8498, "lon": 55.3467, "value": 17.49, "local_i": 0.2585334180449761, "p_value": 0.028, "cluster": "high-high"}, {"index": 7, "lat": -20.8841, "lon": 55.6773, "value": 18.63, "local_i": 0.5285016384848125, "p_value": 0.157, "cluster": "not significant"}, {"index": 8, "lat": -20.81, "lon": 55.2934, "value": 17.63, "local_i": -0.04754887368846638, "p_value": 0.849, "cluster": "not significant"}, {"index": 9, "lat": -20.997, "lon": 55.3389, "value": 14.14, "local_i": 0.2182805779094292, "p_value": 0.051, "cluster": "not significant"}, {"index": 10, "lat": -21.0132, "lon": 55.2947, "value": 16.57, "local_i": -0.10125701040377341, "p_value": 0.172, "cluster": "not significant"}, {"index": 11, "lat": -20.9762, "lon": 55.4001, "value": 14.68, "local_i": -0.05432825930902464, "p_value": 0.238, "cluster": "not significant"}]}
geo lisa <json_points> <json_params>
Description
LISA with parameters: k, band_km, permutations, level (0.95), seed
LISA with parameters: k, band_km, permutations, level (0.95), seed
Parameters
json_points: The points - String - required
json_params: The parameters - String - required
json_points: The points - String - required
json_params: The parameters - String - required
admin
geo lisa "[[-21.132, 55.3016, 11.9], [-21.2167, 55.4508, 11.02], [-20.791, 55.6502, 19.25], [-20.9817, 55.3883, 14.66], [-21.1637, 55.3031, 12.23], [-20.8355, 55.6533, 20.52], [-20.8498, 55.3467, 17.49], [-20.8841, 55.6773, 18.63], [-20.81, 55.2934, 17.63], [-20.997, 55.3389, 14.14], [-21.0132, 55.2947, 16.57], [-20.9762, 55.4001, 14.68]]" "{\"k\": 3, \"permutations\": 199}"
mentdb
{"n": 12, "level": 0.95, "points": [{"index": 0, "lat": -21.132, "lon": 55.3016, "value": 11.9, "local_i": 0.9778330110101863, "p_value": 0.08, "cluster": "not significant"}, {"index": 1, "lat": -21.2167, "lon": 55.4508, "value": 11.02, "local_i": 1.5038237659318292, "p_value": 0.05, "cluster": "low-low"}, {"index": 2, "lat": -20.791, "lon": 55.6502, "value": 19.25, "local_i": 1.2693062256075849, "p_value": 0.055, "cluster": "not significant"}, {"index": 3, "lat": -20.9817, "lon": 55.3883, "value": 14.66, "local_i": 0.057478669231711556, "p_value": 0.65, "cluster": "not significant"}, {"index": 4, "lat": -21.1637, "lon": 55.3031, "value": 12.23, "local_i": 1.0240050877761988, "p_value": 0.09, "cluster": "not significant"}, {"index": 5, "lat": -20.8355, "lon": 55.6533, "value": 20.52, "local_i": 0.9820677468882116, "p_value": 0.255, "cluster": "not significant"}, {"index": 6, "lat": -20.8498, "lon": 55.3467, "value": 17.49, "local_i": 0.16687156982903, "p_value": 0.555, "cluster": "not significant"}, {"index": 7, "lat": -20.8841, "lon": 55.6773, "value": 18.63, "local_i": 0.8038089773607922, "p_value": 0.13, "cluster": "not significant"}, {"index": 8, "lat": -20.81, "lon": 55.2934, "value": 17.63, "local_i": -0.0645099048517303, "p_value": 0.875, "cluster": "not significant"}, {"index": 9, "lat": -20.997, "lon": 55.3389, "value": 14.14, "local_i": 0.11577178886490418, "p_value": 0.58, "cluster": "not significant"}, {"index": 10, "lat": -21.0132, "lon": 55.2947, "value": 16.57, "local_i": -0.21241491018005892, "p_value": 0.04, "cluster": "high-low"}, {"index": 11, "lat": -20.9762, "lon": 55.4001, "value": 14.68, "local_i": -0.15246191625606698, "p_value": 0.15, "cluster": "not significant"}]}
geo hotspots <json_points>
Description
Hot and cold spots (Getis-Ord Gi*): z score and label of each point
Hot and cold spots (Getis-Ord Gi*): z score and label of each point
Parameters
json_points: The points - String - required
json_points: The points - String - required
admin
geo hotspots "[[-21.132, 55.3016, 11.9], [-21.2167, 55.4508, 11.02], [-20.791, 55.6502, 19.25], [-20.9817, 55.3883, 14.66], [-21.1637, 55.3031, 12.23], [-20.8355, 55.6533, 20.52], [-20.8498, 55.3467, 17.49], [-20.8841, 55.6773, 18.63], [-20.81, 55.2934, 17.63], [-20.997, 55.3389, 14.14], [-21.0132, 55.2947, 16.57], [-20.9762, 55.4001, 14.68]]"
mentdb
{"n": 12, "level": 0.95, "points": [{"index": 0, "lat": -21.132, "lon": 55.3016, "value": 11.9, "gi_z": -2.8208577254710465, "p_value": 0.0047895439610896595, "spot": "cold spot"}, {"index": 1, "lat": -21.2167, "lon": 55.4508, "value": 11.02, "gi_z": -2.9389704046481886, "p_value": 0.0032930451716639553, "spot": "cold spot"}, {"index": 2, "lat": -20.791, "lon": 55.6502, "value": 19.25, "gi_z": 2.0309350475858725, "p_value": 0.0422615839145124, "spot": "hot spot"}, {"index": 3, "lat": -20.9817, "lon": 55.3883, "value": 14.66, "gi_z": 0, "p_value": 1, "spot": "not significant"}, {"index": 4, "lat": -21.1637, "lon": 55.3031, "value": 12.23, "gi_z": -2.585845543568397, "p_value": 0.009714044997831683, "spot": "cold spot"}, {"index": 5, "lat": -20.8355, "lon": 55.6533, "value": 20.52, "gi_z": 2.0309350475858725, "p_value": 0.0422615839145124, "spot": "hot spot"}, {"index": 6, "lat": -20.8498, "lon": 55.3467, "value": 17.49, "gi_z": 2.5953831801393026, "p_value": 0.0094485516185987, "spot": "hot spot"}, {"index": 7, "lat": -20.8841, "lon": 55.6773, "value": 18.63, "gi_z": 2.0309350475858725, "p_value": 0.0422615839145124, "spot": "hot spot"}, {"index": 8, "lat": -20.81, "lon": 55.2934, "value": 17.63, "gi_z": 0.15133922617705534, "p_value": 0.8797081276020664, "spot": "not significant"}, {"index": 9, "lat": -20.997, "lon": 55.3389, "value": 14.14, "gi_z": -2.4206316941947605, "p_value": 0.015493566089079591, "spot": "cold spot"}, {"index": 10, "lat": -21.0132, "lon": 55.2947, "value": 16.57, "gi_z": -1.2907616573859728, "p_value": 0.1967863371317029, "spot": "not significant"}, {"index": 11, "lat": -20.9762, "lon": 55.4001, "value": 14.68, "gi_z": 1.1818861174575164, "p_value": 0.23725089111645592, "spot": "not significant"}]}
Complete: a table of places -> [lat, lon, value] -> hot spots
admin
#The table: town, lat, lon, cases; -> "[rows]" "[{\"town\": \"t0\", \"lat\": -21.132, \"lon\": 55.3016, \"cases\": 11.9}, {\"town\": \"t1\", \"lat\": -21.2167, \"lon\": 55.4508, \"cases\": 11.02}, {\"town\": \"t2\", \"lat\": -20.791, \"lon\": 55.6502, \"cases\": 19.25}, {\"town\": \"t3\", \"lat\": -20.9817, \"lon\": 55.3883, \"cases\": 14.66}, {\"town\": \"t4\", \"lat\": -21.1637, \"lon\": 55.3031, \"cases\": 12.23}, {\"town\": \"t5\", \"lat\": -20.8355, \"lon\": 55.6533, \"cases\": 20.52}, {\"town\": \"t6\", \"lat\": -20.8498, \"lon\": 55.3467, \"cases\": 17.49}, {\"town\": \"t7\", \"lat\": -20.8841, \"lon\": 55.6773, \"cases\": 18.63}, {\"town\": \"t8\", \"lat\": -20.81, \"lon\": 55.2934, \"cases\": 17.63}, {\"town\": \"t9\", \"lat\": -20.997, \"lon\": 55.3389, \"cases\": 14.14}, {\"town\": \"t10\", \"lat\": -21.0132, \"lon\": 55.2947, \"cases\": 16.57}, {\"town\": \"t11\", \"lat\": -20.9762, \"lon\": 55.4001, \"cases\": 14.68}]"; json load "tuto_h" (geo hotspots (ml prep matrix [rows] "[\"lat\", \"lon\", \"cases\"]") "{\"k\": 3}"); json load "tuto_t" (ml prep vector [rows] "town"); -> "[res]" ""; for (-> "[i]" 0) (< [i] (json count "tuto_t" "/")) (++ "[i]") { -> "[sp]" (json select "tuto_h" (concat "/points/[" [i] "]/spot")); if (equal [sp] "hot spot") {-> "[res]" (concat [res] (json select "tuto_t" (concat "/[" [i] "]")) ": hot spot ");}; if (equal [sp] "cold spot") {-> "[res]" (concat [res] (json select "tuto_t" (concat "/[" [i] "]")) ": cold spot ");}; }; json unload "tuto_h"; json unload "tuto_t"; [res]
mentdb
t0: cold spot t1: cold spot t2: hot spot t4: cold spot t5: hot spot t7: hot spot
geo hotspots <json_points> <json_params>
Description
Hot spots with parameters: k, band_km, level
Hot spots with parameters: k, band_km, level
Parameters
json_points: The points - String - required
json_params: The parameters - String - required
json_points: The points - String - required
json_params: The parameters - String - required
admin
geo hotspots "[[-21.132, 55.3016, 11.9], [-21.2167, 55.4508, 11.02], [-20.791, 55.6502, 19.25], [-20.9817, 55.3883, 14.66], [-21.1637, 55.3031, 12.23], [-20.8355, 55.6533, 20.52], [-20.8498, 55.3467, 17.49], [-20.8841, 55.6773, 18.63], [-20.81, 55.2934, 17.63], [-20.997, 55.3389, 14.14], [-21.0132, 55.2947, 16.57], [-20.9762, 55.4001, 14.68]]" "{\"band_km\": 20, \"level\": 0.9}"
mentdb
{"n": 12, "level": 0.9, "points": [{"index": 0, "lat": -21.132, "lon": 55.3016, "value": 11.9, "gi_z": -2.585845543568397, "p_value": 0.009714044997831683, "spot": "cold spot"}, {"index": 1, "lat": -21.2167, "lon": 55.4508, "value": 11.02, "gi_z": -2.5953831801393012, "p_value": 0.0094485516185987, "spot": "cold spot"}, {"index": 2, "lat": -20.791, "lon": 55.6502, "value": 19.25, "gi_z": 2.420631694194759, "p_value": 0.015493566089079591, "spot": "hot spot"}, {"index": 3, "lat": -20.9817, "lon": 55.3883, "value": 14.66, "gi_z": -0.9192456701124658, "p_value": 0.35796708813687617, "spot": "not significant"}, {"index": 4, "lat": -21.1637, "lon": 55.3031, "value": 12.23, "gi_z": -2.420404568742732, "p_value": 0.015503247979391066, "spot": "cold spot"}, {"index": 5, "lat": -20.8355, "lon": 55.6533, "value": 20.52, "gi_z": 2.420631694194759, "p_value": 0.015493566089079591, "spot": "hot spot"}, {"index": 6, "lat": -20.8498, "lon": 55.3467, "value": 17.49, "gi_z": 0.15133922617705534, "p_value": 0.8797081276020664, "spot": "not significant"}, {"index": 7, "lat": -20.8841, "lon": 55.6773, "value": 18.63, "gi_z": 2.420631694194759, "p_value": 0.015493566089079591, "spot": "hot spot"}, {"index": 8, "lat": -20.81, "lon": 55.2934, "value": 17.63, "gi_z": 0.9191241410704067, "p_value": 0.3580306435050318, "spot": "not significant"}, {"index": 9, "lat": -20.997, "lon": 55.3389, "value": 14.14, "gi_z": -1.5948647014810546, "p_value": 0.11074249460272911, "spot": "not significant"}, {"index": 10, "lat": -21.0132, "lon": 55.2947, "value": 16.57, "gi_z": -1.5948647014810546, "p_value": 0.11074249460272911, "spot": "not significant"}, {"index": 11, "lat": -20.9762, "lon": 55.4001, "value": 14.68, "gi_z": -0.20717450379635116, "p_value": 0.8358735783644735, "spot": "not significant"}]}
Used in use cases (1 recipe)
Epidemiologist › Dengue incidence by town: spatial autocorrelation and hot spots
Epidemiologist › Dengue incidence by town: spatial autocorrelation and hot spots
geo ripley_k <json_points>
Description
Ripley's K and L functions of a point pattern with a Monte Carlo envelope of complete spatial randomness: clustered, random or dispersed at each distance
Ripley's K and L functions of a point pattern with a Monte Carlo envelope of complete spatial randomness: clustered, random or dispersed at each distance
Parameters
json_points: The points [[lat, lon], ...] - String - required
json_points: The points [[lat, lon], ...] - String - required
admin
geo ripley_k "[[-20.9602, 55.463], [-20.9555, 55.4615], [-20.9462, 55.4474], [-20.9433, 55.4527], [-20.9487, 55.4362], [-20.9493, 55.4589], [-20.9451, 55.46], [-20.9351, 55.4541], [-20.9303, 55.4349], [-20.9524, 55.4248], [-21.1918, 55.7009], [-21.1831, 55.6963], [-21.2203, 55.7128], [-21.2134, 55.6873], [-21.2018, 55.7063], [-21.2051, 55.7019], [-21.2188, 55.7173], [-21.2007, 55.7012], [-21.1941, 55.7017], [-21.198, 55.6907]]"
mentdb
{"n": 20, "area_km2": 974.2808520560134, "simulations": 99, "results": [{"distance_km": 0.7595793642765785, "k": 51.27793958189544, "l": 4.040083552607846, "l_minus_d": 3.2805041883312676, "csr_lower": -0.7595793642765785, "csr_upper": 1.0472009274054197, "pattern": "clustered"}, {"distance_km": 1.519158728553157, "k": 164.08940666206541, "l": 7.227121166727993, "l_minus_d": 5.707962438174835, "csr_lower": -1.519158728553157, "csr_upper": 1.0360144641719415, "pattern": "clustered"}, {"distance_km": 2.278738092829735, "k": 266.6452858258563, "l": 9.212807964061373, "l_minus_d": 6.934069871231637, "csr_lower": -2.278738092829735, "csr_upper": 1.1014383194950272, "pattern": "clustered"}, {"distance_km": 3.038317457106314, "k": 353.81778311507856, "l": 10.612431308289434, "l_minus_d": 7.57411385118312, "csr_lower": -1.2315371654243157, "csr_upper": 1.198957920215495, "pattern": "clustered"}, {"distance_km": 3.797896821382892, "k": 430.7346924879216, "l": 11.70927456938475, "l_minus_d": 7.911377748001858, "csr_lower": -1.5850519254139654, "csr_upper": 1.1501747896670782, "pattern": "clustered"}, {"distance_km": 4.55747618565947, "k": 461.5014562370589, "l": 12.120250657823536, "l_minus_d": 7.562774472164066, "csr_lower": -1.7007057090502244, "csr_upper": 1.2971610990329046, "pattern": "clustered"}, {"distance_km": 5.317055549936049, "k": 461.5014562370589, "l": 12.120250657823536, "l_minus_d": 6.803195107887488, "csr_lower": -1.484295760848401, "csr_upper": 1.1973834352211794, "pattern": "clustered"}, {"distance_km": 6.076634914212628, "k": 461.5014562370589, "l": 12.120250657823536, "l_minus_d": 6.043615743610909, "csr_lower": -1.6509451222747744, "csr_upper": 0.9209950657275305, "pattern": "clustered"}, {"distance_km": 6.836214278489206, "k": 461.5014562370589, "l": 12.120250657823536, "l_minus_d": 5.284036379334331, "csr_lower": -1.725867893039009, "csr_upper": 1.142311458575537, "pattern": "clustered"}, {"distance_km": 7.595793642765784, "k": 461.5014562370589, "l": 12.120250657823536, "l_minus_d": 4.524457015057752, "csr_lower": -2.026922777599343, "csr_upper": 0.9745177870619521, "pattern": "clustered"}]}
geo ripley_k <json_points> <json_params>
Description
Ripley K with parameters: distances_km, simulations (99), seed
Ripley K with parameters: distances_km, simulations (99), seed
Parameters
json_points: The points - String - required
json_params: The parameters - String - required
json_points: The points - String - required
json_params: The parameters - String - required
admin
geo ripley_k "[[-20.9602, 55.463], [-20.9555, 55.4615], [-20.9462, 55.4474], [-20.9433, 55.4527], [-20.9487, 55.4362], [-20.9493, 55.4589], [-20.9451, 55.46], [-20.9351, 55.4541], [-20.9303, 55.4349], [-20.9524, 55.4248], [-21.1918, 55.7009], [-21.1831, 55.6963], [-21.2203, 55.7128], [-21.2134, 55.6873], [-21.2018, 55.7063], [-21.2051, 55.7019], [-21.2188, 55.7173], [-21.2007, 55.7012], [-21.1941, 55.7017], [-21.198, 55.6907]]" "{\"distances_km\": [1, 5, 10], \"simulations\": 49}"
mentdb
{"n": 20, "area_km2": 974.2808520560134, "simulations": 49, "results": [{"distance_km": 1, "k": 76.91690937284316, "l": 4.94807161104997, "l_minus_d": 3.9480716110499703, "csr_lower": -1, "csr_upper": 0.8067802916819982, "pattern": "clustered"}, {"distance_km": 5, "k": 461.5014562370589, "l": 12.120250657823536, "l_minus_d": 7.1202506578235365, "csr_lower": -1.3864394166360037, "csr_upper": 1.2588705266146736, "pattern": "clustered"}, {"distance_km": 10, "k": 461.5014562370589, "l": 12.120250657823536, "l_minus_d": 2.1202506578235365, "csr_lower": -2.5504540151108355, "csr_upper": 0.6124313082894339, "pattern": "clustered"}]}
geo nni <json_points>
Description
Nearest neighbor index (Clark and Evans): R < 1 clustered, R > 1 dispersed, z test
Nearest neighbor index (Clark and Evans): R < 1 clustered, R > 1 dispersed, z test
Parameters
json_points: The points - String - required
json_points: The points - String - required
admin
geo nni "[[-20.9602, 55.463], [-20.9555, 55.4615], [-20.9462, 55.4474], [-20.9433, 55.4527], [-20.9487, 55.4362], [-20.9493, 55.4589], [-20.9451, 55.46], [-20.9351, 55.4541], [-20.9303, 55.4349], [-20.9524, 55.4248], [-21.1918, 55.7009], [-21.1831, 55.6963], [-21.2203, 55.7128], [-21.2134, 55.6873], [-21.2018, 55.7063], [-21.2051, 55.7019], [-21.2188, 55.7173], [-21.2007, 55.7012], [-21.1941, 55.7017], [-21.198, 55.6907]]"
mentdb
{"n": 20, "observed_mean_km": 0.7860148172027988, "expected_mean_km": 3.489772292098751, "r": 0.22523384089627493, "z": -6.628519277710235, "p_value": 3.390709935047198E-11, "pattern": "clustered (R < 1)"}
geo nni <json_points> <json_params>
Description
Nearest neighbor index with parameters: area_km2 (else the bounding box)
Nearest neighbor index with parameters: area_km2 (else the bounding box)
Parameters
json_points: The points - String - required
json_params: The parameters - String - required
json_points: The points - String - required
json_params: The parameters - String - required
admin
geo nni "[[-20.9602, 55.463], [-20.9555, 55.4615], [-20.9462, 55.4474], [-20.9433, 55.4527], [-20.9487, 55.4362], [-20.9493, 55.4589], [-20.9451, 55.46], [-20.9351, 55.4541], [-20.9303, 55.4349], [-20.9524, 55.4248], [-21.1918, 55.7009], [-21.1831, 55.6963], [-21.2203, 55.7128], [-21.2134, 55.6873], [-21.2018, 55.7063], [-21.2051, 55.7019], [-21.2188, 55.7173], [-21.2007, 55.7012], [-21.1941, 55.7017], [-21.198, 55.6907]]" "{\"area_km2\": 900}"
mentdb
{"n": 20, "observed_mean_km": 0.7860148172027988, "expected_mean_km": 3.3541019662496843, "r": 0.23434434167833723, "z": -6.550574301211318, "p_value": 5.7316151824693407E-11, "pattern": "clustered (R < 1)"}
geo dbscan <json_points> <eps_km> <min_points>
Description
DBSCAN clustering of points with a radius in km: clusters, noise points, centers
DBSCAN clustering of points with a radius in km: clusters, noise points, centers
Parameters
json_points: The points - String - required
eps_km: The radius - Number - required
min_points: The minimum number of neighbors - Number - required
json_points: The points - String - required
eps_km: The radius - Number - required
min_points: The minimum number of neighbors - Number - required
admin
geo dbscan "[[-20.9602, 55.463], [-20.9555, 55.4615], [-20.9462, 55.4474], [-20.9433, 55.4527], [-20.9487, 55.4362], [-20.9493, 55.4589], [-20.9451, 55.46], [-20.9351, 55.4541], [-20.9303, 55.4349], [-20.9524, 55.4248], [-21.1918, 55.7009], [-21.1831, 55.6963], [-21.2203, 55.7128], [-21.2134, 55.6873], [-21.2018, 55.7063], [-21.2051, 55.7019], [-21.2188, 55.7173], [-21.2007, 55.7012], [-21.1941, 55.7017], [-21.198, 55.6907]]" 3 4
mentdb
{"clusters": 2, "noise": 0, "labels": [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], "summary": [{"cluster": 0, "size": 10, "center_lat": -20.94661, "center_lon": 55.449349999999995}, {"cluster": 1, "size": 10, "center_lat": -21.202710000000003, "center_lon": 55.70164000000001}]}
geo buffer <lat> <lon> <radius_km>
Description
Circle polygon of a radius around a point (64 segments)
Circle polygon of a radius around a point (64 segments)
Parameters
lat: Latitude - Number - required
lon: Longitude - Number - required
radius_km: The radius - Number - required
lat: Latitude - Number - required
lon: Longitude - Number - required
radius_km: The radius - Number - required
admin
geo buffer -20.88 55.45 1
mentdb
[[-20.8710068, 55.45], [-20.8710501, 55.4509434], [-20.8711796, 55.4518777], [-20.871394, 55.4527939], [-20.8716913, 55.4536832], [-20.8720686, 55.4545371], [-20.8725223, 55.4553473], [-20.8730481, 55.4561059], [-20.8736407, 55.4568058], [-20.8742946, 55.4574402], [-20.8750035, 55.4580029], [-20.8757604, 55.4584885], [-20.8765582, 55.4588924], [-20.8773892, 55.4592107], [-20.8782453, 55.4594402], [-20.8791182, 55.4595789], [-20.8799997, 55.4596253], [-20.8808812, 55.459579], [-20.8817542, 55.4594405], [-20.8826103, 55.459211], [-20.8834413, 55.4588928], [-20.8842392, 55.458489], [-20.8849962, 55.4580034], [-20.8857051, 55.4574407], [-20.886359, 55.4568064], [-20.8869517, 55.4561065], [-20.8874775, 55.4553478], [-20.8879312, 55.4545376], [-20.8883086, 55.4536836], [-20.8886059, 55.4527942], [-20.8888204, 55.4518779], [-20.8889499, 55.4509435], [-20.8889932, 55.45], [-20.8889499, 55.4490565], [-20.8888204, 55.4481221], [-20.8886059, 55.4472058], [-20.8883086, 55.4463164], [-20.8879312, 55.4454624], [-20.8874775, 55.4446522], [-20.8869517, 55.4438935], [-20.886359, 55.4431936], [-20.8857051, 55.4425593], [-20.8849962, 55.4419966], [-20.8842392, 55.441511], [-20.8834413, 55.4411072], [-20.8826103, 55.440789], [-20.8817542, 55.4405595], [-20.8808812, 55.440421], [-20.8799997, 55.4403747], [-20.8791182, 55.4404211], [-20.8782453, 55.4405598], [-20.8773892, 55.4407893], [-20.8765582, 55.4411076], [-20.8757604, 55.4415115], [-20.8750035, 55.4419971], [-20.8742946, 55.4425598], [-20.8736407, 55.4431942], [-20.8730481, 55.4438941], [-20.8725223, 55.4446527], [-20.8720686, 55.4454629], [-20.8716913, 55.4463168], [-20.871394, 55.4472061], [-20.8711796, 55.4481223], [-20.8710501, 55.4490566]]
geo buffer <lat> <lon> <radius_km> <segments>
Description
Circle polygon with a number of segments
Circle polygon with a number of segments
Parameters
lat: Latitude - Number - required
lon: Longitude - Number - required
radius_km: The radius - Number - required
segments: The number of vertices - Number - required
lat: Latitude - Number - required
lon: Longitude - Number - required
radius_km: The radius - Number - required
segments: The number of vertices - Number - required
admin
geo buffer -20.88 55.45 1 8
mentdb
[[-20.8710068, 55.45], [-20.8736407, 55.4568058], [-20.8799997, 55.4596253], [-20.886359, 55.4568064], [-20.8889932, 55.45], [-20.886359, 55.4431936], [-20.8799997, 55.4403747], [-20.8736407, 55.4431942]]
geo convex_hull <json_points>
Description
Convex hull of points (the smallest convex polygon that contains them)
Convex hull of points (the smallest convex polygon that contains them)
Parameters
json_points: The points - String - required
json_points: The points - String - required
admin
geo convex_hull "[[-21.0, 55.4], [-21.0, 55.6], [-21.2, 55.6], [-21.2, 55.4], [-21.1, 55.5]]"
mentdb
{"vertices": 4, "polygon": [[-21.2, 55.4], [-21.2, 55.6], [-21, 55.6], [-21, 55.4]]}
geo simplify <json_line> <tolerance_m>
Description
Simplify a line or a track (Douglas-Peucker): the points closer than the tolerance to the simplified line are removed
Simplify a line or a track (Douglas-Peucker): the points closer than the tolerance to the simplified line are removed
Parameters
json_line: The points of the line - String - required
tolerance_m: The tolerance in meters - Number - required
json_line: The points of the line - String - required
tolerance_m: The tolerance in meters - Number - required
admin
geo simplify "[[-21.0, 55.40], [-21.0001, 55.41], [-21.0, 55.42], [-21.01, 55.43], [-21.0, 55.44]]" 50
mentdb
{"points_before": 5, "points": 4, "line": [[-21, 55.4], [-21, 55.42], [-21.01, 55.43], [-21, 55.44]]}
geo length <json_line>
Description
Length of a line or a track (Vincenty, WGS84)
Length of a line or a track (Vincenty, WGS84)
Parameters
json_line: The points of the line - String - required
json_line: The points of the line - String - required
admin
geo length "[[48.8566, 2.3522], [45.764, 4.8357]]"
mentdb
{"points": 2, "km": 391.7127046734481, "m": 391712.7046734481}
geo bbox <json_points>
Description
Bounding box of points: minimum and maximum latitude and longitude, center, width and height in km
Bounding box of points: minimum and maximum latitude and longitude, center, width and height in km
Parameters
json_points: The points - String - required
json_points: The points - String - required
admin
geo bbox "[[-20.9602, 55.463], [-20.9555, 55.4615], [-20.9462, 55.4474], [-20.9433, 55.4527], [-20.9487, 55.4362], [-20.9493, 55.4589], [-20.9451, 55.46], [-20.9351, 55.4541], [-20.9303, 55.4349], [-20.9524, 55.4248], [-21.1918, 55.7009], [-21.1831, 55.6963], [-21.2203, 55.7128], [-21.2134, 55.6873], [-21.2018, 55.7063], [-21.2051, 55.7019], [-21.2188, 55.7173], [-21.2007, 55.7012], [-21.1941, 55.7017], [-21.198, 55.6907]]"
mentdb
{"min_lat": -21.2203, "max_lat": -20.9303, "min_lon": 55.4248, "max_lon": 55.7173, "center_lat": -21.0753, "center_lon": 55.57105, "width_km": 30.348944636704754, "height_km": 32.24657326772501}
geo intersects <json_polygon_a> <json_polygon_b>
Description
Do two polygons intersect? Also: one inside the other, borders crossing
Do two polygons intersect? Also: one inside the other, borders crossing
Parameters
json_polygon_a: The first polygon - String - required
json_polygon_b: The second polygon - String - required
json_polygon_a: The first polygon - String - required
json_polygon_b: The second polygon - String - required
admin
geo intersects "[[0, 0], [0, 2], [2, 2], [2, 0]]" "[[1, 1], [1, 3], [3, 3], [3, 1]]"
mentdb
{"intersects": true, "first_inside_second": false, "second_inside_first": false, "borders_cross": true}
geo project <lat> <lon> <system>
Description
Project a WGS84 point: lambert93 (EPSG:2154, France) or webmercator (EPSG:3857, web maps), x and y in meters
Project a WGS84 point: lambert93 (EPSG:2154, France) or webmercator (EPSG:3857, web maps), x and y in meters
Parameters
lat: Latitude - Number - required
lon: Longitude - Number - required
system: lambert93 or webmercator - String - required
lat: Latitude - Number - required
lon: Longitude - Number - required
system: lambert93 or webmercator - String - required
admin
geo project 48.8566 2.3522 "lambert93"
mentdb
{"system": "lambert93", "x": 652469.022709136, "y": 6862035.259420077}
geo unproject <x> <y> <system>
Description
Back to WGS84 latitude and longitude from lambert93 or webmercator coordinates
Back to WGS84 latitude and longitude from lambert93 or webmercator coordinates
Parameters
x: x in meters - Number - required
y: y in meters - Number - required
system: lambert93 or webmercator - String - required
x: x in meters - Number - required
y: y in meters - Number - required
system: lambert93 or webmercator - String - required
admin
geo unproject 652469 6862035 "lambert93"
mentdb
{"system": "lambert93", "lat": 48.85659766538409, "lon": 2.352199719516298}
geo kde <json_points>
Description
Kernel density of points (Gaussian kernel, bandwidth by the Scott rule): the densest places
Kernel density of points (Gaussian kernel, bandwidth by the Scott rule): the densest places
Parameters
json_points: The points - String - required
json_points: The points - String - required
admin
geo kde "[[-20.9602, 55.463], [-20.9555, 55.4615], [-20.9462, 55.4474], [-20.9433, 55.4527], [-20.9487, 55.4362], [-20.9493, 55.4589], [-20.9451, 55.46], [-20.9351, 55.4541], [-20.9303, 55.4349], [-20.9524, 55.4248], [-21.1918, 55.7009], [-21.1831, 55.6963], [-21.2203, 55.7128], [-21.2134, 55.6873], [-21.2018, 55.7063], [-21.2051, 55.7019], [-21.2188, 55.7173], [-21.2007, 55.7012], [-21.1941, 55.7017], [-21.198, 55.6907]]"
mentdb
{"bandwidth_km": 8.52306507009422, "grid": 20, "peaks": [{"lat": -21.19855, "lon": 55.6953625, "density_per_km2": 0.0010732798574706122}, {"lat": -20.95205, "lon": 55.4467375, "density_per_km2": 0.001073226076728441}, {"lat": -21.19855, "lon": 55.709987500000004, "density_per_km2": 0.0010707109497919917}, {"lat": -20.937549999999998, "lon": 55.4467375, "density_per_km2": 0.0010685832188708317}, {"lat": -21.213050000000003, "lon": 55.6953625, "density_per_km2": 0.0010650838540807758}, {"lat": -20.95205, "lon": 55.4613625, "density_per_km2": 0.0010629119768960163}, {"lat": -21.213050000000003, "lon": 55.709987500000004, "density_per_km2": 0.0010628008725050043}, {"lat": -20.937549999999998, "lon": 55.4613625, "density_per_km2": 0.0010581259061142351}, {"lat": -20.95205, "lon": 55.432112499999995, "density_per_km2": 0.001050537198751051}, {"lat": -20.937549999999998, "lon": 55.432112499999995, "density_per_km2": 0.0010461662050690536}]}
geo kde <json_points> <json_params>
Description
Kernel density with parameters: bandwidth_km, grid (20 x 20), top (10)
Kernel density with parameters: bandwidth_km, grid (20 x 20), top (10)
Parameters
json_points: The points - String - required
json_params: The parameters - String - required
json_points: The points - String - required
json_params: The parameters - String - required
admin
geo kde "[[-20.9602, 55.463], [-20.9555, 55.4615], [-20.9462, 55.4474], [-20.9433, 55.4527], [-20.9487, 55.4362], [-20.9493, 55.4589], [-20.9451, 55.46], [-20.9351, 55.4541], [-20.9303, 55.4349], [-20.9524, 55.4248], [-21.1918, 55.7009], [-21.1831, 55.6963], [-21.2203, 55.7128], [-21.2134, 55.6873], [-21.2018, 55.7063], [-21.2051, 55.7019], [-21.2188, 55.7173], [-21.2007, 55.7012], [-21.1941, 55.7017], [-21.198, 55.6907]]" "{\"bandwidth_km\": 2, \"top\": 3}"
mentdb
{"bandwidth_km": 2, "grid": 20, "peaks": [{"lat": -21.19855, "lon": 55.6953625, "density_per_km2": 0.01472809485779154}, {"lat": -20.95205, "lon": 55.4467375, "density_per_km2": 0.014070697454535666}, {"lat": -21.19855, "lon": 55.709987500000004, "density_per_km2": 0.013757848024459224}]}
geo grid <json_points> <cell_km>
Description
Counts of points in square cells of a size in km (heat map)
Counts of points in square cells of a size in km (heat map)
Parameters
json_points: The points - String - required
cell_km: The size of the cells - Number - required
json_points: The points - String - required
cell_km: The size of the cells - Number - required
admin
geo grid "[[-20.9602, 55.463], [-20.9555, 55.4615], [-20.9462, 55.4474], [-20.9433, 55.4527], [-20.9487, 55.4362], [-20.9493, 55.4589], [-20.9451, 55.46], [-20.9351, 55.4541], [-20.9303, 55.4349], [-20.9524, 55.4248], [-21.1918, 55.7009], [-21.1831, 55.6963], [-21.2203, 55.7128], [-21.2134, 55.6873], [-21.2018, 55.7063], [-21.2051, 55.7019], [-21.2188, 55.7173], [-21.2007, 55.7012], [-21.1941, 55.7017], [-21.198, 55.6907]]" 5
mentdb
{"cell_km": 5, "cells": 8, "counts": [{"center_lat": -21.18490784452041, "center_lon": 55.71648696684552, "count": 6}, {"center_lat": -20.95881491128113, "center_lon": 55.47581099722632, "count": 5}, {"center_lat": -20.95881491128113, "center_lon": 55.42767580330248, "count": 3}, {"center_lat": -21.230126431168266, "center_lon": 55.71648696684552, "count": 2}, {"center_lat": -20.913596324633275, "center_lon": 55.42767580330248, "count": 1}, {"center_lat": -20.913596324633275, "center_lon": 55.47581099722632, "count": 1}, {"center_lat": -21.18490784452041, "center_lon": 55.66835177292168, "count": 1}, {"center_lat": -21.230126431168266, "center_lon": 55.66835177292168, "count": 1}]}
geo geojson <json_geometry> <type>
Description
Convert points, a line or a polygon to a GeoJSON FeatureCollection (coordinates [lon, lat]), for web maps
Convert points, a line or a polygon to a GeoJSON FeatureCollection (coordinates [lon, lat]), for web maps
Parameters
json_geometry: The points [[lat, lon] or [lat, lon, value]] - String - required
type: points, line or polygon - String - required
json_geometry: The points [[lat, lon] or [lat, lon, value]] - String - required
type: points, line or polygon - String - required
admin
geo geojson "[[-20.88, 55.45, 12], [-21.11, 55.53, 8]]" "points"
mentdb
{"type": "FeatureCollection", "features": [{"type": "Feature", "geometry": {"type": "Point", "coordinates": [55.45, -20.88]}, "properties": {"value": 12}}, {"type": "Feature", "geometry": {"type": "Point", "coordinates": [55.53, -21.11]}, "properties": {"value": 8}}]}
geo spatial_lag <json_points> <json_X>
Description
Spatial lag regression (SAR) by maximum likelihood: y = rho W y + X b + e; rho (spatial dependence) with its likelihood ratio test, coefficients
Spatial lag regression (SAR) by maximum likelihood: y = rho W y + X b + e; rho (spatial dependence) with its likelihood ratio test, coefficients
Parameters
json_points: The points [[lat, lon, y], ...] - String - required
json_X: The covariates of each point - String - required
json_points: The points [[lat, lon, y], ...] - String - required
json_X: The covariates of each point - String - required
admin
geo spatial_lag "[[-21.132, 55.3016, 11.9], [-21.2167, 55.4508, 11.02], [-20.791, 55.6502, 19.25], [-20.9817, 55.3883, 14.66], [-21.1637, 55.3031, 12.23], [-20.8355, 55.6533, 20.52], [-20.8498, 55.3467, 17.49], [-20.8841, 55.6773, 18.63], [-20.81, 55.2934, 17.63], [-20.997, 55.3389, 14.14], [-21.0132, 55.2947, 16.57], [-20.9762, 55.4001, 14.68], [-20.7956, 55.5362, 20.52], [-20.9958, 55.457, 13.78], [-20.9505, 55.4655, 16.44], [-20.8437, 55.2716, 18.85], [-21.2268, 55.5632, 10.23], [-21.0144, 55.4214, 15.93], [-20.7514, 55.3478, 19.4], [-20.9337, 55.3882, 16.68]]" "[[-0.132], [-0.217], [0.209], [0.018], [-0.164], [0.165], [0.15], [0.116], [0.19], [0.003], [-0.013], [0.024], [0.204], [0.004], [0.049], [0.156], [-0.227], [-0.014], [0.249], [0.066]]"
mentdb
{"n": 20, "rho": 0.05744463849745413, "coefficients": [14.27824629734224, 19.91071255145583], "sigma2": 0.9875515148872775, "log_likelihood": -28.258607024754973, "lr_test_rho": 0.03494662700879303, "rho_p_value": 0.8517075435466122, "aic": 64.51721404950995}
geo spatial_lag <json_points> <json_X> <json_params>
Description
Spatial lag regression with parameters: k, band_km
Spatial lag regression with parameters: k, band_km
Parameters
json_points: The points - String - required
json_X: The covariates - String - required
json_params: The parameters - String - required
json_points: The points - String - required
json_X: The covariates - String - required
json_params: The parameters - String - required
admin
geo spatial_lag "[[-21.132, 55.3016, 11.9], [-21.2167, 55.4508, 11.02], [-20.791, 55.6502, 19.25], [-20.9817, 55.3883, 14.66], [-21.1637, 55.3031, 12.23], [-20.8355, 55.6533, 20.52], [-20.8498, 55.3467, 17.49], [-20.8841, 55.6773, 18.63], [-20.81, 55.2934, 17.63], [-20.997, 55.3389, 14.14], [-21.0132, 55.2947, 16.57], [-20.9762, 55.4001, 14.68], [-20.7956, 55.5362, 20.52], [-20.9958, 55.457, 13.78], [-20.9505, 55.4655, 16.44], [-20.8437, 55.2716, 18.85], [-21.2268, 55.5632, 10.23], [-21.0144, 55.4214, 15.93], [-20.7514, 55.3478, 19.4], [-20.9337, 55.3882, 16.68]]" "[[-0.198], [-0.049], [0.15], [-0.112], [-0.197], [0.153], [-0.153], [0.177], [-0.207], [-0.161], [-0.205], [-0.1], [0.036], [-0.043], [-0.035], [-0.228], [0.063], [-0.079], [-0.152], [-0.112]]" "{\"k\": 3}"
mentdb
{"n": 20, "rho": 0.789867413726323, "coefficients": [3.307777579275366, -0.49994105459502336], "sigma2": 2.472599184209587, "log_likelihood": -40.45318532114857, "lr_test_rho": 18.856619518191692, "rho_p_value": 1.409212107550406E-5, "aic": 88.90637064229713}