| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,5 @@ | ||
| ##Basic statistics=group | ||
| ##Layer=vector | ||
| ##Field=Field Layer | ||
| library(nortest) | ||
| >lillie.test(Layer[[Field]]) |
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,20 @@ | ||
| (dp0 | ||
| S'Field' | ||
| p1 | ||
| VA numeric field. | ||
| p2 | ||
| sS'ALG_DESC' | ||
| p3 | ||
| VThis script performs the Lilliefors (Kolmogrov-Smirnov) test for the composite hypothesis of normality.\u000a\u000aR dependencies: library "nortest"\u000a\u000a | ||
| p4 | ||
| sS'R_CONSOLE_OUTPUT' | ||
| p5 | ||
| VThe results of the Lilliefors (Kolmogrov-Smirnov) test. | ||
| p6 | ||
| sS'Layer' | ||
| p7 | ||
| VA vector containing at least one numeric field. | ||
| p8 | ||
| sNV | ||
| p9 | ||
| s. |
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,7 @@ | ||
| ##Home Range Analysis=group | ||
| ##Layer=vector | ||
| ##Percentage=number 10 | ||
| ##Field=Field Layer | ||
| ##Home_ranges=Output vector | ||
| library(adehabitatHR) | ||
| Home_ranges<-mcp(Layer[,Field],percent=Percentage) |
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,36 @@ | ||
| (dp0 | ||
| S'Layer' | ||
| p1 | ||
| VAn vector layer containing the relocations of one or more animals. | ||
| p2 | ||
| sS'Home_ranges' | ||
| p3 | ||
| VThe home ranges of the animals calculated according to the selected "Percentage" parameter. | ||
| p4 | ||
| sS'ALG_CREATOR' | ||
| p5 | ||
| VThis algorithm was written by Filipe S. Dias using the functions written by Clement Calenge, creator of the package "adehabitatHR". | ||
| p6 | ||
| sS'ALG_DESC' | ||
| p7 | ||
| VThis tool computes the home range of one or more animals with the Minimum Convex Polygon estimator.\u000a\u000aR depencies: library "adehabitatHR" | ||
| p8 | ||
| sS'Field' | ||
| p9 | ||
| VA field containing a unique identifier for each animal (type "string").\u000a\u000a\u000a | ||
| p10 | ||
| sS'ALG_HELP_CREATOR' | ||
| p11 | ||
| VFilipe S. Dias | ||
| p12 | ||
| sS'Output' | ||
| p13 | ||
| VThe ouput is a shapefile containing the home range of each animal. | ||
| p14 | ||
| sS'Percentage' | ||
| p15 | ||
| V100 minus the proportion of outliers to be excluded from the computation. E.g. Percentage = 95 means that 5% of the outlier locations will be excluded from the calculations.\u000a\u000a\u000a | ||
| p16 | ||
| sNV | ||
| p17 | ||
| s. |
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,12 @@ | ||
| ##Point pattern analysis=group | ||
| ##Layer=vector | ||
| ##Simulations=number 100 | ||
| ##Optional_plot_name=string | ||
| ##showplots | ||
| library(spatstat) | ||
| library(maptools) | ||
| sp <- as(Layer, "SpatialPoints") | ||
| sp <- as(sp, "ppp") | ||
| e <- envelope(sp, Kest, nsim = Simulations) | ||
| >e | ||
| plot(e, main = Optional_plot_name) |
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,34 @@ | ||
| (dp0 | ||
| S'ALG_DESC' | ||
| p1 | ||
| VThis is a Monte Carlo test for the point patterns. It is based on simulations from the null hypothesis. It generates randomly dinstributed points within the study region and uses K-function for each set of generated points and compares them to the K-function for the original set of points. Detailed description can be found in correspondin section of this book: http://www.csiro.au/resources/pf16h.\u000a\u000aThis script will provide both graphical ('R plots') and verbose ('R console output') output.\u000a\u000aR dependencies: library "maptools" and "spatstat" | ||
| p2 | ||
| sS'R_CONSOLE_OUTPUT' | ||
| p3 | ||
| VDescription of the test results. | ||
| p4 | ||
| sS'Layer' | ||
| p5 | ||
| VPoint layer to be tested. | ||
| p6 | ||
| sS'ALG_CREATOR' | ||
| p7 | ||
| VYury Ryabov\u000ariabovv at gmail dot com\u000a2013\u000aGPLv3 | ||
| p8 | ||
| sS'RPLOTS' | ||
| p9 | ||
| VGraph showing test results. | ||
| p10 | ||
| sS'ALG_HELP_CREATOR' | ||
| p11 | ||
| VYury Ryabov\u000ariabovv at gmail dot com\u000a2013\u000aCC-0 | ||
| p12 | ||
| sS'Simulations' | ||
| p13 | ||
| VNumber of simulations for random points distributions. Positive integer must be provided here. | ||
| p14 | ||
| sS'Optional_plot_name' | ||
| p15 | ||
| VAn Optional name for the graph. It is Ok to leave this field blank. | ||
| p16 | ||
| s. |
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,10 +1,10 @@ | ||
| ##Point pattern analysis=group | ||
| ##Layer=vector | ||
| ##showplots | ||
| library("maptools") | ||
| library("spatstat") | ||
| ppp=as(as(Layer, "SpatialPoints"),"ppp") | ||
| qc=quadratcount(ppp) | ||
| plot(Layer) | ||
| plot(qc, add=TRUE) | ||
| >quadrat.test(ppp); |
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,26 @@ | ||
| (dp0 | ||
| S'ALG_DESC' | ||
| p1 | ||
| VThe script divides the window into quadrats and counts the numbers of points in each quadrat. Then it performs a test of Complete Spatial Randomness based on the quadrat counts.\u000a\u000aR dependencies: library "maptools" and "spatstat" | ||
| p2 | ||
| sS'R_CONSOLE_OUTPUT' | ||
| p3 | ||
| VThe results of the Chi-squared test of complete spatial randomness (CSR) using quadrat counts.\u000a | ||
| p4 | ||
| sS'ALG_CREATOR' | ||
| p5 | ||
| VVictor Olaya, volayaf(at)gmail.com | ||
| p6 | ||
| sS'Layer' | ||
| p7 | ||
| VA vector containg a point pattern. | ||
| p8 | ||
| sS'RPLOTS' | ||
| p9 | ||
| VA display containing the number of points per quadrat. | ||
| p10 | ||
| sS'ALG_HELP_CREATOR' | ||
| p11 | ||
| VFilipe S. Dias, filipesdias(at)gmail.com | ||
| p12 | ||
| s. |
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,6 @@ | ||
| ##Point pattern analysis=group | ||
| ##Layer=vector | ||
| ##Size=number 10 | ||
| ##Output= output vector | ||
| pts=spsample(Layer,Size,type="random") | ||
| Output=SpatialPointsDataFrame(pts, as.data.frame(pts)) |
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,26 @@ | ||
| (dp0 | ||
| S'ALG_DESC' | ||
| p1 | ||
| VThis scripts samples point location within a given polygon(s) using a random sampling method. The used methods assume that the geometry used is not spherical, so objects should be in planar coordinates.\u000a\u000a | ||
| p2 | ||
| sS'ALG_CREATOR' | ||
| p3 | ||
| VVictor Olaya | ||
| p4 | ||
| sS'Layer' | ||
| p5 | ||
| VA vector layer containing polygons. | ||
| p6 | ||
| sS'ALG_HELP_CREATOR' | ||
| p7 | ||
| VFilipe Dias | ||
| p8 | ||
| sS'Output' | ||
| p9 | ||
| VRandomly generated random points. | ||
| p10 | ||
| sS'Size' | ||
| p11 | ||
| VNumber of sample points to be randomly generated | ||
| p12 | ||
| s. |
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,4 +1,4 @@ | ||
| ##Raster processing=group | ||
| ##Layer = raster | ||
| ##showplots | ||
| hist(as.matrix(Layer),main="Histogram",xlab="Layer") |
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,22 @@ | ||
| (dp0 | ||
| S'ALG_CREATOR' | ||
| p1 | ||
| VVictor Olaya, volayaf(at)gmail.com | ||
| p2 | ||
| sS'ALG_DESC' | ||
| p3 | ||
| VThe script creates a raster histogram. | ||
| p4 | ||
| sS'Layer ' | ||
| p5 | ||
| VAn input raster. | ||
| p6 | ||
| sS'RPLOTS' | ||
| p7 | ||
| VHistogram | ||
| p8 | ||
| sS'ALG_HELP_CREATOR' | ||
| p9 | ||
| VFilipe S. Dias, filipesdias(at)gmail.co | ||
| p10 | ||
| s. |
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,6 @@ | ||
| ##Point pattern analysis=group | ||
| ##Layer=vector | ||
| ##Size=number 10 | ||
| ##Output= output vector | ||
| pts=spsample(Layer,Size,type="regular") | ||
| Output=SpatialPointsDataFrame(pts, as.data.frame(pts)) |
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,18 @@ | ||
| (dp0 | ||
| S'Output' | ||
| p1 | ||
| VSampled points | ||
| p2 | ||
| sS'ALG_DESC' | ||
| p3 | ||
| VThis scripts samples point location within a given polygon(s) using a regular (systematically aligned) sampling method. The methods used assume that the geometry used is not spherical, so objects should be in planar coordinates. | ||
| p4 | ||
| sS'Layer' | ||
| p5 | ||
| VA vector layer containing polygons.\u000a | ||
| p6 | ||
| sS'Size' | ||
| p7 | ||
| VNumber of sample points to be generated.\u000a | ||
| p8 | ||
| s. |
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,42 @@ | ||
| (dp0 | ||
| S'ALG_DESC' | ||
| p1 | ||
| VThis algorithm creates a graph that demonstrates the dependency of the intensity of the point process on the value of covariate. In this algorithm the covariate is the distance to the certain objects. The functionality is based on 'rhohat' function of the 'spatstat' package. \u000a\u000aR dependencies: library "maptools", "spatstat" and "rpanel". | ||
| p2 | ||
| sS'ALG_CREATOR' | ||
| p3 | ||
| VYury Ryabov\u000a2013\u000ariabovvv@gmail.com | ||
| p4 | ||
| sS'Layer' | ||
| p5 | ||
| VThe point process which distribution will be investigated. | ||
| p6 | ||
| sS'Covariate_name' | ||
| p7 | ||
| VThis field is mandatory. Enter the name of the covariate. It will appear at the graph. | ||
| p8 | ||
| sS'Legend_position' | ||
| p9 | ||
| VThis field defines the position of the legend at the graph. 'float' means that the legend will be placed at the position that would not overlap the graph itself (or will try at least). Other options are: 'topleft', 'topright', 'bottomleft', 'bottomright'. | ||
| p10 | ||
| sS'x_label' | ||
| p11 | ||
| VOptional label for the X axis. Note that units at the X axis will be the same as in the input layers. | ||
| p12 | ||
| sS'RPLOTS' | ||
| p13 | ||
| VThe empirical graph of the dependency of the intensity of the point process on the distance to the given objects. | ||
| p14 | ||
| sS'ALG_HELP_CREATOR' | ||
| p15 | ||
| VYury Ryabov\u000a2013\u000ariabovvv@gmail.com | ||
| p16 | ||
| sS'Plot_name' | ||
| p17 | ||
| VOptional plot name. | ||
| p18 | ||
| sS'Covariate' | ||
| p19 | ||
| VThe set of objects the distance from which will be calculated and used as a spatial covariate to the point process. | ||
| p20 | ||
| s. |
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,42 @@ | ||
| (dp0 | ||
| S'ALG_DESC' | ||
| p1 | ||
| VThis algorithm creates a graph that demonstrates the dependency of the intensity of the point process on the value of covariate. In this algorithm the covariate is the distance to the certain objects. The functionality is based on 'rhohat' function of the 'spatstat' package. \u000a\u000aR dependencies: library "maptools", "spatstat" and "rpanel". | ||
| p2 | ||
| sS'ALG_CREATOR' | ||
| p3 | ||
| VYury Ryabov\u000a2013\u000ariabovvv@gmail.com | ||
| p4 | ||
| sS'Layer' | ||
| p5 | ||
| VThe point process which distribution will be investigated. | ||
| p6 | ||
| sS'Covariate_name' | ||
| p7 | ||
| VThis field is mandatory. Enter the name of the covariate. It will appear at the graph. | ||
| p8 | ||
| sS'Legend_position' | ||
| p9 | ||
| VThis field defines the position of the legend at the graph. 'float' means that the legend will be placed at the position that would not overlap the graph itself (or will try at least). Other options are: 'topleft', 'topright', 'bottomleft', 'bottomright'. | ||
| p10 | ||
| sS'x_label' | ||
| p11 | ||
| VOptional label for the X axis. Note that units at the X axis will be the same as in the input layers. | ||
| p12 | ||
| sS'RPLOTS' | ||
| p13 | ||
| VThe empirical graph of the dependency of the intensity of the point process on the distance to the given objects. | ||
| p14 | ||
| sS'ALG_HELP_CREATOR' | ||
| p15 | ||
| VYury Ryabov\u000a2013\u000ariabovvv@gmail.com | ||
| p16 | ||
| sS'Plot_name' | ||
| p17 | ||
| VOptional plot name. | ||
| p18 | ||
| sS'Covariate' | ||
| p19 | ||
| VThe set of objects the distance from which will be calculated and used as a spatial covariate to the point process. | ||
| p20 | ||
| s. |
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,29 @@ | ||
| ##Point pattern analysis=group | ||
| ##points=vector | ||
| ##covariate=raster | ||
| ##covariate_name=string mandatory_covariate_name_(no_spaces) | ||
| ##x_label=string | ||
| ##plot_name=string | ||
| ##legend_position=string float | ||
| ##showplots | ||
| library(geostatsp) | ||
| library(maptools) | ||
| library(rpanel) | ||
| if (covariate_name == "") { | ||
| rp.messagebox('"covariate name" must not be empty!', title = 'oops!') | ||
| } | ||
| else { | ||
| S <- points | ||
| SP <- as(S, "SpatialPoints") | ||
| P <- as(SP, "ppp") | ||
| covariate <- raster(covariate, layer = 1) | ||
| covariate <- as.im(covariate) | ||
| library(spatstat) | ||
| S <- points | ||
| SP <- as(S, "SpatialPoints") | ||
| P <- as(SP, "ppp") | ||
| plot(rhohat(P, covariate, covname=covariate_name), xlab= x_label, | ||
| legendpos = legend_position, | ||
| legendargs=list(bg="transparent"), | ||
| main = plot_name) | ||
| } |
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,42 @@ | ||
| (dp0 | ||
| S'ALG_DESC' | ||
| p1 | ||
| VThis algorithm creates a graph that demonstrates the dependency of the intensity of the point process on the value of the given covariate. In this algorithm the covariate must be represented as a raster. The functionality is based on 'rhohat' function of the 'spatstat' package. \u000a\u000aR dependencies: library "geostatsp", "maptools", "rpanel", "spatstat" | ||
| p2 | ||
| sS'legend_position' | ||
| p3 | ||
| VThis field defines the position of the legend at the graph. 'float' means that the legend will be placed at the position that would not overlap the graph itself (or will try at least). Other options are: 'topleft', 'topright', 'bottomleft', 'bottomright'. | ||
| p4 | ||
| sS'ALG_CREATOR' | ||
| p5 | ||
| VYury Ryabov\u000a2013\u000ariabovvv@gmail.com | ||
| p6 | ||
| sS'covariate_name' | ||
| p7 | ||
| VThis field is mandatory. Enter the name of the covariate. It will appear at the graph. | ||
| p8 | ||
| sS'x_label' | ||
| p9 | ||
| VOptional label for the X axis. Note that units at the X axis will be the same as in the input layers. | ||
| p10 | ||
| sS'points' | ||
| p11 | ||
| VThe point process which distribution will be investigated. | ||
| p12 | ||
| sS'RPLOTS' | ||
| p13 | ||
| VThe empirical graph of the dependency of the intensity of the point process on the distance to the given objects. | ||
| p14 | ||
| sS'ALG_HELP_CREATOR' | ||
| p15 | ||
| VYury Ryabov\u000a2013\u000ariabovvv@gmail.com | ||
| p16 | ||
| sS'plot_name' | ||
| p17 | ||
| VOptional plot name. | ||
| p18 | ||
| sS'covariate' | ||
| p19 | ||
| VThe spatial covariate to the point process. The raster must not have discrete values, i.e. it may not be classified. Only rasters that represent continious phenomena (e.g. DEM, distance maps, etc.) are allowed. Though classified rasters will be processed if supplied, but the results will be meaningless. | ||
| p20 | ||
| s. |
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,12 @@ | ||
| ##Point pattern analysis=group | ||
| ##Layer=vector | ||
| ##Output=output vector | ||
| library("spatstat") | ||
| library("maptools") | ||
| proj4string(Layer)->crs | ||
| spatpoints = as(Layer,"SpatialPoints") | ||
| ripras=ripras(as(spatpoints,"ppp")) | ||
| polyg=as(ripras,"SpatialPolygons") | ||
| Output1= SpatialPolygonsDataFrame(polyg, data.frame(1)) | ||
| proj4string(Output1)<-crs | ||
| Output<-Output1 |
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,22 @@ | ||
| (dp0 | ||
| S'ALG_CREATOR' | ||
| p1 | ||
| VVictor Olaya, volayaf(at)gmail.com | ||
| p2 | ||
| sS'Output' | ||
| p3 | ||
| VRiplay-Rasson estimate of the spatial domain. | ||
| p4 | ||
| sS'ALG_DESC' | ||
| p5 | ||
| VThis script computes the Ripley-Rasson estimate of the spatial domain from which an observed pattern of points came.\u000a\u000aR dependencies: library "maptools" and "spatstat" | ||
| p6 | ||
| sS'Layer' | ||
| p7 | ||
| VA vector layer contain a point pattern. | ||
| p8 | ||
| sS'ALG_HELP_CREATOR' | ||
| p9 | ||
| VFilipe S. Dias, filipesdias(at)gmail.com | ||
| p10 | ||
| s. |
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,12 @@ | ||
| ##Home Range Analysis=group | ||
| ##showplots | ||
| ##Layer=vector | ||
| ##Field=Field Layer | ||
| ##Percentage=number 10 | ||
| ##Home_ranges=Output vector | ||
| library(adehabitatHR) | ||
| uu<-clusthr(Layer[,Field]) | ||
| Home_ranges<-getverticeshr(uu,percent=Percentage) | ||
| ii <- MCHu2hrsize(uu, percent=seq(50, 100, by=5)) | ||
| par(mar=c(2,2,2,2)) | ||
| plot(ii) |
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,34 @@ | ||
| (dp0 | ||
| S'ALG_DESC' | ||
| p1 | ||
| VThis script estimates the home range of one or more animals by single-linkage cluster analysis.\u000a\u000aR depencies: library "adehabitatHR" | ||
| p2 | ||
| sS'Home_ranges' | ||
| p3 | ||
| VA multipart vector layer containing the home ranges of each animal, according to the selected "Percentage" value. | ||
| p4 | ||
| sS'ALG_CREATOR' | ||
| p5 | ||
| VFilipe S. Dias, filipesdias(at)gmail.com | ||
| p6 | ||
| sS'Layer' | ||
| p7 | ||
| VA vector layer containing the relocations of one or more animals. | ||
| p8 | ||
| sS'Field' | ||
| p9 | ||
| VThe field that contains the unique identifier (type "string") for each animal. | ||
| p10 | ||
| sS'RPLOTS' | ||
| p11 | ||
| VA plot showing the relationship between the home range size and the percentage of relocations included in the home range.\u000a | ||
| p12 | ||
| sS'ALG_HELP_CREATOR' | ||
| p13 | ||
| VFilipe S. Dias, filipesdias(at)gmail.com | ||
| p14 | ||
| sS'Percentage' | ||
| p15 | ||
| VPercentage of the relocations used in the calculations. | ||
| p16 | ||
| s. |
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,14 @@ | ||
| ##Basic statistics=group | ||
| ##Layer=vector | ||
| ##Field=Field Layer | ||
| Summary_statistics<-data.frame(rbind(sum(Layer[[Field]]), | ||
| length(Layer[[Field]]), | ||
| length(unique(Layer[[Field]])), | ||
| min(Layer[[Field]]), | ||
| max(Layer[[Field]]), | ||
| max(Layer[[Field]])-min(Layer[[Field]]), | ||
| mean(Layer[[Field]]), | ||
| median(Layer[[Field]]), | ||
| sd(Layer[[Field]])),row.names=c("Sum:","Count:","Unique values:","Minimum value:","Maximum value:","Range:","Mean value:","Median value:","Standard deviation:")) | ||
| colnames(Summary_statistics)<-c(Field) | ||
| >Summary_statistics |
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,26 @@ | ||
| (dp0 | ||
| S'ALG_DESC' | ||
| p1 | ||
| VThis tool calculates the following summary statistics for a numeric field: (1) Sum, (2) Count, (3) Unique values, (4) Minimum value, (5) Maximum value, (6) Range, (7) Mean, (8) Median and (9) Standard deviation.\u000a\u000a | ||
| p2 | ||
| sS'R_CONSOLE_OUTPUT' | ||
| p3 | ||
| VSummary statistics table | ||
| p4 | ||
| sS'ALG_CREATOR' | ||
| p5 | ||
| VFilipe S. Dias, filipesdias(at)gmail.com | ||
| p6 | ||
| sS'Layer' | ||
| p7 | ||
| VInput vector with at least one numeric field | ||
| p8 | ||
| sS'Field' | ||
| p9 | ||
| VNumeric field | ||
| p10 | ||
| sS'ALG_HELP_CREATOR' | ||
| p11 | ||
| VFilipe S. Dias, filipesdias(at)gmail.com | ||
| p12 | ||
| s. |
