changeset 1:fc621f3f8226 draft

planemo upload for repository https://github.com/galaxyecology/tools-ecology/tree/master/tools/Ecoregionalization_workflow commit 459ba1277acd7d8d4a02f90dbd7ff444bf8eac92
author ecology
date Wed, 24 Jan 2024 15:52:56 +0000
parents f0d6938d0451
children f8962f1c832a
files BRT_model.xml brt.R cluster_ceamarc.R crea_carte_G.R nb_clust_G.R recup_liste_taxon.R test-data/1_brts_pred_ceamarc.tsv test-data/1_brts_pred_ceamarc.txt test-data/Data.bio_table.tsv test-data/Data_to_cluster.tsv test-data/List_of_taxa.txt test-data/List_of_taxa_clean.txt test-data/SIH_index_plot.png test-data/Summary_of_taxa_model.csv test-data/Summary_of_taxa_model.tsv test-data/ceamarc_env.csv test-data/ceamarc_env.tsv test-data/cnidaria_filtered.csv test-data/cnidaria_filtered.tsv test-data/ecoregions.png test-data/points_clus.tsv test-data/points_clus.txt
diffstat 22 files changed, 156162 insertions(+), 156129 deletions(-) [+]
line wrap: on
line diff
--- a/BRT_model.xml	Wed Oct 18 09:58:51 2023 +0000
+++ b/BRT_model.xml	Wed Jan 24 15:52:56 2024 +0000
@@ -1,4 +1,4 @@
-<tool id="ecoregion_brt_analysis" name="BRT tool prediction" version="0.1.0+galaxy0" profile="22.05">
+<tool id="ecoregion_brt_analysis" name="BRT prediction tool" version="0.1.0+galaxy0" profile="22.05">
     <description>for species distribution modelling</description>
     <requirements>
        <requirement type="package" version="4.3.0">r-base</requirement>
@@ -16,15 +16,25 @@
          '$outputval'
          '$outputspdistri'
          '$outputplots'
+         '$dec_env'
+         '$dec_species'
     ]]></command>
     <inputs>
-      <param name="enviro" type="data" format="txt,csv,tabular" label="Environment Data"/>
-      <param type="data" name="species_files" label="Occurrences Data File" format="tabular,txt,csv" multiple="True" />
-      <param name="abioticname" type="text" label="Write the name of your abiotic parameters (comma separated)"/>
+      <param name="enviro" type="data" format="tabular" label="Input your environment data file of your study area (tabular format only)" help="See example below"/>
+      <param name="dec_env" type="select" label="What's the decimal separator of your environement data file ?">
+              <option value=".">Dot</option>
+              <option value=",">Comma</option>
+      </param>
+      <param type="data" name="species_files" label="Input your occurrences data file(s) containing also the environemental caracteristics where the species has been observe (tabular format only)" format="tabular" multiple="True" help="See example below"/>
+      <param name="dec_species" type="select" label="What's the decimal separator of your occurrences data file(s) ?" help="It must be the same for all your occurences data files" >
+              <option value=".">Dot</option>
+              <option value=",">Comma</option>
+      </param>
+      <param name="abioticname" type="data_column" label="Choose column(s) where your abiotic parameter are in your environment data file." data_ref="enviro" multiple="true"/>
     </inputs>
     <outputs>
       <collection name="outputpred" type="list" label="Prediction files">
-            <discover_datasets pattern="(?P&lt;designation&gt;.+_brts_pred_ceamarc)\.txt" format="txt"/>
+            <discover_datasets pattern="(?P&lt;designation&gt;.+_brts_pred_ceamarc)\.tsv" format="tabular"/>
       </collection>
       <collection name="outputval" type="list" label="Validation files (Taxa, AUC, Tree complexity, Total deviance explained)">
             <discover_datasets pattern="(?P&lt;designation&gt;.+_brts_validation_ceamarc)\.tsv" format="tabular" />
@@ -38,25 +48,15 @@
     </outputs>
     <tests>
         <test>
-            <param name="enviro" value="ceamarc_env.csv"/>
-            <param name="species_files" value="cnidaria_filtered.csv"/>
-            <param name="abioticname" value="Carbo,Grav,Maxbearing,Maxmagnit,Meancurmag,Meansal,Meantheta,Mud,Prof,Rugosity,Sand,Seaice_prod,Sili,Slope,Standcurmag,Standsal,Standtheta"/>
+            <param name="enviro" value="ceamarc_env.tsv"/>
+            <param name="species_files" value="cnidaria_filtered.tsv"/>
+            <param name="abioticname" value="3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19"/>
+            <param name="dec_env" value="Dot"/>
+            <param name="dec_species" value="Comma"/>
             <output_collection name='outputpred' type = "list" count="1"/>
             <output_collection name='outputval' type = "list" count="1"/>
-            <output_collection name='outputspdistri' type = "list" count="2">
-                  <element name="BRT- Actiniaria _pred_plot">
-                       <assert_contents>
-            	           <has_size value="76065" delta="10000"/>
-            	      </assert_contents>
-            	  </element>
-            </output_collection>
-            <output_collection name='outputplots' type = "list">
-                  <element name="BRT- Actiniaria " >
-                       <assert_contents>
-            	           <has_size value="16042" delta="1000"/>
-            	       </assert_contents>
-            	  </element>
-            </output_collection>
+            <output_collection name='outputspdistri' type = "list" count="2"/>
+            <output_collection name='outputplots' type = "list" count="2"/>
         </test>
     </tests>
     <help><![CDATA[
@@ -71,8 +71,12 @@
 **How to use it ?**
 ===================
         
-This tool takes in input the environmental data as well as the species occurrence data. See examples of inputs below. You also need to input the list of abiotic parameters (respecting the case, without spaces and separating them by commas). For example : Carbo,Grav,Maxbearing,...
-This tool gives in output a file containing the predictions of probability of presence of each taxon for each pixel (latitude, longitude) environmental, a visualization of these pixels for each taxon and graphs showing the percentage of model explanation for each environmental parameter. 
+This tool takes in input the environmental data (for all the study areas) as well as the species occurrence data and the environmental characteristics where the species has been observed. See examples of inputs below. These files need to be in tabular format. You also need to select the column where your abiotic parameters are in your environment data file.
+ 
+ .. class:: infomark 
+Your abiotic parameters must be present in your occurrence data file(s) and must be named the same as in your environment file.
+ 
+This tool gives in output a file containing the predictions of the probability of the presence of each taxon for each pixel (latitude, longitude) environmental, a visualization of these pixels for each taxon and graphs showing the percentage of model explanation for each environmental parameter. 
 
 **Example of environmental data input :** 
 -----------------------------------------
@@ -87,22 +91,18 @@
 | ...  | ...  |   ...   | ...  |     ...      | ... |
 +------+------+---------+------+--------------+-----+
 
-
 **Example of occurence data input :** 
 -------------------------------------
 
-+---------+----------+-----------+------------------------+-----------+-----+
-| station |   lat    |   long    |Acanthorhabdus_fragilis | Acarnidae | ... |
-+---------+----------+-----------+------------------------+-----------+-----+
-|    1    |-65,999946|142,3360535|           0            |     1     | ... |
-+---------+----------+-----------+------------------------+-----------+-----+
-|   10    |-66,335407| 141,3028  |           0            |     1     | ... |
-+---------+----------+-----------+------------------------+-----------+-----+
-|   ...   |   ...    |   ...     |          ...           |    ...    | ... |
-+---------+----------+-----------+------------------------+-----------+-----+
-
-
-
++---------+----------+-----------+------------------------+-----------+-----+------+--------------+-----+
+| station |   lat    |   long    |Acanthorhabdus_fragilis | Acarnidae | ... | Grav |  Maxbearing  | ... |
++---------+----------+-----------+------------------------+-----------+-----+------+--------------+-----+
+|    1    |-65,999946|142,3360535|           0            |     1     | ... |28.59 |     3.67     | ... |
++---------+----------+-----------+------------------------+-----------+-----+------+--------------+-----+
+|   10    |-66,335407| 141,3028  |           0            |     1     | ... |28.61 |     3.64     | ... |
++---------+----------+-----------+------------------------+-----------+-----+------+--------------+-----+
+|   ...   |   ...    |   ...     |          ...           |    ...    | ... | ...  |     ...      | ... |
++---------+----------+-----------+------------------------+-----------+-----+------+--------------+-----+
 
     ]]></help>
 </tool>
--- a/brt.R	Wed Oct 18 09:58:51 2023 +0000
+++ b/brt.R	Wed Jan 24 15:52:56 2024 +0000
@@ -1,109 +1,121 @@
-#16/02/2023
-## Analyse BRT data Ceamarc
-
-### Clean environment 
-rm(list = ls(all.names = TRUE))
-options(warn=-1)
-
-### load packages
-
-library(dismo, warn.conflicts = FALSE)
-library(gbm, warn.conflicts = FALSE)
-library(ggplot2, warn.conflicts = FALSE)
-
-
-#load arguments
-args = commandArgs(trailingOnly=TRUE) 
-if (length(args)==0)
-{
-    stop("This tool needs at least one argument")
-}else{
-    enviro <- args[1]
-    species_files <- args[2]
-    abio_para <- args[3]
-}
-
-### load data
-
-env = read.table(enviro, header = TRUE, dec = ".", na.strings = "-9999")
-pred.vars = strsplit(abio_para, ",")[[1]] 
-data_files = strsplit(species_files,",")
-
-#environemental parameters
-#Carbo,Grav,Maxbearing,Maxmagnit,Meancurmag,Meansal,Meantheta,Mud,Prof,Rugosity,Sand,Seaice_prod,Sili,Slope,Standcurmag,Standsal,Standtheta
-
-#Load functions
-
-make.brt <- function(spe,data,pred.vars,env,nb_file){
-   brt_step <- gbm.step(data= data, gbm.x = pred.vars, gbm.y = spe, family = "bernoulli", tree.complexity = 2, learning.rate = 0.0001,max.trees = 10000,plot.main = F)
-   #plot
-   if (is.null(brt_step)==FALSE){
-     pdf(file = paste("BRT-",spe,".pdf"))
-     gbm.plot(brt_step, write.title = T,show.contrib = T, y.label = "fitted function",plot.layout = c(3,3))
-     dev.off()
-     #total deviance explained as (Leathwick et al., 2006)
-     total_deviance <- brt_step$self.statistics$mean.null
-     cross_validated_residual_deviance <- brt_step$cv.statistics$deviance.mean
-     total_deviance_explained <- (total_deviance - cross_validated_residual_deviance)/total_deviance
-     #Validation file
-     valid = cbind(spe,brt_step$cv.statistics$discrimination.mean,brt_step$gbm.call$tree.complexity,total_deviance_explained)
-     write.table(valid, paste(nb_file,"_brts_validation_ceamarc.tsv",sep=""), quote=FALSE, dec=".",sep="\t" ,row.names=F, col.names=F,append = T)}
-   
-   return(brt_step)
-   }
-
-make.prediction.brt <- function(brt_step){
-  #predictions
-  preds <- predict.gbm(brt_step,env,n.trees=brt_step$gbm.call$best.trees, type="response")
-  preds <- as.data.frame(cbind(env$lat,env$long,preds))
-  colnames(preds) <- c("lat","long","Prediction.index")
-  #carto
-  ggplot()+
-    geom_raster(data = preds , aes(x = long, y = lat, fill = Prediction.index))+
-    geom_raster(data = preds , aes(x = long, y = lat, alpha = Prediction.index))+
-    scale_alpha(range = c(0,1), guide = "none")+
-    scale_fill_viridis_c(
-      alpha = 1,
-      begin = 0,
-      end = 1,
-      direction = -1,
-      option = "D",
-      values = NULL,
-      space = "Lab",
-      na.value = "grey50",
-      guide = "colourbar",
-      aesthetics = "fill")+
-    xlab("Longitude") + ylab("Latitude")+ ggtitle(paste(spe,"Plot of BRT predictions"))+
-    theme(plot.title = element_text(size = 10))+
-    theme(axis.title.y = element_text(size = 10))+
-    theme(axis.title.x = element_text(size = 10))+
-    theme(axis.text.y = element_text(size = 10))+
-    theme(axis.text.x = element_text(size = 10))+
-    theme(legend.text = element_text(size = 10))+
-    theme(legend.title = element_text(size = 10))+ 
-    coord_quickmap()
-  output_directory <- ggsave(paste("BRT-",spe,"_pred_plot.png"))
-  
-  #Write prediction in a file
-  preds <- cbind(preds,spe)
-  write.table(preds, paste(nb_file,"_brts_pred_ceamarc.txt",sep=""), quote=FALSE, dec=".", row.names=F, col.names=T,append = T)
-}
-
-#### RUN BRT ####
-nb_file = 0
-
-for (file in data_files[[1]]) {
-  species_data <- read.table(file, dec = ",", sep = ";", header = TRUE, na.strings = "na", colClasses = "numeric")
-  nb_file = nb_file + 1
-  `%!in%` <- Negate(`%in%`)
-  sp = list()
-  for (n in names(species_data)) {
-    if (n %!in% names(env) && n != 'station'){
-       sp = cbind(sp,n)
-    }
-  }
-  
-  for (spe in sp){
-   try(make.prediction.brt(make.brt(spe,species_data,pred.vars,env,nb_file)))
-   }
-}
+#16/02/2023
+## Analyse BRT data
+
+### Clean environment 
+rm(list = ls(all.names = TRUE))
+options(warn=-1)
+
+### load packages
+
+library(dismo, warn.conflicts = FALSE)
+library(gbm, warn.conflicts = FALSE)
+library(ggplot2, warn.conflicts = FALSE)
+
+
+#load arguments
+args = commandArgs(trailingOnly=TRUE) 
+if (length(args)==0)
+{
+    stop("This tool needs at least one argument")
+}else{
+    enviro <- args[1]
+    species_files <- args[2]
+    abio_para <- args[3]
+    dec_env <- args[8]
+    dec_species <- args[9]
+}
+
+### load data
+
+env = read.table(enviro, dec = dec_env, header = TRUE, sep="\t", na.strings = "-9999")
+pred_vars = strsplit(abio_para, ",")[[1]] 
+data_files = strsplit(species_files,",")
+
+pred.vars <- character(length(pred_vars))
+
+for (i in seq_along(pred_vars)) {
+       pred_var_col <- as.numeric(pred_vars[i])
+       pred.vars[i] <- names(env)[pred_var_col]}
+       
+#environemental parameters
+#Carbo,Grav,Maxbearing,Maxmagnit,Meancurmag,Meansal,Meantheta,Mud,Prof,Rugosity,Sand,Seaice_prod,Sili,Slope,Standcurmag,Standsal,Standtheta
+
+#Load functions
+
+make.brt <- function(spe,data,pred.vars,env,nb_file){
+   brt_step <- gbm.step(data= data, gbm.x = pred.vars, gbm.y = spe, family = "bernoulli", tree.complexity = 2, learning.rate = 0.0001,max.trees = 10000,plot.main = F)
+   #plot
+   if (is.null(brt_step)==FALSE){
+     pdf(file = paste("BRT-",spe,".pdf"))
+     gbm.plot(brt_step, write.title = T,show.contrib = T, y.label = "fitted function",plot.layout = c(3,3))
+     dev.off()
+     #total deviance explained as (Leathwick et al., 2006)
+     total_deviance <- brt_step$self.statistics$mean.null
+     cross_validated_residual_deviance <- brt_step$cv.statistics$deviance.mean
+     total_deviance_explained <- (total_deviance - cross_validated_residual_deviance)/total_deviance
+     #Validation file
+     valid = cbind(spe,brt_step$cv.statistics$discrimination.mean,brt_step$gbm.call$tree.complexity,total_deviance_explained)
+     write.table(valid, paste(nb_file,"_brts_validation_ceamarc.tsv",sep=""), quote=FALSE, dec=".",sep="\t" ,row.names=F, col.names=F,append = T)}
+   
+   return(brt_step)
+   }
+
+make.prediction.brt <- function(brt_step){
+  #predictions
+  preds <- predict.gbm(brt_step,env,n.trees=brt_step$gbm.call$best.trees, type="response")
+  preds <- as.data.frame(cbind(env$lat,env$long,preds))
+  colnames(preds) <- c("lat","long","Prediction.index")
+  #carto
+  ggplot()+
+    geom_raster(data = preds , aes(x = long, y = lat, fill = Prediction.index))+
+    geom_raster(data = preds , aes(x = long, y = lat, alpha = Prediction.index))+
+    scale_alpha(range = c(0,1), guide = "none")+
+    scale_fill_viridis_c(
+      alpha = 1,
+      begin = 0,
+      end = 1,
+      direction = -1,
+      option = "D",
+      values = NULL,
+      space = "Lab",
+      na.value = "grey50",
+      guide = "colourbar",
+      aesthetics = "fill")+
+    xlab("Longitude") + ylab("Latitude")+ ggtitle(paste(spe,"Plot of BRT predictions"))+
+    theme(plot.title = element_text(size = 10))+
+    theme(axis.title.y = element_text(size = 10))+
+    theme(axis.title.x = element_text(size = 10))+
+    theme(axis.text.y = element_text(size = 10))+
+    theme(axis.text.x = element_text(size = 10))+
+    theme(legend.text = element_text(size = 10))+
+    theme(legend.title = element_text(size = 10))+ 
+    coord_quickmap()
+  output_directory <- ggsave(paste("BRT-",spe,"_pred_plot.png"))
+  
+  #Write prediction in a file
+  preds <- cbind(preds,spe)
+  write.table(preds, paste(nb_file,"_brts_pred_ceamarc.tsv",sep=""), quote=FALSE, dec=".", row.names=F, col.names=T,append = T,sep="\t")
+}
+
+#### RUN BRT ####
+nb_file = 0
+
+for (file in data_files[[1]]) {
+  species_data <- read.table(file, dec = dec_species, sep = "\t", header = TRUE, na.strings = "NA", colClasses = "numeric")
+  nb_file = nb_file + 1
+  `%!in%` <- Negate(`%in%`)
+  sp = list()
+  for (n in names(species_data)) {
+    if (n %!in% names(env) && n != 'station'){
+       sp = cbind(sp,n)
+    }
+  }     
+  for (spe in sp){
+   try(make.prediction.brt(make.brt(spe,species_data,pred.vars,env,nb_file)))
+   }
+}
+
+cat("Here is the list of your abiotic parameters:\n")
+cat(paste(pred.vars, collapse = ", "), "\n")
+
+
--- a/cluster_ceamarc.R	Wed Oct 18 09:58:51 2023 +0000
+++ b/cluster_ceamarc.R	Wed Jan 24 15:52:56 2024 +0000
@@ -22,7 +22,7 @@
 }
 
 #load data 
-env.data <- read.table(enviro, header=TRUE, sep=" ",dec = ".", na.strings = "-9999.00")
+env.data <- read.table(enviro, header=TRUE, sep="\t",dec = ".", na.strings = "-9999")
 data.bio <- read.table(data.bio, header=TRUE, sep="\t")
 test3 <- read.table(data, header = TRUE, sep="\t") 
 
@@ -43,8 +43,8 @@
 names(clus) <- c("lat", "long", "cluster")
 clus <- cbind(clus,test3,env.data[,3:19])
 
-write.table(clus[1:3], file = "points_clus.txt",quote = FALSE, row.names = FALSE)
-write.table(clus, file = "clus.txt",quote = FALSE, row.names = FALSE)
+write.table(clus[1:3], file = "points_clus.tsv", quote = FALSE, sep="\t", row.names = FALSE)
+write.table(clus, file = "clus.tsv", quote = FALSE, sep="\t", row.names = FALSE)
 
 
 
--- a/crea_carte_G.R	Wed Oct 18 09:58:51 2023 +0000
+++ b/crea_carte_G.R	Wed Jan 24 15:52:56 2024 +0000
@@ -15,7 +15,7 @@
     data <- args[1]
 }
 
-clus <- read.table(data, header=TRUE, na.strings = "na")
+clus <- read.table(data, sep="\t" ,header=TRUE, na.strings = "na")
 
 #tmap method
 
@@ -26,7 +26,7 @@
   summarize()
 
 map <- tm_shape(grouped_data) + 
-  tm_dots(col = "cluster", palette = "Accent", size = 0.1, title = "écorégions")+
+  tm_dots(col = "cluster", palette = "Accent", n=256, size = 0.1, title = "ecoregions")+
   tm_scale_bar(position = c("right","top"))+
   tm_compass(position = c("right","top"))+
   tm_layout(frame = FALSE,legend.position = c("left","bottom"))+
--- a/nb_clust_G.R	Wed Oct 18 09:58:51 2023 +0000
+++ b/nb_clust_G.R	Wed Jan 24 15:52:56 2024 +0000
@@ -21,7 +21,7 @@
 
 #load data 
 
-env.data <- read.table(enviro, header = TRUE, dec = ".", na.strings = "-9999.00") 
+env.data <- read.table(enviro, sep="\t", header = TRUE, dec = ".", na.strings = "-9999") 
 
 ##List of modelled taxa used for clustering
 tv <- read.table(taxa_list, dec=".", sep=" ", header=F, na.strings = "NA") 
@@ -33,7 +33,7 @@
 data.bio = NULL
 
 for (i in 1:length(data_split[[1]])) {
-data.bio1 <- read.table(data_split[[1]][i], dec=".", sep=" ", header=T, na.strings = "NA")
+data.bio1 <- read.table(data_split[[1]][i], dec=".", sep="\t", header=T, na.strings = "NA")
 data.bio <- rbind(data.bio,data.bio1)
 remove(data.bio1)
 }
@@ -69,5 +69,5 @@
 
 # Plot SIH Index Chart by Number of Clusters
 png("Indices_SIH.png")
-plot(2:max_k, sih_values[2:max_k], type = "b", xlab = "Nombre de clusters", ylab = "Indice SIH")
+plot(2:max_k, sih_values[2:max_k], type = "b", xlab = "Number of clusters", ylab = "SIH index")
 dev.off()
--- a/recup_liste_taxon.R	Wed Oct 18 09:58:51 2023 +0000
+++ b/recup_liste_taxon.R	Wed Jan 24 15:52:56 2024 +0000
@@ -16,7 +16,7 @@
     enviro <- args[3]
 }
 
-env = read.table(enviro, header=T, na.strings = "na")
+env = read.table(enviro, sep="\t", dec=".", header=T, na.strings = "-9999")
 occurrence_files = strsplit(data,",")
 preds_files = strsplit(preds,",")
 
@@ -45,7 +45,7 @@
 ##########Execution########
 brt = NULL
 for (j in 1:length(preds_files[[1]])){
-    brt <- rbind(brt,read.table(preds_files[[1]][j], header = TRUE, na.strings = "na"))
+    brt <- rbind(brt,read.table(preds_files[[1]][j], sep="\t", header = TRUE, na.strings = "na"))
 }
 
 for (i in 1:length(occurrence_files[[1]])) {
@@ -53,7 +53,7 @@
   cmpt <- NULL
   taxon <- list()
   
-  occurrence <- read.table(occurrence_files[[1]][i], dec = ",", sep = ";", header = TRUE, na.strings = "na")
+  occurrence <- read.table(occurrence_files[[1]][i], sep = "\t", header = TRUE, na.strings = "na")
   
   taxon_names <- names(occurrence)
   new_taxon <- taxon_names[!(taxon_names %in% names(env)) & taxon_names != "station"]
@@ -66,8 +66,8 @@
 }
 
 #Taxa for which a model was obtained
-have_model2 = subset(have_model, have_model$`Model` != "N")
-have_model3 = subset(have_model, have_model$`Model` != "N")
+have_model2 = subset(have_model, have_model$`Model` != "No")
+have_model3 = subset(have_model, have_model$`Model` != "No")
 
 #Obtain a list of taxa (cleaned) that have obtained a BRT model (file that can be submitted to the match taxa tool of the WoRMS database to obtain their classification and be able to sort duplicates between taxonomic ranks)
 
@@ -80,7 +80,7 @@
 have_model <- have_model %>% filter(!str_ends(Taxa, "sp.1|sp[0-9]"))
 
 #extraction of the have_model object
-write.csv(have_model,file = "have_model.csv", quote = F, row.names = F)
+write.table(have_model,file = "have_model.tsv", sep="\t", quote = F, row.names = F)
 
 #getting list of taxa for next if not using worms
 list_taxon = have_model3$Taxa
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/1_brts_pred_ceamarc.tsv	Wed Jan 24 15:52:56 2024 +0000
@@ -0,0 +1,32 @@
+lat	long	Prediction.index	spe
+-65.57	139.22	0.841140843659849	Actiniaria
+-65.57	139.22	0.84803516905332	Actiniaria
+-65.57	139.23	0.845987230372577	Actiniaria
+-65.57	139.24	0.845807234659773	Actiniaria
+-65.57	139.24	0.845815355113451	Actiniaria
+-65.57	139.25	0.838300654503413	Actiniaria
+-65.57	139.26	0.836294936412005	Actiniaria
+-65.57	139.26	0.836091676730536	Actiniaria
+-65.57	139.27	0.835788235641246	Actiniaria
+-65.57	139.28	0.83554848351174	Actiniaria
+-65.57	139.28	0.842919257873871	Actiniaria
+-65.57	139.29	0.843113627396164	Actiniaria
+-65.57	139.3	0.837674310999705	Actiniaria
+-65.57	139.3	0.78950055854148	Actiniaria
+-65.57	139.31	0.789217507689643	Actiniaria
+lat	long	Prediction.index	spe
+-65.57	139.22	0.247351772498557	Thouarella_vulpicauda
+-65.57	139.22	0.247098939858693	Thouarella_vulpicauda
+-65.57	139.23	0.246144373571671	Thouarella_vulpicauda
+-65.57	139.24	0.245908115738853	Thouarella_vulpicauda
+-65.57	139.24	0.245908115738853	Thouarella_vulpicauda
+-65.57	139.25	0.245908115738853	Thouarella_vulpicauda
+-65.57	139.26	0.292387985632338	Thouarella_vulpicauda
+-65.57	139.26	0.24323878088903	Thouarella_vulpicauda
+-65.57	139.27	0.233523508895553	Thouarella_vulpicauda
+-65.57	139.28	0.222381660561301	Thouarella_vulpicauda
+-65.57	139.28	0.22225741167332	Thouarella_vulpicauda
+-65.57	139.29	0.215965799041526	Thouarella_vulpicauda
+-65.57	139.3	0.224167139202414	Thouarella_vulpicauda
+-65.57	139.3	0.251901045968841	Thouarella_vulpicauda
+-65.57	139.31	0.251653126333346	Thouarella_vulpicauda
--- a/test-data/1_brts_pred_ceamarc.txt	Wed Oct 18 09:58:51 2023 +0000
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,16 +0,0 @@
-lat long Prediction.index spe
--65.57 139.22 0.841029593071458 Actiniaria
--65.57 139.22 0.84809523959125 Actiniaria
--65.57 139.23 0.84593837029871 Actiniaria
--65.57 139.24 0.845795319302531 Actiniaria
--65.57 139.24 0.845803531789338 Actiniaria
--65.57 139.25 0.838195173926856 Actiniaria
--65.57 139.26 0.836419710602451 Actiniaria
--65.57 139.26 0.836029330691246 Actiniaria
--65.57 139.27 0.835738500636347 Actiniaria
--65.57 139.28 0.835442888556642 Actiniaria
--65.57 139.28 0.84289272242705 Actiniaria
--65.57 139.29 0.843110664350552 Actiniaria
--65.57 139.3 0.837595245997102 Actiniaria
--65.57 139.3 0.791165108348526 Actiniaria
--65.57 139.31 0.790943656953059 Actiniaria
--- a/test-data/Data.bio_table.tsv	Wed Oct 18 09:58:51 2023 +0000
+++ b/test-data/Data.bio_table.tsv	Wed Jan 24 15:52:56 2024 +0000
@@ -1,16 +1,31 @@
 lat	long	pred	taxon
--65.57	139.22	0.841029593071458	Actiniaria
--65.57	139.22	0.84809523959125	Actiniaria
--65.57	139.23	0.84593837029871	Actiniaria
--65.57	139.24	0.845795319302531	Actiniaria
--65.57	139.24	0.845803531789338	Actiniaria
--65.57	139.25	0.838195173926856	Actiniaria
--65.57	139.26	0.836419710602451	Actiniaria
--65.57	139.26	0.836029330691246	Actiniaria
--65.57	139.27	0.835738500636347	Actiniaria
--65.57	139.28	0.835442888556642	Actiniaria
--65.57	139.28	0.84289272242705	Actiniaria
--65.57	139.29	0.843110664350552	Actiniaria
--65.57	139.3	0.837595245997102	Actiniaria
--65.57	139.3	0.791165108348526	Actiniaria
--65.57	139.31	0.790943656953059	Actiniaria
+-65.57	139.22	0.841140843659849	Actiniaria
+-65.57	139.22	0.84803516905332	Actiniaria
+-65.57	139.23	0.845987230372577	Actiniaria
+-65.57	139.24	0.845807234659773	Actiniaria
+-65.57	139.24	0.845815355113451	Actiniaria
+-65.57	139.25	0.838300654503413	Actiniaria
+-65.57	139.26	0.836294936412005	Actiniaria
+-65.57	139.26	0.836091676730536	Actiniaria
+-65.57	139.27	0.835788235641246	Actiniaria
+-65.57	139.28	0.83554848351174	Actiniaria
+-65.57	139.28	0.842919257873871	Actiniaria
+-65.57	139.29	0.843113627396164	Actiniaria
+-65.57	139.3	0.837674310999705	Actiniaria
+-65.57	139.3	0.78950055854148	Actiniaria
+-65.57	139.31	0.789217507689643	Actiniaria
+-65.57	139.22	0.247351772498557	Thouarella_vulpicauda
+-65.57	139.22	0.247098939858693	Thouarella_vulpicauda
+-65.57	139.23	0.246144373571671	Thouarella_vulpicauda
+-65.57	139.24	0.245908115738853	Thouarella_vulpicauda
+-65.57	139.24	0.245908115738853	Thouarella_vulpicauda
+-65.57	139.25	0.245908115738853	Thouarella_vulpicauda
+-65.57	139.26	0.292387985632338	Thouarella_vulpicauda
+-65.57	139.26	0.24323878088903	Thouarella_vulpicauda
+-65.57	139.27	0.233523508895553	Thouarella_vulpicauda
+-65.57	139.28	0.222381660561301	Thouarella_vulpicauda
+-65.57	139.28	0.22225741167332	Thouarella_vulpicauda
+-65.57	139.29	0.215965799041526	Thouarella_vulpicauda
+-65.57	139.3	0.224167139202414	Thouarella_vulpicauda
+-65.57	139.3	0.251901045968841	Thouarella_vulpicauda
+-65.57	139.31	0.251653126333346	Thouarella_vulpicauda
--- a/test-data/Data_to_cluster.tsv	Wed Oct 18 09:58:51 2023 +0000
+++ b/test-data/Data_to_cluster.tsv	Wed Jan 24 15:52:56 2024 +0000
@@ -1,16 +1,16 @@
-Actiniaria
-0.841029593071458
-0.84809523959125
-0.84593837029871
-0.845795319302531
-0.845803531789338
-0.838195173926856
-0.836419710602451
-0.836029330691246
-0.835738500636347
-0.835442888556642
-0.84289272242705
-0.843110664350552
-0.837595245997102
-0.791165108348526
-0.790943656953059
+Actiniaria	Thouarella_vulpicauda
+0.841140843659849	0.247351772498557
+0.84803516905332	0.247098939858693
+0.845987230372577	0.246144373571671
+0.845807234659773	0.245908115738853
+0.845815355113451	0.245908115738853
+0.838300654503413	0.245908115738853
+0.836294936412005	0.292387985632338
+0.836091676730536	0.24323878088903
+0.835788235641246	0.233523508895553
+0.83554848351174	0.222381660561301
+0.842919257873871	0.22225741167332
+0.843113627396164	0.215965799041526
+0.837674310999705	0.224167139202414
+0.78950055854148	0.251901045968841
+0.789217507689643	0.251653126333346
--- a/test-data/List_of_taxa.txt	Wed Oct 18 09:58:51 2023 +0000
+++ b/test-data/List_of_taxa.txt	Wed Jan 24 15:52:56 2024 +0000
@@ -1,7 +1,2 @@
-Acanthogorgiidae
 Actiniaria
-Ainigmaptilon_edisto
-Alcyonacea
-Anthozoa
-Thouarella_variabilis
 Thouarella_vulpicauda
--- a/test-data/List_of_taxa_clean.txt	Wed Oct 18 09:58:51 2023 +0000
+++ b/test-data/List_of_taxa_clean.txt	Wed Jan 24 15:52:56 2024 +0000
@@ -1,7 +1,2 @@
-Acanthogorgiidae
 Actiniaria
-Ainigmaptilon edisto
-Alcyonacea
-Anthozoa
-Thouarella variabilis
 Thouarella vulpicauda
Binary file test-data/SIH_index_plot.png has changed
--- a/test-data/Summary_of_taxa_model.csv	Wed Oct 18 09:58:51 2023 +0000
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,8 +0,0 @@
-Taxa,Model,Occurences
-Acanthogorgiidae,No,0
-Actiniaria,Yes,50
-Ainigmaptilon_edisto,No,2
-Alcyonacea,No,43
-Anthozoa,No,62
-Thouarella_variabilis,No,3
-Thouarella_vulpicauda,No,24
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/Summary_of_taxa_model.tsv	Wed Jan 24 15:52:56 2024 +0000
@@ -0,0 +1,8 @@
+Taxa	Model	Occurences
+Acanthogorgiidae	No	0
+Actiniaria	Yes	50
+Ainigmaptilon_edisto	No	2
+Alcyonacea	No	43
+Anthozoa	No	62
+Thouarella_variabilis	No	3
+Thouarella_vulpicauda	Yes	24
--- a/test-data/ceamarc_env.csv	Wed Oct 18 09:58:51 2023 +0000
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,16 +0,0 @@
-long lat Carbo Grav Maxbearing Maxmagnit Meancurmag Meansal Meantheta Mud Prof Rugosity Sand Seaice_prod Sili Slope Standcurmag Standsal Standtheta long_round lat_round
-139.22 -65.57 0.88 28.59 3.67 0.03 0.03 34.62 -0.13 22.72 -441.00 -9999.00 55.76 0.24 3.27 0.28 0.01 0.01 0.18 139,22 -65,57
-139.22 -65.57 0.88 28.61 3.64 0.02 0.03 34.62 -0.13 22.48 -439.00 -9999.00 55.74 0.24 3.29 0.27 0.01 0.01 0.18 139,22 -65,57
-139.23 -65.57 0.92 28.62 3.59 0.02 0.03 34.62 -0.14 22.25 -438.00 -9999.00 56.28 0.25 3.32 0.22 0.01 0.01 0.19 139,23 -65,57
-139.24 -65.57 0.92 28.63 3.51 0.01 0.03 34.62 -0.14 21.95 -436.00 -9999.00 56.57 0.26 3.30 0.08 0.01 0.01 0.19 139,24 -65,57
-139.24 -65.57 0.92 28.64 3.35 0.01 0.03 34.62 -0.14 21.70 -437.00 -9999.00 56.58 0.26 3.28 0.05 0.01 0.01 0.19 139,24 -65,57
-139.25 -65.57 0.93 28.65 3.00 9.6293305978179e-03 0.03 34.62 -0.15 21.44 -436.00 -9999.00 56.63 0.26 3.26 0.29 0.01 0.01 0.19 139,25 -65,57
-139.26 -65.57 0.93 28.63 2.49 8.71255807578564e-03 0.03 34.62 -0.15 21.11 -432.00 -9999.00 56.67 0.26 3.23 0.43 0.01 0.01 0.19 139,26 -65,57
-139.26 -65.57 0.93 28.64 2.01 0.01 0.03 34.62 -0.16 20.83 -429.00 -9999.00 56.71 0.26 3.21 0.37 0.01 0.01 0.19 139,26 -65,57
-139.27 -65.57 0.94 28.65 1.71 0.01 0.03 34.62 -0.16 20.55 -427.00 -9999.00 56.75 0.26 3.19 0.32 0.01 0.01 0.20 139,27 -65,57
-139.28 -65.57 0.94 28.66 1.54 0.01 0.03 34.62 -0.16 20.21 -424.00 -9999.00 56.80 0.26 3.17 0.28 0.01 0.01 0.20 139,28 -65,57
-139.28 -65.57 0.94 28.67 1.44 0.02 0.03 34.62 -0.17 19.74 -422.00 -9999.00 56.84 0.26 3.14 0.26 0.01 0.01 0.20 139,28 -65,57
-139.29 -65.57 0.94 28.68 1.74 0.01 0.03 34.62 -0.17 20.86 -421.00 -9999.00 56.87 0.26 3.13 0.22 0.01 0.01 0.20 139,29 -65,57
-139.30 -65.57 0.95 28.70 3.46 0.01 0.03 34.62 -0.17 21.30 -420.00 -9999.00 56.91 0.26 3.11 0.32 0.01 0.01 0.20 139,30 -65,57
-139.30 -65.57 0.95 28.71 3.91 0.03 0.03 34.62 -0.18 21.01 -414.00 -9999.00 57.18 0.26 3.09 0.59 0.01 0.01 0.21 139,30 -65,57
-139.31 -65.57 0.96 28.72 4.03 0.05 0.03 34.62 -0.18 20.76 -406.00 -9999.00 57.54 0.26 3.07 0.53 0.01 0.01 0.21 139,31 -65,57
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/ceamarc_env.tsv	Wed Jan 24 15:52:56 2024 +0000
@@ -0,0 +1,16 @@
+long	lat	Carbo	Grav	Maxbearing	Maxmagnit	Meancurmag	Meansal	Meantheta	Mud	Prof	Rugosity	Sand	Seaice_prod	Sili	Slope	Standcurmag	Standsal	Standtheta	long_round	lat_round
+1	139.22	-65.57	0.88	28.59	3.67	0.03	0.03	34.62	-0.13	22.72	-441	-9999	55.76	0.24	3.27	0.28	0.01	0.01	0.18	139,22	-65,57
+2	139.22	-65.57	0.88	28.61	3.64	0.02	0.03	34.62	-0.13	22.48	-439	-9999	55.74	0.24	3.29	0.27	0.01	0.01	0.18	139,22	-65,57
+3	139.23	-65.57	0.92	28.62	3.59	0.02	0.03	34.62	-0.14	22.25	-438	-9999	56.28	0.25	3.32	0.22	0.01	0.01	0.19	139,23	-65,57
+4	139.24	-65.57	0.92	28.63	3.51	0.01	0.03	34.62	-0.14	21.95	-436	-9999	56.57	0.26	3.3	0.08	0.01	0.01	0.19	139,24	-65,57
+5	139.24	-65.57	0.92	28.64	3.35	0.01	0.03	34.62	-0.14	21.7	-437	-9999	56.58	0.26	3.28	0.05	0.01	0.01	0.19	139,24	-65,57
+6	139.25	-65.57	0.93	28.65	3	0.0096293305978179	0.03	34.62	-0.15	21.44	-436	-9999	56.63	0.26	3.26	0.29	0.01	0.01	0.19	139,25	-65,57
+7	139.26	-65.57	0.93	28.63	2.49	0.00871255807578564	0.03	34.62	-0.15	21.11	-432	-9999	56.67	0.26	3.23	0.43	0.01	0.01	0.19	139,26	-65,57
+8	139.26	-65.57	0.93	28.64	2.01	0.01	0.03	34.62	-0.16	20.83	-429	-9999	56.71	0.26	3.21	0.37	0.01	0.01	0.19	139,26	-65,57
+9	139.27	-65.57	0.94	28.65	1.71	0.01	0.03	34.62	-0.16	20.55	-427	-9999	56.75	0.26	3.19	0.32	0.01	0.01	0.2	139,27	-65,57
+10	139.28	-65.57	0.94	28.66	1.54	0.01	0.03	34.62	-0.16	20.21	-424	-9999	56.8	0.26	3.17	0.28	0.01	0.01	0.2	139,28	-65,57
+11	139.28	-65.57	0.94	28.67	1.44	0.02	0.03	34.62	-0.17	19.74	-422	-9999	56.84	0.26	3.14	0.26	0.01	0.01	0.2	139,28	-65,57
+12	139.29	-65.57	0.94	28.68	1.74	0.01	0.03	34.62	-0.17	20.86	-421	-9999	56.87	0.26	3.13	0.22	0.01	0.01	0.2	139,29	-65,57
+13	139.3	-65.57	0.95	28.7	3.46	0.01	0.03	34.62	-0.17	21.3	-420	-9999	56.91	0.26	3.11	0.32	0.01	0.01	0.2	139,30	-65,57
+14	139.3	-65.57	0.95	28.71	3.91	0.03	0.03	34.62	-0.18	21.01	-414	-9999	57.18	0.26	3.09	0.59	0.01	0.01	0.21	139,30	-65,57
+15	139.31	-65.57	0.96	28.72	4.03	0.05	0.03	34.62	-0.18	20.76	-406	-9999	57.54	0.26	3.07	0.53	0.01	0.01	0.21	139,31	-65,57
--- a/test-data/cnidaria_filtered.csv	Wed Oct 18 09:58:51 2023 +0000
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,64 +0,0 @@
-station;lat;long;Carbo;Grav;Maxbearing;Maxmagnit;Meancurmag;Meansal;Meantheta;Mud;Prof;Rugosity;Sand;Seaice_prod;Sili;Slope;Standcurmag;Standsal;Standtheta;Acanthogorgiidae;Actiniaria;Ainigmaptilon_edisto;Alcyonacea;Anthozoa;Thouarella_variabilis;Thouarella_vulpicauda
-1;-65,99;142,33;5,51;12,59;2,03;0,16;0,07;34,6;-1,47;29,8;-233;1;56,16;0,11;3,94;0,05;0,03;0,03;0,24;0;1;0;0;1;0;0
-10;-66,33;141,3;3,17;5,31;5,2;0,18;0,08;34,61;-1,35;21,5;-215;1;67,39;0,17;5,8;0,24;0,03;0,02;0,28;0;1;0;1;1;0;0
-11;-66,56;141,29;3,1;3,28;4,93;0,2;0,08;34,65;-1,73;34,89;-192;1;73,13;0,87;4,48;0,71;0,03;0,04;0,24;0;0;0;1;1;0;0
-12;-66,55;140,82;2,78;3,08;3,74;0,34;0,1;34,59;-1,19;25,83;-217;1;68,37;2,62;4,05;2,57;0,06;0,02;0,24;0;1;0;1;1;1;0
-13;-66,15;140,65;2,06;7,62;5,36;0,21;0,09;34,56;-1,04;13,18;-217;1;71,68;0,07;2,89;0,37;0,04;0,02;0,26;0;1;0;0;1;0;0
-14;-66,33;140,67;2,96;3,12;2,42;0,16;0,08;34,54;-1,02;12,15;-171;1;73,16;0,78;1,17;0,08;0,03;0,01;0,22;0;1;0;0;1;0;0
-15;-66,38;139,8;1,06;1,65;1,87;0,14;0,05;34,64;-1,53;69,08;-855;1;48,44;1,43;13,55;2,94;0,03;0,01;0,06;0;1;0;1;1;0;0
-16;-66,34;139,99;1,34;2,78;1,61;0,15;0,05;34,6;-1,12;41,06;-538;1;54,72;1,23;5,97;3,7;0,03;0,00839;0,08;0;1;0;0;1;0;0
-17;-66,17;139,96;1,71;8,13;4,39;0,31;0,12;34,54;-0,96;17,16;-151;1;61,42;0,54;1,99;0,25;0,05;0,02;0,3;0;1;0;1;1;1;0
-18;-66,16;139,65;1,49;7,75;2,24;0,15;0,06;34,59;-1,01;32,71;-432;1;51,4;0,56;3,35;0,42;0,03;0,01;0,26;0;1;0;1;1;0;1
-19;-66,15;139,31;1,18;8,58;5,7;0,12;0,04;34,61;-1,36;47,4;-674;1;46,41;0,34;9,92;0,31;0,02;0,00722;0,09;0;1;0;0;1;0;0
-2;-65,99;141,32;3,3;14,21;5,01;0,16;0,07;34,6;-1,26;14,05;-235;1;67,07;-0,01;2,09;0,13;0,03;0,03;0,32;0;1;1;1;1;0;1
-20;-66;139,99;1,95;20,59;4,98;0,19;0,09;34,56;-1,05;13,25;-192;1;63,46;0,27;1,92;0,21;0,03;0,03;0,26;0;1;0;0;1;0;0
-21;-66;139,64;2,26;18,21;2,85;0,16;0,07;34,58;-1,04;44,81;-277;1;57,14;0,76;5,88;1,66;0,03;0,01;0,26;0;1;0;0;1;0;0
-22;-66;139,31;1,39;19,2;4,87;0,1;0,04;34,6;-1,05;37,84;-476;1;49,4;0,65;7,09;0,25;0,02;0,00884;0,15;0;1;0;1;1;0;0
-26;-66,52;140,02;1,51;1,47;4,4;0,12;0,05;34,6;-1,11;49,11;-247;1;49,52;2,38;10,29;3,16;0,02;0,00984;0,16;0;1;0;0;1;0;0
-27;-66,02;142,74;2,61;11,58;5,42;0,13;0,05;34,64;-1,73;25,07;-440;1;46,97;0,24;2,19;0,23;0,02;0,03;0,17;0;1;0;1;1;0;1
-28;-65,99;143,02;2,15;11,5;5,37;0,14;0,05;34,64;-1,77;39,29;-467;1;38,66;0,24;2,07;0,32;0,02;0,03;0,12;0;1;0;1;1;0;1
-29;-66,02;143,29;1,77;9,98;5,41;0,14;0,05;34,64;-1,78;62,2;-470;1;38,73;0,33;4,81;0,19;0,02;0,03;0,1;0;1;0;1;1;0;1
-3;-65,99;141,98;5,27;14,32;5,31;0,01;0,06;34,6;-1,4;22,84;-245;1;61,04;-0,00886;3,93;0,15;0,03;0,03;0,25;0;1;0;0;1;0;0
-30;-66;143,68;2,06;9,47;5,42;0,15;0,06;34,61;-1,71;54,73;-429;1;41,27;0,39;1,03;0,22;0,03;0,03;0,19;0;1;0;0;1;0;0
-31;-66,55;144,99;1,05;19,55;5,28;0,12;0,03;34,62;-1,73;35,57;-437;1;39,47;5,14;1,77;0,45;0,02;0,03;0,16;0;0;0;1;1;0;1
-34;-66,33;144,34;1,26;6,31;4,92;0,13;0,04;34,63;-1,77;44,96;-455;1;40,49;1,87;2,96;0,39;0,02;0,03;0,12;0;1;0;1;1;0;1
-35;-66,33;144,01;1,2;4,9;2,11;0,12;0,04;34,64;-1,78;49,09;-511;1;39,41;1,54;4,15;0,32;0,02;0,02;0,1;0;1;0;1;1;0;0
-36;-66,32;143,65;1,12;4,29;2,16;0,12;0,04;34,64;-1,79;53,85;-565;1;38,83;1,26;8,68;0,38;0,02;0,02;0,13;0;1;0;1;1;0;1
-37;-66,55;143,31;1,34;4,32;2,02;0,12;0,04;34,66;-1,82;78,15;-820;1;47,92;2,76;13,57;0,26;0,02;0,03;0,11;0;1;0;0;1;0;0
-38;-66,33;143,31;0,82;3,84;2,2;0,1;0,04;34,65;-1,8;84,13;-703;1;41,01;0,98;16,47;0,25;0,02;0,03;0,12;0;1;0;1;1;1;0
-39;-66,56;143,02;1,67;4,11;1,5;0,13;0,05;34,65;-1,8;47,63;-862;1;56,71;2,22;7,3;0,18;0,02;0,02;0,1;0;1;0;0;1;0;0
-40;-66,65;142,98;1,94;3,93;5,42;0,13;0,04;34,63;-1,75;41,4;-598;1;58,72;3,57;5,71;1,57;0,02;0,03;0,12;0;0;0;1;1;0;1
-41;-66,76;142,65;2,67;2,67;0,14;0,15;0,04;34,65;-1,76;38,32;-598;1;62,33;4,43;6,01;4,29;0,02;0,04;0,16;0;0;0;1;1;0;1
-42;-66,87;142,66;2,92;1,71;5,49;0,13;0,04;34,63;-1,72;47,93;-391;1;62,77;8,27;6,89;1,19;0,02;0,05;0,2;0;0;0;1;1;0;1
-43;-66,74;143,33;2;3,28;4,67;0,19;0,06;34,61;-1,74;62,82;-332;1;54,92;7,42;9,35;3,78;0,03;0,05;0,16;0;1;0;1;1;0;0
-45;-66,75;144;2,19;3,12;5,5;0,16;0,04;34,61;-1,8;42,36;-661;1;43,64;7,49;5,95;4,51;0,03;0,02;0,07;0;1;0;1;1;0;1
-46;-66,87;144,1;2,59;1,31;5,89;0,17;0,05;34,59;-1,78;38,87;-561;1;43,42;10,54;4,09;1,16;0,03;0,04;0,14;0;0;0;1;1;0;1
-48;-66,93;144,65;1,59;0,58;5,75;0,21;0,06;34,6;-1,83;73,19;-407;1;40,23;11,89;10,52;5,23;0,03;0,03;0,09;0;1;0;1;1;0;0
-5;-66,32;142,29;3,03;4,93;5,05;0,2;0,1;34,63;-1,61;39,53;-216;1;61,67;0,27;2,63;0,11;0,04;0,02;0,17;0;0;0;1;1;0;1
-50;-66,75;145,27;1,02;5,5;5,49;0,13;0,04;34,64;-1,77;52,4;-596;1;39,8;9,53;4,66;0,23;0,02;0,03;0,1;0;1;0;1;1;0;1
-51;-66,74;145,48;0,95;6,47;5,5;0,2;0,05;34,62;-1,78;49,32;-535;1;40,91;10,66;3,37;0,55;0,03;0,04;0,11;0;1;0;0;1;0;0
-52;-66,55;145,31;1,04;19,26;5,26;0,09;0,03;34,59;-1,67;36,48;-409;1;42,62;6,4;1,12;0,09;0,01;0,03;0,22;0;1;0;0;1;0;0
-53;-66,33;144,66;1,24;6,73;5,36;0,13;0,04;34,61;-1,71;62,77;-420;1;42,45;2,27;3,99;0,17;0,02;0,04;0,18;0;1;0;0;1;0;0
-54;-65,91;144,02;3,17;12,05;5,16;0,15;0,06;34,57;-0,92;31,38;-375;1;46,27;0,41;2,1;2,62;0,02;0,02;0,4;0;1;1;1;1;0;1
-55;-66,33;145,01;1,12;8,85;5,25;0,12;0,04;34,56;-1,68;40,75;-387;1;44,3;3,06;2,2;0,58;0,02;0,03;0,26;0;1;0;1;1;0;1
-56;-66,56;144,67;1,3;16,82;2,34;0,13;0,04;34,65;-1,79;45,94;-582;1;39,22;4,26;3,93;0,38;0,02;0,03;0,1;0;1;0;0;1;0;0
-57;-66,74;145;1,18;5,21;2,42;0,16;0,05;34,65;-1,8;53,42;-646;1;38,62;7,59;7,28;0,68;0,03;0,03;0,09;0;1;0;0;1;0;0
-58;-66,75;144,67;1,28;4,2;2,34;0,18;0,05;34,65;-1,81;79,28;-837;1;34,69;7,08;12,46;0,61;0,03;0,03;0,08;0;1;0;1;1;0;1
-6;-66,32;142,66;1,83;4,69;1,69;0,1;0,08;34,65;-1,74;18,2;-384;1;58,78;0,43;2,05;0,09;0,03;0,02;0,15;0;1;0;1;1;0;0
-60;-66,56;143,93;1,51;7,74;2,05;0,14;0,05;34,65;-1,82;47,04;-799;1;38,88;3,65;7,36;0,94;0,03;0,03;0,09;0;1;0;1;1;0;0
-61;-66,33;142,97;1,15;4,14;5,31;0,13;0,05;34,64;-1,74;52,04;-644;1;49,19;0,67;9,1;0,82;0,02;0,03;0,16;0;1;0;1;1;0;0
-62;-66,15;143,32;1,06;10,88;2,17;0,12;0,04;34,64;-1,76;59,46;-545;1;37,97;0,52;5,25;0,23;0,02;0,02;0,14;0;1;0;1;1;0;0
-63;-65,85;142,98;3,71;20,11;5,24;0,27;0,11;34,61;-1,22;24,73;-423;1;41,04;0,19;1,03;0,56;0,05;0,02;0,44;0;0;0;1;1;0;1
-65;-65,81;143;3,89;21,43;5,23;0,39;0,13;34,61;-0,67;25,78;-777;1;41,24;0,18;1,56;7,69;0,06;0,02;0,33;0;1;0;1;1;0;1
-66;-65,75;143,04;NA;NA;4,48;NA;NA;NA;NA;NA;NA;NA;NA;NA;NA;NA;NA;NA;NA;0;0;0;1;1;0;0
-7;-66,55;142,64;2,12;4,31;1,77;0,18;0,07;34,66;-1,75;15,34;-255;1;65,49;1,46;1,38;6,15;0,03;0,03;0,18;0;0;0;0;0;0;0
-70;-66,42;140,52;2,3;2,63;5,35;0,08;0,03;34,64;-1,49;20,33;-1109;1;67,5;1,56;3,67;5,9;0,01;0,01;0,05;0;1;0;0;1;0;0
-71;-66,39;140,48;2,22;2,24;5,27;0,06;0,02;34,62;-1,36;19,67;-768;1;67,65;1,36;3,1;7,04;0,01;0,01;0,04;0;1;0;1;1;0;1
-72;-66,34;140,48;2,18;2,6;2,34;0,09;0,04;34,58;-1,14;17,49;-407;1;67,61;1,01;2,1;2,74;0,01;0,01;0,11;0;1;0;1;1;0;0
-79;-65,7;140,56;1,83;25,43;4,77;0,34;0,16;34,6;-0,94;3,7;-506;1;66,84;0,09;1,91;5,63;0,06;0,02;0,38;0;1;0;1;1;0;1
-8;-66,56;142,33;3,36;3,2;1,96;0,16;0,06;34,68;-1,85;67,67;-374;1;60,65;1,04;11,68;1,03;0,03;0,03;0,1;0;1;0;1;1;0;1
-81;-65,65;140,44;1,42;28,49;4,93;0,3;0,15;34,62;-0,81;3,75;-1193;1;66,73;0,13;1,29;5,59;0,05;0,02;0,32;0;0;0;1;1;0;0
-84;-65,45;139,37;0,98;28,81;1,16;0,06;0,03;34,62;-0,21;17,56;-395;NA;58,04;0,28;2,92;0,29;0,01;0,01;0,22;0;0;0;1;1;0;0
-86;-65,47;139,35;0,96;28,78;2,13;0,00947;0,03;34,62;-0,2;18,67;-398;NA;57,91;0,27;2,96;0,26;0,01;0,01;0,22;0;1;0;1;1;0;0
-87;-65,49;139,33;0,95;28,75;4,01;0,05;0,03;34,62;-0,19;20,03;-400;NA;57,77;0,27;3,02;0,42;0,01;0,01;0,21;0;1;0;0;1;0;0
-9;-66,55;141,99;3,19;3,31;5,38;0,17;0,05;34,68;-1,85;40,51;-357;1;65,13;0,81;6,85;3,19;0,03;0,03;0,1;0;0;0;1;1;0;1
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/cnidaria_filtered.tsv	Wed Jan 24 15:52:56 2024 +0000
@@ -0,0 +1,64 @@
+station	lat	long	Carbo	Grav	Maxbearing	Maxmagnit	Meancurmag	Meansal	Meantheta	Mud	Prof	Rugosity	Sand	Seaice_prod	Sili	Slope	Standcurmag	Standsal	Standtheta	Acanthogorgiidae	Actiniaria	Ainigmaptilon_edisto	Alcyonacea	Anthozoa	Thouarella_variabilis	Thouarella_vulpicauda
+1	1	-65,99	142,33	5,51	12,59	2,03	0,16	0,07	34,6	-1,47	29,8	-233	1	56,16	0,11	3,94	0,05	0,03	0,03	0,24	0	1	0	0	1	0	0
+2	10	-66,33	141,3	3,17	5,31	5,2	0,18	0,08	34,61	-1,35	21,5	-215	1	67,39	0,17	5,8	0,24	0,03	0,02	0,28	0	1	0	1	1	0	0
+3	11	-66,56	141,29	3,1	3,28	4,93	0,2	0,08	34,65	-1,73	34,89	-192	1	73,13	0,87	4,48	0,71	0,03	0,04	0,24	0	0	0	1	1	0	0
+4	12	-66,55	140,82	2,78	3,08	3,74	0,34	0,1	34,59	-1,19	25,83	-217	1	68,37	2,62	4,05	2,57	0,06	0,02	0,24	0	1	0	1	1	1	0
+5	13	-66,15	140,65	2,06	7,62	5,36	0,21	0,09	34,56	-1,04	13,18	-217	1	71,68	0,07	2,89	0,37	0,04	0,02	0,26	0	1	0	0	1	0	0
+6	14	-66,33	140,67	2,96	3,12	2,42	0,16	0,08	34,54	-1,02	12,15	-171	1	73,16	0,78	1,17	0,08	0,03	0,01	0,22	0	1	0	0	1	0	0
+7	15	-66,38	139,8	1,06	1,65	1,87	0,14	0,05	34,64	-1,53	69,08	-855	1	48,44	1,43	13,55	2,94	0,03	0,01	0,06	0	1	0	1	1	0	0
+8	16	-66,34	139,99	1,34	2,78	1,61	0,15	0,05	34,6	-1,12	41,06	-538	1	54,72	1,23	5,97	3,7	0,03	0,00839	0,08	0	1	0	0	1	0	0
+9	17	-66,17	139,96	1,71	8,13	4,39	0,31	0,12	34,54	-0,96	17,16	-151	1	61,42	0,54	1,99	0,25	0,05	0,02	0,3	0	1	0	1	1	1	0
+10	18	-66,16	139,65	1,49	7,75	2,24	0,15	0,06	34,59	-1,01	32,71	-432	1	51,4	0,56	3,35	0,42	0,03	0,01	0,26	0	1	0	1	1	0	1
+11	19	-66,15	139,31	1,18	8,58	5,7	0,12	0,04	34,61	-1,36	47,4	-674	1	46,41	0,34	9,92	0,31	0,02	0,00722	0,09	0	1	0	0	1	0	0
+12	2	-65,99	141,32	3,3	14,21	5,01	0,16	0,07	34,6	-1,26	14,05	-235	1	67,07	-0,01	2,09	0,13	0,03	0,03	0,32	0	1	1	1	1	0	1
+13	20	-66	139,99	1,95	20,59	4,98	0,19	0,09	34,56	-1,05	13,25	-192	1	63,46	0,27	1,92	0,21	0,03	0,03	0,26	0	1	0	0	1	0	0
+14	21	-66	139,64	2,26	18,21	2,85	0,16	0,07	34,58	-1,04	44,81	-277	1	57,14	0,76	5,88	1,66	0,03	0,01	0,26	0	1	0	0	1	0	0
+15	22	-66	139,31	1,39	19,2	4,87	0,1	0,04	34,6	-1,05	37,84	-476	1	49,4	0,65	7,09	0,25	0,02	0,00884	0,15	0	1	0	1	1	0	0
+16	26	-66,52	140,02	1,51	1,47	4,4	0,12	0,05	34,6	-1,11	49,11	-247	1	49,52	2,38	10,29	3,16	0,02	0,00984	0,16	0	1	0	0	1	0	0
+17	27	-66,02	142,74	2,61	11,58	5,42	0,13	0,05	34,64	-1,73	25,07	-440	1	46,97	0,24	2,19	0,23	0,02	0,03	0,17	0	1	0	1	1	0	1
+18	28	-65,99	143,02	2,15	11,5	5,37	0,14	0,05	34,64	-1,77	39,29	-467	1	38,66	0,24	2,07	0,32	0,02	0,03	0,12	0	1	0	1	1	0	1
+19	29	-66,02	143,29	1,77	9,98	5,41	0,14	0,05	34,64	-1,78	62,2	-470	1	38,73	0,33	4,81	0,19	0,02	0,03	0,1	0	1	0	1	1	0	1
+20	3	-65,99	141,98	5,27	14,32	5,31	0,01	0,06	34,6	-1,4	22,84	-245	1	61,04	-0,00886	3,93	0,15	0,03	0,03	0,25	0	1	0	0	1	0	0
+21	30	-66	143,68	2,06	9,47	5,42	0,15	0,06	34,61	-1,71	54,73	-429	1	41,27	0,39	1,03	0,22	0,03	0,03	0,19	0	1	0	0	1	0	0
+22	31	-66,55	144,99	1,05	19,55	5,28	0,12	0,03	34,62	-1,73	35,57	-437	1	39,47	5,14	1,77	0,45	0,02	0,03	0,16	0	0	0	1	1	0	1
+23	34	-66,33	144,34	1,26	6,31	4,92	0,13	0,04	34,63	-1,77	44,96	-455	1	40,49	1,87	2,96	0,39	0,02	0,03	0,12	0	1	0	1	1	0	1
+24	35	-66,33	144,01	1,2	4,9	2,11	0,12	0,04	34,64	-1,78	49,09	-511	1	39,41	1,54	4,15	0,32	0,02	0,02	0,1	0	1	0	1	1	0	0
+25	36	-66,32	143,65	1,12	4,29	2,16	0,12	0,04	34,64	-1,79	53,85	-565	1	38,83	1,26	8,68	0,38	0,02	0,02	0,13	0	1	0	1	1	0	1
+26	37	-66,55	143,31	1,34	4,32	2,02	0,12	0,04	34,66	-1,82	78,15	-820	1	47,92	2,76	13,57	0,26	0,02	0,03	0,11	0	1	0	0	1	0	0
+27	38	-66,33	143,31	0,82	3,84	2,2	0,1	0,04	34,65	-1,8	84,13	-703	1	41,01	0,98	16,47	0,25	0,02	0,03	0,12	0	1	0	1	1	1	0
+28	39	-66,56	143,02	1,67	4,11	1,5	0,13	0,05	34,65	-1,8	47,63	-862	1	56,71	2,22	7,3	0,18	0,02	0,02	0,1	0	1	0	0	1	0	0
+29	40	-66,65	142,98	1,94	3,93	5,42	0,13	0,04	34,63	-1,75	41,4	-598	1	58,72	3,57	5,71	1,57	0,02	0,03	0,12	0	0	0	1	1	0	1
+30	41	-66,76	142,65	2,67	2,67	0,14	0,15	0,04	34,65	-1,76	38,32	-598	1	62,33	4,43	6,01	4,29	0,02	0,04	0,16	0	0	0	1	1	0	1
+31	42	-66,87	142,66	2,92	1,71	5,49	0,13	0,04	34,63	-1,72	47,93	-391	1	62,77	8,27	6,89	1,19	0,02	0,05	0,2	0	0	0	1	1	0	1
+32	43	-66,74	143,33	2	3,28	4,67	0,19	0,06	34,61	-1,74	62,82	-332	1	54,92	7,42	9,35	3,78	0,03	0,05	0,16	0	1	0	1	1	0	0
+33	45	-66,75	144	2,19	3,12	5,5	0,16	0,04	34,61	-1,8	42,36	-661	1	43,64	7,49	5,95	4,51	0,03	0,02	0,07	0	1	0	1	1	0	1
+34	46	-66,87	144,1	2,59	1,31	5,89	0,17	0,05	34,59	-1,78	38,87	-561	1	43,42	10,54	4,09	1,16	0,03	0,04	0,14	0	0	0	1	1	0	1
+35	48	-66,93	144,65	1,59	0,58	5,75	0,21	0,06	34,6	-1,83	73,19	-407	1	40,23	11,89	10,52	5,23	0,03	0,03	0,09	0	1	0	1	1	0	0
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Binary file test-data/ecoregions.png has changed
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/points_clus.tsv	Wed Jan 24 15:52:56 2024 +0000
@@ -0,0 +1,155824 @@
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--- a/test-data/points_clus.txt	Wed Oct 18 09:58:51 2023 +0000
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,155824 +0,0 @@
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