code edits

shortened the code for some helper functions
boldsystems-central · Oct 2, 2024 · 8b1dc3d · 8b1dc3d
1 parent 393da1d
commit 8b1dc3d
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Showing 3 changed files with 28 additions and 210 deletions.
diff --git a/R/helper.biodiversity_profile_fun.R b/R/helper.biodiversity_profile_fun.R
@@ -32,13 +32,12 @@ preston_profile <- function (df,
       dplyr::mutate(rownum=as.numeric(rownum))%>%
       dplyr::mutate(Octaves=as.factor(2^rownum))
 
-
     preston.plot=pres_res%>%
       ggplot(aes(x=Octaves,
                  y=observed))+
       geom_bar(stat = "identity",
                position = 'dodge',
-               fill="darkcyan",
+               fill="lightseagreen",
                col="black",
                width = 1) +
       geom_point(data = pres_res,
@@ -47,7 +46,7 @@ preston_profile <- function (df,
                      group=1),
                  pch=21,
                  color = "black",
-                 fill="orangered",
+                 fill="sienna1",
                  size=4) +
       geom_line(data = pres_res,
                 aes(x = Octaves,
@@ -64,7 +63,6 @@ preston_profile <- function (df,
       ylab(y_label)+
       ggtitle("Preston plot")
 
-
     preston_results$preston.plot = preston.plot
 
     preston_results$preston.res = preston.res
@@ -78,7 +76,6 @@ shannon_div_profile<-function(df)
 
   {
 
-
   # Shannon diversity
 
   shannon_div=vegan::diversity(df)%>%
@@ -87,7 +84,6 @@ shannon_div_profile<-function(df)
 
   return(shannon_div)
 
-
 }
 
 # Function: Beta diversity profile
@@ -105,8 +101,6 @@ beta_div_profile<-function(df,
                          runs=10,
                          comp = T)
 
-
-
   beta.total = beta.bin.div$Btotal
 
   beta.replace = beta.bin.div$Brepl
@@ -123,5 +117,4 @@ beta_div_profile<-function(df,
 
   return(beta_div_res)
 
-
 }
diff --git a/R/helper.column_presets.R b/R/helper.column_presets.R
@@ -8,10 +8,6 @@ presets<-function(col_groups)
 {
   bold_fields<-bold.fields.info()
 
-  bold_fields[which(bold_fields$field=='country/ocean'),]<-"country.ocean"
-
-  bold_fields[which(bold_fields$field=='province/state'),]<-"province.state"
-
   common_ids<-c("processid","sampleid")
 
   switch(col_groups,
@@ -94,7 +90,6 @@ presets<-function(col_groups)
            },
          "other_meta_data"=
            {
-
              preset<-bold_fields%>%
                dplyr::select(field)%>%
                dplyr::filter(field %in% c(common_ids,
@@ -105,10 +100,8 @@ presets<-function(col_groups)
                                           "tissue_type",
                                           "sampling_protocol"))
            },
-
          "bold_analyze_align_fields" =
            {
-
              preset<-bold_fields%>%
                dplyr::select(field)%>%
                dplyr::filter(field %in% c(common_ids,
@@ -117,31 +110,28 @@ presets<-function(col_groups)
            },
          "bold_analyze_tree_fields" =
            {
-
              preset<-data.frame(field = c("processid",
                                           "aligned_seq",
                                           "msa.seq.name"))
-           },
+             },
          "bol_analyze_map_fields" =
            {
-
              preset<-bold_fields%>%
                dplyr::select(field)%>%
                dplyr::filter(field %in% c(common_ids,
                                           "bin_uri",
                                           "marker_code",
                                           "nuc"))
-           }
-
-  )
+             }
+)
 
   return(preset)
-
 }
 # The function to check and return the data with the necessary columns
 
 check_and_return_preset_df<-function (df,
-                                      category = c("check","check_return"),
+                                      category = c("check",
+                                                   "check_return"),
                                       preset)
 {
 
@@ -150,25 +140,17 @@ check_and_return_preset_df<-function (df,
   preset_col = preset%>%
     dplyr::pull(field)
 
-
   switch (category,
 
-
           "check" =
 
             {
-
-              if(!any(preset_col %in% names(df)))
-              {
-                stop("Please re-check if column names match with the available field names for BCDM dataframe and that minimum field requirement for the analysis is satisfied. Please read the details section of 'bold.export' help for more information on presets.")
-
-              }
-            },
+              if(!any(preset_col %in% names(df))) stop("Please re-check if column names match with the available field names for BCDM dataframe and that minimum field requirement for the analysis is satisfied. Please read the details section of 'bold.export' help for more information on presets.")
+              },
 
           "check_return" =
 
             {
-
               if(!any(preset_col %in% names(df)))
               {
                 stop("Please re-check if column names match with the available field names for the BCDM dataframe and that minimum field requirement for the analysis is satisfied. Please read the details section of 'bold.export' help for more information on presets.")
@@ -177,10 +159,8 @@ check_and_return_preset_df<-function (df,
               {
                 preset_df = df%>%
                   dplyr::select(all_of(preset_col))
-
               }
               return(preset_df)
             }
-  )
-
+          )
 }