i #229 Adds temporal_cum_sum checks

When the weight scheme is used in the wrong function
combination, the code now throws an error advising
the user the correct way to combine them.

In the future, a saner function that only allow for
the correct weight scheme combinations should be
added.

Signed-off-by: Carlos Paradis <carlosviansi@gmail.com>

R/graph.R

@@ -151,6 +151,12 @@ model_directed_graph <- function(edgelist,is_bipartite,color,aggregate_duplicate
 #' @export
 bipartite_graph_projection <- function(graph,mode,weight_scheme_function = NULL){
 
+  # If weight scheme is cum_temporal, then lag must be "all_lag":
+  if(identical(weight_scheme_function,kaiaulu::weight_scheme_cum_temporal)){
+    stop("The weight scheme for cumulative temporal should only be applied to the temporal_graph_projection
+         and lag = all_lag. See ?weight_scheme_cum_temporal.")
+  }
+
   get_combinations <- function(edgelist){
     dt <- edgelist
 
@@ -260,12 +266,23 @@ bipartite_graph_projection <- function(graph,mode,weight_scheme_function = NULL)
 #' doi: 10.1109/ICSE.2015.73.
 temporal_graph_projection <- function(graph,mode,weight_scheme_function = NULL,timestamp_column,lag = c("one_lag","all_lag")){
 
+  # Check if the user specified a lag that doesn't exist
+  lag <- match.arg(lag)
+
+
+
+  # If weight scheme is cum_temporal, then lag must be "all_lag":
+  if(identical(weight_scheme_function,kaiaulu::weight_scheme_cum_temporal) &
+     lag != "all_lag"){
+    stop("The weight scheme for cumulative temporal should only be applied to all_lag. See ?weight_scheme_cum_temporal.")
+  }
+
   # We define the way the pair-wise edges are computed in two
   # separate functions: one_lag_combinations and
   # all_lag combinations.
 
   # The remainder of this function is documented
-  # refering to developers and files, however the
+  # referring to developers and files, however the
   # function can be applied to anything else
   # (e.g. threads and authors, files and commits, etc)
 
@@ -403,7 +420,7 @@ temporal_graph_projection <- function(graph,mode,weight_scheme_function = NULL,t
              new = c("to_edgeid","from_edgeid"))
 
     # Because the function will not generate the final projection, but
-    # rather the intemediate step, showcasing what nodes were deleted, and
+    # rather the intermediate step, showcasing what nodes were deleted, and
     # what weights the pairs of edges had pointing to the deleted node,
     # we use the edge ID to add the information back. Without the edge id,
     # we would be unable to determine which temporal edge the information
@@ -433,8 +450,7 @@ temporal_graph_projection <- function(graph,mode,weight_scheme_function = NULL,t
 
 
 
-  # Check if the user specified a lag that doesn't exist
-  lag <- match.arg(lag)
+
 
   # Copy the graph, so column renames by reference doesn't overwrite parameter objects
   graph <- copy(graph)
@@ -581,7 +597,7 @@ weight_scheme_count_deleted_nodes <- function(projected_graph){
 #' Weight Cumulative Temporal Projection Scheme
 #'
 #' This weight scheme sums the deleted node adjacent edges when re-wired
-#' in the projection graph that *occur before* the temporal edge and the
+#' in the projection graph that *occur before* the temporal edge. See the
 #' in line documentation for details.
 #'
 #' Note this function assumes the rows of `temporally_ordered_projected_graph`