test issue is solwed, empty list is given as defoult to taken_courses…

…; opt_configuration temp files are removed

examples/Notebooks/Opt_Configurations.csv

@@ -1,4 +1,4 @@
-Term Count,6,
+Term Count,8,
 Min Credit,1,
 Max Credit,19,
 Objective Order,Balance;Toxicity;Prereq,

src/DataHandler.jl

@@ -95,7 +95,7 @@ function read_csv(file_path::AbstractString)
             course_count += 1
             read_line = csv_line_reader(readline(csv_file), ',')
         end
-        df_courses = CSV.File(file_path, header=courses_header, limit=course_count-1) |> DataFrame
+        df_courses = CSV.File(file_path, header=courses_header, limit=course_count-1, delim=',') |> DataFrame
         if nrow(df_courses) != nrow(unique(df_courses, Symbol("Course ID")))
             println("All courses must have a unique Course ID")
             return false
@@ -120,7 +120,7 @@ function read_csv(file_path::AbstractString)
             end     
         end
         if additional_course_count > 1
-            df_additional_courses = CSV.File(file_path, header=additional_course_start, limit=additional_course_count-1) |> DataFrame
+            df_additional_courses = CSV.File(file_path, header=additional_course_start, limit=additional_course_count-1, delim=',') |> DataFrame
             df_all_courses = vcat(df_courses,df_additional_courses)
         else
             df_all_courses = df_courses
@@ -135,7 +135,7 @@ function read_csv(file_path::AbstractString)
                 read_line = csv_line_reader(readline(csv_file), ',')
             end  
             if learning_outcomes_count > 1
-                df_course_learning_outcomes = CSV.File(file_path, header=learning_outcomes_start, limit=learning_outcomes_count-1) |> DataFrame
+                df_course_learning_outcomes = CSV.File(file_path, header=learning_outcomes_start, limit=learning_outcomes_count-1, delim=',') |> DataFrame
             end
         end    
         course_learning_outcomes = Dict{Int, Array{LearningOutcome}}()
@@ -155,7 +155,7 @@ function read_csv(file_path::AbstractString)
                 read_line = csv_line_reader(readline(csv_file), ',')
             end            
             if learning_outcomes_count > 1
-                df_curric_learning_outcomes = CSV.File(file_path, header=curric_learning_outcomes_start, limit=curric_learning_outcomes_count-1) |> DataFrame
+                df_curric_learning_outcomes = CSV.File(file_path, header=curric_learning_outcomes_start, limit=curric_learning_outcomes_count-1, delim=',') |> DataFrame
             end
         end  
 
@@ -588,7 +588,7 @@ function read_Opt_Config(file_path)
                 course_count += 1
                 read_line = csv_line_reader(readline(csv_file), ',')
             end
-            df_fixedCourses = CSV.File(file_path, header=header, limit=course_count) |> DataFrame
+            df_fixedCourses = CSV.File(file_path, header=header, limit=course_count, delim=',') |> DataFrame
             header += course_count+1
             for row in DataFrames.eachrow(df_fixedCourses)
                 fixedCourses[row[Symbol("Course ID")]] = row[Symbol("Term")]
@@ -611,7 +611,7 @@ function read_Opt_Config(file_path)
                 consecutivePairCount += 1
                 read_line = csv_line_reader(readline(csv_file), ',')
             end
-            df_consecutivePair = CSV.File(file_path, header=header, limit=consecutivePairCount) |> DataFrame
+            df_consecutivePair = CSV.File(file_path, header=header, limit=consecutivePairCount, delim=',') |> DataFrame
             header += consecutivePairCount+1
             for row in DataFrames.eachrow(df_consecutivePair)
                 consequtiveCourses[row[Symbol("Prior Course ID")]] = row[Symbol("Next Course ID")]
@@ -634,7 +634,7 @@ function read_Opt_Config(file_path)
                 termRangeCount += 1
                 read_line = csv_line_reader(readline(csv_file), ',')
             end
-            df_termRange = CSV.File(file_path, header=header, limit=termRangeCount) |> DataFrame
+            df_termRange = CSV.File(file_path, header=header, limit=termRangeCount, delim=',') |> DataFrame
             header += termRangeCount+1
             for row in DataFrames.eachrow(df_termRange)
                 termRange[row[Symbol("Course Id")]] = (row[Symbol("Min Term")], row[Symbol("Max Term")])
@@ -661,12 +661,23 @@ function read_Opt_Config(file_path)
                 diffMaxCount += 1
                 read_line = csv_line_reader(readline(csv_file), ',')
             end
-            df_diffMax = CSV.File(file_path, header=header, limit=diffMaxCount) |> DataFrame
+            df_diffMax = CSV.File(file_path, header=header, limit=diffMaxCount, delim=',') |> DataFrame
             header += diffMaxCount+1
             for row in DataFrames.eachrow(df_diffMax)
                 diffMax[row[Symbol("Term")]] = row[Symbol("Max Credit")]
             end
+            # If there is a term without max credit, assign default max credit hours
+            for term_id in 1:termCount 
+                if !(term_id in keys(diffMax))
+                    diffMax[term_id] = max_credits_per_term
+                end
+            end
         end
     end
+    # Current file is the temp file created by remove_empty_lines(), remove the file.
+    if file_path[end-8:end] == "_temp.csv"
+        GC.gc()
+        rm(file_path)
+    end
     return consequtiveCourses, fixedCourses, termRange, termCount, min_credits_per_term, max_credits_per_term, obj_order, diffMax
 end

src/Optimization.jl

@@ -123,7 +123,10 @@ function optimize_plan(config_file, curric_degree_file, toxic_score_file= "")
     c_count = length(curric.courses)
     # Create a map from course ID in curriculum to vertex ID of course in the curriculum graph.
     vertex_map = Dict{Int,Int}(c.id => c.vertex_id[curric.id] for c in courses)
-    taken_course_ids = [c.id for c in input[2]]
+    taken_course_ids = []
+    if isa(input, Tuple)
+        taken_course_ids = [c.id for c in input[2]]
+    end
     credit = [c.credit_hours for c in curric.courses]
     # The mask vector is used to determine the term that a course is in, via dot product with a row of the x matrix
     mask = [i for i in 1:term_count]

test/DataHandler.jl

@@ -285,8 +285,8 @@ curric1 = Curriculum("Underwater Basket Weaving", [A,B,C,D,E,F], institution="AC
 # write curriculum to secondary storage
 @test write_csv(curric1, "./UBW-curric.csv") == true
 # read from same location
-# curric2 = read_csv("./UBW-curric.csv") 
-# @test string(curric1) == string(curric2)  # read/write invariance test
+curric2 = read_csv("./UBW-curric.csv") 
+@test string(curric1) == string(curric2)  # read/write invariance test
 rm("./UBW-curric.csv")
 
 terms = Array{Term}(undef, 3)

test/UBW_curric.csv

@@ -0,0 +1,13 @@
+Curriculum,Underwater Basket Weaving,,,,,,,,,
+Institution,ACME State University,,,,,,,,,
+Degree Type,BS,,,,,,,,,
+System Type,semester,,,,,,,,,
+CIP,445786,,,,,,,,,
+Courses,,,,,,,,,,
+"Course ID","Course Name",Prefix,Number,Prerequisites,Corequisites,Strict-Corequisites,Credit Hours,Institution,Canonical Name
+300052638,"Basket Materials & Decoration","BW","214","4037212392",,,3,"ACME State University","Basket Materials",
+1050322132,"Introduction to Baskets","BW","101",,,,3,"ACME State University","Baskets I",
+1888571219,"Swimming","PE","115",,,,3,"ACME State University","Physical Education",
+2012165139,"Advanced Basketry","CS","300","3989163861",,,3,"ACME State University","Baskets II",
+3989163861,"Basic Basket Forms","BW","111","1050322132;1888571219","4037212392",,3,"ACME State University","Baskets I",
+4037212392,"Basic Basket Forms Lab","BW","111L",,,,1,"ACME State University","Baskets I Laboratory",