Evalutuation of the models I saved

evaluation.jl

+using RidePooling
+RP = RidePooling
+using DataFrames
+using Measurements
+import Base.Filesystem
+FS = Base.Filesystem
+
+
+path = "/project.dcf/poss/datasets/planned_pickup/drive_and_wait/anywt1_anydt01/"
+model_path = path * "/models/"
+
+# Values I want to calculate for every model
+req_quantitys_mean = [
+	
+	:relative_delay,
+	#:delay,
+	#:relative_waiting_time,
+	#:waiting_time,
+	#:served,
+	#:requested_distance,
+	#:requested_time,
+	#:total_time,
+	#:travelling_time,
+    #:resubmitted_served_percentage,
+	#:dt_earliest_served,
+    #:dt_earliest,
+	#:relative_dt_earliest
+
+]
+
+req_quantitys_sum = [
+	:count_req,
+	#:resubmitted_all,
+	#:resubmitted_served,
+]
+
+bus_quantitys = [
+	:cooldown_time,
+]
+
+model_quantitys = [
+	:driven_distance,
+	#:efficiency,
+	#:quality
+]
+
+results = DataFrame()
+results[:index] = Int[]
+results[:dt_earliest_pickup] = Float64[]
+results[:weight] = Float64[]
+results[:resubmission_time_factor] = Float64[]
+results[:ν] = Float64[]
+results[:request_type] = Any[]
+for quan in req_quantitys_mean
+	results[quan] = Measurement[]
+end
+
+for quan in req_quantitys_sum
+	results[quan] = Float64[]
+end
+
+for quan in bus_quantitys
+	results[quan] = Measurement[]
+end
+
+for quan in model_quantitys
+	results[quan] = Measurement[]
+end
+
+
+
+filenames = readdir(model_path, join=true)
+
+for model_nr in filenames
+	model=loadmodel(model_nr)
+	row = Dict()
+	
+	
+	row[:index] = parse(Int, FS.splitext(model_nr)[1])
+	row[:dt_earliest_pickup] = model.random_gens[model.request_type][2]
+	row[:idle_wight] = model.cost_idle_weight
+	row[:ν] = model.ν
+	row[:to] = model.t0
+	row[:request_type] = model.request_type
+
+	for quan in req_quantitys_mean
+		row[quan] = ev.quantity(quan, model_now)
+	end
+	for quan in req_quantitys_sum
+		row[quan] = ev.sum(quan, model)
+	end
+	for quan in bus_quantitys
+		row[quan] = ev.quantity(quan, model.agents, model)
+	end
+	for quan in model_quantitys
+		f = @eval (ev.$quan)
+		row[quan] = f(model)
+	end
+	using Serialization
+	push!(results, row)
+end
+
+using Serialization
+serialize(path*"results.jls", df)
+