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Put tests in separate files #196

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Oct 25, 2023
Merged

Put tests in separate files #196

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2434eae
Put tests in separated files
clizbe Oct 25, 2023
a283454
Renamed tests, files, and folders for consistency
clizbe Oct 25, 2023
81cf4a1
Rename tiny folder to Tiny
clizbe Oct 25, 2023
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2 changes: 1 addition & 1 deletion src/TulipaEnergyModel.jl
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Expand Up @@ -7,7 +7,7 @@ using Graphs
using HiGHS
using JuMP

include("input_tables.jl")
include("input-tables.jl")
include("io.jl")
include("model.jl")
include("time-resolution.jl")
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0 src/input_tables.jl → src/input-tables.jl
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0 test/inputs/tiny/assets-data.csv → test/inputs/Tiny/assets-data.csv
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0 test/inputs/tiny/assets-profiles.csv → test/inputs/Tiny/assets-profiles.csv
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0 test/inputs/tiny/bad-assets-data.csv → test/inputs/Tiny/bad-assets-data.csv
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0 test/inputs/tiny/flows-data.csv → test/inputs/Tiny/flows-data.csv
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0 test/inputs/tiny/flows-profiles.csv → test/inputs/Tiny/flows-profiles.csv
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0 test/inputs/tiny/rep-periods-data.csv → test/inputs/Tiny/rep-periods-data.csv
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114 changes: 5 additions & 109 deletions test/runtests.jl
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Expand Up @@ -8,116 +8,12 @@ using Test
const INPUT_FOLDER = joinpath(@__DIR__, "inputs")
const OUTPUT_FOLDER = joinpath(@__DIR__, "outputs")

@testset "TulipaEnergyModel.jl" begin
dir = joinpath(INPUT_FOLDER, "Norse")
parameters, sets = create_parameters_and_sets_from_file(dir)
graph = create_graph(joinpath(dir, "assets-data.csv"), joinpath(dir, "flows-data.csv"))
model = create_model(graph, parameters, sets)
solution = solve_model(model)
@test solution.objective_value ≈ 183696778.98322 atol = 1e-5
save_solution_to_file(
OUTPUT_FOLDER,
sets.assets_investment,
solution.assets_investment,
parameters.assets_unit_capacity,
)
end

@testset "Write lp file" begin
dir = joinpath(INPUT_FOLDER, "tiny")
parameters, sets = create_parameters_and_sets_from_file(dir)
graph = create_graph(joinpath(dir, "assets-data.csv"), joinpath(dir, "flows-data.csv"))
model = create_model(graph, parameters, sets; write_lp_file = true)
solution = solve_model(model)
@test solution.objective_value ≈ 269238.43825 atol = 1e-5
save_solution_to_file(
OUTPUT_FOLDER,
sets.assets_investment,
solution.assets_investment,
parameters.assets_unit_capacity,
)
end

@testset "Infeasible run" begin
dir = joinpath(INPUT_FOLDER, "tiny")
parameters, sets = create_parameters_and_sets_from_file(dir)
parameters.peak_demand["demand"] = -1 # make it infeasible
graph = create_graph(joinpath(dir, "assets-data.csv"), joinpath(dir, "flows-data.csv"))
model = create_model(graph, parameters, sets)
solution = solve_model(model)
@test solution === nothing
end

@testset "Tiny graph" begin
@testset "Graph structure is correct" begin
dir = joinpath(INPUT_FOLDER, "tiny")
graph =
create_graph(joinpath(dir, "assets-data.csv"), joinpath(dir, "flows-data.csv"))

@test Graphs.nv(graph) == 6
@test Graphs.ne(graph) == 5
@test collect(Graphs.edges(graph)) ==
[Graphs.Edge(e) for e in [(1, 6), (2, 6), (3, 6), (4, 6), (5, 6)]]
end
end

@testset "Input validation" begin
@testset "Make sure that input validation fails for bad files" begin
dir = joinpath(INPUT_FOLDER, "tiny")
@test_throws ArgumentError TulipaEnergyModel.read_csv_with_schema(
joinpath(dir, "bad-assets-data.csv"),
TulipaEnergyModel.AssetData,
)
end
end

@testset "Time resolution" begin
@testset "resolution_matrix" begin
rp_periods = [1:4, 5:8, 9:12]
time_steps = [1:4, 5:8, 9:12]
expected = [
1.0 0.0 0.0
0.0 1.0 0.0
0.0 0.0 1.0
]
@test resolution_matrix(rp_periods, time_steps) == expected

time_steps = [1:3, 4:6, 7:9, 10:12]
expected = [
1.0 1/3 0.0 0.0
0.0 2/3 2/3 0.0
0.0 0.0 1/3 1.0
]
@test resolution_matrix(rp_periods, time_steps) == expected

time_steps = [1:6, 7:9, 10:10, 11:11, 12:12]
expected = [
2/3 0.0 0.0 0.0 0.0
1/3 2/3 0.0 0.0 0.0
0.0 1/3 1.0 1.0 1.0
]
@test resolution_matrix(rp_periods, time_steps) == expected
end

@testset "compute_rp_periods" begin
# regular
time_steps1 = [1:4, 5:8, 9:12] # every 4 hours
time_steps2 = [1:3, 4:6, 7:9, 10:12] # every 3 hours
time_steps3 = [i:i for i = 1:12] # hourly

@test compute_rp_periods([time_steps1, time_steps2]) == time_steps1
@test compute_rp_periods([time_steps1, time_steps2, time_steps3]) == time_steps1
@test compute_rp_periods([time_steps2, time_steps3]) == time_steps2

# Irregular
time_steps4 = [1:6, 7:9, 10:11, 12:12]
time_steps5 = [1:2, 3:4, 5:12]
@test compute_rp_periods([time_steps1, time_steps4]) == [1:6, 7:9, 10:12]
@test compute_rp_periods([time_steps1, time_steps5]) == [1:4, 5:12]
@test compute_rp_periods([time_steps4, time_steps5]) == [1:6, 7:12]
end
end
# Add run all test files in test folder
include("test-io.jl")
include("test-time-resolution.jl")
include("test-case-studies.jl")

# Other general tests that don't need their own file
@testset "Ensuring benchmark loads" begin
include(joinpath(@__DIR__, "..", "benchmark", "benchmarks.jl"))
@test SUITE !== nothing
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39 changes: 39 additions & 0 deletions test/test-case-studies.jl
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@@ -0,0 +1,39 @@
@testset "Norse Case Study" begin
dir = joinpath(INPUT_FOLDER, "Norse")
parameters, sets = create_parameters_and_sets_from_file(dir)
graph = create_graph(joinpath(dir, "assets-data.csv"), joinpath(dir, "flows-data.csv"))
model = create_model(graph, parameters, sets)
solution = solve_model(model)
@test solution.objective_value ≈ 183696778.98322 atol = 1e-5
save_solution_to_file(
OUTPUT_FOLDER,
sets.assets_investment,
solution.assets_investment,
parameters.assets_unit_capacity,
)
end

@testset "Tiny Case Study" begin
dir = joinpath(INPUT_FOLDER, "Tiny")
parameters, sets = create_parameters_and_sets_from_file(dir)
graph = create_graph(joinpath(dir, "assets-data.csv"), joinpath(dir, "flows-data.csv"))
model = create_model(graph, parameters, sets; write_lp_file = true)
solution = solve_model(model)
@test solution.objective_value ≈ 269238.43825 atol = 1e-5
save_solution_to_file(
OUTPUT_FOLDER,
sets.assets_investment,
solution.assets_investment,
parameters.assets_unit_capacity,
)
end

@testset "Infeasible Case Study" begin
dir = joinpath(INPUT_FOLDER, "Tiny")
parameters, sets = create_parameters_and_sets_from_file(dir)
parameters.peak_demand["demand"] = -1 # make it infeasible
graph = create_graph(joinpath(dir, "assets-data.csv"), joinpath(dir, "flows-data.csv"))
model = create_model(graph, parameters, sets)
solution = solve_model(model)
@test solution === nothing
end
22 changes: 22 additions & 0 deletions test/test-io.jl
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@@ -0,0 +1,22 @@
@testset "Input validation" begin
@testset "Make sure that input validation fails for bad files" begin
dir = joinpath(INPUT_FOLDER, "Tiny")
@test_throws ArgumentError TulipaEnergyModel.read_csv_with_schema(
joinpath(dir, "bad-assets-data.csv"),
TulipaEnergyModel.AssetData,
)
end
end

@testset "Graph structure" begin
@testset "Graph structure is correct" begin
dir = joinpath(INPUT_FOLDER, "Tiny")
graph =
create_graph(joinpath(dir, "assets-data.csv"), joinpath(dir, "flows-data.csv"))

@test Graphs.nv(graph) == 6
@test Graphs.ne(graph) == 5
@test collect(Graphs.edges(graph)) ==
[Graphs.Edge(e) for e in [(1, 6), (2, 6), (3, 6), (4, 6), (5, 6)]]
end
end
46 changes: 46 additions & 0 deletions test/test-time-resolution.jl
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@testset "Time resolution" begin
@testset "resolution_matrix" begin
rp_periods = [1:4, 5:8, 9:12]
time_steps = [1:4, 5:8, 9:12]
expected = [
1.0 0.0 0.0
0.0 1.0 0.0
0.0 0.0 1.0
]
@test resolution_matrix(rp_periods, time_steps) == expected

time_steps = [1:3, 4:6, 7:9, 10:12]
expected = [
1.0 1/3 0.0 0.0
0.0 2/3 2/3 0.0
0.0 0.0 1/3 1.0
]
@test resolution_matrix(rp_periods, time_steps) == expected

time_steps = [1:6, 7:9, 10:10, 11:11, 12:12]
expected = [
2/3 0.0 0.0 0.0 0.0
1/3 2/3 0.0 0.0 0.0
0.0 1/3 1.0 1.0 1.0
]
@test resolution_matrix(rp_periods, time_steps) == expected
end

@testset "compute_rp_periods" begin
# regular
time_steps1 = [1:4, 5:8, 9:12] # every 4 hours
time_steps2 = [1:3, 4:6, 7:9, 10:12] # every 3 hours
time_steps3 = [i:i for i ∈ 1:12] # hourly

@test compute_rp_periods([time_steps1, time_steps2]) == time_steps1
@test compute_rp_periods([time_steps1, time_steps2, time_steps3]) == time_steps1
@test compute_rp_periods([time_steps2, time_steps3]) == time_steps2

# Irregular
time_steps4 = [1:6, 7:9, 10:11, 12:12]
time_steps5 = [1:2, 3:4, 5:12]
@test compute_rp_periods([time_steps1, time_steps4]) == [1:6, 7:9, 10:12]
@test compute_rp_periods([time_steps1, time_steps5]) == [1:4, 5:12]
@test compute_rp_periods([time_steps4, time_steps5]) == [1:6, 7:12]
end
end
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