Kirill
e48d4bbe88
- Introduced a new benchmark save script to create a stress test scenario with extreme values for simulation performance. - Added a full UI benchmark script to measure frame rates and performance metrics during UI interactions. - Implemented tests for coarse generations to ensure population transitions are handled correctly. - Created tests for extra parameters to validate the loading and application of configuration settings. - Developed simulation optimization tests to verify the efficiency of population drift and rounding mechanisms. - Added split optimization tests to ensure accurate allocation and rounding behavior in population management. - Included startup parameter tests to confirm the correct initialization of global parameters before scene readiness. - Enhanced the audit rounding ledger to compare selective and full rounding results for consistency.
114 lines
6.3 KiB
GDScript
114 lines
6.3 KiB
GDScript
extends SceneTree
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const E = preload("res://world/owniverse/math/exact.gd")
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const Clock = preload("res://world/owniverse/simulation_time.gd")
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var checks: int = 0
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var failures: int = 0
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func _initialize() -> void:
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call_deferred("run")
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func check(condition: bool, message: String) -> void:
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checks = E.add(checks, 1)
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if (not condition):
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failures = E.add(failures, 1)
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push_error(message)
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func fixture():
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var world = load("res://world/owniverse/owniverse.gd").new()
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var global: Node = root.get_node("Global")
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for id in global.OwniverseEntities:
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var entity = load("res://world/owniverse/owniverse_entity.gd").new(global.OwniverseEntities[id])
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world.catalog.entities[id] = entity
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world.state.amount[id] = 0
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world.state.stats.total_amount[id] = 0
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if E.ne(entity.group_as, ""):
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world.state.amount[entity.group_as] = 0
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world.state.stats.total_amount[entity.group_as] = 0
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world.catalog.entities["N"].life_product = {}
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world.catalog.entities["N"].product_per_year_type = "H"
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world.catalog.entities["N"].product_per_year_amount = 10
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world.catalog.entities["N"].auto = 0
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world.state.amount.N = 1
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return world
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func dispose(world) -> void:
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for entity in world.catalog.entities.values():
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entity.free()
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world.free()
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func run() -> void:
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var world = fixture()
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world.catalog.entities.N.lifespan = 100
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world.batches.append_batch(world.state, "N", 2, 10, 10)
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world.batches.append_batch(world.state, "N", 3, 10, 10)
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check(world.state.batches.N.size() == 1 and E.eq(world.state.batches.N[0].amount, 5), "Repeated insertion merges using the cohort index")
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world.batches.append_batch(world.state, "N", 1, 0, 0)
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check(E.eq(world.state.batches.N[0].created_from, 0), "Earlier insertion preserves chronological order")
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var replaced: Array = world.state.batches.N.duplicate(true)
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world.state.batches.N = replaced
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world.batches.append_batch(world.state, "N", 7, 10, 10)
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check(E.eq(replaced[1].amount, 12), "Replacing cohort array invalidates cached references")
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var separate: Dictionary = world.state.duplicate(true)
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world.batches.append_batch(separate, "N", 9, 10, 10)
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check(E.eq(separate.batches.N[1].amount, 21) and E.eq(world.state.batches.N[1].amount, 12), "Index is isolated between transaction states")
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dispose(world)
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world = fixture()
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for speed in range(1, 7):
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world.state.speed = speed
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check(E.eq(world.batches.window_duration(world.state, 100), 2.5 if speed < 4 else pow(10, speed - 2)), "Windows follow selected speed")
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check(E.eq(world.batches.window_duration(world.state, 5), 5), "Short explosions retain their timing")
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var huge: Variant = E.of("10000000000000000000000000000000000000000")
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world.catalog.entities.N.lifespan = 100
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world.state.batches.N = [
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{"amount": huge, "start_year": 100, "end_year": 110, "created_from": 0, "created_to": 10, "withdraw_remainder": 0.25},
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{"amount": 7, "start_year": 120, "end_year": 130, "created_from": 20, "created_to": 30, "withdraw_remainder": 0.5}
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]
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world.batches.coarsen(world.state)
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check(world.state.batches.N.size() == 1, "High speed combines nearby cohorts")
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check(E.eq(world.state.batches.N[0].amount, E.add(huge, 7)), "Coarsening preserves exact large whole counts")
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check(E.eq(world.state.batches.N[0].withdraw_remainder, 0.75), "Coarsening preserves withdrawal carry")
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var combined: Dictionary = world.state.batches.N[0].duplicate(true)
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world.batches.coarsen(world.state)
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check(world.state.batches.N[0] == combined, "Coarsening is idempotent")
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world.state.speed = 1
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world.batches.coarsen(world.state)
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check(world.state.batches.N[0] == combined, "Slowing down does not invent finer history")
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dispose(world)
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world = fixture()
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world.state.batch_origins.LGRB = E.of("10357034.80000000074505806")
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var boundary: Variant = E.of("41215289.79999999701976776")
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for interval in [[E.subtract(boundary, E.of("2.5")), E.add(boundary, E.of("2.25"))], [boundary, E.add(boundary, 2)]]:
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world.state.batches.LGRB = []
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world.batches.append_batch(world.state, "LGRB", 100, interval[0], interval[1])
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var total: Variant = 0
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var last: Variant = E.neg(INF)
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for batch : Dictionary in world.state.batches.LGRB:
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total = E.add(total, batch.amount)
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check(E.gt(batch.created_from, last), "Batch windows advance monotonically")
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check(E.gt(batch.created_to, batch.created_from), "Positive window duration")
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check(E.ge(batch.amount, 0), "No negative batch amounts")
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last = batch.created_from
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check(E.eq(total, 100), "Boundary correction preserves all objects")
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check(E.le(world.state.batches.LGRB.size(), 7), "Finite number of windows")
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dispose(world)
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world = fixture()
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world.batches.append_batch(world.state, "N", 100, 100, 100)
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var first: Dictionary = world.state.batches.N[0].duplicate(true)
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world.batches.append_batch(world.state, "N", 7, 100, 100)
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check(world.state.batches.N.size() == 1 and E.eq(world.state.batches.N[0].amount, 107), "Repeated births merge directly into one window")
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check(E.eq(world.state.batches.N[0].start_year, first.start_year), "Direct merge preserves transition time")
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check(world.batches.withdraw_batches(world.state, "N", 0).is_empty(), "Future cohorts are not withdrawn")
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var untouched: Array = world.state.batches.N
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check(world.batches.withdraw_batches(world.state, "N", 1).is_empty() and is_same(untouched, world.state.batches.N), "Readiness index skips future cohorts")
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world.state.batches.N = [{"amount": 7, "start_year": 0, "end_year": 0, "created_from": 0, "created_to": 0}]
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check(world.batches.withdraw_batches(world.state, "N", 1).size() == 1, "Replacing cohorts invalidates readiness index")
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world.batches.append_batch(world.state, "N", 3, 100, 100)
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check(E.eq(world.state.batches.N[0].amount, 3), "Replacing cohorts invalidates instant merge cache")
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world.batches.withdraw_batches(world.state, "N", 0)
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world.batches.scale_batches(world.state, "N", 0)
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world.batches.withdraw_batches(world.state, "N", 1)
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check(world.state.batches.N.is_empty(), "Scaling invalidates readiness and removes zero cohorts")
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dispose(world)
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print(("Batch boundaries: %d checks, %d failures" % [checks, failures]))
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quit((0 if E.eq(failures, 0) else 1))
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