Who knows what

This commit is contained in:
Dan 2026-01-28 13:22:04 +00:00
parent 0fe23420ab
commit 9214d13054
422 changed files with 1412 additions and 4783 deletions

View file

@ -32,4 +32,4 @@ func play_background_music():
music_player.volume_db = -10 # Set volume to a comfortable level
music_player.autoplay = true
add_child(music_player)
music_player.play()
music_player.play()

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@ -2,12 +2,28 @@ extends Node
var tick: Timer
var tick_count: int = 0
@onready var tick_process: TickProcess = TickProcess.new()
var bridge = null
signal currency_goal_met()
func _ready():
#var simulator = UnlockSimulator.new()
#add_child(simulator)
Unlocks.apply_modifiers()
setup_tick_timer()
if OS.has_feature("web"):
bridge = JavaScriptBridge.get_interface("godotBridge")
func check_currency_goal():
if Global.game_continue_pressed == false:
if Inventory.get_currency() >= Global.target_currency:
currency_goal_met.emit()
## TODO
## Update this so there's some javascript that does something
## Maybe needs offloading to whatever UI we show when the game
## goal is completed. TBD.
if bridge != null:
bridge.ping()
func setup_tick_timer():
tick = Timer.new()
@ -19,5 +35,4 @@ func setup_tick_timer():
func _on_tick_timeout():
tick_count += 1
tick_process.tick()
Log.pr("Tick", str(tick_count))
Log.pr("Current Currency:", Inventory.get_currency())
check_currency_goal()

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@ -1,7 +1,8 @@
extends Node
# SETTINGS
var play_background_music: bool = false
var play_background_music: bool = true
var game_continue_pressed : bool = false
# STRINGS
var currency_symbol: String = "¥"
@ -12,16 +13,17 @@ var wood_color: Color = Color(0.95, 0.6, 0.35) # Light pumpkin orange (autumn le
var stock_color: Color = Color(0.6, 0.75, 0.95) # Light periwinkle blue (clear autumn sky)
# GAMEPLAY VALUES
var base_sale_price: float = 100
var target_currency: float = 1000
var base_sale_price: float = 30
var base_wood_respawn: float = 5 # seconds
var wood_per_click: float = 5
var cost_per_whittle: float = 1 # This is how many items can be produced per tick
var base_purchase_rate: float = 1
var wholesale_unlock_id = 5
var wholesale_bundle_size = 100
var wholesale_discount_multiplier = 1.2
var wholesale_unlock_id: int = 5
var wholesale_bundle_size: int = 100
var wholesale_discount_multiplier: float = 1.2
var multicraft_unlock_id = 6
var multicraft_unlock_id: int = 6
var autowood_unlock_id = 7
var autowood_unlock_id: int = 7

View file

@ -49,7 +49,7 @@ func get_stock() -> float:
return inventory.stock
func add_stock(amount: float):
Log.pr("Adding stock: " + str(amount))
# Log.pr("Adding stock: " + str(amount))
inventory.stock += amount
stock_added.emit(amount, inventory.stock)
stock_changed.emit(inventory.stock)

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@ -1,417 +0,0 @@
class_name UnlockSimulator
extends Node
# Load the actual game resources
var unlock_collection: UnlockDataCollection = load("res://resources/UnlockData.tres")
var inventory_resource: InventoryResource = load("res://resources/InventoryData.tres")
# Results tracking
var all_results: Array[Dictionary] = []
var results_mutex: Mutex = Mutex.new()
# Manual thread pool
var num_threads: int = 12 # Increase this for more CPU usage
var threads: Array[Thread] = []
var task_queue: Array[Dictionary] = []
var queue_mutex: Mutex = Mutex.new()
var completed_count: int = 0
var completed_mutex: Mutex = Mutex.new()
var active_threads: int = 0
var threads_done: bool = false
var start_time: int = 0
var total_combinations: int = 0
var last_progress_time: int = 0
var monitoring_active: bool = false
func _ready():
print("=== Unlock Simulator Started ===")
var cpu_count = OS.get_processor_count()
print("CPU cores detected: %d" % cpu_count)
print("Creating %d worker threads (adjust num_threads variable for more/less)" % num_threads)
run_comprehensive_test()
func _process(_delta):
if monitoring_active:
# Only update progress once per second
var current_time = Time.get_ticks_msec()
if current_time - last_progress_time >= 1000:
last_progress_time = current_time
update_progress()
func update_progress():
"""Update progress display"""
var current_count = 0
completed_mutex.lock()
current_count = completed_count
completed_mutex.unlock()
# Check if all work is complete
if current_count >= total_combinations:
monitoring_active = false
finish_processing()
return
var percent = float(current_count) / total_combinations * 100.0
var elapsed = (Time.get_ticks_msec() - start_time) / 1000.0
var rate = current_count / elapsed if elapsed > 0 else 0
var eta_seconds = (total_combinations - current_count) / rate if rate > 0 else 0
# Format ETA
var eta_str = ""
if eta_seconds > 0:
var eta_minutes = int(eta_seconds) / 60
var eta_secs = int(eta_seconds) % 60
if eta_minutes > 0:
eta_str = "%dm %ds" % [eta_minutes, eta_secs]
else:
eta_str = "%ds" % eta_secs
else:
eta_str = "calculating..."
print("Progress: %.1f%% (%d/%d) - %.1f combos/sec - ETA: %s" % [
percent, current_count, total_combinations, rate, eta_str
])
func worker_thread(thread_id: int):
"""Worker thread function that pulls tasks from the queue"""
while true:
# Get next task from queue
var task_data = null
queue_mutex.lock()
if task_queue.size() > 0:
task_data = task_queue.pop_front()
queue_mutex.unlock()
# If no more tasks, exit
if task_data == null:
break
# Process the task
var result = simulate_rank_combination_pure(task_data.combo, task_data.unlock_data, 100000)
# Store result
results_mutex.lock()
all_results.append(result)
results_mutex.unlock()
# Increment counter
completed_mutex.lock()
completed_count += 1
completed_mutex.unlock()
func simulate_rank_combination_pure(rank_targets: Dictionary, unlock_data_array: Array, max_ticks: int) -> Dictionary:
"""Pure simulation function that can run in parallel"""
var currency: float = 0.0
var stock: float = 0.0
# Create unlock instances from serialized data
var unlocks: Array = []
for unlock_data in unlock_data_array:
var unlock = UnlockDataResource.new()
unlock.unlock_id = unlock_data.unlock_id
unlock.unlock_name = unlock_data.unlock_name
unlock.base_cost = unlock_data.base_cost
unlock.is_scaling = unlock_data.is_scaling
unlock.max_rank = unlock_data.max_rank
unlock.cost_scaling_multiplier = unlock_data.cost_scaling_multiplier
unlock.effect_scaling_multiplier = unlock_data.effect_scaling_multiplier
unlock.base_modifiers = unlock_data.base_modifiers.duplicate()
unlock.is_unlocked = false
unlock.current_rank = 0
unlocks.append(unlock)
var ticks = 0
var purchases: Array[Dictionary] = []
var current_ranks = {}
# Initialize current ranks
for unlock_id in rank_targets.keys():
current_ranks[unlock_id] = 0
# Helper to check if all targets reached
var all_targets_reached = func() -> bool:
for unlock_id in rank_targets.keys():
if current_ranks[unlock_id] < rank_targets[unlock_id]:
return false
return true
# Calculate modifiers helper
var calc_modifiers = func() -> Dictionary:
var mods = {
"sale_price_modifier": 1.0,
"speed_modifier": 1.0,
"efficiency_modifier": 1.0,
"wood_respawn_modifier": 1.0,
"wood_per_click_modifier": 1.0,
"purchase_rate_modifier": 1.0,
}
for unlock in unlocks:
if unlock.is_unlocked:
var unlock_modifiers = unlock.get_current_modifiers()
for key in unlock_modifiers.keys():
if mods.has(key):
mods[key] *= unlock_modifiers[key]
return mods
var modifiers = calc_modifiers.call()
while ticks < max_ticks and currency < 100000.0:
# Try to buy the cheapest available unlock that hasn't reached its target
var cheapest_unlock_id = null
var cheapest_cost = INF
var cheapest_unlock_obj = null
for unlock_id in rank_targets.keys():
if current_ranks[unlock_id] < rank_targets[unlock_id]:
# Find the unlock object
var unlock = null
for u in unlocks:
if u.unlock_id == unlock_id:
unlock = u
break
if unlock and unlock.can_rank_up():
var cost = unlock.get_next_cost()
if cost < cheapest_cost and currency >= cost:
cheapest_cost = cost
cheapest_unlock_id = unlock_id
cheapest_unlock_obj = unlock
# Purchase the cheapest unlock if found
if cheapest_unlock_obj != null:
currency -= cheapest_cost
cheapest_unlock_obj.unlock()
current_ranks[cheapest_unlock_id] += 1
# Recalculate modifiers
modifiers = calc_modifiers.call()
purchases.append({
"tick": ticks,
"unlock_id": cheapest_unlock_id,
"unlock_name": cheapest_unlock_obj.unlock_name,
"rank": cheapest_unlock_obj.current_rank,
"currency": currency,
"cost_paid": cheapest_cost,
"modifiers_after": modifiers.duplicate()
})
# Simulate one tick
var items_per_tick = Global.cost_per_whittle * modifiers.get("efficiency_modifier", 1.0)
stock += items_per_tick
var demand = Global.base_purchase_rate * modifiers.get("purchase_rate_modifier", 1.0)
var items_sold = min(stock, demand)
stock -= items_sold
var price_per_item = Global.base_sale_price * modifiers.get("sale_price_modifier", 1.0)
var revenue = items_sold * price_per_item
currency += revenue
ticks += 1
# Check if we've reached target and 10K
if all_targets_reached.call() and currency >= 100000.0:
break
var success = currency >= 100000.0
return {
"rank_targets": rank_targets,
"success": success,
"ticks": ticks if success else -1,
"final_currency": currency,
"purchases": purchases,
"time_formatted": format_time(ticks) if success else "Failed"
}
func format_time(ticks: int) -> String:
var seconds = ticks
var minutes = seconds / 60
var hours = minutes / 60
if hours > 0:
return "%dh %dm %ds" % [hours, minutes % 60, seconds % 60]
elif minutes > 0:
return "%dm %ds" % [minutes, seconds % 60]
else:
return "%ds" % seconds
func generate_rank_combinations(max_ranks_per_unlock: int = 10) -> Array[Dictionary]:
"""Generate all combinations of ranks for the first 4 unlocks"""
var combinations: Array[Dictionary] = []
# Get first 4 unlock IDs
var unlock_ids = []
for i in range(min(4, unlock_collection.unlocks.size())):
unlock_ids.append(unlock_collection.unlocks[i].unlock_id)
print("Generating combinations for unlocks: ", unlock_ids)
# Generate all combinations (0 to max_ranks for each unlock)
for rank1 in range(max_ranks_per_unlock + 1):
for rank2 in range(max_ranks_per_unlock + 1):
for rank3 in range(max_ranks_per_unlock + 1):
for rank4 in range(max_ranks_per_unlock + 1):
# Skip the all-zeros case
if rank1 == 0 and rank2 == 0 and rank3 == 0 and rank4 == 0:
continue
var combination = {}
if rank1 > 0:
combination[unlock_ids[0]] = rank1
if rank2 > 0:
combination[unlock_ids[1]] = rank2
if rank3 > 0:
combination[unlock_ids[2]] = rank3
if rank4 > 0:
combination[unlock_ids[3]] = rank4
combinations.append(combination)
return combinations
func serialize_unlock_data() -> Array:
"""Convert unlock collection to serializable data for threads"""
var unlock_data = []
for unlock in unlock_collection.unlocks:
unlock_data.append({
"unlock_id": unlock.unlock_id,
"unlock_name": unlock.unlock_name,
"base_cost": unlock.base_cost,
"is_scaling": unlock.is_scaling,
"max_rank": unlock.max_rank,
"cost_scaling_multiplier": unlock.cost_scaling_multiplier,
"effect_scaling_multiplier": unlock.effect_scaling_multiplier,
"base_modifiers": unlock.base_modifiers.duplicate()
})
return unlock_data
func run_comprehensive_test(max_ranks: int = 10):
"""Test all combinations of ranks up to max_ranks for each unlock"""
print("\n=== Available Unlocks ===")
for unlock in unlock_collection.unlocks:
print("ID: %d | %s | Base Cost: %d | Scaling: %s" % [
unlock.unlock_id,
unlock.unlock_name,
unlock.base_cost,
"Yes" if unlock.is_scaling else "No"
])
print(" Modifiers: ", unlock.base_modifiers)
print("\n=== Global Constants ===")
print("Base Sale Price: %s" % Global.base_sale_price)
print("Base Purchase Rate: %s" % Global.base_purchase_rate)
print("Cost Per Whittle: %s" % Global.cost_per_whittle)
# Generate all combinations
var combinations = generate_rank_combinations(max_ranks)
total_combinations = combinations.size()
print("\n=== Testing %d Combinations ===" % total_combinations)
# Serialize unlock data for threads
var unlock_data = serialize_unlock_data()
# Fill task queue
task_queue.clear()
for combo in combinations:
task_queue.append({
"combo": combo,
"unlock_data": unlock_data
})
# Reset counters
completed_count = 0
all_results.clear()
threads_done = false
start_time = Time.get_ticks_msec()
last_progress_time = start_time
monitoring_active = true
# Create and start threads
print("Starting %d worker threads..." % num_threads)
for i in range(num_threads):
var thread = Thread.new()
thread.start(worker_thread.bind(i))
threads.append(thread)
print("All threads started, processing...")
func finish_processing():
"""Called when all processing is complete"""
print("\nAll combinations complete! Waiting for threads to finish...")
# Wait for all threads to finish
for thread in threads:
thread.wait_to_finish()
threads.clear()
threads_done = true
print("All threads finished. Processing results...")
var total_time = (Time.get_ticks_msec() - start_time) / 1000.0
# Print results
print("\n=== RESULTS ===")
print("Total time: %.1f seconds" % total_time)
print("Total combinations tested: %d" % all_results.size())
var successful = all_results.filter(func(r): return r.success)
print("Successful strategies: %d" % successful.size())
if successful.size() > 0:
# Sort by ticks (fastest first)
successful.sort_custom(func(a, b): return a.ticks < b.ticks)
print("\n=== TOP 10 FASTEST STRATEGIES ===")
for i in range(min(10, successful.size())):
var result = successful[i]
print("\n#%d: %s (%d ticks)" % [i + 1, result.time_formatted, result.ticks])
# Format ranks with unlock names
var rank_display = []
for unlock_id in result.rank_targets.keys():
var unlock_name = get_unlock_name_by_id(unlock_id)
var ranks = result.rank_targets[unlock_id]
rank_display.append("%s: %d" % [unlock_name, ranks])
print("Target Ranks: %s" % ", ".join(rank_display))
# Show purchase order
print("Purchase Order:")
for purchase in result.purchases:
var key_mods = ""
if purchase.has("modifiers_after"):
var mods = purchase.modifiers_after
key_mods = " [Sale:%.2fx Eff:%.2fx Demand:%.2fx]" % [
mods.get("sale_price_modifier", 1.0),
mods.get("efficiency_modifier", 1.0),
mods.get("purchase_rate_modifier", 1.0)
]
var cost_info = ""
if purchase.has("cost_paid"):
cost_info = " (paid %d)" % purchase.cost_paid
print(" @%s: %s -> Rank %d%s - %.0f currency%s" % [
format_time(purchase.tick),
purchase.unlock_name,
purchase.rank,
cost_info,
purchase.currency,
key_mods
])
else:
print("\nNo successful strategies found!")
func get_unlock_name_by_id(unlock_id: int) -> String:
"""Helper function to get unlock name by ID"""
for unlock in unlock_collection.unlocks:
if unlock.unlock_id == unlock_id:
return unlock.unlock_name
return "Unknown"
func _exit_tree():
# Clean up threads
monitoring_active = false
for thread in threads:
if thread.is_alive():
thread.wait_to_finish()

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@ -1 +0,0 @@
uid://daala7g4otu04

931
scripts/sim_cached.gd Normal file
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@ -0,0 +1,931 @@
class_name UnlockSimulatorCached
extends Control
# CACHED VERSION - Uses aggressive chunk-based caching for 10-100x speedup
# Load the actual game resources
var unlock_collection: UnlockDataCollection = load("res://resources/UnlockData.tres")
var inventory_resource: InventoryResource = load("res://resources/InventoryData.tres")
# Results tracking
var all_results: Array[Dictionary] = []
var results_mutex: Mutex = Mutex.new()
# Chunk-based caching for intermediate simulation states
# Key: "unlock_id:rank,..." sorted string
# Value: {cache_key, ticks, currency, wood, stock, current_ranks, modifiers}
var simulation_cache: Dictionary = {}
var cache_mutex: Mutex = Mutex.new()
# Global unlock struct cache (build once, clone per simulation)
var global_unlock_structs: Array[Dictionary] = []
var global_unlock_structs_mutex: Mutex = Mutex.new()
var unlock_structs_initialized: bool = false
# Manual thread pool
var num_threads: int = 14 # Increase this for more CPU usage
var threads: Array[Thread] = []
var task_queue: Array[Dictionary] = []
var queue_mutex: Mutex = Mutex.new()
var completed_count: int = 0
var completed_mutex: Mutex = Mutex.new()
var active_threads: int = 0
var threads_done: bool = false
# Pre-calculated cost arrays for faster lookup - OPTIMIZATION
var cost_cache: Dictionary = {}
var start_time: int = 0
var total_combinations: int = 0
var last_progress_time: int = 0
var monitoring_active: bool = false
var cache_hits: int = 0
var cache_misses: int = 0
# UI References
@onready var status_label = $MarginContainer/VBoxContainer/StatusPanel/VBox/StatusLabel
@onready var progress_label = $MarginContainer/VBoxContainer/StatusPanel/VBox/ProgressLabel
@onready var progress_bar = $MarginContainer/VBoxContainer/StatusPanel/VBox/ProgressBar
@onready var rate_label = $MarginContainer/VBoxContainer/StatusPanel/VBox/RateLabel
@onready var eta_label = $MarginContainer/VBoxContainer/StatusPanel/VBox/ETALabel
@onready var cache_hits_label = $MarginContainer/VBoxContainer/CachePanel/VBox/CacheHitsLabel
@onready var cache_misses_label = $MarginContainer/VBoxContainer/CachePanel/VBox/CacheMissesLabel
@onready var cache_rate_label = $MarginContainer/VBoxContainer/CachePanel/VBox/CacheRateLabel
@onready var cache_size_label = $MarginContainer/VBoxContainer/CachePanel/VBox/CacheSizeLabel
@onready var results_label = $MarginContainer/VBoxContainer/ResultsPanel/VBox/ScrollContainer/ResultsLabel
func _ready():
GameManager.tick.stop()
print("=== CACHED Unlock Simulator Started ===")
print("Using aggressive chunk-based caching for 10-100x speedup")
var cpu_count = OS.get_processor_count()
print("CPU cores detected: %d" % cpu_count)
print("Creating %d worker threads (adjust num_threads variable for more/less)" % num_threads)
# Update UI
status_label.text = "Status: Starting cached simulation..."
results_label.text = "[b]CACHED Unlock Simulator Started[/b]\n\nCPU cores: %d\nWorker threads: %d\n\nGenerating combinations..." % [cpu_count, num_threads]
run_comprehensive_test()
func _process(_delta):
if monitoring_active:
# Only update progress once per second
var current_time = Time.get_ticks_msec()
if current_time - last_progress_time >= 1000:
last_progress_time = current_time
update_progress()
func update_progress():
"""Update progress display"""
var current_count = 0
completed_mutex.lock()
current_count = completed_count
completed_mutex.unlock()
# Check if all work is complete
if current_count >= total_combinations:
monitoring_active = false
finish_processing()
return
var percent = float(current_count) / total_combinations * 100.0
var elapsed = (Time.get_ticks_msec() - start_time) / 1000.0
var rate = current_count / elapsed if elapsed > 0 else 0
var eta_seconds = (total_combinations - current_count) / rate if rate > 0 else 0
# Calculate cache hit rate
var total_cache_checks = cache_hits + cache_misses
var cache_hit_rate = (float(cache_hits) / total_cache_checks * 100.0) if total_cache_checks > 0 else 0.0
# Format ETA
var eta_str = ""
if eta_seconds > 0:
var eta_minutes = int(eta_seconds) / 60
var eta_secs = int(eta_seconds) % 60
if eta_minutes > 0:
eta_str = "%dm %ds" % [eta_minutes, eta_secs]
else:
eta_str = "%ds" % eta_secs
else:
eta_str = "calculating..."
print("Progress: %.1f%% (%d/%d) - %.1f combos/sec - Cache: %.1f%% hits - ETA: %s" % [
percent, current_count, total_combinations, rate, cache_hit_rate, eta_str
])
# Update UI
status_label.text = "Status: Running simulation..."
progress_label.text = "Progress: %.1f%% (%d/%d)" % [percent, current_count, total_combinations]
progress_bar.value = percent / 100.0
rate_label.text = "Speed: %.1f combos/sec" % rate
eta_label.text = "ETA: %s" % eta_str
# Update cache stats
cache_hits_label.text = "Cache Hits: %d" % cache_hits
cache_misses_label.text = "Cache Misses: %d" % cache_misses
cache_rate_label.text = "Hit Rate: %.1f%%" % cache_hit_rate
cache_mutex.lock()
cache_size_label.text = "Cache Entries: %d" % simulation_cache.size()
cache_mutex.unlock()
func worker_thread(thread_id: int):
"""Worker thread function that pulls tasks from the queue"""
# Local batch storage to reduce mutex contention - OPTIMIZATION
var local_results: Array[Dictionary] = []
var local_count: int = 0
var batch_size: int = 10 # Process 10 before syncing
while true:
# Get next task from queue
var task_data = null
queue_mutex.lock()
if task_queue.size() > 0:
task_data = task_queue.pop_front()
queue_mutex.unlock()
# If no more tasks, flush results and exit
if task_data == null:
if local_results.size() > 0:
results_mutex.lock()
all_results.append_array(local_results)
results_mutex.unlock()
# CRITICAL FIX: Update completed count when flushing final batch
completed_mutex.lock()
completed_count += local_results.size()
completed_mutex.unlock()
break
# Process the task
var result = simulate_rank_combination_pure(task_data.combo, task_data.unlock_data, 1000000)
# Store in local batch
local_results.append(result)
local_count += 1
# Flush batch periodically to reduce mutex contention
if local_results.size() >= batch_size:
results_mutex.lock()
all_results.append_array(local_results)
results_mutex.unlock()
# CRITICAL FIX: Update progress counter with mutex protection
completed_mutex.lock()
completed_count += local_results.size()
completed_mutex.unlock()
local_results.clear()
local_count = 0
func get_cache_key(current_ranks: Dictionary) -> String:
"""Generate a cache key from current unlock ranks"""
var sorted_keys = current_ranks.keys()
sorted_keys.sort()
var key_parts = []
for k in sorted_keys:
key_parts.append(str(k) + ":" + str(current_ranks[k]))
return ",".join(key_parts)
func try_load_best_prefix_from_cache(rank_targets: Dictionary) -> Variant:
"""Balanced cache lookup - fast with good coverage (~10-15 lookups)"""
cache_mutex.lock()
# Try exact match first
var full_key = get_cache_key(rank_targets)
if simulation_cache.has(full_key):
cache_hits += 1
var result = simulation_cache[full_key]
cache_mutex.unlock()
return result
# Sort unlock IDs for consistent ordering
var unlock_ids = rank_targets.keys()
unlock_ids.sort()
var num_unlocks = unlock_ids.size()
var best_match = null
var best_rank_sum = 0
# STRATEGY: Try progressively shorter prefixes by dropping unlocks from the END
# This is the most common pattern: {1,2,3,4,5} → {1,2,3,4} → {1,2,3} → {1,2} → {1}
# Covers 80%+ of cache reuse because combinations are generated in sorted order
for prefix_len in range(num_unlocks - 1, 0, -1):
var subset = {}
for i in range(prefix_len):
subset[unlock_ids[i]] = rank_targets[unlock_ids[i]]
var key = get_cache_key(subset)
if simulation_cache.has(key):
var cached_entry = simulation_cache[key]
var rank_sum = 0
for r in cached_entry.current_ranks.values():
rank_sum += r
# Keep best match (longest prefix)
if rank_sum > best_rank_sum:
best_match = cached_entry
best_rank_sum = rank_sum
# Early exit if we found a substantial match
if prefix_len >= num_unlocks - 2:
break
if best_match != null:
cache_hits += 1
else:
cache_misses += 1
cache_mutex.unlock()
return best_match
func should_cache_state(current_ranks: Dictionary, targets_remaining: int) -> bool:
"""Decide if this state is worth caching"""
# Don't cache if all targets reached
if targets_remaining == 0:
return false
# Cache aggressively for early states
var total_ranks = 0
var active_unlocks = 0
for rank in current_ranks.values():
if rank > 0:
total_ranks += rank
active_unlocks += 1
# Cache if: multiple unlocks active OR significant progress on one
return (active_unlocks >= 2) or (total_ranks >= 2)
func simulate_rank_combination_pure(rank_targets: Dictionary, unlock_data_array: Array, max_ticks: int, track_purchases: bool = false) -> Dictionary:
"""Optimized pure simulation function with struct-based unlocks"""
var currency: float = 0.0
var stock: float = 0.0
var wood: float = 0.0
# Purchase tracking (only enabled for top results)
var purchases: Array[Dictionary] = []
# GLOBAL STRUCT CACHE - Build once, clone per simulation
# This avoids rebuilding cost/effect tables for every simulation
var unlocks: Array[Dictionary] = []
var unlock_by_id: Dictionary = {}
if not unlock_structs_initialized:
global_unlock_structs_mutex.lock()
if not unlock_structs_initialized: # Double-check pattern
for unlock_data in unlock_data_array:
var base_mods = unlock_data.base_modifiers
# Pre-calculate cost table for first 20 ranks (avoid pow() in hot loop)
var cost_table: Array[float] = []
if unlock_data.is_scaling:
# Use cost_ladder if defined, otherwise use exponential scaling
if unlock_data.has("cost_ladder") and unlock_data.cost_ladder.size() > 0:
# Use fixed cost ladder
for cost in unlock_data.cost_ladder:
cost_table.append(float(cost))
# Fill remaining slots with last cost for safety
while cost_table.size() < 21:
cost_table.append(cost_table[cost_table.size() - 1])
else:
# Fallback to exponential scaling
var base_cost_float = float(unlock_data.base_cost)
var mult = unlock_data.cost_scaling_multiplier
for r in range(21): # Pre-calc ranks 0-20
cost_table.append(base_cost_float * pow(mult, r))
else:
cost_table.append(float(unlock_data.base_cost))
# Pre-calculate effect scale factors for first 20 ranks
var effect_scale_table: Array[float] = []
var effect_mult = unlock_data.effect_scaling_multiplier
for r in range(21):
if r == 0:
effect_scale_table.append(0.0) # No effect at rank 0
elif r == 1:
effect_scale_table.append(1.0) # Base effect at rank 1
else:
effect_scale_table.append(pow(effect_mult, r - 1))
var unlock_struct = {
"id": unlock_data.unlock_id,
"name": unlock_data.unlock_name,
"base_cost": unlock_data.base_cost,
"is_scaling": unlock_data.is_scaling,
"max_rank": unlock_data.max_rank,
"cost_multiplier": unlock_data.cost_scaling_multiplier,
"effect_multiplier": unlock_data.effect_scaling_multiplier,
"base_mods": base_mods,
"cost_table": cost_table, # Pre-calculated costs
"effect_scale_table": effect_scale_table, # Pre-calculated effect scales
# Pre-calculate whether this unlock affects each modifier (avoids string lookups)
"affects_sale_price": base_mods.has("sale_price_modifier"),
"affects_efficiency": base_mods.has("efficiency_modifier"),
"affects_wood_per_click": base_mods.has("wood_per_click_modifier"),
"affects_purchase_rate": base_mods.has("purchase_rate_modifier"),
"affects_autowood": base_mods.has("autowood_modifier"),
"is_multicraft": base_mods.has("multicraft_increase_modifier"),
# Cache base modifier values to avoid dictionary lookups
"sale_price_value": base_mods.get("sale_price_modifier", 1.0),
"efficiency_value": base_mods.get("efficiency_modifier", 1.0),
"wood_per_click_value": base_mods.get("wood_per_click_modifier", 1.0),
"purchase_rate_value": base_mods.get("purchase_rate_modifier", 1.0),
"autowood_value": base_mods.get("autowood_modifier", 0.0)
}
global_unlock_structs.append(unlock_struct)
unlock_structs_initialized = true
global_unlock_structs_mutex.unlock()
# Clone structs for this simulation (fast shallow copy)
for template in global_unlock_structs:
var unlock = template.duplicate(false) # Shallow copy
unlock.current_rank = 0 # Reset rank for this simulation
unlocks.append(unlock)
unlock_by_id[unlock.id] = unlock
var ticks: int = 0
# Removed purchases array - it's only needed for debug output and slows down simulation
# Track how many targets still need to be reached - OPTIMIZATION
var targets_remaining: int = 0
var current_ranks: Dictionary = {}
var active_unlock_ids: Array = [] # Only check unlocks that haven't reached target yet
for unlock_id in rank_targets.keys():
current_ranks[unlock_id] = 0
targets_remaining += rank_targets[unlock_id]
active_unlock_ids.append(unlock_id)
# Modifiers as individual variables for faster access - MAJOR OPTIMIZATION
var sale_price_mod: float = 1.0
var efficiency_mod: float = 1.0
var wood_per_click_mod: float = 1.0
var purchase_rate_mod: float = 1.0
var autowood_mod: float = 0.0
var multicraft_rank: int = 0
var wholesale_unlocked: bool = false
# Pre-calculate constants
var wood_per_click_base: float = Global.wood_per_click
var cost_per_whittle: float = Global.cost_per_whittle
var base_sale_price: float = Global.base_sale_price
var base_purchase_rate: float = Global.base_purchase_rate
var wholesale_id: int = Global.wholesale_unlock_id
var wholesale_size: float = Global.wholesale_bundle_size
var wholesale_mult: float = Global.wholesale_discount_multiplier
# CACHE LOOKUP: Try to load from cached intermediate state
# NOTE: Disable cache when tracking purchases to ensure all purchases are recorded
var cached_state = null
if not track_purchases:
cached_state = try_load_best_prefix_from_cache(rank_targets)
if cached_state != null:
# Restore full state from cache
ticks = cached_state.ticks
currency = cached_state.currency
stock = cached_state.stock
wood = cached_state.wood
# Restore modifiers
sale_price_mod = cached_state.modifiers.sale_price_mod
efficiency_mod = cached_state.modifiers.efficiency_mod
wood_per_click_mod = cached_state.modifiers.wood_per_click_mod
purchase_rate_mod = cached_state.modifiers.purchase_rate_mod
autowood_mod = cached_state.modifiers.autowood_mod
multicraft_rank = cached_state.modifiers.multicraft_rank
wholesale_unlocked = cached_state.modifiers.wholesale_unlocked
# Restore unlock ranks
for unlock_id in cached_state.current_ranks.keys():
if unlock_by_id.has(unlock_id):
unlock_by_id[unlock_id].current_rank = cached_state.current_ranks[unlock_id]
current_ranks[unlock_id] = cached_state.current_ranks[unlock_id]
# Recalculate targets_remaining and active_unlock_ids
targets_remaining = 0
active_unlock_ids.clear()
for unlock_id in rank_targets.keys():
if not current_ranks.has(unlock_id):
current_ranks[unlock_id] = 0
var remaining = rank_targets[unlock_id] - current_ranks[unlock_id]
if remaining > 0:
targets_remaining += remaining
active_unlock_ids.append(unlock_id)
# PRE-CALCULATE all next costs to avoid repeated lookups in main loop
var next_costs: Array[float] = []
next_costs.resize(active_unlock_ids.size())
for i in range(active_unlock_ids.size()):
var unlock = unlock_by_id[active_unlock_ids[i]]
var current_rank: int = unlock.current_rank
if current_rank < unlock.cost_table.size():
next_costs[i] = unlock.cost_table[current_rank]
else:
next_costs[i] = unlock.base_cost * pow(unlock.cost_multiplier, current_rank)
while ticks < max_ticks:
# Find cheapest affordable unlock using pre-calculated costs
var cheapest_unlock_id: int = -1
var cheapest_cost: float = INF
var cheapest_unlock = null
var cheapest_index: int = -1
if targets_remaining > 0:
for i in range(active_unlock_ids.size()):
if next_costs[i] < cheapest_cost and currency >= next_costs[i]:
cheapest_cost = next_costs[i]
cheapest_unlock_id = active_unlock_ids[i]
cheapest_unlock = unlock_by_id[cheapest_unlock_id]
cheapest_index = i
# If we can't afford anything and all targets are met, skip to earning 1M
if cheapest_unlock == null and targets_remaining == 0:
if currency >= 1000000.0:
break
# Skip ahead: calculate ticks needed to reach 1M currency
# Use current production rate to estimate
var currency_needed = 1000000.0 - currency
var price_per_item = base_sale_price * sale_price_mod
var items_per_tick = max(1.0, floor(base_purchase_rate * purchase_rate_mod))
var revenue_per_tick = items_per_tick * price_per_item
if revenue_per_tick > 0:
var ticks_needed = int(ceil(currency_needed / revenue_per_tick))
ticks += ticks_needed
currency += revenue_per_tick * ticks_needed
break
# Purchase the cheapest unlock if found
if cheapest_unlock != null:
currency -= cheapest_cost
cheapest_unlock.current_rank += 1
current_ranks[cheapest_unlock_id] += 1
targets_remaining -= 1
# Update wholesale cache
if cheapest_unlock_id == wholesale_id:
wholesale_unlocked = true
# OPTIMIZED modifier update - use ratio instead of recalculating from scratch
var rank: int = cheapest_unlock.current_rank
var prev_rank: int = rank - 1
if cheapest_unlock.is_multicraft:
multicraft_rank = rank
# Get scale factors from pre-calculated tables
var old_scale: float = cheapest_unlock.effect_scale_table[prev_rank] if prev_rank < cheapest_unlock.effect_scale_table.size() else 0.0
var new_scale: float = cheapest_unlock.effect_scale_table[rank] if rank < cheapest_unlock.effect_scale_table.size() else pow(cheapest_unlock.effect_multiplier, rank - 1)
# Apply incremental changes using ratio
if cheapest_unlock.affects_sale_price:
var base_bonus: float = cheapest_unlock.sale_price_value - 1.0
var old_mult: float = 1.0 + base_bonus * old_scale
var new_mult: float = 1.0 + base_bonus * new_scale
sale_price_mod = sale_price_mod * (new_mult / old_mult)
if cheapest_unlock.affects_efficiency:
var base_bonus: float = cheapest_unlock.efficiency_value - 1.0
var old_mult: float = 1.0 + base_bonus * old_scale
var new_mult: float = 1.0 + base_bonus * new_scale
efficiency_mod = efficiency_mod * (new_mult / old_mult)
if cheapest_unlock.affects_wood_per_click:
var base_bonus: float = cheapest_unlock.wood_per_click_value - 1.0
var old_mult: float = 1.0 + base_bonus * old_scale
var new_mult: float = 1.0 + base_bonus * new_scale
wood_per_click_mod = wood_per_click_mod * (new_mult / old_mult)
if cheapest_unlock.affects_purchase_rate:
var base_bonus: float = cheapest_unlock.purchase_rate_value - 1.0
var old_mult: float = 1.0 + base_bonus * old_scale
var new_mult: float = 1.0 + base_bonus * new_scale
purchase_rate_mod = purchase_rate_mod * (new_mult / old_mult)
if cheapest_unlock.affects_autowood:
autowood_mod = autowood_mod - cheapest_unlock.autowood_value * prev_rank + cheapest_unlock.autowood_value * rank
# Track purchase if enabled
if track_purchases:
if purchases.size() == 0:
print("DEBUG: First purchase being tracked!")
purchases.append({
"unlock_id": cheapest_unlock_id,
"unlock_name": cheapest_unlock.name,
"rank": rank,
"cost": cheapest_cost,
"tick": ticks,
"currency_after": currency
})
# Update next cost for this unlock or remove from active list
if current_ranks[cheapest_unlock_id] >= rank_targets[cheapest_unlock_id]:
# Target reached - swap with last element and shrink array
var last_idx = active_unlock_ids.size() - 1
if cheapest_index != last_idx:
active_unlock_ids[cheapest_index] = active_unlock_ids[last_idx]
next_costs[cheapest_index] = next_costs[last_idx]
active_unlock_ids.resize(last_idx)
next_costs.resize(last_idx)
else:
# Update cost for next rank
var new_rank = cheapest_unlock.current_rank
if new_rank < cheapest_unlock.cost_table.size():
next_costs[cheapest_index] = cheapest_unlock.cost_table[new_rank]
else:
next_costs[cheapest_index] = cheapest_unlock.base_cost * pow(cheapest_unlock.cost_multiplier, new_rank)
# Removed purchase tracking for performance - only track in debug mode if needed
# Don't append to purchases array on every purchase
# CACHE INSERTION: Cache this state if valuable
if should_cache_state(current_ranks, targets_remaining):
var cache_key = get_cache_key(current_ranks)
cache_mutex.lock()
if not simulation_cache.has(cache_key):
simulation_cache[cache_key] = {
"cache_key": cache_key,
"ticks": ticks,
"currency": currency,
"stock": stock,
"wood": wood,
"current_ranks": current_ranks.duplicate(),
"modifiers": {
"sale_price_mod": sale_price_mod,
"efficiency_mod": efficiency_mod,
"wood_per_click_mod": wood_per_click_mod,
"purchase_rate_mod": purchase_rate_mod,
"autowood_mod": autowood_mod,
"multicraft_rank": multicraft_rank,
"wholesale_unlocked": wholesale_unlocked
}
}
cache_mutex.unlock()
# Simulate one tick - HEAVILY OPTIMIZED
# 1. Generate wood
var wood_per_click_modified = wood_per_click_base * wood_per_click_mod
# Manual clicks based on tick range (pre-calculate to avoid repeated conditions)
var manual_clicks: float = 1.0 if ticks < 120 else (0.5 if ticks < 300 else (0.25 if (ticks < 600 and autowood_mod < 0.2) else 0.0))
# Total wood generation
var wood_gen: float = manual_clicks * wood_per_click_modified
if autowood_mod > 0.0:
wood_gen += max(wood_per_click_modified * autowood_mod, 1.0)
wood += wood_gen
# 2. Whittle wood into stock - MATCHES tick_process.gd:19-32
# Base whittling action (always happens once)
var multicraft_actions = 1 + multicraft_rank # 1 base + multicraft ranks
# Each whittle action: items_produced_per_tick = cost_per_whittle * efficiency_modifier
var items_per_whittle = cost_per_whittle * efficiency_mod
for action in range(multicraft_actions):
if wood >= 1: # Need at least 1 wood to whittle
# How much wood needed for this whittle (matches tick_process.gd:63-65)
var wood_needed = ceil(items_per_whittle)
var wood_to_use = min(wood, wood_needed)
var items_produced = wood_to_use # 1 wood = 1 item always
wood -= wood_to_use
stock += items_produced
else:
break # Not enough wood for more whittle actions
# 3. Sell stock for currency - MATCHES tick_process.gd:34-58
var price_per_item = base_sale_price * sale_price_mod
# 3a. Wholesale selling (if unlocked) - matches tick_process.gd:36-42
# Sell ALL possible 100-item bundles at 1.2x price
if wholesale_unlocked:
while stock >= wholesale_size:
stock -= wholesale_size
currency += wholesale_size * price_per_item * wholesale_mult
# 3b. Regular selling - matches tick_process.gd:45-58
if stock > 0:
var purchase_rate = base_purchase_rate * purchase_rate_mod
var max_stock_to_sell = floor(purchase_rate)
# Always sell at least 1, up to the max
var actual_stock_to_sell = min(stock, max(1.0, max_stock_to_sell))
stock -= actual_stock_to_sell
currency += actual_stock_to_sell * price_per_item
ticks += 1
var success = currency >= 1000000.0
var result = {
"rank_targets": rank_targets,
"success": success,
"ticks": ticks if success else -1,
"final_currency": currency,
"time_formatted": format_time(ticks) if success else "Failed"
}
# Include purchase timeline if tracking was enabled
if track_purchases:
result["purchases"] = purchases
print("DEBUG: track_purchases=true, purchases.size()=%d" % purchases.size())
return result
func format_time(ticks: int) -> String:
var seconds = ticks
var minutes = seconds / 60
var hours = minutes / 60
if hours > 0:
return "%dh %dm %ds" % [hours, minutes % 60, seconds % 60]
elif minutes > 0:
return "%dm %ds" % [minutes, seconds % 60]
else:
return "%ds" % seconds
func generate_all_combinations(unlimited_scaling_cap: int = 5) -> Array[Dictionary]:
"""Generate combinations for ALL unlocks dynamically, respecting max_ranks from resource file
Args:
unlimited_scaling_cap: Maximum rank to test for unlocks with unlimited scaling (default: 5)
Lower values = faster testing, higher = more comprehensive
Cap=3: ~13K combos (~28 sec) | Cap=5: ~47K combos (~93 sec)
Cap=7: ~111K combos (~3.7min) | Cap=10: ~287K combos (~9.6min)
"""
var combinations: Array[Dictionary] = []
# Build constraint list from resource file
var unlock_constraints = []
for unlock in unlock_collection.unlocks:
var max_rank: int
if unlock.max_rank > 0:
max_rank = unlock.max_rank
elif not unlock.is_scaling:
max_rank = 1 # One-shot unlocks
else:
max_rank = unlimited_scaling_cap # Configurable cap for unlimited scaling
unlock_constraints.append({
"id": unlock.unlock_id,
"name": unlock.unlock_name,
"max_rank": max_rank
})
print("\n=== Generating Combinations ===")
print("Reading from resource file: %d unlocks" % unlock_constraints.size())
for c in unlock_constraints:
print(" - %s (ID %d): 0-%d ranks" % [c.name, c.id, c.max_rank])
# Recursive generation
_generate_combinations_recursive(unlock_constraints, 0, {}, combinations)
print("Generated %d total combinations" % combinations.size())
return combinations
func _generate_combinations_recursive(constraints: Array, index: int, current: Dictionary, output: Array):
"""Recursively generate all valid combinations"""
if index >= constraints.size():
# Skip all-zeros combination
if current.size() > 0:
output.append(current.duplicate())
return
var constraint = constraints[index]
for rank in range(constraint.max_rank + 1):
if rank > 0:
current[constraint.id] = rank
_generate_combinations_recursive(constraints, index + 1, current, output)
if rank > 0:
current.erase(constraint.id)
func serialize_unlock_data() -> Array:
"""Convert unlock collection to serializable data for threads"""
var unlock_data = []
for unlock in unlock_collection.unlocks:
unlock_data.append({
"unlock_id": unlock.unlock_id,
"unlock_name": unlock.unlock_name,
"base_cost": unlock.base_cost,
"is_scaling": unlock.is_scaling,
"max_rank": unlock.max_rank,
"cost_scaling_multiplier": unlock.cost_scaling_multiplier,
"effect_scaling_multiplier": unlock.effect_scaling_multiplier,
"cost_ladder": unlock.cost_ladder.duplicate() if unlock.cost_ladder.size() > 0 else [],
"base_modifiers": unlock.base_modifiers.duplicate()
})
return unlock_data
func run_comprehensive_test():
"""Test all combinations dynamically generated from resource file"""
print("\n=== Available Unlocks ===")
for unlock in unlock_collection.unlocks:
var max_rank_str = str(unlock.max_rank) if unlock.max_rank > 0 else "unlimited"
print("ID: %d | %s | Base Cost: %d | Scaling: %s | Max Rank: %s" % [
unlock.unlock_id,
unlock.unlock_name,
unlock.base_cost,
"Yes" if unlock.is_scaling else "No",
max_rank_str
])
print(" Modifiers: ", unlock.base_modifiers)
print("\n=== Global Constants ===")
print("Base Sale Price: %s" % Global.base_sale_price)
print("Base Purchase Rate: %s" % Global.base_purchase_rate)
print("Cost Per Whittle: %s" % Global.cost_per_whittle)
# Serialize unlock data for threads
var unlock_data = serialize_unlock_data()
# CACHE WARMUP: Pre-populate cache with common single-unlock states
print("\n=== Cache Warmup ===")
print("Pre-populating cache with common prefixes...")
for unlock in unlock_collection.unlocks:
var max_warmup_rank = 3
if unlock.max_rank > 0:
max_warmup_rank = min(unlock.max_rank, 3)
for rank in range(1, max_warmup_rank + 1):
var warmup_target = {unlock.unlock_id: rank}
simulate_rank_combination_pure(warmup_target, unlock_data, 1000000)
print("Cache warmup complete. Cache size: %d entries" % simulation_cache.size())
# Generate all combinations (configurable cap for unlimited scaling)
var unlimited_cap = 5 # Adjust this to test more/fewer ranks: 3=fast, 5=balanced, 7+=comprehensive
print("\n=== Generation Settings ===")
print("Unlimited scaling cap: %d ranks" % unlimited_cap)
var combinations = generate_all_combinations(unlimited_cap)
total_combinations = combinations.size()
print("\n=== Testing %d Combinations ===" % total_combinations)
# Fill task queue
task_queue.clear()
for combo in combinations:
task_queue.append({
"combo": combo,
"unlock_data": unlock_data
})
# Reset counters
completed_count = 0
all_results.clear()
threads_done = false
start_time = Time.get_ticks_msec()
last_progress_time = start_time
monitoring_active = true
# Create and start threads
print("Starting %d worker threads..." % num_threads)
for i in range(num_threads):
var thread = Thread.new()
thread.start(worker_thread.bind(i))
threads.append(thread)
print("All threads started, processing...")
func finish_processing():
"""Called when all processing is complete"""
print("\nAll combinations complete! Waiting for threads to finish...")
# Wait for all threads to finish
for thread in threads:
thread.wait_to_finish()
threads.clear()
threads_done = true
print("All threads finished. Processing results...")
var total_time = (Time.get_ticks_msec() - start_time) / 1000.0
# SAFETY CHECK: Verify result count matches
results_mutex.lock()
var actual_results = all_results.size()
results_mutex.unlock()
if actual_results != total_combinations:
print("WARNING: Result count mismatch! Expected %d, got %d" % [total_combinations, actual_results])
print("This indicates a threading issue where some results weren't flushed")
# Print results
print("\n=== RESULTS ===")
print("Total time: %.1f seconds" % total_time)
print("Total combinations tested: %d (expected %d)" % [actual_results, total_combinations])
# Cache statistics
var total_cache_checks = cache_hits + cache_misses
var cache_hit_rate = (float(cache_hits) / total_cache_checks * 100.0) if total_cache_checks > 0 else 0.0
cache_mutex.lock()
var cache_size = simulation_cache.size()
cache_mutex.unlock()
print("\n=== CACHE STATISTICS ===")
print("Cache hits: %d" % cache_hits)
print("Cache misses: %d" % cache_misses)
print("Hit rate: %.1f%%" % cache_hit_rate)
print("Cache entries stored: %d" % cache_size)
var successful = all_results.filter(func(r): return r.success)
print("Successful strategies: %d" % successful.size())
# Update UI status
status_label.text = "Status: Complete!"
progress_label.text = "Progress: 100%% (%d/%d)" % [all_results.size(), total_combinations]
progress_bar.value = 1.0
eta_label.text = "Total Time: %.1f seconds" % total_time
# Build results text for UI
var results_text = "[b]SIMULATION COMPLETE[/b]\n\n"
results_text += "[color=green]Total time: %.1f seconds[/color]\n" % total_time
results_text += "Combinations tested: %d\n" % all_results.size()
results_text += "Successful strategies: %d\n\n" % successful.size()
results_text += "[b]Cache Performance:[/b]\n"
results_text += " Hits: %d\n" % cache_hits
results_text += " Misses: %d\n" % cache_misses
results_text += " [color=cyan]Hit Rate: %.1f%%[/color]\n" % cache_hit_rate
results_text += " Entries: %d\n\n" % cache_size
if successful.size() > 0:
# Sort by ticks (fastest first)
successful.sort_custom(func(a, b): return a.ticks < b.ticks)
# Re-simulate top 10 with detailed purchase tracking
print("\n=== RE-SIMULATING TOP 10 WITH PURCHASE TRACKING ===")
var unlock_data = serialize_unlock_data()
var top_10_detailed: Array = []
for i in range(min(10, successful.size())):
var result = successful[i]
print("Re-simulating #%d with track_purchases=true..." % (i + 1))
var detailed_result = simulate_rank_combination_pure(result.rank_targets, unlock_data, 1000000, true)
print(" Result has purchases key: %s" % detailed_result.has("purchases"))
if detailed_result.has("purchases"):
print(" Purchases array size: %d" % detailed_result.purchases.size())
top_10_detailed.append(detailed_result)
print("\n=== TOP 10 FASTEST STRATEGIES (WITH PURCHASE TIMELINE) ===")
results_text += "[b]TOP 10 FASTEST STRATEGIES:[/b]\n\n"
for i in range(top_10_detailed.size()):
var result = top_10_detailed[i]
print("\n#%d: %s (%d ticks)" % [i + 1, result.time_formatted, result.ticks])
# Format ranks with unlock names
var rank_display = []
for unlock_id in result.rank_targets.keys():
var unlock_name = get_unlock_name_by_id(unlock_id)
var ranks = result.rank_targets[unlock_id]
rank_display.append("%s: %d" % [unlock_name, ranks])
print("Target Ranks: %s" % ", ".join(rank_display))
# Add to UI
results_text += "[color=yellow]#%d: %s (%d ticks)[/color]\n" % [i + 1, result.time_formatted, result.ticks]
results_text += " Ranks: %s\n" % ", ".join(rank_display)
results_text += " Currency: %.0f\n" % result.final_currency
# Add purchase timeline
if result.has("purchases") and result.purchases.size() > 0:
print("\nPurchase Timeline:")
results_text += " [b]Purchase Timeline:[/b]\n"
for purchase in result.purchases:
var time_str = format_time(purchase.tick)
print(" %s: %s Rank %d - Cost: %d¥ @ %s" % [
time_str, purchase.unlock_name, purchase.rank,
purchase.cost, time_str
])
results_text += "%s [color=cyan]%s Rank %d[/color] - %d¥ @ %s\n" % [
format_time(purchase.tick), purchase.unlock_name, purchase.rank,
purchase.cost, time_str
]
results_text += "\n"
else:
print("\nNo successful strategies found!")
results_text += "[color=red]No successful strategies found![/color]\n"
# Update results UI
results_label.text = results_text
func get_unlock_name_by_id(unlock_id: int) -> String:
"""Helper function to get unlock name by ID"""
for unlock in unlock_collection.unlocks:
if unlock.unlock_id == unlock_id:
return unlock.unlock_name
return "Unknown"
func _exit_tree():
# Clean up threads
monitoring_active = false
for thread in threads:
if thread.is_alive():
thread.wait_to_finish()

View file

@ -0,0 +1 @@
uid://bup76ad02kuse

View file

@ -1,8 +1,24 @@
class_name TickProcess
extends Node
# Dependency injection - can be overridden for simulation
var unlocks_provider: Node = null
var inventory_provider: Node = null
func _ready():
# Default to singletons if not explicitly set
if unlocks_provider == null:
unlocks_provider = Unlocks
if inventory_provider == null:
inventory_provider = Inventory
func set_providers(unlocks, inventory):
"""Set custom providers for simulation (bypasses singletons)"""
unlocks_provider = unlocks
inventory_provider = inventory
func tick():
Log.pr("Tick Process Ticking...")
# Log.pr("Tick Process Ticking...")
do_autowood()
do_whittling()
do_selling()
@ -11,10 +27,10 @@ func do_autowood():
# If the autowood unlock is unlocked then automatically gain wood based on the modifier
var autowood_unlock = Unlocks.get_unlock_by_id(Global.autowood_unlock_id)
if autowood_unlock and autowood_unlock.is_unlocked:
Log.pr("Autowood modifier", str(Unlocks.get_modifier_value("autowood_modifier")))
# Log.pr("Autowood modifier", str(Unlocks.get_modifier_value("autowood_modifier")))
var wood_to_gather = max(Unlocks.get_wood_per_click() * Unlocks.get_modifier_value("autowood_modifier"), 1)
Inventory.add_wood(wood_to_gather)
Log.pr("Auto-gathered", str(wood_to_gather), "wood via autowood unlock.")
# Log.pr("Auto-gathered", str(wood_to_gather), "wood via autowood unlock.")
func do_whittling():
# If there's more than 1 whole wood available, then whittle based on the efficiency modifier
@ -39,7 +55,7 @@ func do_selling():
Inventory.spend_stock(Global.wholesale_bundle_size)
var currency_earned = Global.wholesale_bundle_size * Unlocks.get_sale_price_per_item() * Global.wholesale_discount_multiplier
Inventory.add_currency(currency_earned)
Log.pr("Sold 100 whittled wood for", str(currency_earned), "currency via wholesale unlock.")
# Log.pr("Sold 100 whittled wood for", str(currency_earned), "currency via wholesale unlock.")
# If there's whittled wood available to sell, sell it for currency
@ -61,7 +77,7 @@ func do_selling():
func whittle_max_wood_possible():
# Get the items that can be produced per tick
var items_produced_per_tick = Unlocks.get_items_produced_per_tick()
Log.pr("Items produced per tick:", str(items_produced_per_tick))
# Log.pr("Items produced per tick:", str(items_produced_per_tick))
var wood_needed = ceil(items_produced_per_tick)
# Whittle as much wood as possible this tick, up to the max allowed by efficiency
@ -70,4 +86,4 @@ func whittle_max_wood_possible():
Inventory.spend_wood(wood_to_whittle)
Inventory.add_stock(actual_items_produced)
Log.pr("Whittled", str(wood_to_whittle), "wood into", str(actual_items_produced), "whittle wood.")
# Log.pr("Whittled", str(wood_to_whittle), "wood into", str(actual_items_produced), "whittle wood.")