f98773237e
Adds tree fading based on camera line of sight. Trees now fade out when they obstruct the player's view, improving visibility. Also includes several fixes: - Fixes tree distribution. - Adds a see-through shader. - Adds camera and occlusion scripts.
74 lines
2.6 KiB
GDScript
74 lines
2.6 KiB
GDScript
class_name MapPopulationClass
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extends Node
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var map_data: Array = Global.map_data
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## Generate the CellDataResource for a given cell
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## Setup the X and Z
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## If it's a path or water we do nothing else for now
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## If it's anything else then we need to:
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## Set grass density directly from the vegetation density
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## Then do the following:
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## Density < 0.5 - chance of spawning special stuff and nothing else
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## Density > 0.6 - add trees, varying quantity from 0.6 to 1
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## Density 0.1 to 0.6 - add bushes, varying quantity TBD
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## Density 0.1 to 0.4 - add flowers, varying quantity TBD
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# Pre-calculate tree distribution for the cell
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static func generate_cell_with_distribution(x: int, z: int, density: float, path: bool = false, water: bool = false, camp: bool = false):
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var cell_data = CellDataResource.new()
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cell_data.x = x
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cell_data.z = z
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cell_data.vegetation_density = density
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cell_data.camp = camp
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if not (path or water or camp):
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if density >= 0.6:
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var tree_preferences = BiomeData.calculate_tree_probabilities(x, z)
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var tree_distribution = calculate_tree_distribution(tree_preferences, density)
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# Add trees based on calculated distribution
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for tree_type in tree_distribution.keys():
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var quantity = tree_distribution[tree_type]["quantity"]
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var resource = tree_distribution[tree_type]["resource"].duplicate()
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if quantity > 0:
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cell_data.add_trees(resource, quantity)
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Global.map_data[x][z] = cell_data
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# Calculate how many of each tree type to spawn
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static func calculate_tree_distribution(tree_preferences: Dictionary, density: float) -> Dictionary:
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var distribution = {}
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if tree_preferences.is_empty():
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return distribution
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# Calculate total number of trees for this cell
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var total_trees = int((density / 5) * 10) + randi_range(1, 2)
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#var total_trees = int((density - 0.6) * 25) + randi_range(3, 8)
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# Normalize the chances to get proportions
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var total_weight = 0.0
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for tree_name in tree_preferences.keys():
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total_weight += tree_preferences[tree_name]["chance"]
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if total_weight <= 0.0:
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return distribution
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# Distribute trees based on weighted probabilities
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for tree_name in tree_preferences.keys():
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var proportion = tree_preferences[tree_name]["chance"] / total_weight
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var base_quantity = int(total_trees * proportion)
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# Add some randomness - chance to get +1 tree based on remainder
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var remainder = (total_trees * proportion) - base_quantity
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if randf() < remainder:
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base_quantity += 1
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if base_quantity > 0:
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distribution[tree_name] = {
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"quantity": base_quantity,
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"resource": tree_preferences[tree_name]["resource"]
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}
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return distribution
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