Adds an event to the queue.

Performs DNA crossover between two parents. # Arguments `parent1` - First parent DNA `parent2` - Second parent DNA `alpha` - Crossover ratio (0 = al

Reduces the organism's energy. # Arguments `amount` - Energy to subtract

Chooses the appropriate mutation strategy based on parameters. If use_targeted is true and brain is a transformer, uses targeted mutation. Otherwise,

Calculates fitness value for breeding selection. Fitness combines survival time (age), combat success (score), and movement (distance). This creates e

Advances the simulation by one timestep with parallel organism updates.

Get a distinct color for each genetic pool matching the organism rendering colors

Mutates a DNA vector with periodic wrapping. # Arguments `dna` - DNA vector to mutate (modified in place) `mutation_rate` - Standard deviation of Ga

Mutates all parameters in the brain.

Updates projectile position based on velocity and time delta. # Arguments `dt` - Time delta since last update

Clears all events

Inferno colormap similar to matplotlib's inferno Maps a value from 0.0 to 1.0 to a color from dark purple/black to yellow/white

Saves the ecosystem state to a JSON file.

Adds a new event to the log

Helper function to build a KD-tree from a collection of items.

Helper function to draw a weight matrix as a colored grid

Increases the organism's energy up to a maximum. # Arguments `amount` - Energy to add `max_energy` - Maximum energy cap

Checks if the organism is alive. # Returns `true` if energy > 0, `false` otherwise.

Checks if this food item has been fully consumed. # Returns `true` if energy is <= 0, `false` otherwise.

Calculates the minimum distance between a line segment and a circle center. # Arguments `line_start` - Starting point of the line segment `line_end`

Spawns new organisms through evolution when population is below target. # Arguments `params` - Simulation parameters `dt` - Delta time in seconds (sp

Flattens all weights and biases into a single vector.

Wraps a position vector around the simulation box boundaries (toroidal topology). # Arguments `v` - Mutable position vector to wrap `box_width` - Wi

Calculates the neural network layer sizes based on simulation parameters.

Returns a reference to the elite pool.

Calculates vision ray directions based on evolved vision parameters. # Returns Vector of vision ray endpoints relative to organism position.

Process all senses and return combined brain inputs. # Arguments `organism` - The organism doing the sensing `ecosystem` - The current state of the

Query organisms within a radius. # Arguments `pos` - Center position for the query `radius` - Search radius (will be squared internally) # Returns

Returns a random position within a cluster belonging to a specific pool. Regenerates clusters if they're empty (e.g., after loading from file).

Samples a mutation scale using logarithmic random distribution.

Spawns a new organism through evolution. # Arguments `generation` - Current generation number `target_pool_id` - Genetic pool for the new organism `

Updates the elite pool with living organisms. Keeps only the top N scorers ever seen across all time.

Applies all queued events to the ecosystem state.

Returns references to the trees as a `SpatialTrees` struct.

Number of asexual deaths tracked

Returns the type of brain architecture.

Checks if the organism can attack (cooldown expired). # Returns `true` if attack cooldown <= 0, `false` otherwise.

Creates a shallow clone of the organism without cloning brain weights. The brain is replaced with an empty dummy brain with minimal memory allocation.

Marks this food as consumed by setting energy to 0.

Calculates the Euclidean distance between two brains. Only works if both brains are the same architecture type.

Drains all events from the queue.

Draws a transparent panel showing recent events

Draws lines between organisms that are interacting (energy sharing or reproduction).

Visualizes transformer architecture with weight heatmaps

Returns all events, newest first

Executes all actions extracted from brain output. # Arguments `entity` - The organism executing actions `brain_outputs` - Neural network outputs `ne

Executes attack action (projectile shooting). # Arguments `entity` - The organism attacking `attack_strength` - Attack strength from brain output `p

Executes energy sharing action. # Arguments `entity` - The organism sharing energy `share_amount` - Amount to share from brain output `neighbors` -

Executes food consumption for all nearby food items. # Arguments `entity` - The organism consuming food `neighbor_foods` - List of nearby food indic

Executes movement action for an organism. # Arguments `entity` - The organism to move `velocity_control` - Desired velocity from brain output (contr

Executes movement rotation action for an organism. # Arguments `entity` - The organism to rotate `rotation` - Rotation amount from brain output `par

Executes vision rotation action for an organism. Vision rotation is now relative to body rotation - the neural network controls the offset angle betw

Finds the nearest organism within reproduction radius for sexual reproduction. # Arguments `entity` - The organism looking to reproduce `neighbors`

Finds the nearest organism within sharing radius. # Arguments `entity` - The organism looking to share `neighbors` - List of nearby organism indices

We can work with them through the trait

Get a distinct color for each genetic pool

Handles mouse wheel zoom centered on cursor position

Number of inter-pool deaths tracked

Checks if the projectile has exceeded its maximum range. # Returns `true` if the projectile should be removed, `false` otherwise.

Kills the organism by setting energy to 0.

Mutates the brain using targeted mutations for transformers. For transformers: randomly selects a specific component (input embedding, a specific bloc

Query food within a radius.