PyCafe - Dash - 3D Swarm of Fish Simulation

app.py
bubble_animation.js
requirements.txt
app.py
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import dash
from dash import dcc, html
from dash.dependencies import Input, Output, State
import plotly.graph_objs as go
import numpy as np

# Initialize the Dash app
app = dash.Dash(__name__)

# Initial parameters
initial_num_fish = 50
initial_velocity = 0.1
num_fish = initial_num_fish
velocity = initial_velocity

# Initialize fish positions and velocities
positions = np.random.rand(num_fish, 3) * 10
velocities = (np.random.rand(num_fish, 3) - 0.5) * velocity

# Define the layout of the app
app.layout = html.Div([
    html.H1("3D Swarm of Fish Simulation", style={'textAlign': 'center'}),
    html.Div([
        html.Label("Number of Fish:"),
        dcc.Slider(
            id='num-fish-slider', 
            min=10, max=1000, step=1, value=initial_num_fish, 
            marks={i: str(i) for i in range(10, 1001, 100)}
        ),
        html.Label("Fish Velocity:"),
        dcc.Slider(
            id='velocity-slider', 
            min=0.01, max=1, step=0.01, value=initial_velocity, 
            marks={i/100: str(i/100) for i in range(1, 101, 10)}
        ),
    ], style={'margin': '0 20px'}),
    dcc.Graph(id='fish-graph'),
    dcc.Interval(id='interval-component', interval=100, n_intervals=0)
], style={'margin': '0', 'padding': '0'})

# Function to update fish positions
def update_positions():
    global positions, velocities, num_fish, velocity
    positions += velocities
    # Simple boundary conditions
    for i in range(num_fish):
        for j in range(3):
            if positions[i, j] > 10:
                positions[i, j] = 10
                velocities[i, j] *= -1
            elif positions[i, j] < 0:
                positions[i, j] = 0
                velocities[i, j] *= -1

# Define the callback to update the graph
@app.callback(
    Output('fish-graph', 'figure'),
    [Input('interval-component', 'n_intervals')],
    [State('num-fish-slider', 'value'), State('velocity-slider', 'value')]
)
def update_graph(n, new_num_fish, new_velocity):
    global positions, velocities, num_fish, velocity

    if new_num_fish != num_fish:
        num_fish = new_num_fish
        positions = np.random.rand(num_fish, 3) * 10
        velocities = (np.random.rand(num_fish, 3) - 0.5) * new_velocity
    if new_velocity != velocity:
        velocity = new_velocity
        velocities = (np.random.rand(num_fish, 3) - 0.5) * new_velocity

    update_positions()
    
    scatter = go.Scatter3d(
        x=positions[:, 0],
        y=positions[:, 1],
        z=positions[:, 2],
        mode='markers',
        marker=dict(size=5, color=['red'] + ['blue'] * (num_fish - 1))  # First fish is red, others are blue
    )
    layout = go.Layout(
        scene=dict(
            xaxis=dict(range=[0, 10], color='white', showbackground=False, gridcolor='white', zerolinecolor='white'),
            yaxis=dict(range=[0, 10], color='white', showbackground=False, gridcolor='white', zerolinecolor='white'),
            zaxis=dict(range=[0, 10], color='white', showbackground=False, gridcolor='white', zerolinecolor='white'),
            bgcolor='rgb(0, 0, 50)'
        ),
        margin=dict(l=0, r=0, b=0, t=0),
        paper_bgcolor='rgb(0, 0, 50)'
    )
    return {'data': [scatter], 'layout': layout}

# Run the app
if __name__ == '__main__':
    app.run_server(debug=True)
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3D Swarm of Fish Simulation - Dash
