Python plot Examples

Example #1

File: test_convergence.py Project: gugarosa/opytimizer

def test_convergence_plot():
    agent_pos = [[0.5, 0.4, 0.3], [0.5, 0.4, 0.3]]

    try:
        convergence.plot(agent_pos[0], agent_pos[1], labels=1)
    except:
        convergence.plot(agent_pos[0], agent_pos[1], labels=["agent[0]", "agent[1]"])

    try:
        convergence.plot(agent_pos[0], agent_pos[1], labels=["agent[0]"])
    except:
        convergence.plot(agent_pos[0], agent_pos[1])

Example #2

def test_convergence_plot():
    new_history = history.History()

    new_history.load('models/test.pkl')

    agents = new_history.get(key='agents', index=(0, 0))

    try:
        convergence.plot(agents[0], agents[1], labels=1)
    except:
        convergence.plot(agents[0], agents[1], labels=['agent[0]', 'agent[1]'])

    try:
        convergence.plot(agents[0], agents[1], labels=['agent[0]'])
    except:
        convergence.plot(agents[0], agents[1])

Example #3

File: convergence_plotting.py Project: ibrahim85/opytimizer

import opytimizer.visualization.convergence as c

# Defines agent's position and fitness
agent_pos = [[0.5, 0.4, 0.3], [0.5, 0.4, 0.3]]
agent_fit = [0.5, 0.32, 0.18]

# Defines best agent's position and fitness
best_agent_pos = [[0.01, 0.005, 0.0001], [0.01, 0.005, 0.0001]]
best_agent_fit = [0.0002, 0.00005, 0.00002]

# Plotting the convergence of agent's positions
c.plot(agent_pos[0],
       agent_pos[1],
       labels=['$x_0$', '$x_1$'],
       title='Sphere Function: $x^2 \mid x \in [-10, 10]$',
       subtitle='Agent: 0 | Algorithm: Particle Swarm Optimization')

# Plotting the convergence of best agent's positions
c.plot(best_agent_pos[0],
       best_agent_pos[1],
       labels=['$x^*_0$', '$x^*_1$'],
       title='Sphere Function: $x^2 \mid x \in [-10, 10]$',
       subtitle="Agent: Best | Algorithm: Particle Swarm Optimization")

# Plotting the convergence of agent's and best agent's fitness
c.plot(agent_fit,
       best_agent_fit,
       labels=['$f(x)$', '$f(x^{*})$'],
       title='Sphere Function: $x^2 \mid x \in [-10, 10]$',
       subtitle="Agents: 0 and Best | Algorithm: Particle Swarm Optimization")

Example #4

File: convergence_plotting.py Project: gugarosa/opytimizer

import opytimizer.visualization.convergence as c

# Defines agent's position and fitness
agent_pos = [[0.5, 0.4, 0.3], [0.5, 0.4, 0.3]]
agent_fit = [0.5, 0.32, 0.18]

# Defines best agent's position and fitness
best_agent_pos = [[0.01, 0.005, 0.0001], [0.01, 0.005, 0.0001]]
best_agent_fit = [0.0002, 0.00005, 0.00002]

# Plotting the convergence of agent's positions
c.plot(
    agent_pos[0],
    agent_pos[1],
    labels=["$x_0$", "$x_1$"],
    title="Sphere Function: $x^2 \mid x \in [-10, 10]$",
    subtitle="Agent: 0 | Algorithm: Particle Swarm Optimization",
)

# Plotting the convergence of best agent's positions
c.plot(
    best_agent_pos[0],
    best_agent_pos[1],
    labels=["$x^*_0$", "$x^*_1$"],
    title="Sphere Function: $x^2 \mid x \in [-10, 10]$",
    subtitle="Agent: Best | Algorithm: Particle Swarm Optimization",
)

# Plotting the convergence of agent's and best agent's fitness
c.plot(
    agent_fit,