def contour(self, **kwargs):
from pyswarms.utils import plotters
plotters.plot_contour(
pos_history=self.samples.points,
**kwargs
)
self.output.to_figure(structure=None, auto_filename="contour")
self.close()
def contour(self, **kwargs):
plotters.plot_contour(
pos_history=self.samples.points,
**kwargs
)
self.output.to_figure(structure=None, auto_filename="contour")
self.mat_plot_1d.figure.close()
def plotPositionHistory(self, optimizer, xLimits, yLimits, filename, xLabel, yLabel):
'''
:param optimizer: optimizer object returned in the application/definition of PSO
:param xLimits: numpy array (minLimit, maxLimit) of x Axis
:param yLimits: numpy array (minLimit, maxLimit) of y Axis
:param filename: name of filename returned by plot_contour (html gif)
:param xLabel: name of X axis
:param yLabel: name of Y axis
'''
try:
##code ref: https://www.tutorialfor.com/questions-83899.htm
d = Designer(limits=[xLimits, yLimits], label=[xLabel, yLabel])
pos = []
for i in range(config.ITERATIONS):
pos.append(optimizer.pos_history[i][:, 0:2])
animation = plot_contour(pos_history=pos,
designer=d)
plt.close(animation._fig)
html_file = animation.to_jshtml()
with open(filename, 'w') as f:
f.write(html_file)
except:
raise CustomError.ErrorCreationModel(config.ERROR_ON_PLOTTING)
def plotPositionHistory(optimizer, xLimits, yLimits, filename, xLabel, yLabel):
'''
:param optimizer: optimizer object returned in the application/definition of PSO
:param xLimits: numpy array (minLimit, maxLimit) of x Axis
:param yLimits: numpy array (minLimit, maxLimit) of y Axis
:param filename: name of filename returned by plot_contour (html gif)
:param xLabel: name of X axis
:param yLabel: name of Y axis
'''
try:
d = Designer(limits=[xLimits, yLimits], label=[xLabel, yLabel])
animation = plot_contour(pos_history=optimizer.pos_history, designer=d)
animation.save(filename, writer='ffmpeg', fps=10)
Image(url=filename)
plt.show()
except:
raise
#history of particle positions for animation hist = optimizer.pos_history #This can plot the cost history, not needed for the assignment: #plot_cost_history(optimizer.cost_history) #Mesh for the plot: m = Mesher(func=fx.sphere, limits=[(-1, 1), (-1, 1)]) #This can be used for designing the animation #but the defaults are enough for this task #d = Designer(limits=[(-1,1),(-1,1),(-0.1,1)], # label=["x-axis","y-axis","z-azis"]) animation = plot_contour(pos_history=hist, mesher=m, mark=(0, 0)) #3D version for fun: #pos_his_3D = m.compute_history_3d(hist) # anim3D = plot_surface(pos_history=pos_his_3D, # mesher=m, mark=(0,0,0)) #Shows the sphere animation, the code continues after the animation is closed: plt.show() #Same for a more interesting function Schaffer N.2 Objective function optimizer2 = ps.single.GlobalBestPSO(n_particles=50, dimensions=2, options=opt) optimizer2.optimize(fx.schaffer2, iters=100) hist2 = optimizer2.pos_history
def test_plot_contour_return_type(pos_history):
"""Tests if the animation function returns the expected type"""
assert isinstance(plot_contour(pos_history), FuncAnimation)
else:
y_plot[d, i * n_particles:(i + 1) * n_particles] = a[:, d]
for nd in range(0, n_dimensions):
if parameter_name[nd] == 'max_depth':
plt.scatter(x_plot[nd, :], (y_plot[nd, :] * 7 + 2))
else:
plt.scatter(x_plot[nd, :], y_plot[nd, :])
plt.title(parameter_name[nd])
plt.savefig("{}.png".format(parameter_name[nd]))
plt.close()
print("{0} saved as {1}.png".format(parameter_name[nd],
parameter_name[nd]))
d = Designer(limits=[(0, 50), (0, 5), (0, 1)], label=param_name)
#FFwriter = animation.FFMpegWriter()
anim = plot_contour(pos_history=optimizer.pos_history, designer=d)
anim.save('animation.html', fps=1)
#anim.save('animation.gif', writer='imagemagick', fps=1)
print("animation saved")
if (args.heatmap):
makeHeatMap("allIter", 0, n_iters, parameter_name, param_max_list,
optimizer.pos_history)
makeHeatMap("FirstTenIter", 0, 10, parameter_name, param_max_list,
optimizer.pos_history)
makeHeatMap("LastTenIter", n_iters - 10, n_iters, parameter_name,
param_max_list, optimizer.pos_history)
f_result = open("result.csv", "w")
keys = "{0},{1},{2},{3}".format("c1", "c2", "w", "cost")
for pos_name in param_name:
keys = keys + ",{}".format(pos_name)
x_min = -1 * np.ones(D)
bounds = (x_min, x_max)
options = {'c1': 0.3, 'c2': 0.1, 'w': 0.9}
optimizer = ps.single.GlobalBestPSO(n_particles=10,
dimensions=D,
options=options,
bounds=bounds)
# now run the optimization
cost, pos = optimizer.optimize(fx.rosenbrock, 100)
# print(optimizer.pos_history)
m = Mesher(func=fx.rosenbrock, limits=[(-1, 2), (-1, 2)])
d = Designer(limits=[(-1, 2), (-1, 2)], label=['x-axis', 'y-axis'])
animation = plot_contour(pos_history=optimizer.pos_history,
mesher=m,
designer=d)
animation.save('plot0.gif', writer='imagemagick', fps=20)
# pos_history_3d = m.compute_history_3d(optimizer.pos_history) # preprocessing
# animation = plot_surface(pos_history=pos_history_3d,
# mesher=m, designer=d,
# mark=(1, 1, 1))
# animation.save('plot0.gif', writer='imagemagick', fps=10)
# cost evolution vs iterations
plot_cost_history(cost_history=optimizer.cost_history)
plt.show()
# Import modules
import matplotlib.pyplot as plt
import numpy as np
from problema import *
# Import PySwarms
import pyswarms as ps
from pyswarms.utils.functions import single_obj as fx
from pyswarms.utils.plotters import (plot_cost_history, plot_contour,
plot_surface)
options = {'c1': 0.5, 'c2': 0.3, 'w': 0.9}
optimizer = ps.single.GlobalBestPSO(n_particles=50,
dimensions=2,
options=options)
cost, pos = optimizer.optimize(funcao_objetivo, iters=100)
from pyswarms.utils.plotters.formatters import Mesher
m = Mesher(func=fx.sphere)
animation = plot_contour(pos_history=optimizer.pos_history,
mesher=m,
mark=(0, 0))
animation.save('plot0.gif', writer='imagemagick', fps=10)
# Perform optimization of the sphere function
# https://pyswarms.readthedocs.io/en/latest/api/pyswarms.utils.functions.html
cost, pos = optimizer.optimize(fx.sphere, iters=100)
# Plot the cost history
from pyswarms.utils.plotters import (plot_cost_history, plot_contour, plot_surface)
plot_cost_history(cost_history=optimizer.cost_history)
plt.show()
# Initialize mesher with sphere function
from pyswarms.utils.plotters.formatters import Mesher
m = Mesher(func=fx.sphere)
# Make animation
animation2d = plot_contour(pos_history=optimizer.pos_history, # Use the cost_history we computed
mesher=m, # Customizations
mark=(0,0)) # Mark minima
# Enables us to view it in a Jupyter notebook
animation2d.save('plot0.gif', writer='imagemagick', fps=10)
Image(url='plot0.gif')
# Obtain a position-fitness matrix using the Mesher.compute_history_3d()
# method. It requires a cost history obtainable from the optimizer class
pos_history_3d = m.compute_history_3d(optimizer.pos_history)
# Make a designer and set the x,y,z limits to (-1,1), (-1,1) and (-0.1,1) respectively
from pyswarms.utils.plotters.formatters import Designer
d = Designer(limits=[(-1,1), (-1,1), (-0.1,1)], label=['x-axis', 'y-axis', 'z-axis'])
# Make animation
