def callback(population):
plot = pv.Plot(xrange=[0, 10], yrange=[0, 10])
pts = [[each[1][0].value, each[1][1].value] for each in population]
#pts = [ pv.Point(each[1][0],each[1][1]) for each in population ]
#print pts
plot.points(pts)
plot.show(delay=10)
def plotConvergence(self):
plot = pv.Plot(title="Population Statistics",xlabel="Iteration",ylabel="Score")
data = [ [i,self.bests[i]] for i in range(len(self.bests)) ]
plot.lines(data,width=3,color='green')
data = [ [i,self.history[i]] for i in range(len(self.bests)) ]
plot.points(data,shape=16,color='blue',size=2)
data = [ [i,self.worsts[i]] for i in range(len(self.bests)) ]
plot.lines(data,width=3,color='red')
return plot
def testPlot(self):
roc = pv.ROC(self.match, self.nonmatch, is_distance=True)
plot = pv.Plot()
roc.plot(plot, method=ROC_PRECISE_SAMPLED, color="red", width=5)
roc.plot(plot, method=ROC_PRECISE_ALL, color='black')
plot.lines([[0, 1], [1, 0]])
eer = roc.getEER()
plot.point([eer, 1 - eer])
plot.asImage()
def addIndividual(self,score,args,kwargs,ilog=None):
# This try block allows multiple values to be returned by the fitness function.
# Everything except the score will be stored in extra and should be picklible.
extras = []
try:
extras = score[1:]
score = score[0]
except:
# this means score must be a single value
pass
if not np.isfinite(score):
return
if score < self.best_score:
self.best_score = score
if ilog != None:
# Print data
print "New Best Score:",score
for i in range(len(args)):
print " arg%02d"%i,args[i]
keys = list(kwargs.keys())
keys.sort()
for key in keys:
print " %10s:"%key,kwargs[key]
self.population.append([score,args,kwargs])
self.population.sort(lambda x,y: cmp(x[0],y[0]))
self.population = self.population[:self.population_size]
self.history.append(score)
self.bests.append(self.population[0][0])
self.worsts.append(self.population[-1][0])
self.iter += 1
if ilog != None:
self.printPopulation()
ilog.pickle([score,args,kwargs],"Fitness_%0.8f"%score)
for i in xrange(len(extras)):
extra = extras[i]
if isinstance(extra,pv.Image):
ilog(extra,"extra_%02d_%0.8f"%(i,score))
else:
ilog.pickle(extra,"extra_%02d_%0.8f"%(i,score))
if self.iter % 25 == 0:
plot = pv.Plot(title="Population Statistics",xlabel="Iteration",ylabel="Score")
data = [ [i,self.bests[i]] for i in range(len(self.bests)) ]
plot.lines(data,width=3,color='green')
data = [ [i,self.history[i]] for i in range(len(self.bests)) ]
plot.points(data,shape=16,color='blue',size=2)
data = [ [i,self.worsts[i]] for i in range(len(self.bests)) ]
plot.lines(data,width=3,color='red')
ilog(plot,"PopulationData")
def createData():
data = np.random.normal(size=(20, 3))
mult = np.random.normal(size=(3, 3))
data = np.dot(data, mult)
xy = pv.Plot(title="X vs Y", x_range=(-5, 5), y_range=(-5, 5))
xy.points(data[:, [0, 1]])
xy.show(window='X vs Y', delay=1)
xy = pv.Plot(title="X vs Z",
x_range=(-5, 5),
y_range=(-5, 5),
ylabel="Z Axis")
xy.points(data[:, [0, 2]])
xy.show(window='X vs Z')
print(repr(data))
return data
def callback(population):
plot = pv.Plot(x_range=[0, 10], y_range=[0, 10], title='Search Space')
plot.point(pv.Point(3, 4), size=20, shape=16, color='gray')
plot.point(pv.Point(8, 2), size=10, shape=16, color='gray')
plot.point(pv.Point(5, 9), size=40, shape=16, color='gray')
pts = [[each[1][0].value, each[1][1].value] for each in population]
#pts = [ pv.Point(each[1][0],each[1][1]) for each in population ]
#print pts
plot.points(pts, color='red')
plot.show(delay=10, window='Search Space')
def addIndividual(self, score, args, kwargs, ilog=None):
if score == np.inf:
return
if score < self.best_score:
self.best_score = score
if ilog != None:
# Print data
print "New Best Score:", score
for i in range(len(args)):
print " arg%02d" % i, args[i]
keys = list(kwargs.keys())
keys.sort()
for key in keys:
print " %10s:" % key, kwargs[key]
self.population.append([score, args, kwargs])
self.population.sort(lambda x, y: cmp(x[0], y[0]))
self.population = self.population[:self.population_size]
self.history.append(score)
self.bests.append(self.population[0][0])
self.worsts.append(self.population[-1][0])
self.iter += 1
if ilog != None:
self.printPopulation()
ilog.pickle([score, args, kwargs], "Fitness_%0.8f" % score)
if self.iter % 25 == 0:
plot = pv.Plot(title="Population Statistics",
xlabel="Iteration",
ylabel="Score")
data = [[i, self.bests[i]] for i in range(len(self.bests))]
plot.lines(data, width=3, color='green')
data = [[i, self.history[i]] for i in range(len(self.bests))]
plot.points(data, shape=16, color='blue', size=2)
data = [[i, self.worsts[i]] for i in range(len(self.bests))]
plot.lines(data, width=3, color='red')
ilog(plot, "PopulationData")
'''
Created on Oct 17, 2010
@author: bolme
'''
import pyvision as pv
import numpy as np
if __name__ == "__main__":
ilog = pv.ImageLog()
plot = pv.Plot(size=(600, 600),
title="Test Plot 1",
xrange=(0, 25),
yrange=(0, 25))
plot.label([0, 25], "Shapes (Size=7)", align='right')
for i in range(0, 26):
plot.point((i, 24), shape=i, size=7, color='red')
plot.label([0, 23], "Shapes (Size=5)", align='right')
for i in range(0, 26):
plot.point((i, 22), shape=i, size=5, color='red')
plot.label([0, 21], "Shapes (Size=3)", align='right')
for i in range(0, 26):
plot.point((i, 20), shape=i, size=3, color='red')
plot.label([0, 19], "Upper Case Alphabet Large (Size=7)", align='right')
for i in range(0, 26):
import pyvision as pv
ilog = pv.ImageLog()
im = pv.Image("baboon.jpg")
ilog(im,"Baboon")
table = pv.Table()
table[1,"image"] = im.filename
table[1,"width"] = im.size[0]
table[1,"height"] = im.size[1]
ilog(table,"ImageData")
print(table)
plot = pv.Plot(title="Some Dots and Lines");
plot.points([[3.5,7.1],[1,1],[5.5,2]],shape=2)
plot.lines([[5.5,7.5],[2,3],[3.3,7]])
ilog(plot,"MyPlot")
ilog.show()
def callback(population):
plot = pv.Plot(x_range=[0, 10], y_range=[0, 10])
pts = [[each[1][0].value, each[1][1].value] for each in population]
plot.points(pts)
