if app.network.f == None:
p = factory.create('org.inviwo.FloatSliderTest', ivec2(75, -25))
p.identifier = "f"
network.addProcessor(p)
app.network.i.prop1.minValue = -10
app.network.i.prop1.maxValue = 10
app.network.f.prop1.minValue = -1
app.network.f.prop1.maxValue = 1
app.network.f.prop1.increment = 0.2
s = ""
for i in app.network.i.prop1.foreach(-3, 8):
s += str(i) + " "
qt.update()
print(s)
s = ""
for i in app.network.i.prop1.foreach(-3, 8, 2):
s += str(i) + " "
qt.update()
print(s)
for p in [app.network.i.prop1, app.network.f.prop1]:
s = ""
for i in p:
s += str(i) + " "
qt.update()
print(s)
import math
import time
import ivw.regression
import ivw.camera
steps = 50
network = inviwopy.app.network
m = ivw.regression.Measurements()
for g in range(0, 2):
isGauss = g == 0
network.ImageLowPass.gaussian.value = isGauss
name = "Gaussian-" if isGauss else "Box-"
r = [1, 3, 5, 10, 15, 30, 32] if isGauss else [1, 2, 3, 5, 11, 17, 32, 60]
p = network.ImageLowPass.sigma if isGauss else network.ImageLowPass.kernelSize
for size in r:
start = time.clock()
p.value = size
inviwoqt.update()
ivw.regression.saveCanvas(network.Lowpass,
name + str(size) + "x" + str(size))
end = time.clock()
m.addFrequency(name + 'time-' + str(size) + "x" + str(size),
end - start)
m.save()
def update():
try:
from inviwopy import qt
qt.update()
except:
pass