def test_reconstruction():
im = get_example_data('image0003')
rec = propagate(im, 4e-6)
verify(rec, 'recon_single')
rec = propagate(im, [4e-6, 7e-6, 10e-6])
verify(rec, 'recon_multiple')
def test_propagate_0_distance():
im = get_example_data('image0003')
rec = propagate(im, 0)
# propagating no distance should leave the image unchanged
assert_obj_close(im, rec)
rec = propagate(im, [0, 3e-6])
verify(rec, 'recon_multiple_with_0')
def slideZ(self, value):
#using reconstructions-- better to use electric field?
'''
When z is changed, instead of recomputing the hologram, we
use the shortcut of reconstructing the last computed hologram.
'''
source = self.sender()
start = time.time()
if self.lastZ == self.lcd3.value():
self.holo = self.lastholo
if self.lastZ < self.lcd3.value():
self.holo = self.lastholo
self.warning.setText(
'Press calculate once you have all your parameters set')
if self.lastZ > self.lcd3.value(
): #reconstructing a plane between hologram and object
self.holo = np.abs(
propagate(self.lastholo, -self.lcd3.value() + self.lastZ))
self.warning.setText('Reconstruction: hologram is approximate')
end = time.time()
#now take only the part that you want to display
x = round(self.sld.value())
y = round(self.sld2.value())
selection = self.holo[256 - x:512 - x, 256 - y:512 - y]
im = scipy.misc.toimage(selection) #PIL image
#https://github.com/shuge/Enjoy-Qt-Python-Binding/blob/master/image/display_img/pil_to_qpixmap.py
#myQtImage = ImageQt(im)
#qimage = QtGui.QImage(myQtImage)
if im.mode == "RGB":
pass
elif im.mode == "L":
im = im.convert("RGBA")
data = im.tostring('raw', "RGBA")
qim = QtGui.QImage(data, 256, 256, QtGui.QImage.Format_ARGB32)
pixmap = QtGui.QPixmap.fromImage(qim)
myScaledPixmap = pixmap.scaled(QtCore.QSize(400, 400))
self.label.setPixmap(myScaledPixmap)
#self.label.setGeometry(10, 10, 400, 400)
#self.label.setScaledContents(True)
self.timer.setGeometry(420, 400, 150, 30)
self.timer.setText('Calc. Time: ' + str(round(end - start, 4)) + ' s')
self.timer.setAlignment(QtCore.Qt.AlignBottom | QtCore.Qt.AlignCenter)
sphere2 = Sphere(n=self.lcd5.value() + .0001j,
r=self.lcd4.value(),
center=(self.lcd.value(), self.lcd2.value(),
self.lcd3.value()))
self.sphObject.setText(repr(sphere2))
def slideZ(self, value):
# using reconstructions-- better to use electric field?
"""
When z is changed, instead of recomputing the hologram, we
use the shortcut of reconstructing the last computed hologram.
"""
source = self.sender()
start = time.time()
if self.lastZ == self.lcd3.value():
self.holo = self.lastholo
if self.lastZ < self.lcd3.value():
self.holo = self.lastholo
self.warning.setText("Press calculate once you have all your parameters set")
if self.lastZ > self.lcd3.value(): # reconstructing a plane between hologram and object
self.holo = abs(propagate(self.lastholo, -self.lcd3.value() + self.lastZ))
self.warning.setText("Reconstruction: hologram is approximate")
end = time.time()
# now take only the part that you want to display
x = round(self.sld.value())
y = round(self.sld2.value())
selection = self.holo[256 - x : 512 - x, 256 - y : 512 - y]
im = toimage(selection) # PIL image
# https://github.com/shuge/Enjoy-Qt-Python-Binding/blob/master/image/display_img/pil_to_qpixmap.py
# myQtImage = ImageQt(im)
# qimage = QtGui.QImage(myQtImage)
if im.mode == "RGB":
pass
elif im.mode == "L":
im = im.convert("RGBA")
data = im.tostring("raw", "RGBA")
qim = QtGui.QImage(data, 256, 256, QtGui.QImage.Format_ARGB32)
pixmap = QtGui.QPixmap.fromImage(qim)
myScaledPixmap = pixmap.scaled(QtCore.QSize(400, 400))
self.hologram.setPixmap(myScaledPixmap)
# self.hologram.setGeometry(10, 10, 400, 400)
# self.hologram.setScaledContents(True)
self.timer.setGeometry(420, 400, 150, 30)
self.timer.setText("Calc. Time: " + str(round(end - start, 4)) + " s")
self.timer.setAlignment(QtCore.Qt.AlignBottom | QtCore.Qt.AlignCenter)
sphere2 = Sphere(
n=self.lcd5.value() + 0.0001j,
r=self.lcd4.value(),
center=(self.lcd.value(), self.lcd2.value(), self.lcd3.value()),
)
self.sphObject.setText(repr(sphere2))
def test_propagate_e_field():
e = calc_field(detector_grid(100, 0.1),
Sphere(1.59, .5, (5, 5, 5)),
illum_wavelen=0.66,
medium_index=1.33,
illum_polarization=(1, 0),
theory=Mie(False))
prop_e = propagate(e, 10)
verify(prop_e, 'propagate_e_field')
def slideZ(self, sphere, schema):
'''
When z is changed, and reconstruction is selected, do reconstruction.
'''
if sphere.parameters == self.oldReconParameters and repr(schema) == repr(self.oldReconSchema):
self.holo = self.oldReconHolo
else:
start = time.time()
if self.lastZ == self.lcd3.value():
self.holo = self.lastholo
if self.lastZ < self.lcd3.value():
self.holo = self.lastholo
self.warning.setText('Cannot reconstruct to larger z')
if self.lastZ > self.lcd3.value(): #reconstructing a plane between hologram and object
self.holo = np.abs(propagate(self.lastholo, -self.lcd3.value()+self.lastZ))
self.warning.setText('Reconstruction: hologram is approximate')
end = time.time()
self.oldReconHolo = self.holo
self.oldReconParameters = sphere.parameters
self.oldReconSchema = schema
from numpy import linspace
import holopy as hp
from holopy.core import Optics
from holopy.propagation import propagate
from holopy.core.tests.common import get_example_data
from holopy.core import load
#holo = get_example_data('image0001.yaml')
#rec_vol = propagate(holo, linspace(4e-6, 10e-6, 7))
#hp.show(rec_vol)
optics = hp.core.Optics(wavelen=.660, index=1.33,
polarization=[1.0, 0.0])
holo = hp.core.load('newredblood2.png',spacing=7.6,optics=optics)
rec_vol = propagate(holo, linspace(1e-3,5e-2,100))
hp.show(holo)
hp.show(rec_vol)
def test_gradient_filter():
im = get_example_data('image0003')
rec = propagate(im, [4e-6, 7e-6, 10e-6], gradient_filter=1e-6)
verify(rec, 'recon_multiple_gradient_filter')
import matplotlib.pyplot as plt
import numpy as np
from mpl_toolkits.mplot3d import Axes3D
lamb=0.632
ind=1
#one='withObject1.png'
img='holoTest.png'
#two='withoutObject1.png'
pixels=6.8
optics = hp.core.Optics(lamb, ind,
polarization=[1.0, 0.0])
holo = hp.load(img, spacing = pixels, optics = optics)
rec_vol = propagate(holo, linspace(0.01, 1, 7))
a=rec_vol.real
xSize=rec_vol.shape[0]
ySize=rec_vol.shape[1]
zSize=rec_vol.shape[2]
x=[i for i in xrange(xSize)]
y=[i for i in xrange(ySize)]
def slices(b):
z=[]
for i in x:
for j in y:
z.append(a[i][j][b])
from numpy import linspace
import holopy as hp
from holopy.core import Optics
from holopy.propagation import propagate
from holopy.core.tests.common import get_example_data
from holopy.core import load
holo = get_example_data('image0001.yaml')
rec_vol = propagate(holo, linspace(4e-6, 10e-6, 7))
hp.show(rec_vol)
from __future__ import print_function
import numpy as np
import holopy as hp
from holopy.propagation import propagate
from holopy.core import load
import matplotlib.pyplot as plt
import time
optics = hp.core.Optics(wavelen=0.405, index=1.33, polarization=[1.0, 0.0])
holo = load("jerichoObject.bmp", spacing=6e-6, optics=optics)
bg = load("jerichoRef.bmp", spacing=6e-6, optics=optics)
holo = holo - bg
rec_vol = propagate(holo, np.linspace(245e-6, 250e-6, 5))
plt.ion()
fig = plt.figure()
ax = fig.gca()
for i in xrange(rec_vol.shape[2]):
print(i)
# name='figure%d.png'%(i,)
# plt.savefig(name,bbox_inches=0)
plt.clf()
plt.imshow(rec_vol[..., i].real, cmap=plt.cm.Greys_r)
fig.canvas.draw()
time.sleep(1)