def myHolo():
''' my holographic setup, which I think works since we use plane waves '''
optics = hp.core.Optics(wavelen=635e-9, index=1.33, polarization=[1.0, 0.0])
obj = hp.load('fibre1.png', spacing=7.6e-6, optics=optics)
ref = hp.load('refFibre1.png', spacing=7.6e-6, optics=optics)
holo = obj - ref
rec = hp.propagate(holo, np.linspace(2.5e-2, 7.5e-2, 200))
return rec
def jericho():
''' using Dr. Jericho's setup and images, currently doesn't work.
I think this is because Jericho using a spherical wave. '''
optics = hp.core.Optics(wavelen=405e-9, index=1.33, polarization=[1.0, 0.0])
obj = hp.load('jerichoObject.bmp', spacing=6e-6, optics=optics)
ref = hp.load('jerichoRef.bmp', spacing=6e-6, optics=optics)
holo=obj-ref
#rec = hp.propagate(holo, np.linspace(200e-6, 300e-6, 10))
rec = hp.propagate(holo, np.linspace(12.5e-3, 13e-3, 20))
return rec
def myHolo():
optics = hp.core.Optics(wavelen=.632, index=1.33, polarization=[1.0, 0.0])
#magnification = 40
#Spacing = 6.8 / magnification
Spacing = 0.1
obj = hp.load('cgh.png', spacing=Spacing, optics=optics)
#ref = hp.load('image0146.tif', spacing=Spacing, optics=optics)
#holo = obj - ref
holo = obj
hp.show(holo)
plt.show()
rec = hp.propagate(holo, np.linspace(100, 150, 50))
return rec
def myHolo():
''' my holographic setup, which I think works since we use plane waves '''
optics = hp.core.Optics(wavelen=635e-9, index=1.33, polarization=[1.0, 0.0])
#obj = hp.load('tryit.png', spacing=7.6e-6, optics=optics)
#ref = hp.load('ref.png', spacing=7.6e-6, optics=optics)
obj = hp.load('fibreBright.png', spacing=7.6e-6, optics=optics)
ref = hp.load('refBright.png', spacing=7.6e-6, optics=optics)
#obj = hp.load('singleBright.png', spacing=7.6e-6, optics=optics)
#ref = hp.load('singleRef.png', spacing=7.6e-6, optics=optics)
holo = obj - ref
''' between 4 cm and 10 cm, should be about 5.5 cm '''
#rec = hp.propagate(holo, np.linspace(4e-2, 10e-2, 200))
rec = hp.propagate(holo, np.linspace(5e-2, 6e-2, 200))
#rec = hp.propagate(holo, np.linspace(0.5e-2, 2e-2, 200))
return rec
from holopy.scattering import Spheres
from holopy.scattering import calc_holo, Sphere
imagepath = get_example_data_path('image01.jpg')
raw_holo = hp.load_image(
imagepath,
spacing=0.0851,
medium_index=1.33,
illum_wavelen=0.66,
)
bgpath = get_example_data_path(['bg01.jpg', 'bg02.jpg', 'bg03.jpg'])
bg = load_average(bgpath, refimg=raw_holo)
holo = bg_correct(raw_holo, bg)
z = np.linspace(0, 20, 200)
rec_vol = hp.propagate(holo, z)
x_arr = np.array([])
y_arr = np.array([])
for x in range(278, 292, 1):
print(x)
for y in range(248, 262, 1):
phase_arr = np.array([])
for i in range(0, len(z)):
phase = np.angle(rec_vol[i][x][y])
p = np.angle(np.e**(-1j * 2 * np.pi * z[i] / (0.66 / 1.33)))
diff = phase - p
if diff < -np.pi:
diff = 0
import numpy as np
import holopy as hp
from holopy.core.io import get_example_data_path, load_average
from holopy.core.process import bg_correct
imagepath = get_example_data_path('image01.jpg')
raw_holo = hp.load_image(
imagepath,
spacing=0.0851,
medium_index=1.33,
illum_wavelen=0.66,
)
bgpath = get_example_data_path(['bg01.jpg', 'bg02.jpg', 'bg03.jpg'])
bg = load_average(bgpath, refimg=raw_holo)
holo = bg_correct(raw_holo, bg)
zstack = np.linspace(0, 20, 11)
rec_vol = hp.propagate(holo, zstack)
hp.show(rec_vol)
''' my holographic setup, which I think works since we use plane waves '''
optics = hp.core.Optics(wavelen=.66, index=1.33, polarization=[1.0, 0.0])
magnification = 40
Spacing = 6.8 / magnification
obj = hp.load('image0148.tif', spacing=Spacing, optics=optics)
ref = hp.load('image0146.tif', spacing=Spacing, optics=optics)
focus = hp.load('image0147.tif', spacing=Spacing, optics=optics)
holo = obj - ref
rec = hp.propagate(holo, np.linspace(1, 100, 50))
hp.show(focus)
plt.show()
hp.show(holo)
plt.show()
hp.show(rec)
plt.show()
''' 3D plotting - useful? '''
#from mayavi import mlab
#mlab.contour3d(recInt)
## mlab.pipeline.volume(mlab.pipeline.scalar_field(newImg))
#mlab.axes(x_axis_visibility=True,y_axis_visibility=True,z_axis_visibility=True)
def loadHolo():
optics = hp.core.Optics(wavelen=.66, index=1.33, polarization=[1.0, 0.0])
magnification = 20
Spacing = 6.8 / magnification
obj = hp.load('P1000017.tiff', spacing=Spacing, optics=optics)
ref = hp.load('P1000019.tiff', spacing=Spacing, optics=optics)
holo = obj - ref
return holo
holo = loadHolo()
#holo = holo[1100:1700,1200:1800]
rec = hp.propagate(holo, np.linspace(1500, 1600, 5))
#rec = hp.propagate(holo, 16000)
#hp.show(holo)
#plt.show()
hp.show(rec)
plt.show()
''' 3D plotting - useful? '''
#from mayavi import mlab
#mlab.contour3d(recInt)
## mlab.pipeline.volume(mlab.pipeline.scalar_field(newImg))
#mlab.axes(x_axis_visibility=True,y_axis_visibility=True,z_axis_visibility=True)
#mlab.outline()
#mlab.show()
#optics = hp.core.Optics(wavelen=.405, index=1.33, polarization=[1.0, 0.0])
optics = hp.core.Optics(wavelen=.635, index=1.33, polarization=[1.0, 0.0])
# loading the images
#obj = hp.load('jerichoObject.bmp',spacing=6,optics=optics)
#ref = hp.load('jerichoRef.bmp',spacing=6,optics=optics)
obj = hp.load('fibre1.png',spacing=7.6,optics=optics)
ref = hp.load('refFibre1.png',spacing=7.6,optics=optics)
# contrast image
holo=obj-ref
# reconstruction, same image for all slices though
#rec = hp.propagate(holo, np.linspace(200,13e7,10))
rec = hp.propagate(holo, np.linspace(3.5e4,5.5e4,100))
# intensity so pyplot can plot it
recInt=abs(rec)*abs(rec)
hp.show(recInt)
plt.show()
''' 3D plotting - useful? '''
#mlab.contour3d(recInt)
## mlab.pipeline.volume(mlab.pipeline.scalar_field(newImg))
#mlab.axes(x_axis_visibility=True,y_axis_visibility=True,z_axis_visibility=True)
#mlab.outline()
#mlab.show()
magnification = 20
Spacing = 6.8 / magnification
obj = hp.load('P1000018.tiff', spacing=Spacing, optics=optics)
ref = hp.load('P1000019.tiff', spacing=Spacing, optics=optics)
holo = obj - ref
return holo
holo = loadHolo()
#hp.show(holo)
#plt.show()
#holo = holo[1100:1700,1200:1800]
rec = hp.propagate(holo, np.linspace(1950, 2000, 5))
#rec = hp.propagate(holo, 16000)
hp.show(rec)
plt.show()
''' 3D plotting - useful? '''
#from mayavi import mlab
#mlab.contour3d(recInt)
## mlab.pipeline.volume(mlab.pipeline.scalar_field(newImg))
#mlab.axes(x_axis_visibility=True,y_axis_visibility=True,z_axis_visibility=True)
#mlab.outline()
#mlab.show()
def loadHolo():
optics = hp.core.Optics(wavelen=.66, index=1.33, polarization=[1.0, 0.0])
magnification = 20
Spacing = 6.8 / magnification
obj = hp.load('P1000006.JPG', spacing=Spacing, optics=optics)
ref = hp.load('P1000007.JPG', spacing=Spacing, optics=optics)
holo = obj - ref
return holo
holo = loadHolo()
#rec = hp.propagate(holo[1000:,1000:], np.linspace(15750, 16500, 10))
rec = hp.propagate(holo, 16000)
#hp.show(holo)
#plt.show()
hp.show(rec)
plt.show()
''' 3D plotting - useful? '''
#from mayavi import mlab
#mlab.contour3d(recInt)
## mlab.pipeline.volume(mlab.pipeline.scalar_field(newImg))
#mlab.axes(x_axis_visibility=True,y_axis_visibility=True,z_axis_visibility=True)
#mlab.outline()
#mlab.show()
spacing=0.0851,
medium_index=1.33,
illum_wavelen=0.66,
)
bgpath = get_example_data_path(['bg01.jpg', 'bg02.jpg', 'bg03.jpg'])
bg = load_average(bgpath, refimg=raw_holo)
holo = bg_correct(raw_holo, bg)
z = [17.5, 20, 27]
x = np.linspace(1, 512, 1000)
p1 = np.angle(np.e**(-1j * 2 * np.pi * z[0] / (0.66 / 1.33)))
p2 = np.angle(np.e**(-1j * 2 * np.pi * z[1] / (0.66 / 1.33)))
p3 = np.angle(np.e**(-1j * 2 * np.pi * z[2] / (0.66 / 1.33)))
rec_vol1 = hp.propagate(holo, z[0])
rec_vol2 = hp.propagate(holo, z[1])
rec_vol3 = hp.propagate(holo, z[2])
amp1 = np.abs(rec_vol1[:, 253, :])
amp2 = np.abs(rec_vol2[:, 253, :])
amp3 = np.abs(rec_vol3[:, 253, :])
phase1 = np.angle(rec_vol1[:, 253, :])
phase2 = np.angle(rec_vol2[:, 253, :])
phase3 = np.angle(rec_vol3[:, 253, :])
plt.figure(1)
plt.plot(amp1, label=z[0])
plt.plot(amp2, label=z[1])
plt.plot(amp3, label=z[2])
optics = hp.core.Optics(wavelen=635e-9, index=1.33, polarization=[1.0, 0.0])
obj = hp.load('fibre1.png', spacing=7.6e-6, optics=optics)
ref = hp.load('refFibre1.png', spacing=7.6e-6, optics=optics)
holo = obj - ref
n,m = holo.shape
distance = np.linspace(2.5e-2, 7.5e-2, 200)
d=distance.shape
rowsX = [comm.rank + comm.size * aa for aa in range(int(n/comm.size)+1) if comm.rank + comm.size*aa < d]
reconstruction = np.empty((n,m))
comm.Barrier()
for z in rowsX:
print(distance[z])
rec = hp.propagate(holo, distance[z])
reconstruction = np.dstack((reconstruction,rec))
comm.Barrier()
recInt = abs(reconstruction) * abs(reconstruction)
hp.show(recInt)
plt.show()
import numpy as np
import matplotlib.pyplot as plt
''' my holographic setup, which I think works since we use plane waves '''
optics = hp.core.Optics(wavelen=.66, index=1.33, polarization=[1.0, 0.0])
magnification = 60
Spacing = 6.8 / magnification
obj = hp.load('image0100.tif', spacing=Spacing, optics=optics)
ref = hp.load('../image0156.tif', spacing=Spacing, optics=optics)
holo = obj - ref
rec = hp.propagate(holo, np.linspace(300, 400, 20))
#hp.show(holo)
#plt.show()
hp.show(rec)
plt.show()
recInt = abs(rec) * abs(rec)
from mayavi import mlab
mlab.contour3d(recInt)
#mlab.pipeline.volume(mlab.pipeline.scalar_field(recInt))
mlab.axes(x_axis_visibility=True,y_axis_visibility=True,z_axis_visibility=True)
mlab.outline()
mlab.show()
lim = int(centro[0])
if centro[1] + lim > Ly:
lim = int(Ly - centro[1])
else:
if centro[1] - lim < 0:
lim = int(centro[1])
if centro[0] + lim > Lx:
lim = int(Lx - centro[0])
print(lim)
#propagazione in z in una immagine ristretta da lim
data_holo = raw_holo[:,
int(centro[0] - lim):int(centro[0] + lim),
int(centro[1] - lim):int(centro[1] + lim)]
rec_vol = hp.propagate(data_holo,
z,
illum_wavelen=illum_wavelen,
medium_index=medium_index)
#calcolo posizione di fuoco sia con ampiexxa del campo che con la fase
modulo = propagation_module(z, rec_vol, lim)
phase = np.angle(rec_vol)
onda_riferimento = np.angle(np.e**((-1j * 2 * np.pi * z /
(illum_wavelen / medium_index))))
fase = propagation_phase(phase, onda_riferimento, z, lim)
fase = np.nan_to_num(fase)
max_d, min_d, max_zarray, min_zarray = maximum_minimum(fase, z)
print("punto massimo (d):", max_d, ", punto minimo (d):", min_d)
print("fuoco nell'array, punto di max:", max_zarray, ", punto di min:",
min_zarray)
index = hype.argmax()
return index
optics = hp.core.Optics(wavelen=.66, index=1.33, polarization=[1.0, 0.0])
magnification = 60
Spacing = 6.8 / magnification
obj = hp.load('image0100.tif', spacing=Spacing, optics=optics)
#obj = hp.load('image0001.tif', spacing=Spacing, optics=optics)
#obj = hp.load('image0020.tif', spacing=Spacing, optics=optics)
ref = hp.load('../image0156.tif', spacing=Spacing, optics=optics)
holo = obj - ref
rec = hp.propagate(holo, np.linspace(475, 505, 20))
#hp.show(holo)
#plt.show()
hp.show(rec)
plt.show()
a, b, c = rec.shape
hype = np.ones((a,b,c))
index = sobHypot(rec)
print(index)
index = TestsobHypot(rec)
optics = hp.core.Optics(wavelen=.66, index=1.33, polarization=[1.0, 0.0])
magnification = 40
Spacing = 6.8 / magnification
obj = hp.load('image0139.tif', spacing=Spacing, optics=optics)
ref = hp.load('image0146.tif', spacing=Spacing, optics=optics)
holo = obj - ref
focus = hp.load('image0136.tif', spacing=Spacing, optics=optics)
hp.show(focus)
plt.show()
hp.show(holo)
plt.show()
rec = hp.propagate(holo, np.linspace(50, 200, 50))
hp.show(rec)
plt.show()
''' 3D plotting - useful? '''
#from mayavi import mlab
#mlab.contour3d(recInt)
## mlab.pipeline.volume(mlab.pipeline.scalar_field(newImg))
#mlab.axes(x_axis_visibility=True,y_axis_visibility=True,z_axis_visibility=True)
#mlab.outline()
#mlab.show()
import numpy as np
import holopy as hp
from holopy.core.io import get_example_data_path, load_average
from holopy.core.process import bg_correct
imagepath = get_example_data_path('image01.jpg')
raw_holo = hp.load_image(imagepath, spacing = 0.0851, medium_index = 1.33, illum_wavelen = 0.66, )
bgpath = get_example_data_path(['bg01.jpg','bg02.jpg','bg03.jpg'])
bg = load_average(bgpath, refimg = raw_holo)
holo = bg_correct(raw_holo, bg)
zstack = np.linspace(0, 20, 11)
rec_vol = hp.propagate(holo, zstack)
hp.show(rec_vol)
def calculate_hologram(window):
print("calculate_hologram called.")
try:
back
raw
except:
print(
"calculate_hologram called with no data pls make sure background and hologram is available."
)
return
global rec_vol
if ui.TabSources.currentIndex() is 0:
print("calculate_hologram called with point source!")
#Calculate background correction and update metadata
holo = hp.core.process.bg_correct(raw, back + 1, back)
holo = hp.core.update_metadata(
holo,
medium_index=window.SpinBoxMedium.value(),
illum_wavelen=window.SpinBoxWavelength.value() * 1e-9)
#get beam center and set output shape
beam_c = center_of_mass(back.values.squeeze())
out_schema = hp.core.detector_grid(shape=ui.SpinBoxNPixOut.value(),
spacing=ui.SpinBoxSpacing.value() *
1e-6 /
ui.SpinBoxMagnification.value())
zstack = np.linspace(window.SpinBoxZMin.value() * 1e-6,
window.SpinBoxZMax.value() * 1e-6,
num=window.SpinBoxZStep.value(),
endpoint=True)
#propagate through the raw hologram in zstack defined distances to reconstruct the wavefront at the object of interest
rec_vol = hp.propagation.ps_propagate(
holo, zstack,
ui.SpinBoxDistance.value() * 1e-3, beam_c, out_schema)
#process the reconstructions
else:
print("calculate_hologram called with collimated source!")
holo = hp.core.process.bg_correct(raw, back)
holo = hp.core.update_metadata(
holo,
medium_index=window.SpinBoxMedium_2.value(),
illum_wavelen=window.SpinBoxWavelength_2.value() * 1e-9)
zstack = np.linspace(window.SpinBoxZMin_2.value() * 1e-6,
window.SpinBoxZMax_2.value() * 1e-6,
num=window.SpinBoxZStep_2.value(),
endpoint=True)
rec_vol = hp.propagate(holo, zstack)
#process the reconstruct further
scene = QtWidgets.QGraphicsScene(
) # scene: manipulate data to be shown in widget
image = qim.array2qimage(
np.abs(rec_vol.values[0]),
True) # get x-y values of the image and convert to QImage
scene.addPixmap(
QtGui.QPixmap(
image).scaledToWidth(ui.GraphicsViewHologram.width() -
2)) # QImage->QPixmap and add to the scene
ui.GraphicsViewHologram.setScene(
scene) # set the scene to the background widget
ui.GraphicsViewHologram.show() # show the picture
ui.HorizontalSliderHologram.setMaximum(ui.SpinBoxZStep.value() - 1)
ui.HorizontalSliderHologram.setEnabled(True)
print("Done calculation.")
obj = hp.load('P1000018.tiff', spacing=Spacing, optics=optics)
ref = hp.load('P1000019.tiff', spacing=Spacing, optics=optics)
holo = obj - ref
return holo
holo = loadHolo()
comm=MPI.COMM_WORLD
slices = np.arange(100,10100,100)
n=100
newSlices = [comm.rank + comm.size * aa for aa in range(int(n/comm.size)+1) if comm.rank + comm.size*aa < n]
comm.Barrier()
with tb.openFile('P1819.hdf','w') as f:
matrix = f.createCArray(f.root, 'complexHologram',tb.ComplexAtom(itemsize=8), shape=(4016,3016,100))
#count = 0
for i in newSlices:
print(i, slices[i])
rec = hp.propagate(holo, slices[i])
matrix[..., i] = rec
#matrix[..., count] = rec
#count += 1