def phase_shift(coefficients,
lambda_1=632,
PR=1,
type='4-step',
noise=0,
sample=200):
"""
Genertate phase_shift Interferogram from interferometer
based on zernike polynomials and twyman_green interferometer
===========================================================
input
----------------------------------------------
Class zernike polynomials coefficients in wavenumber
see Class:opticspy.zernike.Coefficients
lambda_1: wavelength in nanometer, default = 632nm
PR: pupil radius, default = 1(also use this value for aperture matrix generate)
type: PSI algorithm default:'4-step'
boundary: if have a aperture
noise: from 0 to 1, default 0
sample: sample points
output
----------------------------------------------
Interferogram of aberration
"""
lambda_1 = lambda_1 * (10**-9)
coefficients = coefficients.__coefficients__
r = __np__.linspace(-PR, PR, sample)
x, y = __np__.meshgrid(r, r)
rr = __np__.sqrt(x**2 + y**2)
OPD = __zernike__.__zernikecartesian__(coefficients, x, y) * 2 / PR
Ia = 1
Ib = 1
ph = 2 * __np__.pi * OPD
if type == "4-step":
__tools__.makecircle_boundary(OPD, r, PR, 0)
im = __plt__.imshow(OPD, extent=[-PR, PR, -PR, PR], cmap=__cm__.RdYlGn)
__plt__.colorbar()
__plt__.title('Surface figure', fontsize=16)
__plt__.show()
I1 = Ia + Ib + 2 * __np__.sqrt(Ia * Ib) * __np__.cos(ph)
I2 = Ia + Ib + 2 * __np__.sqrt(
Ia * Ib) * __np__.cos(ph + 90.0 / 180 * __np__.pi)
I3 = Ia + Ib + 2 * __np__.sqrt(
Ia * Ib) * __np__.cos(ph + 180.0 / 180 * __np__.pi)
I4 = Ia + Ib + 2 * __np__.sqrt(
Ia * Ib) * __np__.cos(ph + 270.0 / 180 * __np__.pi)
if noise != 0:
# add noise / default noise 0
I1 = I1 + I1 * noise * __np__.random.randn(sample, sample)
I2 = I2 + I2 * noise * __np__.random.randn(sample, sample)
I3 = I3 + I3 * noise * __np__.random.randn(sample, sample)
I4 = I4 + I4 * noise * __np__.random.randn(sample, sample)
__tools__.makecircle_boundary(I1, r, PR, 0)
__tools__.makecircle_boundary(I2, r, PR, 0)
__tools__.makecircle_boundary(I3, r, PR, 0)
__tools__.makecircle_boundary(I4, r, PR, 0)
I = [I1, I2, I3, I4]
__tools__.phase_shift_figure(I, PR, type="4-step")
M = __np__.ones([sample, sample]) #map matrix, which is boundary
__tools__.makecircle_boundary(M, r, PR, 0)
# fig = __plt__.figure(figsize=(8, 6), dpi=80)
# im = __plt__.pcolormesh(M,cmap=__cm__.RdYlGn)
# __plt__.title('Phase value map',fontsize=16)
# __plt__.colorbar()
# __plt__.show()
return [I, PR, M, sample]
else:
print("No this type of PSI")
def phase_shift(coefficients, lambda_1 = 632, PR = 1, type = '4-step', noise = 0, sample = 200):
"""
Genertate phase_shift Interferogram from interferometer
based on zernike polynomials and twyman_green interferometer
===========================================================
input
----------------------------------------------
Class zernike polynomials coefficients in wavenumber
see Class:opticspy.zernike.Coefficients
lambda_1: wavelength in nanometer, default = 632nm
PR: pupil radius, default = 1(also use this value for aperture matrix generate)
type: PSI algorithm default:'4-step'
boundary: if have a aperture
noise: from 0 to 1, default 0
sample: sample points
output
----------------------------------------------
Interferogram of aberration
"""
lambda_1 = lambda_1*(10**-9)
coefficients = coefficients.__coefficients__
r = __np__.linspace(-PR, PR, sample)
x, y = __np__.meshgrid(r,r)
rr = __np__.sqrt(x**2 + y**2)
OPD = __zernike__.__zernikecartesian__(coefficients,x,y)*2/PR
Ia = 1
Ib = 1
ph = 2 * __np__.pi * OPD
if type == "4-step":
__tools__.makecircle_boundary(OPD, r, PR, 0)
im = __plt__.imshow(OPD,extent=[-PR,PR,-PR,PR],cmap=__cm__.RdYlGn)
__plt__.colorbar()
__plt__.title('Surface figure',fontsize=16)
__plt__.show()
I1 = Ia + Ib + 2 * __np__.sqrt(Ia*Ib) * __np__.cos(ph)
I2 = Ia + Ib + 2 * __np__.sqrt(Ia*Ib) * __np__.cos(ph+90.0/180*__np__.pi)
I3 = Ia + Ib + 2 * __np__.sqrt(Ia*Ib) * __np__.cos(ph+180.0/180*__np__.pi)
I4 = Ia + Ib + 2 * __np__.sqrt(Ia*Ib) * __np__.cos(ph+270.0/180*__np__.pi)
if noise != 0:
# add noise / default noise 0
I1 = I1 + I1*noise*__np__.random.randn(sample,sample)
I2 = I2 + I2*noise*__np__.random.randn(sample,sample)
I3 = I3 + I3*noise*__np__.random.randn(sample,sample)
I4 = I4 + I4*noise*__np__.random.randn(sample,sample)
__tools__.makecircle_boundary(I1, r, PR, 0)
__tools__.makecircle_boundary(I2, r, PR, 0)
__tools__.makecircle_boundary(I3, r, PR, 0)
__tools__.makecircle_boundary(I4, r, PR, 0)
I = [I1,I2,I3,I4]
__tools__.phase_shift_figure(I,PR,type = "4-step")
M = __np__.ones([sample,sample]) #map matrix, which is boundary
__tools__.makecircle_boundary(M, r, PR, 0)
# fig = __plt__.figure(figsize=(8, 6), dpi=80)
# im = __plt__.pcolormesh(M,cmap=__cm__.RdYlGn)
# __plt__.title('Phase value map',fontsize=16)
# __plt__.colorbar()
# __plt__.show()
return [I,PR,M,sample]
else:
print("No this type of PSI")
def rebuild_surface(data,
shifttype="4-step",
unwraptype="unwrap2D",
noise=True):
"""
Rebuild surface function
============================================
input
--------------------------------------------
data: Interferogram data from PSI
shifttype: PSI type, default 4-step PSI
unwraptype: phaseunwrap type, default "simple"
output
--------------------------------------------
rebuild surface matrix
"""
if shifttype == "4-step" and unwraptype == "simple" and noise == False:
I = data[0]
PR = data[1]
ph = __np__.arctan2((I[3] - I[1]), (I[0] - I[2]))
fig = __plt__.figure(figsize=(9, 6), dpi=80)
im = __plt__.imshow(ph, extent=[-PR, PR, -PR, PR], cmap=__cm__.RdYlGn)
__plt__.title('Wrapped phase', fontsize=16)
__plt__.colorbar()
__plt__.show()
#-----------------------Phase unwrap-------------------------
rebuild_ph = __unwrap2D__(ph, type="simple")
rebuild_surface = rebuild_ph / 2 / __np__.pi * PR / 2
#------------------------------------------------------------
fig = __plt__.figure(figsize=(9, 6), dpi=80)
im = __plt__.imshow(rebuild_surface,
extent=[-PR, PR, -PR, PR],
cmap=__cm__.RdYlGn)
__plt__.title('Rebuild Surface', fontsize=16)
__plt__.colorbar()
__plt__.show()
return rebuild_surface
elif shifttype == "4-step" and unwraptype == "unwrap2D" and noise == True:
I = data[0]
PR = data[1]
M = data[2]
s = data[3]
r = __np__.linspace(-PR, PR, s)
ph = __np__.arctan2((I[3] - I[1]), (I[0] - I[2]))
fig = __plt__.figure(figsize=(9, 6), dpi=80)
im = __plt__.imshow(ph, extent=[-PR, PR, -PR, PR], cmap=__cm__.RdYlGn)
__plt__.title('Wrapped phase', fontsize=16)
__plt__.colorbar()
__plt__.show()
#-----------------------Phase unwrap-------------------------
ph1 = [ph, M, s]
rebuild_ph = __unwrap2D__(ph1, noise=True)
rebuild_surface = rebuild_ph / 2 / __np__.pi * PR / 2
__tools__.makecircle_boundary(rebuild_surface, r, PR, 0)
fig = __plt__.figure(figsize=(9, 6), dpi=80)
im = __plt__.imshow(rebuild_surface,
extent=[-PR, PR, -PR, PR],
cmap=__cm__.RdYlGn)
__plt__.title('Rebuild Surface', fontsize=16)
__plt__.colorbar()
__plt__.show()
return rebuild_surface
else:
print("No this kind of phase shift type")
return 0
def rebuild_surface(data, shifttype = "4-step", unwraptype = "unwrap2D", noise = True):
"""
Rebuild surface function
============================================
input
--------------------------------------------
data: Interferogram data from PSI
shifttype: PSI type, default 4-step PSI
unwraptype: phaseunwrap type, default "simple"
output
--------------------------------------------
rebuild surface matrix
"""
if shifttype == "4-step" and unwraptype == "simple" and noise == False:
I = data[0]
PR = data[1]
ph = __np__.arctan2((I[3]-I[1]),(I[0]-I[2]))
fig = __plt__.figure(figsize=(9, 6), dpi=80)
im = __plt__.imshow(ph,extent=[-PR,PR,-PR,PR],cmap=__cm__.RdYlGn)
__plt__.title('Wrapped phase',fontsize=16)
__plt__.colorbar()
__plt__.show()
#-----------------------Phase unwrap-------------------------
rebuild_ph = __unwrap2D__(ph,type = "simple")
rebuild_surface = rebuild_ph/2/__np__.pi*PR/2
#------------------------------------------------------------
fig = __plt__.figure(figsize=(9, 6), dpi=80)
im = __plt__.imshow(rebuild_surface,extent=[-PR,PR,-PR,PR],cmap=__cm__.RdYlGn)
__plt__.title('Rebuild Surface',fontsize=16)
__plt__.colorbar()
__plt__.show()
return rebuild_surface
elif shifttype == "4-step" and unwraptype == "unwrap2D" and noise == True:
I = data[0]
PR = data[1]
M = data[2]
s = data[3]
r = __np__.linspace(-PR, PR, s)
ph = __np__.arctan2((I[3]-I[1]),(I[0]-I[2]))
fig = __plt__.figure(figsize=(9, 6), dpi=80)
im = __plt__.imshow(ph,extent=[-PR,PR,-PR,PR],cmap=__cm__.RdYlGn)
__plt__.title('Wrapped phase',fontsize=16)
__plt__.colorbar()
__plt__.show()
#-----------------------Phase unwrap-------------------------
ph1 = [ph,M,s]
rebuild_ph = __unwrap2D__(ph1,noise = True)
rebuild_surface = rebuild_ph/2/__np__.pi*PR/2
__tools__.makecircle_boundary(rebuild_surface, r, PR, 0)
fig = __plt__.figure(figsize=(9, 6), dpi=80)
im = __plt__.imshow(rebuild_surface,extent=[-PR,PR,-PR,PR],cmap=__cm__.RdYlGn)
__plt__.title('Rebuild Surface',fontsize=16)
__plt__.colorbar()
__plt__.show()
return rebuild_surface
else:
print("No this kind of phase shift type")
return 0
