def test_sphere(N = 128, **kwargs):
Nx, Nz = N,N
dx, dz = .05, 0.05
lam = .5
units = (dx,dx,dz)
x = Nx/2*dx*np.linspace(-1,1,Nx)
y = Nx/2*dx*np.linspace(-1,1,Nx)
x = dx*np.arange(-Nx/2,Nx/2)
y = dx*np.arange(-Nx/2,Nx/2)
z = dz*np.arange(0,Nz)
Z,Y,X = np.meshgrid(z,y,x,indexing="ij")
R = np.sqrt(X**2+Y**2+(Z-3.)**2)
dn = .05*(R<1.)
c = StopWatch()
c.tic("bpm")
u = bpm_3d((Nx,Nx,Nz),units= units,
lam = lam,
dn = dn,
**kwargs
)
c.toc("bpm")
print c
return u
if __name__ == '__main__':
api = cluda.cuda_api()
thr = api.Thread.create()
size = (256,256,256)
units = (.1,)*3
lam = .5
u0 = None
n0 = 1.
dn = np.zeros(size[::-1],np.complex64)
clock = StopWatch()
clock.tic("setup")
Nx, Ny, Nz = size
dx, dy, dz = units
dn[Nz/2:,...] = 0.1
#setting up the propagator
k0 = 2.*np.pi/lam
kxs = 2.*np.pi*np.fft.fftfreq(Nx,dx)
kys = 2.*np.pi*np.fft.fftfreq(Ny,dy)
KY, KX = np.meshgrid(kxs,kys, indexing= "ij")
ctx = autoinit.context
if __name__ == '__main__':
api = cluda.cuda_api()
thr = api.Thread.create()
size = (256, 256, 256)
units = (.1, ) * 3
lam = .5
u0 = None
n0 = 1.
dn = np.zeros(size[::-1], np.complex64)
clock = StopWatch()
clock.tic("setup")
Nx, Ny, Nz = size
dx, dy, dz = units
dn[Nz / 2:, ...] = 0.1
#setting up the propagator
k0 = 2. * np.pi / lam
kxs = 2. * np.pi * np.fft.fftfreq(Nx, dx)
kys = 2. * np.pi * np.fft.fftfreq(Ny, dy)
KY, KX = np.meshgrid(kxs, kys, indexing="ij")
def bpm_3d_inverse(u, units, lam=.5, use_fresnel_approx=False):
"""
size - the dimension of the image to be calulcated in pixels (Nx,Ny,Nz)
units - the unit lengths of each dimensions in microns
lam - the wavelength
u - the complex field distribution
returns
dn - the refractive index of the medium (can be complex)
"""
clock = StopWatch()
clock.tic("setup")
Nz, Ny, Nx = u.shape
dx, dy, dz = units
#setting up the propagator
k0 = 2. * np.pi / lam
kxs = np.arange(-Nx / 2., Nx / 2.) / Nx
kys = np.arange(-Ny / 2., Ny / 2.) / Ny
KY, KX = np.meshgrid(kxs, kys, indexing="ij")
H0 = np.sqrt(0.j + (1. / lam)**2 - KX**2 / dx**2 - KY**2 / dy**2)
if use_fresnel_approx:
H0 = 1. / lam * (0.j + 1. - .5 * lam**2 *
(KX**2 / dx**2 + KY**2 / dy**2))
outsideInds = np.isnan(H0)
H = np.exp(2.j * np.pi * dz * H0)
H[outsideInds] = 0.
H0[outsideInds] = 0.
H = np.fft.fftshift(H).astype(np.complex64)
"""
setting up the gpu buffers and kernels
"""
program = OCLProgram(absPath("kernels/bpm_3d_kernels.cl"))
# program = OCLProgram(src_str = kernel_str)
kernel_divide = OCLElementwiseKernel(
"cfloat_t *a_g, cfloat_t *b_g,float kz, cfloat_t *res_g",
"res_g[i] = (cfloat_t)(i,0.)", "divide")
plan = ocl_fft_plan((Ny, Nx))
plane_g = OCLArray.empty((Ny, Nx), np.complex64)
plane0_g = OCLArray.empty((Ny, Nx), np.complex64)
h_g = OCLArray.from_array(H.astype(np.complex64))
u_g = OCLArray.from_array(u.astype(np.complex64))
dn_g = OCLArray.empty((Nz, Ny, Nx), dtype=np.complex64)
clock.toc("setup")
clock.tic("run")
for i in range(Nz - 1):
program.run_kernel("copy_complex", (Nx * Ny, ), None, u_g.data,
plane_g.data, np.int32(i * Nx * Ny))
#calculate the propagated plane
ocl_fft(plane_g, inplace=True, plan=plan)
program.run_kernel("mult", (Nx * Ny, ), None, plane_g.data, h_g.data)
ocl_fft(plane_g, inplace=True, inverse=True, plan=plan)
dn_g[i + 1, ...] = plane_g
# program.run_kernel("copy_complex",(Nx*Ny,),None,
# u_g.data,plane0_g.data,np.int32((i+1)*Nx*Ny))
# program.run_kernel("divide_dn_complex",(Nx*Ny,),None,
# plane0_g.data,plane_g.data,dn_g.data,
# np.float32(k0*dz),
# np.int32((i+1)*Nx*Ny))
clock.toc("run")
print clock
return dn_g.get()
def bpm_3d_inverse(u,units, lam = .5,
use_fresnel_approx = False):
"""
size - the dimension of the image to be calulcated in pixels (Nx,Ny,Nz)
units - the unit lengths of each dimensions in microns
lam - the wavelength
u - the complex field distribution
returns
dn - the refractive index of the medium (can be complex)
"""
clock = StopWatch()
clock.tic("setup")
Nz, Ny, Nx = u.shape
dx, dy, dz = units
#setting up the propagator
k0 = 2.*np.pi/lam
kxs = np.arange(-Nx/2.,Nx/2.)/Nx
kys = np.arange(-Ny/2.,Ny/2.)/Ny
KY, KX = np.meshgrid(kxs,kys, indexing= "ij")
H0 = np.sqrt(0.j+(1./lam)**2-KX**2/dx**2-KY**2/dy**2)
if use_fresnel_approx:
H0 = 1./lam*(0.j+1.-.5*lam**2*(KX**2/dx**2+KY**2/dy**2))
outsideInds = np.isnan(H0)
H = np.exp(2.j*np.pi*dz*H0)
H[outsideInds] = 0.
H0[outsideInds] = 0.
H = np.fft.fftshift(H).astype(np.complex64)
"""
setting up the gpu buffers and kernels
"""
program = OCLProgram(absPath("kernels/bpm_3d_kernels.cl"))
# program = OCLProgram(src_str = kernel_str)
kernel_divide = OCLElementwiseKernel(
"cfloat_t *a_g, cfloat_t *b_g,float kz, cfloat_t *res_g",
"res_g[i] = (cfloat_t)(i,0.)",
"divide")
plan = ocl_fft_plan((Ny,Nx))
plane_g = OCLArray.empty((Ny,Nx),np.complex64)
plane0_g = OCLArray.empty((Ny,Nx),np.complex64)
h_g = OCLArray.from_array(H.astype(np.complex64))
u_g = OCLArray.from_array(u.astype(np.complex64))
dn_g = OCLArray.empty((Nz,Ny,Nx),dtype=np.complex64)
clock.toc("setup")
clock.tic("run")
for i in range(Nz-1):
program.run_kernel("copy_complex",(Nx*Ny,),None,
u_g.data,plane_g.data,np.int32(i*Nx*Ny))
#calculate the propagated plane
ocl_fft(plane_g,inplace = True, plan = plan)
program.run_kernel("mult",(Nx*Ny,),None,
plane_g.data,h_g.data)
ocl_fft(plane_g,inplace = True, inverse = True, plan = plan)
dn_g[i+1,...] = plane_g
# program.run_kernel("copy_complex",(Nx*Ny,),None,
# u_g.data,plane0_g.data,np.int32((i+1)*Nx*Ny))
# program.run_kernel("divide_dn_complex",(Nx*Ny,),None,
# plane0_g.data,plane_g.data,dn_g.data,
# np.float32(k0*dz),
# np.int32((i+1)*Nx*Ny))
clock.toc("run")
print clock
return dn_g.get()
def bpm_3d_free(size, units, dz, lam = .5, u0 = None,
n0 = 1.,
use_fresnel_approx = False):
"""propagates the field u0 to distance dz
"""
clock = StopWatch()
clock.tic("setup")
Nx, Ny = size
dx, dy = units
#setting up the propagator
k0 = 2.*np.pi/lam*n0
kxs = np.arange(-Nx/2.,Nx/2.)/Nx
kys = np.arange(-Ny/2.,Ny/2.)/Ny
KY, KX = np.meshgrid(kxs,kys, indexing= "ij")
H0 = np.sqrt(0.j+(1./lam)**2-KX**2/dx**2-KY**2/dy**2)
if use_fresnel_approx:
H0 = 1./lam*(0.j+1.-.5*lam**2*(KX**2/dx**2+KY**2/dy**2))
outsideInds = np.isnan(H0)
H = np.exp(2.j*np.pi*dz*H0)
H[outsideInds] = 0.
H0[outsideInds] = 0.
H = np.fft.fftshift(H).astype(np.complex64)
if u0 is None:
u0 = np.ones((Ny,Nx),np.complex64)
"""
setting up the gpu buffers and kernels
"""
program = OCLProgram(absPath("kernels/bpm_3d_kernels.cl"))
# program = OCLProgram(src_str = kernel_str)
plan = ocl_fft_plan((Ny,Nx))
plane_g = OCLArray.from_array(u0.astype(np.complex64))
h_g = OCLArray.from_array(H.astype(np.complex64))
clock.toc("setup")
clock.tic("run")
fft(plane_g,inplace = True, plan = plan)
program.run_kernel("mult",(Nx*Ny,),None,
plane_g.data,h_g.data)
fft(plane_g,inplace = True, inverse = True, plan = plan)
clock.toc("run")
return plane_g.get()
def _bpm_3d_image(size,
units,
lam = .5,
u0 = None, dn = None,
subsample = 1,
n0 = 1.,
return_scattering = False,
return_g = False,
return_full_last = False,
use_fresnel_approx = False,
):
"""
simulates the propagation of monochromativ wave of wavelength lam with initial conditions u0 along z in a media filled with dn
size - the dimension of the image to be calulcated in pixels (Nx,Ny,Nz)
units - the unit lengths of each dimensions in microns
lam - the wavelength
u0 - the initial field distribution, if u0 = None an incident plane wave is assumed
dn - the refractive index of the medium (can be complex)
"""
clock = StopWatch()
clock.tic("setup")
Nx, Ny, Nz = size
dx, dy, dz = units
# subsampling
Nx2, Ny2, Nz2 = (subsample*N for N in size)
dx2, dy2, dz2 = (1.*d/subsample for d in units)
#setting up the propagator
k0 = 2.*np.pi/lam
kxs = 2.*np.pi*np.fft.fftfreq(Nx2,dx2)
kys = 2.*np.pi*np.fft.fftfreq(Ny2,dy2)
KY, KX = np.meshgrid(kys,kxs, indexing= "ij")
#H0 = np.sqrt(0.j+n0**2*k0**2-KX**2-KY**2)
H0 = np.sqrt(n0**2*k0**2-KX**2-KY**2)
if use_fresnel_approx:
H0 = 0.j+n0**2*k0-.5*(KX**2+KY**2)
outsideInds = np.isnan(H0)
H = np.exp(-1.j*dz2*H0)
H[outsideInds] = 0.
H0[outsideInds] = 0.
if u0 is None:
u0 = np.ones((Ny2,Nx2),np.complex64)
else:
if subsample >1:
u0 = zoom(np.real(u0),subsample) + 1.j*zoom(np.imag(u0),subsample)
# setting up the gpu buffers and kernels
program = OCLProgram(absPath("kernels/bpm_3d_kernels.cl"))
plan = fft_plan((Ny2,Nx2))
plane_g = OCLArray.from_array(u0.astype(np.complex64))
h_g = OCLArray.from_array(H.astype(np.complex64))
if dn is not None:
if isinstance(dn,OCLImage):
dn_g = dn
else:
if dn.dtype.type in (np.complex64,np.complex128):
dn_complex = np.zeros(dn.shape+(2,),np.float32)
dn_complex[...,0] = np.real(dn)
dn_complex[...,1] = np.imag(dn)
dn_g = OCLImage.from_array(dn_complex)
else:
dn_g = OCLImage.from_array(dn.astype(np.float32))
isComplexDn = dn.dtype.type in (np.complex64,np.complex128)
else:
#dummy dn
dn_g = OCLArray.empty((1,)*3,np.float16)
if return_scattering:
cos_theta = np.real(H0)/n0/k0
# = cos(theta)
scatter_weights = cos_theta
scatter_weights_g = OCLArray.from_array(scatter_weights.astype(np.float32))
# = cos(theta)^2
gfactor_weights = cos_theta**2
gfactor_weights_g = OCLArray.from_array(gfactor_weights.astype(np.float32))
#return None,None,scatter_weights, gfactor_weights
scatter_cross_sec_g = OCLArray.zeros(Nz,"float32")
gfactor_g = OCLArray.zeros(Nz,"float32")
plain_wave_dct = Nx2*Ny2*np.exp(-1.j*k0*n0*np.arange(Nz)*dz).astype(np.complex64)
reduce_kernel = OCLReductionKernel(
np.float32, neutral="0",
reduce_expr="a+b",
map_expr="weights[i]*cfloat_abs(field[i]-(i==0)*plain)*cfloat_abs(field[i]-(i==0)*plain)",
arguments="__global cfloat_t *field, __global float * weights,cfloat_t plain")
# reduce_kernel = OCLReductionKernel(
# np.float32, neutral="0",
# reduce_expr="a+b",
# map_expr = "weights[i]*(i!=0)*cfloat_abs(field[i])*cfloat_abs(field[i])",
# arguments = "__global cfloat_t *field, __global float * weights,cfloat_t plain")
u_g = OCLArray.empty((Nz,Ny,Nx),dtype=np.complex64)
program.run_kernel("copy_subsampled_buffer",(Nx,Ny),None,
u_g.data,plane_g.data,
np.int32(subsample),
np.int32(0))
clock.toc("setup")
clock.tic("run")
for i in range(Nz-1):
for substep in range(subsample):
fft(plane_g,inplace = True, plan = plan)
program.run_kernel("mult",(Nx2*Ny2,),None,
plane_g.data,h_g.data)
if return_scattering and substep == (subsample-1):
scatter_cross_sec_g[i+1] = reduce_kernel(plane_g,
scatter_weights_g,
plain_wave_dct[i+1])
gfactor_g[i+1] = reduce_kernel(plane_g,
gfactor_weights_g,
plain_wave_dct[i+1])
fft(plane_g,inplace = True, inverse = True, plan = plan)
if dn is not None:
if isComplexDn:
program.run_kernel("mult_dn_complex_image",(Nx2,Ny2),None,
plane_g.data,dn_g,
np.float32(k0*dz2),
np.float32(n0),
np.int32(subsample*(i+1.)+substep),
np.int32(subsample))
else:
program.run_kernel("mult_dn_image",(Nx2,Ny2),None,
plane_g.data,dn_g,
np.float32(k0*dz2),
np.float32(n0),
np.int32(subsample*(i+1.)+substep),
np.int32(subsample))
program.run_kernel("copy_subsampled_buffer",(Nx,Ny),None,
u_g.data,plane_g.data,
np.int32(subsample),
np.int32((i+1)*Nx*Ny))
clock.toc("run")
print clock
result = (u_g.get(), dn_g.get(),)
if return_scattering:
# normalizing prefactor dkx = dx2/Nx2
# prefac = 1./Nx2/Ny2*dx2*dy2/4./np.pi/n0
prefac = 1./Nx2/Ny2*dx2*dy2
p = prefac*scatter_cross_sec_g.get()
result += (p,)
if return_g:
prefac = 1./Nx2/Ny2*dx2*dy2
g = prefac*gfactor_g.get()/p
result += (g,)
if return_full_last:
result += (plane_g.get(),)
return result
def _bpm_3d2(size,
units,
lam = .5,
u0 = None,
dn = None,
subsample = 1,
n0 = 1.,
return_scattering = False,
return_g = False,
return_full = True,
return_field = True,
use_fresnel_approx = False,
absorbing_width = 0,
scattering_plane_ind = 0,
return_last_plane = False,
store_dn_as_half = False):
"""
simulates the propagation of monochromatic wave of wavelength lam with initial conditions u0 along z in a media filled with dn
size - the dimension of the image to be calulcated in pixels (Nx,Ny,Nz)
units - the unit lengths of each dimensions in microns
lam - the wavelength
u0 - the initial field distribution, if u0 = None an incident plane wave is assumed
dn - the refractive index of the medium (can be complex)
"""
if subsample != 1:
raise NotImplementedError("subsample still has to be 1")
clock = StopWatch()
clock.tic("setup")
Nx, Ny, Nz = size
dx, dy, dz = units
#setting up the propagator
k0 = 2.*np.pi/lam
kxs = 2.*np.pi*np.fft.fftfreq(Nx,dx)
kys = 2.*np.pi*np.fft.fftfreq(Ny,dy)
KY, KX = np.meshgrid(kys,kxs, indexing= "ij")
#H0 = np.sqrt(0.j+n0**2*k0**2-KX**2-KY**2)
H0 = np.sqrt(n0**2*k0**2-KX**2-KY**2)
if use_fresnel_approx:
H0 = 0.j+n0*k0-.5*(KX**2+KY**2)/n0/k0
outsideInds = np.isnan(H0)
H = np.exp(-1.j*dz*H0)
H[outsideInds] = 0.
H0[outsideInds] = 0.
if u0 is None:
u0 = np.ones((Ny,Nx),np.complex64)
# setting up the gpu buffers and kernels
program = OCLProgram(absPath("kernels/bpm_3d_kernels.cl"))
plan = fft_plan((Ny,Nx))
plane_g = OCLArray.from_array(u0.astype(np.complex64, copy = False))
h_g = OCLArray.from_array(H.astype(np.complex64))
if dn is not None:
if isinstance(dn,OCLArray):
dn_g = dn
else:
if dn.dtype.type in (np.complex64,np.complex128):
isComplexDn = True
dn_g = OCLArray.from_array(dn.astype(np.complex64,copy= False))
else:
isComplexDn = False
if store_dn_as_half:
dn_g = OCLArray.from_array(dn.astype(np.float16,copy= False))
else:
dn_g = OCLArray.from_array(dn.astype(np.float32,copy= False))
else:
#dummy dn
dn_g = OCLArray.empty((1,)*3,np.float32)
if return_scattering:
cos_theta = np.real(H0)/n0/k0
# _H = np.sqrt(n0**2*k0**2-KX**2-KY**2)
# _H[np.isnan(_H)] = 0.
#
# cos_theta = _H/n0/k0
# # = cos(theta)
scatter_weights = cos_theta
#scatter_weights = np.sqrt(KX**2+KY**2)/k0/np.real(H0)
#scatter_weights[outsideInds] = 0.
scatter_weights_g = OCLArray.from_array(scatter_weights.astype(np.float32))
# = cos(theta)^2
gfactor_weights = cos_theta**2
gfactor_weights_g = OCLArray.from_array(gfactor_weights.astype(np.float32))
#return None,None,scatter_weights, gfactor_weights
scatter_cross_sec_g = OCLArray.zeros(Nz,"float32")
gfactor_g = OCLArray.zeros(Nz,"float32")
plain_wave_dct = Nx*Ny*np.exp(-1.j*k0*n0*(scattering_plane_ind+np.arange(Nz))*dz).astype(np.complex64)
reduce_kernel = OCLReductionKernel(
np.float32, neutral="0",
reduce_expr="a+b",
map_expr="weights[i]*cfloat_abs(field[i]-(i==0)*plain)*cfloat_abs(field[i]-(i==0)*plain)",
arguments="__global cfloat_t *field, __global float * weights,cfloat_t plain")
# reduce_kernel = OCLReductionKernel(
# np.float32, neutral="0",
# reduce_expr="a+b",
# map_expr = "weights[i]*(i!=0)*cfloat_abs(field[i])*cfloat_abs(field[i])",
# arguments = "__global cfloat_t *field, __global float * weights,cfloat_t plain")
if return_full:
if return_field:
u_g = OCLArray.empty((Nz,Ny,Nx),dtype=np.complex64)
u_g[0] = plane_g
else:
u_g = OCLArray.empty((Nz,Ny,Nx),dtype=np.float32)
program.run_kernel("copy_intens",(Nx*Ny,),None,
plane_g.data,u_g.data, np.int32(0))
clock.toc("setup")
clock.tic("run")
for i in range(Nz-1):
fft(plane_g,inplace = True, plan = plan)
program.run_kernel("mult",(Nx*Ny,),None,
plane_g.data,h_g.data)
#a = dn_g.sum()
if return_scattering:
scatter_cross_sec_g[i+1] = reduce_kernel(plane_g,
scatter_weights_g,
plain_wave_dct[i+1])
gfactor_g[i+1] = reduce_kernel(plane_g,
gfactor_weights_g,
plain_wave_dct[i+1])
fft(plane_g,inplace = True, inverse = True, plan = plan)
if dn is not None:
if isComplexDn:
kernel_str = "mult_dn_complex"
else:
if dn_g.dtype.type == np.float16:
kernel_str = "mult_dn_half"
else:
kernel_str = "mult_dn"
program.run_kernel(kernel_str,(Nx,Ny,),None,
plane_g.data,dn_g.data,
np.float32(k0*dz),
np.int32(Nx*Ny*(i+1)),
np.int32(absorbing_width))
if return_full:
if return_field:
u_g[i+1] = plane_g
else:
program.run_kernel("copy_intens",(Nx*Ny,),None,
plane_g.data,u_g.data, np.int32(Nx*Ny*(i+1)))
clock.toc("run")
print clock
if return_full:
u = u_g.get()
else:
u = plane_g.get()
if not return_field:
u = np.abs(u)**2
if return_scattering:
# normalizing prefactor dkx = dx/Nx
# prefac = 1./Nx/Ny*dx*dy/4./np.pi/n0
prefac = 1./Nx/Ny*dx*dy
p = prefac*scatter_cross_sec_g.get()
if return_g:
prefac = 1./Nx/Ny*dx*dy
g = prefac*gfactor_g.get()/p
if return_scattering:
if return_g:
result = u, p, g
else:
result = u, p
else:
result = u
if return_last_plane:
if isinstance(result,tuple):
result = result + (plane_g.get(),)
else:
result = (result, plane_g.get())
return result