def fft(data, nfft=None, in_place=False, use_old_plan=True, **kwargs_in):
global _plan
if USE_OLD_PLAN:
use_old_plan = (USE_OLD_PLAN == 1)
# print('USE OLD PLAN %s' % str(use_old_plan))
kwargs = dict(flags=['measure'])
kwargs.update(kwargs_in)
if nfft == None:
nfft = len(data)
if _plan is None or (use_old_plan and nfft != len(_plan.inarray)):
use_old_plan = False
if not use_old_plan:
input_ = fftw3.create_aligned_array(nfft)
if in_place:
output = None
else:
output = fftw3.create_aligned_array(nfft)
_plan = fftw3.Plan(input_, output, **kwargs)
_plan.inarray[:len(data)] = data
_plan.inarray[len(data):] = 0
_plan.outarray[:] = 0
_plan()
if _plan.outarray is None:
ret = _plan.inarray
else:
ret = _plan.outarray
return ret
def ifft(data, nfft=None, in_place=False, use_old_plan=True, **kwargs_in):
global _plan2
if USE_OLD_PLAN:
use_old_plan = (USE_OLD_PLAN == 1)
kwargs = dict(direction='backward', flags=['measure'])
kwargs.update(kwargs_in)
if nfft == None:
nfft = len(data)
if _plan2 is None or (use_old_plan and nfft != len(_plan2.inarray)):
use_old_plan = False
if not use_old_plan:
input_ = fftw3.create_aligned_array(nfft)
if in_place:
output = None
else:
output = fftw3.create_aligned_array(nfft)
_plan2 = fftw3.Plan(input_, output, **kwargs)
_plan2.inarray[:len(data)] = data
_plan2.inarray[len(data):] = 0
_plan2()
if _plan2.outarray is None:
ret = _plan2.inarray
else:
ret = _plan2.outarray
return ret / nfft
def fft(data, nfft=None, in_place=False, use_old_plan=True, **kwargs_in):
global _plan
if USE_OLD_PLAN:
use_old_plan = (USE_OLD_PLAN == 1)
# print('USE OLD PLAN %s' % str(use_old_plan))
kwargs = dict(flags=['measure'])
kwargs.update(kwargs_in)
if nfft == None:
nfft = len(data)
if _plan is None or (use_old_plan and nfft != len(_plan.inarray)):
use_old_plan = False
if not use_old_plan:
input_ = fftw3.create_aligned_array(nfft)
if in_place:
output = None
else:
output = fftw3.create_aligned_array(nfft)
_plan = fftw3.Plan(input_, output, **kwargs)
_plan.inarray[:len(data)] = data
_plan.inarray[len(data):] = 0
_plan.outarray[:] = 0
_plan()
if _plan.outarray is None:
ret = _plan.inarray
else:
ret = _plan.outarray
return ret
def ifft(data, nfft=None, in_place=False, use_old_plan=True, **kwargs_in):
global _plan2
if USE_OLD_PLAN:
use_old_plan = (USE_OLD_PLAN == 1)
kwargs = dict(direction='backward', flags=['measure'])
kwargs.update(kwargs_in)
if nfft == None:
nfft = len(data)
if _plan2 is None or(use_old_plan and nfft != len(_plan2.inarray)):
use_old_plan = False
if not use_old_plan:
input_ = fftw3.create_aligned_array(nfft)
if in_place:
output = None
else:
output = fftw3.create_aligned_array(nfft)
_plan2 = fftw3.Plan(input_, output, **kwargs)
_plan2.inarray[:len(data)] = data
_plan2.inarray[len(data):] = 0
_plan2()
if _plan2.outarray is None:
ret = _plan2.inarray
else:
ret = _plan2.outarray
return ret / nfft
def init(self, n, measure, outn):
inp = fftw3.create_aligned_array(n, dtype=complex)
outp = fftw3.create_aligned_array(n, dtype=complex)
plan = fftw3.Plan(inp,
outp,
direction='backward',
flags=('measure' if measure else 'estimate', ))
return (plan, None, lambda x: x / len(x))
def init(self, n, measure, outn):
inp = fftw3.create_aligned_array(n, dtype=float)
outp = fftw3.create_aligned_array(n // 2 + 1, dtype=complex)
plan = fftw3.Plan(inp,
outp,
direction='forward',
realtypes='halfcomplex r2c',
flags=('measure' if measure else 'estimate', ))
return (plan, None, None)
def init(self, n, measure, outn):
inp = fftw3.create_aligned_array(n, dtype=complex)
outp = fftw3.create_aligned_array(outn if outn is not None else
(n - 1) // 2,
dtype=float)
plan = fftw3.Plan(inp,
outp,
direction='backward',
realtypes='halfcomplex c2r',
flags=('measure' if measure else 'estimate', ))
return (plan, lambda x: x[:n], lambda x: x / len(x))
def __init__(self, nsx=10.0, nsy=10.0 ,nx=200):
nsy /= 2
self.sigma = 4.0 * pi / sqrt(3.0)
self.lx = self.sigma * nsx
self.ly = self.sigma * nsy * sqrt(3.0)
self.nx = nx
self.ny = int(nx * self.ly / self.lx)
vecx = linspace(0,self.lx,num=self.nx,endpoint=False)
vecy = linspace(0,self.ly,num=self.ny,endpoint=False)
self.X,self.Y = meshgrid(vecx, vecy)
nthreads = 1
# flags = ['measure']
f = fftw3.fftw_flags
self.y = fftw3.create_aligned_array((self.ny, self.nx), dtype=typeDict['complex'])
self.yp = fftw3.create_aligned_array((self.ny, self.nx), dtype=typeDict['complex'])
self.y3 = fftw3.create_aligned_array((self.ny, self.nx), dtype=typeDict['complex'])
self.y3p = fftw3.create_aligned_array((self.ny, self.nx), dtype=typeDict['complex'])
self.y_to_yp = lib.fftw_plan_dft_2d(self.y.shape[0], self.y.shape[1], self.y, self.yp, -1, f['measure'] | f['preserve input'])
self.yp_to_y = lib.fftw_plan_dft_2d(self.y.shape[0], self.y.shape[1], self.yp, self.y, 1, f['measure'] | f['preserve input'])
self.y3_to_y3p = lib.fftw_plan_dft_2d(self.y3.shape[0], self.y3.shape[1], self.y3, self.y3p, -1, f['measure'] | f['preserve input'])
self.y3p_to_y3 = lib.fftw_plan_dft_2d(self.y3.shape[0], self.y3.shape[1], self.y3p, self.y3, 1, f['measure'] | f['preserve input'])
xlen, ylen = self.nx, self.ny
kx = array([x for x in range(xlen//2+1)] + [x for x in range(-(xlen-xlen//2-1), 0)])
ky = array([x for x in range(ylen//2+1)] + [x for x in range(-(ylen-ylen//2-1), 0)])
self.lap = zeros_like(self.yp)
lx, ly = self.lx, self.ly
for iy in xrange(self.lap.shape[0]):
for ix in xrange(self.lap.shape[1]):
self.lap[iy,ix] = (-2*pi*1j*kx[ix]/lx)**2.0+(-2*pi*1j*ky[iy]/ly)**2.0
self.dop_partial = self.lap * (1 + self.lap)**2.0
self.dop = None
print(np.sum(a1))
t2 = time.time()
for i in range(Ntest):
b3 = anfft.fft(a0)
a2 = anfft.ifft(b3)
t2b = time.time()
print(np.sum(a2))
t3 = time.time()
# create a forward and backward fft plan
a = fftw3.create_aligned_array(a0.shape, np.complex128, 16)
b = fftw3.create_aligned_array(a0.shape, np.complex128, 16)
c = fftw3.create_aligned_array(a0.shape, np.complex128, 16)
a[:] = a0
ft3fft = fftw3.Plan(a, b, direction="forward", flags=["measure"])
ft3ifft = fftw3.Plan(b, c, direction="backward", flags=["measure"])
t4 = time.time()
for i in range(Ntest):
# perform a forward transformation
ft3fft() # alternatively fft.execute() or fftw.execute(fft)
# perform a backward transformation
ft3ifft()
def init(self,n,measure,outn):
inp = fftw3.create_aligned_array(n,dtype=complex)
outp = fftw3.create_aligned_array(outn if outn is not None else (n-1)//2,dtype=float)
plan = fftw3.Plan(inp,outp, direction='backward', realtypes='halfcomplex c2r', flags=('measure' if measure else 'estimate',))
return (plan,lambda x: x[:n],lambda x: x/len(x))
def init(self,n,measure,outn):
inp = fftw3.create_aligned_array(n,dtype=complex)
outp = fftw3.create_aligned_array(n,dtype=complex)
plan = fftw3.Plan(inp,outp, direction='backward', flags=('measure' if measure else 'estimate',))
return (plan,None,lambda x: x/len(x))
def init(self,n,measure,outn):
inp = fftw3.create_aligned_array(n,dtype=float)
outp = fftw3.create_aligned_array(n//2+1,dtype=complex)
plan = fftw3.Plan(inp,outp, direction='forward', realtypes='halfcomplex r2c',flags=('measure' if measure else 'estimate',))
return (plan,None,None)
print np.sum(a1)
t2 = time.time()
for i in range(Ntest):
b3 = anfft.fft(a0)
a2 = anfft.ifft(b3)
t2b = time.time()
print np.sum(a2)
t3 = time.time()
# create a forward and backward fft plan
a = fftw3.create_aligned_array(a0.shape, np.complex128, 16)
b = fftw3.create_aligned_array(a0.shape, np.complex128, 16)
c = fftw3.create_aligned_array(a0.shape, np.complex128, 16)
a[:] = a0
ft3fft = fftw3.Plan(a, b, direction='forward', flags=['measure'])
ft3ifft = fftw3.Plan(b, c, direction='backward', flags=['measure'])
t4 = time.time()
for i in range(Ntest):
#perform a forward transformation
ft3fft() # alternatively fft.execute() or fftw.execute(fft)
#perform a backward transformation
ft3ifft()
def fftw_array(self, divs):
return fftw3.create_aligned_array(divs, dtype=typeDict['complex'])
def __init__(self,r=-0.2, psi0=-0.5, nsx=10.0, nsy=10.0 ,nx=200, init = 'hex'):
self.frame_counter = 0
nsy /= 2
self.sigma = 4.0 * pi / sqrt(3.0)
self.r,self.psi0 = float(r),float(psi0)
self.lx = (2.0 * pi * nsx) if (init == 'stripe') else (self.sigma * nsx)
self.ly = self.sigma * nsy * sqrt(3.0)
self.nx = nx
self.ny = int(nx * self.ly / self.lx)
vecx = linspace(0,self.lx,num=self.nx,endpoint=False)
self.xvec = vecx
vecy = linspace(0,self.ly,num=self.ny,endpoint=False)
self.X,self.Y = meshgrid(vecx, vecy)
nthreads = 1
# flags = ['measure']
f = fftw3.fftw_flags
self.y = fftw3.create_aligned_array((self.ny, self.nx), dtype=typeDict['complex'])
self.yp = fftw3.create_aligned_array((self.ny, self.nx), dtype=typeDict['complex'])
self.y3 = fftw3.create_aligned_array((self.ny, self.nx), dtype=typeDict['complex'])
self.y3p = fftw3.create_aligned_array((self.ny, self.nx), dtype=typeDict['complex'])
self.y_to_yp = lib.fftw_plan_dft_2d(self.y.shape[0], self.y.shape[1], self.y, self.yp, -1, f['measure'] | f['preserve input'])
self.yp_to_y = lib.fftw_plan_dft_2d(self.y.shape[0], self.y.shape[1], self.yp, self.y, 1, f['measure'] | f['preserve input'])
self.y3_to_y3p = lib.fftw_plan_dft_2d(self.y3.shape[0], self.y3.shape[1], self.y3, self.y3p, -1, f['measure'] | f['preserve input'])
self.y3p_to_y3 = lib.fftw_plan_dft_2d(self.y3.shape[0], self.y3.shape[1], self.y3p, self.y3, 1, f['measure'] | f['preserve input'])
sqrt3p2 = sqrt(3.0) / 2.0
# init
if init == 'ran':
self.y[:] = self.psi0 + 0.001 * (rand(self.ny, self.nx)-0.5)[:]
elif init == 'hex':
self.y[:] = self.psi0 + (2.0 * cos(self.X[:] * sqrt3p2) * cos(self.Y[:] / 2.0) + cos(self.Y[:])) / 3.0
elif init == 'hom':
self.y[:] = self.psi0
elif init == 'stripe':
self.y[:] = self.psi0 + 0.5 * cos(self.X[:])
elif init == 'stripe-exp':
self.y[:] = self.psi0 + cos(self.X[:]) * sqrt(2.0 * (- self.r - 3.0 * self.psi0 ** 2.0) / 3.0) * exp(-0.0005 * (self.X[:] - self.lx / 2.0)**2.0)
else:
raise ValueError('not a proper initial condition')
# envelope = 0.5 * (tanh(- 0.2 * (self.X - self.l / 2.0 - self.l / 15.0)) + 1.0) * 0.5 * (tanh(0.2 * (self.X - self.l / 2.0 + self.l / 15.0)) + 1.0)
# self.y[:] = self.psi0 * (1.0 - envelope[:]) + envelope[:] * self.y[:]
# for ix in xrange(self.y.shape[0]):
# for iy in xrange(self.y.shape[1]):
# if (ix-self.n/2)**2 + (iy-self.n/2)**2 > (self.n/8)**2:
# self.y[ix,iy] = self.psi0
xlen, ylen = self.nx, self.ny
kx = array([x for x in range(xlen//2+1)] + [x for x in range(-(xlen-xlen//2-1), 0)])
ky = array([x for x in range(ylen//2+1)] + [x for x in range(-(ylen-ylen//2-1), 0)])
self.lap = zeros_like(self.yp)
lx, ly = self.lx, self.ly
for iy in xrange(self.lap.shape[0]):
for ix in xrange(self.lap.shape[1]):
self.lap[iy,ix] = (-2*pi*1j*kx[ix]/lx)**2.0+(-2*pi*1j*ky[iy]/ly)**2.0
self.dop = self.lap * (self.r + (1 + self.lap)**2.0)
lib.fftw_execute(self.y_to_yp)
#self.x = linspace(0, self.l, self.n, endpoint=False)
#self.y = sin(2*2*pi/self.l*self.x)+sin(5*2*pi/self.l*self.x)+sin(3*2*pi/self.l*self.x)
# tmp = rfft2(self.y)
# mask = zeros_like(tmp)
# mask[0:mask.shape[0]/2, 0:mask.shape[0]/2] = 1.0
# self.y = irfft(tmp * mask)
#self.y = self.psi0 + zeros_like(self.x)
# self.y = self.psi0 + zeros(self.n)#+ 0.000001 * randn(self.n)
# self.y = self.psi0+0.01*sin(2*pi*self.x)
# self.y = self.psi0+0.001*cos(2.0*pi*self.x)*exp(-2.0*(self.x-self.l/2.0)**2.0)
# self.kmask=ones_like(self.yp)
# self.kmask[:,:20]=0
# self.kmask[:,-20:]=0
# self.kmask[:20,:]=0
# self.kmask[-20:,:]=0
# self.kmask = array([[exp(-0.08 * (k_x**2.0 + k_y**2.0)) for k_x in kx] for k_y in ky])
self.kmask = array([[exp(-0.05 * (k_x**2.0 + (k_y ** 2.0 * self.lx / self.ly))) for k_x in kx] for k_y in ky])
self.saved_curves = []
