def yCos(parm, r=0):
"""
parm: (amp,freq,phase,mean)
amp * N.sin(freq*r + phase(deg)) + mean
r: degree (not radian!!)
"""
a, b, c, d = parm
r = U.deg2rad(r)
c = U.deg2rad(c)
return a * N.cos(b * r + c) + d
def yCos(parm, r=0):
"""
parm: (amp,freq,phase,mean)
amp * N.sin(freq*r + phase(deg)) + mean
r: degree (not radian!!)
"""
a, b, c, d = parm
r = U.deg2rad(r)
c = U.deg2rad(c)
return a * N.cos(b*r + c) + d
def transformMatrix(rot=0.0, mag=1.0):
"""
retrn invmat
"""
rotRadian = N.pi / 180. * rot
cosTheta = N.cos(rotRadian)
sinTheta = N.sin(rotRadian)
affmatrix = N.array([[cosTheta, sinTheta], [-sinTheta, cosTheta]]) * mag
invmat = N.linalg.inv(affmatrix)
return invmat
def transformMatrix(rot=0.0, mag=1.0):
"""
retrn invmat
"""
rotRadian = N.pi / 180. * rot
cosTheta = N.cos(rotRadian)
sinTheta = N.sin(rotRadian)
affmatrix = N.array([ [cosTheta, sinTheta], [-sinTheta, cosTheta] ]) * mag
invmat = N.linalg.inv(affmatrix)
return invmat
def logpolar(image, center=None, angles=None, radii=None):
"""Return log-polar transformed image and log base."""
shape = image.shape
if center is None:
center = shape[0] / 2, shape[1] / 2
if angles is None:
angles = shape[0]
if radii is None:
radii = shape[1]
theta = N.zeros((angles, radii), dtype=N.float64)
theta.T[:] = -N.linspace(0, N.pi, angles, endpoint=False)
#d = radii
d = N.hypot(shape[0] - center[0], shape[1] - center[1])
log_base = 10.0**(N.log10(d) / (radii))
radius = N.empty_like(theta)
radius[:] = N.power(log_base, N.arange(radii, dtype=N.float64)) - 1.0
x = radius * N.sin(theta) + center[0]
y = radius * N.cos(theta) + center[1]
output = N.zeros_like(x)
ndii.map_coordinates(image, [x, y], output=output)
return output, log_base
def logpolar(image, center=None, angles=None, radii=None):
"""Return log-polar transformed image and log base."""
shape = image.shape
if center is None:
center = shape[0] / 2, shape[1] / 2
if angles is None:
angles = shape[0]
if radii is None:
radii = shape[1]
theta = N.zeros((angles, radii), dtype=N.float64)
theta.T[:] = -N.linspace(0, N.pi, angles, endpoint=False)
#d = radii
d = N.hypot(shape[0]-center[0], shape[1]-center[1])
log_base = 10.0 ** (N.log10(d) / (radii))
radius = N.empty_like(theta)
radius[:] = N.power(log_base, N.arange(radii,
dtype=N.float64)) - 1.0
x = radius * N.sin(theta) + center[0]
y = radius * N.cos(theta) + center[1]
output = N.zeros_like(x)
ndii.map_coordinates(image, [x, y], output=output)
return output, log_base
