def closest_point(self, x):
th, r = cart2pol(*(x - self.center).T)
cpx, cpy = pol2cart(th, self.radius)
dist = np.abs(r - self.radius)
cp = np.column_stack((cpx, cpy)) + self.center
# Maybe we should return np.zeros(dist.shape) instead of just one 0?
return cp, dist, 0, {}
def closest_point(self, x):
th, r = cart2pol(*(x-self.center).T)
cpx, cpy = pol2cart(th, self.radius)
dist = np.abs(r - self.radius)
cp = np.column_stack((cpx, cpy)) + self.center
# Maybe we should return np.zeros(dist.shape) instead of just one 0?
return cp, dist, 0, {}
def closestPointToCartesian(self, xx):
# TODO: could probably be vectorized
x,y = xx - self._center
th, r = cart2pol(x, y)
x, y = pol2cart(th, self._radius)
cp = self._center + a([x,y])
dist = norm(xx - cp, 2)
return cp, dist, 0, {}
def closestPointVectorized(self, x, y):
th, r = cart2pol(x - self._center[0], y - self._center[1])
cpx, cpy = pol2cart(th, self._radius)
#dist = norm(xx - cp, 2)
#dist = sqrt( (x-cpx)**2 + (y-cpy)**2 )
sdist = r - self._radius
cpx = cpx + self._center[0]
cpy = cpy + self._center[1]
return cpx, cpy, sdist, 0, {}
def closest_point(self, x):
x = np.atleast_2d(x)
r = np.sqrt(np.sum((x - self.center)**2, axis=1))
xm = x.copy()
r_eq_0 = r == 0
xm[r_eq_0, 0] = self.center[0] + 1
r[r_eq_0] = 1
dim = self.dim
cpx = np.zeros(x.shape)
bdy = np.zeros(x.shape[0])
below_semicircle = xm[:, -1] < self.center[-1]
if dim == 2:
left = (xm[:, 0] <= self.center[0]) & below_semicircle
cpx[left] = self.center - np.array([self.radius, 0.])
bdy[left] = 1
right = ~left & below_semicircle
cpx[right] = self.center + np.array([self.radius, 0.])
bdy[right] = 2
elif dim == 3:
# Here it doesn't matter if xm[below_semicircle, *] has
# shape (0,) because adding a scalar "works" (ie, xx has
# also shape (0,))
xx = xm[below_semicircle, 0] - self.center[0]
yy = xm[below_semicircle, 1] - self.center[1]
th, _ = cart2pol(xx, yy)
xx, yy = pol2cart(th, self.radius)
cpx[below_semicircle] = (np.column_stack((xx,
yy ,
np.zeros(xx.shape))) +
self.center)
bdy[below_semicircle] = 1
else:
raise NotImplementedError(
'Dim {0} not implemented'.format(dim)
)
rest = ~below_semicircle
# This is needed, if xm[rest] is empty (ie shape (0,)) trying
# to add an array results in a ValueError: operands could not
# be broadcast together
if rest.any():
c = (self.radius / r[rest])[:, np.newaxis]
cpx[rest] = c * (xm[rest] - self.center) + self.center
bdy[rest] = 0
dist = np.sqrt(np.sum((x - cpx)**2, axis=1))
return cpx, dist, bdy, {}
def closestPointToCartesian(self, x):
SURF_CEN = self._center
SURF_SR = self._radius
r = norm(x - SURF_CEN, 2)
if (r==0):
tx = SURF_CEN[0] + 1.0
r = 1.0
else:
tx = x[0]
xm = x.copy()
xm[0] = tx
#dim = len(x)
dim = self._dim
if (xm[-1] < SURF_CEN[-1]):
# "below" semicircle,
if (dim == 2):
if (xm[0] <= SURF_CEN[0]): # left
cpx = SURF_CEN - a([SURF_SR, 0.0])
bdy = 1
else: # right
cpx = SURF_CEN + a([SURF_SR, 0.0])
bdy = 2
if (dim == 3):
xx = xm[0] - SURF_CEN[0]
yy = xm[1] - SURF_CEN[1]
th,r = cart2pol(xx,yy)
xx,yy = pol2cart(th,SURF_SR)
cpx = SURF_CEN + a([xx,yy,0])
bdy = 1
if (dim >= 4):
# general case possible?
raise NameError('4D and higher not implemented')
else:
# at or "above" semicircle: same as for whole circle
c = SURF_SR / r
cpx = c*(xm-SURF_CEN) + SURF_CEN
bdy = 0
dist = norm(cpx - x, 2)
return cpx, dist, bdy, {}
def closest_point(self, x):
x = np.atleast_2d(x)
r = np.sqrt(np.sum((x - self.center)**2, axis=1))
xm = x.copy()
r_eq_0 = r == 0
xm[r_eq_0, 0] = self.center[0] + 1
r[r_eq_0] = 1
dim = self.dim
cpx = np.zeros(x.shape)
bdy = np.zeros(x.shape[0])
below_semicircle = xm[:, -1] < self.center[-1]
if dim == 2:
left = (xm[:, 0] <= self.center[0]) & below_semicircle
cpx[left] = self.center - np.array([self.radius, 0.])
bdy[left] = 1
right = ~left & below_semicircle
cpx[right] = self.center + np.array([self.radius, 0.])
bdy[right] = 2
elif dim == 3:
# Here it doesn't matter if xm[below_semicircle, *] has
# shape (0,) because adding a scalar "works" (ie, xx has
# also shape (0,))
xx = xm[below_semicircle, 0] - self.center[0]
yy = xm[below_semicircle, 1] - self.center[1]
th, _ = cart2pol(xx, yy)
xx, yy = pol2cart(th, self.radius)
cpx[below_semicircle] = (np.column_stack(
(xx, yy, np.zeros(xx.shape))) + self.center)
bdy[below_semicircle] = 1
else:
raise NotImplementedError('Dim {0} not implemented'.format(dim))
rest = ~below_semicircle
# This is needed, if xm[rest] is empty (ie shape (0,)) trying
# to add an array results in a ValueError: operands could not
# be broadcast together
if rest.any():
c = (self.radius / r[rest])[:, np.newaxis]
cpx[rest] = c * (xm[rest] - self.center) + self.center
bdy[rest] = 0
dist = np.sqrt(np.sum((x - cpx)**2, axis=1))
return cpx, dist, bdy, {}
def closest_point_loop(self, x):
r = np.linalg.norm(x - self.center, 2)
if r==0:
tx = self.center[0] + 1.0
r = 1.0
else:
tx = x[0]
xm = x.copy()
xm[0] = tx
dim = self.dim
if xm[-1] < self.center[-1]:
# "below" semicircle,
if dim == 2:
if xm[0] <= self.center[0]: # left
cpx = self.center - np.array([self.radius, 0.0])
bdy = 1
else: # right
cpx = self.center + np.array([self.radius, 0.0])
bdy = 2
elif dim == 3:
xx = xm[0] - self.center[0]
yy = xm[1] - self.center[1]
th, r = cart2pol(xx,yy)
xx, yy = pol2cart(th, self.radius)
cpx = self.center + np.array([xx,yy,0])
bdy = 1
else:
# general case possible?
raise NotImplementedError(
'Dim {0} not implemented'.format(dim)
)
else:
# at or "above" semicircle: same as for whole circle
c = self.radius / r
cpx = c*(xm-self.center) + self.center
bdy = 0
dist = np.linalg.norm(cpx - x, 2)
return cpx, dist, bdy, {}
def closest_point_loop(self, x):
r = np.linalg.norm(x - self.center, 2)
if r == 0:
tx = self.center[0] + 1.0
r = 1.0
else:
tx = x[0]
xm = x.copy()
xm[0] = tx
dim = self.dim
if xm[-1] < self.center[-1]:
# "below" semicircle,
if dim == 2:
if xm[0] <= self.center[0]: # left
cpx = self.center - np.array([self.radius, 0.0])
bdy = 1
else: # right
cpx = self.center + np.array([self.radius, 0.0])
bdy = 2
elif dim == 3:
xx = xm[0] - self.center[0]
yy = xm[1] - self.center[1]
th, r = cart2pol(xx, yy)
xx, yy = pol2cart(th, self.radius)
cpx = self.center + np.array([xx, yy, 0])
bdy = 1
else:
# general case possible?
raise NotImplementedError(
'Dim {0} not implemented'.format(dim))
else:
# at or "above" semicircle: same as for whole circle
c = self.radius / r
cpx = c * (xm - self.center) + self.center
bdy = 0
dist = np.linalg.norm(cpx - x, 2)
return cpx, dist, bdy, {}
def closestPointToCartesian(self, xx):
x,y = xx - self.center
th,r = cart2pol(x, y)
if ((th >= self.angle1) and (th <= self.angle2)):
(cpx,cpy) = pol2cart(th, self.radius)
bdy = 0
dist = norm( a([x, y]) - a([cpx,cpy]), 2)
else:
# check the two end points
(cpx,cpy) = pol2cart(self.angle1, self.radius)
dist = norm( a([x, y]) - a([cpx,cpy]), 2)
bdy = 1
(cpx2,cpy2) = pol2cart(self.angle2, self.radius)
dist2 = norm( a([x, y]) - a([cpx2,cpy2]), 2)
if (dist2 < dist):
cpx = cpx2
cpy = cpy2
dist = dist2
bdy = 2
cp = self.center + a([cpx,cpy])
return cp, dist, bdy, {}
def closestPointToCartesian(self, xx):
x, y = xx - self.center
th, r = cart2pol(x, y)
if ((th >= self.angle1) and (th <= self.angle2)):
(cpx, cpy) = pol2cart(th, self.radius)
bdy = 0
dist = norm(a([x, y]) - a([cpx, cpy]), 2)
else:
# check the two end points
(cpx, cpy) = pol2cart(self.angle1, self.radius)
dist = norm(a([x, y]) - a([cpx, cpy]), 2)
bdy = 1
(cpx2, cpy2) = pol2cart(self.angle2, self.radius)
dist2 = norm(a([x, y]) - a([cpx2, cpy2]), 2)
if (dist2 < dist):
cpx = cpx2
cpy = cpy2
dist = dist2
bdy = 2
cp = self.center + a([cpx, cpy])
return cp, dist, bdy, {}
