"""An array class that has methods supporting the type of stencil
operations we see in finite-difference methods, like i+1, i-1, etc.
"""
import numbers
import numpy as np
def _buf_split(b):
""" take an integer or iterable and break it into a -x, +x, -y, +y
value representing a ghost cell buffer
"""
try:
bxlo, bxhi, bylo, byhi = b
except (ValueError, TypeError):
try:
blo, bhi = b
except (ValueError, TypeError):
blo = b
bhi = b
bxlo = bylo = blo
bxhi = byhi = bhi
return bxlo, bxhi, bylo, byhi
[docs]
class ArrayIndexer(np.ndarray):
"""a class that wraps the data region of a single cell-centered data
array (d) and allows us to easily do array operations like
d[i+1,j] using the ip() method.
"""
def __new__(cls, d, grid=None):
obj = np.asarray(d).view(cls)
obj.g = grid
obj.c = len(d.shape)
return obj
def __array_finalize__(self, obj):
if obj is None:
return
self.g = getattr(obj, "g", None)
self.c = getattr(obj, "c", None)
[docs]
def v(self, buf=0, n=0, s=1):
"""return a view of the valid data region for component n, with stride
s, and a buffer of ghost cells given by buf
"""
return self.ip_jp(0, 0, buf=buf, n=n, s=s)
[docs]
def ip(self, shift, buf=0, n=0, s=1):
"""return a view of the data shifted by shift in the x direction. By
default the view is the same size as the valid region, but the
buf can specify how many ghost cells on each side to include.
The component is n and s is the stride
"""
return self.ip_jp(shift, 0, buf=buf, n=n, s=s)
[docs]
def jp(self, shift, buf=0, n=0, s=1):
"""return a view of the data shifted by shift in the y direction. By
default the view is the same size as the valid region, but the
buf can specify how many ghost cells on each side to include.
The component is n and s is the stride
"""
return self.ip_jp(0, shift, buf=buf, n=n, s=s)
[docs]
def ip_jp(self, ishift, jshift, buf=0, n=0, s=1):
"""return a view of the data shifted by ishift in the x direction and
jshift in the y direction. By default the view is the same
size as the valid region, but the buf can specify how many
ghost cells on each side to include. The component is n and s
is the stride
"""
bxlo, bxhi, bylo, byhi = _buf_split(buf)
c = len(self.shape)
if c == 2:
return np.asarray(self[self.g.ilo-bxlo+ishift:self.g.ihi+1+bxhi+ishift:s,
self.g.jlo-bylo+jshift:self.g.jhi+1+byhi+jshift:s])
return np.asarray(self[self.g.ilo-bxlo+ishift:self.g.ihi+1+bxhi+ishift:s,
self.g.jlo-bylo+jshift:self.g.jhi+1+byhi+jshift:s, n])
[docs]
def lap(self, n=0, buf=0):
"""return the 5-point Laplacian"""
l = (self.ip(-1, n=n, buf=buf) - 2*self.v(n=n, buf=buf) + self.ip(1, n=n, buf=buf))/self.g.dx**2 + \
(self.jp(-1, n=n, buf=buf) - 2*self.v(n=n, buf=buf) + self.jp(1, n=n, buf=buf))/self.g.dy**2
return l
[docs]
def norm(self, n=0):
"""
find the norm of the quantity (index n) defined on the same grid,
in the domain's valid region
"""
c = len(self.shape)
if c == 2:
return np.sqrt(self.g.dx * self.g.dy *
np.sum((self[self.g.ilo:self.g.ihi+1, self.g.jlo:self.g.jhi+1]**2).flat))
_tmp = self[:, :, n]
return np.sqrt(self.g.dx * self.g.dy *
np.sum((_tmp[self.g.ilo:self.g.ihi+1, self.g.jlo:self.g.jhi+1]**2).flat))
[docs]
def copy(self, order='C'):
"""make a copy of the array, defined on the same grid"""
return ArrayIndexer(np.asarray(self).copy(order=order), grid=self.g)
[docs]
def is_symmetric(self, nodal=False, tol=1.e-14, asymmetric=False):
"""return True is the data is left-right symmetric (to the tolerance
tol) For node-centered data, set nodal=True
"""
# prefactor to convert from symmetric to asymmetric test
s = 1
if asymmetric:
s = -1
if not nodal:
L = self[self.g.ilo:self.g.ilo+self.g.nx//2,
self.g.jlo:self.g.jhi+1]
R = self[self.g.ilo+self.g.nx//2:self.g.ihi+1,
self.g.jlo:self.g.jhi+1]
else:
L = self[self.g.ilo:self.g.ilo+self.g.nx//2+1,
self.g.jlo:self.g.jhi+1]
print(self.g.ilo+self.g.nx//2, self.g.ihi+2)
R = self[self.g.ilo+self.g.nx//2:self.g.ihi+2,
self.g.jlo:self.g.jhi+1]
e = abs(L - s*np.flipud(R)).max()
return e < tol
[docs]
def is_asymmetric(self, nodal=False, tol=1.e-14):
"""return True is the data is left-right asymmetric (to the tolerance
tol)---e.g, the sign flips. For node-centered data, set nodal=True
"""
return self.is_symmetric(nodal=nodal, tol=tol, asymmetric=True)
[docs]
def fill_ghost(self, n=0, bc=None):
"""Fill the boundary conditions. This operates on a single component,
n. We do periodic, reflect-even, reflect-odd, and outflow
We need a BC object to tell us what BC type on each boundary.
"""
# there is only a single grid, so every boundary is on
# a physical boundary (except if we are periodic)
# Note: we piggy-back on outflow and reflect-odd for
# Neumann and Dirichlet homogeneous BCs respectively, but
# this only works for a single ghost cell
# -x boundary
if bc.xlb in ["outflow", "neumann"]:
if bc.xl_value is None:
for i in range(self.g.ilo):
self[i, :, n] = self[self.g.ilo, :, n]
else:
self[self.g.ilo-1, :, n] = \
self[self.g.ilo, :, n] - self.g.dx*bc.xl_value[:]
elif bc.xlb == "reflect-even":
for i in range(self.g.ilo):
self[i, :, n] = self[2*self.g.ng-i-1, :, n]
elif bc.xlb in ["reflect-odd", "dirichlet"]:
if bc.xl_value is None:
for i in range(self.g.ilo):
self[i, :, n] = -self[2*self.g.ng-i-1, :, n]
else:
self[self.g.ilo-1, :, n] = \
2*bc.xl_value[:] - self[self.g.ilo, :, n]
elif bc.xlb == "periodic":
for i in range(self.g.ilo):
self[i, :, n] = self[self.g.ihi-self.g.ng+i+1, :, n]
# +x boundary
if bc.xrb in ["outflow", "neumann"]:
if bc.xr_value is None:
for i in range(self.g.ihi+1, self.g.nx+2*self.g.ng):
self[i, :, n] = self[self.g.ihi, :, n]
else:
self[self.g.ihi+1, :, n] = \
self[self.g.ihi, :, n] + self.g.dx*bc.xr_value[:]
elif bc.xrb == "reflect-even":
for i in range(self.g.ng):
i_bnd = self.g.ihi+1+i
i_src = self.g.ihi-i
self[i_bnd, :, n] = self[i_src, :, n]
elif bc.xrb in ["reflect-odd", "dirichlet"]:
if bc.xr_value is None:
for i in range(self.g.ng):
i_bnd = self.g.ihi+1+i
i_src = self.g.ihi-i
self[i_bnd, :, n] = -self[i_src, :, n]
else:
self[self.g.ihi+1, :, n] = \
2*bc.xr_value[:] - self[self.g.ihi, :, n]
elif bc.xrb == "periodic":
for i in range(self.g.ihi+1, 2*self.g.ng + self.g.nx):
self[i, :, n] = self[i-self.g.ihi-1+self.g.ng, :, n]
# -y boundary
if bc.ylb in ["outflow", "neumann"]:
if bc.yl_value is None:
for j in range(self.g.jlo):
self[:, j, n] = self[:, self.g.jlo, n]
else:
self[:, self.g.jlo-1, n] = \
self[:, self.g.jlo, n] - self.g.dy*bc.yl_value[:]
elif bc.ylb == "reflect-even":
for j in range(self.g.jlo):
self[:, j, n] = self[:, 2*self.g.ng-j-1, n]
elif bc.ylb in ["reflect-odd", "dirichlet"]:
if bc.yl_value is None:
for j in range(self.g.jlo):
self[:, j, n] = -self[:, 2*self.g.ng-j-1, n]
else:
self[:, self.g.jlo-1, n] = \
2*bc.yl_value[:] - self[:, self.g.jlo, n]
elif bc.ylb == "periodic":
for j in range(self.g.jlo):
self[:, j, n] = self[:, self.g.jhi-self.g.ng+j+1, n]
# +y boundary
if bc.yrb in ["outflow", "neumann"]:
if bc.yr_value is None:
for j in range(self.g.jhi+1, self.g.ny+2*self.g.ng):
self[:, j, n] = self[:, self.g.jhi, n]
else:
self[:, self.g.jhi+1, n] = \
self[:, self.g.jhi, n] + self.g.dy*bc.yr_value[:]
elif bc.yrb == "reflect-even":
for j in range(self.g.ng):
j_bnd = self.g.jhi+1+j
j_src = self.g.jhi-j
self[:, j_bnd, n] = self[:, j_src, n]
elif bc.yrb in ["reflect-odd", "dirichlet"]:
if bc.yr_value is None:
for j in range(self.g.ng):
j_bnd = self.g.jhi+1+j
j_src = self.g.jhi-j
self[:, j_bnd, n] = -self[:, j_src, n]
else:
self[:, self.g.jhi+1, n] = \
2*bc.yr_value[:] - self[:, self.g.jhi, n]
elif bc.yrb == "periodic":
for j in range(self.g.jhi+1, 2*self.g.ng + self.g.ny):
self[:, j, n] = self[:, j-self.g.jhi-1+self.g.ng, n]
[docs]
def pretty_print(self, n=0, fmt=None, show_ghost=True):
"""
Print out a small dataset to the screen with the ghost cells
a different color, to make things stand out
"""
if fmt is None:
if issubclass(self.dtype.type, numbers.Integral):
fmt = "%4d"
elif self.dtype == np.float64:
fmt = "%10.5g"
else:
raise ValueError("ERROR: dtype not supported")
# print j descending, so it looks like a grid (y increasing
# with height)
if show_ghost:
ilo = 0
ihi = self.g.qx-1
jlo = 0
jhi = self.g.qy-1
else:
ilo = self.g.ilo
ihi = self.g.ihi
jlo = self.g.jlo
jhi = self.g.jhi
for j in reversed(range(jlo, jhi+1)):
for i in range(ilo, ihi+1):
if (j < self.g.jlo or j > self.g.jhi or
i < self.g.ilo or i > self.g.ihi):
gc = 1
else:
gc = 0
if self.c == 2:
val = self[i, j]
else:
try:
val = self[i, j, n]
except IndexError:
val = self[i, j]
if gc:
print("\033[31m" + fmt % (val) + "\033[0m", end="")
else:
print(fmt % (val), end="")
print(" ")
leg = """
^ y
|
+---> x
"""
print(leg)
[docs]
class ArrayIndexerFC(ArrayIndexer):
"""a class that wraps the data region of a single face-centered data
array (d) and allows us to easily do array operations like
d[i+1,j] using the ip() method.
"""
def __new__(cls, d, idir, grid=None):
obj = np.asarray(d).view(cls)
obj.g = grid
obj.idir = idir
obj.c = len(d.shape)
return obj
def __array_finalize__(self, obj):
if obj is None:
return
self.g = getattr(obj, "g", None)
self.idir = getattr(obj, "idir", None)
self.c = getattr(obj, "c", None)
[docs]
def ip_jp(self, ishift, jshift, buf=0, n=0, s=1):
"""return a view of the data shifted by ishift in the x direction and
jshift in the y direction. By default the view is the same
size as the valid region, but the buf can specify how many
ghost cells on each side to include. The component is n and s
is the stride
"""
bxlo, bxhi, bylo, byhi = _buf_split(buf)
c = len(self.shape)
if self.idir == 1: # pylint: disable=no-else-return
# face-centered in x
if c == 2:
return np.asarray(self[self.g.ilo-bxlo+ishift:self.g.ihi+2+bxhi+ishift:s,
self.g.jlo-bylo+jshift:self.g.jhi+1+byhi+jshift:s])
return np.asarray(self[self.g.ilo-bxlo+ishift:self.g.ihi+2+bxhi+ishift:s,
self.g.jlo-bylo+jshift:self.g.jhi+1+byhi+jshift:s, n])
else: # idir == 2
# face-centered in y
if c == 2:
return np.asarray(self[self.g.ilo-bxlo+ishift:self.g.ihi+1+bxhi+ishift:s,
self.g.jlo-bylo+jshift:self.g.jhi+2+byhi+jshift:s])
return np.asarray(self[self.g.ilo-bxlo+ishift:self.g.ihi+1+bxhi+ishift:s,
self.g.jlo-bylo+jshift:self.g.jhi+2+byhi+jshift:s, n])
[docs]
def lap(self, n=0, buf=0):
raise NotImplementedError("lap not implemented for ArrayIndexerFC")
[docs]
def norm(self, n=0):
"""
find the norm of the quantity (index n) defined on the same grid,
in the domain's valid region
"""
c = len(self.shape)
if self.idir == 1:
if c == 2:
return np.sqrt(self.g.dx * self.g.dy *
np.sum((self[self.g.ilo:self.g.ihi+2, self.g.jlo:self.g.jhi+1]**2).flat))
_tmp = self[:, :, n]
return np.sqrt(self.g.dx * self.g.dy *
np.sum((_tmp[self.g.ilo:self.g.ihi+2, self.g.jlo:self.g.jhi+1]**2).flat))
# idir == 2
if c == 2:
return np.sqrt(self.g.dx * self.g.dy *
np.sum((self[self.g.ilo:self.g.ihi+1, self.g.jlo:self.g.jhi+2]**2).flat))
_tmp = self[:, :, n]
return np.sqrt(self.g.dx * self.g.dy *
np.sum((_tmp[self.g.ilo:self.g.ihi+1, self.g.jlo:self.g.jhi+2]**2).flat))
[docs]
def copy(self, order='C'):
"""make a copy of the array, defined on the same grid"""
return ArrayIndexerFC(np.asarray(self).copy(order=order), self.idir, grid=self.g)
[docs]
def is_symmetric(self, nodal=False, tol=1.e-14, asymmetric=False):
"""return True is the data is left-right symmetric (to the tolerance
tol) For node-centered data, set nodal=True
"""
raise NotImplementedError()
[docs]
def is_asymmetric(self, nodal=False, tol=1.e-14):
"""return True is the data is left-right asymmetric (to the tolerance
tol)---e.g, the sign flips. For node-centered data, set nodal=True
"""
raise NotImplementedError()
[docs]
def fill_ghost(self, n=0, bc=None):
"""Fill the boundary conditions. This operates on a single component,
n. We do periodic, reflect-even, reflect-odd, and outflow
We need a BC object to tell us what BC type on each boundary.
"""
# there is only a single grid, so every boundary is on
# a physical boundary (except if we are periodic)
# Note: we piggy-back on outflow and reflect-odd for
# Neumann and Dirichlet homogeneous BCs respectively, but
# this only works for a single ghost cell
# -x boundary
if bc.xlb in ["outflow", "neumann", "reflect-even", "reflect-odd", "dirichlet"]:
raise NotImplementedError("boundary condition not implemented for -x")
if bc.xlb == "periodic":
if self.idir == 1:
# face-centered in x
for i in range(self.g.ilo):
self[i, :, n] = self[self.g.ihi-self.g.ng+i+1, :, n]
elif self.idir == 2:
# face-centered in y
for i in range(self.g.ilo):
self[i, :, n] = self[self.g.ihi-self.g.ng+i+1, :, n]
# +x boundary
if bc.xrb in ["outflow", "neumann", "reflect-even", "reflect-odd", "dirichlet"]:
raise NotImplementedError("boundary condition not implemented for +x")
if bc.xrb == "periodic":
if self.idir == 1:
# face-centered in x
for i in range(self.g.ihi+2, 2*self.g.ng + self.g.nx + 1):
self[i, :, n] = self[i-self.g.ihi-1+self.g.ng, :, n]
elif self.idir == 2:
# face-centered in y
for i in range(self.g.ihi+1, 2*self.g.ng + self.g.nx):
self[i, :, n] = self[i-self.g.ihi-1+self.g.ng, :, n]
# -y boundary
if bc.ylb in ["outflow", "neumann", "reflect-even", "reflect-odd", "dirichlet"]:
raise NotImplementedError("boundary condition not implemented for -y")
if bc.ylb == "periodic":
if self.idir == 1:
# face-centered in x
for j in range(self.g.jlo):
self[:, j, n] = self[:, self.g.jhi-self.g.ng+j+1, n]
elif self.idir == 2:
# face-centered in y
for j in range(self.g.jlo):
self[:, j, n] = self[:, self.g.jhi-self.g.ng+j+1, n]
# +y boundary
if bc.yrb in ["outflow", "neumann", "reflect-even", "reflect-odd", "dirichlet"]:
raise NotImplementedError("boundary condition not implemented for +y")
if bc.yrb == "periodic":
if self.idir == 1:
# face-centered in x
for j in range(self.g.jhi+1, 2*self.g.ng + self.g.ny):
self[:, j, n] = self[:, j-self.g.jhi-1+self.g.ng, n]
elif self.idir == 2:
for j in range(self.g.jhi+2, 2*self.g.ng + self.g.ny + 1):
self[:, j, n] = self[:, j-self.g.jhi-1+self.g.ng, n]
[docs]
def pretty_print(self, n=0, fmt=None, show_ghost=True):
"""
Print out a small dataset to the screen with the ghost cells
a different color, to make things stand out
"""
if fmt is None:
if issubclass(self.dtype.type, numbers.Integral):
fmt = "%4d"
elif self.dtype == np.float64:
fmt = "%10.5g"
else:
raise ValueError("ERROR: dtype not supported")
# print j descending, so it looks like a grid (y increasing
# with height)
ilo = ihi = jlo = jhi = -1
if show_ghost:
if self.idir == 1:
ilo = 0
ihi = self.g.qx
jlo = 0
jhi = self.g.qy-1
elif self.idir == 2:
ilo = 0
ihi = self.g.qx-1
jlo = 0
jhi = self.g.qy
else:
if self.idir == 1:
ilo = self.g.ilo
ihi = self.g.ihi+1
jlo = self.g.jlo
jhi = self.g.jhi
elif self.idir == 2:
ilo = self.g.ilo
ihi = self.g.ihi
jlo = self.g.jlo
jhi = self.g.jhi+1
for j in reversed(range(jlo, jhi+1)):
for i in range(ilo, ihi+1):
gc = None
if self.idir == 1:
if (j < self.g.jlo or j > self.g.jhi or
i < self.g.ilo or i > self.g.ihi+1):
gc = 1
else:
gc = 0
elif self.idir == 2:
if (j < self.g.jlo or j > self.g.jhi+1 or
i < self.g.ilo or i > self.g.ihi):
gc = 1
else:
gc = 0
if self.c == 2:
val = self[i, j]
else:
val = self[i, j, n]
if gc:
print("\033[31m" + fmt % (val) + "\033[0m", end="")
else:
print(fmt % (val), end="")
print(" ")
leg = """
^ y
|
+---> x
"""
print(leg)
