def viz(
I, V, f, c, L, dt, C, T, # PDE paramteres
umin, umax, # Interval for u in plots
animate=True, # Simulation with animation?
tool='matplotlib', # 'matplotlib' or 'scitools'
solver_function=solver, # Function with numerical algorithm
version='vectorized', # 'scalar' or 'vectorized'
):
import wave1D_u0
if version == 'vectorized':
# Reuse viz from wave1D_u0, but with the present
# modules' new vectorized solver (which has
# version='vectorized' as default argument;
# wave1D_u0.viz does not feature this argument)
cpu = wave1D_u0.viz(
I, V, f, c, L, dt, C, T, umin, umax,
animate, tool, solver_function=solver)
elif version == 'scalar':
# Call wave1D_u0.viz with a solver with
# scalar code and use wave1D_u0.solver.
cpu = wave1D_u0.viz(
I, V, f, c, L, dt, C, T, umin, umax,
animate, tool,
solver_function=wave1D_u0.solver)
# Method 2: wrap this module's solver with an extra
# argument version='scalar'
#import functools
#scalar_solver = functools.partial(scalar, version='scalar')
return cpu
def viz(
I,
V,
f,
c,
L,
dt,
C,
T, # PDE paramteres
umin,
umax, # Interval for u in plots
animate=True, # Simulation with animation?
tool='matplotlib', # 'matplotlib' or 'scitools'
solver_function=solver, # Function with numerical algorithm
version='vectorized', # 'scalar' or 'vectorized'
):
import wave1D_u0
if version == 'vectorized':
# Reuse viz from wave1D_u0, but with the present
# modules' new vectorized solver (which has
# version='vectorized' as default argument;
# wave1D_u0.viz does not feature this argument)
cpu = wave1D_u0.viz(I,
V,
f,
c,
L,
dt,
C,
T,
umin,
umax,
animate,
tool,
solver_function=solver)
elif version == 'scalar':
# Call wave1D_u0.viz with a solver with
# scalar code and use wave1D_u0.solver.
cpu = wave1D_u0.viz(I,
V,
f,
c,
L,
dt,
C,
T,
umin,
umax,
animate,
tool,
solver_function=wave1D_u0.solver)
# Method 2: wrap this module's solver with an extra
# argument version='scalar'
#import functools
#scalar_solver = functools.partial(scalar, version='scalar')
return cpu
def plug(C=1, Nx=50, animate=True, T=2):
"""Plug profile as initial condition."""
def I(x):
if abs(x-L/2.0) > 0.1:
return 0
else:
return 1
L = 1.
c = 1
dt = (L/Nx)/c # choose the stability limit with given Nx
cpu = viz(I, None, None, c, L, dt, C, T,
umin=-1.1, umax=1.1, animate=animate)
def plug(C=1, Nx=50, animate=True, T=2):
"""Plug profile as initial condition."""
def I(x):
if abs(x-L/2.0) > 0.1:
return 0
else:
return 1
L = 1.
c = 1
dt = (L/Nx)/c # choose the stability limit with given Nx
cpu = viz(I, None, None, c, L, dt, C, T,
umin=-1.1, umax=1.1, animate=animate)
