state.index_capa = 2
#===========================================================================
# Set up controller and controller parameters
#===========================================================================
claw = pyclaw.Controller()
claw.keep_copy = False
claw.output_style = 1
claw.num_output_times = 10
claw.tfinal = 1.0
claw.solution = pyclaw.Solution(state, domain)
claw.solver = solver
claw.outdir = outdir
#===========================================================================
# Solve the problem
#===========================================================================
status = claw.run()
#===========================================================================
# Plot results
#===========================================================================
if htmlplot: pyclaw.plot.html_plot(outdir=outdir)
if iplot: pyclaw.plot.interactive_plot(outdir=outdir)
if __name__ == "__main__":
from pyclaw.util import run_app_from_main
output = run_app_from_main(advection_annulus)
print 'Error: ', output
state.aux_global = {}
state.aux_global['turnZero_half_2D'] = turnZero_half_2D
state.aux_global['t_turnZero'] = t_turnZero
state.mp = 1
state.aux = setaux(grid.x.center,grid.y.center)
#Initial condition
qinit(state,A,x0,y0,varx,vary)
claw.solution = pyclaw.Solution(state)
claw.nout = nout
#claw.p_function = p_function
claw.compute_F = compute_F
grid.add_gauges([[0.25,0.25],[0.75,0.25],[0.25,0.75],[0.75,0.75]])
solver.compute_gauge_values = gauge_pfunction
claw.write_aux_init = False
#Solve
status = claw.run()
#strain=claw.frames[claw.nout].state.gqVec.getArray().reshape([grid.ng[0],grid.ng[1],meqn])[:,:,0]
#return strain
if iplot: pyclaw.plot.interactive_plot()
if htmlplot: pyclaw.plot.html_plot()
if __name__=="__main__":
from pyclaw.util import run_app_from_main
output = run_app_from_main(psystem2D)
state.problem_data['cc']=sqrt(bulk/rho)
#========================================================================
# Set the initial condition
#========================================================================
xc=domain.grid.x.centers
beta=100; gamma=0; x0=0.75
state.q[0,:] = exp(-beta * (xc-x0)**2) * cos(gamma * (xc - x0))
state.q[1,:] = 0.
#========================================================================
# Set up the controller object
#========================================================================
claw = pyclaw.Controller()
claw.solution = pyclaw.Solution(state,domain)
claw.solver = solver
claw.outdir = outdir
claw.tfinal = 1.0
# Solve
status = claw.run()
# Plot results
if htmlplot: pyclaw.plot.html_plot(outdir=outdir)
if iplot: pyclaw.plot.interactive_plot(outdir=outdir)
if __name__=="__main__":
from pyclaw.util import run_app_from_main
output = run_app_from_main(acoustics)
claw.keep_copy = False
claw.outstyle = 1
claw.nout = 10
claw.tfinal = 1.0
claw.solution = pyclaw.Solution(state)
claw.solver = solver
claw.outdir = outdir
#===========================================================================
# Solve the problem
#===========================================================================
status = claw.run()
#===========================================================================
# Plot results
#===========================================================================
if htmlplot: pyclaw.plot.html_plot(outdir=outdir)
if iplot: pyclaw.plot.interactive_plot(outdir=outdir)
if __name__=="__main__":
from pyclaw.util import run_app_from_main
output = run_app_from_main(advection_annulus)
print 'Error: ',output
a2=1.0 #a2values[ii]
KB = Z
rhoB = Z
state.aux_global['KB'] = KB
state.aux_global['rhoB'] = rhoB
state.aux_global['trdone'] = False
state.aux=setaux(xc,rhoB,KB,rhoA,KA,alpha,bc_lower,xupper=xupper)
grid.x.bc_lower=2
grid.x.bc_upper=2
state.t = 0.0
qinit(state,ic=2,a2=a2)
init_solution = Solution(state)
claw.solution = init_solution
claw.solution.t = 0.0
claw.tfinal = tfinal
claw.outdir = './_output_Z'+str(Z)+'_'+str(cellsperlayer)
status = claw.run()
else:
# Solve
status = claw.run()
if htmlplot: pyclaw.plot.html_plot(outdir=outdir)
if iplot: pyclaw.plot.interactive_plot(outdir=outdir)
if __name__=="__main__":
from pyclaw.util import run_app_from_main
output = run_app_from_main(stegoton)
meqn = 5
maux=8
state = pyclaw.State(grid,meqn,maux)
state.aux_global['gamma']= gamma
state.aux_global['gamma1']= gamma1
qinit(state)
auxinit(state)
solver.user_bc_lower=shockbc
claw = pyclaw.Controller()
claw.tfinal = 0.75
claw.solution = pyclaw.Solution(state)
claw.solver = solver
claw.nout = 10
claw.outdir = outdir
# Solve
status = claw.run()
if htmlplot: pyclaw.plot.html_plot(outdir=outdir)
if iplot: pyclaw.plot.interactive_plot(outdir=outdir)
return claw.solution.q
if __name__=="__main__":
from pyclaw.util import run_app_from_main
output = run_app_from_main(shockbubble)
state.q[1, :] = 0.
#===========================================================================
# Setup controller and controller paramters
#===========================================================================
claw = pyclaw.Controller()
claw.keep_copy = True
claw.tfinal = 2.0
claw.solution = pyclaw.Solution(state, domain)
claw.solver = solver
claw.outdir = outdir
#===========================================================================
# Solve the problem
#===========================================================================
status = claw.run()
#===========================================================================
# Plot results
#===========================================================================
if iplot:
pyclaw.plot.interactive_plot(outdir=outdir,
file_format=claw.output_format)
if htmlplot:
pyclaw.plot.html_plot(outdir=outdir, file_format=claw.output_format)
if __name__ == "__main__":
from pyclaw.util import run_app_from_main
output = run_app_from_main(shallow1D)
rhoB,
KB,
rhoA,
KA,
alpha,
bc_lower,
xupper=xupper)
patch.x.bc_lower = 2
patch.x.bc_upper = 2
state.t = 0.0
qinit(state, ic=2, a2=a2)
init_solution = Solution(state, domain)
claw.solution = init_solution
claw.solution.t = 0.0
claw.tfinal = tfinal
claw.outdir = './_output_Z' + str(Z) + '_' + str(cellsperlayer)
status = claw.run()
else:
# Solve
status = claw.run()
if htmlplot: pyclaw.plot.html_plot(outdir=outdir)
if iplot: pyclaw.plot.interactive_plot(outdir=outdir)
if __name__ == "__main__":
from pyclaw.util import run_app_from_main
output = run_app_from_main(stegoton)
num_aux = 1
state = pyclaw.State(domain, num_eqn, num_aux)
state.problem_data['gamma'] = gamma
state.problem_data['gamma1'] = gamma1
qinit(state)
auxinit(state)
solver.user_bc_lower = shockbc
claw = pyclaw.Controller()
claw.tfinal = 0.75
claw.solution = pyclaw.Solution(state, domain)
claw.solver = solver
claw.num_output_times = 10
claw.outdir = outdir
# Solve
status = claw.run()
if htmlplot: pyclaw.plot.html_plot(outdir=outdir)
if iplot: pyclaw.plot.interactive_plot(outdir=outdir)
return claw.solution.q
if __name__ == "__main__":
from pyclaw.util import run_app_from_main
output = run_app_from_main(shockbubble)
ts.setTimeStep(solver.dt)
ts.setDuration(claw.tfinal, max_steps=1000)
ts.setFromOptions()
q0 = x[:].copy()
ts.solve(x)
qfinal = x[:].copy()
dx = grid.d[0]
else:
status = claw.run()
#This test is set up so that the waves pass through the domain
#exactly once, and the final solution should be equal to the
#initial condition. Here we output the 1-norm of their difference.
q0=claw.frames[0].grid.gqVec.getArray().reshape([-1])
qfinal=claw.frames[claw.nout].grid.gqVec.getArray().reshape([-1])
dx=claw.frames[0].grid.d[0]
if htmlplot: plot.html_plot(outdir=outdir,format=output_format)
if iplot: plot.interactive_plot(outdir=outdir,format=output_format)
if petscPlot: plot.plotPetsc(output_object)
print 'Max error:', np.max(qfinal - q0)
return dx*np.sum(np.abs(qfinal-q0))
if __name__=="__main__":
from pyclaw.util import run_app_from_main
error = run_app_from_main(acoustics)
print 'Error: ',error
x = pyclaw.Dimension('x',-2.0,2.0,mx)
y = pyclaw.Dimension('y',-2.0,2.0,my)
domain = pyclaw.Domain([x,y])
num_eqn = 1
state = pyclaw.State(domain,num_eqn)
qinit(state)
solver.dimensional_split = 1
solver.cfl_max = 1.0
solver.cfl_desired = 0.9
solver.num_waves = 2
solver.limiters = pyclaw.limiters.tvd.minmod
claw = pyclaw.Controller()
claw.tfinal = 1.0
claw.solution = pyclaw.Solution(state,domain)
claw.solver = solver
claw.num_output_times = 10
# Solve
status = claw.run()
if htmlplot: pyclaw.plot.html_plot(outdir=outdir)
if iplot: pyclaw.plot.interactive_plot(outdir=outdir)
if __name__=="__main__":
from pyclaw.util import run_app_from_main
output = run_app_from_main(kpp)
hu = np.zeros((mx, my))
hv = np.zeros((mx, my))
hw = np.zeros((mx, my))
# Read solution
for j in range(my):
tmp = np.fromfile(f, dtype='float', sep=" ", count=4 * mx)
tmp = tmp.reshape((mx, 4))
h[:, j] = tmp[:, 0]
hu[:, j] = tmp[:, 1]
hv[:, j] = tmp[:, 2]
hw[:, j] = tmp[:, 3]
# Plot solution in the computational domain
# =========================================
# Fluid height
plt.figure()
CS = plt.contour(xc, yc, h)
plt.title('Fluid height (computational domain)')
plt.xlabel('xc')
plt.ylabel('yc')
plt.clabel(CS, inline=1, fontsize=10)
plt.show()
if __name__ == "__main__":
from pyclaw.util import run_app_from_main
output = run_app_from_main(contourLineSphere)
print 'Error: ', output
hv = np.zeros((mx,my))
hw = np.zeros((mx,my))
# Read solution
for j in range(my):
tmp = np.fromfile(f,dtype='float',sep=" ",count=4*mx)
tmp = tmp.reshape((mx,4))
h[:,j] = tmp[:,0]
hu[:,j] = tmp[:,1]
hv[:,j] = tmp[:,2]
hw[:,j] = tmp[:,3]
# Plot solution in the computational domain
# =========================================
# Fluid height
plt.figure()
CS = plt.contour(xc,yc,h)
plt.title('Fluid height (computational domain)')
plt.xlabel('xc')
plt.ylabel('yc')
plt.clabel(CS, inline=1, fontsize=10)
plt.show()
if __name__=="__main__":
from pyclaw.util import run_app_from_main
output = run_app_from_main(contourLineSphere)
print 'Error: ',output
state.problem_data['cc']=np.sqrt(bulk/rho)
#========================================================================
# Set the initial condition
#========================================================================
xc=grid.x.center
beta=100; gamma=0; x0=0.75
state.q[0,:] = 0.5*np.exp(-80 * xc**2) + 0.5*(np.abs(xc+0.2)<0.1)
state.q[1,:] = 0.
#========================================================================
# Set up the controller object
#========================================================================
claw = pyclaw.Controller()
claw.solution = pyclaw.Solution(state)
claw.solver = solver
claw.outdir = outdir
claw.tfinal = 3.0
claw.num_output_times = 30
# Solve
status = claw.run()
# Plot results
if htmlplot: pyclaw.plot.html_plot(outdir=outdir)
if iplot: pyclaw.plot.interactive_plot(outdir=outdir)
if __name__=="__main__":
from pyclaw.util import run_app_from_main
output = run_app_from_main(fig_31_38)
x = pyclaw.Dimension('x', -8.0, 8.0, 1000)
grid = pyclaw.Grid(x)
num_eqn = 1
state = pyclaw.State(grid, num_eqn)
xc = grid.x.center
state.q[0, :] = (xc > -np.pi) * (xc < np.pi) * (2. * np.sin(3. * xc) +
np.cos(2. * xc) + 0.2)
state.q[0, :] = state.q[0, :] * (np.cos(xc) + 1.)
state.problem_data['efix'] = True
#===========================================================================
# Setup controller and controller parameters. Then solve the problem
#===========================================================================
claw = pyclaw.Controller()
claw.tfinal = 6.0
claw.num_output_times = 30
claw.solution = pyclaw.Solution(state)
claw.solver = solver
claw.outdir = outdir
status = claw.run()
if htmlplot: pyclaw.plot.html_plot(outdir=outdir)
if iplot: pyclaw.plot.interactive_plot(outdir=outdir)
if __name__ == "__main__":
from pyclaw.util import run_app_from_main
output = run_app_from_main(burgers)
state.aux_global['cc']=np.sqrt(bulk/rho)
#========================================================================
# Set the initial condition
#========================================================================
xc=grid.x.center
beta=100; gamma=0; x0=0.75
state.q[0,:] = 0.5*np.exp(-80 * xc**2) + 0.5*(np.abs(xc+0.2)<0.1)
state.q[1,:] = 0.
#========================================================================
# Set up the controller object
#========================================================================
claw = pyclaw.Controller()
claw.solution = pyclaw.Solution(state)
claw.solver = solver
claw.outdir = outdir
claw.tfinal = 3.0
claw.nout = 30
# Solve
status = claw.run()
# Plot results
if htmlplot: pyclaw.plot.html_plot(outdir=outdir)
if iplot: pyclaw.plot.interactive_plot(outdir=outdir)
if __name__=="__main__":
from pyclaw.util import run_app_from_main
output = run_app_from_main(fig_31_38)
state = pyclaw.State(grid,meqn)
state.aux_global['gamma']= gamma
state.aux_global['gamma1']= gamma1
state.q[0,:] = 1.
state.q[1,:] = 0.
x =state.grid.x.center
state.q[2,:] = ( (x<0.1)*1.e3 + (0.1<=x)*(x<0.9)*1.e-2 + (0.9<=x)*1.e2 ) / gamma1
solver.limiters = 4
claw = pyclaw.Controller()
claw.tfinal = 0.038
claw.solution = pyclaw.Solution(state)
claw.solver = solver
claw.nout = 10
claw.outdir = outdir
# Solve
status = claw.run()
if htmlplot: pyclaw.plot.html_plot(outdir=outdir)
if iplot: pyclaw.plot.interactive_plot(outdir=outdir)
return claw.solution.q
if __name__=="__main__":
from pyclaw.util import run_app_from_main
output = run_app_from_main(wcblast)
solver.limiters = pyclaw.limiters.tvd.MC
solver.bc_lower[0] = 2
solver.bc_upper[0] = 2
solver.aux_bc_lower[0] = 2
solver.aux_bc_upper[0] = 2
xlower=0.0; xupper=1.0; mx=100
x = pyclaw.Dimension('x',xlower,xupper,mx)
grid = pyclaw.Grid(x)
maux=1
meqn = 1
state = pyclaw.State(grid,meqn,maux)
qinit(state)
auxinit(state)
claw = pyclaw.Controller()
claw.outdir = outdir
claw.solution = pyclaw.Solution(state)
claw.solver = solver
claw.tfinal = 1.0
status = claw.run()
if htmlplot: pyclaw.plot.html_plot(outdir=outdir)
if iplot: pyclaw.plot.interactive_plot(outdir=outdir)
if __name__=="__main__":
from pyclaw.util import run_app_from_main
output = run_app_from_main(vc_advection)
#qinit(state,mx,my)
#===========================================================================
# Set up controller and controller parameters
#===========================================================================
claw = pyclaw.Controller()
claw.keep_copy = False
claw.output_style = 1
claw.num_output_times = 10
claw.tfinal = 10
claw.solution = pyclaw.Solution(state,domain)
claw.solver = solver
claw.outdir = outdir
#===========================================================================
# Solve the problem
#===========================================================================
status = claw.run()
#===========================================================================
# Plot results
#===========================================================================
if htmlplot: pyclaw.plot.html_plot(outdir=outdir)
if iplot: pyclaw.plot.interactive_plot(outdir=outdir)
if __name__=="__main__":
from pyclaw.util import run_app_from_main
output = run_app_from_main(shallow_4_Rossby_Haurwitz)
solver.aux_bc_lower[0] = 2
solver.aux_bc_upper[0] = 2
xlower = 0.0
xupper = 1.0
mx = 100
x = pyclaw.Dimension('x', xlower, xupper, mx)
domain = pyclaw.Domain(x)
num_aux = 1
num_eqn = 1
state = pyclaw.State(domain, num_eqn, num_aux)
qinit(state)
auxinit(state)
claw = pyclaw.Controller()
claw.outdir = outdir
claw.solution = pyclaw.Solution(state, domain)
claw.solver = solver
claw.tfinal = 1.0
status = claw.run()
if htmlplot: pyclaw.plot.html_plot(outdir=outdir)
if iplot: pyclaw.plot.interactive_plot(outdir=outdir)
if __name__ == "__main__":
from pyclaw.util import run_app_from_main
output = run_app_from_main(vc_advection)
state.problem_data['t_turnZero'] = t_turnZero
state.mp = 1
grid = state.grid
state.aux = setaux(grid.x.centers, grid.y.centers)
#Initial condition
qinit(state, A, x0, y0, varx, vary)
claw.solution = pyclaw.Solution(state, domain)
claw.num_output_times = num_output_times
#claw.p_function = p_function
claw.compute_F = compute_F
grid.add_gauges([[0.25, 0.25], [0.75, 0.25], [0.25, 0.75], [0.75, 0.75]])
solver.compute_gauge_values = gauge_pfunction
claw.write_aux_init = False
#Solve
status = claw.run()
#strain=claw.frames[claw.num_output_times].state.gqVec.getArray().reshape([grid.num_cells[0],grid.num_cells[1],num_eqn])[:,:,0]
#return strain
if iplot: pyclaw.plot.interactive_plot()
if htmlplot: pyclaw.plot.html_plot()
if __name__ == "__main__":
from pyclaw.util import run_app_from_main
output = run_app_from_main(psystem2D)
#===========================================================================
x = pyclaw.Dimension('x',0.0,1.0,500)
grid = pyclaw.Grid(x)
meqn = 1
state = pyclaw.State(grid,meqn)
xc=grid.x.center
state.q[0,:] = np.sin(np.pi*2*xc) + 0.50
state.aux_global['efix']=True
#===========================================================================
# Setup controller and controller parameters. Then solve the problem
#===========================================================================
claw = pyclaw.Controller()
claw.tfinal =0.5
claw.solution = pyclaw.Solution(state)
claw.solver = solver
claw.outdir = outdir
status = claw.run()
if htmlplot: pyclaw.plot.html_plot(outdir=outdir)
if iplot: pyclaw.plot.interactive_plot(outdir=outdir)
if __name__=="__main__":
from pyclaw.util import run_app_from_main
output = run_app_from_main(burgers)
print 'Error: ',output
# Set up controller and controller parameters
#===========================================================================
claw = pyclaw.Controller()
claw.tfinal = 2.5
claw.solution = pyclaw.Solution(state,domain)
claw.solver = solver
claw.outdir = outdir
claw.num_output_times = 10
#===========================================================================
# Solve the problem
#===========================================================================
status = claw.run()
#===========================================================================
# Plot results
#===========================================================================
if iplot: plot.interactive_plot(outdir=outdir,format=claw.output_format)
if htmlplot: plot.html_plot(outdir=outdir,format=claw.output_format)
if __name__=="__main__":
from pyclaw.util import run_app_from_main
output = run_app_from_main(shallow2D)
print 'Error: ', output
solver.cfl_desired = 0.8
x = pyclaw.Dimension('x',0.0,1.0,mx)
grid = pyclaw.Grid(x)
num_eqn = 1
state = pyclaw.State(grid,num_eqn)
state.problem_data['u']=1.
xc=grid.x.center
if IC=='gauss_square':
state.q[0,:] = np.exp(-beta * (xc-x0)**2) + (xc>0.6)*(xc<0.8)
elif IC=='wavepacket':
state.q[0,:] = np.exp(-beta * (xc-x0)**2) * np.sin(80.*xc)
else:
raise Exception('Unrecognized initial condition specification.')
claw = pyclaw.Controller()
claw.solution = pyclaw.Solution(state)
claw.solver = solver
claw.outdir = outdir
claw.tfinal =10.0
status = claw.run()
if htmlplot: pyclaw.plot.html_plot(outdir=outdir)
if iplot: pyclaw.plot.interactive_plot(outdir=outdir)
if __name__=="__main__":
from pyclaw.util import run_app_from_main
output = run_app_from_main(fig_61_62_63)
state.problem_data['gamma'] = gamma
state.problem_data['gamma1'] = gamma1
state.q[0, :] = 1.
state.q[1, :] = 0.
x = state.grid.x.centers
state.q[2, :] = ((x < 0.1) * 1.e3 + (0.1 <= x) * (x < 0.9) * 1.e-2 +
(0.9 <= x) * 1.e2) / gamma1
solver.limiters = 4
claw = pyclaw.Controller()
claw.tfinal = 0.038
claw.solution = pyclaw.Solution(state, domain)
claw.solver = solver
claw.num_output_times = 10
claw.outdir = outdir
# Solve
status = claw.run()
if htmlplot: pyclaw.plot.html_plot(outdir=outdir)
if iplot: pyclaw.plot.interactive_plot(outdir=outdir)
return claw.solution.q
if __name__ == "__main__":
from pyclaw.util import run_app_from_main
output = run_app_from_main(wcblast)
# ================
qinit(state) # This function is defined above
#===========================================================================
# Set up controller and controller parameters
#===========================================================================
claw = pyclaw.Controller()
claw.tfinal = 2.0
claw.solution = pyclaw.Solution(state,domain)
claw.solver = solver
claw.num_output_times = 10
print claw.num_output_times
claw.outdir = outdir
#===========================================================================
# Solve the problem
#===========================================================================
status = claw.run()
#===========================================================================
# Plot results
#===========================================================================
if htmlplot: pyclaw.plot.html_plot(outdir=outdir)
if iplot: pyclaw.plot.interactive_plot(outdir=outdir)
if __name__=="__main__":
from pyclaw.util import run_app_from_main
output = run_app_from_main(advection2D)
state.problem_data['v'] = 1.0
# Initial solution
# ================
qinit(state) # This function is defined above
#===========================================================================
# Set up controller and controller parameters
#===========================================================================
claw = pyclaw.Controller()
claw.tfinal = 2.0
claw.solution = pyclaw.Solution(state, domain)
claw.solver = solver
claw.outdir = outdir
#===========================================================================
# Solve the problem
#===========================================================================
status = claw.run()
#===========================================================================
# Plot results
#===========================================================================
if htmlplot: pyclaw.plot.html_plot(outdir=outdir)
if iplot: pyclaw.plot.interactive_plot(outdir=outdir)
if __name__ == "__main__":
from pyclaw.util import run_app_from_main
output = run_app_from_main(advection2D)
x0 = 0.75
state.q[0,:] = np.exp(-beta * (xc-x0)**2) * np.cos(gamma * (xc - x0))
#===========================================================================
# Set up controller and controller parameters
#===========================================================================
claw = pyclaw.Controller()
claw.solution = pyclaw.Solution(state)
claw.solver = solver
claw.outdir = outdir
claw.tfinal = 1.0
#===========================================================================
# Solve the problem
#===========================================================================
status = claw.run()
#===========================================================================
# Plot results
#===========================================================================
#if htmlplot: pyclaw.plot.html_plot(outdir=outdir)
#if iplot: pyclaw.plot.interactive_plot(outdir=outdir)
if __name__=="__main__":
from pyclaw.util import run_app_from_main
output = run_app_from_main(advection_implicitLW)
print 'Error: ',output
state.num_eqn, grid.num_cells[0],
grid.num_cells[1], grid.num_cells[2]
],
order='F')[0, :, :, :].reshape(-1)
pfinal = claw.frames[
claw.num_output_times].state.gqVec.getArray().reshape([
state.num_eqn, grid.num_cells[0], grid.num_cells[1],
grid.num_cells[2]
])[0, :, :, :].reshape(-1)
else:
pinitial = claw.frames[0].state.q[0, :, :, :].reshape(-1)
pmiddle = claw.frames[3].state.q[0, :, :, :].reshape(-1)
pfinal = claw.frames[claw.num_output_times].state.q[
0, :, :, :].reshape(-1)
final_difference = np.prod(grid.delta) * np.linalg.norm(pfinal - pinitial,
ord=1)
middle_difference = np.prod(grid.delta) * np.linalg.norm(
pmiddle - pinitial, ord=1)
if test == 'hom':
return final_difference
elif test == 'het':
return pfinal
if __name__ == "__main__":
import sys
from pyclaw.util import run_app_from_main
output = run_app_from_main(acoustics3D)
x = pyclaw.Dimension('x', 0.0, 1.0, mx)
grid = pyclaw.Grid(x)
num_eqn = 1
state = pyclaw.State(grid, num_eqn)
state.problem_data['u'] = 1.
xc = grid.x.center
if IC == 'gauss_square':
state.q[0, :] = np.exp(-beta * (xc - x0)**2) + (xc > 0.6) * (xc < 0.8)
elif IC == 'wavepacket':
state.q[0, :] = np.exp(-beta * (xc - x0)**2) * np.sin(80. * xc)
else:
raise Exception('Unrecognized initial condition specification.')
claw = pyclaw.Controller()
claw.solution = pyclaw.Solution(state)
claw.solver = solver
claw.outdir = outdir
claw.tfinal = 10.0
status = claw.run()
if htmlplot: pyclaw.plot.html_plot(outdir=outdir)
if iplot: pyclaw.plot.interactive_plot(outdir=outdir)
if __name__ == "__main__":
from pyclaw.util import run_app_from_main
output = run_app_from_main(fig_61_62_63)
