state.problem_data['co'] = material.co
state.problem_data['zo'] = material.zo
state.problem_data['dx'] = state.grid.x.delta
state.problem_data['nl'] = nl
state.problem_data['psi'] = psi
source._dx = state.grid.x.delta
material._dx = state.grid.x.delta
# array initialization
source.init(state)
material.init(state)
state.q = state.q * state.aux[0:2, :]
# controller
claw = pyclaw.Controller()
claw.tfinal = tf
claw.num_output_times = num_frames
claw.solver = solver
claw.solution = pyclaw.Solution(state, domain)
claw.outdir = outdir
claw.write_aux_always = True
return claw
if __name__ == "__main__":
import sys
from clawpack.pyclaw.util import run_app_from_main
output = run_app_from_main(em1D)
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.compute_p = compute_p
if disable_output:
claw.output_format = None
claw.compute_F = compute_F
claw.solution.state.keep_gauges = True
claw.solution.state.grid.add_gauges([[25.0,0.75],[50.0,0.75],[75.0,0.75],[25.0,1.25],[50.0,1.25],[75.0,1.25]])
solver.compute_gauge_values = gauge_pfunction
claw.write_aux_init = False
#Solve
status = claw.run()
if iplot: pyclaw.plot.interactive_plot()
if htmlplot: pyclaw.plot.html_plot()
return claw.solution.state
if __name__=="__main__":
from clawpack.pyclaw.util import run_app_from_main
output = run_app_from_main(psystem2D)
x0 = -0.5; y0 = 0.
r = np.sqrt((X-x0)**2 + (Y-y0)**2)
width=0.1; rad=0.25
state.q[0,:,:] = (np.abs(r-rad)<=width)*(1.+np.cos(np.pi*(r-rad)/width))
state.q[1,:,:] = 0.
state.q[2,:,:] = 0.
claw = pyclaw.Controller()
claw.keep_copy = True
if disable_output:
claw.output_format = None
claw.solution = pyclaw.Solution(state,domain)
claw.solver = solver
claw.outdir=outdir
claw.num_output_times = 20
claw.write_aux_init = True
# Solve
claw.tfinal = 0.6
status = claw.run()
if htmlplot: pyclaw.plot.html_plot(outdir=outdir,file_format=claw.output_format)
if iplot: pyclaw.plot.interactive_plot(outdir=outdir,file_format=claw.output_format)
return claw
if __name__=="__main__":
import sys
from clawpack.pyclaw.util import run_app_from_main
output = run_app_from_main(acoustics2D)
#,refinement_criterion=refinement_criterion
)
claw.solution = amrclaw.Solution(state, domain)
else:
raise Exception('unsupported amr_type %s' % amr_type)
else:
claw.solver = solver
claw.solution = pyclaw.Solution(state,domain)
#claw.keep_copy = True
#claw.outdir = outdir
claw.keep_copy = False
claw.output_format = None
claw.outdir = None
claw.num_output_times = 10
#===========================================================================
# Plot results
#===========================================================================
if htmlplot: pyclaw.plot.html_plot(outdir=outdir)
if iplot: pyclaw.plot.interactive_plot(outdir=outdir)
return claw
if __name__=="__main__":
from clawpack.pyclaw.util import run_app_from_main
run_app_from_main(shallow2D)
solver.bc_upper[1] = pyclaw.BC.extrap
#Aux variable in ghost cells doesn't matter
solver.aux_bc_lower[0] = pyclaw.BC.extrap
solver.aux_bc_upper[0] = pyclaw.BC.extrap
solver.aux_bc_lower[1] = pyclaw.BC.extrap
solver.aux_bc_upper[1] = pyclaw.BC.extrap
claw = pyclaw.Controller()
claw.keep_copy = True
if disable_output:
claw.output_format = None
# The output format MUST be set to petsc!
claw.tfinal = tfinal
claw.solution = initial_solution
claw.solver = solver
claw.num_output_times = 1
claw.outdir = outdir
# Solve
status = claw.run()
if htmlplot: pyclaw.plot.html_plot(file_format=claw.output_format)
if iplot: pyclaw.plot.interactive_plot(file_format=claw.output_format)
return claw.frames[claw.num_output_times].state
if __name__ == "__main__":
from clawpack.pyclaw.util import run_app_from_main
output = run_app_from_main(shockbubble)
solver.aux_bc_upper[0] = pyclaw.BC.extrap
solver.aux_bc_lower[1] = pyclaw.BC.extrap
solver.aux_bc_upper[1] = pyclaw.BC.extrap
solver.aux_bc_lower[2] = pyclaw.BC.custom
solver.aux_bc_upper[2] = pyclaw.BC.custom
solver.user_aux_bc_lower = customAuxBCLowerZ
solver.user_aux_bc_upper = customAuxBCUpperZ
# Solver Parameters
claw = pyclaw.Controller()
claw.verbosity = 4
claw.solution = pyclaw.Solution(state,domain)
claw.solver = solver
claw.output_format = output_format
claw.output_file_prefix = file_prefix
claw.keep_copy = False
if disable_output:
claw.output_format = None
claw.tfinal = tfinal
claw.num_output_times = num_output_times
claw.outdir = outdir
#state.mp = 1
#claw.compute_p = outputDensity
return claw
# __main__()
if __name__=="__main__":
from clawpack.pyclaw.util import run_app_from_main
output = run_app_from_main(euler3d)
"""
Specify what is to be plotted at each frame.
Input: plotdata, an instance of visclaw.data.ClawPlotData.
Output: a modified version of plotdata.
"""
plotdata.clearfigures() # clear any old figures,axes,items data
plotfigure = plotdata.new_plotfigure(name='', figno=0)
plotaxes = plotfigure.new_plotaxes()
plotaxes.axescmd = 'subplot(211)'
plotaxes.title = 'Density'
plotitem = plotaxes.new_plotitem(plot_type='1d')
plotitem.plot_var = density
plotitem.kwargs = {'linewidth':3}
plotaxes = plotfigure.new_plotaxes()
plotaxes.axescmd = 'subplot(212)'
plotaxes.title = 'Energy'
plotitem = plotaxes.new_plotitem(plot_type='1d')
plotitem.plot_var = energy
plotitem.kwargs = {'linewidth':3}
return plotdata
if __name__=="__main__":
from clawpack.pyclaw.util import run_app_from_main
output = run_app_from_main(setup,setplot)
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 clawpack.pyclaw.util import run_app_from_main
output = run_app_from_main(contourLineSphere)
print 'Error: ', output
# Set up controller and controller parameters
#===========================================================================
claw = pyclaw.Controller()
claw.keep_copy = True
if disable_output:
claw.output_format = None
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)
return claw
if __name__ == "__main__":
from clawpack.pyclaw.util import run_app_from_main
output = run_app_from_main(shallow_4_Rossby_Haurwitz)
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 clawpack.pyclaw.util import run_app_from_main
output = run_app_from_main(kpp)
y0 = -1000
r = np.sqrt((X - x0)**2 + (Y - y0)**2)
width = 500.0
rad = 500
amplitude = 1.0
#ADJUSTING THE PRESSURE
state.q[0, :, :] = amplitude * np.exp(-(X - x0)**2 / width**2)
#ADJUSTING THE PRESSURE
state.q[1, :, :] = 0.
state.q[2, :, :] = 0.
claw = pyclaw.Controller()
claw.keep_copy = True
if disable_output:
claw.output_format = None
claw.solution = pyclaw.Solution(state, domain)
claw.solver = solver
claw.outdir = outdir
claw.tfinal = 1000
claw.num_output_times = 100
claw.write_aux_init = True
claw.setplot = "./setplot.py"
if use_petsc:
claw.output_options = {'format': 'binary'}
return claw
if __name__ == "__main__":
from clawpack.pyclaw.util import run_app_from_main
output = run_app_from_main(setup, "./setplot.py")
X, Y, Z = grid.p_centers
pressure = 3. * (Z <= 0) + 1. * (Z > 0)
state.q[density, :, :, :] = 3. * (Z <= 0) + 1. * (Z > 0)
state.q[x_momentum, :, :, :] = 0.
state.q[y_momentum, :, :, :] = 0.
state.q[z_momentum, :, :, :] = 0.
state.q[energy, :, :, :] = pressure / (gamma - 1.)
solver.all_bcs = pyclaw.BC.extrap
claw = pyclaw.Controller()
claw.solution = pyclaw.Solution(state, domain)
claw.solver = solver
claw.output_format = output_format
claw.keep_copy = True
if disable_output:
claw.output_format = None
claw.tfinal = tfinal
claw.num_output_times = num_output_times
claw.outdir = outdir
return claw
# __main__()
if __name__ == "__main__":
from clawpack.pyclaw.util import run_app_from_main
output = run_app_from_main(shocktube)
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 clawpack.pyclaw.util import run_app_from_main
output = run_app_from_main(kpp)
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 clawpack.pyclaw.util import run_app_from_main
output = run_app_from_main(contourLineSphere)
print 'Error: ',output
#===========================================================================
# Set up controller and controller parameters
#===========================================================================
claw = pyclaw.Controller()
claw.keep_copy = True
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)
return claw
if __name__=="__main__":
from clawpack.pyclaw.util import run_app_from_main
output = run_app_from_main(shallow_4_Rossby_Haurwitz)
claw.tfinal = 600.
elif IC=='rp1':
state.q[0,:] = 0.9*(xc<250.)+0.1*(xc>250.)
state.q[1,:] = state.q[0,:]*(1.+hesitation(state.q[0,:]))
solver.dq_src=None
solver.bc_lower[0] = pyclaw.BC.extrap
solver.bc_upper[0] = pyclaw.BC.extrap
claw.num_output_times = 10
claw.tfinal = 1.
#========================================================================
# Set up the controller object
#========================================================================
claw.solution = pyclaw.Solution(state,domain)
claw.solver = solver
claw.outdir = outdir
# Solve
status = claw.run()
# Plot results
if htmlplot: pyclaw.plot.html_plot(outdir=outdir)
if iplot: pyclaw.plot.interactive_plot(outdir=outdir)
return claw
if __name__=="__main__":
from clawpack.pyclaw.util import run_app_from_main
output = run_app_from_main(arz)
parser.add_argument("fixedTimestepSize", nargs="?", type=float, default=None)
parser.add_argument("forkLevelIncrement", type=int)
parser.add_argument("reduceReductions", type=int)
arguments = parser.parse_args()
global gridSize
gridSize = arguments.gridSize
global patchSize
patchSize = arguments.patchSize
global tfinal
tfinal = 1.0/float(arguments.tfinal)
global usePeano
usePeano = arguments.usePeano
global useHeapCompression
useHeapCompression = arguments.useHeapCompression
global fixedTimestepSize
fixedTimestepSize = arguments.fixedTimestepSize
global forkLevelIncrement
forkLevelIncrement = arguments.forkLevelIncrement
global reduceReductions
reduceReductions = arguments.reduceReductions
output = run_app_from_main(shallow2D)
#if(not output == None):
# print 'Error: ', output
num_eqn = 1
state = pyclaw.State(domain,num_eqn)
grid = state.grid
xc=grid.x.centers
state.q[0,:] = 0.75*(xc<0) + 0.1*(xc>0.)
state.problem_data['efix']=True
state.problem_data['umax']=1.
#===========================================================================
# Setup controller and controller parameters. Then solve the problem
#===========================================================================
claw = pyclaw.Controller()
claw.tfinal =2.0
claw.solution = pyclaw.Solution(state,domain)
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 clawpack.pyclaw.util import run_app_from_main
output = run_app_from_main(traffic)
solver.aux_bc_upper[0] = pyclaw.BC.custom solver.aux_bc_lower[1] = pyclaw.BC.wall solver.aux_bc_upper[1] = pyclaw.BC.wall # Initial solution qinit(state) # controller claw = pyclaw.Controller() claw.keep_copy = True claw.tfinal = 2 claw.num_output_times = 10 claw.solver = solver claw.solution = pyclaw.Solution(state,domain) claw.outdir = save_outdir claw.write_aux_always = True status = claw.run() if htmlplot: pyclaw.plot.html_plot(outdir=save_outdir,file_format=claw.output_format) if iplot: pyclaw.plot.interactive_plot(outdir=save_outdir,file_format=claw.output_format) return claw if __name__=="__main__": import sys from clawpack.pyclaw.util import run_app_from_main output = run_app_from_main(em2D)
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 clawpack.pyclaw.util import run_app_from_main
output = run_app_from_main(advection_annulus)
print 'Error: ',output
plotitem = plotaxes.new_plotitem(plot_type='2d_pcolor')
plotitem.plot_var = 1
plotitem.pcolor_cmap = colormaps.yellow_red_blue
plotitem.add_colorbar = True
plotitem.show = False # show on plot?
# Figure for q[2]
plotfigure = plotdata.new_plotfigure(name='Momentum in y direction',
figno=3)
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.xlimits = [-2.5, 2.5]
plotaxes.ylimits = [-2.5, 2.5]
plotaxes.title = 'Momentum in y direction'
plotaxes.scaled = True
# Set up for item on these axes:
plotitem = plotaxes.new_plotitem(plot_type='2d_pcolor')
plotitem.plot_var = 2
plotitem.pcolor_cmap = colormaps.yellow_red_blue
plotitem.add_colorbar = True
plotitem.show = False # show on plot?
return plotdata
if __name__ == "__main__":
from clawpack.pyclaw.util import run_app_from_main
output = run_app_from_main(setup, setplot)
# 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 clawpack.pyclaw.util import run_app_from_main
output = run_app_from_main(fig_31_38)
#,refinement_criterion=refinement_criterion
#,refinement_criterion=refinement_criterion_gradient
)
claw.solution = amrclaw.Solution(state, domain)
else:
raise Exception('unsupported amr_type %s' % amr_type)
else:
claw.solver = solver
claw.solution = pyclaw.Solution(state,domain)
#claw.keep_copy = True
#claw.outdir = outdir
claw.keep_copy = False
claw.output_format = None
claw.outdir = None
claw.num_output_times = 10
#===========================================================================
# Plot results
#===========================================================================
if htmlplot: pyclaw.plot.html_plot(outdir=outdir)
if iplot: pyclaw.plot.interactive_plot(outdir=outdir)
return claw
if __name__=="__main__":
from clawpack.pyclaw.util import run_app_from_main
output = run_app_from_main(shallow2D)
grid = state.grid
X,Y,Z = grid.p_centers
pressure = 3.*(Z<=0) + 1.*(Z>0)
state.q[density ,:,:,:] = 3.*(Z<=0) + 1.*(Z>0)
state.q[x_momentum,:,:,:] = 0.
state.q[y_momentum,:,:,:] = 0.
state.q[z_momentum,:,:,:] = 0.
state.q[energy ,:,:,:] = pressure/(gamma - 1.)
solver.all_bcs = pyclaw.BC.extrap
claw = pyclaw.Controller()
claw.solution = pyclaw.Solution(state,domain)
claw.solver = solver
claw.output_format = output_format
claw.keep_copy = True
if disable_output:
claw.output_format = None
claw.tfinal = tfinal
claw.num_output_times = num_output_times
claw.outdir = outdir
return claw
# __main__()
if __name__=="__main__":
from clawpack.pyclaw.util import run_app_from_main
output = run_app_from_main(shocktube)
if pinitial != None and pmiddle != None and pfinal != None:
pinitial = pinitial[0, :, :, :].reshape(-1)
pmiddle = pmiddle[0, :, :, :].reshape(-1)
pfinal = pfinal[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 app == None:
print 'Final error: ', final_difference
print 'Middle error: ', middle_difference
#import matplotlib.pyplot as plt
#for i in range(claw.num_output_times):
# plt.pcolor(claw.frames[i].state.q[0,:,:,mz/2])
# plt.figure()
#plt.show()
return pfinal, final_difference
else:
return
if __name__ == "__main__":
import sys
from clawpack.pyclaw.util import run_app_from_main
output = run_app_from_main(acoustics3D)
domain = pyclaw.Domain(x)
num_eqn = 1
state = pyclaw.State(domain, num_eqn)
grid = state.grid
xc = grid.x.centers
state.q[0, :] = 0.75 * (xc < 0) + 0.1 * (xc > 0.)
state.problem_data['efix'] = True
state.problem_data['umax'] = 1.
#===========================================================================
# Setup controller and controller parameters. Then solve the problem
#===========================================================================
claw = pyclaw.Controller()
claw.tfinal = 2.0
claw.solution = pyclaw.Solution(state, domain)
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 clawpack.pyclaw.util import run_app_from_main
output = run_app_from_main(traffic)
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 clawpack.pyclaw.util import run_app_from_main
output = run_app_from_main(wcblast)
state = pyclaw.State(domain,num_eqn)
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 clawpack.pyclaw.util import run_app_from_main
output = run_app_from_main(wcblast)
rhoA,
KA,
alpha,
xlower=xlower,
xupper=xupper)
qinit(state, ic=2, a2=1.0, xupper=xupper)
tfinal = 500.
num_output_times = 10
solver.max_steps = 5000000
solver.fwave = True
solver.before_step = b4step
solver.user_bc_lower = moving_wall_bc
solver.user_bc_upper = zero_bc
claw = pyclaw.Controller()
claw.keep_copy = False
claw.output_style = 1
claw.num_output_times = num_output_times
claw.tfinal = tfinal
claw.solution = pyclaw.Solution(state, domain)
claw.solver = solver
return claw
if __name__ == "__main__":
from clawpack.pyclaw.util import run_app_from_main
output = run_app_from_main(stegoton)
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 clawpack.pyclaw.util import run_app_from_main
output = run_app_from_main(advection_annulus)
print 'Error: ', output
solver.aux_bc_lower[1] = pyclaw.BC.extrap
solver.aux_bc_upper[1] = pyclaw.BC.extrap
solver.aux_bc_lower[2] = pyclaw.BC.custom
solver.aux_bc_upper[2] = pyclaw.BC.custom
solver.user_aux_bc_lower = customAuxBCLowerZ
solver.user_aux_bc_upper = customAuxBCUpperZ
# Solver Parameters
claw = pyclaw.Controller()
claw.verbosity = 4
claw.solution = pyclaw.Solution(state, domain)
claw.solver = solver
claw.output_format = output_format
claw.output_file_prefix = file_prefix
claw.keep_copy = False
if disable_output:
claw.output_format = None
claw.tfinal = tfinal
claw.num_output_times = num_output_times
claw.outdir = outdir
#state.mp = 1
#claw.compute_p = outputDensity
return claw
# __main__()
if __name__ == "__main__":
from clawpack.pyclaw.util import run_app_from_main
output = run_app_from_main(euler3d)
solver.bc_upper[1]=pyclaw.BC.extrap
#Aux variable in ghost cells doesn't matter
solver.aux_bc_lower[0]=pyclaw.BC.extrap
solver.aux_bc_upper[0]=pyclaw.BC.extrap
solver.aux_bc_lower[1]=pyclaw.BC.extrap
solver.aux_bc_upper[1]=pyclaw.BC.extrap
claw = pyclaw.Controller()
claw.keep_copy = True
if disable_output:
claw.output_format = None
# The output format MUST be set to petsc!
claw.tfinal = tfinal
claw.solution = initial_solution
claw.solver = solver
claw.num_output_times = 1
claw.outdir = outdir
# Solve
status = claw.run()
if htmlplot: pyclaw.plot.html_plot(file_format=claw.output_format)
if iplot: pyclaw.plot.interactive_plot(file_format=claw.output_format)
return claw.frames[claw.num_output_times].state
if __name__=="__main__":
from clawpack.pyclaw.util import run_app_from_main
output = run_app_from_main(shockbubble)
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 clawpack.pyclaw.util import run_app_from_main
output = run_app_from_main(fig_61_62_63)
from clawpack import pyclaw
from clawpack import riemann
solver = pyclaw.ClawSolver1D(riemann.burgers_1D)
solver.limiters = pyclaw.limiters.tvd.MC
solver.bc_lower[0] = pyclaw.BC.periodic
solver.bc_upper[0] = pyclaw.BC.periodic
x = pyclaw.Dimension(-8.0,8.0,1000,name='x')
domain = pyclaw.Domain(x)
num_eqn = 1
state = pyclaw.State(domain,num_eqn)
xc = domain.grid.x.centers
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
claw = pyclaw.Controller()
claw.tfinal = 6.0
claw.num_output_times = 30
claw.solution = pyclaw.Solution(state,domain)
claw.solver = solver
return claw
if __name__=="__main__":
from clawpack.pyclaw.util import run_app_from_main
output = run_app_from_main(burgers)
my = 40
x = pyclaw.Dimension('x', 0.0, 2.0, mx)
y = pyclaw.Dimension('y', 0.0, 0.5, my)
domain = pyclaw.Domain([x, y])
num_eqn = 5
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
return claw
if __name__ == "__main__":
from clawpack.pyclaw.util import run_app_from_main
from clawpack.pyclaw.examples import *
output = run_app_from_main(shockbubble, shock_bubble_interaction.setplot)
num_eqn = 1
state = pyclaw.State(domain,num_eqn)
state.problem_data['u']=1.
grid = state.grid
xc=grid.x.centers
beta=100; gamma=0; x0=0.75
state.q[0,:] = np.exp(-beta * (xc-x0)**2) * np.cos(gamma * (xc - x0))
claw = pyclaw.Controller()
claw.keep_copy = True
claw.solution = pyclaw.Solution(state,domain)
claw.solver = solver
if outdir is not None:
claw.outdir = outdir
else:
claw.output_format = None
claw.tfinal =1.0
status = claw.run()
if htmlplot: pyclaw.plot.html_plot(outdir=outdir)
if iplot: pyclaw.plot.interactive_plot(outdir=outdir)
return claw
if __name__=="__main__":
from clawpack.pyclaw.util import run_app_from_main
output = run_app_from_main(advection)
# Initial solution
# ================
# Riemann states of the dam break problem
damRadius = 0.5
hl = 2.
ul = 0.
vl = 0.
hr = 1.
ur = 0.
vr = 0.
qinit(state,hl,ul,vl,hr,ur,vr,damRadius) # This function is defined above
#===========================================================================
# 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
return claw
if __name__=="__main__":
from clawpack.pyclaw.util import run_app_from_main
output = run_app_from_main(setup)
#===========================================================================
# Initialize grids and then initialize the solution associated to the grid
#===========================================================================
x = pyclaw.Dimension('x', -8.0, 8.0, 1000)
domain = pyclaw.Domain(x)
num_eqn = 1
state = pyclaw.State(domain, num_eqn)
xc = domain.grid.x.centers
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, domain)
claw.solver = solver
claw.outdir = outdir
return claw
if __name__ == "__main__":
from clawpack.pyclaw.util import run_app_from_main
output = run_app_from_main(burgers)
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 clawpack.pyclaw.util import run_app_from_main
output = run_app_from_main(fig_31_38)
mx=160; my=40
x = pyclaw.Dimension('x',0.0,2.0,mx)
y = pyclaw.Dimension('y',0.0,0.5,my)
domain = pyclaw.Domain([x,y])
num_eqn = 5
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
return claw
if __name__=="__main__":
from clawpack.pyclaw.util import run_app_from_main
from clawpack.pyclaw.examples import *
output = run_app_from_main(shockbubble,shock_bubble_interaction.setplot)
claw.keep_copy = True
if disable_output:
claw.output_format = None
claw.output_style = 1
claw.num_output_times = 10
claw.tfinal = 10
claw.solution = pyclaw.Solution(state, domain)
claw.solver = solver
claw.outdir = outdir
return claw
if __name__ == "__main__":
from clawpack.pyclaw.util import run_app_from_main
output = run_app_from_main(setup)
def plot_on_sphere():
"""
Plots the solution of the shallow water on a sphere in the
rectangular computational domain. The user can specify the name of the solution
file and its path. If these are not given, the script checks
whether the solution fort.q0000 in ./_output exists and plots it. If it it does
not exist an error message is printed at screen.
The file must be ascii and clawpack format.
To use this, you must first install the basemap toolkit; see
http://matplotlib.org/basemap/users/installing.html.
This function also shows how to manually read and plot the solution stored in
epsilon = claw.frames[-1].q[0, :]
aux = claw.frames[1].aux
from clawpack.riemann.rp_nonlinear_elasticity import sigma
stress = sigma(epsilon, aux[1, :])
dx = state.grid.delta[0]
work = solver.status["totalsteps"]
return stress, dx, work
if __name__ == "__main__":
from clawpack.pyclaw.util import run_app_from_main
output = run_app_from_main(stegoton)
def plot_efficiency(err, work, ork):
import matplotlib.pyplot as plt
p = ork.order()
styles = ["k-s", "b-o", "g-d", "r-p"]
plt.figure()
plt.hold(True)
for i in range(err.shape[0]):
plt.loglog(err[i], work[i], styles[i], linewidth=3, markersize=11)
plt.grid()
plt.xlabel(r"Error", fontsize=15)
plt.ylabel("Derivative evaluations", fontsize=15)
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 clawpack.pyclaw.util import run_app_from_main
output = run_app_from_main(fig_61_62_63)
global CELLS
global SUBDIVISION_FACTOR
import assembleState as AS
import matplotlib.pyplot as plt
for i in range(NUM_OUTPUT_TIMES):
q_peano = AS.assemblePeanoClawState(claw1.frames[i], claw2.frames[i].domain, NUM_EQS, CELLS * SUBDIVISION_FACTOR)
res1 = q_peano[TEST_LEVEL,:,:]
res2 = claw2.frames[i].state.q[0,TEST_LEVEL,:,:]
fig = plt.figure(1)
plt.subplot(131)
plt.pcolor(res1)
plt.colorbar()
plt.subplot(132)
plt.pcolor(res2)
plt.colorbar()
plt.subplot(133)
plt.pcolor(res2 - res1)
plt.colorbar()
plt.show()
if __name__=="__main__":
import sys
from clawpack.pyclaw.util import run_app_from_main
pyclaw_output = run_app_from_main(pyclaw_acoustics3D)
peanoclaw_output = run_app_from_main(acoustics3D)
verify( peanoclaw_output, pyclaw_output)
