def run_validation_script(script, np=1, cfl=None, alg=None, verbose=False):
""" For backwards compatiblity wrap new run_anuga_script as run_validation_script
"""
from anuga import run_anuga_script
run_anuga_script(script, np=np, cfl=cfl, alg=alg, verbose=verbose)
def run_validation_script(script, np=1, cfl=None, alg=None, verbose=False):
""" For backwards compatiblity wrap new run_anuga_script as run_validation_script
"""
from anuga import run_anuga_script
run_anuga_script(script, np=np, cfl=cfl, alg=alg, verbose=verbose)
def produce_report(script, args=None):
import anuga
if args is None:
args = anuga.get_args()
verbose = args.verbose
#print args
# Get the arguments from the calling script
run_anuga_script(script, args=args)
# We don't want to run plot_results in parallel
args.np = 1
run_anuga_script('plot_results.py', args=args)
typeset_report(verbose=verbose)
def produce_report(script, args=None):
import anuga
if args is None:
args = anuga.get_args()
verbose = args.verbose
#print args
# Get the arguments from the calling script
run_anuga_script(script, args=args)
# We don't want to run plot_results in parallel
args.np = 1
run_anuga_script('plot_results.py', args=args)
typeset_report(verbose=verbose)
def test_simulation(self):
if verbose:
print(indent + 'Running simulation script')
s = 'run_okushiri.py'
res = anuga.run_anuga_script(s, args=args)
# Test that script runs ok
assert res == 0
if verbose:
print(indent + 'Running test script')
s = 'test_results.py'
res = os.system('python %s' % s)
# Test that script runs ok
assert res == 0
def test_simulation(self):
if verbose:
print indent+'Running simulation script'
s = 'run_okushiri.py'
res = anuga.run_anuga_script(s,args=args)
# Test that script runs ok
assert res == 0
if verbose:
print indent+'Running test script'
s = 'plot_results.py'
res = os.system('python %s' %s)
# Test that script runs ok
assert res == 0
def test_dam_break_dry(self):
if verbose:
print
print indent + 'Running simulation script'
s = 'numerical_dam_break_dry.py'
res = anuga.run_anuga_script(s, args=args)
# Test that script runs ok
assert res == 0
if verbose:
print indent + 'Testing accuracy'
import anuga.utilities.plot_utils as util
import analytical_dam_break_dry as analytic
p_st = util.get_output('dam_break.sww')
p2_st = util.get_centroids(p_st)
v = p2_st.y[10]
v2 = (p2_st.y == v)
h0 = 1.0
h1 = 10.0
# calculate analytic values at various time slices
h10, u10 = analytic.vec_dam_break(p2_st.x[v2],
p2_st.time[10],
h0=h0,
h1=h1)
h50, u50 = analytic.vec_dam_break(p2_st.x[v2],
p2_st.time[50],
h0=h0,
h1=h1)
h100, u100 = analytic.vec_dam_break(p2_st.x[v2],
p2_st.time[100],
h0=h0,
h1=h1)
#Test stages
# Calculate L^1 error at times corrsponding to slices 10, 50 and 100
eh10 = numpy.sum(numpy.abs(p2_st.stage[10, v2] - h10)) / numpy.sum(
numpy.abs(h10))
eh50 = numpy.sum(numpy.abs(p2_st.stage[50, v2] - h50)) / numpy.sum(
numpy.abs(h50))
eh100 = numpy.sum(numpy.abs(p2_st.stage[100, v2] - h100)) / numpy.sum(
numpy.abs(h100))
print
print indent + 'Errors in stage: ', eh10, eh50, eh100
#Test xmomenta
# Calculate L^1 error at times corrsponding to slices 10, 50 and 100
euh10 = numpy.sum(
numpy.abs(p2_st.xmom[10, v2] - u10 * h10)) / numpy.sum(
numpy.abs(u10 * h10))
euh50 = numpy.sum(
numpy.abs(p2_st.xmom[50, v2] - u50 * h50)) / numpy.sum(
numpy.abs(u50 * h50))
euh100 = numpy.sum(
numpy.abs(p2_st.xmom[100, v2] - u100 * h100)) / numpy.sum(
numpy.abs(u100 * h100))
print indent + 'Errors in xmomentum: ', euh10, euh50, euh100
#Test xvelocity
# Calculate L^1 error at times corrsponding to slices 10, 50 and 100
eu10 = numpy.sum(numpy.abs(p2_st.xvel[10, v2] - u10)) / numpy.sum(
numpy.abs(u10))
eu50 = numpy.sum(numpy.abs(p2_st.xvel[50, v2] - u50)) / numpy.sum(
numpy.abs(u50))
eu100 = numpy.sum(numpy.abs(p2_st.xvel[100, v2] - u100)) / numpy.sum(
numpy.abs(u100))
print indent + 'Errors in xvelocity: ', eu10, eu50, eu100
assert eh10 < 0.1, 'Relative L^1 error %g greater than 0.1' % eh10
assert eh50 < 0.1, 'Relative L^1 error %g greater than 0.1' % eh50
assert eh100 < 0.15, 'Relative L^1 error %g greater than 0.15' % eh100
assert euh10 < 0.25, 'Relative L^1 error %g greater than 0.25' % euh10
assert euh50 < 0.25, 'Relative L^1 error %g greater than 0.25' % euh50
assert euh100 < 0.25, 'Relative L^1 error %g greater than 0.25' % euh100
assert eu10 < 2.0, 'Relative L^1 error %g greater than 2.0' % eu10
assert eu50 < 2.0, 'Relative L^1 error %g greater than 2.0' % eu50
assert eu100 < 0.3, 'Relative L^1 error %g greater than 0.3' % eu100
def test_avalanche_dry(self):
if verbose:
print
print indent + 'Running simulation script'
# Run basic script (can be parallel if -np used in call
# to this script
s = 'numerical_avalanche_dry.py'
res = anuga.run_anuga_script(s, args=args)
# Test that script runs ok
assert res == 0
if verbose:
print indent + 'Testing accuracy'
import anuga.utilities.plot_utils as util
from analytical_avalanche_dry import analytical_sol
p_st = util.get_output('avalanche.sww')
p2_st = util.get_centroids(p_st)
v = p2_st.y[10]
v2 = (p2_st.y == v)
x_n = p2_st.x[v2]
u0, h0, w0, z0, p0 = analytical_sol(x_n, p2_st.time[0])
u10, h10, w10, z10, p10 = analytical_sol(x_n, p2_st.time[10])
u30, h30, w30, z30, p30 = analytical_sol(x_n, p2_st.time[30])
w0_n = p2_st.stage[0, v2]
w10_n = p2_st.stage[10, v2]
w30_n = p2_st.stage[30, v2]
z_n = p2_st.elev[v2]
uh0_n = p2_st.xmom[0, v2]
uh10_n = p2_st.xmom[10, v2]
uh30_n = p2_st.xmom[30, v2]
u0_n = p2_st.xvel[0, v2]
u10_n = p2_st.xvel[10, v2]
u30_n = p2_st.xvel[30, v2]
#Test stages
# Calculate L^1 error at times corrsponding to slices 10, 50 and 100
eh10 = numpy.sum(numpy.abs(w10_n - w10)) / numpy.sum(numpy.abs(w10))
eh30 = numpy.sum(numpy.abs(w30_n - w30)) / numpy.sum(numpy.abs(w30))
print
print indent + 'Errors in stage: ', eh10, eh30
#Test xmomenta
# Calculate L^1 error at times corrsponding to slices 10, 50 and 100
euh10 = numpy.sum(numpy.abs(uh10_n - u10 * h10)) / numpy.sum(
numpy.abs(u10 * h10))
euh30 = numpy.sum(numpy.abs(uh30_n - u30 * h30)) / numpy.sum(
numpy.abs(u30 * h30))
print indent + 'Errors in xmomentum: ', euh10, euh30
#Test xvelocity
# Calculate L^1 error at times corrsponding to slices 10, 50 and 100
eu10 = numpy.sum(numpy.abs(u10_n - u10)) / numpy.sum(numpy.abs(u10))
eu30 = numpy.sum(numpy.abs(u30_n - u30)) / numpy.sum(numpy.abs(u30))
print indent + 'Errors in xvelocity: ', eu10, eu30
assert eh10 < 0.01, 'L^1 error %g greater than 1 percent' % eh10
assert eh30 < 0.01, 'L^1 error %g greater than 1 percent' % eh30
assert euh10 < 0.025, 'L^1 error %g greater than 2.5 percent' % euh10
assert euh30 < 0.025, 'L^1 error %g greater than 2.5 percent' % euh30
assert eu10 < 0.2, 'L^1 error %g greater than 20 percent' % eu10
assert eu30 < 0.2, 'L^1 error %g greater than 20 percent' % eu30
def test_carrier_greenspan_transient(self):
if verbose:
print
print indent + 'Running simulation script'
s = 'numerical_cg_transient.py'
res = anuga.run_anuga_script(s, args=args)
# Test that script runs ok
assert res == 0
if verbose:
print indent + 'Testing accuracy'
import anuga.utilities.plot_utils as util
from analytical_cg_transient import analytical_sol
p_st = util.get_output('carrier_greenspan.sww')
p2_st = util.get_centroids(p_st)
v = p2_st.y[10]
v2 = (p2_st.y == v)
x_n = p2_st.x[v2]
ids = [1, 15, 30]
use_absolute = [False, True, True]
n = len(ids)
W, UH, Z, H, U = [], [], [], [], []
W_n, U_n, UH_n = [], [], []
#Dimensional parameters
L = 5e4 # Length of channel (m)
h0 = 5e2 # Height at origin when the water is still
g = 9.81 # Gravity
for i, id in enumerate(ids):
w, z, u = analytical_sol(x_n / L,
p2_st.time[id] * sqrt(g * h0) / L)
w = w * h0
z = z * h0
u = u * sqrt(g * h0)
h = w - z
uh = u * h
W.append(w)
Z.append(z)
H.append(h)
U.append(u)
UH.append(uh)
W_n.append(p2_st.stage[id, v2])
UH_n.append(p2_st.xmom[id, v2])
U_n.append(p2_st.xvel[id, v2])
#print id, numpy.max(H[i]), numpy.min(H[i])
#print id, numpy.max(U[i]), numpy.min(U[i])
#print id, numpy.max(U_n[i]), numpy.min(U_n[i])
#Test stages
# Calculate L^1 error at times
ew = numpy.zeros(n)
for i, id in enumerate(ids):
ew[i] = numpy.sum(numpy.abs(W_n[i] - W[i])) / numpy.sum(
numpy.abs(W[i]))
print
print indent + 'L^1 Errors in stage: ', ew
#Test xmomenta
# Calculate L^1 error at times
euh = numpy.zeros(n)
for i, id in enumerate(ids):
euh[i] = numpy.sum(numpy.abs(UH_n[i] - U[i] * H[i])) / numpy.sum(
numpy.abs(UH_n[i]))
print indent + 'L^1 Errors in xmomentum: ', euh
#Test xvelocity
# Calculate L^1 error at times
eu = numpy.zeros(n)
for i, id in enumerate(ids):
if use_absolute[i]:
eu[i] = numpy.sum(numpy.abs(U_n[i] - U[i])) / len(U[i])
else:
eu[i] = numpy.sum(numpy.abs(U_n[i] - U[i])) / numpy.sum(
numpy.abs(U[i]))
print indent + 'L^1 Errors in xvelocity: ', eu
for i, id in enumerate(ids):
assert ew[i] < 0.01, 'L^1 error %g greater than 1 percent' % ew[i]
for i, id in enumerate(ids):
assert euh[
i] < 0.025, 'L^1 error %g greater than 2.5 percent' % euh[i]
for i, id in enumerate(ids):
assert eu[
i] < 0.025, 'L^1 error %g greater than 2.5 percent' % eu[i]
def test_carrier_greenspan_periodic(self):
if verbose:
print
print indent + 'Running simulation script'
s = 'numerical_carrier_greenspan.py'
res = anuga.run_anuga_script(s, args=args)
# Test that script runs ok
assert res == 0
if verbose:
print indent + 'Testing accuracy'
import anuga.utilities.plot_utils as util
from analytical_carrier_greenspan import analytic_cg
p_st = util.get_output('carrier_greenspan.sww')
p2_st = util.get_centroids(p_st)
v = p2_st.y[10]
v2 = (p2_st.y == v)
x_n = p2_st.x[v2]
#ids = [288, 296, 304, 312, 320, 328]
ids = [296, 304, 320, 328]
# For the velocity and xmomentum calculations use
# absolute error (as the exact solution is 0)
use_absolute = [False, False, False, False]
n = len(ids)
W, P, Z, H, U = [], [], [], [], []
W_n, U_n, UH_n = [], [], []
for i, id in enumerate(ids):
w0, p0, z0, h0, u0 = analytic_cg(x_n,
p2_st.time[id],
h0=5e2,
L=5e4,
a=1.0,
Tp=900.0)
W.append(w0)
H.append(h0)
U.append(u0)
W_n.append(p2_st.stage[id, v2])
UH_n.append(p2_st.xmom[id, v2])
U_n.append(p2_st.xvel[id, v2])
#print id, numpy.max(H[i]), numpy.min(H[i])
#print id, numpy.max(U[i]), numpy.min(U[i])
#print id, numpy.max(U_n[i]), numpy.min(U_n[i])
#Test stages
# Calculate L^1 error at times
ew = numpy.zeros(n)
for i, id in enumerate(ids):
ew[i] = numpy.sum(numpy.abs(W_n[i] - W[i])) / numpy.sum(
numpy.abs(W[i]))
print
print indent + 'L^1 Errors in stage: ', ew
#Test xmomenta
# Calculate L^1 error at times
euh = numpy.zeros(n)
for i, id in enumerate(ids):
if use_absolute[i]:
euh[i] = numpy.sum(numpy.abs(UH_n[i] - U[i] * H[i])) / len(
U[i])
else:
euh[i] = numpy.sum(
numpy.abs(UH_n[i] - U[i] * H[i])) / numpy.sum(
numpy.abs(UH_n[i]))
print indent + 'L^1 Errors in xmomentum: ', euh
#Test xvelocity
# Calculate L^1 error at times
eu = numpy.zeros(n)
for i, id in enumerate(ids):
if use_absolute[i]:
eu[i] = numpy.sum(numpy.abs(U_n[i] - U[i])) / len(U[i])
else:
eu[i] = numpy.sum(numpy.abs(U_n[i] - U[i])) / numpy.sum(
numpy.abs(U[i]))
print indent + 'L^1 Errors in xvelocity: ', eu
for i, id in enumerate(ids):
assert ew[i] < 0.01, 'L^1 error %g greater than 1 percent' % ew[i]
for i, id in enumerate(ids):
assert euh[
i] < 0.025, 'L^1 error %g greater than 2.5 percent' % euh[i]
for i, id in enumerate(ids):
assert eu[i] < 0.1, 'L^1 error %g greater than 10 percent' % eu[i]
def test_carrier_greenspan_periodic(self):
if verbose:
print
print indent+'Running simulation script'
s = 'numerical_carrier_greenspan.py'
res = anuga.run_anuga_script(s,args=args)
# Test that script runs ok
assert res == 0
if verbose:
print indent+'Testing accuracy'
import anuga.utilities.plot_utils as util
from analytical_carrier_greenspan import analytic_cg
p_st = util.get_output('carrier_greenspan.sww')
p2_st=util.get_centroids(p_st)
v = p2_st.y[10]
v2=(p2_st.y==v)
x_n = p2_st.x[v2]
#ids = [288, 296, 304, 312, 320, 328]
ids = [296, 304, 320, 328]
# For the velocity and xmomentum calculations use
# absolute error (as the exact solution is 0)
use_absolute = [False, False, False, False]
n = len(ids)
W, P, Z, H, U = [], [], [], [], []
W_n, U_n, UH_n = [], [], []
for i, id in enumerate(ids):
w0, p0, z0, h0, u0 = analytic_cg(x_n, p2_st.time[id], h0=5e2, L=5e4, a=1.0, Tp=900.0)
W.append(w0)
H.append(h0)
U.append(u0)
W_n.append(p2_st.stage[id,v2])
UH_n.append(p2_st.xmom[id,v2])
U_n.append(p2_st.xvel[id,v2])
#print id, numpy.max(H[i]), numpy.min(H[i])
#print id, numpy.max(U[i]), numpy.min(U[i])
#print id, numpy.max(U_n[i]), numpy.min(U_n[i])
#Test stages
# Calculate L^1 error at times
ew = numpy.zeros(n)
for i, id in enumerate(ids):
ew[i] = numpy.sum(numpy.abs(W_n[i]-W[i]))/numpy.sum(numpy.abs(W[i]))
print
print indent+'L^1 Errors in stage: ', ew
#Test xmomenta
# Calculate L^1 error at times
euh = numpy.zeros(n)
for i, id in enumerate(ids):
if use_absolute[i]:
euh[i] = numpy.sum(numpy.abs(UH_n[i]-U[i]*H[i]))/len(U[i])
else:
euh[i] = numpy.sum(numpy.abs(UH_n[i]-U[i]*H[i]))/numpy.sum(numpy.abs(UH_n[i]))
print indent+'L^1 Errors in xmomentum: ',euh
#Test xvelocity
# Calculate L^1 error at times
eu = numpy.zeros(n)
for i, id in enumerate(ids):
if use_absolute[i]:
eu[i] = numpy.sum(numpy.abs(U_n[i]-U[i]))/len(U[i])
else:
eu[i] = numpy.sum(numpy.abs(U_n[i]-U[i]))/numpy.sum(numpy.abs(U[i]))
print indent+'L^1 Errors in xvelocity: ', eu
for i, id in enumerate(ids):
assert ew[i] < 0.01, 'L^1 error %g greater than 1 percent'% ew[i]
for i, id in enumerate(ids):
assert euh[i] < 0.025, 'L^1 error %g greater than 2.5 percent'% euh[i]
for i, id in enumerate(ids):
assert eu[i] < 0.1, 'L^1 error %g greater than 10 percent'% eu[i]
def test_dam_break_dry(self):
if verbose:
print
print indent+'Running simulation script'
s = 'numerical_dam_break_dry.py'
res = anuga.run_anuga_script(s,args=args)
# Test that script runs ok
assert res == 0
if verbose:
print indent+'Testing accuracy'
import anuga.utilities.plot_utils as util
import analytical_dam_break_dry as analytic
p_st = util.get_output('dam_break.sww')
p2_st=util.get_centroids(p_st)
v = p2_st.y[10]
v2=(p2_st.y==v)
h0 = 1.0
h1 = 10.0
# calculate analytic values at various time slices
h10,u10 = analytic.vec_dam_break(p2_st.x[v2], p2_st.time[10], h0=h0, h1=h1)
h50,u50 = analytic.vec_dam_break(p2_st.x[v2], p2_st.time[50], h0=h0, h1=h1)
h100,u100 = analytic.vec_dam_break(p2_st.x[v2], p2_st.time[100], h0=h0, h1=h1)
#Test stages
# Calculate L^1 error at times corrsponding to slices 10, 50 and 100
eh10 = numpy.sum(numpy.abs(p2_st.stage[10,v2]-h10))/numpy.sum(numpy.abs(h10))
eh50 = numpy.sum(numpy.abs(p2_st.stage[50,v2]-h50))/numpy.sum(numpy.abs(h50))
eh100 = numpy.sum(numpy.abs(p2_st.stage[100,v2]-h100))/numpy.sum(numpy.abs(h100))
print
print indent+'Errors in stage: ',eh10, eh50, eh100
#Test xmomenta
# Calculate L^1 error at times corrsponding to slices 10, 50 and 100
euh10 = numpy.sum(numpy.abs(p2_st.xmom[10,v2]-u10*h10))/numpy.sum(numpy.abs(u10*h10))
euh50 = numpy.sum(numpy.abs(p2_st.xmom[50,v2]-u50*h50))/numpy.sum(numpy.abs(u50*h50))
euh100 = numpy.sum(numpy.abs(p2_st.xmom[100,v2]-u100*h100))/numpy.sum(numpy.abs(u100*h100))
print indent+'Errors in xmomentum: ',euh10, euh50, euh100
#Test xvelocity
# Calculate L^1 error at times corrsponding to slices 10, 50 and 100
eu10 = numpy.sum(numpy.abs(p2_st.xvel[10,v2]-u10))/numpy.sum(numpy.abs(u10))
eu50 = numpy.sum(numpy.abs(p2_st.xvel[50,v2]-u50))/numpy.sum(numpy.abs(u50))
eu100 = numpy.sum(numpy.abs(p2_st.xvel[100,v2]-u100))/numpy.sum(numpy.abs(u100))
print indent+'Errors in xvelocity: ', eu10, eu50, eu100
assert eh10 < 0.1, 'Relative L^1 error %g greater than 0.1'% eh10
assert eh50 < 0.1, 'Relative L^1 error %g greater than 0.1'% eh50
assert eh100 < 0.15, 'Relative L^1 error %g greater than 0.15'% eh100
assert euh10 < 0.25, 'Relative L^1 error %g greater than 0.25'% euh10
assert euh50 < 0.25, 'Relative L^1 error %g greater than 0.25'% euh50
assert euh100 < 0.25, 'Relative L^1 error %g greater than 0.25'% euh100
assert eu10 < 2.0, 'Relative L^1 error %g greater than 2.0'% eu10
assert eu50 < 2.0, 'Relative L^1 error %g greater than 2.0'% eu50
assert eu100 < 0.3, 'Relative L^1 error %g greater than 0.3'% eu100
def test_avalanche_dry(self):
if verbose:
print
print indent + "Running simulation script"
# Run basic script (can be parallel if -np used in call
# to this script
s = "numerical_avalanche_dry.py"
res = anuga.run_anuga_script(s, args=args)
# Test that script runs ok
assert res == 0
if verbose:
print indent + "Testing accuracy"
import anuga.utilities.plot_utils as util
from analytical_avalanche_dry import analytical_sol
p_st = util.get_output("avalanche.sww")
p2_st = util.get_centroids(p_st)
v = p2_st.y[10]
v2 = p2_st.y == v
x_n = p2_st.x[v2]
u0, h0, w0, z0, p0 = analytical_sol(x_n, p2_st.time[0])
u10, h10, w10, z10, p10 = analytical_sol(x_n, p2_st.time[10])
u30, h30, w30, z30, p30 = analytical_sol(x_n, p2_st.time[30])
w0_n = p2_st.stage[0, v2]
w10_n = p2_st.stage[10, v2]
w30_n = p2_st.stage[30, v2]
z_n = p2_st.elev[v2]
uh0_n = p2_st.xmom[0, v2]
uh10_n = p2_st.xmom[10, v2]
uh30_n = p2_st.xmom[30, v2]
u0_n = p2_st.xvel[0, v2]
u10_n = p2_st.xvel[10, v2]
u30_n = p2_st.xvel[30, v2]
# Test stages
# Calculate L^1 error at times corrsponding to slices 10, 50 and 100
eh10 = numpy.sum(numpy.abs(w10_n - w10)) / numpy.sum(numpy.abs(w10))
eh30 = numpy.sum(numpy.abs(w30_n - w30)) / numpy.sum(numpy.abs(w30))
print
print indent + "Errors in stage: ", eh10, eh30
# Test xmomenta
# Calculate L^1 error at times corrsponding to slices 10, 50 and 100
euh10 = numpy.sum(numpy.abs(uh10_n - u10 * h10)) / numpy.sum(numpy.abs(u10 * h10))
euh30 = numpy.sum(numpy.abs(uh30_n - u30 * h30)) / numpy.sum(numpy.abs(u30 * h30))
print indent + "Errors in xmomentum: ", euh10, euh30
# Test xvelocity
# Calculate L^1 error at times corrsponding to slices 10, 50 and 100
eu10 = numpy.sum(numpy.abs(u10_n - u10)) / numpy.sum(numpy.abs(u10))
eu30 = numpy.sum(numpy.abs(u30_n - u30)) / numpy.sum(numpy.abs(u30))
print indent + "Errors in xvelocity: ", eu10, eu30
assert eh10 < 0.01, "L^1 error %g greater than 1 percent" % eh10
assert eh30 < 0.01, "L^1 error %g greater than 1 percent" % eh30
assert euh10 < 0.025, "L^1 error %g greater than 2.5 percent" % euh10
assert euh30 < 0.025, "L^1 error %g greater than 2.5 percent" % euh30
assert eu10 < 0.2, "L^1 error %g greater than 20 percent" % eu10
assert eu30 < 0.2, "L^1 error %g greater than 20 percent" % eu30
def test_carrier_greenspan_transient(self):
if verbose:
print
print indent+'Running simulation script'
s = 'numerical_cg_transient.py'
res = anuga.run_anuga_script(s,args=args)
# Test that script runs ok
assert res == 0
if verbose:
print indent+'Testing accuracy'
import anuga.utilities.plot_utils as util
from analytical_cg_transient import analytical_sol
p_st = util.get_output('carrier_greenspan.sww')
p2_st=util.get_centroids(p_st)
v = p2_st.y[10]
v2=(p2_st.y==v)
x_n = p2_st.x[v2]
ids = [1, 15, 30]
use_absolute = [False, True, True]
n = len(ids)
W, UH, Z, H, U = [], [], [], [], []
W_n, U_n, UH_n = [], [], []
#Dimensional parameters
L = 5e4 # Length of channel (m)
h0 = 5e2 # Height at origin when the water is still
g = 9.81 # Gravity
for i, id in enumerate(ids):
w, z, u = analytical_sol(x_n/L, p2_st.time[id]*sqrt(g*h0)/L)
w = w*h0
z = z*h0
u = u*sqrt(g*h0)
h = w-z
uh = u*h
W.append(w)
Z.append(z)
H.append(h)
U.append(u)
UH.append(uh)
W_n.append(p2_st.stage[id,v2])
UH_n.append(p2_st.xmom[id,v2])
U_n.append(p2_st.xvel[id,v2])
#print id, numpy.max(H[i]), numpy.min(H[i])
#print id, numpy.max(U[i]), numpy.min(U[i])
#print id, numpy.max(U_n[i]), numpy.min(U_n[i])
#Test stages
# Calculate L^1 error at times
ew = numpy.zeros(n)
for i, id in enumerate(ids):
ew[i] = numpy.sum(numpy.abs(W_n[i]-W[i]))/numpy.sum(numpy.abs(W[i]))
print
print indent+'L^1 Errors in stage: ', ew
#Test xmomenta
# Calculate L^1 error at times
euh = numpy.zeros(n)
for i, id in enumerate(ids):
euh[i] = numpy.sum(numpy.abs(UH_n[i]-U[i]*H[i]))/numpy.sum(numpy.abs(UH_n[i]))
print indent+'L^1 Errors in xmomentum: ',euh
#Test xvelocity
# Calculate L^1 error at times
eu = numpy.zeros(n)
for i, id in enumerate(ids):
if use_absolute[i]:
eu[i] = numpy.sum(numpy.abs(U_n[i]-U[i]))/len(U[i])
else:
eu[i] = numpy.sum(numpy.abs(U_n[i]-U[i]))/numpy.sum(numpy.abs(U[i]))
print indent+'L^1 Errors in xvelocity: ', eu
for i, id in enumerate(ids):
assert ew[i] < 0.01, 'L^1 error %g greater than 1 percent'% ew[i]
for i, id in enumerate(ids):
assert euh[i] < 0.025, 'L^1 error %g greater than 2.5 percent'% euh[i]
for i, id in enumerate(ids):
assert eu[i] < 0.025, 'L^1 error %g greater than 2.5 percent'% eu[i]
def test_avalanche_wet(self):
if verbose:
print
print indent + 'Running simulation script'
s = 'numerical_avalanche_wet.py'
res = anuga.run_anuga_script(s, args=args)
# Test that script runs ok
assert res == 0
if verbose:
print indent + 'Testing accuracy'
import anuga.utilities.plot_utils as util
from analytical_avalanche_wet import analytical_sol
p_st = util.get_output('avalanche.sww')
p2_st = util.get_centroids(p_st)
v = p2_st.y[20]
v2 = (p2_st.y == v)
x_n = p2_st.x[v2]
u0, h0, w0, z0, p0 = analytical_sol(x_n, p2_st.time[0])
u20, h20, w20, z20, p20 = analytical_sol(x_n, p2_st.time[20])
u40, h40, w40, z40, p40 = analytical_sol(x_n, p2_st.time[40])
w0_n = p2_st.stage[0, v2]
w20_n = p2_st.stage[20, v2]
w40_n = p2_st.stage[40, v2]
z_n = p2_st.elev[v2]
uh0_n = p2_st.xmom[0, v2]
uh20_n = p2_st.xmom[20, v2]
uh40_n = p2_st.xmom[40, v2]
u0_n = p2_st.xvel[0, v2]
u20_n = p2_st.xvel[20, v2]
u40_n = p2_st.xvel[40, v2]
#Test stages
# Calculate L^1 error at times corrsponding to slices 20, 40
eh20 = numpy.sum(numpy.abs(w20_n - w20)) / numpy.sum(numpy.abs(w20))
eh40 = numpy.sum(numpy.abs(w40_n - w40)) / numpy.sum(numpy.abs(w40))
print
print indent + 'Errors in stage: ', eh20, eh40
#Test xmomenta
# Calculate L^1 error at times corrsponding to slices 20, 40
euh20 = numpy.sum(numpy.abs(uh20_n - u20 * h20)) / numpy.sum(
numpy.abs(u20 * h20))
euh40 = numpy.sum(numpy.abs(uh40_n - u40 * h40)) / numpy.sum(
numpy.abs(u40 * h40))
print indent + 'Errors in xmomentum: ', euh20, euh40
#Test xvelocity
# Calculate L^1 error at times corrsponding to slices 20, 40
eu20 = numpy.sum(numpy.abs(u20_n - u20)) / numpy.sum(numpy.abs(u20))
eu40 = numpy.sum(numpy.abs(u40_n - u40)) / numpy.sum(numpy.abs(u40))
print indent + 'Errors in xvelocity: ', eu20, eu40
assert eh20 < 0.01, 'L^1 error %g greater than 1 percent' % eh20
assert eh40 < 0.01, 'L^1 error %g greater than 1 percent' % eh40
assert euh20 < 0.025, 'L^1 error %g greater than 2.5 percent' % euh20
assert euh40 < 0.025, 'L^1 error %g greater than 2.5 percent' % euh40
assert eu20 < 0.02, 'L^1 error %g greater than 2 percent' % eu20
assert eu40 < 0.01, 'L^1 error %g greater than 2 percent' % eu40
def test_avalanche_wet(self):
if verbose:
print
print indent + "Running simulation script"
s = "numerical_avalanche_wet.py"
res = anuga.run_anuga_script(s, args=args)
# Test that script runs ok
assert res == 0
if verbose:
print indent + "Testing accuracy"
import anuga.utilities.plot_utils as util
from analytical_avalanche_wet import analytical_sol
p_st = util.get_output("avalanche.sww")
p2_st = util.get_centroids(p_st)
v = p2_st.y[20]
v2 = p2_st.y == v
x_n = p2_st.x[v2]
u0, h0, w0, z0, p0 = analytical_sol(x_n, p2_st.time[0])
u20, h20, w20, z20, p20 = analytical_sol(x_n, p2_st.time[20])
u40, h40, w40, z40, p40 = analytical_sol(x_n, p2_st.time[40])
w0_n = p2_st.stage[0, v2]
w20_n = p2_st.stage[20, v2]
w40_n = p2_st.stage[40, v2]
z_n = p2_st.elev[v2]
uh0_n = p2_st.xmom[0, v2]
uh20_n = p2_st.xmom[20, v2]
uh40_n = p2_st.xmom[40, v2]
u0_n = p2_st.xvel[0, v2]
u20_n = p2_st.xvel[20, v2]
u40_n = p2_st.xvel[40, v2]
# Test stages
# Calculate L^1 error at times corrsponding to slices 20, 40
eh20 = numpy.sum(numpy.abs(w20_n - w20)) / numpy.sum(numpy.abs(w20))
eh40 = numpy.sum(numpy.abs(w40_n - w40)) / numpy.sum(numpy.abs(w40))
print
print indent + "Errors in stage: ", eh20, eh40
# Test xmomenta
# Calculate L^1 error at times corrsponding to slices 20, 40
euh20 = numpy.sum(numpy.abs(uh20_n - u20 * h20)) / numpy.sum(numpy.abs(u20 * h20))
euh40 = numpy.sum(numpy.abs(uh40_n - u40 * h40)) / numpy.sum(numpy.abs(u40 * h40))
print indent + "Errors in xmomentum: ", euh20, euh40
# Test xvelocity
# Calculate L^1 error at times corrsponding to slices 20, 40
eu20 = numpy.sum(numpy.abs(u20_n - u20)) / numpy.sum(numpy.abs(u20))
eu40 = numpy.sum(numpy.abs(u40_n - u40)) / numpy.sum(numpy.abs(u40))
print indent + "Errors in xvelocity: ", eu20, eu40
assert eh20 < 0.01, "L^1 error %g greater than 1 percent" % eh20
assert eh40 < 0.01, "L^1 error %g greater than 1 percent" % eh40
assert euh20 < 0.025, "L^1 error %g greater than 2.5 percent" % euh20
assert euh40 < 0.025, "L^1 error %g greater than 2.5 percent" % euh40
assert eu20 < 0.02, "L^1 error %g greater than 2 percent" % eu20
assert eu40 < 0.01, "L^1 error %g greater than 2 percent" % eu40
