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<?xml version="1.0" encoding="UTF-8" ?>
<testproblem>
<name>p1cv advection-diffusion equation spatial convergence test using element gradient diffusion</name>
<owner userid="cwilson"/>
<tags>flml</tags>
<problem_definition length="short" nprocs="1">
<command_line>fluidity -v1 MMS_A_cv.flml > MMS_A.log; mv Burgers__NumericalSolution.convergence MMS_A_cv.convergence; fluidity -v1 MMS_B_cv.flml > MMS_B.log; mv Burgers__NumericalSolution.convergence MMS_B_cv.convergence; fluidity -v1 MMS_C_cv.flml > MMS_C.log; mv Burgers__NumericalSolution.convergence MMS_C_cv.convergence; fluidity -v1 MMS_D_cv.flml > MMS_D.log; mv Burgers__NumericalSolution.convergence MMS_D_cv.convergence; fluidity -v1 MMS_E_cv.flml > MMS_E.log; mv Burgers__NumericalSolution.convergence MMS_E_cv.convergence</command_line>
</problem_definition>
<variables>
<variable name="ab_convergence_gal_stat" language="python">
from fluidity_tools import stat_parser as stat
from math import log
a_error = stat("MMS_A_cv.stat")["Burgers"]["AbsoluteDifference"]["l2norm"][-1]
b_error = stat("MMS_B_cv.stat")["Burgers"]["AbsoluteDifference"]["l2norm"][-1]
a_error_inf = stat("MMS_A_cv.stat")["Burgers"]["AbsoluteDifference"]["max"][-1]
b_error_inf = stat("MMS_B_cv.stat")["Burgers"]["AbsoluteDifference"]["max"][-1]
print a_error
print b_error
print a_error_inf
print b_error_inf
ab_ratio = a_error / b_error
ab_ratio_inf = a_error_inf / b_error_inf
ab_convergence_gal_stat = [log(ab_ratio, 2), log(ab_ratio_inf, 2)]
</variable>
<variable name="bc_convergence_gal_stat" language="python">
from fluidity_tools import stat_parser as stat
from math import log
b_error = stat("MMS_B_cv.stat")["Burgers"]["AbsoluteDifference"]["l2norm"][-1]
c_error = stat("MMS_C_cv.stat")["Burgers"]["AbsoluteDifference"]["l2norm"][-1]
b_error_inf = stat("MMS_B_cv.stat")["Burgers"]["AbsoluteDifference"]["max"][-1]
c_error_inf = stat("MMS_C_cv.stat")["Burgers"]["AbsoluteDifference"]["max"][-1]
print b_error
print c_error
print b_error_inf
print c_error_inf
bc_ratio = b_error / c_error
bc_ratio_inf = b_error_inf / c_error_inf
bc_convergence_gal_stat = [log(bc_ratio, 2), log(bc_ratio_inf, 2)]
</variable>
<variable name="cd_convergence_gal_stat" language="python">
from fluidity_tools import stat_parser as stat
from math import log
c_error = stat("MMS_C_cv.stat")["Burgers"]["AbsoluteDifference"]["l2norm"][-1]
d_error = stat("MMS_D_cv.stat")["Burgers"]["AbsoluteDifference"]["l2norm"][-1]
c_error_inf = stat("MMS_C_cv.stat")["Burgers"]["AbsoluteDifference"]["max"][-1]
d_error_inf = stat("MMS_D_cv.stat")["Burgers"]["AbsoluteDifference"]["max"][-1]
print c_error
print d_error
print c_error_inf
print d_error_inf
cd_ratio = c_error / d_error
cd_ratio_inf = c_error_inf / d_error_inf
cd_convergence_gal_stat = [log(cd_ratio, 2), log(cd_ratio_inf, 2)]
</variable>
<variable name="de_convergence_gal_stat" language="python">
from fluidity_tools import stat_parser as stat
from math import log
d_error = stat("MMS_D_cv.stat")["Burgers"]["AbsoluteDifference"]["l2norm"][-1]
e_error = stat("MMS_E_cv.stat")["Burgers"]["AbsoluteDifference"]["l2norm"][-1]
d_error_inf = stat("MMS_D_cv.stat")["Burgers"]["AbsoluteDifference"]["max"][-1]
e_error_inf = stat("MMS_E_cv.stat")["Burgers"]["AbsoluteDifference"]["max"][-1]
print d_error
print e_error
print d_error_inf
print e_error_inf
de_ratio = d_error / e_error
de_ratio_inf = d_error_inf / e_error_inf
de_convergence_gal_stat = [log(de_ratio, 2), log(de_ratio_inf, 2)]
</variable>
<!-- <variable name="ef_convergence_gal_stat" language="python">
from fluidity_tools import stat_parser as stat
from math import log
e_error = stat("MMS_E_cv.stat")["Burgers"]["AbsoluteDifference"]["l2norm"][-1]
f_error = stat("MMS_F_cv.stat")["Burgers"]["AbsoluteDifference"]["l2norm"][-1]
e_error_inf = stat("MMS_E_cv.stat")["Burgers"]["AbsoluteDifference"]["max"][-1]
f_error_inf = stat("MMS_F_cv.stat")["Burgers"]["AbsoluteDifference"]["max"][-1]
print e_error
print f_error
print e_error_inf
print f_error_inf
ef_ratio = e_error / f_error
ef_ratio_inf = e_error_inf / f_error_inf
ef_convergence_gal_stat = [log(ef_ratio, 2), log(ef_ratio_inf, 2)]
</variable>-->
<variable name="a_finish_time" language="python">
from fluidity_tools import stat_parser as stat
a_finish_time = stat("MMS_A_cv.stat")["ElapsedTime"]["value"][-1]
</variable>
<variable name="b_finish_time" language="python">
from fluidity_tools import stat_parser as stat
b_finish_time = stat("MMS_B_cv.stat")["ElapsedTime"]["value"][-1]
</variable>
<variable name="c_finish_time" language="python">
from fluidity_tools import stat_parser as stat
c_finish_time = stat("MMS_C_cv.stat")["ElapsedTime"]["value"][-1]
</variable>
<variable name="d_finish_time" language="python">
from fluidity_tools import stat_parser as stat
d_finish_time = stat("MMS_D_cv.stat")["ElapsedTime"]["value"][-1]
</variable>
<variable name="e_finish_time" language="python">
from fluidity_tools import stat_parser as stat
e_finish_time = stat("MMS_E_cv.stat")["ElapsedTime"]["value"][-1]
</variable>
<!-- <variable name="f_finish_time" language="python">
from fluidity_tools import stat_parser as stat
f_finish_time = stat("MMS_F_cv.stat")["ElapsedTime"]["value"][-1]
</variable>-->
<variable name="a_max_adv_it" language="python">
from fluidity_tools import stat_parser as stat
a_max_adv_it = max(stat("MMS_A_cv.convergence")["AdvectionIteration"]["value"])
</variable>
<variable name="b_max_adv_it" language="python">
from fluidity_tools import stat_parser as stat
b_max_adv_it = max(stat("MMS_B_cv.convergence")["AdvectionIteration"]["value"])
</variable>
<variable name="c_max_adv_it" language="python">
from fluidity_tools import stat_parser as stat
c_max_adv_it = max(stat("MMS_C_cv.convergence")["AdvectionIteration"]["value"])
</variable>
<variable name="d_max_adv_it" language="python">
from fluidity_tools import stat_parser as stat
d_max_adv_it = max(stat("MMS_D_cv.convergence")["AdvectionIteration"]["value"])
</variable>
<variable name="e_max_adv_it" language="python">
from fluidity_tools import stat_parser as stat
e_max_adv_it = max(stat("MMS_E_cv.convergence")["AdvectionIteration"]["value"])
</variable>
<!-- <variable name="f_max_adv_it" language="python">
from fluidity_tools import stat_parser as stat
f_max_adv_it = max(stat("MMS_F_cv.convergence")["AdvectionIteration"]["value"])
</variable>-->
</variables>
<pass_tests>
<test name="ab_convergence_stat: L2 order in [1.8,2.2]" language="python">
assert(abs(ab_convergence_gal_stat[0]-2.0) < 0.2)
</test>
<test name="bc_convergence_stat: L2 order in [1.8,2.2]" language="python">
assert(abs(bc_convergence_gal_stat[0]-2.0) < 0.2)
</test>
<test name="cd_convergence_stat: L2 order in [1.8,2.2]" language="python">
assert(abs(cd_convergence_gal_stat[0]-2.0) < 0.2)
</test>
<test name="de_convergence_stat: L2 order in [1.8,2.2]" language="python">
assert(abs(de_convergence_gal_stat[0]-2.0) < 0.2)
</test>
<!-- <test name="ef_convergence_stat: L2 order in [1.8,2.2]" language="python">
assert(abs(ef_convergence_gal_stat[0]-2.0) < 0.2)
</test>-->
<test name="checking A finished in less than 1.0" language="python">
assert(a_finish_time-1.0 < 1.E-10)
</test>
<test name="checking B finished in less than 1.0" language="python">
assert(b_finish_time-1.0 < 1.E-10)
</test>
<test name="checking C finished in less than 1.0" language="python">
assert(c_finish_time-1.0 < 1.E-10)
</test>
<test name="checking D finished in less than 1.0" language="python">
assert(d_finish_time-1.0 < 1.E-10)
</test>
<test name="checking E finished in less than 1.0" language="python">
assert(e_finish_time-1.0 < 1.E-10)
</test>
<!-- <test name="checking F finished in less than 1.0" language="python">
assert(f_finish_time-1.0 < 1.E-10)
</test>-->
<test name="checking A performed less than 10 advection iterations per timestep" language="python">
assert(a_max_adv_it < 10)
</test>
<test name="checking B performed less than 10 advection iterations per timestep" language="python">
assert(b_max_adv_it < 10)
</test>
<test name="checking C performed less than 10 advection iterations per timestep" language="python">
assert(c_max_adv_it < 10)
</test>
<test name="checking D performed less than 10 advection iterations per timestep" language="python">
assert(d_max_adv_it < 10)
</test>
<test name="checking E performed less than 10 advection iterations per timestep" language="python">
assert(e_max_adv_it < 10)
</test>
<!-- <test name="checking F performed less than 20 advection iterations per timestep" language="python">
assert(f_max_adv_it < 20)
</test>-->
</pass_tests>
<warn_tests>
</warn_tests>
</testproblem>
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