M = 2 # integer factor that meshsize is refined by at each level
Lmin = 2 # minimum refinement level
Lmax = 8 # maximum refinement level
L = 7
# list of all levels considered
l_element = []
for i in range(Lmin, Lmax + 1):
l_element.append(i)
bathy = Bathymetry()
bathy.length_x = 1250
bathy.length_y = 1000
bathy.dx = bathy.length_x / M**Lmax
bathy.dy = bathy.length_y / M**Lmax
bathy.mc_slope_test(bathy.dx, bathy.dy, 0.6, 0.15, 0.15)
# interpolation function used to generate bed on new x and y grid
interp_orig_fn = interpolate.interp2d(bathy.x, bathy.y, bathy.z)
# epsilon values - for CDF calculation this should be set to epsilon = [0.001]
epsilon = [0.001, 0.0017, 0.0025, 0.0035, 0.005, 0.006]
N0 = 500 # number of samples used in preliminary run
# set the function which builds XBeach inputs, runs XBeach and records output
build_output = bd_fns.build_xbeach_2d
no_runs = 1
no_parallel_processes = 40 # should be equal to number of cores
# directory where XBeach files will be dumped and code will run - this needs to be changed to reflect name of folder
# directory where XBeach files will be dumped and code will run - this needs to be changed to reflect name of folder
path_stem = '/rds/general/user/mc4117/home/MLMC_Code/slope_2d_mc/1/'
variable_name = 'bed_slope_2d' # name of uncertain variable
M = 2 # integer factor that meshsize is refined by at each level
t1 = time.time()
L_eps = 9 # fineness of grid
bathy = Bathymetry()
bathy.length_x = 1250
bathy.length_y = 1000
bathy.dx = bathy.length_x / M**L_eps
bathy.dy = bathy.length_y / M**L_eps
bathy.mc_slope_test(bathy.dx, bathy.dy, 0.6, 0.15, 0.15)
# interpolation function used to generate bed on new x and y grid
interp_orig_fn = interpolate.interp2d(bathy.x, bathy.y, bathy.z)
# run monte carlo algorithm
outputf, real_soln, file_name = mc_fn.monte_carlo_main(1000, M**L_eps,
build_output, path_stem,
sample, variable_name,
no_parallel_processes,
interp_orig_fn)
t2 = time.time()