def setrun(claw_pkg='geoclaw'):
#------------------------------
"""
Define the parameters used for running Clawpack.
INPUT:
claw_pkg expected to be "geoclaw" for this setrun.
OUTPUT:
rundata - object of class ClawRunData
"""
from clawpack.clawutil import data
assert claw_pkg.lower() == 'geoclaw', "Expected claw_pkg = 'geoclaw'"
num_dim = 2
rundata = data.ClawRunData(claw_pkg, num_dim)
#------------------------------------------------------------------
# GeoClaw specific parameters:
#------------------------------------------------------------------
rundata = setgeo(rundata)
set_multilayer(rundata)
#------------------------------------------------------------------
# Standard Clawpack parameters to be written to claw.data:
# (or to amr2ez.data for AMR)
#------------------------------------------------------------------
clawdata = rundata.clawdata # initialized when rundata instantiated
# Set single grid parameters first.
# See below for AMR parameters.
# ---------------
# Spatial domain:
# ---------------
# Number of space dimensions:
clawdata.num_dim = num_dim
# Lower and upper edge of computational domain:
clawdata.lower[0] = -1 # west longitude
clawdata.upper[0] = 2.0 # east longitude
clawdata.lower[1] = -1.0 # south latitude
clawdata.upper[1] = 2.0 # north latitude
# Number of grid cells: Coarsest grid
clawdata.num_cells[0] = 75
clawdata.num_cells[1] = 75
# ---------------
# Size of system:
# ---------------
# Number of equations in the system:
clawdata.num_eqn = 6
# Number of auxiliary variables in the aux array (initialized in setaux)
clawdata.num_aux = 4 + rundata.multilayer_data.num_layers
# Index of aux array corresponding to capacity function, if there is one:
clawdata.capa_index = 0
# -------------
# Initial time:
# -------------
clawdata.t0 = 0.0
# Restart from checkpoint file of a previous run?
# Note: If restarting, you must also change the Makefile to set:
# RESTART = True
# If restarting, t0 above should be from original run, and the
# restart_file 'fort.chkNNNNN' specified below should be in
# the OUTDIR indicated in Makefile.
clawdata.restart = False # True to restart from prior results
clawdata.restart_file = 'fort.chk00036' # File to use for restart data
# -------------
# Output times:
#--------------
# Specify at what times the results should be written to fort.q files.
# Note that the time integration stops after the final output time.
# The solution at initial time t0 is always written in addition.
clawdata.output_style = 1
if clawdata.output_style==1:
# Output nout frames at equally spaced times up to tfinal:
clawdata.num_output_times = 1
clawdata.tfinal = 1.0
clawdata.output_t0 = True # output at initial (or restart) time?
elif clawdata.output_style == 2:
# Specify a list of output times.
clawdata.output_times = [0.5, 1.0]
elif clawdata.output_style == 3:
# Output every iout timesteps with a total of ntot time steps:
clawdata.output_step_interval = 10
clawdata.total_steps = 100
clawdata.output_t0 = True
clawdata.output_format = 'ascii' # 'ascii' or 'binary'
clawdata.output_q_components = 'all' # need all
clawdata.output_aux_components = 'all' # eta=h+B is in q
clawdata.output_aux_onlyonce = False # output aux arrays each frame
# ---------------------------------------------------
# Verbosity of messages to screen during integration:
# ---------------------------------------------------
# The current t, dt, and cfl will be printed every time step
# at AMR levels <= verbosity. Set verbosity = 0 for no printing.
# (E.g. verbosity == 2 means print only on levels 1 and 2.)
clawdata.verbosity = 1
# --------------
# Time stepping:
# --------------
# if dt_variable==1: variable time steps used based on cfl_desired,
# if dt_variable==0: fixed time steps dt = dt_initial will always be used.
clawdata.dt_variable = True
# Initial time step for variable dt.
# If dt_variable==0 then dt=dt_initial for all steps:
clawdata.dt_initial = 0.00225
# Max time step to be allowed if variable dt used:
clawdata.dt_max = 1e+99
# Desired Courant number if variable dt used, and max to allow without
# retaking step with a smaller dt:
clawdata.cfl_desired = 0.75
clawdata.cfl_max = 1.0
# clawdata.cfl_desired = 0.45
# clawdata.cfl_max = 0.5
# Maximum number of time steps to allow between output times:
clawdata.steps_max = 5000
# ------------------
# Method to be used:
# ------------------
# Order of accuracy: 1 => Godunov, 2 => Lax-Wendroff plus limiters
clawdata.order = 2
# Use dimensional splitting? (not yet available for AMR)
# 0 or 'unsplit' or none' ==> Unsplit
# 1 or 'increment' ==> corner transport of waves
# 2 or 'all' ==> corner transport of 2nd order corrections too
clawdata.dimensional_split = 0
# For unsplit method, transverse_waves can be
# 0 or 'none' ==> donor cell (only normal solver used)
# 1 or 'increment' ==> corner transport of waves
# 2 or 'all' ==> corner transport of 2nd order corrections too
clawdata.transverse_waves = 2
# Number of waves in the Riemann solution:
clawdata.num_waves = 6
# List of limiters to use for each wave family:
# Required: len(limiter) == num_waves
# Some options:
# 0 or 'none' ==> no limiter (Lax-Wendroff)
# 1 or 'minmod' ==> minmod
# 2 or 'superbee' ==> superbee
# 3 or 'mc' ==> MC limiter
# 4 or 'vanleer' ==> van Leer
clawdata.limiter = ['mc', 'mc', 'mc', 'mc', 'mc', 'mc']
clawdata.use_fwaves = True # True ==> use f-wave version of algorithms
# Source terms splitting:
# src_split == 0 or 'none' ==> no source term (src routine never called)
# src_split == 1 or 'godunov' ==> Godunov (1st order) splitting used,
# src_split == 2 or 'strang' ==> Strang (2nd order) splitting used, not recommended.
clawdata.source_split = 'godunov'
# --------------------
# Boundary conditions:
# --------------------
# Number of ghost cells (usually 2)
clawdata.num_ghost = 2
# Choice of BCs at xlower and xupper:
# 0 => user specified (must modify bcN.f to use this option)
# 1 => extrapolation (non-reflecting outflow)
# 2 => periodic (must specify this at both boundaries)
# 3 => solid wall for systems where q(2) is normal velocity
clawdata.bc_lower[0] = 'extrap'
clawdata.bc_upper[0] = 'extrap'
clawdata.bc_lower[1] = 'extrap'
clawdata.bc_upper[1] = 'extrap'
# --------------
# Checkpointing:
# --------------
# Specify when checkpoint files should be created that can be
# used to restart a computation.
clawdata.checkpt_style = 0
if clawdata.checkpt_style == 0:
# Do not checkpoint at all
pass
elif clawdata.checkpt_style == 1:
# Checkpoint only at tfinal.
pass
elif clawdata.checkpt_style == 2:
# Specify a list of checkpoint times.
clawdata.checkpt_times = [0.1,0.15]
elif clawdata.checkpt_style == 3:
# Checkpoint every checkpt_interval timesteps (on Level 1)
# and at the final time.
clawdata.checkpt_interval = 5
# ---------------
# AMR parameters:
# ---------------
amrdata = rundata.amrdata
# max number of refinement levels:
amrdata.amr_levels_max = 1
# List of refinement ratios at each level (length at least mxnest-1)
amrdata.refinement_ratios_x = [2,6]
amrdata.refinement_ratios_y = [2,6]
amrdata.refinement_ratios_t = [2,6]
# Specify type of each aux variable in amrdata.auxtype.
# This must be a list of length maux, each element of which is one of:
# 'center', 'capacity', 'xleft', or 'yleft' (see documentation).
amrdata.aux_type = ['center','center','yleft','center','center','center']
# Flag using refinement routine flag2refine rather than richardson error
amrdata.flag_richardson = False # use Richardson?
amrdata.flag2refine = True
# steps to take on each level L between regriddings of level L+1:
amrdata.regrid_interval = 3
# width of buffer zone around flagged points:
# (typically the same as regrid_interval so waves don't escape):
amrdata.regrid_buffer_width = 2
# clustering alg. cutoff for (# flagged pts) / (total # of cells refined)
# (closer to 1.0 => more small grids may be needed to cover flagged cells)
amrdata.clustering_cutoff = 0.700000
# print info about each regridding up to this level:
amrdata.verbosity_regrid = 0
# ----- For developers -----
# Toggle debugging print statements:
amrdata.dprint = False # print domain flags
amrdata.eprint = False # print err est flags
amrdata.edebug = False # even more err est flags
amrdata.gprint = False # grid bisection/clustering
amrdata.nprint = False # proper nesting output
amrdata.pprint = False # proj. of tagged points
amrdata.rprint = False # print regridding summary
amrdata.sprint = False # space/memory output
amrdata.tprint = True # time step reporting each level
amrdata.uprint = False # update/upbnd reporting
# More AMR parameters can be set -- see the defaults in pyclaw/data.py
# ---------------
# Regions:
# ---------------
rundata.regiondata.regions = []
# to specify regions of refinement append lines of the form
# [minlevel,maxlevel,t1,t2,x1,x2,y1,y2]
# ---------------
# Gauges:
# ---------------
rundata.gaugedata.gauges = []
# for gauges append lines of the form [gaugeno, x, y, t1, t2]
gauge_locations = [-0.1,0.0,0.1,0.2,0.3]
for (i,x_c) in enumerate(gauge_locations):
# y0 = (self.run_data.clawdata.yupper - self.run_data.clawdata.ylower) / 2.0
# x_p,y_p = transform_c2p(x_c,0.0,location[0],location[1],angle)
x_p = x_c * numpy.cos(0.0)
y_p = x_c * numpy.sin(0.0)
# print "+=====+"
# print x_c,0.0
# print x_p,y_p
if (rundata.clawdata.lower[0] < x_p < rundata.clawdata.upper[0] and
rundata.clawdata.lower[1] < y_p < rundata.clawdata.upper[1]):
rundata.gaugedata.gauges.append([i, x_p, y_p, 0.0, 1e10])
# print "Gauge %s: (%s,%s)" % (i,x_p,y_p)
# print "+=====+"
return rundata
def setrun(claw_pkg='geoclaw'):
#------------------------------
"""
Define the parameters used for running Clawpack.
INPUT:
claw_pkg expected to be "geoclaw" for this setrun.
OUTPUT:
rundata - object of class ClawRunData
"""
from clawpack.clawutil import data
assert claw_pkg.lower() == 'geoclaw', "Expected claw_pkg = 'geoclaw'"
num_dim = 2
rundata = data.ClawRunData(claw_pkg, num_dim)
#------------------------------------------------------------------
# Problem-specific parameters to be written to setprob.data:
#------------------------------------------------------------------
theta_island = 220.
probdata = rundata.new_UserData(name='probdata', fname='setprob.data')
probdata.add_param('theta_island', theta_island, 'angle to island')
#------------------------------------------------------------------
# GeoClaw specific parameters:
#------------------------------------------------------------------
rundata = setgeo(rundata)
rundata = set_multilayer(rundata)
#------------------------------------------------------------------
# Standard Clawpack parameters to be written to claw.data:
# (or to amr2ez.data for AMR)
#------------------------------------------------------------------
clawdata = rundata.clawdata # initialized when rundata instantiated
# Set single grid parameters first.
# See below for AMR parameters.
# ---------------
# Spatial domain:
# ---------------
# Number of space dimensions:
clawdata.num_dim = num_dim
# Lower and upper edge of computational domain:
clawdata.lower[0] = -30.0 # xlower
clawdata.upper[0] = 30.0 # xupper
clawdata.lower[1] = 20.0 # ylower
clawdata.upper[1] = 60.0 # yupper
# Number of grid cells:
clawdata.num_cells[0] = 80 # mx
clawdata.num_cells[1] = 80 # my
# ### FOR DEBUGGING
# # Lower and upper edge of computational domain:
# clawdata.lower[0] = 5.0 # xlower
# clawdata.upper[0] = 10.0 # xupper
# clawdata.lower[1] = 25.0 # ylower
# clawdata.upper[1] = 30.0 # yupper
# # Number of grid cells:
# clawdata.num_cells[0] = 5 # mx
# clawdata.num_cells[1] = 5 # my
# ---------------
# Size of system:
# ---------------
# Number of equations in the system:
clawdata.num_eqn = 6
# Number of auxiliary variables in the aux array (initialized in setaux)
clawdata.num_aux = 4 + rundata.multilayer_data.num_layers
# Index of aux array corresponding to capacity function, if there is one:
clawdata.capa_index = 2
# -------------
# Initial time:
# -------------
clawdata.t0 = 0.0
# Restart from checkpoint file of a previous run?
# If restarting, t0 above should be from original run, and the
# restart_file 'fort.chkNNNNN' specified below should be in
# the OUTDIR indicated in Makefile.
clawdata.restart = False # True to restart from prior results
clawdata.restart_file = 'fort.chk00036' # File to use for restart data
# -------------
# Output times:
#--------------
# Specify at what times the results should be written to fort.q files.
# Note that the time integration stops after the final output time.
clawdata.output_style = 3
if clawdata.output_style == 1:
# Output ntimes frames at equally spaced times up to tfinal:
# Can specify num_output_times = 0 for no output
clawdata.num_output_times = 40
clawdata.tfinal = 0.1
clawdata.output_t0 = True # output at initial (or restart) time?
elif clawdata.output_style == 2:
# Specify a list or numpy array of output times:
# Include t0 if you want output at the initial time.
clawdata.output_times = [0., 0.1]
elif clawdata.output_style == 3:
# Output every step_interval timesteps over total_steps timesteps:
clawdata.output_step_interval = 1
clawdata.total_steps = 1000
clawdata.output_t0 = True # output at initial (or restart) time?
clawdata.output_format = 'ascii' # 'ascii' or 'binary'
clawdata.output_q_components = 'all' # need all
clawdata.output_aux_components = 'all' # eta=h+B is in q
clawdata.output_aux_onlyonce = False # output aux arrays each frame
# ---------------------------------------------------
# Verbosity of messages to screen during integration:
# ---------------------------------------------------
# The current t, dt, and cfl will be printed every time step
# at AMR levels <= verbosity. Set verbosity = 0 for no printing.
# (E.g. verbosity == 2 means print only on levels 1 and 2.)
clawdata.verbosity = 1
# --------------
# Time stepping:
# --------------
# if dt_variable==1: variable time steps used based on cfl_desired,
# if dt_variable==0: fixed time steps dt = dt_initial will always be used.
clawdata.dt_variable = True
# Initial time step for variable dt.
# If dt_variable==0 then dt=dt_initial for all steps:
clawdata.dt_initial = 1e-6
# Max time step to be allowed if variable dt used:
clawdata.dt_max = 1e+99
# Desired Courant number if variable dt used, and max to allow without
# retaking step with a smaller dt:
# clawdata.cfl_desired = 0.75
# clawdata.cfl_max = 1.0
clawdata.cfl_desired = 0.45
clawdata.cfl_max = 0.5
# Maximum number of time steps to allow between output times:
clawdata.steps_max = 5000
# ------------------
# Method to be used:
# ------------------
# Order of accuracy: 1 => Godunov, 2 => Lax-Wendroff plus limiters
clawdata.order = 2
# Use dimensional splitting? (not yet available for AMR)
# 0 or 'unsplit' or none' ==> Unsplit
# 1 or 'increment' ==> corner transport of waves
# 2 or 'all' ==> corner transport of 2nd order corrections too
clawdata.dimensional_split = "unsplit"
# For unsplit method, transverse_waves can be
# 0 or 'none' ==> donor cell (only normal solver used)
# 1 or 'increment' ==> corner transport of waves
# 2 or 'all' ==> corner transport of 2nd order corrections too
clawdata.transverse_waves = 2
# Number of waves in the Riemann solution:
clawdata.num_waves = 6
# List of limiters to use for each wave family:
# Required: len(limiter) == num_waves
# Some options:
# 0 or 'none' ==> no limiter (Lax-Wendroff)
# 1 or 'minmod' ==> minmod
# 2 or 'superbee' ==> superbee
# 3 or 'mc' ==> MC limiter
# 4 or 'vanleer' ==> van Leer
clawdata.limiter = ['mc', 'mc', 'mc', 'mc', 'mc', 'mc']
clawdata.use_fwaves = True # True ==> use f-wave version of algorithms
# Source terms splitting:
# src_split == 0 or 'none' ==> no source term (src routine never called)
# src_split == 1 or 'godunov' ==> Godunov (1st order) splitting used,
# src_split == 2 or 'strang' ==> Strang (2nd order) splitting used, not recommended.
clawdata.source_split = 'godunov'
# --------------------
# Boundary conditions:
# --------------------
# Number of ghost cells (usually 2)
clawdata.num_ghost = 2
# Choice of BCs at xlower and xupper:
# 0 => user specified (must modify bcN.f to use this option)
# 1 => extrapolation (non-reflecting outflow)
# 2 => periodic (must specify this at both boundaries)
# 3 => solid wall for systems where q(2) is normal velocity
clawdata.bc_lower[0] = 'extrap'
clawdata.bc_upper[0] = 'extrap'
clawdata.bc_lower[1] = 'extrap'
clawdata.bc_upper[1] = 'extrap'
# --------------
# Checkpointing:
# --------------
# Specify when checkpoint files should be created that can be
# used to restart a computation.
clawdata.checkpt_style = 0
if clawdata.checkpt_style == 0:
# Do not checkpoint at all
pass
elif clawdata.checkpt_style == 1:
# Checkpoint only at tfinal.
pass
elif clawdata.checkpt_style == 2:
# Specify a list of checkpoint times.
clawdata.checkpt_times = [0.1, 0.15]
elif clawdata.checkpt_style == 3:
# Checkpoint every checkpt_interval timesteps (on Level 1)
# and at the final time.
clawdata.checkpt_interval = 5
# ---------------
# AMR parameters: (written to amr.data)
# ---------------
amrdata = rundata.amrdata
# max number of refinement levels:
amrdata.amr_levels_max = 1
# List of refinement ratios at each level (length at least amr_level_max-1)
amrdata.refinement_ratios_x = [4, 4, 4, 4, 8]
amrdata.refinement_ratios_y = [4, 4, 4, 4, 8]
amrdata.refinement_ratios_t = [4, 4, 4, 4, 8]
# Specify type of each aux variable in amrdata.auxtype.
# This must be a list of length num_aux, each element of which is one of:
# 'center', 'capacity', 'xleft', or 'yleft' (see documentation).
# amrdata.aux_type = ['center','capacity','yleft','center','center','center']
amrdata.aux_type = [
'center', 'capacity', 'yleft', 'center', 'center', 'center'
]
# Flag for refinement based on Richardson error estimater:
amrdata.flag_richardson = False # use Richardson?
# Flag for refinement using routine flag2refine:
amrdata.flag2refine = True # use this?
# steps to take on each level L between regriddings of level L+1:
amrdata.regrid_interval = 3
# width of buffer zone around flagged points:
# (typically the same as regrid_interval so waves don't escape):
amrdata.regrid_buffer_width = 2
# clustering alg. cutoff for (# flagged pts) / (total # of cells refined)
# (closer to 1.0 => more small grids may be needed to cover flagged cells)
amrdata.clustering_cutoff = 0.7
# print info about each regridding up to this level:
amrdata.verbosity_regrid = 0
# ---------------
# Regions:
# ---------------
regions = rundata.regiondata.regions
# to specify regions of refinement append lines of the form
# [minlevel,maxlevel,t1,t2,x1,x2,y1,y2]
# allow 2 levels over portion of ocean in correct direction:
# and 3 levels up to time 7000.
if theta_island == 190:
regions.append([1, 2, 0.e0, 1.e10, -5., 5., 35., 55.])
regions.append([1, 5, 0.e0, 7000., -5., 5., 35., 55.])
if theta_island == 220:
regions.append([1, 2, 0.e0, 7000., -5., 20., 35., 55.])
regions.append([1, 5, 0.e0, 7000., -5., 20., 35., 55.])
regions.append([1, 2, 7000., 9000., 10., 20., 45., 52.])
if theta_island == 260:
regions.append([1, 5, 0.e0, 1.e10, -5., 20., 35., 45.])
regions.append([1, 5, 0.e0, 7000., -5., 20., 35., 45.])
# Force refinement near the island as the wave approaches:
# (xisland,yisland) = latlong(1600.e3, theta_island, 40., Rearth)
# x1 = xisland - 1.
# x2 = xisland + 1.
# y1 = yisland - 1.
# y2 = yisland + 1.
# regions.append([4, 5, 0.002, 1.e10, x1,x2,y1,y2])
# x1 = xisland - 0.2
# x2 = xisland + 0.2
# y1 = yisland - 0.2
# y2 = yisland + 0.2
# regions.append([4, 5, 0.002, 1.e10, x1,x2,y1,y2])
# ---------------
# Gauges:
# ---------------
gauges = rundata.gaugedata.gauges
# for gauges append lines of the form [gaugeno, x, y, t1, t2]
# gaugeno = 0
# for d in numpy.linspace(1550e3,1650e3,11):
# gaugeno = gaugeno+1
# x,y = latlong(d, theta_island, 40., Rearth)
# gauges.append([gaugeno, x, y, 0., 1e10])
# ----- For developers -----
# Toggle debugging print statements:
amrdata.dprint = False # print domain flags
amrdata.eprint = False # print err est flags
amrdata.edebug = False # even more err est flags
amrdata.gprint = False # grid bisection/clustering
amrdata.nprint = False # proper nesting output
amrdata.pprint = False # proj. of tagged points
amrdata.rprint = False # print regridding summary
amrdata.sprint = False # space/memory output
amrdata.tprint = False # time step reporting each level
amrdata.uprint = False # update/upbnd reporting
return rundata
