def read_q(path='./_output',frame=0,read_aux=False,read_grid=False,read_q=True,qi=[0,1,2],sampling=[1,1],loc_max=True):
solution = Solution()
solution.read(frame,path=path,file_format='petsc',read_aux=read_aux)
sol_compilation = {}
sol_compilation['sampling'] = sampling
if read_grid:
x,y,dimension = get_grid(solution,sampling)
dict2 = {'x':x,'y':y,'nodes':dimension[0:2,:],'num_cells':dimension[-1,:]}
sol_compilation.update(dict2)
if read_aux:
sol_compilation.update({'aux':solution.state.get_aux_global()[0:3,::sampling[0],::sampling[1]]})
if read_q:
q_all = solution.state.get_q_global()[:,::sampling[0],::sampling[1]]
for qn in qi:
q = solution.state.get_q_global()[qn,::sampling[0],::sampling[1]]
sol_compilation.update({'q'+str(qn):q})
if loc_max:
if not read_grid:
x,y,dimension = get_grid(solution,sampling)
indmax = q[:,:]==q[:,:].max()
sol_compilation.update({'indmax'+str(qn):indmax})
sol_compilation.update({'xmax':x[indmax],'ymax':y[indmax]})
sol_compilation.update({'t':solution.t})
return sol_compilation if not read_q else q_all,sol_compilation
def getAux(self,dirs,frame=None,qn=None):
if frame is None:
frame = self.frame
if qn is None:
qn = self.qn
solution = Solution()
solution.read(frame,path=dirs,file_format=self.file_format,read_aux=True)
auxclaw = solution.state.get_aux_global()[qn]
xclaw = solution.state.grid.x.centers
delta = solution.state.grid.delta
return auxclaw,xclaw,delta
def verify_sedov(controller):
import os
from clawpack.pyclaw.util import check_diff
from clawpack.pyclaw import Solution
thisdir = os.path.dirname(__file__)
verify_dir = os.path.join(thisdir,'./Sedov_regression')
# Expected solution
sol_expected = Solution()
sol_expected.read(1,path=verify_dir,file_format='hdf',read_aux=False)
assert sol_expected.t == 0.1
expected_q = sol_expected.state.q
# Test solution
sol_test = Solution()
sol_test.read(1,path=controller.outdir,
file_format=controller.output_format,
read_aux=False,
options=controller.output_options)
test_q = sol_test.state.get_q_global()
if test_q is not None:
q_err = check_diff(expected_q, test_q, reltol=1e-6)
if q_err is not None:
return q_err
else:
return
def read_fortq(frame):
"""
Import fort.q files to get x,y,z data
"""
fortq = Solution(frame, file_format='ascii')
patch_dict = {}
for stateno, state in enumerate(fortq.states):
patch = state.patch
level = patch.level
Xc, Yc = state.grid.c_centers
h = state.q[0, :, :]
eta = state.q[3, :, :]
drytol_default = 0.001
water = np.copy(eta)
idx = np.where((h <= drytol_default) & (h >= -drytol_default))
water[idx] = np.nan
# idx2 = np.where(eta==0)
# water[idx2] = np.nan
# Save variables to dictionary
long = Xc[:, 0]
lat = Yc[0]
patch_dict[stateno] = {
"lat": lat,
'long': long,
'eta': eta,
'amr_level': level,
'Xc': Xc,
'Yc': Yc,
'water': water
}
return patch_dict, water, h, Xc, Yc, eta
def getAux(self, dirs, frame=None, qn=None):
if frame is None:
frame = self.frame
if qn is None:
qn = self.qn
solution = Solution()
solution.read(frame,
path=dirs,
file_format=self.file_format,
read_aux=True)
auxclaw = solution.state.get_aux_global()[qn]
xclaw = solution.state.grid.x.centers
delta = solution.state.grid.delta
return auxclaw, xclaw, delta
def read_q(path='./_output',
frame=0,
read_aux=False,
read_grid=False,
read_q=True,
qi=[0, 1, 2],
sampling=[1, 1],
loc_max=True):
solution = Solution()
solution.read(frame, path=path, file_format='petsc', read_aux=read_aux)
sol_compilation = {}
sol_compilation['sampling'] = sampling
if read_grid:
x, y, dimension = get_grid(solution, sampling)
dict2 = {
'x': x,
'y': y,
'nodes': dimension[0:2, :],
'num_cells': dimension[-1, :]
}
sol_compilation.update(dict2)
if read_aux:
sol_compilation.update({
'aux':
solution.state.get_aux_global()[0:3, ::sampling[0], ::sampling[1]]
})
if read_q:
q_all = solution.state.get_q_global()[:, ::sampling[0], ::sampling[1]]
for qn in qi:
q = solution.state.get_q_global()[qn, ::sampling[0], ::sampling[1]]
sol_compilation.update({'q' + str(qn): q})
if loc_max:
if not read_grid:
x, y, dimension = get_grid(solution, sampling)
indmax = q[:, :] == q[:, :].max()
sol_compilation.update({'indmax' + str(qn): indmax})
sol_compilation.update({'xmax': x[indmax], 'ymax': y[indmax]})
sol_compilation.update({'t': solution.t})
return sol_compilation if not read_q else q_all, sol_compilation
def getClaw(self,dirs,frame=None,qn=None,homogeneous=None):
if frame is None:
frame = self.frame
if qn is None:
qn = self.qn
if homogeneous is None:
homogeneous = self.homogeneous
solution = Solution()
solution.read(frame,path=dirs,file_format=self.file_format,read_aux=self.homogeneous)
qclaw = solution.state.get_q_global()[qn]
xclaw = solution.state.grid.x.centers
delta = solution.state.grid.delta
if homogeneous:
print 'dividing by aux'
qclaw = qclaw/(solution.state.get_aux_global()[qn])
return qclaw,xclaw,delta
def verify_sedov(controller):
import os
from clawpack.pyclaw.util import check_diff
from clawpack.pyclaw import Solution
thisdir = os.path.dirname(__file__)
verify_dir = os.path.join(thisdir,'./Sedov_regression')
# Expected solution
sol_expected = Solution()
sol_expected.read(1,path=verify_dir,file_format='hdf',read_aux=False)
expected_q = sol_expected.state.q
# Test solution
sol_test = Solution()
sol_test.read(1,path=controller.outdir,
file_format=controller.output_format,
read_aux=False,
options=controller.output_options)
test_q = sol_test.state.get_q_global()
if test_q is not None:
q_err = check_diff(expected_q, test_q, reltol=1e-6)
if q_err is not None:
return q_err
else:
return
def getClaw(self, dirs, frame=None, qn=None, homogeneous=None):
if frame is None:
frame = self.frame
if qn is None:
qn = self.qn
if homogeneous is None:
homogeneous = self.homogeneous
solution = Solution()
solution.read(frame,
path=dirs,
file_format=self.file_format,
read_aux=self.homogeneous)
qclaw = solution.state.get_q_global()[qn]
xclaw = solution.state.grid.x.centers
delta = solution.state.grid.delta
if homogeneous:
print 'dividing by aux'
qclaw = qclaw / (solution.state.get_aux_global()[qn])
return qclaw, xclaw, delta
def plot_transect(ylat, frameno, fg, xcutoff, trname, plotdir):
figure(20, figsize=(10, 3))
clf()
xout = linspace(xlimits[0], xlimits[1], 1000)
yout = ylat * ones(xout.shape)
framesoln = Solution(frameno, path=outdir, file_format=format)
eta = gridtools.grid_output_2d(framesoln, 3, xout, yout)
topo = gridtools.grid_output_2d(framesoln, B, xout, yout)
fill_between(xout, eta, topo, color=[.5, .5, 1])
fill_between(xout, topo, -10000, color=[.5, 1, .5])
plot(xout, eta, 'b')
plot(xout, topo, 'g')
grid(True)
eta = fg.B + fg.h
eta_max = where(fg.X < xcutoff, eta, nan)
plot(fg.X, eta_max, 'r', label='wave height')
xlim(xlimits)
ylim(zlimits)
timestr = timeformat(framesoln.t)
title('Transect of wave at latitude %.1f at time %s' % (ylat, timestr),
fontsize=15)
ticklabel_format(format='plain', useOffset=False)
xticks([-127, -126, -125, -124], fontsize=15)
yticks(linspace(-0.2, 0.6, 5), fontsize=15)
#xlabel('Longitude')
ylabel('meters', fontsize=15)
hl = 3000.
A0 = 0.1328
z = where(topo < -10, -topo, nan)
AG = A0 * (hl / z)**0.25
plot(xout, AG, 'g--', label="Green's Law")
ctx = A0 * 2 * sqrt(hl) / (sqrt(hl) + sqrt(z))
plot(xout, ctx, 'b--', label='Transmission')
legend(loc='upper left', fontsize=15, framealpha=1)
fname = '%s_%s' % (trname, str(frameno).zfill(4))
save_figure(fname)
def get_max_boundary_fluxes(model_output_dir,
max_refinement_depth_to_check=None,
frames_to_check=1):
"""A common cause of instability is a persistant normal flux at the boundary.
This code checks the last frame(s) of a model output and returns the maximum
magnitude normal fluxes and currents at each boundary, as well as the maximum
magnitude fluxes and currents observed within the entire domain.
:Input:
- *model_output_dir* (str) Path to the output directory for a given model
- *max_refinement_depth_to_check* (int or None, optional) How many refinement levels to
loop through to find max values. Runs quicker when just checking level 1, but
you may find higher max values at higher refinement levels. None (default)
means check all levels
- *frames_to_check* (int) How many of the last output frames to check for max. Default
is just one.
"""
# find which frame is last
output_files = glob(join(model_output_dir, 'fort.q*'))
frames = [int(i.split('/')[-1][-4:]) for i in output_files]
last_frame = max(frames)
# get domain and file format
with open(join(model_output_dir, 'claw.data'), 'r') as f:
for l in f:
if '=: lower' in l:
xl, yl = [float(i) for i in l.strip().split()[:2]]
elif '=: upper' in l:
xu, yu = [float(i) for i in l.strip().split()[:2]]
elif '=: output_format' in l:
of = int(l.strip().split()[0]) - 1
file_format = ['ascii', 'netcdf', 'binary'][of]
maxhxl = -np.inf
maxhyl = -np.inf
maxcurrxl = -np.inf
maxcurryl = -np.inf
maxhxu = -np.inf
maxhyu = -np.inf
maxcurrxu = -np.inf
maxcurryu = -np.inf
maxhx_overall = -np.inf
maxhy_overall = -np.inf
maxcurrx_overall = -np.inf
maxcurry_overall = -np.inf
for f in range(last_frame + 1 - frames_to_check, last_frame + 1):
soln = Solution()
soln.read(f,
path=model_output_dir,
file_format=file_format,
read_aux=False)
for s in soln.states:
# only looking at lowest AMR levels
if max_refinement_depth_to_check is not None:
if s.patch.level > max_refinement_depth_to_check:
continue
# get rounding error tolerance
delta = s.grid.dimensions[0].delta
edge_tol = delta * .001
x = s.grid.c_centers[0]
xedges = s.grid.c_nodes[0]
y = s.grid.c_centers[1]
yedges = s.grid.c_nodes[1]
eta = s.q[3, :, :]
h = s.q[0, :, :]
hx = s.q[1, :, :]
curr_x = hx / h
hy = s.q[2, :, :]
curr_y = hy / h
topo = eta - s.q[0, :, :]
maxhx_overall = np.nanmax([np.abs(hx).max(), maxhx_overall])
maxhy_overall = np.nanmax([np.abs(hy).max(), maxhy_overall])
maxcurrx_overall = np.nanmax(
[np.nanmax(np.abs(curr_x)), maxcurrx_overall])
maxcurry_overall = np.nanmax(
[np.nanmax(np.abs(curr_y)), maxcurry_overall])
if abs(xedges[0, 0] - xl) < edge_tol:
maxhxl = np.nanmax([maxhxl, np.nanmax(np.abs(hx[0, :]))])
maxcurrxl = np.nanmax(
[maxcurrxl, np.nanmax(np.abs(curr_x[0, :]))])
if abs(xedges[-1, 0] - xu) < edge_tol:
maxhxu = np.nanmax([maxhxu, np.nanmax(np.abs(hx[-1, :]))])
maxcurrxu = np.nanmax(
[maxcurrxu, np.nanmax(np.abs(curr_x[-1, :]))])
if abs(yedges[0, 0] - yl) < edge_tol:
maxhyl = np.nanmax([maxhyl, np.nanmax(np.abs(hy[:, 0]))])
maxcurryl = np.nanmax(
[maxcurryl, np.nanmax(np.abs(curr_y[:, 0]))])
if abs(yedges[0, -1] - yu) < edge_tol:
maxhyu = np.nanmax([maxhyu, np.nanmax(np.abs(hy[:, -1]))])
maxcurryu = np.nanmax(
[maxcurryu, np.nanmax(np.abs(curr_y[:, -1]))])
return ({
'max_normal_fluxes': {
'W': maxhxl,
'E': maxhxu,
'N': maxhyu,
'S': maxhyl
},
'max_normal_currents': {
'W': maxcurrxl,
'E': maxcurrxu,
'N': maxcurryu,
'S': maxcurryl
},
'domain_maxs': {
'hu': maxhx_overall,
'hv': maxhy_overall,
'u': maxcurrx_overall,
'v': maxcurry_overall
}
})
def quality_check(
model_output_dir,
regions_to_check=[
[-81, 22, -40, 55], # atlantic
[-100, 15, -82, 32], # gulf
[-88.5, 13.25, -70, 19.75]
], # carribean
frames_to_check=4,
mean_tol_abs=.01,
min_depth=300):
"""Run a simple check to flag runs that were potentially numerically unstable.
This function looks through the final *frames_to_check* frames of a model output
and checks all cells in AMR level 1 that are below *min_depth* and
fall within each region in the *regions_to_check* list (which are intended
to encompass individual basins). If the absolute value of the mean surface height
for these cells, which should not really have much surge, is above/mean_tol_abs,
it raises an error.
:Input:
- *model_output_dir* (str) Path to the output directory for a given model
- *regions_to_check* (list of lists of floats) A list of 4-element lists
which define the (left, bottom, right, top) of regions to check within.
- *frames_to_check* (int) The number of final frames of the model output to check
- *mean_tol_abs* (float) Model is flagged if the absolute value of the mean surface
height within any region in *regions_to_check* is above this value (meters).
- *min_depth* (float) Only cells that are below *min_depth* (meters) are checked, in
order to avoid including cells that potentially should have large surge values.
:Raises:
- InstabilityError if the model is flagged as potentially unstable in one of the regions.
"""
# find which frame is last
output_files = glob(join(model_output_dir, 'fort.b*'))
last_frame = int(output_files[-1].split('/')[-1][-4:])
# get sl_init
with open(join(model_output_dir, 'geoclaw.data'), 'r') as f:
for l in f:
if '=: sea_level' in l:
sl_init = float(l.strip().split()[0])
# bring in solution
soln = Solution()
for frame in range(last_frame - frames_to_check + 1, last_frame + 1):
soln.read(frame,
path=model_output_dir,
file_format='binary',
read_aux=False)
for r in regions_to_check:
all_vals = np.array([])
for s in soln.states:
# only looking at lowest AMR level
if s.patch.level > 1:
continue
x = s.grid.c_centers[0]
y = s.grid.c_centers[1]
eta = s.q[3, :, :]
topo = eta - s.q[0, :, :]
# only count
eta = np.where(topo < (-min_depth), eta, np.nan)
in_reg = eta[np.ix_((x[:, 0] >= r[0]) & (x[:, 0] <= r[2]),
(y[0, :] >= r[1]) & (y[0, :] <= r[3]))]
all_vals = np.concatenate([all_vals, in_reg.flatten()])
# adjust for sl_init
all_vals = all_vals - sl_init
if all_vals.shape[0] > 0:
if abs(np.nanmean(all_vals)) > mean_tol_abs:
raise InstabilityError(
"Model possibly unstable due to large magnitude deep "
"ocean surge at end of run ({:.1f} cm in region {})".
format(np.nanmean(all_vals) * 100, r))
def verify_acoustics_io(controller):
""" Verifies I/O on 2d variable-coefficient acoustics application"""
import os
from clawpack.pyclaw.util import check_diff
from clawpack.pyclaw import Solution
thisdir = os.path.dirname(__file__)
verify_dir = os.path.join(thisdir, './io_test_verification')
# Expected solution
sol_0_expected = Solution()
sol_0_expected.read(0,
path=verify_dir,
file_format='ascii',
file_prefix=None,
read_aux=True)
expected_aux = sol_0_expected.state.aux
sol_20_expected = Solution()
sol_20_expected.read(20,
path=verify_dir,
file_format='ascii',
file_prefix=None,
read_aux=False)
expected_q = sol_20_expected.state.q
# Test solution
sol_0_test = Solution()
sol_0_test.read(0,
path=controller.outdir,
file_format=controller.output_format,
file_prefix=None,
read_aux=True,
options=controller.output_options)
test_aux = sol_0_test.state.get_aux_global()
sol_20_test = Solution()
sol_20_test.read(20,
path=controller.outdir,
file_format=controller.output_format,
file_prefix=None,
read_aux=False,
options=controller.output_options)
test_q = sol_20_test.state.get_q_global()
if test_q is not None:
q_err = check_diff(expected_q, test_q, reltol=1e-6)
if q_err is not None:
return q_err
else:
return
if test_aux is not None:
aux_err = check_diff(expected_aux, test_aux, reltol=1e-6)
if aux_err is not None:
return aux_err
else:
return
import os
from numpy import ma
from clawpack.pyclaw import Solution
import subprocess
import numpy as np
#
file_path = os.path.join('c:/', 'fortranprograms', 'plots', '_output') #
# '''''/Users/jeffriesc/clawpack-5.4.1/geoclaw/examples/tsunami/TestingLinearity/SF_8_1m/_output'
solution = Solution()
drytol_default = .001
x = Solution(1, file_format='ascii')
for stateno, state in enumerate(x.states):
# state = x.states[stateno]
patch = state.patch
level = patch.level
print(stateno, patch.level)
Xc, Yc = state.grid.c_centers
xc = Xc[:, 0]
yc = Yc[0, :]
h = state.q[0, :, :]
eta = state.q[3, :, :]
if (np.isnan(eta).any()) == True:
print(np.isnan(eta).any())
topo = eta - h
# water = np.ma.masked_where(h <= drytol_default, eta)
water = eta
ind = np.where(h <= drytol_default)
def assemble_q(path='./_output',
frame_plot_range=[0],
poynting=True,
read_aux=False,
qi=[0, 1, 2],
update_aux=False,
sampling=[1, 1],
frame_split=False,
split_q=False,
figspath='./',
binpath='./',
cut=True):
# create instance of solution object
num_frames = len(frame_plot_range)
solution = Solution()
Q_map_temp = [[], []]
d_map_temp = [[], []]
sol = {}
# print frame_plot_range
sampled = np.zeros([num_frames, 9])
plot_aux = True
# load the frames and assemble values
for f, frame in enumerate(frame_plot_range):
# print frame
ql = [[], []]
dl = [[], []]
if f == 0:
q, grid = read_q(path=path,
frame=frame,
read_q=False,
read_grid=True,
sampling=sampling)
sol['grid'] = grid
if read_aux:
if f == 0 or update_aux:
q, aux = read_q(path=path,
frame=frame,
read_q=False,
read_aux=True,
qi=[1, 2],
sampling=sampling)
sol['aux' + str(f)] = aux
if plot_aux:
plt.close('all')
plt.figure()
fig, axes = plt.subplots(nrows=1)
axes.pcolormesh(grid['x'],
grid['y'],
aux['aux'][1, :, :],
cmap='jet')
axes.set_xlabel('$x$')
axes.set_ylabel('$y$')
aux_name = 'aux' + str(frame).zfill(4)
plt.savefig(os.path.join(figspath, aux_name + '.png'),
format='png',
dpi=320,
bbox_inches='tight')
plt.close()
plot_aux = update_aux
q, solution = read_q(path=path, frame=frame, qi=qi, sampling=sampling)
for k in xrange(1, 3, 1):
dl[k - 1], ql[k - 1] = extract_cut_line(
q[k],
grid['x'],
grid['y'],
plot=cut,
num_points=1000,
outdir=os.path.join(figspath, 'cut_x'),
outname='cut_q' + str(k - 1) + '_' + str(frame).zfill(4),
format='png')
Q_map_temp[k - 1] = np.append(Q_map_temp[k - 1], ql[k - 1])
d_map_temp[k - 1] = np.append(d_map_temp[k - 1], dl[k - 1])
sol['q' + str(f)] = q
sampled[f, 0] = solution['t']
sampled[f, 1] = solution['xmax'].max()
sampled[f, 2] = solution['ymax'].max()
sampled[f, 3] = solution['q1'].max()
sampled[f, 4] = solution['q2'].max()
if poynting:
p1 = q.shape[1] / 100
p2 = q.shape[2] / 50
Sx, Sy = Poynting(q[:, ::p1, ::p2],
plot=True,
streamline=True,
x=grid['x'][::p1, ::p2],
y=grid['y'][::p1, ::p2],
outdir=os.path.join(figspath, 'Poyinting'),
suffix=str(frame).zfill(4),
format='png',
cut_long=True)
if split_q:
for qn in range(0, len(q)):
q_temp = q[qn, :, :, np.newaxis]
aux_temp = aux['aux'][qn, :, :, np.newaxis]
q_temp.tofile(
os.path.join(binpath,
'3D_q' + str(qn) + '.' + str(frame).zfill(4)))
aux_temp.tofile(
os.path.join(
binpath,
'3D_aux' + str(qn) + '.' + str(frame).zfill(4)))
if frame_split:
sol['Sx' + str(f)] = Sx
sol['Sy' + str(f)] = Sy
sol['sampled' + str(f)] = sampled
savemat(os.path.join(figspath, 'sol' + str(frame).zfill(4)), sol)
Q = np.reshape(Q_map_temp,
(2, num_frames, np.shape(Q_map_temp)[1] / num_frames))
d = np.reshape(d_map_temp,
(2, num_frames, np.shape(d_map_temp)[1] / num_frames))
sol['sampled'] = sampled
sol['num_frames'] = num_frames
return Q, d, sol
def assemble_q(path='./_output',
frame_plot_range=[0],
vecmagnitude=True,
poynting=True,
poly_verts=True):
# create instance of solution object
num_frames = len(frame_plot_range)
solution = Solution()
Q_map_temp = []
aux_map_temp = []
derived_quantities = {}
if vecmagnitude: I_map_temp = []
if poynting: S_map_temp = []
if poly_verts: verts = []
sampled = np.zeros([len(frame_plot_range), 12])
# load the frames and assemble values
for f, frame in enumerate(frame_plot_range):
solution = Solution()
solution.read(frame, path=path, file_format='petsc', read_aux=True)
x = solution.state.grid.x.centers
q = solution.state.get_q_global()
aux = solution.state.get_aux_global()[0:2, :]
for n, qn in enumerate(q):
Q_map_temp = np.append(Q_map_temp, qn)
for n, auxn in enumerate(aux):
aux_map_temp = np.append(aux_map_temp, auxn)
sampled[f, 0] = solution.t
if len(x[q[0] == q[0].max()]) == 1:
it = np.sqrt(q[0]**2 + q[1]**2)
# print x[np.where(it==it.max())]
sampled[f, 1] = x[np.where(it == it.max())]
if len(x[q[0] == q[0].max()]) >= 2:
sampled[f, 1] = x[q[0] == q[0].max()][-1]
print(len(x[q[0] == q[0].max()]))
sampled[f, 3] = q[0].max()
sampled[f, 4] = q[1].max()
if poynting:
S = q[0] * q[1]
S_map_temp = np.append(S_map_temp, S, axis=0)
if vecmagnitude:
I = np.sqrt(q[0]**2 + q[1]**2)
sampled[f, 6] = I.max()
I_map_temp = np.append(I_map_temp, I, axis=0)
if poly_verts:
verts.append(list(zip(x, I)))
Q = Q_map_temp.reshape(
(num_frames, len(q), Q_map_temp.size / (len(q) * num_frames)))
A = aux_map_temp.reshape(
(num_frames, len(aux), aux_map_temp.size / (len(aux) * num_frames)))
if vecmagnitude:
I = (I_map_temp.reshape((num_frames, I_map_temp.size / num_frames)))
derived_quantities['I'] = I
if poynting:
S = (S_map_temp.reshape((num_frames, S_map_temp.size / num_frames)))
derived_quantities['S'] = S
if poly_verts:
derived_quantities['vertices'] = verts
derived_quantities['x'] = x
derived_quantities['t'] = sampled[:, 0]
derived_quantities['sampled'] = sampled
return Q, A, num_frames, derived_quantities
def assemble_q(path='./_output',frame_plot_range=[0],vecmagnitude=True,poynting=True,poly_verts=True):
# create instance of solution object
num_frames = len(frame_plot_range)
solution = Solution()
Q_map_temp = []
aux_map_temp = []
derived_quantities = {}
if vecmagnitude: I_map_temp = []
if poynting: S_map_temp = []
if poly_verts: verts = []
sampled = np.zeros([len(frame_plot_range),12])
# load the frames and assemble values
for f,frame in enumerate(frame_plot_range):
solution = Solution()
solution.read(frame,path=path,file_format='petsc',read_aux=True)
x = solution.state.grid.x.centers;
q = solution.state.get_q_global()
aux = solution.state.get_aux_global()[0:2,:]
for n,qn in enumerate(q):
Q_map_temp = np.append(Q_map_temp,qn)
for n,auxn in enumerate(aux):
aux_map_temp = np.append(aux_map_temp,auxn)
sampled[f,0] = solution.t
if len(x[q[0]==q[0].max()])==1:
it = np.sqrt(q[0]**2 + q[1]**2)
# print x[np.where(it==it.max())]
sampled[f,1] = x[np.where(it==it.max())]
if len(x[q[0]==q[0].max()])>=2:
sampled[f,1] = x[q[0]==q[0].max()][-1]
print len(x[q[0]==q[0].max()])
sampled[f,3] = q[0].max()
sampled[f,4] = q[1].max()
if poynting:
S = q[0]*q[1]
S_map_temp = np.append(S_map_temp,S,axis=0)
if vecmagnitude:
I = np.sqrt(q[0]**2 + q[1]**2)
sampled[f,6] = I.max()
I_map_temp = np.append(I_map_temp,I,axis=0)
if poly_verts:
verts.append(list(zip(x,I)))
Q = Q_map_temp.reshape((num_frames,len(q),Q_map_temp.size/(len(q)*num_frames)))
A = aux_map_temp.reshape((num_frames,len(aux),aux_map_temp.size/(len(aux)*num_frames)))
if vecmagnitude:
I = (I_map_temp.reshape((num_frames,I_map_temp.size/num_frames)))
derived_quantities['I'] = I
if poynting:
S = (S_map_temp.reshape((num_frames,S_map_temp.size/num_frames)))
derived_quantities['S'] = S
if poly_verts:
derived_quantities['vertices'] = verts
derived_quantities['x'] = x
derived_quantities['t'] = sampled[:,0]
derived_quantities['sampled'] = sampled
return Q,A,num_frames,derived_quantities
def load_frame(frame_number):
from clawpack.pyclaw import Solution
return Solution(frame_number)
def solution(self):
return Solution()
def verify_acoustics_io(controller):
""" Verifies I/O on 2d variable-coefficient acoustics application"""
import os
from clawpack.pyclaw.util import check_diff
from clawpack.pyclaw import Solution
thisdir = os.path.dirname(__file__)
verify_dir = os.path.join(thisdir,'./io_test_verification')
# Expected solution
sol_0_expected = Solution()
sol_0_expected.read(0,path=verify_dir,file_format='ascii',
file_prefix=None,read_aux=True)
expected_aux = sol_0_expected.state.aux
sol_20_expected = Solution()
sol_20_expected.read(20,path=verify_dir,file_format='ascii',
file_prefix=None,read_aux=False)
expected_q = sol_20_expected.state.q
# Test solution
sol_0_test = Solution()
sol_0_test.read(0,path=controller.outdir,
file_format=controller.output_format,
file_prefix=None,read_aux=True,
options=controller.output_options)
test_aux = sol_0_test.state.get_aux_global()
sol_20_test = Solution()
sol_20_test.read(20,path=controller.outdir,
file_format=controller.output_format,
file_prefix=None,read_aux=False,
options=controller.output_options)
test_q = sol_20_test.state.get_q_global()
if test_q is not None:
q_err = check_diff(expected_q, test_q, reltol=1e-6)
if q_err is not None:
return q_err
else:
return
if test_aux is not None:
aux_err = check_diff(expected_aux, test_aux, reltol=1e-6)
if aux_err is not None:
return aux_err
else:
return
def quality_check(model_output_dir,
regions_to_check = [[-81,22,-40,55], # atlantic
[-100,15,-82,32], # gulf
[-88.5,13.25,-70,19.75]], # carribean
frames_to_check = 4,
mean_tol_abs = .01,
min_depth = 300):
"""Run a simple check to flag runs that were potentially numerically unstable.
This function looks through the final *frames_to_check* frames of a model output
and checks all cells in AMR level 1 that are below *min_depth* and
fall within each region in the *regions_to_check* list (which are intended
to encompass individual basins). If the absolute value of the mean surface height
for these cells, which should not really have much surge, is above/mean_tol_abs,
it raises an error.
:Input:
- *model_output_dir* (str) Path to the output directory for a given model
- *regions_to_check* (list of lists of floats) A list of 4-element lists
which define the (left, bottom, right, top) of regions to check within.
- *frames_to_check* (int) The number of final frames of the model output to check
- *mean_tol_abs* (float) Model is flagged if the absolute value of the mean surface
height within any region in *regions_to_check* is above this value (meters).
- *min_depth* (float) Only cells that are below *min_depth* (meters) are checked, in
order to avoid including cells that potentially should have large surge values.
:Raises:
- InstabilityError if the model is flagged as potentially unstable in one of the regions.
"""
# find which frame is last
output_files = glob(join(model_output_dir,'fort.b*'))
last_frame = int(output_files[-1].split('/')[-1][-4:])
# get sl_init
with open(join(model_output_dir,'geoclaw.data'),'r') as f:
for l in f:
if '=: sea_level' in l:
sl_init = float(l.strip().split()[0])
# bring in solution
soln = Solution()
for frame in range(last_frame-frames_to_check+1, last_frame+1):
soln.read(frame, path = model_output_dir, file_format='binary', read_aux=False)
for r in regions_to_check:
all_vals = np.array([])
for s in soln.states:
# only looking at lowest AMR level
if s.patch.level >1:
continue
x = s.grid.c_centers[0]
y = s.grid.c_centers[1]
eta = s.q[3,:,:]
topo = eta - s.q[0,:,:]
# only count
eta = np.where(topo<(-min_depth),eta,np.nan)
in_reg = eta[np.ix_((x[:,0]>=r[0]) & (x[:,0]<=r[2]),
(y[0,:]>=r[1]) & (y[0,:]<=r[3]))]
all_vals = np.concatenate([all_vals,in_reg.flatten()])
# adjust for sl_init
all_vals = all_vals - sl_init
if all_vals.shape[0]>0:
if abs(np.nanmean(all_vals)) > mean_tol_abs:
raise InstabilityError("Model possibly unstable due to large magnitude deep "
"ocean surge at end of run ({:.1f} cm in region {})".format(
np.nanmean(all_vals)*100, r))
