def plotclaw(outdir='.',
plotdir='_plots',
setplot='setplot.py',
format='ascii',
msgfile=''):
"""
Create html and/or latex versions of plots.
INPUT:
setplot is a module containing a function setplot that will be called
to set various plotting parameters.
format specifies the format of the files output from Clawpack
"""
from clawpack.visclaw.data import ClawPlotData
from clawpack.visclaw import plotpages
plotdata = ClawPlotData()
plotdata.outdir = outdir
plotdata.plotdir = plotdir
plotdata.setplot = setplot
plotdata.format = format
plotdata.msgfile = msgfile
plotpages.plotclaw_driver(plotdata, verbose=False, format=format)
def read_data(outdir="_output", adjoint=False):
from numpy import loadtxt
fname = outdir + '/fort.H'
B = loadtxt(fname)
print "Loaded B"
pd = ClawPlotData()
pd.outdir = outdir
times = []
qxt = []
for frameno in range(5001):
try:
frame = pd.getframe(frameno)
except:
break
q = frame.state.q
t = frame.state.t
q[0, :] = B + q[0, :]
qxt.append(q)
times.append(t)
x = frame.state.patch.x.centers
x = x
X, T = np.meshgrid(x, times)
qxt = np.array(qxt)
if adjoint:
qxt = np.flipud(qxt) # reverse t for adjoint
return X, T, qxt
def read_data(outdir="_output", adjoint=False):
from numpy import loadtxt
fname = outdir + '/fort.H'
B = loadtxt(fname)
print "Loaded B"
pd = ClawPlotData()
pd.outdir = outdir
times = []
qxt = []
for frameno in range(5001):
try:
frame = pd.getframe(frameno)
except:
break
q = frame.state.q
t = frame.state.t
q[0,:] = B + q[0,:]
qxt.append(q)
times.append(t)
x = frame.state.patch.x.centers
x = x
X,T = np.meshgrid(x,times)
qxt = np.array(qxt)
if adjoint:
qxt = np.flipud(qxt) # reverse t for adjoint
return X,T,qxt
def make_getgauge(outdir='_output'):
"""
Create function getgauge that will grab one set of gauge data
from the fort.gauge file in directory specified by outdir.
"""
from clawpack.visclaw.data import ClawPlotData
plotdata = ClawPlotData()
plotdata.outdir = outdir
getgauge = plotdata.getgauge
return getgauge
def make_getgauge(outdir='_output'):
"""
Create function getgauge that will grab one set of gauge data
from the fort.gauge file in directory specified by outdir.
"""
from clawpack.visclaw.data import ClawPlotData
plotdata = ClawPlotData()
plotdata.outdir = outdir
getgauge = plotdata.getgauge
return getgauge
def read_gauges(runDir, nGauges, times):
plotdata = ClawPlotData()
plotdata.outdir = runDir + '/_output' # set to the proper output directory
gauge_data = []
for ii in range(0, nGauges):
g = plotdata.getgauge(ii)
time_indices = np.array([any(np.isclose(t, times)) for t in g.t])
gauge_data.append(g.q[0, time_indices])
gauge_data = np.array(gauge_data)
return gauge_data
def process_gauge(gaugeNo, output):
plotdata = ClawPlotData()
plotdata.outdir = '_output' # set to the proper output directory
g = plotdata.getgauge(gaugeNo)
# g.t is the array of times
# g.q is the array of values recorded at the gauges (g.q[m,n] is the m`th variable at time `t[n])
t = g.t
h = g.q[0,:]
u = np.where(h>0.001,g.q[1,:]/h,0.)
v = np.where(h>0.001,g.q[2,:]/h,0.)
h = h - h[:10].sum()/10.
hu2 = h*u**2
hv2 = h*v**2
header = "Time (s), water depth (m), u-velocity (m/s), v-velocity (m/s), hu^2 (m^3/s^2), hv^2 (m^3/s^2)"
if 'data_at_gauges_txt' not in os.listdir('./'):
os.mkdir('./data_at_gauges_txt')
result = np.vstack((t, h, u, v, hu2, hv2))
result = result.transpose()
np.savetxt('./data_at_gauges_txt/'+output, result, delimiter=',', header=header)
def plotclaw(outdir='.', plotdir='_plots', setplot = 'setplot.py',format='ascii'):
"""
Create html and/or latex versions of plots.
INPUT:
setplot is a module containing a function setplot that will be called
to set various plotting parameters.
format specifies the format of the files output from Clawpack
"""
from clawpack.visclaw.data import ClawPlotData
from clawpack.visclaw import plotpages
plotdata = ClawPlotData()
plotdata.outdir = outdir
plotdata.plotdir = plotdir
plotdata.setplot = setplot
plotdata.format = format
plotpages.plotclaw_driver(plotdata, verbose=False, format=format)
def read_data(outdir="_output", adjoint=False):
pd = ClawPlotData()
pd.outdir = outdir
times = []
qxt = []
for frameno in range(5001):
try:
frame = pd.getframe(frameno)
except:
break
q = frame.state.q
t = frame.state.t
qxt.append(q)
times.append(t)
x = frame.state.patch.x.centers
x = x
X,T = np.meshgrid(x,times)
qxt = np.array(qxt)
if adjoint:
qxt = np.flipud(qxt) # reverse t for adjoint
return X,T,qxt
def make_output_for_dakota():
from clawpack.visclaw.data import ClawPlotData
plotdata = ClawPlotData()
plotdata.outdir = os.path.join(os.getcwd() , '_output') # set to the proper output directory
gaugeno = 34 # gauge number to examine
g = plotdata.getgauge(gaugeno)
gauge_max = g.q[3,:].max()
print "Maximum elevation observed at gauge %s: %6.2f meters" \
% (gaugeno, gauge_max)
fname = 'results.out'
f = open(fname,'w')
f.write("%6.2f\n" % -gauge_max)
f.close()
print "Created ",fname
if 1:
figure()
plot(g.t, g.q[3,:])
title("Gauge %s" % gaugeno)
ylabel('Elevation (meters)')
xlabel('time (seconds)')
fname = 'gauge.png'
savefig(fname)
print 'Created ',fname
import os
close('all')
def savetxt_verbose(fname,d):
print "Created ",fname
savetxt(fname,d,fmt='%12.3e')
def savefig_verbose(fname):
print "Created ",fname
savefig(fname)
plotdata = ClawPlotData()
rundata = setrun()
plotdata.outdir = os.getenv('PWD') # set to the current output directory
ngauges = 516
trans_halfwidth = rundata.probdata.trans_halfwidth
weight_method = 1 # 0 for constant, 1 for gaussian, 2 for super-gaussian
g = plotdata.getgauge(0)
# Interpolate to equally spaced time points,
tend = g.t[-5]
tstart = g.t[0]
dt = 25e-9 # should evenly divide 500e-9 (500 ns)
tt = arange(tstart, tend, dt)
tt_length = len(tt)
p_average = zeros((tt_length,))
u_average = zeros((tt_length,))
figure(1,figsize=(12,6))
def plotclaw(outdir='.', plotdir='_plots', setplot = 'setplot.py',
format='ascii', msgfile='', frames=None, verbose=False):
"""
Create html and/or latex versions of plots.
INPUT:
setplot is a module containing a function setplot that will be called
to set various plotting parameters.
format specifies the format of the files output from Clawpack
"""
from clawpack.visclaw.data import ClawPlotData
from clawpack.visclaw import plotpages
plotdata = ClawPlotData()
plotdata.outdir = outdir
plotdata.plotdir = plotdir
plotdata.setplot = setplot
plotdata.format = format
plotdata.msgfile = msgfile
frametools.call_setplot(plotdata.setplot, plotdata)
if plotdata.num_procs is None:
plotdata.num_procs = int(os.environ.get("OMP_NUM_THREADS", 1))
# Make sure plotdata.parallel is False in some cases:
if plotdata.parallel:
assert type(setplot) in [str, bool, type(None)], \
"*** Parallel plotting is not supported when ClawPlotData " \
+ "attribute setplot is a function."
if plotdata.parallel and (plotdata.num_procs > 1):
# If this is the original call then we need to split up the work and
# call this function again
# First set up plotdir:
plotdata._parallel_todo = 'initialize'
plotpages.plotclaw_driver(plotdata, verbose=False, format=format)
if frames is None:
if plotdata.num_procs is None:
plotdata.num_procs = int(os.environ.get("OMP_NUM_THREADS", 1))
frames = [[] for n in xrange(plotdata.num_procs)]
framenos = frametools.only_most_recent(plotdata.print_framenos,
outdir)
# don't use more procs than frames or infinite loop!!
num_procs = min(plotdata.num_procs, len(framenos))
for (n, frame) in enumerate(framenos):
frames[n%num_procs].append(frame)
# Create subprocesses to work on each
plotclaw_cmd = "python %s" % __file__
process_queue = []
for n in xrange(num_procs):
plot_cmd = "%s %s %s %s" % (plotclaw_cmd,
outdir,
plotdir,
setplot)
plot_cmd = plot_cmd + " " + " ".join([str(i) for i in frames[n]])
process_queue.append(subprocess.Popen(plot_cmd, shell=True))
poll_interval = 5
try:
while len(process_queue) > 0:
time.sleep(poll_interval)
for process in process_queue:
if process.poll() is not None:
process_queue.remove(process)
if verbose:
print "Number of processes currently:",len(process_queue)
# Stop child processes if interrupt was caught or something went
# wrong
except KeyboardInterrupt:
print "ABORTING: A keyboard interrupt was caught. All " + \
"child processes will be terminated as well."
for process in process_queue:
process.terminate()
raise
except:
print "ERROR: An error occurred while waiting for " + \
"plotting processes to complete. Aborting all " + \
"child processes."
for process in process_queue:
process.terminate()
raise
# After all frames have been plotted via recursive calls,
# make index and gauge plots only:
plotdata._parallel_todo = 'finalize'
plotpages.plotclaw_driver(plotdata, verbose=False, format=format)
else:
# make frame plots only:
plotdata._parallel_todo = 'frames'
plotdata.print_framenos = frames
plotpages.plotclaw_driver(plotdata, verbose=False, format=format)
else:
# not in parallel:
plotdata._parallel_todo = None
plotpages.plotclaw_driver(plotdata, verbose=False, format=format)
"""
Create the BM1_leveque.txt file requested by Pat Lynett.
"""
from pylab import *
from clawpack.visclaw.data import ClawPlotData
plotdata = ClawPlotData()
toffset = 0.0
if 1:
plotdata.outdir = "_output_manning010_cfl090"
fname = "BM1_leveque_1.txt"
if 0:
plotdata.outdir = "_output_manning010_cfl089"
fname = "BM1_leveque_2.txt"
if 0:
plotdata.outdir = "_output_manning015_cfl090"
fname = "BM1_leveque_3.txt"
if 0:
plotdata.outdir = "_output_manning015_cfl089"
fname = "BM1_leveque_4.txt"
figure(figsize=(8, 12))
clf()
# --- Gauge 1 ---
d = loadtxt("s1u.txt")
t1u = d[:, 0]
# create executable and .data files:
os.system('make .exe')
os.system('make data')
savefig_ext = '.jpg'
figdir = '../figures'
os.system('mkdir -p %s' % figdir)
def save_figure(fname):
"""Save figure to figdir with desired extension"""
full_fname = os.path.join(figdir, fname) + savefig_ext
savefig(full_fname, bbox_inches='tight')
print('Created %s' % full_fname)
makegrid.makegrid()
outdir = '_output'
if run_code:
runclaw(xclawcmd='xgeo', outdir=outdir) # run clawpack code
pd = ClawPlotData()
pd = setplot.setplot(pd) # reload grid.data for each xs value
pd.outdir = os.path.abspath(outdir)
for frameno in [0, 18]:
plotframe(frameno, pd)
fname = 'transect_frame%s' % str(frameno).zfill(2)
save_figure(fname)
g_obs=tidegauge.read_tide_gauge('1617760__2011-03-11_to_2011-03-13.csv')
outdir = '../Runs/HAI1125-26/_output'
tsec = g_obs[1]
thour = tsec / 3600.
eta = g_obs[3]
figure(3)
clf()
plot(thour,eta,'k',linewidth=1)
plot(thour,eta,'k.',linewidth=1,label='Observed')
# computed results:
plotdata = ClawPlotData()
plotdata.outdir = outdir
print "Looking for GeoClaw results in ",plotdata.outdir
g7760 = plotdata.getgauge(7760)
# shift by 10 minutes:
thour = (g7760.t + 600.) / 3600.
plot(thour, g7760.q[3,:],'r',linewidth=2,label='GeoClaw')
xlim(7.5,13)
ylim(-2,1.5)
legend(loc='lower right')
xticks(range(8,14),fontsize=15)
yticks(fontsize=15)
title('Surface elevation at Gauge 7760',fontsize=15)
if 1:
fname = "TG7760.jpg"
from pylab import *
from clawpack.visclaw.data import ClawPlotData
plotdata = ClawPlotData()
if 1:
plotdata.outdir = '_output'
toffset = 92.
if 0:
plotdata.outdir = '_output_manning_0.025'
toffset = 92.
if 0:
plotdata.outdir = '_output_manning015_cfl090'
toffset = 92.
if 0:
plotdata.outdir = '_output_manning015_cfl089'
toffset = 96.
figure(50,figsize=(18,12))
clf()
# --- Gauge 1 ---
d = loadtxt('s1u.txt')
t1u = d[:,0]
s1u = d[:,1]
d = loadtxt('s1v.txt')
try:
matplotlib # see if it's already been imported (interactive session)
except:
import matplotlib
matplotlib.use('Agg') # set to image backend
import os
from pylab import *
from clawpack.visclaw.data import ClawPlotData
rundir = '../Runs/HAI1107'
outdir = os.path.join(rundir, '_output')
obsdir = os.path.abspath('../Observations')
pd = ClawPlotData()
pd.outdir = outdir
g1 = pd.getgauge(1)
g1107 = pd.getgauge(1107)
g12340 = pd.getgauge(12340)
figure(1)
clf()
t = g1.t / 3600.
plot(t, g1.q[3,:], 'b', linewidth=1, label='Gauge S1')
plot(t, g1107.q[3,:], 'r', linewidth=2, label='HAI1107')
#plot(t, g12340.q[3,:], 'g', linewidth=2, label='TG 2340')
xlabel('Hours post-quake')
ylabel('meters')
ylim(-1,1)
xticks(fontsize=15)
import pylab
from clawpack.visclaw.data import ClawPlotData
outdir1 = '_output_260'
outdir2 = '_output_220'
gaugenos = [1, 2]
plotdata = ClawPlotData()
pylab.figure(301)
pylab.clf()
plotdata.outdir = outdir1
for gaugeno in gaugenos:
gs = plotdata.getgauge(gaugeno)
pylab.plot(gs.t, gs.q[3, :], 'b', linewidth=2)
plotdata.outdir = outdir2
for gaugeno in gaugenos:
gs = plotdata.getgauge(gaugeno)
pylab.plot(gs.t, gs.q[3, :], 'r--', linewidth=2)
pylab.xlim([7500, 14000])
pylab.ylim([-2.5, 4])
pylab.xticks(fontsize=15)
pylab.yticks(fontsize=15)
pylab.annotate('Gauge 1', [8200, 1.9], [7700, 2.5],
arrowprops={
'width': 1,
'color': 'k'
# ----
b1 = loadtxt(datadir + "/B1.txt", skiprows=1)
b1a = reshape(b1, (9000, 4))
b4 = loadtxt(datadir + "/B4.txt", skiprows=1)
b4a = reshape(b4, (9000, 4))
b6 = loadtxt(datadir + "/B6.txt", skiprows=1)
b6a = reshape(b6, (9000, 4))
b9 = loadtxt(datadir + "/B9.txt", skiprows=1)
b9a = reshape(b9, (9000, 4))
plotdata = ClawPlotData()
plotdata.outdir = "_output_3"
figure(50, figsize=(8, 12))
clf()
for gnum, wg in zip([1, 2, 3, 4], [wg1, wg2, wg3, wg4]):
g = plotdata.getgauge(gnum)
subplot(4, 1, gnum)
plot(t, wg, "b", label="Measured")
plot(g.t, g.q[3, :], "r", label="GeoClaw")
xlim(0, 40)
title("Gauge %s" % gnum)
ylabel("surface (m)")
legend(loc="upper left")
if 0:
def make_figs(gaugeno,rundir,outdir,veldir):
# measurement values:
#mdir = os.path.abspath(os.path.join(obsdir, veldir))
mdir = os.path.join(obsdir, veldir)
print "Looking for observations in ",mdir
# Use detided values:
fname = 'detided_harmonic.txt'
t_m,u_m,v_m = loadtxt(os.path.join(mdir,fname), unpack=True)
print "Read detided u,v from ",fname
# computed results:
plotdata = ClawPlotData()
plotdata.outdir = os.path.join(rundir,outdir)
print "Looking for GeoClaw results in ",plotdata.outdir
# from PGV.plot_gauge:
g = plotdata.getgauge(gaugeno)
gh = g.q[0,:]
ghu = g.q[1,:]
ghv = g.q[2,:]
t = g.t + 600. # Add 10 minutes for better agreement
u = where(gh>0.01, ghu/gh * 100., 0.) # convert to cm/sec
v = where(gh>0.01, ghv/gh * 100., 0.) # convert to cm/sec
#t,speed,u,v,eta = PGV.plot_gauge(gaugeno,plotdata)
t = t/3600. # convert to hours
i_ts = find((t_m >= t.min()) & (t_m <= t.min() + 5.))
figure(101)
clf()
#plot(u_m,v_m,'k')
plot(u,v,'r',linewidth=3,label='GeoClaw')
plot(u_m[i_ts],v_m[i_ts],'ko',label='Observed')
smax = max(abs(u).max(),abs(v).max(),abs(u_m).max(),abs(v_m).max()) * 1.05
plot([-smax,smax],[0,0],'k')
plot([0,0],[-smax,smax],'k')
axis('scaled')
axis([-smax,smax,-smax,smax])
legend(loc=('lower right'))
title('Velocities at gauge %s' % gaugeno)
#xlabel('u in cm/sec')
#ylabel('v in cm/sec')
xlabel('u (east-west velocity) in cm/sec')
ylabel('v (north-south velocity) in cm/sec')
fname = "../Figures/figure%sa.png" % gaugeno
savefig(fname)
print "Created ",fname
figure(102) #,figsize=(8,10))
clf()
subplot(2,1,1)
plot(t_m,u_m,'ko-',linewidth=2)
plot(t,u,'r',linewidth=3)
#legend(['Observed','GeoClaw'],'upper left')
title('u (east-west velocity) at gauge %s' % gaugeno)
xlim(t.min(),t.max())
ylim(-smax,smax)
ylabel('cm / sec')
#ylim(-80,40)
subplot(2,1,2)
plot(t_m,v_m,'ko-',linewidth=2,label="Observed")
#plot(t_m[i_ts],v_m[i_ts],'bo-',linewidth=2)
plot(t,v,'r',linewidth=3,label="GeoClaw")
#legend(loc=('lower left'))
title('v (north-south velocity) at gauge %s' % gaugeno)
xlim(t.min(),t.max())
ylim(-smax,smax)
ylabel('cm/sec')
xlabel('Hours post-quake')
fname = "../Figures/figure%sb.png" % gaugeno
savefig(fname)
print "Created ",fname
def check_gauges(self,
save=False,
regression_data_path="regression_data.txt",
tolerance=1e-14):
r"""Basic test to assert gauge equality
Test all gauges found in gauges.data. Do full comparison of all
times, levels, components of q.
:Input:
- *save* (bool) - If *True* will save the output from this test to
the file *regresion_data.txt*. Default is *False*.
- *regression_data_path* (path) - Path to the regression test data.
Defaults to 'regression_data.txt'.
- *tolerance* (float) - Tolerance used in comparison, defaults to
*1e-14*.
"""
from clawpack.visclaw import gaugetools
from clawpack.visclaw.data import ClawPlotData
# Get gauge data
plotdata = ClawPlotData()
plotdata.outdir = self.temp_path
setgauges = gaugetools.read_setgauges(plotdata.outdir)
gauge_numbers = setgauges.gauge_numbers
# read in all gauge data and sort by gauge numbers so we
# can properly compare. Note gauges may be written to fort.gauge
# in random order when OpenMP used.
for gaugeno in gauge_numbers:
g = plotdata.getgauge(gaugeno)
m = len(g.level)
number = numpy.array(m * [g.number])
level = numpy.array(g.level)
data_gauge = numpy.vstack((number, level, g.t, g.q)).T
try:
data = numpy.vstack((data, data_gauge))
except:
data = data_gauge # first time thru loop
# save the gauge number sorted by gaugeno in case user wants to
# compare if assertion fails.
sorted_gauge_file = 'test_gauge.txt'
sorted_gauge_path = os.path.join(self.temp_path, sorted_gauge_file)
numpy.savetxt(sorted_gauge_path, data)
# Get (and save) regression comparison data
regression_data_file = os.path.join(self.test_path,
regression_data_path)
if save:
numpy.savetxt(regression_data_file, data)
print "Saved new regression data to %s" % regression_data_file
regression_data = numpy.loadtxt(regression_data_file)
# if assertion fails, indicate to user what files to compare:
output_dir = os.path.join(os.getcwd(),
"%s_output" % self.__class__.__name__)
sorted_gauge_path = os.path.join(output_dir, sorted_gauge_file)
error_msg = "Full gauge match failed. Compare these files: " + \
"\n %s\n %s" % (regression_data_file, sorted_gauge_path) + \
"\nColumns are gaugeno, level, t, q[0:num_eqn]"
assert numpy.allclose(data, regression_data, tolerance), error_msg
def plot_all(values_to_plot,nb_test,nb_frames,format='ascii',msgfile='',**kargs):
# ============================
# = Create Initial Condition =
# ============================
# Construct output and plot directory paths
name = 'multilayer/dry_state_rarefaction_test'
prefix = 'ml_e%s_m%s_fix_m%s_vel' % (2, 500, values_to_plot[0])
prefix = "".join((prefix, "F"))
outdir,plotdir,log_path = runclaw.create_output_paths(name, prefix, **kargs)
script_dir = os.path.dirname(__file__)
plots_dir = os.path.join(script_dir, 'All_plots/')
if not os.path.isdir(plots_dir):
os.makedirs(plots_dir)
# Set physics data
global g
g=Solution(0, path=outdir,read_aux=True).state.problem_data['g']
global manning
manning=Solution(0, path=outdir,read_aux=True).state.problem_data['manning']
global rho_air
rho_air=Solution(0, path=outdir,read_aux=True).state.problem_data['rho_air']
global rho
rho=Solution(0, path=outdir,read_aux=True).state.problem_data['rho']
global r
r=Solution(0, path=outdir,read_aux=True).state.problem_data['r']
global one_minus_r
one_minus_r=Solution(0, path=outdir,read_aux=True).state.problem_data['one_minus_r']
global num_layers
num_layers=Solution(0, path=outdir,read_aux=True).state.problem_data['num_layers']
global b
b = Solution(0, path=outdir,read_aux=True).state.aux[bathy_index,:]
# Set method parameters, this ensures it gets to the Fortran routines
eigen_method=Solution(0, path=outdir,read_aux=True).state.problem_data['eigen_method']
dry_tolerance=Solution(0, path=outdir,read_aux=True).state.problem_data['dry_tolerance']
inundation_method=Solution(0, path=outdir,read_aux=True).state.problem_data['inundation_method']
entropy_fix=Solution(0, path=outdir,read_aux=True).state.problem_data['entropy_fix']
#num_cells=Solution(0,path=outdir,read_aux=True).state.problem_data['num_cells'] #does not work
num_cells=500
plt.clf()
# Load bathymetery
#b = Solution(0, path=outdir,read_aux=True).state.aux[bathy_index,:]
# Load gravitation
#g = Solution(0, path=outdir,read_aux=True).state.problem_data['g']
# Load one minus r
#one_minus_r=Solution(0, path=outdir,read_aux=True).state.problem_data['one_minus_r']
xlimits=[]
for t in range(nb_frames):
#Depths
plotdata=ClawPlotData()
plotfigure_depths = plotdata.new_plotfigure(name='Depths')
plotfigure_depths.show=True
plotaxes_depths = plotfigure_depths.new_plotaxes()
plotaxes_depths.title = "Depths"
plotaxes_depths.xlimits = xlimits
plotaxes_depths.ylimits = 'auto'
# fig2 = plt.figure(num=2)
# plt.xlabel('x(m)')
# plt.ylabel('Depths')
# plt.title('Solution at t = %3.5f' % t)
# plt.ylim(-1.1, 0.1)
#Entropy
fig7 = plt.figure(num=2)
plt.xlabel('x(m)')
plt.ylabel('Entropy')
plt.title('Entropy as t = %3.5f' % t)
#Composite Froude number
fig12 = plt.figure(num=12)
plt.xlabel('x(m)')
plt.ylabel('Composite Froude number')
plt.title('Composite Froude number at t = %3.5f' % t)
plotdata.outdir = outdir
plotdata.plotdir = plots_dir
print(plotdir)
Solutions_=[]
x = [k/1000 for k in range(0,1000,2)]
print('Plot the figures at frame %s' % t)
for i in range(nb_test):
# Construct output and plot directory paths
name = 'multilayer/dry_state_rarefaction_test'
prefix = 'ml_e%s_m%s_fix_m%s_vel' % (eigen_method, num_cells, values_to_plot[i])
if entropy_fix:
prefix = "".join((prefix, "T"))
else:
prefix = "".join((prefix, "F"))
outdir,plotdir,log_path = runclaw.create_output_paths(name, prefix, **kargs)
#exec("cd_"+str(i)+"='"Solution(t,path=outdir,read_aux=True)+"'")
cd = Solution(t,path=outdir,read_aux=True)
Solutions_ += [Solution(t,path=outdir,read_aux=True)]
#=====Plotting=====
plot_color='g'
plot_style='-'
if values_to_plot[i] >= 3.9 :
if values_to_plot[i] >= 8.0 :
plot_color = 'r'
plot_style = ':'
else :
plot_color = 'b'
plot_style = '-.'
#depth
#plotdata.setplot = setplot
plotdata.format = format
plotdata.msgfile = msgfile
plotitem_depths = plotaxes_depths.new_plotitem(plot_type='1d')
plotitem_depths.plot_var = eta_1
plotitem_depths.plotstyle='k'
plotitem_depths.color=plot_color
plotitem_depths.show=True
# plt.figure(num=2)
# plt.plot(bathy(cd),'k')
# plt.plot(eta_1(cd),'k',color=plot_color,linestyle=plot_style)
# plt.plot(eta_2(cd),'k',color=plot_color,linestyle=plot_style)
# depthname = 'frame00%sfig1002.png' % t
# plt.savefig(plots_dir + depthname)
#plt.close()
#Entropy
# plt.figure(num=7)
# plt.plot(entropy(cd),'k',color=plot_color,linestyle=plot_style)
# entropyname = 'frame00%sfig1007.png' % t
# plt.savefig(plots_dir + entropyname)
#
# #Composite Froude number
# plt.figure(num=12)
# plt.plot(composite_Froude_nb(cd),'k',color=plot_color,linestyle=plot_style)
# froudename = 'frame00%sfig1012.png' % ( t )
# plt.savefig(plots_dir + froudename)
#plt.close()
plt.close('all')
# Folder from out or out2 differ in that the Riemann solver used uses the Lagrangian transformation # on all of water or only in the interface respectively # CHOOSE out or outmap in the outdir to choose from non-mapped or mapped version of code outstr = '_outlim' #plotdata.outdir = '../../_output' # set to the proper output directory #g = plotdata.getgauge(gaugeno) #p = zeros(g.t.size) #p = (gammawat - 1.0)*(g.q[3,:] - 0.5*(g.q[1,:]*g.q[1,:] + g.q[2,:]*g.q[2,:])/g.q[0,:]) - gammawat*pinfwat #p = 0.001*p # Convert to KPa #tt = g.t*1000000 # Convert to microsec #plot(tt, p, '-g', label="Level New", linewidth=3) plotdata.outdir = outstr +'_conv_40x20_lvl6_refrat2-2-2-2-2' # set to the proper output directory g = plotdata.getgauge(gaugeno) p = zeros(g.t.size) p = (gammawat - 1.0)*(g.q[3,:] - 0.5*(g.q[1,:]*g.q[1,:] + g.q[2,:]*g.q[2,:])/g.q[0,:]) - gammawat*pinfwat p = 0.001*p # Convert to KPa tt = g.t*1000000 # Convert to microsec plot(tt, p, '-k', label="Level 6", linewidth=1) plotdata.outdir = outstr +'_conv_40x20_lvl5_refrat2-2-2-2' # set to the proper output directory g = plotdata.getgauge(gaugeno) p = zeros(g.t.size) p = (gammawat - 1.0)*(g.q[3,:] - 0.5*(g.q[1,:]*g.q[1,:] + g.q[2,:]*g.q[2,:])/g.q[0,:]) - gammawat*pinfwat p = 0.001*p # Convert to KPa tt = g.t*1000000 # Convert to microsec plot(tt, p, '-b', label="Level 5", linewidth=1)
def check_gauges(self, save=False,
regression_data_path="regression_data.txt",
tolerance=1e-14):
r"""Basic test to assert gauge equality
Test all gauges found in gauges.data. Do full comparison of all
times, levels, components of q.
:Input:
- *save* (bool) - If *True* will save the output from this test to
the file *regresion_data.txt*. Default is *False*.
- *regression_data_path* (path) - Path to the regression test data.
Defaults to 'regression_data.txt'.
- *tolerance* (float) - Tolerance used in comparison, defaults to
*1e-14*.
"""
from clawpack.visclaw import gaugetools
from clawpack.visclaw.data import ClawPlotData
# Get gauge data
plotdata = ClawPlotData()
plotdata.outdir = self.temp_path
setgauges = gaugetools.read_setgauges(plotdata.outdir)
gauge_numbers = setgauges.gauge_numbers
# read in all gauge data and sort by gauge numbers so we
# can properly compare. Note gauges may be written to fort.gauge
# in random order when OpenMP used.
for gaugeno in gauge_numbers:
g = plotdata.getgauge(gaugeno)
m = len(g.level)
number = numpy.array(m*[g.number])
level = numpy.array(g.level)
data_gauge = numpy.vstack((number,level,g.t,g.q)).T
try:
data = numpy.vstack((data, data_gauge))
except:
data = data_gauge # first time thru loop
# save the gauge number sorted by gaugeno in case user wants to
# compare if assertion fails.
sorted_gauge_file = 'test_gauge.txt'
sorted_gauge_path = os.path.join(self.temp_path, sorted_gauge_file)
numpy.savetxt(sorted_gauge_path, data)
# Get (and save) regression comparison data
regression_data_file = os.path.join(self.test_path,
regression_data_path)
if save:
numpy.savetxt(regression_data_file, data)
print "Saved new regression data to %s" % regression_data_file
regression_data = numpy.loadtxt(regression_data_file)
# if assertion fails, indicate to user what files to compare:
output_dir = os.path.join(os.getcwd(),
"%s_output" % self.__class__.__name__)
sorted_gauge_path = os.path.join(output_dir, sorted_gauge_file)
error_msg = "Full gauge match failed. Compare these files: " + \
"\n %s\n %s" % (regression_data_file, sorted_gauge_path) + \
"\nColumns are gaugeno, level, t, q[0:num_eqn]"
assert numpy.allclose(data, regression_data, tolerance), error_msg
import matplotlib
matplotlib.use('Agg')
from pylab import *
#from pyclaw.plotters.data import ClawPlotData
from clawpack.visclaw.data import ClawPlotData
Runs = '../Runs/'
pd = ClawPlotData()
pd.outdir = Runs + 'HAI1107/_output'
g1 = pd.getgauge(1)
g1107 = pd.getgauge(1107)
g12340 = pd.getgauge(12340)
figure(1)
clf()
t = g1.t / 3600.
plot(t, g1.q[3,:], 'b', linewidth=1, label='Gauge S1')
plot(t, g1107.q[3,:], 'r', linewidth=2, label='HAI1107')
#plot(t, g12340.q[3,:], 'g', linewidth=2, label='TG 2340')
xlabel('Hours post-quake')
ylabel('meters')
legend(loc='upper right')
title('Surface elevation at Honolulu gauges')
figure(2)
clf()
"""
Create the BM1_leveque.txt file requested by Pat Lynett.
"""
from pylab import *
from clawpack.visclaw.data import ClawPlotData
plotdata = ClawPlotData()
toffset = 0.
if 1:
plotdata.outdir = '_output_manning010_cfl090'
fname = 'BM1_leveque_1.txt'
if 0:
plotdata.outdir = '_output_manning010_cfl089'
fname = 'BM1_leveque_2.txt'
if 0:
plotdata.outdir = '_output_manning015_cfl090'
fname = 'BM1_leveque_3.txt'
if 0:
plotdata.outdir = '_output_manning015_cfl089'
fname = 'BM1_leveque_4.txt'
figure(figsize=(8,12))
clf()
# --- Gauge 1 ---
d = loadtxt('s1u.txt')
t1u = d[:,0]
import pylab
from clawpack.visclaw.data import ClawPlotData
outdir1 = '_output_260'
outdir2 = '_output_220'
gaugenos = [1,2]
plotdata = ClawPlotData()
pylab.figure(301)
pylab.clf()
plotdata.outdir = outdir1
for gaugeno in gaugenos:
gs = plotdata.getgauge(gaugeno)
pylab.plot(gs.t, gs.q[3,:], 'b',linewidth=2)
plotdata.outdir = outdir2
for gaugeno in gaugenos:
gs = plotdata.getgauge(gaugeno)
pylab.plot(gs.t, gs.q[3,:], 'r--',linewidth=2)
pylab.xlim([7500,14000])
pylab.ylim([-2.5,4])
pylab.xticks(fontsize=15)
pylab.yticks(fontsize=15)
pylab.annotate('Gauge 1',[8200,1.9],[7700,2.5],arrowprops={'width':1,'color':'k'})
pylab.annotate('Gauge 2',[9300,2.7] ,[9700,3.1],arrowprops={'width':1,'color':'k'})
def compare_gauges(outdir1, outdir2, gaugenos='all', q_components='all',
tol=0., verbose=True, plot=False):
"""
Compare gauge output in two output directories.
:Input:
- *outdir1, outdir2* -- output directories
- *gaugenos* -- list of gauge numbers to compare, or 'all' in which case
outdir1/gauges.data will be used to determine gauge numbers.
- *q_components* -- list of components of q to compare.
- *tol* -- tolerance for checking equality
- *verbose* -- print out dt and dq for each comparison?
- *plot* -- if True, will produce a plot for each gauge, with a
subfigure for each component of q.
Returns True if everything matches to tolerance *tol*, else False.
"""
from clawpack.visclaw.data import ClawPlotData
from matplotlib import pyplot as plt
if gaugenos == 'all':
# attempt to read from gauges.data:
try:
setgauges1 = read_setgauges(outdir1)
setgauges2 = read_setgauges(outdir2)
except:
print '*** could not read gauges.data from one of the outdirs'
return
gaugenos = setgauges1.gauge_numbers
if setgauges2.gauge_numbers != gaugenos:
print '*** warning -- outdirs have different sets of gauges'
if len(gaugenos)==0:
print "*** No gauges found in gauges.data"
return
plotdata1 = ClawPlotData()
plotdata1.outdir = outdir1
plotdata2 = ClawPlotData()
plotdata2.outdir = outdir2
matches = True
for gaugeno in gaugenos:
g1 = plotdata1.getgauge(gaugeno,verbose=verbose)
t1 = g1.t
q1 = g1.q
g2 = plotdata2.getgauge(gaugeno,verbose=verbose)
t2 = g2.t
q2 = g2.q
dt = abs(t1-t2).max()
if verbose:
print "Max difference in t[:] at gauge %s is %g" % (gaugeno,dt)
matches = matches and (dt <= tol)
if q_components == 'all':
q_components = range(q1.shape[0])
for m in q_components:
dq = abs(q1[m,:]-q2[m,:]).max()
if verbose:
print "Max difference in q[%s] at gauge %s is %g" % (m,gaugeno,dq)
matches = matches and (dq <= tol)
if plot:
plt.figure(gaugeno)
plt.clf()
mq = len(q_components)
for k,m in enumerate(q_components):
plt.subplot(mq,1,k+1)
plt.plot(g1.t,g1.q[m,:],'b',label='outdir1')
plt.plot(g2.t,g2.q[m,:],'r',label='outdir2')
plt.legend()
plt.title('q[%s] at gauge number %s' % (m,gaugeno))
return matches
# Folder from out or out2 differ in that the Riemann solver used uses the Lagrangian transformation
# on all of water or only in the interface respectively
# CHOOSE out or outmap in the outdir to choose from non-mapped or mapped version of code
outstr = '_outlim'
#plotdata.outdir = '../../_output' # set to the proper output directory
#g = plotdata.getgauge(gaugeno)
#p = zeros(g.t.size)
#p = (gammawat - 1.0)*(g.q[3,:] - 0.5*(g.q[1,:]*g.q[1,:] + g.q[2,:]*g.q[2,:])/g.q[0,:]) - gammawat*pinfwat
#p = 0.001*p # Convert to KPa
#tt = g.t*1000000 # Convert to microsec
#plot(tt, p, '-g', label="Level New", linewidth=3)
plotdata.outdir = outstr + '_conv_40x20_lvl6_refrat2-2-2-2-2' # set to the proper output directory
g = plotdata.getgauge(gaugeno)
p = zeros(g.t.size)
p = (gammawat - 1.0) * (g.q[3, :] - 0.5 *
(g.q[1, :] * g.q[1, :] + g.q[2, :] * g.q[2, :]) /
g.q[0, :]) - gammawat * pinfwat
p = 0.001 * p # Convert to KPa
tt = g.t * 1000000 # Convert to microsec
plot(tt, p, '-k', label="Level 6", linewidth=1)
plotdata.outdir = outstr + '_conv_40x20_lvl5_refrat2-2-2-2' # set to the proper output directory
g = plotdata.getgauge(gaugeno)
p = zeros(g.t.size)
p = (gammawat - 1.0) * (g.q[3, :] - 0.5 *
(g.q[1, :] * g.q[1, :] + g.q[2, :] * g.q[2, :]) /
g.q[0, :]) - gammawat * pinfwat
matplotlib # see if it's already been imported (interactive session)
except:
import matplotlib
matplotlib.use("Agg") # set to image backend
import os
from pylab import *
from clawpack.visclaw.data import ClawPlotData
rundir = "../Runs/HAI1107"
outdir = os.path.join(rundir, "_output")
obsdir = os.path.abspath("../Observations")
pd = ClawPlotData()
pd.outdir = outdir
g1 = pd.getgauge(1)
g1107 = pd.getgauge(1107)
g12340 = pd.getgauge(12340)
figure(1)
clf()
t = g1.t / 3600.0
plot(t, g1.q[3, :], "b", linewidth=1, label="Gauge S1")
plot(t, g1107.q[3, :], "r", linewidth=2, label="HAI1107")
# plot(t, g12340.q[3,:], 'g', linewidth=2, label='TG 2340')
xlabel("Hours post-quake")
ylabel("meters")
ylim(-1, 1)
xticks(fontsize=15)
# ----
b1 = loadtxt(datadir+'/B1.txt',skiprows=1)
b1a = reshape(b1,(9000,4))
b4 = loadtxt(datadir+'/B4.txt',skiprows=1)
b4a = reshape(b4,(9000,4))
b6 = loadtxt(datadir+'/B6.txt',skiprows=1)
b6a = reshape(b6,(9000,4))
b9 = loadtxt(datadir+'/B9.txt',skiprows=1)
b9a = reshape(b9,(9000,4))
plotdata = ClawPlotData()
#plotdata.outdir = '_output_3'
plotdata.outdir = '_output'
figure(50,figsize=(8,12))
clf()
for gnum,wg in zip([1,2,3,4], [wg1,wg2,wg3,wg4]):
g = plotdata.getgauge(gnum)
subplot(4,1,gnum)
plot(t,wg,'b',label='Measured')
plot(g.t, g.q[3,:],'r',label='GeoClaw')
xlim(0,40)
title('Gauge %s' % gnum)
ylabel('surface (m)')
legend(loc='upper left')
from pylab import *
from clawpack.visclaw.data import ClawPlotData
plotdata = ClawPlotData()
if 1:
plotdata.outdir = '_output'
toffset = 92.
if 0:
plotdata.outdir = '_output_manning_0.025'
toffset = 92.
if 0:
plotdata.outdir = '_output_manning015_cfl090'
toffset = 92.
if 0:
plotdata.outdir = '_output_manning015_cfl089'
toffset = 96.
figure(50, figsize=(18, 12))
clf()
# --- Gauge 1 ---
d = loadtxt('s1u.txt')
t1u = d[:, 0]
s1u = d[:, 1]
d = loadtxt('s1v.txt')
t1v = d[:, 0]
s1v = d[:, 1]
from pylab import *
from clawpack.visclaw.data import ClawPlotData
if 0:
gdata = loadtxt('gauges.data', skiprows=7)
ngauges = gdata.shape[0]
print "Found %s gauges" % ngauges
xc = gdata[:, 1]
yc = gdata[:, 2]
# Load ClawplotData
plotdata = ClawPlotData()
plotdata.format = 'binary'
plotdata.outdir = '_output'
def plot_gauges(goffset=0):
if goffset == 0:
ngauges = 100 # top surface
elif goffset == 200:
ngauges = 100 # bottom of domain
elif goffset == 300:
ngauges = 50 # above fault plane
elif goffset == 400:
ngauges = 50 # below fault plane
plot_okada = (goffset == 0)
figure()
#for t in linspace(0.,120,7):
""" Create the BM2 files requested by Pat Lynett. """ from pylab import * from scipy import interpolate from clawpack.visclaw.data import ClawPlotData plotdata = ClawPlotData() plotdata.outdir = '_output_1-3sec_alltime' #tfinal = 4.9 * 3600. tfinal = 6.4 * 3600. # for alltime dt = 1. # time increment for output files tout = arange(0., tfinal, dt) g = plotdata.getgauge(3333) p = interpolate.interp1d(g.t, g.q[3, :]) # interpolate surface g3333_eta = p(tout) g = plotdata.getgauge(7761) p = interpolate.interp1d(g.t, g.q[3, :]) # interpolate surface g7761_eta = p(tout) g = plotdata.getgauge(1125) u = g.q[1, :] / g.q[0, :] v = g.q[2, :] / g.q[0, :] s = sqrt(u**2 + v**2) p = interpolate.interp1d(g.t, s) # interpolate speed
def plotclaw(outdir='.',
plotdir='_plots',
setplot='setplot.py',
format='ascii',
msgfile='',
frames=None,
verbose=False):
"""
Create html and/or latex versions of plots.
INPUT:
setplot is a module containing a function setplot that will be called
to set various plotting parameters.
format specifies the format of the files output from Clawpack
"""
from clawpack.visclaw.data import ClawPlotData
from clawpack.visclaw import plotpages
plotdata = ClawPlotData()
plotdata.outdir = outdir
plotdata.plotdir = plotdir
plotdata.setplot = setplot
plotdata.format = format
plotdata.msgfile = msgfile
frametools.call_setplot(plotdata.setplot, plotdata)
if plotdata.num_procs is None:
plotdata.num_procs = int(os.environ.get("OMP_NUM_THREADS", 1))
# Make sure plotdata.parallel is False in some cases:
if plotdata.parallel:
assert type(setplot) in [str, bool, type(None)], \
"*** Parallel plotting is not supported when ClawPlotData " \
+ "attribute setplot is a function."
if plotdata.parallel and (plotdata.num_procs > 1):
# If this is the original call then we need to split up the work and
# call this function again
# First set up plotdir:
plotdata._parallel_todo = 'initialize'
plotpages.plotclaw_driver(plotdata, verbose=False, format=format)
if frames is None:
if plotdata.num_procs is None:
plotdata.num_procs = int(os.environ.get("OMP_NUM_THREADS", 1))
frames = [[] for n in range(plotdata.num_procs)]
framenos = frametools.only_most_recent(plotdata.print_framenos,
outdir)
# don't use more procs than frames or infinite loop!!
num_procs = min(plotdata.num_procs, len(framenos))
for (n, frame) in enumerate(framenos):
frames[n % num_procs].append(frame)
# Create subprocesses to work on each
plotclaw_cmd = "python %s" % __file__
process_queue = []
for n in range(num_procs):
plot_cmd = "%s %s %s %s" % (plotclaw_cmd, outdir, plotdir,
setplot)
plot_cmd = plot_cmd + " " + " ".join(
[str(i) for i in frames[n]])
process_queue.append(subprocess.Popen(plot_cmd, shell=True))
poll_interval = 5
try:
while len(process_queue) > 0:
time.sleep(poll_interval)
for process in process_queue:
if process.poll() is not None:
process_queue.remove(process)
if verbose:
print("Number of processes currently:",
len(process_queue))
# Stop child processes if interrupt was caught or something went
# wrong
except KeyboardInterrupt:
print("ABORTING: A keyboard interrupt was caught. All " + \
"child processes will be terminated as well.")
for process in process_queue:
process.terminate()
raise
except:
print("ERROR: An error occurred while waiting for " + \
"plotting processes to complete. Aborting all " + \
"child processes.")
for process in process_queue:
process.terminate()
raise
# After all frames have been plotted via recursive calls,
# make index and gauge plots only:
plotdata._parallel_todo = 'finalize'
plotpages.plotclaw_driver(plotdata, verbose=False, format=format)
else:
# make frame plots only:
plotdata._parallel_todo = 'frames'
plotdata.print_framenos = frames
plotpages.plotclaw_driver(plotdata, verbose=False, format=format)
else:
# not in parallel:
plotdata._parallel_todo = None
plotpages.plotclaw_driver(plotdata, verbose=False, format=format)
""" Create the BM2 files requested by Pat Lynett. """ from pylab import * from scipy import interpolate from clawpack.visclaw.data import ClawPlotData plotdata = ClawPlotData() plotdata.outdir = '_output_1-3sec_alltime' #tfinal = 4.9 * 3600. tfinal = 6.4 * 3600. # for alltime dt = 1. # time increment for output files tout = arange(0., tfinal, dt) g = plotdata.getgauge(3333) p = interpolate.interp1d(g.t, g.q[3,:]) # interpolate surface g3333_eta = p(tout) g = plotdata.getgauge(7761) p = interpolate.interp1d(g.t, g.q[3,:]) # interpolate surface g7761_eta = p(tout) g = plotdata.getgauge(1125) u = g.q[1,:]/g.q[0,:] v = g.q[2,:]/g.q[0,:] s = sqrt(u**2 + v**2) p = interpolate.interp1d(g.t, s) # interpolate speed
def compare_gauges(outdir1,
outdir2,
gaugenos='all',
q_components='all',
tol=0.,
verbose=True,
plot=False):
"""
Compare gauge output in two output directories.
:Input:
- *outdir1, outdir2* -- output directories
- *gaugenos* -- list of gauge numbers to compare, or 'all' in which case
outdir1/gauges.data will be used to determine gauge numbers.
- *q_components* -- list of components of q to compare.
- *tol* -- tolerance for checking equality
- *verbose* -- print out dt and dq for each comparison?
- *plot* -- if True, will produce a plot for each gauge, with a
subfigure for each component of q.
Returns True if everything matches to tolerance *tol*, else False.
"""
from clawpack.visclaw.data import ClawPlotData
from matplotlib import pyplot as plt
if gaugenos == 'all':
# attempt to read from gauges.data:
try:
setgauges1 = read_setgauges(outdir1)
setgauges2 = read_setgauges(outdir2)
except:
print('*** could not read gauges.data from one of the outdirs')
return
gaugenos = setgauges1.gauge_numbers
if setgauges2.gauge_numbers != gaugenos:
print('*** warning -- outdirs have different sets of gauges')
if len(gaugenos) == 0:
print("*** No gauges found in gauges.data")
return
plotdata1 = ClawPlotData()
plotdata1.outdir = outdir1
plotdata2 = ClawPlotData()
plotdata2.outdir = outdir2
matches = True
for gaugeno in gaugenos:
g1 = plotdata1.getgauge(gaugeno, verbose=verbose)
t1 = g1.t
q1 = g1.q
g2 = plotdata2.getgauge(gaugeno, verbose=verbose)
t2 = g2.t
q2 = g2.q
dt = abs(t1 - t2).max()
if verbose:
print("Max difference in t[:] at gauge %s is %g" % (gaugeno, dt))
matches = matches and (dt <= tol)
if q_components == 'all':
q_components = list(range(q1.shape[0]))
for m in q_components:
dq = abs(q1[m, :] - q2[m, :]).max()
if verbose:
print("Max difference in q[%s] at gauge %s is %g" %
(m, gaugeno, dq))
matches = matches and (dq <= tol)
if plot:
plt.figure(gaugeno)
plt.clf()
mq = len(q_components)
for k, m in enumerate(q_components):
plt.subplot(mq, 1, k + 1)
plt.plot(g1.t, g1.q[m, :], 'b', label='outdir1')
plt.plot(g2.t, g2.q[m, :], 'r', label='outdir2')
plt.legend()
plt.title('q[%s] at gauge number %s' % (m, gaugeno))
return matches
