def getframe(self, frameno, outdir=None):
"""
ClawPlotData.getframe:
Return an object of class Solution containing the solution
for frame number frameno.
If self.refresh_frames == True then this frame is read from the fort
files, otherwise it is read from the fort files only if the
the dictionary self.framesoln_dict has no key frameno. If it does, the
frame has previously been read and the dictionary value is returned.
"""
from clawpack.pyclaw import solution
framesoln_dict = self.framesoln_dict
if 0:
if outdir:
key = (frameno, outdir)
else:
key = frameno
outdir = self.outdir
if outdir is None:
outdir = self.outdir
outdir = os.path.abspath(outdir)
key = (frameno, outdir)
if self.refresh_frames or (not framesoln_dict.has_key(key)):
try:
framesoln = solution.Solution(frameno,
path=outdir,
file_format=self.format)
except:
print '*** Error reading frame in ClawPlotData.getframe'
raise
return
if not self.save_frames:
framesoln_dict.clear()
framesoln_dict[key] = framesoln
if key != frameno:
print ' Reading Frame %s at t = %g from outdir = %s' \
% (frameno,framesoln.t,outdir)
else:
print ' Reading Frame %s at t = %g ' \
% (frameno,framesoln.t)
else:
framesoln = self.framesoln_dict[key]
return framesoln
def check_frame(self, save=False, indices=[0], frame_num=1,
file_name="regression_data.txt",
rtol=1e-14, atol=1e-08, tolerance=None):
r"""Compare choosen frame to the comparison data
:Input:
- *save* (bool) - If *True* will save the output from this test to
the file *regresion_data.txt*. Default is *False*.
- *indices* (tuple) - Contains indices to compare in the gague
comparison. Defaults to *(0)*.
- *frame_num* (int) - Frame number to load from the run data. Defaults
to *1*.
- *regression_data_path* (path) - Path to the regression test data.
Defaults to 'regression_data.txt'.
- *rtol* (float) - Relative tolerance used in the comparison, default
is *1e-14*. Note that the old *tolerance* input is now synonymous
with this parameter.
- *atol* (float) - Absolute tolerance used in the comparison, default
is *1e-08*.
"""
if isinstance(tolerance, float):
rtol = tolerance
# Load test data
data = solution.Solution(frame_num, path=self.temp_path)
data_sum = []
for index in indices:
data_sum.append(data.q[index, ...].sum())
# Get (and save) regression comparison data
regression_data_file = os.path.join(self.test_path, "regression_data",
file_name)
if save:
numpy.savetxt(regression_data_file, data_sum)
claw_git_status.make_git_status_file(
outdir=os.path.join(self.test_path, "regression_data"))
regression_sum = numpy.loadtxt(regression_data_file)
assert numpy.allclose(data_sum, regression_sum, rtol=rtol, atol=atol), \
"\n new_data: %s, \n expected: %s" % (data_sum, regression_sum)
def check_frame(self,
save=False,
indices=[0],
frame_num=1,
regression_data_path="regression_data.txt",
tolerance=1e-14):
r"""Compare choosen frame to the comparison data
:Input:
- *save* (bool) - If *True* will save the output from this test to
the file *regresion_data.txt*. Default is *False*.
- *indices* (tuple) - Contains indices to compare in the gague
comparison. Defaults to *(0)*.
- *frame_num* (int) - Frame number to load from the run data. Defaults
to *1*.
- *regression_data_path* (path) - Path to the regression test data.
Defaults to 'regression_data.txt'.
- *tolerance* (float) - Tolerance used in the comparison, default is
*1e-14*.
"""
# Load test data
data = solution.Solution(frame_num, path=self.temp_path)
data_sum = []
for index in indices:
data_sum.append(data.q[index, ...].sum())
# 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_sum)
regression_sum = numpy.loadtxt(regression_data_file)
# regression_sum = []
# for index in indices:
# regression_sum.append(regression_data[index, :].sum())
assert numpy.allclose(data_sum, regression_sum, tolerance), \
"\n new_data: %s, \n expected: %s" % (data_sum, regression_sum)
#!/usr/bin/env python
import numpy
import matplotlib.pyplot as plt
import clawpack.pyclaw.solution as sol
file = open('num_steps.txt', 'r')
num_steps = file.read()
for i in xrange(int(num_steps)):
mySolution = sol.Solution(i, path='./numerical_output')
fig = plt.figure()
axes = fig.add_subplot(1, 1, 1)
axes.plot(mySolution.state.grid.x.centers, mySolution.q[0, :], 'o-')
plt.savefig("./graphic_output/q%s.png" % i)
raw_string = r"%." + str(figs) + "g"
x = [float(raw_string % value) for value in x]
return x
if __name__ == '__main__':
# Construct path to solutions
data_path = os.environ["DATA_PATH"]
eigen_method = 2
rho = [0.98, 1.0]
for test in ['smooth', 'jump']:
for dry in [True, False]:
sol_path = os.path.join(data_path, "well_balancing_%s" % test,
"ml_e%s_d%s_output" % (eigen_method, dry))
sol = solution.Solution(1, path=sol_path, read_aux=True)
if dry:
eta = [0.0, -6.0]
else:
eta = [0.0, -4.0]
print "%s, %s =" % (test, dry)
print " ", sig_fig_round(compute_error(sol.q,
sol.aux,
eta,
rho,
norm=1),
figs=3)
print " ", sig_fig_round(compute_error(sol.q,
sol.aux,
eta,
from clawpack.pyclaw import solution sol = solution.Solution()
outdir = "/_output/"
else:
outdir = ""
# Load reference solution and test solution
n = numpy.infty # n-norm
# Lists to store errors (p-norm) and absolute difference, for h, hu, hv
errors = [[], [], []]
tbegin = 0
tend = 19
print "### Computing error ({:f}-norm) and maximum difference for time step {:d} to {:d} ###".format(
n, tbegin, tend)
for t in xrange(tbegin, tend):
ref = solution.Solution(t, path=sys.argv[1] + outdir, read_aux=False)
sol = solution.Solution(t, path=sys.argv[2] + outdir, read_aux=False)
# print "=== Test solution stats for timestep {:d} ===".format(t)
# print "Number of cells: " + str(ref.q.shape[0])
# print "Number of cells (x-dir): " + str(ref.q.shape[1])
# print "Number of cells (y-dir): " + str(ref.q.shape[2])
# Format: h = h(x, t)
h = sol.q[0, ...]
href = ref.q[0, ...]
hu = sol.q[1, ...]
huref = ref.q[1, ...]
hv = sol.q[2, ...]
hvref = ref.q[2, ...]
#if (t==7):