def _plot_ke_history(self):
from pysph.tools.pprocess import get_ke_history
from matplotlib import pyplot as plt
t, ke = get_ke_history(self.output_files, 'fluid')
plt.clf()
plt.plot(t, ke)
plt.xlabel('t')
plt.ylabel('Kinetic energy')
fig = os.path.join(self.output_dir, "ke_history.png")
plt.savefig(fig, dpi=300)
return t, ke
def post_process(self, info_fname):
"""Save fiber orientation tensor to csv file."""
if len(self.output_files) == 0:
return
from pysph.tools.pprocess import get_ke_history
from matplotlib import pyplot as plt
t, ke = get_ke_history(self.output_files, "fluid")
plt.clf()
plt.plot(t, ke)
plt.xlabel("t")
plt.ylabel("Kinetic energy")
fig = os.path.join(self.output_dir, "ke_history.png")
plt.savefig(fig, dpi=300)
# empty list for time
t = []
# empty lists for fiber orientation tensors
A = []
# iteration over all output files
output_files = remove_irrelevant_files(self.output_files)
for fname in output_files:
data = load(fname)
# extracting time
t.append(data["solver_data"]["t"])
if self.n > 0:
# extrating all arrays.
directions = []
fiber = data["arrays"]["fibers"]
startpoints = [i * (self.options.lf - 1) for i in range(0, self.n)]
endpoints = [
i * (self.options.lf - 1) - 1 for i in range(1, self.n + 1)
]
for start, end in zip(startpoints, endpoints):
px = np.mean(fiber.rxnext[start:end])
py = np.mean(fiber.rynext[start:end])
pz = np.mean(fiber.rznext[start:end])
n = np.array([px, py, pz])
norm = np.linalg.norm(n)
if norm == 0:
p = np.array([1, 0, 0])
else:
p = n / norm
directions.append(p)
N = len(directions)
a = np.zeros([3, 3])
for p in directions:
for i in range(3):
for j in range(3):
a[i, j] += 1.0 / N * (p[i] * p[j])
A.append(a.ravel())
csv_file = os.path.join(self.output_dir, "A.csv")
data = np.hstack((np.matrix(t).T, np.vstack(A)))
np.savetxt(csv_file, data, delimiter=",")
# plot results
data = np.loadtxt(csv_file, delimiter=',')
t = data[:, 0]
plt.figure(figsize=(12, 3))
for j, i in enumerate([0, 4, 8, 1]):
plt.subplot("14"+str(j+1))
p = plt.plot(self.options.G*t, data[:, i+1])
plt.xlabel("Strains")
plt.ylabel("Component %d" % j)
if i % 2 == 0:
plt.ylim([0, 1])
else:
plt.ylim([-1, 1])
plt.tight_layout()
plt.savefig(csv_file.replace('.csv', '.pdf'))
try:
from matplotlib2tikz import save as tikz_save
tikz_save(csv_file.replace('.csv', '.tex'))
except ImportError:
print("Did not write tikz figure.")
