def _plot_velocity(self):
from pysph.tools.interpolator import Interpolator
from pysph.solver.utils import load
from pysph.examples.ghia_cavity_data import get_u_vs_y, get_v_vs_x
# interpolated velocities
_x = np.linspace(0, 1, 101)
xx, yy = np.meshgrid(_x, _x)
# take the last solution data
fname = self.output_files[-1]
data = load(fname)
tf = data['solver_data']['t']
interp = Interpolator(list(data['arrays'].values()), x=xx, y=yy)
ui = np.zeros_like(xx)
vi = np.zeros_like(xx)
# Average out the velocities over the last n_avg timesteps
for fname in self.output_files[-self.n_avg:]:
data = load(fname)
tf = data['solver_data']['t']
interp.update_particle_arrays(list(data['arrays'].values()))
_u = interp.interpolate('u')
_v = interp.interpolate('v')
_u.shape = 101, 101
_v.shape = 101, 101
ui += _u
vi += _v
ui /= self.n_avg
vi /= self.n_avg
# velocity magnitude
self.vmag = vmag = np.sqrt(ui**2 + vi**2)
import matplotlib.pyplot as plt
f = plt.figure()
plt.streamplot(
xx,
yy,
ui,
vi,
density=(2, 2), #linewidth=5*vmag/vmag.max(),
color=vmag)
plt.xlim(0, 1)
plt.ylim(0, 1)
plt.colorbar()
plt.xlabel('$x$')
plt.ylabel('$y$')
plt.title('Streamlines at %s seconds' % tf)
fig = os.path.join(self.output_dir, 'streamplot.png')
plt.savefig(fig, dpi=300)
f = plt.figure()
ui_c = ui[:, 50]
vi_c = vi[50]
s1 = plt.subplot(211)
s1.plot(ui_c, _x, label='Computed')
y, data = get_u_vs_y()
if self.re in data:
s1.plot(data[self.re],
y,
'o',
fillstyle='none',
label='Ghia et al.')
s1.set_xlabel(r'$v_x$')
s1.set_ylabel(r'$y$')
s1.legend()
s2 = plt.subplot(212)
s2.plot(_x, vi_c, label='Computed')
x, data = get_v_vs_x()
if self.re in data:
s2.plot(x,
data[self.re],
'o',
fillstyle='none',
label='Ghia et al.')
s2.set_xlabel(r'$x$')
s2.set_ylabel(r'$v_y$')
s2.legend()
fig = os.path.join(self.output_dir, 'centerline.png')
plt.savefig(fig, dpi=300)
return _x, ui, vi, ui_c, vi_c
data = np.load(file_loc)
ui, vi, t = data['u'], data['v'], data['t']
vmag = np.sqrt(ui**2 + vi**2)
tf = t[-1]
ui_c = ui[:, 50]
vi_c = vi[50]
if cnt == 0:
y, data = get_u_vs_y()
if re in data:
s1.plot(data[re], y, 'o', fillstyle='none', label='Ghia et al.')
s1.plot(ui_c, _x, label=sph_schm_legend[schm])
if cnt == 0:
x, data = get_v_vs_x()
if re in data:
s2.plot(x, data[re], 'o', fillstyle='none', label='Ghia et al.')
cnt = 1
s2.plot(_x, vi_c, label=sph_schm_legend[schm])
s1.set_xlabel(r'$v_x$')
s1.set_ylabel(r'$y$')
s1.legend()
s2.set_xlabel(r'$x$')
s2.set_ylabel(r'$v_y$')
s2.legend()
tle = file_base + '/centerline' + savefig_additional + '.png'
plt.savefig(tle, dpi=400)
################################################################################