def burgers1Dexact(xvect, tvect, x0, qL, qR, iMAX):
for ti in tvect:
# yield flx.nlers2(qL, qR, (xvect-x0)/ti)
xi = (xvect - x0) / ti
solution = []
for i in range(iMAX):
solution.append(flx.nlers(qL, qR, xi[i]))
yield solution
def plot_fv1D(
xL,
xR,
x0,
iMAX,
qL,
qR,
tSTART,
tEND,
courant,
nummtd,
order="first",
solintmtd="simple",
maxiter=10000,
pause=0.005,
ylimext=0.15,
):
# equidistant distribution of iMAX points between xL and xR
xvect, dx = np.linspace(xL, xR, iMAX, retstep=True)
# equidistant distribution of points between each spatial step
xvect_b, dx_b = np.linspace(xL + dx / 2.0, xR - dx / 2.0, iMAX, retstep=True)
# Initial condition
solution = flx.shock(xvect_b, x0, qL, qR)
# plot the first solution for t = o
plt.ion()
fig = plt.figure()
ax = fig.add_subplot(111)
qL_limit, qR_limit = get_q_limit(qL, qR, ylimext)
# import pdb; pdb.set_trace()
# print xvect_b
# print prettyp(solution[:10])
line1, = ax.plot(xvect_b, solution, "o")
# plt.ylim( ( qL_limit, qR_limit ) )
for time, solution in ORDER[order](solution, dx, qL, qR, tSTART, tEND, courant, nummtd, solintmtd, maxiter=10000):
plt.pause(pause)
ax.clear()
# print xvect_b
# print prettyp(solution[:10])
plt.title("Current time t = {:6.5f}".format(time))
line1, = ax.plot(xvect_b, solution, "o")
xi = (xvect - x0) / time
line2, = ax.plot(xvect_b, [flx.nlers(qL, qR, xq) for xq in xi], "r-")
