def run():
dim = 2
_a = mkarray((dim, ))
nr = _a(50)
rmin = _a(0)
rmax = _a(1, 2)
dr = (rmax - rmin) / (nr - 1)
bounds = [rmin, rmax]
_p = np.zeros(nr)
_b = np.zeros(nr)
_r = [np.linspace(0, s, n) for s, n in zip(bounds[1], nr)]
# source
nx, ny = nr
_b[int(nx / 4), int(ny / 4)] = 100
_b[int(3 * nx / 4), int(3 * ny / 4)] = -100
poisson(_p, _b, dr)
plot_2D(_r, _p)
pyplot.show()
p = np.zeros(nr)
nt = 100
return solve(nt, (u, v), dt, dr, p, rho, nu)
def plot_field(X, Y, p, uv):
u, v = uv
fig = pyplot.figure(figsize=(11, 7), dpi=100)
pyplot.contour(X, Y, p, alpha=0.5, cmap=cm.viridis)
pyplot.colorbar()
pyplot.contour(X, Y, p, cmap=cm.viridis)
# pyplot.quiver(X[::2, ::2], Y[::2, ::2], u[::2, ::2], v[::2, ::2])
pyplot.streamplot(X, Y, u, v)
pyplot.xlabel('X')
pyplot.ylabel('Y')
dim = 2
_a = _lib.mkarray((dim,))
nr = _a(41)
rmin = _a(0)
rmax = _a(2)
dr = (rmax - rmin)/(nr - 1)
r = _lib.linspaces([rmin, rmax], nr)
R = np.meshgrid(*r)
if __name__ == '__main__':
uv, p = run(nr, dr)
plot_field(*R, p, uv)
pyplot.show()
# 2D linear convection
import math
import numpy as np
from matplotlib import pyplot, cm
from mpl_toolkits.mplot3d import Axes3D ##New Library required for projected 3d plots
import _lib
from _lib import plot, compare, wall_boundary
# def v(*a): return np.array(a)
v = _lib.mkarray((2, ))
# constants
wall = (1)
rbox = [v(0), v(2)]
num_r = v(11)
num_t = 100
c = 1
dr = rbox[1] / (num_r - 1)
sigma = 0.2
dt = sigma * np.prod(dr)
dx, dy = dr
# iterative
def _step_it(u):
u = u.copy()
for n in range(num_t):
un = u.copy()
row, col = u.shape