tstop = N * dt
tcoor = linspace(0, t, step)
S = array(S[:len(tcoor)])
Y = w(tcoor) - L - S - b / 2. # (w, L, b are global vars.)
plot(tcoor, Y)
# Default values
m = 1
b = 2
L = 10
k = 1
beta = 0
S0 = 1
dt = 2 * pi / 40
g = 9.81
w_formula = '0'
N = 200
m, b, L, k, beta, S0, dt, g, w, N = \
init_prms(m, b, L, k, beta, S0, dt, g, w_formula, N)
w.vectorize(globals()) # w must work with arrays in plot_S
S = solve(m, k, beta, S0, dt, g, w, N, user_action=plot_S)
# Make hardcopy of last plot of S
hardcopy('tmp_S.eps') # or savefig('tmp_S.eps')
tcoor = linspace(0, t, step+1) # t = dt*step
S = array(S[:len(tcoor)])
Y = w(tcoor) - L - S - b/2.0 # (w, L, b are global vars.)
plot(tcoor, Y,
axis=[0, N*dt, min(Y), max(Y)],
xlabel='time', ylabel='Y')
# Default values
m = 1; b = 2; L = 10; k = 1; beta = 0; S0 = 1
dt = 2*pi/40; g = 9.81; w_formula = '0'; N = 200
m, b, L, k, beta, S0, dt, g, w, N = \
init_prms(m, b, L, k, beta, S0, dt, g, w_formula, N)
# Vectorize the StringFunction w
w_formula = str(w) # keep this to see if w=0 later
if ' else ' in w_formula:
w = vectorize(w) # general vectorization
else:
w.vectorize(globals()) # more efficient (when no if)
S = solve(m, k, beta, S0, dt, g, w, N, user_action=plot_S)
# First make a hardcopy of the the last plot of Y
hardcopy('tmp_Y.eps')
# Make plots of several additional interesting quantities
tcoor = linspace(0, tstop, N+1)