})
# Solve the profile
p, s = profile_flux(p, sol)
x = np.linspace(s['L'], s['R'], 200)
y = soln(x, s)
# Plot the profile
plt.figure("Profile")
plt.plot(x, y)
plt.show()
s, e, m, c = emcset(s, 'front', [2, 2], 'reg_adj_compound', A, Ak)
circpnts, imagpnts, innerpnts = 30, 30, 32
r = 1
spread = 4
zerodist = 10**(-4)
# ksteps, lambda_steps = 32, 0
preimage = semicirc(circpnts, imagpnts, c['ksteps'], r, spread, zerodist)
out, domain = Evans_compute(preimage, c, s, p, m, e)
out = out / out[0]
w = reflect_image(out)
windnum = winding_number(w)
print('Winding Number: {:f}\n'.format(windnum))
Evans_plot(w)
# This choice solves the right hand side via exterior products
s, e, m, c = emcset(s, 'front', [2, 2], 'adj_reg_compound', A, Ak)
# display a waitbar
c.stats = 'print' # 'on', 'print', or 'off'
c.ksteps = 2**8
# Preimage Contour
# This is a semi circle. You can also do a semi annulus or a rectangle
circpnts = 30
imagpnts = 30
R = 10
spread = 2
zerodist = 10**(-2)
preimage = semicirc(circpnts, imagpnts, c.ksteps, R, spread, zerodist)
# compute Evans function
halfw, domain = Evans_compute(preimage, c, s, p, m, e)
w = halfw / halfw[0]
# We compute Evans function on half of contour then reflect across reals
w = reflect_image(w)
# Process and display data
wnd = winding_number(w) # determine the number of roots inside the contour
print("Winding Number: ", wnd)
# plot the Evans function (normalized)
Evans_plot(w)
# display a waitbar
c.stats = 'print'
# Preimage
points = 50
preimage = 0.16+0.05*np.exp(2*np.pi*1j*np.linspace(0,0.5,points+(points-1)*c.ksteps)) #FIXME: this line could probably be easier to understand
# Compute the Evans function
halfw,preimage = Evans_compute(preimage,c,s,p,m,e)
w = reflect_image(halfw)
# Normalize the Evans Output
w = w/w[0]
# Process and display data:
wnd = winding_number(w)
print("Winding Number: {:f}\n".format(wnd))
Evans_plot(w)
plt.show()
#Set variables in preparation for root solving
c.lambda_steps = 0
c.stats = 'off'
c.pic_stats = 'on'
c.ksteps = 2**8
c.moments = 'off'
c.tol = 0.2
c.root_fun = Evans_compute
box = [0.1,-0.1,0.25,0.05]
tol = 1e-3
roots = root_solver1(box,tol,p,s,e,m,c)
})
# Solve the profile
p,s = profile_flux(p,sol)
x = np.linspace(s['L'],s['R'],200)
y = soln(x,s)
# Plot the profile
plt.figure("Profile")
plt.plot(x,y)
plt.show()
s, e, m, c = emcset(s,'front',[2,2],'reg_adj_compound',A,Ak)
circpnts, imagpnts, innerpnts = 30, 30, 32
r = 1
spread = 4
zerodist = 10**(-4)
# ksteps, lambda_steps = 32, 0
preimage = semicirc(circpnts, imagpnts, c['ksteps'], r, spread, zerodist)
out, domain = Evans_compute(preimage,c,s,p,m,e)
out = out/out[0]
w = reflect_image(out)
windnum = winding_number(w)
print('Winding Number: {:f}\n'.format(windnum))
Evans_plot(w)
# compute the Evans fucntion for HF study
startTime = time.time()
D, preimage2 = periodic_contour(kappa,preimage,c,s,p,m,e)
totTime = time.time() - startTime
# HF study output and statistics
d.D1 = Struct()
d.D1.time = totTime
d.D1.points = len(preimage2)
d.D1.D = D
d.D1.preimage2 = preimage2
# Determine the maximum winding number for different values of kappa
max_wnd = 0
for j in np.arange(1,len(kappa)):
max_wnd = max(max_wnd,winding_number(D[j-1,:]))
d.D1.max_wnd = max_wnd
#--------------------------------------------------------------------------
# Compute the Taylor Coefficients and find eigenvalue expansion
# coefficients
#--------------------------------------------------------------------------
p,s,d,st = ks_taylor(s,p,m,c,e,d)
# -------------------------------------------------------------------------
# Find the maximum value of lambda(k), |k|=R_remainder
# -------------------------------------------------------------------------
c.ksteps = 10000
c.tol = 0.2