import numpy as np
from scipy.integrate import odeint
from scipy.misc import derivative
from scipy.interpolate import interp1d
import matplotlib.pyplot as plt
global r, n, Psi, Fi, X, XX

LST = open("schrodinger-2b.txt", "wt")

def U(x):
    if abs(x) < L:
      if x < 0:
        return U0 - x/L
      else:
        return U0 + x/L
    else:
        return W

def q(e, x):
  return 2.0*(e-U(x))

def system1(cond1, X):
  global eee
  Y0, Y1 = cond1[0], cond1[1]
  dY0dX = Y1
  dY1dX = -q(eee, X)*Y0
  return [dY0dX, dY1dX]

def system2 (cond2, XX):
  global eee
  Z0, Z1 = cond2[0], cond2[1]
  dZ0dX = Z1
  dZ1dX = -q(eee, XX) *Z0
  return [dZ0dX, dZ1dX]

def f_fun (e):
  global r, n, Psi, Fi, X, XX, eee
  eee = e
  cond1 = [0.0, 1.0]
  sol1 = odeint(system1, cond1, X)
  Psi, Psi1 = sol1[:, 0], sol1[:, 1]
  cond2 = [0.0, 1.0]
  sol2 = odeint(system2, cond2, XX)
  Fi, Fi1 = sol2[:, 0], sol2[:, 1]
  p1 = np. abs(Psi).max()
  p2 = np.abs(Psi).min()
  big = p1 if p1 > p2 else p2
  Psi[:] = Psi[:]/big
  coef = Psi[r]/Fi[rr]
  Fi[:] = coef * Fi[:]
  curve1 = interp1d(XX, Psi, kind='cubic')
  curve2 = interp1d(XX, Fi, kind='cubic')
  der1 = derivative(curve1, X[r], dx=1.e-6)
  der2 = derivative(curve2, XX[rr], dx=1.e-6)
  f = der1 - der2
  return f

def m_bis(x1, x2, tol):
  global r, n
  if f_fun(e=x2) * f_fun(e=x1) > 0.0:
    print("ERROR: no root!!!")
    print("x1=", x1)
    print("x2=", x2)
    print("f_fun(e=x1, r=r, n=n)=", f_fun(e=x1))
    print("f_fun(e=x2, r=r, n=n)=", f_fun(e=x2))
    exit()
  while abs(x2-x1) > tol:
    xr = (x1 + x2)/2.0
    if f_fun(e=x2) * f_fun(e=xr) < 0.0:
      x1 = xr
    else:
      x2 = xr
    if f_fun (e=x1) * f_fun (e=xr) < 0.0:
      x2 = xr
    else:
      x1 = xr
  return (x1 + x2)/2.0

def plotting_f():
  plt.axis([U0, e2, fmin, fmax])
  ZeroE = np.zeros(ne, dtype=float)
  plt.plot(ee, ZeroE, 'k-', linewidth=1.0)
  plt.plot(ee, af, 'bo', markersize=2)
  for i in range (nroots):
    plt.plot([energy[i]], [0.0], color='red', marker='*', markersize=10)
  plt.xlabel("E", fontsize=18, color="k")
  plt.ylabel("f(E)", fontsize=18, color="k")
  plt.grid(True)
  plt.savefig('schrodinger-2b-f.pdf', dpi=300)
  plt.show()

def plotting_wf(e):
    global r, n, Psi, Fi, X, XX
    ff = f_fun(e)
    plt.axis([A, B, U0, W])
    Upot = np.array([U(X[i]) for i in np.arange(n)])
    plt.plot(X, Upot, 'g-', linewidth=6.0, label="U(x)")
    Zero = np.zeros(n, dtype=float)
    plt.plot(X, Zero, 'k-', linewidth=1.0)
    plt.plot(X, Psi, 'r-', linewidth=2.0, label="Psi(x)")
    plt.plot(XX, Fi, 'b-', linewidth=2.0, label="Fi(x)")
    plt.xlabel("X", fontsize=18, color="k")
    plt.ylabel("Psi(x), Fi(x), U(x)", fontsize=18, color="k")
    plt.grid(True)
    plt.legend(fontsize=16, shadow=True, fancybox=True, loc='upper right')
    plt.plot([X[r]], [Psi[r]], color='red', marker='o', markersize=7)
    string1 = "E   = " + format(e, "10.7f")
    string2 = "f(E) = " + format(ff, "10.3e")
    plt.text(-1.5, 2.7, string1, fontsize=14, color='black')
    plt.text(-1.5, 2.3, string2, fontsize=14, color='black')
    name = f"wavefunction_{e:.5f}.png"
    plt.savefig(name, dpi=300)
    plt.show()

L = 2.0
A = -L
B = +L
n = 1001
print("n=", n)
print("n=", n, file=LST)
U0 = -1.0
W = 4.0
X = np.linspace(A, B, n)
XX = np.linspace(B, A, n)
r = (n-1)*3//4
rr = n-r-1
print("r", r)
print("r", r, file=LST)
print("rr=", rr)
print("rr", rr, file=LST)
print("X[r]=", X[r])
print("X[r]=", X[r], file=LST)
print("XX[rr]=", XX[rr])
print("XX[rr]=", XX[rr], file=LST)
e1 = U0+0.05
e2 = 3.0
print("e1=", e1, "   e2=", e2)
print("e1=", e1, "   e2=", e2, file=LST)
ne = 101
print("ne=", ne)
print("ne=", ne, file=LST)
ee = np.linspace(e1, e2, ne)
af = np.zeros(ne, dtype=float)
porog = 5.0
tol = 1.0e-7
energy = []
ngr = 0
for i in np.arange(ne):
  e = ee[i]
  af[i] = f_fun(e)
  stroka = "i = {:3d}   e = {:8.5f}  f[e] = {:12.5e}"
  print(stroka.format(i, e, af[i]))
  print(stroka.format(i, e, af[i]), file=LST)
  if i > 0:
    Log1 = af[i] * af[i-1] < 0.0
    Log2 = np.abs(af[i] - af[i-1]) < porog
    if Log1 and Log2:
      energy1 = ee[i-1]
      energy2 = ee[i]
      eval = m_bis(energy1, energy2, tol)
      print("eval = {:12.5e}".format(eval))
      dummy = plotting_wf(eval)
      energy.append(eval)
      ngr += 1
nroots = len(energy)
print("nroots =", nroots)
print("nroots =", nroots, file=LST)
for i in np.arange(nroots):
  stroka = "i = {:1d}    energy[i] = {:12.5e}"
  print(stroka.format(i, energy [i]))
  print(stroka.format(i, energy [i]), file=LST)
fmax = +10.0
fmin = -10.0
dummy = plotting_f()

решить то же самое но методом пристрелки