Develop Reference

Ellipse construction

I would like to construct an ellipse given the major/minor axes (or radii) and two points. I would like the line between the two points to be on the major axis. This just means that I would like the two points to lie on the major axis, and then construct the ellipse around the major axis. I originally constructed the ellipse at the origin and attempted to rotate and translate the ellipse, which didn't work. The unfinished code I have is listed below. How can I go about constructing an ellipse in this manner? Ideally, this would just return a list. Any insights would be greatly appreciated, and if you have any code for this please feel free to share.
import numpy
import matplotlib.pyplot as plt
import random
import math
from math import sin, cos
# Returns theta in [-pi/2, 3pi/2]
def generate_theta(a, b):
u = random.random() / 4.0
theta = numpy.arctan(b/a * numpy.tan(2*numpy.pi*u))
v = random.random()
if v < 0.25:
return theta
elif v < 0.5:
return numpy.pi - theta
elif v < 0.75:
return numpy.pi + theta
else:
return -theta
def radius(a, b, theta):
return a * b / numpy.sqrt((b*numpy.cos(theta))**2 + (a*numpy.sin(theta))**2)
def random_point(a, b, third_point, center=(0, 0)):
angle = None
if a > b:
random_theta = generate_theta(a, b)
max_radius = radius(a, b, random_theta)
random_radius = max_radius * numpy.sqrt(random.random())
f = round(random_radius * numpy.cos(random_theta))
s = round(random_radius * numpy.sin(random_theta))
angle = math.atan2(third_point[1], third_point[0]) - math.atan2(center[1], center[0])
else:
random_theta = generate_theta(b, a)
max_radius = radius(b, a, random_theta)
random_radius = max_radius * numpy.sqrt(random.random())
f = round(random_radius * numpy.cos(random_theta))
s = round(random_radius * numpy.sin(random_theta))
angle = math.atan2(third_point[1], third_point[0]) - math.atan2(center[1], center[0])
lio = rotate(center, (f, s), angle)
lio = (int(lio[0]), int(lio[1]))
return numpy.array([third, ward])
def rotate(origin, point, angle):
#Rotate a point counterclockwise by a given angle around a given origin.
#The angle should be given in radians.
x = origin[0] + cos(angle) * (point[0] - origin[0]) - sin(angle) * (point[1] - origin[1])
y = origin[1] + sin(angle) * (point[0] - origin[0]) + cos(angle) * (point[1] - origin[1])
return (x, y)
#height
a = 95
#length
b = 25
#rand_p = (-random.randint(300, 400), -random.randint(100, 300))
rand_p = (0, 0)
points = numpy.array([random_point(a, b, (100, 100), (-25, 0)) for _ in range(200)])
#rando = rotate((0, 0), right_most_point, angle)
iopoints = []
# t = x[0] - (int(centroid[0]) - 100)
# t2 = x[1] - (int(centroid[1]) - 100)
centroid = numpy.mean(points, axis=0)
print(centroid)
#plt.plot(rando[0], rando[1], 'ro')
plt.plot(rand_p[0], rand_p[1], 'ro')
plt.scatter(points[:,0], points[:,1])
plt.show()

class ELLIPSE:
def __init__(self, a, b, num_points, start, end):
self.a = a
self.b = b
self.num_points = num_points
self.start = start
self.end = end
self.angle_gen = math.atan2(self.end[1]-self.start[1], self.end[0]-self.start[0])
def generate_theta(self, a, b):
u = random.random() / 4.0
theta = np.arctan(self.b/self.a * np.tan(2*np.pi*u))
v = random.random()
if v < 0.25:
return theta
elif v < 0.5:
return np.pi - theta
elif v < 0.75:
return np.pi + theta
else:
return -theta
def radius(self, a, b, theta):
return self.a * self.b / np.sqrt((b*np.cos(theta))**2 + (a*np.sin(theta))**2)
def random_point(self, major_axis, minor_axis, center, qa):
random_theta = self.generate_theta(self.a, self.b)
max_radius = self.radius(self.a, self.b, random_theta)
random_radius = max_radius * np.sqrt(random.random())
f = round(random_radius * np.cos(random_theta))
s = round(random_radius * np.sin(random_theta))
lio = self.rotate((0, 0), (f, s), self.angle_gen)
return (int(lio[0]+center[0]), int(lio[1]+center[1]))
def rotate(self, origin, point, angle):
"""
Rotate a point counterclockwise by a given angle around a given origin.
The angle should be given in radians.
"""
ox, oy = origin
px, py = point
qx = ox + math.cos(angle) * (px - ox) - math.sin(angle) * (py - oy)
qy = oy + math.sin(angle) * (px - ox) + math.cos(angle) * (py - oy)
return qx, qy
def midpoint(self, p1, p2):
return ((p1[0]+p2[0])/2, (p1[1]+p2[1])/2)
def ret_list(self):
points = [self.random_point(self.a, self.b, self.midpoint(self.start, self.end), self.angle_gen) for _ in range(self.num_points)]
return points

How I can pass data of methods to others using oop, for example with numerical methods in python

This error appears, ValueError: setting an array element with a sequence. I did it without oop and work it nice. I need the data of def loop(self): to pass it to the def f(self, x, y): and keeping the secuence
class rungekuta():
def __init__(self):
self.x = np.linspace(1, 5, 50)
self.y = np.zeros(len(self.x))
self.y[0] = 4
self.loop()
self.f()
def f(self, x, y):
return (self.x*np.sqrt(self.y))
def loop(self):
h = 0.2
for i in range(len(self.x) - 1):
k1 = self.f(self.x[i], self.y[i])
k2 = self.f(self.x[i] + h / 2, self.y[i] + k1 * (h / 2))
k3 = self.f(self.x[i] + h / 2, self.y[i] + k2 * (h / 2))
k4 = self.f(self.x[i] + h, self.y[i] + k3 * h)
self.y[i+1] = self.y[i]+(h / 6) * (k1 + 2 * k2 + 2 * k3 + k4)
def draw(self):
plt.plot(self.x, self.y)
plt.show()
run = rungekuta()
run.draw()
This is the algorith without opp python
def f(x,y):
return (x*np.sqrt(y))
def rk4(f,a,b,y0,h):
x=np.arange(a,b,h)
n=len(x)
k1=np.zeros(len(x))
k2=np.zeros(len(x))
k3=np.zeros(len(x))
k4=np.zeros(len(x))
y=np.zeros(len(x))
y[0]=y0
for i in range(0,len(x)-1):
k1[i]=f(x[i],y[i])
k2[i]=f(x[i]+h/2,y[i]+k1[i]*(h/2))
k3[i]=f(x[i]+h/2,y[i]+k2[i]*(h/2))
k4[i]=f(x[i]+h,y[i]+k3[i]*h)
y[i+1]=y[i]+(h/6)*(k1[i]+2*k2[i]+2*k3[i]+k4[i])
plt.plot(x,y)
plt.show()
rk4(f,1,5,4,0.2)

All problem is method f() in class. It gets x, y and it should use x, y, not self.x, self.y.
And you should remove self.f() from __init__
import numpy as np
import matplotlib.pyplot as plt
class Rungekuta(): # PEP8: `CamerCaseNames` for classes
def __init__(self):
self.x = np.linspace(1, 5, 50)
self.y = np.zeros(len(self.x))
self.y[0] = 4
self.loop()
def f(self, x, y):
return (x * np.sqrt(y))
def loop(self):
h = 0.2
for i in range(len(self.x) - 1):
k1 = self.f(self.x[i], self.y[i])
k2 = self.f(self.x[i] + h / 2, self.y[i] + k1 * (h / 2))
k3 = self.f(self.x[i] + h / 2, self.y[i] + k2 * (h / 2))
k4 = self.f(self.x[i] + h, self.y[i] + k3 * h)
self.y[i+1] = self.y[i]+(h / 6) * (k1 + 2 * k2 + 2 * k3 + k4)
def draw(self):
plt.plot(self.x, self.y)
plt.show()
run = Rungekuta()
run.draw()
PEP 8 --- Style Guide for Python Code

Propagated Solution of Lambert Solver Leads to Wrong Orbit

Excuse me for the length of the title please but this is a pretty specific question. I'm currently simulating a launch of a rocket to mars in the 2022 launch window and I noticed that my rocket is a far distance away from Mars, even though it's traveling in the right direction. After simplifying my code to narrow down the problem, I simply plotted the orbits of the Earth and Mars (Using data from NASA's SPICE library) and propagated the position and velocity given to me by the lambert solver I implemented (Universal variables) to plot the final orbit of the rocket.
I'm only letting the Sun's gravity effect the rocket, not the Earth or Mars, to minimize my problem space. Yet even though I've simplified my problem so far, the intersection between Mars' and my rocket's orbits happens well before the time of flight has been simulated all the way, and the minimum distance between the two bodies is more than a million kilometers at all times.
That being said, something must be wrong but I cannot find the problem. I've made sure the lambert solver code I copied is correct by comparing it to Dario Izzo's method and both gave the same results. Furthermore, I've also checked that my orbit propagator works by propagating Mars' and the Earth's orbits and comparing those ellipses to the data from SPICE.
In conclusion, I assume this must be a stupid little mistake I made somewhere, but cannot find because I lack experience in this field. Thank you for any help! :)
This is the JupyterLab notebook I used:
import numpy as np
import matplotlib.pyplot as plt
import json
import math
import spiceypy as spice
# Physics
G = 6.6741e-11
class Entity:
def __init__(self, x, v, m, do_gravity):
self.x = x
self.v = v
self.a = np.array([0,0,0])
self.m = m
self.do_gravity = do_gravity
def apply_force(self, f):
self.a = np.add(self.a, f / self.m);
def step(self, dt):
self.v = np.add(self.v, self.a * dt)
self.x = np.add(self.x, self.v * dt)
self.a = np.array([0,0,0])
class StaticEntity(Entity):
def __init__(self, body, t, do_gravity):
super().__init__(self.get_state(body, t)[:3], self.get_state(body, t)[3:], self.get_mass(body), do_gravity)
self.body = body
self.t = t
def step(self, dt):
self.t += dt
state = self.get_state(self.body, self.t)
self.x = state[:3]
self.v = state[3:]
#classmethod
def get_state(self, body, t):
[state, lt] = spice.spkezr(body, t, "J2000", "NONE", "SSB")
return state * 1000
#classmethod
def get_mass(self, body):
[dim, gm] = spice.bodvrd(body, "GM", 1)
return gm * 1e9 / G
def get_position(self, t):
return self.get_state(self.body, t)[:3]
def get_velocity(self, t):
return self.get_state(self.body, t)[3:]
class Propagator:
def __init__(self, entities):
self.entities = entities
def step(self, dt):
for e1 in self.entities:
for e2 in self.entities:
if (e1 is e2) or (not e1.do_gravity) or isinstance(e2, StaticEntity):
continue
diff = np.subtract(e1.x, e2.x)
fg = G * e1.m * e2.m / np.dot(diff, diff)
force = fg * diff / np.linalg.norm(diff)
e2.apply_force(force)
for entity in self.entities:
entity.step(dt)
# Lambert solver
def C2(psi):
if psi >= 0.0:
sp = math.sqrt(psi)
return (1 - math.cos(sp)) / psi
else:
sp = math.sqrt(-psi)
return (1 - math.cosh(sp)) / psi
def C3(psi):
if psi >= 0.0:
sp = math.sqrt(psi)
return (sp - math.sin(sp)) / (psi * sp)
else:
sp = math.sqrt(-psi)
return (sp - math.sinh(sp)) / (psi * sp)
def lambert_solve(r1, r2, tof, mu, iterations, tolerance):
R1 = np.linalg.norm(r1)
R2 = np.linalg.norm(r2)
cos_a = np.dot(r1, r2) / (R1 * R2)
A = math.sqrt(R1 * R2 * (1.0 + cos_a))
sqrt_mu = math.sqrt(mu)
if A == 0.0:
return None
psi = 0.0
psi_lower = -4.0 * math.pi * math.pi
psi_upper = 4.0 * math.pi * math.pi
c2 = 1.0 / 2.0
c3 = 1.0 / 6.0
for i in range(iterations):
B = R1 + R2 + A * (psi * c3 - 1.0) / math.sqrt(c2)
if A > 0.0 and B < 0.0:
psi_lower += math.pi
B = -B
chi = math.sqrt(B / c2)
chi3 = chi * chi * chi
tof_new = (chi3 * c3 + A * math.sqrt(B)) / sqrt_mu
if math.fabs(tof_new - tof) < tolerance:
f = 1.0 - B / R1
g = A * math.sqrt(B / mu)
g_dot = 1.0 - B / R2
v1 = (r2 - f * r1) / g
v2 = (g_dot * r2 - r1) / g
return (v1, v2)
if tof_new <= tof:
psi_lower = psi
else:
psi_upper = psi
psi = (psi_lower + psi_upper) * 0.5
c2 = C2(psi)
c3 = C3(psi)
return None
# Set up solar system
spice.furnsh('solar_system.tm')
inject_time = spice.str2et('2022 Sep 28 00:00:00')
exit_time = spice.str2et('2023 Jun 1 00:00:00')
sun = StaticEntity("Sun", inject_time, True)
earth = StaticEntity("Earth", inject_time, False)
mars = StaticEntity("Mars Barycenter", inject_time, False)
(v1, v2) = lambert_solve(earth.get_position(inject_time), mars.get_position(exit_time), exit_time - inject_time, G * sun.m, 1000, 1e-4)
rocket = Entity(earth.x, v1, 100000, False)
propagator = Propagator([sun, earth, mars, rocket])
# Generate data
earth_pos = [[], [], []]
mars_pos = [[], [], []]
rocket_pos = [[], [], []]
t = inject_time
dt = 3600 # seconds
while t < exit_time:
propagator.step(dt)
earth_pos[0].append(earth.x[0])
earth_pos[1].append(earth.x[1])
earth_pos[2].append(earth.x[2])
mars_pos[0].append(mars.x[0])
mars_pos[1].append(mars.x[1])
mars_pos[2].append(mars.x[2])
rocket_pos[0].append(rocket.x[0])
rocket_pos[1].append(rocket.x[1])
rocket_pos[2].append(rocket.x[2])
t += dt
# Plot data
plt.figure()
plt.title('Transfer orbit')
plt.xlabel('x-axis')
plt.ylabel('y-axis')
plt.plot(earth_pos[0], earth_pos[1], color='blue')
plt.plot(mars_pos[0], mars_pos[1], color='orange')
plt.plot(rocket_pos[0], rocket_pos[1], color='green')
EDIT:
I recently remodeled my code so that it uses orbit class to represent the entities. This actually gave me acceptable results, even though the code is, in theory, not doing anything differently (as far as I can tell; obviously something must be different)
def norm(a):
return np.dot(a, a)**0.5
def fabs(a):
return -a if a < 0 else a
def newton_raphson(f, f_dot, x0, n):
res = x0
for i in range(n):
res = res - f(res) / f_dot(res)
return res
def get_ephemeris(body, time):
state, _ = sp.spkezr(body, time, "J2000", "NONE", "SSB")
return np.array(state[:3]) * ap.units.km, np.array(state[3:]) * ap.units.km / ap.units.s
def get_mu(body):
_, mu = sp.bodvrd(body, "GM", 1)
return mu * ap.units.km**3 / ap.units.s**2
class orbit:
def __init__(self, position, velocity, mu):
self.position = position
self.velocity = velocity
self.mu = mu
#staticmethod
def from_body(name, center, time):
return static_orbit(name, center, time)
def get_ephemerides(self, t, dt):
time = 0
positions = []
velocities = []
#M = self.M
position = self.position
velocity = self.velocity
delta_t = dt * ap.units.s
t1 = t * ap.units.s
while time < t1:
g = self.mu / np.dot(position, position)
g_vec = g * -position / norm(position)
velocity = np.add(velocity, g_vec * delta_t)
position = np.add(position, velocity * delta_t)
positions.append(position)
velocities.append(velocity)
time = time + delta_t
return positions, velocities
class static_orbit(orbit):
def __init__(self, name, center, time):
p, v = get_ephemeris(name, time)
pc, vc = get_ephemeris(center, time)
super().__init__(p - pc, v - vc, get_mu(center))
self.name = name
self.center = center
self.time = time
def get_ephemerides(self, t, dt):
time = 0
positions = []
velocities = []
while time < t:
p, v = get_ephemeris(self.name, time + self.time)
pc, vc = get_ephemeris(self.center, time + self.time)
positions.append(p - pc)
velocities.append(v - vc)
time += dt
return positions, velocities
sp.furnsh('solar_system.tm')
t1 = sp.str2et('2022 Sep 28 00:00:00')
t2 = sp.str2et('2023 Jun 10 00:00:00')
eo = orbit.from_body("Earth", "Sun", t1)
mo = orbit.from_body("Mars Barycenter", "Sun", t1)
earth_x, earth_v = eo.get_ephemerides(t2 - t1, 3600)
mars_x, mars_v = mo.get_ephemerides(t2 - t1, 3600)
l = lambert(earth_x[0], mars_x[-1], t2 - t1, get_mu("Sun"), 1000, 1e-6)
ro = orbit(earth_x[0], l.v1, get_mu("Sun"))
rocket_x, rocket_v = ro.get_ephemerides(t2 - t1, 60)
earth_x = np.array(earth_x)
mars_x = np.array(mars_x)
rocket_x = np.array(rocket_x)
fig = go.Figure()
fig.add_trace(go.Scatter3d(x=earth_x[:,0], y=earth_x[:,1], z=earth_x[:,2], marker_size=1, marker_color='blue'))
fig.add_trace(go.Scatter3d(x=mars_x[:,0], y=mars_x[:,1], z=mars_x[:,2], marker_size=1, marker_color='orange'))
fig.add_trace(go.Scatter3d(x=rocket_x[:,0], y=rocket_x[:,1], z=rocket_x[:,2], marker_size=1, marker_color='green'))
fig.show()
This method generated following plot:
Also, before this is mentioned again, I have varied my integration step size and lambert solver tolerance to no avail, the result was qualitatively different.

So, I managed to figure out what the problem was after much head-scratching. I was simply not taking into account that the Sun is not located at (0,0,0) in my coordinate system. I thought this was negligible, but that is what made the difference. In the end, I simply passed the difference between the Earth and Mars's and the Sun's position vectors and passed those into the Lambert solver. This finally gave me the desired results.
The reason that the error ended up being so "small" (It didn't seem like an obvious bug at first) was because my coordinates are centered at the solar system barycenter which is a few million kilometers away from the Sun, as one would expect.
Thanks for the comments!

split step Fourier method in Python

Sorry that this post is long but I am trying to simulate two dimensional Schrodinger equation in python using split-step method.
One dimensional problem of this equation has been explained in this post:
https://jakevdp.github.io/blog/2012/09/05/quantum-python/
I tried adding another dimension and modified the operators following the above post but I am confused as how to plot the psi function now that I added another dimension, here is my modified class equation by adding and extra dimension, I also modified the helper functions now that I added extra dimension:
import numpy as np
from scipy.fftpack import fft, ifft
class Schrodinger(object):
def __init__(self, x,y,psi_x0,psi_y0,V_x,V_y,k0=None, hbar=1, m=1, t0=0.0):
self.x,self.y,psi_x0,psi_y0,self.V_x,V_y=map(np.asarray(x,y,psi_x0,psi_y0,V_x,V_y))
N=self.x.size
assert self.x.shape==(N,)
assert self.y.shape==(N,)
assert psi_x0.shape==(N,)
assert self.V_x.shape==(N,)
assert self.V_y.shape==(N,)
self.hbar = hbar
self.m = m
self.t = t0
self.dt_ = None
self.N = len(x)
self.dx=self.x[1]-self.x[0]
self.dy=self.y[1]-self.y[0]
self.dk = 2 * np.pi / (self.N * self.dx)
if k0 == None:
self.k0 = -0.5 * self.N * self.dk
else:
self.k0 = k0
self.k = self.k0 + self.dk * np.arange(self.N)
self.psi_x = psi_x0
self.psi_y=psi_y0
self.compute_k_from_x()
self.compute_k_from_y()
self.x_evolve_half = None
self.x_evolve = None
self.y_evolve_half = None
self.y_evolve = None
self.k_evolve = None
self.psi_x_line = None
self.psi_y_line = None
self.psi_k_line = None
self.V_x_line = None
self.V_y_line = None
def _set_psi_x(self,psi_x):
self.psi_mode_x=(psi_x*np.exp(-1j*self.k[0]*self.x)*self.dx/np.sqrt(2*np.pi))
def _get_psi_x(self):
return (self.psi_mode_x*np.exp(1j*self.k[0])*np.sqrt(2*np.pi)/self.dx)
def _set_psi_y(self,psi_y):
self.psi_mode_y=(psi_y*np.exp(-1j*self.k[0]*self.y)*self.dy/np.sqrt(2*np.pi))
def _get_psi_y(self):
return (self.psi_mode_y*np.exp(1j*self.k[0])*np.sqrt(2*np.pi)/self.dy)
def _set_psi_k_x(self,psi_k_x):
self.psi_mode_k_x=psi_k_x*np.exp(1j*self.x[0]*self.dk*np.arange(self.N))
def _get_psi_k_x(self):
return self.psi_mode_k_x*np.exp(-1j*self.x[0]*self.dk*np.arange(self.N))
def _set_psi_k_y(self,psi_k_y):
self.psi_mode_k_y=psi_k_y*np.exp(1j*self.y[0]*self.dk*np.arange(self.N))
def _get_psi_k_y(self):
return self.psi_mode_k_y*np.exp(-1j*self.y[0]*self.dk*np.arange(self.N))
def _get_dt(self):
return self.dt_
def _set_dt(self,dt):
if dt!=self.dt_:
self.dt_=dt
self.x_evolve_half=np.exp(-0.5*1j*self.V_x/self.hbar*dt)
self.y_evolve_half=np.exp(-0.5*1j*self.V_y/self.hbar*dt)
self.x_evolve=self.x_evolve_half*self.x_evolve_half
self.y_evolve=self.y_evolve_half*self.y_evolve_half
self.k_evolve=np.exp(-0.5*1j*self.hbar/self.m*(self.k*self.k)*dt)
psi_x=property(_get_psi_x,_set_psi_x)
psi_y=property(_get_psi_y,_set_psi_y)
psi_k_x=property(_get_psi_k_x,_set_psi_k_x)
psi_k_y=property(_get_psi_k_y,_set_psi_k_y)
dz=property(_get_dt,_set_dt)
def compute_k_from_x(self):
self.psi_mode_k_x=fft(self.psi_mode_x)
def compute_k_from_y(self):
self.psi_mode_k_y=fft(self.psi_mode_y)
def compute_x_from_k(self):
self.psi_mode_x=ifft(self.psi_mode_k_x)
def compute_y_from_k(self):
self.psi_mode_y=ifft(self.psi_mode_k_y)
def time_step(self,dt,Nsteps=1):
self.dt=dt
if Nsteps>0:
self.psi_mode_x*=self.x_evolve_half
self.psi_mode_y*=self.y_evolve_half
for i in range(Nsteps-1):
self.compute_k_from_x()
self.compute_k_from_y()
self.psi_mode_k_x*=self.k_evolve
self.psi_mode_k_y*=self.k_evolve
self.compute_x_from_k()
self.compute_y_from_k()
self.psi_mode_x*=self.x_evolve
self.psi_mode_y*=self.y_evolve
self.compute_k_from_x()
self.compute_k_from_y()
self.psi_mode_k_x*=self.k_evolve
self.psi_mode_k_y*=self.k_evolve
self.compute_x_from_k()
self.psi_mode_x*=self.x_evolve_half
self.compute_y_from_k()
self.psi_mode_y*=self.y_evolve_half
self.compute_k_from_x()
self.compute_k_from_y()
self.t+=dt*Nsteps
def gauss_x(x, a, x0, k0):
return ((a*np.sqrt(np.pi))**(-0.5)* np.exp(-0.5*((x-x0)* 1./a)**2 +1j*x*k0))
def gauss_y(y, a, y0, k0):
return ((a*np.sqrt(np.pi))**(-0.5)* np.exp(-0.5*((y-y0)* 1./a)**2 +1j*y*k0))
def gauss_k_x(k,a,x0,k0):
return ((a/np.sqrt(np.pi))**0.5* np.exp(-0.5*(a*(k- k0))** 2- 1j*(k- k0)*x0))
def gauss_k_y(k,a,y0,k0):
return ((a/np.sqrt(np.pi))**0.5* np.exp(-0.5*(a*(k- k0))** 2- 1j*(k- k0)*y0))
def theta(x):
x = np.asarray(x)
y = np.zeros(x.shape)
y[x > 0] = 1.0
return y
def square_barrier(x, width, height):
return height * (theta(x) - theta(x - width))
dt = 0.01
N_steps = 50
t_max = 120
frames = int(t_max / float(N_steps * dt))
hbar = 1.0
m = 1.9
N = 2 ** 11
dx = 0.1
dy=0.1
x = dx * (np.arange(N) - 0.5 * N)
y = dy * (np.arange(N) - 0.5 * N)
V0 = 1.5
L = hbar / np.sqrt(2 * m * V0)
a = 3 * L
x0 = -60 * L
y0 = -60 * L
V_x = square_barrier(x, a, V0)
V_y = square_barrier(y, a, V0)
V_x[x < -98] = 1E6
V_x[x > 98] = 1E6
V_y[y < -98] = 1E6
V_y[y > 98] = 1E6
p0 = np.sqrt(2 * m * 0.2 * V0)
dp2 = p0 * p0 * 1./80
d = hbar / np.sqrt(2 * dp2)
k0 = p0 / hbar
v0 = p0 / m
psi_x0 = gauss_x(x, d, x0, k0)
psi_y0 = gauss_y(y, d, y0, k0)
S =Schrodinger(x=x,y=y,psi_x0=psi_x0,psi_y0=psi_y0,V_x=V,V_y=V_y,hbar=hbar,m=m,k0=-28)
the code for one-dimensional plot and the animation is as below:
from matplotlib import pyplot as pl
from matplotlib import animation
fig = pl.figure()
xlim = (-100, 100)
klim = (-5, 5)
ymin = 0
ymax = V0
ax1 = fig.add_subplot(211, xlim=xlim,
ylim=(ymin - 0.2 * (ymax - ymin),
ymax + 0.2 * (ymax - ymin)))
psi_x_line, = ax1.plot([], [], c='r', label=r'$|\psi(x)|$')
V_x_line, = ax1.plot([], [], c='k', label=r'$V(x)$')
center_line = ax1.axvline(0, c='k', ls=':',
label = r"$x_0 + v_0t$")
title = ax1.set_title("")
ax1.legend(prop=dict(size=12))
ax1.set_xlabel('$x$')
ax1.set_ylabel(r'$|\psi(x)|$')
ymin = abs(S.psi_k).min()
ymax = abs(S.psi_k).max()
ax2 = fig.add_subplot(212, xlim=klim,
ylim=(ymin - 0.2 * (ymax - ymin),
ymax + 0.2 * (ymax - ymin)))
psi_k_line, = ax2.plot([], [], c='r', label=r'$|\psi(k)|$')
p0_line1 = ax2.axvline(-p0 / hbar, c='k', ls=':', label=r'$\pm p_0$')
p0_line2 = ax2.axvline(p0 / hbar, c='k', ls=':')
mV_line = ax2.axvline(np.sqrt(2 * V0) / hbar, c='k', ls='--',
label=r'$\sqrt{2mV_0}$')
ax2.legend(prop=dict(size=12))
ax2.set_xlabel('$k$')
ax2.set_ylabel(r'$|\psi(k)|$')
V_x_line.set_data(S.x, S.V_x)
# Animate plot
def init():
psi_x_line.set_data([], [])
V_x_line.set_data([], [])
center_line.set_data([], [])
psi_k_line.set_data([], [])
title.set_text("")
return (psi_x_line, V_x_line, center_line, psi_k_line, title)
def animate(i):
S.time_step(dt, N_steps)
psi_x_line.set_data(S.x, 4 * abs(S.psi_x))
V_x_line.set_data(S.x, S.V_x)
center_line.set_data(2 * [x0 + S.t * p0 / m], [0, 1])
psi_k_line.set_data(S.k, abs(S.psi_k))
title.set_text("t = %.2f" % S.t)
return (psi_x_line, V_x_line, center_line, psi_k_line, title)
anim = animation.FuncAnimation(fig, animate, init_func=init,
frames=frames, interval=30, blit=True)
pl.show()

Intersection between bezier curve and a line segment

I am writing a game in Python (with pygame) that requires me to generate random but nice-looking "sea" for each new game. After a long search I settled on an algorithm that involves Bezier curves as defined in padlib.py. I now need to figure out when the curves generated by padlib intersect a line segment.
The brute force method would be to just use the set of approximating line segments produced by padlib to find the answer. However, I suspect that a better answer can be found analytically. I only have a few dozen spline segments - searching them should be faster than thousand of line segments.
A little search took me down this road: Bezier Curve -> Kochanek-Bartels Spline -> Cubic Hermite spline
On the last page, I found this function:
p(t) = h00(t)p0 + h10(t)m0 + h01(t)p1 + h11(t)m1
where p(t) is a actually a point (2-dimensional vector), hij(t) functions are cubic polynomials, p0, p1, m0 and m1 are points I can get from padlib code.
Now, I can see that the solution to my problem is p(t) = u + v * t1, where u and v are the end of my line segment.
However, working out the analytical solution is beyond me. Does anyone here know of an existing solution? Or can help me with solving the equations?

As a rough outline, rotate and translate the system so that the line segment lies on the X axis. Now the y coordinate is a cubic function of the parameter t. Find the 'zeros' (the analytic formulae will be found in good math texts or wikipedia). Now evaluate the x coordinates corresponding to those zero points and test against your line segment.

I've finally got to a working code to illustrate the method suggested by Mark Thornton. Below is the Python code for the intersection routine, together with pygame code to test it visually. The cubic roots solution can be written based on this question.
import pygame
from pygame.locals import *
import sys
import random
from math import sqrt, fabs, pow
from lines import X, Y
import itertools
import pygame
from pygame import draw, Color
import padlib
from roots_detailed import cubicRoots
def add_points(*points):
X = 0
Y = 0
for (x,y) in points:
X += x
Y += y
return (X,Y)
def diff_points(p2, p1):
# p2 - p1
return (X(p2)-X(p1), Y(p2)-Y(p1));
def scale_point(factor, p):
return (factor * X(p), factor*Y(p))
def between(v0, v, v1):
if v0 > v1: v0, v1 = v1, v0
return v >= v0 and v <= v1
# the point is guaranteed to be on the right line
def pointOnLineSegment(l1, l2, point):
return between(X(l1), X(point), X(l2)) and between(Y(l1), Y(point), Y(l2))
def rotate(x, y, R1, R2, R3, R4):
return (x*R1 + y*R2, x*R3 + y * R4);
def findIntersections(p0, p1, m0, m1, l1, l2):
# We're solving the equation of one segment of Kochanek-Bartels
# spline intersecting with a line segment
# The spline is described at http://en.wikipedia.org/wiki/Cubic_Hermite_spline
# The discussion on the adopted solution can be found at https://stackoverflow.com/questions/1813719/intersection-between-bezier-curve-and-a-line-segment
#
# The equation we're solving is
#
# h00(t) p0 + h10(t) m0 + h01(t) p1 + h11(t) m1 = u + v t1
#
# where
#
# h00(t) = 2t^3 - 3t^2 + 1
# h10(t) = t^3 - 2t^2 + t
# h01(t) = -2t^3 + 3t^2
# h11(t) = t^3 - t^2
# u = l1
# v = l2-l1
u = l1
v = diff_points(l2, l1);
# The first thing we do is to move u to the other side:
#
# h00(t) p0 + h10(t) m0 + h01(t) p1 + h11(t) m1 - u = v t1
#
# Then we're looking for matrix R that would turn (v t1) into
# ({|v|, 0} t1). This is rotation of coordinate system matrix,
# described at http://mathworld.wolfram.com/RotationMatrix.html
#
# R(h00(t) p0 + h10(t) m0 + h01(t) p1 + h11(t) m1 - u) = R(v t1) = {|v|, 0}t1
#
# We only care about R[1,0] and R[1,1] because it lets us solve
# the equation for y coordinate where y == 0 (intersecting the
# spline segment with the x axis of rotated coordinate
# system). I'll call R[1,0] = R3 and R[1,1] = R4 .
v_abs = sqrt(v[0] ** 2 + v[1] ** 2)
R1 = X(v) / v_abs
R2 = Y(v) / v_abs
R3 = -Y(v) / v_abs
R4 = X(v) / v_abs
# The letters x and y are denoting x and y components of vectors
# p0, p1, m0, m1, and u.
p0x = p0[0]; p0y = p0[1]
p1x = p1[0]; p1y = p1[1]
m0x = m0[0]; m0y = m0[1]
m1x = m1[0]; m1y = m1[1]
ux = X(u); uy = Y(u)
#
#
# R3(h00(t) p0x + h10(t) m0x + h01(t) p1x + h11(t) m1x - ux) +
# + R4(h00(t) p0y + h10(t) m0y + h01(t) p1y + h11(t) m1y - uy) = 0
#
# Opening all parentheses and simplifying for hxx we get:
#
# h00(t) p0x R3 + h10(t) m0x R3 + h01(t) p1x R3 + h11(t) m1x R3 - ux R3 +
# + h00(t) p0y R4 + h10(t) m0y R4 + h01(t) p1y R4 + h11(t) m1y R4 - uy R4 = 0
#
# h00(t) p0x R3 + h10(t) m0x R3 + h01(t) p1x R3 + h11(t) m1x R3 - ux R3 +
# + h00(t) p0y R4 + h10(t) m0y R4 + h01(t) p1y R4 + h11(t) m1y R4 - uy R4 = 0
#
# (1)
# h00(t) (p0x R3 + p0y R4) + h10(t) (m0x R3 + m0y R4) +
# h01(t) (p1x R3 + p1y R4) + h11(t) (m1x R3 + m1y R4) - (ux R3 + uy R4) = 0
#
# We now introduce new substitution
K00 = p0x * R3 + p0y * R4
K10 = m0x * R3 + m0y * R4
K01 = p1x * R3 + p1y * R4
K11 = m1x * R3 + m1y * R4
U = ux * R3 + uy * R4
# Expressed in those terms, equation (1) above becomes
#
# h00(t) K00 + h10(t) K10 + h01(t) K01 + h11(t) K11 - U = 0
#
# We will now substitute the expressions for hxx(t) functions
#
# (2t^3 - 3t^2 + 1) K00 + (t^3 - 2t^2 + t) K10 + (-2t^3 + 3t^2) K01 + (t^3 - t^2) K11 - U = 0
#
# 2 K00 t^3 - 3 K00 t^2 + K00 +
# + K10 t^3 - 2 K10 t^2 + K10 t -
# - 2 K01 t^3 + 3 K01 t^2 +
# + K11 t^3 - K11 t^2 - U = 0
#
# 2 K00 t^3 - 3 K00 t^2 + 0t + K00
# + K10 t^3 - 2 K10 t^2 + K10 t
# - 2 K01 t^3 + 3 K01 t^2
# + K11 t^3 - K11 t^2 + 0t - U = 0
#
# (2 K00 + K10 - 2K01 + K11) t^3
# +(-3 K00 - 2K10 + 3 K01 - K11) t^2
# + K10 t
# + K00 - U = 0
#
#
# (2 K00 + K10 - 2K01 + K11) t^3 + (-3 K00 - 2K10 + 3 K01 - K11) t^2 + K10 t + K00 - U = 0
#
# All we need now is to solwe a cubic equation
valuesOfT = cubicRoots((2 * K00 + K10 - 2 * K01 + K11),
(-3 * K00 - 2 * K10 + 3 * K01 - K11),
(K10),
K00 - U)
# We can then put the values of it into our original spline segment
# formula to find the potential intersection points. Any point
# that's on original line segment is an intersection
def h00(t): return 2 * t**3 - 3 * t**2 + 1
def h10(t): return t**3 - 2 * t**2 + t
def h01(t): return -2 * t**3 + 3 * t**2
def h11(t): return t**3 - t**2
intersections = []
for t in valuesOfT:
if t < 0 or t > 1.0: continue
# point = h00(t) * p0 + h10(t) * m0 + h01(t) * p1 + h11(t) * m1
point = add_points(
scale_point(h00(t), p0),
scale_point(h10(t), m0),
scale_point(h01(t), p1),
scale_point(h11(t), m1)
)
if pointOnLineSegment(l1, l2, point): intersections.append(point)
return intersections
def findIntersectionsManyCurves(p0_array, p1_array, m0_array, m1_array, u, v):
result = [];
for (p0, p1, m0, m1) in itertools.izip(p0_array, p1_array, m0_array, m1_array):
result.extend(findIntersections(p0, p1, m0, m1, u, v))
return result
def findIntersectionsManyCurvesManyLines(p0, p1, m0, m1, points):
result = [];
for (u,v) in itertools.izip(*[iter(points)]*2):
result.extend(findIntersectionsManyCurves(p0, p1, m0, m1, u, v))
return result
class EventsEmitter(object):
def __init__(self):
self.consumers = []
def emit(self, eventName, *params):
for method in self.consumers:
funcName = method.im_func.func_name if hasattr(method, "im_func") else method.func_name
if funcName == eventName:
method(*params)
def register(self, method):
self.consumers.append(method)
def unregister(self, method):
self.consumers.remove(method)
class BunchOfPointsModel(EventsEmitter):
def __init__(self):
EventsEmitter.__init__(self)
self.pts = []
def points(self):
return self.pts.__iter__()
def pointsSequence(self):
return tuple(self.pts)
def have(self, point):
return point in self.pts
def addPoint(self,p):
self.pts.append(p)
self.emit("pointsChanged", p)
def replacePoint(self, oldP, newP):
idx = self.pts.index(oldP)
self.pts[idx] = newP
self.emit("pointsChanged", newP)
def removePoint(self, p):
self.point.remove(p)
self.emit("pointsChanged", p)
class BunchOfPointsCompositeModel(object):
def __init__(self, m1, m2):
self.m1 = m1
self.m2 = m2
def points(self):
return itertools.chain(self.m1.points(), self.m2.points())
def have(self, point):
return self.m1.have(point) or self.m2.have(point)
def replacePoint(self, oldP, newP):
if self.m1.have(oldP):
self.m1.replacePoint(oldP, newP)
else:
self.m2.replacePoint(oldP, newP)
def removePoint(self, p):
if self.m1.have(p):
self.m1.removePoint(p)
else:
self.m2.removePoint(p)
def register(self, method):
self.m1.register(method)
self.m2.register(method)
def unregister(self, method):
self.m1.unregister(method)
self.m2.unregister(method)
class BunchOfPointsDragController(EventsEmitter):
def __init__(self, model):
EventsEmitter.__init__(self)
self.model = model
self.draggedPoint = None
def mouseMovedTo(self, x,y):
if self.draggedPoint != None:
newPoint = (x,y)
draggedPoint = self.draggedPoint
self.draggedPoint = newPoint
self.model.replacePoint(draggedPoint, newPoint)
def buttonDown(self, x,y):
if self.draggedPoint == None:
closePoint = self.getCloseEnoughPoint(x,y)
if closePoint != None:
self.draggedPoint = closePoint
self.emit("dragPointChanged",closePoint)
def buttonUp(self, x,y):
self.mouseMovedTo(x,y)
self.draggedPoint = None
self.emit("dragPointChanged", None)
def getCloseEnoughPoint(self, x,y):
minSquareDistance = 25
closestPoint = None
for point in self.model.points():
dx = X(point) - x
dy = Y(point) - y
distance = dx*dx + dy*dy
if minSquareDistance > distance:
closestPoint = point
minSquareDistance = distance
return closestPoint
def isDraggedPoint(self, p):
return p is self.draggedPoint
class CurvesLinesViewPointsView(object):
def __init__(self, screen, modelCurves, modelLines, model, controller):
self.screen = screen
self.modelLines = modelLines
self.modelCurves = modelCurves
self.controller = controller
controller.register(self.dragPointChanged)
model.register(self.pointsChanged)
def draw(self):
self.screen.fill(Color("black"))
pygame.draw.lines(self.screen, Color("cyan"), 0, self.modelLines.pointsSequence(), 3)
(p0, p1, m0, m1) = padlib.BezierCurve(screen,modelCurves.pointsSequence(),3,100,Color("magenta"))
self.drawPointSet(self.modelCurves.points(),
lambda(p):self.controller.isDraggedPoint(p),
Color("white"), Color("red"))
self.drawPointSet(self.modelLines.points(),
lambda(p):self.controller.isDraggedPoint(p),
Color("lightgray"), Color("red"))
self.drawSimplePointSet(findIntersectionsManyCurvesManyLines(p0, p1, m0, m1,self.modelLines.points()),
Color("blue"))
def drawSimplePointSet(self, points, normalColor):
self.drawPointSet(points, lambda(p):True, None, normalColor);
def drawPointSet(self, points, specialPoint, normalColor, specialColor):
for p in points:
if specialPoint(p):
draw.circle(self.screen, specialColor, p, 6)
else:
draw.circle(self.screen, normalColor, p, 2)
pygame.display.update()
def dragPointChanged(self, p): self.draw()
def pointsChanged(self, p): self.draw()
class PygameEventsDistributor(EventsEmitter):
def __init__(self):
EventsEmitter.__init__(self)
def processEvent(self, e):
if e.type == MOUSEMOTION:
self.emit("mouseMovedTo", e.pos[0], e.pos[1])
elif e.type == MOUSEBUTTONDOWN:
self.emit("buttonDown", e.pos[0], e.pos[1])
elif e.type == MOUSEBUTTONUP:
self.emit("buttonUp", e.pos[0], e.pos[1])
modelLines = BunchOfPointsModel()
modelCurves = BunchOfPointsModel()
model = BunchOfPointsCompositeModel(modelLines, modelCurves);
controller = BunchOfPointsDragController(model)
distributor = PygameEventsDistributor()
distributor.register(controller.mouseMovedTo)
distributor.register(controller.buttonUp)
distributor.register(controller.buttonDown)
pygame.init()
screen = pygame.display.set_mode((640, 480))
modelCurves.addPoint((29,34))
modelCurves.addPoint((98,56))
modelCurves.addPoint((200, 293))
modelCurves.addPoint((350, 293))
modelLines.addPoint((23,123))
modelLines.addPoint((78,212))
view = CurvesLinesViewPointsView(screen, modelCurves, modelLines, model, controller)
keepGoing = True
try:
while (keepGoing):
for event in pygame.event.get():
if event.type == QUIT:
keepGoing = False
break
distributor.processEvent(event)
pass
finally:
pygame.quit()