r = 18
h = 1.7
num_of_steps = 1000
emp = 3
time = np.arange(0, 100, 1)
phi = []
theta = []
Amp = np.pi/8
fphi = 4
ftheta = 2
pics = []
for j in time:
kampas = np.radians(2*np.pi*fphi*j)
kitaskampas = Amp*(np.sin(np.radians(2*np.pi*ftheta*j)))
phi.append(kampas)
theta.append(kitaskampas)
#this loop creates two lists of angles theta and phi in time
x = r * np.cos(phi)
y = r * np.sin(phi) * np.cos(theta) - h * np.sin(theta)
z = r * np.sin(phi) * np.sin(theta) + h * np.cos(theta)
#calculating lists of x, y and z coordinates
points = [x, y, z]
points = np.transpose(points)
#adding the x, y and z coordinates into a list and transposing it so that
#while iterating through it, i would get x, y and z
n = len(points)
# Calculate the first and second derivative of the
points
dX = np.apply_along_axis(np.gradient, axis=0,
arr=points)
ddX = np.apply_along_axis(np.gradient, axis=0, arr=dX)
# Normalize all tangents
f = lambda m: m / np.linalg.norm(m)
T = np.apply_along_axis(f, axis=1, arr=dX)
# Calculate and normalize all binormals
B = np.cross(dX, ddX)
B = np.apply_along_axis(f, axis=1, arr=B)
# Calculate all normals
N = np.cross(B, T)
for t in range(len(theta)):
fig = plt.figure('Parametrinai blynai')
ax = fig.add_subplot(111, projection='3d')
ax.clear()
ax.plot(x[1:t], y[1:t], z[1:t], '-r', linewidth=3)
ax.azim = 0
ax.dist = 10
ax.elev = 25
#plotting the frame and the point at each index and setting the view of the plot
ax.set_xlabel('X', fontweight='bold', fontsize=14)
ax.set_ylabel('Y', fontweight='bold', fontsize=14)
ax.set_zlabel('Z', fontweight='bold', fontsize=14)
ax.set_xlim([-20, 20])
ax.set_ylim([-20, 20])
ax.set_zlim([-10, 10])
plt.title('Parametrinis blynas', fontweight='bold', fontsize=16)
ax.quiver(x[t - 1], y[t - 1], z[t - 1], emp * T[t, 0], emp * T[t, 1], emp * T[t, 2], color='r')#raudona
ax.quiver(x[t - 1], y[t - 1], z[t - 1], emp * B[t, 0], emp * B[t, 1], emp * B[t, 2], color='b')#melyna
ax.quiver(x[t - 1], y[t - 1], z[t - 1], emp * N[t, 0], emp * N[t, 1], emp * N[t, 2], color='g')#zalia
#plotting the three little coordinate axes that follow the point
I have this code that produces a point, following a trajectory and three coordinate axes that follow that point and rotate accordingly to the "points" matrix. I am trying to incorporate this code:
point = np.array([1, 2, 3])
normal = np.array([1, 1, 2])
# a plane is a*x+b*y+c*z+d=0
# [a,b,c] is the normal. Thus, we have to calculate
# d and we're set
d = -point.dot(normal)
x = np.linspace(0, 5, 20)
y = np.linspace(0, 5, 20)
# create x,y
xx, yy = np.meshgrid(range(5), range(5))
print(yy)
#print(yy)
# calculate corresponding z
z = (-normal[0] * xx - normal[1] * yy - d) * 1. /normal[2]
# plot the surface
plt3d = plt.figure().gca(projection='3d')
plt3d.plot_surface(xx, yy, z)
plt.show()
to plot a circle, perpendicular to the blue coordinate line on top of the original plot. In the perfect scenario that circle also tilts according to the movement of the point a.k.a. according to angle theta and variable h. Any ideas on how to make this work? All my attempts have been too far off.
