made script for optimal circle compuation more general by allowing also other number of circles

master
Simon Pirkelmann 2019-08-27 11:38:04 +02:00
parent 3398f44be0
commit b0a658a7b7
30 changed files with 192 additions and 161 deletions

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# N (number of circles) | radius of enclosed circles (enclosing circle has radius of 1)
# source: http://www.packomania.com
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from casadi import *
import matplotlib.pyplot as plt
import math
import operator
file = open('tmp2019_cci_08_26_11_36_00.txt')
N = 7 # number of enclosed circles
# this function reads and processes data for optimal circle packaging obtained form packomania.com
def read_circle_data(N):
coords_raw = open('cci/cci{}.txt'.format(N))
radii_raw = open('cci/radii.txt'.format(N))
coords_raw = coords_raw.readlines()
coords_raw = [c.split() for c in coords_raw if c[0] != '#']
coords = {}
for c in coords_raw:
coords[int(c[0])] = (float(c[1]), float(c[2]))
coords = sort_ccw(coords, (0,0))
radii_raw = radii_raw.readlines()
radii_raw = [r.split() for r in radii_raw if r[0] != '#']
radii = {}
for r in radii_raw:
radii[int(r[0])] = float(r[1])
return radii[N], coords
# this function sorts enclosed circle coordinates counter-clockwise w.r.t. the center point
# TODO: there is a problem when circles are present that are not touching the boundary of the enclosing circle (e.g. N = 7)
def sort_ccw(coords, center):
a = {}
for c in coords:
a[c] = math.atan2(coords[c][1] - center[1], coords[c][0] - center[0])
a_sort = sorted(a.items(), key=operator.itemgetter(1))
coords_sort = []
for a in a_sort:
coords_sort.append(coords[a[0]])
return coords_sort
# read radius and center coordinates for enclosed circles
rtilde, coords = read_circle_data(N)
c = (0.0, 0.0) # center of big circle
R = 15.0 # radius of big circle
R = 1.0 # radius of big circle
# center for smaller circles
p1 = (-5.55287862, -7.64288174)
p2 = (5.55287862, -7.64288174)
p3 = (-8.98474635, 2.91932105)
p4 = (8.98474635, 2.91932105)
p5 = (0.00000000, 9.44712138)
rtilde = 5.5 # radius of smaller circles
points = [p1, p2, p3, p4, p5]
# midpoint between center of two circles
m = np.mean([p1, p2], axis=0)
# vector in direction of midpoint
v = m - np.array(c)
v = v/np.linalg.norm(v)
plt.xlim((-16, 16))
plt.ylim((-16, 16))
plt.xlim((-1, 1))
plt.ylim((-1, 1))
plt.gca().set_aspect('equal', 'box')
plt.ion()
plt.show()
for p in points:
for p in coords:
plt.plot(p[0], p[1], 'o')
circle = plt.Circle(p, rtilde, fill=False)
plt.gca().add_artist(circle)
circle = plt.Circle(c, R, fill=False)
plt.gca().add_artist(circle)
#plt.show()
plt.plot(c[0], c[1], 'o')
plt.plot(m[0], m[1], 'o')
opti = casadi.Opti()
for k in range(0, N):
p1 = coords[k]
p2 = coords[(k+1) % N]
r = opti.variable(1) # radius of new circle
p = opti.variable(2) # center of new circle
#v1 = opti.variable(2) # direction vector from
#v2 = opti.variable(2)
lamb = opti.variable(1)
# midpoint between center of two circles
m = np.mean([p1, p2], axis=0)
opti.minimize(-r)
opti.subject_to(p == c + v * lamb)
opti.subject_to((p[0] - p1[0])**2 + (p[1] - p1[1])**2 >= (rtilde + r)**2)
#opti.subject_to(p == (rtilde + r) * v1 + p1)
#opti.subject_to(p == (rtilde + r) * v2 + p2)
#opti.subject_to((v1[0]**2+v1[1]**2)**0.5 == 1)
#opti.subject_to((v2[0]**2+v2[1]**2)**0.5 == 1)
opti.subject_to(R == lamb + r)
opti.subject_to(r >= 0)
opti.subject_to(r <= R)
#opti.subject_to(lamb >= 0.6 * R)
# vector in direction of midpoint
v = m - np.array(c)
v = v/np.linalg.norm(v)
plt.plot(m[0], m[1], 'o')
opti.solver('ipopt')
opti = casadi.Opti()
init_r = 0.1
init_lamb = R - init_r
init_p = c + v * init_lamb
r = opti.variable(1) # radius of new circle
p = opti.variable(2) # center of new circle
lamb = opti.variable(1)
opti.minimize(-r)
opti.subject_to(p == c + v * lamb)
opti.subject_to((p[0] - p1[0])**2 + (p[1] - p1[1])**2 >= (rtilde + r)**2)
opti.subject_to(R == lamb + r)
opti.subject_to(r >= 0)
opti.subject_to(r <= R)
opti.set_initial(r, init_r)
opti.set_initial(p, init_p)
opti.set_initial(lamb, init_lamb)
#opti.set_initial(v1, )
opti.solver('ipopt')
sol = opti.solve()
init_r = 0.1
init_lamb = R - init_r
init_p = c + v * init_lamb
p = sol.value(p)
r = sol.value(r)
lamb = sol.value(lamb)
opti.set_initial(r, init_r)
opti.set_initial(p, init_p)
opti.set_initial(lamb, init_lamb)
print("p = {}".format(p))
print("r = {}".format(r))
print("lambda = {}".format(lamb))
print("v = {}".format(v))
sol = opti.solve()
plt.plot(p[0], p[1], 'o')
circle = plt.Circle(p, r, fill=False)
plt.gca().add_artist(circle)
plt.show()
p = sol.value(p)
r = sol.value(r)
lamb = sol.value(lamb)
print("p = {}".format(p))
print("r = {}".format(r))
print("lambda = {}".format(lamb))
print("v = {}".format(v))
plt.plot(p[0], p[1], 'o')
circle = plt.Circle(p, r, fill=False)
plt.gca().add_artist(circle)
pass

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