Files
caveclusters/generate.py
T
2023-11-18 18:04:31 +01:00

169 lines
4.4 KiB
Python
Executable File

#/usr/bin/python
import random
import math
import time
import matplotlib.pyplot as plt
fig = plt.figure()
def plotShit(points, centroids=None):
"""splits dimensions for matplotlib, scatterplots it"""
if dim >= 2:
x = [point[0] for point in points]
y = [point[1] for point in points]
if centroids:
xc = [point[0] for point in centroids]
yc = [point[1] for point in centroids]
if dim >= 3:
threedplot = fig.add_subplot(projection='3d')
z = [point[2] for point in points]
threedplot.scatter(x, y, z)
if centroids:
zc = [point[1] for point in centroids]
threedplot.scatter(xc, yc, zc, s=190.0)
else:
plot = fig.add_subplot()
plot.scatter(x, y)
if centroids:
plot.scatter(xc, yc)
plt.show()
def printPixels(pixels):
print(chr(27) + "[2J") #Clear
print('┌' + '─'*len(pixels[0])+'┐', flush=False)
for row in pixels:
print('│', end='', flush=False)
for cell in row:
print((' ' if cell == 0 else f'\033[{31+cell}m{cell}\033[0m'), end='', flush=False)
print('│')
print('└' + '─'*len(pixels[0])+'┘', flush=False)
n = 2000 # initial points
dim = 2 # in 2 of 3 dimensies. Alleen zinnig voor 2, maar werkt ook voor 3
k = 4 # aantal clusters/kamers
domains = [(0,1000)]*dim
points = [tuple(round(random.uniform(lb, ub),2) for lb, ub in domains) for _ in range(n)]
centroids = random.sample(points, k)
epochs = 0
while epochs < 5:
dists = [tuple(math.dist(p, c) for c in centroids) for p in points]
point_cluster_index = list(map(lambda x: x.index(min(x)), dists))
points_per_cluster = [[p for i, p in enumerate(points) if point_cluster_index[i] == j] for j in range(k)]
centroids = [tuple(sum(col) / float(len(col)) for col in zip(*points_per_cluster[i])) for i in range(k)]
epochs += 1
#print(points)
#print(centroids)
#print(dists)
#print(point_cluster_index)
#print(points_per_cluster)
#print("---")
#plotShit(points, centroids)
width= 320
height = 48
#pixels=[[0]*width]*height #kut python
pixels=[[0]*width for _ in range(height)] # aanspreken als pixels[y][x] (rows columns, verwarrend).
# map cluster centers to pixels:
cluster_pixels = [(int(c[0]/domains[0][1]*width), int(c[1]/domains[1][1]*height))for c in centroids]
for i, c in enumerate(cluster_pixels):
pixels[c[1]][c[0]] = i+1
epochs = 0
while epochs < width*height/200:
for i, c in enumerate(cluster_pixels):
for y, row in enumerate(pixels):
for x, cell in enumerate(row):
if cell == i+1:
nx = x-random.randrange(-1,2) # randrange heeft non-inclusive upperbound. leuk.
ny = y-random.randrange(-1,2)
if nx >= 0 and ny >= 0 and nx < width and ny < height and pixels[ny][nx] == 0:
pixels[ny][nx] = i+1
epochs += 1
printPixels(pixels)
def checknb(x,y,v):
if x > 0:
if pixels[y][x-1] not in [v, 0]:
return True
if y > 0:
if pixels[y-1][x-1] not in [v, 0]:
return True
if x > 0:
if pixels[y-1][x-1] not in [v, 0]:
return True
if x < width-1:
if pixels[y][x+1] not in [v, 0]:
return True
if y < height-1:
if pixels[y+1][x] not in [v, 0]:
return True
if x < width-1:
if pixels[y+1][x+1] not in [v, 0]:
return True
return False
# Edging the caves
nb = 1
while nb > 0:
nb = 0
for y, row in enumerate(pixels):
for x, cell in enumerate(row):
if cell != 0:
if checknb(x,y,cell):
nb += 1
pixels[y][x] = 0
printPixels(pixels)
#centroid distances
c_dists = [[math.dist(p, c) for c in centroids] for p in centroids]
edges = []
print(centroids)
for i, cdist in enumerate(c_dists):
f = [x if x > 0 else 99999999 for x in cdist]
m = min(f)
one = f.index(m)
f[one] = 9999999
print(f"Centroid {i+1} is closest to centroid {one+1}")
m = min(f)
two = f.index(m)
edges.append((one, two))
print(f"Centroid {i+1} is second closest to centroid {two+1}")
print(cluster_pixels)
def draw(x0, y0, x1, y1):
dx = x1 - x0
dy = y1 - y0
D = 2*dy - dx
y = y0
#for x from x0 to x1
for x in range(x0-1, x1+1):
if pixels[y][x] <= 0:
pixels[y][x] = 9
#plot(x, y)
if D > 0:
y = y + 1
D = D - 2*dx
D = D + 2*dy
print(edges)
# draw edges:
for i, edge in enumerate(edges):
print(f"drawing edges for cluster {i+1}. To {edge[0]+1} and {edge[1]+1}")
draw(
cluster_pixels[edge[0]][0],
cluster_pixels[edge[0]][1],
cluster_pixels[i][0],
cluster_pixels[i][1])
draw(
cluster_pixels[edge[1]][0],
cluster_pixels[edge[1]][1],
cluster_pixels[i][0],
cluster_pixels[i][1])
printPixels(pixels)
#cluster_pixels = [(int(c[0]/domains[0][1]*width), int(c[1]/domains[1][1]*height))for c in centroids]