feat(map-generator): mountain-agent for generating mountains

This commit is contained in:
Mahdi Dibaiee 2019-04-14 12:19:54 +04:30
parent 3cd25bb458
commit 8d4010b5dc

View File

@ -1,22 +1,35 @@
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import colors, cm
import scipy.interpolate as interpolate
from scipy import ndimage
import math
WIDTH = 900
HEIGHT = 450
RATIO = WIDTH / HEIGHT
MAX_ELEVATION = 100
MOUNTAIN_SEA_DISTANCE = 50
MOUNTAIN_SEA_THRESHOLD = 2
MOUNTAIN_JAGGEDNESS = 1
CONTINENT_MAX_TRIALS = 1e4
MOUNTAIN_RATIO = 0.3
SEA_COLOR = np.array((53, 179, 220, 255)) / 255
SHARPNESS = 0.7
WATER_LEVEL = 0
MAX_ELEVATION = 30
GROUND_NOISE = 15
WATER_PROPORTION = 0.6
GROUND_PROPORTION = 1 - WATER_PROPORTION
DIRECTIONS = [(-1, -1), (-1, 0), (-1, 1), (1, 1), (1, 0), (1, -1), (0, -1), (0, 1)]
def s(x):
# return x
return -2 * x**3 + 3 * x**2
WATER_LEVEL = 0
WATER_PROPORTION = 0.4
GROUND_PROPORTION = 1 - WATER_PROPORTION
# class Point(object):
# def __init__(self, x, y, z):
# self.x = x
@ -32,6 +45,11 @@ GROUND_PROPORTION = 1 - WATER_PROPORTION
def is_ground(value):
return value > WATER_LEVEL
def in_range(p, m, size):
x, y = p
mx, my = m
return ((x - mx)**2 + (y - my)**2) < size
def max_recursion(fn, max_recursion=0):
def f(*args, recursion=0, **kwargs):
if recursion > max_recursion:
@ -39,35 +57,134 @@ def max_recursion(fn, max_recursion=0):
return fn(*args, **kwargs)
def bound_check(ground, point):
x, y = point
w, h = ground.shape
x = max(min(x, w - 1), 0)
y = max(min(y, h - 1), 0)
return (x, y)
def continent_agent(ground, position, size):
if size <= 0: return
x, y = position
w, h = ground.shape
trials = 0
while True:
if size <= 0: break
if size <= 0 or trials > CONTINENT_MAX_TRIALS: break
dx = np.random.randint(2) or -1
dy = np.random.randint(2) or -1
x = max(min(x + dx, w - 1), 0)
y = max(min(y + dy, h - 1), 0)
r = np.random.randint(3)
new_point = bound_check(ground, (x + dx, y + dy))
if r == 0:
x = new_point[0]
elif r == 1:
y = new_point[1]
else:
x, y = new_point
if not is_ground(ground[x, y]):
if not is_ground(ground[x, y]) and in_range((x, y), position, size):
trials = 0
size -= 1
ground[x, y] = 1
ground[x, y] = np.random.randint(1, GROUND_NOISE)
else:
trials += 1
def neighbours(ground, position, radius):
x, y = position
return ground[x-radius:x+radius+1, y-radius:y+radius+1]
def away_from_sea(ground, position, radius=MOUNTAIN_SEA_DISTANCE):
ns = neighbours(ground, position, radius).flatten()
sea = len([1 for x in ns if not is_ground(x)])
return sea < MOUNTAIN_SEA_THRESHOLD
MOUNTAIN_AREA_ELEVATION = 0.4
MOUNTAIN_AREA_ELEVATION_N = 5
MOUNTAIN_AREA_ELEVATION_AREA = 10
def random_elevate_agent(ground, position, height, size=MOUNTAIN_AREA_ELEVATION_N):
position = position + np.random.random_integers(-MOUNTAIN_AREA_ELEVATION_AREA, MOUNTAIN_AREA_ELEVATION_AREA, size=2)
for i in range(size):
d = DIRECTIONS[np.random.randint(len(DIRECTIONS))]
change = height * MOUNTAIN_AREA_ELEVATION + np.random.randint(MOUNTAIN_JAGGEDNESS + 1)
new_index = bound_check(ground, position + np.array(d))
if is_ground(ground[new_index]):
ground[new_index] += change
def mountain_agent(ground, position):
if not away_from_sea(ground, position):
return
x, y = position
height = np.random.randint(MAX_ELEVATION)
ground[x, y] = height
last_height = height
for i in range(1, height):
for d in DIRECTIONS:
change = np.random.randint(MOUNTAIN_JAGGEDNESS + 1)
distance = np.array(d)*i
new_index = bound_check(ground, position + distance)
if is_ground(ground[new_index]):
ground[new_index] = last_height - change
last_height = last_height - MOUNTAIN_JAGGEDNESS
random_elevate_agent(ground, position, height)
# takes an initial position and a list of (direction, probability) tuples to walk on
# def split_agent(ground, position, directions):
def constant_filter(a):
if a[0] > (1 - SHARPNESS):
return max(1, a[0])
return 0
def generate_map(width, height, continents=4):
ground = np.zeros((width, height))
ground_size = width * height * GROUND_PROPORTION
# position = (int(width / 2), int(height / 2))
# ground_size = width * height * GROUND_PROPORTION
# continent_agent(ground, position, size=ground_size)
for continent in range(continents):
position = (np.random.randint(0, width), np.random.randint(0, height))
size = np.random.randint(width * height * GROUND_PROPORTION / continents)
print(size)
continent_agent(ground, position, size=size)
print(position)
continent_agent(ground, position, size=ground_size)
plt.imshow(ground.T, cmap='hot')
ground = ndimage.gaussian_filter(ground, sigma=(1 - SHARPNESS) * 20)
for i in range(int(ground_size * MOUNTAIN_RATIO / MAX_ELEVATION**2)):
position = (np.random.randint(0, width), np.random.randint(0, height))
mountain_agent(ground, position)
norm = colors.Normalize(vmin=1)
greys = cm.get_cmap('Greys')
greys.set_under(color=SEA_COLOR)
ground = ndimage.gaussian_filter(ground, sigma=4)
ground = ndimage.generic_filter(ground, constant_filter, size=1)
print(np.min(ground), np.max(ground), MAX_ELEVATION)
print(np.unique(ground))
plt.imshow(ground.T, cmap=greys, norm=norm)
plt.show()