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

map-generator/index.py

@@ -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()