17-2-anim

18/18-1.py

@@ -58,7 +58,7 @@ def shortest_path(array, start, end):
         for dx, dy in [(0, 1), (1, 0), (0, -1), (-1, 0)]:
             nx, ny = x + dx, y + dy
             if 0 <= nx < zeilen and 0 <= ny < spalten and array[nx][ny] == '.' and (nx, ny) not in visited:
-                queue.append(((nx, ny), pfad + [(nx, ny)]))
+                queue.append(((nx, ny), pfad + [(ny, nx)]))
                 visited.add((nx, ny))
 
     return -1, []  # Kein Pfad gefunden

18/18-2-anim.py

@@ -0,0 +1,135 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+import numpy as np
+from PIL import Image, ImageDraw, ImageFont
+import cv2
+from time import time
+from copy import deepcopy
+start_time = time()
+
+file = "./input.txt"
+XY_DIMENSION = 70
+FIRST_BYTES = 1024
+
+#file = "./ex.txt"
+#XY_DIMENSION = 6
+#FIRST_BYTES = 12
+
+
+out_file_name = "solution_10"
+GROW_FACTOR = 10
+
+fourcc = cv2.VideoWriter_fourcc(*'mp4v')
+fps = 30
+frame_size = ((XY_DIMENSION+1) * GROW_FACTOR, (XY_DIMENSION + 1) * GROW_FACTOR)
+out_mp4 = cv2.VideoWriter(f'./{out_file_name}.mp4', fourcc, fps, frame_size)
+gif_anim=[]
+
+
+
+def array_to_image(ar):
+    global GROW_FACTOR
+    # Konvertiere das Array in ein NumPy-Array
+    np_array = np.array(ar)
+    # Erstelle ein leeres RGB-Bild
+    height, width = np_array.shape
+    image = Image.new('RGB', (width * GROW_FACTOR, height * GROW_FACTOR))
+    # Fülle das Bild mit Pixeln basierend auf den Array-Werten
+    for y in range(height):
+        for x in range(width):
+            if np_array[y, x] == "#":
+                color = (200, 0, 0)
+            elif np_array[y, x] == "O":
+                color = (50, 200,50)
+            else:
+                color = (0,0,0)  # Standardfarbe schwarz
+            for dy in range(GROW_FACTOR):
+                for dx in range(GROW_FACTOR):
+                    image.putpixel((x * GROW_FACTOR + dx, y * GROW_FACTOR + dy), color)
+
+    return image
+
+def add_text_to_image(image, num):
+    draw = ImageDraw.Draw(image)
+    font = ImageFont.truetype("arial.ttf", 20)  # Wählen Sie eine Schriftart und Größe
+    draw.text((5,5), f"{num:04d}", fill=(255, 255, 255), font=font)  # Weißer Text
+    return image
+
+def pil_to_cv2(pil_image):
+    return cv2.cvtColor(np.array(pil_image), cv2.COLOR_RGB2BGR)
+
+
+def make_empty_grid(dimension:int)->list[list[str]]:
+    result = []
+    for _ in range(dimension+1):
+        result.append(["." for _ in range(dimension+1)])
+    return result
+
+def print_grid(f):
+    for r in f:
+        for s in r:
+            if s == 0:
+                print(".", end="")
+            else:
+                print(s, end="")
+        print()
+
+def fill_grid(gri:list[list[str]], ma:list[list[int]], filler:str)->list[list[str]]:
+    result = deepcopy(gri)
+    for m in ma:
+        x , y = m[0],m[1]
+        result[y][x] = filler
+    return result
+
+def read_input(input_file:str, ) -> list[list[int]]:
+    out = []
+    f = open(input_file, "r")
+    for line in f:
+        line = line.strip()
+        if line == "":
+            continue
+        else:
+            out.append(list(map(int,line.split(','))))
+    f.close()
+    return out
+from collections import deque
+
+def shortest_path(array, start, end):
+    zeilen, spalten = len(array), len(array[0])
+    visited = set()
+    queue = deque([(start, [start])])
+    while queue:
+        (x, y), pfad = queue.popleft()
+        if (x, y) == end:
+            return len(pfad) - 1, pfad
+        for dx, dy in [(0, 1), (1, 0), (0, -1), (-1, 0)]:
+            nx, ny = x + dx, y + dy
+            if 0 <= nx < zeilen and 0 <= ny < spalten and array[nx][ny] == '.' and (nx, ny) not in visited:
+                queue.append(((nx, ny), pfad + [(ny, nx)]))
+                visited.add((nx, ny))
+
+    return -1, []  # Kein Pfad gefunden
+
+
+if __name__ == "__main__":
+    grid = make_empty_grid(XY_DIMENSION)
+    corrupted = read_input(file)
+    for i in range(FIRST_BYTES, len(corrupted)):
+        g = fill_grid(grid,corrupted[:i],"#")
+        sp = shortest_path(g,(0,0),(XY_DIMENSION,XY_DIMENSION))
+        g_with_path = fill_grid(g, sp[1], "O")
+
+        img = array_to_image(g_with_path)
+        gif_anim.append(img)
+        cv2_image = pil_to_cv2(img)
+        out_mp4.write(cv2_image)
+        if sp[0] == -1:
+            print(f"First Blocking Field: {corrupted[:i][-1]}")
+            break
+
+    out_mp4.release()
+    gif_anim[0].save(f'./{out_file_name}.gif', save_all=True, append_images=gif_anim[1:],
+                     optimize=False, duration=30, loop=0)
+
+
+    print(f'Runtime: {time()-start_time:.4f} s')

18/18-2-anim2.py

@@ -0,0 +1,149 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+import numpy as np
+from PIL import Image, ImageDraw, ImageFont
+import cv2
+from time import time
+from copy import deepcopy
+start_time = time()
+
+file = "./input.txt"
+XY_DIMENSION = 70
+FIRST_BYTES = 1024
+
+#file = "./ex.txt"
+#XY_DIMENSION = 6
+#FIRST_BYTES = 12
+
+
+out_file_name = "solution_10_2"
+GROW_FACTOR = 10
+
+fourcc = cv2.VideoWriter_fourcc(*'mp4v')
+fps = 30
+frame_size = ((XY_DIMENSION+1) * GROW_FACTOR, (XY_DIMENSION + 1) * GROW_FACTOR)
+out_mp4 = cv2.VideoWriter(f'./{out_file_name}.mp4', fourcc, fps, frame_size)
+gif_anim=[]
+
+
+
+def array_to_image(ar):
+    global GROW_FACTOR
+    # Konvertiere das Array in ein NumPy-Array
+    np_array = np.array(ar)
+    # Erstelle ein leeres RGB-Bild
+    height, width = np_array.shape
+    image = Image.new('RGB', (width * GROW_FACTOR, height * GROW_FACTOR))
+    # Fülle das Bild mit Pixeln basierend auf den Array-Werten
+    for y in range(height):
+        for x in range(width):
+            if ist_zahl(np_array[y, x]):
+                r = np_array[y,x]
+                color = (135+(int(r)*4), 0, 100)
+                #print(int(r)+100)
+            elif np_array[y, x] == "#":
+                color = (255, 0, 0)
+            elif np_array[y, x] == "O":
+                color = (50, 200,50)
+            else:
+                color = (0,0,0)  # Standardfarbe schwarz
+            for dy in range(GROW_FACTOR):
+                for dx in range(GROW_FACTOR):
+                    image.putpixel((x * GROW_FACTOR + dx, y * GROW_FACTOR + dy), color)
+    return image
+
+def ist_zahl(zelle):
+    return np.issubdtype(zelle.dtype, np.number) or (isinstance(zelle.item(), str) and zelle.item().isdigit())
+
+def add_text_to_image(image, num):
+    draw = ImageDraw.Draw(image)
+    font = ImageFont.truetype("arial.ttf", 20)  # Wählen Sie eine Schriftart und Größe
+    draw.text((5,5), f"{num:04d}", fill=(255, 255, 255), font=font)  # Weißer Text
+    return image
+
+def pil_to_cv2(pil_image):
+    return cv2.cvtColor(np.array(pil_image), cv2.COLOR_RGB2BGR)
+
+
+def make_empty_grid(dimension:int)->list[list[str]]:
+    result = []
+    for _ in range(dimension+1):
+        result.append(["." for _ in range(dimension+1)])
+    return result
+
+def print_grid(f):
+    for r in f:
+        for s in r:
+            print(s, end="")
+        print()
+
+def fill_grid(gri:list[list[str]], ma:list[list[int]], filler:str)->list[list[str]]:
+    result = deepcopy(gri)
+    for m in ma:
+        x , y = m[0],m[1]
+        result[y][x] = filler
+    return result
+
+def fill_grid_2(gri: list[list[str]], ma: list[list[int]], filler: str) -> list[list[str]]:
+    result = deepcopy(gri)
+    # Fülle die ersten Einträge mit dem filler
+    for j, m in enumerate(ma[:-30]):
+        x, y = m[0], m[1]
+        result[y][x] = filler
+    # Fülle die letzten 155 Einträge mit Zahlen von 1 bis 155
+    for j, m in enumerate(ma[-30:], start=1):
+        x, y = m[0], m[1]
+        result[y][x] = str(j)
+    return result
+
+def read_input(input_file:str, ) -> list[list[int]]:
+    out = []
+    f = open(input_file, "r")
+    for line in f:
+        line = line.strip()
+        if line == "":
+            continue
+        else:
+            out.append(list(map(int,line.split(','))))
+    f.close()
+    return out
+from collections import deque
+
+def shortest_path(array, start, end):
+    zeilen, spalten = len(array), len(array[0])
+    visited = set()
+    queue = deque([(start, [start])])
+    while queue:
+        (x, y), pfad = queue.popleft()
+        if (x, y) == end:
+            return len(pfad) - 1, pfad
+        for dx, dy in [(0, 1), (1, 0), (0, -1), (-1, 0)]:
+            nx, ny = x + dx, y + dy
+            if 0 <= nx < zeilen and 0 <= ny < spalten and array[nx][ny] == '.' and (nx, ny) not in visited:
+                queue.append(((nx, ny), pfad + [(ny, nx)]))
+                visited.add((nx, ny))
+    return -1, []  # Kein Pfad gefunden
+
+
+if __name__ == "__main__":
+    grid = make_empty_grid(XY_DIMENSION)
+    corrupted = read_input(file)
+    for i in range(FIRST_BYTES, len(corrupted)):
+        g = fill_grid_2(grid,corrupted[:i],"#")
+        sp = shortest_path(g,(0,0),(XY_DIMENSION,XY_DIMENSION))
+        g_with_path = fill_grid(g, sp[1], "O")
+
+        img = array_to_image(g_with_path)
+        gif_anim.append(img)
+        cv2_image = pil_to_cv2(img)
+        out_mp4.write(cv2_image)
+        if sp[0] == -1:
+            print(f"First Blocking Field: {corrupted[:i][-1]}")
+            break
+
+    out_mp4.release()
+    gif_anim[0].save(f'./{out_file_name}.gif', save_all=True, append_images=gif_anim[1:],
+                     optimize=False, duration=30, loop=0)
+
+
+    print(f'Runtime: {time()-start_time:.4f} s')

18/18-2.py

@@ -1,5 +1,6 @@
 #!/usr/bin/env python3
 # -*- coding: utf-8 -*-
+from copy import deepcopy
 
 file = "./input.txt"
 XY_DIMENSION = 70
@@ -29,10 +30,11 @@ def print_grid(f):
         print()
 
 def fill_grid(gri:list[list[str]], ma:list[list[int]], filler:str)->list[list[str]]:
+    result = deepcopy(gri)
     for m in ma:
         x , y = m[0],m[1]
-        gri[y][x] = filler
+        result[y][x] = filler
-    return gri
+    return result
 
 def read_input(input_file:str, ) -> list[list[int]]:
     out = []
@@ -58,7 +60,7 @@ def shortest_path(array, start, end):
         for dx, dy in [(0, 1), (1, 0), (0, -1), (-1, 0)]:
             nx, ny = x + dx, y + dy
             if 0 <= nx < zeilen and 0 <= ny < spalten and array[nx][ny] == '.' and (nx, ny) not in visited:
-                queue.append(((nx, ny), pfad + [(nx, ny)]))
+                queue.append(((nx, ny), pfad + [(ny, nx)]))
                 visited.add((nx, ny))
 
     return -1, []  # Kein Pfad gefunden