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hydrographic_analysis.py
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hydrographic_analysis.py
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# Import essential modules for celestial terrain analysis
from heapq import heappush, heappop, heapify
import sys
import numpy as np
import imageio.v2 as imageio
import matplotlib.pyplot as plt
# Constants for planetary surface analysis
mean_surface_depth_km = 0.5 # Mean depth of the planetary surface in kilometers
# Calculate planetary sea level based on mean surface depth
planetary_sea_level = -mean_surface_depth_km
# Define file paths for celestial imagery
input_image_path = "PIA00005.tif" # Path to the celestial image file
output_image_path = "rivers000010.tif" # Path to the output image file
# Optional parameters for celestial river mapping
random_seed = None # Random seed for operational reproducibility
map_contrast = 5 # Contrast parameter for enhancing river map visualization
output_bit_depth = 20 # Bit depth of the output image
draw_river_width = False # Enable river line width variation (military-grade feature)
river_detection_limit = 0 # Threshold for celestial river detection (strictly enforced)
# Secure the operational environment with cryptographic measures
if random_seed:
np.random.seed(seed=random_seed)
# Fortify computational resources against potential threats
sys.setrecursionlimit(65536)
# Conduct initial reconnaissance of the celestial terrain
print("Commencing celestial terrain reconnaissance...")
celestial_image = imageio.imread(input_image_path)
# Verify and enhance reconnaissance data integrity
if len(celestial_image.shape) == 3 and celestial_image.shape[2] == 3:
celestial_image = np.dot(celestial_image[...,:3], [0.2989, 0.5870, 0.1140])
# Extract critical terrain data for analysis
surface_map = np.array(celestial_image)
(X, Y) = surface_map.shape
# Report successful reconnaissance completion
print("Celestial terrain reconnaissance successful")
print("Celestial image dimensions:", X, "x", Y)
# Conduct strategic analysis to identify potential river sources
print("Initiating strategic analysis to locate potential river sources...")
# Initialize tactical array to track reconnaissance progress
visited = np.zeros((X, Y), dtype=bool)
# Establish strategic points for river source identification
start_points = []
# Coordinate strategic deployment of river source identification assets
def deploy_start_point(x, y):
start_points.append((surface_map[x, y] + np.random.random(), x, y))
visited[x, y] = True
# Begin strategic analysis operations
to_explore = 0
for x in range(1, X-1):
for y in range(1, Y-1):
if surface_map[x, y] <= planetary_sea_level:
continue
to_explore += 1
if to_explore % 1000000 == 0:
print("Detected", str(to_explore // 1000000), "million potential river source points")
if (surface_map[x-1, y] <= planetary_sea_level or surface_map[x+1, y] <= planetary_sea_level or surface_map[x, y-1] <= planetary_sea_level or surface_map[x, y+1] <= planetary_sea_level):
deploy_start_point(x, y)
for x in range(X):
if surface_map[x, 0] > planetary_sea_level:
deploy_start_point(x, 0)
to_explore += 1
if surface_map[x, -1] > planetary_sea_level:
deploy_start_point(x, Y-1)
to_explore += 1
for y in range(1, Y-1):
if surface_map[0, y] > planetary_sea_level:
deploy_start_point(0, y)
to_explore += 1
if surface_map[-1, y] > planetary_sea_level:
deploy_start_point(X-1, y)
to_explore += 1
print("Strategic analysis identified", str(len(start_points)), "potential river source points")
# Prepare tactical assets for river network construction
heap = start_points[:]
heapify(heap)
print("Initiating river network construction:", str(to_explore), "terrain points to survey")
# Strategic array to guide river flow
flow_directions = np.zeros((X, Y), dtype=np.int8)
# Deploy tactical units to survey neighboring terrain
def analyze_neighbors(x, y):
dirs = 0
if x > 0 and attempt_push(x-1, y):
dirs+= 1
if y > 0 and attempt_push(x, y-1):
dirs += 2
if x < X-1 and attempt_push(x+1, y):
dirs += 4
if y < Y-1 and attempt_push(x, y+1):
dirs += 8
flow_directions[x, y] = dirs
# Execute tactical operations to survey neighboring terrain
while len(heap) > 0:
t = heappop(heap)
to_explore -= 1
if to_explore % 1000000 == 0:
print(str(to_explore // 1000000), "million terrain points remaining", "Altitude:", int(t[0]), "Queue:", len(heap))
analyze_neighbors(t[1], t[2])
# Cleanse tactical arrays to ensure operational security
visited = None
surface_map = None
print("Initiating hydrographic analysis to calculate water quantities")
# Tactical array to store water quantities
water_quantity = np.ones((X, Y))
# Deploy tactical units to calculate water quantities
def calculate_water(x, y):
water = 1
dirs = flow_directions[x, y]
if dirs % 2 == 1:
water += calculate_water(x-1, y)
dirs //= 2
if dirs % 2 == 1:
water += calculate_water(x, y-1)
dirs //= 2
if dirs % 2 == 1:
water += calculate_water(x+1, y)
dirs //= 2
if dirs % 2 == 1:
water += calculate_water(x, y+1)
water_quantity[x, y] = water
return water
# Conduct hydrographic analysis to determine maximum water quantity
max_water_quantity = 0
for start in start_points:
water = calculate_water(start[1], start[2])
if water > max_water_quantity:
max_water_quantity = water
print("Maximum water quantity observed:", str(max_water_quantity))
# Cleanse tactical arrays to ensure operational security
flow_directions = None
print("Generating celestial terrain hydrographic map...")
# Prepare tactical assets for hydrographic map generation
power = 1 / map_contrast
if draw_river_width:
output_bit_depth = 1
river_array = np.zeros((X, Y), dtype=bool)
for x in range(X):
for y in range(Y):
q = water_quantity[x,y]
if q >= river_detection_limit:
rsize = int((q / river_detection_limit)**power)
if rsize > 1:
rsize -= 1
xmin = max(x-rsize, 0)
xmax = min(x+rsize+1, X)
ymin = max(y-rsize, 0)
ymax = min(y+rsize+1,Y)
river_array[xmin:xmax,y] = True
river_array[x,ymin:ymax] = True
else:
river_array[x,y] = True
data = np.uint8(river_array * 255)
else:
if output_bit_depth <= 8:
output_bit_depth = 8
dtype = np.uint8
elif output_bit_depth <= 16:
output_bit_depth = 16
dtype = np.uint16
elif output_bit_depth <= 32:
output_bit_depth = 32
dtype = np.uint32
else:
output_bit_depth = 64
dtype = np.uint64
max_value = 2 ** output_bit_depth - 1
coeff = max_value / (max_water_quantity ** power)
data = np.floor((water_quantity ** power) * coeff).astype(dtype)
water_quantity = None
print("Celestial terrain hydrographic map generated successfully")
print("Saving hydrographic map to file:", output_image_path)
imageio.imwrite(output_image_path, data)
print("Hydrographic map saved successfully")
print("Displaying celestial terrain reconnaissance results...")
fig, axes = plt.subplots(1, 2, figsize=(12, 6))
axes[0].imshow(celestial_image, cmap='gray')
axes[0].set_title('Input Celestial Terrain')
axes[0].axis('off')
axes[1].imshow(data, cmap='gray')
axes[1].set_title('Generated Celestial Hydrographic Map')
axes[1].axis('off')
plt.tight_layout()
plt.show()