Refactor two_dim_interp function and add plotting option

germany_beer_map/src/algorithms/two_dim_interp.py

@@ -4,94 +4,114 @@
 import matplotlib.pyplot as plt
 import random
 
-def two_dim_interp(ref_contour, centres_of_holes=None, mapping="germany_beer_map/data/mapping/mapping.csv"):
+def two_dim_interp(centres_of_holes, plotting=False, ref_contour=None, mapping="germany_beer_map/data/mapping/mapping.csv"):
 
-	reference_contour_x = ref_contour[:, 0]
-	# negate the y values to match the mapping file
-	reference_contour_y = -ref_contour[:, 1]
+	if plotting and ref_contour is None:
+		raise ValueError("centres_of_holes must be provided when plotting is True")
 
-	# Read the mapping file
 	mapping = np.loadtxt(mapping, delimiter=',', skiprows=1)
 
-	# Extract the distinctive points
+	centres_of_holes = np.array(centres_of_holes)
+	centres_of_holes_x = centres_of_holes[:, 0]
+	# Convert to signed int16 to avoid errors when negating y-values
+	centres_of_holes_y = centres_of_holes[:, 1].astype(np.int16)
+
+	print(centres_of_holes_x)
+	print(centres_of_holes_y)
+
 	distinctive_points_x = mapping[:, 0]
 	distinctive_points_y = mapping[:, 1]
 	distinctive_points_longitude = mapping[:, 3]
 	distinctive_points_latitude = mapping[:, 2]
 
-
-	# Interpolate longitude and latitude based on distinctive points
-	interp_longitude = griddata(
+	circles_interp_longitude = griddata(
 		(distinctive_points_x, distinctive_points_y),
 		distinctive_points_longitude,
-		(reference_contour_x, reference_contour_y),
+		(centres_of_holes_x, -centres_of_holes_y),
 		method='cubic'
 	)
 
-	interp_latitude = griddata(
+	circles_interp_latitude = griddata(
 		(distinctive_points_x, distinctive_points_y),
 		distinctive_points_latitude,
-		(reference_contour_x, reference_contour_y),
+		(centres_of_holes_x, -centres_of_holes_y),
 		method='cubic'
 	)
 
+	print(circles_interp_latitude)
+
+	if plotting:
+		reference_contour_x = ref_contour[:, 0]
+		reference_contour_y = -ref_contour[:, 1]
+
+		hull = ConvexHull(np.column_stack((distinctive_points_x, distinctive_points_y)))
+
+
+		contour_interp_longitude = griddata(
+			(distinctive_points_x, distinctive_points_y),
+			distinctive_points_longitude,
+			(reference_contour_x, reference_contour_y),
+			method='cubic'
+		)
+
+		contour_interp_latitude = griddata(
+			(distinctive_points_x, distinctive_points_y),
+			distinctive_points_latitude,
+			(reference_contour_x, reference_contour_y),
+			method='cubic'
+		)
+
+		fig, axs = plt.subplots(1, 2, figsize=(20, 10))
+
+		axs[0].plot(reference_contour_x, reference_contour_y, 'b-', label='Contour')
+
+		for i, simplex in enumerate(hull.simplices):
+			if i == 0:
+				axs[0].plot(distinctive_points_x[simplex], distinctive_points_y[simplex], 'k-', label='Convex Hull')
+			else:
+				axs[0].plot(distinctive_points_x[simplex], distinctive_points_y[simplex], 'k-')
+
+		axs[0].set_xlabel('x-coordinate')
+		axs[0].set_ylabel('y-coordinate')
+		axs[0].legend()
+
+		axs[1].scatter(distinctive_points_longitude, distinctive_points_latitude, color='red', label='Distinctive Points')
+		for i in range(len(distinctive_points_longitude)):
+			axs[1].text(distinctive_points_longitude[i], distinctive_points_latitude[i], f'({distinctive_points_x[i]}, {distinctive_points_y[i]}, {i+1})', fontsize=8)
+		axs[1].plot(contour_interp_longitude, contour_interp_latitude, 'b-', label='Interpolated Contour')
+
+		for i in range(0, len(contour_interp_longitude), 50):
+			if not np.isnan(contour_interp_longitude[i]) and not np.isnan(contour_interp_latitude[i]):
+				rounded_contour_longitude = round(contour_interp_longitude[i], 3)
+				rounded_contour_latitude = round(contour_interp_latitude[i], 3)
+				axs[1].scatter(rounded_contour_longitude, rounded_contour_latitude, color='green')
+				axs[1].text(rounded_contour_longitude, rounded_contour_latitude, f'({rounded_contour_longitude}, {rounded_contour_latitude})', fontsize=8)
 
-	# Compute the convex hull of the distinctive points
-	hull = ConvexHull(np.column_stack((distinctive_points_x, distinctive_points_y)))
-
-	# Create two subplots side by side
-	fig, axs = plt.subplots(1, 2, figsize=(20, 10))
-
-	# Plot the distinctive points, contour, and convex hull on the first subplot
-	axs[0].plot(reference_contour_x, reference_contour_y, 'b-', label='Contour')
-	# Plot the convex hull of distinctive points
-	for i, simplex in enumerate(hull.simplices):
-		if i == 0:
-			# Plot the first simplex with a label
-			axs[0].plot(distinctive_points_x[simplex], distinctive_points_y[simplex], 'k-', label='Convex Hull')
-		else:
-			axs[0].plot(distinctive_points_x[simplex], distinctive_points_y[simplex], 'k-')
-
-	axs[0].set_xlabel('x-coordinate')
-	axs[0].set_ylabel('y-coordinate')
-	axs[0].legend()
-
-	# Plot the interpolated contour on the second subplot
-	axs[1].scatter(distinctive_points_longitude, distinctive_points_latitude, color='red', label='Distinctive Points')
-	for i in range(len(distinctive_points_longitude)):
-		axs[1].text(distinctive_points_longitude[i], distinctive_points_latitude[i], f'({distinctive_points_x[i]}, {distinctive_points_y[i]}, {i+1})', fontsize=8)
-	axs[1].plot(interp_longitude, interp_latitude, 'b-', label='Interpolated Contour')
-
-	# Add text annotations for every 50th point on the interpolated contour
-	for i in range(0, len(interp_longitude), 50):
-		if not np.isnan(interp_longitude[i]) and not np.isnan(interp_latitude[i]):
-			rounded_longitude = round(interp_longitude[i], 3)
-			rounded_latitude = round(interp_latitude[i], 3)
-			axs[1].scatter(rounded_longitude, rounded_latitude, color='green')
-			axs[1].text(rounded_longitude, rounded_latitude, f'({rounded_longitude}, {rounded_latitude})', fontsize=8)
-
-	# Check if centres_of_holes is provided
-	if centres_of_holes is not None:
-		# Convert the list of arrays to a 2D numpy array
-		centres_of_holes = np.array(centres_of_holes)
-		# Extract the x and y coordinates
-		centres_of_holes_x = centres_of_holes[:, 0]
-		centres_of_holes_y = centres_of_holes[:, 1]. astype(np.int16)  # convert to signed integer
-
-		# Compute the convex hull of the centres of the holes
 		holes_hull = ConvexHull(np.column_stack((centres_of_holes_x, -centres_of_holes_y)))
-		# Plot the centres of the hole cutouts as points on the first subplot
+
 		axs[0].scatter(centres_of_holes_x, -centres_of_holes_y, color='purple', label='Centres of Holes')
-		# Plot the convex hull of distinctive points
+
+		for i in range(0, len(circles_interp_latitude)):
+			rounded_circles_longitude = round(circles_interp_longitude[i], 3)
+			rounded_circles_latitude = round(circles_interp_latitude[i], 3)
+			if i ==0:
+				axs[1].scatter(rounded_circles_longitude, rounded_circles_latitude, color='purple', label='Centres of Holes')
+				axs[1].text(rounded_circles_longitude, rounded_circles_latitude, f'({rounded_circles_longitude}, {rounded_circles_latitude})', fontsize=8)
+			else:
+				axs[1].scatter(rounded_circles_longitude, rounded_circles_latitude, color='purple')
+				axs[1].text(rounded_circles_longitude, rounded_circles_latitude, f'({rounded_circles_longitude}, {rounded_circles_latitude})', fontsize=8)
+
 		for i, simplex in enumerate(holes_hull.simplices):
 			if i == 0:
-				# Plot the first simplex with a label
 				axs[0].plot(centres_of_holes_x[simplex], -centres_of_holes_y[simplex], 'g-', label='Convex Hull of Circle Centres')
 			else:
 				axs[0].plot(centres_of_holes_x[simplex], -centres_of_holes_y[simplex], 'g-')
 
-	axs[1].set_xlabel('Longitude')
-	axs[1].set_ylabel('Latitude')
-	axs[1].legend()
 
-	plt.show()
+		axs[1].set_xlabel('Longitude')
+		axs[1].set_ylabel('Latitude')
+		axs[1].legend()
+
+		plt.show()
+
+	return contour_interp_longitude, contour_interp_latitude

germany_beer_map/src/main.py

@@ -45,9 +45,9 @@
 
 contour_rotated = rotate_contour_around_centroid(contour, -rotation_angle)
 
-two_dim_interp(ref_contour_scaled_aligned, circles)
+two_dim_interp(circles, True,  ref_contour_scaled_aligned)
 
-# exit(0)
+exit(0)
 
 # draw_contours(ref_contour_scaled_aligned)