# Create 3D plot with Fully Labeled subpoints, colorized points, and grounded in Hypothetical training data
fig = plt.figure(figsize=(18, 18))
ax = fig.add_subplot(111, projection='3d')

# Creating a color map
colors = cm.jet(np.linspace(0, 1, len(continents)))

# Scatter plot for each continent and full subpoint labels with colorization
for i, continent in enumerate(continents):
x = i # Index as a placeholder for demonstration
y = temperature_rise[i] # Hypothetical data for demonstration
z = np.mean(subpoints_temperature[i]) # Hypothetical data for demonstration
ax.scatter(x, y, z, label=f"{continent} (Hypothetical)", s=100, color=colors[i])

# Plot subpoints connected to main point and add labels
for j, sub in enumerate(subpoints_temperature[i]):
ax.plot([x, x], [y, y], [z, sub], color='gray', linestyle='--', linewidth=0.5)
ax.text(x, y, sub, subpoint_labels_temperature[j], color='black')

# Labels and title with reference to hypothetical training data
ax.set_xticks(range(len(continents)))
ax.set_xticklabels(continents)
ax.set_ylabel('Temperature Rise (°C) [Hypothetical]')
ax.set_zlabel('Subpoints (°C) [Hypothetical]')
ax.set_title('Colorized and Fully Labeled Climate Polyplex Chart: Temperature Rise Across Continents [Hypothetical]')
ax.legend(loc='upper right', bbox_to_anchor=(1.4, 1))

plt.show()