Brainstorm (Mind Map)

# === IMPORTS ===
import matplotlib.pyplot as plt
import networkx as nx
import numpy as np
import pandas as pd
from matplotlib.patches import FancyBboxPatch, Circle
from matplotlib.path import Path
import matplotlib.patches as mpatches

# === USER-EDITABLE PARAMETERS ===
# Change: Customize the mind map content
center_node = 'Product Launch Strategy'
main_branches = [
    'Market Research',
    'Product Development',
    'Marketing Plan',
    'Sales Strategy',
    'Timeline'
]
sub_branches = {
    'Market Research': ['Competitor Analysis', 'Customer Surveys', 'Focus Groups'],
    'Product Development': ['Features', 'Testing', 'Quality Assurance', 'Documentation'],
    'Marketing Plan': ['Social Media', 'PR Campaign', 'Influencer Outreach', 'Paid Ads'],
    'Sales Strategy': ['Pricing', 'Distribution Channels', 'Sales Training', 'Launch Promotions'],
    'Timeline': ['Q1 Research', 'Q2 Development', 'Q3 Soft Launch', 'Q4 Full Launch']
}

# Change: Premium gradient-inspired hex colors for each main branch
branch_colors = {
    'Market Research': '#4A90E2',  # Deep blue
    'Product Development': '#F5A623',  # Warm orange
    'Marketing Plan': '#7ED321',  # Vibrant green
    'Sales Strategy': '#D0021B',  # Rich red
    'Timeline': '#9013FE'  # Deep purple
}
central_color = '#FF6B9D'  # Vibrant pink for central node

# Change: Enhanced node sizes with better proportions
node_size_center = 8000
node_size_main = 4500
node_size_sub = 2500

# Change: Premium visual styling
figsize = (24, 20)  # Larger figure for better detail
edge_alpha = 0.4  # More subtle connections
node_alpha = 0.95  # More opaque nodes
font_size_center = 22  # Larger central text
font_size_main = 18   # Clearer main branch text
font_size_sub = 14    # Readable sub-branch text
line_width = 4.0      # Thicker, more prominent lines

# Change: Elegant plot title
plot_title = 'Product Launch Strategy: A Comprehensive 5-Phase Roadmap'

# === DATA PREPARATION: Build the graph structure ===
G = nx.DiGraph()
G.add_node(center_node)

# Add main branches and connections
for main in main_branches:
    G.add_edge(center_node, main)

# Add sub-branches and connections
for main, subs_list in sub_branches.items():
    for sub in subs_list:
        G.add_edge(main, sub)

total_nodes = len(G.nodes())
print(f"Generated mind map with {len(main_branches)} main branches and {sum(len(s) for s in sub_branches.values())} sub-branches.")
print(f"Total nodes: {total_nodes} (1 center + {len(main_branches)} main + {sum(len(s) for s in sub_branches.values())} sub)")
print("Branches:", ', '.join(main_branches))

# === LAYOUT CALCULATION: Enhanced radial mind map positions ===
pos = {}
theta = np.linspace(0, 2 * np.pi, len(main_branches), endpoint=False)
branch_radius = 7.5  # Increased for better spacing
sub_radius = 4.8     # Increased for clarity

# Central node at origin
pos[center_node] = (0, 0)

# Position main branches radially with slight offset for visual interest
for i, main in enumerate(main_branches):
    mx = branch_radius * np.cos(theta[i])
    my = branch_radius * np.sin(theta[i])
    pos[main] = (mx, my)

# Position sub-branches in outward fan from each main
sub_angle_span = 1.8  # Increased spread for better separation
for i, main in enumerate(main_branches):
    main_pos = pos[main]
    mx, my = main_pos
    main_angle = theta[i]
    num_subs = len(sub_branches[main])
    sub_angles = np.linspace(main_angle - sub_angle_span / 2, main_angle + sub_angle_span / 2, num_subs)
    for j, sub in enumerate(sub_branches[main]):
        sx = mx + sub_radius * np.cos(sub_angles[j])
        sy = my + sub_radius * np.sin(sub_angles[j])
        pos[sub] = (sx, sy)

# === ENHANCED VISUAL PROPERTIES ===
# Node colors with gradient effect simulation
node_colors = {}
node_colors[center_node] = central_color
for main in main_branches:
    node_colors[main] = branch_colors[main]
    for sub in sub_branches[main]:
        node_colors[sub] = branch_colors[main]

# Node sizes by importance
node_sizes_dict = {}
node_sizes_dict[center_node] = node_size_center
for main in main_branches:
    node_sizes_dict[main] = node_size_main
for main in sub_branches:
    for sub in sub_branches[main]:
        node_sizes_dict[sub] = node_size_sub

# Labels without icons
labels = {node: node for node in G.nodes()}

# === CREATE ENHANCED PLOT ===
fig, ax = plt.subplots(figsize=figsize)
ax.set_aspect('equal')

# Set background color to light blue gradient
fig.patch.set_facecolor('#F0F8FF')  # Alice Blue background
ax.set_facecolor('#E6F0FF')  # Lighter blue for plot area

# Draw enhanced curved connecting lines with gradient effect
for edge in G.edges():
    start_pos = pos[edge[0]]
    end_pos = pos[edge[1]]
    
    # Create curved path
    control_offset = 0.3
    mid_x = (start_pos[0] + end_pos[0]) / 2
    mid_y = (start_pos[1] + end_pos[1]) / 2
    
    # Add curve control point
    if edge[0] == center_node:
        # Main branches: curve outward
        control_x = mid_x + control_offset * (mid_x - 0)
        control_y = mid_y + control_offset * (mid_y - 0)
    else:
        # Sub branches: slight curve
        control_x = mid_x + control_offset * 0.5 * (mid_x - start_pos[0])
        control_y = mid_y + control_offset * 0.5 * (mid_y - start_pos[1])
    
    # Draw curved line with gradient effect
    path = Path([start_pos, [control_x, control_y], end_pos], 
                [Path.MOVETO, Path.CURVE3, Path.CURVE3])
    patch = mpatches.PathPatch(path, facecolor='none', 
                              edgecolor='#666666', 
                              linewidth=line_width,
                              alpha=edge_alpha,
                              linestyle='-')
    ax.add_patch(patch)

# Draw nodes with shadow effect
for node in G.nodes():
    x, y = pos[node]
    size = node_sizes_dict[node]
    color = node_colors[node]
    
    # Shadow
    shadow = Circle((x + 0.1, y - 0.1), size/2000, 
                   facecolor='black', alpha=0.2, zorder=1)
    ax.add_patch(shadow)
    
    # Main node
    circle = Circle((x, y), size/2000, 
                   facecolor=color, 
                   edgecolor='white',
                   linewidth=3,
                   alpha=node_alpha,
                   zorder=2)
    ax.add_patch(circle)

# Center label with enhanced styling
cx, cy = pos[center_node]
ax.text(cx, cy, labels[center_node],
        fontsize=font_size_center, fontweight='bold', color='white',
        ha='center', va='center', transform=ax.transData,
        bbox=dict(boxstyle="round,pad=0.4", 
                 facecolor='#00000080',  # Black with 50% transparency
                 alpha=0.7, 
                 edgecolor='none',
                 linewidth=0))

# Main branch labels centered in nodes
for main in main_branches:
    mx, my = pos[main]
    ax.text(mx, my, labels[main],
            fontsize=font_size_main, fontweight='bold', 
            color='white',
            ha='center', va='center', transform=ax.transData,
            bbox=dict(boxstyle="round,pad=0.3", 
                     facecolor='#00000080',  # Black with 50% transparency
                     alpha=0.7, 
                     edgecolor='none',
                     linewidth=0))

# Sub-branch labels centered in nodes
for main in main_branches:
    for sub in sub_branches[main]:
        sx, sy = pos[sub]
        ax.text(sx, sy, labels[sub],
                fontsize=font_size_sub, fontweight='600', 
                color='white',
                ha='center', va='center', transform=ax.transData,
                bbox=dict(boxstyle="round,pad=0.2", 
                         facecolor='#00000080',  # Black with 50% transparency
                         alpha=0.7, 
                         edgecolor='none',
                         linewidth=0))

# Add decorative elements
for angle in np.linspace(0, 2*np.pi, 36, endpoint=False):
    x = 10 * np.cos(angle)
    y = 10 * np.sin(angle)
    ax.plot(x, y, 'o', color='#CCCCCC', alpha=0.3, markersize=2)

# Finalize layout with enhanced styling
ax.set_title(plot_title, fontsize=22, pad=20, fontweight='bold', color='#2C3E50')
ax.axis('off')
ax.margins(0.05)  # Reduced margins
plt.subplots_adjust(top=0.88)  # Adjusted title position
plt.tight_layout()

# CRITICAL: Assign final plot to fig variable
fig = plt.gcf()
plt.show()
# END-OF-CODE

Mind map: 1 central topic, 5 branches, 19 sub-topics