Food Production Chain

import matplotlib.pyplot as plt
import matplotlib.patches as mpatches
from matplotlib.path import Path

def draw_flow(ax, x0, y0, x1, y1, w0, w1, color, alpha=0.6):
    cx = (x0 + x1) / 2
    verts = [
        (x0, y0 + w0/2), (cx, y0 + w0/2), (cx, y1 + w1/2), (x1, y1 + w1/2),
        (x1, y1 - w1/2), (cx, y1 - w1/2), (cx, y0 - w0/2), (x0, y0 - w0/2),
        (x0, y0 + w0/2)
    ]
    codes = [Path.MOVETO] + [Path.CURVE4]*3 + [Path.LINETO] + [Path.CURVE4]*3 + [Path.CLOSEPOLY]
    ax.add_patch(mpatches.PathPatch(Path(verts, codes), fc=color, alpha=alpha, ec='none'))

def draw_node(ax, x, y, w, h, color, label):
    ax.add_patch(mpatches.FancyBboxPatch((x-w/2, y-h/2), w, h, boxstyle="round,pad=0.02",
                                          fc=color, ec='#374151', lw=1.5))
    ax.text(x, y, label, ha='center', va='center', fontsize=8, color='white', fontweight='bold')

fig, ax = plt.subplots(figsize=(14, 8), facecolor='#ffffff')
ax.set_facecolor('#ffffff')

s = 0.004

# Farms to processor
draw_flow(ax, 0.5, 5, 2.5, 5, 1000*s, 1000*s, '#6CF527', 0.6)

# Processor split
draw_flow(ax, 3.5, 5.5, 5.5, 7.5, 100*s, 100*s, '#C82909', 0.6)  # Waste
draw_flow(ax, 3.5, 4.5, 5.5, 4, 900*s, 900*s, '#F5B027', 0.6)   # Processed

# Distribution
draw_flow(ax, 6.5, 4.5, 8.5, 6.5, 400*s, 400*s, '#27D3F5', 0.6)  # Supermarket
draw_flow(ax, 6.5, 3.8, 8.5, 3.5, 300*s, 300*s, '#4927F5', 0.6)  # Restaurant
draw_flow(ax, 6.5, 3.2, 8.5, 1, 200*s, 200*s, '#F5276C', 0.6)   # Export

# Nodes
draw_node(ax, 0, 5, 0.6, 1000*s*1.2, '#6CF527', 'Farms\n1000t')
draw_node(ax, 3, 5, 0.6, 1000*s*1.2, '#27F5B0', 'Processor\n1000t')
draw_node(ax, 6, 7.5, 0.6, 100*s*3, '#C82909', 'Waste\n100t')
draw_node(ax, 6, 4, 0.6, 900*s*1.2, '#F5B027', 'Packaged\n900t')
draw_node(ax, 9, 6.5, 0.6, 400*s*1.5, '#27D3F5', 'Retail\n400t')
draw_node(ax, 9, 3.5, 0.6, 300*s*1.7, '#4927F5', 'Food Svc\n300t')
draw_node(ax, 9, 1, 0.6, 200*s*2, '#F5276C', 'Export\n200t')

ax.set_title('Food Production & Distribution Flow', fontsize=16, color='#1f2937', fontweight='bold', pad=20)
ax.set_xlim(-1, 10)
ax.set_ylim(-0.5, 9)
ax.axis('off')
plt.tight_layout()
plt.show()