This code creates and saves a simple flowchart visualization of...

September 2, 2025 at 03:12 AM

import matplotlib.pyplot as plt

# Create figure
fig, ax = plt.subplots(figsize=(7, 4))
ax.axis("off")

# Steps of vaccination process
steps = [
    "Vaccine (antigen) injected",
    "Immune system detects antigen",
    "Antibodies + memory cells made",
    "Future infection recognised quickly",
    "Fast & strong response → Immunity"
]

# Plot boxes with arrows
y = 0.8
for i, step in enumerate(steps):
    ax.text(0.5, y, step, ha="center", va="center", fontsize=10,
            bbox=dict(boxstyle="round,pad=0.4", facecolor="#e6f7ff", edgecolor="black"))
    if i < len(steps)-1:
        ax.annotate("", xy=(0.5, y-0.12), xytext=(0.5, y-0.04),
                    arrowprops=dict(arrowstyle="->", lw=1.5, color="black"))
    y -= 0.2

plt.tight_layout()
plt.savefig("/mnt/data/vaccine_flowchart.png")
plt.close()

"/mnt/data/vaccine_flowchart.png"

This code creates and saves a simple flowchart visualization of the vaccination process using Matplotlib. Here's a step-by-step description of what it does:

Imports matplotlib.pyplot:
- The matplotlib.pyplot library is imported to allow plotting and visualization.
Sets up a figure and axes:
- fig, ax = plt.subplots(figsize=(7, 4)) creates a figure of size 7x4 inches and a set of axes for the plot.
- ax.axis("off") turns off the axis lines and labels, creating a clean canvas for the flowchart.
Defines the flowchart steps:
- The list steps contains strings that describe the steps in the vaccination process:
  1. "Vaccine (antigen) injected"
  2. "Immune system detects antigen"
  3. "Antibodies + memory cells made"
  4. "Future infection recognised quickly"
  5. "Fast & strong response → Immunity"
Plots the flowchart:
- The code iterates over the steps and places them on the plot as text inside rounded rectangles (boxes). These are centered at a fixed x-coordinate (0.5) and positioned vertically using the y-coordinate (y).
- It uses the bbox parameter to create the rounded rectangles with a light blue background and black edges.
- After each step (except the last), an arrow is drawn from the current step to the next step using ax.annotate. It connects the y-coordinate of the current box to a position slightly lower (y-0.12).
Layouts and saves the plot:
- plt.tight_layout() adjusts the layout to minimize overlaps.
- The flowchart is saved as a PNG image at the specified location: /mnt/data/vaccine_flowchart.png.
- plt.close() closes the current figure to free up memory.

Purpose: The code generates a visual representation of the vaccination process, plotting the steps with arrows connecting them, and saves it as an image file.

Generate your own explanations

Download our vscode extension

Read other generated explanations

Built by @thebuilderjr