Packaged code by murugapy

README.md

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-# diffusion2d
+\# murugapy\_diffusion2d
 
-## Instructions for students
 
-Please follow the instructions in [pypi_exercise.md](https://github.com/Simulation-Software-Engineering/Lecture-Material/blob/main/03_building_and_packaging/pypi_exercise.md).
 
-The code used in this exercise is based on [Chapter 7 of the book "Learning Scientific Programming with Python"](https://scipython.com/book/chapter-7-matplotlib/examples/the-two-dimensional-diffusion-equation/).
+2D diffusion equation solver and snapshot plotter. Refactored from the SciPython example.
 
-## Description
 
-## Installing the package
 
-## Running this package
+\## Overview
+
+This package solves the two-dimensional diffusion equation on a square plate with a hot circular disc in the center. It uses finite difference discretization and plots snapshots of the temperature field at selected times.
+
+
+
+\## Usage
+
+```python
+
+from murugapy\_diffusion2d import solve
+
+
+
+\# Use defaults
+
+solve()
+
+
+
+\# Custom parameters
+
+solve(dx=0.05, dy=0.05, D=4.0)
+
 
-## Citing
 

murugapy_diffusion2d/__init__.py

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+from .diffusion2d import solve
+
+__all__=["solve"]

murugapy_diffusion2d/diffusion2d.py

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+import numpy as np
+import matplotlib.pyplot as plt
+
+from .output import create_plot, output_plots
+
+
+def do_timestep(u_nm1, u, D, dt, dx2, dy2):
+    u[1:-1, 1:-1] = (
+        u_nm1[1:-1, 1:-1] +
+        D * dt * (
+            (u_nm1[2:, 1:-1] - 2*u_nm1[1:-1, 1:-1] + u_nm1[:-2, 1:-1]) / dx2 +
+            (u_nm1[1:-1, 2:] - 2*u_nm1[1:-1, 1:-1] + u_nm1[1:-1, :-2]) / dy2
+        )
+    )
+    return u.copy(), u
+
+
+def solve(dx=0.1, dy=0.1, D=4.0):
+    # Plate size
+    w = h = 10.0
+
+    # Temperatures
+    T_cold = 300
+    T_hot = 700
+
+    # Mesh points
+    nx, ny = int(w / dx), int(h / dy)
+
+    # Time step (stable)
+    dx2, dy2 = dx*dx, dy*dy
+    dt = dx2 * dy2 / (2 * D * (dx2 + dy2))
+    print("dt =", dt)
+
+    # Initial fields
+    u0 = T_cold * np.ones((nx, ny))
+    u = u0.copy()
+
+    # Hot circular region
+    r = min(h, w) / 4
+    cx, cy = w/2, h/2
+    r2 = r*r
+
+    for i in range(nx):
+        for j in range(ny):
+            p2 = (i*dx - cx)**2 + (j*dy - cy)**2
+            if p2 < r2:
+                u0[i, j] = T_hot
+
+    nsteps = 101
+    output_steps = [0, 10, 50, 100]
+
+    fig = plt.figure()
+    fig_counter = 0
+    last_im = None  # for colorbar reference
+
+    for n in range(nsteps):
+        u0, u = do_timestep(u0, u, D, dt, dx2, dy2)
+
+        if n in output_steps:
+            fig_counter += 1
+            last_im = create_plot(fig, u, n, dt, T_cold, T_hot, fig_counter)
+
+    output_plots(fig, last_im)
+
+
+if __name__ == "__main__":
+    solve()

murugapy_diffusion2d/output.py

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+import matplotlib.pyplot as plt
+
+def create_plot(fig, u, timestep, dt, T_cold, T_hot, fig_counter):
+    ax = fig.add_subplot(220 + fig_counter)
+    im = ax.imshow(u.copy(),
+                   cmap=plt.get_cmap('hot'),
+                   vmin=T_cold, vmax=T_hot)
+    ax.set_axis_off()
+    ax.set_title('{:.1f} ms'.format(timestep * dt * 1000))
+    return im
+
+
+def output_plots(fig, im):
+    fig.subplots_adjust(right=0.85)
+    cbar_ax = fig.add_axes([0.9, 0.15, 0.03, 0.7])
+    cbar_ax.set_xlabel('$T$ / K', labelpad=20)
+    fig.colorbar(im, cax=cbar_ax)
+    plt.show()

pyproject.toml

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+[build-system]
+requires = ["setuptools>=61.0", "wheel"]
+build-backend = 'setuptools.build_meta'
+
+[project]
+name = "murugapy_diffusion2d"
+version = "0.0.1"
+description = "2D diffusion PDE solver and plotting (from scipython example)"
+readme = "README.md"
+requires-python = ">=3.6"
+authors = [
+	{ name = "Prasith Basky M", email = "[email protected]" }
+	]
+license = { file = "LICENSE" }
+
+dependencies = [
+	"numpy",
+	"matplotlib"
+	]
+urls = { "Repository" = "https://github.com/prasithbasky/diffusion2d" }