Packaged code for PyPI by luosg

README.md

@@ -7,13 +7,28 @@ Please follow the instructions in [pypi_exercise.md](https://github.com/Simulati
 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/).
 
 ## Project description
+This code solves the diffusion equation in 2D over a square domain which is at a certain temperature and a circular disc at the center which is at a higher temperature. This code solves the diffusion equation using the Finite Difference Method. The thermal diffusivity and initial conditions of the system can be changed by the user. The code produces four plots at various timepoints of the simulation. The diffusion process can be clearly observed in these plots.
 
 ## Installing the package
 
 ### Using pip3 to install from PyPI
 
+```bash
+pip install -i https://test.pypi.org/simple/ luosg-diffusion2d==0.0.1
+```
+
 ### Required dependencies
 
+- **Python** >= 3.6
+- **NumPy**
+- **Matplotlib**
+
 ## Running this package
+Following Commands could be run in python Shell:
+```python
+>>> from luosg_diffusion2d import diffusion2d
+>>> diffusion2d.solve()
+```
 
 ## Citing
+Instructions in [pypi_exercise.md](https://github.com/Simulation-Software-Engineering/Lecture-Material/blob/main/03_building_and_packaging/pypi_exercise.md).

luosg_diffusion2d/diffusion2d.py

@@ -0,0 +1,73 @@
+"""
+Solving the two-dimensional diffusion equation
+
+Example acquired from https://scipython.com/book/chapter-7-matplotlib/examples/the-two-dimensional-diffusion-equation/
+"""
+
+import numpy as np
+import matplotlib.pyplot as plt
+from luosg_diffusion2d.output import create_plot, output_plots
+
+
+def solve(dx = 0.1, dy = 0.1, D = 4):
+    # plate size, mm
+    w = h = 10.
+
+
+    # Initial cold temperature of square domain
+    T_cold = 300
+
+    # Initial hot temperature of circular disc at the center
+    T_hot = 700
+
+    # Number of discrete mesh points in X and Y directions
+    nx, ny = int(w / dx), int(h / dy)
+
+    # Computing a stable time step
+    dx2, dy2 = dx * dx, dy * dy
+    dt = dx2 * dy2 / (2 * D * (dx2 + dy2))
+
+    print("dt = {}".format(dt))
+
+    u0 = T_cold * np.ones((nx, ny))
+    u = u0.copy()
+
+    # Initial conditions - circle of radius r centred at (cx,cy) (mm
+    r = min(h, w) / 4.0
+    cx = w / 2.0
+    cy = h / 2.0
+    r2 = r ** 2
+    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
+
+
+    def do_timestep(u_nm1, u, D, dt, dx2, dy2):
+        # Propagate with forward-difference in time, central-difference in space
+        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)
+
+        u_nm1 = u.copy()
+        return u_nm1, u
+
+
+    # Number of timesteps
+    nsteps = 101
+    # Output 4 figures at these timesteps
+    n_output = [0, 10, 50, 100]
+    fig_counter = 0
+    fig = plt.figure()
+
+    # Time loop
+    for n in range(nsteps):
+        u0, u = do_timestep(u0, u, D, dt, dx2, dy2)
+
+        # Create figure
+        if n in n_output:
+            im, fig_counter = create_plot(T_cold, T_hot, dt, u, fig_counter, fig, n)
+
+    # Plot output figures
+    output_plots(fig, im)

luosg_diffusion2d/output.py

@@ -0,0 +1,16 @@
+import matplotlib.pyplot as plt
+
+def create_plot(T_cold, T_hot, dt, u, fig_counter, fig, n): 
+    fig_counter += 1
+    ax = fig.add_subplot(220 + fig_counter)
+    im = ax.imshow(u.copy(), cmap=plt.get_cmap('hot'), vmin=T_cold, vmax=T_hot)  # image for color bar axes
+    ax.set_axis_off()
+    ax.set_title('{:.1f} ms'.format(n * dt * 1000))
+    return im, fig_counter
+
+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

@@ -0,0 +1,28 @@
+[build-system]
+requires = ["setuptools", "wheel"]
+
+[project]
+name = "luosg_diffusion2d"
+version = "0.0.1"
+authors = [
+	{name="Luo, Shiting", email="[email protected]"}
+]
+description = "2D diffusion equation simulation"
+readme = "README.md"
+requires-python = ">=3.6"
+license = { file = "LICENSE" }
+keywords = ["sse", "2D diffusion"]
+classifiers = [
+    "Programming Language :: Python :: 3",
+]
+dependencies = [
+    "numpy",
+    "matplotlib",
+]
+
+[project.urls]
+Homepage = "https://github.com/Simulation-Software-Engineering/diffusion2D"
+
+
+[project.entry-points."simulation"]
+solve = "luosg_diffusion2d:solve"

setup.py

@@ -0,0 +1,4 @@
+from setuptools import setup
+
+if __name__ == "__main__":
+    setup()

test.py

@@ -0,0 +1,3 @@
+from luosg_diffusion2d.diffusion2d import solve
+
+solve(dx = 0.1, dy = 0.1, D = 4)