Packaged code for PyPI by sashanje

README.md

@@ -8,12 +8,29 @@ The code used in this exercise is based on [Chapter 7 of the book "Learning Scie
 
 ## 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
+pip install -i https://test.pypi.org/simple/ sashanje-diffusion2d --extra-index-url https://pypi.org/simple
 
 ### Required dependencies
+matplotlib
+numpy
 
 ## Running this package
 
+```python
+from sashanje_diffusion2d import diffusion2d
+
+diffusion2d.solve(
+    dx = 0.1, # intervals in x- direction, mm
+    dy = 0.1, # intervals in y- direction, mm
+    D = 4 # Thermal diffusivity of steel, mm^2/s
+    )
+```
+
 ## Citing
+Forked from https://github.com/Simulation-Software-Engineering/diffusion2D
+[pypi_exercise.md](https://github.com/Simulation-Software-Engineering/Lecture-Material/blob/main/03_building_and_packaging/pypi_exercise.md)

pyproject.toml

@@ -0,0 +1,22 @@
+[build-system]
+requires = ["setuptools"]
+
+[project]
+name = "sashanje_diffusion2d"
+authors = [
+    {name = "Sashan Samarajeewa"},
+]
+version = "0.0.3"
+description = "Solves the diffusion equation in 2D over a square domain"
+readme = "README.md"
+keywords = ["diffusion", "simulation"]
+classifiers = [
+    "Programming Language :: Python :: 3"
+]
+dependencies = [
+    "numpy",
+    "matplotlib"
+]
+
+[project.urls]
+"Homepage" = "https://github.com/Simulation-Software-Engineering/diffusion2D"

sashanje_diffusion2d.egg-info/PKG-INFO

@@ -0,0 +1,49 @@
+Metadata-Version: 2.1
+Name: sashanje_diffusion2d
+Version: 0.0.3
+Summary: Solves the diffusion equation in 2D over a square domain
+Author: Sashan Samarajeewa
+Project-URL: Homepage, https://github.com/Simulation-Software-Engineering/diffusion2D
+Keywords: diffusion,simulation
+Classifier: Programming Language :: Python :: 3
+Description-Content-Type: text/markdown
+License-File: LICENSE
+Requires-Dist: numpy
+Requires-Dist: matplotlib
+
+# 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/).
+
+## 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
+pip install -i https://test.pypi.org/simple/ sashanje-diffusion2d --extra-index-url https://pypi.org/simple
+
+### Required dependencies
+matplotlib
+numpy
+
+## Running this package
+
+```python
+from sashanje_diffusion2d import diffusion2d
+
+diffusion2d.solve(
+    dx = 0.1, # intervals in x- direction, mm
+    dy = 0.1, # intervals in y- direction, mm
+    D = 4 # Thermal diffusivity of steel, mm^2/s
+    )
+```
+
+## Citing
+Forked from https://github.com/Simulation-Software-Engineering/diffusion2D
+[pypi_exercise.md](https://github.com/Simulation-Software-Engineering/Lecture-Material/blob/main/03_building_and_packaging/pypi_exercise.md)

sashanje_diffusion2d.egg-info/SOURCES.txt

@@ -0,0 +1,11 @@
+LICENSE
+README.md
+pyproject.toml
+sashanje_diffusion2d/__init__.py
+sashanje_diffusion2d/diffusion2d.py
+sashanje_diffusion2d/output.py
+sashanje_diffusion2d.egg-info/PKG-INFO
+sashanje_diffusion2d.egg-info/SOURCES.txt
+sashanje_diffusion2d.egg-info/dependency_links.txt
+sashanje_diffusion2d.egg-info/requires.txt
+sashanje_diffusion2d.egg-info/top_level.txt

sashanje_diffusion2d.egg-info/dependency_links.txt

@@ -0,0 +1 @@
+

sashanje_diffusion2d.egg-info/requires.txt

@@ -0,0 +1,2 @@
+numpy
+matplotlib

sashanje_diffusion2d.egg-info/top_level.txt

@@ -0,0 +1 @@
+sashanje_diffusion2d

sashanje_diffusion2d/diffusion2d.py

@@ -0,0 +1,75 @@
+"""
+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 sashanje_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
+
+    # 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:
+            fig_counter += 1
+            ax = fig.add_subplot(220 + fig_counter)
+            im = create_plot(n, plt, u, ax, T_cold, T_hot, dt)
+
+    # Plot output figures
+    output_plots(fig, plt, im)
+
+
+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
+
+
+

sashanje_diffusion2d/output.py

@@ -0,0 +1,12 @@
+def create_plot(n, plt, u, ax, T_cold, T_hot, dt):
+        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
+
+def output_plots(fig, plt, 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()