Packaged code for PyPI by puranivt

README.md

@@ -8,12 +8,47 @@ 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
 
+Direct installation is possible from PyPI by using the following command:
+
+```sh
+pip install -i https://test.pypi.org/simple/ puranivt-diffusion2d==0.0.1
+```
+
 ### Required dependencies
 
+The following dependencies will be automatically installed:
+
+1. `numpy`: It supports large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays.
+2. `matplotlib`: A plotting library commonly used in Python. It provides an object-oriented API for embedding plots into applications using general-purpose GUI toolkits.
+
 ## Running this package
 
+The equation solver is implemented in the `solve` function of the package. To make the code run:
+
+Simply open a python shell and run the following commands:
+
+```python
+from puranivt_diffusion2d.diffusion2d import solve
+
+solve(dx = 0.1, dy = 0.1, D = 4)
+```
+
+Play around with the values of these parameters to observe changes in the output.
+
 ## Citing
+
+```bibtex
+@software{puranivt_diffusion2d,
+  author       = {Vedant Puranik},
+  title        = {{{puranivt_diffusion2d}: A project that implementes the diffusion equation solver over a series of timesteps based on configurable parameters: (dx, dy, D)}},
+  year         = {2024},
+  version      = {0.0.1},
+  url          = {"https://github.com/VedantKP/diffusion2D"},
+}
+```

puranivt_diffusion2d.egg-info/PKG-INFO

@@ -0,0 +1,75 @@
+Metadata-Version: 2.1
+Name: puranivt_diffusion2d
+Version: 0.0.1
+Summary: A project that implementes the diffusion equation solver over a series of timesteps based on configurable parameters: (dx, dy, D)
+Author-email: Vedant Puranik <[email protected]>
+Project-URL: Homepage, https://github.com/VedantKP/diffusion2D
+Keywords: diffusion_equation,diffusion2d,puranivt,SSE
+Classifier: Programming Language :: Python :: 3
+Classifier: License :: CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
+Classifier: Operating System :: OS Independent
+Requires-Python: >=3.6
+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
+
+Direct installation is possible from PyPI by using the following command:
+
+```sh
+pip3 install puranivt-diffusion2d
+```
+
+### Required dependencies
+
+The following dependencies will be automatically installed:
+
+1. `numpy`: It supports large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays.
+2. `matplotlib`: A plotting library commonly used in Python. It provides an object-oriented API for embedding plots into applications using general-purpose GUI toolkits.
+
+## Running this package
+
+The equation solver is implemented in the `solve` function of the package. To make the code run:
+
+Either simply open a python shell and run the following commands:
+
+```python
+from puranivt_diffusion2d.diffusion2d import solve
+
+solve(dx = 0.1, dy = 0.1, D = 4)
+```
+**OR**
+
+As the starting point of the package is defined as the `solve` function itself, only calling the solve function with the optional parameters would suffice.
+
+```python
+solve(dx = 0.1, dy = 0.1, D = 4)
+```
+
+## Citing
+
+```bibtex
+@software{puranivt_diffusion2d,
+  author       = {Vedant Puranik},
+  title        = {{{puranivt_diffusion2d}: A project that implementes the diffusion equation solver over a series of timesteps based on configurable parameters: (dx, dy, D)}},
+  year         = {2024},
+  version      = {0.0.1},
+  url          = {"https://github.com/VedantKP/diffusion2D"},
+}
+```

puranivt_diffusion2d.egg-info/SOURCES.txt

@@ -0,0 +1,12 @@
+LICENSE
+README.md
+pyproject.toml
+puranivt_diffusion2d/__init__.py
+puranivt_diffusion2d/diffusion2d.py
+puranivt_diffusion2d/output.py
+puranivt_diffusion2d.egg-info/PKG-INFO
+puranivt_diffusion2d.egg-info/SOURCES.txt
+puranivt_diffusion2d.egg-info/dependency_links.txt
+puranivt_diffusion2d.egg-info/entry_points.txt
+puranivt_diffusion2d.egg-info/requires.txt
+puranivt_diffusion2d.egg-info/top_level.txt

puranivt_diffusion2d.egg-info/dependency_links.txt

@@ -0,0 +1 @@
+

puranivt_diffusion2d.egg-info/entry_points.txt

@@ -0,0 +1,2 @@
+[console_scripts]
+solve = puranivt_diffusion2d.diffusion2d:solve

puranivt_diffusion2d.egg-info/requires.txt

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

puranivt_diffusion2d.egg-info/top_level.txt

@@ -0,0 +1 @@
+puranivt_diffusion2d

puranivt_diffusion2d/diffusion2d.py

@@ -0,0 +1,78 @@
+"""
+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 puranivt_diffusion2d.output import create_plot, output_plots
+
+def solve(dx: float = 0.1, dy: float = 0.1, D: int = 4):
+    """Wrapper for the diffusion equation solver and image rendering functionality
+
+    Keyword arguments:
+    dx -- intervals in x- directions, mm
+    dy -- intervals in y- directions, mm
+    D -- Thermal diffusivity of steel, mm^2/s
+    """
+    # 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
+            fig, im = create_plot(fig_counter, fig, u, T_cold, T_hot, n, dt)
+
+    # Plot output figures
+    output_plots(fig, 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

puranivt_diffusion2d/output.py

@@ -0,0 +1,34 @@
+import matplotlib.pyplot as plt
+
+
+def create_plot(fig_counter, fig, u, T_cold, T_hot, n, dt):
+    """Create one plot for a particular time stamp
+
+    Keyword arguments:
+    fig_counter -- counter for the subfigure
+    fig -- matplotlib figure object
+    u -- matrix of temperature values
+    T_cold -- value representing cold temperature
+    T_hot -- value representing hot temperature
+    n -- value for timestep
+    dt -- stable timestamp value
+    """
+    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 fig, im
+
+
+def output_plots(fig, im):
+    """Outputs all the plots as one figure
+
+    Keyword arguments:
+    fig -- matplotlib figure object
+    im -- image for color bar axes
+    """
+    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 = "puranivt_diffusion2d"
+authors = [
+    {name = "Vedant Puranik", email = "[email protected]"},
+]
+description = "A project that implementes the diffusion equation solver over a series of timesteps based on configurable parameters: (dx, dy, D)"
+readme = "README.md"
+keywords = ["diffusion_equation", "diffusion2d", "puranivt", "SSE"]
+classifiers = [
+    "Programming Language :: Python :: 3",
+    "License :: CC0 1.0 Universal (CC0 1.0) Public Domain Dedication",
+    "Operating System :: OS Independent",
+]
+dependencies = [
+    "numpy",
+    "matplotlib",
+]
+version = "0.0.1"
+requires-python = ">=3.6"
+
+[project.entry-points.console_scripts]
+solve = "puranivt_diffusion2d.diffusion2d:solve" 
+
+[project.urls]
+Homepage = "https://github.com/VedantKP/diffusion2D"