IBB-Helper 0.1.2

helper functions

Matrix and Plotting Helper Toolkit

Author: Institut fuer Baustatik und Baudynamik,Universitaet Stuttgart License: ADD LICENSE here Version: 1.0 Date: July 2025

Description:

This helper module provides a set of tools to make symbolic math, matrix visualization, and plotting (2D/3D) more intuitive and presentation-friendly, especially when working with SymPy, NumPy, Matplotlib, and Plotly in Jupyter Notebooks or other Python environments.

Modules Included:

1. DMAT

   • Pretty-prints a truncated matrix with optional decimal or rational evaluation.

2. DIS

   • Nicely formats scalars, vectors, or matrices in LaTeX for display.

3. DIS_EI

   • Computes and displays eigenvalues and eigenvectors using clean LaTeX formatting.

4. plot_2d

   • Plots symbolic expressions or numeric datasets in 2D using Matplotlib.

5. plot_3d

   • Plots symbolic 3D surfaces using Plotly for interactive visualization.

6. extend_plots

   • Merges multiple plots side-by-side (e.g., shifted versions).

7. append_plots

   • Stacks multiple Matplotlib or Plotly plots into one combined figure.

Dependencies:

• Python 3.8+
• numpy
• sympy
• matplotlib
• plotly
• IPython (for LaTeX rendering in notebooks)

How to Use:

1. Import the helper script:

   from your_module_name import *

2. Visualize a matrix:

   DMAT(np.array([[1, 2], [3, 4]]), name="A")

3. Display a symbolic expression:

   x = sp.Symbol('x') DIS(sp.sin(x)**2 + sp.cos(x)**2, name="Identity")

4. Plot a symbolic 2D graph:

   plot_2d([sp.sin(x), sp.cos(x)], var=(x, (-np.pi, np.pi)), labels=["sin(x)", "cos(x)"])

5. Plot a 3D surface:

   plot_3d(sp.sin(x*y), var=(x, (-2, 2), y, (-2, 2)), title="sin(xy) surface")

Notes:

• This toolkit is especially suited for education, math research, or lab reports where symbolic clarity and visualization are critical.
• Functions are designed to handle both SymPy and NumPy formats seamlessly.

License:

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