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SignalBlocks

SignalBlocks is a Python library for visualizing and manipulating signals & systems.

Developed by Miguel Á. Martín-Fernández, the goal of this package is to make it easy to create publication-ready block diagrams and plot symbolic signal definitions and combinations, including time-domain operations (shifting, scaling, convolution) and complex plane Z-Transform ROC representations with a minimal and intuitive API.

🚀 Installation

You can install the library using pip (once published):

pip install signalblocks

If you're working locally with the repository:

pip install -e .

📦 Features

  • Create and draw block diagrams:
    • Draw basic blocks, summing junctions, arrows, and multipliers
    • Horizontal/vertical or any angle layout support
    • Customizable labels and positions
    • Easy integration with Jupyter notebooks
    • Thread for several lines in diagrams
    • Feedback branches
  • Define and plot signals:
    • Typical signals: steps, deltas, rect, tri, sinc, ramp, ...
    • Piecewise signals.
    • Periodic signals support.
    • Time shift operations.
    • Signal combinations.
    • Time sampling support.
    • Convolutions with intermediate signals plot.
  • Z-Transform Complex Plane Visualization (ComplexPlane)
    • Display Z-transform Region of convergence (ROC):
      • Inner disk (|z| < a)
      • Outer disk (|z| > a)
      • Annular regions (a < |z| < b)
    • Plot poles and zeros directly in the complex plane.
    • Accept both Cartesian (complex numbers) and polar (modulus/angle) coordinates.
    • Support for multiplicities: automatically groups multiple poles/zeros at same location.
    • Draw unit circle, radial guides, and custom annotations. Automatic label placement with overlap avoidance.

🧰 Block Diagram Basic Example

from signalblocks import DiagramBuilder

db = DiagramBuilder(block_length=1, fontsize=16)

# Diagram drawing
db.add("x(t)", kind="input")
db.add("h_{aa}(t)", kind="block")
db.add("x_c(t)", kind="arrow")
db.add("mult", kind="combiner", input_text="p(t)", operation='mult', input_side='bottom')
db.add("x_p(t)", kind="arrow")
db.add("C/D", kind="block", input_text="T_s", input_side='bottom')
db.add("x_d[n]", kind="arrow")
db.add("D/C", kind="block")
db.add("x_p(t)", kind="arrow")
db.add("h_r(t)", kind="block")
db.add("x_r(t)", kind="output")

#db.show()
db.show(savepath = "diag1.png")

This will generate a basic sample and interpolation diagram.

Block Diagram

🧰 Additional examples

Additional examples notebook 1 Additional examples notebook 2

📊 Signal Basic Example

from signalblocks import SignalPlotter

sp = SignalPlotter()
sp.add_signal("x1(t)=2*delta(t-1)")
sp.add_signal("x2(t)=rect(t)")
sp.add_signal("x3(t)=x1(t) + x2(t)")
sp.plot("x3")

This will generate a basic signal with a shifted Dirac Delta and a rect.

Signal Plot

📊 Additional examples

Additional examples notebook 1

🔵 Z-Transform Complex Plane Visualization Examples

import numpy as np
from signalblocks import ComplexPlane

cp = ComplexPlane(xlim=(-2, 2), ylim=(-2, 2))

poles = [1 + 1j, (1, np.pi/2), 1j, 1 - 1j]
zeros = [0.5 + 0.5j, (0.5, -np.pi/4), 0.5 + 0.5j]

cp.draw_poles_and_zeros(poles=poles, zeros=zeros)
r1 = cp.min_pole_modulus()
r2 = cp.max_pole_modulus()
cp.draw_ROC(f"|z|>{r2}")

cp.draw_radial_guides(labels=["|a|", "|b|"],
                      radii=[r1, r2],
                      angles=None,  # auto-ajuste
                      circles=[True, False])

cp.show(savepath="complex_plane1.png")

Signal Plot

📚 Documentation

See the API Documentation for full reference of all available drawing functions and parameters.

🛠️ Contributing

Feel free to open issues or pull requests on GitHub if you'd like to contribute or report bugs.

📄 License

This project is licensed under the GNU GPL v3.0 or later.