SLiCAP

What it is

• SLiCAP is an acronym for: S ymbolic Li near C ircuit A nalysis P rogram
• SliCAP is a tool for algorithm-based analog design automation
• SLiCAP is intended for setting up and solving design equations of electronic circuits
• SLiCAP is a an open source application written in Python and maxima CAS
• SLiCAP is part of the tool set for teaching 'Structured Electronic Design' at the Delft University of Technology

Why you should use it

• SLiCAP facilitates analog design automation
• SLiCAP speeds up the circuit engineering process
• SLiCAP makes complex symbolic math doable
• SLiCAP integrates documentation and design
• SLiCAP facilitates design education and knowledge building

Features

• Accepts SPICE-like netlists as input
• Concurrent design and documentation
• Supports and facilitates structured analog design

Capabilities

• Conversion of hierarchically structured SPICE netlist into mixed symbolic/numeric matrix equation
• Symbolic and numeric noise analysis
• Symbolic and numeric noise integration over frequency
• Symbolic and numeric determination of transfer functions and polynomial coefficients of transfer functions
• Symbolic and numeric inverse Laplace Transform
• Symbolic and numeric determination of network solutions
• Accurate numeric pole-zero analysis
• Root-locus analysis with a arbitrarily selected circuit parameters as root locus variable(s)
• Symbolic and numeric DC and DC variance analysis for determination of budgets for resistor tolerances and offset and bias quantities
• Symbolic and numeric derivation and solution of design equations for bandwidh, frequency response, noise performance, dc variance and temperature stability

Technology

• Python, Maxima CAS, HTML, CSS, LaTeX, MathJax, Jupyter Lab

Setting up SLiCAP

To set up SLiCAP, the following components are required:

• A Python 3 install - Dependencies of packages is found in requirements.txt
• Maxima CAS
• SLiCAP can generate netlists from schematics made with:
  • LTspice
  • gschem
  • lepton-eda

The dependencies are listed in the 'requirements.txt' file. When installing SLiCAP on an Anaconda distribution, it requires installing the 'in-place' module, which can be installed using the 'python -m pip install in-place'. SLiCAP can be installed by running 'python setup.py install' or 'python setup.py install --user'.

First Run

To verify setting up of SLiCAP has been done correctly, it is possible to run one of the example projects that are in the examples/ directory. Here either jupyter notebooks or the python file with the name of the example can be ran. Please take care to verify that the paths in the SLiCAPconfig.py of the example project are set correctly.

Full Documentation

The full documentation can be found in the doc/_build/ directory, this can be rebuilt with Sphinx given that all dependencies are installed (such as the sphinx-rtd-theme). In addition to the reference of functions, the documentation also contains elaborate information on the syntax that is to be used including examples.

Contributing

This github page is to be used for contributing to SLiCAP.

Adding features

Features should be added through pull requests and pass all checks that have been set up on the github page. These tests include:

• Functional python tests
• Style tests verified using a linter

Bugs

In case bugs are found, please report them to the 'Issues' page where we can resolve the issues and keep track of any possible bugs.