Metadata-Version: 2.1
Name: spicepy
Version: 1.0.3
Summary: Circuit simulator written in Python
Home-page: https://github.com/giaccone/SpicePy
Author: Luca Giaccone
Author-email: luca.giaccone@polito.it
Project-URL: wiki, https://github.com/giaccone/SpicePy/wiki
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
License-File: LICENSE

# 1. About SpicePy
**SpicePy** is a name coming from the merge of **SPICE** (*Simulation Program with Integrated Circuit Emphasis*) and **Python**, hence, it goes without saying that it is a _Circuit simulator written in python_

**SpicePy** borns as a teaching project. It is shared with students of *basic circuit theory* with two aims:

* to allow them to check the results of exercises solved analytically
* to show them how a numerical code to solve circuit is made

This document provides information basic about features and installation procedure. For the user's guide please refer to the [Wiki section](https://github.com/giaccone/SpicePy/wiki).

##  1.1 What can I do with SpicePy?
SpicePy allows you to simulate
1. linear circuits
    * operating point
    * transient simulation
    * alternating current simulation
2. the following components:
    * resistor
    * capacitor
    * inductor
    * independent voltage source
    * independent current source
    * dependent sources (`VCVS`, `VCCS`, `CCVS`, `CCCS`)
3. transient sources (`pwl`, `pulse`, `sin`, `exp`)

# 2. Installation

This project is based on Python 3 (version `>= 3.6` is constrained in the setup). I'm use to run this project on the latest version provided by [miniconda](hnttps://docs.conda.io/en/latest/miniconda.html). For the sake of completeness, Python 2 is **not** supported.

The project makes use of the following Python modules:
* `numpy`
* `scipy`
* `matplotlib`

Usually, the last version of these Python modules is the one under use.

In the following three options for the installation are described.

## 2.1 Install from Pypi
Run this command (optionally, you can activate you virtual environment first):
```
pip install spicepy
```

## 2.2 Install (manually) from GitHub
1. Clone the repository:

`git clone https://github.com/giaccone/SpicePy.git`

2. put the project in the desired location
3. add SpicePy folder to the path of your interpreter


## 2.3 Install within Google Colab
1. Open a notebook in [`google colab`](https://colab.research.google.com/)
2. install `spicepy` with

```
!pip install spicepy    # please note the exclamation mark before 'pip'
```

3. now you can use `spicepy` within the notebook


# 3. Verify the installation
* Download the [benchmark](https://github.com/giaccone/SpicePy/tree/master/benchmark) and the [demo](https://github.com/giaccone/SpicePy/tree/master/demo) folder from the [GitHub project](https://github.com/giaccone/SpicePy),
* put the two folder at the same location,
* enter the `benchmark` folder and run the script `run_benckmark.py`.

If everything is configured correctly, you will obtain the following results:
<p align="center">
<img src="https://raw.githubusercontent.com/giaccone/SpicePy/master/benchmark/run_benchmark.png" width="800">
</p>

# 4. Work in progress

Here you can read about aspects that I'm thinking to include in this project. The list does not certifies that I will integrate all it is described. It's a simple list of the topics that potentially will be developed.

* **non-linearity**: I'm planning to implement a non-linear solver based on Newthon-Rapshon method. A rough implementation already exists but it is far from be harmonized to the entire project. Since I prefer *stability* over *new features* I will include non-linearity when I will have some more (free) time that currently I do not have.
* **GUI**: a small project was developed in order to create a text editor with tools to write netlists and with SpicePy integrated. But It is not sufficiently stable.
