Soft Computing Library (numpysc-lib)
A Python package that stores practical programs for Soft Computing & Neural Networks (Simple Neural Networks, Sigmoidal Functions, McCulloch-Pitts, Hebb Rule, Backpropagation, Fuzzy Sets, Perceptron) and prints their source code on demand, from Python or the terminal.
Install it once with pip, then view any practical code on any machine without copying files around.
Practicals Included
| Practical | Topic / Description |
|---|---|
1A-Simple-Neural-Network |
Design a Simple Neural Network (SNN) with Ramp activation |
1B-Sigmoidal-Functions |
Binary and Bipolar Sigmoidal Activation Functions |
2A-McCulloch-Pitts Neural Network |
ANDNOT function using McCulloch-Pitts Neuron |
2B-XOR function using McCulloch-Pitts Neural Network |
XOR function using McCulloch-Pitts Network |
3-AND Hebb Rule Network |
AND function with Hebbian learning rule (bipolar inputs) |
4-Back Propagation Problem |
Single-step forward & backward error propagation |
5-Error Back Propagation |
Multi-epoch Error Backpropagation Training |
6-Identity Operators |
Identity and Membership Operators in Python |
7-Fuzzy |
Fuzzy Set Operations (Union, Intersection, Complement, Algebraic/Bounded Sum & Diff) |
8-Perceptron |
Perceptron Learning Algorithm for Linear Classification |
Step 1: Install
pip install numpysc-lib
To update to the latest version:
pip install --upgrade numpysc-lib
Requires Python 3.6 or newer.
Step 2: View the programs
Option A: From the terminal
Show all practicals:
numpysc
# or
numpysc-lib
Show a single practical (type the name or partial name):
numpysc "1A-Simple-Neural-Network"
numpysc "7-Fuzzy"
numpysc "8-Perceptron"
Option B: From Python
import numpysc_lib
numpysc_lib.show_codes() # Show all practicals
numpysc_lib.show_codes("7-Fuzzy") # Show specific practical
numpysc_lib.show_codes("1A-Simple-Neural-Network") # Show specific practical
Option C: In Google Colab or Jupyter
!pip install numpysc-lib
import numpysc_lib
numpysc_lib.show_codes("8-Perceptron")
Publishing a new version (for maintainers)
- Make any additions or updates in the
numpysc_lib/folder. - Increment
versioninsetup.py(e.g.1.1.2). - Clean old builds:
rm -rf dist build *.egg-info
- Build:
python3 -m build
- Check and Upload to PyPI:
python3 -m twine upload dist/*
License
MIT. See LICENSE.
Metadata
Release files for numpysc-lib 1.1.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| numpysc_lib-1.1.2.tar.gz | 8.0 kB | Without provenance | Details for numpysc_lib-1.1.2.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| numpysc_lib-1.1.2-py3-none-any.whl | Python 3 | none | any | Details for numpysc_lib-1.1.2-py3-none-any.whl |
Total release size: 17.9 kB
Release files / numpysc_lib-1.1.2.tar.gz
| Download URL | numpysc_lib-1.1.2.tar.gz |
|---|---|
| Size | 8.0 kB |
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| Download URL | numpysc_lib-1.1.2-py3-none-any.whl |
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| Size | 10.0 kB |
| Tags | Python 3 |
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