semvec/pypi-packages huggingface dataset:
ddd-layer 0.0.2
this calculate symbolic determinants
Requires Python: >=3.4

# Hi welcome to ddd_layer V 0.0.2

DDD Method should compute matrix whit size 4x4 and up. If you try compute a system 3x3 or 2x2
is important don't use DDD, just use Sympy method (ADJ, GE or LU).

DDD works whit symengine is fast and also DDD works better.


1.- instructions for use:
example to use:

	#from ddd_layer import DDD
	#from symengine import symbols as sym
	#import numpy as np

	#R1 = sym('R1'); R2 = sym('R2'); R3 = sym('R3'); R4 = sym('R4'); R5 = sym('R5')
	#C1 = sym('C1'); C2 = sym('C2'); C3 = sym('C3'); C4 = sym('C4'); C5 = sym('C5')
	#L1 = sym('L1'); L2 = sym('L2'); L3 = sym('L3'); L4 = sym('L4'); L5 = sym('L5')
	#s = sym('s')
	#V1 = sym('V1');V2=sym('V2');V3=sym('V3');I1=sym('I1');I2=sym('I2');I3=sym('I3')
	#A = [[1/R1+1/R2, R1, 1/R2+1/R3, 1/R5, 1/R4+1/(L3*s), C1*s],
        #    [C2*s, C3*s+1/R1+1/(L4*s), 1/R2, L1,L2,L3],
     	#    [C1,C2,C3,C4,C5,R5],
     	#    [C1*s,C2*s,C3*s,C4*s,1/(L1*s)+1/(L2*s)+1/(L3*s)+1/(L4*s),1/(R1+C1*s)],
        #    [1/(L1*s),1/(L2*s),1/(L3*s),1/(L4*s),1/(L5*s),1/(R1+(1/R5))],
     	#    [58+R1,0.6*R2,1e-6*C5*s,235+1/R5,1/L4*s+235,1/R1 + 1/R2]
    	#    ]

	#x = [[],
	#     [],
 	#     [],
  	#     [],
  	#     []]

	#z = [[V1],
	#     [V2],
  	#     [V3],
  	#     [I1],
  	#     [I2],
   	#     [I3]]

	#A = np.array(A,dtype=object)
	#x = np.array(x,dtype=object)
	#z = np.array(z,dtype=object)

	#out = DDD.DDDs(A,x,z)
swiml_bartneck 2.1.0
Use Python to write Swimming Markup Language (swiML)
Requires Python: >=3.8

# swiML

[![PyPI - Version](https://img.shields.io/pypi/v/swiml.svg)](https://pypi.org/project/swiml)
[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/swiml.svg)](https://pypi.org/project/swiml)

-----

**Table of Contents**

- [Installation](#installation)
- [License](#license)
## Introduction
The Swimming Markup Language (swiML) formalises swim training programs. It uses XML technology to specify and transform data. The project is hosted at [https://github.com/bartneck/swiML](https://github.com/bartneck/swiML). Please report any problems and issues through GitHub. We welcome your contributions.

This Python library allows you to create valid swiML programs using the Python programming language. We are working on proper documentation. For now, please refer to GitHub for some examples of how to use it.
## Installation

```console
pip install swiml
```

## License

`swiml` is distributed under the terms of the [MIT](https://spdx.org/licenses/MIT.html) license.