semvec/pypi-packages huggingface dataset:
tangiball 0.4.2
Small package to identify and analyse peaks in a specific time-series
Requires Python: >=3.9

# Tangiball Package

A small analysis package designed for identification and examination of peaks in a voltage time-series

MIT License

Copyright (c) 2022 Joseph David Starkey

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
pydspace 0.1
Python interface to operate with dspace.
Requires Python: >=3.6

# WIP
Python interface for interoperability with dSpace running in Matlab.
pyDspace has been designed to used inside Jupyter Notebooks.
# Dependencies
- python >= 3.6
- numpy
- matlabengineforpython

# Installation
```shell
pip install pydspace
```

# API
Import the module as usual
```python
import pydspace
```
When importing the module a Matlab engine is created and you can use:
```python
pydspace.get_matlab_engine()
pydspace.reset_matlab_engine()
pydspace.kill_matlab_engine()
```
In order to open dspace from the jupyter notebook, first you must specify where the Matlab Dspace is located
with:
```python
pydspace.set_dspace_path(dspace_path)
```
now you can call dspace as usual with numpy arrays, pandas dataframes and queries made with datajoint.
```python
df = pd.read_csv(CSV_PATH)
N = len(df)

M1 = np.random.rand(N,100)
M2 = np.random.rand(N,100)
M_no_name = np.random.rand(N,100)

# Datajoint 
data = query.fetch()

dspace = pydspace.dspace(df, "matrix1", M1, "matrix2", M2, M_no_name, data)
```
the returned object is a DspaceWrapper object that implements the following methods:
```python
dspace.dsource_info() # Prints info about the dsource object
dspace.add_data("new_matrix", M3, M2_no_name) # Adds additional sources.
```
you can find more detailed info about the methods in their corresponding docstring.
Keygener 0.2
Password and key generating tool
Requires Python: >=3.6
Keywords: key generate,password generate,random number picker

# Keygener a easy to use password or key generater

[![forthebadge made-with-python](http://ForTheBadge.com/images/badges/made-with-python.svg)](https://www.python.org/)
[![Python 3.6](https://img.shields.io/badge/python-3.6-blue.svg)](https://www.python.org/downloads/release/python-360/)

## Functionality of Keygener

- Generate unique Keys
- Generate unique Passwords
- Pick Random Number from a list of numbers

## Usage

- Make sure you have Python installed in your system.
- Run Following command in the CMD.
 ```
  pip install Keygener
  ```
# Keygener has 3 functions that you can use 
- 1. genKey(length of the key you need to generate) 
- 2. genPass(length of the Password you need to generate)
- 3. pickRan(list('12345678'),How much values you need to pick)
## Example
 ```
# genKey()
import keygener
keygener.genKey(10)
- Out put
XV6gmjB5CV
 ```
# genPass()
import keygener
keygener.genPass(20)
- Out put
±j/U?f,I4hv%L{V7§^ez
 ```
# pickRan()
import keygener
keygener.pickRan(list('1234567890',2)
- Out put
26
 ```