semvec/pypi-packages huggingface dataset:
tepet 0.1.1
Small timing tool to run performance analysis
Requires Python: >= 3.7

# tepet
**TE**mporal **PE**rformance **T**ool

~~25-cent term for a 5-cent concept!~~

[![PyPI](https://img.shields.io/pypi/v/tepet)](https://pypi.org/project/tepet/)
[![Test Python package](https://github.com/Toshakins/tepet/actions/workflows/python-package.yml/badge.svg)](https://github.com/Toshakins/tepet/actions/workflows/python-package.yml)

## What is this
tepet is a small utility to help you understand and track execution time of your code. You could write it anytime, but why do this every other day?

## Usage
Can be used as a context manager

```python
from tepet import PerfTimer

with PerfTimer():
    print('doing stuff...')

# Output:
#
# > 2020 May 31 20:11:49 +0000 ==== started
# > doing stuff...
# > 2020 May 31 20:11:49 +0000 ==== elapsed 0.00000 seconds
```
and a function decorator
```python
from tepet import PerfTimer
@PerfTimer()
def work():
  print("working...")

work()

# Output:
#
# > 2020 May 31 20:14:25 +0000 ==== started
# > working...
# > 2020 May 31 20:14:25 +0000 ==== elapsed 0.00001 seconds
```

Also, can be used in production environments for naive tracking:

```python
from tepet import Timer

def printer(seconds):
        print(f'code block 1: {seconds:.5f} elapsed')

with Timer(printer):
    ...

# Output:
# > code block 1: 0.00000 elapsed
```
ephysvibe 0.0.2
.
Requires Python: >=3.7
Keywords: electrophysiology neuroscience

# EphysVibe
Implementing pipeline analyses for electrophysiology data. 
Spiking and LFP activity of 32 channels linear probes from LIP; 64 Utah Arrays channels from PFC; 64 Utah Arrays channels from V4?
Animals perform a delay conjunction matching task, controlled by MonkeyLogic (Matlab): https://monkeylogic.nimh.nih.gov/
Raw electrophysiology data are acquired with OpenEphys: https://github.com/open-ephys
w2widget 0.0.3
Widget for exploring and sampling words from text data through w2v
Requires Python: >=3.7

# w2widget
Widget for exploring and sampling words from text data through word2vec models in order to construct topic dictionaries.

## Package content

The `w2widget` package contains two modules:
- `doc2vec.py`
- `widget.py`

## Examples

In the `widget_example.ipynb` you can play with the widget from pretrained data from [Reuters](http://kdd.ics.uci.edu/databases/reuters21578/reuters21578.html) dataset.

If you want to see an example of the data-workflow generating the necessary input, check out `workflow_example.ipynb`.

### Doc2Vec

This module helps with calculating and handling doc2vec. The approach applied is that every document's vector is calculated by taking a weighted (ie. based on inverse frequencies) average of the document's word vectors.

```python
from w2widget.doc2vec import calculate_inverse_frequency, Doc2Vec

# Calculate word weigts from inverse frequency
word_weights = calculate_inverse_frequency(document_tokens)

# Initiate the model
dv_model = Doc2Vec(wv_model, word_weights)

# Add documents and calculated the document vectors
dv_model.add_doc2vec(document_tokens)

# reduce the dimensions
dv_model.reduce_dimensions()

# Store the embeddings
two_dim_doc_embedding = dv_model.TSNE_embedding_array
```

### Widget

This widget module displays the results from:
- A gensim word2vec model,
- it's 2-dimensional embedding (ie. TSNE).
- The custom implemented doc2vec model,
- it's 2-dimensional embedding (ie. TSNE).
- A list of tokenized documents with whitespaces and
- optionally a list of initial search words

```python
from w2widget.widget import Widget

wv_widget = Widget(
    wv_model,
    two_dim_word_embedding,
    tokens_with_ws
    dv_model=None,
    two_dim_doc_embedding=None,
    initial_search_words=[],
)

wv_widget.display_widget()
```

You can save the topics to a `json` file from the widget, or access them from the dictionary stored in `wv_widget.topics`.
nuwavsource 0.0.8
A package for source exclusion in NuStar observation data using wavelet decomposition

# nuwavsource

This package is supposed to be used to detect the sources in NuStar observations and generate a mask excluding the signal from the sources of any kind. 

Additionaly, it generates a table containing:

Useful data about the observation:

1. OBS_ID
2. Detector
3. Coordinates in equatorial (ra,dec) and galactical (lon,lat) systems
4. Time of the observation in seconds
5. Exposure

Useful algorythm-related data:

6. Average count rate on unmasked area
7. Portion of unmasked area
8. Specific statistical metric[1] before and after masking the detected sources
9. Root-mean-square of counts in unmasked area

## Installation
This package is to be used with Python 3.x.x

To install tha package write

```bash
pip install nuwavsource
```

## Usage

To use the package in your project, import it in by writing

```python
from nuwavsource import nuwavsource
```

You can process the cl.evt file by creating an Observation class object:

```python
obs = nuwavsource.Observation(path_to_evt_file)
```

Additionally, the energy band in KeV to get events from can be passed as an argument. The default value is [3,20].

```python
obs = nuwavsource.Observation(path_to_evt_file,E_borders=[E_min,E_max])
```
create-pyscript-app 0.0.3
Set up a PyScript web app by running one command.
Requires Python: >=3.6

<div align="center">
<h1>create-pyscript-app</h1>

<div>Create PyScript web app project.</div>

<br />

<!-- Badges -->

![License](https://badgen.net/github/license/yeoularu/create-pyscript-app)
![Version](https://badgen.net/pypi/v/create-pyscript-app)
![Python Version](https://badgen.net/badge/python/>=3.6/blue)

<br />
<pre>pip install <a href="https://pypi.org/project/create-pyscript-app">create-pyscript-app</a></pre>

<br />
<img src="sample.gif" width="600" />
</div>

<br />

_you can see the preview site [HERE](https://yeoularu.github.io/pyscript-deploy-test/)_

<br />

## Creating an App

- You'll need to have **Python 3.6 or later version** on local development machine.

- **To run PyScript, Internet connection is required** because it use assets served on [https://pyscript.net](https://pyscript.net). If you want to download the source and build it yourself, follow the instructions in the [PyScript README.md](https://github.com/pyscript/pyscript/blob/main/README.md) file.

To create a new app, first install package with pip:

```sh
pip install create-pyscript-app
```

and run following command with project directory name(in this example, my-app):

```sh
python -m create-pyscript-app my-app
```

It will create a directory called `my-app` inside the current folder.

<br />
Inside that directory, it will generate the initial project structure:

```
my-app
├── index.html
├── index.css
├── app.py
└── favicon.ico
```

## Run the App in local browser

Once the installation is done, you can open your project foler:

```sh
cd my-app
```

and open local http server with run following command:

```sh
python -m http.server
```

check the following message about port (default :8000) and open url "http://localhost:8000/" in browser ([Chrome](https://www.google.com/chrome/) recommended).

---

## What is PyScript

~~**Py**thon + Java**Script**~~

> Python in the browser

PyScript is a framework that allows users to create rich Python applications in the browser using HTML's interface and the power of Pyodide, WASM, and modern web technologies.

## Reference

[PyScript](https://pyscript.net/)

[Create React App](https://create-react-app.dev/)

create-next-app ([Next.js](https://github.com/vercel/next.js))

## License

This project is [Apache-2.0](https://github.com/yeoularu/create-pyscript-app/blob/main/LICENSE) licensed. This software is powered by [PyScript](https://pyscript.net/) software.