semvec/pypi-packages huggingface dataset:
astro-brutus 0.8.2
Brute-force Bayesian inference for photometric distances, reddenings, and stellar properties
License: MIT
Keywords: brute force,photometry,bayesian,stellar,star,cluster,isochrone,dust,reddening,parallax,distance,template fitting

# brutus
#### _**Et tu, Brute?**_

`brutus` is a Pure Python package whose core modules involve using
"brute force" Bayesian inference to derive distances, reddenings, and 
stellar properties from photometry using a grid of stellar models.

The package is designed to be highly modular, with current modules including
utilities for modeling individual stars, star clusters, and
stellar-based 3-D dust mapping.

### Documentation
**Currently nonexistent.**

### Data

**Various files needed to run different `brutus` modules can be downloaded
[here](https://www.dropbox.com/sh/ozq9tk8iyy8fhte/AAC_G0wA9eQ8shHbZzAKwLe-a?dl=0).**
Various components of these are described below.

#### Stellar Models
Note that while `brutus` can (in theory) be run over an arbitrary set of
stellar models, it is configured for two by default: 
[MIST](http://waps.cfa.harvard.edu/MIST/)
and [Bayestar](https://arxiv.org/abs/1401.1508).

#### Zero-points
Zero-point offsets in several bands have been estimated using Gaia data
and can be included during runtime. 
**These are currently not thoroughly vetted, so use at your own risk.**

#### Dust Map
`brutus` is able to incorporate a 3-D dust prior. The current prior is
based on the "Bayestar19" dust map from
[Green et al. (2019)](https://arxiv.org/abs/1905.02734).

#### Generating SEDs
`brutus` contains built-in SED generation utilities based on the MIST
stellar models, modeled off of
[`minesweeper`](https://github.com/pacargile/MINESweeper).
These are optimized for either generating photometry from stellar mass
tracks or for a single-age stellar isochrone based on
artificial neural networks trained on bolometric correction tables.

Empirical corrections to the MIST models derived using several clusters are
implemented by default, which improves main sequence behavior
down to ~0.5 solar masses.
These can be easily disabled by users using the appropriate flag.
**These are currently not thoroughly vetted.**

Please contact Phil Cargile (pcargile@cfa.harvard.edu) and Josh Speagle
(jspeagle@cfa.harvard.edu) for more information on the provided data files.

### Installation
`brutus` can be installed by running
```
python setup.py install
```
from inside the repository.

### Demos
Several Jupyter notebooks currently outline very basic usage of the code.
Please contact Josh Speagle (jspeagle@cfa.harvard.edu) with any questions.
Gaussiandistribution 0.0.1
A very basic Gaussian distribution package calculate mean, std dev
License: MIT
Keywords: calculator

This is juat a Gaussian Distribution (Normal) package that takes two values and calculated mean,  standard derivation.It also calculate two normal distribution values and shows to you.   

Change Log 
==========


0.0.1 (22-05-2020)
------------------
- First Release
django-telethon-multisession 0.5
Telethon Session
License: MIT

\![alt text][pypi_version] ![alt text][licence_version]

# Django Telethon MultiSession

A Telethon session storage implementation backed for Django ORM to use telethon in django projects.

Tested with:
* Python 3.7+
* Django 2.2+

Use the following command to install using pip:
```
pip install django-telethon-session
```

## Usage example
Usage is very simple, just follow three simple steps below
### Add Django-Telethon-Session to your installed apps
First add django telethon session to your installed apps in your django project settings:

```python
INSTALLED_APPS = [
    ...,
    'django_telethon_session2',
    ...
]
```

### Migrate the database
Then run `migrate` command to create migrations in database.

```shell script
python manage.py migrate
```

### Use custom session
Use the session in `django_telethon_session.sessions` to initialize telegram client:
```python
from django_telethon_session2.sessions import DjangoSession
client = TelegramClient(DjangoSession())
```

Feel free to send pull requests or report issues!

[pypi_version]: https://img.shields.io/pypi/v/pykson.svg "PYPI version"
[licence_version]: https://img.shields.io/badge/license-MIT%20v2-brightgreen.svg "MIT Licence"
django-telethon-session 0.9
Telethon Session
License: MIT

\![alt text][pypi_version] ![alt text][licence_version]

# Django Telethon Session

A Telethon session storage implementation backed for Django ORM to use telethon in django projects.

Tested with:
* Python 3.7+
* Django 2.2+

Use the following command to install using pip:
```
pip install django-telethon-session
```

## Usage example
Usage is very simple, just follow three simple steps below
### Add Django-Telethon-Session to your installed apps
First add django telethon session to your installed apps in your django project settings:

```python
INSTALLED_APPS = [
    ...,
    'django_telethon_session',
    ...
]
```

### Migrate the database
Then run `migrate` command to create migrations in database.

```shell script
python manage.py migrate
```

### Use custom session
Use the session in `django_telethon_session.sessions` to initialize telegram client:
```python
from django_telethon_session.sessions import DjangoSession
client = TelegramClient(DjangoSession())
```

Feel free to send pull requests or report issues!

[pypi_version]: https://img.shields.io/pypi/v/pykson.svg "PYPI version"
[licence_version]: https://img.shields.io/badge/license-MIT%20v2-brightgreen.svg "MIT Licence"