semvec/pypi-packages huggingface dataset:
probeye 3.0.4
A general framework for setting up parameter estimation problems.
Requires Python: >=3.6

# probeye

[![Continuous integration](https://github.com/BAMresearch/probeye/actions/workflows/push.yaml/badge.svg)](https://github.com/BAMresearch/probeye/actions)
[![PyPI version](https://img.shields.io/pypi/v/probeye)](https://pypi.org/project/probeye/)
![python versions](https://img.shields.io/pypi/pyversions/probeye)
[![coverage](https://img.shields.io/endpoint?url=https://gist.githubusercontent.com/aklawonn/5eb707145cc7d75de25b43d25b13c972/raw/probeye_main_coverage.json)](https://en.wikipedia.org/wiki/Code_coverage)
[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)

This package provides a transparent and easy-to-use framework for solving parameter estimation problems (i.e., [inverse problems](https://en.wikipedia.org/wiki/Inverse_problem)) in a characteristic two-step approach. 

1. In the first step, the problem at hand is defined in a **solver-independent** fashion, i.e., without specifying which computational means are supposed to be utilized for finding a solution.
2. In the second step, the problem definition is handed over to a **user-selected solver**, that finds a solution to the problem via frequentist methods, such as a [maximum likelihood fit](https://en.wikipedia.org/wiki/Maximum_likelihood_estimation), or Bayesian methods such as [Markov chain Monte Carlo sampling](https://en.wikipedia.org/wiki/Markov_chain_Monte_Carlo).

The parameter estimation problems _probeye_ aims at are problems that are centered around forward models that are computationally expensive (e.g., parameterized finite element models), and the corresponding observations of which are not particularly numerous (typically around tens or hundreds of experiments). Such problems are often encountered in engineering problems where simulation models are calibrated based on laboratory tests, which are - due to their relatively high costs - not available in high numbers. 

The source code of _probeye_ is jointly developed by [_Bundesanstalt für Materialforschung und -prüfung (BAM)_](https://www.bam.de) and [_Netherlands Organisation for applied scientific research (TNO)_](https://www.tno.nl) for calibrating parameterized physics-based models and quantifying uncertainties in the obtained parameter estimates.

## Documentation
A documentation including explanations on the package's use as well as some examples can be found [here](https://probeye.readthedocs.io/en/latest/index.html).
cristalyze 0.0.4
Criação de tabelas e geração de arquivos JSON
Requires Python: >=3.6

<h1>O que é o Cristalyze</h1>
<p>O Cristalize é um projeto que Visa a atende de maneira imediata a necessidade de se armazenar dados, tanto para profissionais de data Science, como também para profissionais do desenvolvimento de softwares em geral que precisam de uma rápida abordagem para o salvamento de seus dados.<p>
<h1>Nossa filosofia</h1>
<p>Este projeto nasceu com o intuito de ser leve e eficaz sem a necessidade de instalação de bibliotecas adicionais. Todo o projeto é de rápida instalação e download sendo realmente uma alternativa muito prática para a essas questões de salvamento de dados no dia a dia dos desenvolvedores de softwares.<p>
____________________________
<h1>What is Cristalyze</h1>
Cristal is an immediate project aimed at the need to also meet data, both for Science professionals and for software development professionals in general who need a quick way to save their data.
<h1>Our philosophy</h1>
<p>This project was born with the intention of being light and efficient without the need to install additional libraries. The entire project is quick to install and download and is really a very practical alternative to these data saving issues in the day to day of software developers.</p>
televiewshka 0.0.1
A framework to develop UI & logic for telegram bots with class based views

# Televiewshka

> Note: as for now, this is neither stable nor working code.
Being Created in ... purposes it is a subject for further updates and improvements

_viewshka_ - Russian noun: informal of eng. "view", obtained by adding a diminutive suffix "shka"

Televiewshka allows you develop UI & logic for telegram bots with class based views.
In views you can define its content and how user actions and replies must be handled on it.
When all stuff related particular step in user flow is held in one class, you can clearly
see relationship between components

Televiewshka supposed to be developed in such a manner to be compatible
with a bunch of libs and frameworks for telegram bot api widely used by community

I guess I should write few adaptors for this purpose someday

## (Supposed) Example

```py
from telebot import TeleBot
from televiewshka import KeyboardView, \
    KeyboardLayout, Button, adaptors, handler, render

# create adaptor for your lib/framework
bot = TeleBot("super-secret")
bot = adaptors.create_adaptor(bot)


# specify views
class FirstView(KeyboardView):
    @bot.action_handler(action="next")
    def go_next(self, query: Query):
        return render("NextView", inplace=True, param=42)

    @staticmethod
    def render():
        return KeyboardLayout(
            keyboard = (
                Button("Go next", on_click="next"),
            ))


class NextView(KeyboardView):
    @bot.action_handler()
    def back(self, query: Query):
        return render(FirstView, inplace=True)

    @staticmethod
    def render(param: int):
        return KeyboardLayout(
            text=f"Passed param: {param}",
            keyboard = (
                Button("Go back", on_click="back"),
            ))

# run the bot
bot.start()
```

## Some details explained

### Views

something that can be rendered to user
and than handle user actions on itselves
actions are dispatched to appropriate view' and method
in accordance with user state (e.g. current_scene flag)
which is set when the view is rendered

### Dispatch

messages are being dispatched according to user' state
state = current view
callback data or message = view method

### User state

pass
photogrammetry-photos-pipeline 0.1.3
Prepare photos for a photogrammetry assembly
Requires Python: >=3.9

# photogrammetry-photos-pipeline

A pipeline to prepare jpeg photos for photogrammetry reconstruction, with:
 * dehazing
    * he-2009: Single Image Haze Removal Using Dark Channel Prior
    * meng-2013: Efficient Image Dehazing with Boundary Constraint and Contextual Regularization
 * calibrating with external GPX coordinates

## Install

    pip install photogrammetry-photos-pipeline

## Run

    photogrammetry-photos-pipeline \
        --images /path/to/orig/*.JPG \
        --output /path/to/output \
        --dehaze he-2009|meng-2013 \
        --gpx /path/to/track.gpx


## Dependencies
 * he-2009 method was copied from https://github.com/He-Zhang/image_dehaze
 * meng-2013 method from https://pypi.org/project/image-dehazer/
 * coordinates-label-photos from coordinates-label-photos

## License
MIT

## Author

Alexandre Masselot