semvec/pypi-packages huggingface dataset:
ptir 1.2.1
Python Terminal Image Renderer
License: MIT

# PTIR (Python Terminal Image Renderer)

### Installation
`pip install ptir`

### Usage
```python
import ptir

image_path = ...

# Render the given image
ptir.render(image_path)

# Display entire 8-bit colour space
ptir.view8BitPalette()

# Display entire 24-bit colour space
ptir.view24BitPalette()
```
### Documentation
- `ptir.render(image_path, width=100, height=100, interp_method='bilinear', only8Bit=False, only24Bit=False)`
  - `image_path` : Path to the image that will be rendered
  - `width` : The width of the output (will be 2 * `width` characters wide)
  - `height` : The height of the output (will be `height` characters tall)
  - `interp_method` : Rescale interpolation method (Either 'bilinear' or 'nearest_neighbour')
  - `only8Bit` : If True the image will be rendered without any 24-bit colour 
  - `only24Bit` : If True the image will be rendered without any 8-bit colour. This mode is recommended to be used only if you are confident that the terminal will support 24-bit colour but are unsure if unicode characters are supported by the terminal font
- Not all terminal windows support 24-bit colour (Visit [this website](https://gist.github.com/XVilka/8346728) for more information on TrueColour support)
- **The macOS default Terminal.app DOES NOT support 24-bit colour!**
- By default the image will be rendered with two layers, 24-bit foreground to display properly on supporting terminals, and a 8-bit background to display if 24-bit colour is not available
  
### Example #1
**Original**:

![mountain original](https://braggbucket.ml/mountain.jpeg)

**24-bit**:

![mountain 24-bit](https://braggbucket.ml/mountain24.png)

**8-bit**:

![mountain 8-bit](https://braggbucket.ml/mountain8.png)

### Example #2
**Original**:

![mario original](https://braggbucket.ml/mario.jpg)

**24-bit**:

![mario 24-bit](https://braggbucket.ml/mario24.png)

**8-bit**:

![mario 8-bit](https://braggbucket.ml/mario8.png)

### Dependencies
- `pillow`
- `numpy`
higradpy 0.17
Python Implementation of Hierarchical Incremental Gradient Descent
License: MIT
Keywords: Statistical Inference,Machine Learning,Stochastic Gradient Descent

This is the Python package for HiGrad (Hierarchical Incremental Gradient Descent), an algorithm for statistical inference for online learning and stochastic approximation.

Stochastic gradient descent (SGD) is an immensely popular approach for online learning in settings where data arrives in a stream or data sizes are very large. However, despite an ever-increasing volume of work on SGD, much less is known about the statistical inferential properties of SGD-based predictions. Taking a fully inferential viewpoint, this paper introduces a novel procedure termed HiGrad to conduct statistical inference for online learning, without incurring additional computational cost compared with the vanilla SGD. The HiGrad procedure begins by performing SGD iterations for a while and then split the single thread into a few, and this procedure hierarchically operates in this fashion along each thread. With predictions provided by multiple threads in place, a t-based confidence interval is constructed by decorrelating predictions using covariance structures given by the Ruppert–Polyak averaging scheme. Under certain regularity conditions, the HiGrad confidence interval is shown to attain asymptotically exact coverage probability.

Reference: Weijie Su and Yuancheng Zhu. (2018) Statistical Inference for Online Learning and Stochastic Approximation via Hierarchical Incremental Gradient Descent.

GitHub: https://github.com/vihan13singh/higradpy
betfair-scraper 1.0
Betfair website scraper library
License: MIT
Requires Python: >=3.8

# betfair-scraper

This library helps scraping the sportsbook games and odds from Betfair.com
Scraping is primarily implemented using robobrowser with a mix of API requests

Installation & Usage
Python 3.8.0 or greater required

Install latest stable build

pip install -U betfair_scraper

Install latest development build from GitHub

pip install git+https://github.com/meister245/betfair-scraper.git@development
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