A single Python file with some tools for visualizing machine learning in the terminal.

Related tags

Machine Learningmlvt
Overview

Machine Learning Visualization Tools

A single Python file with some tools for visualizing machine learning in the terminal.

This demo is composed of three ideas, which are explained below. Here's how to get started:

git clone https://github.com/bwasti/mlvt.git
cd mlvt
python3 -m pip install -r requirements.txt
python3 test.py # demo above

or just copy the mlvt.py file!

mlvt.Reprint

Reprint helps with in-line animations. It works by keeping track of how much it printed so far and reprinting it when flush() is called.

You can use the with statement to hijack print statements and auto_flush=True to avoid calling flush() in a loop, like so:

print("loading!")
with mlvt.Reprint(auto_flush=True) as rp:
  for i in range(100):
    print(f"{i+1}%") # Reprint detects the loop and overwrites in-place
    time.sleep(0.02)
print("done!")

reprint.gif

or, if you'd prefer to avoid contexts, loop-detection and hijacked builtins

print("loading!")
rp = mlvt.Reprint()
for i in range(100):
  rp.print(f"{i+1}%")
  rp.flush()
  time.sleep(0.02)
print("done!")

mlvt.horiz_concat

horiz_concat concatenates multi-line strings horizontally, accounting for padding and ANSI escape sequences (for color text).

a = """
{ hello! }
          \_    
"""
b = """
 ___
|. .|
| ^ |
| o |
"""
print(mlvt.horiz_concat(a, b, padding=2))

yields


               ___
{ hello! }    |. .|
          \_  | ^ |
              | o |
              

plotille wrappers

Finally, there are a couple of small plotille wrappers that decouple updating charts and printing them. That library is great on its own, so I encourage you to check it out!

import mlvt
import numpy as np

# all charts take in width, height, color
hist = mlvt.Histogram(32, 8, color="bright_blue")
hist.update(np.random.randn(100))
print(hist)

gives us

 (Counts)  ^
8.80000000 |
7.70000000 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢠⡄⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀
6.60000000 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀
5.50000000 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⡇⣶⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀
4.40000000 | ⠀⠀⠀⠀⠀⠀⠀⠀⢰⣶⣶⠀⠀⢸⡇⣿⠀⢰⣶⡆⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀
3.30000000 | ⠀⠀⠀⠀⠀⠀⠀⣿⢸⣿⣿⣿⣿⢸⣿⣿⣿⢸⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀
2.20000000 | ⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣿⣿⢸⣿⣿⣿⣿⣿⣿⣿⣿⡇⢸⣿⠀⠀⠀⢸⡇⠀⠀
1.10000000 | ⠀⠀⢀⣀⡀⣿⣀⣿⣿⣿⣿⣿⣿⣸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⣇⣸⡇⠀⠀
         0 | ⠀⠀⢸⣿⡇⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⣿⣿⡇⠀⠀
-----------|-|---------|---------|---------|-> (X)
           | -2.124059 -0.741902 0.6402548 2.0224115
Owner
Bram Wasti
https://twitter.com/bwasti
Bram Wasti
AP1 Transcription Factor Binding Site Prediction

A machine learning project that predicted binding sites of AP1 transcription factor, using ChIP-Seq data and local DNA shape information.

1 Jan 21, 2022
A Software Framework for Neuromorphic Computing

A Software Framework for Neuromorphic Computing

Lava 338 Dec 26, 2022
onelearn: Online learning in Python

onelearn: Online learning in Python Documentation | Reproduce experiments | onelearn stands for ONE-shot LEARNning. It is a small python package for o

15 Nov 06, 2022
Machine-Learning with python (jupyter)

Machine-Learning with python (jupyter) 머신러닝 야학 작심 10일과 쥬피터 노트북 기반 데이터 사이언스 시작 들어가기전 https://nbviewer.org/ 페이지를 통해서 쥬피터 노트북 내용을 볼 수 있다. 위 페이지에서 현재 레포 기

HyeonWoo Jeong 1 Jan 23, 2022
Python Extreme Learning Machine (ELM) is a machine learning technique used for classification/regression tasks.

Python Extreme Learning Machine (ELM) Python Extreme Learning Machine (ELM) is a machine learning technique used for classification/regression tasks.

Augusto Almeida 84 Nov 25, 2022
Pandas Machine Learning and Quant Finance Library Collection

Pandas Machine Learning and Quant Finance Library Collection

148 Dec 07, 2022
Kaggle Tweet Sentiment Extraction Competition: 1st place solution (Dark of the Moon team)

Kaggle Tweet Sentiment Extraction Competition: 1st place solution (Dark of the Moon team)

Artsem Zhyvalkouski 64 Nov 30, 2022
a distributed deep learning platform

Apache SINGA Distributed deep learning system http://singa.apache.org Quick Start Installation Examples Issues JIRA tickets Code Analysis: Mailing Lis

The Apache Software Foundation 2.7k Jan 05, 2023
Continuously evaluated, functional, incremental, time-series forecasting

timemachines Autonomous, univariate, k-step ahead time-series forecasting functions assigned Elo ratings You can: Use some of the functionality of a s

Peter Cotton 343 Jan 04, 2023
Automated machine learning: Review of the state-of-the-art and opportunities for healthcare

Automated machine learning: Review of the state-of-the-art and opportunities for healthcare

42 Dec 23, 2022
Banpei is a Python package of the anomaly detection.

Banpei Banpei is a Python package of the anomaly detection. Anomaly detection is a technique used to identify unusual patterns that do not conform to

Hirofumi Tsuruta 282 Jan 03, 2023
Backprop makes it simple to use, finetune, and deploy state-of-the-art ML models.

Backprop makes it simple to use, finetune, and deploy state-of-the-art ML models. Solve a variety of tasks with pre-trained models or finetune them in

Backprop 227 Dec 10, 2022
OptaPy is an AI constraint solver for Python to optimize planning and scheduling problems.

OptaPy is an AI constraint solver for Python to optimize the Vehicle Routing Problem, Employee Rostering, Maintenance Scheduling, Task Assignment, School Timetabling, Cloud Optimization, Conference S

OptaPy 208 Dec 27, 2022
MLR - Machine Learning Research

Machine Learning Research 1. Project Topic 1.1. Exsiting research Benmark: https://paperswithcode.com/sota ACL anthology for NLP papers: http://www.ac

Charles 69 Oct 20, 2022
Automated Machine Learning Pipeline for tabular data. Designed for predictive maintenance applications, failure identification, failure prediction, condition monitoring, etc.

Automated Machine Learning Pipeline for tabular data. Designed for predictive maintenance applications, failure identification, failure prediction, condition monitoring, etc.

Amplo 10 May 15, 2022
Toolss - Automatic installer of hacking tools (ONLY FOR TERMUKS!)

Tools Автоматический установщик хакерских утилит (ТОЛЬКО ДЛЯ ТЕРМУКС!) Оригиналь

14 Jan 05, 2023
Machine-learning-dell - Repositório com as atividades desenvolvidas no curso de Machine Learning

📚 Descrição Neste curso da Dell aprofundamos nossos conhecimentos em Machine Learning. 🖥️ Aulas (Em curso) 1.1 - Python aplicado a Data Science 1.2

Claudia dos Anjos 1 Jan 05, 2022
Upgini : data search library for your machine learning pipelines

Automated data search library for your machine learning pipelines → find & deliver relevant external data & features to boost ML accuracy :chart_with_upwards_trend:

Upgini 175 Jan 08, 2023
Mosec is a high-performance and flexible model serving framework for building ML model-enabled backend and microservices

Mosec is a high-performance and flexible model serving framework for building ML model-enabled backend and microservices. It bridges the gap between any machine learning models you just trained and t

164 Jan 04, 2023
pymc-learn: Practical Probabilistic Machine Learning in Python

pymc-learn: Practical Probabilistic Machine Learning in Python Contents: Github repo What is pymc-learn? Quick Install Quick Start Index What is pymc-

pymc-learn 196 Dec 07, 2022