👷 add black formatter and CI hook

Author: karlosos

Diff for: .github/workflows/black.yml

@@ -0,0 +1,11 @@
+name: Lint
+
+on: [push, pull_request]
+
+jobs:
+  lint:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v2
+      - uses: actions/setup-python@v2
+      - uses: psf/black@stable

Diff for: .gitignore

@@ -163,3 +163,5 @@ img/output/
 *.mtc1
 *.out
 *.synctex.gz
+
+.vscode/

Diff for: .pre-commit-config.yaml

@@ -0,0 +1,12 @@
+# See https://pre-commit.com for more information
+# See https://pre-commit.com/hooks.html for more hooks
+repos:
+  - repo: https://github.com/psf/black
+    rev: 19.10b0 # Replace by any tag/version: https://github.com/psf/black/tags
+    hooks:
+      - id: black
+        language_version: python
+  -   repo: https://github.com/pre-commit/pre-commit-hooks
+      rev: v2.0.0
+      hooks:
+      - id: flake8

Diff for: README.md

@@ -1,6 +1,7 @@
-
 <h1 align="center">Quantization - team project</h1>
 
+[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
+
 ## Development
 
 1. Create virtual environment with `virtualenv .venv`.

Diff for: pyproject.toml

@@ -0,0 +1,4 @@
+[tool.black]
+line-length = 119
+target-version = ['py37']
+include = '\.pyi?$'

Diff for: vector_quantization/image_noiser.py

@@ -2,22 +2,23 @@
 import numpy as np
 import math
 
-def PSNR(original, compressed): 
-    mse = np.mean((original - compressed) ** 2) 
-    if(mse == 0):  # MSE is zero means no noise is present in the signal . 
-                  # Therefore PSNR have no importance. 
+
+def PSNR(original, compressed):
+    mse = np.mean((original - compressed) ** 2)
+    if mse == 0:  # MSE is zero means no noise is present in the signal .
+        # Therefore PSNR have no importance.
         return 100
     max_pixel = 255.0
-    psnr = 20 * math.log10(max_pixel / math.sqrt(mse)) 
-    return psnr 
+    psnr = 20 * math.log10(max_pixel / math.sqrt(mse))
+    return psnr
+
 
-img = Image.open('../img/input/balloon.bmp')
+img = Image.open("./img/input/balloon.bmp")
 
 img_arr = np.array(img)
-img_arr_noise = img_arr & 254 
+img_arr_noise = img_arr & 254
 
 img_noise = Image.fromarray(img_arr_noise)
-img_noise.save("../img/input/balloon_noise.bmp")
+img_noise.save("./img/input/balloon_noise.bmp")
 
 print(f"PSNR: {PSNR(img_arr, img_arr_noise)}")
-