Update README

README.md

@@ -1,2 +1,43 @@
-# cmat
-A utility module for confusion matrices
+# Confusion Matrix
+
+A simple pandas/numpy-based module for constructing, analysing, and plotting confusion matrices that I found myself copying between projects so often that I decided to make it a separate, pip-installable package. It was written with **python 3.6**, but \_\_future\_\_ statements have been included and f-string have been avoided intentionally. 
+## Installation 
+
+Install via pip (from PyPi)
+```
+pip install cmat
+```
+Or, alternatively, just copy the [main module](cmat/confusion_matrix.py) into your project and hardcode all config.xx values.
+
+## Usage
+
+The functionality should be intuitive for anyone familiar with the confusion_matrix and classification_report from [scikit-learn](https://scikit-learn.org/stable/). Below follow basic instructions for instantiating the class.
+
+To create a confusion matrix, do:
+```python
+import cmat
+
+cm = cmat.ConfusionMatrix.create(
+  # 1D arrray with ground truth labels
+  y_true = ground_truth,
+  # 2D array with predictions
+  y_pred = predictions
+  # (optional) List of values that might occur in y_true/y_pred
+  labels = class_labels
+  # (optional) List of names corresponding to labels
+  names = class_names
+)
+```
+From there, you can get several metrics. A supplementary [jupyter notebook](notebooks/demo.ipynb) has been included for more in depth documentation.
+
+
+## Development 
+
+Since the project is so small, no CI features have been added. There is, however, a small test suite which at the time of writing got 66% coverage on the main script.j Pylint has not been applied because it hates my intentation style.
+
+Feel free to fork, post issues, or make pull requests if you have any suggestions to improvements.
+
+Some possible TODOs include:
+
+- Plot for comparing multiple confusion matrices w.r.t. a specific metric. This could be useful for e.g. cross-validation comparisons
+- Support for adding sample or class weight when creating the matrix