Quickstart¶
A quick example how to learn a model on a given dataset.
from distfit import distfit
import numpy as np
X = np.random.normal(0, 2, 1000)
y = [-8,-6,0,1,2,3,4,5,6]
# Initialize model
dist = distfit()
# Find best theoretical distribution for emperical data X
dist.fit_transform(X)
dist.plot()
# Make prediction
dist.predict(y)
dist.plot()
Installation¶
Create environment
If desired, install distfit
in an isolated Python environment using conda:
conda create -n env_distfit python=3.6
conda activate env_distfit
Install via pip
:
# The installation from pypi is disabled:
pip install distfit
# Install directly from github
pip install git+https://github.com/erdogant/distfit
Uninstalling¶
If you want to remove your distfit
installation with your environment, it can be as following:
# List all the active environments. distfit should be listed.
conda env list
# Remove the distfit environment
conda env remove --name env_distfit
# List all the active environments. distfit should be absent.
conda env list