weer

# %% markdown
# WEER IMPACT

# %%
# SETUP
import pandas as pd
import numpy as np
import pickle
import matplotlib
import matplotlib.pyplot as plt
import shap
shap.initjs()

# %%
# DATA
pickle_in = open('booster.pickle', 'rb')
booster = pickle.load(pickle_in) # Load XGBoost booster object

pickle_in = open('features.pickle', 'rb')
features = pickle.load(pickle_in) # Load features object

# %%
# SHAP VALUE COMPUTATION
explainer = shap.TreeExplainer(booster)
shap_values = explainer.shap_values(features).astype('float64')

# %%
# SHAP ATTRIBUTIONS
shap.summary_plot(shap_values, features, max_display=20, show=False, auto_size_plot=True)