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cd cpp
cmake -DCMAKE_BUILD_TYPE=Release -S. -B build
cd build
make FUSINTER_v3_pybind 

import numpy as np

from fusinter import FUSINTERDiscretizer
from sklearn.datasets import load_iris

x = load_iris()["data"]
y = load_iris()["target"]

discretizer = FUSINTERDiscretizer(0.95, 0.99)
discretizer.fit(x,y)

print(discretizer.splits)
print(discretizer.transform(x))

import numpy as np
import pandas as pd
from fusinter import FUSINTERDiscretizer

cov_x = pd.read_csv("datasets/covtype.data", header=None)
data_y = cov_x.pop(cov_x.shape[1] - 1).to_numpy()
data_x = cov_x.iloc[:, 0:10].to_numpy()

discretizer1 = FUSINTERDiscretizer().fit(data_x, data_y)
results1 = discretizer1.transform(data_x)
discretizer1.save_splits("splits.txt")

discretizer2 = FUSINTERDiscretizer()
discretizer2.load_splits("splits.txt")
results2 = discretizer2.transform(data_x)

if np.all(results1 == results2):
    print("it worked")
else:
    print("it failed")

alpha = 0.95
lam = 0.975
start = time.perf_counter()
discretizer = FUSINTERDiscretizer(alpha, lam, not_concurrent=False, discretizer_python=False)
res1 = discretizer.fit(data_x, data_y)

discretizer = FUSINTERDiscretizer(min_examples_in_interval=100).fit(data_x, data_y)