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import harmonypy as hm
import pandas as pd
import numpy as np
def test_lisi():
X = pd.read_csv("data/lisi_x.tsv.gz", sep = "\t")
metadata = pd.read_csv("data/lisi_metadata.tsv.gz", sep = "\t")
label_colnames = metadata.columns
perplexity = 30
lisi = hm.compute_lisi(X, metadata, label_colnames, perplexity)
lisi_test = pd.read_csv("data/lisi_lisi.tsv.gz", sep="\t")
lisi_test = lisi_test.iloc[:,-2:].to_numpy()
assert np.allclose(lisi, lisi_test)
# def timereps(reps, func):
# from time import time
# start = time()
# for i in range(0, reps):
# func()
# end = time()
# return (end - start) / reps
#
# # 0.3 seconds per loop (too slow)
# timereps(10, lambda: hm.compute_lisi(X, metadata, label_colnames, perplexity))
#
#
# # Try https://github.com/rkern/line_profiler
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