# Check deepsea against
import kipoi
import pandas as pd
import numpy as np
import os
import pytest
model_root = "./"
def test_ref_seq():
# Get pure fasta predictions
model_dir = model_root + "./"
model = kipoi.get_model(model_dir, source="dir")
# The preprocessor
Dataloader = kipoi.get_dataloader_factory(model_dir, source="dir")
dataloader_arguments = {
"fasta_file": "/nfs/research1/stegle/users/rkreuzhu/opt/manuscript_code/data/raw/dataloader_files/shared/hg19.fa",
"intervals_file": "test_files/test_encode_roadmap.bed"
}
# predict using results
preds = model.pipeline.predict(dataloader_arguments)
#
res_orig = pd.read_csv("/nfs/research1/stegle/users/rkreuzhu/deeplearning/Basset/data/test_encode_roadmap_short_pred.txt", "\t", header=None)
assert np.isclose(preds, res_orig.values, atol=1e-3).all()
