app.py

import streamlit as st
from predict_chromosome import predict_and_write


st.title("DeepLoop")


#########
# INPUT #
#########

# TODO A drop down of models for different depths
# depth = st.selectbox("Select Model", ["Model 1", "Model 2", "Model 3"])
# HACK
chromosome = "chr11"

# Load the model from hugging face
from huggingface_hub import from_pretrained_keras

model = from_pretrained_keras("funlab/DeepLoop-CPGZ-LoopDenoise")

from huggingface_hub import snapshot_download

anchors = snapshot_download(
    repo_id="funlab/hg19_HindIII_anchor_bed", repo_type="dataset"
)
HiCorr_data = snapshot_download("funlab/HiCorr_test_data", repo_type="dataset")

predict_and_write(
    model,
    full_matrix_dir=HiCorr_data + f"/anchor_2_anchor.loop.{chromosome}",
    input_name=HiCorr_data + f"/anchor_2_anchor.loop.{chromosome}.p_val",
    outdir="results",
    anchor_dir=anchors,
    chromosome=chromosome,
    small_matrix_size=128,
    step_size=128,
    dummy=5,
    # max_dist,
    val_cols=["obs" "exp" "pval"],
    # keep_zeros,
)

# Print and list the files
import os

st.write("Files created:")
st.write(os.listdir("results"))

# Offer a download
st.write("Download the results")
st.download_button(
    label="Download Results",
    data="results",
    file_name="results.zip",
    mime="application/zip",
)