refactor: Clean up "results" folder

app.py

@@ -13,6 +13,7 @@ st.title("DeepLoop")
 # depth = st.selectbox("Select Model", ["Model 1", "Model 2", "Model 3"])
 # HACK
 chromosome = "chr11"
+prefix = "results"
 
 # Load the model from hugging face
 from huggingface_hub import from_pretrained_keras
@@ -28,13 +29,13 @@ HiCorr_data = snapshot_download("funlab/HiCorr_test_data", repo_type="dataset")
 
 import os
 
-os.makedirs("results", exist_ok=True)
+os.makedirs(prefix, exist_ok=True)
 
-predict_and_write(
+denoised_anchor_to_anchor = 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",
+    outdir=prefix,
     anchor_dir=anchors,
     chromosome=chromosome,
     small_matrix_size=128,
@@ -46,15 +47,11 @@ predict_and_write(
 )
 
 # Print and list the files
-
-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",
+    label="Download Denoised Results",
+    data=os.path.join(prefix, chromosome + ".denoised.anchor.to.anchor"),
+    file_name=chromosome + ".denoised.anchor.to.anchor",
+    mime="text/csv",
 )
+st.dataframe(denoised_anchor_to_anchor)
+st.write(os.listdir(prefix))

predict_chromosome.py

@@ -221,13 +221,7 @@ def predict_and_write(
         index=False,
         header=False,
     )
-    st.download_button(
-        label="Download Denoised Results",
-        data=os.path.join(outdir, chromosome + ".denoised.anchor.to.anchor"),
-        file_name=chromosome + ".denoised.anchor.to.anchor",
-        mime="text/csv",
-    )
-    st.dataframe(denoised_anchor_to_anchor)
+    return denoised_anchor_to_anchor
 
 
 if __name__ == "__main__":