Maybe they'll be printed?

predict_chromosome.py

@@ -8,6 +8,7 @@ import time
 from tqdm import tqdm
 from tensorflow.keras.models import model_from_json
 from scipy.sparse import csr_matrix, triu
+import streamlit as st
 
 logger = getLogger(__name__)
 
@@ -144,6 +145,7 @@ def predict_and_write(
         names=["anchor1", "anchor2"] + val_cols,
         usecols=["anchor1", "anchor2"] + val_cols,
     )  # read chromosome anchor to anchor file
+    st.dataframe(chr_anchor_file)
     if "obs" in val_cols and "exp" in val_cols:
         chr_anchor_file["ratio"] = (chr_anchor_file["obs"] + dummy) / (
             chr_anchor_file["exp"] + dummy
@@ -175,6 +177,7 @@ def predict_and_write(
             chr_tile["anchor2"].values
         )  # convert anchor names to column indices
         logger.info(chr_tile)
+        st.dataframe(chr_tile)
         sparse_matrix = csr_matrix(
             (chr_tile["ratio"], (rows, cols)),
             shape=(anchor_step, anchor_step),