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import os
import streamlit as st
import pandas as pd
from io import StringIO
from util.evaluation import statistical_tests,calculate_correlations,calculate_divergences
def check_password():
def password_entered():
if password_input == os.getenv('PASSWORD'):
st.session_state['password_correct'] = True
else:
st.error("Incorrect Password, please try again.")
password_input = st.text_input("Enter Password:", type="password")
submit_button = st.button("Submit", on_click=password_entered)
if submit_button and not st.session_state.get('password_correct', False):
st.error("Please enter a valid password to access the demo.")
def app():
st.title('Result Evaluation')
if not st.session_state.get('password_correct', False):
check_password()
else:
st.sidebar.success("Password Verified. Proceed with the demo.")
# Allow users to upload a CSV file with processed results
uploaded_file = st.file_uploader("Upload your processed CSV file", type="csv")
if uploaded_file is not None:
data = StringIO(uploaded_file.getvalue().decode('utf-8'))
df = pd.read_csv(data)
st.write('Uploaded Data:', df)
if st.button('Evaluate Data'):
with st.spinner('Evaluating data...'):
statistical_results = statistical_tests(df)
correlation_results = calculate_correlations(df)
divergence_results = calculate_divergences(df)
flat_statistical_results = {f"Statistical_{key1}": value1 for key1, value1 in statistical_results.items()}
flat_correlation_results = {f"Correlation_{key1}": value1 for key1, value1 in correlation_results.items()}
flat_divergence_results = {f"Divergence_{key1}": value1 for key1, value1 in divergence_results.items()}
results_combined = {**flat_statistical_results, **flat_correlation_results, **flat_divergence_results}
results_df = pd.DataFrame(list(results_combined.items()), columns=['Metric', 'Value'])
st.write('Combined Results:', results_df)
st.download_button(
label="Download Evaluation Results",
data=results_df.to_csv(index=False).encode('utf-8'),
file_name='evaluation_results.csv',
mime='text/csv',
)
if __name__ == "__main__":
app()
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