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| import streamlit as st | |
| import pandas as pd | |
| import plotly.express as px | |
| from datasets import load_dataset | |
| import os | |
| from src.basic_plot import basic_chart | |
| from src.map_viz import calling_map_viz | |
| from src.map_viz_pred import calling_pred_map_viz | |
| from src.data_ingestion import daily_average | |
| from src.heatmap import HeatMap | |
| from src.data_ingestion import remove_previous_view, merge_volumes | |
| from src.pred_plot import prep_data_pred_plot, data_split, train_model, predicted_figure, get_today, gen_fig, pred_bars | |
| from datetime import date | |
| def fetch_data(): | |
| # comment out for local testing, but be sure to include after testing | |
| dataset = load_dataset("tappyness1/causion", use_auth_token=os.environ['TOKEN']) | |
| # print (dataset) | |
| # print (pd.DataFrame(dataset['train'])) | |
| counts_df = pd.DataFrame(dataset['train']) | |
| # only use this part before for local testing | |
| # once local testing is completed, comment out and use the dataset above | |
| # counts_df = pd.read_csv("data/counts_dataset.csv") | |
| return counts_df | |
| def main(): | |
| counts_df = fetch_data() | |
| pred_df = counts_df.copy() | |
| counts_df1 = counts_df.copy() | |
| counts_df = remove_previous_view(counts_df) | |
| counts_df = merge_volumes(counts_df) | |
| # st.set_page_config(layout="wide") | |
| height = 650 | |
| st.markdown(""" <style> | |
| #MainMenu {visibility: hidden;} | |
| footer {visibility: hidden;} | |
| </style> """, | |
| unsafe_allow_html=True | |
| ) | |
| hours = [ | |
| "00:00", "01:00", "02:00", "03:00", "04:00", "05:00", | |
| "06:00", "07:00", "08:00", "09:00", "10:00", "11:00", | |
| "12:00", "13:00", "14:00", "15:00", "16:00", "17:00", | |
| "18:00", "19:00", "20:00", "21:00", "22:00", "23:00", | |
| ] | |
| st.write("<- Click on the sidebar to select your plot preferences") | |
| # Select Plot Option | |
| plot_type = st.sidebar.selectbox("Choose Plot Type", options = ['Historical', 'Predictive']) | |
| if plot_type == 'Historical': | |
| st.sidebar.markdown("Select Plots to show") | |
| checkbox_one = st.sidebar.checkbox('Overall Traffic', value = True) # rename as necessary | |
| checkbox_two = st.sidebar.checkbox('Traffic Map', value = True) | |
| checkbox_three = st.sidebar.checkbox('Heat Map', value = True) | |
| view_options = list(counts_df["view"].unique()) | |
| view_options.append('All') | |
| view = st.sidebar.selectbox("Choose View", options=view_options, index = view_options.index("Woodlands - to Johor")) | |
| if view != 'All': | |
| st.header(f"Showing Traffic for {view}") | |
| counts_df = counts_df[counts_df['view'] == view] | |
| if checkbox_one: | |
| st.subheader("Overall Traffic") | |
| plot = st.selectbox("Choose Plot", options=["Day", "Hour", "Raw"], index = 0) | |
| st.plotly_chart(basic_chart(counts_df, plot = plot),use_container_width=True) | |
| if checkbox_two: | |
| st.subheader("Traffic Map") | |
| st.pyplot(calling_map_viz(counts_df1)) | |
| if checkbox_three: | |
| heatmap = HeatMap(counts_df) | |
| # st.header("Mean Vehicle Count by Day of Week") | |
| # st.plotly_chart(heatmap.vehicle_count_bar()) | |
| st.subheader("Heatmap") | |
| st.plotly_chart(heatmap.heatmap()) | |
| hour_choice = st.selectbox( | |
| "Choose Hour", | |
| options= hours, | |
| key = "hour", index = hours.index("08:00") | |
| ) | |
| st.subheader(f"Traffic Volume of Each Day at {hour_choice}") | |
| st.plotly_chart(heatmap.update_hour_bar_chart(hour_choice)) | |
| days = ["Monday", "Tuesday", "Wednesday", | |
| "Thursday", "Friday","Saturday", "Sunday"] | |
| day_choice = st.selectbox("Choose Day of the Week", options = days, key = "day", index = days.index("Saturday")) | |
| st.subheader(f"Traffic Volume of Each Hour on {day_choice}") | |
| st.plotly_chart(heatmap.update_day_bar_chart(day_choice)) | |
| else: | |
| st.sidebar.markdown("Select Plots to show") | |
| checkbox_two_pred = st.sidebar.checkbox('Predictive Traffic Map', value = True) | |
| figs = gen_fig() | |
| today = get_today() | |
| final_table = prep_data_pred_plot(pred_df) | |
| x_train, _, y_train, _ = data_split(final_table) | |
| clf = train_model(x_train, y_train) | |
| col1, col2, col3 = st.columns(3) | |
| with col1: | |
| d = st.date_input( | |
| "Choose Your Planned Date", | |
| date(today[0],today[1], today[2])) | |
| with col2: | |
| pred_view_choice = st.selectbox( | |
| "Choose View", | |
| options= ['Johor-Tuas','Johor-Woodlands', 'Tuas-Johor', 'Woodlands-Johor'], | |
| key = "pred_view" | |
| ) | |
| with col3: | |
| pred_hour_choice = st.selectbox( | |
| "Choose Your Planned Hour", | |
| options= hours, | |
| key = "pred_hour", index = hours.index("08:00") | |
| ) | |
| starter_variables = [x_train, str(d), pred_hour_choice, pred_view_choice] | |
| st.plotly_chart(predicted_figure(clf, starter_variables, figs)) | |
| st.plotly_chart(pred_bars(d, final_table)) | |
| if checkbox_two_pred: | |
| st.subheader("Predictive Traffic Map") | |
| hour_choice = st.selectbox( | |
| "Choose Hour", | |
| options= hours, | |
| key = "hour", index = hours.index("08:00") | |
| ) | |
| days = ["Monday", "Tuesday", "Wednesday", | |
| "Thursday", "Friday","Saturday", "Sunday"] | |
| day_choice = st.selectbox("Choose Day of the Week", options = days, key = "day", index = days.index("Saturday")) | |
| st.pyplot(calling_pred_map_viz(counts_df, day_choice, hour_choice)) | |
| if __name__ == "__main__": | |
| main() |