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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.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, convert_date, gen_fig
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:
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)
pred_hour_choice = st.selectbox(
"Choose Your Planned Hour",
options= hours,
key = "pred_hour", index = hours.index("08:00")
)
pred_view_choice = st.selectbox(
"Choose View",
options= ['Johor-Tuas','Johor-Woodlands', 'Tuas-Johor', 'Woodlands-Johor'],
key = "pred_view"
)
d = st.date_input(
"Choose Your Planned Date",
date(today[0],today[1], today[2]))
starter_variables = [x_train, str(d), pred_hour_choice, pred_view_choice]
st.plotly_chart(predicted_figure(clf, starter_variables, figs))
if __name__ == "__main__":
main() |