# server.py
import matplotlib.pyplot as plt
from shiny import render, ui, reactive
import faicons as fa
#from fontawesomefree import icons
import numpy as np
from utils import conlogo, vendorlogo
from utils import create_pie_chart, create_bar_chart, create_bar_chart, create_stacked_bar_chart
import plotly.express as px
from utils import load_data, filter_trips
from shinywidgets import output_widget, render_widget
import plotly.graph_objects as go

# Load the data
zones, trips = load_data()

def create_server(app_dir):
    def server(input, output, session):

        @render.image
        def rsglogo():
            return conlogo()
        
        @render.image
        def clientlogo():
            return vendorlogo()
        
        @render.plot
        def bar_chart():
            # Sample data for bar chart
            categories = ["Category A", "Category B", "Category C"]
            values = [10, 20, 30]

            return create_bar_chart(categories, values, plottitle = "Bar Chart Example")

        @render.plot
        def pie_chart():
            # Data for pie chart
            labels = ["Home-Based Work", "Home-Based Other", "Non-Home-Based"]
            #labels = [f"{icons['fa-car']} Cars", f"{icons['fa-bicycle']} Bikes", f"{icons['fa-bus']} Buses"]
            #labels = [f"{fa.icon_svg("briefcase")} Cars", f"{fa.icon_svg("briefcase")} Bikes", f"{fa.icon_svg("briefcase")} Buses"]
            

            sizes = [22, 41, 37]
            colors = ["#00b3b3", "#70d281", "#ff7f0e"]
            explode = (0.1, 0, 0)  # Explode the first slice for emphasis
            
            return create_pie_chart(labels, sizes, plottitle ="What Types of Trips are Occuring within Napa County on a Weekday?")

        @render.plot
        def stacked_bar_chart():
            # Data for the stacked bar chart
            categories = ["Early AM", "AM Peak", "Mid-Day", "PM Peak", "Evening"]
            intra_napa = [2000, 16000, 14000, 12000, 5000]
            into_napa = [1000, 8000, 2000, 3000, 2000]
            out_napa = [2000, 4000, 2000, 5000, 1000]

            return create_stacked_bar_chart(categories, intra_napa, into_napa, out_napa)
        
        # Reactive values to track selections
        selected_origin = reactive.Value(None)
        selected_destination = reactive.Value(None)

        @reactive.Effect
        #@reactive.event(input)
        @reactive.event(input.origin_map_click, input.destination_map_click)
        def update_selections():
            """Update selections when a map is clicked."""
            selected_origin.set(input.origin_map_click.get("customdata"))
            selected_destination.set(input.destination_map_click.get("customdata"))

        @reactive.Calc
        def filtered_data():
            """Filter trips based on selected origin or destination."""
            return filter_trips(trips, zones, selected_origin.get(), selected_destination.get())

        @output
        #@render.plot
        #@render.ui
        @render_widget
        def origin_map():
            filtered_origins, _ = filtered_data()
            fig = px.choropleth(
                filtered_origins,
                geojson=filtered_origins.geometry,
                locations=filtered_origins.index,
                color="trip_count",
                title="Trip Origins",
                custom_data=["FPID"],
                #mapbox_style="open-street-map",
                #zoom=7.5,
                #center={"lat": filtered_origins.geometry.centroid.y.mean(), "lon": filtered_origins.geometry.centroid.x.mean()},
                #opacity=0.7,
                # color_continuous_scale="amp",
                # labels={
                #     "Zone ID": "FPID",
                #     "Trips": "trip_count"
                # }
            )
            fig.update_geos(fitbounds="locations", visible=False)
            #fig.update_layout(coloraxis_colorbar=dict(title="Trip Count"))  # Add legend
            return fig
            #return ui.HTML(fig.to_html())
            #return ui.HTML(fig.to_html(full_html=False, include_plotlyjs="cdn"))

        @output
        #@render.plot
        #@render.ui
        @render_widget
        def destination_map():
            _, filtered_destinations = filtered_data()
            fig = px.choropleth(
                filtered_destinations,
                geojson=filtered_destinations.geometry,
                locations=filtered_destinations.index,
                color="trip_count",
                title="Trip Destinations",
                custom_data=["FPID"]
            )
            fig.update_geos(fitbounds="locations", visible=False)
            #fig.update_layout(coloraxis_colorbar=dict(title="Trip Count"))  # Add legend
            return fig
            #return ui.HTML(fig.to_html())
            #return ui.HTML(fig.to_html(full_html=False, include_plotlyjs="cdn"))
        
                
    return server