import pandas as pd
import plotly.express as px
from dash import Dash, dcc, html, Input, Output
import base64
import qrcode
from io import BytesIO

# ---------- QR CODE SETUP ----------
public_url = "https://your-deployment-url.com/"  # Change this after deployment

def generate_qr_code(url):
    qr = qrcode.QRCode(box_size=4, border=2)
    qr.add_data(url)
    qr.make(fit=True)
    img = qr.make_image(fill="black", back_color="white")
    buffer = BytesIO()
    img.save(buffer, format="PNG")
    encoded = base64.b64encode(buffer.getvalue()).decode()
    return f"data:image/png;base64,{encoded}"

qr_code_img = generate_qr_code(public_url)

# ---------- DATA PREPARATION ----------
df = pd.read_csv("New_DNR.csv")

positive_df = df[df['Confirmed'] == 'Y'].copy()
positive_df = positive_df.dropna(subset=['X', 'Y'])
positive_df['County'] = positive_df['County'].str.strip().str.title()
positive_df['Sex'] = positive_df['Sex'].str.title()
positive_df['Age'] = positive_df['Age'].str.title()
positive_df['Year'] = positive_df['Year'].astype(int)

sex_options = [{'label': 'All', 'value': 'All'}] + [{'label': s, 'value': s} for s in sorted(positive_df['Sex'].dropna().unique())]
age_options = [{'label': 'All', 'value': 'All'}] + [{'label': a, 'value': a} for a in sorted(positive_df['Age'].dropna().unique())]
county_options = [{'label': 'All', 'value': 'All'}] + [{'label': c, 'value': c} for c in sorted(positive_df['County'].dropna().unique())]

years = sorted(positive_df['Year'].unique())
cumulative_data = []
for year in years:
    subset = positive_df[positive_df['Year'] <= year].copy()
    subset['Animation_Year'] = str(year)
    cumulative_data.append(subset)

cumulative_df = pd.concat(cumulative_data)

# ---------- DASH APP ----------
app = Dash(__name__)
server = app.server  # For deployment on platforms like Render

app.layout = html.Div([
    html.H1("CWD Cumulative Timelapse in Iowa from 2013-2024", style={'paddingBottom': '10px'}),

    html.Div([
        html.Label("Sex", style={'fontWeight': 'bold'}),
        dcc.Dropdown(id='sex-dropdown', options=sex_options, value='All', clearable=False),

        html.Br(),
        html.Label("Age", style={'fontWeight': 'bold'}),
        dcc.Dropdown(id='age-dropdown', options=age_options, value='All', clearable=False),

        html.Br(),
        html.Label("County", style={'fontWeight': 'bold'}),
        dcc.Dropdown(id='county-dropdown', options=county_options, value='All', clearable=False),

        html.Br(),
        html.Button("Reset Filters", id="reset-button", n_clicks=0, style={
            'marginTop': '10px', 'backgroundColor': '#f0f0f0', 'border': '1px solid #ccc'
        }),

        html.Br(), html.Br(),
        html.Label("Scan to View on Phone:", style={'fontWeight': 'bold'}),
        html.Img(src=qr_code_img, style={"width": "150px", "height": "150px", "marginTop": "10px"}),
    ], style={'width': '25%', 'display': 'inline-block', 'verticalAlign': 'top', 'paddingRight': '20px'}),

    html.Div([
        dcc.Loading(
            id="loading",
            type="circle",
            children=dcc.Graph(id='timelapse-map')
        ),
        html.Div(id='no-data-message', style={'color': 'red', 'fontWeight': 'bold', 'paddingTop': '10px'})
    ], style={'width': '70%', 'display': 'inline-block'})
], style={'padding': '20px'})


@app.callback(
    Output('sex-dropdown', 'value'),
    Output('age-dropdown', 'value'),
    Output('county-dropdown', 'value'),
    Input('reset-button', 'n_clicks'),
    prevent_initial_call=True
)
def reset_filters(n_clicks):
    return 'All', 'All', 'All'


@app.callback(
    Output('timelapse-map', 'figure'),
    Output('no-data-message', 'children'),
    Input('sex-dropdown', 'value'),
    Input('age-dropdown', 'value'),
    Input('county-dropdown', 'value')
)
def update_timelapse(selected_sex, selected_age, selected_county):
    df = cumulative_df.copy()

    if selected_sex != 'All':
        df = df[df['Sex'] == selected_sex]
    if selected_age != 'All':
        df = df[df['Age'] == selected_age]
    if selected_county != 'All':
        df = df[df['County'] == selected_county]

    if df.empty:
        fig = px.scatter_mapbox(
            pd.DataFrame(columns=['X', 'Y']),
            lat=[],
            lon=[],
            zoom=6,
            height=550
        )
        fig.update_layout(
            mapbox_style="carto-positron",
            margin={"r": 0, "t": 40, "l": 0, "b": 0},
            title="Cumulative Spread of CWD Over Time"
        )
        return fig, "No data available for the selected filters."

    fig = px.scatter_mapbox(
        df,
        lat="Y",
        lon="X",
        hover_name="County",
        hover_data={
            "X": False, "Y": False, "County": False,
            "Year": True, "Sex": True, "Age": True,
            "Animation_Year": False
        },
        animation_frame="Animation_Year",
        color_discrete_sequence=["red"],
        zoom=6,
        height=550
    )

    if fig.layout.sliders:
        for slider in fig.layout.sliders:
            slider.currentvalue.visible = False
            slider.pad = {"t": 30, "r": 150, "b": 0, "l": 100}

    fig.update_layout(
        mapbox_style="carto-positron",
        margin={"r": 0, "t": 40, "l": 0, "b": 0},
        title="Cumulative Spread of CWD Over Time"
    )

    return fig, ""


if __name__ == '__main__':
    app.run_server()