import streamlit as st
import plotly.graph_objects as go
import plotly.express as px

def indicator_plot(value, title, value_range, domain):

    plot = go.Indicator(
        mode = 'gauge+delta',
        value = value,
        domain = domain,
        title = title,
        delta = {
            'reference': 0, 
            'decreasing': {'color': '#ec4899'},
            'increasing': {'color': '#36def1'}
            },
        gauge = {
            'axis': {'range': value_range, 'tickwidth': 1, 'tickcolor': 'black'},
            'bar': {'color': '#4361ee'},
            'bgcolor': 'white',
            'borderwidth': 2,
            'bordercolor': '#efefef',
            'steps': [
                {'range': [value_range[0], 0], 'color': '#efefef'},
                {'range': [0, value_range[1]], 'color': '#efefef'}
            ],
            'threshold': {
                'line': {'color': '#4361ee', 'width': 8},
                'thickness': 0.75,
                'value': value
            }
        }
    )

    return plot

def scatter_plot(df, group_var):

    colors = ['#36def1', '#4361ee'] if group_var else ['#4361ee']

    plot = px.scatter(
        df, 
        x='Machine-ratings', 
        y='Human-ratings',
        color=group_var,
        facet_col='x_group', 
        facet_col_wrap=2,
        trendline='ols',
        trendline_scope='trace',
        hover_data={
            'Text': df.text,
            'Language': False,
            'x_group': False,            
            'Human-ratings': ':.2f',
            'Machine-ratings': ':.2f',
            'Study': df.study,
            'Instrument': df.instrument,
        },
        width=400,
        height=400,
        color_discrete_sequence=colors
    )
    
    plot.for_each_annotation(lambda a: a.update(text=a.text.split('=')[-1]))
    plot.update_layout(
        legend={
            'orientation':'h',
            'yanchor': 'bottom',
            'y': -.30
        })
    plot.update_xaxes(title_standoff = 0)

    return plot

def show_scores(sentiment, desirability, input_text):
    with st.container():
        p1 = indicator_plot(
            value=sentiment,
            title=f'Item Sentiment',
            value_range=[-1, 1],
            domain={'x': [0, .45], 'y': [0, .5]},
        )

        p2 = indicator_plot(
            value=desirability,
            title=f'Item Desirability',
            value_range=[-4, 4],
            domain={'x': [.55, 1], 'y': [0, .5]}
        )

        fig = go.Figure()
        fig.add_trace(p1)
        fig.add_trace(p2)

        fig.update_layout(
            title=dict(text=f'"{input_text}"', font=dict(size=36),yref='paper'),
            paper_bgcolor = 'white', 
            font = {'color': 'black', 'family': 'Arial'})
            
        st.plotly_chart(fig, theme=None, use_container_width=True)
                
        st.markdown("""
            Item sentiment: Absolute differences between positive and negative sentiment.
            Item desirability: z-transformed values, 0 indicated "neutral".        
        """)