plots.py

import streamlit as st
import matplotlib
import matplotlib.pyplot as plt
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():

        num_steps = 10        
        colorscale = plt.get_cmap('viridis', num_steps)
  
        steps_sentiment = [{
            'range': [i/num_steps*2-1, (i+1)/num_steps*2-1],
            'color': matplotlib.colors.rgb2hex(colorscale(i)[:3])
        } for i in range(num_steps)]

        steps_desirability = [{
            'range': [i/num_steps*8-4, (i+1)/num_steps*8-4],
            'color': matplotlib.colors.rgb2hex(colorscale(i)[:3])
            } for i in range(num_steps)]        

        plot1 = go.Indicator(
            mode = 'number+gauge',
            value = sentiment,
            domain = {'x': [0.25, 1], 'y': [0.45, 0.65]},
            title = {'text': 'Sentiment', 'font': {'color': 'black', 'size': 22}},
            number={'font': {'color': 'black', 'size': 26}, 'valueformat': '.2f'},
            gauge = {
                'shape': 'bullet',
                'axis': {'range': [-1, 1]},
                'threshold': {
                    'line': {'color': '#36def1', 'width': 10},
                    'thickness': 0.75,
                    'value': sentiment},
                'steps': steps_sentiment,
                'bar': {'color': 'rgba(0,0,0,0)'}
            }
        )
        
        plot2 = go.Indicator(
            mode = 'number+gauge',
            value = desirability,
            domain = {'x': [0.25, 1], 'y': [0.15, 0.35]},
            title = {'text': 'Desirability', 'font': {'color': 'black', 'size': 22}},
            number={'font': {'color': 'black', 'size': 26}, 'valueformat': '.2f'},
            gauge = {
                'shape': 'bullet',
                'axis': {'range': [-4, 4]},
                'threshold': {
                    'line': {'color': '#36def1', 'width': 10},
                    'thickness': 0.75,
                    'value': desirability},
                'steps': steps_desirability,
                'bar': {'color': 'rgba(0,0,0,0)'}
            }
        )

        fig = go.Figure()
        fig.add_trace(plot1)
        fig.add_trace(plot2)

        plot_title = f'Estimated Sentiment and Desirability for <br><i>"{input_text}</i>"'

        fig.update_layout(    
            annotations=[
                go.layout.Annotation(
                    text=plot_title,
                    align='center',
                    showarrow=False,
                    xref='paper',
                    yref='paper',
                    x=0.5,
                    y=.85,
                    xanchor='center',
                    yanchor='bottom',
                    font=dict(size=22)
                ),
                go.layout.Annotation(
                    text="Negative",
                    showarrow=False,
                    xref='paper',
                    yref='paper',
                    x=0.25,
                    y=0.8,
                    font=dict(size=18)
                ),
                go.layout.Annotation(
                    text="Positive",
                    showarrow=False,
                    xref='paper',
                    yref='paper',
                    x=.81,
                    y=.8,
                    font=dict(size=18)
                ),
            ],

            font = {'color': 'black', 'family': 'Arial'},
            height=300,
            margin={'t': 50, 'b': 0, 'l': 0}
        )

        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".        
        """)