| 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". | |
| """) |