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| import streamlit as st | |
| import altair as alt | |
| import pandas as pd | |
| from plots import altair_gauge, pred_bar_chart | |
| import streamlit.components.v1 as components | |
| md_about_qual = ''' | |
| The Quality of Assessment for Learning (QuAL) score measures three | |
| components of high-quality feedback via three subscores: | |
| 1. A detailed description of the behavior observed (rated 0-3 depending on detail level) | |
| 2. A suggestion for improvement is present (rated no = 0, yes = 1) | |
| 3. Linkage between the behavior and the suggestion is present (rated no = 0, yes = 1) | |
| The final QuAL score is the sum of these subscores, so it ranges from 0 (lowest quality) | |
| to 5 (highest quality). | |
| ''' | |
| class NQDFullReport(object): | |
| def __init__(self, parent : st, results : dict): | |
| self.p = parent | |
| self.results = results | |
| def draw(self): | |
| st = self.p | |
| st.header('Understand Your Score') | |
| st.subheader('About the QuAL Score') | |
| # with st.expander('About the QuAL Score', True): | |
| st.markdown(md_about_qual) | |
| st.subheader('Level of Detail') | |
| c1, c2 = st.columns(2) | |
| with c1: | |
| gauge = altair_gauge(self.results['q1']['label'], 3, 'Level of Detail') | |
| gauge_html = gauge.to_html() | |
| # components.html(gauge_html, height=225, width=334) | |
| st.altair_chart(gauge, use_container_width=True) | |
| with c2: | |
| bar = pred_bar_chart(self.results['q1']['scores']) | |
| st.altair_chart(bar, use_container_width=True) | |
| st.subheader('Suggestion for Improvement') | |
| c1, c2 = st.columns(2) | |
| with c1: | |
| q2lab = self.results['q2i']['label'] | |
| st.markdown('#### Suggestion Given') | |
| if q2lab == 0: | |
| md_str = '# ✅ Yes' | |
| else: | |
| md_str = '# ❌ No' | |
| st.markdown(md_str) | |
| # st.metric('Suggestion Given', (md_str), | |
| # help='Did the evaluator give a suggestion for improvement?') | |
| gauge = altair_gauge(self.results['q2i']['label'], 1, 'Suggestion for Improvement') | |
| # st.altair_chart(gauge, use_container_width=True) | |
| with c2: | |
| bar = pred_bar_chart(self.results['q2i']['scores'], binary_labels={0: 'Yes', 1: 'No'}) | |
| st.altair_chart(bar, use_container_width=True) | |
| st.subheader('Suggestion Linking') | |
| c1, c2 = st.columns(2) | |
| with c1: | |
| q2lab = self.results['q3i']['label'] | |
| st.markdown('#### Suggestion Linked') | |
| if q2lab == 0: | |
| md_str = '# ✅ Yes' | |
| else: | |
| md_str = '# ❌ No' | |
| st.markdown(md_str) | |
| # st.metric('Suggestion Given', (md_str), | |
| # help='Did the evaluator give a suggestion for improvement?') | |
| gauge = altair_gauge(self.results['q3i']['label'], 1, 'Suggestion for Improvement') | |
| # st.altair_chart(gauge, use_container_width=True) | |
| with c2: | |
| bar = pred_bar_chart(self.results['q3i']['scores'], binary_labels={0: 'Yes', 1: 'No'}) | |
| st.altair_chart(bar, use_container_width=True) | |