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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)
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