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| from matplotlib.cm import get_cmap | |
| import plotly.graph_objects as go | |
| class NQDOverview(object): | |
| def __init__(self, parent, results, | |
| dial_cmap='RdYlGn'): | |
| self.p = parent | |
| self.results = results | |
| self.cmap = get_cmap(dial_cmap) | |
| def _get_color(self): | |
| color = self.cmap(self.results['qual']['label'] / 6.0) | |
| color = f'rgba({int(color[0]*256)}, {int(color[1]*256)}, {int(color[2]*256)}, {int(color[3]*256)})' | |
| return color | |
| def _build_figure(self): | |
| color = self._get_color() | |
| fig = go.Figure(go.Indicator( | |
| domain = {'x': [0, 1], 'y': [0, 1]}, | |
| value = self.results['qual']['label'], | |
| mode = "gauge+number", | |
| title = {'text': "QuAL"}, | |
| gauge = {'axis': {'range': [None, 5], 'showticklabels': True, 'ticks': ""}, | |
| 'bgcolor': 'lightgray', | |
| 'bar': {'color': color, 'thickness': 1.0} | |
| } | |
| ), | |
| layout=go.Layout(margin=dict(t=0, b=135)) | |
| ) | |
| return fig | |
| def draw(self): | |
| st = self.p | |
| fig = self._build_figure() | |
| cols = st.columns([7, 3]) | |
| with cols[0]: | |
| st.plotly_chart(fig, use_container_width=True) | |
| with cols[1]: | |
| q1lab = self.results['q1']['label'] | |
| if q1lab == 0: | |
| md_str = '😥 None' | |
| elif q1lab == 1: | |
| md_str = '😐 Low' | |
| elif q1lab == 2: | |
| md_str = '😊 Medium' | |
| elif q1lab == 3: | |
| md_str = '😁 High' | |
| cols[1].metric('Level of Detail', md_str, | |
| help='How specific was the evaluator in describing the behavior?') | |
| q2lab = self.results['q2i']['label'] | |
| if q2lab == 0: | |
| md_str = '✅ Yes' | |
| else: | |
| md_str = '❌ No' | |
| cols[1].metric('Suggestion Given', (md_str), | |
| help='Did the evaluator give a suggestion for improvement?') | |
| q3lab = self.results['q3i']['label'] | |
| if q3lab == 0: | |
| md_str = '✅ Yes' | |
| else: | |
| md_str = '❌ No' | |
| cols[1].metric('Suggestion Linked', md_str, | |
| help='Is the suggestion for improvement linked to the described behavior?') |