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?')