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aa0f861 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 | import plotly.graph_objects as go
import plotly.express as px
from plotly.subplots import make_subplots
import pandas as pd
from models import EcoScoreResult
class SustainabilityVisualizer:
@staticmethod
def create_eco_score_gauge(eco_score: float) -> go.Figure:
"""Create a gauge chart for the eco score"""
# Determine color based on score
if eco_score >= 7:
color = "green"
elif eco_score >= 4:
color = "orange"
else:
color = "red"
fig = go.Figure(go.Indicator(
mode = "gauge+number",
value = eco_score,
domain = {'x': [0, 1], 'y': [0, 1]},
title = {'text': "Eco Score", 'font': {'size': 24}},
gauge = {
'axis': {'range': [1, 10], 'tickwidth': 1},
'bar': {'color': color},
'steps': [
{'range': [1, 4], 'color': 'lightcoral'},
{'range': [4, 7], 'color': 'lightsalmon'},
{'range': [7, 10], 'color': 'lightgreen'}
],
'threshold': {
'line': {'color': "black", 'width': 4},
'thickness': 0.75,
'value': eco_score
}
}
))
fig.update_layout(
height=300,
margin=dict(l=10, r=10, t=50, b=10)
)
return fig
@staticmethod
def create_impact_breakdown(eco_result: EcoScoreResult) -> go.Figure:
"""Create a bar chart showing impact breakdown"""
factors = ['Deforestation', 'Pollution', 'Biodiversity']
scores = [
eco_result.factors.deforestation_risk,
eco_result.factors.pollution_risk,
eco_result.factors.biodiversity_impact
]
colors = ['brown' if s > 7 else 'orange' if s > 4 else 'green' for s in scores]
fig = go.Figure(data=[
go.Bar(
x=factors,
y=scores,
marker_color=colors,
text=[f"{s}/10" for s in scores],
textposition='outside',
)
])
fig.update_layout(
title="Environmental Impact Breakdown",
xaxis_title="Impact Factors",
yaxis_title="Risk Level (1-10)",
yaxis=dict(range=[0, 11]),
height=400,
showlegend=False
)
return fig
@staticmethod
def create_radar_chart(eco_result: EcoScoreResult) -> go.Figure:
"""Create a radar chart for environmental impact"""
categories = ['Deforestation Risk', 'Pollution Risk', 'Biodiversity Impact']
fig = go.Figure()
# Add trace for product
fig.add_trace(go.Scatterpolar(
r=[
eco_result.factors.deforestation_risk,
eco_result.factors.pollution_risk,
eco_result.factors.biodiversity_impact
],
theta=categories,
fill='toself',
name=eco_result.product_name,
line_color='red'
))
# Add ideal trace (low impact)
fig.add_trace(go.Scatterpolar(
r=[2, 2, 2],
theta=categories,
fill='toself',
name='Ideal (Low Impact)',
line_color='green',
opacity=0.3
))
fig.update_layout(
polar=dict(
radialaxis=dict(
visible=True,
range=[0, 10]
)),
showlegend=True,
height=400,
title="Environmental Impact Radar"
)
return fig
@staticmethod
def create_comparison_chart(product_name: str, alternatives: list,
product_score: float, alt_scores: list) -> go.Figure:
"""Create a comparison chart between product and alternatives"""
names = [product_name] + [alt['name'] for alt in alternatives]
scores = [product_score] + alt_scores
colors = ['red'] + ['green'] * len(alternatives)
fig = go.Figure(data=[
go.Bar(
x=names,
y=scores,
marker_color=colors,
text=[f"{s}/10" for s in scores],
textposition='outside',
)
])
fig.update_layout(
title="Product vs Alternatives - Eco Score Comparison",
xaxis_title="Products",
yaxis_title="Eco Score (1-10)",
yaxis=dict(range=[0, 11]),
height=400,
showlegend=False
)
return fig |