Spaces:
Sleeping
Sleeping
File size: 11,732 Bytes
69aa668 |
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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 |
import plotly.graph_objects as go
import plotly.express as px
from wordcloud import WordCloud
import matplotlib.pyplot as plt
import io
import base64
from typing import List, Dict
import numpy as np
import logging
logger = logging.getLogger(__name__)
class VisualizationGenerator:
"""
Generate various visualizations for emotion analysis
"""
def __init__(self):
"""Initialize visualization generator"""
self.emotion_colors = {
'joy': '#FFD700',
'sadness': '#4682B4',
'anger': '#DC143C',
'fear': '#483D8B',
'surprise': '#00CED1',
'neutral': '#A9A9A9',
'disgust': '#556B2F'
}
def create_visualizations(self, results: List[Dict]) -> Dict:
"""
Create all visualizations from emotion analysis results
Args:
results: List of emotion detection results
Returns:
Dictionary containing all visualization data
"""
try:
# Aggregate emotions
aggregated = self._aggregate_results(results)
# Create various charts
emotion_pie = self._create_emotion_pie(aggregated['emotions'])
emotion_bar = self._create_emotion_bar(aggregated['emotions'])
sentiment_gauge = self._create_sentiment_gauge(aggregated['sentiment_score'])
timeline = self._create_emotion_timeline(results)
radar_chart = self._create_emotion_radar(aggregated['emotions'])
return {
"emotion_pie": emotion_pie,
"emotion_bar": emotion_bar,
"sentiment_gauge": sentiment_gauge,
"emotion_timeline": timeline,
"emotion_radar": radar_chart,
"statistics": {
"total_texts": len(results),
"dominant_emotion": aggregated['dominant_emotion'],
"avg_sentiment": aggregated['sentiment_score'],
"sentiment_label": aggregated['sentiment_label']
}
}
except Exception as e:
logger.error(f"Error creating visualizations: {str(e)}")
return {}
def _aggregate_results(self, results: List[Dict]) -> Dict:
"""Aggregate multiple emotion results"""
if not results:
return {}
# Initialize
emotion_sums = {}
sentiment_sum = 0.0
# Aggregate
for result in results:
for emotion, score in result['emotions'].items():
emotion_sums[emotion] = emotion_sums.get(emotion, 0) + score
sentiment_sum += result.get('sentiment_score', 0)
# Calculate averages
n = len(results)
emotions_avg = {emotion: score / n for emotion, score in emotion_sums.items()}
# Get dominant
dominant = max(emotions_avg.items(), key=lambda x: x[1])
# Sentiment
avg_sentiment = sentiment_sum / n
sentiment_label = "positive" if avg_sentiment > 0.1 else "negative" if avg_sentiment < -0.1 else "neutral"
return {
"emotions": emotions_avg,
"dominant_emotion": dominant[0],
"sentiment_score": avg_sentiment,
"sentiment_label": sentiment_label
}
def _create_emotion_pie(self, emotions: Dict[str, float]) -> str:
"""Create a pie chart of emotion distribution"""
try:
# Filter significant emotions
significant = {k: v for k, v in emotions.items() if v > 0.05}
if not significant:
significant = emotions
# Create pie chart
fig = go.Figure(data=[go.Pie(
labels=[e.capitalize() for e in significant.keys()],
values=list(significant.values()),
marker=dict(colors=[self.emotion_colors.get(e, '#808080') for e in significant.keys()]),
hole=0.3,
textinfo='label+percent',
textfont=dict(size=14),
hovertemplate='<b>%{label}</b><br>%{percent}<extra></extra>'
)])
fig.update_layout(
title={
'text': 'Emotion Distribution',
'x': 0.5,
'xanchor': 'center',
'font': {'size': 20, 'color': '#333'}
},
showlegend=True,
height=400,
paper_bgcolor='rgba(0,0,0,0)',
plot_bgcolor='rgba(0,0,0,0)',
font=dict(family="Arial, sans-serif")
)
return fig.to_json()
except Exception as e:
logger.error(f"Error creating pie chart: {str(e)}")
return "{}"
def _create_emotion_bar(self, emotions: Dict[str, float]) -> str:
"""Create a bar chart of emotions"""
try:
# Sort emotions
sorted_emotions = sorted(emotions.items(), key=lambda x: x[1], reverse=True)
labels = [e[0].capitalize() for e in sorted_emotions]
values = [e[1] * 100 for e in sorted_emotions]
colors = [self.emotion_colors.get(e[0], '#808080') for e in sorted_emotions]
fig = go.Figure(data=[go.Bar(
x=labels,
y=values,
marker=dict(color=colors),
text=[f'{v:.1f}%' for v in values],
textposition='auto',
hovertemplate='<b>%{x}</b><br>%{y:.1f}%<extra></extra>'
)])
fig.update_layout(
title={
'text': 'Emotion Intensity',
'x': 0.5,
'xanchor': 'center',
'font': {'size': 20, 'color': '#333'}
},
xaxis_title='Emotion',
yaxis_title='Intensity (%)',
height=400,
paper_bgcolor='rgba(0,0,0,0)',
plot_bgcolor='rgba(0,0,0,0)',
font=dict(family="Arial, sans-serif"),
yaxis=dict(gridcolor='#E5E5E5')
)
return fig.to_json()
except Exception as e:
logger.error(f"Error creating bar chart: {str(e)}")
return "{}"
def _create_sentiment_gauge(self, sentiment_score: float) -> str:
"""Create a gauge chart for sentiment"""
try:
# Normalize to 0-100 scale
gauge_value = (sentiment_score + 1) * 50
# Determine color
if sentiment_score > 0.1:
color = '#28a745'
elif sentiment_score < -0.1:
color = '#dc3545'
else:
color = '#ffc107'
fig = go.Figure(go.Indicator(
mode="gauge+number+delta",
value=gauge_value,
domain={'x': [0, 1], 'y': [0, 1]},
title={'text': "Sentiment Score", 'font': {'size': 20}},
gauge={
'axis': {'range': [0, 100], 'tickwidth': 1},
'bar': {'color': color},
'steps': [
{'range': [0, 33], 'color': '#ffebee'},
{'range': [33, 66], 'color': '#fff9e6'},
{'range': [66, 100], 'color': '#e8f5e9'}
],
'threshold': {
'line': {'color': "red", 'width': 4},
'thickness': 0.75,
'value': 50
}
}
))
fig.update_layout(
height=300,
paper_bgcolor='rgba(0,0,0,0)',
font=dict(family="Arial, sans-serif")
)
return fig.to_json()
except Exception as e:
logger.error(f"Error creating gauge: {str(e)}")
return "{}"
def _create_emotion_timeline(self, results: List[Dict]) -> str:
"""Create a timeline of emotion changes"""
try:
if len(results) < 2:
return "{}"
# Extract emotion data over time
emotions_over_time = {}
for emotion in results[0]['emotions'].keys():
emotions_over_time[emotion] = [r['emotions'][emotion] * 100 for r in results]
# Create line chart
fig = go.Figure()
for emotion, values in emotions_over_time.items():
if max(values) > 5: # Only show significant emotions
fig.add_trace(go.Scatter(
x=list(range(1, len(values) + 1)),
y=values,
mode='lines+markers',
name=emotion.capitalize(),
line=dict(color=self.emotion_colors.get(emotion, '#808080'), width=2),
marker=dict(size=6)
))
fig.update_layout(
title={
'text': 'Emotion Timeline',
'x': 0.5,
'xanchor': 'center',
'font': {'size': 20, 'color': '#333'}
},
xaxis_title='Text Entry',
yaxis_title='Emotion Intensity (%)',
height=400,
paper_bgcolor='rgba(0,0,0,0)',
plot_bgcolor='rgba(0,0,0,0)',
font=dict(family="Arial, sans-serif"),
hovermode='x unified',
yaxis=dict(gridcolor='#E5E5E5'),
xaxis=dict(gridcolor='#E5E5E5')
)
return fig.to_json()
except Exception as e:
logger.error(f"Error creating timeline: {str(e)}")
return "{}"
def _create_emotion_radar(self, emotions: Dict[str, float]) -> str:
"""Create a radar chart of emotions"""
try:
categories = [e.capitalize() for e in emotions.keys()]
values = [v * 100 for v in emotions.values()]
fig = go.Figure()
fig.add_trace(go.Scatterpolar(
r=values,
theta=categories,
fill='toself',
fillcolor='rgba(75, 192, 192, 0.2)',
line=dict(color='rgb(75, 192, 192)', width=2),
marker=dict(size=8)
))
fig.update_layout(
polar=dict(
radialaxis=dict(
visible=True,
range=[0, max(values) * 1.2] if max(values) > 0 else [0, 100],
gridcolor='#E5E5E5'
),
angularaxis=dict(gridcolor='#E5E5E5')
),
title={
'text': 'Emotion Profile',
'x': 0.5,
'xanchor': 'center',
'font': {'size': 20, 'color': '#333'}
},
height=400,
paper_bgcolor='rgba(0,0,0,0)',
font=dict(family="Arial, sans-serif"),
showlegend=False
)
return fig.to_json()
except Exception as e:
logger.error(f"Error creating radar chart: {str(e)}")
return "{}"
|