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cc54551 | 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 | """Tests for dashboard visualization components."""
import pytest
import pandas as pd
import plotly.graph_objects as go
from ..components import (
# Traffic flow
create_speed_heatmap,
create_hourly_volume_chart,
create_congestion_timeline,
# Incentive analytics
create_funnel_chart,
create_spend_chart,
create_effectiveness_chart,
# Behavioral
create_elasticity_curve,
create_feature_importance_chart,
create_model_metrics_display,
# Simulation
create_scenario_comparison_chart,
create_cost_effectiveness_chart,
# Metrics
create_kpi_gauge,
create_metric_card,
create_sparkline,
# Map
create_corridor_map,
create_zone_comparison,
)
class TestTrafficComponents:
"""Test traffic flow visualization components."""
def test_speed_heatmap_empty_data(self):
"""Test heatmap handles empty data gracefully."""
df = pd.DataFrame()
fig = create_speed_heatmap(df)
assert isinstance(fig, go.Figure)
def test_speed_heatmap_with_data(self):
"""Test heatmap with valid data."""
df = pd.DataFrame({
'hour': list(range(24)),
'day_of_week': [0] * 24,
'avg_speed': [50] * 24
})
fig = create_speed_heatmap(df)
assert isinstance(fig, go.Figure)
assert len(fig.data) > 0
def test_hourly_volume_chart(self):
"""Test hourly volume chart creation."""
df = pd.DataFrame({
'hour': [7, 8, 9, 17, 18, 19],
'time_period': ['AM_PEAK'] * 3 + ['PM_PEAK'] * 3,
'total_vehicles': [100, 150, 120, 130, 160, 140],
'avg_speed': [35, 30, 32, 28, 25, 30]
})
fig = create_hourly_volume_chart(df)
assert isinstance(fig, go.Figure)
def test_congestion_timeline(self):
"""Test congestion timeline chart."""
df = pd.DataFrame({
'hour_bucket': pd.date_range('2024-01-01', periods=24, freq='h'),
'corridor_id': ['I-24'] * 24,
'avg_speed_mph': [45 + i % 10 for i in range(24)],
'level_of_service': ['B'] * 24
})
fig = create_congestion_timeline(df)
assert isinstance(fig, go.Figure)
class TestIncentiveComponents:
"""Test incentive analytics components."""
def test_funnel_chart(self):
"""Test funnel chart creation."""
df = pd.DataFrame({
'incentive_type': ['CARPOOL', 'PACER'],
'total_offers': [100, 80],
'accepts': [60, 50],
'completions': [40, 35]
})
fig = create_funnel_chart(df)
assert isinstance(fig, go.Figure)
def test_spend_chart(self):
"""Test spending pie chart."""
df = pd.DataFrame({
'incentive_type': ['CARPOOL', 'PACER', 'TRANSIT'],
'total_spend': [5000, 3000, 2000],
'n_events': [200, 150, 100],
'avg_payout': [25, 20, 20]
})
fig = create_spend_chart(df)
assert isinstance(fig, go.Figure)
def test_effectiveness_chart(self):
"""Test cost effectiveness bar chart."""
df = pd.DataFrame({
'incentive_type': ['CARPOOL', 'PACER'],
'n_completed': [40, 35],
'total_cost': [1000, 700],
'avg_cost': [25, 20]
})
fig = create_effectiveness_chart(df)
assert isinstance(fig, go.Figure)
class TestBehavioralComponents:
"""Test behavioral calibration components."""
def test_elasticity_curve(self):
"""Test elasticity curve visualization."""
df = pd.DataFrame({
'incentive_bucket': ['NONE', 'LOW', 'MEDIUM', 'HIGH'],
'n_trips': [100, 150, 120, 80],
'carpool_rate': [0.1, 0.18, 0.28, 0.38],
'avg_incentive': [0, 1.5, 3.5, 7.0]
})
fig = create_elasticity_curve(df)
assert isinstance(fig, go.Figure)
def test_feature_importance_chart(self):
"""Test feature importance bar chart."""
df = pd.DataFrame({
'feature': ['incentive', 'distance', 'time'],
'importance': [0.4, 0.35, 0.25]
})
fig = create_feature_importance_chart(df)
assert isinstance(fig, go.Figure)
def test_model_metrics_display(self):
"""Test model metrics radar chart."""
metrics = {'auc': 0.78, 'rmse': 0.15, 'accuracy': 0.82, 'n_samples': 1000}
fig = create_model_metrics_display(metrics)
assert isinstance(fig, go.Figure)
class TestSimulationComponents:
"""Test simulation comparison components."""
def test_scenario_comparison_chart(self):
"""Test scenario comparison bar chart."""
df = pd.DataFrame({
'scenario_name': ['Carpool', 'Pacer', 'Transit'],
'n_agents': [10000] * 3,
'treatment_avg_speed': [48, 46, 44],
'baseline_avg_speed': [42] * 3,
'speed_improvement_pct': [14.3, 9.5, 4.8],
'vmt_reduction_pct': [12, 8, 5],
'peak_reduction_pct': [10, 6, 4],
'treatment_spend': [5000, 4000, 3000]
})
fig = create_scenario_comparison_chart(df)
assert isinstance(fig, go.Figure)
def test_cost_effectiveness_chart(self):
"""Test cost vs impact scatter."""
df = pd.DataFrame({
'scenario_name': ['A', 'B'],
'treatment_spend': [5000, 3000],
'vmt_reduction_pct': [12, 8],
'speed_improvement_pct': [10, 6]
})
fig = create_cost_effectiveness_chart(df)
assert isinstance(fig, go.Figure)
class TestMetricsComponents:
"""Test real-time metrics components."""
def test_kpi_gauge(self):
"""Test KPI gauge creation."""
fig = create_kpi_gauge(75, 'Test Metric', '%', 0, 100)
assert isinstance(fig, go.Figure)
def test_metric_card(self):
"""Test metric card creation."""
fig = create_metric_card(42.5, 'Test Value', prefix='$', format_str='.1f')
assert isinstance(fig, go.Figure)
def test_sparkline(self):
"""Test sparkline creation."""
values = [10, 12, 15, 14, 18, 20]
fig = create_sparkline(values, 'Trend')
assert isinstance(fig, go.Figure)
class TestMapComponents:
"""Test geospatial components."""
def test_corridor_map(self):
"""Test corridor map creation."""
df = pd.DataFrame({
'segment_id': ['1', '2'],
'segment_name': ['Seg 1', 'Seg 2'],
'latitude': [36.10, 36.12],
'longitude': [-86.72, -86.75],
'avg_speed_mph': [35, 45],
'congestion_level': ['Moderate', 'Light'],
'vehicle_count': [400, 300]
})
fig = create_corridor_map(df)
assert isinstance(fig, go.Figure)
def test_zone_comparison(self):
"""Test zone comparison chart."""
df = pd.DataFrame({
'zone': ['Downtown', 'Suburbs'],
'avg_speed': [25, 45],
'carpool_rate': [0.25, 0.15],
'incentive_uptake': [0.35, 0.20]
})
fig = create_zone_comparison(df)
assert isinstance(fig, go.Figure)
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