// ABOUTME: Unit tests for pattern_detection module
// ABOUTME: Tests pattern detection functionality with comprehensive test coverage
//
// SPDX-License-Identifier: MIT OR Apache-2.0
// Copyright (c) 2025 Pierre Fitness Intelligence
#![allow(clippy::unwrap_used, clippy::expect_used, clippy::panic)]
#![allow(missing_docs)]
use chrono::{Duration, Utc};
use pierre_mcp_server::intelligence::{PatternDetector, RiskLevel};
use pierre_mcp_server::models::{Activity, ActivityBuilder, SportType};
fn create_test_activity(days_ago: i64, distance_km: f64, avg_hr: Option<u32>) -> Activity {
let date = Utc::now() - Duration::days(days_ago);
#[allow(clippy::cast_possible_truncation, clippy::cast_sign_loss)]
let duration = (distance_km * 300.0) as u64; // ~5 min/km pace
let mut builder = ActivityBuilder::new(
format!("test_{}", date.timestamp()),
"Test Activity",
SportType::Run,
date,
duration,
"test",
)
.distance_meters(distance_km * 1000.0);
if let Some(hr) = avg_hr {
builder = builder.average_heart_rate(hr);
}
builder.build()
}
#[test]
fn test_weekly_schedule_detection() {
// Create consistent Monday/Wednesday/Friday pattern
let mut activities = Vec::new();
for week in 0..4 {
activities.push(create_test_activity(week * 7, 10.0, Some(140))); // Monday
activities.push(create_test_activity(week * 7 + 2, 8.0, Some(135))); // Wednesday
activities.push(create_test_activity(week * 7 + 4, 12.0, Some(145)));
// Friday
}
let pattern = PatternDetector::detect_weekly_schedule(&activities);
// With 3 equally distributed days, consistency score ~= 33 (1/3² + 1/3² + 1/3²) * 100
assert!(
pattern.consistency_score > 30.0,
"Expected consistency > 30, got {}",
pattern.consistency_score
);
assert!(pattern.avg_activities_per_week > 2.5);
}
#[test]
fn test_hard_easy_pattern_detection() {
// Create alternating hard/easy pattern
let mut activities = Vec::new();
for i in 0..10 {
let is_hard = i % 2 == 0;
let hr = if is_hard { 170 } else { 130 };
activities.push(create_test_activity(i, 10.0, Some(hr)));
}
let pattern = PatternDetector::detect_hard_easy_pattern(&activities);
assert!(pattern.pattern_detected);
assert!(pattern.hard_percentage > 40.0 && pattern.hard_percentage < 60.0);
}
#[test]
fn test_hr_drift_detection() {
// Create activities with increasing HR (fatigue signal)
let mut activities = Vec::new();
for i in 0..12 {
let hr = 140 + (i * 2); // HR increases over time
#[allow(clippy::cast_sign_loss)]
activities.push(create_test_activity(i64::from(i), 10.0, Some(hr as u32)));
}
let signals = PatternDetector::detect_overtraining_signals(&activities);
assert!(signals.hr_drift_detected);
assert!(signals.risk_level != RiskLevel::Low);
}
#[test]
fn test_volume_spike_detection() {
// Week 0: 30km (3 weeks ago, days 18-20)
// Note: create_test_activity uses days_ago, so larger values = older dates
let mut activities = vec![
create_test_activity(20, 10.0, Some(140)),
create_test_activity(19, 10.0, Some(140)),
create_test_activity(18, 10.0, Some(140)),
// Week 2: 60km (this week, days 2-7 - creating 100% spike)
create_test_activity(7, 10.0, Some(140)),
create_test_activity(6, 10.0, Some(140)),
create_test_activity(5, 10.0, Some(140)),
create_test_activity(4, 10.0, Some(140)),
create_test_activity(3, 10.0, Some(140)),
create_test_activity(2, 10.0, Some(140)),
];
// Sort by date to ensure chronological order (oldest first)
activities.sort_by_key(Activity::start_date);
let pattern = PatternDetector::detect_volume_progression(&activities);
// Debug output if test fails
if !pattern.volume_spikes_detected {
eprintln!("Weekly volumes: {:?}", pattern.weekly_volumes);
eprintln!("Week numbers: {:?}", pattern.week_numbers);
eprintln!("Spike weeks: {:?}", pattern.spike_weeks);
}
assert!(
pattern.volume_spikes_detected,
"Expected to detect 100% volume spike (30km to 60km)"
);
assert!(
!pattern.spike_weeks.is_empty(),
"Expected spike weeks to be non-empty"
);
}
