#![allow(
    clippy::assertions_on_constants,
    clippy::assertions_on_result_states,
    clippy::clone_on_copy,
    clippy::decimal_literal_representation,
    clippy::doc_markdown,
    clippy::empty_line_after_doc_comments,
    clippy::field_reassign_with_default,
    clippy::get_unwrap,
    clippy::identity_op,
    clippy::inconsistent_digit_grouping,
    clippy::indexing_slicing,
    clippy::integer_division,
    clippy::len_zero,
    clippy::let_underscore_must_use,
    clippy::manual_div_ceil,
    clippy::manual_let_else,
    clippy::manual_range_contains,
    clippy::modulo_arithmetic,
    clippy::needless_range_loop,
    clippy::non_ascii_literal,
    clippy::redundant_clone,
    clippy::shadow_reuse,
    clippy::shadow_same,
    clippy::shadow_unrelated,
    clippy::single_match_else,
    clippy::str_to_string,
    clippy::string_slice,
    clippy::tests_outside_test_module,
    clippy::too_many_lines,
    clippy::unnecessary_wraps,
    clippy::unseparated_literal_suffix,
    clippy::use_debug,
    clippy::useless_vec,
    clippy::wildcard_enum_match_arm,
    clippy::else_if_without_else,
    clippy::expect_used,
    clippy::missing_const_for_fn,
    clippy::similar_names,
    clippy::type_complexity,
    clippy::collapsible_else_if,
    clippy::doc_lazy_continuation,
    clippy::items_after_test_module,
    clippy::map_clone,
    clippy::multiple_unsafe_ops_per_block,
    clippy::unwrap_or_default,
    clippy::assign_op_pattern,
    clippy::needless_borrow,
    clippy::println_empty_string,
    clippy::unnecessary_cast,
    clippy::used_underscore_binding,
    clippy::create_dir,
    clippy::implicit_saturating_sub,
    clippy::exit,
    clippy::expect_fun_call,
    clippy::too_many_arguments,
    clippy::unnecessary_map_or,
    clippy::unwrap_used,
    dead_code,
    unused_imports,
    unused_variables,
    clippy::cloned_ref_to_slice_refs,
    clippy::neg_multiply,
    clippy::while_let_loop,
    clippy::bool_assert_comparison,
    clippy::excessive_precision,
    clippy::trivially_copy_pass_by_ref,
    clippy::op_ref,
    clippy::redundant_closure,
    clippy::unnecessary_lazy_evaluations,
    clippy::if_then_some_else_none,
    clippy::unnecessary_to_owned,
    clippy::single_component_path_imports,
)]
//! TDD Tests for Ensemble Uncertainty Fields in Hyperopt
//!
//! Validates that ensemble uncertainty parameters are properly set as fixed defaults
//! in the current 39D search space (ensemble params were removed from search space,
//! they are now fixed in from_continuous).

use ml::hyperopt::adapters::dqn::DQNParams;
use ml::hyperopt::ParameterSpace;
use ml::trainers::dqn::DQNHyperparameters;

#[test]
fn test_dqn_hyperparameters_has_ensemble_fields() {
    // WAVE 26 P1.4: Verify DQNHyperparameters struct has 6 new ensemble fields
    let hyperparams = DQNHyperparameters::conservative();

    // Check default values exist (compilation test - if fields don't exist, this won't compile)
    let _use_ensemble = hyperparams.use_ensemble_uncertainty;
    let _ensemble_size = hyperparams.ensemble_size;
    let _beta_variance = hyperparams.beta_variance;
    let _beta_disagreement = hyperparams.beta_disagreement;
    let _beta_entropy = hyperparams.beta_entropy;
    let _variance_cap = hyperparams.variance_cap;

    // Verify conservative defaults are reasonable
    assert!(!hyperparams.use_ensemble_uncertainty, "Default should be disabled for conservative config");
    assert_eq!(hyperparams.ensemble_size, 5, "Default ensemble size should be 5");
    assert!(hyperparams.beta_variance >= 0.0 && hyperparams.beta_variance <= 1.0, "Beta variance should be in [0, 1]");
    assert!(hyperparams.beta_disagreement >= 0.0 && hyperparams.beta_disagreement <= 1.0, "Beta disagreement should be in [0, 1]");
    assert!(hyperparams.beta_entropy >= 0.0 && hyperparams.beta_entropy <= 1.0, "Beta entropy should be in [0, 1]");
    assert!(hyperparams.variance_cap > 0.0, "Variance cap should be positive");
}

#[test]
fn test_dqn_params_has_ensemble_fields() {
    // WAVE 26 P1.4: Verify DQNParams struct has 5 new ensemble fields
    let params = DQNParams::default();

    // Check default values exist (compilation test)
    let _use_ensemble = params.use_ensemble_uncertainty;
    let _ensemble_size = params.ensemble_size;
    let _beta_variance = params.beta_variance;
    let _beta_disagreement = params.beta_disagreement;
    let _beta_entropy = params.beta_entropy;

    // Verify defaults match conservative config
    assert!(!params.use_ensemble_uncertainty, "Default should be disabled");
    assert_eq!(params.ensemble_size, 5.0, "Default ensemble size should be 5.0");
    assert!(params.beta_variance > 0.0, "Beta variance should be positive");
    assert!(params.beta_disagreement > 0.0, "Beta disagreement should be positive");
    assert!(params.beta_entropy > 0.0, "Beta entropy should be positive");
}

#[test]
fn test_ensemble_search_space_bounds() {
    // Ensemble params (ensemble_size, beta_variance, etc.) are no longer in the
    // continuous search space — they are fixed in from_continuous(). Verify that
    // the 39D search space is properly sized and ensemble defaults are set.
    let bounds = DQNParams::continuous_bounds();
    assert_eq!(bounds.len(), 39, "Search space should have 39 continuous parameters total (C8: +8 reward/policy weights)");

    // Ensemble params are NOT in bounds — they're fixed in from_continuous.
    // Verify a DQNParams default still has correct ensemble defaults.
    let params = DQNParams::default();
    assert!(!params.use_ensemble_uncertainty, "Default: ensemble disabled");
    assert_eq!(params.ensemble_size, 5.0, "Default ensemble size should be 5.0");
    assert!(params.beta_variance > 0.0, "Beta variance should be positive");
    assert!(params.beta_disagreement > 0.0, "Beta disagreement should be positive");
    assert!(params.beta_entropy > 0.0, "Beta entropy should be positive");
}

#[test]
fn test_from_continuous_validates_ensemble_params() {
    // Ensemble params are now fixed in from_continuous() (not in 39D search space).
    // Verify that from_continuous produces correct fixed ensemble defaults.
    let bounds = DQNParams::continuous_bounds();
    let x: Vec<f64> = bounds.iter().map(|(lo, hi)| (lo + hi) / 2.0).collect();
    assert_eq!(x.len(), 39, "Should produce 39D midpoint vector");

    let params = DQNParams::from_continuous(&x).expect("Should convert valid parameters");

    // Ensemble parameters are fixed to conservative defaults
    assert_eq!(params.ensemble_size, 5.0, "Ensemble size should be fixed to 5.0");
    assert_eq!(params.beta_variance, 0.5, "Beta variance should be fixed to 0.5");
    assert_eq!(params.beta_disagreement, 0.5, "Beta disagreement should be fixed to 0.5");
    assert_eq!(params.beta_entropy, 0.2, "Beta entropy should be fixed to 0.2");
    assert!(!params.use_ensemble_uncertainty, "Ensemble uncertainty should be disabled");
}

#[test]
fn test_from_continuous_clamps_ensemble_params() {
    // Ensemble parameters are now fixed (not in search space), so clamping
    // is not relevant. Instead verify that from_continuous rejects wrong-length input.
    let x = vec![0.0; 40]; // Wrong length (should be 39)
    let result = DQNParams::from_continuous(&x);
    assert!(result.is_err(), "Should reject wrong-length (40) input");

    let x2 = vec![0.0; 31]; // Also wrong length
    let result2 = DQNParams::from_continuous(&x2);
    assert!(result2.is_err(), "Should reject wrong-length (31) input");

    // Correct length (39) with valid midpoints should succeed
    let bounds = DQNParams::continuous_bounds();
    let x38: Vec<f64> = bounds.iter().map(|(lo, hi)| (lo + hi) / 2.0).collect();
    let params = DQNParams::from_continuous(&x38).expect("Should accept 39D input");
    // Ensemble params are fixed regardless of input
    assert_eq!(params.ensemble_size, 5.0, "Ensemble size fixed to 5.0");
}

#[test]
fn test_to_continuous_includes_reward_weights() {
    // C8: Verify that to_continuous() includes 7 composite reward weights (indices 31-37)
    let mut params = DQNParams::default();

    // Set reward weights to specific values
    params.w_dsr = 1.5;
    params.w_pnl = 0.5;
    params.w_dd = 2.0;
    params.w_idle = 0.05;
    params.dd_threshold = 0.04;
    params.loss_aversion = 2.0;
    params.time_decay_rate = 0.001;

    let continuous = params.to_continuous();
    assert_eq!(continuous.len(), 39, "Continuous representation should have 39 values");

    // Verify reward weight positions (indices 31-37)
    assert_eq!(continuous[31], 1.5, "w_dsr should be at position 31");
    assert_eq!(continuous[32], 0.5, "w_pnl should be at position 32");
    assert_eq!(continuous[33], 2.0, "w_dd should be at position 33");
    assert_eq!(continuous[34], 0.05, "w_idle should be at position 34");
    assert_eq!(continuous[35], 0.04, "dd_threshold should be at position 35");
    assert_eq!(continuous[36], 2.0, "loss_aversion should be at position 36");
    assert_eq!(continuous[37], 0.001, "time_decay_rate should be at position 37");

    // Ensemble params are NOT in the continuous vector (they're fixed)
    // Verify the vector doesn't include them
    assert_eq!(continuous.len(), 39);
}

#[test]
fn test_ensemble_size_fixed_in_from_continuous() {
    // Ensemble size is now fixed at 5.0 in from_continuous() — not in search space.
    // Verify that from_continuous always produces ensemble_size=5.0 regardless of input.
    let bounds = DQNParams::continuous_bounds();
    let x: Vec<f64> = bounds.iter().map(|(lo, hi)| (lo + hi) / 2.0).collect();
    let params = DQNParams::from_continuous(&x).expect("Should convert");
    assert_eq!(params.ensemble_size, 5.0, "Ensemble size should always be fixed to 5.0");
    assert!(!params.use_ensemble_uncertainty, "Ensemble uncertainty should be disabled");
}