// Neuromorphic Computing Optimization
//
// This module implements optimization algorithms specifically designed for neuromorphic
// computing platforms, including spike-based optimization, event-driven parameter updates,
// and energy-efficient optimization strategies for neuromorphic chips.

use crate::error::Result;
use crate::optimizers::Optimizer;
use scirs2_core::ndarray::{Array1, Array2, ArrayBase, Data, DataMut, Dimension};
use scirs2_core::numeric::Float;
use std::collections::{HashMap, VecDeque};
use std::fmt::Debug;
use std::time::{Duration, Instant};

pub mod energy_efficient;
pub mod event_driven;
pub mod spike_based;

// Re-export key types
pub use energy_efficient::{EnergyBudget, EnergyEfficientOptimizer, EnergyOptimizationStrategy};
pub use event_driven::{EventDrivenConfig, EventDrivenOptimizer, EventType};
pub use spike_based::{SpikeTrainOptimizer, SpikingConfig, SpikingOptimizer};

/// Neuromorphic computing platform types
#[derive(Debug, Clone)]
#[allow(dead_code)]
pub enum NeuromorphicPlatform {
    /// Intel Loihi neuromorphic chip
    IntelLoihi,

    /// SpiNNaker platform
    SpiNNaker,

    /// IBM TrueNorth
    IBMTrueNorth,

    /// BrainChip Akida
    BrainChipAkida,

    /// University research platforms
    Research,

    /// Custom neuromorphic hardware
    Custom(String),
}

/// Neuromorphic optimization configuration
#[derive(Debug, Clone)]
#[allow(dead_code)]
pub struct NeuromorphicConfig<T: Float + Debug + Send + Sync + 'static> {
    /// Target neuromorphic platform
    pub platform: NeuromorphicPlatform,

    /// Spike-based optimization settings
    pub spike_config: SpikingConfig<T>,

    /// Event-driven optimization settings
    pub event_config: EventDrivenConfig<T>,

    /// Energy optimization settings
    pub energy_config: EnergyOptimizationConfig<T>,

    /// Enable temporal coding
    pub temporal_coding: bool,

    /// Enable rate coding
    pub rate_coding: bool,

    /// Spike timing dependent plasticity (STDP) parameters
    pub stdp_config: STDPConfig<T>,

    /// Membrane potential dynamics
    pub membrane_dynamics: MembraneDynamicsConfig<T>,

    /// Synaptic plasticity model
    pub plasticity_model: PlasticityModel,

    /// Enable homeostatic mechanisms
    pub homeostatic_plasticity: bool,

    /// Enable metaplasticity
    pub metaplasticity: bool,

    /// Population dynamics configuration
    pub population_config: PopulationConfig,
}

/// Spike Timing Dependent Plasticity configuration
#[derive(Debug, Clone)]
pub struct STDPConfig<T: Float + Debug + Send + Sync + 'static> {
    /// Learning rate for potentiation
    pub learning_rate_pot: T,

    /// Learning rate for depression
    pub learning_rate_dep: T,

    /// Time constant for potentiation (ms)
    pub tau_pot: T,

    /// Time constant for depression (ms)
    pub tau_dep: T,

    /// Maximum weight value
    pub weight_max: T,

    /// Minimum weight value
    pub weight_min: T,

    /// Enable triplet STDP
    pub enable_triplet: bool,

    /// Triplet learning rate
    pub triplet_learning_rate: T,
}

/// Membrane potential dynamics configuration
#[derive(Debug, Clone)]
pub struct MembraneDynamicsConfig<T: Float + Debug + Send + Sync + 'static> {
    /// Membrane time constant (ms)
    pub tau_membrane: T,

    /// Resting potential (mV)
    pub resting_potential: T,

    /// Threshold potential (mV)
    pub threshold_potential: T,

    /// Reset potential (mV)
    pub reset_potential: T,

    /// Refractory period (ms)
    pub refractory_period: T,

    /// Capacitance (pF)
    pub capacitance: T,

    /// Leak conductance (nS)
    pub leak_conductance: T,

    /// Enable adaptive threshold
    pub adaptive_threshold: bool,

    /// Threshold adaptation time constant
    pub threshold_adaptation_tau: T,
}

/// Synaptic plasticity models
#[derive(Debug, Clone, Copy)]
#[allow(dead_code)]
pub enum PlasticityModel {
    /// Hebbian plasticity
    Hebbian,

    /// Anti-Hebbian plasticity
    AntiHebbian,

    /// Spike Timing Dependent Plasticity
    STDP,

    /// Triplet STDP
    TripletSTDP,

    /// Voltage-dependent plasticity
    VoltageDependentSTDP,

    /// Calcium-based plasticity
    CalciumBased,

    /// BCM (Bienenstock-Cooper-Munro) rule
    BCM,

    /// Oja's rule
    Oja,
}

/// Population-level configuration
#[derive(Debug, Clone)]
pub struct PopulationConfig {
    /// Population size
    pub population_size: usize,

    /// Enable lateral inhibition
    pub lateral_inhibition: bool,

    /// Inhibition strength
    pub inhibition_strength: f64,

    /// Enable winner-take-all dynamics
    pub winner_take_all: bool,

    /// Population coding strategy
    pub coding_strategy: PopulationCodingStrategy,

    /// Enable population bursting
    pub enable_bursting: bool,

    /// Synchronization mechanisms
    pub synchronization: SynchronizationMechanism,
}

/// Population coding strategies
#[derive(Debug, Clone, Copy)]
#[allow(dead_code)]
pub enum PopulationCodingStrategy {
    /// Distributed coding
    Distributed,

    /// Sparse coding
    Sparse,

    /// Local coding
    Local,

    /// Vector coding
    Vector,

    /// Rank order coding
    RankOrder,
}

/// Synchronization mechanisms
#[derive(Debug, Clone, Copy)]
#[allow(dead_code)]
pub enum SynchronizationMechanism {
    /// No synchronization
    None,

    /// Global clock
    GlobalClock,

    /// Phase-locked loops
    PhaseLocked,

    /// Adaptive synchronization
    Adaptive,

    /// Network oscillations
    NetworkOscillations,
}

/// Energy optimization configuration
#[derive(Debug, Clone)]
#[allow(dead_code)]
pub struct EnergyOptimizationConfig<T: Float + Debug + Send + Sync + 'static> {
    /// Energy budget (nJ per operation)
    pub energy_budget: T,

    /// Energy optimization strategy
    pub strategy: EnergyOptimizationStrategy,

    /// Enable dynamic voltage scaling
    pub dynamic_voltage_scaling: bool,

    /// Enable clock gating
    pub clock_gating: bool,

    /// Enable power gating
    pub power_gating: bool,

    /// Sleep mode configuration
    pub sleep_mode_config: SleepModeConfig<T>,

    /// Energy monitoring frequency
    pub monitoring_frequency: Duration,

    /// Thermal management
    pub thermal_management: ThermalManagementConfig<T>,
}

/// Sleep mode configuration for energy efficiency
#[derive(Debug, Clone)]
#[allow(dead_code)]
pub struct SleepModeConfig<T: Float + Debug + Send + Sync + 'static> {
    /// Enable sleep mode
    pub enable_sleep_mode: bool,

    /// Sleep threshold (inactivity time)
    pub sleep_threshold: Duration,

    /// Wake-up time (ms)
    pub wakeup_time: T,

    /// Sleep energy consumption (nW)
    pub sleep_power: T,

    /// Wake-up energy cost (nJ)
    pub wakeup_energy: T,
}

/// Thermal management configuration
#[derive(Debug, Clone)]
#[allow(dead_code)]
pub struct ThermalManagementConfig<T: Float + Debug + Send + Sync + 'static> {
    /// Enable thermal management
    pub enable_thermal_management: bool,

    /// Target temperature (°C)
    pub target_temperature: T,

    /// Maximum temperature (°C)
    pub max_temperature: T,

    /// Thermal time constant (s)
    pub thermal_time_constant: T,

    /// Thermal throttling strategy
    pub throttling_strategy: ThermalThrottlingStrategy,
}

/// Thermal throttling strategies
#[derive(Debug, Clone, Copy)]
#[allow(dead_code)]
pub enum ThermalThrottlingStrategy {
    /// Frequency scaling
    FrequencyScaling,

    /// Voltage scaling
    VoltageScaling,

    /// Activity reduction
    ActivityReduction,

    /// Selective shutdown
    SelectiveShutdown,

    /// Dynamic load balancing
    DynamicLoadBalancing,
}

/// Spike representation for neuromorphic optimization
#[derive(Debug, Clone)]
#[allow(dead_code)]
pub struct Spike<T: Float + Debug + Send + Sync + 'static> {
    /// Neuron ID
    pub neuron_id: usize,

    /// Spike time (ms)
    pub time: T,

    /// Spike amplitude (mV)
    pub amplitude: T,

    /// Spike width (ms)
    pub width: Option<T>,

    /// Associated synapse weight
    pub weight: T,

    /// Presynaptic neuron ID
    pub presynaptic_id: Option<usize>,

    /// Postsynaptic neuron ID
    pub postsynaptic_id: Option<usize>,
}

/// Spike train representation
#[derive(Debug, Clone)]
pub struct SpikeTrain<T: Float + Debug + Send + Sync + 'static> {
    /// Neuron ID
    pub neuron_id: usize,

    /// Spike times
    pub spike_times: Vec<T>,

    /// Inter-spike intervals
    pub inter_spike_intervals: Vec<T>,

    /// Firing rate (Hz)
    pub firing_rate: T,

    /// Spike train duration (ms)
    pub duration: T,

    /// Spike count
    pub spike_count: usize,
}

impl<T: Float + Debug + Send + Sync + 'static + std::iter::Sum> SpikeTrain<T> {
    /// Create a new spike train from spike times
    pub fn new(neuron_id: usize, spike_times: Vec<T>) -> Self {
        let spike_count = spike_times.len();
        let duration = if spike_count > 0 {
            spike_times[spike_count - 1] - spike_times[0]
        } else {
            T::zero()
        };

        let firing_rate = if duration > T::zero() {
            T::from(spike_count).unwrap_or_else(|| T::zero())
                / (duration / T::from(1000.0).unwrap_or_else(|| T::zero()))
        } else {
            T::zero()
        };

        let inter_spike_intervals = if spike_count > 1 {
            spike_times.windows(2).map(|w| w[1] - w[0]).collect()
        } else {
            Vec::new()
        };

        Self {
            neuron_id,
            spike_times,
            inter_spike_intervals,
            firing_rate,
            duration,
            spike_count,
        }
    }

    /// Calculate coefficient of variation of inter-spike intervals
    pub fn coefficient_of_variation(&self) -> T {
        if self.inter_spike_intervals.len() < 2 {
            return T::zero();
        }

        let mean = self.inter_spike_intervals.iter().cloned().sum::<T>()
            / T::from(self.inter_spike_intervals.len()).unwrap();

        let variance = self
            .inter_spike_intervals
            .iter()
            .map(|&isi| (isi - mean) * (isi - mean))
            .sum::<T>()
            / T::from(self.inter_spike_intervals.len()).unwrap();

        variance.sqrt() / mean
    }

    /// Calculate local variation measure
    pub fn local_variation(&self) -> T {
        if self.inter_spike_intervals.len() < 2 {
            return T::zero();
        }

        let mut lv_sum = T::zero();
        for window in self.inter_spike_intervals.windows(2) {
            let isi1 = window[0];
            let isi2 = window[1];
            let diff = isi1 - isi2;
            let sum = isi1 + isi2;

            if sum > T::zero() {
                lv_sum = lv_sum + (diff * diff) / (sum * sum);
            }
        }

        let three = T::from(3.0).unwrap_or_else(|| T::zero());
        three * lv_sum / T::from(self.inter_spike_intervals.len() - 1).unwrap()
    }
}

/// Event-driven update representation
#[derive(Debug, Clone)]
#[allow(dead_code)]
pub struct NeuromorphicEvent<T: Float + Debug + Send + Sync + 'static> {
    /// Event type
    pub event_type: EventType,

    /// Event timestamp
    pub timestamp: T,

    /// Source neuron
    pub source_neuron: usize,

    /// Target neuron
    pub target_neuron: Option<usize>,

    /// Event value/weight
    pub value: T,

    /// Energy cost of processing this event
    pub energy_cost: T,

    /// Priority level
    pub priority: EventPriority,
}

/// Event priority levels for neuromorphic processing
#[derive(Debug, Clone, Copy, PartialEq, Eq, PartialOrd, Ord)]
#[allow(dead_code)]
pub enum EventPriority {
    Low,
    Normal,
    High,
    Critical,
    RealTime,
}

/// Neuromorphic optimization metrics
#[derive(Debug, Clone)]
pub struct NeuromorphicMetrics<T: Float + Debug + Send + Sync + 'static> {
    /// Total spikes processed
    pub total_spikes: usize,

    /// Average firing rate (Hz)
    pub average_firing_rate: T,

    /// Energy consumption (nJ)
    pub energy_consumption: T,

    /// Power consumption (nW)
    pub power_consumption: T,

    /// Spike timing precision (ms)
    pub timing_precision: T,

    /// Synaptic operations per second
    pub synaptic_ops_per_sec: T,

    /// Plasticity events per second
    pub plasticity_events_per_sec: T,

    /// Memory bandwidth utilization
    pub memory_bandwidth_utilization: T,

    /// Thermal efficiency score
    pub thermal_efficiency: T,

    /// Network synchronization measure
    pub network_synchronization: T,
}

impl<T: Float + Debug + Send + Sync + 'static> Default for NeuromorphicMetrics<T> {
    fn default() -> Self {
        Self {
            total_spikes: 0,
            average_firing_rate: T::zero(),
            energy_consumption: T::zero(),
            power_consumption: T::zero(),
            timing_precision: T::from(0.1).unwrap_or_else(|| T::zero()), // 0.1ms default
            synaptic_ops_per_sec: T::zero(),
            plasticity_events_per_sec: T::zero(),
            memory_bandwidth_utilization: T::zero(),
            thermal_efficiency: T::one(),
            network_synchronization: T::zero(),
        }
    }
}

impl<T: Float + Debug + Send + Sync + 'static> Default for NeuromorphicConfig<T> {
    fn default() -> Self {
        Self {
            platform: NeuromorphicPlatform::IntelLoihi,
            spike_config: SpikingConfig::default(),
            event_config: EventDrivenConfig::default(),
            energy_config: EnergyOptimizationConfig::default(),
            temporal_coding: true,
            rate_coding: false,
            stdp_config: STDPConfig::default(),
            membrane_dynamics: MembraneDynamicsConfig::default(),
            plasticity_model: PlasticityModel::STDP,
            homeostatic_plasticity: false,
            metaplasticity: false,
            population_config: PopulationConfig::default(),
        }
    }
}

impl<T: Float + Debug + Send + Sync + 'static> Default for STDPConfig<T> {
    fn default() -> Self {
        Self {
            learning_rate_pot: T::from(0.01).unwrap_or_else(|| T::zero()),
            learning_rate_dep: T::from(0.01).unwrap_or_else(|| T::zero()),
            tau_pot: T::from(20.0).unwrap_or_else(|| T::zero()),
            tau_dep: T::from(20.0).unwrap_or_else(|| T::zero()),
            weight_max: T::one(),
            weight_min: T::zero(),
            enable_triplet: false,
            triplet_learning_rate: T::from(0.001).unwrap_or_else(|| T::zero()),
        }
    }
}

impl<T: Float + Debug + Send + Sync + 'static> Default for MembraneDynamicsConfig<T> {
    fn default() -> Self {
        Self {
            tau_membrane: T::from(20.0).unwrap_or_else(|| T::zero()),
            resting_potential: T::from(-70.0).unwrap_or_else(|| T::zero()),
            threshold_potential: T::from(-55.0).unwrap_or_else(|| T::zero()),
            reset_potential: T::from(-80.0).unwrap_or_else(|| T::zero()),
            refractory_period: T::from(2.0).unwrap_or_else(|| T::zero()),
            capacitance: T::from(100.0).unwrap_or_else(|| T::zero()),
            leak_conductance: T::from(10.0).unwrap_or_else(|| T::zero()),
            adaptive_threshold: false,
            threshold_adaptation_tau: T::from(100.0).unwrap_or_else(|| T::zero()),
        }
    }
}

impl Default for PopulationConfig {
    fn default() -> Self {
        Self {
            population_size: 1000,
            lateral_inhibition: false,
            inhibition_strength: 0.1,
            winner_take_all: false,
            coding_strategy: PopulationCodingStrategy::Distributed,
            enable_bursting: false,
            synchronization: SynchronizationMechanism::None,
        }
    }
}

impl<T: Float + Debug + Send + Sync + 'static> Default for EnergyOptimizationConfig<T> {
    fn default() -> Self {
        Self {
            energy_budget: T::from(10.0).unwrap_or_else(|| T::zero()), // 10 nJ per operation
            strategy: EnergyOptimizationStrategy::DynamicVoltageScaling,
            dynamic_voltage_scaling: true,
            clock_gating: true,
            power_gating: false,
            sleep_mode_config: SleepModeConfig::default(),
            monitoring_frequency: Duration::from_millis(100),
            thermal_management: ThermalManagementConfig::default(),
        }
    }
}

impl<T: Float + Debug + Send + Sync + 'static> Default for SleepModeConfig<T> {
    fn default() -> Self {
        Self {
            enable_sleep_mode: true,
            sleep_threshold: Duration::from_millis(100),
            wakeup_time: T::from(1.0).unwrap_or_else(|| T::zero()),
            sleep_power: T::from(0.1).unwrap_or_else(|| T::zero()),
            wakeup_energy: T::from(0.01).unwrap_or_else(|| T::zero()),
        }
    }
}

impl<T: Float + Debug + Send + Sync + 'static> Default for ThermalManagementConfig<T> {
    fn default() -> Self {
        Self {
            enable_thermal_management: true,
            target_temperature: T::from(65.0).unwrap_or_else(|| T::zero()),
            max_temperature: T::from(85.0).unwrap_or_else(|| T::zero()),
            thermal_time_constant: T::from(10.0).unwrap_or_else(|| T::zero()),
            throttling_strategy: ThermalThrottlingStrategy::FrequencyScaling,
        }
    }
}
