kaira.benchmarks.StandardMetrics

Inheritance diagram for StandardMetrics

class kaira.benchmarks.StandardMetrics

Bases: object

Collection of standard metrics for communication system evaluation.

Methods

__init__
bit_error_rate	Calculate Bit Error Rate (BER).
block_error_rate	Calculate Block Error Rate (BLER).
channel_capacity	Calculate Shannon channel capacity.
computational_complexity	Estimate computational complexity of a PyTorch model.
confidence_interval	Calculate confidence interval for data.
latency_statistics	Calculate latency statistics.
mutual_information	Estimate mutual information between two variables.
signal_to_noise_ratio	Calculate Signal-to-Noise Ratio (SNR) in dB.
throughput	Calculate throughput in bits per second.

static bit_error_rate(transmitted: Tensor, received: Tensor) → float

Calculate Bit Error Rate (BER).

static block_error_rate(transmitted: Tensor, received: Tensor, block_size: int) → float

Calculate Block Error Rate (BLER).

static signal_to_noise_ratio(signal: Tensor, noise: Tensor) → float

Calculate Signal-to-Noise Ratio (SNR) in dB.

static mutual_information(x: Tensor, y: Tensor, bins: int = 50) → float

Estimate mutual information between two variables.

static throughput(bits_transmitted: int, time_elapsed: float) → float

Calculate throughput in bits per second.

static latency_statistics(latencies: Tensor) → Dict[str, float]

Calculate latency statistics.

static computational_complexity(model: Module, input_shape: tuple) → Dict[str, Any]

Estimate computational complexity of a PyTorch model.

static channel_capacity(snr_db: float, bandwidth: float = 1.0) → float

Calculate Shannon channel capacity.

static confidence_interval(data: Tensor, confidence: float = 0.95) → tuple

Calculate confidence interval for data.

__init__()