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BenchmarkRecord

fpm_rs::benchmark

Struct BenchmarkRecord 

Source 
pub struct BenchmarkRecord {
Show 33 fields
    pub format_version: u32,
    pub case_id: String,
    pub run_id: String,
    pub dataset_name: String,
    pub dataset_version: Option<String>,
    pub preset_name: Option<String>,
    pub crate_version: String,
    pub random_seed: Option<u64>,
    pub spatial_crop: Option<[usize; 4]>,
    pub algorithm: String,
    pub algorithm_configuration: String,
    pub success: bool,
    pub error: Option<String>,
    pub frame_count: usize,
    pub image_shape: [usize; 2],
    pub reconstruction_shape: [usize; 2],
    pub completed_iterations: usize,
    pub elapsed_seconds: f64,
    pub initial_objective: Option<f64>,
    pub final_objective: Option<f64>,
    pub final_to_initial_objective_ratio: Option<f64>,
    pub amplitude_rmse: Option<f64>,
    pub phase_rmse: Option<f64>,
    pub complex_field_relative_error: Option<f64>,
    pub fourier_domain_relative_error: Option<f64>,
    pub pupil_amplitude_rmse: Option<f64>,
    pub pupil_phase_rmse: Option<f64>,
    pub illumination_position_rmse: Option<f64>,
    pub per_frame_residual_mean: Option<f64>,
    pub per_frame_residual_max: Option<f64>,
    pub frames: Vec<BenchmarkFrameRecord>,
    pub output_paths: Vec<PathBuf>,
    pub metadata: BTreeMap<String, String>,

}
Expand description

Serializable summary of one algorithm run on one immutable problem.

Fields§

§format_version: u32

Record schema version; must equal BENCHMARK_RECORD_FORMAT_VERSION.

§case_id: String

Deterministic identity of the immutable case configuration.

§run_id: String

Unique identity of this execution.

§dataset_name: String

Human-readable dataset or synthetic-case name.

§dataset_version: Option<String>

Optional immutable dataset version.

§preset_name: Option<String>

Optional stable simulation preset name.

§crate_version: String

fpm-rs crate version that produced the record.

§random_seed: Option<u64>

Optional deterministic simulation or schedule seed.

§spatial_crop: Option<[usize; 4]>

Original-image crop as [row, column, height, width], when applicable.

§algorithm: String

Stable reconstruction algorithm name.

§algorithm_configuration: String

Caller-supplied serialized or human-readable algorithm configuration.

§success: bool

Whether reconstruction and requested metrics completed successfully.

§error: Option<String>

Captured failure message when success is false.

§frame_count: usize

Acquisition-frame count.

§image_shape: [usize; 2]

Low-resolution shape as [height, width].

§reconstruction_shape: [usize; 2]

High-resolution shape as [height, width].

§completed_iterations: usize

Complete iterations represented by the result.

§elapsed_seconds: f64

Wall-clock runtime in seconds.

§initial_objective: Option<f64>

First recorded objective, when an iteration completed.

§final_objective: Option<f64>

Last recorded objective, when an iteration completed.

§final_to_initial_objective_ratio: Option<f64>

Final objective divided by the initial objective.

§amplitude_rmse: Option<f64>

Root-mean-square reconstructed amplitude error against ground truth.

§phase_rmse: Option<f64>

Root-mean-square wrapped phase error in radians against ground truth.

§complex_field_relative_error: Option<f64>

Globally aligned complex-field relative L2 error.

§fourier_domain_relative_error: Option<f64>

Centered Fourier-spectrum relative L2 error.

§pupil_amplitude_rmse: Option<f64>

Support-aware pupil-amplitude RMSE.

§pupil_phase_rmse: Option<f64>

Support-aware pupil-phase RMSE in radians.

§illumination_position_rmse: Option<f64>

Source-position RMS error in Fourier-grid pixels.

§per_frame_residual_mean: Option<f64>

Mean of per-frame normalized intensity L2 errors.

§per_frame_residual_max: Option<f64>

Maximum per-frame normalized intensity L2 error.

§frames: Vec<BenchmarkFrameRecord>

Optional metrics in acquisition-frame order.

§output_paths: Vec<PathBuf>

Generated artifact paths associated with this run.

§metadata: BTreeMap<String, String>

Extensible stable string metadata.

Implementations§

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impl BenchmarkRecord

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pub fn from_result( case_id: impl Into<String>, dataset_name: impl Into<String>, algorithm_configuration: impl Into<String>, result: &ReconstructionResult, ) -> Self

Builds a normalized benchmark record for an already completed result.

Callers provide the deterministic case_id; a fresh run_id is generated for this execution.

Trait Implementations§

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impl Clone for BenchmarkRecord

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fn clone(&self) -> BenchmarkRecord

Returns a duplicate of the value. Read more
1.0.0 (const: unstable) · Source§

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source. Read more
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impl Debug for BenchmarkRecord

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fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter. Read more
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impl<'de> Deserialize<'de> for BenchmarkRecord

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fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>
where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer. Read more
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impl Serialize for BenchmarkRecord

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fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error>
where __S: Serializer,

Serialize this value into the given Serde serializer. Read more

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