Crate calibrator

Calibrator is a library for working with measurement systems.

Structs

• CalibratedSystem
• CalibrationBuilder
• ChannelData
• Detectable
• Fit
  The results of a polynomial fit.
• MockSourceBuilder
• Observation
• ObservationBuilder
• Operating
• ProbabilisticLimitConfig
• ResponseTag
• StandardNormal
  Samples floating-point numbers according to the normal distribution N(0, 1) (a.k.a. a standard normal, or Gaussian). This is equivalent to Normal::new(0.0, 1.0) but faster.
• StimulusTag
• StochasticCalibrationDataConfig
• StochasticLimitConfig
• TargetRange

Enums

• BuildError
• CalibrationDataGenError
• MockBuilderError
• NetStateLimits
• PolyCalError
• ScalarLimit

Traits

• Calibrate
  The Calibrate trait transforms self, which is a system without calibration data attached, into it’s calibrated form
• Calibrated
• CalibrationFloat
• CalibrationMatrix
• CalibrationVector
• Distribution
  Types (distributions) that can be used to create a random instance of T.
• LinfaFloat
  Floating point numbers
• Metrics
• ScalarStochasticMeasurementModel
  In a stochastic model the relationship between the stimulus and response is not deterministic.
• StochasticMeasurementModel
  A general stochastic measurement model.

Type Aliases

• Array1
  one-dimensional array
• Array2
  two-dimensional array
• CalibratedStochastic
• StochasticCalibratedSystemError
• UncalibratedStochastic
  An UncalibratedStochastic measurement system is one which ingests and returns float-like stimulus and response.