Expand description
Calibrator is a library for working with measurement systems.
Structs§
- Calibrated
System - Calibration
Builder - Channel
Data - Detectable
- Fit
- The results of a polynomial fit.
- Mock
Source Builder - Observation
- Observation
Builder - Operating
- Probabilistic
Limit Config - Response
Tag - Standard
Normal - Samples floating-point numbers according to the normal distribution
N(0, 1)(a.k.a. a standard normal, or Gaussian). This is equivalent toNormal::new(0.0, 1.0)but faster. - Stimulus
Tag - Stochastic
Calibration Data Config - Stochastic
Limit Config - Target
Range
Enums§
Traits§
- Calibrate
- The
Calibratetrait transforms self, which is a system without calibration data attached, into it’s calibrated form - Calibrated
- Calibration
Float - Calibration
Matrix - Calibration
Vector - Distribution
- Types (distributions) that can be used to create a random instance of
T. - Linfa
Float - Floating point numbers
- Metrics
- Scalar
Stochastic Measurement Model - In a stochastic model the relationship between the stimulus and response is not deterministic.
- Stochastic
Measurement Model - A general stochastic measurement model.
Type Aliases§
- Array1
- one-dimensional array
- Array2
- two-dimensional array
- Calibrated
Stochastic - Stochastic
Calibrated System Error - Uncalibrated
Stochastic - An
UncalibratedStochasticmeasurement system is one which ingests and returns float-like stimulus and response.