# NXcalibration¶

**Status**:

base class, extends NXobject

**Description**:

Subclass of NXprocess to describe post-processing calibrations.

**Symbols**:

The symbols used in the schema to specify e.g. dimensions of arrays

ncoeff: Number of coefficients of the calibration function

nfeat: Number of features used to fit the calibration function

ncal: Number of points of the calibrated and uncalibrated axes

**Groups cited**:none

**Structure**:

last_process: (optional) NX_CHARIndicates the name of the last operation applied in the NXprocess sequence.

applied: (optional) NX_BOOLEANHas the calibration been applied?

coefficients: (optional) NX_FLOAT (Rank: 1, Dimensions: [ncoeff]) {units=NX_ANY}For non-linear energy calibrations, e.g. in a TOF, a polynomial function is fit to a set of features (peaks) at well defined energy positions to determine E(TOF). Here we can store the array of fit coefficients.

fit_function: (optional) NX_CHARFor non-linear energy calibrations. Here we can store the formula of the fit function.

Use a0, a1, …, an for the coefficients, corresponding to the values in the coefficients field.

Use x0, x1, …, xn for the variables.

The formula should be numpy compliant.

scaling: (optional) NX_FLOAT {units=NX_ANY}For linear calibration. Scaling parameter.

offset: (optional) NX_FLOAT {units=NX_ANY}For linear calibration. Offset parameter.

calibrated_axis: (optional) NX_FLOAT (Rank: 1, Dimensions: [ncal]) {units=NX_ANY}A vector representing the axis after calibration, matching the data length

original_axis: (optional) NX_FLOAT (Rank: 1, Dimensions: [ncal]) {units=NX_ANY}Vector containing the data coordinates in the original uncalibrated axis

description: (optional) NX_CHARA description of the procedures employed.

## Hypertext Anchors¶

List of hypertext anchors for all groups, fields, attributes, and links defined in this class.