# Normaliz

### Purpose

Normalizes rows of matrix to unit vectors.

### Synopsis

- [ndat,norms] = normaliz(dat)
- [ndat,norms] = normaliz(dat,
*out,normtype,window*) - [ndat,norms] = normaliz(dat,normtype,options);

### Description

NORMALIZ can be used for pattern normalization, which is useful for preprocessing in some pattern recognition applications and also for correction of pathlength effects for some quantification applications. The "norm type" defines the order of normalization (see algorithm below). Typical values cause each row to be normalized to:

- 1 = the absolute value of the area "under the curve" (sum of the absolute value of all values)
- 2 = the summed squared value of the values (the multivariate vector "length")
- inf = the maximum value in of the row

#### Inputs

**dat**= the data matrix

#### Optional Inputs

**out**= flag to suppress warnings about the norm of a vector being zero. Supresses when set to 0 (zero) {default = 0}.**normtype**= used to specify the type of norm {default = 2}.**window**= indices for which columns of**dat**should be used to calculate the norm {default = [] which implies all values}

**NOTE:** If *normtype* is specified then *out* must be included, *out* can be empty [] giving the default value.

Alternatively, the **out** and **window** options can be passed in an options structure:

**options**= An options structure can be passed as third input along with (dat) and (normtype). This input takes the place of the remaining inputs and should contain one or more of the following fields:**display**: [ 'off' |{'on'}] controls display (replacement for**out**input above)**window**: replacement for standard (window) input above (default = [])

#### Outputs

**ndat**= matrix of normalized data where the*rows*have been normalized**norms**= vector of norms used in the normalization

### Algorithm

For a 1 by *N* vector **x**, the norm *n*_{x} is given by
where *p* is *normtype*. The normalized 1 by *N* vector **x**_{n} is given by **x**/*n*_{x}.

However, when *p* is inf (infinity) a simple location of the maximum value replaces the equation above.