The GAUSSINT function evaluates the integral of the Gaussian probability function.

The Gaussian integral is defined as: ## Examples Plot the Gaussian probability function for a range of numbers raised to one of several exponents:

`; Generate our base values.`
`X = FINDGEN(50)/100.`
` `
`; Plot the base values against their Gaussian probability integrals.`
`; Then plot the base values raised to an exponent against their `
`; Gaussian probability integrals.`
`p1 = PLOT(X, GAUSSINT(X), XTITLE='Numbers', \$`
`   YTITLE='Gaussian Integral', \$`
`   TITLE="Gaussian Integrals for Numbers", \$`
`   COLOR='red', NAME='Number to the Power of 1')`
`p1 = PLOT((X^2), GAUSSINT(X), COLOR='blue', \$`
`   NAME='Number to the Power of 2', /OVERPLOT)`
`p1 = PLOT((X^3), GAUSSINT(X), COLOR='purple', \$`
`   NAME='Number to the Power of 3', /OVERPLOT)`
`p1 = PLOT((X^4), GAUSSINT(X), COLOR='green', \$`
`   NAME='Number to the Power of 4', /OVERPLOT)`
`p1 = PLOT((X^5), GAUSSINT(X), COLOR='chocolate', \$`
`   NAME='Number to the Power of 5', /OVERPLOT)`
`L = LEGEND(POSITION=[0.4,90], /DATA)`

## Syntax

Result = GAUSSINT(X [, Y])

## Return Value

Returns the result of the Gaussian probability function integral evaluation.

If Y is supplied, the result is for a two-dimensional integral. If either X or Y is double-precision, the result is double-precision, otherwise the argument is converted to single-precision and the result is single-precision.

If both X and Y are scalars, the result is a scalar. If both X and Y are arrays, the result is an array with the structure of the shorter of the arrays and excess elements are ignored. If X is a scalar and Y is an array or vice versa, the result has the structure of the array.

## Arguments

### X

The upper limit of integration in the first dimension at which the Gaussian integral is evaluated.

### Y

The upper limit of integration in the second dimension at which the Gaussian integral is evaluated.