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Least Squares Fit Linear Regression SASS function
/// leastSquaresFit
/// Calculate the least square fit linear regression of provided values
/// @param {map} $map - A SASS map of viewport width and size value combinations
/// @return Linear equation as a calc() function
/// @example
/// font-size: leastSquaresFit((576: 24, 768: 24, 992: 34));
/// @author Jake Wilson <jake.e.wilson@gmail.com>
@function leastSquaresFit($map) {
// Get the number of provided breakpoints
$length: length(map-keys($map));
// Error if the number of breakpoints is < 2
@if ($length < 2) {
@error "leastSquaresFit() $map must be at least 2 values"
}
// Calculate the Means
$resTotal: 0;
$valueTotal: 0;
@each $res, $value in $map {
$resTotal: $resTotal + $res;
$valueTotal: $valueTotal + $value;
}
$resMean: $resTotal/$length;
$valueMean: $valueTotal/$length;
// Calculate some other stuff
$multipliedDiff: 0;
$squaredDiff: 0;
@each $res, $value in $map {
// Differences from means
$resDiff: $res - $resMean;
$valueDiff: $value - $valueMean;
// Sum of multiplied differences
$multipliedDiff: $multipliedDiff + ($resDiff * $valueDiff);
// Sum of squared resolution differences
$squaredDiff: $squaredDiff + ($resDiff * $resDiff);
}
// Calculate the Slope
$m: $multipliedDiff / $squaredDiff;
// Calculate the Y-Intercept
$b: $valueMean - ($m * $resMean);
// Return the CSS calc equation
@return calc(#{$m*100}vw + #{$b}px);
}
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