0.5 * ((2.0 * self) / (1.0 - self)).ln_1p()
}
- /// Linear interpolation between `start` and `end`.
- ///
- /// This enables linear interpolation between `start` and `end`, where start is represented by
- /// `self == 0.0` and `end` is represented by `self == 1.0`. This is the basis of all
- /// "transition", "easing", or "step" functions; if you change `self` from 0.0 to 1.0
- /// at a given rate, the result will change from `start` to `end` at a similar rate.
- ///
- /// Values below 0.0 or above 1.0 are allowed, allowing you to extrapolate values outside the
- /// range from `start` to `end`. This also is useful for transition functions which might
- /// move slightly past the end or start for a desired effect. Mathematically, the values
- /// returned are equivalent to `start + self * (end - start)`, although we make a few specific
- /// guarantees that are useful specifically to linear interpolation.
- ///
- /// These guarantees are:
- ///
- /// * If `start` and `end` are [finite], the value at 0.0 is always `start` and the
- /// value at 1.0 is always `end`. (exactness)
- /// * If `start` and `end` are [finite], the values will always move in the direction from
- /// `start` to `end` (monotonicity)
- /// * If `self` is [finite] and `start == end`, the value at any point will always be
- /// `start == end`. (consistency)
- ///
- /// [finite]: #method.is_finite
- #[must_use = "method returns a new number and does not mutate the original value"]
- #[unstable(feature = "float_interpolation", issue = "86269")]
- pub fn lerp(self, start: f64, end: f64) -> f64 {
- // consistent
- if start == end {
- start
-
- // exact/monotonic
- } else {
- self.mul_add(end, (-self).mul_add(start, start))
- }
- }
-
// Solaris/Illumos requires a wrapper around log, log2, and log10 functions
// because of their non-standard behavior (e.g., log(-n) returns -Inf instead
// of expected NaN).