Remove fNN::lerp - consensus unlikely
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@ -881,42 +881,6 @@ impl f64 {
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0.5 * ((2.0 * self) / (1.0 - self)).ln_1p()
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}
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/// Linear interpolation between `start` and `end`.
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///
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/// This enables linear interpolation between `start` and `end`, where start is represented by
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/// `self == 0.0` and `end` is represented by `self == 1.0`. This is the basis of all
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/// "transition", "easing", or "step" functions; if you change `self` from 0.0 to 1.0
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/// at a given rate, the result will change from `start` to `end` at a similar rate.
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///
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/// Values below 0.0 or above 1.0 are allowed, allowing you to extrapolate values outside the
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/// range from `start` to `end`. This also is useful for transition functions which might
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/// move slightly past the end or start for a desired effect. Mathematically, the values
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/// returned are equivalent to `start + self * (end - start)`, although we make a few specific
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/// guarantees that are useful specifically to linear interpolation.
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///
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/// These guarantees are:
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///
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/// * If `start` and `end` are [finite], the value at 0.0 is always `start` and the
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/// value at 1.0 is always `end`. (exactness)
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/// * If `start` and `end` are [finite], the values will always move in the direction from
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/// `start` to `end` (monotonicity)
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/// * If `self` is [finite] and `start == end`, the value at any point will always be
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/// `start == end`. (consistency)
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///
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/// [finite]: #method.is_finite
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#[must_use = "method returns a new number and does not mutate the original value"]
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#[unstable(feature = "float_interpolation", issue = "86269")]
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pub fn lerp(self, start: f64, end: f64) -> f64 {
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// consistent
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if start == end {
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start
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// exact/monotonic
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} else {
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self.mul_add(end, (-self).mul_add(start, start))
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}
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}
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// Solaris/Illumos requires a wrapper around log, log2, and log10 functions
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// because of their non-standard behavior (e.g., log(-n) returns -Inf instead
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// of expected NaN).
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