Introduce idx_prev to use as iguess

[SouthEndMusic]

Fixes half of https://github.com/SciML/DataInterpolations.jl/issues/271

Checklist

• [x] Appropriate tests were added (n/a)
• [x] Any code changes were done in a way that does not break public API
• [x] All documentation related to code changes were updated
• [x] The new code follows the contributor guidelines, in particular the SciML Style Guide and COLPRAC.
• [x] Any new documentation only uses public API

[SouthEndMusic]

Quick benchmark:

using DataInterpolations
using BenchmarkTools

N = 1000
u = rand(N)
t = cumsum(rand(N))

itp = LinearInterpolation(u, t)

t_eval = range(first(t), last(t), length = 10000)

@btime itp.(t_eval)

# old: 276.000 μs (3 allocations: 78.25 KiB)
# new: 166.600 μs (3 allocations: 78.27 KiB)

So the better iguess gives a speedup because successive evaluations are close together. What kind of benchmarking would you like to see?

[sathvikbhagavan]

@ChrisRackauckas, can you approve CI?