Make median and quantile consistent to base R

[hcirellu]

median and quantile have unexpected results when comparing it with integer transfered to integer64.

main:

median(as.integer64(c(1, 3)))
# integer64
# [1] 3

PR:

median(as.integer64(c(1, 3)))
# integer64
# [1] 2

I had to fix two existing tests.

Closes #247

[hcirellu]

I also had to change the optimizer64 in a way that the comparing quantile is called with type=7, which is the default in R. In addition I needed to add a custom round function, that does not round to the next even number for the conversion from double to integer64.
This way it meets the integer64 logic of calculating the in-between values in sortqtl.integer64 and orderqtl.integer64 where the resulting value is calculated by the interpolation of the neighboring values, i.e.:

neighboring_values[1L,] + (neighboring_values[2L,] - neighboring_values[1L,])*(sel%%1)

This boils down to:

as.integer64(1L) + as.integer64(2L - 1L)*0.5
# integer64
# [1] 2

which is different to coercing the double result to integer64 for comparison:

as.integer64(1L + (2L - 1L)*0.5)
# integer64
# [1] 1

Is this ok? Or should the calculation in sortqtl.integer64 and orderqtl.integer64 be changed to meet the requirement that median(as.integer(1:2)) equals as.integer64(median(1:2)), which seems inconsistent with the interpolation of neighboring values using +, -, and * for integer64?
WDYT?