added c2tcio

[prakharcode]

@giordano and @helgee any idea why this error is coming up?

[codecov-io]

Codecov Report

Merging #23 into master will increase coverage by 0.01%. The diff coverage is 100%.

@@            Coverage Diff             @@
##           master      #23      +/-   ##
==========================================
+ Coverage   98.64%   98.66%   +0.01%     
==========================================
  Files           5        5              
  Lines          74       75       +1     
==========================================
+ Hits           73       74       +1     
  Misses          1        1

Impacted Files	Coverage Δ
src/AstroBase.jl	98.3% <100%> (+0.02%)	:arrow_up:

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[giordano]

Which error?

[prakharcode]

there's a difference in ERFA and Julia's implementation. For any random matrix A and B and a random angle.

julia> celestial_to_terrestrial_matrix(a, 1.2, b)
3×3 Array{Float64,2}:
 1.37602  -0.539649  1.37863
 1.42513  -0.75699   1.38733
 1.40573  -0.898893  1.21214

julia> ERFA.c2tcio(a, 1.2, b)
3×3 Array{Float64,2}:
  1.46296    0.722696   0.929215
 -0.165709  -0.16177   -0.32488 
  1.04642    0.574121   0.529976

[giordano]

Probably because eraRxr(A, B) actually performs B * A?

julia> A = collect(reshape(1.0:9.0, 3, 3))
3×3 Array{Float64,2}:
 1.0  4.0  7.0
 2.0  5.0  8.0
 3.0  6.0  9.0

julia> B = collect(reshape(10.0:18.0, 3, 3))
3×3 Array{Float64,2}:
 10.0  13.0  16.0
 11.0  14.0  17.0
 12.0  15.0  18.0

julia> A * B
3×3 Array{Float64,2}:
 138.0  174.0  210.0
 171.0  216.0  261.0
 204.0  258.0  312.0

julia> B * A
3×3 Array{Float64,2}:
 84.0  201.0  318.0
 90.0  216.0  342.0
 96.0  231.0  366.0

julia> ERFA.rxr(A, B)
3×3 Array{Float64,2}:
 84.0  201.0  318.0
 90.0  216.0  342.0
 96.0  231.0  366.0

julia> ERFA.rxr(B, A)
3×3 Array{Float64,2}:
 138.0  174.0  210.0
 171.0  216.0  261.0
 204.0  258.0  312.0

or, more probably, (A' * B')' (= B*A), given the different memory layout of matrices between C and Julia

[helgee]

I think that we do not really this function. Multiplying matrices in C is a pain and a simple function like this helps but in Julia it's a piece of cake...

[prakharcode]

Sure, I'll close it then after the implementations.

[helgee]

I will close this now so we have it off the to-do list.