Tests and documentation for genetic_relatedness_weighted

[brieuclehmann]

I've created a new PR to address the remaining tasks for #1246, namely adding tests and documentation. The tests are a bit messy but I think they cover everything. I'm not sure how to write the raw summary function under the general_stat framework, so would appreciate a hand / some pointers with this @petrelharp !

[petrelharp]

Well, let's see: do you mean writing the python general stat function, for tests here? We just need to translate the C code to python, really:

genetic_relatedness_weighted_summary_func(tsk_size_t state_dim, const double *state,
    tsk_size_t result_dim, double *result, void *params)
{
    indexed_weight_stat_params_t args = *(indexed_weight_stat_params_t *) params;
    const double *x = state;
    tsk_id_t i, j;
    tsk_size_t k;
    double meanx, ni, nj;

    meanx = state[state_dim - 1] / args.total_weights[state_dim - 1];
    for (k = 0; k < result_dim; k++) {
        i = args.index_tuples[2 * k];
        j = args.index_tuples[2 * k + 1];
        ni = args.total_weights[i];
        nj = args.total_weights[j];
        result[k] = (x[i] - ni * meanx) * (x[j] - nj * meanx) / 2;
    }
    return 0;
}

... or, better, go back and look at the definition of this and see what the python code ought to be? Let's see, I actually think it should be exactly the same as what you've got there, from genetic relatedness, which is:

        def f(x):
            mx = np.sum(x) / n  # this will be in the last entry of `state` in the C code
            return np.array(
                [(x[i] - n[i] * mx) * (x[j] - n[j] * mx) / 2 for i, j in indexes]

Edit: not quite, I think just mx might need adjusting? Need to check the theory.

[petrelharp]

Comments above; otherwise, things look good! Thanks!

[jeromekelleher]

I'll have a look after you've addressed @petrelharp's comments @brieuclehmann, and can sort out any remaining details (if they're giving you trouble)

[brieuclehmann]

Thanks @petrelharp, I forgot we had derived the weighted function in the overleaf too! That's all working now. I've updated the docs too.

@jeromekelleher I'm not sure how to resolve the remaining failed checks - I'm sure it's to do with the fact that the branch is quite old so would appreciate your help with any git surgery!

[mergify]

⚠️ The sha of the head commit of this PR conflicts with #1246. Mergify cannot evaluate rules on this PR. ⚠️

[jeromekelleher]

I just did a bit of git surgery @brieuclehmann - I'll take it from here, thanks!

[codecov]

Codecov Report

Merging #2785 (8f5e416) into main (555913c) will increase coverage by 0.04%.
The diff coverage is 94.61%.

@@            Coverage Diff             @@
##             main    #2785      +/-   ##
==========================================
+ Coverage   89.89%   89.93%   +0.04%     
==========================================
  Files          30       30              
  Lines       29043    29171     +128     
  Branches     5672     5697      +25     
==========================================
+ Hits        26107    26236     +129     
+ Misses       1667     1666       -1     
  Partials     1269     1269              

Flag	Coverage Δ
c-tests	86.42% <93.75%> (+0.02%)	⬆️
lwt-tests	80.13% <ø> (ø)
python-c-tests	67.12% <71.95%> (+0.07%)	⬆️
python-tests	99.02% <100.00%> (+<0.01%)	⬆️

Flags with carried forward coverage won't be shown. Click here to find out more.

Impacted Files	Coverage Δ
c/tskit/core.h	100.00% <ø> (ø)
c/tskit/trees.c	90.80% <93.33%> (+0.02%)	⬆️
python/_tskitmodule.c	88.56% <93.44%> (+0.15%)	⬆️
c/tskit/core.c	95.78% <100.00%> (+0.01%)	⬆️
python/tskit/trees.py	98.66% <100.00%> (+0.01%)	⬆️

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