diff options
Diffstat (limited to 'gn3/computations/partial_correlations.py')
| -rw-r--r-- | gn3/computations/partial_correlations.py | 22 |
1 files changed, 15 insertions, 7 deletions
diff --git a/gn3/computations/partial_correlations.py b/gn3/computations/partial_correlations.py index f316f67..597c5a3 100644 --- a/gn3/computations/partial_correlations.py +++ b/gn3/computations/partial_correlations.py @@ -70,7 +70,9 @@ def control_samples(controls: Sequence[dict], sampleslist: Sequence[str]): [__process_control__(trait_data) for trait_data in controls], (tuple(), tuple(), tuple(), tuple())) -def fix_samples(primary_trait: dict, control_traits: Sequence[dict]) -> Sequence[Sequence[Any]]: +def fix_samples( + primary_trait_data: dict, + control_traits_data: Sequence[dict]) -> Sequence[Sequence[Any]]: """ Corrects sample_names, values and variance such that they all contain only those samples that are common to the reference trait and all control traits. @@ -80,20 +82,26 @@ def fix_samples(primary_trait: dict, control_traits: Sequence[dict]) -> Sequence """ primary_samples = tuple( present[0] for present in - ((sample, all(sample in control.keys() for control in control_traits)) - for sample in primary_trait.keys()) + ((sample, + all(sample in control["data"].keys() + for control in control_traits_data)) + for sample in primary_trait_data["data"].keys()) if present[1]) control_vals_vars: tuple = reduce( lambda acc, x: (acc[0] + (x[0],), acc[1] + (x[1],)), ((item["value"], item["variance"]) - for sublist in [tuple(control.values()) for control in control_traits] + for sublist in [ + tuple(control["data"].values()) + for control in control_traits_data] for item in sublist), (tuple(), tuple())) return ( primary_samples, - tuple(primary_trait[sample]["value"] for sample in primary_samples), + tuple(primary_trait_data["data"][sample]["value"] + for sample in primary_samples), control_vals_vars[0], - tuple(primary_trait[sample]["variance"] for sample in primary_samples), + tuple(primary_trait_data["data"][sample]["variance"] + for sample in primary_samples), control_vals_vars[1]) def find_identical_traits( @@ -628,7 +636,7 @@ def check_for_common_errors(# pylint: disable=[R0914] fixed_primary_vals, fixed_control_vals, _primary_variances, - _cntrl_variances) = fix_samples(primary_trait, cntrl_traits) + _cntrl_variances) = fix_samples(primary_trait_data, cntrl_traits_data) if len(common_primary_control_samples) < corr_min_informative: return { |