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| author | Frederick Muriuki Muriithi | 2021-11-04 12:38:27 +0300 |
|---|---|---|
| committer | Frederick Muriuki Muriithi | 2021-11-04 12:38:27 +0300 |
| commit | 0357f5c5e6eeb146eb259337019c87079363a256 (patch) | |
| tree | fb6d03e8120ca983473568dec214a92251386c65 /gn3/computations | |
| parent | 32e6d788ac5b6fa8daf4c26b2ad7bca32d71d828 (diff) | |
| download | genenetwork3-0357f5c5e6eeb146eb259337019c87079363a256.tar.gz | |
Implement `build_data_frame`
Issue:
https://github.com/genenetwork/gn-gemtext-threads/blob/main/topics/gn1-migration-to-gn2/partial-correlations.gmi
* gn3/computations/partial_correlations.py: new function (`build_data_frame`)
* tests/unit/computations/test_partial_correlations.py: Add tests for new
function
Add a new function to build a pandas DataFrame object from the provided
values:
- x: a vector of floats (represented with a tuple of floats)
- y: a vector of floats (represented with a tuple of floats)
- z: a vector OR matrix of floats (represented with a tuple of floats or a
tuple of tuples of floats)
Diffstat (limited to 'gn3/computations')
| -rw-r--r-- | gn3/computations/partial_correlations.py | 16 |
1 files changed, 16 insertions, 0 deletions
diff --git a/gn3/computations/partial_correlations.py b/gn3/computations/partial_correlations.py index 07dc16d..ffdf0c5 100644 --- a/gn3/computations/partial_correlations.py +++ b/gn3/computations/partial_correlations.py @@ -10,6 +10,8 @@ from typing import Any, Tuple, Sequence from scipy.stats import pearsonr, spearmanr from gn3.settings import TEXTDIR +import pandas + from gn3.data_helpers import parse_csv_line def control_samples(controls: Sequence[dict], sampleslist: Sequence[str]): @@ -258,6 +260,20 @@ def compute_partial_correlations_fast(# pylint: disable=[R0913, R0914] else fetched_correlations[corr[0]][0:2]) for idx, corr in enumerate(all_correlations)) +def build_data_frame( + xdata: Tuple[float, ...], ydata: Tuple[float, ...], + zdata: Union[ + Tuple[float, ...], + Tuple[Tuple[float, ...], ...]]) -> pandas.DataFrame: + """ + Build a pandas DataFrame object from xdata, ydata and zdata + """ + x_y_df = pandas.DataFrame({"x": xdata, "y": ydata}) + if isinstance(zdata[0], float): + return x_y_df.join(pandas.DataFrame({"z": zdata})) + return x_y_df.join(pandas.DataFrame( + {"z{}".format(i): val for i, val in enumerate(row)} for row in zdata)) + def partial_correlation_matrix( xdata: Tuple[float, ...], ydata: Tuple[float, ...], zdata: Tuple[float, ...], method: str = "pearsons", |