csv-npy

name	csv_npy
description	Plain .csv / .npy / .npz array loaders — last-resort generic data import
layer	L0
group	consumer_eeg
metadata	{"tags":["io","csv","npy","npz","generic","scientific_python"],"formats":[".csv",".npy",".npz"],"modalities":["eeg","meg","seeg","ecog","fnirs","lfp"]}

CSV / NPY / NPZ

Format Overview

Plain scientific-Python arrays:

• .csv: text, row-major or column-major.
• .npy: numpy save format; one array.
• .npz: numpy archive; multiple arrays.

Used as last resort when no domain format applies, or as an intermediate between pipeline steps.

Loader

Primary:

• np.load for .npy / .npz.
• pandas.read_csv or np.genfromtxt for .csv.

Common Pitfalls

• Orientation. (n_channels, n_times) is EasyBCI convention; CSV often is the transpose.
• No metadata. Sample rate, channel names, units — must come from a sidecar or user declaration.
• Memory mode. Large .npy should use mmap_mode="r".

EasyBCI Path

- load:csv,sfreq=USER_PROVIDED,layout=channel_x_time
- load:npy,sfreq=USER_PROVIDED

References

1. (none specific — generic format.)

Boundary

• mat: MATLAB array variant.
• custom_binary: raw binary without numpy framing.