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Parse/write FCS (Flow Cytometry) files v2.0-3.1. Events as NumPy, channel metadata, multi-dataset files, CSV/FCS export. Use FlowKit for gating/compensation.
Passed 22 of 22 test cases with the skill, and 6 of 22 without it.
and 22 more in the full report
16 fixed6 passed either way0 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 16 test cases the skill fixed. Same model, same prompt, with and without the skill.
I need to look up acquisition date (`$DATE`) and cytometer model (`$CYT`) in `sample.fcs` in Python without splitting raw binary strings manually. How do I access the dictionary of standard header keywords?
| Checked | Without skill | With skill |
|---|---|---|
| Accesses the text attribute dictionary on FlowData. | Missed | Passed |
The instructions your model reads when the skill loads.
FlowIO is a lightweight Python library for reading and writing Flow Cytometry Standard (FCS) files. It parses FCS metadata, extracts event data as NumPy arrays, and creates new FCS files. Supports FCS versions 2.0, 3.0, and 3.1. Minimal dependencies — ideal for data pipelines and preprocessing before advanced analysis.
pip install flowio numpy pandas
Requires Python 3.9+. No compiled dependencies — installs on any platform.
from flowio import FlowData
flow = FlowData("experiment.fcs")
print(f"Events: {flow.event_count}, Channels: {flow.channel_count}")
print(f"Channels: {flow.pnn_labels}")
events = flow.as_array() # Shape: (n_events, n_channels)
print(f"Data shape: {events.shape}")
test cases passed, vs 6 / 22 without
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