csiphon

csiphon is a Python library for preprocessing WiFi Channel State Information. You plug DSP steps together into a pipeline, csiphon checks that the pieces fit before you run anything, and the finished pipeline handles recordings and live streams alike. Every signal carries its axes by name, so you never have to wonder which one was the subcarrier again.

from csiphon import AcquisitionProfile, Pipeline
from csiphon.steps import GainNormalize, Magnitude, WindowedVariance

# Describe the capture setup
profile = AcquisitionProfile(
    n_rx_antennas=3,
    subcarrier_indices=tuple(range(52)),
    sampling_rate_hz=1000.0,
)

# Define the pipeline steps
siphon = (
    Pipeline()
    .then(Magnitude())
    .then(GainNormalize())
    .then(WindowedVariance(win_size_s=0.1))
    .compile(profile)
)

# Generate a summary of the pipeline
print(siphon.describe())

# Push some data through it to run
features = siphon.pour(profile.raw_signal(csi, timestamps)).single()

A compiled pipeline is a Siphon. You pour() a recording through it or stream() live data, and collect results from named Outlets, which you can tap anywhere along the pipeline.

What it does

• Catches structural mistakes before execution. Compilation checks axes, shapes, value semantics, and physical representations before data starts flowing.
• Runs the same recipe in batch or live. Every step states whether its streaming computation matches batch, differs intentionally, or requires the complete recording.
• Supports branching pipelines. Split into parallel feature paths, merge them again, and expose named intermediate outlets.
• Merges receivers. Feed several receivers through their own inlets and line them up on timestamps or on packet sequence numbers, which survive clock drift.
• Keeps real timestamps. Non-uniform CSI sampling is expected; resampling is explicit rather than silently assumed. You can also drop packets on purpose, with independent or bursty loss, to test how a pipeline copes.
• Describes itself. describe() draws a compiled siphon as a data-flow graph in the terminal. Steps and siphons expose their contracts, layouts, parameters, and streaming behavior, and can save that information alongside results for reproducibility.
• Measures itself. siphon.measure(signal) pours once and reports each step's time and output shape (memory on request), per step or for a named group of consecutive steps.

The built-in steps cover components, scaling, cleaning, calibration, normalization, baseline removal, filtering, temporal features, delay and time-frequency transforms, pooling, statistics, reduction, restructuring, and resampling. The steps README lists the categories. Custom steps use the same contracts and inspection tools.

Install

pip install csiphon

The core only depends on NumPy. A few steps (filters, STFT, multitaper, cubic-spline resampling) need the [filters] extra (SciPy), and the synchrosqueezed transform needs [sst]. Install everything with:

pip install "csiphon[all]"

Runnable recipes live in examples/.