Python

Install

You can install the python bindings through pip. It ships the whole library (so you don't have to install it beforehand).

pip install libspot

The bindings are implemented as a CPython C extension (i.e. directly using the CPython API). So the overhead is low (but it deserves to be evaluated).

Info

This C extension uses the CPython Limited API. It makes the built wheels compatible with multiple versions of Python. So in practice, a single wheel is built for each OS et can be installed along with any CPython>=3.6.

Get started

import matplotlib.pyplot as plt
import numpy as np

from libspot import ANOMALY, Spot

# Fancyness ---------------------------------------------------------------- #
colors = {
    "bg": "#242933",
    "stream": "#88c0d0",
    "threshold": "#ebcb8b",
    "anomaly": "#bf616a",
    "axes": "#eceff4",
}
style = {
    "figure.facecolor": colors["bg"],
    "axes.facecolor": colors["bg"],
    "axes.edgecolor": colors["axes"],
    "xtick.color": colors["axes"],
    "ytick.color": colors["axes"],
    "font.family": "monospace",
    "font.monospace": "IBM Plex Mono",
    "font.size": 20,
    "svg.fonttype": "none",
    "lines.markersize": 10.0,
}
# -------------------------------------------------------------------------- #


TRAIN = np.random.standard_normal(size=10_000)
STREAM = np.random.standard_normal(size=100_000)
THRESHOLD = np.zeros(STREAM.size)

spot = Spot(q=5e-6, max_excess=2000, level=0.99)
spot.fit(TRAIN)

Ax = []
Ay = []
for i, x in enumerate(STREAM):
    r = spot.step(x)
    if r == ANOMALY:
        Ax.append(i)
        Ay.append(x)
    THRESHOLD[i] = spot.anomaly_threshold


with plt.rc_context(style):
    fig, ax = plt.subplots(figsize=(14, 6))
    ax.plot(STREAM, color=colors["stream"])
    ax.plot(THRESHOLD, ls="--", lw=2, color=colors["threshold"])
    ax.scatter(Ax, Ay, color=colors["anomaly"])
    fig.tight_layout()
    fig.savefig("../docs/img/basic.svg")