signal-scope 0.1.0

A tiny (<200 line) Python tool for analyzing time-series signals: trends, volatility, drift, regime shifts, anomalies.

signal-scope

A tiny (<200 lines) Python tool for analyzing time-series data:

• Trend strength
• Volatility
• Drift detection
• Regime shifts
• Anomaly scoring
• Optional matplotlib visualizations

Perfect for finance, forecasting, sensor data, and fast exploratory analysis.

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Install

pip install signal-scope

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Usage

from signal_scope.core import analyze_ts

result = analyze_ts("my_data.csv", col="price", plot=True)
print(result)

Expected output:

{
  "trend": 0.87,
  "volatility": 0.032,
  "drift": -0.12,
  "turning_points": 5,
  "anomaly_score": 0.014
}

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Input format

CSV must contain a numeric column, e.g.:

timestamp,price
2024-01-01,120.3
2024-01-02,121.0
...

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Programmatic usage

import pandas as pd
from signal_scope.metrics import volatility

df = pd.read_csv("my_data.csv")
print(volatility(df["price"]))

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Plotting

Enable visual output:

analyze_ts("my_data.csv", col="price", plot=True)

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MIT License.