echotime 0.17.0

Explainable structural similarity for time series and time-series datasets.

EchoTime

Explainable time-series similarity for humans and agents.

EchoTime compares time series and time-series datasets, explains why they match or differ, and emits compact JSON plus shareable HTML reports.

Why this package exists

Most time-series tooling helps after you decide what to model. EchoTime helps one step earlier: compare two signals clearly, compare two datasets structurally, and emit a result that a human or an agent can actually act on.

Quickstart

pip install echotime
python -c "import numpy as np; from echotime import compare_series; x=np.sin(np.linspace(0,8*np.pi,128)); y=np.sin(np.linspace(0,8*np.pi,128)+0.2); print(compare_series(x,y).to_summary_card_markdown())"

Expected output starts like this:

# EchoTime similarity summary
overall similarity: ...
top components: shape similarity, trend similarity, spectral similarity

Use your own data

EchoTime is meant to run on real files, not just toy arrays.

• single numeric column -> profile_series(...)
• wide table with one timestamp column and one or more numeric columns -> profile_dataset(df, domain=...)
• irregular long table -> rename columns to subject, timestamp, channel, value, then call profile_dataset(...)
• two columns to compare -> compare_series(df["left"], df["right"])

Tabular inputs are auto-detected from names such as timestamp / time, value / measurement, channel / sensor / metric, and subject / patient / participant.

from pathlib import Path

import pandas as pd
from echotime import profile_dataset

df = pd.read_csv("my_timeseries.csv").rename(columns={"date": "timestamp"})
profile = profile_dataset(df, domain="energy")
print(profile.to_summary_card_markdown())
Path("my_dataset_report.html").write_text(profile.to_html_report(), encoding="utf-8")

What ships in v0.17.0

• compare-first public package surface
• agent-ready JSON wrappers with stable envelopes
• GitHub Pages-ready docs bundle
• local live demo for pasted arrays
• starter datasets, notebooks, and flagship demos
• compatibility presets and environment doctor guidance for mixed scientific stacks

Common entry points

• echotime-demo --open-browser
• echotime --guide quickstart
• echotime --guide doctor
• echotime --export-pages docs

Links

• README: README.md
• Start here: START_HERE.md
• Compatibility: COMPATIBILITY.md
• Local live demo: LIVE_DEMO.md
• Agent input contract: AGENT_INPUT_CONTRACT.md

Maintainer

• Zipeng Wu
• The University of Birmingham
• [e-mail]
• https://github.com/ZipengWu365/EchoWave