Quickstart

This section provides a quick introduction to using the findpeaks library for peak detection and analysis. The example demonstrates the basic workflow from data import to visualization using findpeaks.findpeaks.findpeaks.fit(), findpeaks.findpeaks.findpeaks.plot(), and findpeaks.findpeaks.findpeaks.plot_persistence().

A quick example how to learn a model on a given dataset.

# Import library
from findpeaks import findpeaks

# Initialize with topology method (most robust)
fp = findpeaks(method='topology')

# Example data:
X = fp.import_example('1dpeaks')

# Peak detection
results = fp.fit(X)

# Plot results
fp.plot()

# Plot persistence diagram
fp.plot_persistence()

Installation

This section covers the installation process for the findpeaks library, including environment setup and package management.

Create Environment

For optimal performance and to avoid dependency conflicts, it’s recommended to install findpeaks in an isolated Python environment using conda:

conda create -n env_findpeaks python=3.6
conda activate env_findpeaks

Install via pip:

# Installation from PyPI (recommended):
pip install findpeaks

# Install directly from GitHub (unstable version but it is the latest development version):
pip install git+https://github.com/erdogant/findpeaks

Uninstalling

If you want to remove your findpeaks installation and clean up your environment, follow these steps:

# Remove findpeaks package
pip uninstall findpeaks

# Deactivate the conda environment
conda deactivate

# List all environments to verify
conda env list

# Remove the findpeaks environment
conda env remove --name env_findpeaks

# Verify environment removal
conda env list

---

---