libemd

libemd is a library of functions for Python for computing the empirical mode decomposition and it's variations.

libemd is still in production, but is under active development.

Installation

pip install libemd

Usage

>>> from libemd import emd
>>> imfs = emd(x)

By default, libemd uses the S-number stoppage criterion with an S-number of 1. You can adjust this with the method keyword argument.

libemd uses the SciPy functions argrelmax and argrelmin for locating the extrema in signals. You can override this with the peakfindermax and peakfindermin keyword arguments, which both accept function objects that accept a signal as their only argument and return the indices of extrema in a numpy array.

You can also optionally specify a filter to apply to the signal before any peakfinding takes place. This filter is just used for peakfinding, and does not affect the signal during the decomposition.

Features

Algorithms

• EMD
• EEMD
• CEEMDAN
• MEMD

Stopping criteria

• Standard deviation
• S-number
• Threshold-based

Multivariate algorithms are the exception in this planned feature list, as they are still somewhat emerging.

Algorithms will, at first, be implemented in Python. On completion, algorithms will also be implemented in Cython. Ultimately, libemd will have a usage analagous to the code block below, wherein the API for the Python and Cython algorithms is identical, and they can be easily interchanged with import statements.

try:
    from libemd import cyemd as emd
except ImportError:
    from libemd import emd

Tests

Tests are designed to utilise pytest. Test source code is organized in the following form:

# == Class/function testing

# -- pytest fixtures

def get_params_testA():
    return {'params': [], 'ids': []}

@pytest.fixture(**get_params_testA())
def params_testA(request):
    return request.get


# -- Tests

def test_A(params_testA):
    """
    pytest unpacks params and param ids from fixture to use in test.
    """
    pass