Multivariate Functional Example

This notebook will show how to use the fdasrsf package to align and statistically analyze a set of multivariate functions using the SRVF framework

Load Packages

We will load the required packages and the example data set (MPEG7)

import fdasrsf as fs
import matplotlib.pyplot as plt
import numpy as np
data = np.load('../bin/gait_data.npz',allow_pickle=True)
f = data['f']
g = data['g']
time = data['time']

Now we will construct a 2-D array of a set of 1-D functions from the gait data

M,K = f.shape

beta = np.zeros((2,M,K))
beta[0,:,:] = f
beta[1,:,:] = g

Analyze

We now will construct a fdacurve object

obj = fs.fdacurve(beta,N=M)

Next, find the Karcher mean and align the curves to the mean

obj.karcher_mean(rotation=False)
obj.srvf_align(rotation=False)

Computing Karcher Mean of 39 curves in SRVF space with lam=0
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We will now plot the results

obj.plot(multivariate=True)