test.py

import pyPLS
import numpy as np
import sys
import time


def test_pls():
    #out = pyPLS.nopls(Xt, Yt[:, 0], cvfold=7, scaling=1., penalization=True)
    # print("noPLS1 R2 = ", out.R2Y, out.ncp)
    # print("noPLS1 Q2 = ", out.Q2Y, out.ncp)
    out = pyPLS.pls(Xt, Yt[:, 0], ncp=2, scaling=1., cvfold=7)
    print("PLS1 R2 = ", out.R2Y, out.ncp)
    print("PLS1 Q2 = ", out.Q2Y, out.ncp)
    # out = pyPLS.nopls(Xt, Yt[:, 0:2], cvfold=7, scaling=1., penalization=True)
    # print("noPLS2 R2 = ", out.R2Ycol[0], out.R2Ycol[1], out.ncp)
    # print("noPLS2 Q2 = ", out.Q2Ycol[0], out.Q2Ycol[1], out.ncp)
    out = pyPLS.pls(Xt, Yt[:, 0:2], ncp=2, cvfold=7, scaling=1.)
    print("PLS2 R2 = ", out.R2Ycol[0], out.R2Ycol[1], out.ncp)
    print("PLS2 Q2 = ", out.Q2Ycol[0], out.Q2Ycol[1], out.ncp)


def test_pca():
    start_time = time.time()
    out = pyPLS.pca(Xt,4)
    print("PCA using svd on the kernel  --- %s seconds ---" % (time.time() - start_time))
    start_time = time.time()
    out = pyPLS.pca(Xt, 4, method='nipals')
    print("PCA using nipals  --- %s seconds ---" % (time.time() - start_time))
    start_time = time.time()
    out = pyPLS.pca(Xt, 4, method='longTable')
    print("PCA using svd on the covariance matrix  --- %s seconds ---" % (time.time() - start_time))

def prediction():

    out = pyPLS.pls(Xt, Yt[:, 0], ncp=2, scaling=1., cvfold=7)
    Yhat, stats = out.predict(Xt, statistics=True)

    out = pyPLS.pca(Xt, 3, scaling=1)
    That = out.predict(Xt)


if __name__ == '__main__':
    Xt, Z, Yt = pyPLS.simulateData(600, 2, 30, 5., signalToNoise=100.)
    # for i in np.arange(50):
    #     Xt[i,i] = np.NaN
    if "nopls" in sys.argv[1:]:
        test_pls()
    if "pca" in sys.argv[1:]:
        test_pca()
    if "prediction" in sys.argv[1:]:
        prediction()