def test_pandas(self, close_figures):
pc = PCA(pd.DataFrame(self.x))
pc1 = PCA(self.x)
assert_allclose(pc.factors.values, pc1.factors)
fig = pc.plot_scree()
fig = pc.plot_scree(ncomp=10)
fig = pc.plot_scree(log_scale=False)
fig = pc.plot_rsquare()
fig = pc.plot_rsquare(ncomp=5)
proj = pc.project(2)
PCA(pd.DataFrame(self.x), ncomp=4, gls=True)
PCA(pd.DataFrame(self.x), ncomp=4, standardize=False)
def test_rsquare(self):
x = self.x + 0.0
mu = x.mean(0)
x_demean = x - mu
std = np.std(x, 0)
x_std = x_demean / std
pc = PCA(self.x)
nvar = x.shape[1]
rsquare = np.zeros(nvar + 1)
tss = np.sum(x_std**2)
for i in range(nvar + 1):
errors = x_std - pc.project(i, transform=False, unweight=False)
rsquare[i] = 1.0 - np.sum(errors**2) / tss
assert_allclose(rsquare, pc.rsquare)
pc = PCA(self.x, standardize=False)
tss = np.sum(x_demean**2)
for i in range(nvar + 1):
errors = x_demean - pc.project(i, transform=False, unweight=False)
rsquare[i] = 1.0 - np.sum(errors**2) / tss
assert_allclose(rsquare, pc.rsquare)
pc = PCA(self.x, standardize=False, demean=False)
tss = np.sum(x**2)
for i in range(nvar + 1):
errors = x - pc.project(i, transform=False, unweight=False)
rsquare[i] = 1.0 - np.sum(errors**2) / tss
assert_allclose(rsquare, pc.rsquare)
def test_rsquare(self):
x = self.x + 0.0
mu = x.mean(0)
x_demean = x - mu
std = np.std(x, 0)
x_std = x_demean / std
pc = PCA(self.x)
nvar = x.shape[1]
rsquare = np.zeros(nvar + 1)
tss = np.sum(x_std ** 2)
for i in range(nvar + 1):
errors = x_std - pc.project(i, transform=False, unweight=False)
rsquare[i] = 1.0 - np.sum(errors ** 2) / tss
assert_allclose(rsquare, pc.rsquare)
pc = PCA(self.x, standardize=False)
tss = np.sum(x_demean ** 2)
for i in range(nvar + 1):
errors = x_demean - pc.project(i, transform=False, unweight=False)
rsquare[i] = 1.0 - np.sum(errors ** 2) / tss
assert_allclose(rsquare, pc.rsquare)
pc = PCA(self.x, standardize=False, demean=False)
tss = np.sum(x ** 2)
for i in range(nvar + 1):
errors = x - pc.project(i, transform=False, unweight=False)
rsquare[i] = 1.0 - np.sum(errors ** 2) / tss
assert_allclose(rsquare, pc.rsquare)
def test_pandas(self):
pc = PCA(pd.DataFrame(self.x))
pc1 = PCA(self.x)
assert_equal(pc.factors.values, pc1.factors)
fig = pc.plot_scree()
fig = pc.plot_scree(ncomp=10)
fig = pc.plot_scree(log_scale=False)
fig = pc.plot_rsquare()
fig = pc.plot_rsquare(ncomp=5)
proj = pc.project(2)
PCA(pd.DataFrame(self.x), ncomp=4, gls=True)
PCA(pd.DataFrame(self.x), ncomp=4, standardize=False)
