print_statistics

pyapprox.variables.print_statistics(samples, values=None, sample_labels=None, value_labels=None)[source]

Print statistics about a set of samples and associated values

Parameters:

samplesnp.ndarray (num_vars,num_samples): Random samples
valuesnp.ndarray (num_samples,num_qoi): Function values at samples

Examples

>>> num_vars = 2
>>> np.random.seed(1)
>>> samples = np.random.normal(0, 1, (num_vars, 100))
>>> values = np.array([np.sum(samples**2, axis=0), 2*np.sum(samples**2, axis=0)]).T
>>> print_statistics(samples, values)
           z0         z1         y0         y1
count  100.000000 100.000000 100.000000 100.000000
mean     0.060583   0.152795   1.679132   3.358265
std      0.885156   0.931995   1.705877   3.411753
min     -2.301539  -2.434838   0.031229   0.062458
max      2.185575   2.528326   9.575905  19.151810