numpy.polynomial.polynomial.polyval(x, c, tensor=True)

RandomState.triangular(left, mode, right, size=None) Draw samples from the triangular distribution. The

numpy.ma.min(obj, axis=None, out=None, fill_value=None)

numpy.polynomial.laguerre.lagdomain = array([0, 1])

numpy.arcsinh(x[, out]) = Inverse hyperbolic sine element-wise.

numpy.histogramdd(sample, bins=10, range=None, normed=False, weights=None)

numpy.testing.assert_approx_equal(actual, desired, significant=7, err_msg='', verbose=True)

New in version 1.4.0.

numpy.mat(data, dtype=None)

numpy.core.defchararray.decode(a, encoding=None, errors=None)