RandomState.lognormal(mean=0.0, sigma=1.0, size=None) Draw samples from a log-normal distribution. Draw

numpy.newbuffer(size) Return a new uninitialized buffer object.

numpy.core.defchararray.rindex(a, sub, start=0, end=None)

chararray.ljust(width, fillchar=' ')

numpy.core.defchararray.isnumeric(a)

MaskedArray.tobytes(fill_value=None, order='C')

numpy.dot(a, b, out=None) Dot product of two arrays. For 2-D arrays it is equivalent to matrix multiplication, and for 1-D

numpy.linalg.solve(a, b)

numpy.core.defchararray.less(x1, x2)

numpy.polynomial.laguerre.lagvander(x, deg)