scipy.interpolate.splrep — SciPy v1.11.3 Manual
scipy.interpolate.splrep# scipy.interpolate.splrep(x, y, w=None, xb=None, xe=None, k=3, task=0, s=None, t=None, full_output=0, per=0, quiet=1)[source]# Find the B-spline representation of a 1-D curve. Given the set of data points (x[i], y[i]) determine a smooth spline approximation of degree k on the interval xb <= x <= xe. Parameters: x, yarray_likeThe data points defining a curve y = f(x). warra
Random sampling (numpy.random) — NumPy v1.15 Manual
Return a sample (or samples) from the “standard normal” distribution.
numpy.random.normal — NumPy v1.10 Manual
numpy.random.normal¶ numpy.random.normal(loc=0.0, scale=1.0, size=None)¶ Draw random samples from a normal (Gaussian) distribution. The probability density function of the normal distribution, first derived by De Moivre and 200 years later by both Gauss and Laplace independently [R250], is often called the bell curve because of its characteristic shape (see the example below). The normal distribut
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scipy.stats.norm — SciPy v0.16.1 Reference Guide
