sc_math#

Extensions to Numpy, including finding array elements and smoothing data.

Highlights:

sc.findinds(): find indices of an array matching a condition
sc.findnearest(): find nearest matching value
sc.rolling(): calculate rolling average
sc.smooth(): simple smoothing of 1D or 2D arrays

Functions

`approx`	Determine whether two scalars (or an array and a scalar) approximately match.
`safedivide`	Handle divide-by-zero and divide-by-nan elegantly.
`findinds`	Find matches even if two things aren't eactly equal (e.g. floats vs.
`findfirst`	Alias for `sc.findinds(..., first=True)`.
`findlast`	Alias for `sc.findinds(..., last=True)`.
`findnearest`	Return the index of the nearest match in series to value -- like `sc.findinds()`, but always returns an object with the same type as value (i.e. findnearest with a number returns a number, findnearest with an array returns an array).
`count`	Count the number of matching elements.
`dataindex`	Take an array of data and return either the first or last (or some other) non-NaN entry.
`getvalidinds`	Return the indices that are valid based on the validity of the input data from an arbitrary number of 1-D vector inputs.
`getvaliddata`	Return the data value indices that are valid based on the validity of the input data.
`sanitize`	Sanitize input to remove NaNs.
`rmnans`	Sanitize input to remove NaNs.
`fillnans`	Alias for `sc.sanitize(..., replacenans=True)` with nearest interpolation (or a specified value).
`findnans`	Alias for `sc.findinds(np.isnan(data))`.
`nanequal`	Compare two or more arrays for equality element-wise, treating NaN values as equal.
`isprime`	Determine if a number is prime.
`numdigits`	Count the number of digits in a number (or list of numbers).
`perturb`	Define an array of numbers uniformly perturbed with a mean of 1.
`normsum`	Multiply a list or array by some normalizing factor so that its sum is equal to the total.
`normalize`	Rescale an array between a minimum value and a maximum value.
`inclusiverange`	Like `numpy.arange()`/numpy.linspace, but includes the start and stop points.
`randround`	Round a float, list, or array probabilistically to the nearest integer.
`cat`	Like `numpy.concatenate()`, but takes anything and returns an array.
`linregress`	Simple linear regression returning the line of best fit and R value.
`sem`	Calculate the standard error of the mean (SEM).
`rolling`	Alias to `pandas.Series.rolling()` (window) method to smooth a series.
`convolve`	Like `numpy.convolve()`, but always returns an array the size of the first array (equivalent to mode='same'), and solves the boundary problem present in `numpy.convolve()` by adjusting the edges by the weight of the convolution kernel.
`smooth`	Very simple function to smooth a 1D or 2D array.
`smoothinterp`	Smoothly interpolate over values
`gauss1d`	Gaussian 1D smoothing kernel.
`gauss2d`	Gaussian 2D smoothing kernel.