class numpy.errstate(**kwargs) [source] Context manager for floating-point error handling. Using an instance of errstate as a context manager allows statements in that context to execute with a known error handling behavior. Upon entering the context the error handling is set with seterr and seterrcall, and upon exiting it is reset to what it was before. Parameters: kwargs : {divide, over, under, invalid} Keyword arguments. The valid keywords are the possible floating-point exceptions. Ea

MaskedArray.__ne__(other) [source] Check whether other doesn?t equal self elementwise

MaskedArray.__ifloordiv__(other) [source] Floor divide self by other in-place.

MaskedArray.__truediv__(other) [source] Divide other into self, and return a new masked array.

numpy.fft.ifft(a, n=None, axis=-1, norm=None) [source] Compute the one-dimensional inverse discrete Fourier Transform. This function computes the inverse of the one-dimensional n-point discrete Fourier transform computed by fft. In other words, ifft(fft(a)) == a to within numerical accuracy. For a general description of the algorithm and definitions, see numpy.fft. The input should be ordered in the same way as is returned by fft, i.e., a[0] should contain the zero frequency term, a[1:n//

numpy.clip(a, a_min, a_max, out=None) [source] Clip (limit) the values in an array. Given an interval, values outside the interval are clipped to the interval edges. For example, if an interval of [0, 1] is specified, values smaller than 0 become 0, and values larger than 1 become 1. Parameters: a : array_like Array containing elements to clip. a_min : scalar or array_like Minimum value. a_max : scalar or array_like Maximum value. If a_min or a_max are array_like, then they will be br

numpy.set_printoptions(precision=None, threshold=None, edgeitems=None, linewidth=None, suppress=None, nanstr=None, infstr=None, formatter=None) [source] Set printing options. These options determine the way floating point numbers, arrays and other NumPy objects are displayed. Parameters: precision : int, optional Number of digits of precision for floating point output (default 8). threshold : int, optional Total number of array elements which trigger summarization rather than full repr

class numpy.matrix [source] Returns a matrix from an array-like object, or from a string of data. A matrix is a specialized 2-D array that retains its 2-D nature through operations. It has certain special operators, such as * (matrix multiplication) and ** (matrix power). Parameters: data : array_like or string If data is a string, it is interpreted as a matrix with commas or spaces separating columns, and semicolons separating rows. dtype : data-type Data-type of the output matrix. co

dtype.name A bit-width name for this data-type. Un-sized flexible data-type objects do not have this attribute.

RandomState.uniform(low=0.0, high=1.0, size=None) Draw samples from a uniform distribution. Samples are uniformly distributed over the half-open interval [low, high) (includes low, but excludes high). In other words, any value within the given interval is equally likely to be drawn by uniform. Parameters: low : float, optional Lower boundary of the output interval. All values generated will be greater than or equal to low. The default value is 0. high : float Upper boundary of the outpu