Utilities

Utilities module within the ketos library

This module provides a number of auxiliary methods.

complex_value(mag, angle)	Computes complex value from magnitude and phase angle.
detect_peaks(df[, distance, multiplicity, ...])	Detect peaks in time-series data.
ensure_dir(file_path)	Ensure that destination directory exists.
factors(n)	Returns sorted set of all divisors of n
get_member(cls, member_name)	Query class member by name.
morlet_func(time, frequency, width, displacement)	Compute Morlet wavelet function
ndim(a)	Returns the number of dimensions of a list/tuple/array.
nearest_values(x, i, n)	Returns the n values nearest to index i from the array x.
octave_bands([band_min, band_max])	Compute the min, central, and max frequency value of the specified octave bands, using the following formulas,
octave_bands_json(band_min, band_max)	Produce a string of the specified octave bands in json format
random_floats([size, low, high, seed])	Returns a random number or numpy array of randum numbers uniformly distributed in the half-open interval [low, high)
signif(x, p)	Round to a specified number of significant digits.
str_is_int(s[, signed])	Check if a given string represents a (signed) integer.
tostring(box[, decimals])	Convert an array, tuple or list into a string.
ceil(a[, decimals])	This function adds the ability to ceil to a decimal precision instead of to the nearest integer.
floor(a[, decimals])	This function adds the ability to floor to a decimal precision instead of to the nearest integer.
ceil_round_down(a[, decimals])	Provides a convenient way to use ceil while specifying a decimal precision to floor instead This helps deal with imprecision of finite number of floating points arithmetics
floor_round_up(a[, decimals])	Provides a convenient way to use floor while specifying a decimal precision to ceil instead This helps deal with imprecision of finite number of floating points arithmetics