Example Usage¶

Simplest example (10 steps with width 50 samples, normal distribution with unit standard deviation and zero mean) follows.

import signalz
x = signalz.random_steps(50, 10)

More complicated example with normal distribution (standard deviation and mean value is changed) follows.

import signalz
x = signalz.random_steps(50, steps_count=10, distribution="normal", std=30, mean=-10)

Another example, this time the size of the data is not requested by number of steps, but by number of samples (size=500).

import signalz
x = signalz.random_steps(50, size=500)

Function Documentation¶

signalz.generators.random_steps.random_steps(step_width, steps_count=10, size=None, distribution='normal', maximum=1, minimum=0, std=1, mean=0)[source]¶

This function generates random steps.

Args:

• step_width - desired width of every step (int)

Kwargs:

• steps_count - desired number steps (int), this variable is used, if the size is not defined
• size - lenght of desired output in samples (int), if this variable is defined, it determines the size of data instead of steps_count
• distribution - distribution of random numbers (str), Options are normal and uniform.
• maximum - maximal value for steps (float), this value is used in case of uniform distribution.
• minimum - minimal value for steps (float), this value is used in case of uniform distribution.
• std - standard deviation of random variable (float), this value is used in case of gaussian (normal) distribution.
• mean - mean value of random variable (float), this value is used in case of gaussian (normal) distribution.

Returns:

• vector of values representing desired steps (1d array)