Noise package

mesohops.dynamics.hops_noise class

class HopsNoise(noise_param, noise_corr)

Bases: mesohops.util.dynamic_dict.Dict_wDefaults

This is the BaseClass for defining a hops noise trajectory. All noise classes will inherit from here. Anything that defines the input-output structure of a noise trajectory should be controlled from this class - rather than any of the model-specific child classes.

get_noise(self, t_axis)

Gets the noise

Parameters
1. t_axislist

a list of time points

Returns
1. noiselist

a list of list of noise values sampled at the given time points

mesohops.dynamics.noise_fft module

class FFTFilterNoise(noise_param, noise_corr)

Bases: mesohops.dynamics.hops_noise.HopsNoise

This is a class that describes the noise function for a calculation.

static fft_filter_noise_diagonal(s_zz, seed=None)

This function calculates a noise trajectory using the bath correlation function (s_zz). This function is based on the description given by:

“Exact Simulation of Noncircular or Improper Complex-Valued Stationary Gaussian Processes using circulant embedding.” Adam M. Sykulski and Donald B. Percival IEEE Internation Workship on Machine Learning for Signal Processing (2016)

Parameters
1. s_zzlist

correlation function sampled at specific time points

2. seedint

the seed for the random number generator

Returns
1. noiselist

the random noise trajectory sampled at the same time points as s_zz

prepare_noise(self)

This function is defined for each specific noise model (children classes of HopsNoise class) and provides the specific rules for calculating a noise trajectory using

Parameters
None
Returns
None

mesohops.dynamics.noise_trajectories module

class NoiseTrajectory

Bases: abc.ABC

This is the abstract base class for Noise objects.

A noise object has two guaranteed functions: - get_noise(t_axis) - get_taxis()

class NumericNoiseTrajectory(noise, t_axis)

Bases: mesohops.dynamics.noise_trajectories.NoiseTrajectory

This is the class for noise that is explicitly calculated and does not support interpolation.

get_noise(self, taxis_req)

This function simply returns the noise values for the selected times.

NOTE: INTERPOLATION SHOULD BE IMPLEMENTED BY DEFAULT. USE FCSPLINE

FROM RICHARD TO DO IT!

Parameters
1. taxis_reqlist

a list of requested time points

Returns
1. noiselist

a list of list of noise at the requested time points

mesohops.dynamics.noise_zero module

class ZeroNoise(noise_param, noise_corr)

Bases: mesohops.dynamics.hops_noise.HopsNoise

This is a class that describes the noise function for a calculation.

get_noise(self, t_axis)

This is a function that simply returns a zero array of the correct length.

Parameters
1. taxislist

list of time points

Returns
1. list_zeroslist

a list of zeros

prepare_noise(self)

This function is defined for each specific noise model (children classes of HopsNoise class) and provides the specific rules for calculating a noise trajectory using

Parameters
None
Returns
None

mesohops.dynamics.prepare_functions module

prepare_noise(noise_param, system_param, flag=1)

This is a function that will return the proper noise class given the user inputs.

Parameters
1. noise_paramdict

dictionary of noise parameter

2. system_paramdict

dictionary of system parameters

3. flagint

1-NOISE1 parameters, 2-NOISE2 parameters

Returns
1. noiseHopsNoise object

an instantiation of HopsNoise based on user input