Metadata-Version: 2.1
Name: ROA
Version: 1.4
Summary: A simple function to compute the running optimal average and effective no. of parameters.
Home-page: https://github.com/FergusDonnan/Running-Optimal-Average
Author: Fergus Donnan
License: UNKNOWN
Platform: UNKNOWN
Description-Content-Type: text/markdown
Requires-Dist: numpy (>=1.19.2)

# Running-Optimal-Average

Usage:

t, model, errs, P = RunningOptimalAverage(t_data, Flux, Flux_err, delta)

Calculate running optimal average on a fine grid. Also returns errors and effective number of parameters.

Import using:

from ROA import RunningOptimalAverage

Parameters
----------
t_data  :  float array :
    Time values of data points

Flux  : float array :
    Flux data values

Flux_err : float array :
    Errors for flux data points

delta  : float :
    Window width of Gaussian memory function - controls how flexible model is


Returns
----------
t  : float array :
    Time values of grid used to calculate ROA

model : float array :
    Running optimal average's calculated for each time t

errs : float array :
    Errors of running optimal average

P : float :
    Effective number of parameters for model







