ivs.asteroseismology.granulation

Module granulation

Simulation of a granulation signal

Author: Joris De Ridder

Error messages are written to the logger "granulation".

Functions

ndarray

Example:

>>> time = np.linspace(0,100,200)             # E.g. in days
>>> timescale = np.array([5.0, 20.])          # time scales in days
>>> varscale = np.array([10.0, 50.0])         # variation scale in ppm
>>> gransignal = granulation(time, timescale, varscale)
>>> flux = 100000.0                           # mean flux level
>>> signal = flux * (1.0 + gransignal)        # signal in flux

granulation(time, timescale, varscale)
Simulates a time series showing granulation variations

source code

Variables

[hide private]

logger = logging.getLogger("granulation")

nullHandler = NullHandler()

Function Details

[hide private]

granulation(time, timescale, varscale)

source code

Simulates a time series showing granulation variations

A first-order autoregressive process is used, as this gives a Harvey model in the frequency domain. See also: De Ridder et al., 2006, MNRAS 365, pp. 595-605.

Parameters:

time (ndarray) - time points
timescale (ndarray) - array of time scale "tau_i" of each granulation component of the granulation/magnetic activity. Same units as 'time'.
varscale (ndarray) - array of variation scale "sigma_i" of each component of the granulation/magnetic activity in the appropriate passband. Same size as the timescale array. Unit: ppm

Returns: ndarray Example: >>> time = np.linspace(0,100,200) # E.g. in days >>> timescale = np.array([5.0, 20.]) # time scales in days >>> varscale = np.array([10.0, 50.0]) # variation scale in ppm >>> gransignal = granulation(time, timescale, varscale) >>> flux = 100000.0 # mean flux level >>> signal = flux * (1.0 + gransignal) # signal in flux

the granulation signal