simulate_lc

Python function that simulates a light curve based on the Timmer & Koenig 1995 algorithm.

Dependencies:

1. Python 2.0 or greater
2. numpy

Example Usage

Make sure simulate_lc.py is in your Python path. Open up an IPython session.

import simulate_lc

# Set the mean of the simulated light curve
mlc = 0.0

# Choose a PSD model
model = 'sharp'

# Set the number of timesteps in the simulated light curve and 
# the length of each timestep in seconds.
nn = 256.
delt = 1.0

# Set the parameters of the PSD model.
# For the 'sharp' model the parameters are the normalization, the break frequency,
# the low frequency slope, the high frequency slope, and white noise level.
params = [1.0, 10**(-6), -1.0, -2.0, 0.0]

# Simulate the light curve
sim_lc = simulate_lc.lc_sim(nn, delt, mean_lc, model, params)

sim_lc is now a 1D array containing the data points of the simulated light curve.

PSD models

The function can handle 3 different PSD models:

1. Unbroken powerlaw (model = 'unbroken')
2. Sharply broken powerlaw (model = 'sharp')
3. Bended knee (model = 'slow')