Source code for gammapy.time.plot_periodogram

# Licensed under a 3-clause BSD style license - see LICENSE.rst
from __future__ import absolute_import, division, print_function, unicode_literals
import numpy as np

__all__ = ["plot_periodogram"]


[docs]def plot_periodogram( time, flux, periods, power, flux_err=None, best_period=None, fap=None ): """ Plot a light curve and its periodogram. The highest period of the periodogram and its false alarm probability (FAP) is added to the plot, if given. Parameters ---------- time : `numpy.ndarray` Time array of the light curve flux : `numpy.ndarray` Flux array of the light curve periods : `numpy.ndarray` Periods for the periodogram power : `numpy.ndarray` Periodogram peaks of the data flux_err : `numpy.ndarray` (optional, default=None) Flux error array of the light curve. Is set to 0 if not given. best_period : float (optional, default=None) Period of the highest periodogram peak fap : float (optional, default=None) False alarm probability of ``best_period`` under a certain significance criterion. Returns ------- fig : `~matplotlib.figure.Figure` Matplotlib figure """ import matplotlib.pyplot as plt if flux_err is None: flux_err = np.zeros_like(flux) # set up the figure & axes for plotting fig = plt.figure(figsize=(16, 9)) grid_spec = plt.GridSpec(2, 1) # plot the light curve ax = fig.add_subplot(grid_spec[0, :]) ax.errorbar( time, flux, flux_err, fmt="ok", label="light curve", elinewidth=1.5, capsize=0 ) ax.set_xlabel("time") ax.set_ylabel("flux") ax.legend() # plot the periodogram ax = fig.add_subplot(grid_spec[1, :]) ax.plot(periods, power, c="k", label="periodogram") # mark the best period and label with significance if best_period is not None: if fap is None: raise ValueError( "Must give a false alarm probability if you give a best_period" ) # set precision for period format pre = int(abs(np.floor(np.log10(np.max(np.diff(periods)))))) label = "Detected period p = {:.{}f} with {:.2E} FAP".format( best_period, pre, fap ) ymax = power[periods == best_period] ax.axvline(best_period, ymin=0, ymax=ymax, label=label, c="r") ax.set_xlabel("period") ax.set_ylabel("power") ax.set_xlim(0, np.max(periods)) ax.legend() return fig