index.rst

Astrophysical source population models (gammapy.astro.population)

gammapy.astro.population

Introduction

The gammapy.astro.population module provides a simple framework for population synthesis of gamma-ray sources.

Getting Started

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Radial surface density distributions

Here is a comparison plot of all available radial distribution functions of the surface density of pulsars and related objects used in literature:

import matplotlib.pyplot as plt import numpy as np from gammapy.astro.population import radial_distributions from gammapy.utils.distributions import normalize

max_radius = 20 # kpc r = np.linspace(0, max_radius, 100) colors = ['b', 'k', 'k', 'b', 'g', 'g']

for color, key in zip(colors, radial_distributions.keys()):

model = radial_distributions[key]() if model.evolved: linestyle = '-' else: linestyle = '--' label = model.__class__.__name__ plt.plot(r, normalize(model, 0, max_radius)(r), color=color, linestyle=linestyle, label=label)

plt.xlim(0, max_radius) plt.ylim(0, 0.28) plt.xlabel('Galactocentric Distance [kpc]') plt.ylabel('Normalized Surface Density [kpc^-2]') plt.legend(prop={'size': 10}) plt.show()

Velocity distributions

Here is a comparison plot of all available velocity distribution functions:

import matplotlib.pyplot as plt import numpy as np from gammapy.astro.population import velocity_distributions from gammapy.utils.distributions import normalize

v_min, v_max = 10, 3000 # km / s v = np.linspace(v_min, v_max, 200) colors = ['b', 'k', 'g']

for color, key in zip(colors, velocity_distributions.keys()):

model = velocity_distributions[key]() label = model.__class__.__name__ plt.plot(v, normalize(model, v_min, v_max)(v), color=color, linestyle='-', label=label)

plt.xlim(v_min, v_max) plt.ylim(0, 0.004) plt.xlabel('Velocity [km/s]') plt.ylabel('Probability Density [(km / s)^-1]') plt.semilogx() plt.legend(prop={'size': 10}) plt.show()

Reference/API

gammapy.astro.population