MultiPartPowerLaw#

class agabpylib.simulation.imf.MultiPartPowerLaw(slopes, break_points)#

Bases: IMF

Multi-part power-law IMF.

This class represents a multi-part power-law IMF, such as the one defined by Kroupa (https://ui.adsabs.harvard.edu/#abs/2001MNRAS.322..231K/abstract).

slopes#

The slopes alpha for each part of the power law, where the IMF is proportional to mass^(-alpha).

Type:

float array

break_points#

The masses where the slopes change. Must contain one element less than the slopes array, the array should thus be empty for a single slope. The values should form an increasing sequence.

Type:

float array

Methods Summary

cdf(mass, min_mass, max_mass)

Evaluate the IMF in its cumulative form for the input set of masses.

gen_masses(n, min_mass, max_mass, rng)

Generate random masses from this IMF.

getinfo()

returns:

info -- String with information about the IMF.

getmeta()

returns:

meta -- Metadata about the IMF.

lnpdf(mass, min_mass, max_mass)

Evaluate the IMF (the probability density as a function of mass) for the input set of masses.

Methods Documentation

cdf(mass, min_mass, max_mass)#

Evaluate the IMF in its cumulative form for the input set of masses.

Parameters:

  • mass (float or float array) – The mass value or array of mass values for which to evaluate the cumulative mass distribution function.

  • min_mass (float) – Minimum mass of interval over which to evaluate the IMF.

  • max_mass (float) – Maximum mass of interval over which to evaluate the IMF.

Returns:

cdfval – Value of the cumulative mass distribution function for each of the input masses

Return type:

float array

gen_masses(n, min_mass, max_mass, rng)#

Generate random masses from this IMF.

Parameters:

  • n (int) – Number of random mass values to generate.

  • min_mass (float) – Minimum mass of interval over which to evaluate the IMF.

  • max_mass (float) – Maximum mass of interval over which to evaluate the IMF.

  • rng (numpy.random.Generator) – Random number generator. This is provided separately to enable user control over the random number sequence.

Returns:

masses – Array of random mass values.

Return type:

float array

getinfo()#
Returns:

info – String with information about the IMF.

Return type:

str

getmeta()#
Returns:

meta – Metadata about the IMF.

Return type:

dict

lnpdf(mass, min_mass, max_mass)#

Evaluate the IMF (the probability density as a function of mass) for the input set of masses.

Parameters:

  • mass (float or float array) – The mass value or array of mass values for which to evaluate the IMF.

  • min_mass (float) – Minimum mass of interval over which to evaluate the IMF.

  • max_mass (float) – Maximum mass of interval over which to evaluate the IMF.

Returns:

lnpdf_val – Value of the natural logarithm of the IMF for each of the input masses.

Return type:

float array