MC_samp

cosmic.MC_samp.galactic_positions(gx_component, size, model='McMillan')

Sample a set of Galactic positions of size=size distributed according to the user specified model. X,Y,Z positions in [pc]; Galactocentric distance in [kpc]

Parameters

gx_component : str

Choose from : ‘ThinDisk’, ‘Bulge’, ‘ThickDisk’

size : int

Size of the sample

model : str

Current default model is ‘McMillan’

Returns

xGx, yGx, zGx, inc, OMEGA, omega : array

Array of sampled positions in Galactic cartesian coordinates centered on the Galactic center and orientations in radians

cosmic.MC_samp.mass_weighted_number(dat, total_sampled_mass, component_mass)

Compute the total number of systems in the synthetic catalog based on the total sampled mass of the simulated system and the total mass of a given galactic component

Parameters

dat : DataFrame

DataFrame containing the fixed population created from cosmic-pop

total_sampled_mass : float

total amount of mass sampled to generate the fixed population including single stars

component_mass : float

mass of the Galactic component we are simulating

Returns

nSystems : int

number of systems in a Milky Way population for the selected Galactic population and fixed population

cosmic.MC_samp.sample_exponential_radial(size, scale_height)

Sample a collection of numbers of size=size distributed according to a radial exponential function with a user specific scale height

Parameters

size : int

Size of the sample

scale_height : float

Scale height of the distribution

Returns

distributed_nums : array

Array of sampled values

cosmic.MC_samp.sample_exponential_square_radial(size, scale_height)

Sample a collection of numbers of size=size distributed according to an exponential squared function with a user specific scale height

Parameters

size : int

Size of the sample

scale_height : float

Scale height of the distribution

Returns

distributed_nums : array

Array of sampled values

cosmic.MC_samp.sample_exponential_vertical(size, scale_height)

Sample a collection of numbers of size=size distributed according to a vertical exponential function with a user specific scale height

Parameters

size : int

Size of the sample

scale_height : float

Scale height of the distribution

Returns

distributed_nums : array

Array of sampled values

cosmic.MC_samp.sample_sech_squared(size, scale_height=0.3)

Sample a collection of numbers of size=size distributed according to a sech sqaured function with a user specific scale height

Parameters

size : int

Size of the sample

scale_height : float

Scale height of the distribution; Default=0.3

Returns

distributed_nums : array

Array of sampled values

cosmic.MC_samp.select_component_mass(gx_component)

Select the Galactic component mass according to McMillan (2011)

Parameters

gx_component : str

Choose from: ‘ThinDisk’, ‘Bulge’, ‘ThickDisk’

Returns

gx_component_mass : float

Galactic component mass [Msun]