Distributions

The basic required object to create a population synth are a spatial and (optional if a derived luminosity sampler is create) luminosity distribution.

[1]:

%matplotlib inline


import matplotlib.pyplot as plt
from jupyterthemes import jtplot

jtplot.style(context="notebook", fscale=1, grid=False)
purple = "#B833FF"
yellow = "#F6EF5B"

import networkx as nx
import numpy as np
import warnings

warnings.simplefilter("ignore")

popsynth comes with several built in distributions included

[2]:

import popsynth
popsynth.update_logging_level("INFO")


popsynth.list_available_distributions()

Distribution
BPLDistribution
SFRDistribution
ZPowerCosmoDistribution
DeltaDistribution
FlatlandDistribution
Log10NormalDistribution
LogNormalDistribution
ParetoDistribution
SchechterDistribution
ConstantSphericalDistribution
ZPowerSphericalDistribution
SpiralGalaxyDistribution
LogUniLuminiosityDistribution
UniformCosmoDistribution

Creating a simple population synth

First we create a spatial distribution, in the case, a Spherical distribution with a power law density.

[3]:

spatial_distribution = popsynth.ZPowerSphericalDistribution()

spatial_distribution.Lambda = 30
spatial_distribution.delta = -2
spatial_distribution.r_max = 10

And now we create a powerlaw luminosity distribution

[4]:

luminosity_distribution = popsynth.ParetoDistribution()

luminosity_distribution.alpha = 1.5
luminosity_distribution.Lmin = 1

Combining these together with a random seed, we have a population synthesis object

[5]:

pop_gen = popsynth.PopulationSynth(luminosity_distribution=luminosity_distribution,
                                   spatial_distribution = spatial_distribution,
                                   seed=1234


                                  )

[6]:

pop_gen.display()

Luminosity Function

$\displaystyle \frac{\alpha L_{\rm min}^{\alpha}}{L^{\alpha+1}}$

	parameter	value
0	alpha	1.5
1	Lmin	1.0

Spatial Function

$\displaystyle \Lambda (1+r)^{\delta}$

	parameter	value
0	Lambda	30
1	delta	-2
2	r_max	10

[7]:

population = pop_gen.draw_survey()

 INFO     |  The volume integral is 2304.6599413369304

 INFO     |  Expecting 2257 total objects 
 INFO     |  applying selection to fluxes 
 WARNING  |  NO HIDDEN OBJECTS 
 INFO     |  Detected 2257 distances 
 INFO     |  Detected 2257 objects out to a distance of 10.00

[8]:

fig=population.display_obs_fluxes_sphere(background_color="black",size=0.7);

Cosmological Distributions

If we want to create cosmological spatial distributions, we can use some of those that are built in.

[9]:

spatial_distribution = popsynth.ZPowerCosmoDistribution()
spatial_distribution.Lambda = 100
spatial_distribution.delta = -2
spatial_distribution.r_max = 10

These distributions know about the cosmological Universe and have their fluxes computed using the luminosity distance rather than linear distace.

[10]:

luminosity_distribution = popsynth.SchechterDistribution()

luminosity_distribution.alpha = 1.5
luminosity_distribution.Lmin = 1

[11]:

pop_gen = popsynth.PopulationSynth(luminosity_distribution=luminosity_distribution,
                                   spatial_distribution = spatial_distribution,
                                   seed=1234


                                  )

[12]:

pop_gen.display()

Luminosity Function

$\displaystyle \frac{1}{L_{\rm min}^{1+\alpha}\Gamma\left(1+\alpha\right)} L^{\alpha} \exp\left[ - \frac{L}{L_{\rm min}}\right]$

	parameter	value
0	alpha	1.5
1	Lmin	1.0

Spatial Function

$\displaystyle \Lambda (z+1)^{\delta}$

	parameter	value
0	Lambda	100
1	delta	-2
2	r_max	10

[13]:

population = pop_gen.draw_survey()

 INFO     |  The volume integral is 742.0199985657756

 INFO     |  Expecting 715 total objects 
 INFO     |  applying selection to fluxes 
 WARNING  |  NO HIDDEN OBJECTS 
 INFO     |  Detected 715 distances 
 INFO     |  Detected 715 objects out to a distance of 9.67

[14]:

fig=population.display_obs_fluxes_sphere(cmap="viridis", background_color="black",size=0.7);

The cosmological parameters used when simulating are stored in the cosmology object:

[15]:

popsynth.cosmology.Om

[15]:

0.3070000112056732

[16]:

popsynth.cosmology.h0

[16]:

67.69999694824219

[17]:

popsynth.cosmology.Ode

[17]:

0.6929130577203088

Note: The values of Om and h0 can be changed and will change the values of all cosmological calculations

[18]:

popsynth.cosmology.Om=0.7

[19]:

popsynth.cosmology.Ode

[19]:

0.299913080846911

Let’s re run the last simulation to see how this changes things

[20]:

pop_gen.clean()

 WARNING  |  removing all registered Auxiliary Samplers 
 WARNING  |  removing flux selector 
 WARNING  |  removing distance selector 
 WARNING  |  removing spatial selector

[21]:

population = pop_gen.draw_survey()

 INFO     |  The volume integral is 378.8422500823972

 INFO     |  Expecting 359 total objects 
 INFO     |  applying selection to fluxes 
 WARNING  |  NO HIDDEN OBJECTS 
 INFO     |  Detected 359 distances 
 INFO     |  Detected 359 objects out to a distance of 7.12

[22]:

fig=population.display_obs_fluxes_sphere(background_color="black",size=0.7);

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