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__distributions.py
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__distributions.py
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# PROJECT JULY-SEPTEMBRE 2019
# SOLVING THE N-BODIES PROBLEM / FUNCTIONS
# By Enguerran VIDAL
# This .py file contains the fucntions responsible for creating the different random distributions of massive objects
# we will later let evolve using our algorithms
###############################################################
# IMPORTS #
###############################################################
#-----------------MODULES
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import random
import matplotlib.animation
#-----------------PYTHON FILES
from __constants_conversions import*
from __functions import*
from __algorithms import*
###############################################################
# FONCTIONS #
###############################################################
def Random_Distribution_2D(distribution_type,distribution_seed,n_objects):
''' Creates a random distribution of objects in a 2D space by following a certain distribution type.
Available 2D Distributions : Uniform Square, Uniform Disk, '''
assert distribution_seed!=None and type(distribution_seed)==int
np.random.seed(distribution_seed)
n=n_objects
objects=[]
if distribution_type=='uniform_square':
X=np.random.uniform(-10**(20), 10**(20),n)
Y=np.random.uniform(-10**(20), 10**(20),n)
dX=np.random.uniform(-10**(3), 10**(3),n)
dY=np.random.uniform(-10**(3), 10**(3),n)
M=np.random.uniform(10**(29),10**(32),n)
for i in range(n):
position=np.array([X[i],Y[i]])
speed=np.array([dX[i],dY[i]])
mass=M[i]
objectI=Object(mass,position,speed)
objects.append(objectI)
if distribution_type=='uniform_disk':
for i in range(n):
u=np.random.normal(0,1)
v=np.random.normal(0,1)
norm=np.sqrt(u*u+v*v)
r=np.cbrt(np.random.random())
U=np.array([u,v])
position=(U/norm)*10**(20)*r # position on 1m sphere * radius
dx=np.random.uniform(-10**(3), 10**(3))
dy=np.random.uniform(-10**(3), 10**(3))
speed=np.array([dx,dy])
mass=np.random.uniform(10**(29),10**(32))
objectI=Object(mass,position,speed)
objects.append(objectI)
return objects
def Random_Distribution_3D(distribution_type,distribution_seed,n_objects):
''' Creates a random distribution of objects in a 3D space by following a certain distribution type.
Available 3D Distributions : Uniform Cube, Uniform Square, Uniform Sphere, Uniform Ball, Uniform Disk,
Uniform Cylinder, Uniform Disk with cluster and Central Back Hole,
Uniform Ball with cluster and Central Back Hole'''
assert distribution_seed!=None and type(distribution_seed)==int
np.random.seed(distribution_seed)
n=n_objects
objects=[]
if distribution_type=='uniform_cube':
X=np.random.uniform(-10**(20), 10**(20),n)
Y=np.random.uniform(-10**(20), 10**(20),n)
Z=np.random.uniform(-10**(20), 10**(20),n)
dX=np.random.uniform(-10**(3), 10**(3),n)
dY=np.random.uniform(-10**(3), 10**(3),n)
dZ=np.random.uniform(-10**(3), 10**(3),n)
M=np.random.uniform(10**(29),10**(32),n)
for i in range(n):
position=np.array([X[i],Y[i],Z[i]])
speed=np.array([dX[i],dY[i],dZ[i]])
mass=M[i]
objectI=Object(mass,position,speed)
objects.append(objectI)
if distribution_type=='uniform_square':
X=np.random.uniform(-10**(20), 10**(20),n)
Y=np.random.uniform(-10**(20), 10**(20),n)
Z=np.zeros_like(X)
dX=np.random.uniform(-10**(3), 10**(3),n)
dY=np.random.uniform(-10**(3), 10**(3),n)
dZ=np.zeros_like(dX)
M=np.random.uniform(10**(29),10**(32),n)
for i in range(n):
position=np.array([X[i],Y[i],Z[i]])
speed=np.array([dX[i],dY[i],dZ[i]])
mass=M[i]
objectI=Object(mass,position,speed)
objects.append(objectI)
if distribution_type=='uniform_sphere':
# We construct a sphere using the Muller method
for i in range(n):
u=np.random.normal(0,1)
v=np.random.normal(0,1)
w=np.random.normal(0,1)
norm=np.sqrt(u*u+v*v+w*w)
U=np.array([u,v,w])
position=(U/norm)*10**(20) # position on 1m sphere * radius
dx=np.random.uniform(-10**(3), 10**(3))
dy=np.random.uniform(-10**(3), 10**(3))
dz=np.random.uniform(-10**(3), 10**(3))
speed=np.array([dx,dy,dz])
mass=np.random.uniform(10**(29),10**(32))
objectI=Object(mass,position,speed)
objects.append(objectI)
if distribution_type=='uniform_ball':
# We construct a sphere using the Muller method
for i in range(n):
u=np.random.normal(0,1)
v=np.random.normal(0,1)
w=np.random.normal(0,1)
norm=np.sqrt(u*u+v*v+w*w)
r=np.cbrt(np.random.random())
U=np.array([u,v,w])
position=(U/norm)*10**(20)*r # position on 1m sphere * radius
dx=np.random.uniform(-10**(3), 10**(3))
dy=np.random.uniform(-10**(3), 10**(3))
dz=np.random.uniform(-10**(3), 10**(3))
speed=np.array([dx,dy,dz])
mass=np.random.uniform(10**(29),10**(32))
objectI=Object(mass,position,speed)
objects.append(objectI)
if distribution_type=='uniform_disk':
for i in range(n):
u=np.random.normal(0,1)
v=np.random.normal(0,1)
norm=np.sqrt(u*u+v*v)
r=np.cbrt(np.random.random())
U=np.array([u,v,0])
position=(U/norm)*10**(20)*r # position on 1m disk * radius
dx=np.random.uniform(-10**(3), 10**(3))
dy=np.random.uniform(-10**(3), 10**(3))
dz=np.zeros_like(dx)
speed=np.array([dx,dy,dz])
mass=np.random.uniform(10**(29),10**(32))
objectI=Object(mass,position,speed)
objects.append(objectI)
if distribution_type=='uniform_cylinder':
for i in range(n-1):
u=np.random.normal(0,1)
v=np.random.normal(0,1)
z=np.random.uniform(-10**(20),10**(20))
norm=np.sqrt(u*u+v*v)
r=np.cbrt(np.random.random())
U=np.array([u,v,0])
position=(U/norm)*10**(20)*r # position on 1m disk * radius
position[2]=z
dx=np.random.uniform(-10**(3), 10**(3))
dy=np.random.uniform(-10**(3), 10**(3))
dz=np.zeros_like(dx)
speed=np.array([dx,dy,dz])
mass=np.random.uniform(10**(29),10**(32))
objectI=Object(mass,position,speed)
objects.append(objectI)
if distribution_type=='uniform_disk_cluster+bh':
for i in range(n-1):
u=np.random.normal(0,1)
v=np.random.normal(0,1)
norm=np.sqrt(u*u+v*v)
r=np.cbrt(np.random.random())
U=np.array([u,v,0])
position=(U/norm)*10**(20)*r # position on 1m disk * radius
dx=np.random.uniform(-10**(2), 10**(2))
dy=np.random.uniform(-10**(2), 10**(2))
dz=np.zeros_like(dx)
speed=np.array([dx,dy,dz])
mass=np.random.uniform(10**(29),10**(32))
objectI=Object(mass,position,speed)
objects.append(objectI)
BH=Object(10**(36),np.array([0,0,0]),np.array([0,0,0]))
objects.append(BH)
if distribution_type=='uniform_ball_cluster+bh':
# We construct a sphere using the Muller method
for i in range(n-1):
u=np.random.normal(0,1)
v=np.random.normal(0,1)
w=np.random.normal(0,1)
norm=np.sqrt(u*u+v*v+w*w)
r=np.cbrt(np.random.random())
U=np.array([u,v,w])
position=(U/norm)*10**(20)*r # position on 1m sphere * radius
dx=np.random.uniform(-10**(5), 10**(5))
dy=np.random.uniform(-10**(5), 10**(5))
dz=np.random.uniform(-10**(5), 10**(5))
speed=np.array([dx,dy,dz])
mass=np.random.uniform(10**(29),10**(32))
objectI=Object(mass,position,speed)
objects.append(objectI)
BH=Object(10**(36),np.array([0,0,0]),np.array([0,0,0]))
objects.append(BH)
return objects