import mechanica as m
import numpy as np
# potential cutoff distance
cutoff = 1
# dimensions of universe
dim=[10., 10., 10.]
# new simulator, don't load any example
m.Simulator(example="", dim=dim)
# create a potential representing a 12-6 Lennard-Jones potential
# A The first parameter of the Lennard-Jones potential.
# B The second parameter of the Lennard-Jones potential.
# cutoff
pot = m.Potential.lennard_jones_12_6(0.275 , cutoff, 9.5075e-06 , 6.1545e-03 , 1.0e-3 )
# create a particle type
# all new Particle derived types are automatically
# registered with the universe
class Argon(m.Particle):
mass = 39.4
# bind the potential with the *TYPES* of the particles
m.Universe.bind(pot, Argon, Argon)
# uniform random cube
positions = np.random.uniform(low=0, high=10, size=(10000, 3))
# number of particles
count = 6000
# number of time points we avg things
avg_pts = 3
# dimensions of universe
dim = np.array([50., 50., 100.])
center = dim / 2
# new simulator
m.Simulator(dim=dim,
cutoff=cutoff,
integrator=m.FORWARD_EULER,
bc=m.BOUNDARY_NONE,
dt=0.001,
max_distance=0.2,
threads=8,
cells=[5, 5, 5])
clump_radius = 8
class Yolk(m.Particle):
mass = 500000
radius = 20
frozen = True
class Cell(m.Particle):
mass = 10
import mechanica as m
m.Simulator()
class Bead(m.Particle):
species = ['S1']
radius = 3
style = {"colormap" : {"species" : "S1", "map" : "rainbow", "range" : "auto"}}
def __init__(self, pos, value):
super().__init__(pos)
self.species.S1 = value
# make a ring of of 50 particles
pts = m.points(m.Ring, 100) * 4 + m.Universe.center
# constuct a particle for each position, make
# a list of particles
beads = [Bead(p, i/100.) for i, p in enumerate(pts)]
Bead.i = 0
def keypress(e):
names = m.Colormap.names()
name = None
if (e.key_name == "n"):
Bead.i = (Bead.i + 1) % len(names)
name = names[Bead.i]
print("setting colormap to: ", name)
import mechanica as m
import numpy as np
# potential cutoff distance
cutoff = 8
count = 3000
# dimensions of universe
dim=np.array([20., 20., 20.])
center = dim / 2
# new simulator, don't load any example
m.Simulator(example="", dim=dim, cutoff=cutoff, bc=m.BOUNDARY_NONE)
class Yolk(m.Particle):
mass = 500000
radius = 3
class Cell(m.Particle):
mass = 5
radius = 0.2
target_temperature=0
dynamics = m.Overdamped
pot_bs = m.Potential.soft_sphere(kappa=5, epsilon=20, r0=2.9, \
eta=3, tol = 0.1, min=0, max=9)
pot_ss = m.Potential.soft_sphere(kappa=10, epsilon=0.000000001, r0=0.2, \
eta=2, tol = 0.05, min=0, max=3)
# bind the potential with the *TYPES* of the particles
import mechanica as m
import numpy as np
m.Simulator(dim=[25., 25., 25.], dt=0.0005, cutoff=3, bc=m.BOUNDARY_NONE)
class Green(m.Particle):
mass = 1
radius = 0.1
dynamics = m.Overdamped
style = {'color': 'mediumseagreen'}
class Big(m.Particle):
mass = 10
radius = 8
frozen = True
style = {'color': 'orange'}
# simple harmonic potential to pull particles
pot = m.Potential.harmonic(k=1, r0=0.1, max=3)
# potentials between green and big objects.
pot_yc = m.Potential.glj(e=1, r0=1, m=3, min=0.01)
pot_cc = m.Potential.glj(e=0.0001, r0=0.1, m=3, min=0.005, max=2)
# random points on surface of a sphere
pts = m.random_points(m.Sphere,
10000) * (Green.radius + Big.radius) + m.Universe.center
import mechanica as m
import numpy as np
m.Simulator(dim=[20., 20., 20.], cutoff=8, bc=m.BOUNDARY_NONE)
class Bead(m.Particle):
mass = 1
radius = 0.1
dynamics = m.Overdamped
pot = m.Potential.harmonic(k=1, r0=0.1, max=3)
pts = m.random_points(m.SolidCube, 10000) * 18 + m.Universe.center
beads = [Bead(p) for p in pts]
m.bind_pairwise(pot, beads, 1)
m.run()
import mechanica as m
import numpy as np
# potential cutoff distance
cutoff = 8
count = 3
# dimensions of universe
dim = np.array([20., 20., 20.])
center = dim / 2
# new simulator, don't load any example
m.Simulator(example="", dim=dim, cutoff=cutoff)
class Bead(m.Particle):
mass = 1
radius = 0.5
dynamics = m.Overdamped
pot = m.Potential.glj(e=1)
# bind the potential with the *TYPES* of the particles
m.bind(pot, Bead, Bead)
# create a random force. In overdamped dynamcis, we neeed a random force to
# enable the objects to move around, otherwise they tend to get trapped
# in a potential
rforce = m.forces.random(0, 0.01)
cutoff = 10
# number of particles
count = 6000
# number of time points we avg things
avg_pts = 3
# dimensions of universe
dim = np.array([30., 30., 30.])
center = dim / 2
# new simulator, don't load any example
m.Simulator(example="",
dim=dim,
cutoff=cutoff,
integrator=m.FORWARD_EULER,
dt=0.002)
clump_radius = 2
# number of bins we use for averaging
avg_bins = 3
prev_pos = np.zeros((count, 3))
avg_vel = np.zeros((count, 3))
avg_pos = np.zeros((count, 3))
avg_index = 0
# the output display array.
# matplotlib uses (Y:X) axis arrays instead of normal (X:Y)
import mechanica as m
import numpy as np
cutoff = 8
count = 3
# dimensions of universe
dim = np.array([20., 20., 20.])
center = dim / 2
m.Simulator(dim=dim, cutoff=cutoff)
class B(m.Particle):
mass = 1
dynamics = m.Overdamped
# make a glj potential, this automatically reads the
# particle radius to determine rest distance.
pot = m.Potential.glj(e=1)
m.bind(pot, B, B)
p1 = B(center + (-2, 0, 0))
p2 = B(center + (2, 0, 0))
p1.radius = 1
p2.radius = 2
m.Simulator.run()
import mechanica as m
import numpy as np
# potential cutoff distance
cutoff = 1
# new simulator, don't load any example
m.Simulator(example="", dim=[20., 20., 20.])
pot = m.Potential.soft_sphere(kappa=10, epsilon=0.1,
r0=0.6, eta=3, tol = 0.1, min=0.05, max=4)
class Cell(m.Particle):
mass = 20
target_temperature = 0
radius=0.5
m.on_time(Cell.fission, period=1, distribution='exponential')
m.Universe.bind(pot, Cell, Cell)
Cell([10., 10., 10.])
# run the simulator interactive
m.Simulator.run()
import mechanica as m
import numpy as np
# potential cutoff distance
cutoff = 8
receptor_count = 500
# dimensions of universe
dim = np.array([20., 20., 20.])
center = dim / 2
# new simulator, don't load any example
m.Simulator(example="",
dim=dim,
cutoff=cutoff,
cells=[4, 4, 4],
integrator=m.RUNGE_KUTTA_4)
class Big(m.Particle):
mass = 500000
radius = 3
class Receptor(m.Particle):
mass = 0.1
radius = 0.1
target_temperature = 1
dynamics = m.Overdamped
import mechanica as m
import numpy as np
# potential cutoff distance
cutoff = 8
receptor_count = 10000
# dimensions of universe
dim=np.array([20., 20., 20.])
center = dim / 2
# new simulator, don't load any example
m.Simulator(example="", dim=dim, cutoff=cutoff, cells=[4, 4, 4], threads=8)
class Nucleus(m.Particle):
mass = 500000
radius = 1
class Receptor(m.Particle):
mass = 0.2
radius = 0.05
target_temperature=1
#dynamics = m.Overdamped
# locations of initial receptor positions
receptor_pts = m.random_points(m.SolidSphere, receptor_count) * 5 + center
pot_nr = m.Potential.well(k=15, n=3, r0=7)
pot_rr = m.Potential.soft_sphere(kappa=15, epsilon=0, r0=0.3, eta=2, tol=0.05, min=0.01, max=1)
import mechanica as m
import numpy as np
cutoff = 1
m.Simulator(example="", dim=[10., 10., 10.])
class Argon(m.Particle):
mass = 39.4
target_temperature = 100
# hook up the destroy method on the Argon type to the
# on_time event
m.on_time(Argon.destroy, period=2, distribution='exponential')
pot = m.Potential.lennard_jones_12_6(0.275, cutoff, 9.5075e-06, 6.1545e-03,
1.0e-3)
m.Universe.bind(pot, Argon, Argon)
tstat = m.forces.berenderson_tstat(10)
m.Universe.bind(tstat, Argon)
size = 100
# uniform random cube
positions = np.random.uniform(low=0, high=10, size=(size, 3))
velocities = np.random.normal(0, 0.2, size=(size, 3))
import mechanica as m
m.Simulator(dim=[6.5, 6.5, 6.5], bc=m.FREESLIP_FULL)
class A(m.Particle):
radius = 0.1
species = ['S1', 'S2', 'S3']
style = {"colormap": {"species": "S1", "map": "rainbow", "range": "auto"}}
m.flux(A, A, "S1", 5)
uc = m.lattice.sc(0.25, A)
parts = m.lattice.create_lattice(uc, [25, 25, 25])
parts[24, 24, 24][0].species.S1 = 5000
m.show()
