def main():
from differential import Differential
from render import Render
from time import time
from helpers import print_stats
# from helpers import print_debug
DL = Differential(NMAX, 8, NZ, ZMAX, RAD, NEARL, FARL)
render = Render(SIZE, BACK, FRONT)
render.ctx.set_source_rgba(*FRONT)
render.ctx.set_line_width(LINEWIDTH)
angles = sorted(random(100))
DL.init_circle(MID, MID, RAD * 50.0, angles)
for i in count():
t_start = time()
steps(DL, STEPS_ITT)
t_stop = time()
print_stats(i * STEPS_ITT, t_stop - t_start, DL)
fn = "./img/print10k_5px_{:010d}.png".format(i * STEPS_ITT)
show(render, DL, fn)
def main():
import gtk
from differential import Differential
from render import Animate
from time import time
from helpers import print_stats
DL = Differential(NMAX, 8, NZ, ZMAX, RAD, NEARL, FARL)
# angles = sorted(random(10)*TWOPI)
angles = sorted(random(INIT_NUM) * TWOPI)
# angles = sorted(random(1000)*TWOPI)
DL.init_circle(MID, MID, INIT_RAD, angles)
def wrap(steps_itt, render):
t1 = time()
steps(DL, steps_itt)
edges_coordinates = DL.get_edges_coordinates()
show(render, edges_coordinates)
t2 = time()
print_stats(render.steps, t2 - t1, DL)
return True
render = Animate(SIZE, BACK, FRONT, STEPS_ITT, wrap)
render.ctx.set_source_rgba(*FRONT)
render.ctx.set_line_width(LINEWIDTH)
gtk.main()
class Entry:
def __init__(self, revision, diff, repo_uri, stage_uri):
self.revision = revision
self.diff = diff
self.repo_uri = repo_uri
self.stage_uri = stage_uri
self.differential = Differential(self.diff, self.revision)
def __record_data(self):
logs.info("Record data to database")
def __feedback(self):
msg = "NOTE: Trigger build success, please wait build result."
self.differential.feedback(msg)
def exec_entry(self):
self.__record_data()
self.__feedback()
N = 100 # number of people
num_recovered = 0 # initial number of recovered people
num_infectious = 1 # initial number of infected people
num_susceptible = N - num_infectious - num_recovered
# define unknowns
S = Unknown('S', num_susceptible, 'susceptible')
I = Unknown('I', num_infectious, 'infectious')
R = Unknown('R', num_recovered, 'recovered')
# parameters
beta = .001 # disease ratio
gamma = .0001 # recovery ratio
mu = .0 # population birth rate
nu = .0 # population death rate
xi = 0.0 # ratio of recovered people who become susceptible again
# SIRS equations with vital dynamics
S.dt = -beta * S * I / N + mu * N - nu * S + xi * R
I.dt = beta * S * I / N - gamma * I - nu * I
R.dt = gamma * I - nu * R - xi * R
# time points
t = np.linspace(0, 3500, 300)
# solve ODE
diff = Differential(S, I, R)
diff.solve(t)
diff.plot(t)
from differential import Differential, Unknown
import numpy as np
# initial condition
alpha = 2 / 3
beta = 4 / 3
gamma = 1
delta = 1
# create unknowns
x = Unknown('x', 2, label='proie') # proie
y = Unknown('y', 1.5, label='prédateur') # prédateur
# write down equation
x.dt = alpha * x - beta * x * y
y.dt = delta * x * y - gamma * y
# time points
t = np.linspace(0, 20, 1000)
# solve ODE
diff = Differential(x, y)
diff.solve(t)
diff.plot(t)
def __init__(self, revision, diff, repo_uri, stage_uri):
self.revision = revision
self.diff = diff
self.repo_uri = repo_uri
self.stage_uri = stage_uri
self.differential = Differential(self.diff, self.revision)
