INPUTS = []
FORMULA = {"w": "noise"}
x0 = {'w':0}
M = 2
params = {'d':np.ones(M)}
T = 0.001
fs = 1000
stochastic = True
gpu = False
if gpu:
time, outs = run_ode( FORMULA, FUNCTION, INPUTS, x0, params, T , fs, inputs = None, stochastic = stochastic, Tterm = 0, gpu = gpu , dtype = np.float32)
w = outs['w']
else:
outs = run_ode( FORMULA, FUNCTION, INPUTS, x0, params, T , fs, inputs = None, stochastic = stochastic, nthreads= 1, Tterm = 0, gpu = gpu , dtype = np.float32,debug=True,seed=1234)
w = np.zeros((int(T*fs),len(outs)))
for i,o in enumerate(outs):
w[:,i] = o['out'][1]['w'].T
pl.figure()
pl.plot(w)
pl.figure()
# -*- coding: utf-8 -*-
from __future__ import division
from gpuODE import run_ode
import numpy as np
import pylab as pl
FUNCTION = { "func" : ( ["x"], "sin(x)" )}
INPUTS = []
FORMULA = {"ph": "w",
"w": "-g*func(ph)-e*w "}
x0 = {'ph':np.pi-0.01,'w':-40.}
params = {"e":[1.0],"g":[1000]}
T = 10.0
fs = 10000
outs = run_ode( FORMULA, FUNCTION, INPUTS, x0, params, T , fs, inputs = None, stochastic = False, Tterm = 0, gpu = False, nthreads = 1 , dtype = np.float32)
ph = outs[0]['out'][1]['ph']
w = outs[0]['out'][1]['w']
t = np.arange(T*fs)/fs
pl.plot(t,ph)
pl.xlabel("Time (s)")
pl.ylabel("Phase")
