Exemplo n.º 1
0
def run_ode( FORMULA, FUNCTIONS, INPUTS,  inits, params, T , fs, inputs = None, decimate=1 ,variable_length = False, stochastic = False, Tterm = 0, gpu = False, nthreads = 4 , dtype = np.float32, debug = False,seed =None,threads_per_block=32 ):
    from gpuODE import ode, param_grid, funcs2code

           
    PARAMETERS = params.keys()
       
    odeRK4 = ode("ode")
    odeRK4.setup(FORMULA, PARAMETERS, INPUTS)
    
    Tt = T + Tterm
    dt = 1.0/np.array(fs)
    N = np.int32(Tt*fs)
    
    Nterm = np.int32(Tterm*fs)
    
    extra_funcs = funcs2code(FUNCTIONS, gpu = gpu)
    odeRK4.extra_func = extra_funcs
    odeRK4.generate_code(debug=debug, gpu = gpu,variable_length = variable_length, stochastic=stochastic, dtype = dtype)
    odeRK4.compile()

    if gpu==True:

        time, out = odeRK4.run(inits, param_grid(**params) , dt, decimate = decimate, inputs=inputs, N = N, Nterm = Nterm,seed = seed,threads_per_block=threads_per_block)
        return time, out
        
    else:

        import distributed_exploration as de
        import timeit
        from random import randint
        seed_off = 0

        #Modifications are needed to change the seed on differnet threads
        def func(**args):
            seedr = seed + randint(0,10000)
            time,out = odeRK4.run(inits, args, dt ,decimate=decimate, inputs=inputs, N = N , Nterm = Nterm,seed = seedr)
            return time, out
        
        tic = timeit.default_timer()
        out0 = de.explore_thread(func, param_grid(**params) ,nthreads=nthreads)
        toc = timeit.default_timer()

        Nm = int(T*fs)/decimate
        M = len(out0)

        out = {}

        for j,k in enumerate(FORMULA.keys()):   

            out[k] = np.zeros((Nm,M))
            
        for i,o in enumerate(out0):
            for j,k in enumerate(FORMULA.keys()):
                out[k][:,i] = o['out'][1][k].T[0,:N]
    
            
        return toc-tic, out
Exemplo n.º 2
0
M = 32

mu = np.linspace(-1,10,M)

params = {'mu': mu}

Tterm = 0
T = 100 + Tterm
fs = 100
dt = 1/fs
N = int(T*fs)
Nterm = int(Tterm*fs)
t = np.arange(N-Nterm)/fs

pgrid = param_grid(**params)

time, out = vdp.run(x0, pgrid ,dt, N = N, Nterm = Nterm)

x = out['x']
print x.dtype

pl.figure(56)
pl.clf()
pl.plot( x[:,-1] ,'o-',label="float32")

vdp.generate_code(debug=False, stochastic = False, gpu = True, dtype = np.float64)
vdp.compile()
time, out = vdp.run(x0, pgrid ,dt, N = N, Nterm = Nterm)

x = out['x']
Exemplo n.º 3
0
T = T + Tterm
dt = 1.0/float(fs)
N = np.int32(T*fs)

Nterm = np.int32(Tterm*fs).min()
dtype = np.float32
variable_length = False

extra_funcs = funcs2code(FUNCTION, gpu = gpu)
odeRK4.extra_func = extra_funcs
odeRK4.generate_code(debug=debug, gpu = gpu,variable_length = variable_length, stochastic=stochastic, dtype = dtype )
odeRK4.compile()

if gpu==True:

    time, out = odeRK4.run(x0, param_grid(**params) , dt, decimate = decimate, inputs=inputs, N = N, Nterm = Nterm)

    w = out['w']
    
else:



    time,out = odeRK4.run(x0, param_grid(**params) , dt,decimate=decimate, inputs=inputs, N = N , Nterm = Nterm,seed = 1234) 
    
    w = out['w']
        
        
#    
#
#pl.figure()