maedoc

maedoc

import time
import tqdm
import numpy as np
import tensorflow as tf
import numba as nb
#tf.config.experimental.set_visible_devices([], 'GPU')
tf.zeros((1,), tf.float32)

maedoc

import sys
import time
from autograd import numpy as np, grad
from autograd.misc.optimizers import adam, rmsprop, sgd
from scipy.optimize import minimize
import pylab as pl


# simplification of the generic 2d oscillator
def dfun(state, w, theta):

maedoc

import time
from autograd import numpy as np, grad
from autograd.scipy.integrate import odeint
from autograd.builtins import tuple
from autograd.scipy.stats import norm
from autograd.misc.optimizers import adam


def vdpo(y, t0, a, k, tau=3.0):
    x, y = np.reshape(y, (2, -1))

maedoc

import numpy as np
import tvb.simulator.lab as tvb
from tvb.basic.neotraits.api import Final, List

# setup model based on paper's parameters
model_pars = dict(
    A=3.25,
    B=22.0,
    v0=6.0,
    a=0.1, # TVB uses ms, not s

maedoc

import pystan

try:
    model  # avoid recompiling during IPython/notebook session
except:
    model = pystan.StanModel('sdde.stan')

data = dict(
    nt=500,
    d=50,

maedoc

from autograd import grad, numpy as np
from autograd.scipy.stats import norm
from autograd.misc.optimizers import adam

def simple_vi(n=2000):
    x = np.random.normal(loc=+1.5, scale=+0.3, size=10)
    log_p = lambda z: np.mean(norm.logpdf(x[:, None], z[0], np.exp(z[1])), axis=0)
    log_q = lambda z, l: norm.logpdf(z, l[:, None], 0.3)
    samp_q = lambda l: np.random.normal(l[:, None], 0.3, (2, n))
    # https://arxiv.org/pdf/1401.0118.pdf, eq 3

maedoc

from pycallgraph import PyCallGraph
from pycallgraph.output import GraphvizOutput

from pycallgraph import GlobbingFilter
from pycallgraph import Config

from tvb.simulator.models.wong_wang import ReducedWongWang
from tvb.simulator.lab import *
import numpy

maedoc

> be me
> dukenukem.jpg
> tired of playing ITCrowd.exe
> drool while looking at HMC.jpeg

> install numpyro
> assume homogeneous coupling

maedoc

import IPython.core.magic, subprocess
@IPython.core.magic.register_cell_magic
def ssh(line, cell):
    proc = subprocess.Popen(['ssh'] + line.split(),
                            stdin=subprocess.PIPE, stdout=subprocess.PIPE, stderr=subprocess.STDOUT)
    out, _ = proc.communicate(cell.encode('ascii'))
    print(out.decode('ascii'))