marekyggdrasil

code:

	console.log('socket.io', token);
	console.log(realtime);
	let session = yield _.find(realtime, function(data) {
		return data.token === token;
	});
	console.log('session object to be set');
	console.log(session);
	if (!session.socket) {

marekyggdrasil

trpo-gae-v0 and cem-v1 by @joschu

Any of available agents starts by checking if observation space is a Box, reference

CEM by @jietang

Same situation as trpo-gae-v0 and cem-v1, reference

DDPG by rmst It is clearly stated that only Box will be accepted reference

marekyggdrasil

from tools.ContentMathML import mml2sympy
from lxml import etree

xml = """
<apply>
  <int/>
  <bvar><ci>x</ci></bvar>
  <lowlimit><cn>a</cn></lowlimit>
  <uplimit><ci>b</ci></uplimit>
  <apply>

marekyggdrasil

import cPickle as pickle
import io

lst = range(16)
with io.open('list.p', 'wb') as f :
    pickler = pickle.Pickler(f)
    for l in lst :
        pickler.dump(l)

marekyggdrasil

from dlx import DLX

def genInstance(labels, rows) :
    columns = []
    indices_l = {}
    for i in range(len(labels)) :
        label = labels[i]
        indices_l[label] = i
        columns.append(tuple([label,0]))
    return labels, rows, columns, indices_l

marekyggdrasil

from dlx import DLX

def genInstance(labels, rows) :
    columns = []
    indices_l = {}
    for i in range(len(labels)) :
        label = labels[i]
        indices_l[label] = i
        columns.append(tuple([label,0]))
    return labels, rows, columns, indices_l

marekyggdrasil

import matplotlib
import matplotlib.pyplot as plt

import numpy as np

from qutip import *
from scipy import *

def operators(N) :
    si = qeye(2)

marekyggdrasil

import matplotlib.pyplot as plt
import numpy as np
from qutip import basis


def _ket(n, N):
    return basis(N, n)


def _bra(n, N):

marekyggdrasil

OSX Sierra version 10.12.6

if you are getting error like

ERROR:  Could not find a valid gem '<some package name>' (>= 0), here is why:
          Unable to download data from https://rubygems.org/ - SSL_connect retur

test your TLS v1.2 support

marekyggdrasil

from scipy.integrate import solve_ivp
import numpy as np

def exponential_decay(t, y, alpha, beta): return -alpha*y + beta

for alpha in np.linspace(0.5, 0.7, 5) :
    beta = 1.
    sol = solve_ivp(lambda t, y: exponential_decay(t, y, alpha, beta), [0, 10], [2, 4, 8])