Recent Changes

Monday, September 15

  1. page space.menu edited [[include component="navigation"]] Here's how some help to change the Navigation p…
    [[include component="navigation"]]
    Here's howsome help to change the
    Navigation page
    Python
    install Python on different platforms.
    (view changes)
    8:59 am

Friday, July 4

  1. page toto (deleted) edited
    4:21 am
  2. page toto (deleted) edited
    4:20 am

Thursday, January 30

  1. page codesTD1 edited import random, math x y_max = 0.0 delta 1.0 / math.sqrt(2.0 * math.pi) x_cut = 0.5 for…

    import random, math
    xy_max = 0.0
    delta
    1.0 / math.sqrt(2.0 * math.pi)
    x_cut
    = 0.5
    for k in range(100000):
    x_new
    5.0
    n_data
    = x + random.uniform(-delta, delta)
    if random.uniform(0.0, 1.0)
    100000
    data = []
    n_accept = 0
    while n_accept
    < \
    math.exp (- x_new ** 2 / 2.0) / math.exp (- x ** 2 / 2.0):
    n_data:
    y = random.uniform(0.0, y_max)

    x = x_new
    print
    random.uniform(-x_cut, x_cut)
    if y < math.exp( -
    x **2 / 2.0)/math.sqrt(2.0 * math.pi):
    n_accept += 1
    data.append(x)
    if n_accept == n_data: break

    (view changes)
    3:08 pm
  2. page codesTD1 edited import random N random, math x = 10 L 0.0 delta = 20.0 sigma = 0.75 n_runs = 10 ** 4…

    import random
    N
    random, math
    x
    = 10
    L
    0.0
    delta
    = 20.0
    sigma = 0.75
    n_runs = 10 ** 4
    data = []
    0.5
    for runsk in range(n_runs):
    y
    range(100000):
    x_new
    = [random.uniform(0.0, L -x + random.uniform(-delta, delta)
    if random.uniform(0.0, 1.0) < \
    math.exp (- x_new **
    2 * N * sigma) for k in range(N)]
    y.sort()
    / 2.0) / math.exp (- x ** 2 / 2.0):
    x = [y[i] + (2 * i + 1) * sigma for i in range(N)]
    data +=
    x_new
    print
    x
    (view changes)
    2:55 pm

Wednesday, January 29

  1. page codesTD1 edited ... L = 20.0 sigma = 0.75 n_runs = 10**4 10 ** 4 data = [] for runs in range(n_runs):
    ...
    L = 20.0
    sigma = 0.75
    n_runs = 10**410 ** 4
    data = []
    for runs in range(n_runs):
    (view changes)
    3:52 pm
  2. page codesTD1 edited import random, pylab random N = 10 L = 20.0

    import random, pylabrandom
    N = 10
    L = 20.0
    (view changes)
    3:50 pm
  3. page codesTD1 edited import random random, pylab N = 15 10 L = 10.0 20.0 sigma = 0.1 0.75 n_runs = 20…

    import randomrandom, pylab
    N = 1510
    L = 10.020.0
    sigma = 0.10.75
    n_runs = 2000
    rejected
    10**4
    data
    = 0[]
    for runruns in range(n_runs):
    x

    y
    = []
    while len(x) < N:
    x.append(random.uniform(sigma,
    [random.uniform(0.0, L - sigma))
    for
    2 * N * sigma) for k in range(len(x)-1):
    if abs(x[-1] - x[k]) < 2.0 * sigma:
    range(N)]
    y.sort()

    x = []
    rejected
    [y[i] + (2 * i + 1) * sigma for i in range(N)]
    data
    += 1
    break
    print
    x
    (view changes)
    3:50 pm

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