Python BlindFunc.__call__ Beispiele

Beispiel #1

Datei: test_functor.py Projekt: vishalbelsare/probfit

def test_blindfunc():
    np.random.seed(0)
    f = BlindFunc(gaussian, "mean", "abcd", width=1.5, signflip=True)
    arg = f.__shift_arg__((1, 1, 1))
    totest = [1.0, -2.1741271445170067, 1.0]
    assert_almost_equal(arg[0], totest[0])
    assert_almost_equal(arg[1], totest[1])
    assert_almost_equal(arg[2], totest[2])
    assert_almost_equal(f.__call__(0.5, 1.0, 1.0), 0.011171196819867517)
    np.random.seed(575345)
    f = BlindFunc(gaussian, "mean", "abcd", width=1.5, signflip=True)
    arg = f.__shift_arg__((1, 1, 1))
    assert_almost_equal(arg[0], totest[0])
    assert_almost_equal(arg[1], totest[1])
    assert_almost_equal(arg[2], totest[2])
    assert_almost_equal(f.__call__(0.5, 1.0, 1.0), 0.011171196819867517)

Beispiel #2

Datei: testfunctor.py Projekt: piti118/probfit

def test_blindfunc():
    np.random.seed(0)
    f = BlindFunc(gaussian, "mean", "abcd", width=1.5, signflip=True)
    arg = f.__shift_arg__((1, 1, 1))
    totest = [1.0, -1.1665264284482637, 1.0]
    assert_almost_equal(arg[0], totest[0])
    assert_almost_equal(arg[1], totest[1])
    assert_almost_equal(arg[2], totest[2])
    assert_almost_equal(f.__call__(0.5, 1.0, 1.0), 0.0995003913596)
    np.random.seed(575345)
    f = BlindFunc(gaussian, "mean", "abcd", width=1.5, signflip=True)
    arg = f.__shift_arg__((1, 1, 1))
    assert_almost_equal(arg[0], totest[0])
    assert_almost_equal(arg[1], totest[1])
    assert_almost_equal(arg[2], totest[2])
    assert_almost_equal(f.__call__(0.5, 1.0, 1.0), 0.0995003913596)

Beispiel #3

Datei: test_functor.py Projekt: iminuit/probfit

def test_blindfunc():
    np.random.seed(0)
    f = BlindFunc(gaussian, 'mean', 'abcd', width=1.5, signflip=True)
    arg = f.__shift_arg__((1, 1, 1))
    totest = [1., -2.1741271445170067, 1.]
    assert_almost_equal(arg[0], totest[0])
    assert_almost_equal(arg[1], totest[1])
    assert_almost_equal(arg[2], totest[2])
    assert_almost_equal(f.__call__(0.5, 1., 1.), 0.011171196819867517)
    np.random.seed(575345)
    f = BlindFunc(gaussian, 'mean', 'abcd', width=1.5, signflip=True)
    arg = f.__shift_arg__((1, 1, 1))
    assert_almost_equal(arg[0], totest[0])
    assert_almost_equal(arg[1], totest[1])
    assert_almost_equal(arg[2], totest[2])
    assert_almost_equal(f.__call__(0.5, 1., 1.), 0.011171196819867517)

Beispiel #4

Datei: testfunctor.py Projekt: mtresch/probfit

def test_blindfunc():
    np.random.seed(0)
    f = BlindFunc(gaussian, 'mean', 'abcd', width=1.5, signflip=True)
    arg = f.__shift_arg__((1, 1, 1))
    totest = [1., -1.1665264284482637, 1.]
    assert_almost_equal(arg[0], totest[0])
    assert_almost_equal(arg[1], totest[1])
    assert_almost_equal(arg[2], totest[2])
    assert_almost_equal(f.__call__(0.5, 1., 1.), 0.0995003913596)
    np.random.seed(575345)
    f = BlindFunc(gaussian, 'mean', 'abcd', width=1.5, signflip=True)
    arg = f.__shift_arg__((1, 1, 1))
    assert_almost_equal(arg[0], totest[0])
    assert_almost_equal(arg[1], totest[1])
    assert_almost_equal(arg[2], totest[2])
    assert_almost_equal(f.__call__(0.5, 1., 1.), 0.0995003913596)