Python is_scalar Exemples

Exemple #1

def range_in(x, y, p):
    if is_scalar(x) or not is_scalar(y):
        return x
    else:
        splitY = int((x.shape[0] - 1) * (y + 1) / 2.0)
        splitP = int((x.shape[0] - 1) * (p + 1) / 2.0)
        start = min(splitY, splitP)
        end = max(splitY, splitP)
        return np.copy(x[start:end + 1])

Exemple #2

def differences(x, y, p):
    if is_scalar(x):
        return x
    else:
        z = x.flatten()
        if z.size > 2:
            return np.copy(np.diff(x.flatten()))
        else:
            return z

Exemple #3

Fichier : functions_test.py Projet : aHeraud/cgp-tetris

 def test_pass_through(self):
     inp = 1
     exp = True
     act = supp.is_scalar(inp)
     self.assertEqual(exp, act)
     inp = np.array([1])
     exp = False
     act = supp.is_scalar(inp)
     self.assertEqual(exp, act)
     inp = np.array([[1], [2]])
     exp = False
     act = supp.is_scalar(inp)
     self.assertEqual(exp, act)
     inp = np.array([[1], [2]])
     exp = False
     act = supp.is_scalar(inp)
     self.assertEqual(exp, act)
     inp = np.array([1, 2, 3])
     exp = False
     act = supp.is_scalar(inp)
     self.assertEqual(exp, act)

Exemple #4

def f_last(x, y, p):
    if is_scalar(x):
        return x
    else:
        z = x.flatten()
        return z[len(z) - 1]

Exemple #5

def f_first(x, y, p):
    if is_scalar(x):
        return x
    else:
        return x.flatten()[0]

Exemple #6

def vectorize(x, y, p):
    if is_scalar(x):
        return x
    else:
        return np.copy(x.flatten())

Exemple #7

def index_p(x, y, p):
    if is_scalar(x):
        return x
    else:
        splitP = int((x.shape[0] - 1) * (p + 1) / 2.0)
        return np.copy(x[splitP])

Exemple #8

def index_y(x, y, p):
    if is_scalar(x) or not is_scalar(y):
        return x
    else:
        splitY = int((x.shape[0] - 1) * (y + 1) / 2.0)
        return np.copy(x[splitY])

Exemple #9

def ones(x, y, p):
    if is_scalar(x):
        return np.array([1])
    else:
        return np.ones(x.shape)

Exemple #10

def zeros(x, y, p):
    if is_scalar(x):
        return np.array([0])
    else:
        return np.zeros(x.shape)

Exemple #11

def constvectord(x, y, p):
    if is_scalar(x):
        return np.array([p])
    else:
        return np.full(x.shape, p)

Exemple #12

def split_after(x, y, p):
    if is_scalar(x):
        return x
    else:
        splitIndex = int((x.shape[0] - 1) * (p + 1) / 2.0)
        return np.copy(x[splitIndex:])

Exemple #13

def vec_from_double(x, y, p):
    if is_scalar(x):
        return np.array([x])
    else:
        return x

Exemple #14

def transpose(x, y, p):
    if is_scalar(x):
        return x
    else:
        return np.transpose(x)

Exemple #15

def rotate(x, y, p):
    if is_scalar(x):
        return x
    else:
        return np.roll(x, int(np.ceil(p)))

Exemple #16

def split_before(x, y, p):
    if is_scalar(x):
        return x
    else:
        splitIndex = int((x.shape[0] - 1) * (p + 1) / 2.0)
        return np.copy(x[:splitIndex + 1])