import numpy

numpy.linalg.norm

import numpy as np

np.lookfor("solve")

np.e

np.pi

np.log(2)

np.array([1, 2, 3])

a = np.array([1, 2, 3.0])
print(a.dtype)

np.array([1, 2, "3"])

np.array([1, 2, 3], dtype=float)

np.array([1, 2, 3], dtype=complex)

a

a.astype(int)

N, M = 100, 100
a = np.empty(10000).reshape(N, M)
b = np.random.rand(10000).reshape(N, M)
c = np.random.rand(10000).reshape(N, M)

%%timeit
for i in range(N):
    for j in range(M):
        a[i, j] = b[i, j] + c[i, j]

%%timeit
a = b + c

a = np.array([
    [1, 2, 3],
    [4, 5, 6]
])
a

a[0]

a[0, 0]

a[0, 1:3]

a[0, ::2]

np.identity(5).astype(int)

_.shape

np.zeros((3, 4))

np.zeros(3, 4)

np.ones((3, 4))

i3 = np.identity(3)
i3

i3.shape

np.ones(i3.shape)

np.ones_like(i3)

np.linspace(0, 1, num=10)

np.logspace(0, 3)

x = np.linspace(0, 1, num=5)
y = np.linspace(0, 1, num=5)

xx, yy = np.meshgrid(x, y)

xx, yy

xx + 1j * yy

a = np.arange(2 * 3).reshape(2, 3)
a

np.sqrt(a)

np.sqrt(np.arange(-3, 3))

np.arange(-3, 3).astype(complex)

np.sqrt(_)

a = np.arange(6)
b = np.ones(6).astype(int)
a, b

a < b

np.any(a < b)

np.all(a < b)

a = np.arange(6).astype(float)
b = np.ones(6)
a, b

np.isclose(a, b, rtol=1e-6)

np.allclose(a, b, rtol=1e-6)

0.1 + 0.2 + 0.3

0.3 + 0.2 + 0.1

0.1 + 0.2 + 0.3 == 0.3 + 0.2 + 0.1

a = np.zeros((3, 4))
a

a[0, :] = 1
a

b = np.zeros((3, 4))
b[-1] = np.arange(5, 9)
b

v = np.ones(10)
v

v[::2] = 2
v

tablero = np.zeros((8, 8))
tablero

tablero[1::2, ::2] = 1
tablero[::2, 1::2] = 1
tablero