แอตทริบิวต์และการตรวจสอบอาร์เรย์

import numpy as np

a = np.array([[1, 2, 3], [4, 5, 6]])
print('ndim:', a.ndim)    # 2
print('shape:', a.shape)  # (2, 3)
print('size:', a.size)    # 6
print('dtype:', a.dtype)  # int64

import numpy as np

v = np.array([1, 2, 3])
print(v.ndim)   # 1

m = np.zeros((4, 5))
print(m.ndim)   # 2

t = np.ones((2, 3, 4))
print(t.ndim)   # 3

import numpy as np

a = np.arange(24).reshape(2, 3, 4)
print(a.shape)       # (2, 3, 4)

n_rows, n_cols = np.zeros((5, 7)).shape
print(n_rows, n_cols)  # 5 7

import numpy as np

a = np.ones((3, 4, 5))
print(a.size)          # 60  (3*4*5)
print(np.prod(a.shape))# 60

# Memory estimate in bytes
print(a.size * a.itemsize, 'bytes')  # 480 bytes

import numpy as np

a = np.array([1.5, 2.5, 3.5])
print(a.dtype)      # float64
print(a.itemsize)   # 8 bytes

b = a.astype(np.float32)
print(b.dtype)      # float32
print(b.itemsize)   # 4 bytes

import numpy as np

a = np.ones((1000, 1000), dtype=np.float64)
print(a.nbytes)  # 8000000 (8 MB)

b = a.astype(np.float32)
print(b.nbytes)  # 4000000 (4 MB)

import numpy as np

a = np.arange(12)
print(a.shape)          # (12,)

b = a.reshape(3, 4)
print(b.shape)          # (3, 4)

c = a.reshape(2, -1)    # -1 inferred as 6
print(c.shape)          # (2, 6)

import numpy as np

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

r = m.ravel()     # view (usually)
f = m.flatten()   # always a copy

print(r)  # [1 2 3 4 5 6]
print(f)  # [1 2 3 4 5 6]

import numpy as np

m = np.array([[1, 2, 3], [4, 5, 6]])  # shape (2, 3)
print(m.T.shape)   # (3, 2)
print(m.T)
# [[1 4]
#  [2 5]
#  [3 6]]

import numpy as np

a = np.ones((3, 4), dtype=np.float64)
print(a.strides)    # (32, 8)  — 4 cols x 8 bytes, 1 col x 8 bytes

b = a.T
print(b.strides)    # (8, 32)  — strides swapped, no data copy

import numpy as np

a = np.arange(6)
b = a.reshape(2, 3)  # view
print(np.shares_memory(a, b))  # True

c = a.copy()
print(np.shares_memory(a, c))  # False