再战CS231-数组的访问

1.切片访问和整形访问的区别

你可以同时使用整型和切片语法来访问数组。但是，这样做会产生一个比原数组低阶的新数组

import numpy as np

# Create the following rank 2 array with shape (3, 4)
# [[ 1  2  3  4]
#  [ 5  6  7  8]
#  [ 9 10 11 12]]
a = np.array([[1,2,3,4], [5,6,7,8], [9,10,11,12]])

# Two ways of accessing the data in the middle row of the array.
# Mixing integer indexing with slices yields an array of lower rank,
# while using only slices yields an array of the same rank as the
# original array:
row_r1 = a[1, :]    # Rank 1 view of the second row of a
row_r2 = a[1:2, :]  # Rank 2 view of the second row of a
print (row_r1, row_r1.shape)  # Prints "[5 6 7 8] (4,)"
print (row_r2, row_r2.shape )# Prints "[[5 6 7 8]] (1, 4)"

# We can make the same distinction when accessing columns of an array:
col_r1 = a[:, 1]
col_r2 = a[:, 1:2]
print (col_r1, col_r1.shape)  # Prints "[ 2  6 10] (3,)"
print (col_r2, col_r2.shape)  # Prints "[[ 2]
                            #          [ 6]
                            #          [10]] (3, 1)"