例如给定两个矩阵
[1 2] and [5 6]
[3 4] [7 8],
有没有办法将它们连接起来得到下面的矩阵？
[1 2 1 2]
[3 4 3 4]
[5 5 6 6]
[7 7 8 8]
请您参考如下方法:
基于 NumPy 的方法
使用数组初始化 broadcasted-assignment -
def assign_as_blocks(a,b):
m1,n1 = a.shape
m2,n2 = b.shape
out = np.empty((m1+m2,n2,n1),dtype=int)
out[:m1] = a[:,None,:]
out[m1:] = b[:,:,None]
return out.reshape(m1+m2,-1)
要使用 tensorflow 工具，修改后的版本为:
def assign_as_blocks_v2(a,b):
shape1 = tf.shape(a)
shape2 = tf.shape(b)
m1 = shape1[0]
n1 = shape1[1]
m2 = shape2[0]
n2 = shape2[1]
p1 = tf.tile(a,[1,n2])
p2 = tf.reshape(tf.tile(tf.expand_dims(b, 1),[1,1,n1]), [m2,-1])
out = tf.concat((p1,p2),axis=0)
return out
样本运行
案例#1(问题样本):
In [95]: a
Out[95]:
array([[1, 2],
[3, 4]])
In [96]: b
Out[96]:
array([[5, 6],
[7, 8]])
In [97]: assign_as_blocks(a, b)
Out[97]:
array([[1, 2, 1, 2],
[3, 4, 3, 4],
[5, 5, 6, 6],
[7, 7, 8, 8]])
案例 #2(通用形状随机数组):
In [106]: np.random.seed(0)
...: a = np.random.randint(0,9,(2,3))
...: b = np.random.randint(0,9,(4,5))
In [107]: a
Out[107]:
array([[5, 0, 3],
[3, 7, 3]])
In [108]: b
Out[108]:
array([[5, 2, 4, 7, 6],
[8, 8, 1, 6, 7],
[7, 8, 1, 5, 8],
[4, 3, 0, 3, 5]])
In [109]: assign_as_blocks(a, b)
Out[109]:
array([[5, 0, 3, 5, 0, 3, 5, 0, 3, 5, 0, 3, 5, 0, 3],
[3, 7, 3, 3, 7, 3, 3, 7, 3, 3, 7, 3, 3, 7, 3],
[5, 5, 5, 2, 2, 2, 4, 4, 4, 7, 7, 7, 6, 6, 6],
[8, 8, 8, 8, 8, 8, 1, 1, 1, 6, 6, 6, 7, 7, 7],
[7, 7, 7, 8, 8, 8, 1, 1, 1, 5, 5, 5, 8, 8, 8],
[4, 4, 4, 3, 3, 3, 0, 0, 0, 3, 3, 3, 5, 5, 5]])
