1.排序： .sort
# 方法一：import numpy as npa = np.array([[4,3,5,],[1,2,1]])PRint (a)b = np.sort(a, axis=1) # 对a按每行中元素从小到大排序print (b)# 输出 [[4 3 5] [1 2 1]][[3 4 5] [1 1 2]]# 方法二：import numpy as npa = np.array([[4,3,5,],[1,2,1]])print (a)a.sort(axis=1)print (a)# 输出 [[4 3 5] [1 2 1]][[3 4 5] [1 1 2]]# 方法三：import numpy as npa = np.array([4, 3, 1, 2])b = np.argsort(a) # 求a从小到大排序的坐标print (b)print (a[b]) # 按求出来的坐标顺序排序# 输出 [2 3 1 0][1 2 3 4]2.按行或按列找到最大值的索引： .argmax
import numpy as npdata = np.sin(np.arange(20)).reshape(5, 4)print (data)ind = data.argmax(axis=0) # 按列得到每一列中最大元素的索引，axis=1为按行print (ind)data_max = data[ind, range(data.shape[1])] # 将最大值取出来print (data_max)# 输出 [[ 0. 0.84147098 0.90929743 0.14112001] [-0.7568025 -0.95892427 -0.2794155 0.6569866 ] [ 0.98935825 0.41211849 -0.54402111 -0.99999021] [-0.53657292 0.42016704 0.99060736 0.65028784] [-0.28790332 -0.96139749 -0.75098725 0.14987721]][2 0 3 1][ 0.98935825 0.84147098 0.99060736 0.6569866 ]print data.max(axis=0) #也可以直接取最大值# 输出 [ 0.98935825 0.84147098 0.99060736 0.6569866 ]3.多重复制： .tile
import numpy as npa = np.array([5, 10, 15])print(a)print('---')b = np.tile(a, (4, 1)) # 参数(4, 1)为按行复制4倍，按列复制1倍print(b)# 输出 [ 5 10 15]---[[ 5 10 15] [ 5 10 15] [ 5 10 15] [ 5 10 15]]c = np.tile(a, (2, 3)) # 参数(2, 3)为按行复制2倍，按列复制3倍print(c)# 输出 [[ 5 10 15 5 10 15 5 10 15] [ 5 10 15 5 10 15 5 10 15]]新闻热点
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