如果你总是在每一行都有一个1，在反向数组上使用numpy.argmax：
如果你总是在每一行都有一个1，在反向数组上使用numpy.argmax：
#ndarray.compress(condition, axis=None, out=None) #返回按照axis维度的切片,条件是1-D布尔数组 m = np.array ( [ [ 1, 0, 3 ], [ 4, 2, 0 ], [ 2, 2, 0 ] ] ) print ( m.compress ( [False , True, False, True ] ) ) #按照条件返回元素axis=None,等于先flat再操作 print ( m...
To find the index at which the maximum occurs, you can use theNumPy where()function.np.where(condition)returns an array of all indices where theconditionisTrue. You’ll have to tap into the array and access the item at the first index. To find where the maximum value occurs, we set t...
where()方法 where函数的两种用法: 1.np.where(condition, x, y) 满足条件(condition),输出x,不满足输出y。 2.np.where(condition) 只有条件 (condition),没有x和y,则输出满足条件 (即非0) 元素的坐标(索引)。 比如: arr=np.array([0,1,2,3,4,5,6,7,8,9]) ...
If there are no elements, the if condition will become true and it will print the empty message. If our array is equal to: a = numpy.array([]) The output of the above code will be as below: Find the index of a value To find the index of value, we can use the where() method...
Position = np.where(B[0]<0) #numpy.where和find用法相同 print('B[0]<0的位置:',Position[0],'(横坐标);',Position[1],'(纵坐标)') print('B[0][condition])=',B[0][B[0]<0]) # 找第一维数组中满足条件的元素 print('Dot(B[0][0],B[0][0])=',np.dot(B[0][0],B[0][0...
where(condition, [x, y]) 根据条件,返回x或y中的元素。 indices(dimensions[, dtype]) 返回表示网格索引的数组。 ix_(*args) 从多个序列构建开放网格。 ogrid 返回开放多维“网格”的nd _ grid实例。 ravel_multi_index(multi_index, dims[, mode, …]) 将索引数组元组转换为平面索引数组,将边界模式应用...
numpy.where() numpy.where(condition, [x=None, y=None])Return elements chosen fromxorydepending oncondition. 【例】满足条件condition,输出x,不满足输出y。 import numpy as np x = np.arange(10) print(x) # [0 1 2 3 4 5 6 7 8 9] ...
The numpy.where function is a vectorized version of the ternary expression x if condition else y. Suppose we had a boolean array and two arrays of values: In [165]: xarr = np.array([1.1, 1.2, 1.3, 1.4, 1.5]) In [166]: yarr = np.array([2.1, 2.2, 2.3, 2.4, 2.5]) In [167...