np.argmax()返回数组中最大值的索引。 6. 查找满足条件的第一个值的索引 有时我们只需要找到满足条件的第一个值的索引。 importnumpyasnp arr=np.array([1,2,3,4,5,3,7,8,9])first_index=np.where(arr==3)[0][0]print("numpyarray.com: First index of value 3:",first_index) Python Copy ...
np.max np.nanmax Find maximum value np.argmin np.nanargmin Find index of minimum value np.argmax np.nanargmax Find index of maximum value np.median np.nanmedian Compute median of elements np.percentile np.nanpercentile Compute rank-based statistics of elements np.any N/A Evaluate whether ...
np.prod np.nanprod Compute product of elements np.mean np.nanmean Compute mean of elements np.std np.nanstd Compute standard deviation np.var np.nanvar Compute variance np.min np.nanmin Find minimum value np.max np.nanmax Find maximum value np.argmin np.nanargmin Find index of minimum v...
importnumpyasnp# 创建一个二维随机数组matrix=np.random.rand(3,4)print("Matrix:\n",matrix)# 使用argmax找出最大值的索引,默认展平处理index_of_max_flat=np.argmax(matrix)print("Index of max value in flattened array:",index_of_max_flat)# 指定轴0,找出每列的最大值的索引index_of_max_axis0...
np.maxnp.nanmax Find maximum value np.argmin np.nanargmin Find index of minimum value np.argmax np.nanargmax Find index of maximum value np.median np.nanmedian Compute median of elements np.percentile np.nanpercentile Compute rank-based statistics of elements ...
[-0.28790332, -0.96139749, -0.75098725, 0.14987721]]) >>> # index of the maxima for each series >>> ind = data.argmax(axis=0) >>> ind array([2, 0, 3, 1]) >>> # times corresponding to the maxima >>> time_max = time[ind] >>> >>> data_max = data[ind, range(data....
"Maximum value:", a.max() print "Index of max.:", get_max_index(a) if __name__ =="__main__": test_run() 13. 记录python操作花费的时间 """using time function """ import time def test_run(): t1 = time.time() print("ML4T") ...
np.argmax np.nanargmax Find index of maximum value np.median np.nanmedian Compute median of elements np.percentile np.nanpercentile Compute rank-based statistics of elements np.any N/A Evaluate whether any elements are true np.all N/A Evaluate whether all elements are true ...
max(iterable, *[, default=obj, key=func]) -> valuemax(arg1, arg2, *args, *[, key=func]) -> valueWith a single iterable argument, return its biggest item. Thedefault keyword-only argument specifies an object to return ifthe provided iterable is empty.With two or more arguments, ...
ind = data.argmax(axis=0) # index of the maxima for each series # array([2, 0, 3, 1]) time_max = time[ind] # times corresponding to the maxima # array([ 82.5 , 20. , 113.75, 51.25]) data_max = data[ind, range(data.shape[1])] # => data[ind[0],0], data[ind[1]...