如何获得 numpy 第一个 True Only

Question

i have array of data as given below.

a=np.array([1,2,3,4,5,6,7,8,1,2,3,4,5,6])

i want to get conditional formatting like a>5

i can get it with np.where . But np.where is continuous checking for next true

np.where(a>5,'T','F')
> array(['F', 'F', 'F', 'F', 'F', 'T', 'T', 'T', 'F', 'F', 'F', 'F', 'F', 'T'], dtype='<U1')

i want to skip the consecutive True Value like when a>5 comes to 6 its True but for 7 also it is True which i dont want. I want only 1st one.

But also if value drops from 7 to 4 and again rise to 6 then that 6 should be True

Answer 1

You can use np.roll to shift the values and then check if original element is True and shifted element is False

a_bool = a > 5
a_shifted_bool = np.roll(a_bool, 1)
a_shifted_bool[0] = False # first element is last element of a_bool, which we need to ignore

np.where(a_bool & ~a_shifted_bool, 'T', 'F')
array(['F', 'F', 'F', 'F', 'F', 'T', 'F', 'F', 'F', 'F', 'F', 'F', 'F',
       'T'], dtype='<U1')

Answer 2

I guess @Suraj S analyze stock with Best Times of the value to Buy and Sell Stocks.

I try other example, and I think @ggaurav answer is a good way, I learn more in your answer.

import numpy as np

a=np.array([1,2,3,4,5,6,7,8,1,2,3,4,5,6,4,5,6,7,8,4,2,3,6,4,7,9,4,1,2,3,2,5])

a_bool = a > 5
a_shifted_bool = np.roll(a_bool, 1)
a_shifted_bool[0] = False # first element is last element of a_bool, which we need to ignore

np.where(a_bool & ~a_shifted_bool, 'T', 'F')

array(['F', 'F', 'F', 'F', 'F', 'T', 'F', 'F', 'F', 'F', 'F', 'F', 'F', 'T', 'F', 'F', 'T', 'F', 'F', 'F', 'F', 'F', 'T', 'F', 'T', 'F', 'F', 'F', 'F', 'F', 'F', 'F'], dtype='<U1')