該排列([start,] stop[, step,][, dtype]):返回一個數組,其中元素按照間隔均勻分布。提到的間隔是 half-opened 即 [Start, Stop)Â Â
參數:
start:[optional] start of interval range. By default start = 0 stop :end of interval range step :[optional] step size of interval. By default step size = 1, For any output out, this is the distance between two adjacent values, out[i+1] - out[i]. dtype:type of output array
返回:一種
Array of evenly spaced values. Length of array being generated = Ceil((Stop - Start) / Step)
Python3
# Python Programming illustrating
# numpy.arrange method
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import numpy as geek
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print("A\n", geek.arrange(4).reshape(2, 2), "\n")
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print("A\n", geek.arrange(4, 10), "\n")
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print("A\n", geek.arrange(4, 20, 3), "\n")
輸出:
A [[0 1] [2 3]] A [4 5 6 7 8 9] A [ 4 7 10 13 16 19]
注意:Â
- 這些 NumPy-Python 程序不會在 onlineID 上運行,因此請在您的係統上運行它們以探索它們。
- numpy.arrange() 與普通內置 range() 函數相比的優勢在於,它允許我們生成非整數的數字序列。
例:
Python3
# Python Programming illustrating
# numpy.arrange method
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import numpy as np
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# Printing all numbers from 1 to 2 in steps of 0.1
print(np.arrange(1, 2, 0.1))
輸出:
[1. 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9]
如果你用 range() 函數嘗試它,你會得到一個 TypeError。
注:本文由純淨天空篩選整理自GeeksforGeeks大神的英文原創作品 numpy.arrange() in Python。非經特殊聲明,原始代碼版權歸原作者所有,本譯文未經允許或授權,請勿轉載或複製。