This time I will show you how to assign uniform values to array elements in numpy, and what are the precautions for assigning uniform values to array elements in numpy. The following is a practical case, let's take a look.
The overall array assignment operation in Numpy has always been a bit confusing to me, and I often don’t understand it deeply. Today I will list the relevant knowledge points separately and summarize them.
Let’s look at two small examples of code snippets:
Example 1:
In [2]: arr =np.empty((8,4)) In [3]: arr Out[3]: array([[ 0., 0., 0., 0.], [ 0., 0., 0., 0.], [ 0., 0., 0., 0.], [ 0., 0., 0., 0.], [ 0., 0., 0., 0.], [ 0., 0., 0., 0.], [ 0., 0., 0., 0.], [ 0., 0., 0., 0.]]) In [4]: arr[1] = 1 In [5]: arr Out[5]: array([[ 0., 0., 0., 0.], [ 1., 1., 1., 1.], [ 0., 0., 0., 0.], [ 0., 0., 0., 0.], [ 0., 0., 0., 0.], [ 0., 0., 0., 0.], [ 0., 0., 0., 0.], [ 0., 0., 0., 0.]])
Example 2:
In [6]: arr1 =np.empty(2) In [8]: arr1 Out[8]:array([ 7.74860419e-304, 7.74860419e-304]) In [9]: arr1 = 0 In [10]: arr1 Out[10]: 0
These two paragraphs seem to have behavior inconsistent, but in fact the use is generally The object-oriented tag understanding model can still be understood.
In Example 1, the label after adding index actually refers to the specific storage area, while in Example 2, a label is used directly. So how to achieve the overall assignment of a one-dimensional array? In fact, you only need to index all elements.
The specific method is as follows:
In [11]: arr1 =np.empty(2) In [12]: arr1 Out[12]: array([0., 0.]) In [13]: arr1[:] Out[13]: array([0., 0.]) In [14]: arr1[:] =0 In [15]: arr1 Out[15]: array([0., 0.])
It seems quite simple, but without doing a slightly in-depth analysis , it is indeed a little difficult to understand.
I believe you have mastered the method after reading the case in this article. For more exciting information, please pay attention to other related articles on the php Chinese website!
Recommended reading:
How Python Numpy operates arrays and matrices
How to merge Python’s numpy arrays
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