如果满足条件,则替换 Numpy 中的行 - 变体
我仍在弄清楚 Numpy 语法!我有一些可行的方法,但必须有一种更简洁的方法来执行此任务。在下面的示例中,我将数组的选定行替换为新条目,其中条件仅针对一个元素。
import numpy as np
big_array = np.random.randint(10, size=(5, 2)) # multi-dimension array
print(big_array)
bad_values = np.less_equal(big_array[:,0], 4) # condition value in one dimension
bad_rows = np.nonzero(bad_values)[0] # indexes to change, e.g. rows
print(f'these are the rows to replace {bad_rows}')
new_rows = np.random.randint(10, size=((bad_rows.size),2))+10 # smaller multi-dim array
np.put(big_array[:,0],bad_rows,y[:,0]) # should be a single line to combine this
np.put(big_array[:,1],bad_rows,y[:,1]) # with this?
print(big_array)
我想要的示例输出可能看起来像
[[2 4]
[5 9]
[6 6]
[6 7]
[0 6]]
these are the rows to replace [0 4]
[[16 17]
[ 5 9]
[ 6 6]
[ 6 7]
[18 17]]
我不知道如何为不同维度的参数格式化 put
。这看起来应该是一句单行话。 (如果我尝试where
,我会收到广播长度问题。)我错过了什么?
I am still figuring out Numpy syntax! I have something that works but there must be a more concise way to perform this task. In the example below, I replace selected rows of an array with new entries, where the condition is just on one element.
import numpy as np
big_array = np.random.randint(10, size=(5, 2)) # multi-dimension array
print(big_array)
bad_values = np.less_equal(big_array[:,0], 4) # condition value in one dimension
bad_rows = np.nonzero(bad_values)[0] # indexes to change, e.g. rows
print(f'these are the rows to replace {bad_rows}')
new_rows = np.random.randint(10, size=((bad_rows.size),2))+10 # smaller multi-dim array
np.put(big_array[:,0],bad_rows,y[:,0]) # should be a single line to combine this
np.put(big_array[:,1],bad_rows,y[:,1]) # with this?
print(big_array)
sample output that I want might look like
[[2 4]
[5 9]
[6 6]
[6 7]
[0 6]]
these are the rows to replace [0 4]
[[16 17]
[ 5 9]
[ 6 6]
[ 6 7]
[18 17]]
I don't know how to format put
for arguments with different dimensions. This seems like it should be a one-liner. (If I try where
I get length issues broadcasting.) What am I missing?
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