"NumPy foreach row"의 두 판 사이의 차이

2021년 12월 12일 (일) 16:23 기준 최신판

import numpy as np
m = np.matrix([[101,102,103],
               [201,202,203],
               [301,302,303],
               [401,402,403]])
m

for i, row in enumerate(m):
  print(i, row)

def myfunc(x):
  print(x)
np.apply_along_axis(myfunc, axis=1, arr=m)

np.apply_along_axis(lambda x: print(x), axis=1, arr=m)

@@ 2번째 줄: / 2번째 줄: @@
 ;NumPy foreach row
-<syntaxhighlight lang='python' run>
+<syntaxhighlight lang='python' notebook>
 import numpy as np
-m = np.matrix([[101,102,103,104],
+m = np.matrix([[101,102,103],
-                [201,202,203,204],
+                [201,202,203],
-                [301,302,303,304]])
+                [301,302,303],
+               [401,402,403]])
+m
+</syntaxhighlight>
+<syntaxhighlight lang='python' notebook>
 for i, row in enumerate(m):
    print(i, row)
 </syntaxhighlight>
+<syntaxhighlight lang='python' notebook>
+def myfunc(x):
+  print(x)
+np.apply_along_axis(myfunc, axis=1, arr=m)
+</syntaxhighlight>
+<syntaxhighlight lang='python' notebook>
+np.apply_along_axis(lambda x: print(x), axis=1, arr=m)
+</syntaxhighlight>
 ==같이 보기==
+* [[NumPy apply_along_axis()]]
+* [[NumPy foreach column]]
 * [[Python foreach]]
 [[분류: NumPy]]