PYTHON의 NUMPY.ZEROS()

그만큼 numpy.zeros() 함수는 주어진 모양과 유형의 새로운 배열을 0으로 반환합니다. 통사론:

numpy.zeros(shape, dtype = None, order = 'C')

매개변수:

  shape :   integer or sequence of integers   order :   C_contiguous or F_contiguous  C-contiguous order in memory(last index varies the fastest)  C order means that operating row-rise on the array will be slightly quicker  FORTRAN-contiguous order in memory (first index varies the fastest).  F order means that column-wise operations will be faster.    dtype :   [optional, float(byDeafult)] Data type of returned array.

반품 :

ndarray of zeros having given shape, order and datatype.

코드 1:

파이썬

# Python Program illustrating> # numpy.zeros method> > import> numpy as geek> > b> => geek.zeros(> 2> , dtype> => int> )> print> (>

'Matrix b : 
'>

, b)> > a> => geek.zeros([> 2> ,> 2> ], dtype> => int> )> print> (>

'
Matrix a : 
'>

, a)> > c> => geek.zeros([> 3> ,> 3> ])> print> (>

'
Matrix c : 
'>

, c)>

출력 :

Matrix b :   [0 0] Matrix a :   [[0 0]  [0 0]] Matrix c :   [[ 0. 0. 0.]  [ 0. 0. 0.]  [ 0. 0. 0.]]

코드 2: 데이터 유형 조작

파이썬

# Python Program illustrating> # numpy.zeros method> > import> numpy as geek> > # manipulation with data-types> b> => geek.zeros((> 2> ,), dtype> => [(> 'x'> ,> 'float'> ), (> 'y'> ,> 'int'> )])> print> (b)>

출력 :