Det numpy.zeros() funktion returnerer en ny matrix af given form og type med nuller. Syntaks:
numpy.zeros(shape, dtype = None, order = 'C')>
Parametre:
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.>
Vender tilbage :
ræv vs ulv
ndarray of zeros having given shape, order and datatype.>
Kode 1:
Python
# 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)> |
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>
Output:
Matrix b : [0 0] Matrix a : [[0 0] [0 0]] Matrix c : [[ 0. 0. 0.] [ 0. 0. 0.] [ 0. 0. 0.]]>
Kode 2 : Manipulering af datatyper
Python
palindrom nummer
# 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)> |
>
tostring metode
>
Output:
[(0.0, 0) (0.0, 0)]>
Bemærk : nuller, i modsætning til nuller og tomme, sætter ikke matrixværdierne til henholdsvis nul eller tilfældige værdier. Disse koder vil heller ikke køre på online IDE'er. Kør dem venligst på dine systemer for at udforske arbejdet.