De numpy.zeros() funksjonen returnerer en ny matrise med gitt form og type, med nuller. Syntaks:
numpy.zeros(shape, dtype = None, order = 'C')>
Parametere:
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.>
Returnerer:
string.valueof
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)> |
>
>
Utgang:
Matrix b : [0 0] Matrix a : [[0 0] [0 0]] Matrix c : [[ 0. 0. 0.] [ 0. 0. 0.] [ 0. 0. 0.]]>
Kode 2 : Manipulere datatyper
Python
git pull origin master
# 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-metoden
>
Utgang:
[(0.0, 0) (0.0, 0)]>
Merk : nuller, i motsetning til nuller og tomme, setter ikke matriseverdiene til henholdsvis null eller tilfeldige verdier. Disse kodene vil heller ikke kjøre på nettbaserte IDE-er. Kjør dem på systemene dine for å utforske hvordan de fungerer.