The numpy.zeros() funkcija atgriež jaunu noteiktas formas un veida masīvu ar nullēm. Sintakse:
numpy.zeros(shape, dtype = None, order = 'C')>
Parametri:
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.>
Atgriešanās:
ndarray of zeros having given shape, order and datatype.>
1. kods:
Python
virkne kā masīvs
# 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)> |
>
>
Izvade:
Matrix b : [0 0] Matrix a : [[0 0] [0 0]] Matrix c : [[ 0. 0. 0.] [ 0. 0. 0.] [ 0. 0. 0.]]>
Kods 2 : manipulācijas ar datu tipiem
Python
# 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)> |
>
>
Izvade:
[(0.0, 0) (0.0, 0)]>
Piezīme : nulles, atšķirībā no nullēm un tukšas, neiestata masīva vērtības attiecīgi uz nulli vai nejaušām vērtībām. Turklāt šie kodi nedarbosies tiešsaistes IDE. Lūdzu, palaidiet tos savās sistēmās, lai izpētītu darbību.