NumPy Array Iteration

a gudanar fannin

a gudanar a kai gudanar kowane scalar:

domin ake amfana da fannin da ke da kwayoyi, ake amfana da kai amfana da fannin a kowane wuri.

domin ake amfana da fannin da ke da kwayoyi, ake amfana da kai gudanar kowane scalar a kowane scalar.

Mafi

a gudanar kowane scalar a 1-D fannin:

import numpy as np
arr = np.array([1, 2, 3])
for x in arr:
  print(x)

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a gudanar 2-D fannin

a gudanar a kai tsuntsaye dukkan wuri a 2-D fannin.

Mafi

a gudanar kowane scalar a 2-D fannin:

import numpy as np
arr = np.array([[1, 2, 3], [4, 5, 6]])
for x in arr:
  print(x)

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domin ake amfana da fannin da ke da kwayoyi, ake amfana da kai gudanar kowane wuri a kowane wuri.

domin ake amfana da kowane scalar, a na iya amfana da kai gudanar kowane wuri.

Mafi

a gudanar kowane scalar a 2-D fannin:

import numpy as np
arr = np.array([[1, 2, 3], [4, 5, 6]])
for x in arr:
  for y in x:
    print(y)

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a gudanar 3-D fannin

a gudanar a kai tsuntsaye dukkan 2-D fannin a 3-D fannin.

Mafi

a gudanar kowane scalar a 3-D fannin:

import numpy as np
arr = np.array([[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]])
for x in arr:
  print(x)

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domin ake amfana da kowane scalar, a na iya amfana da kai gudanar kowane wuri.

Mafi

a gudanar scalar:

import numpy as np
arr = np.array([[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]])
for x in arr:
  for y in x:
    for z in y:
      print(z)

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a gudanar fannin nditer() a fannin

aiki nditer() wannan shine hanyar aiki, wanda ake amfana da dukkan nau'yan gudanar daga tsawon yauwa zuwa tsawon da yauwa, ake amfana da amfana. Wannan ya halarci dukkan waɗanda ake amfana da kara amfana da ake amfana da suka kai. Ake amfana da kai tsuntsaye na tushen tushen da kai tsuntsaye na yauwa.

a gudanar kowane scalar a fannin

a gudanar a kai tsuntsaye for a gudanar a kai tsuntsaye, ake amfana da kowane scalar a fannin, a na iya amfana da n. for a gudanar a kai tsuntsaye, domin ake amfana da fannin da ke da kwayoyi da yauwa ake amfana da suka kai.

Mafi

a gudanar dukkan 3-D fannin:

import numpy as np
arr = np.array([[[1, 2], [3, 4]], [[5, 6], [7, 8]]])
for x in np.nditer(arr):
  print(x)

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a gudanar dukkan nau'yan fannin da ake amfana da

Ake amfana ne ne op_dtypes 参数，ka a datti kan tashi da datti kara cikin aikataka, domin kara a gudanar da saurin nau'yan fannin da ake amfana da.

NumPy ba a gudanar da kaiwa sabunta da kaiwa kuduwa dukkanin abubuwan (abubuwan yana cikin array), sabonni a kaiwa shi da wuri dake, wuri na yadda a kaiwa shi da: nditer() Dukiya, bayan da ake kaiwa sa, a kaiwa sa: flags=['buffered'].

Mafi

Kaiwa iteration da yadda ake kuduwa masu:

import numpy as np
arr = np.array([1, 2, 3])
for x in np.nditer(arr, flags=['buffered'], op_dtypes=['S']):
  print(x)

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Kaiwa iteration da tsawon hanyar da yake

A kaiwa shi da fadar, kai kaiwa iteration.

Mafi

Kaiwa iteration kai tsaye 2D kuduwa scalar element, kai kaiwa 1 element:

import numpy as np
arr = np.array([[1, 2, 3, 4], [5, 6, 7, 8]])
for x in np.nditer(arr[:, ::2]):
  print(x)

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Kaiwa iteration da ndenumerate()

Kudade na yin kuduwa dukkanin abubuwan da ake kuduwa su ne.

Dukiya, bayan da ake yin iteration, a kaiwa shi da index na kudan, wa'annan kuma, a kaiwa shi da ndenumerate() Hanyar.

Mafi

Kudade 1D kuduwa 1D:

import numpy as np
arr = np.array([1, 2, 3])
for idx, x in np.ndenumerate(arr):
  print(idx, x)

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Mafi

Kudade 2D kuduwa kuduwa 2D:

import numpy as np
arr = np.array([[1, 2, 3, 4], [5, 6, 7, 8]])
for idx, x in np.ndenumerate(arr):
  print(idx, x)

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