5.2. Array Slice¶
>>>
... a[ 0 ] # int
... a[ [0,1] ] # list[int]
... a[ [True,False] ] # list[bool]
... a[ [[True,False], [True,False]] ] # list[list[bool]]
... a[ 0:1 ] # slice(start,stop)
... a[ 0:1:2 ] # slice(start,stop,step)
...
... a[ 0,1 ] # tuple[int]
... a[ (0,1) ] # tuple[int]
... a[ [0,1], [2,3] ] # tuple[list[int]]
... a[ :,: ] # tuple[slice]
... a[ [True,False], [False,True] ] # tuple[list[bool]]
1-dimensional Array:
int
list[int]
list[bool]
list[list[bool]]
slice(start,stop)
slice(start,stop,step)
2-dimensional Array:
tuple[int]
tuple[list[int]]
tuple[slice]
tuple[list[bool]]
5.2.1. SetUp¶
>>> import numpy as np
5.2.2. Recap¶
slice(start:stop:step)data[start:stop:step]By default
start=0By default
stop=len(data)By default
step=1
>>> data = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9])
>>> data[1:5:2] # slice(start=1, stop=5, step=2)
array([2, 4])
>>> data[:5:2] # slice(start=0, stop=5, step=2)
array([1, 3, 5])
>>> data[1::2] # slice(start=1, stop=len(data), step = 2)
array([2, 4, 6, 8])
>>> data[1:5] # slice(start=1, stop=5, step=1)
array([2, 3, 4, 5])
>>> data[::2] # slice(start=0, stop=len(data), step=2)
array([1, 3, 5, 7, 9])
>>> data[:] # slice(start=0, stop=len(data), step=1)
array([1, 2, 3, 4, 5, 6, 7, 8, 9])
5.2.3. 1-dimensional Array¶
>>> import numpy as np
1-dimensional Array:
>>> a = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9])
>>>
>>> a[1:5]
array([2, 3, 4, 5])
>>> a[3:8]
array([4, 5, 6, 7, 8])
>>>
>>> a[0:5]
array([1, 2, 3, 4, 5])
>>> a[:5]
array([1, 2, 3, 4, 5])
>>> a[5:9]
array([6, 7, 8, 9])
>>>
>>> a[5:len(a)]
array([6, 7, 8, 9])
>>> a[5:]
array([6, 7, 8, 9])
>>> a[-2:]
array([8, 9])
>>> a[-5:]
array([5, 6, 7, 8, 9])
>>> a[-6:-2]
array([4, 5, 6, 7])
>>>
>>> a[3:8:2]
array([4, 6, 8])
>>> a[-8:-3:2]
array([2, 4, 6])
>>> a[::2]
array([1, 3, 5, 7, 9])
>>> a[1::2]
array([2, 4, 6, 8])
>>>
>>> a[0:len(a)]
array([1, 2, 3, 4, 5, 6, 7, 8, 9])
>>> a[0:]
array([1, 2, 3, 4, 5, 6, 7, 8, 9])
>>> a[:len(a)]
array([1, 2, 3, 4, 5, 6, 7, 8, 9])
>>> a[:]
array([1, 2, 3, 4, 5, 6, 7, 8, 9])
5.2.4. 2-dimensional Array¶
>>> import numpy as np
Rows:
>>> a = np.array([[1, 2, 3],
... [4, 5, 6],
... [7, 8, 9]])
>>>
>>> a[:]
array([[1, 2, 3],
[4, 5, 6],
[7, 8, 9]])
>>>
>>> a[1:]
array([[4, 5, 6],
[7, 8, 9]])
>>>
>>> a[:1]
array([[1, 2, 3]])
>>>
>>> a[1:3]
array([[4, 5, 6],
[7, 8, 9]])
>>>
>>> a[::2]
array([[1, 2, 3],
[7, 8, 9]])
>>>
>>> a[1::2]
array([[4, 5, 6]])
Columns:
>>> a = np.array([[1, 2, 3],
... [4, 5, 6],
... [7, 8, 9]])
>>>
>>> a[:, 0]
array([1, 4, 7])
>>>
>>> a[:, 1]
array([2, 5, 8])
>>>
>>> a[:, 2]
array([3, 6, 9])
>>>
>>> a[:, -1]
array([3, 6, 9])
>>>
>>> a[:, 0:1]
array([[1],
[4],
[7]])
>>>
>>> a[:, 0:2]
array([[1, 2],
[4, 5],
[7, 8]])
>>>
>>> a[:, :2]
array([[1, 2],
[4, 5],
[7, 8]])
>>>
>>> a[:, ::2]
array([[1, 3],
[4, 6],
[7, 9]])
>>>
>>> a[:, 1::2]
array([[2],
[5],
[8]])
Rows and Columns:
>>> a = np.array([[1, 2, 3],
... [4, 5, 6],
... [7, 8, 9]])
>>>
>>> a[0:1, 0:1]
array([[1]])
>>>
>>> a[0:1, 0:2]
array([[1, 2]])
>>>
>>> a[0:1, 0:3]
array([[1, 2, 3]])
>>>
>>> a[0:2, 0:2]
array([[1, 2],
[4, 5]])
>>>
>>> a[-1:, -2:]
array([[8, 9]])
>>>
>>> a[::2, ::2]
array([[1, 3],
[7, 9]])
>>>
>>> a[1::2, 1::2]
array([[5]])
>>>
>>> a[[2,1], ::2]
array([[7, 9],
[4, 6]])
5.2.5. Assignments¶
"""
* Assignment: Numpy Slice 1
* Complexity: easy
* Lines of code: 3 lines
* Time: 3 min
English:
1. Print inner 2x2 elements
2. Run doctests - all must succeed
Polish:
1. Wybierz wewnętrzne 2x2 elementy
2. Uruchom doctesty - wszystkie muszą się powieść
Tests:
>>> import sys; sys.tracebacklimit = 0
>>> assert result is not Ellipsis, \
'Assign result to variable: `result`'
>>> assert type(result) is np.ndarray, \
'Variable `result` has invalid type, expected: np.ndarray'
>>> result
array([[8, 4],
[5, 2]])
"""
import numpy as np
DATA = np.array([
[2, 8, 1, 5],
[8, 8, 4, 4],
[5, 5, 2, 5],
[1, 0, 6, 0],
])
result = ...
"""
* Assignment: Numpy Slice 2
* Complexity: easy
* Lines of code: 3 lines
* Time: 3 min
English:
1. Print inner 4x4 elements
2. Inner matrix is exactly in the middle of outer
3. Run doctests - all must succeed
Polish:
1. Wypisz środkowe 4x4 elementy
2. Środkowa macierz jest dokładnie w środku większej
3. Uruchom doctesty - wszystkie muszą się powieść
Tests:
>>> import sys; sys.tracebacklimit = 0
>>> assert result is not Ellipsis, \
'Assign result to variable: `result`'
>>> assert type(result) is np.ndarray, \
'Variable `result` has invalid type, expected: np.ndarray'
>>> result
array([[2, 0, 7, 5],
[1, 2, 9, 1],
[8, 8, 8, 2],
[4, 3, 6, 9]])
"""
import numpy as np
DATA = np.array([[5, 0, 3, 3, 7, 9, 3, 5, 2, 4, 7, 6, 8, 8, 1, 6],
[7, 7, 8, 1, 5, 9, 8, 9, 4, 3, 0, 3, 5, 0, 2, 3],
[8, 1, 3, 3, 3, 7, 0, 1, 9, 9, 0, 4, 7, 3, 2, 7],
[2, 0, 0, 4, 5, 5, 6, 8, 4, 1, 4, 9, 8, 1, 1, 7],
[9, 9, 3, 6, 7, 2, 0, 3, 5, 9, 4, 4, 6, 4, 4, 3],
[4, 4, 8, 4, 3, 7, 5, 5, 0, 1, 5, 9, 3, 0, 5, 0],
[1, 2, 4, 2, 0, 3, 2, 0, 7, 5, 9, 0, 2, 7, 2, 9],
[2, 3, 3, 2, 3, 4, 1, 2, 9, 1, 4, 6, 8, 2, 3, 0],
[0, 6, 0, 6, 3, 3, 8, 8, 8, 2, 3, 2, 0, 8, 8, 3],
[8, 2, 8, 4, 3, 0, 4, 3, 6, 9, 8, 0, 8, 5, 9, 0],
[9, 6, 5, 3, 1, 8, 0, 4, 9, 6, 5, 7, 8, 8, 9, 2],
[8, 6, 6, 9, 1, 6, 8, 8, 3, 2, 3, 6, 3, 6, 5, 7],
[0, 8, 4, 6, 5, 8, 2, 3, 9, 7, 5, 3, 4, 5, 3, 3],
[7, 9, 9, 9, 7, 3, 2, 3, 9, 7, 7, 5, 1, 2, 2, 8],
[1, 5, 8, 4, 0, 2, 5, 5, 0, 8, 1, 1, 0, 3, 8, 8],
[4, 4, 0, 9, 3, 7, 3, 2, 1, 1, 2, 1, 4, 2, 5, 5]])
result = ...
Figure 5.5. Inner 4x4 elements¶