Python 2d array boolean reduction

up vote
7
down vote

favorite

I've got a 2D array comprised of boolean values (True,False). I'd like to consolidate the array to a 1D based on a logical function of the contents.

e.g.
Input:

[[True, True, False],
 [False, False, False],
 [True, True, True]]

Output (logical AND):

[False,
 False,
 True]

How would this be done without a loop ?

edited 44 mins ago

Willem Van Onsem

131k16125210

asked 51 mins ago

DnRng

735

add a commentÂ |Â

up vote
7
down vote

favorite

I've got a 2D array comprised of boolean values (True,False). I'd like to consolidate the array to a 1D based on a logical function of the contents.

e.g.
Input:

[[True, True, False],
 [False, False, False],
 [True, True, True]]

Output (logical AND):

[False,
 False,
 True]

How would this be done without a loop ?

edited 44 mins ago

Willem Van Onsem

131k16125210

asked 51 mins ago

DnRng

735

add a commentÂ |Â

up vote
7
down vote

favorite

I've got a 2D array comprised of boolean values (True,False). I'd like to consolidate the array to a 1D based on a logical function of the contents.

e.g.
Input:

[[True, True, False],
 [False, False, False],
 [True, True, True]]

Output (logical AND):

[False,
 False,
 True]

How would this be done without a loop ?

edited 44 mins ago

Willem Van Onsem

131k16125210

asked 51 mins ago

DnRng

735

I've got a 2D array comprised of boolean values (True,False). I'd like to consolidate the array to a 1D based on a logical function of the contents.

e.g.
Input:

[[True, True, False],
 [False, False, False],
 [True, True, True]]

Output (logical AND):

[False,
 False,
 True]

How would this be done without a loop ?

python arrays reduction

edited 44 mins ago

Willem Van Onsem

131k16125210

asked 51 mins ago

DnRng

735

edited 44 mins ago

Willem Van Onsem

131k16125210

asked 51 mins ago

DnRng

735

edited 44 mins ago

Willem Van Onsem

131k16125210

edited 44 mins ago

Willem Van Onsem

131k16125210

edited 44 mins ago

Willem Van Onsem

131k16125210

asked 51 mins ago

DnRng

735

asked 51 mins ago

DnRng

735

asked 51 mins ago

DnRng

735

add a commentÂ |Â

5 Answers
5

active

oldest

votes

up vote
4
down vote

You can do this without NumPy too. Here is one solution using list comprehension. Explanation: It will loop over sub-lists and even if one of the items in each sub-list is False, it outputs False else True.

inp = [[True, True, False],[False, False, False],[True, True, True]]
out = [False if False in i else True for i in inp]
print (out)

# [False, False, True]

Alternative (less verbose) as suggested by Jean below:

out = [False not in i for i in inp]

edited 44 mins ago

answered 48 mins ago

Bazingaa

6,9951822

out = [False if False in i else True for i in inp] is a cumbersome way to write out = [False not in i for i in inp]
â€“Â Jean-FranÃ§ois Fabre
45 mins ago

@Jean-FranÃ§oisFabre: I added your suggestion too. Thanks :)
â€“Â Bazingaa
44 mins ago

This is clever but not exactly equivalent to x1 and x2 and ... xn for each sublist when you can have other falsy values in the sublists (such as 0). Of course, OP explicitly said boolean values, so this is just a sidenote.
â€“Â timgeb
31 mins ago

add a commentÂ |Â

up vote
4
down vote

You can use Python's built-in all method with a list-comprehension:

[all(x) for x in my_list]

If that's still too loopy for you, combine it with map:

map(all, my_list)

Note that map doesn't return a list in Python 3. If you want a list as your result, you can call list(map(all, my_list)) instead.

edited 40 mins ago

answered 44 mins ago

Woody1193

1,295624

1

brilliant use of all
â€“Â Jean-FranÃ§ois Fabre
43 mins ago

@Jean-FranÃ§oisFabre Thank you very much
â€“Â Woody1193
42 mins ago

careful with map in python 3 though, as it doesn't create a list (but is even better when used within a loop)
â€“Â Jean-FranÃ§ois Fabre
41 mins ago

@Jean-FranÃ§oisFabre True, I'll make a note of it
â€“Â Woody1193
41 mins ago

add a commentÂ |Â

up vote
3
down vote

I'm assuming you want to apply logical ANDs to the rows. You can apply numpy.all.

>>> import numpy as np
>>> a = np.array([[True, True, False], [False, False, False], [True, True, True]])
>>> a
array([[ True, True, False],
 [False, False, False],
 [ True, True, True]])
>>> 
>>> np.all(a, axis=1)
array([False, False, True])

For a solution without numpy, you can use operator.and_ and functools.reduce.

>>> from operator import and_
>>> from functools import reduce
>>> 
>>> lst = [[True, True, False], [False, False, False], [True, True, True]]
>>> [reduce(and_, sub) for sub in lst]
[False, False, True]

edit: actually, reduce is a bit redundant in this particular case.

>>> [all(sub) for sub in lst]
[False, False, True]

does the job just as well.

edited 39 mins ago

answered 47 mins ago

timgeb

38.8k105177

add a commentÂ |Â

up vote
2
down vote

You can do this with numpy with the numpy.all function:

>>> import numpy as np
>>> arr = np.array([[True, True, False],
... [False, False, False],
... [True, True, True]]
... )
>>> np.all(arr, axis=1)
array([False, False, True])

Here thus the i-th element is True if all elements of the i-th row are True, and False otherwise. Note that the list should be rectangular (all sublists should contain the same number of booleans).

In "pure" Python, you can use the all function as well, like:

>>> data = [[True, True, False], [False, False, False], [True, True, True]]
>>> list(map(all, data))
[False, False, True]

This approach will work as well if the "matrix" is not rectangular. Note that for an empty sublist, this will return True, since all elements in an empty sublist are True.

answered 48 mins ago

Willem Van Onsem

131k16125210

add a commentÂ |Â

up vote
2
down vote

You can also do this with map and reduce:

from functools import reduce

l = [[True, True, False],
 [False, False, False],
 [True, True, True]]

final = list(map(lambda x: reduce(lambda a, b: a and b, x), l))
print(final)
# [False, False, True]

The benefit here is that you can change the reduce function to something else (say, an OR or something more adventurous).

edited 37 mins ago

answered 44 mins ago

slider

2,900926

add a commentÂ |Â

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5 Answers
5

active

oldest

votes

5 Answers
5

active

oldest

votes

up vote
4
down vote

inp = [[True, True, False],[False, False, False],[True, True, True]]
out = [False if False in i else True for i in inp]
print (out)

# [False, False, True]

Alternative (less verbose) as suggested by Jean below:

out = [False not in i for i in inp]

edited 44 mins ago

answered 48 mins ago

Bazingaa

6,9951822

out = [False if False in i else True for i in inp] is a cumbersome way to write out = [False not in i for i in inp]
â€“Â Jean-FranÃ§ois Fabre
45 mins ago

@Jean-FranÃ§oisFabre: I added your suggestion too. Thanks :)
â€“Â Bazingaa
44 mins ago

This is clever but not exactly equivalent to x1 and x2 and ... xn for each sublist when you can have other falsy values in the sublists (such as 0). Of course, OP explicitly said boolean values, so this is just a sidenote.
â€“Â timgeb
31 mins ago

add a commentÂ |Â

up vote
4
down vote

inp = [[True, True, False],[False, False, False],[True, True, True]]
out = [False if False in i else True for i in inp]
print (out)

# [False, False, True]

Alternative (less verbose) as suggested by Jean below:

out = [False not in i for i in inp]

edited 44 mins ago

answered 48 mins ago

Bazingaa

6,9951822

out = [False if False in i else True for i in inp] is a cumbersome way to write out = [False not in i for i in inp]
â€“Â Jean-FranÃ§ois Fabre
45 mins ago

@Jean-FranÃ§oisFabre: I added your suggestion too. Thanks :)
â€“Â Bazingaa
44 mins ago

This is clever but not exactly equivalent to x1 and x2 and ... xn for each sublist when you can have other falsy values in the sublists (such as 0). Of course, OP explicitly said boolean values, so this is just a sidenote.
â€“Â timgeb
31 mins ago

add a commentÂ |Â

up vote
4
down vote

inp = [[True, True, False],[False, False, False],[True, True, True]]
out = [False if False in i else True for i in inp]
print (out)

# [False, False, True]

Alternative (less verbose) as suggested by Jean below:

out = [False not in i for i in inp]

edited 44 mins ago

answered 48 mins ago

Bazingaa

6,9951822

inp = [[True, True, False],[False, False, False],[True, True, True]]
out = [False if False in i else True for i in inp]
print (out)

# [False, False, True]

Alternative (less verbose) as suggested by Jean below:

out = [False not in i for i in inp]

edited 44 mins ago

answered 48 mins ago

Bazingaa

6,9951822

edited 44 mins ago

answered 48 mins ago

Bazingaa

6,9951822

answered 48 mins ago

Bazingaa

6,9951822

answered 48 mins ago

Bazingaa

6,9951822

out = [False if False in i else True for i in inp] is a cumbersome way to write out = [False not in i for i in inp]
â€“Â Jean-FranÃ§ois Fabre
45 mins ago

@Jean-FranÃ§oisFabre: I added your suggestion too. Thanks :)
â€“Â Bazingaa
44 mins ago

This is clever but not exactly equivalent to x1 and x2 and ... xn for each sublist when you can have other falsy values in the sublists (such as 0). Of course, OP explicitly said boolean values, so this is just a sidenote.
â€“Â timgeb
31 mins ago

add a commentÂ |Â

out = [False if False in i else True for i in inp] is a cumbersome way to write out = [False not in i for i in inp]
â€“Â Jean-FranÃ§ois Fabre
45 mins ago

@Jean-FranÃ§oisFabre: I added your suggestion too. Thanks :)
â€“Â Bazingaa
44 mins ago

This is clever but not exactly equivalent to x1 and x2 and ... xn for each sublist when you can have other falsy values in the sublists (such as 0). Of course, OP explicitly said boolean values, so this is just a sidenote.
â€“Â timgeb
31 mins ago

out = [False if False in i else True for i in inp] is a cumbersome way to write out = [False not in i for i in inp]
â€“Â Jean-FranÃ§ois Fabre
45 mins ago

@Jean-FranÃ§oisFabre: I added your suggestion too. Thanks :)
â€“Â Bazingaa
44 mins ago

This is clever but not exactly equivalent to x1 and x2 and ... xn for each sublist when you can have other falsy values in the sublists (such as 0). Of course, OP explicitly said boolean values, so this is just a sidenote.
â€“Â timgeb
31 mins ago

add a commentÂ |Â

up vote
4
down vote

You can use Python's built-in all method with a list-comprehension:

[all(x) for x in my_list]

If that's still too loopy for you, combine it with map:

map(all, my_list)

Note that map doesn't return a list in Python 3. If you want a list as your result, you can call list(map(all, my_list)) instead.

edited 40 mins ago

answered 44 mins ago

Woody1193

1,295624

1

brilliant use of all
â€“Â Jean-FranÃ§ois Fabre
43 mins ago

@Jean-FranÃ§oisFabre Thank you very much
â€“Â Woody1193
42 mins ago

careful with map in python 3 though, as it doesn't create a list (but is even better when used within a loop)
â€“Â Jean-FranÃ§ois Fabre
41 mins ago

@Jean-FranÃ§oisFabre True, I'll make a note of it
â€“Â Woody1193
41 mins ago

add a commentÂ |Â

up vote
4
down vote

You can use Python's built-in all method with a list-comprehension:

[all(x) for x in my_list]

If that's still too loopy for you, combine it with map:

map(all, my_list)

Note that map doesn't return a list in Python 3. If you want a list as your result, you can call list(map(all, my_list)) instead.

edited 40 mins ago

answered 44 mins ago

Woody1193

1,295624

1

brilliant use of all
â€“Â Jean-FranÃ§ois Fabre
43 mins ago

@Jean-FranÃ§oisFabre Thank you very much
â€“Â Woody1193
42 mins ago

careful with map in python 3 though, as it doesn't create a list (but is even better when used within a loop)
â€“Â Jean-FranÃ§ois Fabre
41 mins ago

@Jean-FranÃ§oisFabre True, I'll make a note of it
â€“Â Woody1193
41 mins ago

add a commentÂ |Â

up vote
4
down vote

You can use Python's built-in all method with a list-comprehension:

[all(x) for x in my_list]

If that's still too loopy for you, combine it with map:

map(all, my_list)

Note that map doesn't return a list in Python 3. If you want a list as your result, you can call list(map(all, my_list)) instead.

edited 40 mins ago

answered 44 mins ago

Woody1193

1,295624

You can use Python's built-in all method with a list-comprehension:

[all(x) for x in my_list]

If that's still too loopy for you, combine it with map:

map(all, my_list)

Note that map doesn't return a list in Python 3. If you want a list as your result, you can call list(map(all, my_list)) instead.

edited 40 mins ago

answered 44 mins ago

Woody1193

1,295624

edited 40 mins ago

answered 44 mins ago

Woody1193

1,295624

answered 44 mins ago

Woody1193

1,295624

answered 44 mins ago

Woody1193

1,295624

1

brilliant use of all
â€“Â Jean-FranÃ§ois Fabre
43 mins ago

@Jean-FranÃ§oisFabre Thank you very much
â€“Â Woody1193
42 mins ago

careful with map in python 3 though, as it doesn't create a list (but is even better when used within a loop)
â€“Â Jean-FranÃ§ois Fabre
41 mins ago

@Jean-FranÃ§oisFabre True, I'll make a note of it
â€“Â Woody1193
41 mins ago

add a commentÂ |Â

1

brilliant use of all
â€“Â Jean-FranÃ§ois Fabre
43 mins ago

@Jean-FranÃ§oisFabre Thank you very much
â€“Â Woody1193
42 mins ago

careful with map in python 3 though, as it doesn't create a list (but is even better when used within a loop)
â€“Â Jean-FranÃ§ois Fabre
41 mins ago

@Jean-FranÃ§oisFabre True, I'll make a note of it
â€“Â Woody1193
41 mins ago

brilliant use of all
â€“Â Jean-FranÃ§ois Fabre
43 mins ago

@Jean-FranÃ§oisFabre Thank you very much
â€“Â Woody1193
42 mins ago

careful with map in python 3 though, as it doesn't create a list (but is even better when used within a loop)
â€“Â Jean-FranÃ§ois Fabre
41 mins ago

@Jean-FranÃ§oisFabre True, I'll make a note of it
â€“Â Woody1193
41 mins ago

add a commentÂ |Â

up vote
3
down vote

I'm assuming you want to apply logical ANDs to the rows. You can apply numpy.all.

>>> import numpy as np
>>> a = np.array([[True, True, False], [False, False, False], [True, True, True]])
>>> a
array([[ True, True, False],
 [False, False, False],
 [ True, True, True]])
>>> 
>>> np.all(a, axis=1)
array([False, False, True])

For a solution without numpy, you can use operator.and_ and functools.reduce.

>>> from operator import and_
>>> from functools import reduce
>>> 
>>> lst = [[True, True, False], [False, False, False], [True, True, True]]
>>> [reduce(and_, sub) for sub in lst]
[False, False, True]

edit: actually, reduce is a bit redundant in this particular case.

>>> [all(sub) for sub in lst]
[False, False, True]

does the job just as well.

edited 39 mins ago

answered 47 mins ago

timgeb

38.8k105177

add a commentÂ |Â

up vote
3
down vote

I'm assuming you want to apply logical ANDs to the rows. You can apply numpy.all.

>>> import numpy as np
>>> a = np.array([[True, True, False], [False, False, False], [True, True, True]])
>>> a
array([[ True, True, False],
 [False, False, False],
 [ True, True, True]])
>>> 
>>> np.all(a, axis=1)
array([False, False, True])

For a solution without numpy, you can use operator.and_ and functools.reduce.

>>> from operator import and_
>>> from functools import reduce
>>> 
>>> lst = [[True, True, False], [False, False, False], [True, True, True]]
>>> [reduce(and_, sub) for sub in lst]
[False, False, True]

edit: actually, reduce is a bit redundant in this particular case.

>>> [all(sub) for sub in lst]
[False, False, True]

does the job just as well.

edited 39 mins ago

answered 47 mins ago

timgeb

38.8k105177

add a commentÂ |Â

up vote
3
down vote

I'm assuming you want to apply logical ANDs to the rows. You can apply numpy.all.

>>> import numpy as np
>>> a = np.array([[True, True, False], [False, False, False], [True, True, True]])
>>> a
array([[ True, True, False],
 [False, False, False],
 [ True, True, True]])
>>> 
>>> np.all(a, axis=1)
array([False, False, True])

For a solution without numpy, you can use operator.and_ and functools.reduce.

>>> from operator import and_
>>> from functools import reduce
>>> 
>>> lst = [[True, True, False], [False, False, False], [True, True, True]]
>>> [reduce(and_, sub) for sub in lst]
[False, False, True]

edit: actually, reduce is a bit redundant in this particular case.

>>> [all(sub) for sub in lst]
[False, False, True]

does the job just as well.

edited 39 mins ago

answered 47 mins ago

timgeb

38.8k105177

I'm assuming you want to apply logical ANDs to the rows. You can apply numpy.all.

>>> import numpy as np
>>> a = np.array([[True, True, False], [False, False, False], [True, True, True]])
>>> a
array([[ True, True, False],
 [False, False, False],
 [ True, True, True]])
>>> 
>>> np.all(a, axis=1)
array([False, False, True])

For a solution without numpy, you can use operator.and_ and functools.reduce.

>>> from operator import and_
>>> from functools import reduce
>>> 
>>> lst = [[True, True, False], [False, False, False], [True, True, True]]
>>> [reduce(and_, sub) for sub in lst]
[False, False, True]

edit: actually, reduce is a bit redundant in this particular case.

>>> [all(sub) for sub in lst]
[False, False, True]

does the job just as well.

edited 39 mins ago

answered 47 mins ago

timgeb

38.8k105177

edited 39 mins ago

answered 47 mins ago

timgeb

38.8k105177

answered 47 mins ago

timgeb

38.8k105177

answered 47 mins ago

timgeb

38.8k105177

add a commentÂ |Â

up vote
2
down vote

You can do this with numpy with the numpy.all function:

>>> import numpy as np
>>> arr = np.array([[True, True, False],
... [False, False, False],
... [True, True, True]]
... )
>>> np.all(arr, axis=1)
array([False, False, True])

In "pure" Python, you can use the all function as well, like:

>>> data = [[True, True, False], [False, False, False], [True, True, True]]
>>> list(map(all, data))
[False, False, True]

This approach will work as well if the "matrix" is not rectangular. Note that for an empty sublist, this will return True, since all elements in an empty sublist are True.

answered 48 mins ago

Willem Van Onsem

131k16125210

add a commentÂ |Â

up vote
2
down vote

You can do this with numpy with the numpy.all function:

>>> import numpy as np
>>> arr = np.array([[True, True, False],
... [False, False, False],
... [True, True, True]]
... )
>>> np.all(arr, axis=1)
array([False, False, True])

In "pure" Python, you can use the all function as well, like:

>>> data = [[True, True, False], [False, False, False], [True, True, True]]
>>> list(map(all, data))
[False, False, True]

This approach will work as well if the "matrix" is not rectangular. Note that for an empty sublist, this will return True, since all elements in an empty sublist are True.

answered 48 mins ago

Willem Van Onsem

131k16125210

add a commentÂ |Â

up vote
2
down vote

You can do this with numpy with the numpy.all function:

>>> import numpy as np
>>> arr = np.array([[True, True, False],
... [False, False, False],
... [True, True, True]]
... )
>>> np.all(arr, axis=1)
array([False, False, True])

In "pure" Python, you can use the all function as well, like:

>>> data = [[True, True, False], [False, False, False], [True, True, True]]
>>> list(map(all, data))
[False, False, True]

This approach will work as well if the "matrix" is not rectangular. Note that for an empty sublist, this will return True, since all elements in an empty sublist are True.

answered 48 mins ago

Willem Van Onsem

131k16125210

You can do this with numpy with the numpy.all function:

>>> import numpy as np
>>> arr = np.array([[True, True, False],
... [False, False, False],
... [True, True, True]]
... )
>>> np.all(arr, axis=1)
array([False, False, True])

In "pure" Python, you can use the all function as well, like:

>>> data = [[True, True, False], [False, False, False], [True, True, True]]
>>> list(map(all, data))
[False, False, True]

This approach will work as well if the "matrix" is not rectangular. Note that for an empty sublist, this will return True, since all elements in an empty sublist are True.

answered 48 mins ago

Willem Van Onsem

131k16125210

answered 48 mins ago

Willem Van Onsem

131k16125210

answered 48 mins ago

Willem Van Onsem

131k16125210

answered 48 mins ago

Willem Van Onsem

131k16125210

add a commentÂ |Â

up vote
2
down vote

You can also do this with map and reduce:

from functools import reduce

l = [[True, True, False],
 [False, False, False],
 [True, True, True]]

final = list(map(lambda x: reduce(lambda a, b: a and b, x), l))
print(final)
# [False, False, True]

The benefit here is that you can change the reduce function to something else (say, an OR or something more adventurous).

edited 37 mins ago

answered 44 mins ago

slider

2,900926

add a commentÂ |Â

up vote
2
down vote

You can also do this with map and reduce:

from functools import reduce

l = [[True, True, False],
 [False, False, False],
 [True, True, True]]

final = list(map(lambda x: reduce(lambda a, b: a and b, x), l))
print(final)
# [False, False, True]

The benefit here is that you can change the reduce function to something else (say, an OR or something more adventurous).

edited 37 mins ago

answered 44 mins ago

slider

2,900926

add a commentÂ |Â

up vote
2
down vote

You can also do this with map and reduce:

from functools import reduce

l = [[True, True, False],
 [False, False, False],
 [True, True, True]]

final = list(map(lambda x: reduce(lambda a, b: a and b, x), l))
print(final)
# [False, False, True]

The benefit here is that you can change the reduce function to something else (say, an OR or something more adventurous).

edited 37 mins ago

answered 44 mins ago

slider

2,900926

You can also do this with map and reduce:

from functools import reduce

l = [[True, True, False],
 [False, False, False],
 [True, True, True]]

final = list(map(lambda x: reduce(lambda a, b: a and b, x), l))
print(final)
# [False, False, True]

The benefit here is that you can change the reduce function to something else (say, an OR or something more adventurous).

edited 37 mins ago

answered 44 mins ago

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edited 37 mins ago

answered 44 mins ago

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2,900926

answered 44 mins ago

slider

2,900926

answered 44 mins ago

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2,900926

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