[Numpy-discussion] Adding an nd generalization of np.ma.mask_rowscols

[Eric Wieser]

Today, numpy has a np.ma.mask_rowcols function, which stretches masks along
the full length of an axis. For example, given the matrix::

>>> a2d = np.zeros((3, 3), dtype=int)
>>> a2d[1, 1] = 1
>>> a2d = np.ma.masked_equal(a2d, 1)
>>> print(a2d)
[[0 0 0]
 [0 -- 0]
 [0 0 0]]

The API allows::

>>> print(np.ma.mask_rowcols(a2d, axis=0))
[[0 0 0]
 [-- -- --]
 [0 0 0]]

>>> print(np.ma.mask_rowcols(a2d, axis=1))
[[0 -- 0]
 [0 -- 0]
 [0 -- 0]]

>>> print(np.ma.mask_rowcols(a2d, axis=None))
[[0 -- 0]
 [-- -- --]
 [0 -- 0]]

However, this function only works for 2D arrays.
It would be useful to generalize this to work on ND arrays as well.

Unfortunately, the current function is messy to generalize, because axis=0
means “spread the mask along axis 1”, and vice versa. Additionally, the
name is not particularly good for an ND function.

My proposal in PR 14998  is to
introduce a new function, mask_extend_axis, which fixes this shortcoming.
Given an 3D array::

>>> a3d = np.zeros((2, 2, 2), dtype=int)
>>> a3d[0, 0, 0] = 1
>>> a3d = np.ma.masked_equal(a3d, 1)
>>> print(a3d)
[[[-- 0]
  [0 0]]

 [[0 0]
  [0 0]]]

This, in my opinion, has clearer axis semantics:

>>> print(np.ma.mask_extend_axis(a2d, axis=0))
[[[-- 0]
  [0 0]]

 [[-- 0]
  [0 0]]]

>>> print(np.ma.mask_extend_axis(a2d, axis=1))
[[[-- 0]
  [-- 0]]

 [[0 0]
  [0 0]]]

>>> print(np.ma.mask_extend_axis(a2d, axis=2))
[[[-- --]
  [0 0]]

 [[0 0]
  [0 0]]]

Stretching over multiple axes remains possible:

>>> print(np.ma.mask_extend_axis(a2d, axis=(1, 2)))
[[[-- --]
  [-- 0]]

 [[0 0]
  [0 0]]]

# extending sequentially is not the same as extending in parallel
>>> print(np.ma.mask_extend_axis(np.ma.mask_extend_axis(a2d, axis=1), axis=2))
[[[-- --]
  [-- --]]

 [[0 0]
  [0 0]]]

Questions for the mailing list then:

   - Can you think of a better name than mask_extend_axis?
   - Does my proposed meaning of axis make more sense to you than the one
   used by mask_rowcols?
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Re: [Numpy-discussion] Adding an nd generalization of np.ma.mask_rowscols

[Sebastian Berg]

On Fri, 2020-01-17 at 10:39 +, Eric Wieser wrote:
> Today, numpy has a np.ma.mask_rowcols function, which stretches masks
> along
> the full length of an axis. For example, given the matrix::
> 


> Questions for the mailing list then:
> 

The additional question: I think I am good with adding a new name if we
cannot reasonably reuse the old ones.

> Can you think of a better name than mask_extend_axis?

Doubt it is good, but to put it there: extend_mask_along_axis

"along" shows up 2-3 times, although "along" really is the default for
most things in NumPy.

Tried thesaurus for "extend", the main other word seemed "spread" (but
it is very different from the current choice).

> Does my proposed meaning of axis make more sense to you than the one
> used by mask_rowcols?

It does to me (although I hardly ever use masked arrays). The `axis`
argument usually denotes the axis being operated on/along.

- Sebastian

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Re: [Numpy-discussion] Adding an nd generalization of np.ma.mask_rowscols

[Hameer Abbasi]

IMHO, masked arrays and extending masks like that is a weird API. I would 
prefer a more functional approach: Where we take in an input 1-D or N-D boolean 
array in addition to a masked array with multiple axes over which to extend the 
mask.

From: NumPy-Discussion 
 on behalf of 
Eric Wieser 
Reply to: Discussion of Numerical Python 
Date: Friday, 17. January 2020 at 11:40
To: Discussion of Numerical Python 
Subject: [Numpy-discussion] Adding an nd generalization of np.ma.mask_rowscols


Today, numpy has a np.ma.mask_rowcols function, which stretches masks along
the full length of an axis. For example, given the matrix::

>>> a2d = np.zeros((3, 3), dtype=int)

>>> a2d[1, 1] = 1

>>> a2d = np.ma.masked_equal(a2d, 1)

>>> print(a2d)

[[0 0 0]

 [0 -- 0]

 [0 0 0]]

The API allows::

>>> print(np.ma.mask_rowcols(a2d, axis=0))

[[0 0 0]

 [-- -- --]

 [0 0 0]]



>>> print(np.ma.mask_rowcols(a2d, axis=1))

[[0 -- 0]

 [0 -- 0]

 [0 -- 0]]



>>> print(np.ma.mask_rowcols(a2d, axis=None))

[[0 -- 0]

 [-- -- --]

 [0 -- 0]]

However, this function only works for 2D arrays.
It would be useful to generalize this to work on ND arrays as well.

Unfortunately, the current function is messy to generalize, because axis=0 
means “spread the mask along axis 1”, and vice versa. Additionally, the name is 
not particularly good for an ND function.

My proposal in PR 14998 is to 
introduce a new function, mask_extend_axis, which fixes this shortcoming.
Given an 3D array::

>>> a3d = np.zeros((2, 2, 2), dtype=int)

>>> a3d[0, 0, 0] = 1

>>> a3d = np.ma.masked_equal(a3d, 1)

>>> print(a3d)

[[[-- 0]

  [0 0]]



 [[0 0]

  [0 0]]]

This, in my opinion, has clearer axis semantics:

>>> print(np.ma.mask_extend_axis(a2d, axis=0))

[[[-- 0]

  [0 0]]



 [[-- 0]

  [0 0]]]



>>> print(np.ma.mask_extend_axis(a2d, axis=1))

[[[-- 0]

  [-- 0]]



 [[0 0]

  [0 0]]]



>>> print(np.ma.mask_extend_axis(a2d, axis=2))

[[[-- --]

  [0 0]]



 [[0 0]

  [0 0]]]

Stretching over multiple axes remains possible:

>>> print(np.ma.mask_extend_axis(a2d, axis=(1, 2)))

[[[-- --]

  [-- 0]]



 [[0 0]

  [0 0]]]



# extending sequentially is not the same as extending in parallel

>>> print(np.ma.mask_extend_axis(np.ma.mask_extend_axis(a2d, axis=1), axis=2))

[[[-- --]

  [-- --]]



 [[0 0]

  [0 0]]]

Questions for the mailing list then:
· Can you think of a better name than mask_extend_axis?
· Does my proposed meaning of axis make more sense to you than the one 
used by mask_rowcols?
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Re: [Numpy-discussion] Adding an nd generalization of np.ma.mask_rowscols

[Eric Wieser]

IMHO, masked arrays and extending masks like that is a weird API.

To give some context, I needed this nd generalization internally in order
to fix the issue on these lines

.

I would prefer a more functional approach

Can you elaborate on that with an example of the API you’d prefer instead
of np.ma.mask_extend_axis(a, axis=(0, 1))?

On Fri, 17 Jan 2020 at 15:30, Hameer Abbasi 
wrote:

> IMHO, masked arrays and extending masks like that is a weird API. I would
> prefer a more functional approach: Where we take in an input 1-D or N-D
> boolean array in addition to a masked array with multiple axes over which
> to extend the mask.
>
>
>
> *From: *NumPy-Discussion  gmail@python.org> on behalf of Eric Wieser <
> wieser.eric+nu...@gmail.com>
> *Reply to: *Discussion of Numerical Python 
> *Date: *Friday, 17. January 2020 at 11:40
> *To: *Discussion of Numerical Python 
> *Subject: *[Numpy-discussion] Adding an nd generalization of
> np.ma.mask_rowscols
>
>
>
> Today, numpy has a np.ma.mask_rowcols function, which stretches masks
> along
> the full length of an axis. For example, given the matrix::
>
> >>> a2d = np.zeros((3, 3), dtype=int)
>
> >>> a2d[1, 1] = 1
>
> >>> a2d = np.ma.masked_equal(a2d, 1)
>
> >>> print(a2d)
>
> [[0 0 0]
>
>  [0 -- 0]
>
>  [0 0 0]]
>
> The API allows::
>
> >>> print(np.ma.mask_rowcols(a2d, axis=0))
>
> [[0 0 0]
>
>  [-- -- --]
>
>  [0 0 0]]
>
>
>
> >>> print(np.ma.mask_rowcols(a2d, axis=1))
>
> [[0 -- 0]
>
>  [0 -- 0]
>
>  [0 -- 0]]
>
>
>
> >>> print(np.ma.mask_rowcols(a2d, axis=None))
>
> [[0 -- 0]
>
>  [-- -- --]
>
>  [0 -- 0]]
>
> However, this function only works for 2D arrays.
> It would be useful to generalize this to work on ND arrays as well.
>
> Unfortunately, the current function is messy to generalize, because axis=0
> means “spread the mask along axis 1”, and vice versa. Additionally, the
> name is not particularly good for an ND function.
>
> My proposal in PR 14998  is to
> introduce a new function, mask_extend_axis, which fixes this shortcoming.
> Given an 3D array::
>
> >>> a3d = np.zeros((2, 2, 2), dtype=int)
>
> >>> a3d[0, 0, 0] = 1
>
> >>> a3d = np.ma.masked_equal(a3d, 1)
>
> >>> print(a3d)
>
> [[[-- 0]
>
>   [0 0]]
>
>
>
>  [[0 0]
>
>   [0 0]]]
>
> This, in my opinion, has clearer axis semantics:
>
> >>> print(np.ma.mask_extend_axis(a2d, axis=0))
>
> [[[-- 0]
>
>   [0 0]]
>
>
>
>  [[-- 0]
>
>   [0 0]]]
>
>
>
> >>> print(np.ma.mask_extend_axis(a2d, axis=1))
>
> [[[-- 0]
>
>   [-- 0]]
>
>
>
>  [[0 0]
>
>   [0 0]]]
>
>
>
> >>> print(np.ma.mask_extend_axis(a2d, axis=2))
>
> [[[-- --]
>
>   [0 0]]
>
>
>
>  [[0 0]
>
>   [0 0]]]
>
> Stretching over multiple axes remains possible:
>
> >>> print(np.ma.mask_extend_axis(a2d, axis=(1, 2)))
>
> [[[-- --]
>
>   [-- 0]]
>
>
>
>  [[0 0]
>
>   [0 0]]]
>
>
>
> # extending sequentially is not the same as extending in parallel
>
> >>> print(np.ma.mask_extend_axis(np.ma.mask_extend_axis(a2d, axis=1), axis=2))
>
> [[[-- --]
>
>   [-- --]]
>
>
>
>  [[0 0]
>
>   [0 0]]]
>
> Questions for the mailing list then:
>
> · Can you think of a better name than mask_extend_axis?
>
> · Does my proposed meaning of axis make more sense to you than
> the one used by mask_rowcols?
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>
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