Re: [Numpy-discussion] Can't seem to use np.insert() or np.append() for structured arrays
On Fr, 2014-08-29 at 22:10 -0400, Benjamin Root wrote:
Consider the following:
a = np.array([(1, 'a'), (2, 'b'), (3, 'c')], dtype=[('foo', 'i'),
('bar', 'a1')])
b = np.append(a, (4, 'd'))
Traceback (most recent call last):
File stdin, line 1, in module
File
/home/ben/miniconda/lib/python2.7/site-packages/numpy/lib/function_base.py,
line 3555, in append
return concatenate((arr, values), axis=axis)
TypeError: invalid type promotion
b = np.insert(a, 4, (4, 'd'))
Traceback (most recent call last):
File stdin, line 1, in module
File
/home/ben/miniconda/lib/python2.7/site-packages/numpy/lib/function_base.py,
line 3464, in insert
new[slobj] = values
ValueError: could not convert string to float: d
Ooops, nice bug in there, might have been me :) (will open a PR).
- Sebastian
In my original code snippet I was developing which has a more involved
dtype, I actually got a different exception:
b = np.append(a, c)
Traceback (most recent call last):
File stdin, line 1, in module
File
/home/ben/miniconda/lib/python2.7/site-packages/numpy/lib/function_base.py,
line 3553, in append
values = ravel(values)
File
/home/ben/miniconda/lib/python2.7/site-packages/numpy/core/fromnumeric.py,
line 1367, in ravel
return asarray(a).ravel(order)
File
/home/ben/miniconda/lib/python2.7/site-packages/numpy/core/numeric.py, line
460, in asarray
return array(a, dtype, copy=False, order=order)
ValueError: setting an array element with a sequence.
Luckily, this works as a work-around:
b = np.append(a, np.array([(4, 'd')], dtype=a.dtype))
b
array([(1, 'a'), (2, 'b'), (3, 'c'), (4, 'd')],
dtype=[('foo', 'i'), ('bar', 'S1')])
The same happens whether I enclose the value with square bracket or
not. I suspect that this array type just wasn't considered when its
checking logic was developed. This is with 1.8.2 from miniconda.
Should we consider this a bug or are structured arrays just not
expected to be modified like this?
Cheers!
Ben Root
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Re: [Numpy-discussion] Can't seem to use np.insert() or np.append() for structured arrays
On Sa, 2014-08-30 at 09:04 +0100, Sebastian Berg wrote:
On Fr, 2014-08-29 at 22:10 -0400, Benjamin Root wrote:
Consider the following:
a = np.array([(1, 'a'), (2, 'b'), (3, 'c')], dtype=[('foo', 'i'),
('bar', 'a1')])
b = np.append(a, (4, 'd'))
Traceback (most recent call last):
File stdin, line 1, in module
File
/home/ben/miniconda/lib/python2.7/site-packages/numpy/lib/function_base.py,
line 3555, in append
return concatenate((arr, values), axis=axis)
TypeError: invalid type promotion
b = np.insert(a, 4, (4, 'd'))
Traceback (most recent call last):
File stdin, line 1, in module
File
/home/ben/miniconda/lib/python2.7/site-packages/numpy/lib/function_base.py,
line 3464, in insert
new[slobj] = values
ValueError: could not convert string to float: d
Actually, for insert it is easy to fix
(https://github.com/numpy/numpy/pull/5022), for append there are some
difficulties, because the dtype is not forced to be the arrays dtype,
but gotten from both the original and the appended value currently.
- Sebastian
Ooops, nice bug in there, might have been me :) (will open a PR).
- Sebastian
In my original code snippet I was developing which has a more involved
dtype, I actually got a different exception:
b = np.append(a, c)
Traceback (most recent call last):
File stdin, line 1, in module
File
/home/ben/miniconda/lib/python2.7/site-packages/numpy/lib/function_base.py,
line 3553, in append
values = ravel(values)
File
/home/ben/miniconda/lib/python2.7/site-packages/numpy/core/fromnumeric.py,
line 1367, in ravel
return asarray(a).ravel(order)
File
/home/ben/miniconda/lib/python2.7/site-packages/numpy/core/numeric.py,
line 460, in asarray
return array(a, dtype, copy=False, order=order)
ValueError: setting an array element with a sequence.
Luckily, this works as a work-around:
b = np.append(a, np.array([(4, 'd')], dtype=a.dtype))
b
array([(1, 'a'), (2, 'b'), (3, 'c'), (4, 'd')],
dtype=[('foo', 'i'), ('bar', 'S1')])
The same happens whether I enclose the value with square bracket or
not. I suspect that this array type just wasn't considered when its
checking logic was developed. This is with 1.8.2 from miniconda.
Should we consider this a bug or are structured arrays just not
expected to be modified like this?
Cheers!
Ben Root
___
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http://mail.scipy.org/mailman/listinfo/numpy-discussion
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http://mail.scipy.org/mailman/listinfo/numpy-discussion
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Re: [Numpy-discussion] inplace unary operations?
On Sat, Aug 30, 2014 at 6:43 PM, josef.p...@gmail.com wrote: Is there a way to negate a boolean, or to change the sign of a float inplace ? np.logical_not(arr, out=arr) np.negative(arr, out=arr) -n -- Nathaniel J. Smith Postdoctoral researcher - Informatics - University of Edinburgh http://vorpus.org ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] inplace unary operations?
Random thoughts are the best kinds of thoughts! I didn't even know there was a np.negative() function! I will keep this card up my sleeve at work for one of those save-the-day moments in optimization. Cheers! Ben Root On Sat, Aug 30, 2014 at 1:45 PM, Nathaniel Smith n...@pobox.com wrote: On Sat, Aug 30, 2014 at 6:43 PM, josef.p...@gmail.com wrote: Is there a way to negate a boolean, or to change the sign of a float inplace ? np.logical_not(arr, out=arr) np.negative(arr, out=arr) -n -- Nathaniel J. Smith Postdoctoral researcher - Informatics - University of Edinburgh http://vorpus.org ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] inplace unary operations?
On Sat, Aug 30, 2014 at 7:39 PM, Benjamin Root ben.r...@ou.edu wrote: Random thoughts are the best kinds of thoughts! I didn't even know there was a np.negative() function! Me neither, I had to look it up :-) -n -- Nathaniel J. Smith Postdoctoral researcher - Informatics - University of Edinburgh http://vorpus.org ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
