Can't seem to use np.insert() or np.append() for structured arrays
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 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
On Fri, Aug 29, 2014 at 8:10 PM, Benjamin Root <ben.root@ou.edu> 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
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?
Could be one of many bug reports related to assignment to structured types. Can you try using `x`? In [25]: x = array([(4, 'd')], dt)[0] In [26]: type(x) Out[26]: numpy.void In [27]: x Out[27]: (4, 'd') Chuck
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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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
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
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Benjamin Root -
Charles R Harris -
Sebastian Berg