Hi,
I noticed a typechecking inconsistency between assignments using slicing and fancyindexing. The first will happily cast on assignment (regardless of type), while the second will throw a type error if there's reason to believe the casting will be unsafe. I'm not sure which would be the "correct" behavior, but the inconsistency is surprising.
Best, Tony
Example:
import numpy as np a = np.arange(10) b = np.ones(10, dtype=np.uint8)
# this runs without error
b[:5] = a[:5]
mask = a < 5 b[mask] = b[mask]
TypeError: array cannot be safely cast to required type
On Sun, Oct 16, 2011 at 12:39 PM, Tony Yu tsyu80@gmail.com wrote:
Hi,
I noticed a typechecking inconsistency between assignments using slicing and fancyindexing. The first will happily cast on assignment (regardless of type), while the second will throw a type error if there's reason to believe the casting will be unsafe. I'm not sure which would be the "correct" behavior, but the inconsistency is surprising.
Best, Tony
Example:
import numpy as np a = np.arange(10) b = np.ones(10, dtype=np.uint8)
# this runs without error
b[:5] = a[:5]
mask = a < 5 b[mask] = b[mask]
TypeError: array cannot be safely cast to required type
And I just noticed that 1D arrays behave differently than 2D arrays. If you
replace the above definitions of a, b with:
a = np.arange(10)[:, np.newaxis] b = np.ones((10, 1), dtype=np.uint8)
The rest of the code will run without error.
(16.10.2011 18:39), Tony Yu wrote:
import numpy as np a = np.arange(10) b = np.ones(10, dtype=np.uint8)
# this runs without error
b[:5] = a[:5]
mask = a < 5 b[mask] = b[mask]
TypeError: array cannot be safely cast to required type
Seems to be fixed in Git master
import numpy as np a = np.arange(10) b = np.ones(10, dtype=np.uint8) mask = a < 5 b[mask] = b[mask] b[mask] = a[mask] np.__version__
'2.0.0.dev1dc1877'
On Sun, Oct 16, 2011 at 12:49 PM, Pauli Virtanen pav@iki.fi wrote:
(16.10.2011 18:39), Tony Yu wrote:
import numpy as np a = np.arange(10) b = np.ones(10, dtype=np.uint8)
# this runs without error
b[:5] = a[:5]
mask = a < 5 b[mask] = b[mask]
TypeError: array cannot be safely cast to required type
Seems to be fixed in Git master
import numpy as np a = np.arange(10) b = np.ones(10, dtype=np.uint8) mask = a < 5 b[mask] = b[mask] b[mask] = a[mask] np.__version__
'2.0.0.dev1dc1877'
(I see you noticed the typo in my original example: b > a). Agreed, I'm getting this error with an old master. I just tried master and it worked fine, but the maintenance branch ('1.6.2.dev396dbb9') does still have this issue.
On Sun, Oct 16, 2011 at 11:02 AM, Tony Yu tsyu80@gmail.com wrote:
On Sun, Oct 16, 2011 at 12:49 PM, Pauli Virtanen pav@iki.fi wrote:
(16.10.2011 18:39), Tony Yu wrote:
import numpy as np a = np.arange(10) b = np.ones(10, dtype=np.uint8)
# this runs without error
b[:5] = a[:5]
mask = a < 5 b[mask] = b[mask]
TypeError: array cannot be safely cast to required type
Seems to be fixed in Git master
import numpy as np a = np.arange(10) b = np.ones(10, dtype=np.uint8) mask = a < 5 b[mask] = b[mask] b[mask] = a[mask] np.__version__
'2.0.0.dev1dc1877'
(I see you noticed the typo in my original example: b > a). Agreed, I'm getting this error with an old master. I just tried master and it worked fine, but the maintenance branch ('1.6.2.dev396dbb9') does still have this issue.
1.6.2 hasn't been kept up to date. I suspect 1.7.0 will be the next release.
Chuck
participants (3)

Charles R Harris

Pauli Virtanen

Tony Yu