Asking for code reviews is ok as long as you. Make sure you also include the exact command if possible to produce the output included in your test case. If you are unclear what to include see the issue template displayed in. The implementation is essentially a for loop. Do not link to some intermediary page that contains mostly only a link to the actual page and no additional value. Disagreement and technical critiques are ok, but personal attacks are not. Do not include a link to a final product or to a demo in your post.
Read our and search old posts before asking your question. There may be a bit annoyance with object arrays, where you never do this for item assignment, since you assume that the array should be the object. . That'd at least give us some data to discuss. If you got an error, include the full error message.
In general, if you want to apply a function that accepts a single element to every element in an array, you can use : import numpy as np import matplotlib. A look at the latest documentation of , allow us to see the signature of the : virtual bool cv::ml::StatModel::train InputArray samples, int layout, InputArray responses Apparently, a new layout argument was added. Have a question about this project? Communicate to others the same way you would at your workplace. The next step would be to try making the change and see how much stuff breaks e. Asking conceptual questions Many conceptual questions have already been asked and answered. But… I expect there are some annoying cases to solve and it might have a pretty large downstream impact which would make it a very slow change indeed I am not sure, I think I might have tried it at some time way back, heh. Also, did you compile from source or install a binary? Questions that straddle the line between learning programming and learning other tech topics are ok: we don't expect beginners to know how exactly to categorize their question.
This probably constitutes a roadblock for the suggested change. Always cut and paste the complete traceback. You are trying to convert an array basically just a list into an int. Again, debugging becomes easier if you make your script self- contained, e. As another pain point, this behavior is a tad confusing when combined with pybind11, where you can define overloads.
Eric, hehe, that should succeed, but without checking I am not actually sure anymore if it sidesteps and just does item assignment currently, though I doubt it. For example, linking to some tweet or some half-hearted blog post which links to the page is not ok; but linking to a tweet with interesting replies or to a blog post that does some extra analysis is. Also include your TensorFlow version. Since my answer was not as clean as ayhan's, I thought I'd use this space to show that this is another such instance to illustrate that vectorize is around 10% slower than building a list in Python. But that wouldn't even have to change.
We ask for this in the issue submission template, because it is really difficult to help without that information. Also, I cannot run your script as it relies upon data that you don't provide. I will file a pybind11 issue as well, with a workaround that is specific to pybind11, but it would have been nice if NumPy were a tad more strict on how it treats scalars vs. If you look at the call signature of np. Not sure if there is more, but if it is the main point, it should not be all that bad…. There is this section of code which throws an error.
Making them write it this way eliminates a class of bug, which is exactly what we should be aiming to do with DeprecationWarnings Whether reverse broadcasting is actually desirable is also perhaps questionable, but you've made it clear to me that it's an orthogonal issue. When in doubt, message the mods and ask them to review your post. I originally ran into this when writing a custom dtype, but found this was the behavior for floats too. This includes piracy: asking for or posting links to pirated material is strictly forbidden and can result in an instant and permanent ban. You could do this, but it's not a purely-numpy solution. Instead of recommending to insert. So one of the arguments passed to call model.
But it's is a little obscure from the documentation. See our for more details. There may be a bit annoyance with object arrays I think that collectively, we've hit the nail on the head there - reverse broadcasting has no place in scalar assignments, because it just doesn't generalize to object arrays. Abusive, racist, or derogatory comments are absolutely not tolerated. I've adapted to original post to reflect the fact that arrays of larger rank can be converted to floats as well. In particular, it is not appropriate to offer a reward, bounty, or bribe to try and expedite answers to your question, nor is it appropriate to offer to pay somebody to do your work or homework for you.
The problem with these things is that often you only know how bad this kind of change is for downstream until they start seriously using it. Sign up for a free GitHub account to open an issue and contact its maintainers and the community. Do not suggest or help somebody do something illegal or unethical. In short, link to only your code and be specific about what you want feedback on. Have a question about this project? This overload behavior makes things great when you want to distinguish between int and float overloads, but it makes things painful when NumPy can implicitly convert its arrays to scalars, but lists themselves to do not get collapsed to scalars.
By retyping the error message or omitting the traceback you are stripping off information that is valuable for debugging your problem. In replacing it with the proper expressions, I've even discovered a small bug in scipy. Personally agree with you there is a reason we got rid of the operator. See our for more details. I understand that it can be painful to deprecate stuff, particularly if its not clear how much a functionality is actually used downstream. Distinguishing between tasteless and tasteful self-promotion is inherently subjective.