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Tag: arrays

How to make the elements of a NumPy array property settable?

I have a property of a Python object that returns an array. Now, I can set the setter of that property such that the whole array is settable. However, I’m missing how to make the elements by themselves settable through the property. I would expect from a user perspective (given an empty SomeClass class): Now, suppose that SomeClass.array is a

Test if an array is broadcastable to a shape?

What is the best way to test whether an array can be broadcast to a given shape? The “pythonic” approach of trying doesn’t work for my case, because the intent is to have lazy evaluation of the operation. I’m asking how to implement is_broadcastable below: or better yet: Answer I really think you guys are over thinking this, why not

numpy genfromtxt collapse recarray when data file has only one row

I am using genfromtxt function to read data from a csv file. Then I can access the array columns with e.g.: which then returns a 1-dimensional vector. Only when the source file has exactly one data row, the array is collapsed – its shape==() and therefore the vector returned by data[“My column name”] is not a vector but just a

Pop multiple items from the beginning and end of a list

Suppose I have a list of items like this: I want to pop two items from the left (i.e. a and b) and two items from the right (i.e. h,i). I want the most concise an clean way to do this. I could do it this way myself: Any other alternatives? Answer From a performance point of view: mylist =

All possible points of (latitude,longitude) from latitude/longitude coordinates in separate arrays

I have latitude and longitude coordinates in two separate arrays: How can I easily find all possible points made up of these coordinates? I’ve been messing around with itertools.combinations: but this doesn’t work for me because the points (71,75) and (43,42) are latitude/latitude and longitude/longitude pairs. What I would like to have is this: The a and b arrays will

Force NumPy ndarray to take ownership of its memory in Cython

Following this answer to “Can I force a numpy ndarray to take ownership of its memory?” I attempted to use the Python C API function PyArray_ENABLEFLAGS through Cython’s NumPy wrapper and found it is not exposed. The following attempt to expose it manually (this is just a minimum example reproducing the failure) fails with a compile error: My question: Is

Remove rows in 3D numpy array

I need to remove some rows from a 3D numpy array. For exampe: and I want to remove the third row of both pages of the matrix in order to obtain something like: I have tried with but I can’t obtain what I need. Answer axis should 1.

unexpected result in numpy array slicing (view vs copy)

I’m trying to reduce the amount of copying in my code and I came across surprising behavior when dealing with numpy array slicing and views, as explained in: Scipy wiki page on copying numpy arrays I’ve stumbled across the following behavior, which is unexpected for me: Case 1.: As expected, this outputs: Case 2: When performing the slicing and addition

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