I’m trying to translate some Matlab code into Python (using NumPy). I’m not very familiar with Matlab, and I’ve encountered a line that I’m having trouble parsing: I’d hazard a guess that a p-long head of x is being used as indices to select p entries of w, and that those entries in w are being replaced by corresponding entries
Tag: numpy
UserWarning: converting a masked element to nan
Executing a python script (way to long to include here) I wrote leads to a warning message. I don’t know at which line in my code this gets raised. How can I get this information? Furthermore, what does this mean exactly? In fact, I didn’t know I was using a masked array of some sort? Answer You can use the
Correct way to generate random numbers in Cython?
What is the most efficient and portable way to generate a random random in [0,1] in Cython? One approach is to use INT_MAX and rand() from the C library: Is it OK to use INT_MAX in this way? I noticed that it’s quite different from the constant you get from Python’s max int: yields: Which is the right “normalization” number
AttributeError: ‘module’ object has no attribute ‘percentile’
I use this function to calculate percentile from here: But I get this error : I also tried but it didn’t I got the same error. my numpy version is 1.3.0 I tried to upgrade but it seems like it won’t I used : [sudo pip install –upgrade scipy][2] but I found that there’s no upgrade. my ubuntu version 9.10
Averaging over every n elements of a numpy array
I have a numpy array. I want to create a new array which is the average over every consecutive triplet of elements. So the new array will be a third of the size as the original. As an example: should return the array: Can anyone suggest an efficient way of doing this? I’m drawing blanks. Answer If your array arr
Reversed array in numpy?
Numpy tentative tutorial suggests that a[ : :-1] is a reversed a. Can someone explain me how we got there? I understand that a[:] means for each element of a (with axis=0). Next : should denote the number of elements to skip (or period) from my understanding. Answer As others have noted, this is a python slicing technique, and numpy
Sliding window of M-by-N shape numpy.ndarray
I have a Numpy array of shape (6,2): I need a sliding window with step size 1 and window size 3 like this: I’m looking for a Numpy solution. If your solution could parametrise the shape of the original array as well as the window size and step size, that’d be great. I found this related answer Using strides for
Creating your own contour in opencv using python
I have a set of boundary points of an object. I want to draw it using opencv as contour. I have no idea that how to convert my points to contour representation. To the same contour representation which is obtained by following call Any ideas? Thanks Answer By looking at the format of the contours I would think something like
Is it possible to create a numpy.ndarray that holds complex integers?
I would like to create numpy.ndarray objects that hold complex integer values in them. NumPy does have complex support built-in, but for floating-point formats (float and double) only; I can create an ndarray with dtype=’cfloat’, for example, but there is no analogous dtype=’cint16′. I would like to be able to create arrays that hold complex values represented using either 8-
Check if variable is defined with Numpy array?
Sometimes I have a situation where I want to test whether a variable is 0 or None or not. In pure Python, this is simply but when foo is possibly a Numpy object (such as numpy.ndarray), this does not work anymore and I get the error: and in this case I want a.any(), however this fails on non-iterable objects. Of