First thing is to remember that python uses zero indexing. You can iterate throught the list except using the range function to get the indexes of the items you want or slices to get the elements. What I think is becoming confusing here is that in your example, the values and the indexes are the … Read more
Code: Console: System Info: OS X El Capitan, Macbook Air, 1.3 GHz Intel Core i5, 8 GB 1600 HMz DDR3 I have already attempted updating numpy. I had to add cv.py to the python2.7 folder in Spyder-Py2 is there something else I need to add?
(It is possible that my interpretation of the question is wrong. If the question is how to get from a discrete PDF into a discrete CDF, then np.cumsum divided by a suitable constant will do if the samples are equispaced. If the array is not equispaced, then np.cumsum of the array multiplied by the distances between the points will … Read more
That’s the warning you get when you try to evaluate log with 0: I agree it’s not very clear. So in your case, I would check why your input to log is 0. PS: this is on numpy 1.10.4
UPDATE: more efficient solutions have been proposed, uniform_filter1d from scipy being probably the best among the “standard” 3rd-party libraries, and some newer or specialized libraries are available too. You can use np.convolve for that: Explanation The running mean is a case of the mathematical operation of convolution. For the running mean, you slide a window along the input and compute the mean of … Read more
You can always take a look at the .size attribute. It is defined as an integer, and is zero (0) when there are no elements in the array:
They are the same number. What differs is their representation; the Python native type uses a “sane” representation, and the NumPy type uses an accurate representation.
Give np.ix_ a try: This returns your desired result:
Does Numpy/Python automatically detect the presence of GPU and utilize it to speed up matrix computation (e.g. numpy.multiply, numpy.linalg.inv, … etc)? No. Or do I have code in a specific way to exploit the GPU for fast computation? Yes. Search for Numba, CuPy, Theano, PyTorch or PyCUDA for different paradigms for accelerating Python with GPUs.
This question already has answers here: How to normalize a NumPy array to a unit vector? (13 answers) Closed 3 years ago. Lets say I have a vector v, and I want the unit vector, i.e. v has length 1.0 Is there a direct way to get that from numpy? I want something like: Rather … Read more