The numpy.load routine is for loading pickled .npy or .npz binary files, which can be created using numpy.save and numpy.savez, respectively. Since you have text data, these are not the routines you want. You can load your comma-separated values with numpy.loadtxt. Full Example Here’s a complete example (using StringIO to simulate the file I/O). Now we have:
It sounds like you have three arrays itemNameList, array_x, and array_y Assuming they are all the same shape, you can just do: EDIT Your problem is that array_x and array_y are not actual numpy.array objects, but likely numpy.int32 (or some other non-iterable) objects: Perhaps their initialization is not going as expected, or they are being changed from arrays somewhere in your code?
After opening up an issue with the SciPy team, we found that you need to upgrade pip with: And in Python 3 this works: for SciPy to install properly. Why? Because: Older versions of pip have to be told to use wheels, IIRC with –use-wheel. Or you can upgrade pip itself, then it should pick … Read more
Download it from here. I’m not sure about that site you referred to, but I always start at: http://www.scipy.org
176 @steve‘s answer is actually the most elegant way of doing it. For the “correct” way see the order keyword argument of numpy.ndarray.sort However, you’ll need to view your array as an array with fields (a structured array). The “correct” way is quite ugly if you didn’t initially define your array with fields… As a … Read more
Yeah, you can install opencv (this is a library used for image processing, and computer vision), and use the cv2.resize function. And for instance use: Here img is thus a numpy array containing the original image, whereas res is a numpy array containing the resized image. An important aspect is the interpolation parameter: there are … Read more
Using /= and *= allows you to eliminate an intermediate temporary array, thus saving some memory. Multiplication is less expensive than division, so is marginally faster than Since we are using basic numpy methods here, I think this is about as efficient a solution in numpy as can be. In-place operations do not change the … Read more
If you look at the line which is causing the error, you’ll see this: This line comment states the dependency as numpy+mkl (numpy with Intel Math Kernel Library). This means that you’ve installed the numpy by pip, but the scipy was installed by precompiled archive, which expects numpy+mkl. This problem can be easy solved by installation for numpy+mkl from whl file from here.
you can calculate like this way.
I’m going to assume that you want to compute the expression given by the following pseudocode: i.e. the square root of the mean of the squared values of elements of y. In numpy, you can simply square y, take its mean and then its square root as follows: So, for example: Do clarify your question … Read more