One simple method would be to assign the default value first and then perform 2 loc calls: If you wanted to use np.where then you could do it with a nested np.where: So here we define the first condition as where x is less than -2, return 1, then we have another np.where which tests the other condition where x is greater … Read more
Although using virtual environment is advisable in many use-cases, it is not strictly required. You can have a system python3.5 and a pip installation associated with it. Note that Python 3.5 is now end-of-life and pip has now dropped support. The final version of pip supporting Python 3.5 was 20.3.4 (Jan 2021). Download this file: pip-20.3.4-py2.py3-none-any.whl Bootstrap a pip installation using the wheel … Read more
It looks like you’re trying to extend a list with a scalar float variable. The argument to extend must be an iterable (i.e. not a float). From your first bit of code it looks like means[i][j][k] returns a float, The problem is here, If you expect that means[i][j][k] will always be a single value and not a list you … Read more
Summary The following tests are meant to give some insights into the different approaches and should be taken with a grain of salt. What is being tested here is not exactly generic filtering, but rather just applying a threshold, which has the notable feature that computing the condition is pretty fast. Very different results would … Read more
It’s working exactly as it’s supposed to. The transpose of a 1D array is still a 1D array! (If you’re used to matlab, it fundamentally doesn’t have a concept of a 1D array. Matlab’s “1D” arrays are 2D.) If you want to turn your 1D vector into a 2D array and then transpose it, just slice it with np.newaxis (or None, they’re … Read more
I am assuming you have a 3-layer NN with W1, b1 for is associated with the linear transformation from input layer to hidden layer and W2, b2 is associated with linear transformation from hidden layer to output layer. Z1 and Z2 are the input vector to the hidden layer and output layer. a1 and a2 represents the output of the hidden layer and output layer. a2 is your predicted output. delta3 and delta2 are the … Read more
When you specify the array x and X you need to make sure it is of complex data type, i.e: EDIT: To fix the plot you need to plot both real and imaginary parts: This gives me: ….which looks like your Matlab graph.
I am using Python 3.6b3 for a long running project, developing on Windows. For this project I also need NumPy. I’ve tried Python36 -m pip install numpy, but it seems that pip is not yet in the beta. What’s the best way to install NumPy for Python 3.6b3? [EDIT: Added installation log, after using ensurepip]
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
Seems like this is due to pandas version higher than 0.21.0 and numpy version 1.13.3 that is pulled by TensorFlow not playing well together. Here is how I fixed it in my end: