Behavior of numpy max and argmax for dict_values
There are some questions for np.max, np.argmax, np.argmin.
I know dict implementation in python is some sort of hash table, but i think behavior of these functions cannot be called intuitive and can create some bugs.
Why do NumPy scalars multiply with custom sequences but not with lists?
I have a question to NumPy experts. Consider a NumPy scalar: c = np.arange(3.0).sum(). If I try to multiply it with a custom sequence like e.g.
Issue with installing wrf-python
i am not able to install wrf-python in linux. it always tells me that numpy module is not found however i have already installed numpy. can anyone help out.
Issue with installing wrf-python
i am not able to install wrf-python in linux. it always tells me that numpy module is not found however i have already installed numpy. can anyone help out.
How does numpy.polyfit return a slope and y-intercept when its documentation says it returns otherwise?
I have seen examples where slope, yintercept = numpy.polyfit(x,y,1) is used to return slope and y-intercept, but the documentation does not mention “slope” or “intercept” anywhere.
How can I get the subarray indicies of a binary array using numpy?
I have an array that looks like this
How can I get the subarray indicies of a binary array using numpy?
I have an array that looks like this
Numpy: Sum N successive array elements, where N comes from a list
Here is code I am trying to optimize:
Python numpy, math: Any way raising a negative number to a decimal power without resulting in Nan?
I am getting errors trying to raise a negative number to a decimal power. For example, I want to calculate this
(-2)^(4.8) which should result in valid, real number output (27.85 from my TI-89).
numpy get mask of false positive from given two vectors of y_true and y_pred
Given three classes (5,6,7) of two arrays: