NumPy chained comparison with two predicates
In NumPy, I can generate a boolean array like this:
numpy
Preserve custom attributes when pickling subclass of numpy array
I’ve created a subclass of numpy ndarray following the numpy documentation. In particular, I have added a custom attribute by modifying the code provided.
Searching a sequence in a NumPy array
Let’s say I have the following array :
Creating cx_Freeze exe with Numpy for Python
Im trying to create a basic exe using cx_Freeze. It works for .py programs that don’t have numpy but I can’t get one made correctly with numpy.
Numpy Two-Dimensional Moving Average
I have a 2d numpy array. I want to take the average value of the n nearest entries to each entry, just like taking a sliding average over a one-dimensional array. What is the cleanest way to do this?
Numpy Pure Functions for performance, caching
I’m writing some moderately performance critical code in numpy.
This code will be in the inner most loop, of a computation that’s run time is measured in hours.
A quick calculation suggest that this code will be executed up something like 10^12 times, in some variations of the calculation.
numpy.array.__iadd__ and repeated indices
at(a, indices, b=None)
python recursive vectorization with timeseries
I have a Timeseries (s) which need to be processed recursively to get a timeseries result (res). Here is my sample code:
fitting data with numpy
Let me start by telling that what I get may not be what I expect and perhaps you can help me here. I have the following data:
Formatting floats in a numpy array
If I have a numpy array like this: [2.15295647e+01, 8.12531501e+00, 3.97113829e+00, 1.00777250e+01] how can I move the decimal point and format the numbers so I end up with a numpy array like this: [21.53, 8.13, 3.97, 10.08] np.around(a, decimals=2) only gives me [2.15300000e+01, 8.13000000e+00, 3.97000000e+00, 1.00800000e+01] Which I don’t want and I haven’t found another … Read more