I noticed that the dask FFT wrapper internally uses numpy 's FFT. Unless this is done to avoid a scipy dependency, I'd suggest switching to scipy.fft (not scipy.fftpack, which is now legacy) instead.

FFT benchmarks for NumPy* and SciPy* This FFF benchmarking framework is useful to measure FFT performance of different NumPy and SciPy versions and vendors. In addition to Python implementation we ...

[153Armstrong] did a short post on how easy it is to generate waveforms using Python. We agree it is simple, but actually, it isn’t so much Python per se, it is some pretty cool libraries (SciPy ...

Fortunately, the NumPy and SciPy modules are a popular and effective way to greatly improve the performance of Python for numerical computing. This course aims to introduce the basic features of the ...

Fortunately, the NumPy and SciPy modules are a popular and effective way to greatly improve the performance of Python for numerical computing. In this course you will learn to use the basics of the ...

Book Description Python has tremendous potential within the scientific computing domain. This updated edition of Scientific Computing with Python features new chapters on graphical user interfaces, ...

The sparse module of the popular SciPy Python library is widely used across applications in scientific computing, data analysis and machine learning. The standard implementation of SciPy is restricted ...