numpyirfft

numpy.irfft is a function in the NumPy library that computes the inverse of a discrete Fourier Transform for real input. This means it takes a sequence of Fourier coefficients, which represent the frequency components of a signal, and reconstructs the original real-valued signal. The function assumes that the input is the result of an rfft (real-valued discrete Fourier Transform) and efficiently computes the inverse.

The primary use of numpy.irfft is in signal processing and data analysis where a signal's frequency domain representation is often more convenient for analysis or manipulation. After performing operations in the frequency domain using rfft, irfft is used to transform the data back into the time or spatial domain for interpretation or further processing.

The function takes the array of FFT coefficients as its main argument. It also accepts optional arguments such as `n` to specify the expected length of the output signal and `axis` to indicate along which axis the inverse FFT should be performed. By default, it infers the output length from the input array's shape. The output of numpy.irfft is a real-valued array, consistent with the assumption that the original signal was real. This makes it a crucial counterpart to numpy.rfft for working with real-valued signals in the Fourier domain.