aspcore.fouriertransform

Functions

angular_freqs_to_wavenum(angular_freqs, c)	Converts an array of angular frequencies to wave numbers
convolve_euclidian_ff(freq_filter, freq_signal)	Convolves every channel of input with every channel of the filter
convolve_euclidian_ft(freq_filter, time_signal)	Convolves every channel of input with every channel of the filter
convolve_sum(freq_filter, time_signal)	Performs linear convolution between a time-domain signal and a frequency-domain filter
correlate_cartesian_tt(time_filter, time_signal)	Computes the linear correlation between two time-domain signals
correlate_euclidian_ff(freq_filter, freq_signal)	Correlates every channel of input with every channel of the filter
correlate_euclidian_ft(freq_filter, time_signal)	Correlates every channel of input with every channel of the filter
correlate_euclidian_tf(time_filter, freq_signal)	Correlates every channel of input with every channel of the filter
correlate_sum_ff(freq_filter, freq_signal)	Computes linear correlation between two frequency-domain signals
correlate_sum_ft(freq_filter, time_signal)	Computes linear correlation between a time-domain signal and a frequency-domain filter
correlate_sum_tf(time_filter, freq_signal)	Computes linear correlation between a frequency-domain signal and a time-domain filter
correlate_sum_tt(time_filter, time_signal)	Computes linear correlation between two time-domain signals
czt(time_sig, M[, w, a])	The Chirp-z Transform
czt_unit_circle(time_sig, M, w_angle, a_angle)	Chirp-z transform on the unit circle
dft_mat(dft_len)	DFT matrix corresponding to the real DFT.
dft_vector(freq_idx, dft_len)	All exponential values to calculate the DFT for a specific frequency bin
fft(time_sig[, n])	Computes the FFT
freqs_to_angular_freqs(freqs)	Converts an array of frequencies to angular frequencies
freqs_to_wavenum(freqs, c)	Converts an array of frequencies to wave numbers
get_angular_freqs(num_freq, samplerate)	Returns the angular frequencies associated with the sampled frequencies of the DFT
get_freqs(num_freq, samplerate)	Returns the sampled frequencies in Hz for a discrete Fourier transform
get_real_angular_freqs(num_freq, samplerate)	Returns angular frequencies associated with the real frequencies of the DFT
get_real_freqs(num_freq, samplerate)	Returns the real sampled frequencies in Hz for a discrete Fourier transform
get_real_wavenum(num_freq, samplerate, c)	Get wave numbers associated with the real frequencies of the DFT
get_wavenum(num_freq, samplerate, c)	Returns the wave numbers associated with the sampled frequencies of the DFT
iczt(freq_sig, N[, w, a])	The Inverse Chirp-z Transform
iczt_unit_circle(freq_sig, N, w_angle, a_angle)	Inverse Chirp-z transform on the unit circle
idft_vector(freq_idx, dft_len)	All exponential values to calculate the IDFT for a specific output time step
ifft(freq_signal)	Computes the inverse FFT
insert_negative_frequencies(freq_signal, even)	Inserts the values associated with negative frequencies.
irdft_mat(dft_len[, num_freqs_removed_low])	DFT matrix corresponding to the inverse real DFT.
irfft(freq_signal[, n, num_freqs_removed_low])	Inverse FFT, and moves the first axis to the last axis
rdft_mat(dft_len[, num_freqs_removed_low])	DFT matrix corresponding to the real DFT.
rdft_weighting(num_freqs, dft_len, ...)	The weighting required for the real DFT to be the same as the complex DFT.
rfft(time_sig[, n, num_freqs_removed_low])	Computes the real FFT
zoom_dft(time_sig, M, freq_limits, samplerate)	Zoom Discrte Fourier Transform
zoom_idft(freq_sig, N, freq_limits, samplerate)	Zoom Inverse Discrte Fourier Transform

Modules

chirp_z_transform	Methods for the chirp z transform
dft	Methods for discrete Fourier transform
frequencyfiltering	Methods for linear convolution and correlation in the frequency domain