[ot][spam][random][crazy][random][crazy]

[Undescribed Horrific Abuse, One Victim & Survivor of Many]

here is my draft. to test it, i should give a full range and verify
it's the same as the fft.

def micro_ft(time_data, max_period):
    N = time_data.shape[-1]
    # for the highest frequencies, we can still probably do k * n / N
    # but rather than starting at k = 0, we'll want to start at the
minimum, and have
    # fractional k's prior to that.
        # max_period is number of samples
        # k is calculable from it
    min_k = N / max_period
    k = np.linspace(min_k / N, 1, N)
    n = np.arange(N)
    # freq[k] = sum_over_n(time[n] * exp(-2 * pi * i * k * n / N))
    return time_data * np.exp(-2j * np.pi * k * n)

def micro_ift(freq_data, max_period):
    N = time_data.shape[-1]
    min_k = N / max_period
    k = np.linspace(min_k / N, 1, N)
    n = np.arange(N)
    # time[n] = sum_over_k(freq[k] * exp(2 * pi * i * k * n / N))
    return freq_data * exp(2j * np.pi * k * n)