import numpy as np


def synthesize_note_dynamics(note_on, duration, amplitude, sr=22050):
    v = np.zeros(round((duration + note_on + 1.0) * sr))
    for itr in range(len(v)):
        t = itr / sr

        if t >= note_on and t < note_on + 1.25:
            amp_attack = np.cos(((t - note_on) / 1.25) * (np.pi / 2.0)) * 0.4 + 0.6
        else:
            amp_attack = 0.0

        if t > note_on + 1.25:
            amp_decay = 0.6 + (np.exp(-(t - (note_on + 1.25)) / (duration - 1.25)) - 1.0) * 0.175
        else:
            amp_decay = 0.0

        if t >= note_on - 0.015 and t < note_on + 0.005:
            amp_spike1 = (1.0 - abs((t - (note_on - 0.005)) / 0.01)) / 4.0
        else:
            amp_spike1 = 0.0

        # Note: There is also a fade of about 33% that occurs near the end that lasts about 100ms.
        #       The rest of the fade is handled by an articulation from phoneme to silence.
        #       The fade is not modeled here since its time depends on the length of that articulation.

        v[itr] = (amp_spike1 + amp_attack + amp_decay) * amplitude

    return v

# In cents/log-scale
# XXX: Special case for very large legato, >1 ocatve
def synthesize_legato(start_time, duration, start_pitch, end_pitch, sr=22050):
    v = np.zeros(round((duration + start_time + 1.0) * sr))
    for itr in range(len(v)):
        t = itr / sr
        if t >= start_time and t < start_time + duration:
            if end_pitch >= start_pitch:
                v[itr] = start_pitch + (end_pitch - start_pitch) * (((t - start_time) / duration) ** 0.8)
            else:
                v[itr] = end_pitch + (start_pitch - end_pitch) * ((1.0 - (t - start_time) / duration) ** 1.5)
        elif t < start_time:
            v[itr] = start_pitch
        else:
            v[itr] = end_pitch

    return v