A visualization library for the Löve framework.
Supports 0.10.2 and the yet-unreleased 0.11 nightlies.
v0.0.0 - May work, but not "officially" released.
Note that these names were chosen to hopefully minimize the gigantic overlap that exists in music/audio/dsp terminology.
Fractional dimensional values mean that one dimension is "folded", i.e. it's not represented by a spatial axis.
Rarity is a somewhat ad-hoc value, relative to my own experiences with music players and DAW software, whether or not they included a specific type of visualizer.
1 Dimensional: A(t)
A(t): Signal amplitude at a moment in time.
Common
One of the most basic types of visualizers.
1 Dimensional: φ(t)
φ(t): Signal phase at a moment in time.
Rare
It's more common to use Wave Scope equivalents if one wants to see the phase of the signal.
1.5 Dimensional: C(t)/t
C(t): Spectral centroid of signal at a moment in time.
t: Time.
Uncommon
The first dimension is folded into the properities (e.g. color) of the data points.
The music player Amarok supports this type of visualization.
1.5 Dimensional: A(t)/t
A(t): Signal amplitude at a moment in time.
t: Time.
Uncommon
The first dimension is folded into the properities (e.g. color) of the data points, and that the second dimension is actually the distance from a specified "center", since this is actually a polar visualizer.
The DOS module player "XTC-PLAY" includes this type of visualization.
2 Dimensional: A(t)/t
A(t): Signal amplitude at a moment in time.
t: Time.
Rare
It's more common to see either Wave Scopes or Level Meters instead.
2 Dimensional: φ(t)/t
φ(t): Signal phase at a moment in time.
t: Time.
Common
One of the most basic types of visualizers.
2 Dimensional: A(F(i,t))/F(i)
A(F(i,t)): Amplitude of frequency bins/bands at a moment in time.
F(i): Frequency bins/bands.
Common
One of the most basic types of visualizers.
2 Dimensional: φ(F(i,t))/F(i)
φ(F(i,t)): Phase of frequency bins/bands at a moment in time.
F(i): Frequency bins/bands.
Rare
Freq Scope equivalents either discard the complex values, or actually do a Real-only FFT to get the frequency data used in them; this one shows both.
2 Dimensional: φ(t)/φ'(t)
φ(t): Signal phase at a moment in time.
φ'(t): First derivative (slope) of signal phase at a moment in time.
Uncommon
2 Dimensional: φ(L(t))/φ(R(t))
φ(L(t)): Signal phase of left channel at a moment in time.
φ(R(t)): Signal phase of right channel at a moment in time.
Common
2 Dimensional: φ(Re(F(i,t)))/φ(Im(F(i,t)))
φ(Re(F(i,t))): Phase of the real part of frequency bins/bands at a moment in time.
φ(Im(F(i,t))): Phase of the imaginary part of frequency bins/bands at a moment in time.
Rare
I personally never seen this type of visualization used in either music players or DAWs before, though it is known as an example of how a more complex waveform can be built up from multiple sine waves; this is just the inverse of that.
2.5 Dimensional: A(F(i,t))/F(i)/t
A(F(i,t)): Amplitude of frequency bins/bands at a moment in time.
F(i): Frequency bins/bands.
t: Time.
Uncommon
The first dimension is folded into the properities (e.g. color) of the data points.
2.5 Dimensional: |φ(i)-φ(j)|/i/j
|φ(i)-φ(j)|: Distance of the ith samplepoint's phase value from the jth samplepoint's.
i: The first index of the samples in a chunk of samplepoints.
j: The second index of the samples in a chunk of samplepoints.
Rare
The first dimension is folded into the properities (e.g. color) of the data points.
3 Dimensional: A(F(i,t))/F(i)/t
A(F(i,t)): Amplitude of frequency bins/bands at a moment in time.
F(i): Frequency bins/bands.
t: Time.
Uncommon
ISC License