In signal processing, noise is typically the unwanted aspect. In a noisy room it's harder to hear someone than in a quiet room. Audio noise is random numbers arranged in a line (1D). In a noisy image it's harder to see a pattern than in a clean image. Image noise is random numbers arranged in a grid (2D). You can also have noise in 3D, 4D, etc.
For example, if you specified dim_z=2 and then try to assign a 3x3 matrix to R (the measurement noise matrix you will get an assert exception because R should be 2x2. (If for whatever reason you need to alter the size of things midstream just use the underscore version of the matrices to assign directly: your_filter._R = a_3x3_matrix.)
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