scaled_rand

scaled_rand([rng], [T], dims...;
    scaling=0.1)

Create and return a matrix with random values, uniformly distributed within a range defined by scaling.

Arguments

• rng: Random number generator. Default is Utils.default_rng() from WeightInitializers.
• T: Type of the elements in the reservoir matrix. Default is Float32.
• dims: Dimensions of the matrix. Should follow res_size x in_size.

Keyword arguments

• scaling: A scaling factor to define the range of the uniform distribution. The factor can be passed in three different ways:

  • A single number. In this case, the matrix elements will be randomly chosen from the range [-scaling, scaling]. Default option, with a the scaling value set to 0.1.
  • A tuple (lower, upper). The values define the range of the distribution.
  • A vector. In this case, the columns will be scaled individually by the entries of the vector. The entries can be numbers or tuples, which will mirror the behavior described above.

Examples

julia> res_input = scaled_rand(8, 3)
8×3 Matrix{Float32}:
 -0.0669356  -0.0292692  -0.0188943
  0.0159724   0.004071   -0.0737949
  0.026355   -0.0191563   0.0714962
 -0.0177412   0.0279123   0.0892906
 -0.0184405   0.0567368   0.0190222
  0.0944272   0.0679244   0.0148647
 -0.0799005  -0.0891089  -0.0444782
 -0.0970182   0.0934286   0.03553

julia> tt = scaled_rand(5, 3, scaling = (0.1, 0.15))
5×3 Matrix{Float32}:
  0.13631   0.110929  0.116177
  0.116299  0.136038  0.119713
  0.11535   0.144712  0.110029
  0.127453  0.12657   0.147656
  0.139446  0.117656  0.104712

Example with vector:

julia> tt = scaled_rand(5, 3, scaling = [0.1, 0.2, 0.3])
5×3 Matrix{Float32}:
  0.0452399   -0.112565   -0.105874
 -0.0348047    0.0883044  -0.0634468
 -0.0386004    0.157698   -0.179648
  0.00981022   0.012559    0.271875
  0.0577838   -0.0587553  -0.243451

julia> tt = scaled_rand(5, 3, scaling = [(0.1, 0.2), (-0.2, -0.1), (0.3, 0.5)])
5×3 Matrix{Float32}:
  0.17262   -0.178141  0.364709
  0.132598  -0.127924  0.378851
  0.1307    -0.110575  0.340117
  0.154905  -0.14686   0.490625
  0.178892  -0.164689  0.31885