We combute h_i th number to elements in the i-th equidistant subdivision of the interval [min L, max L] into n parts
i1 : M=(randomChainComplex({20,20},{20},ZeroMean=>true)).dd_1; 40 40 o1 : Matrix ZZ <--- ZZ |
i2 : (svds,U,Vt)=SVD(M**RR_53); |
i3 : (entries matrix {svds})_0/log o3 = {6.37106, 6.31472, 6.27245, 6.10348, 6.02102, 5.98252, 5.92934, 5.83927, ------------------------------------------------------------------------ 5.72509, 5.63923, 5.51957, 5.51441, 5.45378, 5.3237, 5.14787, 5.11063, ------------------------------------------------------------------------ 4.80679, 4.71988, 4.56427, 3.9834, -30.0405, -30.1905, -30.222, ------------------------------------------------------------------------ -30.2852, -30.4198, -30.4877, -30.5496, -30.6978, -30.7377, -30.8283, ------------------------------------------------------------------------ -31.0297, -31.0967, -31.2371, -31.3948, -31.5393, -31.6439, -32.0612, ------------------------------------------------------------------------ -32.4003, -32.4744, -33.7828} o3 : List |
i4 : maximalEntry M o4 = 138 o4 : RR (of precision 53) |
i5 : histogram(svds/log,10) o5 = {20, 0, 0, 0, 0, 0, 0, 0, 0, 20} o5 : List |
i6 : histogram(svds_{0..19}/log,10) o6 = {1, 0, 1, 2, 2, 1, 4, 2, 4, 3} o6 : List |
i7 : histogram(svds_{20..39}/log,10) o7 = {1, 0, 0, 2, 1, 2, 2, 3, 5, 4} o7 : List |
The object histogram is a method function.