Result Size: 625 x 571
x
 
import numpy
x = numpy.random.uniform(0.0, 5.0, 250)
print(x)
[4.16457941 2.53336934 0.76094645 2.19728824 0.26461522 2.47763846 
 1.01861707 1.81286031 3.31170377 1.82227842 0.9851678  3.39704211 
 2.80936846 3.5178459  2.43532755 2.16588249 0.51356737 2.13931298 
 3.29456667 3.9949609  3.55884565 3.25152112 4.10826858 4.59093062 
 1.10645521 2.00119659 1.35298074 3.19715447 3.9095812  4.49572829 
 0.19396857 1.98504038 3.4434233  1.4264503  2.5929941  1.93930881 
 1.40465862 0.68521082 3.13884087 0.19739132 3.7006942  3.03040889 
 0.44557704 4.93506348 0.01016715 4.49707411 0.0250856  1.6161289 
 4.0614196  0.07539926 0.14178923 3.53735644 2.92626772 4.24309409 
 2.93614483 4.19271678 2.11085992 0.89565608 2.91128253 2.03085369 
 0.25994798 1.52378501 4.62784889 0.88462656 4.34725502 1.90010131 
 2.70673256 4.7833187  3.90638155 2.21866015 3.22971977 4.23391232 
 1.34365916 4.09616657 1.90472694 2.40922049 0.17677846 4.69405223 
 3.37608853 4.21936793 2.32993106 3.2160566  4.29338672 3.8085986 
 0.03532943 0.1336674  3.29150384 3.487193   4.83582545 0.77023456 
 2.9306055  3.45004702 0.95169535 1.59869558 1.99953255 4.45373969 
 0.46106712 0.77225608 2.5982888  2.41894188 4.7730061  2.49255828 
 2.67640541 4.81062781 0.18381472 3.8635721  0.72421463 3.29070047 
 3.21078948 1.97673306 2.23160857 2.14947338 1.57228967 4.03231597 
 1.93193546 4.83317115 4.57366509 2.72148306 2.76236854 2.45620923 
 3.27250864 3.27347015 0.20148648 2.74118186 3.00158603 3.50135538 
 2.75769371 3.21769774 3.76810699 2.05289646 1.41288639 4.97371182 
 1.87598207 0.17278485 4.27510981 0.31476547 0.00893708 1.04915326 
 1.54613005 1.91131455 4.12173165 0.64393556 1.49024513 0.35966727 
 2.38830249 3.59406423 0.67916137 1.18438456 4.4451865  3.99320972 
 1.53586504 4.86559434 4.867244   4.92217506 3.78949487 1.66934268 
 4.0403024  3.61716084 4.0901871  1.48687033 1.10239527 0.37455416 
 2.89031213 3.02845543 2.85232673 2.7275596  4.02031037 2.69293241 
 2.73244605 3.24139436 4.93317182 3.33097023 1.06817254 0.72802594 
 0.47194159 4.71601616 0.91228598 0.53578222 4.6864055  1.82696259 
 2.97684839 4.51509617 2.32623158 4.65218818 0.92864795 2.92965377 
 1.05175105 4.92930102 1.34231746 3.58343988 2.06728736 2.39001083 
 1.68120088 3.73902319 0.96690738 2.60878368 4.20396981 1.49623894 
 2.87431876 4.36249686 0.9025258  3.76298156 3.55854602 4.56100202 
 4.01188567 3.83115035 4.11706811 2.06614667 1.41638643 2.89719905 
 2.06946139 1.52044048 3.54159028 3.95656091 0.42960599 1.09079623 
 2.46292254 4.95074464 3.87291033 2.1211344  3.80070747 0.00888656 
 4.16287847 2.94661859 3.1512899  2.96793599 2.61313196 3.34480097 
 4.8391801  0.74660596 3.55424576 4.63494792 2.34374201 4.51295525 
 4.60275672 2.97788828 3.30910678 1.37742008 0.09007784 4.0066061 
 3.85646881 0.55971376 0.07674231 1.0299027  3.77871601 3.86643305 
 3.06371385 4.01894688 2.00470197 2.14495597]