Get your own Python server Result Size: 625 x 565
x
 
import numpy
x = numpy.random.uniform(0.0, 5.0, 250)
print(x)
[4.70107872 0.24787675 0.2195555  3.06204253 4.77830208 4.3809458 
 4.57322999 4.36807984 1.67478644 3.68797008 3.99521373 3.20963264 
 0.94637018 1.51078597 0.13048172 4.37043882 4.91572869 4.9944569 
 2.32662378 3.00030176 3.67345324 1.86468628 3.27187565 3.75195031 
 4.67731372 4.97360003 4.51354256 4.16388364 2.07021774 0.62298694 
 2.47066525 4.0448314  3.42833033 1.33428236 1.73459005 3.21883822 
 3.74238411 0.70161377 4.10076553 2.71635406 4.25199618 1.71047347 
 0.56080893 1.52101476 3.268613   0.44348611 4.75300544 1.93018848 
 4.02334818 4.2936394  3.86262357 4.65161361 3.18855835 1.7270845 
 3.00572657 4.33593454 0.72605499 2.18322726 0.45156024 1.19257312 
 4.06588255 3.55786778 1.7739621  3.46521942 3.31536931 1.91225274 
 3.03644112 4.40795135 3.41339553 1.58513041 3.04306268 4.17387258 
 3.87451494 1.48655976 0.81035771 2.79862049 1.93737551 2.77350631 
 0.02961769 0.76614433 0.30462889 1.96064363 3.61984286 0.18390026 
 2.12864059 1.24368084 3.12624663 0.87324141 2.49182244 0.73894522 
 3.28624627 0.54325432 1.14019016 0.19408833 0.27587769 2.76731562 
 4.24239649 1.62670982 3.48601752 2.34165538 4.33079158 3.32373447 
 3.95982219 2.59970366 0.55374039 1.53498152 1.84149167 1.7103894 
 0.07011496 2.95268057 3.19355581 3.44488969 4.62279333 3.96444207 
 4.08320222 2.45938531 4.40211166 3.08226174 2.7413684  0.65249907 
 3.88554841 0.54426484 3.1453845  1.11706224 2.71756474 3.54715157 
 0.26560431 1.80808047 0.80432088 3.69086109 0.9538585  2.37378315 
 0.13003854 0.176845   0.15389107 3.69736303 0.64101966 4.06556222 
 1.8471563  2.71152545 0.8789574  1.9509209  3.85439304 3.00958342 
 0.82933679 2.68746095 2.63675    3.31097973 2.64676176 1.24868746 
 3.57576447 2.29019517 4.57538641 1.09943657 0.35057439 0.32663094 
 3.41203514 3.07271481 1.78668303 4.9319088  4.44909133 2.0572905 
 2.7863201  1.82312893 3.50405799 2.06544361 4.22933649 0.59760683 
 3.4048237  0.56655243 3.26653888 2.4388069  3.62042053 0.28400035 
 1.23169562 1.74053627 1.86822616 3.40158413 1.51949388 3.96485747 
 1.91560046 2.03155272 1.07299191 4.44833549 4.49162578 1.68513371 
 3.7402374  2.42013058 1.2598136  4.5316802  1.50186405 1.23001043 
 4.14823233 2.89923774 1.61491513 4.694959   2.62637724 4.15848057 
 2.29320707 0.19248169 2.92876948 0.66504363 2.96658345 2.61105925 
 2.10844525 1.9866828  4.33847884 2.1361846  3.51735449 0.3373951 
 2.51504308 4.52648976 0.11202356 3.20143812 3.46439049 2.42704263 
 4.49869534 2.28628955 4.64371298 1.09661546 2.69151894 3.93238154 
 2.56424271 2.14934753 0.84539193 4.32824987 2.04898603 1.41383722 
 3.0403419  1.51738193 4.93516012 4.49610783 1.63867322 1.40193809 
 0.74791302 2.89177327 2.71531315 1.96517301 1.83925883 4.90219347 
 4.23705842 1.77975734 3.25498864 4.15504765 0.02360116 4.88180179 
 2.65075243 3.26660281 2.65401096 1.13530684]