Result Size: 625 x 571
demo_ml_numpy_uniform.py:
x
 
import numpy
x = numpy.random.uniform(0.0, 5.0, 250)
print(x)
C:\Users\My Name>python demo_ml_numpy_uniform.py
[4.14619735 1.9552595  4.81022049 1.0968941  4.11274364 0.21639106 
 2.46779085 3.63434948 3.36301571 0.49473579 0.84308846 4.86567504 
 2.64851019 0.80986244 3.57851433 1.89214394 0.84532696 0.83982164 
 4.50273987 3.72569777 2.71395596 2.80718614 0.13682429 1.50192508 
 4.24345368 2.86685435 3.91837419 2.63038818 3.39149488 0.06864272 
 2.52768163 2.60785676 4.65715641 0.67466319 2.23679372 3.80532419 
 1.38909838 2.3781367  1.81770276 2.54898401 3.47726349 0.08312499 
 4.17156455 0.02445146 0.58956393 0.28822263 2.65365878 3.33637814 
 2.1780257  1.06303769 3.2860173  4.89156038 3.71513111 1.3576868 
 2.02281717 1.22769807 1.47824985 4.00783433 2.18767303 4.86374514 
 2.03177648 0.07894736 0.63471153 4.22039654 3.14316448 0.8936408 
 2.77963225 3.27212563 3.71620874 0.43802949 0.0781136  3.84756592 
 0.06873103 3.60761195 2.42185599 2.7738046  1.30947283 1.68520784 
 0.1997738  1.94162999 4.8836188  4.54735355 1.93515215 3.09240874 
 4.20973564 4.5814245  2.83309024 0.48367579 4.04874981 1.09302006 
 1.92708589 2.02647728 3.8844002  0.88228264 3.16869994 3.00826512 
 2.62970373 2.93514296 2.65581593 0.97874955 3.01782751 1.96513311 
 1.38169088 1.42786296 3.74122295 1.39782504 4.98859005 1.04194425 
 3.31394805 3.62021192 1.44196379 1.11706674 1.30513855 1.8090919 
 0.07418898 4.33164226 2.43087729 2.38001734 1.13339749 4.51971628 
 1.9228575  2.22840913 1.0618156  1.06420671 2.53761478 4.50371547 
 0.53253118 1.18415222 0.15649756 1.11444282 2.57544174 0.21320602 
 2.52493498 1.97020628 1.90997023 2.7076085  1.91884148 1.91370305 
 4.86681321 3.94264716 1.62843708 0.17171088 0.60260953 0.52008987 
 4.8147667  4.56974787 0.87203621 0.74379435 3.91028704 2.62782365 
 2.42712218 0.17308461 1.20803628 0.51563858 0.57255411 1.48897993 
 4.8861758  3.193811   0.71705053 3.68563021 3.23519528 0.05587595 
 0.2790102  3.62916886 2.74773308 0.83845609 2.73226692 0.26144253 
 0.5239676  1.67265185 3.70556753 2.0760212  1.90163154 1.73475818 
 0.61383056 3.32353115 2.7472151  0.50900875 2.80524775 3.1337009 
 2.26534016 2.760253   1.77648448 1.7902465  2.9682087  3.74168884 
 4.80854565 3.421855   0.43805139 3.83452936 2.0671818  4.30440785 
 4.88547747 3.56821188 1.86153968 4.81653238 3.59297684 2.08701563 
 2.37683626 4.67529513 2.29862762 3.32591517 1.9741528  1.28495873 
 0.85840353 2.11965041 4.86973673 1.14542779 2.14859491 4.07413461 
 1.10030647 4.70417509 0.54430517 3.56567735 0.65737196 2.32202992 
 3.69455169 0.30046087 3.14794355 0.1529399  2.56057869 1.62831389 
 0.59513738 2.88118293 3.48538776 1.51646823 4.56633362 4.36426006 
 0.8081832  2.25090906 0.89153983 3.62916629 4.3764022  1.94851477 
 3.61773111 4.25951901 0.3726178  2.00640265 4.1203295  1.95783702 
 0.31408415 1.44097649 3.46703699 2.28421742 4.19566549 4.96378613 
 0.45498472 3.41349449 3.11805307 0.10641257]