Sep-09-2019, 07:41 PM
Hi again!
I have modified once again the program to show that interacting the way you want with such big matrices produce an even more humongous matrix of almost 1 million and a half elements, because matrix 'x' has 800 elements, and matrix 'y' has 1800 elements, so your equation interacting with both of them gives a number of elements equal to the product of 800*1800, that is to say, 1440000 elements!!!
I have modified once again the program to show that interacting the way you want with such big matrices produce an even more humongous matrix of almost 1 million and a half elements, because matrix 'x' has 800 elements, and matrix 'y' has 1800 elements, so your equation interacting with both of them gives a number of elements equal to the product of 800*1800, that is to say, 1440000 elements!!!
import numpy as np
x = np.arange(4,12,.01)
bigx = len(x)
print("\nThe matrix 'x' has", bigx, "elements.")
y = np.arange(0,18,.01)
bigy = len(y)
print("The matrix 'y' has", bigy, "elements.")
mother_of_matrices = bigx*bigy
print("Therefore, the interaction of matrices 'x' and 'y' produces a huge matrix of:", mother_of_matrices, "elements.")
k = 10/(6+x)
print('\n\nThese are the values for "x":\n\n', x)
print('\n\nThese are the values for "y":\n\n', y)
print('\n\nThese are the values for "k":\n\n', k)and that produces the following huge output:Output:The matrix 'x' has 800 elements.
The matrix 'y' has 1800 elements.
Therefore, the interaction of matrices 'x' and 'y' produces a huge matrix of: 1440000 elements.
These are the values for "x":
[ 4. 4.01 4.02 4.03 4.04 4.05 4.06 4.07 4.08 4.09 4.1 4.11
4.12 4.13 4.14 4.15 4.16 4.17 4.18 4.19 4.2 4.21 4.22 4.23
4.24 4.25 4.26 4.27 4.28 4.29 4.3 4.31 4.32 4.33 4.34 4.35
4.36 4.37 4.38 4.39 4.4 4.41 4.42 4.43 4.44 4.45 4.46 4.47
4.48 4.49 4.5 4.51 4.52 4.53 4.54 4.55 4.56 4.57 4.58 4.59
4.6 4.61 4.62 4.63 4.64 4.65 4.66 4.67 4.68 4.69 4.7 4.71
4.72 4.73 4.74 4.75 4.76 4.77 4.78 4.79 4.8 4.81 4.82 4.83
4.84 4.85 4.86 4.87 4.88 4.89 4.9 4.91 4.92 4.93 4.94 4.95
4.96 4.97 4.98 4.99 5. 5.01 5.02 5.03 5.04 5.05 5.06 5.07
5.08 5.09 5.1 5.11 5.12 5.13 5.14 5.15 5.16 5.17 5.18 5.19
5.2 5.21 5.22 5.23 5.24 5.25 5.26 5.27 5.28 5.29 5.3 5.31
5.32 5.33 5.34 5.35 5.36 5.37 5.38 5.39 5.4 5.41 5.42 5.43
5.44 5.45 5.46 5.47 5.48 5.49 5.5 5.51 5.52 5.53 5.54 5.55
5.56 5.57 5.58 5.59 5.6 5.61 5.62 5.63 5.64 5.65 5.66 5.67
5.68 5.69 5.7 5.71 5.72 5.73 5.74 5.75 5.76 5.77 5.78 5.79
5.8 5.81 5.82 5.83 5.84 5.85 5.86 5.87 5.88 5.89 5.9 5.91
5.92 5.93 5.94 5.95 5.96 5.97 5.98 5.99 6. 6.01 6.02 6.03
6.04 6.05 6.06 6.07 6.08 6.09 6.1 6.11 6.12 6.13 6.14 6.15
6.16 6.17 6.18 6.19 6.2 6.21 6.22 6.23 6.24 6.25 6.26 6.27
6.28 6.29 6.3 6.31 6.32 6.33 6.34 6.35 6.36 6.37 6.38 6.39
6.4 6.41 6.42 6.43 6.44 6.45 6.46 6.47 6.48 6.49 6.5 6.51
6.52 6.53 6.54 6.55 6.56 6.57 6.58 6.59 6.6 6.61 6.62 6.63
6.64 6.65 6.66 6.67 6.68 6.69 6.7 6.71 6.72 6.73 6.74 6.75
6.76 6.77 6.78 6.79 6.8 6.81 6.82 6.83 6.84 6.85 6.86 6.87
6.88 6.89 6.9 6.91 6.92 6.93 6.94 6.95 6.96 6.97 6.98 6.99
7. 7.01 7.02 7.03 7.04 7.05 7.06 7.07 7.08 7.09 7.1 7.11
7.12 7.13 7.14 7.15 7.16 7.17 7.18 7.19 7.2 7.21 7.22 7.23
7.24 7.25 7.26 7.27 7.28 7.29 7.3 7.31 7.32 7.33 7.34 7.35
7.36 7.37 7.38 7.39 7.4 7.41 7.42 7.43 7.44 7.45 7.46 7.47
7.48 7.49 7.5 7.51 7.52 7.53 7.54 7.55 7.56 7.57 7.58 7.59
7.6 7.61 7.62 7.63 7.64 7.65 7.66 7.67 7.68 7.69 7.7 7.71
7.72 7.73 7.74 7.75 7.76 7.77 7.78 7.79 7.8 7.81 7.82 7.83
7.84 7.85 7.86 7.87 7.88 7.89 7.9 7.91 7.92 7.93 7.94 7.95
7.96 7.97 7.98 7.99 8. 8.01 8.02 8.03 8.04 8.05 8.06 8.07
8.08 8.09 8.1 8.11 8.12 8.13 8.14 8.15 8.16 8.17 8.18 8.19
8.2 8.21 8.22 8.23 8.24 8.25 8.26 8.27 8.28 8.29 8.3 8.31
8.32 8.33 8.34 8.35 8.36 8.37 8.38 8.39 8.4 8.41 8.42 8.43
8.44 8.45 8.46 8.47 8.48 8.49 8.5 8.51 8.52 8.53 8.54 8.55
8.56 8.57 8.58 8.59 8.6 8.61 8.62 8.63 8.64 8.65 8.66 8.67
8.68 8.69 8.7 8.71 8.72 8.73 8.74 8.75 8.76 8.77 8.78 8.79
8.8 8.81 8.82 8.83 8.84 8.85 8.86 8.87 8.88 8.89 8.9 8.91
8.92 8.93 8.94 8.95 8.96 8.97 8.98 8.99 9. 9.01 9.02 9.03
9.04 9.05 9.06 9.07 9.08 9.09 9.1 9.11 9.12 9.13 9.14 9.15
9.16 9.17 9.18 9.19 9.2 9.21 9.22 9.23 9.24 9.25 9.26 9.27
9.28 9.29 9.3 9.31 9.32 9.33 9.34 9.35 9.36 9.37 9.38 9.39
9.4 9.41 9.42 9.43 9.44 9.45 9.46 9.47 9.48 9.49 9.5 9.51
9.52 9.53 9.54 9.55 9.56 9.57 9.58 9.59 9.6 9.61 9.62 9.63
9.64 9.65 9.66 9.67 9.68 9.69 9.7 9.71 9.72 9.73 9.74 9.75
9.76 9.77 9.78 9.79 9.8 9.81 9.82 9.83 9.84 9.85 9.86 9.87
9.88 9.89 9.9 9.91 9.92 9.93 9.94 9.95 9.96 9.97 9.98 9.99
10. 10.01 10.02 10.03 10.04 10.05 10.06 10.07 10.08 10.09 10.1 10.11
10.12 10.13 10.14 10.15 10.16 10.17 10.18 10.19 10.2 10.21 10.22 10.23
10.24 10.25 10.26 10.27 10.28 10.29 10.3 10.31 10.32 10.33 10.34 10.35
10.36 10.37 10.38 10.39 10.4 10.41 10.42 10.43 10.44 10.45 10.46 10.47
10.48 10.49 10.5 10.51 10.52 10.53 10.54 10.55 10.56 10.57 10.58 10.59
10.6 10.61 10.62 10.63 10.64 10.65 10.66 10.67 10.68 10.69 10.7 10.71
10.72 10.73 10.74 10.75 10.76 10.77 10.78 10.79 10.8 10.81 10.82 10.83
10.84 10.85 10.86 10.87 10.88 10.89 10.9 10.91 10.92 10.93 10.94 10.95
10.96 10.97 10.98 10.99 11. 11.01 11.02 11.03 11.04 11.05 11.06 11.07
11.08 11.09 11.1 11.11 11.12 11.13 11.14 11.15 11.16 11.17 11.18 11.19
11.2 11.21 11.22 11.23 11.24 11.25 11.26 11.27 11.28 11.29 11.3 11.31
11.32 11.33 11.34 11.35 11.36 11.37 11.38 11.39 11.4 11.41 11.42 11.43
11.44 11.45 11.46 11.47 11.48 11.49 11.5 11.51 11.52 11.53 11.54 11.55
11.56 11.57 11.58 11.59 11.6 11.61 11.62 11.63 11.64 11.65 11.66 11.67
11.68 11.69 11.7 11.71 11.72 11.73 11.74 11.75 11.76 11.77 11.78 11.79
11.8 11.81 11.82 11.83 11.84 11.85 11.86 11.87 11.88 11.89 11.9 11.91
11.92 11.93 11.94 11.95 11.96 11.97 11.98 11.99]
These are the values for "y":
[0.000e+00 1.000e-02 2.000e-02 ... 1.797e+01 1.798e+01 1.799e+01]
These are the values for "k":
[1. 0.999001 0.99800399 0.99700897 0.99601594 0.99502488
0.99403579 0.99304866 0.99206349 0.99108028 0.99009901 0.98911968
0.98814229 0.98716683 0.98619329 0.98522167 0.98425197 0.98328417
0.98231827 0.98135427 0.98039216 0.97943193 0.97847358 0.97751711
0.9765625 0.97560976 0.97465887 0.97370983 0.97276265 0.9718173
0.97087379 0.9699321 0.96899225 0.96805421 0.96711799 0.96618357
0.96525097 0.96432015 0.96339114 0.96246391 0.96153846 0.96061479
0.9596929 0.95877277 0.95785441 0.9569378 0.95602294 0.95510984
0.95419847 0.95328885 0.95238095 0.95147479 0.95057034 0.94966762
0.9487666 0.9478673 0.9469697 0.94607379 0.94517958 0.94428706
0.94339623 0.94250707 0.94161959 0.94073377 0.93984962 0.93896714
0.9380863 0.93720712 0.93632959 0.9354537 0.93457944 0.93370682
0.93283582 0.93196645 0.9310987 0.93023256 0.92936803 0.92850511
0.92764378 0.92678406 0.92592593 0.92506938 0.92421442 0.92336103
0.92250923 0.92165899 0.92081031 0.9199632 0.91911765 0.91827365
0.91743119 0.91659028 0.91575092 0.91491308 0.91407678 0.91324201
0.91240876 0.91157703 0.91074681 0.90991811 0.90909091 0.90826521
0.90744102 0.90661831 0.9057971 0.90497738 0.90415913 0.90334237
0.90252708 0.90171326 0.9009009 0.90009001 0.89928058 0.8984726
0.89766607 0.89686099 0.89605735 0.89525515 0.89445438 0.89365505
0.89285714 0.89206066 0.8912656 0.89047195 0.88967972 0.88888889
0.88809947 0.88731145 0.88652482 0.88573959 0.88495575 0.8841733
0.88339223 0.88261253 0.88183422 0.88105727 0.88028169 0.87950748
0.87873462 0.87796313 0.87719298 0.87642419 0.87565674 0.87489064
0.87412587 0.87336245 0.87260035 0.87183958 0.87108014 0.87032202
0.86956522 0.86880973 0.86805556 0.86730269 0.86655113 0.86580087
0.8650519 0.86430424 0.86355786 0.86281277 0.86206897 0.86132644
0.8605852 0.85984523 0.85910653 0.8583691 0.85763293 0.85689803
0.85616438 0.85543199 0.85470085 0.85397096 0.85324232 0.85251492
0.85178876 0.85106383 0.85034014 0.84961767 0.84889643 0.84817642
0.84745763 0.84674005 0.84602369 0.84530854 0.84459459 0.84388186
0.84317032 0.84245998 0.84175084 0.84104289 0.84033613 0.83963056
0.83892617 0.83822297 0.83752094 0.83682008 0.8361204 0.83542189
0.83472454 0.83402836 0.83333333 0.83263947 0.83194676 0.8312552
0.83056478 0.82987552 0.8291874 0.82850041 0.82781457 0.82712986
0.82644628 0.82576383 0.82508251 0.82440231 0.82372323 0.82304527
0.82236842 0.82169269 0.82101806 0.82034454 0.81967213 0.81900082
0.81833061 0.81766149 0.81699346 0.81632653 0.81566069 0.81499593
0.81433225 0.81366965 0.81300813 0.81234768 0.81168831 0.81103001
0.81037277 0.8097166 0.80906149 0.80840744 0.80775444 0.8071025
0.80645161 0.80580177 0.80515298 0.80450523 0.80385852 0.80321285
0.80256822 0.80192462 0.80128205 0.80064051 0.8 0.79936051
0.79872204 0.7980846 0.79744817 0.79681275 0.79617834 0.79554495
0.79491256 0.79428118 0.79365079 0.79302141 0.79239303 0.79176564
0.79113924 0.79051383 0.78988942 0.78926598 0.78864353 0.78802206
0.78740157 0.78678206 0.78616352 0.78554595 0.78492936 0.78431373
0.78369906 0.78308536 0.78247261 0.78186083 0.78125 0.78064012
0.7800312 0.77942323 0.7788162 0.77821012 0.77760498 0.77700078
0.77639752 0.77579519 0.7751938 0.77459334 0.77399381 0.7733952
0.77279753 0.77220077 0.77160494 0.77101002 0.77041602 0.76982294
0.76923077 0.76863951 0.76804916 0.76745971 0.76687117 0.76628352
0.76569678 0.76511094 0.76452599 0.76394194 0.76335878 0.76277651
0.76219512 0.76161462 0.76103501 0.76045627 0.75987842 0.75930144
0.75872534 0.75815011 0.75757576 0.75700227 0.75642965 0.7558579
0.75528701 0.75471698 0.75414781 0.7535795 0.75301205 0.75244545
0.7518797 0.7513148 0.75075075 0.75018755 0.74962519 0.74906367
0.74850299 0.74794316 0.74738416 0.74682599 0.74626866 0.74571216
0.74515648 0.74460164 0.74404762 0.74349442 0.74294205 0.7423905
0.74183976 0.74128984 0.74074074 0.74019245 0.73964497 0.7390983
0.73855244 0.73800738 0.73746313 0.73691968 0.73637703 0.73583517
0.73529412 0.73475386 0.73421439 0.73367572 0.73313783 0.73260073
0.73206442 0.7315289 0.73099415 0.73046019 0.72992701 0.7293946
0.72886297 0.72833212 0.72780204 0.72727273 0.72674419 0.72621641
0.7256894 0.72516316 0.72463768 0.72411296 0.723589 0.7230658
0.72254335 0.72202166 0.72150072 0.72098053 0.7204611 0.7199424
0.71942446 0.71890726 0.7183908 0.71787509 0.71736011 0.71684588
0.71633238 0.71581961 0.71530758 0.71479628 0.71428571 0.71377587
0.71326676 0.71275837 0.71225071 0.71174377 0.71123755 0.71073205
0.71022727 0.70972321 0.70921986 0.70871722 0.7082153 0.70771408
0.70721358 0.70671378 0.70621469 0.7057163 0.70521862 0.70472163
0.70422535 0.70372977 0.70323488 0.70274069 0.70224719 0.70175439
0.70126227 0.70077085 0.70028011 0.69979006 0.6993007 0.69881202
0.69832402 0.69783671 0.69735007 0.69686411 0.69637883 0.69589422
0.69541029 0.69492703 0.69444444 0.69396253 0.69348128 0.69300069
0.69252078 0.69204152 0.69156293 0.691085 0.69060773 0.69013112
0.68965517 0.68917988 0.68870523 0.68823125 0.68775791 0.68728522
0.68681319 0.6863418 0.68587106 0.68540096 0.68493151 0.6844627
0.68399453 0.683527 0.68306011 0.68259386 0.68212824 0.68166326
0.68119891 0.68073519 0.68027211 0.67980965 0.67934783 0.67888663
0.67842605 0.6779661 0.67750678 0.67704807 0.67658999 0.67613252
0.67567568 0.67521945 0.67476383 0.67430883 0.67385445 0.67340067
0.67294751 0.67249496 0.67204301 0.67159167 0.67114094 0.67069081
0.67024129 0.66979236 0.66934404 0.66889632 0.6684492 0.66800267
0.66755674 0.66711141 0.66666667 0.66622252 0.66577896 0.66533599
0.66489362 0.66445183 0.66401062 0.66357001 0.66312997 0.66269052
0.66225166 0.66181337 0.66137566 0.66093853 0.66050198 0.66006601
0.65963061 0.65919578 0.65876153 0.65832785 0.65789474 0.6574622
0.65703022 0.65659882 0.65616798 0.6557377 0.65530799 0.65487885
0.65445026 0.65402224 0.65359477 0.65316786 0.65274151 0.65231572
0.65189048 0.6514658 0.65104167 0.65061809 0.65019506 0.64977258
0.64935065 0.64892927 0.64850843 0.64808814 0.64766839 0.64724919
0.64683053 0.64641241 0.64599483 0.64557779 0.64516129 0.64474533
0.6443299 0.643915 0.64350064 0.64308682 0.64267352 0.64226076
0.64184852 0.64143682 0.64102564 0.64061499 0.64020487 0.63979527
0.63938619 0.63897764 0.6385696 0.63816209 0.6377551 0.63734863
0.63694268 0.63653724 0.63613232 0.63572791 0.63532402 0.63492063
0.63451777 0.63411541 0.63371356 0.63331222 0.63291139 0.63251107
0.63211125 0.63171194 0.63131313 0.63091483 0.63051702 0.63011972
0.62972292 0.62932662 0.62893082 0.62853551 0.6281407 0.62774639
0.62735257 0.62695925 0.62656642 0.62617408 0.62578223 0.62539087
0.625 0.62460962 0.62421973 0.62383032 0.6234414 0.62305296
0.62266501 0.62227754 0.62189055 0.62150404 0.62111801 0.62073246
0.62034739 0.6199628 0.61957869 0.61919505 0.61881188 0.61842919
0.61804697 0.61766523 0.61728395 0.61690315 0.61652281 0.61614295
0.61576355 0.61538462 0.61500615 0.61462815 0.61425061 0.61387354
0.61349693 0.61312078 0.6127451 0.61236987 0.6119951 0.6116208
0.61124694 0.61087355 0.61050061 0.61012813 0.6097561 0.60938452
0.6090134 0.60864273 0.60827251 0.60790274 0.60753341 0.60716454
0.60679612 0.60642814 0.60606061 0.60569352 0.60532688 0.60496068
0.60459492 0.60422961 0.60386473 0.6035003 0.60313631 0.60277275
0.60240964 0.60204696 0.60168472 0.60132291 0.60096154 0.6006006
0.6002401 0.59988002 0.59952038 0.59916117 0.5988024 0.59844405
0.59808612 0.59772863 0.59737157 0.59701493 0.59665871 0.59630292
0.59594756 0.59559261 0.5952381 0.594884 0.59453032 0.59417706
0.59382423 0.59347181 0.59311981 0.59276823 0.59241706 0.59206631
0.59171598 0.59136606 0.59101655 0.59066745 0.59031877 0.5899705
0.58962264 0.58927519 0.58892815 0.58858152 0.58823529 0.58788948
0.58754407 0.58719906 0.58685446 0.58651026 0.58616647 0.58582308
0.58548009 0.58513751 0.58479532 0.58445354 0.58411215 0.58377116
0.58343057 0.58309038 0.58275058 0.58241118 0.58207218 0.58173357
0.58139535 0.58105752 0.58072009 0.58038305 0.5800464 0.57971014
0.57937428 0.5790388 0.5787037 0.578369 0.57803468 0.57770075
0.57736721 0.57703405 0.57670127 0.57636888 0.57603687 0.57570524
0.57537399 0.57504313 0.57471264 0.57438254 0.57405281 0.57372347
0.5733945 0.5730659 0.57273769 0.57240985 0.57208238 0.57175529
0.57142857 0.57110223 0.57077626 0.57045066 0.57012543 0.56980057
0.56947608 0.56915196 0.56882821 0.56850483 0.56818182 0.56785917
0.56753689 0.56721497 0.56689342 0.56657224 0.56625142 0.56593096
0.56561086 0.56529112 0.56497175 0.56465274 0.56433409 0.56401579
0.56369786 0.56338028 0.56306306 0.5627462 0.5624297 0.56211355
0.56179775 0.56148231 0.56116723 0.5608525 0.56053812 0.56022409
0.55991041 0.55959709 0.55928412 0.55897149 0.55865922 0.55834729
0.55803571 0.55772448 0.5574136 0.55710306 0.55679287 0.55648303
0.55617353 0.55586437]
newbieAuggie2019
"That's been one of my mantras - focus and simplicity. Simple can be harder than complex: You have to work hard to get your thinking clean to make it simple. But it's worth it in the end because once you get there, you can move mountains."
Steve Jobs
"That's been one of my mantras - focus and simplicity. Simple can be harder than complex: You have to work hard to get your thinking clean to make it simple. But it's worth it in the end because once you get there, you can move mountains."
Steve Jobs
