BevölkerungspyramideDE
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;; pyramid ;; $Id: BevölkerungspyramideDE.nlogo 42 2018-10-04 06:41:32Z Walke $ ;; Rainer Walke, Daniel Ciganda, Sebastian Klüsener MPIDR globals [Year Age Female Male maxFemale maxMale baselineASFR mxFemale mxMale Total MigInFemale MigOutFemale MigInMale MigOutMale] patches-own [pAge pFemale pFemaleTemp pMale pMaleTemp pmxFemale pmxMale pDeathFemale pDeathMale pASFR pChildren pMigInFemale pMigOutFemale pMigInMale pMigOutMale] to setup clear-all set Year 2013 ;; Germany 2013 Age set Age [ 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 ] ;; Germany 2013 Female set Female [ 328424 324398 333776 328157 338176 337377 330494 336208 345307 345772 351900 360084 377333 377762 386794 399231 392199 380842 387726 405897 418170 438410 485243 484370 499927 492943 489744 475815 476747 481999 495268 496479 499255 476648 470965 467494 460737 447891 456664 461881 501782 553128 574871 617164 647571 667014 686405 688004 703098 698645 679132 672380 650605 633395 599063 587365 572893 558701 552881 537307 536691 526007 525646 506993 461711 435041 379811 336545 447193 452372 437776 533179 560362 549981 507450 469763 449952 427405 388458 305692 296941 293235 297883 276704 258276 230890 215518 196367 168348 146051 129553 112803 90585 54449 26702 19405 15771 14556 13315 8690 5450 3252 1843 1014 574 261 122 53 27 10 6 ] ;; Germany 2013 Male set Male [ 345987 341450 350534 345843 355497 355946 349430 354047 363634 364094 371262 380625 397086 398743 406763 419850 413981 401881 409325 427173 436659 457637 506959 504480 522826 516186 508240 492650 493215 496340 509069 503976 504384 482236 476846 473924 464830 453873 459627 465095 507509 562426 584257 632277 663538 682713 704379 709241 722309 716393 691967 680451 656755 639144 603042 588349 569966 548968 533700 513489 511566 500160 498521 482106 440203 409528 354444 306329 407759 411093 393870 469677 484252 465943 423782 383067 356626 329803 291345 220938 205791 194328 187993 166713 148968 120209 98820 80844 59521 48213 41270 33238 24614 13857 6500 4316 3283 2863 2322 1473 847 420 229 130 46 23 6 3 2 1 0 ] ;; Baseline Female ASFR - Germany 2013 set baselineASFR [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00003 0.00036 0.00125 0.00304 0.00643 0.01166 0.01751 0.02333 0.02884 0.03469 0.04152 0.05034 0.06098 0.0711 0.0806 0.08955 0.09613 0.10149 0.10329 0.09951 0.09351 0.08602 0.07585 0.06433 0.05297 0.04152 0.0313 0.02178 0.01366 0.00809 0.00449 0.00229 0.00109 0.00056 0.00026 0.00013 0.00009 0.00006 0.00004 0.00002 0.00001 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 ] ;; Germany 2013 mx Female set mxFemale [ 0.002972 0.000271 0.000112 0.000112 0.000078 0.000094 0.000087 0.000066 0.000079 0.000058 0.00006 0.000056 0.000087 0.000079 0.000115 0.000138 0.000157 0.000166 0.000182 0.000203 0.000209 0.000181 0.00016 0.000227 0.000216 0.000226 0.000222 0.000226 0.000246 0.00029 0.000292 0.000306 0.000355 0.00039 0.000391 0.000446 0.000454 0.000533 0.000589 0.000646 0.000747 0.000729 0.000864 0.000953 0.001068 0.001161 0.001345 0.001529 0.001636 0.001825 0.002018 0.002405 0.002601 0.002989 0.003104 0.003545 0.003846 0.003962 0.004465 0.004884 0.005115 0.005682 0.006171 0.006851 0.007653 0.008121 0.009041 0.009195 0.010789 0.011371 0.012127 0.013243 0.013784 0.01617 0.017622 0.019949 0.02318 0.026469 0.031616 0.035494 0.041041 0.047187 0.055744 0.064031 0.07416 0.084419 0.098077 0.113474 0.130757 0.148093 0.167352 0.191227 0.211485 0.25834 0.230578 0.285676 0.330631 0.343762 0.410442 0.407152 0.446375 0.487612 0.52139 0.559208 0.608025 0.633877 0.633759 0.570523 0.821505 0.91607 1.117037 ] ;; Germany 2013 mx Male set mxMale [ 0.003644 0.000307 0.000166 0.000135 0.000097 0.000117 0.000077 0.000097 0.00008 0.000124 0.000062 0.000061 0.00008 0.000095 0.000099 0.00016 0.000238 0.000282 0.000443 0.000453 0.000435 0.000446 0.000426 0.000467 0.000461 0.000516 0.000544 0.000478 0.00057 0.000572 0.000658 0.000641 0.000669 0.000704 0.000814 0.000857 0.000836 0.000881 0.001014 0.001201 0.001217 0.001306 0.001459 0.001688 0.001818 0.002098 0.002403 0.002556 0.00293 0.00334 0.003595 0.004281 0.004751 0.005344 0.005982 0.00655 0.007056 0.007974 0.008871 0.009478 0.01048 0.011193 0.011982 0.013041 0.014119 0.015249 0.016663 0.017911 0.020125 0.021197 0.022404 0.025119 0.026439 0.02989 0.032203 0.035366 0.040286 0.044649 0.051918 0.056072 0.063882 0.07311 0.084006 0.094824 0.106097 0.117804 0.130485 0.148224 0.166583 0.185359 0.204738 0.234709 0.254843 0.308031 0.259591 0.344735 0.378649 0.392058 0.493306 0.475073 0.602986 0.59679 0.507168 0.68606 0.689942 1.087985 0.831354 0.495868 2.598477 2.554945 6 ] ;; Germany 2013 MigIn Female set MigInFemale [ 3126 6509 6181 5789 5546 5341 4782 4469 4043 4056 3857 3522 3470 3364 3101 3223 3914 4007 7208 12636 16914 19982 21212 22173 20902 19594 17285 15876 14670 13471 12627 12088 11086 10415 9607 9374 8589 8270 7953 7568 7160 7006 6585 6408 6381 6187 5669 4854 4833 4604 4542 4033 3876 3752 3403 3226 2923 2550 2364 2127 1872 1643 1526 1383 1256 1155 965 804 623 622 576 532 489 474 455 380 350 324 308 250 220 200 167 176 157 122 94 89 58 50 39 34 27 16 8 6 4 4 4 3 2 2 0 0 0 0 0 0 0 0 0 ] ;; Germany 2013 MigOut Female set MigOutFemale [ 908 2645 2883 2833 2799 2680 2872 2316 1908 1896 1827 1648 1589 1531 1421 1375 1702 1946 2893 5125 7610 11331 12907 13063 12485 12024 10703 9877 9093 8403 8075 7549 7220 6690 6037 5885 5538 5284 5174 4862 4549 4558 4379 4236 4141 4175 3920 3385 3439 3252 3159 2965 2827 2777 2488 2423 2244 2054 1912 1748 1592 1536 1413 1435 1270 1286 1179 907 794 716 720 664 632 617 537 497 494 420 360 329 326 282 221 216 226 177 134 124 95 95 109 96 75 46 21 17 13 13 13 8 4 4 0 0 0 0 0 0 0 0 0 ] ;; Germany 2013 MigIn Male set MigInMale [ 3416 6812 6403 6188 5815 5523 5029 4637 4299 4251 4109 3865 3659 3638 3569 3758 4901 5044 9485 15338 18448 22102 24716 27470 27530 27678 26409 25667 24290 22962 21796 21106 19889 19907 18597 17682 17621 16654 16207 15568 14132 14006 13413 13213 12585 12266 11362 9932 9342 9078 8314 7597 7111 6848 6036 5508 4880 4388 3717 3139 2609 2130 1912 1581 1385 1357 1091 961 763 727 631 644 606 552 461 402 342 289 231 212 170 131 107 109 89 75 67 52 32 23 29 24 17 9 5 3 2 2 2 1 1 0 0 0 0 0 0 0 0 0 0 ] ;; Germany 2013 MigOut Male set MigOutMale [ 909 2829 3033 3061 2855 2875 2981 2443 2153 2022 1976 1806 1620 1618 1554 1548 1836 2011 3102 5651 8687 12211 14543 15774 16603 16950 16657 16573 15820 15507 15035 15027 14390 14210 13678 13040 12977 12492 12187 11654 10825 10648 10230 10234 9932 9482 8941 8036 7579 7302 6935 6186 5919 5679 5106 4772 4233 3850 3372 2875 2442 2064 1830 1749 1649 1778 1562 1210 1062 974 964 877 866 834 737 637 591 488 393 336 342 244 203 219 170 132 117 88 72 60 66 53 38 21 11 6 4 4 4 2 2 0 0 0 0 0 0 0 0 0 0 ] set maxFemale 800000 set maxMale 800000 ask patches [ set pAge item pycor Age set pFemale item pycor Female set pMale item pycor Male set pASFR item pycor baselineASFR set pmxFemale item pycor mxFemale set pmxMale item pycor mxMale set pmxMale item pycor mxMale set pMigInFemale item pycor MigInFemale set pMigOutFemale item pycor MigOutFemale set pMigInMale item pycor MigInMale set pMigOutMale item pycor MigOutMale ] create-y-line-labels set Total round( sum [pFemale + pMale] of patches with [pxcor = 0] ) ask patches with [pxcor = 0] [ set pcolor white - 2 ] reset-ticks ask patches with [pxcor = 0 and pycor = (Year + ticks - Kohorte) ] [ set pcolor yellow ] ask patches with [pxcor < 0] [ ifelse (( pMale / maxMale ) > ( pxcor / -50)) [ set pcolor 104 ] [set pcolor 0] ] ask patches with [pxcor > 0] [ ifelse (( pFemale / maxFemale ) > ( pxcor / 50)) [ set pcolor 14 ] [ set pcolor 0] ] output-print Year + ticks end ;; display y values to create-y-line-labels ask patches with [pxcor = 2] [ set plabel-color black if pycor = 0 [ set plabel 0 ] if pycor = 10 [ set plabel 10 ] if pycor = 20 [ set plabel 20 ] if pycor = 30 [ set plabel 30 ] if pycor = 40 [ set plabel 40 ] if pycor = 50 [ set plabel 50 ] if pycor = 60 [ set plabel 60 ] if pycor = 70 [ set plabel 70 ] if pycor = 80 [ set plabel 80 ] if pycor = 90 [ set plabel 90 ] if pycor = 100 [ set plabel 100 ] if pycor = 110 [ set plabel 110 ] ] ask patches with [pxcor = -2] [ set plabel-color black if pycor = 5 [ set plabel 5 ] if pycor = 15 [ set plabel 15 ] if pycor = 25 [ set plabel 25 ] if pycor = 35 [ set plabel 35 ] if pycor = 45 [ set plabel 45 ] if pycor = 55 [ set plabel 55 ] if pycor = 65 [ set plabel 65 ] if pycor = 75 [ set plabel 75 ] if pycor = 85 [ set plabel 85 ] if pycor = 95 [ set plabel 95 ] if pycor = 105 [ set plabel 105 ] ] end to boost20 ask patches with [pycor = 20] [ set pFemale ( pFemale * 1.2) set pMale ( pMale * 1.2) ask patches with [pxcor < 0 and pycor = 20] [ ifelse (( pMale / maxMale ) > ( pxcor / -50)) [ set pcolor 104 ] [set pcolor 0] ] ask patches with [pxcor > 0 and pycor = 20] [ ifelse (( pFemale / maxFemale ) > ( pxcor / 50)) [ set pcolor 14 ] [ set pcolor 0] ] ] set Total round( sum [pFemale + pMale] of patches with [pxcor = 0] ) end to boost2013 ask patches [ set pFemale ( pFemale + pMigInFemale - pMigOutFemale) set pMale ( pMale + pMigInMale - pMigOutMale) ] ask patches with [pxcor < 0] [ ifelse (( pMale / maxMale ) > ( pxcor / -50)) [ set pcolor 104 ] [set pcolor 0] ] ask patches with [pxcor > 0] [ ifelse (( pFemale / maxFemale ) > ( pxcor / 50)) [ set pcolor 14 ] [ set pcolor 0] ] set Total round( sum [pFemale + pMale] of patches with [pxcor = 0] ) end to set1 set jährlich_20 FALSE set jährlich FALSE set Sterblichkeit 1.0 set Kinderzahl 1.42 set Kohorte 1969 end to go-once go end to go if jährlich_20 [ boost20 ] if jährlich [boost2013] ;; modify fertility ask patches [ set pASFR ( ( item pycor baselineASFR ) * Kinderzahl / sum (baselineASFR) ) ] ;; compute the number of newborn children depending on the number of women and the ASFR ask patches [ set pChildren round( pASFR * pFemale ) ] ;; compute the number of death for each age ask patches [ set pDeathFemale ceiling( pmxFemale * pFemale ) set pDeathMale ceiling( pmxMale * pMale ) ] ask patches [ set pMale max (list 0 ( pMale - pDeathMale ) ) set pFemale max ( list 0 ( pFemale - pDeathFemale ) ) ] ask patches with [pycor > 0] [ set pMaleTemp [pMale] of patch pxcor (pycor - 1) set pFemaleTemp [pFemale] of patch pxcor (pycor - 1) ] ask patches with [pycor = 0] [ set pMaleTemp round(( sum [pChildren] of patches with [pxcor = 0] ) / 2) set pFemaleTemp round(( sum [pChildren] of patches with [pxcor = 0] ) / 2) ] ask patches [ set pMale pMaleTemp set pFemale pFemaleTemp ] ask patches with [pxcor < 0] [ ifelse (( pMale / maxMale ) > ( pxcor / -50)) [ set pcolor 104 ] [set pcolor 0] ] ask patches with [pxcor > 0] [ ifelse (( pFemale / maxFemale ) > ( pxcor / 50)) [ set pcolor 14 ] [ set pcolor 0] ] tick ;; modify mortality ask patches [ set pmxMale ( pmxMale * Sterblichkeit ) set pmxFemale ( pmxFemale * Sterblichkeit ) ] ask patches with [pxcor = 0 ] [ set pcolor white - 2 ] ask patches with [pxcor = 0 and pycor = (Year + ticks - Kohorte) ] [ set pcolor yellow ] set Total round( sum [pFemale + pMale] of patches with [pxcor = 0] ) output-print Year + ticks end
There is only one version of this model, created about 6 years ago by Rainer Walke.
Attached files
| File | Type | Description | Last updated | |
|---|---|---|---|---|
| BevölkerungspyramideDE.png | preview | Preview for 'BevölkerungspyramideDE' | about 6 years ago, by Rainer Walke | Download |
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