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12 Commits

Author SHA1 Message Date
fordprefect
4a4f6d1c6b fixed raw data 2023-08-13 21:55:29 +02:00
fordprefect
d88c9d2b6e fix rane10-10 data, add overview plots 2023-08-13 21:54:35 +02:00
fordprefect
ede67b5af6 implement ptplot 2023-08-13 19:14:46 +02:00
fordprefect
2746d10564 new raw and parser for new type of plot 2023-08-13 19:14:30 +02:00
fordprefect
cb749a449a finalize all plots (so far) 2023-07-10 14:13:54 +02:00
fordprefect
63e6724d2c fix formatting for parser 2023-07-10 14:12:07 +02:00
fordprefect
a0e1b29ac2 implement first idea of eplot 2023-07-10 11:51:08 +02:00
fordprefect
f02f890461 fix parsing routine 2023-07-10 11:50:31 +02:00
fordprefect
ca35e94f85 new files for new e diagram 2023-07-10 11:17:23 +02:00
fordprefect
f048a98a83 Uplot data amendment 2023-07-10 11:16:44 +02:00
fordprefect
f87b3df23c U- and Z-plot properly done 2023-07-06 16:52:00 +02:00
fordprefect
8a6ce15fdb remove outlier 2023-07-06 16:51:25 +02:00
8 changed files with 254 additions and 81 deletions

79
data_ediagram.py Normal file
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#Plot: x-Achse: Al, y-Achse Fe, No ist egal, alle Epi_E_a mit einer Farbe und in Legende Bezeichnung „Epi_E_a“, usw.
rawdata = [
"""No. 229 230 231 232 252 253 254 255 256 307 308 309 310 311
Epi_E_a Epi_E_a Epi_E_a Epi_E_a Epi_E_b Epi_E_b Epi_E_b Epi_E_b Epi_E_b Epi_E_c Epi_E_c Epi_E_c Epi_E_c Epi_E_c
Al 2,93241133320791 2,9517948142983 2,92856594815371 2,90506582679333 2,89658762937309 2,90681620895172 2,95236414704128 2,91374571497044 2,45747553229356 2,53688512906265 2,90221591085952 2,91448506221199 2,91382940302767 2,94304507974937
Fe+3 0,0738059065117476 0,050928262764455 0,0682348033150973 0,0824736762809354 0,122109173460867 0,0797197538583904 0,0531746087169284 0,0750998173148713 0,569435047767714 0,465346519422234 0,0937334717419173 0,0549985486816274 0,0734492480313419 0,0636042926797437""",
"""No. 183 184 252 253 345 346 347 348 349 350
Epi_E_d Epi_E_d Epi_E_e Epi_E_e Epi_E_f Epi_E_f Epi_E_f Epi_E_g Epi_E_g Epi_E_g
Al 2,3211321203245 2,56569075271161 2,34866353535515 2,33764178096418 2,38549902272546 2,44101343171515 2,43252321725985 2,64273909318701 2,54516053548287 2,64522713463196
Fe+3 0,564715399175452 0,302176553751045 0,56188080692161 0,565253779889425 0,55168541071089 0,474199676877068 0,458548694452138 0,269641308975537 0,364153221729885 0,26248715223474""",
"""No. 351 352 353 354 32 33 34 128 129 130
Epi_E_h Epi_E_h Epi_E_h Epi_E_h Epi_E_i Epi_E_i Epi_E_i Epi_E_j Epi_E_j Epi_E_j
Al 2,33807425110074 2,34053672866791 2,38290443369389 2,3672668438269 2,87614939294447 2,84733707207427 2,83402682658253 2,73479742201638 2,72162727777866 2,71989247957813
Fe+3 0,614561836666928 0,591836889041518 0,562676984045455 0,581807648005309 0,0671844427520575 0,0871417513551472 0,11640502802312 0,216917151917929 0,220934373075201 0,218288833455775""",
"""No. 15 16 17 18 19 20 44 45 46 47 48 49 50 51 52 83 84 85 86 87 88 89
Epi_E_k Epi_E_k Epi_E_k Epi_E_k Epi_E_k Epi_E_k Epi_E_l Epi_E_l Epi_E_l Epi_E_l Epi_E_l Epi_E_l Epi_E_l Epi_E_l Epi_E_l Epi_E_m Epi_E_m Epi_E_m Epi_E_m Epi_E_m Epi_E_m Epi_E_m
Al 2,23803832994323 2,27088377084141 2,30398440933804 2,3311892274406 2,41249562087074 2,40817997869596 2,25084040252057 2,08840485293262 2,35186690290207 2,34693924105135 2,39932891124769 2,06920110479273 2,19571704213787 2,23866580333112 2,31641461316187 2,32700583406629 2,35627094588088 2,29984779024087 1,39734497654841 2,14368050236642 2,2405064522685 2,30092014650739
Fe+3 0,713835952962848 0,69659158131678 0,607578677279297 0,657799395214154 0,552765811321079 0,532802296316212 0,727675372811064 0,83843175252463 0,596309911427646 0,605680843189107 0,56019383930035 0,871047065977394 0,76873557636038 0,73142117046558 0,647890420291867 0,644249033314204 0,590722956716691 0,654917989765932 0,55475099974521 0,755121474256949 0,725174206943835 0,65559842830768""",
"""No. 48 49 50 51 52 103 104 105 106 107 108 138 139 140 141
Epi_Fro_a Epi_Fro_a Epi_Fro_a Epi_Fro_a Epi_Fro_a Epi_Fro_b Epi_Fro_b Epi_Fro_b Epi_Fro_b Epi_Fro_b Epi_Fro_b Epi_Fro_c Epi_Fro_c Epi_Fro_c Epi_Fro_c
Al 2,85237208018488 2,89132121196934 2,86829953964949 2,87842750294436 2,93240670570976 2,61849677550985 2,29589538762623 2,61410137305755 2,64258213720569 2,66420042890076 2,57165845075151 2,58213993141373 2,5632717146903 2,54963051498439 2,53852108918408
Fe+3 0,137421199716151 0,139878060209798 0,130249537222605 0,136637539671679 0,0780938825470317 0,388867303201215 0,723374720501857 0,406260512165727 0,346957727732163 0,351218924994998 0,433205152860762 0,35102622856358 0,361107038158408 0,425307482024452 0,411475851430893""",
"""No. 160 161 162 172 173 174 175 25 26 27 28
Epi_Fro_d Epi_Fro_d Epi_Fro_d Epi_Fro_e Epi_Fro_e Epi_Fro_e Epi_Fro_e Epi_Fro_f Epi_Fro_f Epi_Fro_f Epi_Fro_f
Al 2,343252099666 2,3212170818885 2,29813888481623 2,20525786733392 2,22750445940276 2,30964404064813 2,35481641911625 2,23581396029492 2,21624345660384 2,20332021741968 2,21957329382193
Fe+3 0,645547366575881 0,63865710405176 0,69621676240418 0,78275014460138 0,716790297122701 0,668285316238327 0,531628980198307 0,756610936041688 0,78171442700135 0,797458706873903 0,766006232199339""",
"""No. 50 51 52 60 61 62 69 70 100 101 102 103 104
Epi_Fro_g Epi_Fro_g Epi_Fro_g Epi_Fro_h Epi_Fro_h Epi_Fro_h Epi_Fro_i Epi_Fro_i Epi_Fro_j Epi_Fro_j Epi_Fro_j Epi_Fro_j Epi_Fro_j
Al 2,45854294394831 2,36625997205822 2,34045238400722 2,40315075368061 2,40015262377715 2,32844282722795 2,34272515058542 2,33136923906842 1,85276573810898 1,85505603170204 1,82074245087717 1,84112034723124 1,85338889504735
Fe+3 0,508607123881933 0,590462611164006 0,621787882493695 0,57510237357414 0,590153092518535 0,64008998886145 0,618313506311464 0,659811805656024 1,7189960853372 1,79621051158201 1,85729798340094 1,77078579293587 1,80537514557715""",
"""No. 270 271 272 183 184 185 187 188 189 190 213 214 215
Epi_Fro_k Epi_Fro_k Epi_Fro_k Epi_Fro_l Epi_Fro_l Epi_Fro_l Epi_Fro_l Epi_Fro_l Epi_Fro_l Epi_Fro_l Epi_Fro_m Epi_Fro_m Epi_Fro_m
Al 2,58877018381275 2,57262792875167 2,57168780190379 1,8279966568131 2,56886214966037 2,20602572477669 2,55807207503061 2,59848688834496 2,5635149982321 2,52355457745325 2,57879618531635 2,57645141656476 2,43950508005609
Fe+3 0,371532296693202 0,359530131730853 0,389397233611845 0,380127701063786 0,338599718782561 0,301792824875321 0,329298263548948 0,31493746727952 0,342439458454303 0,403709321421708 0,329267750784328 0,325891659607313 0,464467745133605""",
"""No. 335 336 337 338 339 340 349 350 351 352 353 392 393 394
Epi_Fro_n Epi_Fro_n Epi_Fro_n Epi_Fro_n Epi_Fro_n Epi_Fro_n Epi_Fro_o Epi_Fro_o Epi_Fro_o Epi_Fro_o Epi_Fro_o Epi_Fro_p Epi_Fro_p Epi_Fro_p
Al 2,39650025345515 2,36509789693306 2,38306665321643 2,60547841331133 2,55062503821418 2,52945450163079 2,66152306385287 2,53638900826945 2,51926778023304 2,50013163798528 2,53230398187015 2,32165149739709 1,92233432749447 2,2152145750714
Fe+3 0,646967319885096 0,67060058038901 0,634332433880778 0,390127660594466 0,463092946287179 0,480783780771496 0,334265143380398 0,461349914203222 0,48761584438644 0,513827382934719 0,455238697880172 0,684486585941876 1,75024231652052 0,797480509686296""",
"""No. 32 33 34 35 36 448 449
Epi_Fro_q Epi_Fro_q Epi_Fro_r Epi_Fro_s Epi_Fro_s Epi_Fro_t Epi_Fro_t
Al 2,40096985266195 2,38332802260323 2,48845056404113 2,43803592497744 2,46300504056357 2,15455100535075 2,10626857303588
Fe+3 0,495295307043025 0,519912385715743 0,406063905437858 0,472986774143588 0,477241309361155 0,733398904124484 0,759605355841605""",
"""No. 132 133 134 135 136 137 138 160 161 162 163 164 282 283 284 285 286 287 288
Epi_Fro_u Epi_Fro_u Epi_Fro_u Epi_Fro_u Epi_Fro_u Epi_Fro_u Epi_Fro_u Epi_Fro_v Epi_Fro_v Epi_Fro_v Epi_Fro_v Epi_Fro_v Epi_Fro_w Epi_Fro_w Epi_Fro_w Epi_Fro_w Epi_Fro_w Epi_Fro_w Epi_Fro_w
Al 2,17255446555271 2,19235872841047 2,24127676285561 2,2167891391999 2,19180339584333 2,29106385728859 2,17181283336184 2,21504421704291 2,09835789648747 2,18837554001955 2,20326223208813 2,22259517525392 2,42508019806652 2,14278466705158 2,18552778507985 2,14905241085173 2,24962659797287 2,14246062897699 2,3327936136744
Fe+3 0,767790522060898 0,776217818372491 0,720004218600254 0,749194339131505 0,784076288263845 0,643696100251768 0,783071315587265 0,749621323983758 0,779060340037785 0,796665025674518 0,759581052653747 0,737902162502921 0,490435828297395 0,782670381360682 0,735981521421355 0,793861274981069 0,718467284424362 0,802399166994268 0,611098256201509""",
"""No. 227 228 229 230 231 232 233 286 287 288 289
Epi_Rane_a Epi_Rane_a Epi_Rane_a Epi_Rane_b Epi_Rane_b Epi_Rane_b Epi_Rane_b Epi_Rane_c Epi_Rane_c Epi_Rane_c Epi_Rane_c
Al 2,49409450823092 2,81436754418619 2,81584171055651 2,81508792984036 2,81071936705869 2,80373646222146 1,06886410904301 2,78525748653209 2,81675723209331 2,82678615187416 2,81633661275731
Fe+3 0,442776264359581 0,10601338850713 0,117435099127739 0,11783903840454 0,107488645447369 0,120538230849844 0,39336721721071 0,131381896142243 0,119278558392504 0,108524669815512 0,104405344764322""",
"""No. 220 221 222 223 224 225 226 250 251 252 253 254 368 369 370 371
Epi_Rane_d Epi_Rane_d Epi_Rane_d Epi_Rane_d Epi_Rane_d Epi_Rane_d Epi_Rane_d Epi_Rane_e Epi_Rane_e Epi_Rane_e Epi_Rane_e Epi_Rane_e Epi_Rane_f Epi_Rane_f Epi_Rane_g Epi_Rane_g
Al 2,2981177560916 2,00914682630984 2,1550799590996 1,99301218260343 2,17929573010852 2,35592811946789 2,24762104986111 2,41434799978562 2,55562651498457 2,506878442723 2,48798427611867 1,33046725096498 2,27713956558791 2,26525903643226 2,27786295057994 2,28677527488395
Fe+3 0,650852093071001 0,928212948153806 0,795960089904116 0,934015014000395 0,74303726896531 0,609716266934655 0,710584362233489 0,447730655790762 0,387000066717139 0,463987910145945 0,458733209558447 0,344625303142351 0,638932639038263 0,659565313478828 0,649523999630508 0,625302755954743
"""]
def _convert(d):
dat = []
d = d.replace("Al\t", "").replace("Fe+3\t", "")
ds = list(map(lambda x: x.split(), d.split("\t\t")))
for s in ds:
dat.append(list(map(float, list(map(lambda x: x.replace(",","."), s)))))
return dat
def get_data():
data = []
for dataset in rawdata:
lines = dataset.split("\n")
#probe_label = lines[0].split("\t")[0]
data.append({"index": lines[0].split()[1:],
"labels": lines[1].split(),
"al": _convert(lines[2]),
"fe": _convert(lines[3])})
return data
data = get_data()
if __name__ == "__main__":
print(data)

63
data_ptdiagram.py Normal file
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import numpy as np
rawdata = """E11-1 core core core core core core core core core core core core core core core core core core core core core core core core core core core core core core core core core core core core core core core core core core core core core core core core core core core core core core core core core core core core core core core core core core core core core core core core core core core core rim rim rim rim rim rim rim rim rim rim rim rim rim rim rim rim rim rim rim rim rim rim rim rim rim rim rim
p 9,5 8 8 9,5 9,5 10 8,5 8 9,2 9 9,2 7,8 7 9,4 9,4 9,7 8 8,7 9,2 9,2 10 9,7 8,8 8 9,3 8,8 9 7,6 7,4 9,2 9,2 8,4 9,2 9,2 10 8,6 8 9,2 8,6 9 9,2 9,6 9,6 8,6 9,5 9,5 10 8,8 8 9,6 8,8 9,2 9,6 9,6 9,6 8,6 9,5 9,5 10 8,8 8 9,6 8,8 9,2 9,6 9,4 9,7 8,4 9,4 9,4 9,8 8,6 9,4 8,6 9,1 9,4 14,5 19 15,0 19,5 17,0 18,0 20,0 15,5 14,0 15 19,5 15 20 17,5 19 20 16 14,5 15,5 20 15,5 20,5 18,5 20 17 15 24
T 374,2 293,7 326,5 367,6 369,3 394,7 334,7 301,6 368,6 337,3 353,3 285,4 264,5 372,5 378,6 380,9 297,7 332,8 371,2 372,9 399,5 282,5 339,9 305,6 373,5 341,0 357,2 288,8 269,3 369 370 324 362 364 390 331 298 364 332 349 368 378 380 331 371 372 399 338 303 373 339 356 377 378 380 331 371 372 399 338 303 373 339 356 377 369 371 323 362 364 389 330 364 331 348 368 700 852 631 886 742 880 961 673 606 718 874 646 909 761 905 982 690 623 755 921 678 958 803 957 727 654 1170
E11-2b2 core core core core transition transition transition transition rim rim rim rim rim rim rim rim
p 10,9 9,2 10,5 7,5 10,7 9,2 10,2 7,4 16,8 10 12 13,5 16,8 9,6 12 13,4
T 443 361 420 287 435 354 411 281 750 394 512 583 762 391 515 588
E11-2b3 core core core core core core core core transition transition transition transition transition transition rim rim rim rim rim rim rim rim
p 13,5 15,6 13,5 12,5 13 15,2 13,2 12,5 14,8 15,1 12,1 15,6 15,9 12,5 15,2 17,1 14,6 16,5 15,5 17,4 15 16,9
T 579,307690489454 691,580192070313 586,792447493203 542,311848722592 563,038706095721 673,487268563628 571,244675445446 528,779385288307 651,808675290907 675,132343795834 504,715224513113 696,632605445166 722,003330839937 534,956500901985 680,394999155916 789,416497900048 642,265855469304 742,712680121769 699,380201422214 810,167230070622 660,930160035844 763,23758422422
E11-2c2 core core transition transition transition transition rim rim rim rim
p 6,1 6,1 10,3 9,3 9 8,4 14,9 12,1 13,2 10,8
T 276 278 404,914118545545 366,830331111749 347,467589680629 316,350829656469 657,125231122506 494,956854076839 575,186688198204 438,589717810896
Fro1a core core core core transition transition transition transition transition transition rim rim rim rim rim rim
p 8,3 6,6 10,4 8,9 10,2 10 9,1 10,8 10,5 9,2 11,7 11,7 10,4 11,1 10,8 9,7
T 311,234420431724 262,823220089942 412,206373153549 342,352025469124 406,781817449735 404,501245271818 356,711257079056 436,068755313578 433,242960713223 381,033114042144 499,106911973762 470,638656937731 410,834790904437 467,696232384829 440,448586673909 385,512756032861
Fro5-2 core core core core core core transition transition transition transition transition transition rim rim rim rim rim rim
p 6,7 9,4 7,2 10,8 7,8 10,8 8,5 9,3 8,2 8,9 9 9,6 9,2 6,9 9,1 6,8 9,8 7,3
T 264 383 293 440 299 448 334 368 314 343 353 388 362 271 356 268 384 288
Fro12-11 core core core core transition transition transition transition rim rim rim rim rim rim rim rim rim
p 10,5 10,9 10,2 10,5 9,2 8,7 9 8,3 19,3 12,8 18,6 19,3 12,7 18,6 14,1 9,9 13,4
T 420 435 406 420 368 336 349 319 850 535 816 851 536 817 588,326560252509 391,06600545418 566,239270864729
Fro12-13a transition transition transition transition transition transition transition transition transition transition transition transition rim rim rim rim rim rim rim rim rim rim rim rim
p 13,4 11 13 11 12,1 10,2 12,3 10,6 15,1 12,9 14 12,1 20,6 20,1 20,2 20,5 19,2 19,3 20 20,2 22,7 22,3 20,2 20,2
T 626 465 605 453 548 412 578,237596822832 433,840418546991 755,769155278269 552,865035728822 674,92829420201 503,68112340178 805 827 816 844 783 807 813,208089931722 839,845159804565 917,653430329754 947,090941121732 795,115404629457 819,421221878283
Rane10-3 core core core core core core core core core core core core transition transition transition transition transition transition transition transition transition transition transition transition transition transition transition transition rim rim rim rim rim rim rim rim rim rim rim rim rim rim rim rim
p 10,2 9,3 9,5 6,8 10,4 9,7 9,9 7,2 10,3 9,6 9,7 6,8 10,6 10,5 10,7 9 10,7 10,7 11 9,2 10,2 9,9 10,2 8,8 11,5 11,6 11,4 9,9 12,2 14,9 15 12,8 12,7 15,4 15,3 12,9 12,3 15,1 15,4 13 12,2 15 15,3 12,8
T 404 369 381 264 421 387 398 278,901678670781 409,494301482043 375,533427916256 386,298013929303 269,422101590477 427 422 436 349 443 438 453 361,251084048528 402,742560356777 397,290404754501 409,887933680074 332,155441944561 483,254544257058 477,558572644372 492,214317009013 392,575336069011 516 645 620 541 531 666 639 555,699311677766 523,893893210169 655,908617463107 631,551872262378 549,721533665992 519,994628770231 652,207885553591 627,755793167068 545,452999968155
Rane10-10 core core core core transition transition transition transition rim rim rim rim rim rim rim rim rim rim rim rim
p 6,5 6,6 6,9 6,9 11,4 12,6 12,8 14 16,3 17,9 15,8 15,9 17,3 19,1 16,8 16,8 17,3 19,1 16,8 16,8
T 453 461 505 507 452 495 501 575 618 667 595 598 657 710 632 634,717258249757 656,108445904902 710,362518667749 631,32528493392 634,142181436897"""
def parse_data():
data = {}
for i, dataset in enumerate(rawdata.split("\n\n")):
lines = dataset.split("\n")
label = lines[0].split("\t")[0]
region = lines[0].split("\t")[2:]
p = np.array(list(map(float, lines[1].replace(",", ".").split("\t")[2:])))
t = np.array(list(map(float, lines[2].replace(",", ".").split("\t")[2:])))
cmask = np.array(region) == "core"
tmask = np.array(region) == "transition"
rmask = np.array(region) == "rim"
data[label] = {"raw": {"p": p, "t": t, "region": region},
"core": {"p": p[cmask], "t": t[cmask]},
"transition": {"p": p[tmask], "t": t[tmask]},
"rim": {"p": p[rmask], "t": t[rmask]}
}
#print(label, "\n", data[label])
return data
data = parse_data()

View File

@@ -4,9 +4,9 @@ Al (iv) 1.17168760603347 1.03621345449937 1.07847577080796 1.07904245954011 0.9
Al (vi) 0.34574794613374 0.405710686785444 0.168168513653823 0.172746304298536 0.157980594727049 0.858484179410594 1.94036214251573
""",
"""Fro5-2 amph_Fro_i amph_Fro_j amph_Fro_k amph_Fro_l amph_Fro_m amph_Fro_o
No. 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293
Al (iv) 0.722019855619663 0.618805763255942 1.02501004682069 1.10486521183116 1.18493217142932 1.19295407392041 1.15759451353221 1.16429698850985 1.21123469040152 1.20507209553264 1.30861065282402 1.09144150899768 0.982439956144869 0.918193863276047 0.405664661926494 0.362530813021841 0.372980250495114 0.328547821159988 0.243986930365164 0.296408654943485 0.307909880246553 0.359144170412725 0.872444059303483 0.858107376299246 0.844286361278411 1.2200291006557 0.978363396613103 1.06809097270696 1.10896600646457 1.55676512895417 1.00453603762971 0.873231869108992 0.664710569810095 0.393495015337273 0.359070626763721 0.315505017892295 0.158166254469616 0.206867394174812 1.39351036719127 1.31571242621294 0.59785059241193 0.420801602841876 0.264833006671243 0.328230289116427 0.370141500529203 2.70447549631297 0.477022110003905 0.294780639391238 0.671248066534227 0.894151188287977 1.41253847593417 0.353860906997785 0.421185639874149 0.326373971471085 0.316768682167532 0.298709896920723 0.312106822828219 0.333263330736797 1.15527021350207 0.979882525568701 0.708172715407262 0.597919267700598 0.410307264204808 0.296606171848898 0.367569499388969 0.421663528818793 0.333330343809449 0.282690916058288 0.327614137469426 0.388701589377633 0.237887121812194 0.235656809658487 0.192344872665882 0.308308746647008 0.255445884050983 0.239425364568866 0.315366207415213
Al (vi) 0.933489100997222 1.06666153315248 0.877876448676666 0.919369206527092 0.912710727349233 0.93050011160589 1.00821494084138 0.969406552353089 0.981774854119898 0.970280109244273 0.978003417382252 0.958376300795917 0.796594495931627 0.832584234383143 1.31229512954086 1.36217316381665 1.3762468969197 1.41247477820508 1.51235653390907 1.42844729725813 1.40019958371494 1.35728809962144 0.889266058203009 0.867031554138447 0.86188965356094 0.72720585444048 0.86700036591186 0.757753452875172 0.849755233916429 0.981246182964492 0.73255198503012 0.803888066140904 1.00117464606099 1.3267923469654 1.37655085682166 1.47596769680823 1.66558076284081 1.5778281638066 1.02461156119325 0.868002940635026 1.22602856950507 1.29265036135634 1.43338130324905 1.4171314070923 1.39361718073771 4.9163157805524 1.2156203834852 1.39503157494463 1.06582838399492 0.835616008986315 0.783232923753725 1.36077278004045 1.3810262185537 1.47027538517149 1.47748835813899 1.48593971990796 1.49843545764423 1.46859890842675 0.879251188709484 0.924169365409821 1.12285334809971 1.19755834530786 1.34451290628813 1.44417170575338 1.34965540297918 1.28127198505971 1.33211799086708 1.41002240525348 1.36018855138295 1.30219682716984 1.47950693452883 1.46419425399954 1.49704799262834 1.39576034271885 1.45635643701559 1.4698053796526 1.4041558429872
No. 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 254 255 256 257 258 259 260 261 262 263 264 265 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293
Al (iv) 0.722019855619663 0.618805763255942 1.02501004682069 1.10486521183116 1.18493217142932 1.19295407392041 1.15759451353221 1.16429698850985 1.21123469040152 1.20507209553264 1.30861065282402 1.09144150899768 0.982439956144869 0.918193863276047 0.405664661926494 0.362530813021841 0.372980250495114 0.328547821159988 0.243986930365164 0.296408654943485 0.307909880246553 0.359144170412725 0.872444059303483 0.858107376299246 0.844286361278411 1.2200291006557 0.978363396613103 1.06809097270696 1.10896600646457 1.55676512895417 1.00453603762971 0.873231869108992 0.664710569810095 0.393495015337273 0.359070626763721 0.315505017892295 0.158166254469616 0.206867394174812 1.39351036719127 1.31571242621294 0.59785059241193 0.420801602841876 0.264833006671243 0.328230289116427 0.370141500529203 0.477022110003905 0.294780639391238 0.671248066534227 0.894151188287977 1.41253847593417 0.353860906997785 0.421185639874149 0.326373971471085 0.316768682167532 0.298709896920723 0.312106822828219 0.333263330736797 1.15527021350207 0.979882525568701 0.708172715407262 0.597919267700598 0.410307264204808 0.296606171848898 0.367569499388969 0.421663528818793 0.333330343809449 0.282690916058288 0.327614137469426 0.388701589377633 0.237887121812194 0.235656809658487 0.192344872665882 0.308308746647008 0.255445884050983 0.239425364568866 0.315366207415213
Al (vi) 0.933489100997222 1.06666153315248 0.877876448676666 0.919369206527092 0.912710727349233 0.93050011160589 1.00821494084138 0.969406552353089 0.981774854119898 0.970280109244273 0.978003417382252 0.958376300795917 0.796594495931627 0.832584234383143 1.31229512954086 1.36217316381665 1.3762468969197 1.41247477820508 1.51235653390907 1.42844729725813 1.40019958371494 1.35728809962144 0.889266058203009 0.867031554138447 0.86188965356094 0.72720585444048 0.86700036591186 0.757753452875172 0.849755233916429 0.981246182964492 0.73255198503012 0.803888066140904 1.00117464606099 1.3267923469654 1.37655085682166 1.47596769680823 1.66558076284081 1.5778281638066 1.02461156119325 0.868002940635026 1.22602856950507 1.29265036135634 1.43338130324905 1.4171314070923 1.39361718073771 1.2156203834852 1.39503157494463 1.06582838399492 0.835616008986315 0.783232923753725 1.36077278004045 1.3810262185537 1.47027538517149 1.47748835813899 1.48593971990796 1.49843545764423 1.46859890842675 0.879251188709484 0.924169365409821 1.12285334809971 1.19755834530786 1.34451290628813 1.44417170575338 1.34965540297918 1.28127198505971 1.33211799086708 1.41002240525348 1.36018855138295 1.30219682716984 1.47950693452883 1.46419425399954 1.49704799262834 1.39576034271885 1.45635643701559 1.4698053796526 1.4041558429872
""",
"""Fro12-4 amph_Fro_ad amph_Fro_ah amph_Fro_ai amph_Fro_aj
No. 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249
@@ -32,7 +32,20 @@ Al (vi) 1.474 1.592 1.478 1.330 1.559 1.340 0.646 0.678 0.578 0.570 0.571 0.681
No. 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 301 302 303 304 305 306 326 327 328 329 330 331 332 333 334 335 336 337 338 389 390 391 392 394 395 396 397 398 399 400 401 402 403 404 405
Al (iv) 0.115 0.282 0.292 0.508 0.453 0.524 0.832 0.142 0.179 0.200 0.203 0.206 0.239 0.934 0.848 0.846 0.730 0.092 0.085 0.077 0.123 0.278 0.279 0.216 0.352 0.399 1.081 1.028 0.105 0.236 0.245 1.404 1.315 1.717 0.157 0.179 0.189 0.199 0.223 0.253 0.536 0.780 0.392 0.736 0.120 0.165 0.143 0.179 0.139 0.146 0.189 0.214 0.223 0.337 0.382 0.292 0.335 0.477 1.151 1.186 1.390 1.627 1.502
Al (vi) 1.463 1.290 1.258 1.104 1.116 1.077 0.862 1.472 1.435 1.397 1.371 1.364 0.867 0.370 0.347 0.316 0.068 1.521 1.534 1.519 1.466 1.299 1.329 1.394 1.259 1.185 0.318 0.315 1.491 1.321 1.300 0.652 0.711 0.725 1.445 1.441 1.428 1.413 1.423 1.355 1.104 0.882 1.164 0.972 1.444 1.394 1.399 1.422 1.485 1.480 1.434 1.451 1.387 1.305 1.270 1.248 1.244 1.104 0.565 0.500 0.595 0.558 0.681
"""]
""", # second data set starts below
"""Fro11-6c_(gln) amph_Fro_ca amph_Fro_cb amph_Fro_cc amph_Fro_cd
No. 33 34 35 36 37 38 40 41 42 43 44 53 54 55 56 57 58 59 74 75 76 77 78 79 80 81 82 83 89 90 91 92 93 94 95 96 97 98
Al (iv) 0.946816804407802 0.915374936513542 0.937271642498776 0.847760968902469 0.747719228173619 0.714829698146967 1.86571227579049 1.71838080893279 1.71103734452366 1.70879657970424 1.64092677390816 0.461022184356462 0.693023395327311 0.982951765167888 1.52795621943651 1.53036132489667 1.49209394814901 1.62995787481642 0.698900346977771 0.816799574124805 0.764948598355243 0.869872587451249 1.5530690903298 1.79468904739747 1.84420792449185 1.99843039623898 1.56667648786992 1.57383359070777 0.630928262769171 0.561577760147696 0.548056344005859 0.786375842376335 1.00513689464044 1.87745464654207 1.93338975656706 0.615313278112884 0.50168136117628 1.61995337675513
Al (vi) 0.838942186807262 0.815361670511523 0.808137144270259 0.862078768661791 0.939090197132293 0.963779498333328 0.560748890921683 0.484482276634198 0.473542874470649 0.609182415010286 0.599143153793783 1.12725569400285 0.966366578088712 0.806510848833191 3.51621774600843 3.56674385825125 3.57782677128492 3.36773309452869 0.942984820030193 0.887441228699995 0.944724260781667 0.901423930916418 0.386579399482084 0.481158896581861 0.53578885415416 0.76897845900415 0.400356157934341 0.510848459618583 0.998093322898503 1.03315559508081 1.02774242501428 0.951305106175528 0.819026996150823 0.798236792336004 1.54853682884571 0.988494165008363 1.06735883175549 0.576081223535151""",
"""Fro12-2_(gln) amph_Fro_ce amph_Fro_cf amph_Fro_cg amph_Fro_ch amph_Fro_ci amph_Fro_cj amph_Fro_ck
No. 191 192 193 194 195 196 197 198 199 200 201 202 222 223 224 225 226 227 228 229 230 231 232 233 245 246 247 248 249 250 251 252 253 259 260 261 262 263 264 265 266 267 268 269 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315
Al (iv) 0.328188388002119 0.361256275224842 0.362429861161353 0.342701124396405 0.375689071786472 0.410922546562091 0.433489035412379 0.215393190830418 0.352438484877891 0.860029563686514 0.981522439883262 1.08818373565835 0.384753748828151 0.388117260733489 0.347654152270255 0.529919556378776 0.583522801938067 0.377562975184153 0.417591727752516 0.877417733596414 1.1786437776632 1.22285207322467 0.951286956138196 0.974460816925085 0.887289832741685 0.360677366131962 0.428434921439195 0.412327022806907 0.502578452044203 1.01026038416063 1.08387614318567 1.16025742016281 0.854098229490802 0.375855418045937 0.289692422406622 0.436627446505401 0.54555536543532 0.402297240781901 0.827694244724913 0.883768905233 1.01023249853057 1.16494077314581 1.05218100302439 1.07271367271352 0.770950749006239 0.27531264327789 0.374033825154145 0.338852609962906 0.36706682043426 0.817341101615991 0.762079236826144 1.25500977497809 1.08211101979398 1.11167158638088 1.0643412222582 1.08026436357389 1.03519777229883 0.947204233180861 0.386067094610256 0.357594948027232 0.29320791126707 0.338630493331255 0.370393547817729 0.347849859930496 0.32545386771765 0.337512298104357 0.414621915838326 0.625592554904839 0.887937451012005 0.947577578612908 1.02858068580916 1.02952059000579 1.15762177585972 1.07719594023792 0.392634480405641 0.405076921869238 0.331509741636521 0.382734742735397 0.369638226563933 0.761249808607752 0.872380301765923 0.95152692000307 0.922540441086865 0.986008478205388 0.98738227238653 1.9257930295669 1.48390529065649
Al (vi) 1.37017335890543 1.36844364037036 1.32288688936552 1.37029541618546 1.37024211844302 1.35087782045706 1.29461573002652 1.50861073865596 1.3267869122613 0.612766609051898 0.693097818545363 0.670250981028784 1.3113133967853 1.34586514772034 1.35120737985726 1.17787883422592 1.12431189432453 1.36570772342889 1.33366175301796 0.549125324096053 0.63185534306506 0.629769910820257 0.514554244651119 0.640588186644977 0.929064970765926 1.36945947220338 1.28702756326837 1.31522311951817 1.23519616350027 0.598196994561467 0.596610834619597 0.573975596813212 0.2257536612153 1.37957308340145 1.42031965165414 1.08294441110912 1.11684264289059 1.34256283430956 0.893482190348614 0.505383059504192 0.660494005191579 0.580331722771146 0.656397074917925 0.634530014440569 0.618954716080268 1.50568132348632 1.34859276445898 1.41407627333516 1.35881473682596 0.635224674181522 0.543399719473396 0.859870249699252 0.630056681042227 0.707551804332569 0.752200148416642 0.711696461129994 0.68907797385245 0.725583405687959 1.32471185901789 1.361178184943 1.46613949231631 1.36801377871056 1.35482566723579 1.40188108196994 1.41669289870394 1.41701792117051 1.3173557632398 1.05825229558851 0.604084399396854 0.572378684337928 0.638198011270666 0.623548230339987 0.707997620150112 0.602927533124502 1.2937876942767 1.29620291613596 1.43353543228735 1.35113875560262 1.32831854491189 0.694020039147137 0.659831222815137 0.5729544062121 0.687856225738848 0.691489332662949 0.70608557115278 2.48251955219877 4.02806549864933""",
"""Fro12-13a_(gln) amph_Fro_cl amph_Fro_cm amph_Fro_cn amph_Fro_co amph_Fro_cp amph_Fro_cq amph_Fro_cr amph_Fro_cs amph_Fro_ct amph_Fro_cu amph_Fro_cv
No. 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 88 109 110 111 112 113 114 115 116 137 138 139 140 141 142 143 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 450 451 452 453 454 455 456 457 458 459
Al (iv) 0 0.314353485701544 0.325291246418307 0.381403755363658 0.374302906412133 0.489528008310402 0.402225876198907 1.75871040410334 1.84146892417324 1.45935094146606 1.27284089871442 1.05421242353845 0.850022770011366 0.839986208459827 0.32211912468823 0.285872871643965 0.261919641645515 0.284384131951545 0.349818354093864 0.313322857319986 0.425344884166535 0.505290552823106 0.903938357238606 0.311516192198159 0.40284833961657 0.381826799315414 0.341443209938549 1.0312673119157 1.05362107396374 1.11817520899743 0.269991406049937 0.310167696154493 0.348350989371074 0.331714596146752 0.36820771230222 0.31276106321326 0.424055902995629 0.408894424685645 0.646334308987496 0.903507639568968 1.01920305688623 0.261897957134529 0.245147508828516 0.367981013369273 1.06140937955948 1.56469269258899 1.11004722485604 2.15682423580188 2.05816222486019 0.215868941603327 0.201187312466408 0.345088393266079 0.311130260948995 0.349404027913159 0.328721574850613 0.620205621992563 0.353629416457129 0.398192685066014 0.318986023530274 0.433273205055643 0.276962637949195 0.447159671998953 0.403137001587158 0.318877624551829 0.257356458438419 0.370597054569883 0.403461649478006 0.359611754760731 1.32449774843963 1.25870193800869 1.29793985417384 1.19587675638665 1.19627997028856 1.40232459545016 1.60790438309744 1.54007466576874 0.505282011535206 1.10047535393283 1.08032365713327 0.59829553968101 0.246349955322835 0.327210473418903 0.303732680014742
Al (vi) 1.74791037980584 1.34349648179927 1.34436593711445 1.28937857759042 1.27271508985709 1.2033095164389 1.22829701384197 0.803611053526665 0.602741049046181 0.895348347630978 1.0239106639883 1.02334251717134 1.03350201423128 0.976808916850934 1.32239104480213 1.42669502418355 1.41394709734442 1.39706921721595 1.35371764042877 1.30996665202343 1.22308886742955 1.1525484796713 0.881750123558456 1.32145376636871 1.24472981086873 1.26601793376856 1.33443728114338 0.976993949443575 0.82897264994853 0.837403150612387 1.41298027039234 1.45266468208903 1.39307155029634 1.37198822682148 1.2830570595143 1.37706097406316 1.2454933797397 1.27042358958718 1.10385060851776 0.915678660168757 0.903723174448463 1.48696583008407 1.37504764516274 1.2956723675947 0.762055964856206 0.603198270035297 0.470375922080046 0.496910816778194 1.54410092366639 1.47126018385118 1.44799487512134 1.31896152413539 1.36336161435732 1.39280911709791 1.31292300266436 1.14669041153757 1.36820806821928 1.27897483345219 1.32011814900904 1.22265769666829 1.3784136968127 1.20726257533416 1.31339720508611 1.3646558937751 1.4350383479321 1.24281673273374 1.2340357656236 1.29801329059426 0.144475455643813 0.253179259915687 0.265909524205712 0.282541006058353 0.291017591003584 0.810272603510621 0.622012381914396 0.420188235749915 1.19961584594336 0.855091117230516 0.9216006831554 1.00800053725834 1.45175578408793 1.36103426245815 1.38259411407457"""
]
def _convert(d):
dat = []
@@ -53,3 +66,10 @@ def get_data():
return data
data = get_data()
if __name__ == "__main__":
for entry in data:
print(entry)
for k in ['zones', 'index', 'al4', 'al6']:
print(k, len(data[entry][k]))

View File

@@ -3,8 +3,8 @@ import matplotlib.pyplot as pp
import numpy as np
import data_ternary
import data_udiagram
import data_zdiagram
import data_ediagram
import data_ptdiagram
def plotTdiagram():
scale = 100
@@ -25,45 +25,17 @@ def plotTdiagram():
# Set Axis labels and Title
fontsize = 12
offset = 0.14
#tax.set_title(group+"\n", fontsize=fontsize)
tax.right_corner_label("Sps", fontsize=fontsize)
tax.top_corner_label("Grs", fontsize=fontsize)
tax.left_corner_label("Prp", fontsize=fontsize)
#tax.left_axis_label("Left label $\\alpha^2$", fontsize=fontsize, offset=offset)
#tax.right_axis_label("Right label $\\beta^2$", fontsize=fontsize, offset=offset)
#tax.bottom_axis_label("Bottom label $\\Gamma - \\Omega$", fontsize=fontsize, offset=offset)
# Draw lines parallel to the axes
#tax.horizontal_line(16)
#tax.left_parallel_line(10, linewidth=2., color='red', linestyle="--")
#tax.right_parallel_line(20, linewidth=3., color='blue')
# Draw an arbitrary line, ternary will project the points for you
#p1 = (22, 8, 10)
#p2 = (2, 22, 16)
#tax.line(p1, p2, linewidth=3., marker='s', color='green', linestyle=":")
for item in group:
points = list(zip(*(data_ternary.data[item]['Sps'],
data_ternary.data[item]['Grs'],
data_ternary.data[item]['Prp'],
)))
#print(points)
tax.scatter(points, label=item)
#p1 = (data_ternary.data[item][val][0] for val in ['Prp', 'Sps', 'Grs'])
p1 = points[0]
#p2 = (data_ternary.data[item][val][-1] for val in ['Prp', 'Sps', 'Grs'])
p2 = points[-1]
print(p1, p2)
#tax.line(p1, p2, linewidth=3., marker='s', color='green', linestyle="-")
# line.axes.annotate('',
# xytext=(xdata[start_ind], ydata[start_ind]),
# xy=(xdata[end_ind], ydata[end_ind]),
# arrowprops=dict(arrowstyle="->", color=color),
# size=size
# )
tax.legend(frameon=False)
# edit this for ax ticks
@@ -72,71 +44,33 @@ def plotTdiagram():
# leave this alone
tax.get_axes().axis('off')
tax.clear_matplotlib_ticks()
pp.savefig(f"ternary_{group}.png")
tax.show()
pp.savefig(f"ternary_{'_'.join(group)}.png")
#tax.show()
def plotUdiagram():
figures = {}
figures["E11-9a_amph_E11_ab"] = pp.subplots(1)
figures["Fro5-2_amph_Fro_i"] = pp.subplots(1)
figures["Fro5-2_amph_Fro_j"] = figures["Fro5-2_amph_Fro_i"] #pp.subplots(1)
figures["Fro5-2_amph_Fro_k"] = figures["Fro5-2_amph_Fro_i"] #pp.subplots(1)
figures["Fro5-2_amph_Fro_l"] = figures["Fro5-2_amph_Fro_i"] #pp.subplots(1)
figures["Fro5-2_amph_Fro_m"] = figures["Fro5-2_amph_Fro_i"] #pp.subplots(1)
figures["Fro5-2_amph_Fro_o"] = figures["Fro5-2_amph_Fro_i"] #pp.subplots(1)
figures["Fro12-4_amph_Fro_ad"] = pp.subplots(1)
figures["Fro12-4_amph_Fro_ah"] = figures["Fro12-4_amph_Fro_ad"] #pp.subplots(1)
figures["Fro12-4_amph_Fro_ai"] = figures["Fro12-4_amph_Fro_ad"] #pp.subplots(1)
figures["Fro12-4_amph_Fro_aj"] = figures["Fro12-4_amph_Fro_ad"] #pp.subplots(1)
figures["Fro1312b1_amph_Fro_bb"] = pp.subplots(1)
figures["Fro1312b1_amph_Fro_be"] = figures["Fro1312b1_amph_Fro_bb"] #pp.subplots(1)
figures["Fro1312b1_amph_Fro_bi"] = figures["Fro1312b1_amph_Fro_bb"] #pp.subplots(1)
figures["Rane10-3_amph_Rane_a"] = pp.subplots(1)
figures["Rane10-3_amph_Rane_b"] = figures["Rane10-3_amph_Rane_a"] #pp.subplots(1)
figures["Rane10-3_amph_Rane_c"] = figures["Rane10-3_amph_Rane_a"] #pp.subplots(1)
figures["Rane10-3_amph_Rane_e"] = figures["Rane10-3_amph_Rane_a"] #pp.subplots(1)
figures["Rane10-3_amph_Rane_f"] = figures["Rane10-3_amph_Rane_a"] #pp.subplots(1)
figures["Rane10-4_amph_Rane_g"] = figures["Rane10-3_amph_Rane_a"] #pp.subplots(1)
figures["Rane10-4_amph_Rane_l"] = figures["Rane10-3_amph_Rane_a"] #pp.subplots(1)
figures["Rane10-4_amph_Rane_m"] = figures["Rane10-3_amph_Rane_a"] #pp.subplots(1)
figures["Rane10-10_amph_Rane_p"] = pp.subplots(1)
figures["Rane10-10_amph_Rane_q"] = figures["Rane10-10_amph_Rane_p"] #pp.subplots(1)
figures["Rane10-10_amph_Rane_r"] = figures["Rane10-10_amph_Rane_p"] #pp.subplots(1)
figures["Rane10-10_amph_Rane_s"] = figures["Rane10-10_amph_Rane_p"] #pp.subplots(1)
figures["Rane10-10_amph_Rane_t"] = figures["Rane10-10_amph_Rane_p"] #pp.subplots(1)
figures["Rane10-10_amph_Rane_u"] = figures["Rane10-10_amph_Rane_p"] #pp.subplots(1)
figures["Rane10-10_amph_Rane_v"] = figures["Rane10-10_amph_Rane_p"] #pp.subplots(1)
figures["Rane10-10_amph_Rane_w"] = figures["Rane10-10_amph_Rane_p"] #pp.subplots(1)
for g in data_udiagram.data.keys():
dat = data_udiagram.data[g]
for i, zone in enumerate(dat['zones']):
fig, ax = figures[f"{g}_{zone}"]
name = f"{g}_{zone}"
fig, ax = pp.subplots(1, num=name)
ax.plot(dat['index'][i], dat['al4'][i], label="Al(IV)", color="blue", marker=".")
ax.plot(dat['index'][i], dat['al6'][i], label="Al(VI)", color="orange", marker=".")
ax.set_xlabel("No.")
ax.set_ylabel("value")
ax.set_ylabel("pfu")
ax.set_title(f"{g}: {zone}")
ax.legend(frameon=False)
ax.xaxis.get_major_locator().set_params(integer=True)
figs = list(set([figures[i] for i in figures]))
for key in figures:
if key not in figs: continue
fig, ax = figures[key]
pp.gcf()
pp.savefig(f"uplot_{key}.png")
fig.savefig(f"uplot_{g}_{zone}.png")
pp.show()
#pp.show()
def plotZdiagram():
#fig, ax = pp.subplots(1)
for g in data_udiagram.data.keys():
fig, ax = pp.subplots(1, num=g)
@@ -150,14 +84,91 @@ def plotZdiagram():
ax.legend(frameon=False)
#ax.xaxis.get_major_locator().set_params(integer=True)
pp.savefig(f"zplot_{g}.png")
fig.savefig(f"zplot_{g}.png")
#pp.show()
def plotEdiagram():
#line = [[2.75, 1], [2,.75, 0]]
line = [[2.75, 2.075], [1, 0]]
labelpositions = {
"Epi_E_a": [[2.1,0.8], [2.4,0.1]],
"Epi_E_d": [[2.1,0.4], [2.4,0.1]],
"Epi_E_h": [[2.1,0.5], [2.4,0.1]],
"Epi_E_k": [[1.8,0.4], [2.4,0.1]],
"Epi_Fro_a": [[2.1,0.5], [2.4,0.1]],
"Epi_Fro_d": [[2.01,0.5], [2.4,0.1]],
"Epi_Fro_g": [[2.1,0.8], [2.4,0.1]],
"Epi_Fro_k": [[2.1,0.8], [2.4,0.1]],
"Epi_Fro_n": [[2,0.5], [2.4,0.1]],
"Epi_Fro_q": [[2.1,0.4], [2.4,0.1]],
"Epi_Fro_u": [[2.08,0.3], [2.4,0.1]],
"Epi_Rane_a": [[2.1,0.8], [2.225,0.02]],
"Epi_Rane_d": [[1.7,0.3], [2.4,0.1]],
}
for dataset in data_ediagram.data:
#print(dataset)
firstname = dataset['labels'][0]
fig, ax = pp.subplots(1, num=firstname)
ax.plot(line[0], line[1], color="k")
lens = list(map(len, dataset['al']))
for idx in range(len(lens)):
labelidx = sum(lens[:idx])
label = dataset['labels'][labelidx]
aldata = dataset['al'][idx]
fedata = dataset['fe'][idx]
ax.plot(aldata, fedata, linestyle="", marker="o", label=label)
ax.annotate("Epidote", labelpositions[firstname][0])
ax.annotate("Zoisite/Clinozoisite", labelpositions[firstname][1])
ax.legend(frameon=False)
ax.set_xlabel("Al")
ax.set_ylabel("Fe+3")
fig.savefig(f"eplot_{firstname}")
pp.show()
def plotPTdiagram():
plots = {i: pp.subplots(1, num=i) for i in ["E", "F", "R"]}
colors={"core": "tab:blue", "transition": "tab:orange", "rim": "tab:green"}
for label in data_ptdiagram.data:
print(label)
fig, ax = pp.subplots(1, num=label)
for region in ["core", "transition", "rim"]:
# individual sample plot
ax.plot(data_ptdiagram.data[label][region]["t"], data_ptdiagram.data[label][region]["p"], marker="o", linestyle="", label=region)
# overview plot
plots[label[0]][1].plot(data_ptdiagram.data[label][region]["t"],
data_ptdiagram.data[label][region]["p"],
marker="o", linestyle="", color=colors[region])
ax.legend(frameon=False)
ax.set_ylabel("p [kbar]")
ax.set_xlabel("T [°C]")
ax.set_title(label)
fig.savefig(f"ptplot_{label}.png")
names = {"E": "E11", "F": "Fro", "R": "Rane"}
for plot in plots:
plots[plot][1].set_ylabel("p [kbar]")
plots[plot][1].set_xlabel("T [°C]")
plots[plot][1].set_title(names[plot])
plots[plot][0].savefig(f"ptplot_{plot}overview.png")
#pp.show()
if __name__ == "__main__":
pass
#plotTdiagram()
#plotUdiagram()
plotZdiagram()
#plotZdiagram()
#plotEdiagram()
plotPTdiagram()

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