{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# 4e. Monte Carlo approach for errors on melt composition\n", "\n", "This allows you to use a Monte Carlo approach to calculate the various compositions of a given melt within specified errors." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Python set-up\n", "You need to install VolFe once on your machine, if you haven't yet. Then we need to import a few Python packages (including VolFe). " ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "# Install VolFe on your machine. Don't remove the # from this line!\n", "# pip install VolFe # Remove the first # in this line if you have not installed VolFe on your machine before.\n", "\n", "# import python packages\n", "import pandas as pd\n", "import matplotlib.pyplot as plt\n", "import VolFe as vf" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Definte the inputs\n", "\n", "The melt composition, temperature, and associated errors can be given in a dataframe, or read from a csv file. The size of the error and its type (i.e., R = relative or A = absolute) must be specified.\n", "\n", "In this example it is read from a dataframe:" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "my_analyses = pd.read_csv(\"../files/example_marianas_wT.csv\") # load data" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Run the calculation\n", "\n", "And then calculate 50 versions (last number) for row number 29 (middle number)." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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5029120043.8979170.72130219.0665189.4898580.228886.75450513.4415311.4529660.3809940.1072294.3115991032.6130790.01610.1415170.236531
5129120043.7440460.65707919.2758499.333570.2207796.71595213.0896181.4449750.374660.1063994.7194681043.0208650.01598.5378930.23441
5229120044.5163050.65838819.1167659.2754480.2290676.67444813.5517651.4614580.3999590.1162994.531881992.9199830.01355.2407640.242655
5329120044.5123980.65974118.9955349.4483870.2123276.64202113.2729351.460070.3630850.1079754.576778870.1697990.01463.5153740.240544
\n", "
" ], "text/plain": [ "0 Sample T_C SiO2 TiO2 Al2O3 FeOT MnO \\\n", "1 Ala02-16A 1200 43.97 0.7 19.09 9.36 0.22 \n", "2 sds 0.01 0.05 0.01 0.01 0.05 \n", "3 sd types R R R R R \n", "4 29 1200 43.492294 0.700604 19.104957 9.380647 0.221504 \n", "5 29 1200 43.699984 0.789328 19.206477 9.228089 0.24087 \n", "6 29 1200 44.341452 0.708732 19.316096 9.325322 0.216973 \n", "7 29 1200 43.72343 0.782993 19.165176 9.448362 0.21416 \n", "8 29 1200 44.327725 0.703916 19.171718 9.337419 0.215364 \n", "9 29 1200 43.445399 0.709615 19.048732 9.383361 0.209258 \n", "10 29 1200 43.665766 0.648681 18.981298 9.309443 0.214209 \n", "11 29 1200 44.686811 0.720756 19.085082 9.472572 0.217927 \n", "12 29 1200 44.200792 0.744299 19.14058 9.193596 0.221465 \n", "13 29 1200 44.713282 0.676253 19.089949 9.456022 0.22656 \n", "14 29 1200 44.240178 0.65719 19.206907 9.310391 0.210962 \n", "15 29 1200 43.908047 0.679829 18.980097 9.371746 0.208664 \n", "16 29 1200 44.150178 0.667668 18.699405 9.347138 0.222872 \n", "17 29 1200 44.432107 0.652906 19.234759 9.404858 0.23594 \n", "18 29 1200 43.981403 0.722547 19.171629 9.51004 0.21115 \n", "19 29 1200 44.297989 0.622613 19.350142 9.324711 0.221942 \n", "20 29 1200 44.148016 0.738097 19.366471 9.354367 0.219616 \n", "21 29 1200 44.7145 0.661599 19.263313 9.224883 0.215717 \n", "22 29 1200 43.663924 0.745548 19.031171 9.264562 0.20557 \n", "23 29 1200 44.424053 0.690766 19.110631 9.456249 0.240029 \n", "24 29 1200 43.796838 0.710532 19.541126 9.58271 0.199618 \n", "25 29 1200 44.587223 0.70231 19.461602 9.319447 0.220242 \n", "26 29 1200 44.442309 0.690041 19.15542 9.475661 0.223572 \n", "27 29 1200 43.90267 0.724708 19.231145 9.292592 0.237997 \n", "28 29 1200 43.12831 0.713801 19.271057 9.420975 0.248435 \n", "29 29 1200 44.306994 0.728679 18.923893 9.271533 0.223005 \n", "30 29 1200 43.76908 0.680471 19.070716 9.378608 0.205754 \n", "31 29 1200 43.392221 0.685353 19.08496 9.307277 0.191188 \n", "32 29 1200 44.324145 0.769371 19.129561 9.342489 0.231949 \n", "33 29 1200 44.736429 0.678605 18.961839 9.50516 0.219787 \n", "34 29 1200 44.046685 0.683486 19.211456 9.26906 0.223999 \n", "35 29 1200 43.580517 0.735733 19.053397 9.339462 0.232999 \n", "36 29 1200 44.50666 0.678726 19.578375 9.394451 0.22845 \n", "37 29 1200 44.67878 0.781093 18.675126 9.194347 0.22292 \n", "38 29 1200 43.701506 0.63293 19.208332 9.234954 0.210494 \n", "39 29 1200 43.049115 0.686705 19.618806 9.486796 0.236432 \n", "40 29 1200 44.770515 0.708771 18.963172 9.395814 0.217261 \n", "41 29 1200 43.263535 0.718849 19.278691 9.401648 0.200404 \n", "42 29 1200 43.940875 0.736015 18.882935 9.335818 0.224211 \n", "43 29 1200 44.171598 0.729358 19.065782 9.459613 0.215508 \n", "44 29 1200 43.353353 0.729949 19.238693 9.344044 0.204355 \n", "45 29 1200 43.642745 0.759195 19.002606 9.448796 0.225489 \n", "46 29 1200 43.859826 0.666607 18.860764 9.349348 0.220956 \n", "47 29 1200 43.65781 0.705336 19.485612 9.475089 0.202206 \n", "48 29 1200 43.349076 0.747788 18.824621 9.240216 0.217991 \n", "49 29 1200 44.094892 0.665216 19.232082 9.338916 0.225369 \n", "50 29 1200 43.897917 0.721302 19.066518 9.489858 0.22888 \n", "51 29 1200 43.744046 0.657079 19.275849 9.33357 0.220779 \n", "52 29 1200 44.516305 0.658388 19.116765 9.275448 0.229067 \n", "53 29 1200 44.512398 0.659741 18.995534 9.448387 0.212327 \n", "\n", "0 MgO CaO Na2O K2O P2O5 H2O CO2ppm \\\n", "1 6.76 13.28 1.46 0.37 0.11 4.32 999 \n", "2 0.01 0.01 0.01 0.05 0.05 0.25 75 \n", "3 R R R R R A A \n", "4 6.776891 13.363895 1.481518 0.371929 0.107746 4.667413 1027.370362 \n", "5 6.842727 13.374412 1.46053 0.376602 0.113082 4.12724 1021.121919 \n", "6 6.891873 13.161528 1.485737 0.391169 0.117245 4.362767 1029.989059 \n", "7 6.845775 13.429698 1.468796 0.326891 0.109856 4.472351 926.945077 \n", "8 6.773963 13.141357 1.447546 0.334356 0.114912 4.333905 945.508938 \n", "9 6.650155 13.304776 1.488822 0.354108 0.117471 4.216744 843.519806 \n", "10 6.686915 13.197334 1.475805 0.378279 0.113747 4.315099 1193.8749 \n", "11 6.780296 13.460011 1.488355 0.392499 0.109724 4.338568 1138.164016 \n", "12 6.740652 13.299842 1.478217 0.361144 0.116281 4.39815 1082.733319 \n", "13 6.790454 13.258116 1.463195 0.390343 0.109899 4.276809 942.325382 \n", "14 6.813238 13.520333 1.448826 0.36463 0.102059 4.070174 947.933566 \n", "15 6.811198 13.079984 1.433581 0.347361 0.113575 4.424176 1000.06122 \n", "16 6.732251 13.205388 1.45673 0.391725 0.108969 3.856246 986.455957 \n", "17 6.786409 13.370133 1.481343 0.398791 0.112005 3.914394 1078.658085 \n", "18 6.711398 13.365762 1.46213 0.416281 0.102292 4.403714 935.676198 \n", "19 6.717626 13.343027 1.465968 0.380829 0.113261 4.045715 1045.052683 \n", "20 6.673864 13.1454 1.440118 0.373962 0.112602 4.339856 1008.782977 \n", "21 6.686877 13.230175 1.453365 0.386632 0.109087 4.106869 931.102199 \n", "22 6.737609 13.441857 1.454634 0.378786 0.108398 4.409521 874.132132 \n", "23 6.825719 13.389175 1.476053 0.381389 0.111292 4.176697 997.771692 \n", "24 6.746838 13.358001 1.473664 0.35609 0.109681 4.331799 1040.875407 \n", "25 6.715725 13.310739 1.446644 0.387752 0.10878 4.460826 979.891431 \n", "26 6.775171 13.212262 1.456161 0.352139 0.1082 4.247956 1061.791376 \n", "27 6.751415 13.190443 1.437604 0.354914 0.117909 4.675176 976.122926 \n", "28 6.74914 13.066253 1.467704 0.407568 0.113431 4.303281 963.087801 \n", "29 6.718395 13.279591 1.452717 0.345827 0.112789 4.593974 1160.669133 \n", "30 6.765318 13.062402 1.472113 0.376461 0.108449 4.170577 996.037704 \n", "31 6.908128 13.367261 1.45352 0.400263 0.107726 4.47365 1122.775035 \n", "32 6.752541 13.440442 1.43367 0.400788 0.105656 4.30654 921.13761 \n", "33 6.894508 13.410175 1.476835 0.348503 0.119127 4.08783 1036.652657 \n", "34 6.818507 13.208145 1.45779 0.336217 0.112302 4.653409 1035.074529 \n", "35 6.794395 13.348612 1.450421 0.360893 0.110183 4.12065 995.061245 \n", "36 6.861766 13.373681 1.457784 0.375266 0.114059 4.825341 863.556293 \n", "37 6.803605 13.482582 1.477621 0.3355 0.112655 4.468948 995.328127 \n", "38 6.649366 13.149255 1.455507 0.396825 0.10778 3.951969 980.035533 \n", "39 6.732568 13.095247 1.462762 0.360359 0.103343 4.169188 1081.523262 \n", "40 6.785645 13.274776 1.444858 0.385249 0.117641 4.238615 1089.025268 \n", "41 6.786487 13.290115 1.436638 0.402499 0.105152 4.360818 996.144351 \n", "42 6.884706 13.277355 1.455011 0.385394 0.11312 4.058611 1039.751455 \n", "43 6.809008 13.30287 1.458624 0.342678 0.108302 4.676664 1026.426587 \n", "44 6.776455 13.34937 1.458403 0.393296 0.116069 3.956577 1113.844319 \n", "45 6.740649 13.478277 1.438106 0.380612 0.110198 3.952846 1056.435717 \n", "46 6.697337 13.162407 1.489681 0.366784 0.110183 4.288626 997.156506 \n", "47 6.842934 13.15392 1.435485 0.366094 0.107631 4.164924 955.978183 \n", "48 6.708542 13.700027 1.455188 0.370771 0.102871 3.70975 1054.907963 \n", "49 6.871103 13.512645 1.471766 0.351561 0.109482 4.148637 960.052889 \n", "50 6.754505 13.441531 1.452966 0.380994 0.107229 4.311599 1032.613079 \n", "51 6.715952 13.089618 1.444975 0.37466 0.106399 4.719468 1043.020865 \n", "52 6.674448 13.551765 1.461458 0.399959 0.116299 4.531881 992.919983 \n", "53 6.642021 13.272935 1.46007 0.363085 0.107975 4.576778 870.169799 \n", "\n", "0 Xppm STppm Fe3FeT \n", "1 0 1544.07 0.238 \n", "2 0 100 0.005 \n", "3 A A A \n", "4 0.0 1522.486314 0.232664 \n", "5 0.0 1395.069449 0.227176 \n", "6 0.0 1385.235187 0.228095 \n", "7 0.0 1592.957784 0.244078 \n", "8 0.0 1627.374309 0.245801 \n", "9 0.0 1635.593573 0.232164 \n", "10 0.0 1599.545616 0.235223 \n", "11 0.0 1543.860302 0.231942 \n", "12 0.0 1587.460345 0.241328 \n", "13 0.0 1635.258895 0.243809 \n", "14 0.0 1564.337144 0.250178 \n", "15 0.0 1613.930774 0.235752 \n", "16 0.0 1775.324305 0.243901 \n", "17 0.0 1801.188876 0.231448 \n", "18 0.0 1618.881682 0.227654 \n", "19 0.0 1304.673451 0.239003 \n", "20 0.0 1600.995744 0.235279 \n", "21 0.0 1704.918711 0.243478 \n", "22 0.0 1629.267272 0.241317 \n", "23 0.0 1632.991298 0.240582 \n", "24 0.0 1699.692866 0.230592 \n", "25 0.0 1532.633418 0.238441 \n", "26 0.0 1585.042808 0.248404 \n", "27 0.0 1517.690863 0.236569 \n", "28 0.0 1712.09 0.236268 \n", "29 0.0 1678.2394 0.227182 \n", "30 0.0 1539.622349 0.238542 \n", "31 0.0 1533.027369 0.23362 \n", "32 0.0 1404.296101 0.238582 \n", "33 0.0 1441.358521 0.237492 \n", "34 0.0 1658.016188 0.232469 \n", "35 0.0 1604.00072 0.234714 \n", "36 0.0 1752.785814 0.247001 \n", "37 0.0 1635.701246 0.23757 \n", "38 0.0 1778.122711 0.239776 \n", "39 0.0 1539.761708 0.233111 \n", "40 0.0 1601.733763 0.233946 \n", "41 0.0 1620.295963 0.244046 \n", "42 0.0 1549.050372 0.234062 \n", "43 0.0 1615.544955 0.23025 \n", "44 0.0 1538.60807 0.231908 \n", "45 0.0 1514.782862 0.23424 \n", "46 0.0 1578.398163 0.236465 \n", "47 0.0 1413.343724 0.23962 \n", "48 0.0 1488.514135 0.240292 \n", "49 0.0 1443.89743 0.229757 \n", "50 0.0 1610.141517 0.236531 \n", "51 0.0 1598.537893 0.23441 \n", "52 0.0 1355.240764 0.242655 \n", "53 0.0 1463.515374 0.240544 " ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "vf.calc_comp_error(my_analyses,29,50)" ] } ], "metadata": { "kernelspec": { "display_name": "base", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.11.7" } }, "nbformat": 4, "nbformat_minor": 2 }