{ "cells": [ { "cell_type": "code", "execution_count": 1, "id": "a3c17f52-de4f-4454-b77f-0fa439a27baa", "metadata": {}, "outputs": [], "source": [ "import Thermobar as pt\n", "import pandas as pd\n", "import numpy as np\n", "import matplotlib.pyplot as plt" ] }, { "cell_type": "markdown", "id": "cba190f4-91af-4b64-91a4-5cf39f5a9f1d", "metadata": {}, "source": [ "## Load in data here from your system - in this case some data from La Palma compiled by David Neave" ] }, { "cell_type": "code", "execution_count": 2, "id": "68bff4d6-9402-4d81-a14d-002af003f482", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "C:\\Users\\penny\\anaconda3\\lib\\site-packages\\openpyxl\\worksheet\\_reader.py:312: UserWarning: Unknown extension is not supported and will be removed\n", " warn(msg)\n" ] } ], "source": [ "out=pt.import_excel('teneguia1971_py.xlsx', sheet_name=\"Liquid\")\n", "#input_Liqs=out['my_input']\n", "Liquids1=out['Liqs']\n", "\n", "out2=pt.import_excel('teneguia1971_py.xlsx', sheet_name=\"Pyroxene\")\n", "#input_Cpxs=out2['my_input']\n", "Cpxs1=out2['Cpxs']\n", "\n", "out3=pt.import_excel('teneguia1971_py.xlsx', sheet_name=\"Amphibole\")\n", "#input_Amps=out3['my_input']\n", "Amps1=out3['Amps']\n", "Amp_input=out3['my_input']" ] }, { "cell_type": "markdown", "id": "9f241e36-4966-4639-8a29-c585b2953ed0", "metadata": {}, "source": [ "## Calculate P and T using Ridolfi 2021" ] }, { "cell_type": "code", "execution_count": 3, "id": "ad0ff5c2-d600-419d-bf60-87ec8d7c2661", "metadata": {}, "outputs": [], "source": [ "PT_Ridolfi=pt.calculate_amp_only_press_temp(amp_comps=Amps1, equationT=\"T_Ridolfi2012\", equationP=\"P_Ridolfi2021\")" ] }, { "cell_type": "markdown", "id": "fd3e2b88-17b7-492e-b5c9-742cf97a9b86", "metadata": {}, "source": [ "## Now you may want to plot this within the calibration range.\n", "- There are two ways to do this, first you can use the test=pt.return_Ridolfi21_cali_dataset() function to get the calibration dataset as a dataframe, which you can then plot using matplotlib anyway you want. " ] }, { "cell_type": "code", "execution_count": 4, "id": "bcf20a27-f00d-44d0-ba0d-9b3f55d1576a", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0, 0.5, 'SiO$_2$ Amp')" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "Ridolfi_Cali=pt.return_Ridolfi21_cali_dataset()\n", "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(10,5))\n", "ax1.plot(PT_Ridolfi['T_K_calc'], PT_Ridolfi['P_kbar_calc'], '^k', mfc='red', ms=8, label='Data')\n", "ax1.plot(Ridolfi_Cali['T_K'], Ridolfi_Cali['P_kbar'], 'ok', mfc='white', ms=5, label='Cali')\n", "ax1.legend()\n", "ax1.set_xlabel('Temp (K)')\n", "ax1.set_ylabel('Pressure (kbar)')\n", "\n", "ax2.plot(PT_Ridolfi['Al2O3_Amp'], PT_Ridolfi['Na2O_Amp'], '^k', mfc='red', ms=8, label='Data')\n", "ax2.plot(Ridolfi_Cali['Al2O3_Amp'], Ridolfi_Cali['Na2O_Amp'], 'ok', mfc='white', ms=5, label='Cali')\n", "ax2.legend()\n", "ax2.set_xlabel('Al$_2$O$_3$ Amp')\n", "ax2.set_ylabel('SiO$_2$ Amp')\n", "\n" ] }, { "cell_type": "markdown", "id": "93c78014-8bee-4b95-a33a-9a565251e124", "metadata": {}, "source": [ "- Alternatively, you can use this built in function to plot specific x and y values" ] }, { "cell_type": "code", "execution_count": 5, "id": "004cc79a-a1a3-4f88-b543-ebdde153e277", "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "a=pt.Ridolfi21_cali_plot(amp_comps=Amps1,\n", " x='Na2O_Amp', y='Al2O3_Amp'\n", ")" ] }, { "cell_type": "markdown", "id": "e3e9dcb7-fd46-44a8-b2bf-b6cb4bc75106", "metadata": {}, "source": [ "- If you want to plot P and T, you have to tell the plotting function what these are" ] }, { "cell_type": "code", "execution_count": 6, "id": "a43c97b5-4233-499d-bb9e-dd67daa4cf26", "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "a=pt.Ridolfi21_cali_plot(amp_comps=Amps1, P_kbar=PT_Ridolfi['P_kbar_calc'],\n", " T_K=PT_Ridolfi['T_K_calc'], \n", " x='P_kbar', y='T_K')" ] }, { "cell_type": "markdown", "id": "8d371984-9b16-4462-a5b4-5377b2c6902e", "metadata": {}, "source": [ "- You can also edit the marker sizes etc." ] }, { "cell_type": "code", "execution_count": 9, "id": "9ac74007-f11c-44c4-bfe2-9ef3c2657dc7", "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# First, lets add our estimated water content\n", "Amp_input['H2O_Liq']=2.5\n", "\n", "\n", "b=pt.Ridolfi21_cali_plot(amp_comps=Amp_input, P_kbar=PT_Ridolfi['P_kbar_calc'],\n", " T_K=PT_Ridolfi['T_K_calc'], figsize=(7, 5),x='H2O_Liq', y='P_kbar',\n", " shape_cali='o', mfc_cali='white', mec_cali='k', ms_cali=5,\n", " shape_data='^', mfc_data='red', mec_data='k', ms_data=10)" ] }, { "cell_type": "code", "execution_count": null, "id": "a6ec27e3-06db-42d9-b203-1830b7441869", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "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": "3.8.12" } }, "nbformat": 4, "nbformat_minor": 5 }