{ "metadata": { "name": "", "signature": "sha256:82c1deb7a650eab5a3de4973bbc07ca92620d64ddb87ba6764770b237b4d115e" }, "nbformat": 3, "nbformat_minor": 0, "worksheets": [ { "cells": [ { "cell_type": "heading", "level": 1, "metadata": {}, "source": [ "Supporting information for \"Full vector low-temperature magnetic measurements of geologic materials\"" ] }, { "cell_type": "heading", "level": 1, "metadata": {}, "source": [ "Introduction" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This IPython notebook contains data analysis associated with the paper:\n", "\n", "> **Full vector low-temperature magnetic measurements of geologic materials**\n", "\ufffc\n", "\n", "> Joshua M. Feinberg $^1$, Peter A. Solheid $^1$, Nicholas L. Swanson-Hysell $^{1,2}$, Mike Jackson $^1$ and Julie A. Bowles $^{1,3}$\n", "\n", "> $^1$Institute for Rock Magnetism, University of Minnesota, Minneapolis, MN, USA;\n", "$^2$Department of Earth and Planetary Science, University of California, Berkeley\n", "CA, USA;\n", "$^3$Department of Geosciences, University of Wisconsin, Milwaukee, WI, USA\n", "\n", "This notebook is part of the paper's supporting online materials and is available at https://github.com/Swanson-Hysell/2014_Feinberg-et-al_LowT along with the necessary files to execute the code. Within this github repository are the following folders:\n", "\n", "1. [Code](https://github.com/Swanson-Hysell/2014_Feinberg-et-al_LowT/tree/master/Code) This folder contains this notebook file as well as necessary non-standard function libraries.\n", "2. [Data](https://github.com/Swanson-Hysell/2014_Feinberg-et-al_LowT/tree/master/Data) This folder contains the data generated for the case studies presented in this work that are used in the data analysis and presented in the paper.\n", "3. [Manuscript](https://github.com/2014_Feinberg-et-al_LowT/tree/master/Manuscript) This folder contains the paper text and figures.\n", "\n", "If you are viewing this supporting material as a PDF document and want to run the code in the notebook you will need to download the code from the Github repository and you will also need a Python distribution that includes IPython and the other standard scientific python libraries. There are good instructions for installing IPython/jupyter here: http://ipython.org/install.html. Alternatively you can view the notebook online with the jupyter nbviewer at this link: https://nbviewer.jupyter.org/github/swanson-hysell/2014_Feinberg-et-al_low-temp/blob/master/Code/LowT_Data_Analysis.ipynb or this shortened version: http://bit.ly/1slx6p2\n", "\n", "Within this notebook there are data from runs on a variety of types of specimens:\n", "\n", "* **Magnetite**: isothermal remanent magnetizations applied to a single magnetite crystal\n", "* **Hematite**: isothermal remanent magnetization applied to a strongly foliated polycrystalline hematite sample\n", "* **Hematite/Magnetite**: isothermal remanent magnetization applied to a Nature Company polycrystalline sample comprised of hematite and trace magnetite\n", "* **Pyrrhotite**: isothermal remanent magnetization applied to a a single crystal of pyrrhotite\n", "* **Coarse-grained diabase**: natural and anhysteric remanent magnetizations for samples collected from the coarse grained interior of sills from the Umkondo Large Igneous Province of Botswana" ] }, { "cell_type": "heading", "level": 1, "metadata": {}, "source": [ "Import needed libraries into notebook environment" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The numpy, scipy, matplotlib and pandas libraries are standard libraries for scientific python (see http://www.scipy.org). The pmag and pmagplotlib libraries are part of the PmagPy project and can be obtained from that project's github repository (https://github.com/ltauxe/PmagPy). The check_updates and get_version functions of the PmagPy libraries cause errors in the interactive environment of IPython so the code below uses a slightly modified version of those libraries that is included in the Github repository for this work. There are other functions that are necessary for the interactive plotting of paleomagnetic data (some of them edited from PmagPy) that are within the IPmag.py (see https://github.com/Swanson-Hysell/PmagPy_IPython) library that is imported in the code block below." ] }, { "cell_type": "code", "collapsed": false, "input": [ "import pmag, pmagplotlib, IPmag\n", "import numpy as np\n", "from scipy import interpolate\n", "import pandas as pd\n", "from IPython.display import display, Image, display_svg, SVG\n", "import matplotlib.pyplot as plt\n", "%matplotlib inline" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 1 }, { "cell_type": "markdown", "metadata": {}, "source": [ "When the notebook is being exported into a PDF it looks much better to have the plots be in svg format rather than png. However, when viewing the notebook as rendered html it is much faster to have the plots be png files so this line will generally be commented out." ] }, { "cell_type": "code", "collapsed": false, "input": [ "#%config InlineBackend.figure_format = 'svg'" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 2 }, { "cell_type": "heading", "level": 2, "metadata": {}, "source": [ "Background subtraction function" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "As discussed in the main text and figures, subtracting the magnetization of the blank probe is a necessary aspect of the data analysis. In order to do so, let's define a function called background_subtraction() that we can use to subtract data of a blank probe run (without a loaded sample) from data experimental runs on specimens. This function uses a spline fit to the background holder data in order to interpolate data to the temperatures where measurements were taking during the sample runs. Examples of fits to background data and subsequent background subtraction are given later in this notebook." ] }, { "cell_type": "code", "collapsed": false, "input": [ "def background_sub(background_moment, background_temp, \n", " measurement_moment, measurement_temp):\n", " \"\"\"\n", " subtract out data from a blank run from measurement data from a sample\n", " \n", " This function takes data measured with the holder alone and subtracts \n", " it from sample measurement data by interpolating that blank run at the\n", " temperatures for which data were \n", " \"\"\"\n", " x = background_temp\n", " y = background_moment\n", " spline = interpolate.splrep(x,y,s=0)\n", " xnew = measurement_temp\n", " background_moment_interpolated = interpolate.splev(xnew,spline,der=0)\n", " bsub_moment = measurement_moment - background_moment_interpolated\n", " return bsub_moment" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 3 }, { "cell_type": "heading", "level": 1, "metadata": {}, "source": [ "Polycrystalline hematite experiments" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "A polycrystalline hematite sample \"Labrador hematite\" was pulsed with a 1.2 T field to impart an isothermal remanent magentization (IRM) along the z axis which was then cycled from room temperature to ~130 K and back using the Institute for Rock Magnetism low temperature probe (IRM-LTI) in a superconducting rock magnetometer to collect full vector data. A low-temperature cycling experiment was also conducted using a Magnetic Properties Measurement System (MPMS) to collect 1-axis data." ] }, { "cell_type": "heading", "level": 2, "metadata": {}, "source": [ "IRM-LTI experiment" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The data from the IRM-LTI experiment (cooling and warming data separately) can be loaded into a dataframe with the first 5 rows of the dataframe displayed using the .head() function. Note that this .head() function will be used throughout this notebook in order to give a glimpse of the data without taking the space to print all of the data out. All the data files loaded into the notebook are availible in the Github repository." ] }, { "cell_type": "code", "collapsed": false, "input": [ "Labr_hem_cooling = pd.read_csv('../Data/Labr_hematite/Labr_hem_cooling.csv')\n", "Labr_hem_warming = pd.read_csv('../Data/Labr_hematite/Labr_hem_warming.csv')\n", "Labr_hem_warming.head()" ], "language": "python", "metadata": {}, "outputs": [ { "html": [ "
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specimenMx[Am2]My[Am2]Mz[Am2]MN[Am2]ME[Am2]MV[Am2]Mtot[Am2]Dec[deg]Inc[deg]...timeseriesposition[cm]Drift_ratioJa/Jrrun#DescriptionMeas_T[K]ModeType
0 Labrador hematite 02a-7.398300e-08-1.075430e-08-0-0-1.075430e-08 7.398300e-08 0.000000 181.371 9.34415... 1:25:55 PM 1NaNNaN 0NaN NaN 128 DISCRETENaN
1 Labrador hematite 02a-7.496650e-08-2.935900e-09-0-0-2.935900e-09 7.496650e-08 0.000000 180.373 9.44262... 1:33:42 PM 1NaNNaN 0NaN NaN 133 DISCRETENaN
2 Labrador hematite 02a-7.558250e-08-1.850900e-09-0-0-1.850900e-09 7.558250e-08 0.000000 180.238 9.62523... 1:42:26 PM 1NaNNaN 0NaN NaN 139 DISCRETENaN
3 Labrador hematite 02a-7.607250e-08-1.196550e-09-0-0-1.196550e-09 7.607250e-08 0.000000 180.155 9.77792... 1:48:29 PM 1NaNNaN 0NaN NaN 143 DISCRETENaN
4 Labrador hematite 02a-8.034000e-08-2.277900e-09-0-0-2.277900e-09 8.034000e-08 0.000001 180.264 9.23522... 1:55:15 PM 1NaNNaN 0NaN NaN 148 DISCRETENaN
\n", "

5 rows \u00d7 35 columns

\n", "
" ], "metadata": {}, "output_type": "pyout", "prompt_number": 4, "text": [ " specimen Mx[Am2] My[Am2] Mz[Am2] MN[Am2] \\\n", "0 Labrador hematite 02a -7.398300e-08 -1.075430e-08 -0 -0 \n", "1 Labrador hematite 02a -7.496650e-08 -2.935900e-09 -0 -0 \n", "2 Labrador hematite 02a -7.558250e-08 -1.850900e-09 -0 -0 \n", "3 Labrador hematite 02a -7.607250e-08 -1.196550e-09 -0 -0 \n", "4 Labrador hematite 02a -8.034000e-08 -2.277900e-09 -0 -0 \n", "\n", " ME[Am2] MV[Am2] Mtot[Am2] Dec[deg] Inc[deg] ... \\\n", "0 -1.075430e-08 7.398300e-08 0.000000 181.371 9.34415 ... \n", "1 -2.935900e-09 7.496650e-08 0.000000 180.373 9.44262 ... \n", "2 -1.850900e-09 7.558250e-08 0.000000 180.238 9.62523 ... \n", "3 -1.196550e-09 7.607250e-08 0.000000 180.155 9.77792 ... \n", "4 -2.277900e-09 8.034000e-08 0.000001 180.264 9.23522 ... \n", "\n", " time series position[cm] Drift_ratio Ja/Jr run# Description \\\n", "0 1:25:55 PM 1 NaN NaN 0 NaN NaN \n", "1 1:33:42 PM 1 NaN NaN 0 NaN NaN \n", "2 1:42:26 PM 1 NaN NaN 0 NaN NaN \n", "3 1:48:29 PM 1 NaN NaN 0 NaN NaN \n", "4 1:55:15 PM 1 NaN NaN 0 NaN NaN \n", "\n", " Meas_T[K] Mode Type \n", "0 128 DISCRETE NaN \n", "1 133 DISCRETE NaN \n", "2 139 DISCRETE NaN \n", "3 143 DISCRETE NaN \n", "4 148 DISCRETE NaN \n", "\n", "[5 rows x 35 columns]" ] } ], "prompt_number": 4 }, { "cell_type": "markdown", "metadata": {}, "source": [ "During the warming portion of the experiment one of the data points was collected during a flux jump on the SRM that was noted by the analyzer at the time and therefore has 'flux jump' in the 'Description' column. This point should be removed from the dataframe." ] }, { "cell_type": "code", "collapsed": false, "input": [ "Labr_hem_warming = Labr_hem_warming[Labr_hem_warming['Description'] != 'flux jump']\n", "Labr_hem_warming.reset_index(inplace=True)" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 5 }, { "cell_type": "markdown", "metadata": {}, "source": [ "The M$_x$, M$_y$, M$_z$, M$_{total}$ values can be plotted as a function of temperature for this experiment showing the pronounced loss of remenance associated with cooling through hematite's Morin transition." ] }, { "cell_type": "code", "collapsed": false, "input": [ "plt.figure(figsize=(5,5))\n", "plt.plot(Labr_hem_cooling['Meas_T[K]'], Labr_hem_cooling['Mx[Am2]'], \n", " 'rs-',label='M$_x$ cooling')\n", "plt.plot(Labr_hem_cooling['Meas_T[K]'], Labr_hem_cooling['My[Am2]'], \n", " 'bs-',label='M$_y$ cooling')\n", "plt.plot(Labr_hem_cooling['Meas_T[K]'], Labr_hem_cooling['Mz[Am2]'], \n", " 'gs-',label='M$_z$ cooling')\n", "plt.plot(Labr_hem_cooling['Meas_T[K]'], Labr_hem_cooling['Mtot[Am2]'], \n", " 'ks-',label='M$_{total}$ cooling')\n", "plt.plot(Labr_hem_warming['Meas_T[K]'], Labr_hem_warming['Mx[Am2]'], \n", " 'ro-',label='M$_x$ warming')\n", "plt.plot(Labr_hem_warming['Meas_T[K]'], Labr_hem_warming['My[Am2]'], \n", " 'bo-',label='M$_y$ warming')\n", "plt.plot(Labr_hem_warming['Meas_T[K]'], Labr_hem_warming['Mz[Am2]'], \n", " 'go-',label='M$_z$ warming')\n", "plt.plot(Labr_hem_warming['Meas_T[K]'], Labr_hem_warming['Mtot[Am2]'], \n", " 'ko-',label='M$_{total}$ warming')\n", "plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)\n", "plt.xlabel('temperature (K)')\n", "plt.ylabel('Magnetic moment (Am$^2$)')\n", "plt.title('Labrador hematite IRM thermal cycling (no background subtraction)')\n", "plt.show()" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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qwTrP77fzd90PPNtgOpYHpdSWe0BVcz3SNdR+E4F3VPUIhqAh/jvUbYf9JPtHrIk4f1PV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\nnT+QGTNmsGTJEhISEqrFbdmypcqVb13iEhMT6dWrF6mpfmdmr2jwi4q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"text": [ "" ] } ], "prompt_number": 6 }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "Background subtraction" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "These data need to have the background subtracted from them. We will use a run of the blank probe without a loaded sample that was conducted on 04/28/2010. Data from that blank run is imported into dataframes and plotted below." ] }, { "cell_type": "code", "collapsed": false, "input": [ "blank_hem_data_cooling = pd.read_csv('../Data/Labr_hematite/20100428_blank_cooling.csv')\n", "blank_hem_data_warming = pd.read_csv('../Data/Labr_hematite/20100428_blank_warming.csv')\n", "\n", "fignum=1\n", "plt.figure(num=fignum,figsize=(6,3))\n", "plt.plot(blank_hem_data_cooling['Meas_T[K]'], blank_hem_data_cooling['Mx[Am2]'], 'rs',\n", " label='Mx cooling')\n", "plt.plot(blank_hem_data_warming['Meas_T[K]'], blank_hem_data_warming['Mx[Am2]'], 'ro',\n", " label='Mx warming')\n", "plt.plot(blank_hem_data_cooling['Meas_T[K]'], blank_hem_data_cooling['My[Am2]'], 'bs',\n", " label='My cooling')\n", "plt.plot(blank_hem_data_warming['Meas_T[K]'], blank_hem_data_warming['My[Am2]'], 'bo',\n", " label='My warming')\n", "plt.plot(blank_hem_data_cooling['Meas_T[K]'], blank_hem_data_cooling['Mz[Am2]'], 'gs',\n", " label='Mz cooling')\n", "plt.plot(blank_hem_data_warming['Meas_T[K]'], blank_hem_data_warming['Mz[Am2]'], 'go',\n", " label='Mz warming')\n", "\n", "plt.ylabel('Magnetic moment (Am$^2$)')\n", "plt.xlabel('Temperature (K)')\n", "plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)\n", "plt.title('cold finger blank run (04/28/2010)')\n", "plt.show()" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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GBs888wyqysMPP+xT3r333sv69ev5+uuvOXz4MM8//zwhISFs27aNW2+9lWnTpnHw4EH6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\nuG5nY75zTjuNoYMHU151mDHDBiW1ZUBA+r6/vEXt8Si9KUH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0ESkFhqjqHRnynY132Wxq\nuzTMGNPl2ciNMV1fV/0L5QlgivgXuQl2PfDzdmiPMSZH2MiNMcYYY3KKjdwYY4wxJqdYcGOMMcaY\nnGLBjTHGGGNyigU3xhhjjMkpFtwYY4wxJqf8fxsdkCuWUgmPAAAAAElFTkSuQmCC\n", "text": [ "" ] } ], "prompt_number": 7 }, { "cell_type": "markdown", "metadata": {}, "source": [ "The background_subtraction() function can be used to subtract the interpolation of data from this cold finger blank run from the measured data during the low-temperature cycling experiment on the hematite. Given that the magnetization of the cold finger looks to be more or less reversible with temperature and that there is better resolution (without a gap between 250 and 300 K) for the cooling curve, the cooling curve will be used for the background subtraction." ] }, { "cell_type": "code", "collapsed": false, "input": [ "#For the interpolate function within the background_subtraction function to \n", "#work, the x values (temperature) need to be sorted to be ascending. \n", "blank_hem_data_cooling = blank_hem_data_cooling.sort(['Meas_T[K]'])\n", "\n", "Mx_cooling_bsub = background_sub(blank_hem_data_cooling['Mx[Am2]'],\n", " blank_hem_data_cooling['Meas_T[K]'],\n", " Labr_hem_cooling['Mx[Am2]'],\n", " Labr_hem_cooling['Meas_T[K]'])\n", "\n", "My_cooling_bsub = background_sub(blank_hem_data_cooling['My[Am2]'],\n", " blank_hem_data_cooling['Meas_T[K]'],\n", " Labr_hem_cooling['My[Am2]'],\n", " Labr_hem_cooling['Meas_T[K]'])\n", "\n", "Mz_cooling_bsub = background_sub(blank_hem_data_cooling['Mz[Am2]'], \n", " blank_hem_data_cooling['Meas_T[K]'],\n", " Labr_hem_cooling['Mz[Am2]'],\n", " Labr_hem_cooling['Meas_T[K]'])\n", "\n", "Mx_warming_bsub = background_sub(blank_hem_data_cooling['Mx[Am2]'],\n", " blank_hem_data_cooling['Meas_T[K]'],\n", " Labr_hem_warming['Mx[Am2]'],\n", " Labr_hem_warming['Meas_T[K]'])\n", "\n", "My_warming_bsub = background_sub(blank_hem_data_cooling['My[Am2]'], \n", " blank_hem_data_cooling['Meas_T[K]'],\n", " Labr_hem_warming['My[Am2]'],\n", " Labr_hem_warming['Meas_T[K]'])\n", "\n", "Mz_warming_bsub = background_sub(blank_hem_data_cooling['Mz[Am2]'],\n", " blank_hem_data_cooling['Meas_T[K]'],\n", " Labr_hem_warming['Mz[Am2]'],\n", " Labr_hem_warming['Meas_T[K]'])\n", "\n", "#calculate the full vector after background subtraction\n", "Mtotal_cooling = np.sqrt(Mx_cooling_bsub**2+My_cooling_bsub**2+Mz_cooling_bsub**2)\n", "Mtotal_warming = np.sqrt(Mx_warming_bsub**2+My_warming_bsub**2+Mz_warming_bsub**2)\n", "#the specimen weighs 1.0129 g to get the units into Am2/kg let's divide by 1.0129/1000\n", "Mtotal_cooling_mass_normalized = Mtotal_cooling/(1.0129/1000)\n", "Mtotal_warming_mass_normalized = Mtotal_warming/(1.0129/1000)" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 8 }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "Directional data" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In addition to plotting the magnetization along each axis, the directions of the data can be plotted on an equal area plot. The code below generates a plot that shows the directions from throughout the low-temperature cycling both without background subtraction and with background subtraction." ] }, { "cell_type": "code", "collapsed": false, "input": [ "directions_cooling_cart=[]\n", "directions_warming_cart=[]\n", "\n", "for n in range(len(Labr_hem_cooling)):\n", " directions_cooling_cart.append([Labr_hem_cooling['Mx[Am2]'][n],\n", " Labr_hem_cooling['My[Am2]'][n],\n", " Labr_hem_cooling['Mz[Am2]'][n]])\n", "for n in range(len(Labr_hem_warming)):\n", " directions_warming_cart.append([Labr_hem_warming['Mx[Am2]'][n],\n", " Labr_hem_warming['My[Am2]'][n],\n", " Labr_hem_warming['Mz[Am2]'][n]])\n", "\n", "directions_cooling_DI=pmag.cart2dir(directions_cooling_cart)\n", "directions_warming_DI=pmag.cart2dir(directions_warming_cart)\n", "\n", "directions_bsub_cooling_cart=[]\n", "directions_bsub_warming_cart=[]\n", "\n", "for n in range(len(Labr_hem_cooling)):\n", " directions_bsub_cooling_cart.append([Mx_cooling_bsub[n],\n", " My_cooling_bsub[n],\n", " Mz_cooling_bsub[n]])\n", "for n in range(len(Labr_hem_warming)):\n", " directions_bsub_warming_cart.append([Mx_warming_bsub[n],\n", " My_warming_bsub[n],\n", " Mz_warming_bsub[n]])\n", "\n", "directions_bsub_cooling_DI=pmag.cart2dir(directions_bsub_cooling_cart)\n", "directions_bsub_warming_DI=pmag.cart2dir(directions_bsub_warming_cart)\n", "\n", "fig=plt.figure(figsize=(8,5),dpi=160)\n", "\n", "plt.subplot(121)\n", "pmagplotlib.plotNET(fignum)\n", "IPmag.iplotDI(directions_cooling_DI,'b')\n", "IPmag.iplotDI(directions_warming_DI,'r')\n", "plt.title('no background correction')\n", "\n", "plt.subplot(122)\n", "pmagplotlib.plotNET(fignum)\n", "IPmag.iplotDI(directions_bsub_cooling_DI,'b')\n", "IPmag.iplotDI(directions_bsub_warming_DI,'r')\n", "plt.title('background correction')\n", "plt.savefig('code_output/Labr_hem_eqarea.pdf')\n", "plt.show()" ], "language": "python", "metadata": {}, "outputs": [ { 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BHYB5gYWAOUm5pfEi53lSfplQoETEe708b2+5ZiZSYdR4UbYIkxZTCwP/zq/xKHARKdc8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\n7814oToWOKNJLQNzAq8WjqW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"text": [ "" ] } ], "prompt_number": 9 }, { "cell_type": "markdown", "metadata": {}, "source": [ "It is clear from the above plot that the background subtraction implementation was effective in removing signal associated with the blank probe. Note that at the time of this experiment the probe was more magnetic than it is at present as there were subsequent improvements. See the main text for details." ] }, { "cell_type": "heading", "level": 2, "metadata": {}, "source": [ "MPMS experiment" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In addition to the 3-axis data obtained with the IRM-LTI, we obtained single axis data on the hematite sample using an MPMS. These data can be imported into a data frame." ] }, { "cell_type": "code", "collapsed": false, "input": [ "Labr_hem_MPMS = pd.read_csv('../Data/Labr_hematite/Labr_hem_MPMS.csv')\n", "Labr_hem_MPMS.head()" ], "language": "python", "metadata": {}, "outputs": [ { "html": [ "
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T [K]Bapp [T]M [Am2/kg]reg fittimestampT [K].1Bapp [T].1M [Am2/kg].1reg fit.1timestamp.1
0 299.9905 0 0.041991 0.970553 5/7/2010 12:11:45 PM 19.99694 0 0.001129 0.989705 5/7/10 15:18
1 294.3364 0 0.041716 0.970341 5/7/2010 12:15:20 PM 25.49144 0 0.001129 0.989654 5/7/10 15:20
2 289.1934 0 0.041456 0.970064 5/7/2010 12:16:10 PM 30.56160 0 0.001129 0.989615 5/7/10 15:21
3 284.0423 0 0.041179 0.969775 5/7/2010 12:16:56 PM 35.57994 0 0.001128 0.989613 5/7/10 15:22
4 279.7256 0 0.040682 0.969927 5/7/2010 12:19:34 PM 40.53156 0 0.001128 0.989653 5/7/10 15:23
\n", "
" ], "metadata": {}, "output_type": "pyout", "prompt_number": 10, "text": [ " T [K] Bapp [T] M [Am2/kg] reg fit timestamp T [K].1 \\\n", "0 299.9905 0 0.041991 0.970553 5/7/2010 12:11:45 PM 19.99694 \n", "1 294.3364 0 0.041716 0.970341 5/7/2010 12:15:20 PM 25.49144 \n", "2 289.1934 0 0.041456 0.970064 5/7/2010 12:16:10 PM 30.56160 \n", "3 284.0423 0 0.041179 0.969775 5/7/2010 12:16:56 PM 35.57994 \n", "4 279.7256 0 0.040682 0.969927 5/7/2010 12:19:34 PM 40.53156 \n", "\n", " Bapp [T].1 M [Am2/kg].1 reg fit.1 timestamp.1 \n", "0 0 0.001129 0.989705 5/7/10 15:18 \n", "1 0 0.001129 0.989654 5/7/10 15:20 \n", "2 0 0.001129 0.989615 5/7/10 15:21 \n", "3 0 0.001128 0.989613 5/7/10 15:22 \n", "4 0 0.001128 0.989653 5/7/10 15:23 " ] } ], "prompt_number": 10 }, { "cell_type": "heading", "level": 2, "metadata": {}, "source": [ "Comparision between IRM-LTI and MPMS data" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "As can be seen in the output of the code cell below, the magnetization measured at ~289 K (the temperature to which the plots have been normalized) for the specimen was about 33% lower on the specimen on the MPMS than on the IRM-LTI. This could be due, in part, to a portion of the magnetization being off of the one axis being measured on the MPMS although it is unlikely that a misorientation would be as great as the 48\u00ba angle that would be required for this to be the sole explanation for the difference." ] }, { "cell_type": "code", "collapsed": false, "input": [ "Labr_hem_MPMS_289 = Labr_hem_MPMS['M [Am2/kg]'][2]\n", "Labr_hem_LTI_289 = Mtotal_cooling_mass_normalized[7]\n", "print 'At this temperature (K):'\n", "print Labr_hem_MPMS['T [K]'][2]\n", "print 'The magnetization of the hematite sample on the MPMS is (Am2/kg):'\n", "print Labr_hem_MPMS_289\n", "print ''\n", "print 'At this temperature (K):'\n", "print Labr_hem_cooling['Meas_T[K]'][7]\n", "print 'The magnetization of the hematite sample on the IRM-LTI is (Am2/kg):'\n", "print Labr_hem_LTI_289\n", "print \"\"\n", "print 'The percentage difference between the magnetizations is:'\n", "print ((Labr_hem_LTI_289-Labr_hem_MPMS_289)/Labr_hem_LTI_289)*100" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "At this temperature (K):\n", "289.1934\n", "The magnetization of the hematite sample on the MPMS is (Am2/kg):\n", "0.041456254\n", "\n", "At this temperature (K):\n", "289.0\n", "The magnetization of the hematite sample on the IRM-LTI is (Am2/kg):\n", "0.0622871852112\n", "\n", "The percentage difference between the magnetizations is:\n", "33.4433658232\n" ] } ], "prompt_number": 11 }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let's make a plot where the MPMS and LTI data are normalized so that they can be directly compared. " ] }, { "cell_type": "code", "collapsed": false, "input": [ "adjustprops = dict(left=0.1, bottom=0.1, right=0.97, top=0.93, wspace=0.25, hspace=0.25)\n", "fig=plt.figure(figsize=(6,8),dpi=160)\n", "fig.subplots_adjust(**adjustprops)\n", "ax1 = plt.subplot(211)\n", "\n", "ax1.plot(Labr_hem_cooling['Meas_T[K]'], Mx_cooling_bsub/(1.0129/1000), \n", " 'rs-',label='M$_x$ cooling')\n", "ax1.plot(Labr_hem_cooling['Meas_T[K]'], My_cooling_bsub/(1.0129/1000), \n", " 'bs-',label='M$_y$ cooling')\n", "ax1.plot(Labr_hem_cooling['Meas_T[K]'], Mz_cooling_bsub/(1.0129/1000), \n", " 'gs-',label='M$_z$ cooling')\n", "ax1.plot(Labr_hem_warming['Meas_T[K]'], Mx_warming_bsub/(1.0129/1000), \n", " 'ro-',label='M$_x$ warming')\n", "ax1.plot(Labr_hem_warming['Meas_T[K]'], My_warming_bsub/(1.0129/1000), \n", " 'bo-',label='M$_y$ warming')\n", "ax1.plot(Labr_hem_warming['Meas_T[K]'], Mz_warming_bsub/(1.0129/1000), \n", " 'go-',label='M$_z$ warming')\n", "plt.legend(loc=3)\n", "plt.title('IRM-LTI 3 axis thermal cycling')\n", "plt.xlabel('Temperature (K)')\n", "plt.ylabel('Magnetization (Am$^2$/kg)')\n", "\n", "ax2 = plt.subplot(212)\n", "ax2.plot(Labr_hem_cooling['Meas_T[K]'],Mtotal_cooling_mass_normalized/Labr_hem_LTI_289, \n", " 'ks-', label='IRM-LTI cooling')\n", "ax2.plot(Labr_hem_warming['Meas_T[K]'],Mtotal_warming_mass_normalized/Labr_hem_LTI_289, \n", " 'ko-', label='IRM-LTI warming')\n", "ax2.plot(Labr_hem_MPMS['T [K]'],Labr_hem_MPMS['M [Am2/kg]']/Labr_hem_MPMS_289, \n", " 'cs-', label='MPMS cooling')\n", "ax2.plot(Labr_hem_MPMS['T [K].1'],Labr_hem_MPMS['M [Am2/kg].1']/Labr_hem_MPMS_289, \n", " 'co-', label='MPMS warming')\n", "plt.xlim(120, 300)\n", "plt.ylim(ymin=0)\n", "plt.title('MPMS thermal single axis thermal cycling')\n", "plt.xlabel('Temperature (K)')\n", "plt.ylabel('Magnetization (normalized to 289 K)')\n", "plt.legend(loc=2)\n", "plt.savefig('code_output/Labr_hem_data.pdf')\n", "plt.show()" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, 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alsqNZ95IamIqia5E3lGn6dpwIOEANy64kX3l+9ixfwdVVMFSYFiw3Ob+m7l3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\ngwa0sDmIUYMbgjgcu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"text": [ "" ] } ], "prompt_number": 12 }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "Estimating the Morin transition" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "There looks to be a slight temperature difference between loss of remanence observed using the IRM-LTI and the MPMS. This difference can be see more clearly in the gradient of the low-temperature cycling data. These gradient data can then be used to make estimates of the Morin transition temperature with each method to quantify the magnitude of this temperature difference." ] }, { "cell_type": "code", "collapsed": false, "input": [ "gradient_LTI_cooling = np.gradient(Mtotal_cooling_mass_normalized)\n", "gradient_MPMS_cooling = np.gradient(Labr_hem_MPMS['M [Am2/kg]'][0:94])\n", "gradient_LTI_warming = np.gradient(Mtotal_warming_mass_normalized)\n", "gradient_MPMS_warming = np.gradient(Labr_hem_MPMS['M [Am2/kg].1'])\n", "\n", "fig=plt.figure(figsize=(10,4))\n", "plt.plot(Labr_hem_cooling['Meas_T[K]'], gradient_LTI_cooling, \n", " 'bs-',label='LTI gradient on cooling')\n", "plt.plot(Labr_hem_MPMS['T [K]'][0:94],gradient_MPMS_cooling, \n", " 'bd-', label='MPMS gradient on cooling')\n", "plt.plot(Labr_hem_warming['Meas_T[K]'], gradient_LTI_warming, \n", " 'rs-',label='LTI gradient on warming')\n", "plt.plot(Labr_hem_MPMS['T [K].1'],gradient_MPMS_warming, \n", " 'rd-', label='MPMS gradient on warming')\n", "plt.xlim(250, 265)\n", "plt.xlabel('Temperature (K)')\n", "plt.ylabel('gradient of magnetization (Am$^2$/kg/K)')\n", "plt.legend(loc=4)\n", "plt.show()" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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PPwY6CuuWW551TdeR6fjxSaxaNZmJEwv2GfLX50+VHzrIwoPW4JVs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\neFt6586dAWjVqhUuLi5W51led+71uLm5MWrUKK5evQpAfHw8Dg4O5mu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"text": [ "" ] } ], "prompt_number": 13 }, { "cell_type": "markdown", "metadata": {}, "source": [ "To estimate the Morin temperature using these data, let's fit cubic splines to the data. For comparision of the warming and cooling data the negative of the gradient upon warming will be calculated and plotted. The plot compares the data points themselves with the interpolated spline fit." ] }, { "cell_type": "code", "collapsed": false, "input": [ "from scipy.interpolate import interp1d\n", "\n", "#interpolate the data using a cubic spline\n", "f_LTI_cooling_inter = interp1d(Labr_hem_cooling['Meas_T[K]'], gradient_LTI_cooling, \n", " kind='cubic')\n", "f_MPMS_cooling_inter = interp1d(Labr_hem_MPMS['T [K]'][0:94], gradient_MPMS_cooling, \n", " kind='cubic')\n", "f_LTI_warming_inter = interp1d(Labr_hem_warming['Meas_T[K]'], -gradient_LTI_warming, \n", " kind='cubic')\n", "f_MPMS_warming_inter = interp1d(Labr_hem_MPMS['T [K].1'], -gradient_MPMS_warming, \n", " kind='cubic')\n", "\n", "xnew = np.linspace(250,265,100)\n", "\n", "gradient_MPMS_cooling_interpolated = f_MPMS_cooling_inter(xnew)\n", "gradient_LTI_cooling_interpolated = f_LTI_cooling_inter(xnew)\n", "gradient_MPMS_warming_interpolated = f_MPMS_warming_inter(xnew)\n", "gradient_LTI_warming_interpolated = f_LTI_warming_inter(xnew)\n", "\n", "fig=plt.figure(figsize=(10,4))\n", "plt.plot(Labr_hem_cooling['Meas_T[K]'],gradient_LTI_cooling, \n", " 'bs',label='LTI gradient on cooling')\n", "plt.plot(Labr_hem_MPMS['T [K]'][0:94],gradient_MPMS_cooling, \n", " 'bd', label='MPMS gradient on cooling')\n", "plt.plot(Labr_hem_warming['Meas_T[K]'],-gradient_LTI_warming, \n", " 'rs',label='LTI gradient on warming')\n", "plt.plot(Labr_hem_MPMS['T [K].1'],-gradient_MPMS_warming, \n", " 'rd', label='MPMS gradient on warming')\n", "plt.xlim(250, 265)\n", "plt.title('MPMS thermal single axis thermal cycling')\n", "plt.xlabel('Temperature (K)')\n", "plt.ylabel('gradient of magnetization (Am$^2$/kg/K)')\n", "plt.legend(loc=4)\n", "\n", "plt.plot(xnew, gradient_MPMS_cooling_interpolated, 'b-')\n", "plt.plot(xnew, gradient_LTI_cooling_interpolated, 'b-')\n", "plt.plot(xnew, gradient_MPMS_warming_interpolated, 'r-')\n", "plt.plot(xnew, gradient_LTI_warming_interpolated, 'r-')\n", "plt.show()" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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hC4zHU+CVd7vd2ND3J18x5QTsMTHYvC8s3pcY7584JgZiYth1KINvf4ziuLMD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"text": [ "" ] } ], "prompt_number": 14 }, { "cell_type": "markdown", "metadata": {}, "source": [ "The downhill simplex algorithm as implemented in scipy.optimize can be used to find the peak of the interpolated data. This peak is the estimate of the Morin transition temperature." ] }, { "cell_type": "code", "collapsed": false, "input": [ "from scipy.optimize import fmin\n", "gradient_LTI_cooling_min = fmin(f_LTI_cooling_inter, x0=257)\n", "print 'The peak gradient for LTI cooling is at: ' + str(gradient_LTI_cooling_min)\n", "print \"\"\n", "gradient_MPMS_cooling_min = fmin(f_MPMS_cooling_inter, x0=259)\n", "print 'The peak gradient for MPMS cooling is at: ' + str(gradient_MPMS_cooling_min)\n", "print \"\"\n", "gradient_LTI_warming_min = fmin(f_LTI_warming_inter, x0=257)\n", "print 'The peak gradient for LTI warming is at: ' + str(gradient_LTI_warming_min)\n", "print \"\"\n", "gradient_MPMS_warming_min = fmin(f_MPMS_warming_inter, x0=259)\n", "print 'The peak gradient for MPMS warming is at: ' + str(gradient_MPMS_warming_min)" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "Optimization terminated successfully.\n", " Current function value: -0.019496\n", " Iterations: 18\n", " Function evaluations: 36\n", "The peak gradient for LTI cooling is at: [ 257.37332764]\n", "\n", "Optimization terminated successfully.\n", " Current function value: -0.007081\n", " Iterations: 18\n", " Function evaluations: 37\n", "The peak gradient for MPMS cooling is at: [ 259.39302902]\n", "\n", "Optimization terminated successfully.\n", " Current function value: -0.004769\n", " Iterations: 18\n", " Function evaluations: 36\n", "The peak gradient for LTI warming is at: [ 257.7300869]\n", "\n", "Optimization terminated successfully.\n", " Current function value: -0.001900\n", " Iterations: 18\n", " Function evaluations: 37\n", "The peak gradient for MPMS warming is at: [ 259.51168861]\n" ] } ], "prompt_number": 15 }, { "cell_type": "markdown", "metadata": {}, "source": [ "Given that the magnitude of the transition is greater upon cooling, we use the Morin transition temperature estimates from the cooling curves in the main text of the paper where we note that there is a 2 degree difference between the Morin transition temperature was estimated using the IRM-LTI (257.4 K) in comparision to the MPMS (259.4 K)." ] }, { "cell_type": "heading", "level": 1, "metadata": {}, "source": [ "Single crystal magnetite experiments" ] }, { "cell_type": "heading", "level": 2, "metadata": {}, "source": [ "IRM-LTI experiments" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "A specimen cut from single crystal magnetite octahedron (IKON magnetite) underwent a series of experiments where IRM magnetizations were applied along different axes and then cycled to low temperature using the IRM-LTI.\n", "\n", "* Series 1 experiment was designed to apply an IRM along the $<111>$\n", "* Series 2 experiment was designed to apply an IRM along the $<100>$ \"SIRM 1.2T (350 Volt pulse) along 100 (along Z)\"\n", "* Series 3 experiment was designed to apply the magnetization along the $<110>$\n", "\n", "A schematic drawing of the specimen and its orientation relative to the measurement axes of the superconducting rock magnetometer (SRM) and to the orientations of three separate 1.2 T IRMs is shown below." ] }, { "cell_type": "code", "collapsed": false, "input": [ "Image(filename=('../Data/Ikon_magnetite/experiment_schematic.png'))" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "png": 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796dM2bKkJCejKAr1GzSgW89ePF2nLiaTCV9fXw798gsd2rXjyOHDhe6cLTYr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\ne6XRaFCr1URERJCXl4cKCAsLo8h9HA0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r1fqnvw0ZOoQVK1fg7OyC3sGB9LQ0erzQjS8+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\nQmCC\n", "prompt_number": 16, "text": [ "" ] } ], "prompt_number": 16 }, { "cell_type": "markdown", "metadata": {}, "source": [ "The data from these experiments can be imported into data frames." ] }, { "cell_type": "code", "collapsed": false, "input": [ "Ikon_series1_cooling = pd.read_csv('../Data/Ikon_magnetite/Ikon_mag_series1_cooling.csv')\n", "Ikon_series1_warming = pd.read_csv('../Data/Ikon_magnetite/Ikon_mag_series1_warming.csv')\n", "\n", "Ikon_series2_cooling = pd.read_csv('../Data/Ikon_magnetite/Ikon_mag_series2_cooling.csv')\n", "Ikon_series2_warming = pd.read_csv('../Data/Ikon_magnetite/Ikon_mag_series2_warming.csv')\n", "\n", "Ikon_series3_cooling = pd.read_csv('../Data/Ikon_magnetite/Ikon_mag_series3_cooling.csv')\n", "Ikon_series3_warming = pd.read_csv('../Data/Ikon_magnetite/Ikon_mag_series3_warming.csv')" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 17 }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "Background subtraction" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The blank holder data used for the background correction of the Labrador hematite sample will also be used to the background correction for these experiments as these data were collected in the same interval of time that the instrument was in use." ] }, { "cell_type": "code", "collapsed": false, "input": [ "#For the interpolate function to work the x values (temperature) need to be ascending. \n", "#The blank_hem_data_cooling can be sorted so that temperatures are ascending\n", "blank_hem_data_cooling = blank_hem_data_cooling.sort(['Meas_T[K]'])\n", "\n", "Ikon_series1_cooling['Mx_bsub[Am2]'] = background_sub(blank_hem_data_cooling['Mx[Am2]'],\n", " blank_hem_data_cooling['Meas_T[K]'],\n", " Ikon_series1_cooling['Mx[Am2]'],\n", " Ikon_series1_cooling['Meas_T[K]'])\n", "\n", "Ikon_series1_cooling['My_bsub[Am2]'] = background_sub(blank_hem_data_cooling['My[Am2]'],\n", " blank_hem_data_cooling['Meas_T[K]'],\n", " Ikon_series1_cooling['My[Am2]'],\n", " Ikon_series1_cooling['Meas_T[K]'])\n", "\n", "Ikon_series1_cooling['Mz_bsub[Am2]'] = background_sub(blank_hem_data_cooling['Mz[Am2]'],\n", " blank_hem_data_cooling['Meas_T[K]'],\n", " Ikon_series1_cooling['Mz[Am2]'],\n", " Ikon_series1_cooling['Meas_T[K]'])\n", "\n", "Ikon_series1_warming['Mx_bsub[Am2]'] = background_sub(blank_hem_data_cooling['Mx[Am2]'],\n", " blank_hem_data_cooling['Meas_T[K]'],\n", " Ikon_series1_warming['Mx[Am2]'],\n", " Ikon_series1_warming['Meas_T[K]'])\n", "\n", "Ikon_series1_warming['My_bsub[Am2]'] = background_sub(blank_hem_data_cooling['My[Am2]'],\n", " blank_hem_data_cooling['Meas_T[K]'],\n", " Ikon_series1_warming['My[Am2]'],\n", " Ikon_series1_warming['Meas_T[K]'])\n", "\n", "Ikon_series1_warming['Mz_bsub[Am2]'] = background_sub(blank_hem_data_cooling['Mz[Am2]'],\n", " blank_hem_data_cooling['Meas_T[K]'],\n", " Ikon_series1_warming['Mz[Am2]'],\n", " Ikon_series1_warming['Meas_T[K]'])\n", "\n", "Ikon_series2_cooling['Mx_bsub[Am2]'] = background_sub(blank_hem_data_cooling['Mx[Am2]'],\n", " blank_hem_data_cooling['Meas_T[K]'],\n", " Ikon_series2_cooling['Mx[Am2]'],\n", " Ikon_series2_cooling['Meas_T[K]'])\n", "\n", "Ikon_series2_cooling['My_bsub[Am2]'] = background_sub(blank_hem_data_cooling['My[Am2]'],\n", " blank_hem_data_cooling['Meas_T[K]'],\n", " Ikon_series2_cooling['My[Am2]'],\n", " Ikon_series2_cooling['Meas_T[K]'])\n", "\n", "Ikon_series2_cooling['Mz_bsub[Am2]'] = background_sub(blank_hem_data_cooling['Mz[Am2]'],\n", " blank_hem_data_cooling['Meas_T[K]'],\n", " Ikon_series2_cooling['Mz[Am2]'],\n", " Ikon_series2_cooling['Meas_T[K]'])\n", "\n", "Ikon_series2_warming['Mx_bsub[Am2]'] = background_sub(blank_hem_data_cooling['Mx[Am2]'],\n", " blank_hem_data_cooling['Meas_T[K]'],\n", " Ikon_series2_warming['Mx[Am2]'],\n", " Ikon_series2_warming['Meas_T[K]'])\n", "\n", "Ikon_series2_warming['My_bsub[Am2]'] = background_sub(blank_hem_data_cooling['My[Am2]'],\n", " blank_hem_data_cooling['Meas_T[K]'],\n", " Ikon_series2_warming['My[Am2]'],\n", " Ikon_series2_warming['Meas_T[K]'])\n", "\n", "Ikon_series2_warming['Mz_bsub[Am2]'] = background_sub(blank_hem_data_cooling['Mz[Am2]'],\n", " blank_hem_data_cooling['Meas_T[K]'],\n", " Ikon_series2_warming['Mz[Am2]'],\n", " Ikon_series2_warming['Meas_T[K]'])\n", "\n", "Ikon_series3_cooling['Mx_bsub[Am2]'] = background_sub(blank_hem_data_cooling['Mx[Am2]'],\n", " blank_hem_data_cooling['Meas_T[K]'],\n", " Ikon_series3_cooling['Mx[Am2]'],\n", " Ikon_series3_cooling['Meas_T[K]'])\n", "\n", "Ikon_series3_cooling['My_bsub[Am2]'] = background_sub(blank_hem_data_cooling['My[Am2]'],\n", " blank_hem_data_cooling['Meas_T[K]'],\n", " Ikon_series3_cooling['My[Am2]'],\n", " Ikon_series3_cooling['Meas_T[K]'])\n", "\n", "Ikon_series3_cooling['Mz_bsub[Am2]'] = background_sub(blank_hem_data_cooling['Mz[Am2]'],\n", " blank_hem_data_cooling['Meas_T[K]'],\n", " Ikon_series3_cooling['Mz[Am2]'],\n", " Ikon_series3_cooling['Meas_T[K]'])\n", "\n", "Ikon_series3_warming['Mx_bsub[Am2]'] = background_sub(blank_hem_data_cooling['Mx[Am2]'],\n", " blank_hem_data_cooling['Meas_T[K]'],\n", " Ikon_series3_warming['Mx[Am2]'],\n", " Ikon_series3_warming['Meas_T[K]'])\n", "\n", "Ikon_series3_warming['My_bsub[Am2]'] = background_sub(blank_hem_data_cooling['My[Am2]'],\n", " blank_hem_data_cooling['Meas_T[K]'],\n", " Ikon_series3_warming['My[Am2]'],\n", " Ikon_series3_warming['Meas_T[K]'])\n", "\n", "Ikon_series3_warming['Mz_bsub[Am2]'] = background_sub(blank_hem_data_cooling['Mz[Am2]'],\n", " blank_hem_data_cooling['Meas_T[K]'],\n", " Ikon_series3_warming['Mz[Am2]'],\n", " Ikon_series3_warming['Meas_T[K]'])" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 18 }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "Total vector calculation" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "From these background corrected three-axis data the total vector can be calculated." ] }, { "cell_type": "code", "collapsed": false, "input": [ "Ikon_series1_cooling['Mtotal_bsub[Am2]'] = np.sqrt(Ikon_series1_cooling['Mx_bsub[Am2]']**2+\n", " Ikon_series1_cooling['My_bsub[Am2]']**2+\n", " Ikon_series1_cooling['Mz_bsub[Am2]']**2)\n", "Ikon_series1_warming['Mtotal_bsub[Am2]'] = np.sqrt(Ikon_series1_warming['Mx_bsub[Am2]']**2+\n", " Ikon_series1_warming['My_bsub[Am2]']**2+\n", " Ikon_series1_warming['Mz_bsub[Am2]']**2)\n", "\n", "Ikon_series2_cooling['Mtotal_bsub[Am2]'] = np.sqrt(Ikon_series2_cooling['Mx_bsub[Am2]']**2+\n", " Ikon_series2_cooling['My_bsub[Am2]']**2+\n", " Ikon_series2_cooling['Mz_bsub[Am2]']**2)\n", "Ikon_series2_warming['Mtotal_bsub[Am2]'] = np.sqrt(Ikon_series2_warming['Mx_bsub[Am2]']**2+\n", " Ikon_series2_warming['My_bsub[Am2]']**2+\n", " Ikon_series2_warming['Mz_bsub[Am2]']**2)\n", "\n", "Ikon_series3_cooling['Mtotal_bsub[Am2]'] = np.sqrt(Ikon_series3_cooling['Mx_bsub[Am2]']**2+\n", " Ikon_series3_cooling['My_bsub[Am2]']**2+\n", " Ikon_series3_cooling['Mz_bsub[Am2]']**2)\n", "Ikon_series3_warming['Mtotal_bsub[Am2]'] = np.sqrt(Ikon_series3_warming['Mx_bsub[Am2]']**2+\n", " Ikon_series3_warming['My_bsub[Am2]']**2+\n", " Ikon_series3_warming['Mz_bsub[Am2]']**2)" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 19 }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "Directional and intensity plots for all three experiments" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Plot the three-axis data for each experiment." ] }, { "cell_type": "code", "collapsed": false, "input": [ "plt.figure(figsize=(3,3),dpi=160)\n", "plt.plot(Ikon_series1_cooling['Meas_T[K]'], Ikon_series1_cooling['Mx_bsub[Am2]'], 'rs-',\n", " label='Mx cooling')\n", "plt.plot(Ikon_series1_cooling['Meas_T[K]'], Ikon_series1_cooling['My_bsub[Am2]'], 'bs-',\n", " label='My cooling')\n", "plt.plot(Ikon_series1_cooling['Meas_T[K]'], Ikon_series1_cooling['Mz_bsub[Am2]'], 'gs-',\n", " label='Mz cooling')\n", "plt.plot(Ikon_series1_warming['Meas_T[K]'], Ikon_series1_warming['Mx_bsub[Am2]'], 'ro-',\n", " label='Mx warming')\n", "plt.plot(Ikon_series1_warming['Meas_T[K]'], Ikon_series1_warming['My_bsub[Am2]'], 'bo-',\n", " label='My warming')\n", "plt.plot(Ikon_series1_warming['Meas_T[K]'], Ikon_series1_warming['Mz_bsub[Am2]'], 'go-',\n", " label='Mz warming')\n", "plt.ylabel('Moment (x10$^{-6}$ Am$^2$)')\n", "plt.ticklabel_format(style='sci', scilimits=(0,0), axis='y')\n", "plt.xlabel('Temperature (K)')\n", "plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)\n", "plt.title('IKON magnetite (series 1 experiment)')\n", "plt.show()\n", "\n", "plt.figure(figsize=(3,3),dpi=160)\n", "plt.plot(Ikon_series2_cooling['Meas_T[K]'], Ikon_series2_cooling['Mx_bsub[Am2]'], 'rs-',\n", " label='Mx cooling')\n", "plt.plot(Ikon_series2_cooling['Meas_T[K]'], Ikon_series2_cooling['My_bsub[Am2]'], 'bs-',\n", " label='My cooling')\n", "plt.plot(Ikon_series2_cooling['Meas_T[K]'], Ikon_series2_cooling['Mz_bsub[Am2]'], 'gs-',\n", " label='Mz cooling')\n", "plt.plot(Ikon_series2_warming['Meas_T[K]'], Ikon_series2_warming['Mx_bsub[Am2]'], 'ro-',\n", " label='Mx warming')\n", "plt.plot(Ikon_series2_warming['Meas_T[K]'], Ikon_series2_warming['My_bsub[Am2]'], 'bo-',\n", " label='My warming')\n", "plt.plot(Ikon_series2_warming['Meas_T[K]'], Ikon_series2_warming['Mz_bsub[Am2]'], 'go-',\n", " label='Mz warming')\n", "plt.ylabel('Moment (x10$^{-6}$ Am$^2$)')\n", "plt.ticklabel_format(style='sci', scilimits=(0,0), axis='y')\n", "plt.xlabel('Temperature (K)')\n", "plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)\n", "plt.title('IKON magnetite (series 2 experiment)')\n", "plt.savefig('code_output/Ikon_magnetite_series2.pdf')\n", "plt.show()\n", "\n", "plt.figure(figsize=(3,3),dpi=160)\n", "plt.plot(Ikon_series3_cooling['Meas_T[K]'], Ikon_series3_cooling['Mx_bsub[Am2]'], 'rs-',\n", " label='Mx cooling')\n", "plt.plot(Ikon_series3_cooling['Meas_T[K]'], Ikon_series3_cooling['My_bsub[Am2]'], 'bs-',\n", " label='My cooling')\n", "plt.plot(Ikon_series3_cooling['Meas_T[K]'], Ikon_series3_cooling['Mz_bsub[Am2]'], 'gs-',\n", " label='Mz cooling')\n", "plt.plot(Ikon_series3_warming['Meas_T[K]'], Ikon_series3_warming['Mx_bsub[Am2]'], 'ro-',\n", " label='Mx warming')\n", "plt.plot(Ikon_series3_warming['Meas_T[K]'], Ikon_series3_warming['My_bsub[Am2]'], 'bo-',\n", " label='My warming')\n", "plt.plot(Ikon_series3_warming['Meas_T[K]'], Ikon_series3_warming['Mz_bsub[Am2]'], 'go-',\n", " label='Mz warming')\n", "plt.ylabel('Moment (x10$^{-6}$ Am$^2$)')\n", "plt.ticklabel_format(style='sci', scilimits=(0,0), axis='y')\n", "plt.xlabel('Temperature (K)')\n", "plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)\n", "plt.title('IKON magnetite (series 3 experiment)')\n", "plt.show()" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", 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KRf6elKZ8sLptnT0LmZnQpo0hWLUnQdXAWxer8u7Diqf0M5s3b2bXrl2MHTuW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\nFcxGwNKqNRu1NrgrG3V3XZVVoxE1xjIa1jJqyOp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2WwFlK919UR/HEeBVbLaTXHZZU5YvH8+vv87VgrWekXkyk/SO6eUOd8KyJvuA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\nAlK4CiEeFULYhRBN63ouQK3npdfj1e/xNBoIQOE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vRJF0JIn0Telk5WdRlAPFJ3pCfjBwM5bTwIxzaheQmwt79mzn4Yc/JDR0PUFB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\nbgEhoH9/2LpVF9dahHFEPzp6Nrm57vj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"text": [ "" ] } ], "prompt_number": 20 }, { "cell_type": "markdown", "metadata": {}, "source": [ "The total moment as calculated from the 3-axis data is plotted below in a single plot that shows all three experiments." ] }, { "cell_type": "code", "collapsed": false, "input": [ "plt.figure(figsize=(6,5),dpi=160)\n", "plt.plot(Ikon_series1_cooling['Meas_T[K]'], Ikon_series1_cooling['Mtotal_bsub[Am2]'], 's-',\n", " label='Series1 cooling',color='#CD5F28')\n", "plt.plot(Ikon_series1_warming['Meas_T[K]'], Ikon_series1_warming['Mtotal_bsub[Am2]'], 'o-',\n", " label='Series1 warming',color='#CD5F28')\n", "plt.plot(Ikon_series2_cooling['Meas_T[K]'], Ikon_series2_cooling['Mtotal_bsub[Am2]'], 's-',\n", " label='Series2 cooling',color='#0077A2')\n", "plt.plot(Ikon_series2_warming['Meas_T[K]'], Ikon_series2_warming['Mtotal_bsub[Am2]'], 'o-',\n", " label='Series2 warming',color='#0077A2')\n", "plt.plot(Ikon_series3_cooling['Meas_T[K]'], Ikon_series3_cooling['Mtotal_bsub[Am2]'], 's-',\n", " label='Series3 cooling',color='#3B8B36')\n", "plt.plot(Ikon_series3_warming['Meas_T[K]'], Ikon_series3_warming['Mtotal_bsub[Am2]'], 'o-',\n", " label='Series3 warming',color='#3B8B36')\n", "\n", "plt.ylabel('Moment (Am$^2$)')\n", "plt.xlabel('Temperature (K)')\n", "plt.xlim(0, 290)\n", "plt.ylim(0, .0000055)\n", "plt.ticklabel_format(style='sci', scilimits=(0,0), axis='y')\n", "plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)\n", "plt.title('IKON magnetite (total moment)')\n", "plt.savefig('code_output/Ikon_magnetite_total.pdf')\n", "plt.show()" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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Yli9fTlVVFenp6Wg0GtLS0ujQoQNlZWXMmzePuLg4ysrKePbZZ1m+fDm2trYU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\nmZlZqf4GMktEChuWydcAAAAASUVORK5CYII=\n", "text": [ "" ] } ], "prompt_number": 21 }, { "cell_type": "markdown", "metadata": {}, "source": [ "The remanence lost in each experiment between 260 K and just prior to the Verwey transition increase." ] }, { "cell_type": "code", "collapsed": false, "input": [ "series1_260 = Ikon_series1_cooling['Mtotal_bsub[Am2]'][0]\n", "series2_260 = Ikon_series2_cooling['Mtotal_bsub[Am2]'][0]\n", "series3_260 = Ikon_series3_cooling['Mtotal_bsub[Am2]'][2]\n", "series1_min = Ikon_series1_cooling['Mtotal_bsub[Am2]'].min()\n", "series2_min = Ikon_series2_cooling['Mtotal_bsub[Am2]'].min()\n", "series3_min = Ikon_series3_cooling['Mtotal_bsub[Am2]'].min()\n", "print 'Series 1 percent lost between 260K and minima'\n", "print ((series1_260-series1_min)/series1_260)*100\n", "print 'Series 2 percent lost between 260K and minima'\n", "print ((series2_260-series2_min)/series2_260)*100\n", "print 'Series 3 percent lost between 260K and minima'\n", "print ((series3_260-series3_min)/series3_260)*100" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "Series 1 percent lost between 260K and minima\n", "67.8202160088\n", "Series 2 percent lost between 260K and minima\n", "75.1987424572\n", "Series 3 percent lost between 260K and minima\n", "71.7873125177\n" ] } ], "prompt_number": 22 }, { "cell_type": "markdown", "metadata": {}, "source": [ "The remanence lost in each experiment between 260 K and the plateau following the Verwey transition increase." ] }, { "cell_type": "code", "collapsed": false, "input": [ "series1_260 = Ikon_series1_cooling['Mtotal_bsub[Am2]'][0]\n", "series2_260 = Ikon_series2_cooling['Mtotal_bsub[Am2]'][0]\n", "series3_260 = Ikon_series3_cooling['Mtotal_bsub[Am2]'][2]\n", "series1_50 = Ikon_series1_cooling['Mtotal_bsub[Am2]'][35]\n", "series2_50 = Ikon_series2_cooling['Mtotal_bsub[Am2]'][58]\n", "series3_50 = Ikon_series3_cooling['Mtotal_bsub[Am2]'][33]\n", "print 'Series 1 post-Verwey plateau remanence as percent of 260K remanence'\n", "print (series1_50/series1_260)*100\n", "print 'Series 2 post-Verwey plateau remanence as percent of 260K remanence'\n", "print (series2_50/series2_260)*100\n", "print 'Series 3 post-Verwey plateau remanence as percent of 260K remanence'\n", "print (series3_50/series3_260)*100" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "Series 1 post-Verwey plateau remanence as percent of 260K remanence\n", "53.4020260118\n", "Series 2 post-Verwey plateau remanence as percent of 260K remanence\n", "60.9993296955\n", "Series 3 post-Verwey plateau remanence as percent of 260K remanence\n", "56.4923557659\n" ] } ], "prompt_number": 23 }, { "cell_type": "markdown", "metadata": {}, "source": [ "The remanence lost in each experiment following thermal cycling." ] }, { "cell_type": "code", "collapsed": false, "input": [ "series1_260_warming = Ikon_series1_warming['Mtotal_bsub[Am2]'][41]\n", "series2_260_warming = Ikon_series2_warming['Mtotal_bsub[Am2]'][63]\n", "series3_260_warming = Ikon_series3_warming['Mtotal_bsub[Am2]'][35]\n", "print 'Series 1 post-thermal cycling remanence (at 250-260K) as percent of 260K remanence'\n", "print (series1_260_warming/series1_260)*100\n", "print 'Series 2 post-thermal cycling remanence (at 250-260K) as percent of 260K remanence'\n", "print (series2_260_warming/series2_260)*100\n", "print 'Series 3 post-thermal cycling remanence (at 250-260K) as percent of 260K remanence'\n", "print (series3_260_warming/series3_260)*100" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "Series 1 post-thermal cycling remanence (at 250-260K) as percent of 260K remanence\n", "43.8987720207\n", "Series 2 post-thermal cycling remanence (at 250-260K) as percent of 260K remanence\n", "47.7466227538\n", "Series 3 post-thermal cycling remanence (at 250-260K) as percent of 260K remanence\n", "40.1523508649\n" ] } ], "prompt_number": 24 }, { "cell_type": "markdown", "metadata": {}, "source": [ "The directional data for the three experiments is plotted on a single equal area plot." ] }, { "cell_type": "code", "collapsed": false, "input": [ "directions_cart_series1_cooling=[]\n", "directions_cart_series1_warming=[]\n", "\n", "for n in range(len(Ikon_series1_cooling)):\n", " directions_cart_series1_cooling.append([Ikon_series1_cooling['Mx_bsub[Am2]'][n],\n", " Ikon_series1_cooling['My_bsub[Am2]'][n],\n", " Ikon_series1_cooling['Mz_bsub[Am2]'][n]])\n", "for n in range(len(Ikon_series1_warming)):\n", " directions_cart_series1_warming.append([Ikon_series1_warming['Mx_bsub[Am2]'][n],\n", " Ikon_series1_warming['My_bsub[Am2]'][n],\n", " Ikon_series1_warming['Mz_bsub[Am2]'][n]])\n", "\n", "directions_DI_series1_cooling=pmag.cart2dir(directions_cart_series1_cooling)\n", "directions_DI_series1_warming=pmag.cart2dir(directions_cart_series1_warming)\n", "\n", "directions_cart_series2_cooling=[]\n", "directions_cart_series2_warming=[]\n", "\n", "for n in range(len(Ikon_series2_cooling)):\n", " directions_cart_series2_cooling.append([Ikon_series2_cooling['Mx_bsub[Am2]'][n],\n", " Ikon_series2_cooling['My_bsub[Am2]'][n],\n", " Ikon_series2_cooling['Mz_bsub[Am2]'][n]])\n", "for n in range(len(Ikon_series2_warming)):\n", " directions_cart_series2_warming.append([Ikon_series2_warming['Mx_bsub[Am2]'][n],\n", " Ikon_series2_warming['My_bsub[Am2]'][n],\n", " Ikon_series2_warming['Mz_bsub[Am2]'][n]])\n", "\n", "directions_DI_series2_cooling=pmag.cart2dir(directions_cart_series2_cooling)\n", "directions_DI_series2_warming=pmag.cart2dir(directions_cart_series2_warming)\n", "\n", "directions_cart_series3_cooling=[]\n", "directions_cart_series3_warming=[]\n", "\n", "for n in range(len(Ikon_series3_cooling)):\n", " directions_cart_series3_cooling.append([Ikon_series3_cooling['Mx_bsub[Am2]'][n],\n", " Ikon_series3_cooling['My_bsub[Am2]'][n],\n", " Ikon_series3_cooling['Mz_bsub[Am2]'][n]])\n", "for n in range(len(Ikon_series3_warming)):\n", " directions_cart_series3_warming.append([Ikon_series3_warming['Mx_bsub[Am2]'][n],\n", " Ikon_series3_warming['My_bsub[Am2]'][n],\n", " Ikon_series3_warming['Mz_bsub[Am2]'][n]])\n", "\n", "directions_DI_series3_cooling=pmag.cart2dir(directions_cart_series3_cooling)\n", "directions_DI_series3_warming=pmag.cart2dir(directions_cart_series3_warming)\n", "\n", "fignum = 1\n", "plt.figure(num=fignum,figsize=(6,6),dpi=160)\n", "pmagplotlib.plotNET(fignum)\n", "IPmag.iplotDI(directions_DI_series1_cooling,color='#CD5F28', label='Series 1')\n", "IPmag.iplotDI(directions_DI_series1_warming,color='#CD5F28')\n", "IPmag.iplotDI(directions_DI_series2_cooling,color='#0077A2', label='Series 2')\n", "IPmag.iplotDI(directions_DI_series2_warming,color='#0077A2')\n", "IPmag.iplotDI(directions_DI_series3_cooling,color='#3B8B36', label='Series 3')\n", "IPmag.iplotDI(directions_DI_series3_warming,color='#3B8B36')\n", "plt.legend(loc=6)\n", "plt.savefig('code_output/Ikon_magnetite_EA.pdf')\n", "plt.show()" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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U6jgNmKJwEkk+d18O3Eu0DZKUk0ZQKSC+xulL4Ep3fyd0PSKyeWbWBJgC7KHOu+WjEVRq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\n25ho5LSf98/d1PU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kBZSIiCSSAkpERBJJASUiIomkgBIRkURSQImISCIpoERE\nJJEUUCIikkgKKBERSSQFlIiIJJICSkREEkkBJSIiiaSAEhGRRFJAiYhIIimgREQkkRRQIiKSSAoo\nERFJJAWUiIgkkgJKREQSSQElIiKJpIASEZFEUkCJiEgiKaBERCSRFFAiIpJICigREUkkBZSIiCSS\nAkpERBJJASUiIomkgBIRkURSQImISCIpoEREJJH+H3f8KYi4Ww/8AAAAAElFTkSuQmCC\n", "text": [ "" ] } ], "prompt_number": 25 }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "Additional plots of directional change in <100> experiment" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "There are some quite interesting directional changes in the Series 2 data set. The data from that experiment is plotted below on Zijderveld plots." ] }, { "cell_type": "code", "collapsed": false, "input": [ "#make a datablock with this format: [treatment step, dec, inc, intensity]\n", "datablock_cooling=[]\n", "for n in range(0,len(Ikon_series2_cooling)):\n", " datablock_cooling.append([Ikon_series2_cooling['Meas_T[K]'][n],\n", " directions_DI_series2_cooling[n][0],\n", " directions_DI_series2_cooling[n][1],\n", " directions_DI_series2_cooling[n][2]])\n", "datablock_warming=[]\n", "for n in range(0,len(Ikon_series2_warming)):\n", " datablock_warming.append([Ikon_series2_warming['Meas_T[K]'][n],\n", " directions_DI_series2_warming[n][0],\n", " directions_DI_series2_warming[n][1],\n", " directions_DI_series2_warming[n][2]]) \n", "datablock_all=datablock_cooling+datablock_warming \n", " \n", "#plot with pmagplotlib.plotZ(fignum,datablock,angle,s,norm)\n", "fignum = 1\n", "pmagplotlib.plotZ(1,datablock_cooling,90,'series 2 cooling',0)\n", "plt.ticklabel_format(style='sci', scilimits=(0,0), axis='y')\n", "plt.ticklabel_format(style='sci', scilimits=(0,0), axis='x')\n", "plt.ylim(.0000004,-.000004,)\n", "plt.xlim(0,.000002,)\n", "plt.savefig('code_output/Ikon_magnetite_series2_zplot_cooling.pdf')\n", "plt.show()\n", "\n", "fignum = 2\n", "pmagplotlib.plotZ(1,datablock_warming,90,'series 2 warming',0)\n", "plt.ticklabel_format(style='sci', scilimits=(0,0), axis='y')\n", "plt.ticklabel_format(style='sci', scilimits=(0,0), axis='x')\n", "plt.ylim(.0000004,-.000004,)\n", "plt.xlim(0,.000002,)\n", "plt.savefig('code_output/Ikon_magnetite_series2_zplot_warming.pdf')\n", "plt.show()\n", "\n", "fignum = 3\n", "pmagplotlib.plotZ(1,datablock_all,90,'series 2 all',0)\n", "plt.ticklabel_format(style='sci', scilimits=(0,0), axis='y')\n", "plt.ticklabel_format(style='sci', scilimits=(0,0), axis='x')\n", "plt.ylim(.0000004,-.000004,)\n", "plt.xlim(0,.000002,)\n", "plt.savefig('code_output/Ikon_magnetite_series2_zplot.pdf')\n", "plt.show()" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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CN5jZfrmMxTnnXGrpNGa3RsPtHQpzoncC7mnoltoUSRcC\n/49Q9eWcc64NlcyAO+ecc63Dn0fhnHMuJU8UzjnnUvJE4ZxzLiVPFM4551LyROGccy6l/w8l8JwX\n8HAdSwAAAABJRU5ErkJggg==\n", "text": [ "" ] } ], "prompt_number": 26 }, { "cell_type": "heading", "level": 1, "metadata": {}, "source": [ "Polycrystalline magnetite and hematite experiments" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This sample is from a product marketed as \"Nature Company hematite\" (referred to as naco in the code and the data folder) that is a polycrystalline mix of hematite with magnetite impurity. Low-temperature cycling experiments on this specimen (cf-naco-1) were conducted on the IRM-LTI and the MPMS." ] }, { "cell_type": "heading", "level": 2, "metadata": {}, "source": [ "IRM-LTI experiment" ] }, { "cell_type": "code", "collapsed": false, "input": [ "Naco_cooling = pd.read_csv('../Data/NaCo/Naco_cooling.csv')\n", "Naco_warming = pd.read_csv('../Data/NaCo/Naco_warming.csv')\n", "Naco_cooling.head()" ], "language": "python", "metadata": {}, "outputs": [ { "html": [ "
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specimenMx[Am2]My[Am2]Mz[Am2]MN[Am2]ME[Am2]MV[Am2]Mtot[Am2]Dec[deg]Inc[deg]...timeseriesposition[cm]Drift_ratioJa/Jrrun#DescriptionMeas_T[K]ModeType
0 cf-naco-1 0.000083-4.335590e-08-0.000003 0.000083-4.335590e-08-0.000003 0.000083-0.029839-2.17446... 10:41:36 AM 1NaNNaN 0NaN 292.893 291.28 DISCRETENaN
1 cf-naco-1 0.000083-4.275720e-08-0.000003 0.000083-4.275720e-08-0.000003 0.000083-0.029466-2.18214... 10:45:05 AM 1NaNNaN 0NaN 292.920 291.26 DISCRETENaN
2 cf-naco-1 0.000083-4.030780e-08-0.000003 0.000083-4.030780e-08-0.000003 0.000083-0.027778-2.17731... 10:46:28 AM 1NaNNaN 0NaN 292.929 291.26 DISCRETENaN
3 cf-naco-1 0.000083-5.599900e-08-0.000003 0.000083-5.599900e-08-0.000003 0.000083-0.038592-2.18009... 10:48:48 AM 1NaNNaN 0NaN 284.969 291.23 DISCRETENaN
4 cf-naco-1 0.000083-5.100280e-08-0.000003 0.000083-5.100280e-08-0.000003 0.000083-0.035174-2.17820... 11:32:19 AM 1NaNNaN 0NaN 181.799 290.19 DISCRETENaN
\n", "

5 rows \u00d7 35 columns

\n", "
" ], "metadata": {}, "output_type": "pyout", "prompt_number": 27, "text": [ " specimen Mx[Am2] My[Am2] Mz[Am2] MN[Am2] ME[Am2] \\\n", "0 cf-naco-1 0.000083 -4.335590e-08 -0.000003 0.000083 -4.335590e-08 \n", "1 cf-naco-1 0.000083 -4.275720e-08 -0.000003 0.000083 -4.275720e-08 \n", "2 cf-naco-1 0.000083 -4.030780e-08 -0.000003 0.000083 -4.030780e-08 \n", "3 cf-naco-1 0.000083 -5.599900e-08 -0.000003 0.000083 -5.599900e-08 \n", "4 cf-naco-1 0.000083 -5.100280e-08 -0.000003 0.000083 -5.100280e-08 \n", "\n", " MV[Am2] Mtot[Am2] Dec[deg] Inc[deg] ... time series \\\n", "0 -0.000003 0.000083 -0.029839 -2.17446 ... 10:41:36 AM 1 \n", "1 -0.000003 0.000083 -0.029466 -2.18214 ... 10:45:05 AM 1 \n", "2 -0.000003 0.000083 -0.027778 -2.17731 ... 10:46:28 AM 1 \n", "3 -0.000003 0.000083 -0.038592 -2.18009 ... 10:48:48 AM 1 \n", "4 -0.000003 0.000083 -0.035174 -2.17820 ... 11:32:19 AM 1 \n", "\n", " position[cm] Drift_ratio Ja/Jr run# Description Meas_T[K] Mode \\\n", "0 NaN NaN 0 NaN 292.893 291.28 DISCRETE \n", "1 NaN NaN 0 NaN 292.920 291.26 DISCRETE \n", "2 NaN NaN 0 NaN 292.929 291.26 DISCRETE \n", "3 NaN NaN 0 NaN 284.969 291.23 DISCRETE \n", "4 NaN NaN 0 NaN 181.799 290.19 DISCRETE \n", "\n", " Type \n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", "[5 rows x 35 columns]" ] } ], "prompt_number": 27 }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "Blank run and background subtraction" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "A blank run with the probe empty was done close in time to the experiment on the cf-naco-a specimen. That data is imported below into a dataframe and then plotted to determine the best way to background subtract the probe measurement from the sample data." ] }, { "cell_type": "code", "collapsed": false, "input": [ "blank_naco_data_cooling = pd.read_csv('../Data/NaCo/20110520cf_blank_cooling.csv')\n", "blank_naco_data_warming = pd.read_csv('../Data/NaCo/20110520cf_blank_warming.csv')\n", "blank_naco_data_warming.head()" ], "language": "python", "metadata": {}, "outputs": [ { "html": [ "
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specimenMx[Am2]My[Am2]Mz[Am2]MN[Am2]ME[Am2]MV[Am2]Mtot[Am2]Dec[deg]Inc[deg]...timeseriesposition[cm]Drift_ratioJa/Jrrun#DescriptionMeas_T[K]ModeType
0 CF-blank-4.684120e-08-6.720820e-08 0 0-6.720820e-08 4.684120e-08 0-28.5181 18.4050... 1:17:33 PM 7NaNNaN 0NaN 15.227 17.63 DISCRETENaN
1 CF-blank-4.699740e-08-6.693490e-08 0 0-6.693490e-08 4.699740e-08 0-28.4446 18.4917... 1:18:19 PM 7NaNNaN 0NaN 18.948 22.16 DISCRETENaN
2 CF-blank-4.690780e-08-6.685280e-08 0 0-6.685280e-08 4.690780e-08 0-28.4037 18.4572... 1:19:10 PM 7NaNNaN 0NaN 20.988 24.07 DISCRETENaN
3 CF-blank-4.700080e-08-6.680970e-08 0 0-6.680970e-08 4.700080e-08 0-28.4008 18.5009... 1:20:15 PM 7NaNNaN 0NaN 22.501 25.58 DISCRETENaN
4 CF-blank-4.673360e-08-6.666500e-08 0 0-6.666500e-08 4.673360e-08 0-28.3368 18.4045... 1:21:35 PM 7NaNNaN 0NaN 23.577 27.08 DISCRETENaN
\n", "

5 rows \u00d7 35 columns

\n", "
" ], "metadata": {}, "output_type": "pyout", "prompt_number": 28, "text": [ " specimen Mx[Am2] My[Am2] Mz[Am2] MN[Am2] ME[Am2] \\\n", "0 CF-blank -4.684120e-08 -6.720820e-08 0 0 -6.720820e-08 \n", "1 CF-blank -4.699740e-08 -6.693490e-08 0 0 -6.693490e-08 \n", "2 CF-blank -4.690780e-08 -6.685280e-08 0 0 -6.685280e-08 \n", "3 CF-blank -4.700080e-08 -6.680970e-08 0 0 -6.680970e-08 \n", "4 CF-blank -4.673360e-08 -6.666500e-08 0 0 -6.666500e-08 \n", "\n", " MV[Am2] Mtot[Am2] Dec[deg] Inc[deg] ... time series \\\n", "0 4.684120e-08 0 -28.5181 18.4050 ... 1:17:33 PM 7 \n", "1 4.699740e-08 0 -28.4446 18.4917 ... 1:18:19 PM 7 \n", "2 4.690780e-08 0 -28.4037 18.4572 ... 1:19:10 PM 7 \n", "3 4.700080e-08 0 -28.4008 18.5009 ... 1:20:15 PM 7 \n", "4 4.673360e-08 0 -28.3368 18.4045 ... 1:21:35 PM 7 \n", "\n", " position[cm] Drift_ratio Ja/Jr run# Description Meas_T[K] Mode \\\n", "0 NaN NaN 0 NaN 15.227 17.63 DISCRETE \n", "1 NaN NaN 0 NaN 18.948 22.16 DISCRETE \n", "2 NaN NaN 0 NaN 20.988 24.07 DISCRETE \n", "3 NaN NaN 0 NaN 22.501 25.58 DISCRETE \n", "4 NaN NaN 0 NaN 23.577 27.08 DISCRETE \n", "\n", " Type \n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", "[5 rows x 35 columns]" ] } ], "prompt_number": 28 }, { "cell_type": "code", "collapsed": false, "input": [ "blank_naco_data_cooling = pd.read_csv('../Data/NaCo/20110520cf_blank_cooling.csv')\n", "blank_naco_data_warming = pd.read_csv('../Data/NaCo/20110520cf_blank_warming.csv')\n", "blank_naco_data_warming.head()\n", "fignum=1\n", "plt.figure(num=fignum,figsize=(6,3),dpi=160)\n", "plt.plot(blank_naco_data_cooling['Meas_T[K]'], blank_naco_data_cooling['Mx[Am2]'], 'rs',\n", " label='Mx cooling')\n", "plt.plot(blank_naco_data_warming['Meas_T[K]'], blank_naco_data_warming['Mx[Am2]'], 'ro',\n", " label='Mx warming')\n", "plt.plot(blank_naco_data_cooling['Meas_T[K]'], blank_naco_data_cooling['My[Am2]'], 'bs',\n", " label='My cooling')\n", "plt.plot(blank_naco_data_warming['Meas_T[K]'], blank_naco_data_warming['My[Am2]'], 'bo',\n", " label='My warming')\n", "plt.plot(blank_naco_data_cooling['Meas_T[K]'], blank_naco_data_cooling['Mz[Am2]'], 'gs',\n", " label='Mz cooling')\n", "plt.plot(blank_naco_data_warming['Meas_T[K]'], blank_naco_data_warming['Mz[Am2]'], 'go',\n", " label='Mz warming')\n", "\n", "plt.ylabel('Moment (Am$^2$)')\n", "plt.xlabel('Temperature (K)')\n", "plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)\n", "plt.title('cold finger blank run (04/28/2010)')\n", "\n", "plt.show()" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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QXkRygCeAAABjzGvGmI9EZJiI7MW6We59F6+2Siml1KXpyJEjjBkzhpMnT9Kt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\nzEN+9+2KZ3zYPk5AgB+hockEB58mYaj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"text": [ "" ] } ], "prompt_number": 29 }, { "cell_type": "markdown", "metadata": {}, "source": [ "The cooling run was completed in full for the blank while there were gaps in the warming data. Let's use the cooling data which looks to be reversible for the z (while there is an unexplained offset in the y and x) for the background correction using the background_subtraction() function." ] }, { "cell_type": "code", "collapsed": false, "input": [ "#For the interpolate function to work the x values (temperature) need to be ascending. \n", "#The blank_hem_data_cooling can be sorted so that temperatures are ascending\n", "blank_naco_data_cooling = blank_naco_data_cooling.sort(['Meas_T[K]'])\n", "\n", "Naco_cooling['Mx_bsub[Am2]'] = background_sub(blank_naco_data_cooling['Mx[Am2]'], \n", " blank_naco_data_cooling['Meas_T[K]'],\n", " Naco_cooling['Mx[Am2]'],\n", " Naco_cooling['Meas_T[K]'])\n", "\n", "Naco_cooling['My_bsub[Am2]'] = background_sub(blank_naco_data_cooling['My[Am2]'], \n", " blank_naco_data_cooling['Meas_T[K]'],\n", " Naco_cooling['My[Am2]'],\n", " Naco_cooling['Meas_T[K]'])\n", "\n", "Naco_cooling['Mz_bsub[Am2]'] = background_sub(blank_naco_data_cooling['Mz[Am2]'], \n", " blank_naco_data_cooling['Meas_T[K]'],\n", " Naco_cooling['Mz[Am2]'],\n", " Naco_cooling['Meas_T[K]'])\n", "\n", "Naco_cooling['Mtotal_bsub[Am2]'] = np.sqrt(Naco_cooling['Mx_bsub[Am2]']**2 + \n", " Naco_cooling['My_bsub[Am2]']**2 + \n", " Naco_cooling['Mz_bsub[Am2]']**2)\n", "\n", "Naco_warming['Mx_bsub[Am2]'] = background_sub(blank_naco_data_cooling['Mx[Am2]'],\n", " blank_naco_data_cooling['Meas_T[K]'],\n", " Naco_warming['Mx[Am2]'],\n", " Naco_warming['Meas_T[K]'])\n", "\n", "Naco_warming['My_bsub[Am2]'] = background_sub(blank_naco_data_cooling['My[Am2]'],\n", " blank_naco_data_cooling['Meas_T[K]'],\n", " Naco_warming['My[Am2]'],\n", " Naco_warming['Meas_T[K]'])\n", "\n", "Naco_warming['Mz_bsub[Am2]'] = background_sub(blank_naco_data_cooling['Mz[Am2]'],\n", " blank_naco_data_cooling['Meas_T[K]'],\n", " Naco_warming['Mz[Am2]'],\n", " Naco_warming['Meas_T[K]'])\n", "\n", "Naco_warming['Mtotal_bsub[Am2]'] = np.sqrt(Naco_warming['Mx_bsub[Am2]']**2 + \n", " Naco_warming['My_bsub[Am2]']**2 + \n", " Naco_warming['Mz_bsub[Am2]']**2)" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 30 }, { "cell_type": "heading", "level": 2, "metadata": {}, "source": [ "Equal area plot" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The direction of the Naco specimen throughout thermal cycling on the LTI can be plotted on an equal area plot. A subsection of this equal area plot was included in the figure concerning the Naco hematite/magnetite specimen in the main text." ] }, { "cell_type": "code", "collapsed": false, "input": [ "directions_cart_cooling=[]\n", "directions_cart_warming=[]\n", "\n", "#data point 0 is oriented (remember python starts at 0)\n", "for n in range(len(Naco_cooling)):\n", " directions_cart_cooling.append([Naco_cooling['Mx[Am2]'][n],\n", " Naco_cooling['My[Am2]'][n],\n", " Naco_cooling['Mz[Am2]'][n]])\n", "for n in range(len(Naco_warming)):\n", " directions_cart_warming.append([Naco_warming['Mx[Am2]'][n],\n", " Naco_warming['My[Am2]'][n],\n", " Naco_warming['Mz[Am2]'][n]])\n", "\n", "directions_DI_cooling=pmag.cart2dir(directions_cart_cooling)\n", "directions_DI_warming=pmag.cart2dir(directions_cart_warming)\n", "\n", "directions_cart_cooling=[]\n", "directions_cart_warming=[]\n", "\n", "#data point 0 is oriented (remember python starts at 0)\n", "for n in range(len(Naco_cooling)):\n", " directions_cart_cooling.append([Naco_cooling['Mx_bsub[Am2]'][n],\n", " Naco_cooling['My_bsub[Am2]'][n],\n", " Naco_cooling['Mz_bsub[Am2]'][n]])\n", "for n in range(len(Naco_warming)):\n", " directions_cart_warming.append([Naco_warming['Mx_bsub[Am2]'][n],\n", " Naco_warming['My_bsub[Am2]'][n],\n", " Naco_warming['Mz_bsub[Am2]'][n]])\n", "\n", "directions_DI_cooling=pmag.cart2dir(directions_cart_cooling)\n", "directions_DI_warming=pmag.cart2dir(directions_cart_warming)\n", "\n", "fignum=1\n", "fig=plt.figure(figsize=(8,5),dpi=160)\n", "plt.subplot(121)\n", "plt.figure(num=fignum,figsize=(8,8),dpi=160)\n", "pmagplotlib.plotNET(fignum)\n", "IPmag.iplotDI(directions_DI_cooling,'b')\n", "IPmag.iplotDI(directions_DI_warming,'r')\n", "plt.title('NaCo low-t cycling (no background correction)')\n", "\n", "plt.subplot(122)\n", "plt.figure(num=fignum,figsize=(8,8),dpi=160)\n", "pmagplotlib.plotNET(fignum)\n", "IPmag.iplotDI(directions_DI_cooling,'b')\n", "IPmag.iplotDI(directions_DI_warming,'r')\n", "plt.title('NaCo low-t cycling (background corrected)')\n", "plt.savefig('code_output/Naco_directions.pdf')\n", "plt.show()" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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nI+L+cpFZafnka4nG/SCvdXkKsHmdx4+5EJoAkhYArgBOjIhflY6nijplWvtm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\nk/8nsH+nF0HgQmjAIuJOYGPSZay+dHX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"text": [ "" ] } ], "prompt_number": 31 }, { "cell_type": "heading", "level": 2, "metadata": {}, "source": [ "Comparision between IRM-LTI and MPMS data" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Having subtracted the holder off of the LTI experiment data, the background subtracted data is plotted below along with the data acquired during the low-temperature cycling experiment on the MPMS." ] }, { "cell_type": "code", "collapsed": false, "input": [ "Naco_MPMS = pd.read_csv('../Data/NaCo/Naco_MPMS.csv',header=3)\n", "Naco_MPMS.head()" ], "language": "python", "metadata": {}, "outputs": [ { "html": [ "
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T [K]Bapp [T]M [Am2/kg]reg fittimestampUnnamed: 5T [K].1Bapp [T].1M [Am2/kg].1reg fit.1timestamp.1
0 NaNNaN NaN NaN NaNNaN NaNNaN NaN NaN NaN
1 300.0231 0 0.744367 0.974488 5/27/2011 2:06:42 PMNaN 14.99718 0 0.079222 0.974658 5/27/2011 3:28:22 PM
2 294.4838 0 0.744338 0.974525 5/27/2011 2:10:08 PMNaN 20.55822 0 0.079240 0.974714 5/27/2011 3:29:41 PM
3 289.3426 0 0.742235 0.974490 5/27/2011 2:11:13 PMNaN 25.55299 0 0.079243 0.974558 5/27/2011 3:30:42 PM
4 284.1801 0 0.739180 0.974057 5/27/2011 2:12:05 PMNaN 30.67751 0 0.079225 0.974482 5/27/2011 3:31:44 PM
\n", "
" ], "metadata": {}, "output_type": "pyout", "prompt_number": 32, "text": [ " T [K] Bapp [T] M [Am2/kg] reg fit timestamp Unnamed: 5 \\\n", "0 NaN NaN NaN NaN NaN NaN \n", "1 300.0231 0 0.744367 0.974488 5/27/2011 2:06:42 PM NaN \n", "2 294.4838 0 0.744338 0.974525 5/27/2011 2:10:08 PM NaN \n", "3 289.3426 0 0.742235 0.974490 5/27/2011 2:11:13 PM NaN \n", "4 284.1801 0 0.739180 0.974057 5/27/2011 2:12:05 PM NaN \n", "\n", " T [K].1 Bapp [T].1 M [Am2/kg].1 reg fit.1 timestamp.1 \n", "0 NaN NaN NaN NaN NaN \n", "1 14.99718 0 0.079222 0.974658 5/27/2011 3:28:22 PM \n", "2 20.55822 0 0.079240 0.974714 5/27/2011 3:29:41 PM \n", "3 25.55299 0 0.079243 0.974558 5/27/2011 3:30:42 PM \n", "4 30.67751 0 0.079225 0.974482 5/27/2011 3:31:44 PM " ] } ], "prompt_number": 32 }, { "cell_type": "code", "collapsed": false, "input": [ "adjustprops = dict(left=0.1, bottom=0.1, right=0.97, top=0.93, wspace=0.25, hspace=0.25)\n", "fig=plt.figure(figsize=(10,9))\n", "fig.subplots_adjust(**adjustprops)\n", "ax1 = plt.subplot(221)\n", "\n", "ax1.plot(Naco_cooling['Meas_T[K]'], Naco_cooling['Mx_bsub[Am2]'], 'rs-',label='M$_x$ cooling')\n", "ax1.plot(Naco_cooling['Meas_T[K]'], Naco_cooling['My_bsub[Am2]'], 'bs-',label='M$_y$ cooling')\n", "ax1.plot(Naco_cooling['Meas_T[K]'], Naco_cooling['Mz_bsub[Am2]'], 'gs-',label='M$_z$ cooling')\n", "ax1.plot(Naco_warming['Meas_T[K]'], Naco_warming['Mx_bsub[Am2]'], 'ro-',label='M$_x$ warming')\n", "ax1.plot(Naco_warming['Meas_T[K]'], Naco_warming['My_bsub[Am2]'], 'bo-',label='M$_y$ warming')\n", "ax1.plot(Naco_warming['Meas_T[K]'], Naco_warming['Mz_bsub[Am2]'], 'go-',label='M$_z$ warming')\n", "plt.legend(loc=2, borderaxespad=0.)\n", "plt.ylabel('Moment (Am$^2$)')\n", "plt.xlabel('Temperature (K)')\n", "plt.title('Naco 1.2 T IRM cycling on LTI (background subtracted)')\n", "\n", "ax2 = plt.subplot(222)\n", "ax2.plot(Naco_cooling['Meas_T[K]'], Naco_cooling['Mtotal_bsub[Am2]'], \n", " 'ks-',label='M$_{total}$ cooling')\n", "ax2.plot(Naco_warming['Meas_T[K]'], Naco_warming['Mtotal_bsub[Am2]'], \n", " 'ko-',label='M$_{total}$ warming')\n", "plt.legend(loc=2, borderaxespad=0.)\n", "plt.ylabel('Moment (Am$^2$)')\n", "plt.xlabel('Temperature (K)')\n", "plt.title('Naco 1.2 T IRM cycling on LTI (background subtracted)')\n", "\n", "ax3 = plt.subplot(223)\n", "ax3.plot(Naco_MPMS['T [K]'],Naco_MPMS['M [Am2/kg]']/10000,'cs-',label='M cooling')\n", "ax3.plot(Naco_MPMS['T [K].1'],Naco_MPMS['M [Am2/kg].1']/10000,'co-',label='M warming')\n", "plt.legend(loc=2, borderaxespad=0.)\n", "plt.ylabel('Moment (Am$^2$)')\n", "plt.ylim(0,0.00009)\n", "plt.xlabel('Temperature (K)')\n", "plt.xlim(0,300)\n", "plt.title('Naco 1.2 T IRM thermal cycling on MPMS')\n", "\n", "ax4 = plt.subplot(224)\n", "ax4.plot(Naco_cooling['Meas_T[K]'], \n", " Naco_cooling['Mtotal_bsub[Am2]']/Naco_cooling['Mtotal_bsub[Am2]'][0],\n", " 'ks-',label='LTI cooling')\n", "ax4.plot(Naco_warming['Meas_T[K]'], \n", " Naco_warming['Mtotal_bsub[Am2]']/Naco_cooling['Mtotal_bsub[Am2]'][0],\n", " 'ko-',label='LTI warming')\n", "ax4.plot(Naco_MPMS['T [K]'],\n", " Naco_MPMS['M [Am2/kg]']/Naco_MPMS['M [Am2/kg]'][3],\n", " 'cs-',label='MPMS cooling')\n", "ax4.plot(Naco_MPMS['T [K].1'],\n", " Naco_MPMS['M [Am2/kg].1']/Naco_MPMS['M [Am2/kg]'][3],\n", " 'co-',label='MPMS warming')\n", "plt.ylabel('Moment (normalized to M at 290 K)')\n", "plt.xlabel('Temperature (K)')\n", "plt.legend(loc=2, borderaxespad=0.)\n", "plt.xlim(0,300)\n", "plt.ylim(ymin=0)\n", "plt.title('Naco 1.2 T IRM thermal cycling on MPMS and LTI')\n", "plt.show()" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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NH/7wBwYNGhRqUZQ6QjCDH8M1Brsi1KNdAephqR4cDgevv/46t99+e51Q0uo5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\nEWHMmDFEo1HuueceNmzYkHOd+2L69OlUVFRw++23Ew6H+c1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bbrutZAPtYra3tjKkGRwy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"text": [ "" ] } ], "prompt_number": 33 }, { "cell_type": "markdown", "metadata": {}, "source": [ "The total magnetic moment between the LTI and MPMS are quite similiar. The values obtained on the LTI are slightly higher which could be associated with there being small off-axis components that were not resolved using the MPMS. The code block below displays the values of the magnetic moments at ~290 degrees on both instruments. These values are written on the figure in the main manuscript." ] }, { "cell_type": "code", "collapsed": false, "input": [ "#values quoted on figure\n", "a = Naco_cooling['Mtotal_bsub[Am2]'][0]\n", "b = Naco_cooling['Meas_T[K]'][5]\n", "print \"For the temperature of\", b, \"on the LTI the magnetic moment is:\", a, \"Am2\"\n", "c = Naco_MPMS['T [K]'][3]\n", "d = Naco_MPMS['M [Am2/kg]'][3]/10000\n", "print \"For the temperature of\", c, \"on the MPMS the magnetic moment is:\", d, \"Am2\"\n", "print \"Number of data points collected during LTI run:\", len(Naco_cooling['Meas_T[K]'])" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "For the temperature of 289.13 on the LTI the magnetic moment is: 8.33181600855e-05 Am2\n", "For the temperature of 289.3426 on the MPMS the magnetic moment is: 7.422345e-05 Am2\n", "Number of data points collected during LTI run: 114\n" ] } ], "prompt_number": 34 }, { "cell_type": "markdown", "metadata": {}, "source": [ "A simplified version of the figure made above needs to be generated to use within the main manuscript." ] }, { "cell_type": "code", "collapsed": false, "input": [ "adjustprops = dict(left=0.1, bottom=0.1, right=0.97, top=0.93, wspace=0.15, hspace=0.1)\n", "fig=plt.figure(figsize=(14,6),dpi=160)\n", "fig.subplots_adjust(**adjustprops)\n", "\n", "ax1 = plt.subplot(121)\n", "ax1.plot(Naco_cooling['Meas_T[K]'], Naco_cooling['Mx_bsub[Am2]'], \n", " 'rs-',label='M$_x$ cooling')\n", "ax1.plot(Naco_cooling['Meas_T[K]'], Naco_cooling['My_bsub[Am2]'], \n", " 'bs-',label='M$_y$ cooling')\n", "ax1.plot(Naco_cooling['Meas_T[K]'], Naco_cooling['Mz_bsub[Am2]'], \n", " 'gs-',label='M$_z$ cooling')\n", "ax1.plot(Naco_warming['Meas_T[K]'], Naco_warming['Mx_bsub[Am2]'], \n", " 'ro-',label='M$_x$ warming')\n", "ax1.plot(Naco_warming['Meas_T[K]'], Naco_warming['My_bsub[Am2]'], \n", " 'bo-',label='M$_y$ warming')\n", "ax1.plot(Naco_warming['Meas_T[K]'], Naco_warming['Mz_bsub[Am2]'], \n", " 'go-',label='M$_z$ warming')\n", "plt.legend(loc=2)\n", "plt.ylabel('Magnetic moment (Am$^2$)')\n", "plt.xlabel('Temperature (K)')\n", "#plt.title('thermal cycling on IRM-LTI (background subtracted)')\n", "\n", "ax2 = plt.subplot(122)\n", "ax2.plot(Naco_cooling['Meas_T[K]'],\n", " Naco_cooling['Mtotal_bsub[Am2]']/Naco_cooling['Mtotal_bsub[Am2]'][0],\n", " 'ks-',label='LTI cooling')\n", "ax2.plot(Naco_warming['Meas_T[K]'], \n", " Naco_warming['Mtotal_bsub[Am2]']/Naco_cooling['Mtotal_bsub[Am2]'][0], \n", " 'ko-',label='LTI warming')\n", "ax2.plot(Naco_MPMS['T [K]'],Naco_MPMS['M [Am2/kg]']/Naco_MPMS['M [Am2/kg]'][3],\n", " 'cs-',label='MPMS cooling')\n", "ax2.plot(Naco_MPMS['T [K].1'],Naco_MPMS['M [Am2/kg].1']/Naco_MPMS['M [Am2/kg]'][3],\n", " 'co-',label='MPMS warming')\n", "plt.ylabel('Magnetic moment (normalized to M at 290 K)')\n", "plt.xlabel('Temperature (K)')\n", "#plt.title('thermal cycling on IRM-LTI and MPMS')\n", "plt.legend(loc=2)\n", "plt.xlim(0,300)\n", "plt.ylim(ymin=0)\n", "plt.savefig('code_output/Naco_LTcycle.pdf')\n", "plt.show()" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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6dUyePBmAo0ePkpWVZZNAKqWYPn06c+fOJSsri4kTJxIVFcW+ffsACAkJIT4+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P9k7Zmh0i/iBcP5ysz03LAM2PLly31nnAYgHGbnxRdzRSDAS6tX04nXQ7zk/PP1PHEfKCgWGYsG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\n7H8D7wMeqGVyzQ+6k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"text": [ "" ] } ], "prompt_number": 35 }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "Estimating Morin and Verwey transition temperatures" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In order to estimate the Morin and Verwey transition temperatures, the gradient of the cooling data can be plotted." ] }, { "cell_type": "code", "collapsed": false, "input": [ "gradient_LTI_cooling = np.gradient(Naco_cooling['Mtotal_bsub[Am2]'])\n", "\n", "from scipy.interpolate import interp1d\n", "\n", "#interpolate the data using a cubic spline\n", "f_LTI_cooling_inter = interp1d(Naco_cooling['Meas_T[K]'][3:], \n", " gradient_LTI_cooling[3:], \n", " kind='cubic')\n", "\n", "xnew = np.linspace(80,280,1000)\n", "\n", "gradient_LTI_cooling_interpolated = f_LTI_cooling_inter(xnew)\n", "\n", "plt.figure(figsize=(10,8),dpi=160)\n", "plt.subplot(311)\n", "plt.plot(Naco_cooling['Meas_T[K]'], gradient_LTI_cooling, \n", " 'bs-',label='LTI gradient on cooling')\n", "plt.plot(xnew, gradient_LTI_cooling_interpolated, 'r-')\n", "plt.xlim(50, 280)\n", "plt.ylabel('gradient of magnetization')\n", "\n", "plt.subplot(312)\n", "plt.plot(Naco_cooling['Meas_T[K]'], gradient_LTI_cooling, \n", " 'bs-',label='LTI gradient on cooling')\n", "plt.plot(xnew, gradient_LTI_cooling_interpolated, 'r-')\n", "plt.xlim(100, 140)\n", "plt.ylabel('gradient of magnetization')\n", "\n", "plt.subplot(313)\n", "plt.plot(Naco_cooling['Meas_T[K]'], gradient_LTI_cooling, \n", " 'bs-',label='LTI gradient on cooling')\n", "plt.plot(xnew, gradient_LTI_cooling_interpolated, 'r-')\n", "plt.xlim(240, 265)\n", "plt.ylabel('gradient of magnetization')\n", "\n", "plt.xlabel('Temperature (K)')\n", "plt.show()" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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JwFEisgm4SVXnBOH9GxOQz7iYi/mMmWWBYwPw3Xdwzz3csWY1TzCWK5hGAVWf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/cDlygOkSx1iJsnbYO0dyOnss8/Afuy/gpwOrUbwEDFep7SLpcj\naVjSntKcD8De8o0RsQ6cB65LGs+GjvD7jqWZ9QknjmZmbT+ASWBG0muqn+ULqnfcloArkhaB/cBs\nRHzrEDePNQ08lPQSWM/G5oEL6XVB54A7wFiKNwp8roh3F1gEXqVX7MxSqjalk9xNScfLMdLzlQ3g\nnqQzaewUXZzuNrP/hyJcbTAz2wrp0Ml8RIz85aV0TdIUcCgiZjrMG6YopTe2ZWFm1lO842hmtrX+\n1V/jc8CE8pc4bu4ycGMb1mNmPcg7jmZmZmZWi3cczczMzKwWJ45mZmZmVosTRzMzMzOrxYmjmZmZ\nmdXixNHMzMzMavkFGNr/ZGpAAs0AAAAASUVORK5CYII=\n", "text": [ "" ] } ], "prompt_number": 36 }, { "cell_type": "code", "collapsed": false, "input": [ "LTI_morin = fmin(f_LTI_cooling_inter, x0=252)\n", "print 'The Morin estimate using LTI cooling data is: ' + str(LTI_morin)\n", "print \"\"\n", "LTI_verwey = fmin(f_LTI_cooling_inter, x0=118)\n", "print 'The Verwey estimate using LTI cooling data is: ' + str(LTI_verwey)\n", "print \"\"" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "Optimization terminated successfully.\n", " Current function value: -0.000006\n", " Iterations: 18\n", " Function evaluations: 36\n", "The Morin estimate using LTI cooling data is: [ 253.17009888]\n", "\n", "Optimization terminated successfully.\n", " Current function value: -0.000003\n", " Iterations: 17\n", " Function evaluations: 34\n", "The Verwey estimate using LTI cooling data is: [ 119.51677246]\n", "\n" ] } ], "prompt_number": 37 }, { "cell_type": "heading", "level": 1, "metadata": {}, "source": [ "Pyrrhotite experiments" ] }, { "cell_type": "heading", "level": 2, "metadata": {}, "source": [ "IRM-LTI experiments" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "There were three experiments performed on this single crystal of pyrrhotite:\n", "\n", "- an isothermal remanent magnetization bisecting the c and a$_1$ axes (series 5)\n", "- an isothermal remanent magnetization along the c axis (series 6)\n", "- an isothermal remanent magnetization bisecting the a$_1$ and -a$_3$ axes (series 7)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Import the data into a dataframe" ] }, { "cell_type": "code", "collapsed": false, "input": [ "pyrrhotite_data = pd.read_csv('../Data/Pyrrhotite/Pyrrhotite_Experiments.csv')" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 38 }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "Blank run and background subtraction" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "A blank run of the empty coldfinger probe was conducted on 2/6/2012 (the day before the series 5 experiment). The data can be loaded into a dataframe." ] }, { "cell_type": "code", "collapsed": false, "input": [ "blank_for_pyrrhotite = pd.read_csv('../Data/Pyrrhotite/cf_blank.csv')\n", "\n", "plt.figure(figsize=(6,3),dpi=160)\n", "plt.plot(blank_for_pyrrhotite['measurement_T[K]'], blank_for_pyrrhotite['Mx[Am2]'], \n", " 'rs', label='Mx')\n", "plt.plot(blank_for_pyrrhotite['measurement_T[K]'], blank_for_pyrrhotite['My[Am2]'], \n", " 'bs', label='My')\n", "plt.plot(blank_for_pyrrhotite['measurement_T[K]'], blank_for_pyrrhotite['Mz[Am2]'], \n", " 'gs', label='Mz')\n", "plt.ylabel('Magnetic moment (Am$^2$)')\n", "plt.xlabel('Temperature (K)')\n", "plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)\n", "plt.title('cold finger blank run (02/06/2012)')\n", "plt.show()" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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TpnDTTTfx4IMPsnDhQurq6rj++us5/vjjOfnkk/nZz36GmfG1r30tdT2u3J2ixJVUY1Nj\npJALEVOS7bTTfm97dHp2Pj9PKUR9urLbT03oOMQ6CDlWgzTHhiTkL2ZZ6O+0QG8KeqB8FXzU7zgD\ny5w5c1i6dCknnHAC06ZNY8KE7uNMjjjiCBYuXMgZZ5zBa6+9xpo1a/pksnflXqE0jGkgc3cm0Vt+\ns22mk17M7LuR0R2jgbzRdhFqdtUkyl8ovCzEOgg5Voe0HY0P5eWHHlaLLAPpTNgf+iNXXxW/dxgc\nJ0ISc+bM4fjjj2fdunXMnTu3xzayc+fO5Wtf+xpnn30273znO/tUjyv3CqXYD96hHziU11a+1iN8\n7LCxXWb0nFElRCPUeyNFPH3q9K7g9cPWQ0fpijmJbHlFR/UxRo0clVhfofA0lKWDEHwCgFyzflu6\nYjJPZnpOGwCZrZk+Cjb49FXxD0SHwXGGKpMmTWLy5MmsXLmS6667rkf8/Pnz+djHPsaqVat48MEH\n+eAHP5i6DlfuQ5C1v1nba5oeP5gN4SvhB7Pp75t6Os/RPbc72KRR2IU6CGmtBVnfghxSjvI7hnck\nzvN3rKzOI8T7aonoi+Lv7xJOZw+koSHZ8a2hYfeWEVi0aBFtbW2MGDGCnTt3AtFhN8uWLeOxxx7j\n8ccf57bbbmPevHk8/vjj7L333qnKd+VepaT5gSs1bdy5Lj886Qe4EPU765m+bnqP8PXD1ieGZ/bN\nsImea/7TUEjpj91rLFPXTc0Ja+loSdVBSMW9sHXb1nQOf32gXO9qsCmk+EdnRicu7ezNEpAtMynO\nOwXVTanL3Qa6jCyTJ0/OuZfEiy++yBe/+EVuv/12Ro4cyezZs7ntttv40pe+xLXXXpuqfFfuTsn0\nNqear0wyWzNwN0w9NFd5NhyX7oc0ybJQqOyCHYThmUSFPfXIqT220S3kOFiog1C7oZaRK0fm1NXY\n1Mi2N7cltqfzk50lOfxl1maov7+eugPqerRl1K5RnMiJPcrOKrBiz7exqbFgXDXQF0fEzN2ZxOfi\nSt8pJ+vWJZuxhg8fTmdnNHB47bXcKdcbb7yxT3W5cnfKwkD+AJZtWVk/px4KWRwy4zI5uwm2084m\nNlH7WG3JZdfsVUPnhzq78meV/+iVo3tMEbTTDrcnl/PAmgd6VVLFRvW9xQ+lUX8aOnZ2uNJ3qgpX\n7s4eQTl+iJNG+RCNhJOmDUaOGFmyg2BaZ8KO4cnKKNFcHds0KE7+vHVrWyuNTY00jGkoeChQkoUG\nelf8Q7XDUEjpuz+AU+m4cnecPHob2ZZK0ki/0Hz+QNO19j9GoXnrzO09R6uZJzNQnzDFElNYxRR/\n2imdbL5KVvxp/QGKWQGy5SXFeYfA6Quu3B0nj3L9mKaZz68kEq0CrcCH6GGhSOoIQO7oNWsRgGRl\n1RfFX8i3opI7BMWsAND3TYkcJwlX7o6zGylkFSjk8FfppJoeoO9WgTQUswQAyc9/Z2U+/8za3jtP\npYS7BWDPw5W74/STNGb8Qj+whRz+0nr/VzrltgrEySqwvnYIkp7/YCv9QqP9Qp2nvkwJuNKvTvqk\n3CXVA2Zm28ssj+MMOcrx45i2jDSdgcGa5+8vaa0CSR2sUne/S9vpqmTzfxJpVwO4BWDoU5JylzQM\nOBOYDXwAGBYFqxP4LXADcKvlb5DbRyTNAq4EaoAfmdkVCWmuAk4FtgFNZvZYsbyS9gduAt5BNFY4\nx8zaQtxXgM8CncBFZnZXCD8aWEy0M/kdZnZxCD8U+C9gVHgWl5jZynK03XFKob/7BECVWQUKrAjI\nrM1dptgV3kerQJy0/gCDbQVIIq1loD8WAN9mePdS6sh9NXA/8G9AS3bELqkOOAo4HfgicEJ/BZJU\nA/wAOBnYAPxO0gozeyaW5jTgUDObImkGcDUws5e8lwB3m9m3JX053F8iaRpwLjANmADcI2lK6Khc\nDVxoZmsk3SFplpmtAhYC15vZtZIOB+4gd0sSx6kYymEVKLRpUCV1BAqtCEiiHEsJiy0ZTKLXvRaG\ngC9Aoc5Ay8qez+fRBx+l5m01Xfdbt22lc1hndM7F7FhCdxocEEpV7h9JMsGHsIeAh4KiLwfHAmvN\nrBVA0o3AGcAzsTSnA0uCDA9LGiNpPJGCLZT3dOja0msJUYflkhC/3Mx2AK2S1gIzJL0A7GNma0Ke\npUTWi1XAy0D2V2MMUUfCcaoCtwr0JKnj0JfRf5rOABTeQ6HSaK9v76H0a35fQ+epCds130z3OQ0d\n8PCuhwdcvkqhoaGBl19+mY0bN/K2t72tK/yoo47i8ccfp7W1lUmTJpWlrpKUeylz62Wcf58AvBS7\nXw/MKCHNBOCgInnHmVn2v2QTMC5cH0TUQckva0e4zrIhhAN8C/itpL8D9gY+XErDHKfa2FOsAkmU\nwyegNwo5axbqPA2JKYFa4BPh+ufQsX33HKTU1NRMa2vP8IYGWLy4ebeUIYnJkyezfPlyFixYAMAT\nTzzBW2+91acz24tRid7ypc7bl/IklFSemZmk/vgHfIdoPv+7kmYC1wNH5Cdqbm7uum5sbKSxsbEf\nVTrO0GegrAIV7zRY4i6BWfrj+Z9Epa4GAOCt3N/KgaK1Fe67L6me0usuRxkXXHABS5cu7VLuS5Ys\nYe7cuSxcuJBXX32VY445hldeeaVL2d9yyy18/etfp6WlpeQ6oDKV+wbg4Nj9weSOoJPSTAxpahPC\nsybzTZLGm9krkg4EXu2lrA3hOj8cIqfCSwHM7CFJ9ZLGmlnOjv+74w/WcaqVNIqt0OZABc8DGASr\nQJpdAss9D122JZgD0RnYO/e38rLLLitv+RXGzJkzWbZsGZlMhilTpnDTTTfx4IMPsnDhQg444ADG\njh3LnXfeyaxZswBYtmwZ8+bNS11Pqd7yo8xsq6RaYJeZ9fPcy6I8AkyR1ABsJHJ2m52XZgWwALgx\njJzbzGyTpNeL5F0BzAOuCN+3xsJ/LOk7RGb3KcCaMLrfEhz21gBzgKtCngyR096S4FBXn6/YHcfZ\nfRTca6DACYRVZRUoQCne6eWYVmnJtNBeP/Sez2AyZ84cli5dygknnMC0adOYMGFCV9zcuXO5/vrr\nmTVrFps3b+auu+7immuuSV1Hr8pd0j8BYyUNB75JNN/8udQ1lYiZ7ZS0ALiTaDnbIjN7RtIXQvy1\nZnaHpNOC89ubwGeK5Q1FXw7cLOlCwlK4kOdpSTcDTwM7gfmxJX3ziZbCjSBaCrcqhP8jsEjSF4nM\n/um7VY7jlI20Sqoc0wOV7hPQ29G3faFgR6mttUe5j771KDUrI2/59jfaI7sqRN7yMWpqatiTkMSc\nOXM4/vjjWbduHXPnziWrciRx/vnnc8QRR7Bt2zZuvvlmTjjhBMaNG9dLqT0pZeT+cPjsIBoJD0td\nS0rCmvGVeWHX5t0vKDVvCN9MNNpOyvNNoo5LfvijwLsTwv8INBZsgOM4VUM5TNoDOfovNELPrM30\ne4FuuUb/4983nk2jYl7/94bvLVA7vPSjkauFSZMmMXnyZFauXMl1112XEzdx4kRmzpzJLbfcwvXX\nX8/8+fP7VEcpyv1Nok1iriEyX+95b8JxHCePcvgEpCVJ2bZkWmg/tWfHIXGNf5E1+0ntKdfof9Zx\ns1j1yCo6duYO2+v3r2fWcbPSFdZHGhogyfEtCt99ZWRZtGgRbW1tjBgxgp07d+bEzZ07l8svv5yX\nXnqJs846K33hlKDczewRonnw7P2SPtXkOI6zh5J2SVuh44UTlW1rOlnSrNkvx+gfynfSYr9kKHG5\n20CXkWXy5Mk59/GlcGeddRbz58/nrLPOor6+vk/lp/KWl3QM8FWgIZbXzOw9fardcRxnD6AvjmsD\nqWzzKbZm3ykf69YlmzyGDx9OZ2e3n/qIESN4+9vfzpw5c/pcV9qlcDcA/wA8Cezqc62O4zhOQQqZ\nw9Mo26RlgLvD89/3kO8/t9xyC5I46aST+lxGWuX+JzNb0efaHMdxnN3C1COn9tjutlxz/8UYCC/9\nPYnGxkYymQzLli3rVzlplftlkhYB9wD/G8LMzG7plxSO4zhOnxm9cjTTp+aO0gvN26eh0CZA5Sjb\nSWb16tVlKSetcp8HvCvki5vlXbk7juMMMInKtqF0k3chx75Ca/aTRv/O0CCtcn8fMLVc57Y7juM4\npdNfZZt2zb6P0IcuaZX7b4jOPX9qAGRxHMdxKLKd7gApW3d0qz7SKvf3Ay2S1gHZI159KZzjOE4Z\nGcrKdnd3TJxklMbCHg5kgWg/dQGTgEvM7LSySzbEkeSzF47jOCmRhJn163DzPen3t9DzSjVyN7NW\nSe8lOmntU0R7I/2sLBI6juM4jlMWSjoERtK7JDVLega4EngRGGZmjWb2/QGV0HEcx3GqgIaGBurq\n6nj99ddzwo866iiGDRvGiy++WLa6Sh25PwP8AvhLM3sRQNKXyiaF4ziO4wwg5dg5r79lSGLy5Mks\nX76cBQuig02feOIJ3nrrrZy95ctBqcr9LCJT/H9LWgX8hGjO3XEcx3EqnnLsnFeOMi644AKWLl3a\npdyXLFnC3LlzWbhwIRs2bGDatGldir6zs5OOjg527Uq/23tJZnkzu9XMzgWOBO4HvggcIOlqSaek\nrtVxHMdx9kBmzpzJli1byGQydHZ2ctNNN3HBBRcAMGHCBLZu3cobb7zBG2+8wVlnncXs2bP7VE9a\nh7qtRIfH3CBpf+Bs4BLgrj7V7jiO4zh7GHPmzGHp0qWccMIJTJs2jQkTJvRIc8UVV/Dss8/ywAMP\n9KmOkpS7EtYVmNlm4P+FT2Iax3Ecx3G6kcScOXM4/vjjWbduHXPnziVfda5cuZKrrrqKNWvWUFdX\n16d6SjLLA6sl/aOkwxIEfZekL8MAHzXkOI7jOFXApEmTmDx5MitXruSss87KiXv22WdpamriJz/5\nSeKIvlRKNcufApwP/IekI4E3iBzqRhGd7X4DcHKfpchD0iyiJXc1wI/M7IqENFcBpwLbgCYze6xY\n3jCNcBPwDqL1+eeYWVuI+wrwWaATuMjM7grhRwOLgXrgDjO7OFb/OcClRBv6PG5m55er/Y7jOE55\nKcfOeeXcfW/RokW0tbUxYsQIdu7cCUB7ezuf+tSn+MY3vsEHPvCB1GXGSbVDHYCkGmBsuH3NzDr7\nJUFy+c8SdRY2AL8DZpvZM7E0pwELzOw0STOA75nZzGJ5JX07yPvtYGnYz8wukTQN+DFwDDCB6Djb\nKWZmktaEetZIugO4ysxWSZpC1FH4kJm1SxprZq/ltcNnKRzHcVJSzTvUHXLIISxatIiTTjopJ3zn\nzp3U1dVx3XXX8ZnPfIa99967K04SW7ZsKVhmWXaoAwjKfFPafCk4FlhrZq0Akm4EziBaa5/ldGBJ\nkOdhSWMkjQcOKZL3dODEkH8JsJrIGfAMYLmZ7QBaJa0FZkh6AdjHzNaEPEuBM4FVwOeAH5hZe5Ah\nR7E7juM4Tj7r1iWvmRs+fDidndE4ed68eWWpq9Q5993JBOCl2P36EFZKmoOK5B1nZtlOySZgXLg+\nKKRLKiseviFW1hTgXZIekPRbSX9ZWtMcx3EcZ+BJPXLfDZRqSynFbKOk8oLJvT82m1rgUCJLwMFE\nm/u8OzuSz9Lc3Nx13djYSGNjYz+qdBzHqT5Wr17N6tWrB1uMqiOVcpd0hZl9ubewfrKBSGFmOZjc\nEXRSmokhTW1C+IZwvUnSeDN7RdKBwKu9lLUhXOeHQ2QdeDhMUbRKeo5I2T8aFzKu3B3HcZye5A98\nLrvsssETpopIa5ZP2o2u3Me9PgJMkdQgaS/gXGBFXpoVwFwASTOBtmByL5Z3BZCdzJgH3BoLP0/S\nXpIOITK5rzGzV4AtkmYo2gtwDnBbyHMr0BjqHwscBjxfrgfgOI7jOP2h1E1s/gaYD7xT0hOxqH2A\nB8spkJntlLQAuJNoOdui4O3+hRB/rZndIem04Pz2JvCZYnlD0ZcDN0u6kLAULuR5WtLNwNPATmB+\nzM1yPtFSuBFES+FWhTx3SjpF0lNEy+f+wcz+XM7n4DiO4zh9paSlcJJGA/sRKcgv0z3f/YaZvV4w\n4x5MpS7FcBzHqWSqeSncQFDoeaVe5+6Uxp70x+U4jlMuyqXcyyXPUKDf69wl1QOfBBpiec3Mvt5v\n6RzHcRx7PWsmAAAf6UlEQVSnDPS3c1ANpF0KdxvQRuQV3lF+cRzHcRzH6S9plfsEM/MNWxzHcRyn\ngkm7FO43kt4zIJI4juM4jlMWUjnUSXqGaLOWdcD2EGxm5go/D3eocxzHSU85HOqc9Gb5U8O3Udr2\nr47jOI7j7GbSmuVfBI4H5oWT13YBby+3UI7jOI7j9J20yv2HwPuBT4f7rSHMcRzHcZwKIa1ZfoaZ\nHSXpMQAz2yypdgDkchzHcRynj6Qduf+vpJrsjaQDiEzzjuM4juNUCGmV+/eBnwNvl/RNokNjvlV2\nqRzHcRzH6TOp95aXdDjw4XD7azN7uuxSVQG+FM5xHCc9vhSuPPjBMQOEK3fHcZz0uHIvD2kPjjkG\n+Co9D47xTWwcx3Ecp0JI6y1/A/APwJO4I53jOI7jVCRplfufzGzFgEjiOI7jOE5ZSLu3/CnAucA9\nwP+GYDOzWwZAtiGNz7k7juOkx+fcy0Pakfs84F0hX9ws78rdcRzHcSqEtOvc3wccY2bzzOwz2U+5\nhZI0S1JG0h8kfblAmqtC/OOSjuotr6T9Jd0t6TlJd0kaE4v7SkifCdaJbPjRkp4Icd9LkOGTknZJ\nem/5Wu84juM4/SP1ee7AtIEQJEvYAe8HwKxQ1+ywtj6e5jTgUDObAnweuLqEvJcAd5vZYcCvwj2S\nphFNNUwL+X4oKWsSuhq4MNQzRdKsmAz7ABcDD5X3CTiO4zhO/0ir3N8PtITR7xPh8z9llulYYK2Z\ntZrZDuBG4Iy8NKcDSwDM7GFgjKTxveTtyhO+zwzXZwDLzWxHOOluLTBD0oHAPma2JqRbGssD8C/A\n5UTn2vv8kOM4jlMxpJ1zz45cs55iA6HUJgAvxe7XAzNKSDMBOKhI3nFmtilcbwLGheuDyB19Z8va\nEa6zbAjhBDP8BDO7Q9I/0v08HMdxHGfQSaXczaxV0nSiM90NuN/MHi+zTKUqylI6Fkoqz8xMUp8U\ncjDZf4fIubCoLM3NzV3XjY2NNDY29qVKx3GcqmX16tWsXr16sMWoOtLuUHcx8Dki73gB10v6TzO7\nqowybQAOjt0fTO4IOinNxJCmNiF8Q7jeJGm8mb0STO6v9lLWhnCdH74PcASwOkzNjwdWSPq4mf0+\nLmRcuTuO4zg9yR/4XHbZZYMnTBWRds79r4jOdP9nM/u/wEwiZV9OHiFyXmuQtBeRs1v+xjkrgLkA\nkmYCbcHkXizvCrpH2/OAW2Ph50naS9IhwBRgjZm9AmyRNCOM1ucAt5nZFjM7wMwOMbNDiEz6PRS7\n4ziO4wwWaefcIXd9e9m3oDWznZIWAHcCNcAiM3tG0hdC/LVhrvs0SWuBN4HPFMsbir4cuFnShUAr\ncE7I87Skm4GngZ3A/NjuM/OBxcAI4A4zW1Xu9jqO4zhOuUm7Q92XgCa6zfJnAovN7LsDIt0Qxneo\ncxzHSY/vUFce+nKe+9HAcXQ71D02EIINdVy5O47jpMeVe3nw89wHCFfujuM46XHlXh78PHfHcRzH\nqTL8PHfHcRzHqTL8PHfHcRzHqTL8PPcBwufcHcdx0uNz7uXBz3N3HMdxnCojrXJ/HzDVh6SO4ziO\nU7lU3HnujuM4juP0j7Rz7hngncA6onPMwZfCJeJz7o7jOOnxOffy0Nfz3B3HcRzHqVB8h7oBwkfu\njuM46fGRe3lIO+fuOI7jOE6F48rdcRzHcaqMVMpd0lJJ+8Xu95d0XfnFchzHcRynr6Qdub/HzP6c\nvTGzzcB7yyuS4ziO4zj9Ia1yl6T9Yzf7AzXlFclxHMdxnP6QdincvwO/lXQzIOBTwDfKLpXjOI7j\nOH0m9VI4SUcAJwEG3GtmTw2EYEMdXwrnOI6THl8KVx5Se8ub2VNm9n0z+8FAKXZJsyRlJP1B0pcL\npLkqxD8u6aje8gbnv7slPSfpLkljYnFfCekz4eS7bPjRkp4Icd+LhX9J0lOh7nskTSr/U3Acx3Gc\nvlGScpf0YPjeKumNvM+WcgokqQb4AdFueNOA2ZIOz0tzGnComU0BPg9cXULeS4C7zeww4FfhHknT\niI6xnRby/VBSttd4NXBhqGeKpOwOfb8HjjazvwB+Cny7nM/AcRzHcfpDScrdzD4YvkeZ2T55n33L\nLNOxwFozazWzHcCNwBl5aU4HlgSZHgbGSBrfS96uPOH7zHB9BrDczHaYWSuwFpgh6UBgHzNbE9It\nzeYxs9Vm1hHCHwYmlqfpjuM4jtN/0q5zv6KUsH4yAXgpdr8+hJWS5qAieceZ2aZwvQkYF64PCumS\nyoqHb0iQA+BC4I7CzXEcx3Gc3Utab/lTgPw58NMSwvpDqV5opThcKKk8MzNJ/fZ2k3QB0Tr/LybF\nNzc3d103NjbS2NjY3yodx3GqitWrV7N69erBFqPqKEm5S/obYD7wTklPxKL2AR4ss0wbgINj9weT\nO4JOSjMxpKlNCN8QrjdJGm9mrwST+6u9lLWBXHN7vCwknQx8FTghTAH0IK7cHcdxnJ7kD3wuu+yy\nwROmiijVLP9j4OPACuBj4fNxIqey88ss0yNEzmsNkvYicnZbkZdmBTAXQNJMoC2Y3IvlXQHMC9fz\ngFtj4edJ2kvSIcAUYI2ZvQJskTQjONjNyeYJ3vnXAB83s9fK3H7HcRzH6Rep1rlLGgacDxxiZl8P\nS8DGx5zOyiOUdCpwJdHud4vM7FuSvgBgZteGNFmv+DeBz5jZ7wvlDeH7AzcDk4BW4BwzawtxXwU+\nC+wELjazO0P40cBiYARwh5ldFMLvBo4EXgkiv2BmWQe9bBt8nbvjOE5KfJ17eUir3K8BdgEnmdnU\noDDvMrP3DZSAQxVX7o7jOOlx5V4e0jrUzTCzoyQ9BtHBMZJqB0Aux3Ecx3H6SNod6v43bBQDgKQD\niEbyjuM4juNUCGmV+/eBnwNvl/RNIk/5b5VdKsdxHMdx+kxfDo45nOjgGAG/MrNnBkKwoY7PuTuO\n46TH59zLQ1qHunrgk0AD3fP1ZmZfL79oQxtX7o7jOOlx5V4e0jrU3Qa0AY8CHb2kdRzHcRxnEEir\n3CeY2V8OiCSO4ziO45SFtA51v5H0ngGRxHEcx3GcspB2zv0Z4FBgHbA9BJuZucLPw+fcHcdx0uNz\n7uUhrVn+1AGRwnEcx3GcspF6KZxTGj5ydxzHSY+P3MtDqpG7pP9DdD569sEb0A48amYtZZbNcRzH\ncZw+kHbO/cfA+4DbiRT8R4EngHcAPzWzKwZCyKGIj9wdx3HS4yP38pBWud8PnGpmW8P9KOAOoqNX\nHzWzwwdEyiGIK3fHcZz0uHIvD2mXwh0A/G/sfgcwzsy24ZvaOI7jOE5FkNZb/gbgYUm3EpnlPw78\nWNLewNPlFs5xHMdxnPT05eCYY4APEjnTPWhmjwyEYEOdwTbLNzU109raM7yhARYvbi45XanxmUwL\nHR1juuLr6wHaaG8fTl3dqJy827c/z+jRk5k6tYFMppWOjmyeNqZOnd5VPlAW2QYqvi+kKbNYWuj7\ns+ktr+MMJm6WLw99Ue77A1OAeiIFj5n9d/lFG9r0V7k3NTWzalW34stSX9/Gm29upqZmco88Y8e2\ncdxx02lthZaWVtrbG2KxLcB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"text": [ "" ] } ], "prompt_number": 39 }, { "cell_type": "markdown", "metadata": {}, "source": [ "The probe's magnetic moment appears to be largely reversible. Let's use the values upon cooling of the blank probe for the background correction of the pyrrhotite experimental data." ] }, { "cell_type": "code", "collapsed": false, "input": [ "blank_for_pyrrhotite_cooling = blank_for_pyrrhotite[0:51]\n", "blank_for_pyrrhotite_cooling = blank_for_pyrrhotite_cooling.sort(['measurement_T[K]'])\n", "\n", "pyrrhotite_data['Mx_bsub[Am2]'] = background_sub(blank_for_pyrrhotite_cooling['Mx[Am2]'], \n", " blank_for_pyrrhotite_cooling['measurement_T[K]'],\n", " pyrrhotite_data['Mx[Am2]'],\n", " pyrrhotite_data['Meas_T[K]'])\n", "pyrrhotite_data['My_bsub[Am2]'] = background_sub(blank_for_pyrrhotite_cooling['My[Am2]'], \n", " blank_for_pyrrhotite_cooling['measurement_T[K]'],\n", " pyrrhotite_data['My[Am2]'],\n", " pyrrhotite_data['Meas_T[K]'])\n", "pyrrhotite_data['Mz_bsub[Am2]'] = background_sub(blank_for_pyrrhotite_cooling['Mz[Am2]'], \n", " blank_for_pyrrhotite_cooling['measurement_T[K]'],\n", " pyrrhotite_data['Mz[Am2]'],\n", " pyrrhotite_data['Meas_T[K]'])\n", "\n", "pyrrhotite_data['Mtotal_bsub[Am2]'] = np.sqrt(pyrrhotite_data['Mx_bsub[Am2]']**2 + \n", " pyrrhotite_data['My_bsub[Am2]']**2 + \n", " pyrrhotite_data['Mz_bsub[Am2]']**2)" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 40 }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "3-axis and total magnetization plots" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Split the data into series 5, 6 and 7, reset the indices for each series and view the first 5 rows of pyrrhotite_data_series7." ] }, { "cell_type": "code", "collapsed": false, "input": [ "pyrrhotite_data_series5 = pyrrhotite_data.ix[pyrrhotite_data.series==5]\n", "pyrrhotite_data_series6 = pyrrhotite_data.ix[pyrrhotite_data.series==6]\n", "pyrrhotite_data_series6.reset_index(inplace=True)\n", "pyrrhotite_data_series7 = pyrrhotite_data.ix[pyrrhotite_data.series==7]\n", "pyrrhotite_data_series7.reset_index(inplace=True)\n", "pyrrhotite_data_series7.head()" ], "language": "python", "metadata": {}, "outputs": [ { "html": [ "
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indexspecimenMx[Am2]My[Am2]Mz[Am2]MN[Am2]ME[Am2]MV[Am2]Mtot[Am2]Dec[deg]...Ja/Jrrun#DescriptionMeas_T[K]ModeTypeMx_bsub[Am2]My_bsub[Am2]Mz_bsub[Am2]Mtotal_bsub[Am2]
0 230 CF AA pyrrhotite-5 0.000130 0.000063-0.000029 0.000130 0.000063-0.000029 0.000147 25.83010... 0NaN 289.42 290.745 DISCRETENaN 0.000131 0.000063-0.000037 0.000150
1 231 CF AA pyrrhotite-5 0.000148 0.000007-0.000051 0.000148 0.000007-0.000051 0.000156 2.89964... 0NaN 290.98 291.961 DISCRETENaN 0.000149 0.000007-0.000062 0.000162
2 232 CF AA pyrrhotite-5 0.000148 0.000007-0.000051 0.000148 0.000007-0.000051 0.000156 2.88449... 0NaN 291.24 292.114 DISCRETENaN 0.000149 0.000007-0.000062 0.000161
3 233 CF AA pyrrhotite-5 0.000148 0.000007-0.000051 0.000148 0.000007-0.000051 0.000156 2.87935... 0NaN 291.33 292.170 DISCRETENaN 0.000149 0.000007-0.000062 0.000161
4 234 CF AA pyrrhotite-5 0.000148 0.000007-0.000051 0.000148 0.000007-0.000051 0.000156 2.87825... 0NaN 291.40 292.230 DISCRETENaN 0.000149 0.000007-0.000062 0.000161
\n", "

5 rows \u00d7 40 columns

\n", "
" ], "metadata": {}, "output_type": "pyout", "prompt_number": 41, "text": [ " index specimen Mx[Am2] My[Am2] Mz[Am2] MN[Am2] \\\n", "0 230 CF AA pyrrhotite-5 0.000130 0.000063 -0.000029 0.000130 \n", "1 231 CF AA pyrrhotite-5 0.000148 0.000007 -0.000051 0.000148 \n", "2 232 CF AA pyrrhotite-5 0.000148 0.000007 -0.000051 0.000148 \n", "3 233 CF AA pyrrhotite-5 0.000148 0.000007 -0.000051 0.000148 \n", "4 234 CF AA pyrrhotite-5 0.000148 0.000007 -0.000051 0.000148 \n", "\n", " ME[Am2] MV[Am2] Mtot[Am2] Dec[deg] ... Ja/Jr run# \\\n", "0 0.000063 -0.000029 0.000147 25.83010 ... 0 NaN \n", "1 0.000007 -0.000051 0.000156 2.89964 ... 0 NaN \n", "2 0.000007 -0.000051 0.000156 2.88449 ... 0 NaN \n", "3 0.000007 -0.000051 0.000156 2.87935 ... 0 NaN \n", "4 0.000007 -0.000051 0.000156 2.87825 ... 0 NaN \n", "\n", " Description Meas_T[K] Mode Type Mx_bsub[Am2] My_bsub[Am2] \\\n", "0 289.42 290.745 DISCRETE NaN 0.000131 0.000063 \n", "1 290.98 291.961 DISCRETE NaN 0.000149 0.000007 \n", "2 291.24 292.114 DISCRETE NaN 0.000149 0.000007 \n", "3 291.33 292.170 DISCRETE NaN 0.000149 0.000007 \n", "4 291.40 292.230 DISCRETE NaN 0.000149 0.000007 \n", "\n", " Mz_bsub[Am2] Mtotal_bsub[Am2] \n", "0 -0.000037 0.000150 \n", "1 -0.000062 0.000162 \n", "2 -0.000062 0.000161 \n", "3 -0.000062 0.000161 \n", "4 -0.000062 0.000161 \n", "\n", "[5 rows x 40 columns]" ] } ], "prompt_number": 41 }, { "cell_type": "code", "collapsed": false, "input": [ "plt.figure(figsize=(6,10),dpi=160)\n", "plt.subplot(211)\n", "plt.plot(pyrrhotite_data_series5['Meas_T[K]'], pyrrhotite_data_series5['Mx[Am2]'], \n", " 'rs-', label='Mx')\n", "plt.plot(pyrrhotite_data_series5['Meas_T[K]'], pyrrhotite_data_series5['My[Am2]'], \n", " 'bs-', label='My')\n", "plt.plot(pyrrhotite_data_series5['Meas_T[K]'], pyrrhotite_data_series5['Mz[Am2]'], \n", " 'gs-', label='Mz')\n", "plt.ylabel('Magnetic moment (Am$^2$)')\n", "plt.xlabel('Temperature (K)')\n", "plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)\n", "plt.title('Series 5 experiment (uncorrected)')\n", "plt.subplot(212)\n", "plt.plot(pyrrhotite_data_series5['Meas_T[K]'], pyrrhotite_data_series5['Mx_bsub[Am2]'], \n", " 'rs-', label='Mx')\n", "plt.plot(pyrrhotite_data_series5['Meas_T[K]'], pyrrhotite_data_series5['My_bsub[Am2]'], \n", " 'bs-', label='My')\n", "plt.plot(pyrrhotite_data_series5['Meas_T[K]'], pyrrhotite_data_series5['Mz_bsub[Am2]'], \n", " 'gs-', label='Mz')\n", "plt.ylabel('Magnetic moment (Am$^2$)')\n", "plt.xlabel('Temperature (K)')\n", "plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)\n", "plt.title('Series 5 experiment (background corrected)')\n", "plt.show()\n", "\n" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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HPrcA5wOtQK2qvpIqrz+a/gFgOt50sZ9Q1SZ/2zeBTwOdwBe7b5kTkTpgIrDf\nf9nzVHVnFg7ZZENQd/moUXDeeXDaafDii4HZrbvcGJPr0hqdPpD87vpb8RZbmQ1cJiInJOxzAXCc\nqs4APgv8LI281wJPq+rxwO/954jIbLzpZGf7+X4aN9JegX9S1VP8Hwvg+eTAAXf6aafB174GpaUD\nWx9jjMmwUC1xEblJVb/RW1o/nQlsUtWYX/79eBPMbIzb5yJgBYCqvigilSIyETgmRd6LgAV+/hVA\nHV4gvxi4T1XbgZiIbALmAi90H2IGj81kSODI8unTiVx1Ffz0p/DSS6kLse5yY0yeC9ud/mEgMWBf\n4Ejrj8nAtrjnDXhBtbd9JgNHp8g7QVW7r+U3AhP8x0dzOGB35zk67vkKEWkHfqWq/zvcoZisCeoq\nLyuDtWvhC1+AHTvguecCi7DucmNMvkt3FbPPA9cAx4pI/M2zo4Hgb8m+CZiQOrlaae6TVJ6qqoik\n8zqXq+oOf7rZX4nIYlW9K3GnSCRy6HFNTQ01NTVpFG16E9jaTtVSPv54bxY1EXjwwSzVzBgTVl1d\nHXV1dYNdjSEn3Zb4vcAq4Ea8Vnd3AN2rqrsyXKftwNS451PxWsep9pni71PsSN/uP24UkYmq+paI\nTALeTlHWdgBV3eH/bhGRe/G6+lMGcZNBQa3tv/89eInPykovgIN1lxuTQxIbONdff/3gVWYISfc+\n8WagGfhUdqsDwFpghohUATvwBp1dlrDP48BS4H4RmQc0qWqjiOxKkfdx4ErgJv/3o3Hp94rIj/C6\n5GcAa/xBckeo6k4RKQY+hs0RnxtKSmDmzF7nLbfucmPMUBd2YFsp8I9AVVxeVdUbMlUhVe0QkaXA\nb/FuE1umqhtF5HP+9ttU9QkRucAfhLYPuCpVXr/oG4EHReRq/FvM/DwbRORBYAPQAVzjd7eXAk/6\nAbwQeBr4RaaO06QhqLU9bdrA1sMYY3JU2IFtjwFNwMtAW+ar41HVVXjd9/FptyU8X5puXj99NwFT\nw6rq94HvJ6TtA04PVXGTGfv2wbXXwsaNwftYV7kxxoQO4pNV9SNZqYkZdpwD15qaYPNmIpdcAqef\nDn/6kzuvdZUbY0zoIP4nETlZVf+SldqYISflCPOggWsnnugt9VlbS6R7CtTEvMYYY0IH8bOBq0Rk\nC9A9HZaq6smZrZbJJ30K1Lt2QVvAFZlx3vo61to2xpjUwgbx8/3fis1kNmykCtKR5ctTB+rWVneh\n27fbtKc05ZvxAAAgAElEQVTGGNNPYYP4Vrx1xY9R1RtEZBreAiGxTFfMDJw+B+mWFnjsMWhIvI3f\nt307lJe7t53sd968+WZfqmyMMYbwQfynQBdwDnAD0OKn2SjufBYUpDs6YM0aeOstd76NG+H222H/\nfvf27kC9fbt7uzHGmH4JG8TnquopIvIKeLdt+fdRm6Ho+efh85+H3bvd2884A379a6ip8eYpD8tu\nEzPGmH4JG8QP+jOZASAi4/Fa5iaHpewu//rXYdMmd8YPfABWr/aCtKOlnpYUgdoGrhljTP+EDeL/\nATwCHCUi3wc+DlyX8VqZzArqLv/zn+Gpp6Ao4M9A0hy7aIHaGGMGRaggrqp3i8jLwLl+0iJV3ZD5\napkBMW2aN//4eefBtm3B+/XS7W2B2hhjBkfYljj+XOQp5sM0eWPcOCgutiBtjDF5KuwCKGcA3yJ5\nARSb7CWPWZA2xpj8FLYlfg/wVeCv2IC2/LFnz2DXwBhjTBaEDeLvqOrjWamJyY6uLti6lcjMmTBx\nYs9tdiuXMcbkNVHV9HcW+TDwSeB3wEE/WVX14SzULS+IiIZ5DwfcsmXez7PPQkHBYNfGGGMAEBFU\n1abv7qewLfErgZl+vvju9GEbxHNaUxN8+9vwxBMWwI0xZggK2xJ/FZiV203PgZXTLfEvfclbKey2\n2wa7JsYY04O1xDMj9HriwGzgb1moi8mkv/4V7rsPNtht/MYYM1SFbYlHgWMBW0/cl5MtcVU45xz4\n+MfhC1/oV1HdU7bWR6NU+ut/N7S2sqe9nTLgqIT924Dm0lKqKyqomjXrUHp9NEol9EgDqG9oYM6U\nKckvbLO9GTOkWUs8M8IG8Sr/YXcmAVDVWCYrlU9yMog/+CCRz33OW0XMnzr1UBAuLaUJDgVkSksP\nBVZXQI3V17O8uZkIHJoQJoK39mxVXFq8WmB5Qlp8/h77VlSwvLk5KX3RhAnMSQj4QXUMSg86cbAT\nBGMGnwXxzAg77WpMROYAZ+MF8j+q6rqs1Mz0zb59RK66ipgIy5955lByxP8hISDT3AyNjYAXUCOb\nN/coLkKWdXY6kyv373fO9+6qY1B6xP/pPr5ui6JRIjU1SWWE6RXodQ12Y4wZAGFnbPsS8M94o9EF\nuFtEfqGqt2SjcqYPfvADGDmSqnfeCZ/X0SLOun373OlBE9Ts3etOD1rT3KGyrS3UCYIr6Hf3UKSz\nL2SmByFMGanS7UQjPa4TtUx8Nrlehv195JewA9s+g7em+D4AEbkReAGwIJ4LNm+Gn/8cZsyAvgTx\n0aODg2S2jBnjPnkYM8YdyMvK3IE/3RXXIPgYuy8xJKjcty8p6EcCig57ghCmByFMGanKjtXXJ51o\nZOIEIdeDU9hjjEWjLE/4DCL0/7PJ9TIiSblNLgu9AAo97w+3qVcHWY/Wwvr1UFFBbONGqvpSWC7d\nSx4UlIOWTS0thQMH3NsSBZ0IBI1tCOotcAnqzQg6cWhpSb/s9nZ3ekeHO73L/e+5vLk5aX34TJ0g\nRCBng1NfjjFtAe914GfjEnASmfbfNcDBg+70MGWYvBI2iN8JvCgi3d3pi4A7Ml4rk764tcIjALt3\nZ/wlaisqaCotpTZhdPoWku817B6dXusYnV5LcuuoqaGByJw5yS8ajWavez/oRKCszP0lGNRb4BLU\nmxF04lBSAq2t6ZUd9EUcdCkhTK9K0PEFpYeZjz+ofmFOjoKOJczfSNhjCVN2Bi7zBJ5EBowbcQo6\n0QtThskrYQe2/UhEVgMfwBvYVquqr2SlZqZPIvQcRd6tHvhUYSGl48bRBIcCcvzo9KCAWjUI18gi\ntbVEHAPHguroSg86ccjqCUJQb0bQiUNxcfpljxrlrvfo0e70ior0jzPo8kVQ+siR6fciBPWqFBen\n31INOgkKqp9L0AlW0LGEKTvovQ76bFyCTiLLy9MvY+RI975hyjB5pS/rib8MvJyFupi+CDrzjhOr\nqGDOnDl5NWAlm/UMe4IQFPRrKyqoStw/mycI2RQUaIPSCwvTLzvoUseIEem3VINOgsKMhQg6wQo6\nljBlGzNIbD3xfNbUBOuS7/CLJD6fM4dIXd1A1CgvhD1BCAr6rh6KbPYghCkjKD1WX5+fJxmDoKm0\nNCufTa6XYasb5pewk728hmM9cZvsZRAme9m7F847j8i2bUR27ACCJ1SJLFhgQdwAwfe32+h0uxVv\noNlkL5lh64nno3374MILYc4cmDmTyBtvUB+NUrpzpw1gMSlZUDJmaAkbxK8XkWXYeuKDZ/9+uPhi\nqK6Gn/6UiH+dL1JTA6tXJ7XEYxUVVFn3mDHGDElhu9PvwVtP/G/07E6/KvNVyw/97U6P1NYSe/LJ\npHtEm0pLmbNwYc+W08GDRKqr4eBB6kWoPHCAhtZWxnV10dXZyYOu8q0r3RiTg6w7PTPCtsRPx9YT\nz6xYLGlWKIBIczP1K1bwwRUrGA+0A4V4H9j9HL7+Hf9jjDFmeLH1xHNYJTCHngE64tzTGGPMcGTr\nifdTf7vT58yayKudjbT7c34cGpa2D+jAO80aCXRBsUJnGxSWQ1cLjBrpzZBWijdnxukdUNUEy+Pu\nILLudGNMLrLu9Mzo63riPdgtZn0P4qOOH8O+yx2zSP0BvIW/gQ8mpH8w4TfAW3jR/CCUdIF0woSR\nFVQWjaN+7aY+188YY7LBgnhmhF5PPEv1GLY6ukb0v5D4oM7hLpI3aKZqi2MGMmOMMUNCDi1bNUxl\neeWwaDSW1fKNMcYMHgvig6y0vDyr5QetbmiMMSb/hQriIrJSRI6Iez5WRGwp0lzxh+Sflo63qP3X\n2kGtljHGmOwIO7CtXlXn9JY2nPR3YNvEWXNo7HwVirtXI/PHpztGp6PF0NYBo9TbXjoGCvbCJ/Xw\nALfu6+PdA92Awq5CRpWPorSolIWnL2T5zcv7XF9jjMkEG9iWGWHvExcRGauqu/0nY/HmIMkoEVkI\n3OyXfbuq3uTY5xbgfKCVuHXNg/L6dX0AmA7EgE+oapO/7ZvAp/Ei6BdV9Sk//TRgOV44fEJVv5Tp\nY104bxEPPPBX2tu9j6KzswtvqfZ38G4gKwN/upeiokI6OpooKKuAT9RR0FVOx39Vwp3HQMdaGNPG\noZOAiRwa6NZJJ81/aKaZZh594VEmnj6RtiKvn720qJRZx3kLRTS81sCU43suBBH9a9Q7+jYO5Wnd\n1Up7azsUA+VA97+hei9f2lFKxaSKQ+XGlxOfFvSamUrP1GtWVVbZiY8xJieFbYkvAb4NPIj31X0p\n8D1VXZmxCokUAq8CHwK2Ay8Bl6nqxrh9LgCWquoFIjIX+LGqzkuVV0R+COxU1R+KyDeAI1T1WhGZ\nDdwLnAFMxpsXfoaqqois8V9njYg8Adyiqk8m1HdAJ7B7+WVYuBB+X3eQf3/tMzz4o4cY0XIkrXvb\n6Sxqg8uae7bKu8WNXu/xOE7Fqgqaz09YpjLxlrbuNNftb90eAf4hIS3Ma2YqPUOvOeHXE5j1np4n\nAtk8KbGTDzMcWEs8M8LeYrZSRF4GzsFrd12iqpmeve1MYFP37Wwicj9wMbAxbp+LgBV+nV4UkUoR\nmQgckyLvRcACP/8KoA641t9+n6q2AzER2QTMFZE3gNGqusbPsxJYBPQI4gPttNPgxhvhU5eO4MUX\nV1C3vI5tH9rmbfxD6ry92de+r/8VDKm1vdWZfqDjgDu9051+sPOgM92lo6vDmR50MtZW1MbqY1b3\nTIwBH4RGek6ZWxGtYPMxm5PKCJWeobKjv45SU1vTMy3HTz5ypYxcr182y7CTv/wStjsdP2hnc9rV\nycC2uOcNwNw09pkMHJ0i7wRV7f5WbAQm+I+PBl5wlNXuP+623U8fdFdfDc8/D5/5jHBMZTXbehxy\n3xUXFNOBO8BlS6EU0k57UnqnupdU7exyp7d3JZcRZH/Hfmf6ngN7nOnNbcmt8yBBJyX7292vGbS/\nS3un+xiD3qu8PPnIlTJyvX5ZLIMtSdlNDktrdLqIPOf/bhGRvQk/7m++vku3bzqdbhhxlef3f+f1\nIi633gqbN8P27Qkburu6+2BEYQYmngmppKjEmV5e7L71Lih9ZPHItF9z9IjRzvSK0gr3/iXu/V0K\nC9xDRETcf65B+7sE9ULsO+juQQlz8rH3oGPWwBRltxxsSbvstg73fY5B6S5BJ15hToKCepqC6hGm\ndydo3zDHGHQiGuYENaiXKSjd5L+0WuKq+n7/96jsVgfwWrxT455PpWeL2LXPFH+fYkd6d5hrFJGJ\nqvqWiEwC3u6lrO3+Y1dZPUQikUOPa2pqqKmpcR9ZBpWWwkMPQfU5MTjbT4y/Zr0FeMufkB2Fgt7/\niVtb7aZylwJJ/07MksIS2kh+H0uLSjlAchAO2t9l1IhRNJMcmMeUjAlM30N659hlRWXsIznIFRe6\ne2dKCktoJf0A6hJqPE7AOXtQT45LUE+TBpzPhwmeQfsGle0SeAkpIN0l6GQnKH0g1dXVUWfrOGRc\nqO50EblJVb/RW1o/rQVm+PO07wA+CVyWsM/jwFLgfhGZBzSpaqOI7EqR93HgSuAm//ejcen3isiP\n8LrLZwBr/IFte/yBc2uAxcAtrgrHB/GBVFUFZWUkf5V+EGgeDeuaQP0AVDEH7qz0Hneshbf8j76j\nFDq8a2KdB16i4pHpPYras/tN2FEAbV1oo/+F1Nru3f72LodPhbp1AC0g95QypnzCoeTWPTspfAjm\nnnZ6j90bChqY45gaNhPp0ZYoPO24bhiy7GhR1Bkkc11Q69+lqMD9VTCicAT7SQ4AxYXFjr3dgk5g\nyorLOEh6rd3Ak6Ci9E+Cgo6lrMhdj5HFI9P+3IP2DSrbJegkLSjdZfSI0c59g9IHUmID5/rrrx+8\nygwhYa+JfxhIDNgXONL6TFU7RGQp8Fu828SW+aPLP+dvv01VnxCRC/xBaPuAq1Ll9Yu+EXhQRK7G\nv8XMz7NBRB4ENuCFoGvihptfg3eLWRneLWaDOqjNZXRnJa13VvnPYkAVFGyGse/CpZ+Ah++CjjJo\nXgTNEX+/CK5FTUdX1NK8bnlCaoTkVcsjh1/LuThqLcryhK+MCOUVMTiyqueub9fDCMc0A5lIb6gE\nKqGo52t+4HhYvtxVb7faf60ltiXWIy1TJwh28mGM6Y+0griIfB4voB0rIuvjNo0Gnst0pVR1FbAq\nIe22hOdL083rp+/Gu/XMlef7wPcd6S8DJ6Vd8UEwa+IiGldH/GeRwz9bO6DqdbjyXLjvMUdzPVlz\nlr/vm5uXszphnFVFRS2bN0eS9s1MegSI0JgwbicaXURNTXIZDQ31TJniCJINTUyZUtMjbdaoGqqq\nwp0MDLR8PPnIlTJyvX7ZLKOqsiopv8ld6bbE78ULjDdyuNUtwF5V3ZWNipm+igAx6KyCh++GD/4v\nOLkado6B9jp/nxhQB01V0LwcKmqhMkZBYZSuzprDRTVVQXNVVmsbdOKwJ+BSbkvAeKr9IS757d9f\nyepDJz6HhT1BqK+PJZ0M5FJgt9uEzECqrY0QiyWn59L/xFCU7sC2ZqBZRP4JuBw4RlVvEJFpInJs\n3L3UZlBFev7WAvjv78F7HoIrXsMbJtDtDbgTaAYqY3DVaroA4m83uZOsB/HRo2GvY2D0yJHugF1S\nAq2OXoUQl39DnyAcDLik6epZCN/KT06PRuuBSmbNquqRbl+G+ccV2II+30z8jQzm31kshvPk2H3J\nzWRK2GviP8Wbxfsc4AagxU87PVUmkz1VVZD4TxKN1tPc3EJxcS1tbdC+91135iPWMHrGXDqaXncM\n94lTUQuVdXjz44DXkm+Dpolx19n7Jmgl1sKAO6+KA8ZTlZbCgTQH8VZUuHsAgk4Q2tMfpExLS2Za\n+Zm5DND/L/+gL/R8DE5hyshU2dFojMbG5QmpEVyfbyb+RjJRhgXd/BI2iM9V1VNE5BXwrjOLSPrD\nVE3GpXPGPObkKlx3AZeUjGDJl8/g9h+sd2wFGb+GUTN20fpWA50fbwLe6LnDnfuh+VKoWAOV3dGv\nCynooKjoScYWTGTWxEUA1NfHsn7Nvb+CThBGjkx/vEBQt76rtwHSP/EAaGvL3glCUBlBJw75GJyy\nOc4iqIwxY2qT0oJ0BNwFGpTuErT0cJi/M5Nfwgbxg/785ACIyHjwe2FNzgpq7R58p5JRz9xK0bu/\n4UBigAZKCkpZ8uUF3HPLPc75Y06aO53f/e0nfOILn+gxM5gC7exh1pZZ1PknGV7LLZJURkNDE3Pm\nZCfdazXVJrWaotHsDeIbPdpddlkZ7HPMNdLpnmzNKajOrnIh3DiBroD/4qDxA+XltWmXHRRAgi5T\nuAQFJ1fPSZCgfYPep6D31SXs2I4w9QjzOQbdeh/0+Zr8FzaI/wfe8hZHicj3gY8D12W8VmZAlJfB\niBHBXxIlB8Zw6wW38tANv8E1DVz0zdeYeetMmrfs8WatT9wejXHc6XPY2ZGcd1xRJZvW1vfzCPom\nEycUYXsWigL+08rL0z+hCBo/UFzsbq2FGScQ1FMQFITCtOyCTlTCXKYICk6FhemXE7Rv0PsU9L66\nBH02QZdugspw7RuU7lJW5j45Cko3+S/sAih3xy2AIsDF8auLmdxU2lZJ86F7yQ8bVdrEDTfAfz5Y\nSaNje8u+Jq65BpoDvsjL90xk99e3UPHAVPY6JrPbWfQW78puDn7M8e32yOCNZs1E2UEnAtls5Qf1\nqASdiGVinMCYMe5APmpU+scZdKIS5jJFUBAqKQlupae7b9D7lOoEN1HQZzOcdI/PWbcOpk6FsWPj\n0022hJ2xrRQ4FW8RyiLgE/5SnDdko3ImMxbOWxQYLCHxXvPDTpoTYeZM6Pidu9w9e+Ckk4SW/e4/\no653K+gc4Y4iXao8+cKjNLZVJm2LvtVErg+uCToRyEQrfzAuAwQJ05o3yUpL0/98M/E3koky+hp0\nu/8nPvYx+Od/hosu6ls5Jpyw64n/Fq9f9WXgUCeZqv7fzFctPwz0euLZUFMTcV73XLAgQl1dhImz\n5jiD7diiJv7wcD3vv7yKlo8nX1Mf+UtvCtd9lyZv4/cCbWVwYfKFyopHptNUH7P7ThMEvR8DP7oa\nJkxYxKxZuTmyPJdGpw/Hv9VLLoHLL4d//MfU+9l64pkR9pr4ZFX9SFZqYgaN6za1w+kpWuoLIpx8\nMoxsr6QloLu+rdS9pNrovZM5UNjKQcdUcgfblZYWUrbUa2vpNcAPtZOAwahzUM9CVdWcvHwPTfaN\nGBFuvIPpn7BB/E8icrKq/iUrtTGDor9fxkFBftaCCPVNy515CrSQso7RHGR30rb9Yxs44tNL6BzR\nAJetS9re9sj0tCaW6G2foRbks8HeBxNWcbENohtIYYP42cBVIrIFDi0ppKp6cmarZXJJby31VNsb\n/lrp3c+QYFxRpXPUOsCofRO5/l/ex9e+/pBzIcfmZli99VGYXpe07dm/NnHqqREKCuDVV53F09QE\nDQ2wZQs880xyvXP9erwxucxa4gMrbBA/Pyu1MDmtt9ZY6u3B2ybOq3KusTVyRDFfOfvz3LD/Jppd\n96+Pb6aoooN9/5DcSi97aDq33+7dF/vZz8IrrySX//rrcPrp8HbiMqrGmH6zlvjACnuLWSxL9TDD\n0MJ5NUmrbAFUzatKma+rqJ19ZTuc2woL4dRTvcdjxrjzn3oq1NXB2WfDs88mb9++HRob4RvfsO52\nY8KylvjACnuL2f/Em5Cre0Sh4i2h8bKqDs7MHSZv9bbKVmkpzpb62K5x7G9W9rA1aVuXHJ6dI/qW\nu8u9+xa2oPnZ9+yBmTO926uamiKOPbw0u6ZuTDJriQ+ssN3pp+EtdvJrvEB+IbAe+B8i8pCq3pTh\n+plhLFVL/ckX6nDNQbN3zA7m3j6XRTMX0XHE27AwucudVdNTvu4JJ8ATT8AZZ3jXzxN1TwxiqzYZ\nk6y42FriAylsEJ8KnKqqLQAi8m/AE8ACvHvHLYibjEnVUq+praHRcb387KoP8J1zvsOj0UfZW+5e\n6r77Ht9UA/LKy2H8ePdrv/QSVFeHm1vbmOFixAhriQ+ksEF8PBD/8bQDE1S1VUTSnPzQmP6rqqyC\nLY70I6o4t/pczq0+l7888Bee4ZnAMvra5f3+98PPfgaLFrkHx3W31K273QxHxcW2atpAChvE7wFe\nFJFH8brTPwbcKyIjgQ2ZrpwxQXq7ng7ejFAunV0hlg5zlguzZ8PRR8Pf/568fe1ab3tzM+zYEXGU\n4EozZmgYMSJ4QR2TeWFHp39XRJ4E3o83qO1zqrrW33x5pitnTDas3bGWZ7c+ywemfSDlfr3dHx/k\nrLPgRz+CSy9NvZ+11M1QZNfEB1bYljjAZqAAKAXKRWS+qgb3WRozSIK63AumFnDpLy/lyBePZGzZ\nWAqkICnf8puX9xpIUwX5006DadO8CWUSrVsHv/gFvPYaPP+86zVSv64xucxuMRtYYW8x+2fgi8AU\noB6YBzyPtzSpMTklVZf7O/ve4YTfn8DfTvxb8kY/8Nb+ay2xpljS5nSDfJCjj4bf/Q7WrOlTdmNy\nmt1iNrDCtsS/BJwBPK+qHxSRWcAPMl8tY7Jr/MjxnDj+ROfAt/3t++nSLmJNMVYfszo5s6N1Heq1\nx8MDDwRPNmNMPrOW+MAKG8TbVHW/iCAipaoaFZGZWamZMVkWNPCtvrGeI246At4EjgnO31tLvbdr\n6kGTzaxbB48/Dg89FGFr8nw2ds3c5DRriQ+ssEG8QUSOAB4FnhaRd4FYxmtlzCB635T38asv/opz\nXjmHv5C8YN/W5q0888YzbN69mWePdTSl/ZZ6XwPtxInw3e/C+vVw4ICrjIgNijM5y1riAyvs6PRF\n/sOIiPwBqACezHitjBlkR5YfyRFlRzi3Hew8yNee/hovbXsJjg0uoz8t9Tvv9OZ4r3dMZvz2295E\nM2vXJue1QXFmsFlLfGClFcRF5Nf0nDM93meAizJZKWMGQuCEMZVVKfMdN/Y46j5Tx9nPnM2zJLfE\nY00xntv6HK+/+zp/rP5jcgHdr1kZg6pY8vbKKkTgzf3uud8372qio5GU88Kn0tvJhTH9YbeYDax0\nW+LzgAbgPuBFPy1+ERRj8k5vAau3IF9Y4L6o3dnVydJVS1m/bT1UJ29vOdjC6+++zmu7XuP5455P\n3sF/zbbSJrjMsdzqI97c782OpVhbfjkdVZhxxhzneu3jiiqZ8p7KwAF7qQI8YMHf9MqmXR1Y6Qbx\nScB5wGX+z38B96mq4/4cY4aGvgamY8ceS93n6jjr2bN4nuQgvfGdjZy78lwatjfAccn5/9L4Fy5/\n+HL2l7nnfj9Y3IK7UwxaW5X3vQ927G9i/yeS55bnEZisFc68qtrriPxMB/9U2+zEID9ZS3xgpRXE\nVbUDWAWsEpESvEC+WkQiqnprNitoTK7qraU+onCEM98Zk8+g7kt11LxSw2qSg+Lk0ZM5/7jzebxg\nFa4GTVfpfjq73B1gOnUrWz5yDPt/86Zz+54x2/jj1q3OHoJn3njGm/jGMSJ/feP6wG27Wnex98Be\n/jzrz8kbewn+qbZZr0B+soFtAyvtgW0iUoq39OingCrgx8Aj2amWMbkvW8HiyPIjueLkK7h9xu3O\nID/v2DOIRmPOVdzGH5jKn/7H73jvr97PPhqTto/cO4nykgLeZlvStqPapjHj+Kk8x3NJ2yaNnkSX\ndrGTnUnbtu/dzsFOd//pmu1rKJRCZ/Dfvmd74IkO0KdegejTUWpqa5LSLbhnX/dJ15498Pc9UFPr\npdt7n13pDmy7CzgRb9nRG1R1fVZrZcwQ0NeBc+mYNavKGcRnz6rm2LHHUtRZ6sy3r7mI9oC4eaBN\nKCpwfyWMKx8HwEY2Jm07ecLJAM4TjhPHn0indvIKryRtaznYQnuXu8n2/Lbnvbo4gv+be9+kuLDY\nma+toy10y77htQamHD8l7fRc6wnIxHFFN0WhDWa9Z1afy6iP1tNc2gwfBN7Lob+GZ3/1LM+e9Syb\n/rQp1HGZ9KTbEr8c2Ic3Y9uXEibJUFUdk+mKGZPv+jtwrteTgD6cIJSXQ+euSrgzeb/S0uSBcP01\ncsTIwG0zx3nzRLmC/ymTTqGjq4OXeTlpW/OBZto73cG/5WBLYHp0Z5QXZ7yYtK0iWsHmYzannd6X\nnoCwJwq9pUc3RWnr8FZ/bmltofNgJ0z0d/pgH47rGOAP0HhMY+/79lJGos6xnexsS+7BMZmR7jXx\ngt73MsaE0VuQ70+LblxRpfNi17jSSqbMXMTq1ZGkbZPmRNi2/lEq6qcnbWsoauIDH5gTeOLgagn2\nR2mRuycBYNY4r7XoCv4lhSW00pqUvnHnRjo6O2BGcnl7D7rXzewOkoma25oDZ/sL6gkIe6LQa3pi\nD8Uf8IJ3XBDt0i5nHVXTv6GotT35vQTYe8DWGs0VfVnFzBiT4zatdcwS46upiTjTX3sNOjsXOWeJ\nm7MgwvKb3fnA69Ltc69BBk8MgrrZzzj6DMAd+MuKytjHvqT0oGC3+d3Ngdua25qd6XsO7HGmp+o5\ncJZ/wF2+S1CgDaqLS6EU0k5yr0d5cTktuOtoBpYFcWMMAKef7s0E93JyDzbQ2/rnyzNen76cGEQ7\nojSTfqADAscBlBWXcdBxf8Cpk04F3CcEY0rGsIfkIDlyxEhn0AvqOSgpcqePHjGavaTXCq4orXC+\nF0HpLiVFJbSR3CMRNEeCGXgWxI0ZZlJN9+oK0uDN4/7OO7BhQ3K+bE312pfLCbX/WktsSywpPRtd\n/i5B3eyF4g56QT0HxQXu9ALJ8Sub7+C8Lm6yx4K4McNMqgVSgrrax42D7duzU59MShX4g1r2DQUN\nzNkyJ+30TPcEZFJFW8WhOoc5rkOj07fM6nXfoPT6aD3NLc2QcP5R2FXIuFHj+nI4Jg0WxI0xvZo0\nyftZ7bh7q6kJlizJ/WVTB+LWr6CegLAnCr2lx49OByjtKGXWlllUzRu8e7K7b3Xr7ITnnoP58710\nu4R5MugAACAASURBVE88uyyIG2MO6UtX+9//Dhs2QHt7cr7htqracA5W3cfe3g5lZVC3fFCrM2xY\nEDfGHNKXrvYzzoD9+2HNmuRtHR29DYgLfj2Tn4qKoLMTurqgIMcv4Q8FFsSNMWnpSyv9+efhb3+D\npqbkfMOtlT5ciBxeBKWkZLBrM/TlVBAXkbHAA8B0IAZ8QlWTppESkYXAzUAhcLuq3tRbfhH5JvBp\noBP4oqo+5aefBiwHSoEnVPVLfnot8H/wlmAF+A9VvSPTx2xMvuhLK/2ss2D3bu+6uRk+uhdBsSCe\nfTkVxIFrgadV9Yci8g3/+bXxO4hIIXAr8CFgO/CSiDyuqhuD8ovIbOCTwGxgMvA7EZmh3owNPwOu\nVtU1IvKEiCxU1Sfx1km/T1W/OCBHbswQVFgI48e7tzU1WVf7UFVcbGuKD5RcC+IXAQv8xyuAOhKC\nOHAmsElVYwAicj9wMbAxRf6L8QJyOxATkU3AXBF5Axitqt1X81YCi4An8RZsdt/0aYzpoS9d7dEo\nvPGGdbUPRbYc6cDJtSA+QVW7Z+BvBCY49pkMPdZRbADm9pL/aOCFhDyTgXYOd5eD17Kf7D9W4B9F\nZAHwKvBlVY3f1xjj60tX+5lnwltvBXe1Wys9f1lLfOAMeBAXkac5vN5OvG/HP1FVFRHXBMWJaeJI\nS5U/Xb8G7lXVdhH5LF7L/tx+lGfMsJSqlV5Q4N2ilmjvXtiyBZ55JjmftdJzX/fANpN9Ax7EVfW8\noG0i0igiE1X1LRGZBLzt2G07MDXu+RQ/DSAovytPg58+JSF9u1/P3XHpy4AfBtU7EokcelxTU0NN\nTU3QrsYMO31ppW/Y4N2iFMRa6bltxIjklnhdXR11dXWDUp+hLNe60x8HrgRu8n8/6thnLTBDRKqA\nHXgD1i7rJf/jwL0i8iO87vIZwBq/tb5HROYCa4DFwC0A3ScDfv6LgA1BlY4P4saY/jvzTGhthbVr\nk7e1tXnX2V3LqVorPTe4WuKJDZzrr79+YCs1ROVaEL8ReFBErsa/RQxARI4GfqGqF6pqh4gsBX6L\nd4vZMn9kemB+Vd0gIg/iBeIO4Bo9vJbgNXi3mJXh3WL2pJ/+RRG5yN9/F1CbrYM2Zrjqy4C4l1/2\nJhRxiUZjzta9tdAHlg1sGzgSZoF4k0xE1N5DYzKvpibibG3Pnx+hpQX+/OfkbaNH17J37/Kk9AUL\nIoEnBhbgM2/uXPjxj2HevOB9RARVtTuA+inXWuLGGAP0rZW+N8VS20Fd8NForbXeM8xa4gPHgrgx\nJif1ZUDcmDGwZ09y+oYNMGqUu6y2NgvumWa3mA0cC+LGmLwT1EqPRpucQXzsWGhpcZe1f787PSi4\nQ8RGx/fCWuIDx4K4MSbvBAXKmpoIjY3J6RP9mSm2b0/eJgFXZVtbg18/bNd8Q0M9U6Ykrw+er0Hf\ndRITjcZ4550tiEyisxOeesqbB6CgYCfTpo1i0ybXzUamvyyIG2OGjL5cRy8thQMHktODltF88UWv\npekS1HqvqKhl8+bk9LBBvzs9Go3R1ualtba2ATspL59CaWkTs2bNSauMnvWIAYfz9laPaLSexkZX\nUI7Q/f6rekuSdnZG2Lkz5tjXZIIFcWPMkJGqVVtbGyGoC765OXn/oOD+nvd4XcXr1iVvc3XlgxfM\nXMIG/aB0iNDc7P00Nkb6XEZ33t72HT261pHfDAYL4saYYSEowHtdw8nbgoL7yJHBrzFypPva+759\n7v2Dgn5QV77rpCJIUBlBYwBcgkb7p7oLwAwsC+LGmGEtbHBP1TVfWOhOHzOGwBMCV9AvLHQPDAtq\n0QfVxVVG0BgAl7Iy9wlIRYX7eMzAsyBujDEOmeyaDxIU9EtKOHTNO155efrBM6iMoMsELkEz45nc\nYR+RMcaEFLb13tDQxJw5yelhg36uKC0l6XgOj06P9kgvKNjJuHEBN+mbfrNpV/vJpl01xvRV0P3m\nuT46PRO3xtm0q5lhQbyfLIgbY0x4FsQzI+BOSGOMMcbkOgvixhhjTJ6yIG6MMcbkKQvixhhjTJ6y\nIG6MMcbkKQvixhhjTJ6yIG6MMcbkKQvixhhjTJ6yIG6MMcbkKQvixhhjTJ6yIG6MMcbkKQvixhhj\nTJ6yIG6MMcbkKQvixhhjTJ6yIG6MMcbkKQvixhhjTJ6yIG6MMcbkKQvixhhjTJ6yIG6MMcbkKQvi\nxhhjTJ6yIG6MMcbkKQvixhhjTJ6yIG6MMcbkKQvixhhjTJ6yIG6MMcbkKQvixhhjTJ6yIG6MMcbk\nKQvixhhjTJ6yIG6MMcbkKQvixhhjTJ7KqSAuImNF5GkReU1EnhKRyoD9FopIVET+LiLfSCe/iHzT\n3z8qIh+OS/+eiGwVkb0Jr1EiIg/4eV4QkenZOOZcV1dXN9hVyKqhfHxD+djAjs8YyLEgDlwLPK2q\nxwO/95/3ICKFwK3AQmA2cJmInJAqv4jM/v/s3Xt8FNXd+PHPNxBIuAUQBORiQFGK1mK9oRaIPmq1\nF7VWrVbBtLaPLaVa+/Ti09K6tk+t9qmttRfrr8WCUBVbr23FS58KKlVQNAhCVJQo13BNIIRALt/f\nH3MSNrszm51kN9ndfN+vV17ZPTNz5szOJt85Z86cA3zOrX8+8DsREbfN48CpPmW5FtipquOBXwK3\np+QIs0yu/yPJ5ePL5WMDOz5jIPOC+IXAPPd6HnCxzzqnAutUtUJV64EHgYva2P4i4AFVrVfVCmAd\ncBqAqi5X1a1tlOVh4D/ae1DGGGNMOmRaEB+mqpXudSUwzGedkcCGqPcbXVqi7Y9w6/ltE6RlP6ra\nAFSLyOBkDsIYY4zpDKKqnbtDkWeB4T6Lvg/MU9VBUevuUtVWgVNEPgucr6pfdu+nA6eo6vUisttv\nexH5NfCyqv7Zpf8ReFJVH4lad6+q9o96vwr4uKpudu/XAaeq6q6Y8nTuB2iMMTlCVaXttUwiPTt7\nh6p6btAyEakUkeGqulVERgDbfFbbBIyOej/KpQEEbZ9omyCbgDHAZhHpCRTFBnB3PPYlNMYY0yUy\nrTn9CeAa9/oa4DGfdV4FxotIsYj0wuuw9kQb2z8BXCEivURkLDAeWB6iLJfidZQzxhhjMkamBfHb\ngHNF5G3gbPceETlCRP4BLfenZwFPA2uAhaq6NtH2qroGeMitvwiYqe4+goj8TEQ2AIUiskFEfujy\nmgMcJiLvAN/Ap6e8McYY05U6/Z64McYYY1Ij02riWSVo0JlsJSIVIvKGiLwuIstdWlID8GQiEbnX\n9bNYFZUWekCgTBVwfBER2ejO4esickHUsqw5PhEZLSLPicibIrJaRK536Tlx/hIcX66cvwIRWSYi\nZSKyRkR+6tJz4vxlFFW1n3b8AD3wnjcvBvKBMuBDXV2uDh7TemBwTNrPgO+4198FbuvqcoY4ninA\nicCqto4HbyCgMncui925zevqY2jH8d0MfNNn3aw6PrwnWCa51/2At4AP5cr5S3B8OXH+XJn7uN89\ngZeBj+XK+cukH6uJt1+iQWeyWWxv+2QG4MlIqvoCsDsmOcyAQH4j+WWMgOOD+HMIWXZ8qrpVVcvc\n6xpgLd7YDTlx/hIcH+TA+QNQ1Vr3shdepWc3OXL+MokF8fZLNOhMtlLgnyLyqoh82aUlMwBPNknl\ngECZ6usislJE5kQ1V2bt8YlIMV6LwzJy8PxFHd/LLiknzp+I5IlIGd55ek5V3yQHz19XsyDefrnY\nI/BMVT0RuAD4mohMiV6oXrtXzhx3EseTjcd6NzAWmARsAe5IsG7GH5+I9MMb9vgGVW01SVEunD93\nfH/FO74acuj8qWqTqk7CG5djqoicFbM8689fJrAg3n6xA8iMpvWVZNZR1S3u93bgUbzmrEoRGQ6Q\nYACebBJ0PO0ZECjjqOo2dYA/cqhJMuuOT0Ty8QL4fFVtHvMhZ85f1PEtaD6+XDp/zVS1GvgHcBI5\ndP4yhQXx9ks06EzWEZE+ItLfve4LnAesIrkBeLJJKgcEyjjuH2Ozz+CdQ8iy4xMRwRurYY2q3hm1\nKCfOX9Dx5dD5G9J8K0BECoFzgdfJkfOXSTp92NVcoaoNItI86EwPYI4eGnQmGw0DHvX+t9AT+LOq\nPiMirwIPici1QAVwedcVMRwReQCYBgwRb0CfH+INABR3PKq6RkSaBwRqIGpAoEzlc3w3AyUiMgmv\nKXI9cB1k5fGdCVwNvCEir7u0/yZ3zp/f8X0Pb2rlXDh/I4B5IpKHV1mcr6r/5441F85fxrDBXowx\nxpgsZc3pxhhjTJayIG6MMcZkKQvixhhjTJayIG6MMcZkKQvixhhjTJayIG6MMcZkKQvixnSAiBwW\nNW3klqhpJF8TkYwah0FEponI6WnMv7eILBFPsbSeIvXLbkz+gSLyi9ghfY0x7ZNR/2SMyTaquhNv\n8gpE5GZgr6r+oqvKIyI9VLUxYPFZwF7gpRD59VTVhiRXvwr4u6qqGzSoOY/pwCzgLFWtEpG78cYE\nfyHZchhj/FlN3JjUEhE5SUQWu5rnU1FjRS92tdBXRGStiJwiIo+KyNsi8mO3TrGIlIvIAhFZIyJ/\nccNW0ka+vxSRV4AbRORTIvKyaw14VkQOF2+mrOuAG136x0Rkroh8NqrgNe53iYi8ICKPA6vFm43q\nf0VkuXiza/1nwLFfCTwe82Fcjjdv9LmqugtAVd8BiuXQDF3GmHayIG5MaglwF3Cpqp4M/An4iVum\nwAFVPQVvtqrHga8AxwOlIjLIrXcM8FtVnQjsAWa6pvlfA58NyDdfVU9xrQAvqupkVf0osBD4jpuj\n+ffAL1T1o6r6IvGzREW/PxG4XlUnAF8CqlT1VLwJOb7sLgoOHbRID+B4VX07KrnYlflcVY2dOOd1\nIG1N+8Z0F9acbkxq9cYLys+6JuUewOao5c2T5KwGVjfPrSwi7+HN4rQH2KCqzU3eC4DrgaeA4/Dm\ne/fLd2HU69FuHOrhQC/gvahlQnKWq+r77vV5wIdF5FL3fgBwNN7Y182G4DXVR9sG7MSbHOjOmGWb\n8YK8MaYDLIgbk1oCvKmqZwQsP+B+N0W9bn7f/PcYXSMW976tfPdFvf418HNV/buITAMiAds04Frj\n3EQVvQLyA5ilqs8G5BNd1mi1wCeBF0Rkm6reH7OuTdxgTAdZc7oxqXUAGCoik8GbM1pEJobMY0zz\n9sDn8TqAvdVGvtEBdACHaumlUel7gf5R7yvw5ngGuBDIDyjP0xxq0kdEjhGRPjHr7AD6xW7o5qY/\nH7hVRM6LWjSC1jV5Y0w7WBA3JrUagUuB20WkjOB7v0pwTfQt4GsisgYoAu5W1fo28o3OKwL8xU0j\nuz1q2d+Az7hH4M4E/gBMc/lNBmoC8vsj3hSRr7nHxu4mphXP9YhfLSLHxubh7sdfCNwrIie7ZScS\nope8McafTUVqTAZxHcb+pqof7uKihCYipcAwVb29jfWOwWvuv7BTCmZMDrOauDGZJ1uvrO8HPinR\nD4n7+wrws04ojzE5z2rixhhjTJaymrgxxhiTpSyIG2OMMVnKgrgxxhiTpSyIG2OMMVnKgrgxxhiT\npSyIG2OMMVnKgrhJSET2xs5Y1R2JyBQRKe/qcgQRkYluKtLm9xUi8h8p3keJiGxIZZ6dwU3v2uTG\nh+8WRKRURF5wr3u7qW+HdHW5TOp1my91d+Hmif63iFSJyE4ReTFqqMvQVLW/GzYzZVyAqXUXCHtF\n5KlU5p8OqvqCm5azU4UIQD8G/jfqfaJhXU2Gc3PEX5uKvFT1AHAvcFMq8jOZxYJ4DhGRAcDfgV8B\ng4CRwC20ni0r2bzSOcOdAp9yFwj9VfX8NO6rw9L8WSQrcBQ0ERkBlACPdVppOijXasV+3xE3x3p7\npfoC7AHgGhEJmuTGZKmc+kMyHAOoqi5UT52qPquqq5pXEJEvisgaEdklIk+JyJioZU0iMlNE3sGb\nhKM5bZx73VtEfi4i74vIVhG5W0QK3LIhIvJ3EdntWgCeb2P4zaTmtRbPTSKyTkR2iMhCERnklt0t\nIn+NWvd2Efmne10iIhtF5L9FZLuIrBeRz0etm+hYmrf9johsAebENiW71oRvicgbrjVhjogME5FF\nIlItIs+KyMCo9Se7FpLdIlIm3hShzcsWi8iPXKvJHhF5WkQOc4ufd7+r3H5O8/mYzgVWqOrBmPRT\nReRNd67vFZHebn8D3bna5pb9TURGRpVnsIj8SUQ2ueWPBpyb613+R7j33xGRze6z+1LMd2eu+4yf\nFJEaoEREPuSOfbeIrBaRT8d8JtdGvW9pHnbvm0TkOhF5223/m6hlee7cbheRd/GmQw0kIqNF5BH3\neewQkV9H5TPbnetKEZkn3oVydAvJF0XkfeD/ROQaEVkqIr8QkR3AzSLSK+h75vK5yH0fqt13/OMi\n8hNgCvAbd87vcutOcN+rnSJSLiKXReVzmIg84fJZBhwVfYyquhHYjf9kPCabqar95MgP3jSTO4C5\neNM/DopZfhHwDnAs3gXc94GlUcub8KadHAj0jkob517/Eq+2NxBv2skngFvdsp/izW7Vw/2cmaCc\n64GtwDa3vxMSrHsD8G/gCLypMn8P3O+WFeJdbFyD909vO3CEW1YC1AM/d9tNxZul65gkjqV525+6\nbQtc2oaYY/g3MNSVrRJ4DfgI0Bv4P+CHbt2R7ryc796f494f5t4vduflaLev54CfumVHunOQl+Az\n+l/g1zFpFcAbbt+DgBeBH7tlg4HPuH31Ax4CHo3a9h94NbcivNnKpkR9Lhvc6x8Cr0Ydw/nAFuBD\n7rwsoPV3Zy5QBZwe9V1dh9fE2xM4C9gDjHfLnwO+GFWmUuCFmO/qE3jTro7G+y593C37CrA26tif\nw5tdLu4zxPuurgTucOXuDZzhln3RnZdioC/wMHCfW1bsyjDXbVfgylgPfA3v76uAxN+zU91n8h/u\n/RHAsQHH3xfYgPddzwMm4X3fP+SWP+h+CoHjgI3A8zHH+jjw9a7+P2U/qf3p8gLYT4pPKEwA/uT+\n4OvdH+7hbtmimH8MecA+YLR73wSUxOTXBIzDqznXNP9TdstOB95zr29x/6yOSqKMp7t/loXun/gW\noChg3TXA2VHvRwAHm/8hu3+Eu/CC1uei1itxx18YlbYQmJ3EsZTg3YLoFZNfbBC/Mur9X4HfRr2f\nhQuMwHdx//yjlj8FzHCvnwO+F7Xsq8Ai97qYtoP4/8MF/Zjy/WfU+wuAdQHbTwJ2RX2+jX7nw30G\nG4Ff4LUQ9I9adi/wk6j3RxEfxOdGLZ8CbInJ/37g5qjPpK0gfkbMuf2Oe/2vmGM/N+gzdOd9W8Cy\n/wO+EvX+mObvXtR5KY4p4/tR79v6nt0D3BFwTp4Dro16/znig/I9eBdTPVy5jola9pPoz8ulLQB+\n0Nbfp/1k1481p+cYVS1X1S+o6mjgeLyr+zvd4iOBX7nmx93ATpc+MiqLoN7HQ4E+wIqo7RcBzT1e\n/xevZvWMiLwrIt9NUMaXVPWAqu5X1dvwaiNTAlYvBh6N2ucaoAEY5vJaDrzn1v1LzLa7VXV/1Pv3\n8YLUkDaOBWC7xjdPx6qMer0/5n0dXs0LvM/9suZ9uf2dCQyPWn9rTF79SN5uvJptrOhz+QHedwER\n6SMi97hm4mpgCVAkIoJXq92lqtUB+xoIfAm4TVX3RqWPiNnfxpjtNCbtCOK/a+83lzFJ0Z9ZLYc+\ns9iyfJAgj9F4gbfJZ9kIV6bofHrivntO7DFEv2/rb2YU8G6CskXfFz8SOC3mO/R5V5YhrlxtHXN/\nvO+KySEWxHOYqr4FzMML5uD9Yf+nqg6K+umrqi9HbxaQ3Q684DIxatuBqjrA7atGVb+lqkcBFwLf\nFJGzky1qgmUf4DVDR5e5j6puARCRrwG9gM3Ad2K2HSQifaLeH+nWS3gsSZQpSNB9/g+A+THH0F9V\nk5mOM5lyvIFXS4w1Jub1Jvf6v9z6p6pqETDNlV3wAsFgESkK2Ndu4FPAn0TkjKj0LXgBsdlo4kUf\ny2ZgtLtwaHZkVBn34TUhN4u+4GnLFuKPPcgGYIz4d0LbjHcRGZ1PA60v1mLPT/T7tr5nG/BuofiJ\nzfcDYInPd+hrbj8NtH3MH8K7dWByiAXxHCIix4rIN5s7KYnIaOBK4CW3yu+B74nIRLe8KLpzTCKu\npvIH4E4RGeq2Hyki57nXnxSRo90/5T14TbKNPmUcLSJnug4/BSLybeAwYGnArn8P3CquA56IDBWR\nC93rY/AerboKmAF8R0Q+ErP9LSKSLyJT8Do4/UVVNdGxpMEC4NMicp6I9HDHXSJRnckIvgDYjtds\ne1TAcoB/Ah8VkV4x+X3NHddgvP4PC92yfnjBpdotu7l5I3dxtAj4nXgd4PJFZGr0zlT1ebzP/BER\nOcUlPwR8wXW+6gP8IKaMscf3Ml7t+TtuHyV4FwcPuuVlwCUiUigiRwNtPW7VfBHSXJbr3bEPIvGj\nVcvwgv5troWiIOri5AHgRteJrR9wK/BgQK09Tlt/M8AcvM/sbPE60Y0UkWPdskpan/O/A8eIyNXu\n88oXkVNEZIKqNgKPABH3eU3Eu3feciHgvmuD8T53k0MsiOeWvcBpwDLxegC/hFdL+y8AVX0MuB14\n0DWjrgI+HrW9X60vOu27eE3mL7vtn+VQDXC8e78Xr8PXb1V1iU9+/YHf4d3H3gicB1ygqkHNfL/C\n6wz0jIjsccd0qqs5zcdr1l2lquuA7wHz5dBjNFvxao6b3brXqerbSRxLMp+FH415rdDSM/giV75t\neLWq/6J1YAvathbv/uZS14x6atxOVSvx7gNfHJPHn4Fn8Jps3wH+xy27E68/wg68c7UoZv/T8foT\nlOMFk+tjy6mq/8Tr+PU3EZmkqk8Bd+Hdy32bQxeOB6K2a9mHqtYDn8a7V78d+A0wPer8/BLvPm8l\nXh+PBT6fETHvm9P+gNdhciVe57uHfdZvLkeTK8fReOdlA3C5W3wv3vfmebxbNrXA15MsQ7PA75mq\nvgJ8wR1rFV4Hx+Ya9K+AS8V7OuBOVa3B+1u5Aq+1Ygtex8vmC7dZeBdnW125740px+fx+iTU+30O\nJnuJVynJLCJyPt4/mh7AH1X1dp917sL7B1ALlKrq64m2dTWOhXhNdhXA5apa5dIfBk7G+5J/PWof\ni/Ga8Zrvq56rqjtSfsAm5VzNbr7rG5DzRORDwDxVjQvyXcGVZxVe58Ckaq4mPcR7tLAM7ykD+/+V\nYzKuJu5qWL/Be2RlInCl+4cQvc4ngKNVdTzwn3iPNrW17U3As6p6DF6v0+Ymtjq8Hsvf8imOAp9X\n1RPdj/0BmIykqmu7OoCLyGfEe/5+EF6LzxMWwLue60T6Ifv/lZsyLojjPTK0TlUrXNPPg3hNkdEu\nxOuwhaouAwaKyPA2tm3Zxv2+2G1fq6pLCR7VLKlBSUxGyrxmptz2n3jN3+vwmuO/2rXFMSb3ZcJw\nkrFGEv+oSuwoVX7rjCT+sZXobYe5e4fg/aOJfkwEgv/hzxOReuBhVf2fgHVMhlHVxSTulWxSTFUv\n6OoyGNPdZGIQT7b2lEwNWfzyU1UVkWT2c5WqbnY9Ux8WkemqOr/VDpLLxxhjTAxV7VBLZ3f7/+v3\neWVic/om4p83jR04InadUW4dv/Tm504rXZN784QR29oqiKpudr9r8EaT8r3nGHaEnWz6ufnmm7u8\nDHZ8dmx2fLn3kypdfRxd/XllYhB/FRjvns3shTfc4BMx6zyB91wwIjIZqFKvqTzRtk/gPTuJ+x07\n41OrKxz3PO8Q9zof7zGUVRhjjDEZIuOa01W1QURm4T3n2QOYo6prReQ6t/weVX1SRD4hIuvwRnb6\nQqJtXda3AQ+JNzNSBYeeBUVEKvCeX+4lIhfjjbX8AfCUC+A98J7v/EN6j94YY4xJXsYFcQBVXYQ3\nAEV02j0x72clu61L34U3e5TfNsUBRTk5ieLmtJKSkq4uQlrl8vHl8rGBHZ8xkKGDvWQTEVH7DI0x\nJhwRQVPQsa27/P8N+rwy8Z64McYYk7WKi4vp3bs3O3fubJV+4oknkpeXxwcfJJpYLxwL4sYYY0wK\niQjjxo3jgQceaElbtWoV+/fvRyS144dZc3oHdafmHGOMSZV0NadHSkuhoiJ+5eJiInPnJpVvR/MY\nO3YsX/rSl3j88cdZvnw5AN/61rcYPHgws2fP5q233uLyyy/n2muvZdasWTQ2NjJ16lQuuOACZs+e\n7Ztn0OeVkR3bjDHGmHapqCCyJH4CxUgn5zF58mTmz59PeXk548ePZ+HChSxdupTZs2fTu3dvFixY\nwJQpUzjnnHN4+OGHUVW+//3vhyklYEHcGGOMSYvp06dz3333MXXqVCZOnMjIkSNblh133HHMnj2b\niy66iB07drB8+fJ2NbVbEDfGGJP7liyBFN+PTkREmD59OlOmTGH9+vXMmDEjbuS1GTNm8P3vf59L\nL72Uo446ql37sY5txhhjct+0aaCa3M+0aSnZ5ZgxYxg3bhyLFi3ikksuiVs+c+ZMPvWpT/HUU0+x\ndOnSdu3DauLGGGM6LBUdynLRnDlzqKqqorCwkIaGBsAb733+/Pm8/vrrrFy5kscff5xrrrmGlStX\n0rdv31D5WxA3xhjTcanoUJYKxcX++ywu7tw8nHHjxrV6LyJ88MEH3Hjjjfztb3+jT58+XHnllTz+\n+ON885vf5J577gnIyZ89YtZB9oiZMcZApKTEP4hPm0Zk8eK4dBuxLRwbsc0YY4zJMRbEjTHGmCxl\nQdwYY4zJUtaxzRhjTMc1dwbbsAEOHICjj25JN+ljHds6qDt1rDDGmDbNnw9PPw0LFiRczTq2hWMd\n24wxxqTf4YfDtm1dXYpuw4K4McaY1Bk61IJ4J7J74sYY00WCRjkr27iRSaNGBaZXlJdDXR0AdbW1\n7ABG9elDVUEBkyZMSJhH2kdQO/xw2L49ffmbVuyeeAd1p3syxpjEQgfl8nIeq6yMSy8tKmJuZT6R\nOgAAIABJREFUdXXS6ZGYn4R5DBtGsQv0zSrKy6mClguAtsqd8ELgwAHo39/7nWDCEbsnHo7NJ26M\nMSkSGKwTBOXIu+/Gp/fv77+D+nr/9IMHky9kU5N/el1d4PCokZiyB5a7vJxISUl83s3BvU8fqKqC\nQYOSL28OKS4uZsuWLWzevJnDDjusJf3EE09k5cqVVFRUMGbMmJTsy4K4Mcb4SDShR9A44aX9+vln\ntndvuPQDB/zTg4J7mLx9aueB3IQdcQIuBC57/nmuWLAAGhthyBAQYUdeHv3GjOGxdeuS32+WExHG\njRvHAw88wKxZswBYtWoV+/fvb9ec4YlYEDfGGD9BE3o0NUFtrf82+/b5pxcW+i8rKvIPqv36+af3\n7Zt8EA7Ku3//4AAfa/9+//SaGt/k41SJNDZ6b1xLQKSxkYodO5LbXwqUlkYCr73mzo10Wh5XX301\n9913X0sQnzdvHjNmzGD27Nls27aNU045ha1bt7YE9UceeYQf/ehHlJWVJZV/MwvixphuLVHTuK8X\nX4SCAv9lAwb4B86eGfSvNi/EQ0n9+/sfT+/ewRcyXayiApYsifgs8UtLXx6TJ09m/vz5lJeXM378\neBYuXMjSpUuZPXs2Q4cOZciQITz99NOcf/75AMyfP59rrrkm6fybZdA3yxhjukBQ03hQ4P3Yx7xA\n6LNNaAUFRCZNikuu2rgxYbpf7/RS1zs94jqnBeZRXh6uSd1Pfn7Htu8mpk+fzn333cfUqVOZOHEi\nI0eObFk2Y8YMFixYwPnnn8+uXbt45pln+P3vfx96HxbEjTHdQmCNe+1a/w3y8/3vCSeqyYYMysXp\nftzLR6S0lEjM59DcOz0S0zs9rRcCnWzJkoSd5VNORJg+fTpTpkxh/fr1zJgxg+ae9CLCVVddxXHH\nHUdtbS0PPfQQU6dOZdiwYaH3Y0HcGNM9BNW4g9bv1Sv4nnDzOOFxyZ0flMNKRfl8LwTKyijO4MA+\nbRr4TGvuq6QkNQ0tY8aMYdy4cSxatIh777231bJRo0YxefJkHnnkERYsWMDMmTPbtQ8L4saYnJGw\nR3lQQA7q6BVQq077YClZwO/4I6WlrF64kCtietDvyMuj35AhnVSyzDNnzhyqqqooLCykIaZlZ8aM\nGdx2221s2LCBSy65pF35WxA3xuSOoB7lK1cG9qgOah4vnjCBSLJVN+MF9gy4uPEmTYsEpHdeHs3G\njRvX6n30I2aXXHIJM2fO5JJLLqEgqLNkGyyIG2Ny3/Dh3pjeL7wQvyxBjdtkn2QfAUtnHuvXr/dN\n79mzJ43Nj+ABhYWFHH744UyfPr3d+7IgbozJOr7N5g0NlL3xhv8GCToMWY3bdJVHHnkEEeHss89u\ndx4WxI0x2SfsY2EQ2BnNatymK5SUlFBeXs78+fM7lI8FcWNM9olqkmwlwYhm3b0zmsksi1PU+mNB\n3BiTkXybzA8e9DqoBT3bbfe3TTdjQdwYk5mCepqPGAEnngivvBK3zO5vm+7GgrgxpsskfK47aMau\nY45JY4mMyS4WxI0xXSfRc9179gRvZ53UjAEsiBtjMtERR8Dxx3szhvmwTmrGeCyIG2O6TtB0lkOH\ndm45jMlSFsSNMWnle9+7vh527oR33w3e0JrMTZYqLi5my5YtbN68mcMOO6wl/cQTT2TlypVUVFQw\nZsyYlOzLgrgxJr2C7nsfcQSceir8+9++m1mTuclWIsK4ceN44IEHmDVrFgCrVq1i//79rcZOT4WM\nDOIicj5wJ9AD+KOq3u6zzl3ABUAtUKqqryfaVkQGAwuBI4EK4HJVrXLpDwMnA3NV9etR+zgJmAsU\nAE+q6g1pOWBjuqPx473adn5+/DKrbZt2Kv1GKRVVFXHpxQOLmXvn3E7L4+qrr+a+++5rCeLz5s1j\nxowZzJ49m02bNjFx4sSWgN7Y2EhdXR1NTU1J5R0t44K4iPQAfgOcA2wCXhGRJ1R1bdQ6nwCOVtXx\nInIacDcwuY1tbwKeVdWfich33fubgDpgNnC8+4l2N3Ctqi4XkSdF5HxVfSqNh29MVgp8VGzIkIRN\n5lbbNqlWUVXBkrE+k4H7z0mStjwmT57M/PnzKS8vZ/z48SxcuJClS5cye/ZsRo4cSU3UrHpXX301\nqpp85lEyLogDpwLrVLUCQEQeBC4CoodouhCYB6Cqy0RkoIgMB8Ym2PZCYJrbfh6wGLhJVWuBpSIy\nProQIjIC6K+qy13SfcDFgAVxY2IFNZn36OHNIGZMNzR9+nTuu+8+pk6dysSJExk5cmTcOrfffjtv\nvfUWLwY8idGWTAziI4ENUe83Aqclsc5I4IgE2w5T1Ur3uhKIndYo9jJopNu+2SaXZoxJ1uTJ0LMn\nbNrU1SUx3dySiiXILUnej67AqxJ2gIgwffp0pkyZwvr165kxY0ZcbXvRokXcddddLF++nN69e7dr\nP5kYxJNtU0jmbIhffqqqItK+tgtjTLy6Ov/0nj2tl7nJCNOKp7H45sVJrVuyvoQl+DSnhzRmzBjG\njRvHokWLuPfee1ste+uttygtLeXRRx/1raEnKxOD+CZgdNT70bSuEfutM8qtk++T3lwFqBSR4aq6\n1TWVb0uiHKMC8molEom0vC4pKaGkpKSNrI3JPr73vRsbYe9eWL06eDu7723wZu1K1cxd2WTOnDlU\nVVVRWFhIQ0MDANXV1Vx22WX85Cc/4YwzzuhQ/pkYxF8FxotIMbAZ+BxwZcw6TwCzgAdFZDJQpaqV\nIrIzwbZPANcAt7vfj8Xk2apmr6pbRGSP6zi3HJgO3OVX4OggbkzOCrrvPWQInHwyLFvWBYUy2SK2\ngnPLLbekZT/FA4t9O6AVDyzu1DyajRs3rtV7EeG1117j7bff5sYbb+TGG29sSd+TaKjhANLeHnHp\nJCIXcOgxsTmq+lMRuQ5AVe9x6/wGOB/YB3xBVV8L2talDwYeAsYQ9YiZW1YB9Ad6AVXAuapaHvWI\nWSHeI2bX+5RVM/EzNCbVIiUl/kF82jSvaTxgIhOriRs/IoKqduih6e70/zfo88rIIJ5NutOXyHRv\nkSlTiPj0oI1Mm2bTf5rQLIiHE/R5ZWJzujGmi/je91b1fpYv99vEGNOFLIgbYw4Juu/dty9MnAhl\nZV1QKGNMEAvixpi2nXQSjB1LpKgofpk9KmZMl7Egbow55OBB/3QR66BmTAayIG5MN+N73/vAAaiq\ngnfe6YoiGWPayYK4Md1N0H3vUaPglFPg5Ze7oFDGmPawIG6M8Rx1lPdct98Yznbf22SoVM/PnW0s\niBuTgwKnBh06FN5+O3g7u+9tskhHnzPPBRbEjclFiaYGHTGiCwpkjEkHC+LGdCenngq9esHG2DmF\njDHZyIK4Md1Jr142NagxOaRdQVxECvCm5T6Q4vIYY1Jh69bARXbf25jckVQQF5E84GK8aT3PAPK8\nZGkEXgL+DDzWbUaiNyZTqcLNN/t3ajPG5Jxka+KLgReAnwNlzTVwEekNnAhcCNwITE1DGY0xyair\ng2uvhffeg4suIlJZGb+ONZkbk1OSmopURHq31XSezDq5qDtNhWcyR9wjZPX1sHo1DBpEZO1aKCzs\nqqIZk5RUTEVqkqyJJxOcu2MAN6bLBD1CNmmSBXBjupG8ri6AMSaFuvnoVcZ0NxbEjclG9fVdXQJj\nTAZIKoiLSD/3O19EeqS3SMaYQKqwcCG88kpXl8QYkwHavCcuIt8BhohIT+BW4KfAl9NdMGO6u7jO\nawcOeOOeNzbC8cfD6693VdGMMRkimY5ty9xPPfA5rAnemM4R1HltyhQYN47IgAHx29gjZMZ0K8kE\n8X1Aqar+HrhfRPLTXCZjTCJ5eTbqmjEGSCKIq+qrwKtR7+eltUTGGNi1C955p6tLYYzJcKHGTheR\nU4DvAcVR26qqnpDichmT83zn/FaFAweIvPce9LT5iYwxiYX9L/Fn4FvAaqAp9cUxphsJuuddVATP\nPw/XXw9btnRBwYwx2SJsEN+uqk+kpSTGGM9HPgInnGBThhpj2hQ2iN8iInOAfwIHXZqq6iOpLZYx\n3cD+/f7pbtQ167xmjGlL2CB+DXCs2y66Od2CuDExfO95gzdJSf/+8NprnV0kY0yOCRvETwYm2LRd\nxiQh6J53z57wwx/CaafB0qVdUDBjTK4IG8T/DUwE3kxDWYzpHk47DX7wA3j3XS+gx7J73saYJIUN\n4qcDZSKyHmieetQeMTPGT02Nf7oL3HbP2xjTUWGD+PnutwICjAFuSmmJjMkSgfe8i4qI9OoFb7zR\n2UUyxnQzoYK4qlaIyEeBK4HLgArg4TSUy5jMl+ie9623wtat8OKLXVAwY0x3kVQQF5Fj8QL354Dt\nwF+APFUtSV/RjMlSp50G3/42vPkmkR4+M/faPW9jTIokWxNfC/wd+LiqfgAgIt9MW6mMyXQNDbBj\nh/8yu+dtjOkkyQbxS/Bq4s+LyFN4NXFJW6mMyQC+97wPHIC6OiI7dkB1dVcUyxhjWiQVxFX1MeAx\nEekHXATcCAwVkbuBR1X1mTSW0ZiuEXTPe8QIWLQIbrgBfJYbY0xnCduxrQZvEpQ/i8hg4FK83ukW\nxE3WCexdXlzsNYXX1vpveMwx3vjmNra5MaaLJduxTWJHaVPVXcD/cz++6xiT0YJq2hs2wMknt/mI\nmN3zNsZ0tbwk11ssIt8WkWNiF4jIsSLyXcDaFU1u2LcPbrsNTj+9q0tijDEJJducfh5wFfBbETke\n2IvXsa0f3tzifwbOSUsJjWmnhM3lv/xl8FzdEybAOefA//xPOotnjDEdlmzHtgPAvcC9ItIDGOIW\n7VDVxnQVzpgOCWouX7UKHnkEevVKvL3d8zbGZLiww67ignZlGsrSQkTOB+4EegB/VNXbfda5C7gA\nqAVKVfX1RNu6jngLgSPxRpq7XFWr3LL/Br4INALXN/e2F5HFwHCgeeLnc1U14OFgkzWGDoXly+HC\nCxP2Lrd73saYTBc6iKebq+n/Bq95fhPwiog8oapro9b5BHC0qo4XkdOAu4HJbWx7E/Csqv7M3cO/\nCbhJRCbijUQ3ERgJ/FNExrtOegp8XlVt4udss3EjrF/vv2z4cBgwwGraxpisl3FBHDgVWKeqFQAi\n8iDes+lro9a5EJgHoKrLRGSgiAwHxibY9kJgmtt+HrAYL5BfBDygqvVAhYisA04DXnbr2qA2Gcj3\nfrcq9O5NpF8/WLwYCgsT52E1bWNMlgsVxEXkdlX9bltpHTQS2BD1fiNeUG1rnZHAEQm2HaaqzbcB\nKoFh7vURHArYzdscEfV+nojUAw+rqvV06kSJOqYF3u/u0wfuuAPmzYNPfxo2b053MY0xpsuErYmf\nB8QG7E/4pHVEss+aJ1NDFr/8VFVFJJn9XKWqm91IdQ+LyHRVnZ9k+UxHBQXqpibYu9d/m5NPhq98\nxXttzeXGmByX7GAvXwVmAkeJyKqoRf2BpSku0yZgdNT70Xi140TrjHLr5Pukb3KvK0VkuKpuFZER\nwLYEeW0CUNXN7neNiNyP19QfF8QjkUjL65KSEkpKSto6RtMRS5cGN5XLoWs7ay43JnMsXryYxYsX\nd3Uxck6yNfH7gUXAbXi17ub/lHtVdWeKy/QqMF5EioHNeJ3OroxZ5wlgFvCgiEwGqlS1UkR2Jtj2\nCeAa4Hb3+7Go9PtF5Bd4TfLjgeWuk9wgVd0hIvnApwkYXjY6iJtOcPrp3kxhNm65MVkjtoJzyy23\ndF1hckiyz4lXA9XAFektDqhqg4jMAp7Ge0xsjqquFZHr3PJ7VPVJEfmE64S2D/hCom1d1rcBD4nI\ntbhHzNw2a0TkIWAN0ADMdM3tBcBTLoD3AJ4F/pDu4zfOzp2wZo3/sp6Z2B/TGGM6n4QZ7twFts8C\nxRy6AFBV/VHqi5YdbMj49gvsuJaXR6S8nEheHpFNm+IWR6ZNa+ncFqd58hJjTEYTEVTVnv7poLBV\nmseBKmAFUJf64phc064e5gUF8MwzMGcOEQvUxhgTKGwQH6mqH09LSUzWalegTpThySfDlClEpkxJ\nSfmMMSZXhQ3i/xaRE1Q18RyNJqe0Oe92ewL1qlVQF9CY06NH6DIaY0x3FDaITwG+ICLrgQMuTVX1\nhNQWy2SU9gRp8AJ1ba3/suHDoaAAXrMRbY0xpr3CBvEL3G/FhiPNGW3WtIO88443Ktorr/gvHz4c\n+vSBV1+NXzZ0aDtKaowxJlrYIP4B3rziY1X1RyIyBm+Wr4pUF8x0oqCa9oYNcN118Prr/tsVFsKX\nvuTNy71iRfzytgK1jahmjDEdEjaI/w5oAs4GfgTUuLSTU1wu05mamvzT6+rgIx+Bl1+GN3y6QYwa\nBRddBL/8ZXDeCQK19TA3xpiOCRvET1PVE0XkdQBV3eUGQzEZLLC5fPBgIscc4wVpP+PHw8yZ8NBD\niXdggdoYY7pE2CB+0A1HCoCIDMWrmZtMFtRc3rMn3HADTJoUfF8b2mz2tkBtjDFdI2wQ/zXwKHC4\niNwKXArMTnmpTOc4/XT4+c+hjQlbLEgbY0xmChXEVXWBiKwA/sMlXayqAQNcm4yXl+f9tg5mxhiT\nlULPJOEmFFnb5oomc7QxtrvVtI0xJjuFCuIicgrwPeInQLHBXjLZ5s1dXQJjjDFpELYm/mfgW8Bq\nrENbdti5EzZsIHLSSdCvX+tl1lxujDFZLexUpEtV9cw0lifrZPxUpDNnemOR//rXXV0SY4xpYVOR\npkbYIH4e8Dngn8BBl6yq+kgaypYVMjqIl5XBxz8Oa9fC4MFdXRpjjGlhQTw1wjanXwMc67aLbk7v\ntkE8Y6nC9dfDj39sAdwYY3JU2CB+MjAhc6uepsWDD0JNDVx7bVeXxBhjTJqEnk8cmAi8mYaymFSp\nqYFvfxsWLmyZmzt66NWy8nIGNs/lXVBA8YQJXvrGjUwaNapVVmXl5QwEqqBlm421teypr6cQODxm\n13VAdUEB44qKWvKNzic6LWif7Um3IV6NMd1R2Hvi5cBRgM0n7mTkPfHvfY/Igw/CmDEtSRVlZcyt\nrga8ecAjPpuVFhW1rNMsEvPTnFaB95yhbz7A3Ji0MPtsT/rFw4YxKfYCIeSFg10IGNN57J54aoSt\niZ/vfjdHLTsBmWbdOiJ33EFF797MXb++JTmSzLb19ekqVbD9+/3TDxzwT29s9E0eWFcXNz58xP1Q\nWdkqvbSoiMi778blcXF5ORGfIWgTtVBYy4JJxG/yoVR8d9KZh333skvYYVcrRGQSMAUvkL+gqivT\nUjLTPjfeCCNHUhwVwJMWFDjTSQKuAwOCNfv2+af71M4DNTT4JvtdCIB/0I8Q7gIhTHoEr+Uk9oIi\nFRcI6bz4yPTg1BXHWFFeztyY70iEjn930plHJG5rk8nCjth2A/BlvN7oAiwQkT+o6l3pKJxpW6sr\n/Z07Yd06Knr1org9mfXrFy4YpkJBgf/FQ58+/mUZMMA/vX9/2Ls3uX0G1f6Djr22Nrl8AQ4e9E8P\nuHAISp9bXQ0xFxSpukCIQNouPjqad6bkkcq8kxbUEhb03fETdPEbJg+TVcI2p38Jb07xfQAichvw\nMmBBvKv4TDMaae601p00T+aSjP79gy8Q9uyJT+/RI/lbDUHrBV04BKX78SsbBF+8BLVahClHUHqY\n71hQYAlz+yZof2EusILWDTrGMJ9f0LkJc1Ec1BIW5jsSVOYweZisEnoCFFo/H25Dr2aQiPtdAb41\n8QhQUVREVUEBpT6906s2biQyaVKrbcrKyynF651eGtM7fT3xjyk0904v9emdXkp8M6TfPtuTTnl5\nx1sRgpr2e/dOPmj17RvcUhAmPSjvmpr49MJC/3/e+fnJ18CCjj0oPUxnzqDAEub2TdD+wlxgBa0b\ndIxhPr+gcxN0YegnqCUszHckUUtVZ7eymU4RNoj/CVgmIs3N6RcD96a8VKbdIrTuRR6toqiI4osv\nzslOK5HSUiI+HYhKSf7CISUXAunkHheM0zPgz7hXr+RrYEG3NYLSCwuDbx3ECgosYW7fBO0vzAVW\n0LpBxxjm8ws6N0EXCMakSNiObb8QkSXAx/A6tpWq6utpKZlJThL/BCuKiiieNIniHO51morj8rsQ\ngMQtFOloWagoK8vsiwmTtKqCgrR8d9KZh02MlF1CPSdu4nXpc+Kvvkrk9NOJuCa/CP49SyPTphFZ\nvLjzymU6xO+xJMicHuTpzDtT8khV3va4VjB7Tjw1bD7xbLVyJXzykzBlCpEmr2uC1eByg/3TN8Yk\ny+YTz0Zr1sD558NvfkPksssAV3srK+vachljjOlUYYP4dlV9Ii0lMclZtw7OOw9+9jO47LKWpteK\nsjKKq6v9O7PZPS5jjMlJNp94B3X0nniktJTVCxfS0z360tTYiALb8R7XKgSGAvVAj549qWpoYEhe\nHjt69WJU797U1dTwYGOj3Q83xmQVuyeeGjafeFerqOCvPo+9RPCZZKShwQvWTU1E6uq8n04oojHG\nmMxk84kbY4wxWSrEWJXAofnEjTHGGNPFwtbETwfKRMTmE89AkajXzQO82MANxhiTu8J2bCv2S1fV\nitQUJ/t0tGPbpOGTeavyMOopBMCbKkKAbXhd2wqAw4GD5KM0UkUPhtBEJf0Yyl52oRyO0EQ+TQgH\nGFbUm4FDaihb98+OHp4xxqSFdWxLDRuxrYM6GsSLh1/B+5UP+iyJ4NO1jUPjsvn9HFJUVMGkScUU\nF8Pcua2XGWNMV7MgnhrtmcXMpFDxhAm8X9n2esmJtLw6NB11JGBdY4wx2S5sxzZjjDHGZIhQQVxE\n7hORQVHvB4uITUVqjDHGdIGwNfETVHV38xtV3QV8NLVFMsYYY0wywt4TFxEZ7II3IjIY6JHqQonI\n+cCdLu8/qurtPuvcBVwA1BI1r3nQtq6sC4Ej8XqMXa6qVW7ZfwNfxOscfr2qPuPSTwLm4nURf1JV\nb0j1sRYXw7Jll1Jf752KxsYmaDXw6vvA5UA9PXv2oKGhCpEr6NVrBwUFpdTWbqSp6Qq3nTHGmO4k\n7CNmM4DvAw/hPQd1GfATVb0vZQUS6QG8BZwDbAJeAa5U1bVR63wCmKWqnxCR04BfqerkRNuKyM+A\nHar6MxH5LjBIVW8SkYnA/cApwEi8ceHHq6qKyHK3n+Ui8iRwl6o+FVPeTh3ArrYWTj8drrsOZs48\nlF5aGqGiAnbsgE2b4CMf8dKtd7oxJhNZ7/TUCP2ImYgcB5yNV118TlXfTGmBRE4HblbV8937mwBU\n9baodX7v9r3QvS8HSoCxQdu6daapaqWIDAcWq+oEVwtviqqxP4XXpft94F+q+iGXfgVQoqpfiSlv\nh4J46TdKWfivhdTjTYDS2NTofbL7gAYgH+gDNEF+z3yoAy2Ehqoe9D28Nwera2kqbCJP8kDz0Pqe\nNNQN4fBeA/nQiIsBC+TGmMxjQTw1Qj9i5oJ2SgN3jJHAhqj3G4HTklhnJHBEgm2HqWrzw1yVwDD3\n+gjgZZ+86t3rZptcekpVVFVQ99n4CVB4DqgCBgJneUn11HvpZwHP1bPvrLqW943PNboNDwD72La1\nim0Vi6GqGO9Zc2OMMbkmqSAuIktV9UwRqcGrJ0ZTVR2QwjIlW61N5gpO/PJzTeUpawOPRCItr0tK\nSigpKUlV1uGcFf2mGlgCf6qgrKyEkpKI1ciNMV1m8eLFLLZpkVMuqSCuqme63/3SWxzAq/GOjno/\nmtY1Yr91Rrl18n3SN7nXlSIyXFW3isgIvHFNE+W1yb32y6uV6CCeiaqri1mypIwXXyzgqadKgSrq\n6gYCUFAAEyYUA7BxYxmjRk2K296CvzGmo2IrOLfcckvXFSaHhGpOF5HbVfW7baV10KvAeDdO+2bg\nc8CVMes8AcwCHhSRyUCVu9e9M8G2T+DNh367+/1YVPr9IvILvOby8cByV1vf4zrOLQemA3el8DhT\n7zmftIIqKKqA6kk0NkaorIToYVqrq3FpUFRUyrvvRmIyiFBWVsHw4Re3BP7a2o3U1+8BCvHGdY9W\nR0FBNUVF41ouDgDKy8uAga3SIPjCIWy6XWgYY7qjsPfEzwNiA/YnfNLaTVUbRGQW8DTeY2JzXO/y\n69zye1T1SRH5hIisw+sC9oVE27qsbwMeEpFrcY+YuW3WiMhDwBq8rmQzo3qqzcR7xKwQ7xGzVj3T\nM9JZsQnV8KcKqC5uc9P6ev/06uq5VFdHODSEawT/cd09dXWl1NXNbbk4OLRNJCYt6MIhfHp5+cWU\nlERi0sJdONiFgDEm2yR7T/yreAHtKBFZFbWoP7A01YVS1UXAopi0e2Lez0p2W5e+C+/RM79tbgVu\n9UlfAXw46YK3Q/HAYpY9vCy4d3o13gN9rne61imNf21E9yn9n+zP3sp9sFCAxkOV4ueArXhPtwP0\neRHGvAB9boX6wdBQACz2llUVQ/VcAA40Ty7biYIuHBoa/NObAh6Hr6sbyJIlkZjUCGEuHPwuBMCC\nvjEmcyX1iJmIFAGD8GqzzbVuAfaq6s70FS/zdfZz4gCqyux/zeYva/7CoH9cwPKnfwVFpTD8Mbiy\n+lCzenSt/Lmo99HN7luLoM4LUFK3Ai04qfXOGl6Fgn5QVwP93DXf/r3Q0ORdAvaNKVwDUJMHfYZC\nw4T4fKLTAGpXQJ+YfaYqPWif+1dAoU8edSsg9vhJ8LkUNlLUd1ir5MadTZx01Bfj8ljx7r30OCx+\ngMQhPQey7tWy+LIYk2Wax6qIFXSxa4+YpUbYwV7ygKuAsar6IxEZAwxX1eXpKmCm64og3uzuV+7m\na9/8Olr5ETjYHwrKkg/icc3uwIP5cEVM1bjlkbaY7WMef2vlUeAzMWlh9pmq9KB9PpAPV/rkESY9\nKO8/FkCP2CcigfxlcHX8o4QypxcDBo9olbZn1xYoyGNAn9YXCDXbt9Nv6NC4PBr37uGkKSfEpW98\neyOjjhnVKq18dTkUwISjJ7S5btj0VOQdlMeKF96gR//4h2D8PpOgzy/M5xS0z7DnJkyFmmg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"text": [ "" ] } ], "prompt_number": 42 }, { "cell_type": "code", "collapsed": false, "input": [ "plt.figure(figsize=(6,10),dpi=160)\n", "plt.subplot(211)\n", "plt.plot(pyrrhotite_data_series6['Meas_T[K]'], pyrrhotite_data_series6['Mx[Am2]'], \n", " 'rs-', label='Mx')\n", "plt.plot(pyrrhotite_data_series6['Meas_T[K]'], pyrrhotite_data_series6['My[Am2]'], \n", " 'bs-', label='My')\n", "plt.plot(pyrrhotite_data_series6['Meas_T[K]'], pyrrhotite_data_series6['Mz[Am2]'], \n", " 'gs-', label='Mz')\n", "plt.ylabel('Magnetic moment (Am$^2$)')\n", "plt.xlabel('Temperature (K)')\n", "plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)\n", "plt.title('Series 6 experiment (uncorrected)')\n", "plt.subplot(212)\n", "plt.plot(pyrrhotite_data_series6['Meas_T[K]'], pyrrhotite_data_series6['Mx_bsub[Am2]'], \n", " 'rs-', label='Mx')\n", "plt.plot(pyrrhotite_data_series6['Meas_T[K]'], pyrrhotite_data_series6['My_bsub[Am2]'], \n", " 'bs-', label='My')\n", "plt.plot(pyrrhotite_data_series6['Meas_T[K]'], pyrrhotite_data_series6['Mz_bsub[Am2]'], \n", " 'gs-',label='Mz')\n", "plt.ylabel('Magnetic moment (Am$^2$)')\n", "plt.xlabel('Temperature (K)')\n", "plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)\n", "plt.title('Series 6 experiment (background corrected)')\n", "plt.show()" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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YsYJrrrkGgLVr19LV1TWse4YnY0HcGGNMwWhpgTVrYo4trrTMlXH55ZezfPnyg0F84J7i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"text": [ "" ] } ], "prompt_number": 43 }, { "cell_type": "code", "collapsed": false, "input": [ "plt.figure(figsize=(8,10),dpi=160)\n", "plt.subplot(211)\n", "plt.plot(pyrrhotite_data_series7['Meas_T[K]'], pyrrhotite_data_series7['Mx[Am2]'], \n", " 'rs-', label='Mx')\n", "plt.plot(pyrrhotite_data_series7['Meas_T[K]'], pyrrhotite_data_series7['My[Am2]'], \n", " 'bs-', label='My')\n", "plt.plot(pyrrhotite_data_series7['Meas_T[K]'], pyrrhotite_data_series7['Mz[Am2]'], \n", " 'gs-', label='Mz')\n", "plt.ylabel('Magnetic moment (Am$^2$)')\n", "plt.xlabel('Temperature (K)')\n", "plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)\n", "plt.title('Series 7 experiment (uncorrected)')\n", "plt.subplot(212)\n", "plt.plot(pyrrhotite_data_series7['Meas_T[K]'], pyrrhotite_data_series7['Mx_bsub[Am2]'], \n", " 'rs-', label='Mx')\n", "plt.plot(pyrrhotite_data_series7['Meas_T[K]'], pyrrhotite_data_series7['My_bsub[Am2]'], \n", " 'bs-', label='My')\n", "plt.plot(pyrrhotite_data_series7['Meas_T[K]'], pyrrhotite_data_series7['Mz_bsub[Am2]'], \n", " 'gs-', label='Mz')\n", "plt.ylabel('Magnetic moment (Am$^2$)')\n", "plt.xlabel('Temperature (K)')\n", "plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)\n", "plt.title('Series 7 experiment (background corrected)')\n", "plt.show()" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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89a/wyivw8ccNbJ2iKIoSCzGl0hCRC4FfANkhbY0x5uw426UoSiz4DVWWlsIt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\nIvWTAoZmDu3o5ihBtLs4M8Zc7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"text": [ "" ] } ], "prompt_number": 44 }, { "cell_type": "code", "collapsed": false, "input": [ "plt.figure(figsize=(6,6),dpi=160)\n", "plt.plot(pyrrhotite_data_series5['Meas_T[K]'], \n", " pyrrhotite_data_series5['Mtotal_bsub[Am2]'], \n", " 'gs-', label='M (series 5)')\n", "plt.plot(pyrrhotite_data_series6['Meas_T[K]'], \n", " pyrrhotite_data_series6['Mtotal_bsub[Am2]'], \n", " 'bs-', label='M (series 6)')\n", "plt.plot(pyrrhotite_data_series7['Meas_T[K]'], \n", " pyrrhotite_data_series7['Mtotal_bsub[Am2]'], \n", " 'ks-', label='M (series 7)')\n", "plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)\n", "plt.ticklabel_format(style='sci', scilimits=(0,0), axis='y')\n", "plt.ylabel('Magnetic moment (Am$^2$)')\n", "plt.xlabel('Temperature (K)')\n", "plt.savefig('code_output/pyrrhotite_totalM_allseries.pdf')\n", "plt.show()" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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kFnpbAxgg3moPHO/OQKfNnTxed2q3U72O5S0BiBsXnGf1ybOTycnOcWv3lnD4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\nKo8gvQ6gwxdKlZoGBiqfUswxWAy8kfa8D8jYIlB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QSh199NhlpfBWJQCPGGPO\nLHFRAhORTmCRMeaWw1x3Gt5QxxXzUjClVFnSHgOlZpRrlHw/8NuSvomB3R8D35iH8iilypj2GCil\nlFIqRXsMlFJKKZWigYFSSimlUjQwUEoppVSKBgZKKaWUStHAQCmllFIpGhgopZRSKuX/A71gme4F\nxF69AAAAAElFTkSuQmCC\n", "text": [ "" ] } ], "prompt_number": 45 }, { "cell_type": "code", "collapsed": false, "input": [ "pyrrhotite_data_series7['Meas_T[K]']" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 46, "text": [ "0 290.745\n", "1 291.961\n", "2 292.114\n", "3 292.170\n", "4 292.230\n", "5 292.252\n", "6 292.283\n", "7 291.859\n", "8 291.835\n", "9 290.075\n", "10 284.960\n", "11 279.741\n", "12 274.496\n", "13 269.182\n", "14 263.808\n", "...\n", "89 213.871\n", "90 218.972\n", "91 224.069\n", "92 229.171\n", "93 234.283\n", "94 239.450\n", "95 244.630\n", "96 249.785\n", "97 254.831\n", "98 259.870\n", "99 264.904\n", "100 269.936\n", "101 274.958\n", "102 288.559\n", "103 288.568\n", "Name: Meas_T[K], Length: 104, dtype: float64" ] } ], "prompt_number": 46 }, { "cell_type": "code", "collapsed": false, "input": [ "s5_temp_290 = pyrrhotite_data_series5['Meas_T[K]'][3]\n", "s5_moment_290 = pyrrhotite_data_series5['Mtotal_bsub[Am2]'][3]\n", "\n", "s5_temp_20 = pyrrhotite_data_series5['Meas_T[K]'][49]\n", "s5_moment_20 = pyrrhotite_data_series5['Mtotal_bsub[Am2]'][49]\n", "\n", "s5_temp_last = pyrrhotite_data_series5['Meas_T[K]'][114]\n", "s5_moment_last = pyrrhotite_data_series5['Mtotal_bsub[Am2]'][114]\n", "\n", "print 'For the series 5 experiment'\n", "print \"The percentage remanence remaining after cooling from \" + str(s5_temp_290) + \" to \" + str(s5_temp_20) + \" is \"\n", "print s5_moment_20/s5_moment_290*100\n", "\n", "print \"The percentage remanence remaining after thermal cycling back to \" + str(s5_temp_last) + \" is \"\n", "print s5_moment_last/s5_moment_290*100\n", "\n", "s6_temp_290 = pyrrhotite_data_series6['Meas_T[K]'][6]\n", "s6_moment_290 = pyrrhotite_data_series6['Mtotal_bsub[Am2]'][6]\n", "\n", "s6_temp_20 = pyrrhotite_data_series6['Meas_T[K]'][56]\n", "s6_moment_20 = pyrrhotite_data_series6['Mtotal_bsub[Am2]'][56]\n", "\n", "s6_temp_last = pyrrhotite_data_series6['Meas_T[K]'][114]\n", "s6_moment_last = pyrrhotite_data_series6['Mtotal_bsub[Am2]'][114]\n", "\n", "print \"\"\n", "print 'For the series 6 experiment'\n", "print \"The percentage remanence remaining after cooling from \" + str(s6_temp_290) + \" to \" + str(s6_temp_20) + \" is \"\n", "print s6_moment_20/s6_moment_290*100\n", "\n", "print \"The percentage remanence remaining after thermal cycling back to \" + str(s5_temp_last) + \" is \"\n", "print s6_moment_last/s6_moment_290*100\n", "\n", "s7_temp_290 = pyrrhotite_data_series7['Meas_T[K]'][9]\n", "s7_moment_290 = pyrrhotite_data_series7['Mtotal_bsub[Am2]'][9]\n", "\n", "s7_temp_20 = pyrrhotite_data_series7['Meas_T[K]'][51]\n", "s7_moment_20 = pyrrhotite_data_series7['Mtotal_bsub[Am2]'][51]\n", "\n", "s7_temp_last = pyrrhotite_data_series7['Meas_T[K]'][103]\n", "s7_moment_last = pyrrhotite_data_series7['Mtotal_bsub[Am2]'][103]\n", "\n", "print \"\"\n", "print 'For the series 6 experiment'\n", "print \"The percentage remanence remaining after cooling from \" + str(s7_temp_290) + \" to \" + str(s7_temp_20) + \" is \"\n", "print s7_moment_20/s7_moment_290*100\n", "\n", "print \"The percentage remanence remaining after thermal cycling back to \" + str(s5_temp_last) + \" is \"\n", "print s7_moment_last/s7_moment_290*100\n" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "For the series 5 experiment\n", "The percentage remanence remaining after cooling from 292.01 to 20.604 is \n", "9.75562057483\n", "The percentage remanence remaining after thermal cycling back to 274.388 is \n", "17.6555731402\n", "\n", "For the series 6 experiment\n", "The percentage remanence remaining after cooling from 291.577 to 18.551 is \n", "25.1795062718\n", "The percentage remanence remaining after thermal cycling back to 274.388 is \n", "17.0246798302\n", "\n", "For the series 6 experiment\n", "The percentage remanence remaining after cooling from 290.075 to 20.758 is \n", "18.349355273\n", "The percentage remanence remaining after thermal cycling back to 274.388 is \n", "21.6751911695\n" ] } ], "prompt_number": 47 }, { "cell_type": "markdown", "metadata": {}, "source": [ "In each of the experiments the Besnus transition is prominent. Let's make a plot that zooms in the transition to highlight this aspect of the datasets. The series 5 warming data has a lot of points across the transition." ] }, { "cell_type": "code", "collapsed": false, "input": [ "plt.figure(figsize=(3,3),dpi=160)\n", "plt.plot(pyrrhotite_data_series5['Meas_T[K]'][:52], \n", " pyrrhotite_data_series5['Mx_bsub[Am2]'][:52], \n", " 'rs-', label='Mx')\n", "plt.plot(pyrrhotite_data_series5['Meas_T[K]'][:52], \n", " pyrrhotite_data_series5['My_bsub[Am2]'][:52], \n", " 'bs-', label='My')\n", "plt.plot(pyrrhotite_data_series5['Meas_T[K]'][:52], \n", " pyrrhotite_data_series5['Mz_bsub[Am2]'][:52],\n", " 'gs-', label='Mz')\n", "plt.plot(pyrrhotite_data_series5['Meas_T[K]'][52:], \n", " pyrrhotite_data_series5['Mx_bsub[Am2]'][52:], \n", " 'ro-', label='Mx')\n", "plt.plot(pyrrhotite_data_series5['Meas_T[K]'][52:], \n", " pyrrhotite_data_series5['My_bsub[Am2]'][52:], \n", " 'bo-', label='My')\n", "plt.plot(pyrrhotite_data_series5['Meas_T[K]'][52:], \n", " pyrrhotite_data_series5['Mz_bsub[Am2]'][52:], \n", " 'go-', label='Mz')\n", "plt.vlines(32, -2e-5,4.5e-5, colors='c')\n", "plt.xlim(15,60)\n", "plt.ylim(-2e-5,4.5e-5)\n", "plt.ticklabel_format(style='sci', scilimits=(0,0), axis='y')\n", "plt.ylabel('Magnetic moment (Am$^2$)')\n", "plt.xlabel('Temperature (K)')\n", "plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)\n", "#plt.title('Series 5 experiment (background corrected)')\n", "plt.savefig('code_output/pyrrhotite_detail.pdf')\n", "plt.show()" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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zmxCIx+Orj9y06T2cPPl/Nnc8AjwHQFjYfmJi2gOQk3OAgoJ2NvUPAa0JCzsE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\n5rGoPcLH3hAITqfT38JyCP0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"text": [ "" ] } ], "prompt_number": 48 }, { "cell_type": "markdown", "metadata": {}, "source": [ "In the above plot, the cooling rate is significantly faster than the warming rate. As a result: (a) cooling measurements are widely spaced and (b) the sample is probably not in thermal equilibrium while cooling through the Besnus transition resulting in apparent hysteresis." ] }, { "cell_type": "heading", "level": 2, "metadata": {}, "source": [ "Equal area plots" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The directional data for these experiments is quite interesting. The pulse magnetizations were applied in different directions, but in each case the magnetization itself was acquired in the basal plane of the crystal." ] }, { "cell_type": "code", "collapsed": false, "input": [ "series5_cart=[]\n", "for n in range(len(pyrrhotite_data_series5)):\n", " series5_cart.append([pyrrhotite_data_series5['Mx[Am2]'][n],\n", " pyrrhotite_data_series5['My[Am2]'][n],\n", " pyrrhotite_data_series5['Mz[Am2]'][n]])\n", "series5_cart_bsub=[]\n", "for n in range(len(pyrrhotite_data_series5)):\n", " series5_cart_bsub.append([pyrrhotite_data_series5['Mx_bsub[Am2]'][n],\n", " pyrrhotite_data_series5['My_bsub[Am2]'][n],\n", " pyrrhotite_data_series5['Mz_bsub[Am2]'][n]])\n", "\n", "series5_DI=pmag.cart2dir(series5_cart)\n", "series5_DI_bsub=pmag.cart2dir(series5_cart_bsub)\n", "\n", "fignum=1\n", "fig=plt.figure(figsize=(8,5),dpi=160)\n", "plt.subplot(121)\n", "pmagplotlib.plotNET(fignum)\n", "IPmag.iplotDI(series5_DI,'b')\n", "plt.title('series 5 (raw)')\n", "\n", "plt.subplot(122)\n", "pmagplotlib.plotNET(fignum)\n", "IPmag.iplotDI(series5_DI_bsub,'b')\n", "plt.title('series 5 (bsub)')\n", "plt.show()\n", "\n", "series6_cart=[]\n", "for n in range(len(pyrrhotite_data_series6)):\n", " series6_cart.append([pyrrhotite_data_series6['Mx[Am2]'][n],\n", " pyrrhotite_data_series6['My[Am2]'][n],\n", " pyrrhotite_data_series6['Mz[Am2]'][n]])\n", "series6_cart_bsub=[]\n", "for n in range(len(pyrrhotite_data_series6)):\n", " series6_cart_bsub.append([pyrrhotite_data_series6['Mx_bsub[Am2]'][n],\n", " pyrrhotite_data_series6['My_bsub[Am2]'][n],\n", " pyrrhotite_data_series6['Mz_bsub[Am2]'][n]])\n", " \n", "series6_DI=pmag.cart2dir(series6_cart)\n", "series6_DI_bsub=pmag.cart2dir(series6_cart_bsub)\n", "\n", "fignum=2\n", "fig=plt.figure(figsize=(8,5),dpi=160)\n", "plt.subplot(121)\n", "pmagplotlib.plotNET(fignum)\n", "IPmag.iplotDI(series6_DI,'b')\n", "plt.title('series 6 (raw)')\n", "\n", "plt.subplot(122)\n", "pmagplotlib.plotNET(fignum)\n", "IPmag.iplotDI(series6_DI_bsub,'b')\n", "plt.title('series 6 (bsub)')\n", "plt.show()\n", "\n", "series7_cart=[]\n", "for n in range(len(pyrrhotite_data_series7)):\n", " series7_cart.append([pyrrhotite_data_series7['Mx[Am2]'][n],\n", " pyrrhotite_data_series7['My[Am2]'][n],\n", " pyrrhotite_data_series7['Mz[Am2]'][n]])\n", " \n", "series7_cart_bsub=[]\n", "for n in range(len(pyrrhotite_data_series7)):\n", " series7_cart_bsub.append([pyrrhotite_data_series7['Mx_bsub[Am2]'][n],\n", " pyrrhotite_data_series7['My_bsub[Am2]'][n],\n", " pyrrhotite_data_series7['Mz_bsub[Am2]'][n]])\n", " \n", "series7_DI=pmag.cart2dir(series7_cart)\n", "series7_DI_bsub=pmag.cart2dir(series7_cart_bsub)\n", "\n", "fignum=3\n", "fig=plt.figure(figsize=(8,5),dpi=160)\n", "plt.subplot(121)\n", "pmagplotlib.plotNET(fignum)\n", "IPmag.iplotDI(series7_DI,'b')\n", "plt.title('series 7 (raw)')\n", "\n", "plt.subplot(122)\n", "pmagplotlib.plotNET(fignum)\n", "IPmag.iplotDI(series7_DI_bsub,'b')\n", "plt.title('series 7 (bsub)')\n", "plt.show()\n" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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MsYdss8xRQ/Q6jZGro29PGrq6JPfqNFYkOFm+8j2DNH79cNloQrvY/BnYjvTh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\nBlZPo0sHUDPzAfuROgDWJK203MH282X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VJenrwCIR8blSMdR5imor4HQnN2ZtdRWpJs57SgdSB/nGawNgNUnvKh2PWacp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\nfLRvnCK1nzkAWJy07ftX3db5ux2c4HR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/3YHcF1gbuG6o/5d1/wC2BcYN5+++VeeuVp/nOvk8WsVjlP47GuD5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\n", "text": [ "" ] } ], "prompt_number": 49 }, { "cell_type": "markdown", "metadata": {}, "source": [ "For the figure in the manuscript, we presented the background-corrected data upon cooling for each experiment. The code below generates the equal area plots for that figure." ] }, { "cell_type": "code", "collapsed": false, "input": [ "plt.figure(figsize=(12,5),dpi=160)\n", "\n", "plt.subplot(131)\n", "pmagplotlib.plotNET(fignum)\n", "IPmag.iplotDI(series5_DI_bsub[1:45],'k')\n", "#just plotting the points during cooling \n", "plt.title('series 5')\n", "\n", "plt.subplot(132)\n", "pmagplotlib.plotNET(fignum)\n", "IPmag.iplotDI(series6_DI_bsub[4:56],'k')\n", "#just plotting the points during cooling \n", "plt.title('series 6')\n", "\n", "plt.subplot(133)\n", "pmagplotlib.plotNET(fignum)\n", "IPmag.iplotDI(series7_DI_bsub[1:50],'k')\n", "plt.title('series 7')\n", "\n", "plt.savefig('code_output/pyrrhotite_equal_area.pdf')\n", "plt.show()" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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ovy0pgMtzkTW5dK5m6Pg1WJK+AWwJdLlHpjV8DlbrSDqA1JBv0GY7YnYsSasD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\n0ozAfwGvkaMAXEZsE4iIVyVtANwq6f2I+FHtmFp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"text": [ "" ] } ], "prompt_number": 50 }, { "cell_type": "heading", "level": 1, "metadata": {}, "source": [ "Umkondo Large Igneous Province sill experiments " ] }, { "cell_type": "heading", "level": 2, "metadata": {}, "source": [ "Blank probe runs" ] }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "Cold Finger Blank run on July 14, 2013" ] }, { "cell_type": "code", "collapsed": false, "input": [ "blank1_data_cooling = pd.read_table('../Data/Umkondo/Blank/20130714_blank_cooling.txt')\n", "blank1_data_warming = pd.read_table('../Data/Umkondo/Blank/20130714_blank_warming.txt')\n", "blank1_data_cooling.head()" ], "language": "python", "metadata": {}, "outputs": [ { "html": [ "
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measurement_T[K]Mx[Am2]My[Am2]Mz[Am2]M_N[Am2]moment[Am2]
0 18.34-1.339330e-08 6.227380e-09-6.973380e-09-1.339330e-08 1.633370e-08
1 26.43-2.113220e-08 2.720220e-08-9.012280e-09-2.113220e-08 3.560550e-08
2 32.02-2.133780e-08 3.355980e-08-8.730760e-09-2.133780e-08 4.071600e-08
3 37.88-2.063060e-08 3.554850e-08-8.082560e-09-2.063060e-08 4.188850e-08
4 42.43-1.917700e-08 3.565210e-08-7.594180e-09-1.917700e-08 4.118860e-08
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" ], "metadata": {}, "output_type": "pyout", "prompt_number": 51, "text": [ " measurement_T[K] Mx[Am2] My[Am2] Mz[Am2] M_N[Am2] \\\n", "0 18.34 -1.339330e-08 6.227380e-09 -6.973380e-09 -1.339330e-08 \n", "1 26.43 -2.113220e-08 2.720220e-08 -9.012280e-09 -2.113220e-08 \n", "2 32.02 -2.133780e-08 3.355980e-08 -8.730760e-09 -2.133780e-08 \n", "3 37.88 -2.063060e-08 3.554850e-08 -8.082560e-09 -2.063060e-08 \n", "4 42.43 -1.917700e-08 3.565210e-08 -7.594180e-09 -1.917700e-08 \n", "\n", " moment[Am2] \n", "0 1.633370e-08 \n", "1 3.560550e-08 \n", "2 4.071600e-08 \n", "3 4.188850e-08 \n", "4 4.118860e-08 " ] } ], "prompt_number": 51 }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "Cold Finger Blank run on July 24, 2013" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Import the blank run data into dataframes." ] }, { "cell_type": "code", "collapsed": false, "input": [ "blank2_data_cooling = pd.read_table('../Data/Umkondo/Blank/20130724_blank_cooling.txt')\n", "blank2_data_warming = pd.read_table('../Data/Umkondo/Blank/20130724_blank_warming.txt')\n", "blank2_data_warming.tail()" ], "language": "python", "metadata": {}, "outputs": [ { "html": [ "
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measurement_T[K]Mx[Am2]My[Am2]Mz[Am2]moment[Am2]
240 284.97-2.893900e-09 4.405760e-09-2.202820e-09 5.712950e-09
241 285.97-2.974400e-09 4.076580e-09-2.199280e-09 5.504760e-09
242 286.94-3.071310e-09 4.289740e-09-2.199440e-09 5.715980e-09
243 287.60-2.690500e-09 4.263650e-09-2.193600e-09 5.498130e-09
244 287.61-3.253950e-09 4.218480e-09-2.131440e-09 5.738190e-09
\n", "
" ], "metadata": {}, "output_type": "pyout", "prompt_number": 52, "text": [ " measurement_T[K] Mx[Am2] My[Am2] Mz[Am2] moment[Am2]\n", "240 284.97 -2.893900e-09 4.405760e-09 -2.202820e-09 5.712950e-09\n", "241 285.97 -2.974400e-09 4.076580e-09 -2.199280e-09 5.504760e-09\n", "242 286.94 -3.071310e-09 4.289740e-09 -2.199440e-09 5.715980e-09\n", "243 287.60 -2.690500e-09 4.263650e-09 -2.193600e-09 5.498130e-09\n", "244 287.61 -3.253950e-09 4.218480e-09 -2.131440e-09 5.738190e-09" ] } ], "prompt_number": 52 }, { "cell_type": "code", "collapsed": false, "input": [ "plt.figure(figsize=(8,5),dpi=300)\n", "plt.plot(blank1_data_cooling['measurement_T[K]'], blank1_data_cooling['Mx[Am2]'], 'rs',\n", " label='Mx cooling (7/14)')\n", "plt.plot(blank1_data_warming['measurement_T[K]'], blank1_data_warming['Mx[Am2]'], 'ro',\n", " label='Mx warming (7/14)')\n", "plt.plot(blank1_data_cooling['measurement_T[K]'], blank1_data_cooling['My[Am2]'], 'bs',\n", " label='My cooling (7/14)')\n", "plt.plot(blank1_data_warming['measurement_T[K]'], blank1_data_warming['My[Am2]'], 'bo',\n", " label='My warming (7/14)')\n", "plt.plot(blank1_data_cooling['measurement_T[K]'], blank1_data_cooling['Mz[Am2]'], 'gs',\n", " label='Mz cooling (7/14)')\n", "plt.plot(blank1_data_warming['measurement_T[K]'], blank1_data_warming['Mz[Am2]'], 'go',\n", " label='Mz warming (7/14)')\n", "plt.plot(blank2_data_cooling['measurement_T[K]'], blank2_data_cooling['Mx[Am2]'], 'rd',\n", " label='Mx cooling (7/24)')\n", "plt.plot(blank2_data_warming['measurement_T[K]'], blank2_data_warming['Mx[Am2]'], 'r*',\n", " label='Mx warming (7/24)')\n", "plt.plot(blank2_data_cooling['measurement_T[K]'], blank2_data_cooling['My[Am2]'], 'bd',\n", " label='My cooling (7/24)')\n", "plt.plot(blank2_data_warming['measurement_T[K]'], blank2_data_warming['My[Am2]'], 'b*',\n", " label='My warming (7/24)')\n", "plt.plot(blank2_data_cooling['measurement_T[K]'], blank2_data_cooling['Mz[Am2]'], 'gd',\n", " label='Mz cooling (7/24)')\n", "plt.plot(blank2_data_warming['measurement_T[K]'], blank2_data_warming['Mz[Am2]'], 'g*',\n", " label='Mz warming (7/24)')\n", "\n", "plt.ylabel('Magnetic moment (Am$^2$)')\n", "plt.xlabel('Temperature (K)')\n", "plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)\n", "plt.title('cold finger blank run (07/24/2014)')\n", "plt.show()" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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vX+4QkK5btw5fX19bL3AB++2eCjz++OMOOxvMnDmTpUuXEh0dTf369Yu0s379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\nuxVzXtxvi1aekuSKLFcjTQ1n0hBjO7QQ5kJ+Z8PT05NFX3xx23ScPn1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JgQjxFAUF6pX9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wLfKYrypKIo/wa+A56vZZt2Aa0URYlVFEUPjAfW13IZfvjhhx9++OFHJTh69DhPPrmXwsIbASgs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\n8MwfnjmpeUBBUDdgwAAuvfRSNm7cyMCBAyO2gGZnZ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"text": [ "" ] } ], "prompt_number": 53 }, { "cell_type": "markdown", "metadata": {}, "source": [ "The origin of this signal from the sample holder apparatus is currently unknown and will be investigated further in the future. The signal seems to remain broadly similar through repeated thermal cycling (compare the July 14, 2013 data to the July 24, 2013 data) so we will take the approach of subtracting the holder signal from the sample data. To do this holder subtraction, it is necessary to interpolate the holder signal at the temperatures for which sample data are collected. Here is an example of the spline interpolation of these data that we will use for this purpose. This spline interpolation is the one that is used in the background_sub() function defined above." ] }, { "cell_type": "code", "collapsed": false, "input": [ "x = blank1_data_warming['measurement_T[K]']\n", "y = blank1_data_warming['My[Am2]']\n", "spline = interpolate.splrep(x,y,s=0)\n", "xnew = np.linspace(blank1_data_warming['measurement_T[K]'].min(), \n", " blank1_data_warming['measurement_T[K]'].max()-1, 300)\n", "ynew = interpolate.splev(xnew,spline,der=0)\n", "\n", "plt.figure(num=fignum,figsize=(8,5),dpi=300)\n", "plt.plot(x, y, 'bo',\n", " label='My warming')\n", "plt.plot(xnew,ynew, 'r-')\n", "\n", "#For the interpolate function to work the x values (temperature) need to be ascending. \n", "#The blank1_data_cooling can be sorted so that temperatures are ascending\n", "blank1_data_cooling = blank1_data_cooling.sort(['measurement_T[K]'])\n", "\n", "x = blank1_data_cooling['measurement_T[K]']\n", "y = blank1_data_cooling['My[Am2]']\n", "tck = interpolate.splrep(x,y,s=0)\n", "xnew = np.linspace(blank1_data_cooling['measurement_T[K]'].min(), \n", " blank1_data_cooling['measurement_T[K]'].max(), 300)\n", "ynew = interpolate.splev(xnew,tck,der=0)\n", "\n", "plt.plot(x, y, 'bs',\n", " label='My cooling')\n", "plt.plot(xnew,ynew, 'r-',label='spline fits for interpolation')\n", "plt.ylabel('Magnetic moment (Am$^2$)')\n", "plt.xlabel('Temperature (K)')\n", "plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)\n", "plt.title('cold finger blank run (07/24/2014) with spline fit')\n", "plt.show()" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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LH4iIiIiIJJUoRqiPBvqEddLVgFpmNs7dB8W0WUhwRn6+dOLMpWpmSrJFRKRCcfcyueKk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\njfkhc3tv7ymULu1GdHQMV6+monUd4DyQDvxstW9TZpv7EUdXnqcHSTR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"text": [ "" ] } ], "prompt_number": 54 }, { "cell_type": "heading", "level": 2, "metadata": {}, "source": [ "Experiments on PW10-7d" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "PW10 is a sill we refer to as the Rapitsane Sill from within the Umkondo Large Igneous Province in Botswana. Location: S 24.41968\u00ba, E 025.58463\u00ba. MPMS experiments and liquid nitrogen demagnetization revealed that this specimen lost a high percentage of its remanence upon cycling to and from low-temperature in low/near-zero field. The remenance removed during this low-temperature cycling is clearly an overprint on top of a primary" ] }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "NRM demagnetization" ] }, { "cell_type": "code", "collapsed": false, "input": [ "PW10_7a_demag = pd.read_csv('../Data/Umkondo/PW10/PW10-7a.csv')\n", "PW10_7a_demag" ], "language": "python", "metadata": {}, "outputs": [ { "html": [ "
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specimenstepintensitydec_geoinc_geodec_specinc_spec
0 PW10-7a 0.0 0.001106 287.293 58.389400 131.3 49.4
1 PW10-7a 0.0 0.000362 205.501 25.299800 331.1 65.1
2 PW10-7a 1.0 0.000366 204.858 24.588300 330.4 64.2
3 PW10-7a 1.5 0.000369 204.310 23.822200 330.0 63.3
4 PW10-7a 2.0 0.000372 203.611 22.952500 329.4 62.3
5 PW10-7a 2.5 0.000375 202.734 21.649100 328.9 60.8
6 PW10-7a 5.0 0.000385 197.607 13.624400 326.2 51.5
7 PW10-7a 7.5 0.000348 192.869 6.610280 323.9 43.2
8 PW10-7a 10.0 0.000276 186.925 0.377430 320.2 35.1
9 PW10-7a 15.0 0.000214 184.698 -2.601010 319.3 31.4
10 PW10-7a 20.0 0.000190 187.394 -1.962070 321.9 33.2
11 PW10-7a 25.0 0.000170 189.228 -1.561390 323.7 34.3
12 PW10-7a 30.0 0.000163 189.053 -1.088220 323.3 34.6
13 PW10-7a 40.0 0.000145 186.617 4.399750 317.7 38.6
14 PW10-7a 50.0 0.000141 184.853 0.728249 317.8 34.5
\n", "
" ], "metadata": {}, "output_type": "pyout", "prompt_number": 55, "text": [ " specimen step intensity dec_geo inc_geo dec_spec inc_spec\n", "0 PW10-7a 0.0 0.001106 287.293 58.389400 131.3 49.4\n", "1 PW10-7a 0.0 0.000362 205.501 25.299800 331.1 65.1\n", "2 PW10-7a 1.0 0.000366 204.858 24.588300 330.4 64.2\n", "3 PW10-7a 1.5 0.000369 204.310 23.822200 330.0 63.3\n", "4 PW10-7a 2.0 0.000372 203.611 22.952500 329.4 62.3\n", "5 PW10-7a 2.5 0.000375 202.734 21.649100 328.9 60.8\n", "6 PW10-7a 5.0 0.000385 197.607 13.624400 326.2 51.5\n", "7 PW10-7a 7.5 0.000348 192.869 6.610280 323.9 43.2\n", "8 PW10-7a 10.0 0.000276 186.925 0.377430 320.2 35.1\n", "9 PW10-7a 15.0 0.000214 184.698 -2.601010 319.3 31.4\n", "10 PW10-7a 20.0 0.000190 187.394 -1.962070 321.9 33.2\n", "11 PW10-7a 25.0 0.000170 189.228 -1.561390 323.7 34.3\n", "12 PW10-7a 30.0 0.000163 189.053 -1.088220 323.3 34.6\n", "13 PW10-7a 40.0 0.000145 186.617 4.399750 317.7 38.6\n", "14 PW10-7a 50.0 0.000141 184.853 0.728249 317.8 34.5" ] } ], "prompt_number": 55 }, { "cell_type": "code", "collapsed": false, "input": [ "PW10_7a_datablock_geo=[]\n", "PW10_7a_datablock_spec=[]\n", "PW10_7a_DI_geo=[]\n", "PW10_7a_DI_spec=[]\n", "for n in range(0,len(PW10_7a_demag)):\n", " PW10_7a_datablock_geo.append([PW10_7a_demag['step'][n],\n", " PW10_7a_demag['dec_geo'][n],\n", " PW10_7a_demag['inc_geo'][n],\n", " PW10_7a_demag['intensity'][n]])\n", " PW10_7a_datablock_spec.append([PW10_7a_demag['step'][n],\n", " PW10_7a_demag['dec_spec'][n],\n", " PW10_7a_demag['inc_spec'][n],\n", " PW10_7a_demag['intensity'][n]])\n", " PW10_7a_DI_geo.append([PW10_7a_demag['dec_geo'][n],\n", " PW10_7a_demag['inc_geo'][n]])\n", " PW10_7a_DI_spec.append([PW10_7a_demag['dec_spec'][n],\n", " PW10_7a_demag['inc_spec'][n]])" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 56 }, { "cell_type": "heading", "level": 4, "metadata": {}, "source": [ "Intensity plot" ] }, { "cell_type": "code", "collapsed": false, "input": [ "plt.figure(figsize=(5,5))\n", "plt.plot(PW10_7a_demag['step'],PW10_7a_demag['intensity'],marker='o')\n", "plt.xlabel('AF demag step (mT)')\n", "plt.ylabel('Magnetization (Am^2/kg)')\n", "plt.xlim((-1,50))\n", "plt.show()\n", "\n", "print 'The remanence lost (in %) following low-temp cycling is:'\n", "print ((PW10_7a_demag['intensity'][0]-PW10_7a_demag['intensity'][1])/PW10_7a_demag['intensity'][0])*100" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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"text": [ "" ] }, { "output_type": "stream", "stream": "stdout", "text": [ "The remanence lost (in %) following low-temp cycling is:\n", "67.2532472231\n" ] } ], "prompt_number": 57 }, { "cell_type": "markdown", "metadata": {}, "source": [ "The large loss of remanence is associated with the 77K nitrogen bath." ] }, { "cell_type": "heading", "level": 4, "metadata": {}, "source": [ "Plots in geographic coordinates" ] }, { "cell_type": "code", "collapsed": false, "input": [ "#plot with pmagplotlib.plotZ(fignum,datablock,angle,s,norm)\n", "pmagplotlib.plotZ(1,PW10_7a_datablock_geo,90,'series 2 cooling',0)\n", "plt.ticklabel_format(style='sci', scilimits=(0,0), axis='y')\n", "plt.ticklabel_format(style='sci', scilimits=(0,0), axis='x')\n", "plt.show()\n", "\n", "plt.figure(figsize=(5,5))\n", "pmagplotlib.plotNET(1)\n", "IPmag.iplotDI(PW10_7a_DI_geo)\n", "plt.title('Equal Area of demag')\n", "plt.show()" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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jH6Fjx4b3PfuSSzhy4EBYsoQ1gT2BjRcu5OC+fTlxyBBuHDmSKxYtom629snL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\nxXtkZq8A7SR1KmyYBZHpZ74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SX/vVkt5ft6LO4pFsG8pzYX8NTCFtSXcksGtE7F61sA7WC1erLUXS94EZwInApqSw3Tki\nbqtZV6dwyLYZScsDNwKnR8SZDZ8f417YyHme7MgN/N6TtC/pcvJbe3+MJXO7oI3kE12nA78DvtV4\nnwPWahn4vRcRPyS1D85RwzI6G5znybaXg4BtgH/yVK3R87Laoo4mrT78OPCVyrW0NbcL2oSkTUm7\nak2OiD/UrqfbuF3QfJJeCdxEulCnN5NZBLcL2kBecHA+8GkHrHWKvNT2SOC8fC7BBuGQbQ//CjwK\neE+CcqbVLqAbRcSFwK2kTb9tEG4XVCZpG9Ky2S0i4pHa9ZgNl6TxpJO1B/oS9C/lkWxFkpYDzgM+\n4oC1ThURTwIHA2dLWqV2Pe3GI9mKJH0B2Dgi3lO7FrPRkvRtYF5EHFm7lnbikK1E0iTgOmDziJhV\nux6z0cr7G8wApkTELbXraRduF1TQsOjgCw5Y6xYR8QTpYoxnSlq6dj3twiFbx37AeOCbtQsxa7Lz\ngKeBw2oX0i7cLmgxSesCfwT2i4if166nV3iDmNaRNJl0sc+tI+KO2vXU5pFs6x0J3E06EzvVk7hb\npq92Ad1O0jhJxwH/BdwBHFW5pLbgkG0hSWsDHwLeCbwemATsULUos+bZGtge2BbYFXhX3razp7ld\n0EJ5istTEXFc7Vp6wcANYoAT8t+9QUwLSPok8PqI2Kd2LTU5ZFtE0iakDWBenSdvWwt5g5jWy62w\nu4C9I+J/atdTi9sFrXMicIoD1npFRDxDegdxcu1aanLItoCk15L6VJ6yVc+02gX0qO8C60ravnYh\ntbhd0AL5qrPTI+KU2rWYtZqkQ4A9I2K32rXU4JAtTNKGpGt2bRgRf61dj1mrSRoHzCQtt/1t7Xpa\nze2C8o4DznDAWq+KiLmkS9R8snYtNXgkW5CktYDbSTttza5dj1ktklYkjWa3j4g7a9fTSh7JlnUI\n8EMHrPW6iPg76cofH65dS6t5JFtIvm7XfcAuEXF75XJ6nvcuqE/SesBvgfUi4una9bSKR7Ll7AHc\n44BtG321C+h1EfEAaQ/l/WrX0koO2XKOIO0Za2YLnA58OO+p3BPG1C6gG0nalLT5y09r19LLBu5d\n0PBz7b0L6rkaWBF4I3BD5VpawiFbxgeA8yJiXu1CelkO0mkAkvDeBfVFxHxJZwEH0iMh63ZBk+UT\nXh8F5uVrHplZJmllYD7wwfz3rueQbb43A48CrwJmSjqpcj2WTKtdQK+T9CngAVKr4G56ZC9lT+Fq\nMklnAvdFxEn5N/U6vgSHGUh6NfB4RDwh6VBgh4h4b+26SnPINpGkscAsYKuIuL92PWbtStJqpBVg\n63b7knO3C5prB+BOB6zZ4kXEHNKc2Sm1aynNIdtcU4Bf1C7CrENcBOxeu4jS3C5okjy5un87N/dg\nzZZA0jrAdGCNiHi+dj2leCTbPJvmP2dUrcKsQ0TEQyyYbdC1HLLNMwW4JPzWoC3l1V/Wfi6hy/uy\nDtnm2Z30DWPtqa92ATaoi+nyvqxDtgkkLQe8Hri2di1mHeYW4JV5SldX8t4FzfEG4I5e2iOzE3iD\nmPYXEc9LugHYDvh57XpKcMg2x/akOX/WRrxBTMe4FphMl4as2wXNMRm3CsxG6lrSQKUreZ7sKEka\nAzwBbJBXsVgb8uVn2pekZYHZwCvytcC6ikeyo7cpMMsB294csO0rIv4B/I508rjrOGRHb3PgttpF\nmHW46aSfpa7jkB29LXDImo3WbaSfpa7jnuwoSXqI9Fv4UuD3wPURMb9uVWadQdKbgNcBOwF9ETGh\ncklN55HsKORNYVYEfkN6qzO1akFmnedTwDbATcAK+URyV/FIdhQkrUlq2L/cexaYjY6kO4G9IqKr\nNlnySHZ0NgLudsC2P28Q0xHuATasXUSzOWRHZyJpD9meJmkXSVfm2y6161mEvtoF2BLNJP1MdZWu\n63+02Ab0eMjmUP0psFz+1HaS9oqIKyqWZZ1pJulnqqs4ZEdnInBN7SIqO5oFAUv++9FA9ZD1BjEd\n517grbWLaDaH7OhMBM6qXYQNzhvEdJyubBe4Jzs66wAP1i6isq8AzzZ8/Gz+nNlwPQisW7uIZnPI\njs4E4PHaRdSUe697AVflW7v2Y6fVLsCW6ClgeUljaxfSTJ4nO0L5aghPAct6CpdZc0j6M7BlRDxS\nu5Zm8Uh25CYAsx2wZk31OOlnq2s4ZEeu51sFZgXMBlavXUQzOWRHbgLgPWTNmmsOHslatjzgCyea\nNdfTpJ+truGQHblxwNzaRZh1mblAV80ucMiO3JBDdqibkwxnE5PhbnhS+ng/pr0fU/L4Jn9/zyP9\nbHUNh+zIjSV9QwxFX5OPG+6xrTjej2nvx5Q8fqjHDuW4uThkLXO7wKz5uq5d4L0LRm4McJikw/o/\nEREv7kAy1M1JhrOJyXA3PCl9vB/T3o8peXyzv78lDZxv/sWB9XWsiPBtBDfgMOBbQzx2ajOPG+6x\nrTjej2nvx5Q8vpnf38BJwPHD/Xq0883tgpHrut6RWRsYx9DPdXQEh+zIzWPovaNpTT5uuMe24ng/\npr0fU/L4oR47lOO67lyHN4gZIUnvBt4XEXvXrsWsW0j6DnBjRHyndi3N4pHsyLldYNZ8bhfYi/4K\nvKx2EWZd5mWkn62u4ZAdudl02UYWZm1gAulnq2s4ZEeu67ZkM2sDq9NlW4g6ZEfuCWC8pKVrF2LW\nRTyStSQiniP1jlapXYtZN5A0BlgJeLJ2Lc3kkB2dx4E1ahdhSzaSna6s5SYAT0bE/NqFNJNDdnTu\nB15Zuwgbkr7aBdgSrQ/cV7mGpnPIjs5MYGLtIsy6xETSz1RX8S5cozMT2KB2ETa4kex0ZVVtgEPW\nBrgXeGPtImxwOUinAUgiIqbWrMeWaCJwY+0ims3tgtFxu8CsebqyXeCQHZ27gVf1z5WVNL5yPbZo\n02oXYC8labwW9HEmAXfVrKcE78I1SpLmAH8ANiL90lorIp6vW5VZZ5D0J9J+BX8EtgJWiC4LJY9k\nR+8e4DpgG2ANB6zZsGwEbA5cCtzbbQELDtlmuBQgIh7sxm8Qs5IimQW8AFxZu54SHLKjdxvpN7GZ\njdzmpJ+lruOQHb3bgNc3NO/NbPi2BKbXLqIEh+zoPUB6q+OpXGYjIGkCsDZwe+1aSnDIjlLuw14L\nTK5diy2aN4hpa9sBN3TrSWOHbHNcB2xfuwhbrL7aBdgibU8aqHQlh2xzXItD1mykJpMGKl3Jexc0\nxwxgVUlr5eko1ga8QUz7k7QSsClwc+1aSnHINkFEzJd0DbAz8N3a9VjiDWI6wg7A/0TEP2oXUorb\nBc1zMbB77SLMOszuwEW1iyjJexc0iaQ1SOuv14iIebXrsYVJ6nOLoL3kueUPA2+JiLtr11OKR7JN\nEhGPknYQ2q52LfZSDti2tCXw924OWHDINtvFwJTaRZh1iCmkn5mu5pBtrouAPb3E1mxI9qTL+7Hg\nkG226cA84J9qF2LWziRNAl5BFy9C6OeQbaK8xPYCYH9J4yS9S9IHatdl1g4kvUfS+yQtD+wP/DAi\nXqhdV2kO2eb7CXAw6azpR4Cn65Zj1jaeBg4k/WwcBfysajUt4ilcBUiaCUyNiPNq12KJp3C1D0m7\nA2eRLtU0v3Y9pXkkW8apwK61i7CF9NUuwF70duD0XghYcMiWcgGwm6TVaxdi1k4krQjsB5xTu5ZW\n8d4FBUTEHEk/BQ4CTq5dT6/yBjFtaT/gVxHxYO1CWsU92UIkbQP8GNioF86gtjtJU71BTF15/vht\nwDERcVXtelrF7YJCIuJm4HHcmzXrty2wHPDL2oW0kkO2rNOBI2sXYUDe8tCqOgI4o1dOePVzu6Ag\nScsCM4G3R0RXXonTbCgkbQDcAmwYEU/VrqeVPJItKG9E/FXg+Nq1mFV2LPCtXgtY8Ei2uHx5jZnA\nm7p9SzezwUhaE7gDmBQRj9Wup9U8ki0sIv5G6s0eV7sWs0o+DnyvFwMWPJJtCUmrAXcDm/fS/ECz\nhu/9LSLigdr11OCRbAtExBzgW8DUyqX0rLwwwVrvU8CPezVgwSu+Wulk4C5Jm0XE7bWL6UF9eBpX\nS0lan7Tr1mZVC6nMI9kWyWdVvwSc1P85SS/L07zMOp6kMZJWbfjU54FvRMQjtWpqBx7JttbpwEfz\nW9eJwInAocAvahbVrbx3Qcu9CfiJpM8BNwA7ARvXLak+h2wLRcRcSacAl5AuVfPOvPzWCshBOg1A\nEt67oKyIuFbSjqS54V8CTsmza3qa2wWt923gAeAcB6x1m4j4PXAmMAf4cuVy2oKncFUgaXPgSmCz\niHi8dj29wFdGaI28+GYGsF9EXFe7nnbgkK1E0v8HVomIg2rXYtYs+ft6fER8sHYt7cIhW0nDb/z3\nRcT1tesxGy2/Qxuce7KV5BMCHwO+5Wlc1ukkjSEtuPlXB+zCHLJ1/SdpNPv52oWYjdJxwN9IV6G1\nBm4XVCZpAvA7YN+IuLZ2PWbDJWlL4ApgK+/N8VIeyVYWEbNJCxLOzX1aK8B7F5SRW13nAR93wA7O\nIdsGIuIi4L9Jk7itjL7aBXSpzwF3AhfULqRdOWTbx8eBPkn71i7EbCgk7Uq6xPfh4b7jInlZbZuI\niL9K2ge4UtL0iPhD7Zo6nfcuKEfSesC5wD6eTbB4PvHVZiR9iDS16w0R8XTterqFpKneu6A5JI0D\nrgUujAgvnV0Ctwvaz1nAzaT5s4IXt5B7Td2yrFdJmpSDtd+XgVnAVyqV1FEcsm0m97Y+DLwOOFLS\nysDFwGerFtb5ptUuoIN9DLha0uqS3g+8Hfig+7BD43ZBm8rXqb8RmAtcBBwVEc/Xrcp6kaSlgC8A\nHwCWBSZHxB11q+ocHsm2qYi4lzQ9ZjzwbQes1RIR84FzgBWAUx2ww+OQbWMR8U3gQ8BF+dr1HUHS\nLpKuzLddatdjo5MvKXMJcFxEeAn4MLld0AEkfRrYC3hru+80n0P1p8By+VPPAntFxBX1qrKRyiu6\nLgdujohja9fTiRyyHSDPMjiTdL2k3SLi2colLZKkK4GdB3z6fyNiqxr12MhJWoa0idEzwP4R8ULl\nkjqS2wUdoGHGwSzSherGVi5puLao3Tbw3gXDI2lp4HxAwPsdsCPnkO0Q+Zv8QOA54Ht5/8529BVg\n/oDPLQV8o0Itjfoqv37HyLMJvgWsTlrR9VzlkjqaQ7aD5G/2fUkzDr6TRxttJfdeB1uptlHt0awt\nWW5NfRXYFNgjIv5RuaSO555sB5K0Amnu7J+BD7TbSEPSrcDrB7nrqoh4Wwvr6KNh7wLghPx3710w\niDyCPR3YEtg1Ip6sXFJXcMh2KEnLARcCz5M2/G6bEUcesV7KS98pVTsB5r0LFi+3n84F1gHe0e6z\nWDqJ2wUdKs8weBcwjzSPdoXKJb0otwxm1q7DhibvS3AhsCpp9ooDtokcsh0sIuYB7wMeJG2RuFr/\nfZLWl/TmasXBvYN8bk7Lq1hgWsXXbhuStpS0ScPHLyO1nl4A9oyIZ6oV16Ucsh0uzzr4EHA9cKOk\njRt+cGrOTf0KaSFCv2epuGuTe7Av2gy4WNKEvCfs9aR3HfvmX9rWZO7JdhFJ/0y68u29wHQq71if\ne7NH5w+/4lVf7UHSl4BdgDVI2xae6h21ynHIdpkctN8ADouIc2rXY+1H0t6ka3J9NiJOrl1Pt3PI\ndiFJm5L2oP0Z8Il2m+JldeR51Z8BDibNgb21ckk9wT3ZLhQRM4CtgVcD10hau3JJ1fX6slpJqwOX\nAZOBrR2wreOQ7VIR8QTwDtJ81Zsl7Vi5pNr6ahdQi6RtgVvzbeeI+HPlknqKQ7aLRcT8iPgi8P+A\n8yV9pvaeB95rtnUkLSXpaFLb6IiI+KQ3f28992R7hKS1SCt6VgYOiIg7K9TQ0r1me3lZraT1Sf/f\nY0i7aA02b9lawCHbQ/LmH4eTwuYE4PR8aZFWvf5ge822ZD+DXllWm/+PDwROAf6dNHXO2xRW5HZB\nD4nkdODNwP6kVWLrDzxO0rj+y5Fbexpwie7+z61Fag38C7BjRJzigK3PIduDIuIuYHvgauAWSZ8c\nsBH4acCRBV665iqwaS16neLyZbm/2/DxGElHAb8Dfg+8ISJ+V6s+W5jbBT0uX3r868BE0tUXngSu\nBCaV2OpdMenCAAAFgklEQVTOq8BGT9LywB9IJzSfA84g/b8dERF/qFmbvZRD1vr7eHuSRrBjgdMi\n4kt1q7LFkXQocCJpF7Zjge97aWx7csjaiyStQrpw3hbAt4GTI+KpulVZI0krkt4JfBS4nbSxyyN1\nq7LFcU/WXhQRT0XEjsDmwMuBuyR9bLCTLNZakpaRdDhwN2kl3zYR8RYHbPtzyNpLRMRDEXEwsEO+\n3SnpcEnLlnrN0osUOnVZraSxkj4I3AG8G5gSEftFhDdF7xAOWVukiLg9It4B7AfsDsyUdIyklZr5\nOg2LFHbOt58WCNq+Jj9fUZKWk/QR4B7SdLvDgZ2850DnccjaEkXEbyJiCrAbaeOZmZJOkPSKwY5X\nsmu+MN9QHM2CVWDkvx+9iGM7nqS3SVpmEfdNkPRJ0p7AO5Iuyb1TRPzSJ7Y6U9V17NZZIuI2YF9J\nG5NC8A+SLidd4fT6hhDYlgWXla5m4LLahvUVtZfVngAsA1wCL87ueANpCt07gV+QRq23V6vQmsaz\nC2zEJK0MHEAKhxdIYfsD0tSihyPixCE+z5D3NBjpPNt2WlYr6cOkLQcPAfYhff1WIc13PScial4L\nzZrMIWujlkdifaS+4S7AssBRwHfzVXWH8hxLDM/RbDDTLiGbV9a9BzibVP80Urhe2cp9JKx1HLLW\nVLlP+2+kaUZbkdbSXwhcM9TAbXguAa8hhfbtpItD7jTgsGnAMcC9eQ/dRT1XX60WQZ4CN5k0O2Bv\nYAbp33NyRNxfoyZrHYesFZM3LNmXtJpsC1IgXgxcEhEPL+GxywA3AxuTWhEvAMuTepmNniOF1rrA\nwRHxsyb+EwbWtB2wUUScO4Rj1yCdKJxC+sUwA/g58AMHa29xyFpLSFoV2JUUOrsADwG/Aq4FrouI\nRwccfzzwBVIonw/8iPT2enkWnhUzA3iYFGCfAzYstUpN0m7AxyJi4HaNSJoAbEcasU4GNiLtAXEx\ncFlEPF6iJmt/DllruXx1hm1IYbQ9aevFx0mBezPpcuafz/dvDYwj9WLXWczTPgs8RrpA4PRBXjMi\nYlTbN0paN9e3AbAZaWXcNvnfsDZwA3Bdvt0YEfNG83rWHRyyVl2+iupmpLB6PSm8NgeWJu2lcA9w\nHLCkkHwOWGOw3cOGG7K5H7waaXeyDYANc43vJW3KchdwG/BbUqhO96VdbDAOWWtLkl4O3EdqDTwH\nrMCSQ/Yh0gyFfwBzSWE4N99uIY2Yx5JGxmNJJ9RWBSYMuK1JCtfnSYsCZuY/7wD+BlwREU835R9q\nXc8ha20rX8b6y6S34veTlvf2758wjxS6/SfCngeuILUNxg24jSWNkG9kQej2B/ATpFbF7Ibbo6TZ\nCk3fT9d6j0PWOsbAubT5T28Abm3NIWtmVpA3iDEzK8gha2ZWkEPWzKwgh6yZWUEOWTOzghyyZmYF\nOWTNzApyyJqZFeSQNTMryCFrZlaQQ9bMrCCHrJlZQQ5ZM7OCHLJmZgU5ZM3MCnLImpkV5JA1MyvI\nIWtmVpBD1sysIIesmVlBDlkzs4IcsmZmBTlkzcwKcsiamRXkkDUzK8gha2ZWkEPWzKwgh6yZWUEO\nWTOzghyyZmYFOWTNzApyyJqZFeSQNTMryCFrZlaQQ9bMrCCHrJlZQQ5ZM7OCHLJmZgU5ZM3MCnLI\nmpkV5JA1MyvIIWtmVpBD1sysIIesmVlBDlkzs4IcsmZmBTlkzcwKcsiamRXkkDUzK8gha2ZWkEPW\nzKwgh6yZWUEOWTOzghyyZmYFOWTNzApyyJqZFeSQNTMryCFrZlaQQ9bMrCCHrJlZQQ5ZM7OCHLJm\nZgU5ZM3MCnLImpkV5JA1MyvIIWtmVpBD1sysIIesmVlBDlkzs4IcsmZmBTlkzcwKcsiamRX0f75v\n5KUlAHvKAAAAAElFTkSuQmCC\n", "text": [ "" ] } ], "prompt_number": 58 }, { "cell_type": "markdown", "metadata": {}, "source": [ "In the plots above, the large directional change and reduction in magnetization accompanies a low-temperature demagnetization step (i.e. 77 K nitrogen bath in a very low-field environment). Along with the following AF steps an overprint is removed that brings the data to the shallow southerly pointing vector which is consistent with other data from the ~1100 Ma Umkondo large igneous province." ] }, { "cell_type": "code", "collapsed": false, "input": [ "print \"The angular change (in degrees) associated with the LTD step is:\"\n", "print pmag.angle(PW10_7a_DI_geo[0],PW10_7a_DI_geo[1])" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "The angular change (in degrees) associated with the LTD step is:\n", "[ 64.43078671]\n" ] } ], "prompt_number": 59 }, { "cell_type": "heading", "level": 4, "metadata": {}, "source": [ "Specimen coordinates" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "These data plotted in specimen coordinates are more directly comparable to the data acquired on another specimen from the same sample using the IRM-LTI." ] }, { "cell_type": "code", "collapsed": false, "input": [ "#plot with pmagplotlib.plotZ(fignum,datablock,angle,s,norm)\n", "pmagplotlib.plotZ(1,PW10_7a_datablock_spec,90,'series 2 cooling',0)\n", "plt.ticklabel_format(style='sci', scilimits=(0,0), axis='y')\n", "plt.ticklabel_format(style='sci', scilimits=(0,0), axis='x')\n", "plt.savefig('code_output/Umk_Pw10-7a_specimen_zplot.pdf')\n", "plt.show()\n", "\n", "plt.figure(figsize=(5,5))\n", "pmagplotlib.plotNET(1)\n", "IPmag.iplotDI(PW10_7a_DI_spec)\n", "plt.title('Equal Area of demag')\n", "plt.savefig('code_output/Umk_Pw10-7a_specimen_eqaplot.pdf')\n", "plt.show()" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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D0s/tgetXr+b/gA8IHfIWEpLF/sDCjz9OewznXPy8jsIVxNBhwxgyaxasWMHDwM2EuwiA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\nZeSJwjnnXEaeKJxzzmXkicI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" ], "metadata": {}, "output_type": "pyout", "prompt_number": 61, "text": [ " T [K] Bapp [T] M [Am2/kg] reg fit timestamp Unnamed: 5 \\\n", "0 299.9879 2.5 2.885055 0.990173 2/5/2013 4:13:32 PM NaN \n", "1 294.2503 2.5 2.899802 0.989840 2/5/2013 4:16:42 PM NaN \n", "2 288.9702 2.5 2.914910 0.989691 2/5/2013 4:17:28 PM NaN \n", "3 283.9853 2.5 2.931989 0.989543 2/5/2013 4:18:06 PM NaN \n", "4 278.9876 2.5 2.951009 0.989169 2/5/2013 4:18:40 PM NaN \n", "\n", " T [K].1 Bapp [T].1 M [Am2/kg].1 reg fit.1 timestamp.1 \\\n", "0 19.99881 0 0.457038 0.990071 2/5/2013 5:27:50 PM \n", "1 25.59370 0 0.434746 0.989292 2/5/2013 5:29:09 PM \n", "2 30.62943 0 0.415489 0.989056 2/5/2013 5:30:10 PM \n", "3 35.51034 0 0.401149 0.988457 2/5/2013 5:31:10 PM \n", "4 40.58522 0 0.389925 0.988874 2/5/2013 5:32:11 PM \n", "\n", " Unnamed: 11 T [K].2 Bapp [T].2 M [Am2/kg].2 reg fit.2 \\\n", "0 NaN 19.99765 0 0.483920 0.988106 \n", "1 NaN 25.55709 0 0.465696 0.987919 \n", "2 NaN 30.55221 0 0.451775 0.988061 \n", "3 NaN 35.59132 0 0.442285 0.987936 \n", "4 NaN 40.54948 0 0.434388 0.988107 \n", "\n", " timestamp.2 Unnamed: 17 T [K].3 Bapp [T].3 M [Am2/kg].3 \\\n", "0 2/5/2013 7:43:34 PM NaN 300.0001 0 0.292515 \n", "1 2/5/2013 7:44:54 PM NaN 294.4174 0 0.292170 \n", "2 2/5/2013 7:45:55 PM NaN 289.0140 0 0.291212 \n", "3 2/5/2013 7:46:57 PM NaN 283.8555 0 0.290107 \n", "4 2/5/2013 7:47:56 PM NaN 279.0740 0 0.288958 \n", "\n", " reg fit.3 timestamp.3 Unnamed: 23 T [K].4 Bapp [T].4 \\\n", "0 0.989795 2/5/2013 8:53:56 PM NaN 19.99720 0 \n", "1 0.989635 2/5/2013 8:56:51 PM NaN 25.65808 0 \n", "2 0.989510 2/5/2013 8:57:42 PM NaN 30.53962 0 \n", "3 0.989398 2/5/2013 8:58:22 PM NaN 35.66172 0 \n", "4 0.989000 2/5/2013 8:58:58 PM NaN 40.49764 0 \n", "\n", " M [Am2/kg].4 reg fit.4 timestamp.4 \n", "0 0.044147 0.987200 2/5/2013 10:03:51 PM \n", "1 0.044205 0.987814 2/5/2013 10:05:12 PM \n", "2 0.044195 0.987583 2/5/2013 10:06:11 PM \n", "3 0.044043 0.987072 2/5/2013 10:07:14 PM \n", "4 0.043838 0.987979 2/5/2013 10:08:12 PM " ] } ], "prompt_number": 61 }, { "cell_type": "code", "collapsed": false, "input": [ "fig=plt.figure(figsize=(12,6),dpi=160)\n", "ax1 = fig.add_subplot(1, 2, 1)\n", "ax2 = fig.add_subplot(1, 2, 2)\n", "ax1.scatter(PW10_MPMS['T [K].1'],PW10_MPMS['M [Am2/kg].1'], c='b', label='FC')\n", "ax1.scatter(PW10_MPMS['T [K].2'],PW10_MPMS['M [Am2/kg].2'], c='r', label='ZFC')\n", "ax2.scatter(PW10_MPMS['T [K].3'],PW10_MPMS['M [Am2/kg].3'], c='b', label='cooling')\n", "ax2.scatter(PW10_MPMS['T [K].4'],PW10_MPMS['M [Am2/kg].4'], c='r', label='warming')\n", "ax1.set_xlabel('temperature (K)')\n", "ax1.set_ylabel('magnetization (Am$^2$/kg)')\n", "ax1.legend()\n", "ax1.set_title('FC/ZFC experiments on MPMS on specimen PW10-7c')\n", "ax2.set_xlabel('temperature (K)')\n", "ax2.set_ylabel('magnetization (Am$^2$/kg)')\n", "ax2.legend()\n", "ax2.set_title('RTSIRM experiment on MPMS on specimen PW10-7c')\n", "plt.savefig('code_output/PW10-7c_MPMS.svg')\n", "plt.show()" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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cw9KlS1m8eDGzZs3i4Ycfzs/7H7h7wf6F4otIvkp1jL722mveseMODgsdqryo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\ncznnJlGSfp8Ua+MkKd4kxQrJi7cWrWjhXgbsdvdH3P0l4Cbg9MgxK4F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"text": [ "" ] } ], "prompt_number": 62 }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "IRM-LTI experiments" ] }, { "cell_type": "heading", "level": 4, "metadata": {}, "source": [ "Experiment on 07/21/2013 on specimen PW10-7d (measurement series 1 and 2):\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This experiment was designed to be low-temperature cycling of the specimens natural remanent magnetization (NRM).\n", "
    \n", "
  1. Load the sample with arrow (down core z-axis) pointing out of SRM (old 2G at IRM) and make measurement (measurement series #1, measurement #1,2,3,4). The direction should be approx. the same as the measurement of the sister \"a-series\" specimen.
  2. \n", "
  3. Twist the sample screw tight as is needed for running in low-temperature insert which results in sample being rotated about the z-axis (measurement series #1, measurement #5).
  4. \n", "
  5. Cover the sample holder with the sapphire radiation shield and vacuum shroud ((measurement series #1, measurement #5) and then begin cooling. Measurements are made upon cooling (measurement series #2).
  6. \n", "
  7. Once at minimum temperature (slightly below 20K) warm the probe back up progressively making measurements as it warms (measurement series #2).\n", "
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Import data file which has the format: \n", "\n", " \n", " \n", " \n", "
TEMPERATURE (K)M_x [Am2]M_y [Am2]M_z [Am2]M_total [Am2]MEASUREMENT SERIES
" ] }, { "cell_type": "code", "collapsed": false, "input": [ "data_file='../Data/Umkondo/PW10/PW10-7d_rotation.txt' \n", "data = np.genfromtxt(data_file, skip_header=1)\n", "\n", "temp=data[:,0]\n", "Mx=data[:,1]\n", "My=data[:,2]\n", "Mz=data[:,3]\n", "Mtotal=data[:,4]" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 63 }, { "cell_type": "code", "collapsed": false, "input": [ "full_vector_oriented=[]\n", "full_vector_rotated=[]\n", "\n", "#data point 3 is oriented (remember python starts at 0)\n", "for n in range(3,4):\n", " Mx_full,My_full,Mz_full=Mx[n],My[n],Mz[n]\n", " full_vector_oriented.append([Mx_full,My_full,Mz_full])\n", "\n", "#data point 4 is rotated about z (remember python starts at 0)\n", "for n in range(4,5):\n", " Mx_full,My_full,Mz_full=Mx[n],My[n],Mz[n]\n", " full_vector_rotated.append([Mx_full,My_full,Mz_full])\n", " \n", "oriented_directions=pmag.cart2dir(full_vector_oriented)\n", "rotated_directions=pmag.cart2dir(full_vector_rotated)\n", "\n", "#rotate rotated directions about the z-axis to correspond to the oriented measurement\n", "angle = 360 + oriented_directions.item(0) - rotated_directions.item(0)\n", "\n", "x_prime = Mx[4]*np.cos(np.radians(angle)) - My[4]*np.sin(np.radians(angle))\n", "y_prime = Mx[4]*np.sin(np.radians(angle)) + My[4]*np.cos(np.radians(angle))\n", "z_prime = Mz[4]\n", "\n", "full_vector_rotated_prime= [[x_prime,y_prime,z_prime]]\n", "rotated_directions_prime=pmag.cart2dir(full_vector_rotated_prime)\n", "\n", "#plot the oriented measurement and the rotated measurement\n", "fignum = 1\n", "plt.figure(num=fignum,figsize=(4,4))\n", "pmagplotlib.plotNET(fignum)\n", "IPmag.iplotDI(oriented_directions,'k')\n", "IPmag.iplotDI(rotated_directions,'b')\n", "plt.title('PW10-7d NRM oriented (black) and rotated (blue)');\n", "\n", "#plot the oriented measurement and the corrected rotated measurement\n", "fignum = 2\n", "plt.figure(num=fignum,figsize=(4,4))\n", "pmagplotlib.plotNET(fignum)\n", "IPmag.iplotDI(oriented_directions,'k')\n", "IPmag.iplotDI(rotated_directions_prime,'b')\n", "plt.title('PW10-7d NRM oriented (black) and rotated (corrected; blue)');" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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"text": [ "" ] } ], "prompt_number": 64 }, { "cell_type": "code", "collapsed": false, "input": [ "data_file_cooling='../Data/Umkondo/PW10/PW10-7d_cooling.txt' \n", "data_cooling = np.genfromtxt(data_file_cooling, skip_header=1)\n", "\n", "temp_cooling=data_cooling[:,0]\n", "Mx_cooling=data_cooling[:,1]\n", "My_cooling=data_cooling[:,2]\n", "Mz_cooling=data_cooling[:,3]\n", "Mtotal_cooling=data_cooling[:,4]\n", "\n", "data_file_warming='../Data/Umkondo/PW10/PW10-7d_warming.txt' \n", "data_warming = np.genfromtxt(data_file_warming, skip_header=1)\n", "\n", "temp_warming=data_warming[:,0]\n", "Mx_warming=data_warming[:,1]\n", "My_warming=data_warming[:,2]\n", "Mz_warming=data_warming[:,3]\n", "Mtotal_warming=data_warming[:,4]" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 65 }, { "cell_type": "code", "collapsed": false, "input": [ "Mx_cooling_bsub = background_sub(blank1_data_cooling['Mx[Am2]'],\n", " blank1_data_cooling['measurement_T[K]'],\n", " Mx_cooling,temp_cooling)\n", "\n", "My_cooling_bsub = background_sub(blank1_data_cooling['My[Am2]'],\n", " blank1_data_cooling['measurement_T[K]'],\n", " My_cooling,temp_cooling)\n", "\n", "Mz_cooling_bsub = background_sub(blank1_data_cooling['Mz[Am2]'],\n", " blank1_data_cooling['measurement_T[K]'],\n", " Mz_cooling,temp_cooling)\n", "\n", "Mx_warming_bsub = background_sub(blank1_data_warming['Mx[Am2]'],\n", " blank1_data_warming['measurement_T[K]'],\n", " Mx_warming[:-8],temp_warming[:-8])\n", "\n", "My_warming_bsub = background_sub(blank1_data_warming['My[Am2]'],\n", " blank1_data_warming['measurement_T[K]'],\n", " My_warming[:-8],temp_warming[:-8])\n", "\n", "Mz_warming_bsub = background_sub(blank1_data_warming['Mz[Am2]'],\n", " blank1_data_warming['measurement_T[K]'],\n", " Mz_warming[:-8],temp_warming[:-8])\n", "\n", "fignum=1\n", "plt.figure(num=fignum,figsize=(10,10),dpi=160)\n", "\n", "ax=plt.subplot(211)\n", "plt.plot(temp_cooling, Mx_cooling, 'r*-',label=\"Mx cooling\")\n", "plt.plot(temp_cooling, My_cooling, 'b*-',label=\"My cooling\")\n", "plt.plot(temp_cooling, Mz_cooling, 'g*-',label=\"Mz cooling\")\n", "plt.plot(temp_warming, Mx_warming, 'rv-',label=\"Mx warming\")\n", "plt.plot(temp_warming, My_warming, 'bv-',label=\"My warming\")\n", "plt.plot(temp_warming, Mz_warming, 'gv-',label=\"Mz warming\")\n", "plt.xlabel('Temperature (K)')\n", "plt.ylabel('Magnetic moment (Am$^2$)')\n", "plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)\n", "\n", "ax=plt.subplot(212)\n", "plt.plot(temp_cooling, Mx_cooling_bsub, 'rs-',\n", " label=\"Mx cooling (background corrected)\")\n", "plt.plot(temp_cooling, My_cooling_bsub, 'bs-',\n", " label=\"My cooling (background corrected)\")\n", "plt.plot(temp_cooling, Mz_cooling_bsub, 'gs-',\n", " label=\"Mz cooling (background corrected)\")\n", "plt.plot(temp_warming[:-8], Mx_warming_bsub, 'ro-',\n", " label=\"Mx warming (background corrected)\")\n", "plt.plot(temp_warming[:-8], My_warming_bsub, 'bo-',\n", " label=\"My warming (background corrected)\")\n", "plt.plot(temp_warming[:-8], Mz_warming_bsub, 'go-',\n", " label=\"Mz warming (background corrected)\")\n", "plt.xlabel('Temperature (K)')\n", "plt.ylabel('Magnetic moment (Am$^2$)')\n", "plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)\n", "plt.show()\n" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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OlejoaImNjZUXXnhBjDGyZ8+e0p4qN1X9/dHt/NqMiP7yWdUYY0TPu6IoNQERYdrMacx9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jZLndq1OT24VzbrGbb/btmSpuvWQaVKvLhzJ+/+9BMdK1ak3cGD3NO/f+hZtunpjBs7lkfvuSe8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Musf25JPhmGPg2Wf3a1wiIiIicmAltc6sVI5Daf00kepiX8OIw6FQ4gmieveGo47SEGQRkTJo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\n+uzbtg02bOjM2jazte2dkh999lm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"text": [ "" ] } ], "prompt_number": 66 }, { "cell_type": "code", "collapsed": false, "input": [ "full_vector_cooling=[]\n", "for n in range(0,len(temp_cooling)):\n", " full_vector_cooling.append([Mx_cooling[n],My_cooling[n],Mz_cooling[n]])\n", "full_vector_warming=[]\n", "for n in range(0,len(temp_warming)):\n", " full_vector_warming.append([Mx_warming[n],My_warming[n],Mz_warming[n]])\n", " \n", "cooling_directions=pmag.cart2dir(full_vector_cooling)\n", "warming_directions=pmag.cart2dir(full_vector_warming)\n", "\n", "fignum=3\n", "plt.figure(num=fignum,figsize=(4,4),dpi=160)\n", "pmagplotlib.plotNET(fignum)\n", "IPmag.iplotDI(cooling_directions,'b')\n", "IPmag.iplotDI(warming_directions,'r')\n", "plt.title('LT-cycling of NRM (rotated; no background subtraction)')\n", "#plt.savefig('PW10-7d_3axisLTD_eqarea.svg')\n", "plt.show()\n", "\n", "full_vector_cooling=[]\n", "for n in range(0,len(temp_cooling)):\n", " full_vector_cooling.append([Mx_cooling_bsub[n],My_cooling_bsub[n],Mz_cooling_bsub[n]])\n", "full_vector_warming=[]\n", "for n in range(0,len(Mx_warming_bsub)):\n", " full_vector_warming.append([Mx_warming_bsub[n],My_warming_bsub[n],Mz_warming_bsub[n]])\n", " \n", "cooling_directions=pmag.cart2dir(full_vector_cooling)\n", "warming_directions=pmag.cart2dir(full_vector_warming)\n", "\n", "fignum=3\n", "plt.figure(num=fignum,figsize=(4,4),dpi=160)\n", "pmagplotlib.plotNET(fignum)\n", "IPmag.iplotDI(cooling_directions,'b')\n", "IPmag.iplotDI(warming_directions,'r')\n", "plt.title('LT-cycling of NRM (rotated; background subtraction)')\n", "#plt.savefig('PW10-7d_3axisLTD_eqarea.svg')\n", "plt.show()" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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cGRGzSE0MdwE/y/EsS0q0OwJflPQEcDFwLnBjuBZic8k1WBu3XFPdAfh3YBPSIffPSYn1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\nM6uIE6yZWUWcYM3MKuIEa2ZWkf8Pb8bbNcoruzcAAAAASUVORK5CYII=\n", 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"text": [ "" ] } ], "prompt_number": 67 }, { "cell_type": "markdown", "metadata": {}, "source": [ "These plots show that the background subtraction is imperfect along the y-axis and is thereby adding an artifact to the data that is making it so that the end cooling values are not matching the start warming values. As can be seen in the data for the empty probe above, the y-axis has the highest magnetization in the blank probe runs with significant temperature dependent change. Given that the majority of the specimens directional change is in the z-axis and the z-axis data is minimally effected by the background subtraction, let's proceed with plotting the data that is not corrected for the holder, but is rotated back into specimen coordinates (e.g. Mz_cooling rather than Mz_cooling_bsub)." ] }, { "cell_type": "code", "collapsed": false, "input": [ "Mx_cooling_prime = Mx_cooling*np.cos(np.radians(angle)) - My_cooling*np.sin(np.radians(angle))\n", "My_cooling_prime = Mx_cooling*np.sin(np.radians(angle)) + My_cooling*np.cos(np.radians(angle))\n", "Mz_cooling_prime = Mz_cooling\n", "full_vector_cooling=[]\n", "for n in range(0,len(temp_cooling)):\n", " full_vector_cooling.append([Mx_cooling_prime[n],My_cooling_prime[n],Mz_cooling_prime[n]])\n", " \n", "Mx_warming_prime = Mx_warming*np.cos(np.radians(angle)) - My_warming*np.sin(np.radians(angle))\n", "My_warming_prime = Mx_warming*np.sin(np.radians(angle)) + My_warming*np.cos(np.radians(angle))\n", "Mz_warming_prime = Mz_warming\n", "full_vector_warming=[]\n", "for n in range(0,len(temp_warming)):\n", " full_vector_warming.append([Mx_warming_prime[n],My_warming_prime[n],Mz_warming_prime[n]])\n", "\n", "fignum=2\n", "plt.figure(num=fignum,figsize=(12,8),dpi=160)\n", "plt.plot(temp_cooling, Mx_cooling_prime, 'rs-',label=\"Mx cooling\")\n", "plt.plot(temp_cooling, My_cooling_prime, 'bs-',label=\"My cooling\")\n", "plt.plot(temp_cooling, Mz_cooling_prime, 'gs-',label=\"Mz cooling\")\n", "plt.plot(temp_warming, Mx_warming_prime, 'ro-',label=\"Mx warming\")\n", "plt.plot(temp_warming, My_warming_prime, 'bo-',label=\"My warming\")\n", "plt.plot(temp_warming, Mz_warming_prime, 'go-',label=\"Mz warming\")\n", "plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)\n", "plt.xlabel('Temperature (K)')\n", "plt.ylabel('Magnetic moment (Am$^2$)')\n", "plt.title('rotated PW10-7d data')\n", "plt.savefig('code_output/PW10-7d_3axisLTD.svg')" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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cn/zkJ6Snp581uDTG8OMf/5hu3boBMH78eJYtWwbAP/7xD8aMGcNVV10FwO9+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\nN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"text": [ "" ] } ], "prompt_number": 68 }, { "cell_type": "code", "collapsed": false, "input": [ "cooling_directions=pmag.cart2dir(full_vector_cooling)\n", "warming_directions=pmag.cart2dir(full_vector_warming)\n", "\n", "fignum=3\n", "plt.figure(num=fignum,figsize=(7,7),dpi=160)\n", "pmagplotlib.plotNET(fignum)\n", "IPmag.iplotDI(cooling_directions,'b')\n", "IPmag.iplotDI(warming_directions,'r')\n", "plt.title('PW10-7d NRM upon cooling and warming (specimen coordinates)')\n", "plt.savefig('code_output/PW10-7d_3axisLTD_eqarea.svg')\n", "plt.show()" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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pHYeNH0mvA24EPhMRZ5eOx4bmKnSbSZ7b+1fAUU7eZr0jzxm+E/AzSUuUjseG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\nzTEuaS7gXOBeYC9fLdKdnMCtZSTtQ/p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"text": [ "" ] } ], "prompt_number": 69 }, { "cell_type": "code", "collapsed": false, "input": [ "print \"The angular change from NRM to the end of LT-cycling is:\"\n", "print pmag.angle(cooling_directions[0],warming_directions[240])" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "The angular change from NRM to the end of LT-cycling is:\n", "[ 84.7946601]\n" ] } ], "prompt_number": 70 }, { "cell_type": "code", "collapsed": false, "input": [ "PW10_7d_datablock=[]\n", "\n", "for n in range(0,len(cooling_directions)):\n", " PW10_7d_datablock.append([temp_cooling[n],\n", " cooling_directions[n][0],\n", " cooling_directions[n][1],\n", " cooling_directions[n][2]])\n", "for n in range(0,len(warming_directions)):\n", " PW10_7d_datablock.append([temp_warming[n],\n", " warming_directions[n][0],\n", " warming_directions[n][1],\n", " warming_directions[n][2]])\n", " \n", "#plot with pmagplotlib.plotZ(fignum,datablock,angle,s,norm)\n", "pmagplotlib.plotZ(1,PW10_7d_datablock,90,'series 2 cooling',0)\n", "plt.ticklabel_format(style='sci', scilimits=(0,0), axis='y')\n", "plt.ticklabel_format(style='sci', scilimits=(0,0), axis='x')\n", "plt.savefig('code_output/Umk_Pw10-7a_specimen_zplot.pdf')\n", "plt.show()" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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BsmVjgR/VbPfaxepqP7dK4l8l3vTUOjUlRzFR0kWSekgqiT8yXjLnMiAxX/Eh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\nbLh8OVf997+cfswxHixcVjV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"text": [ "" ] } ], "prompt_number": 71 }, { "cell_type": "heading", "level": 2, "metadata": {}, "source": [ "PW15-4" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This sample is from the interior (~ 11 meters from margin) of an Umkondo Large Igneous Province diabase sill (the Mogatelwane 2 sill) and displayed a large loss in remanence associated with a liquid nitrogen treatment step that was applied during initial demagnetization of the NRM. Due to this behavior the sample was targeted for experiments on the low-temperature probe." ] }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "NRM demagnetization" ] }, { "cell_type": "code", "collapsed": false, "input": [ "PW15_4a_demag = pd.read_csv('../Data/Umkondo/PW15/PW15-4a.csv')\n", "PW15_4a_demag" ], "language": "python", "metadata": {}, "outputs": [ { "html": [ "
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specimenstep(mT)intensitydec_geoinc_geodec_specinc_spec
0 PW15-4 0 0.034587 200.2 -7.8 354.3 72.1
1 PW15-4 0 0.016562 200.1 -9.1 354.2 70.8
2 PW15-4 5 0.015866 200.1 -8.8 354.3 71.1
3 PW15-4 10 0.010725 199.8 -8.1 352.9 71.7
4 PW15-4 15 0.005063 198.5 -9.9 349.8 69.8
5 PW15-4 20 0.002243 196.5-12.2 346.0 67.2
6 PW15-4 25 0.001239 194.6-11.6 341.1 67.2
7 PW15-4 30 0.000706 194.5-11.6 340.7 67.1
8 PW15-4 40 0.000372 194.5-12.4 341.4 66.4
9 PW15-4 50 0.000212 194.1-13.3 341.2 65.4
10 PW15-4 60 0.000135 193.5-14.0 340.5 64.6
11 PW15-4 70 0.000090 192.0-12.6 336.1 65.3
12 PW15-4 80 0.000075 192.5-15.6 339.6 62.7
13 PW15-4 90 0.000058 192.7-11.5 336.4 66.6
14 PW15-4 100 0.000046 188.5-10.8 326.9 65.3
\n", "
" ], "metadata": {}, "output_type": "pyout", "prompt_number": 72, "text": [ " specimen step(mT) intensity dec_geo inc_geo dec_spec inc_spec\n", "0 PW15-4 0 0.034587 200.2 -7.8 354.3 72.1\n", "1 PW15-4 0 0.016562 200.1 -9.1 354.2 70.8\n", "2 PW15-4 5 0.015866 200.1 -8.8 354.3 71.1\n", "3 PW15-4 10 0.010725 199.8 -8.1 352.9 71.7\n", "4 PW15-4 15 0.005063 198.5 -9.9 349.8 69.8\n", "5 PW15-4 20 0.002243 196.5 -12.2 346.0 67.2\n", "6 PW15-4 25 0.001239 194.6 -11.6 341.1 67.2\n", "7 PW15-4 30 0.000706 194.5 -11.6 340.7 67.1\n", "8 PW15-4 40 0.000372 194.5 -12.4 341.4 66.4\n", "9 PW15-4 50 0.000212 194.1 -13.3 341.2 65.4\n", "10 PW15-4 60 0.000135 193.5 -14.0 340.5 64.6\n", "11 PW15-4 70 0.000090 192.0 -12.6 336.1 65.3\n", "12 PW15-4 80 0.000075 192.5 -15.6 339.6 62.7\n", "13 PW15-4 90 0.000058 192.7 -11.5 336.4 66.6\n", "14 PW15-4 100 0.000046 188.5 -10.8 326.9 65.3" ] } ], "prompt_number": 72 }, { "cell_type": "code", "collapsed": false, "input": [ "PW15_4a_datablock_geo=[]\n", "PW15_4a_datablock_spec=[]\n", "PW15_4a_DI_geo=[]\n", "PW15_4a_DI_spec=[]\n", "for n in range(0,len(PW15_4a_demag)):\n", " PW15_4a_datablock_geo.append([PW15_4a_demag['step(mT)'][n],\n", " PW15_4a_demag['dec_geo'][n],\n", " PW15_4a_demag['inc_geo'][n],\n", " PW15_4a_demag['intensity'][n]])\n", " PW15_4a_datablock_spec.append([PW15_4a_demag['step(mT)'][n],\n", " PW15_4a_demag['dec_spec'][n],\n", " PW15_4a_demag['inc_spec'][n],\n", " PW15_4a_demag['intensity'][n]])\n", " PW15_4a_DI_geo.append([PW15_4a_demag['dec_geo'][n],\n", " PW15_4a_demag['inc_geo'][n]])\n", " PW15_4a_DI_spec.append([PW15_4a_demag['dec_spec'][n],\n", " PW15_4a_demag['inc_spec'][n]])" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 73 }, { "cell_type": "heading", "level": 4, "metadata": {}, "source": [ "Intensity plot" ] }, { "cell_type": "code", "collapsed": false, "input": [ "plt.figure(figsize=(5,5))\n", "plt.plot(PW15_4a_demag['step(mT)'],PW15_4a_demag['intensity'],marker='o')\n", "plt.xlabel('AF demag step (mT)')\n", "plt.ylabel('Magnetization (Am^2/kg)')\n", "plt.xlim((-1,50))\n", "plt.ylim((0,.04))\n", "plt.savefig('code_output/PW15_4a_intensity.pdf')\n", "plt.show()\n", "\n", "print 'The remanence lost (in %) following low-temp cycling is:'\n", "print ((PW15_4a_demag['intensity'][0]-PW15_4a_demag['intensity'][1])/PW15_4a_demag['intensity'][0])*100" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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IsmVw4onw2GNw6KHFjsasNHm4wBp0+OHwve/B+efDpvpnSTSzVuYk28F84xuw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\nqjs3p2wUcG2x/+/B245bR5n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"text": [ "" ] }, { "output_type": "stream", "stream": "stdout", "text": [ "The remanence lost (in %) following low-temp cycling is:\n", "52.116666763\n" ] } ], "prompt_number": 74 }, { "cell_type": "markdown", "metadata": {}, "source": [ "The large loss of remanence is associated with a low-temperature nitrogen bath in near-zero field." ] }, { "cell_type": "heading", "level": 4, "metadata": {}, "source": [ "Z-plot and equal area in specimen coordinates" ] }, { "cell_type": "code", "collapsed": false, "input": [ "#plot with pmagplotlib.plotZ(fignum,datablock,angle,s,norm)\n", "pmagplotlib.plotZ(1,PW15_4a_datablock_spec,90,'series 2 cooling',0)\n", "plt.ticklabel_format(style='sci', scilimits=(0,0), axis='y')\n", "plt.ticklabel_format(style='sci', scilimits=(0,0), axis='x')\n", "plt.savefig('code_output/PW15_4a_specimen_zplot.pdf')\n", "plt.show()\n", "\n", "plt.figure(figsize=(5,5))\n", "pmagplotlib.plotNET(1)\n", "IPmag.iplotDI(PW15_4a_DI_spec)\n", "plt.title('Equal Area of demag')\n", "plt.savefig('code_output/PW15_4a_specimen_eqaplot.pdf')\n", "plt.show()" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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Mm1n9uERhZmatNSigmZn1LQcKMzMr5UBhZmalHCjMzKyUA4WZmZVyoDAzs1IO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\nYII=\n", 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k28fHgD5J+9YuxGw4JO1K2uL70HC/45A8rbZNRMTfJe0DXC5pZkT8oXZNnc5r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\n", "text": [ "" ] } ], "prompt_number": 75 }, { "cell_type": "heading", "level": 2, "metadata": {}, "source": [ "IRM-LTI experiments" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The experiments conducted on the samples were as follows.\n", "
    \n", "
  1. Load the sample with arrow (down core z-axis) pointing out of SRM (old 2G at IRM) and make measurement (measurement series #1, measurement #1). The direction should be approx. the same as the measurement of the sister \"a-series\" specimen.
  2. \n", "
  3. Twist the sample screw tight as is needed for running in low-temperature insert which results in sample being rotated about the z-axis (measurement series #1, measurement #2).
  4. \n", "
  5. Cover the sample holder with the sapphire radiation shield and vacuum shroud and then being cooling. Measurements are made upon cooling (measurement series #2).
  6. \n", "
  7. Once at minimum temperature (slightly below 20K) warm the probe back up progressively making measurements as it warms (measurement series #2).\n", "
" ] }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "LT-cycling of NRM" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Import data file which has the format: \n", "\n", " \n", " \n", " \n", "
TEMPERATURE (K)M_x [Am2]M_y [Am2]M_z [Am2]M_total [Am2]MEASUREMENT SERIES
" ] }, { "cell_type": "code", "collapsed": false, "input": [ "PW15_data = pd.read_table('../Data/Umkondo/PW15/PW15-4d_LTI_experiments.txt')\n", "PW15_data.head()" ], "language": "python", "metadata": {}, "outputs": [ { "html": [ "
\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
measurement_T[K]Mx[Am2]My[Am2]Mz[Am2]moment[Am2]Measurement_series
0 293.03 0.000007 0.000000 0.000024 0.000025 1
1 292.90-0.000002-0.000007 0.000024 0.000025 1
2 293.30-0.000002-0.000007 0.000024 0.000025 2
3 293.59-0.000002-0.000007 0.000024 0.000025 2
4 293.26-0.000002-0.000007 0.000024 0.000025 2
\n", "
" ], "metadata": {}, "output_type": "pyout", "prompt_number": 76, "text": [ " measurement_T[K] Mx[Am2] My[Am2] Mz[Am2] moment[Am2] \\\n", "0 293.03 0.000007 0.000000 0.000024 0.000025 \n", "1 292.90 -0.000002 -0.000007 0.000024 0.000025 \n", "2 293.30 -0.000002 -0.000007 0.000024 0.000025 \n", "3 293.59 -0.000002 -0.000007 0.000024 0.000025 \n", "4 293.26 -0.000002 -0.000007 0.000024 0.000025 \n", "\n", " Measurement_series \n", "0 1 \n", "1 1 \n", "2 2 \n", "3 2 \n", "4 2 " ] } ], "prompt_number": 76 }, { "cell_type": "code", "collapsed": false, "input": [ "full_vector_oriented=[]\n", "full_vector_rotated=[]\n", "\n", "#data point 0 is oriented\n", "for n in range(0,1):\n", " full_vector_oriented.append([PW15_data['Mx[Am2]'][n],\n", " PW15_data['My[Am2]'][n],\n", " PW15_data['Mz[Am2]'][n]])\n", "\n", "#data point 1 is rotated about z\n", "for n in range(1,2):\n", " full_vector_rotated.append([PW15_data['Mx[Am2]'][n],\n", " PW15_data['My[Am2]'][n],\n", " PW15_data['Mz[Am2]'][n]])\n", "\n", " \n", "oriented_directions=pmag.cart2dir(full_vector_oriented)\n", "rotated_directions=pmag.cart2dir(full_vector_rotated)\n", "\n", "#rotate the rotated directions about the z-axis \n", "#to correspond to the oriented measurement\n", "angle = 360 + oriented_directions.item(0) - rotated_directions.item(0)\n", "\n", "x_prime = PW15_data['Mx[Am2]'][1]*np.cos(np.radians(angle)) - PW15_data['My[Am2]'][1]*np.sin(np.radians(angle))\n", "y_prime = PW15_data['Mx[Am2]'][1]*np.sin(np.radians(angle)) + PW15_data['My[Am2]'][1]*np.cos(np.radians(angle))\n", "z_prime = PW15_data['Mz[Am2]'][1]\n", "\n", "full_vector_rotated_prime= [[x_prime,y_prime,z_prime]]\n", "rotated_directions_prime=pmag.cart2dir(full_vector_rotated_prime)\n", "\n", "#plot the oriented measurement and the rotated measurement\n", "fignum = 1\n", "plt.figure(num=fignum,figsize=(4,4),dpi=160)\n", "pmagplotlib.plotNET(fignum)\n", "IPmag.iplotDI(oriented_directions,'k')\n", "IPmag.iplotDI(rotated_directions,'b')\n", "plt.title('PW15-4d NRM oriented (black) and rotated (blue)');\n", "\n", "#plot the oriented measurement and the corrected rotated measurement\n", "fignum = 2\n", "plt.figure(num=fignum,figsize=(4,4),dpi=160)\n", "pmagplotlib.plotNET(fignum)\n", "IPmag.iplotDI(oriented_directions,'k')\n", "IPmag.iplotDI(rotated_directions_prime,'b')\n", "plt.title('PW15-4d NRM oriented (black) and rotated (corrected; blue)');" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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"text": [ "" ] } ], "prompt_number": 77 }, { "cell_type": "markdown", "metadata": {}, "source": [ "It will be more convenient to have the data for measurement series 2 (LT-cycling) split into cooling and warming." ] }, { "cell_type": "code", "collapsed": false, "input": [ "PW15_s2_cooling = PW15_data[2:121]\n", "PW15_s2_cooling.reset_index(inplace='True')\n", "PW15_s2_warming = PW15_data[129:374]\n", "PW15_s2_warming.reset_index(inplace='True')\n", "\n", "PW15_s2_warming.tail()" ], "language": "python", "metadata": {}, "outputs": [ { "html": [ "
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indexmeasurement_T[K]Mx[Am2]My[Am2]Mz[Am2]moment[Am2]Measurement_series
240 369 284.16-0.000001-0.000003 0.000012 0.000013 2
241 370 284.47-0.000001-0.000003 0.000012 0.000013 2
242 371 284.39-0.000001-0.000003 0.000012 0.000013 2
243 372 284.46-0.000001-0.000003 0.000012 0.000013 2
244 373 284.52-0.000001-0.000003 0.000012 0.000013 2
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" ], "metadata": {}, "output_type": "pyout", "prompt_number": 78, "text": [ " index measurement_T[K] Mx[Am2] My[Am2] Mz[Am2] moment[Am2] \\\n", "240 369 284.16 -0.000001 -0.000003 0.000012 0.000013 \n", "241 370 284.47 -0.000001 -0.000003 0.000012 0.000013 \n", "242 371 284.39 -0.000001 -0.000003 0.000012 0.000013 \n", "243 372 284.46 -0.000001 -0.000003 0.000012 0.000013 \n", "244 373 284.52 -0.000001 -0.000003 0.000012 0.000013 \n", "\n", " Measurement_series \n", "240 2 \n", "241 2 \n", "242 2 \n", "243 2 \n", "244 2 " ] } ], "prompt_number": 78 }, { "cell_type": "markdown", "metadata": {}, "source": [ "The data need to be rotated into the oriented specimen coordinates. These rotated data will be called 'prime'." ] }, { "cell_type": "code", "collapsed": false, "input": [ "PW15_s2_cooling['Mx_prime[Am2]'] = PW15_s2_cooling['Mx[Am2]']*np.cos(np.radians(angle)) - PW15_s2_cooling['My[Am2]']*np.sin(np.radians(angle))\n", "PW15_s2_cooling['My_prime[Am2]'] = PW15_s2_cooling['Mx[Am2]']*np.sin(np.radians(angle)) + PW15_s2_cooling['My[Am2]']*np.cos(np.radians(angle))\n", "PW15_s2_cooling['Mz_prime[Am2]'] = PW15_s2_cooling['Mz[Am2]']\n", "\n", "full_vector_cooling_prime=[]\n", "for n in range(len(PW15_s2_cooling)):\n", " full_vector_cooling_prime.append([PW15_s2_cooling['Mx_prime[Am2]'][n],\n", " PW15_s2_cooling['My_prime[Am2]'][n],\n", " PW15_s2_cooling['Mz_prime[Am2]'][n]])\n", "\n", "PW15_s2_warming['Mx_prime[Am2]'] = PW15_s2_warming['Mx[Am2]']*np.cos(np.radians(angle)) - PW15_s2_warming['My[Am2]']*np.sin(np.radians(angle))\n", "PW15_s2_warming['My_prime[Am2]'] = PW15_s2_warming['Mx[Am2]']*np.sin(np.radians(angle)) + PW15_s2_warming['My[Am2]']*np.cos(np.radians(angle))\n", "PW15_s2_warming['Mz_prime[Am2]'] = PW15_s2_warming['Mz[Am2]']\n", "\n", "full_vector_warming_prime=[]\n", "for n in range(len(PW15_s2_warming)):\n", " full_vector_warming_prime.append([PW15_s2_warming['Mx_prime[Am2]'][n],\n", " PW15_s2_warming['My_prime[Am2]'][n],\n", " PW15_s2_warming['Mz_prime[Am2]'][n]])" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 79 }, { "cell_type": "code", "collapsed": false, "input": [ "cooling_directions_prime=pmag.cart2dir(full_vector_cooling_prime)\n", "warming_directions_prime=pmag.cart2dir(full_vector_warming_prime)\n", "\n", "fignum=1\n", "plt.figure(num=fignum,figsize=(6,6),dpi=160)\n", "pmagplotlib.plotNET(fignum)\n", "IPmag.iplotDI(cooling_directions_prime,'b')\n", "IPmag.iplotDI(warming_directions_prime,'r')\n", "plt.title('PW15-4d NRM upon cooling and warming (specimen coordinates)')\n", "plt.savefig('code_output/PW15-4d_equalarea.pdf')\n", "plt.show()\n", "\n", "#the specimen has a mass of .6483 g\n", "fignum=2\n", "plt.figure(num=fignum,figsize=(6,6),dpi=160)\n", "plt.plot(PW15_s2_cooling['measurement_T[K]'], \n", " PW15_s2_cooling['Mx_prime[Am2]']/(.6483/1000), 'rs-')\n", "plt.plot(PW15_s2_warming['measurement_T[K]'], \n", " PW15_s2_warming['Mx_prime[Am2]']/(.6483/1000), 'ro-')\n", "plt.plot(PW15_s2_cooling['measurement_T[K]'], \n", " PW15_s2_cooling['My_prime[Am2]']/(.6483/1000), 'bs-')\n", "plt.plot(PW15_s2_warming['measurement_T[K]'], \n", " PW15_s2_warming['My_prime[Am2]']/(.6483/1000), 'bo-')\n", "plt.plot(PW15_s2_cooling['measurement_T[K]'], \n", " PW15_s2_cooling['Mz_prime[Am2]']/(.6483/1000), 'gs-')\n", "plt.plot(PW15_s2_warming['measurement_T[K]'], \n", " PW15_s2_warming['Mz_prime[Am2]']/(.6483/1000), 'go-')\n", "plt.xlabel('Temperature (K)')\n", "plt.ylabel('Magnetization (Am$^2$/kg)')\n", "plt.legend(('Mx cooling','Mx warming','My cooling',\n", " 'My warming','Mz cooling','Mz warming'),loc=0)\n", "plt.savefig('code_output/PW15-4d_3axis.svg')\n", "plt.show()" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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9fW9T3Ken1+zmubr6bnT4PSnwryAttE8AhkfEBFKw7EVq7fgp6bCgCflx25BaJp4nrTz/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\ndD1mrUzSMNL+5LMj4o+l62k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C8W7L8Vg9ntL2iXOscxGR08aYVOAyIA04aoxpKyJHjDHtgGO+Xtw9EJWlYUPf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\nLGAU97LtTqXG44uQEmEWoO3tY9+ZGxkpaevo6OCMRYvoOfV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"text": [ "" ] } ], "prompt_number": 80 }, { "cell_type": "code", "collapsed": false, "input": [ "moment_290 = cooling_directions_prime[1,2]\n", "moment_20 = cooling_directions_prime[118,2]\n", "moment_postcycle = warming_directions_prime[244,2]\n", "\n", "print \"Percent remanence remaining at 20K\"\n", "print moment_20/moment_290*100\n", "print \"Percent remanence remaining after thermal cycling\"\n", "print moment_postcycle/moment_290*100" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "Percent remanence remaining at 20K\n", "21.234697426\n", "Percent remanence remaining after thermal cycling\n", "51.6463378548\n" ] } ], "prompt_number": 81 }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "ARM/pARM acquisition and low-temperature cycling" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This experiment was designed to impart an ARM to the sample and a perpendicular pARM (to low coercivities) to the sample in order to ascertain the behavior of the low-coercivity ARM and resolve directional change during low-temperature cycling.\n", "
    \n", "
  1. Give the specimen a negative z-axis ARM (0.03 mT bias field in 200 mT AF field) and measure (measurement 1 in measurement series #3) (after the measurement the decision was made to increase the bias field in order to increase the moment)
  2. \n", "
  3. Give the specimen a negative z-axis ARM (0.1 mT bias field in 200 mT AF field) and measure (measurement 2 in measurement series #3)
  4. \n", "
  5. Give the specimen a negative x-axis ARM (0.1 mT bias field in 5 mT AF field) and measure (measurement 3 in measurement series #3) (after the measurement the decision was made to increase the of this pARM bias field in order to increase the moment)
  6. Give the specimen a negative x-axis ARM (0.2 mT bias field in 5 mT AF field) and measure (measurement 4 in measurement series #3)
  7. \n", "
  8. Tightening the sample holder for the cryogenic experiment requires rotating the sample an unknown amount about the z-axis (measurement 5 in measurement series #3)
  9. Cover the sample holder with the sapphire radiation shield and vacuum shroud and then being cooling. Measurements are made upon cooling and subsequent warming (measurement series #4).
  10. \n", "
" ] }, { "cell_type": "heading", "level": 4, "metadata": {}, "source": [ "ARM/pARM acquisition" ] }, { "cell_type": "code", "collapsed": false, "input": [ "zARM_oriented=[]\n", "zARMxARM_oriented=[]\n", "zARMxARM_rotated=[]\n", "\n", "#negative z-axis ARM (0.1 mT bias field in 200 mT AF field)\n", "for n in range(375,376):\n", " Mx_full=PW15_data['Mx[Am2]'][n]\n", " My_full=PW15_data['My[Am2]'][n]\n", " Mz_full=PW15_data['Mz[Am2]'][n]\n", " zARM_oriented.append([Mx_full,My_full,Mz_full])\n", "\n", "#negative z-axis ARM (0.1 mT bias field in 200 mT AF field) + negative x-axis ARM (0.2 mT bias field in 5 mT AF field)\n", "for n in range(377,378):\n", " Mx_full=PW15_data['Mx[Am2]'][n]\n", " My_full=PW15_data['My[Am2]'][n]\n", " Mz_full=PW15_data['Mz[Am2]'][n]\n", " zARMxARM_oriented.append([Mx_full,My_full,Mz_full])\n", " \n", "#negative z-axis ARM (0.1 mT bias field in 200 mT AF field) + negative x-axis ARM (0.2 mT bias field in 5 mT AF field) rotated about z-axis\n", "for n in range(378,379):\n", " Mx_full=PW15_data['Mx[Am2]'][n]\n", " My_full=PW15_data['My[Am2]'][n]\n", " Mz_full=PW15_data['Mz[Am2]'][n]\n", " zARMxARM_rotated.append([Mx_full,My_full,Mz_full])\n", " \n", "zARM_oriented_directions=pmag.cart2dir(zARM_oriented)\n", "zARMxARM_oriented_directions=pmag.cart2dir(zARMxARM_oriented)\n", "zARMxARM_rotated_directions=pmag.cart2dir(zARMxARM_rotated)\n", "\n", "#rotate the rotated directions about the z-axis to correspond to the oriented measurement\n", "angle = zARMxARM_oriented_directions.item(0) - zARMxARM_rotated_directions.item(0)\n", "\n", "x_prime = PW15_data['Mx[Am2]'][378]*np.cos(np.radians(angle)) - PW15_data['My[Am2]'][378]*np.sin(np.radians(angle))\n", "y_prime = PW15_data['Mx[Am2]'][378]*np.sin(np.radians(angle)) + PW15_data['My[Am2]'][378]*np.cos(np.radians(angle))\n", "z_prime = PW15_data['Mz[Am2]'][378]\n", "\n", "zARMxARM_rotated_prime = [[x_prime,y_prime,z_prime]]\n", "zARMxARM_rotated_directions_prime=pmag.cart2dir(zARMxARM_rotated_prime)\n", "\n", "#plot the oriented measurements and the rotated measurement\n", "fignum = 1\n", "plt.figure(num=fignum,figsize=(4,4),dpi=160)\n", "pmagplotlib.plotNET(fignum)\n", "IPmag.iplotDI(zARM_oriented_directions,'r')\n", "IPmag.iplotDI(zARMxARM_oriented_directions,'k')\n", "IPmag.iplotDI(zARMxARM_rotated_directions,'b')\n", "plt.title('zARM oriented (red) z&xARM oriented (black) and rotated (blue)');\n", "plt.savefig('code_output/PW15-4d_eqarea_ARMex.svg')\n", "\n", "#plot the oriented measurement and the corrected rotated measurement\n", "fignum = 2\n", "plt.figure(num=fignum,figsize=(4,4),dpi=160)\n", "pmagplotlib.plotNET(fignum)\n", "IPmag.iplotDI(zARMxARM_oriented_directions,'k')\n", "IPmag.iplotDI(zARMxARM_rotated_directions_prime,'b')\n", "plt.title('z&xARM oriented (black) and rotated (corrected; blue)');" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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"text": [ "" ] } ], "prompt_number": 82 }, { "cell_type": "code", "collapsed": false, "input": [ "#these values were needed to plot with the low-temp cycling data\n", "#on the vector component and equal area plot\n", "print zARM_oriented_directions\n", "print zARMxARM_rotated_directions_prime" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "[[ 2.74201770e+02 -8.45885759e+01 7.45321764e-07]]\n", "[[ 2.15129124e+02 -7.80651803e+01 7.16487969e-07]]\n" ] } ], "prompt_number": 83 }, { "cell_type": "heading", "level": 4, "metadata": {}, "source": [ "Low-temperature cycling" ] }, { "cell_type": "code", "collapsed": false, "input": [ "data_file_cooling='../Data/Umkondo/PW15/Pw15-4d_ARMex_cooling.txt'\n", "data_cooling = np.genfromtxt(data_file_cooling, skip_header=1)\n", "\n", "temp_cooling=data_cooling[:,0]\n", "Mx_cooling=data_cooling[:,1]\n", "My_cooling=data_cooling[:,2]\n", "Mz_cooling=data_cooling[:,3]\n", "Mtotal_cooling=data_cooling[:,4]\n", "\n", "data_file_warming='../Data/Umkondo/PW15/Pw15-4d_ARMex_warming.txt'\n", "data_warming = np.genfromtxt(data_file_warming, skip_header=1)\n", "\n", "temp_warming=data_warming[:,0]\n", "Mx_warming=data_warming[:,1]\n", "My_warming=data_warming[:,2]\n", "Mz_warming=data_warming[:,3]\n", "Mtotal_warming=data_warming[:,4]\n", "\n", "#For the interpolate function to work the x values (temperature) need to be ascending. \n", "#The blank_hem_data_cooling can be sorted so that temperatures are ascending\n", "blank2_data_cooling = blank2_data_cooling.sort(['measurement_T[K]'])\n", "\n", "Mx_cooling_bsub = background_sub(blank2_data_cooling['Mx[Am2]'],\n", " blank2_data_cooling['measurement_T[K]'],\n", " Mx_cooling,temp_cooling)\n", "\n", "My_cooling_bsub = background_sub(blank2_data_cooling['My[Am2]'],\n", " blank2_data_cooling['measurement_T[K]'],\n", " My_cooling,temp_cooling)\n", "\n", "Mz_cooling_bsub = background_sub(blank2_data_cooling['Mz[Am2]'],\n", " blank2_data_cooling['measurement_T[K]'],\n", " Mz_cooling,temp_cooling)\n", "\n", "Mx_warming_bsub = background_sub(blank2_data_warming['Mx[Am2]'],\n", " blank2_data_warming['measurement_T[K]'],\n", " Mx_warming,temp_warming)\n", "\n", "My_warming_bsub = background_sub(blank2_data_warming['My[Am2]'],\n", " blank2_data_warming['measurement_T[K]'],\n", " My_warming,temp_warming)\n", "\n", "Mz_warming_bsub = background_sub(blank2_data_warming['Mz[Am2]'],\n", " blank2_data_warming['measurement_T[K]'],\n", " Mz_warming,temp_warming)\n", "\n", "Mtotal_cooling_bsub=[]\n", "Mtotal_warming_bsub=[]\n", "\n", "for n in range(0,len(temp_cooling)):\n", " Mtotal_cooling_bsub.append(np.sqrt(Mx_cooling_bsub[n]**2+My_cooling_bsub[n]**2+Mz_cooling_bsub[n]**2))\n", " \n", "for n in range(0,len(temp_warming)): \n", " Mtotal_warming_bsub.append(np.sqrt(Mx_warming_bsub[n]**2+My_warming_bsub[n]**2+Mz_warming_bsub[n]**2))\n", " \n", "fignum=1\n", "plt.figure(num=fignum,figsize=(10,12),dpi=160)\n", "\n", "ax=plt.subplot(211)\n", "plt.plot(temp_cooling, Mx_cooling, 'r*-',label=\"Mx cooling\")\n", "plt.plot(temp_cooling, My_cooling, 'b*-',label=\"My cooling\")\n", "plt.plot(temp_cooling, Mz_cooling, 'g*-',label=\"Mz cooling\")\n", "plt.plot(temp_warming, Mx_warming, 'rv-',label=\"Mx warming\")\n", "plt.plot(temp_warming, My_warming, 'bv-',label=\"My warming\")\n", "plt.plot(temp_warming, Mz_warming, 'gv-',label=\"Mz warming\")\n", "plt.xlabel('Temperature (K)')\n", "plt.ylabel('Magnetic moment (Am$^2$)')\n", "plt.axis([0, 300, -0.000001, 0.0000004])\n", "plt.title('raw PW15-4d data')\n", "plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)\n", "\n", "ax=plt.subplot(212)\n", "plt.plot(temp_cooling, Mx_cooling_bsub, 'rs-',\n", " label=\"Mx cooling (background corrected)\")\n", "plt.plot(temp_cooling, My_cooling_bsub, 'bs-',\n", " label=\"My cooling (background corrected)\")\n", "plt.plot(temp_cooling, Mz_cooling_bsub, 'gs-',\n", " label=\"Mz cooling (background corrected)\")\n", "plt.plot(temp_warming, Mx_warming_bsub, 'ro-',\n", " label=\"Mx warming (background corrected)\")\n", "plt.plot(temp_warming, My_warming_bsub, 'bo-',\n", " label=\"My warming (background corrected)\")\n", "plt.plot(temp_warming, Mz_warming_bsub, 'go-',\n", " label=\"Mz warming (background corrected)\")\n", "plt.plot(temp_cooling, Mtotal_cooling_bsub, 'ks-',\n", " label=\"Mtotal cooling (background corrected)\")\n", "plt.plot(temp_warming, Mtotal_warming_bsub, 'ko-',\n", " label=\"Mtotal warming (background corrected)\")\n", "plt.xlabel('Temperature (K)')\n", "plt.ylabel('Magnetic moment (Am$^2$)')\n", "plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)\n", "plt.title('background corrected unrotated PW15-4d data')\n", "plt.axis([0, 300, -0.000001, 0.0000008])\n", "plt.show()" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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zz9ZAxS+//JIePXrQpEkTevbsyebNm13H7d+/n1tuuYWwsDA6duzI66+/Xmr9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\n6JGezqPffsu16en8tGNHcU9JKaVUCRPSrZxydTSmKtAfuElEuoR1VmW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NAAAg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"text": [ "" ] } ], "prompt_number": 84 }, { "cell_type": "markdown", "metadata": {}, "source": [ "The fan turning on and off on another instrument in the lab resulted in flux jumps during a portion of time during initial cooling. These data need to be filtered out of the data set which is done below. The data also need to be rotated into the specimen's core coordinates." ] }, { "cell_type": "code", "collapsed": false, "input": [ "Mx_cooling_prime = Mx_cooling_bsub*np.cos(np.radians(angle)) - My_cooling_bsub*np.sin(np.radians(angle))\n", "My_cooling_prime = Mx_cooling_bsub*np.sin(np.radians(angle)) + My_cooling_bsub*np.cos(np.radians(angle))\n", "Mz_cooling_prime = Mz_cooling_bsub\n", "Mx_cooling_prime_nf = []\n", "My_cooling_prime_nf = []\n", "Mz_cooling_prime_nf = []\n", "Mtotal_cooling_prime_nf = []\n", "full_vector_cooling=[]\n", "temp_cooling_prime = []\n", "temp_cooling_prime_nf = []\n", "\n", "for n in range(0,len(temp_cooling)):\n", " if My_cooling[n] < 1.45000000e-07 and temp_cooling[n] != 269.77999999999997: \n", " #this filter is instituted to remove data points that are spurious due to flux jumps\n", " Mx_cooling_prime_nf.append(Mx_cooling_prime[n])\n", " My_cooling_prime_nf.append(My_cooling_prime[n])\n", " Mz_cooling_prime_nf.append(Mz_cooling_prime[n])\n", " temp_cooling_prime_nf.append(temp_cooling[n])\n", " Mtotal_cooling_prime_nf.append(np.sqrt(Mx_cooling_prime[n]**2+My_cooling_prime[n]**2+Mz_cooling_prime[n]**2))\n", " full_vector_cooling.append([Mx_cooling_prime[n],My_cooling_prime[n],Mz_cooling_prime[n]])\n", " \n", "Mx_warming_prime = Mx_warming_bsub*np.cos(np.radians(angle)) - My_warming_bsub*np.sin(np.radians(angle))\n", "My_warming_prime = Mx_warming_bsub*np.sin(np.radians(angle)) + My_warming_bsub*np.cos(np.radians(angle))\n", "Mz_warming_prime = Mz_warming_bsub\n", "\n", "Mtotal_warming_prime= []\n", "full_vector_warming=[]\n", "\n", "for n in range(0,len(temp_warming)):\n", " full_vector_warming.append([Mx_warming_prime[n],My_warming_prime[n],Mz_warming_prime[n]])\n", " Mtotal_warming_prime.append(np.sqrt(Mx_warming_prime[n]**2+My_warming_prime[n]**2+Mz_warming_prime[n]**2))" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 85 }, { "cell_type": "markdown", "metadata": {}, "source": [ "These rotated, background corrected data are plotted below along with data that shows the change in magnetocrystalline anisotropy as a function of temperature for the sake of comparision with the patterns of demagnetization observed for the z-axis component (full ARM up to 200 mT except 0 to 5 mT) and the x-axis pARM (applied to low coercivity grains with a 0 to 5 mT AF field)." ] }, { "cell_type": "code", "collapsed": false, "input": [ "fignum=2\n", "plt.figure(num=fignum,figsize=(5,10),dpi=160)\n", "ax=plt.subplot(311)\n", "plt.plot(temp_cooling_prime_nf, np.negative(Mtotal_cooling_prime_nf), \n", " 'ks-',label=\"M$_{total}$ cooling\")\n", "plt.plot(temp_warming, np.negative(Mtotal_warming_prime), \n", " 'ko-',label=\"M$_{total}$ warming\")\n", "plt.plot(temp_cooling_prime_nf, Mx_cooling_prime_nf, 'rs-',label=\"M$_x$ cooling\")\n", "plt.plot(temp_warming, Mx_warming_prime, 'ro-',label=\"M$_x$ warming\")\n", "#plt.plot(temp_cooling_prime_nf, My_cooling_prime_nf, 'bs-',label=\"M$_y$ cooling\")\n", "#plt.plot(temp_warming, My_warming_prime, 'bo-',label=\"M$_y$ warming\")\n", "plt.plot(temp_cooling_prime_nf, Mz_cooling_prime_nf, 'gs-',label=\"M$_z$ cooling\")\n", "plt.plot(temp_warming, Mz_warming_prime, 'go-',label=\"M$_z$ warming\")\n", "plt.vlines(130, 1e-7,-8e-7, colors='b')\n", "plt.vlines(122, 1e-7,-8e-7, colors='c')\n", "plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)\n", "plt.ylabel('Magnetic moment (Am$^2$)')\n", "#plt.title('background corrected and rotated PW6-5f data')\n", "plt.ylim(1e-7,-8e-7)\n", "plt.savefig('code_output/PW15-4d_3axisLTD_ARMex.svg')\n", "\n", "ax=plt.subplot(312)\n", "plt.plot(temp_cooling_prime_nf, Mx_cooling_prime_nf/Mx_cooling_prime_nf[0], \n", " 'rs-',label=\"Mx cooling\")\n", "plt.plot(temp_warming, Mx_warming_prime/Mx_cooling_prime_nf[0], \n", " 'ro-',label=\"Mx warming\")\n", "plt.plot(temp_cooling_prime_nf, Mz_cooling_prime_nf/Mz_cooling_prime_nf[0], \n", " 'gs-',label=\"Mx cooling\")\n", "plt.plot(temp_warming, Mz_warming_prime/Mz_cooling_prime_nf[0], \n", " 'go-',label=\"Mx warming\")\n", "plt.vlines(130, -.2, 1.2, colors='b')\n", "plt.vlines(122, -.2, 1.2, colors='c')\n", "#plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)\n", "plt.ylabel('Magnetic moment (normalized to initial)')\n", "#plt.title('background corrected and rotated PW6-5f data')\n", "plt.ylim(-.2, 1.2)\n", "plt.savefig('code_output/PW15-4d_3axisLTD_ARMex.svg')\n", "\n", "Bickford_data = pd.read_csv('../Data/Umkondo/Bickford1957a_data.csv')\n", "\n", "ax=plt.subplot(313)\n", "plt.plot(Bickford_data['temp'],Bickford_data['Kone'],'ko-')\n", "plt.vlines(130, -2, 0.5, colors='b')\n", "plt.vlines(122, -2, 0.5, colors='c')\n", "plt.hlines(0, 0, 300, colors='k',linestyles='--')\n", "plt.xlim(0,300)\n", "plt.ylim(-2,0.5)\n", "plt.xlabel('Temperature (K)')\n", "plt.ylabel('K1 (x10$^{-4}$Jm$^{-3}$')\n", "\n", "cooling_directions=pmag.cart2dir(full_vector_cooling)\n", "warming_directions=pmag.cart2dir(full_vector_warming)\n", "\n", "plt.savefig('code_output/PW15-4d_3axisLTD_ARMex.pdf')" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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LgtAKcA2sUu0U42eNZ//X+6lOqq4JnvIUIFU78MnWwJZKzX+Cp80hrmCI67f2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\n3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"text": [ "" ] } ], "prompt_number": 86 }, { "cell_type": "code", "collapsed": false, "input": [ "Mz_initial = np.negative(Mz_cooling_prime_nf[0])\n", "Mz_end = np.negative(Mz_warming_prime[243])\n", "\n", "print 'Percent of initial remanence remaining along z axis'\n", "print Mz_end/Mz_initial*100" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "Percent of initial remanence remaining along z axis\n", "71.2291884462\n" ] } ], "prompt_number": 87 }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let's export the data in order to make a space-delimited file to be plotted using the PmagPy program zeq.py outside of this IPython notebook." ] }, { "cell_type": "code", "collapsed": false, "input": [ "np.savetxt(\"code_output/PW15-4d_cooling.txt\", cooling_directions, delimiter=\" \")\n", "np.savetxt(\"code_output/PW15-4d_coolingtemp.txt\", temp_cooling_prime_nf, delimiter=\" \")\n", "np.savetxt(\"code_output/PW15-4d_warming.txt\", warming_directions, delimiter=\" \")\n", "np.savetxt(\"code_output/PW15-4d_warmingtemp.txt\", temp_warming, delimiter=\" \")\n", "lowT_endpoint = warming_directions[len(warming_directions)-1]\n", "print lowT_endpoint" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "[ 2.68489944e+02 -8.23278382e+01 4.99277242e-07]\n" ] } ], "prompt_number": 88 }, { "cell_type": "markdown", "metadata": {}, "source": [ "Another figure to make is to compare the direction of the z-axis ARM with the z-axis ARM + x-axis pARM with the end point following low-temperature cycling." ] }, { "cell_type": "code", "collapsed": false, "input": [ "fignum = 1\n", "plt.figure(num=fignum,figsize=(6,6),dpi=160)\n", "pmagplotlib.plotNET(fignum)\n", "IPmag.iplotDI(zARM_oriented_directions,'r')\n", "IPmag.iplotDI(zARMxARM_rotated_directions_prime,'k')\n", "IPmag.iplotDI([[268.4,-82.3]],'b')\n", "plt.title('PW15-4d zARM oriented (red) z&xARM oriented (black) and following lowT-demag (blue)');\n", "plt.savefig('code_output/PW15-4d_eqarea_ARMex.svg')" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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gvwhprNrAj8c9pC6+oV7Xx4DJatiLLVsduH6IeQ8ntYi+PlKX18ByMRIj/j4NYZZ1B0O8\nN6OZL6/brwH2BW6MiBeAy0nrw9si4jFGb5blgOGXgdpqjYiPV35vvp7rXCRviAyYzMzlfrTfnSG/\nh5LeCuwP7JTXeYsATzJzeR3xezbMunaZhuuTGXz5+A9pQ3BANVDdQ9rYXqzymheKWQfwrg7cFRH/\nGarG8TgOyKWkH9Vqqvxzvu2qSmsJkuZWGkg4AZhbaSDR3HnaepJWVRqYtBjwA+BPlZaHRpuT+s7f\nQEq5A0HoR3nL/nRgqtKgnTUYflzCx0h9hLs3THoXKciszsy+xtXzax5o5ZhlqzQi/khqHvxk4/NE\nxMWk/tyjhnhNVScBH5T0hjwW4XDgyoYWn0Hl1/8z4EhJS+TXuExlzMacPEjqyhnwV2C60oCn+fPn\n+HpJ6+bppwAHSVpY0rLAPo0P2OAPzBy83Ez9p5AGUa6eVwpTBnmYt5FaTWYzzOd9M3Ar8OPcIjEv\ncAGpCfzpyvybkJoy98h/j5I0sPW1F6l17g2Vy47AO5QGHw/m68A+DSu4AXuTmp2fHWTay3L4vRw4\nIn+v1iKNVRnpCPgTgXdK2mrge6o0WLm6shqqBeZhUlCrDvQ+mrQr9Brw8oC1nfK0P5B20Xu30h5c\nn2HWlVujPwJra9aBlAI+lZeLRUndVYMdd2BB0vf+EWAuSR8ktYAM+D/g85LWVrKSZt3NeTqpC2wT\nSUe8/ORpPbY2afkYzCtJy8xT+T0cye6xA+/vSJbvweYbcBLwJaWBjouTxk6N5JgVc5rvYlKQGxjU\n2E9qqW4c5DinWquv87NKg6cXJnVljHTjtI5aAYiIu4GrgUMkzaM0KHS7yl1G+90ZriVzIuk35xGl\nwcRfIbW0Daiua5fJr2m492ywde2Skj6TX8tOwGr5fo3+Rlrul1MaQH3QwISIuB84H/iupIn5d3vF\nvG4c8LYhHvdl4xFALiY1u/y5ctul+bbGpq4vk5rgDiSt/J8lrTgg/eCdAzxF2mPkWSq7ITaKiMci\n4qF8eZC0tfF4pRXm06SVwAOkPtXhdv3dlTRY575K09tBpJBxbETc2/BcPwTel8NTMPsC8C1S68y8\njdMj4k8RMdAkNdi8A/e7ML9fvyGFq9fkOl++y2CzVf4/kBSErlRqAr6AWbcih1tojwHWyE1rp+dA\nsB0p6N1B+sH5KTO/GIeQmvHuJHU5HD+Hx/8pqWuhWkvj/YesPyLOBY4k9SH/i9Q18vL8SnsLrc7Q\nu20O9nl/ofI6FyZtOdwLvAVYh/QD+NXcsnUc8KmIuD8i/pzfr2OVBpQuRwrBD1UuZ+XXMvD5zfJa\nI+L3pOW0OoBrYNodEXFtw3s1lN1IW4X3kQL4VyINShyYr3Hel2+LiHtJg5oPJrUgTiNtMarh/oPN\n+wypReiyvMysFxG/JY1rODl/fi/vBRYRj5AGYH6dFAxWYtb1R+N78CDps67uvRKkfvjzSZ/VraQx\nGbPUGhE3Ad8htco+QAofLz9XRJyWa/8Vad1zOmnwX/X5nySNKdpG0iH55neSNpCq3QtVh5ACypOk\ngci/YfjPrvp+Drt8DzdvdhjpB/OGfLmaQd6bQcxpvotJ69SB9folpIBXXc831jLkMkfayDg/P9c1\npC7qlxq6hocyHrUOVfNg3kcaZvAYKewc9/LMY/juDDL93Hz5F6ll9Flm7YI7lLReupP03p1KGhs4\nlMHWtVeSNqoeJo1D3DEiZutKzBvTvya9v1eRluNq3XuSNtJuIr0vpzLrhsSuwP8OUxtKLc1m9ZL0\nS+CUaMHByJR2kb0tIo4e78e2MiStDhwXEeuVrgVA0pWkwXo3zfHONiKStiENxF2hdC2dQtInSIPo\nNx3mPi1b1w7znO8E3h8Ruw57PwcQMzOrW+7G2oy0Jb8UqZXo8oj4XNHC2pikVzFzN96VSYPhj4qI\nHxQtrEkOIGZmVjulQf4Xk8YgPEv6Mf3scIMWe10en/R7UhfyE6SxMAdFxItFC2uSA4iZmZnVrmfO\nhmtmZmbtwwHEzMzMaucAYmZmZrVzADEzM7PaOYCYmZlZ7RxAzMzMrHYOIGZmZlY7BxAzMzOrnQOI\nmZmZ1c4BxMzMzGrnAGJmZma1cwAxMzOz2jmAmJmZWe0cQMzMzKx2DiBmZmZWOwcQMzMzq50DiJmZ\nmdXOAcTMzMxq5wBiZmZmtXMAMTMzs9o5gJiZmVntHEDMzMysdg4gZmZmVjsHEDMzM6udA4iZmZnV\nzgHEzMzMaucAYmZmZrVzADEzM7PaOYCYmZlZ7RxAzMzMrHYOIGZmZlY7BxAzMzOrnQOImZmZ1c4B\nxMzMzGrnAGJmZma1cwAxMzOz2jmAmJmZWe0cQMzMzKx2DiBmZmZWOwcQMzMzq50DiJmZmdXOAcTM\nzMxq5wBiZmZmtXMAMTMzs9o5gJiZmVntHEDMzMysdg4gZmZmVjsHEDMzM6udA4iZmZnVzgHEzMzM\naucAYmZmZrVzADEzM7PaOYCYmZlZ7RxAzMzMrHYOIGZmZlY7BxAzMzOrnQOImZmZ1c4BxMzMzGrn\nAGJmZma1cwAxMzOz2jmAmJmZWe0cQMzMzKx2DiBmZmZWOwcQMzMzq50DiJmZmdVuQukCzKwzSJoP\nmBeYJ19eCSwG3Ae8BPwXeB54NiJeKlWnmXUGRUTpGsysAEnzA8sDk/NlqXxZMl8WAyYCk/LfIAWM\nF/NlifxQ/wbmJoWT+YD5gWeB6cBTwJPAw8BDwIP577+Bu4G7gAfDKyKznuMAYtbFJAnYiBQiVgdW\ny39XBBYB7iWFgGnA/aRwMHB5lBQgngKmR8Tzgzx+RIQabpsLWJCZ4WVhUlgZCDZLAcsAK5CCz0RS\nGPkncAtwM6lV5caIuH883gczaz8OIGZdIoeNlYD1gLXz5U2kENAP3Ej6cb8FuBW4PyJmjPE5Zwsg\nTTzGgqQwsiopHK0ObE5qgbkTuA64FrgG+GtETB/L85lZe3AAMetQkiYA6wIbk1o53kLqIvkL6cf6\nunw5C9gvIv7cghrGHECGeNyzgONIYWkgSK2b/94KXJYvF0fEfeP9/GbWeg4gZh0it3CsAmwJbAH0\nkbouLiH/IEfEPYPM9zPg2oj4SQtqalUAuRPYKiJubbh9XlIg2YgUvDYBHgAuAP5ICiRuITHrAA4g\nZm1M0jykH9rt82Ve0o/tBcBFEfHgCB7jM8BqEfHJVtY6XiRNIo0BWWhOe9NImpvUKrJlvrwZuBw4\nEzhzsEBmZu3BAcSszeSt/C2BXYBtgTvIP6jADaPdY0TSssBiEXH9eNfaCnnvnA0j4qIm5p0IbEUK\na9uSBteeBvw6Im4f10LNbEwcQMzaQN6S/zCwDvAe0tiHXwNnRMS9JWvrVHmMzEbAzsBOpAGtfyC1\njFxXsjYzcwAxK0rSZOADwIdIu6YeAfwsIqaVrKvb5DCyKfBd0p5CFwLHAmdHxH9L1mbWq3wodrOa\nSZogaUdJF5D2VlkceBdwPPBkJ4UPSX2laxiJiHgR+BPpvX4LcArwGeBeSd+RtGLJ+sx6kQOIWU0k\nLSHpYFJXwL6kLfBlI2Kf3CVwPLBHyRqb0Fe6gFHYArgnIq6LiOMjoo8URl4ErpR0tqSt84HUzKzF\n/EUzazFJq0k6BvgX8Fpg+4h4a0ScFBHPVe56CbCwpJWLFNr9dgROqN4QEbdFxIGkQ9KfTuoCu1nS\nRyW9okCNZj3DY0DMWkTSBsCBpK3sHwE/johH5jDPpIh4qo76mpW7Xfry1SnAIfn//ojoL1DSiOS9\ni+aOiGeHuY9IxxY5gHS8ke8DP4mIJ+up0qx3OICYjTNJGwOHklo7vg0cGxHPlK2qNSRNjYippeto\nBUlrkoLIO4AfA9+JiCfKVmXWPdwFYzZOJK0v6TxSM/8JwMoR8cNuDR/dLiJujIg9SIeAfzVwq6Qv\n5wOlmdkYOYCYjZGkNfK5S04FfgOsGhE/j4gXCpdWh/7SBbRaRNwZEXuTutJWAW6T9DlJ8xUuzayj\nOYCYNUnSqyQdTfoRvojU4vHTXjquRDuP+RhvEXFrbhHpIx1T5GZJO+dxI2Y2Sg4gZqMk6RWSfg/c\nBDxNOs/K9yLi+cKlWQ0i4qaIeCfpyLVfAO6U9N7CZZl1HA9CNRsFSdsARwHPAQ9ExBaFS7KC8kDV\ny0hB9GzgoDnt6WRmiVtAzEZA0mRJZwA/APYhnbNlBUlbla3MSsldL98FvgisRgohN0n6uA9mZjZn\n/pKYDUPSXJL2Aa4GrgXWjIhzcnfLfsCRkuYpWqSVsj1p75ifRMSTEbEv6WiruwOXSlq9aHVmbW5C\n6QLM2lX+Afk/YAawcUT8s+EuZwJLkr5HvbDHi83qPuDD+TwzAETEDZI2AT5BCiHfBb7VI3tEmY2K\nx4CYNZA0N/D5fJkCHB0RM8pW1Z4k9fXSnjCjkc90fDTwKmDPiLixcElmbcVdMGYVklYgnTV1G2Dd\niPixw8ew+koX0K4i4m7SUVSPAi6S9D8eG2I2k78MZqQBhZL2AK4CzgI2zz8gZk2L5FhgfeC9wPmS\nli1clllb8BgQ63mSXgn8hHTysS0i4vrCJbW1xpPRVY7D1dYnoyspIu6Q9DbSyQmvlrR3RPy+dF1m\nJXkMiPU0Sa8nHUL9cmAfn7dldLr5ZHStImkj4KR8+ZIHqFqvcheM9SxJe5HGexwREXs7fFgdIuIy\nUmvbWsCf3CVjvcoBxHqOpHkk/RA4CHhbRBxfuqYO1l+6gE6Uj5a6LfAH4C+5VcSsp7gLxnqKpCVI\nXS7/Ad4fEU8WLsl6nKR3AL8AvhgRPytcjllt3AJiPUPSzsDfSefu2MHhw9pBRPwB2Bj4nKQ/S5q/\ndE1mdXAAsZ4gaWvSQaFeAZwaES8VLsms6lbgSmAV4HRJEwvXY9ZyDiDW9SR9hNTEPXAK9TMlLV20\nKLNZ7Us6weEqwDTSYdyXKVuSWWv5OCDWtfLZSg8DdgbeGhG35ttXB07OhxH3ICgrStJbgP2BDSPi\nCUkfBw4ArpC0rQ/hbt3Kg1CtK+XzufwEeCOwbUQ8XJkmYJVBTi5nVjtJE4AVIuK2htt3A44kjVe6\nskhxZi3kAGJdR9K8wInAYsC7ImJ64ZLMmiJpG+A44H0R8cfS9ZiNJ48Bsa4iaQHgTGAeUsuHw0cL\n5cOyW4tExDnAjsCvJL2ndD1m48kBxLpGDh9nAQ8DO0XEc4VL6gV9pQvodhFxKfB24MeSdipdj9l4\n8SBU6wqV8PFv4IPezda6SURcJ+ntwHmSiIhTS9dkNlYOINbxHD7q5bPhlhER1zuEWDdxALGOJmk+\n4AzgPhw+apFDRj9A/iGcWrKeXtIQQp6LiLNK12TWLI8BsY6Vd7U9EXgahw/rERFxPemgesd4ELB1\nMgcQ60j5WB7/CyxC2kXxxcIl9ar+0gX0ooi4CtgFOEXSuqXrMWuGjwNiHUnS10njELaIiP8ULses\nCEk7kM5x9LaI+FfpesxGw2NArOPkQ1W/h3ToaocP61kR8TtJiwN/kLRh9Yi/Zu3OLSDWUSS9AziG\ndG6X2+Z0f7NeIOkwYHNgs4h4tnQ9ZiPhAGIdQ9IuwI+B7SLiitL1mLWLPCbqRGAyqTvGA7Kt7XkQ\nqnUESUuRwocAp2azWc0NPAGsDXyzcC1mI+IAYm0vn1zuNOBHwF7AmflMoWY9T9JCwNnAysAbgPdK\n2rFsVWZz5i4Ya3uSjgaWBt4dETMkrQn8Gtg8Iu4vW51ZWZK+BiwE7BsRL0paBziX9P24oWx1ZkNz\nALG2JukjwP8AG0TEU5Xb53Y/d3mS+nz49bIG+y5Ieh9wGLBORDxepjKz4bkLxtqWpDcChwPvqYYP\nAIePttFXuoBeN9h3ISJ+ReqW+bkqJ+sxaycOINaWJE0CTgU+GxG3lK7HrAPtD7wa2Ld0IWaD8YHI\nrO3kLbafARflLTlrIz4bbmeIiOfzrut/kXRFRFxZuiazKgcQa0d7A6sBG5QuxGbns+F2joi4U9JH\ngZMkvaGxK9OsJHfBWFuRtBJwBOkEcz6io9kYRcRvgfOBH5SuxazKAcTahqQJwAnAYRHxj9L12Ij0\nly7ARmQ/YCNJ7y1diNkA74ZrbUPSl4FNgLdHxIzS9Zh1E0nrA2cCb4qI+0rXY+YAYm1B0lrAhaSV\n472l6zFRxiRUAAAdWUlEQVTrRpIOAd4E7BBe+Vth7oKx4nLXyzHAQQ4fZi11OPBaYOfShZg5gFg7\n2Bd4ihRCzKxFIuJ50l5mR0pavHQ91tvcBWNFSVoR+AuwXkTcUboes14g6TvAUhGxe+larHc5gFgx\n+YBjvycdwMqnEDeriaQFgX8AH4yIP5Wux3qTu2CspB2AFYAjC9dh1lMi4mnSSR5/JGme0vVYb3IA\nsSIkLUAKHp+OiP+WrsesB/0WuBv4bOlCrDe5C8aKkHQesCDwVu8O2Lkk9fn8L50rHxukH9goIq4t\nXI71GLeAWO0kLUc6z8siwMWS3lS4JGteX+kCbPQkzStpP9IYrBvxGXOtAAcQK+Ew4ChgLeBE4BxJ\n7yxbkllPuQDYDNgI2BJ4ez4YoFlt3AVjtZK0Nmmra5WImJ5vWxh43ief6wyS+pjZ8jEFOCT/3+/u\nmM4gaemIuL9yfR9g24jYumBZ1mMcQKxWki4ETo2Io0vXYmMnaWpETC1dh42NpHmBv5MGhZ9fuh7r\nDe6CsdpI2hRYHh/x1Kyt5D3RvgR8LR+fx6zlHECsFnml9lXgkIh4oXQ9Nm76Sxdg4+Y0YD5gu9KF\nWG9wF4zVQtJWwPeB10fES6XrMbPZSXo38BVgnYiYUboe625uAbGWy60fhwJTHT7M2tpvgQDeVboQ\n634OIFaHTYGFgVNLF2JmQ8sHBTwUONhjQazVHECsDl8AvuEmXbOOcCbpKMWblS7EupsDiLVUPu7H\nGsAvS9diZnOWNxS+CRxYuhbrbg4g1moHAN/zCefMOsovgTUkrVO6EOte3gvGWkbS8sDfgMkDRz01\ns84gaX9gzYjYs3Qt1p0cQKxlJB0OLBgRPt23WYeRtChwO7BqRDxUuh7rPu6CsZaQ9Argw8CPStdi\nrZPPC2NdKCIeIx2c7KOla7Hu5ABirbILcG1E/Kt0IdZSfaULsJY6Cvi4pHlKF2LdxwHEWuUTuPXD\nrKNFxA3Anfjw7NYCE0oXYN1H0utIJ507p3QtNv5yt0tfvjqlcryq/ojoL1CStdb/AR8CzihdiHUX\nD0K1cSfp28ALEXFQ6VqstSRNjYippeuw1pG0IHAv8LqIuK90PdY93AVj4yoPPt0DOLZ0LWY2dhHx\nNGkw6l6la7Hu4gBi4+0LwCRgD0krly7GWq6/dAHWOpLmlbQDsCLwFZ8fxsaTA4iNt9WA75BCyJ8l\n/dkj6LuXx3x0L0nvAf4N7AecBDwIvLFoUdZVPAbExk3uK74PWDEiHsnBY52IuLJwaWY2SpKWAeaN\niDvz9cOBuSPC54ixceEAYuNG0q7AXhGxTelazGx8SVoLOAtYIfzDYePAXTA2nnYFTi5dhJm1xI3A\n08AGpQux7uAAYuMid79sBpxZuhYzG3+51eM04N2la7Hu4ABi42UL4KqIeLx0IWbWMmcC25cuwrqD\nA4iNl+1x64dZt7sWmChp1dKFWOdzALExkzQ38E7SADUz61IRMQO3gtg4cQCx8bAO8HBE3FG6EDNr\nubOBbUsXYZ3PAcTGw5bA+aWLsPrlE9NZb7kYWCcPPDdrmgOIjYctgD+WLsKK6CtdgNUrIv5DGgvy\n1tK1WGdzALExyVtBbyZtFZlZb7iA1PJp1rQJpQuwjrcxcG3eKrIekLtd+vLVKZXzk/X73DA944/A\n/5YuwjqbA4iN1VuBS0oXYfXJIaMfQBIRMbVkPVbENcBrJS0cEU+ULsY6k7tgbKw2Ai4rXYSZ1Sci\nXgCuxodltzFwALGm5bPdrgtcUboWK6a/dAFWzGWkDRCzpjiA2Fi8EbjLTbC9y2M+etplpDFgZk1x\nALGxWB+4snQRZlbElcC6kvw7Yk3xgmNj8SbSYDQz6zH5xJMPAyuVrsU6kwOIjcXapAMSmVlvuo60\nHjAbNQcQa4qk+YBVgRtL12JmxVyLA4g1SRFRugbrQJLeB/wCOIcUQm4EzvOAVLPuJmltYENgTWAT\nYPGIWLJsVdaJ3AJizZqbdDjmE4CXgF0Ar4TMut87gLWAfwCHAC+WLcc6lVtArCmSDgNe9FEwzXpX\n3gNmOrB0RDxVuh7rLG4BsWatDtxcuggzKyciZgD/BFYrXYt1HgcQa9ZqwC2li7Cy8onprLfdjAOI\nNcEBxEYtN7uuCNxauhYrrq90AVbcv4CVSxdhnccBxJqxFPBURDxTuhAzK+5uYHLpIqzzTChdgHWk\nFYC7CtdgheRul758dYqkgUn9PjdMT7qLtE4wGxUHEGvGZNJWj/WgHDL6ASThPaF6nltArCnugrFm\nLI8DiJkl9wKvkuQNWhsVBxBrxtLA/aWLsLbQX7oAKysiXgCeABYvXYt1FgcQa8aSwEOli7DyPObD\nsofwkZBtlBxArBlLAg+WLsLM2sZDpL3jzEbMAcSa4RYQM6t6ELeA2Cg5gFgzFgceKV2EmbWNR/AY\nEBslBxBrxiTAJ54yswHTgYmli7DO4gBio5IPw74A8J/StZhZ25hO2jAxGzEHEButVwLP5LNgmplB\nahF1C4iNigOIjdZE0taOmdkAd8HYqDmA2GjNBzxfugirQepuMxuJ50nrBrMR8wrGRmsC8MJoZsgn\nLxuVZuYpMV/Jecd7fokJEkJ6HdL1wAtItyFtWMfz99r87b6Mj/L+LwDzjObxzRxAbLTmAV4c5Tx9\nTTxPM/OUmK/kvOMyv8REidOBZyCeOpyDLgV+QNqi3Q/4LdJirXr+Hp6/2Xnrmm80938Bn9zURskB\nxEZr1C0g1va+DzwNLHQIU3b4KR99pYgHiXiRiN8B/wLWKluitbkXcQuIjZITq43W3MBakqJ6Y0So\nej033/blq1Oklyf3D3X+kGbmKTFfyXlbMT8c+AScciLctf5X4Ia5mDHje/zPNrDY2UiTgNdSOfJt\nu9XfSfO3+zLexP2j8TazEYsIX3wZ8YW0JXzjKOeZ2sTzjHqeEvOVnHe85oe4HGKXdD30Rq694VC+\n9GjA0QE3B3y/nevv1PnbfRkfzf2BbYBzx/Je+tJ7F7eA2Gi5r7f77AecKfEOYJm/8aYXTmCP3YCV\ngTOA84tWZ51gHtw1a6PkHxIbrWb6evubeJ5m5ikxX8l5x2X+CK6QWA/YnHSE29+9Pv7+LCMLHmN+\n/h6ev9l565pvNPf32DAbNUW4C89GTtJrSP3Bk0vXYmbtQdIuwI4RsXPpWqxzeC8YG61ngPlLF2Fm\nbWUB0rrBbMQcQGy0fMhlM2vkUzTYqDmA2Gg9C8wjyfv8m9mASTiA2Cg5gNioRBo05FYQM6uaSDoj\nrtmIOYBYM54EFipdhJm1jYVwALFRcgCxZjwMLFG6CDNrG0uQ1gtmI+YAYs14EFiqdBFm1jaWJK0X\nzEbMAcSa8RBphWNmBmmD5KE53suswgHEmvEQbgHpOpKWk/QtSf8rabsRztPX4rKsM7gFxEbNAcSa\ncR+wTOkibPxIejVwRb56A/BDSR8awax9LSvKOoKkBYF5gSdK12KdxeeCsWbcDWxVuggbV3sCZ0fE\n/gCSrgaOB44tWpV1gsnAtPB5PWyUHECsGXcBKxSuwcbXfMy6BftEvm02udulL1+dImlgUn9E9Lem\nPGtjK5DWCWaj4gBizbgbmCxJ3urpGqcDF0m6nvT5fgM4abA75pDRDyCJiJhaT4nWpiaTlhmzUXEA\nsVGLiCckvQQsBjxSuh4bu4i4UdKOwBTSYbXPBA4vW5V1iNfgFhBrggOINeufwKo4gHSNiLgE2HyU\ns/W3oBTrLKsCx5UuwjqP94KxZt0CrFa6CCvLYz4MWJ20PjAbFQcQa9bNpBUPAJImSJq7YD1mVgNJ\n8zX8vzxwW7mKrFO5C8aadR+wp6QlgLVIzbCbAFcXrcrMWu0XeU+oG0nrgUci4r9lS7JO5BYQa9ad\nwLLApcDHgCUiwuHDrPu9D1gfOJJ0ALJHy5ZjncotINasy4AAfhsRHohq1iPyrvfTgGm5JeQfZSuy\nTuUWEGtKRMwArgPeVLoWMytmbeDa0kVYZ3IAsbG4lrQCMrMeo3QI3DfhAGJNcgCxsbgWWLd0EWZW\nxGTg+YjwWXCtKQ4gNhZXAhuqcjIQM+sZb2HmGZTNRs0BxMbidmAe0nEAzKy3bEQajG7WFAcQa1oe\nDX8ZaUVkPSjvBWG9yQHExsQBxMbqMmDj0kVYMX2lC7D6SZoErETaE86sKQ4gNlYX4x8hs16zCfBX\nHwHVxsIHIrOxug5YStKyEXFv6WKs9XK3S1++OqUyBrnfJ6frGVsCF5QuwjqbA4iNSUS8JOki0mnc\nfUruHpBDRj+AJCJiasl6rIgtgL1KF2GdzV0wNh4uIG0RmVmXk7QM8Co8/sPGyAHExsMFwJaSvDz1\nnv7SBVjttgIujIiXShdinc0/GDZmEXEn8DCwXularF4e89GTtgfOKl2EdT4HEBsvZ5JWTGbWpSTN\nD2wG/KF0Ldb5HEBsvPwOBxCzbrcZcF1EPFq6EOt8DiA2Xq4CFpO0UulCzKxldsDdLzZOHEBsXETE\nDOB0YKfStZjZ+JM0D/Bu4Dela7Hu4ABi4+lkYNfSRZhZS2wO3BoRd5UuxLqDA4iNp8tI3TBrKHmL\npENUOVSmmXUGSRtJ2kfSEvmm3UgbGWbjwgHExk3uhjkb+AlwK3AM8Bw+4q5ZJ3oG2AC4VdLZwI7A\nqWVLsm7iAGLj7WLgjaStpTUi4oiIeKFwTdYi+bww1oUi4rqIeD+wHHA38EhE3F+4LOsiDiA23k4G\n7gImRkQUrsVar690AdZaETEdWBE4uHQt1l0cQGxc5dBxLPCh0rWY2dhJWh54M3BG6Vqsu7hv3lrh\nROAQSQtHxBOli7Hxlbtd+vLVKZUxxv0+NHtX2gs4OSKeLV2IdRe5ldxaQdKvgT9HxFGla7HWkTQ1\nIqaWrsNaQ9LcwO3AjhFxTel6rLu4C8Za5cfAp7wLrllH2w54wOHDWsEBxFrlEuC/wBalC7GW6i9d\ngLXUPoBbMa0l3AVjLSPpo8B2EeGT1Jl1GEmrA38CJkfE86Xrse7jAGItI2lB0vED1o+I20vXY2Yj\nJ+knwMMR8ZXStVh3cgCxlpL0NWCRiPhk6VrMbGQkLQXcDKweEQ+Wrse6kwOItZRXZGadJ284LBoR\nnyhdi3UvBxBrOUk/Bh6PiC+WrsXMhidpEnAH7jq1FnMAsZaT9Frgr8CKEfFk6XrMbGiS9gfWjYhd\nStdi3c0BxGoh6Tjg9og4tHQtZjY4Sa8EbgO2jIgbS9dj3c0BxGohaSXgSmDliHi8dD1mNjtJXwDe\nGBG7lq7Fup8DiNVG0v8B90fEl0vXYmazymM/bgPeFhE3l67Hup+PhGp1Ogz4pKQlShdi4yOfmM66\nw2eB8xw+rC4OIFabiLgL+CXgFpDu0Ve6ABu7vLv8vsDUwqVYD3EAsbodCuwmaZWBGyS9XdLkgjWZ\n9RRJO0pavHLTVOA473ZrdZpQugDrLRHxiKRvAV+XdCDwXWA1YHfSYdutzeVul758dUrlhMf9EdFf\noCQbvQ2BoyUdRjrfy3uBVcuWZL3Gg1CtdpJeAdxHaoH7GvADn+yqM0maGhFTS9dhoydpDeB7wFtI\n30EfKNBq5S4Yq11EPAd8mxRCvufwYVa/iLgJOAp4Avh64XKsBzmAWClHkALIp0oXYmPSX7oAa46k\n+YHvA3tHxPTS9VjvcReMFSNpNeBSYM2IeKB0PWa9RNIU0nfvvaVrsd7kAGJFSfo6sFxEvL90LWa9\nQtKKwF+AtSNiWul6rDc5gFhRkhYEbgQ+HRF/KF2PWbdT2m3pIuDsiPhO6Xqsd3kMiBUVEU8DHyHt\nEjipdD1mPeDDwALAkaULsd7mFhBrC/k8Mf+NiE+WrsWsW0laFrgO2DQi/l66HuttDiDWFiQtDPwd\n2CMi/lS6HrNuk7tezgau8rFbrB24C8baQkQ8QeqKOS6HETMbXx8DlgIOL12IGbgFxNqMpB8BC3uv\nGLPxI2lV4DJg44i4pXQ9ZuAWEGs/+wPrSNq1dCE2Z/m8MNbGJM0DnAhMcfiwduIAYm0lIp4B3g/8\nQNJrS9djc9RXugCbo8OAh4Efly7ErMoBxNpORFxDOkndKZLmK12PWaeStB2wG7BnuL/d2ozHgFhb\nyiP2TwPuj4hPl67HZsrdLn356hTgkPx/f0T0FyjJBiFpeeAq4D0RcVnpeswaOYBY28p7w1wDHBwR\nvy5dj81O0lTv0tl+JM0LXAycERHfLF2P2WDcBWNtK++auxPwQ0lrVadJel1uJTHraZKWG+Qowj8A\nHgK+XaAksxFxALG2FhHXAp8FfitpMSX7AH8EXlW2OgP6Sxdg7AFcLuk1AJI+DmxCOqjfjKKVmQ3D\nXTDWESR9E1gX+BewMfDOiLizbFVm5eWWwH2Ag4BDSWNyNoqIW4sWZjYHDiDWESTNDfwTmACsFRFP\nFS7JrK1I2gs4Ftg9Ik4qXY/ZnLgLxjpCRLxEalaeTjpku5llkhYltYAc4PBhncItINZR8q6FlwP7\nRsRppesxKy0fK+d84OqI2K90PWYj5QBiHUfS2sB5wA4RcXnpesxKkTQXcAIwH7CzB51aJ3EXjHWc\nvGfMnsAZjbvnmvWKPPj0SGAy3uPFOpADiHWkiDiHtHvuOZJWKl2PWQFTgbcC20XEs4VrMRs1BxDr\nWBFxMmm3wwskLVO6nl7ks+GWIWlf0jlets4H7DPrOA4g1tEi4n+Bo4ELJS1dup4e1Fe6gF4j6RPA\n/wBbRMSDpesxa9aE0gWYjVVEfEPSBOBPkjaNiPtL12TWCjl8fAHYNCKmla7HbCwcQKwrRMTX8qlh\nHEJarPFsuJVT8vhsuC3UED7uKF2P2Vg5gFjXyCEkgIslbeEtxNbIIaMfQBI+G27rSfos8DkcPqyL\nOIBYV4mIwyU9A1wqaauI+GfpmsyalXe1nQK8D9gkIu4uXJLZuHEAsa4TEUdKehLol7RtPm6ItUZ/\n6QK6VT7I2JGkUxC81QNOrdt4LxjrShHxc+BTwLmSNq9Ok7SwpE+rMnjBmuMxH2MnabKk3Rtumxc4\nDlgb6HP4sG7kAGJdKyJOB3YGfpXPFEreW+YUYKXweQisfXxD0jsAJC1COtXAK4GtfJwP61Y+F4x1\nPUlrAL8HfgEsCbwWeGdEvFiyLrMBkjYAzgR2J3W7nAd8Pp8F2qwrOYBYT5D0KuAyYDFgVTdpW7uR\nNAX4MrB/RHyvdD1mreYuGOsJEfEAsB5p0OTZkpYtW5HZTJI+TBqz9AmHD+sVbgGxnpIHnh4AfAbY\nKSIuL1yS9TBJ8wDfA7YAdvBu49ZL3AJiPSWSbwAfBs6QtI/3hrES8gkULwRWANZ3+LBe4wBiPSki\nzgHeAnwAOEXSQmUr6kw+G25zJL0duJo02HT7iHiycElmtXMAsZ4VEbcDGwEPAddIWrtwSZ2or3QB\nnUTSBEmHAccAu0bE1yJiRum6zEpwALGeFhHPRcSngINJBy07QNLcpeuy7iNpReAS0mDodSLi4sIl\nmRXlQahmmaTJwPFAAHv5vBuDazwbLnBI/t9nwx1EHmP0QeAbwGHAUW71MHMAMZtFbv3YD/g8sD9w\nvI+YOjRJU3023KHl48/8BHgNsHtE/L1wSWZtw10wZhUR8VJEfBPYCtgXOCe3jJiNmJK9gOuBm0l7\nuTh8mFU4gJgNIiL+Ruqrvxi4Op+8bpbvi6T5JZ0laWKRIttDf+kCSpG0u6RPDXL7ZOAcUoDdOiIO\njojnay/QrM05gJgNISJeiIgjgLcCuwKXS1qncpfPAc9HxPQiBbaBHh/zcTUwVdKSkM5gK+kLwDWk\n4LpeRFxXskCzduYxIGYjkFs/9gKOAE4HfkTao+HNEXFHydqsHElHAvMDpwI/BG4DPpt38TazYTiA\nmI1CPlX6YcCHSN0PPqtuD5P0JuAK4FHg4xFxVuGSzDqGu2DMRiEiHs/HDfkgsABwo6TtfDj33iJp\nUUnfBf4IHAus6fBhNjoOIGZNiIiTScfC+DzwTeBCSesVLcpaTtICkj4P/JPU9bJGRHwyIh4rXJpZ\nx3EAMWtSPrHd74G1gJOB3+S9YnrmkO69ci4YSa+QtA9pjMdbgLdFxCci4sHCpZl1LAcQszGKiBcj\n4qfAyqSTi50l6YweCSJ9pQtopbyr9SeAW4EtgW0j4j0RcVPh0sw6ngOI2TjJ55X5IbASaTfM30k6\nX9JmHiPSWSQtLOlg4A7gHcCOEbG9d6s1Gz/eC8asRSTNC7wfOAD4D/Bt4PSIeGGYebYGrmjn07N3\n6rlgJK0PPBgRdw1zn8nAp0l7OZ0NfMtHMDVrDQcQsxbLxxDZHvgssApwNPCziHig4X4LAv8GVomI\nh2ovtAmddC4YSd8AiIgDG24XsBmwD7AxcBzw/YiYVnuRZj3EXTBmLRYRMyLitxGxKbA1sCxws6ST\nJG1eOcT7u4HLOiV8dKATgPfnEw4iaQlJ+wL/AI4E/gBMjoj9HD7MWs8tIGYF5AOa7Q7sDSwE/BzY\nAvhx3sW3I0jqa+dul0aSriUdtXQd0vt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