{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "import matplotlib\n", "import matplotlib.pyplot as plt\n", "import pyerrors as pe" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "plt.style.use('./base_style.mplstyle')\n", "import shutil\n", "usetex = shutil.which('latex') != ''\n", "plt.rc('text', usetex=usetex)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Read data from the pcac example" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Data has been written using pyerrors 2.0.0.\n", "Format version 0.1\n", "Written by fjosw on 2022-01-06 11:27:34 +0100 on host XPS139305, Linux-5.11.0-44-generic-x86_64-with-glibc2.29\n", "\n", "Description: SF correlation function f_P on a test ensemble\n" ] } ], "source": [ "fP = pe.Corr(pe.input.json.load_json(\"./data/f_P\"), padding=[1, 1])\n", "fP.gamma_method()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can now define a custom fit function, in this case a single exponential. __Here we need to use the autograd wrapped version of numpy__ (imported as anp) to use automatic differentiation." ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "import autograd.numpy as anp\n", "def func_exp(a, x):\n", " y = a[1] * anp.exp(-a[0] * x)\n", " return y" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Fit single exponential to f_P. The kwarg `resplot` generates a figure which visualizes the fit with residuals." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Fit with 2 parameters\n", "Method: Levenberg-Marquardt\n", "`xtol` termination condition is satisfied.\n", "chisquare/d.o.f.: 0.0023324250917749687\n", "\n", " Goodness of fit:\n", "χ²/d.o.f. = 0.002332\n", "p-value = 1.0000\n", "Fit parameters:\n", "0\t 0.2036(92)\n", "1\t 16.3(1.3)\n", "\n" ] }, { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "start_fit = 9\n", "stop_fit = 18\n", "\n", "fit_result = fP.fit(func_exp, [start_fit, stop_fit], resplot=True)\n", "fit_result.gamma_method()\n", "print(\"\\n\", fit_result)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The covariance of the two fit parameters can be computed in the following way" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Covariance: 0.009831165592706342\n", "Normalized covariance: 0.8384671239654656\n" ] } ], "source": [ "cov_01 = pe.fits.covariance([fit_result[0], fit_result[1]])[0, 1]\n", "print('Covariance: ', cov_01)\n", "print('Normalized covariance: ', cov_01 / fit_result[0].dvalue / fit_result[1].dvalue)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Effective mass" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Calculate the effective mass for comparison" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "m_eff_fP = fP.m_eff()\n", "m_eff_fP.tag = r\"Effective mass of f_P\"" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Calculate the corresponding plateau and compare the two results" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Fit with 1 parameters\n", "Method: Levenberg-Marquardt\n", "`ftol` termination condition is satisfied.\n", "chisquare/d.o.f.: 0.13241808096937788\n", "\n", "Effective mass:\t 0.2057(68)\n", "Fitted mass:\t 0.2036(92)\n" ] } ], "source": [ "m_eff_fP.gamma_method()\n", "m_eff_plateau = m_eff_fP.plateau([start_fit, stop_fit])\n", "m_eff_plateau.gamma_method()\n", "print()\n", "print('Effective mass:\\t', m_eff_plateau)\n", "print('Fitted mass:\\t', fit_result[0])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can now visualize the effective mass compared to the result of the fit" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "m_eff_fP.show(plateau=fit_result[0])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Fitting with x-errors" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We first generate pseudo data" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(Obs[0.53(35)], Obs[0.38(25)])\n", "(Obs[1.73(35)], Obs[0.59(25)])\n", "(Obs[3.92(35)], Obs[-1.23(25)])\n", "(Obs[5.73(35)], Obs[-1.18(25)])\n", "(Obs[7.74(35)], Obs[-0.40(25)])\n" ] } ], "source": [ "ox = []\n", "oy = []\n", "for i in range(0,10,2):\n", " ox.append(pe.pseudo_Obs(i + 0.35 * np.random.normal(), 0.35, str(i)))\n", " oy.append(pe.pseudo_Obs(np.sin(i) + 0.25 * np.random.normal() - 0.2 * i + 0.17, 0.25, str(i)))\n", "\n", "[o.gamma_method() for o in ox + oy]\n", "[print(o) for o in zip(ox, oy)];" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "And choose a function to fit" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [], "source": [ "def func(a, x):\n", " y = a[0] + a[1] * x + a[2] * anp.sin(x)\n", " return y" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can then fit this function to the data and get the fit parameter as Obs with the function `odr_fit` which uses orthogonal distance regression." ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Fit with 3 parameters\n", "Method: ODR\n", "Sum of squares convergence\n", "Residual variance: 0.08780824312692749\n", "Parameter 1 : 0.06(25)\n", "Parameter 2 : -0.160(47)\n", "Parameter 3 : 0.80(18)\n" ] } ], "source": [ "beta = pe.fits.total_least_squares(ox, oy, func)\n", "\n", "for i, item in enumerate(beta):\n", " item.gamma_method()\n", " print('Parameter', i + 1, ':', item)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "For the visulization we determine the value of the fit function in a range of x values" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "x_t = np.arange(min(ox).value - 1, max(ox).value + 1, 0.01)\n", "y_t = func([o.value for o in beta], x_t)\n", "\n", "plt.errorbar([e.value for e in ox], [e.value for e in oy], xerr=[e.dvalue for e in ox], yerr=[e.dvalue for e in oy], marker='D', lw=1, ls='none', zorder=10)\n", "plt.plot(x_t, y_t, '--')\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can also take a look at how much the inidividual ensembles contribute to the uncetainty of the fit parameters" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Parameter 0\n", "\n", "Parameter 1\n", "\n", "Parameter 2\n", "\n" ] }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAiQAAAFdCAYAAAAzNnbkAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8/fFQqAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAzeElEQVR4nO3deXhU9b0/8Pf3JJmwJ4BsgjAsQgKETQTZhF/UW9t0r7a2vW3uba1NTffb6tj21lSvNWrdG41aq2jVyuJWR61gVBZBFAgMEHYGQla2TMiemfn+/phEI2uSWT7nzHm/nmeewEDOefu0DG++21FaaxARERFJMqQDEBEREbGQEBERkTgWEiIiIhLHQkJERETiWEiIiIhIHAsJERERiWMhISIiInEsJERERCSOhYSIiIjEsZAQERGROBYSIiIiEsdCQkREROJYSIiIiEgcCwkRERGJYyEhIiIicSwkREREJI6FhIiIiMSxkBAREZE4FhIiIiISx0JCRERE4lhIiIiISBwLCREREYlLlA5ARGR3SqkbAKQCqAEwFsCdWusawUhEMcdCQmRzTpe7J4BBHV4XnONrKoAkAAkIfX4kAEj8RU2P3Q6ocQCCAAJtrzqE/oI916sCwEEAB3ILM+uj919pXkqpmwA83l5AlFKpAJ4AcK1gLKKYU1pr6QxEFGVOlzsBoX95p7e9JrZ9nQCgb7jX/2VNj91JUOPDvMxRAAcAeNte7T/ehVBhicsPK6XUCq31Ved7jyjecYSEKI44Xe5EfLZwtP/4YgDJgtE644K216Vn+DVfQU7RFgCbO7x25BZm+mOYL1pqlFIrAFyrta5RSo0BsF86FFGscYSEyMKcLncygNkAFgK4HMAcAL1jnSNCIyRd1QxgO0LlZAOAd3MLM/fEOEPY2qZoNgIYA+BuAPu01o+LhiISwEJCZCFOl7sXQqVjYdtrFoAeoqEgVkjOpBTAu22votzCzEPCeTqlbVHrVQCuAbASbaMloqGIYoyFhMjE2qZgFgG4AqECMhOhRaWmYqJCcqr9AIoQKihv5xZmHhXOcxql1F0AVmitV7ZN1ywFkKq1HiscjSimWEiITMbpcichVECuBfAVAANlE52fiQtJRwEAqwAsB/BSbmFmhXAetBWQm7XWPz7l/Y0Ibf1dJpOMKPa4qJXIBNpKyFX4tIT0l00UlxIA/L+218MFOUXrECony3MLMw8KZRqD0PbnUz0W4xxE4jhCQiTE6XI7APwHQusGvoLQGR+WZJERknPZCGAZgOdyCzNLY3njjjtsOrz32KmjJkTxjoWEKMacLvcsAD8B8DUAKcJxIiIOCkm7IIC3EDqY7PVYbCtu22VzC4BjCI2WpKLDQWlEdsFCQhQDbdtzrwOQizOfs2FpcVRIOqoA8DSAv+UWZvJcEKIoYyEhiiKny30RQqMh1yN0/HpcitNC0k4jtFPnCQAv5xZmtgjnIYpLLCREUeB0uTMB/BTAlxFaTBnX4ryQdFQF4EEAj+QWZvqkwxDFExYSoghxuty9AWQjNC0zUThOTNmokLSrBfAogAdyCzMrpcMQxQMWEqIwOV3uHgiVEBdCz2KxHRsWknZNABYDuCe3MHOfdBgiK2MhIeqmtrNDfgTg9wAuFI4jysaFpF0AoW3D+bmFmcXCWYgsiYWEqIucLncCgO8BuBWAUzaNObCQfMYyAL/PLczcLR2EyEpYSIg6yelyKwDfBJAHIE02jbmwkJzGD+DvAP6UW5hZLh2GyApYSIg6welyfwnA7QCmSmcxIxaSs2oAcB9CUzn10mGIzIyFhOgcnC73NACPAJgjHMXUWEjOqwLA/wJ4KrcwMygdhsiMWEiIzqBtC+9tAH4BG5wjEi4Wkk7bAuAnuYWZ66SDEJkNCwnRKZwu9xcBFAAYKZ3FKlhIuiQIoBDALbmFmbXSYYjMgoWEqI3T5b4QwMMAvi6dxWpYSLqlDMBPcwszX5EOQmQGLCRke06X20DoYLP/A9BPOI4lsZCE5RUAudyNQ3bHQkK21rZo9XHE4RN4Y4mFJGy1AG4B8GhuYSY/lMmWWEjIlpwudzJCIyK/Ahetho2FJGLWAvhebmHmAekgRLFmSAcgijWny50G4EMAvwHLCJnLPADFBTlF10kHIYo1jpCQrThd7h8BeABAL+EocYUjJFHxNEKLXnmgGtkCCwnZgtPl7g/gCQDfkM4Sj1hIomY3gG/nFmZukg5CFG0sJBT3nC73pQCWAhglnSVesZBEVQtCC17v54JXimdcQ0Jxzely5wJYA5YRsi4HgHsBvFGQU3SBdBiiaOEICcUlp8vdB6EpGi4OjAGOkMSMF8BXcgszt0oHIYo0jpBQ3HG63BMAfASWEYo/TgBrC3KKviqcgyjiWEgorjhd7gUAPgCQJp2FKEr6AHipIKfo99JBiCKJUzYUN5wu97cALAaQLJ3FbjhlI+YFAD/MLcxslA5CFC6OkFBccLrcv0Xow5llhOzk2wBWFeQUXSgdhChcHCEhS3O63AkAHgJwo3QWO+MIibgKAF/KLczcKB2EqLs4QkKW5XS5ewF4CSwjRMMAFBXkFC2UDkLUXSwkZElOl3swgHcBfFk6C5FJ9APwVkFOUZZ0EKLuYCEhy3G63OMBrAMwSzoLkcn0APByQU7Rt6WDEHUVCwlZitPlnoHQtt4x0lmITCoJwD8KcopypIMQdQULCVmG0+WeAmAFgIHSWYhMzgDwaEFO0c3SQYg6i4WELMHpck8EsBLAAOksRBaSX5BTdKd0CKLOYCEh02tbM/IOgEHSWYgsyFWQU3SHdAii82EhIVNzutxjABQBGCqdhcjCfleQU3STdAiic2EhIdNyutyjECojw6WzEMWBu7jQlcyMhYRMyelyj0CojIySzkIURwoKcoq+Kx2C6ExYSMh0nC73UITWjHBrL1FkGQCeLsgp+op0EKJTsZCQqThd7gsQKiN8LgpRdCQCeLEgp+gK6SBEHbGQkGk4XW4HQs+mmSidhSjOJQN4tSCniKcdk2mwkJCZPApggXQIIpvojVApGSEdhAhgISGTcLrcvwLwA+kcRDYzFKFS0ks6CBELCYlzutxXA7hHOgeRTc0AsLggp0hJByF7YyEhUU6XOw3APwEkSGchsrFrANwqHYLsjYWExDhd7gEA/gUgRToLEeGPBTlF35QOQfbFQkIinC53IoAlAMZJZyEiAIBC6IySS6SDkD2xkJCUBwDwHAQic+mJ0CJXPjuKYo6FhGLO6XL/GECudA4iOqPhAJ7lIleKNRYSiimnyz0ZwIPSOYjonK4EcLN0CLIXFhKKGafLnQzgOYROiSQic7u9IKdotnQIsg8WEoqlOwBMkQ5BRJ2SCOCFgpwi7oKjmGAhoZhwutyZAH4tnYOIumQ0gMekQ5A9sJBQ1Dld7lQAixHaVkhE1vKtgpyiH0qHoPjHQkKxUAiAD/Aisq6HCnKK0qRDUHxjIaGocrrc3wXwLekcRBSWXgCeK8gp4iMeKGpYSChqnC73SAAF0jmIKCJmAPiNdAiKXywkFBVOl9sA8Az4nBqieJJXkFM0XjoExScWEoqWnwFYKB2CiCKqB4AneYorRQMLCUWc0+UeAuA26RxEFGFaHx+z/zWV+V7uj6WjUPxhIaFoyAfQTzoEEUVOr/qKtfM/uCXoPPTveQDuLElL5wP4KKISpQNQfHG63JcByJbOQUSRoYKBw+k7n6kcWv3xvA5vpyL0xO7ronJPpe4CsK/tp8e11suicR8yF6W1ls5AcaJtIeuHAGZKZ6HY+mVNj91JUFzsGE+0DvQ/sWvNlG2PzUwItvQ+y+/6XPrOkrcjdUulVCqAdwBcobWuUUrNALBRa801KzbAERKKpB+AZYTI8oxA866pWx8J9PftPd/C9HtL0tKnpe8sCUTo1ncBeFFrXQMAWutNSqmrInRtMjkWEoqItuPh/yydg4jCoHXjsMr1Gybsfn6eoYOd+fthMoDrEbnn3dwAYKxSagyAMVrrlVrrlRG6NpkcF7VSpNwGYJB0CCLqnqSWk5tmb7i9On3XPxZ2soy0u60kLb1vuPdvKyFA6AC2VAD7lVKPKaWuDPfaZA0cIaGwOV3uDAA3Sucgom7Q+sRor3v76INvzu/mFQYDuAXA78JM0l5IarTWmwBAKXUzgAMA+od5bbIAjpBQJDwMgM+4ILKYXvWVH8z74BZ/GGWk3a9K0tJHRiQU8HH7D9rWkqRylMQeOEJCYXG63F8HT2QlshQVDBxO3/Vs5dCqj+ZG6JI9EDp/6DthXGP/Wd6vwaejJxTHOEJC4fqjdAAi6iStg6kndr1/+Zrf9B9a9VGkd8RdV5KWPqu736y13o9QKTm1fKSiw6gJxS+OkFC3OV3uLwGYKp2DiM7PCLTsnup5pLV/zZ5ojWgqhBa3Xx3GNW4G8C0A7WtIrgGwsn1NCcU3FhIKx/9KByCi89C6aWjVhvVpu/4xv4u7Z7rjcyVp6Zel7yxZ351v1lovU0oNUErd1PbWQK01zyGxCRYS6hany/05AJdK5yCis0tqObl5RvED/Xs3VC6K4W3zEMYoidb68chFISthIaHu+oN0ACI6C61rnAff8IzxvrFA4O5hjZKQfbGQUJc5Xe5FAMLdJkhEUdCzoeqDGcUPXJzcUitRRtr9DsCXBe9PFsRCQt3B0REis9GB8vRdzx8eVrk+Ult5w/HFkrT0jPSdJR7pIGQdLCTUJU6Xew6AK6RzEFEbrYOpvr2rp3gevSQx0NztbbcRphAaJfm2dBCyDp5DQl3F0REikzACLXumbXmoZEbxAwsTA819pPOc4tqStPSLpEOQdXCEhDrN6XLPAPAF6RxEtqd185Dqj9al73x2nqGDSdJxziIBwE8Q/jNuyCY4QkJd8QvpAER2l9RaVzzrozvKJ5UsXmTiMtLu+pK09GTpEGQNHCGhTnG63CkArpHOQWRbWvucB9/aOtr7+nwVWqNhBYMAXAdgsXQQMj8WEuqs7wLoJR2CyI56NlSvm1H8wNjkFp/kVt7u+ilYSKgTWEios66XDkBkOzpQkbbr+dILK9fPkY4Shpklaemz03eWfCgdhMyNhYTOq20x63TpHES2oXUwxbdv9VTPIzNMtJU3HD8DwEJC58RFrdQZHB0hihEj0LJ32ta/br+k+P6FiYHmvtJ5IuTakrT0QdIhyNw4QhIH2p6MWdP201St9d2RurbT5e4F4DuRuh4RnYXWzYOrN66buPOZuYYOOKTjRJgDoc+RB6WDkHmxkFhc+2O625+QqZS6Uin1mNb6xxG6xbUAUiJ0LSI6g8TW+i0zih/o26e+fJF0lij6PlhI6ByU1lo6A4VBKXUCwGitdU2H97TWOiLbAp0u92rwQXp0Hr+s6bE7CWq8dA7L0do36tDbW8cceM1KW3nDkZG+s2SbdAgyJ64hsTCl1BiEpmhqzvBrV4Z7fafLPQEsI0RR0bPxyPq56/7QNPbAawvivYxoQJ/sgS3/WGTwpGc6K07ZWNuYs7xfAyA1Atf/YQSuQUQd6WDlhN3/PDi8Yu1l0lGirSURe9elqbKlC4xx1alqKoDU1xZn3OPJ9nBonk7DQhKfjgMYEM4FnC63Ap/USRQ5Wut+tQdWT9taMC0x0DRbOk60BBQqtznVriULjGF7hqvxAMZ1+OVRAOYA+EAmHZkZC0l8CquMtJkJYEQErkNke0awdV+G57H6gSdKLpfOEg0aqD04GFuXzzN6b5igpmqlhp7jt18HFhI6AxYSa9t/lvdTz/FrnfW1ML+fiLRuGXxk0wcTSxbH3VZeDbQe7YfNr88yAiunq+mtiaqz682+mbE441eebE8gqgHJclhILExrvV8pVaOUGqO13n/Kr60M8/JfDfP7iWwtsbVh6/TiB3r3rS9bJJ0lkuqT4Vk5TdW8dpkx6WQv1Z1TZIcAmAdgVYSjkcWxkFjfnQCuBNB+Dsk17T/urrbdNenhRyOyIa1rR5au3DJ2/ytxs5W3NQEHPpygDi6db4ypGKgyInDJz4OFhE7BQmJxWuu7lVI3tRURALg0AoeifTXM7yeypR6Nxz6cUXz/yB7NJ6z4VN7PCCpU7xipSpbONwaXjFTpAEZH8PJXA7glgtejOMBCEgdOOSp+WQQumRWBaxDZhw5Wjd+z5MCI8tWW3sqrgbrSQdjy0lyjx/o0NS1oqIVRutXUjMUZQz3ZnsooXZ8siIWEPsPpcqcitC2PiM5Ha93vpHf11C0FU5MCjZYsIxrwn+iDYvelRsu/L1HTWpLUvBjcVgH4HIDFMbgXWQQLCZ3qKvD/F0TnpYKt+zO2PXHyguPbLbmVt8GB7e9OUcdemWtM9PVWMwUiXA0WEuqAf/HQqXi0M9G5aN0y6GjxB5N2PD3H0P5k6Thd4Tdw8KPxyrtkgeEsu0BNEo5zVcbiDMOT7QkK5yCTYCGhT7Sdznq1dA4is0r0N3imFz/Us29d6SLpLJ0VBI7uugg7ls43Bm5zGpMQOi3VDAYidADjBukgZA4sJNTRJADnOmGRyJ60PnnR4aLN4/a9PF9Bm/6hpBpoKBuI4lfmGElrJqnpQUOZdVrparCQUBsWEurIkovyiKIpuen4hhmb77+oZ/Nxs/6lDgDQQKCmN4rfnGk0vTVTTW1yqLnSmTrhagC3SYcgc2AhoY7i9oFfRF2mg9Xj9y7dN6Jslal3nTUmoeT9DFX98lwj/URfdYl0ni6albE4o7cn21MvHYTksZBQRxwhIdJa9z15aM20rQ9PSfI3mrKM+A2Ubhqn9i1ZYIw8NFilw7onKycAmA5gjXQQksdCQgAAp8vdF8BE6RxEklTQf2Dy9r/5Bh3zmO6k1SBwfM9wbFs23+i/ZYyRAeAi6UwRcilYSAgsJPSpmQBMv1iPKCq0br3g6Ja1k3c8NcfQ/kgekR4WDTRV9sfmV+YYCasmq+mBBNMuTg3HpdIByBxYSKgd14+QLSX4G7dNL34wuZ9JtvJqIFjbC1v+fYlR756ppjT2UKacNoogFhICwEJCn2IhIXvRum5E2XsbL967fIEZtvI2JWH3mkmqYvlcY/yxFDVdOk8MjctYnNHfk+05IR2EZLGQUDsWErKN5KYTG2YU3zeiZ9PxaD08rlMCCmXFY9XeJQuM4QeGqvEAxkvmETQTwArpECSLhYTgdLlHAhgmnYMo6nTwyMV7l++9qOw9sWkQDfj2DcPWZfOMfpvGqSlQarhUFhO5FCwktsdCQgBHR8gG+p48tHraloczkvwNMS8jGmiuTsXm12Yb6t0papo/UZluF48wriMhFhICAMySDkAULSro907e/mTNoGNbY1oCNKDremLLiunq5L9mGVPqeyqe83N2LCTEQkIArHuoEtHZae0feMyzdvKOJ2cnBP3OWN22ORF71qWr8mXzjXHVqWparO5rccMzFmcM9GR7jkkHITksJAQAY6QDEEVSgr9x+/QtDyf1O3kwJotWAwoVHqfavWSBMWzvcDUewMWxuG+cGQuAhcTGWEhszulyKwBO6RxEEaF13fCy9zeO37ss6lt5NVDrHYKty+cZvT8ar6ZqpbgwPDxjwCf/2hoLCQ0D0FM6BFG4kptrPpqx+b4LezYdi9qoiAZaj/bD5n/NNgLvTFPTWxPV/Gjdy4bGSgcgWSwkxOkasjYdPDJu38t7Rh4umhuVywO6vge2vTNNnXhttjH5ZC/FReDRwUJicywkxEJCltXn5OE107c8NCnJXx/xMtKagP3r09ShpfONsZUDVEakr0+n4WeRzbGQED8EyHJU0H9w0o6njg0+WhzRKZOgQvX2kapk6QJjyM6LVBr45yOWOEJicywkxA9csg6t/QOPb18zefvfZicEW0dF5JJAXekgbHlprtFzfZqaGjSU6HHyNjY8Y3FGsifb0ywdhGSwkBALCVlCgr9px7Stf01IqT2wKNxracB/vC82uy81Wt+eoaa1JKl5EYhI4VEARgPYKR2EZLCQEAsJmZvW9cPLV388fs+S+Qo6IZxL1Sdj27tT1PFX5xgTfb0VTwc1n7FgIbEtFhIbc7rcPQEMlc5BdDaO5pqPZxTfP7RX49FuT6O0GvB+NF4dXLrAcJZdoCZHMh9F3EjpACSHhcTeRiA0TEpkLjp4dOz+V3eNKl3ZramUoMKRnSNQsnSBMXD7KGMSePifVQyQDkByWEjsLVU6ANGpeteVrZm+5cGJjtb6LpURDTSUDUTxy3MNx9qJalrQUJdHKyNFTap0AJLDQmJvfaUDELVTQf+hiSWLjww5sqnTW3k1EKjpjeI3LjWa/n2JmtrkUFE5HI1ipr90AJLDQmJvLCQkT+vAgBMlqzO2PTErIdjSqTUEjQ7seH+yOvrSPCO9po+6JNoRKWZYSGyMhcTe+kkHIHtLCDSXTN3ysErtxFZev4HSjePU/iULjJGlg9XEGMSj2EuVDkByWEjsjSMkJEPrhgsrPvhowu4XzrmVNwgc3zMc25bONwZsHWNMBnBRDFNS7HGExMZYSOyNIyQUc46W2o0zNt83uFfjkTNu5dVAY8UAFL9ymZG4erKaFkjg4lQbYSGxMRYSe+MICcWODh4bc+BfO52H3j5t94wGgrW9sOWtS4yGNy5VUxqT1RyJiCQuVToAyWEhsTeOkFBM9K4vXzu9+ME0R2vdZ8pIUxJ2rZ6kKl+aZ0w41k9Nl8pHppGSsTjD8GR7gtJBKPZYSOyNIyQUVSoYODyxZHHVkCMbPykiAQOHN49Re5cuMEYcGKomAJggGJHMRQHoA6BWOgjFHguJvXGEhKJD60D/EzvXTNn2+KUJwZYRGqjZNwyeZfONlE1jVQaUGiEdkUyLp0fbFAuJvXGEhCLOCDTvnLa1QKf49l1WlYrNr11mqPemqOn+BLVAOhtZgpYOQDJYSOyN//tT5GjdOKxy3fphh1/o985U3fj6rIQL63uqy6RjkeWwkNgU/0Kyt2bpABQf6ozq/YHAUweXZ5ZPOpJqXCidhyyNhcSmWEjsjYWEwjZLleyY4bx3wM2DB2ZAqZ7SecjyWEhsypAOQKJYSCgsSfC3POPIT/pCQ8OsB6uP7oLW9dKZyPJYSGyKhcTeWqQDkLU9nPTQuh6q9WIAyGxonPZo1ZF90JpbNikcPIPEplhI7I0jJNRtM9TunZ8zPv7MQWfzG5umPFlZXQqtfVK5yPI4QmJTLCT2xkJC3ZIIf+tzjj8bSp2+Dm1WU/OkZyuqKpTWxyWykeWxkNgUC4m9sZBQtzyYVLC2p2oZf7Zfn9bckvZ8edUxpfWRWOaiuMApG5tiIbE3FhLqsmlq764vGB+e9oC8U01uabl4SXllraF1VSxyUVxo8GR7/NIhSAYLib2xkFCXJCDgf95xB5RCUmd+f1pL69iXyyqaErQuj3Y2igvHpAOQHBYSe2MhoS65P+mRNb1Uc5cehjem1T/q1cMVwQStD0crF8UNrjuyMRYSe2uSDkDWMUXt2/MlY93c7nzvKL9/hPtwuZGo9cFI56K4whESG2MhsTcuOKROSUDA/4LjDr9ScHT3GsP9gQvfKi3v4dB6fySzUVxhIbExFhJ7K5MOQNZwT9Jja3qrpvRwrzMkEBjy79KyvsnB4J5I5KK4w0JiYywk9sY5fTqvSerA3q8Za7o1VXMmFwSCg1aUlg/sGQzujNQ1KW6wkNgYC4m9cYSEzslAMPCi4/aWcKZqzqR/MDhgRWn50N7B4PZIXpcsj4XExlhIbMybn1UPgEd801nlJz6+uo9qmhiNa6cEg6krDpVd1DcQ3BqN65MlsZDYGAsJcdqGzihdHdx3bcKqOdG8R1+t+60oLRuTGggUR/M+ZBksJDbGQkKctqHTGAgGljhua1IKydG+V2+t+6woLZ8w0B/YGO17kekdkg5AclhIiCMkdJo7Ep9c01c1TorV/Xpo3fPt0rLJQ/z+j2J1TzIdDWCvdAiSw0JCHCGhz5igDh24LuHd2bG+rwNIfqO0fOqFrf4PY31vMoUyT7anUToEyWEhIRYS+oRCMLjEcVudUughcX8H4HAfLr9kVGvrOon7kyieTWNzLCTEKRv6xO2JT61OUQ0ZkhkSgcRXD1fMGtfSslYyB8UcC4nNsZCQVzoAmcPF6rD3uwnvzJLOAQAJQMLysso56c0tq6WzUMywkNgcCwntAp/6a3sKweBSx59qlUJP6SztDMB4sbxy/rSm5lXSWSgmWEhsjoXE5rz5WX4APC3T5m5NfGZNqqqfIp3jVApQz1ZUXT6rsel96SwUdSwkNsdCQgBQLB2A5IxR5QezE96eKZ3jXJ6srF54eUPje9I5KGqCAPZJhyBZLCQEsJDYmNbLHXknlEIv6STnU1B1ZNFV9Q3vSeegqCj1ZHs4dWxzLCQEAJulA5CMPyT+Y3V/VTdNOkdn3Vd9dNGXTta9J52DIm6bdACSx0JCALAFoVMSyUacqqL0hwlvXiKdo6v+fPT4omtrT3JNSXzhCb3EQkKANz/rJID90jkolrRe7sg7qhR6Syfpjj8eO7Hw+77aVdCaRTo+fBypCymlVkTqWhRbLCTUrlg6AMXOLYkvrBmoTk6XzhGO3x6vufxHvto10DoonYXCFpFCopS6BsCVkbgWxR4LCbUrlg5AsTFSVR2+IeF1S5eRdj8/4VvwsxO+D6B1QDoLdVupJ9tTFe5FlFKpAAaEH4eksJBQu2LpABQbLzlurVYKfaRzRMoNvtr5vz1e8yG09ktnoW6J1MMUvwlgSYSuRQJYSKgdd9rYwG8TX1x9gaqdIZ0j0r5fe3LuH46d+Bhat0pnoS4L+5lFSqkrAayMQBYSxEJCAABvflYZuLA1ro1QR8pvTHh1qnSOaPnWybrLbj96fDO05nkW1vJBBK6RqrXm55fFsZBQR1ydHsdectxarhT6SeeIpq/W1c+6+8ixbdC6UToLdUojwhydVUrdoLVeFqE8JIiFhDp6WzoARcevEpeuGaxqTH08fKR8vr7hkgeqj+6E1vXSWei8PvJke7o9zaaUmoEIbhkmWYnSAchUigAEACRIB6HIGY4jFT9PeDlDOkcsXdHQOP2RqiNbbxwyaDSU6iudh87q3TC/fwCAGW1rSABgLAAopW4CsJ8jJ9aieK4QdeR0udcBuEw6B0XO+uTcj4eqE7YYHTnVhz2St18/dPAIKJUinYXOaJYn2xOxU1rbRkw2aq1VpK5JscMpGzoVp23iyM8SXlpr1zICALObmictrqgqV1ofl85Cp6lCZE9ovQbALW0/vqvDqAlZBEdI6DOcLvc8AGukc1D4huFY5QfJP+upFGw/OuBxOHZ/98Ih/bVSg6Sz0CcWe7I9/yUdgsyDIyR0qg8B1EqHoPAtT771EMtISEZLy/gl5ZW1htZhnwhKEeOWDkDmwkJCn+HNz/Ij/IVmJOwnCa+uvVAdnyWdw0zSWlrHvlRW0WhoXSGdheAHp4fpFCwkdCb8oLCwIThe/dvEFydJ5zCjsa1+52uHK/wJWh+WzmJzaz3ZHp90CDIXFhI6ExYSC1uenHfAUEiVzmFWo/z+i14/XK4StT4oncXGOF1Dp2EhodN487P2AtglnYO67oaE1z8YoY7Ols5hdiP8geFvlpYnO3jcuBQWEjoNCwmdzYvSAahrBuPEEVfiC2nSOaxiaCAw9K3Ssr7JweAe6Sw24/Vke3ZIhyDzYSGhs3lBOgB1zTLHn/YZSg+QzmElgwLBQW+Xlg/oEQxyRDB2lkoHIHNiIaEz8uZn7QRQLJ2DOucHCW+uG2lU84TdbhgQDA5cWVo+pHcwyH+1x8Zi6QBkTiwkdC7/lA5A5zcQvqN/SPzHeOkcVpYSDKauOFQ2om8g6JHOEuc2ebI926VDkDmxkNC5/BMAj/I1uWWOvD2G0gOlc1hdX637rSgtG50SCBRLZ4ljz0gHIPNiIaGz8uZnHQSwWjoHnd33E/69brRRNUc6R7zorXWfFaXl4wcEApuks8QhP4DnpUOQebGQ0Pk8JR2AzmwAfMfyEp8ZJ50j3vTUutfbpWUTB/v9EXsKLQEA3vRke45IhyDzYiGh81kGoF46BJ1uqeO23YbSfFhcFCRr9HiztHzqha3+D6WzxBFO19A5sZDQOXnzs+oQKiVkIt9JWLl+rFHBqZoocgAO9+HyS0a1tq6TzhIHTgD4l3QIMjcWEuoMTtuYSCpOnrg98amx0jnsIBFIfPVwxayxLS1rpbNY3IuebE+zdAgyNxYS6oxVAHZLh6CQpY7bShI4VRMzCUDCS2WVc9KbW7jAu/v4jxo6LxYSOi9vfpYGcL90DgK+mfDuhouNsrnSOezGAIwXyyvnT21qXiWdxYLWebI9G6RDkPmxkFBnPQ2AK+QFpaCu5s7Ev42SzmFXClD/qKi6/NLGpvels1jMvdIByBpYSKhTvPlZTQAKpHPY2YuO27cnKD1EOofd/b2yeuH8hsb3pHNYxD4AL0uHIGtgIaGuKADQKB3Cjr5hrPoozSidJ52DQh6tOrLoyvoGjpSc3wOebE9QOgRZAwsJdZo3P+soQlM3FEP9UOe7O+nxi6Rz0GfdX310YVZd/XvSOUzsBLiYlbqAhYS66j4A/BdPDL3guMOToIJDpXPQ6fKPHFt0Te1JjpScWaEn28NDFanTWEioS7z5WXsBvCKdwy6+Yqz9eJJxcL50Djq7W4+dWPifvtr3oTUfRPmpFgAPS4cga2Ehoe64RzqAHfRBQ+29SY8Ol85B53fz8ZqFP/LVrmEp+cTznmxPhXQIshYWEuoyb37WegA8uTLKXnDcsTVRBYdJ56DO+fkJ34Kf1vjWQmtOaYamdom6hIWEuusv0gHi2ReNdRszjAOcqrGYH9fUzv+f4zXrobVfOougZZ5sj0c6BFkPCwl116sANkuHiEe90XjygaQCLmK1qP+qPTn398dOfAytW6WzCPAD+J10CLImFhLqlrbj5P9HOkc8es7x5+JEFeTaEQu77mTdZbcdPb4ZWtvtgXJPerI9e6RDkDWxkFC3efOz3gXgls4RT642Ptw0zdi3QDoHhe9rdfWz7jpyzAOt7XKYYAOAP0mHIOtiIaFw/RZAQDpEPOiNxrqHk/46WDoHRc4X6htm3l99dCe0bpDOEgMPcmcNhYOFhMLizc8qAfA36Rzx4BlH/qYkFRghnYMi68qGxukFVUf2QOuT0lmi6DiAu6RDkLWxkFAk3Aognj9so+4/jI82z1B7OFUTpy5vbJr6RGX1QWjtk84SJXd6sj3x+t9GMcJCQmHz5mdVAbhbOodV9UJTfUHSQxcoBSWdhaLnsqbmyU9XVJcrrU9IZ4mwUvBUVooAFhKKlHsBlEmHsKKnHXdtTFIBPjzPBi5pbk5/rrzqiNL6qHSWCLrVk+2x224iigIWEooIb35WI4A/SOewmkxj05ZL1S5O1dhIRkvL+BfLK32G1tXSWSJgHfgEcIoQFhKKpGcAFEuHsIqeaG54LOn+VE7V2E96S+vY5WWV9YbWVt6V0grgBk+2h8/voYhgIaGI8eZnBQH8AgA/oDrh70n3fJykAqOkc5CMca2to189XNGaoPVh6Szd9BdPtmebdAiKHywkFFHe/KxVAB6VzmF2i4zirZcZO/isGptz+v0jXz9crhK1PiidpYv2ArhNOgTFFxYSioabARyQDmFWPdDc+HjSff2U4p8/Akb4A8PfKC13JGltpT8zOZ5sT5N0CIov/ECkiPPmZ9UB+CE4dXNGTyTdu8Gh/E7pHGQewwKBYf8uLeuTHAzulc7SCc96sj3vSIeg+MNCQlHR9pybx6RzmM18w+OZb2zjrho6zaBAcNDbpeX9ewSDu6SznMMxAL+WDkHxiYWEoum3AKw2Nx41yWhpejLpnj6cqqGzGRAMDlxZWj6kVzC4QzrLWfzGk+2JpzNUyET4wUhR02HqhgA8lnTfh8nKP1o6B5lbSjCYuqK0bHifQNAjneUUKz3ZnqelQ1D8YiGhqPLmZ70DTt1grrFt+0JjK3fVUKf0C+qUlaVlo1MCgS3SWdocAfB96RAU31hIKBZsPXXjQGvzU0n39FAKCdJZyDp6a91nRWn5xQMCgU3CUTSAbE+2x8qHuJEFsJBQ1Hnzs04CuF46h5RHkx5Yn6xax0rnIOvpqXWvt0vLJg7y+z8WjHG/J9vzpuD9ySZYSCgmvPlZKxF6AJ+tzFIlOzKNzZyqoW5L1ujxVmn5lGF+/waB228EcIvAfcmGWEgolm4G8J50iFhJgr/lGUe+g1M1FC4H4HCXlk+/qLV1XQxvexLAdZ5sT0sM70k2xkJCMePNzwoA+BYAqz67o0sKkh78oIdqHSedg+JDEpD0r8MVs8a2tK6N0S1/4sn2WOGgNooTLCQUU978rGoA1wCI6391zVS7Sq4yNnKqhiIqAUh4qaxiTlpzy5oo32qxJ9vzXJTvQfQZLCQUc978rA8ReipwXEqEv/VZx52JSiFROgvFHwMwlpRXzstoal4VpVvsAvDTKF2b6KxYSEiENz+rEMBT0jmi4aGkv67tqVouls5B8UsB6vmKqstnNja9H+FLnwDwZU+2py7C1yU6LxYSknQjQqv448Z0tWfX540N86RzkD08VVm9cF5D43sRulwrgGs82Z7dEboeUZewkJAYb35WE4BvIPTALstLhL/1OccdSikkSWch+yisOrLoivqGSIyU3OjJ9hRF4DpE3cJCQqK8+VkHAXwbQFA6S7juT3pkbS/VMl46B9nPA9VHF36hrj6cUnKvJ9vzt4gFIuoGFhIS583PWgGLP9J8qtq7+4vGek7VkJi7jhxb+I3auu6UktcA3BTpPERdxUJCpuDNz3oQwJ+lc3RHAgL+5x13BDhVQ9Lyjh1f+F1f7fvQWnfyW4oBfMeT7bH8CCVZHwsJmYY3P+v3sOCTgf+SVLimt2pOl85BBACu4zULr/fVrulEKakA8CVPtqc+FrmIzoeFhMzmRgBLpEN01iR1YO9XjbVzpXMQdfSLE74FuTW+tdD6bCMf9QC+4sn22OLUZLIGFhIyFW9+VhDA9wC8LZ3lfAwEAy86bm9RCg7pLESnyqmpnf/rEzXroHXglF9qRqiMfCSRi+hsWEjIdLz5WS0Avg7gQ+ks53J30uOr+6imidI5iM7mv30n591y7MQGaN3a9pYfwLWebM87krmIzoSFhEzJm59VD+ALALZLZzmTdHVw3zeMVXOkcxCdz3dO1s3509Hjm6F1I4DvebI9/5LORHQmqvOLsYliz+lyXwhgLQCncJRPGAgGtiT/aGdf1ThJOgtRJ+m1PXt8d97NVS9IByE6G46QkKl587PKAfwHgCrpLO3uTPzbGpYRshAN4HqWETI7FhIyPW9+1h4AlwM4KJ1lgjp04JsJ782WzkHUSRrA9cjz/V06CNH5sJCQJXjzs3YDmA+gRCqDQjC41HFbnVLoIZWBqAtYRshSWEjIMrz5WYcBLACwQeL+/5f499X9VEOGxL2JuigI4IcsI2QlLCRkKd78rGMArgCwMpb3vVgd9n4noWhWLO9J1E0NAL6OPN9T0kGIuoKFhCzHm59VByALwLJY3C80VfOnWqXQMxb3IwpDFYCFyPO9Kh2EqKtYSMiS2g5P+xaAJ6J9r7zExWtSVf2UaN+HKEw7AMxGnu9j6SBE3cFzSMjynC73nQBc0bj2GFV+8B3HbwYphV7RuD5RhLwD4BvI8/mkgxB1F0dIyPK8+Vm3APgNQrsKIkjr5Y68GpYRMrmnAXyeZYSsjoWE4oI3P+teAF8CUBOpa/4x8dnV/VXd1EhdjygK/og8338jz9d6/t9KZG6csqG44nS5xwJ4CUBYaz5Gq/JDRY7fDFQKvSOTjCiiWgD8AHm+56SDEEUKR0gornjzs/YBmAMgjA9qrZc5/nSMZYRM6jiAq1hGKN5whITiltPl/hmAewEkdeX7fpf43KobEt2XRycVUVg2ArgOeb690kGIIo2FhOKa0+WeB2ApgGGd+f2jVOXh9xy/TlUKfaKbjKhLNELl+ndcL0LxioWE4p7T5R4GYAlCz8I5p4+TczZdoGpnRD8VUadVAshGnu9t6SBE0cQ1JBT3vPlZFQAyATx0rt93U+I/V7OMkMm8AWAKywjZAUdIyFacLvdXATwOYFDH9y9S1WWrHL/spxT6igQj+qxmADcDeAh5Pn5Iky2wkJDtOF3uQQAeA/C19vc2JP9k42Dlu0QuFdEndgL4NvJ8xdJBiGKJhYRsy+lyfw/AQ79OXLLt54mvnHd9CVEMPAHgl8jzNUgHIYo1FhKyNafLPWJX8vfvS1b+a6WzkK0dAXAj8nwxeYI1kRmxkBABQF7KdwA8gFPWlhBFWQDAowD+F3m+GuEsRKJYSIja5aUMBHA/gO9JRyFb+ABALteKEIWwkBCdKi/lcwAKATiFk1B8qkZoB81i7qAh+hQLCdGZ5KUkA/gZgN8B6C+chuJDAMAjCD2ht0Y4C5HpsJAQnUteSn8AtyBUTnoIpyHrWovQ9MwW6SBEZsVCQtQZeSkjAdwO4D/BE46p86oB3ATgGU7PEJ0bCwlRV+SlTAFwF4CrpaOQqR1HaNfWQ8jz+YSzEFkCCwlRd+SlXAHgbgB89g11VA3gPgCPIM93UjoMkZWwkBB1V16KAnAdgDsAjBZOQ7LKAdwD4HGeskrUPSwkROHKS0kEcA2AXwKYLRuGYuwQQlN4TyLP1ywdhsjKWEiIIikvZTZCxeQaAImyYSiK9gHIR+gskVbpMETxgIWEKBryUoYDyAVwA4CBwmkocrYC+AuA55HnC0iHIYonLCRE0ZSX0hOho+h/AWCicBrqHh+AFxCalvlYOgxRvGIhIYqVvJSrEJrO+TwAJRuGzkMDeA/A3wEsR56vUTYOUfxjISGKtbyUUQC+2faaKZyGPuswgKcBPIU8337hLES2wkJCJCkvZQw+LSfThdPYVQuA1wA8CeBt5PmCwnmIbImFhMgs8lIuxqflZIpwmnhXC2AlgDcBvII831HhPES2x0JCZEZ5KWn4tJxMEk4TL3YAeKPttYbbdYnMhYWEyOzyUsYBWAjg8ravo2QDWUYDgCK0l5A830HhPER0DiwkRFYTevJwe0G5HMB42UCmEQBQgk9LyHs8PZXIOlhIiKwuL2UoPi0nCxGa4on3bcWtALYD2NT22ghgC7fnElkXCwlRvMlLSUXoELYJANI6fB0Lax5n3wzAg0+LxyYAHo5+EMUXFhIiuwg9BHAsTi8qEyB/vL0PgBfAwQ4vL4C9AHZwASpR/GMhISIgL6UXgP4dXgNO+fmZXgqhqZOOr5YzvNf+fjOAIwAqAVS1fQ298nx1MfivJCITYyEhIiIicYZ0ACIiIiIWEiIiIhLHQkJERETiWEiIiIhIHAsJERERiWMhISIiInEsJERERCTOisdIE1EcU0rd1PbDsQCgtf6xYBwiihEejEZEpqGUuktrfXOHnz8GYIzW+irBWEQUA5yyISJTUEqlApjR9rXdYwCuVEqNEQlFRDHDQkJEZjITQMfysb/ta2rsoxBRLHENCRGZgta6BqGH9nV0ZdvX/SCiuMYREiIys1sA/LitrBBRHOOiViIyJaXUXQCOaa3vls5CRNHHQkJEpqOUugbAAK3149JZiCg2OGVDRKailLoSANrLiFIqlbtsiOIfCwkRmYZSagaAGQA2KaXGtBWRGwAcl01GRNHGKRsiMoW280cO4AxbfLXWKtZ5iCi2WEiIiIhIHKdsiIiISBwLCREREYljISEiIiJxLCREREQkjoWEiIiIxLGQEBERkTgWEiIiIhLHQkJERETiWEiIiIhIHAsJERERiWMhISIiInH/H3QEbH4G77DzAAAAAElFTkSuQmCC", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "for i, item in enumerate(beta):\n", " print('Parameter', i)\n", " item.plot_piechart()\n", " print()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "interpreter": { "hash": "916dbcbb3f70747c44a77c7bcd40155683ae19c65e1c03b4aa3499c5328201f1" }, "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.8.10" } }, "nbformat": 4, "nbformat_minor": 4 }