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+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "%matplotlib inline\n",
+ "%load_ext autoreload\n",
+ "%autoreload 2"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "../utils/plot.py:24: UserWarning: \n",
+ "This call to matplotlib.use() has no effect because the backend has already\n",
+ "been chosen; matplotlib.use() must be called *before* pylab, matplotlib.pyplot,\n",
+ "or matplotlib.backends is imported for the first time.\n",
+ "\n",
+ "The backend was *originally* set to 'module://ipykernel.pylab.backend_inline' by the following code:\n",
+ " File \"/home/shivesh/programs/anaconda2/lib/python2.7/runpy.py\", line 174, in _run_module_as_main\n",
+ " \"__main__\", fname, loader, pkg_name)\n",
+ " File \"/home/shivesh/programs/anaconda2/lib/python2.7/runpy.py\", line 72, in _run_code\n",
+ " exec code in run_globals\n",
+ " File \"/home/shivesh/programs/anaconda2/lib/python2.7/site-packages/ipykernel_launcher.py\", line 16, in <module>\n",
+ " app.launch_new_instance()\n",
+ " File \"/home/shivesh/programs/anaconda2/lib/python2.7/site-packages/traitlets/config/application.py\", line 658, in launch_instance\n",
+ " app.start()\n",
+ " File \"/home/shivesh/programs/anaconda2/lib/python2.7/site-packages/ipykernel/kernelapp.py\", line 499, in start\n",
+ " self.io_loop.start()\n",
+ " File \"/home/shivesh/programs/anaconda2/lib/python2.7/site-packages/tornado/ioloop.py\", line 1073, in start\n",
+ " handler_func(fd_obj, events)\n",
+ " File \"/home/shivesh/programs/anaconda2/lib/python2.7/site-packages/tornado/stack_context.py\", line 300, in null_wrapper\n",
+ " return fn(*args, **kwargs)\n",
+ " File \"/home/shivesh/programs/anaconda2/lib/python2.7/site-packages/zmq/eventloop/zmqstream.py\", line 450, in _handle_events\n",
+ " self._handle_recv()\n",
+ " File \"/home/shivesh/programs/anaconda2/lib/python2.7/site-packages/zmq/eventloop/zmqstream.py\", line 480, in _handle_recv\n",
+ " self._run_callback(callback, msg)\n",
+ " File \"/home/shivesh/programs/anaconda2/lib/python2.7/site-packages/zmq/eventloop/zmqstream.py\", line 432, in _run_callback\n",
+ " callback(*args, **kwargs)\n",
+ " File \"/home/shivesh/programs/anaconda2/lib/python2.7/site-packages/tornado/stack_context.py\", line 300, in null_wrapper\n",
+ " return fn(*args, **kwargs)\n",
+ " File \"/home/shivesh/programs/anaconda2/lib/python2.7/site-packages/ipykernel/kernelbase.py\", line 283, in dispatcher\n",
+ " return self.dispatch_shell(stream, msg)\n",
+ " File \"/home/shivesh/programs/anaconda2/lib/python2.7/site-packages/ipykernel/kernelbase.py\", line 233, in dispatch_shell\n",
+ " handler(stream, idents, msg)\n",
+ " File \"/home/shivesh/programs/anaconda2/lib/python2.7/site-packages/ipykernel/kernelbase.py\", line 399, in execute_request\n",
+ " user_expressions, allow_stdin)\n",
+ " File \"/home/shivesh/programs/anaconda2/lib/python2.7/site-packages/ipykernel/ipkernel.py\", line 208, in do_execute\n",
+ " res = shell.run_cell(code, store_history=store_history, silent=silent)\n",
+ " File \"/home/shivesh/programs/anaconda2/lib/python2.7/site-packages/ipykernel/zmqshell.py\", line 537, in run_cell\n",
+ " return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)\n",
+ " File \"/home/shivesh/programs/anaconda2/lib/python2.7/site-packages/IPython/core/interactiveshell.py\", line 2724, in run_cell\n",
+ " self.events.trigger('post_run_cell')\n",
+ " File \"/home/shivesh/programs/anaconda2/lib/python2.7/site-packages/IPython/core/events.py\", line 74, in trigger\n",
+ " func(*args, **kwargs)\n",
+ " File \"/home/shivesh/programs/anaconda2/lib/python2.7/site-packages/ipykernel/pylab/backend_inline.py\", line 164, in configure_once\n",
+ " activate_matplotlib(backend)\n",
+ " File \"/home/shivesh/programs/anaconda2/lib/python2.7/site-packages/IPython/core/pylabtools.py\", line 315, in activate_matplotlib\n",
+ " matplotlib.pyplot.switch_backend(backend)\n",
+ " File \"/home/shivesh/programs/anaconda2/lib/python2.7/site-packages/matplotlib/pyplot.py\", line 231, in switch_backend\n",
+ " matplotlib.use(newbackend, warn=False, force=True)\n",
+ " File \"/home/shivesh/programs/anaconda2/lib/python2.7/site-packages/matplotlib/__init__.py\", line 1422, in use\n",
+ " reload(sys.modules['matplotlib.backends'])\n",
+ " File \"/home/shivesh/programs/anaconda2/lib/python2.7/site-packages/matplotlib/backends/__init__.py\", line 16, in <module>\n",
+ " line for line in traceback.format_stack()\n",
+ "\n",
+ "\n",
+ " mpl.use('Agg')\n"
+ ]
+ }
+ ],
+ "source": [
+ "import sys\n",
+ "sys.path.extend(['.', '..'])\n",
+ "\n",
+ "import numpy as np\n",
+ "import matplotlib as mpl\n",
+ "from matplotlib import rc\n",
+ "rc('text', usetex='True')\n",
+ "import matplotlib.pyplot as plt\n",
+ "from matplotlib.patches import Circle, Rectangle, Wedge\n",
+ "from matplotlib.legend_handler import HandlerPatch\n",
+ "plt.style.use('./paper.mplstyle')\n",
+ "\n",
+ "mpl.rcParams['text.latex.preamble'] = [\n",
+ " r'\\usepackage{amsmath}',\n",
+ " r'\\usepackage{amssymb}',\n",
+ " r'\\usepackage{accents}',\n",
+ " r'\\DeclareSymbolFont{matha}{OML}{txmi}{m}{it}',\n",
+ " r'\\DeclareMathSymbol{\\nu}{\\mathord}{matha}{118}']\n",
+ "mpl.rcParams['text.latex.unicode'] = True\n",
+ "\n",
+ "import ternary\n",
+ "\n",
+ "from utils import fr as fr_utils\n",
+ "from utils import misc as misc_utils\n",
+ "from utils import plot as plot_utils\n",
+ "from utils.enums import Texture"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "tRed = np.array([226,101,95]) / 255.\n",
+ "tBlue = np.array([96,149,201]) / 255.\n",
+ "tGreen = np.array([170,196,109]) / 255."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "class HandlerCircle(HandlerPatch):\n",
+ " def create_artists(self, legend, orig_handle,\n",
+ " xdescent, ydescent, width, height,\n",
+ " fontsize, trans):\n",
+ " r = 10\n",
+ " x = r + width//2 + 10\n",
+ " y = height//2 - 3\n",
+ "\n",
+ " # create \n",
+ " p = Circle(xy=(x, y), radius=r)\n",
+ "\n",
+ " # update with data from oryginal object\n",
+ " self.update_prop(p, orig_handle, legend)\n",
+ "\n",
+ " # move xy to legend\n",
+ " p.set_transform(trans)\n",
+ "\n",
+ " return [p]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[array([0.33333333, 0.66666667, 0. ]), array([0.30535346, 0.3527747 , 0.34187184])]\n",
+ "[array([0., 1., 0.]), array([0.18301213, 0.43765598, 0.37933189])]\n",
+ "[array([1., 0., 0.]), array([0.55003613, 0.18301213, 0.26695174])]\n"
+ ]
+ }
+ ],
+ "source": [
+ "s = [1, 2, 0]\n",
+ "SM_120 = [fr_utils.normalise_fr(s), fr_utils.u_to_fr(s, np.array(fr_utils.NUFIT_U, dtype=np.complex128))]\n",
+ "s = [0, 1, 0]\n",
+ "SM_010 = [fr_utils.normalise_fr(s), fr_utils.u_to_fr(s, np.array(fr_utils.NUFIT_U, dtype=np.complex128))]\n",
+ "s = [1, 0, 0]\n",
+ "SM_100 = [fr_utils.normalise_fr(s), fr_utils.u_to_fr(s, np.array(fr_utils.NUFIT_U, dtype=np.complex128))]\n",
+ "print SM_120\n",
+ "print SM_010\n",
+ "print SM_100\n",
+ "\n",
+ "SM_X = np.load('./chains/mc_x.npy')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 8,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "../utils/plot.py:24: UserWarning: \n",
+ "This call to matplotlib.use() has no effect because the backend has already\n",
+ "been chosen; matplotlib.use() must be called *before* pylab, matplotlib.pyplot,\n",
+ "or matplotlib.backends is imported for the first time.\n",
+ "\n",
+ "The backend was *originally* set to 'module://ipykernel.pylab.backend_inline' by the following code:\n",
+ " File \"/home/shivesh/programs/anaconda2/lib/python2.7/runpy.py\", line 174, in _run_module_as_main\n",
+ " \"__main__\", fname, loader, pkg_name)\n",
+ " File \"/home/shivesh/programs/anaconda2/lib/python2.7/runpy.py\", line 72, in _run_code\n",
+ " exec code in run_globals\n",
+ " File \"/home/shivesh/programs/anaconda2/lib/python2.7/site-packages/ipykernel_launcher.py\", line 16, in <module>\n",
+ " app.launch_new_instance()\n",
+ " File \"/home/shivesh/programs/anaconda2/lib/python2.7/site-packages/traitlets/config/application.py\", line 658, in launch_instance\n",
+ " app.start()\n",
+ " File \"/home/shivesh/programs/anaconda2/lib/python2.7/site-packages/ipykernel/kernelapp.py\", line 499, in start\n",
+ " self.io_loop.start()\n",
+ " File \"/home/shivesh/programs/anaconda2/lib/python2.7/site-packages/tornado/ioloop.py\", line 1073, in start\n",
+ " handler_func(fd_obj, events)\n",
+ " File \"/home/shivesh/programs/anaconda2/lib/python2.7/site-packages/tornado/stack_context.py\", line 300, in null_wrapper\n",
+ " return fn(*args, **kwargs)\n",
+ " File \"/home/shivesh/programs/anaconda2/lib/python2.7/site-packages/zmq/eventloop/zmqstream.py\", line 450, in _handle_events\n",
+ " self._handle_recv()\n",
+ " File \"/home/shivesh/programs/anaconda2/lib/python2.7/site-packages/zmq/eventloop/zmqstream.py\", line 480, in _handle_recv\n",
+ " self._run_callback(callback, msg)\n",
+ " File \"/home/shivesh/programs/anaconda2/lib/python2.7/site-packages/zmq/eventloop/zmqstream.py\", line 432, in _run_callback\n",
+ " callback(*args, **kwargs)\n",
+ " File \"/home/shivesh/programs/anaconda2/lib/python2.7/site-packages/tornado/stack_context.py\", line 300, in null_wrapper\n",
+ " return fn(*args, **kwargs)\n",
+ " File \"/home/shivesh/programs/anaconda2/lib/python2.7/site-packages/ipykernel/kernelbase.py\", line 283, in dispatcher\n",
+ " return self.dispatch_shell(stream, msg)\n",
+ " File \"/home/shivesh/programs/anaconda2/lib/python2.7/site-packages/ipykernel/kernelbase.py\", line 233, in dispatch_shell\n",
+ " handler(stream, idents, msg)\n",
+ " File \"/home/shivesh/programs/anaconda2/lib/python2.7/site-packages/ipykernel/kernelbase.py\", line 399, in execute_request\n",
+ " user_expressions, allow_stdin)\n",
+ " File \"/home/shivesh/programs/anaconda2/lib/python2.7/site-packages/ipykernel/ipkernel.py\", line 208, in do_execute\n",
+ " res = shell.run_cell(code, store_history=store_history, silent=silent)\n",
+ " File \"/home/shivesh/programs/anaconda2/lib/python2.7/site-packages/ipykernel/zmqshell.py\", line 537, in run_cell\n",
+ " return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)\n",
+ " File \"/home/shivesh/programs/anaconda2/lib/python2.7/site-packages/IPython/core/interactiveshell.py\", line 2724, in run_cell\n",
+ " self.events.trigger('post_run_cell')\n",
+ " File \"/home/shivesh/programs/anaconda2/lib/python2.7/site-packages/IPython/core/events.py\", line 74, in trigger\n",
+ " func(*args, **kwargs)\n",
+ " File \"/home/shivesh/programs/anaconda2/lib/python2.7/site-packages/ipykernel/pylab/backend_inline.py\", line 164, in configure_once\n",
+ " activate_matplotlib(backend)\n",
+ " File \"/home/shivesh/programs/anaconda2/lib/python2.7/site-packages/IPython/core/pylabtools.py\", line 315, in activate_matplotlib\n",
+ " matplotlib.pyplot.switch_backend(backend)\n",
+ " File \"/home/shivesh/programs/anaconda2/lib/python2.7/site-packages/matplotlib/pyplot.py\", line 231, in switch_backend\n",
+ " matplotlib.use(newbackend, warn=False, force=True)\n",
+ " File \"/home/shivesh/programs/anaconda2/lib/python2.7/site-packages/matplotlib/__init__.py\", line 1422, in use\n",
+ " reload(sys.modules['matplotlib.backends'])\n",
+ " File \"/home/shivesh/programs/anaconda2/lib/python2.7/site-packages/matplotlib/backends/__init__.py\", line 16, in <module>\n",
+ " line for line in traceback.format_stack()\n",
+ "\n",
+ "\n",
+ " mpl.use('Agg')\n"
+ ]
+ }
+ ],
+ "source": [
+ "nbins = 25\n",
+ "fontsize = 23"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 9,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "../utils/plot.py:258: RuntimeWarning: divide by zero encountered in double_scalars\n",
+ " circum_r = a*b*c/(4.0*area)\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 864x864 with 1 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# Figure\n",
+ "fig = plt.figure(figsize=(12, 12))\n",
+ "\n",
+ "# Axis\n",
+ "ax = fig.add_subplot(111)\n",
+ "#ax_labels = [r'$f_{e,\\oplus}$', r'$f_{\\mu,\\oplus}$', r'$f_{\\tau,\\oplus}$']\n",
+ "ax_labels = [r'$\\nu_e\\:\\:{\\rm fraction}\\:\\left( f_{e,\\oplus}\\right)$',\n",
+ " r'$\\nu_\\mu\\:\\:{\\rm fraction}\\:\\left( f_{\\mu,\\oplus}\\right)$',\n",
+ " r'$\\nu_\\tau\\:\\:{\\rm fraction}\\:\\left( f_{\\tau,\\oplus}\\right)$']\n",
+ "tax = plot_utils.get_tax(ax, scale=nbins, ax_labels=ax_labels, rot_ax_labels=True)\n",
+ "\n",
+ "# Plot\n",
+ "tax.scatter([SM_120[0]*nbins], marker='o', s=350, facecolors=tRed,\n",
+ " edgecolors='k', linewidth=2.3, zorder=10,\n",
+ " label=r'$(1:2:0\\smash{)_{\\rm S}}$')\n",
+ "tax.scatter([SM_010[0]*nbins], marker='s', s=350, facecolors=tGreen,\n",
+ " edgecolors='k', linewidth=2.3, zorder=10,\n",
+ " label=r'$(0:1:0\\smash{)_{\\rm S}}$')\n",
+ "tax.scatter([SM_100[0]*nbins], marker='^', s=350, facecolors=tBlue,\n",
+ " edgecolors='k', linewidth=2.3, zorder=10,\n",
+ " label=r'$(1:0:0\\smash{)_{\\rm S}}$')\n",
+ "\n",
+ "tax.scatter([SM_120[1]*nbins], marker='o', s=350, edgecolors='k',\n",
+ " facecolors='white', linewidth=2.3, zorder=10)\n",
+ "tax.scatter([SM_010[1]*nbins], marker='s', s=350, edgecolors='k',\n",
+ " facecolors='white', linewidth=2.3, zorder=10)\n",
+ "tax.scatter([SM_100[1]*nbins], marker='^', s=350, edgecolors='k',\n",
+ " facecolors='white', linewidth=2.3, zorder=10)\n",
+ "\n",
+ "ax.annotate(\"\", xy=np.array([0.415, 0.42])*nbins, xytext=np.array([0.499, 0.83])*nbins,\n",
+ " arrowprops=dict(arrowstyle=\"-|>\",facecolor='k',lw=2))\n",
+ "ax.annotate(\"\", xy=np.array([0.505, 0.335])*nbins, xytext=np.array([0.64, 0.55])*nbins,\n",
+ " arrowprops=dict(arrowstyle=\"-|>\",facecolor='k',lw=2))\n",
+ "ax.annotate(\"\", xy=np.array([0.67, 0.14])*nbins, xytext=np.array([0.975, 0.014])*nbins,\n",
+ " arrowprops=dict(arrowstyle=\"-|>\",facecolor='k',lw=2))\n",
+ "\n",
+ "# Legend\n",
+ "l_size = fontsize\n",
+ "legend = plt.legend(loc=(0.7, 0.75), title=r'Source composition',\n",
+ " fontsize=l_size, prop={'size': fontsize})\n",
+ "plt.setp(legend.get_title(), fontsize=l_size)\n",
+ "ax.add_artist(legend)\n",
+ "\n",
+ "plot_utils.flavour_contour(\n",
+ " frs = SM_X,\n",
+ " ax = ax,\n",
+ " fill = True,\n",
+ " nbins = nbins,\n",
+ " coverage = 90,\n",
+ " linewidth = 1.5,\n",
+ " edgecolor = 'k',\n",
+ " facecolor = 'none',\n",
+ " alpha = 1,\n",
+ " zorder = 2,\n",
+ " oversample = 10,\n",
+ " delaunay = True,\n",
+ " d_alpha = 0.1,\n",
+ " smoothing = 4,\n",
+ " hatch = 'XXX'\n",
+ ")\n",
+ "\n",
+ "legend_elements = []\n",
+ "legend_elements.append(\n",
+ " Circle((0., 0.), 0.1, facecolor='none', hatch='XXX', edgecolor='k',\n",
+ " linewidth=2., label=r'Standard Model')\n",
+ ")\n",
+ "legend = plt.legend(handles=legend_elements, loc=(-0.05, 0.85),\n",
+ " fontsize=l_size,\n",
+ " handler_map={Circle: HandlerCircle()})\n",
+ "plt.setp(legend.get_title(), fontsize=l_size)\n",
+ "legend.get_frame().set_linestyle('-')\n",
+ "ax.add_artist(legend)\n",
+ "\n",
+ "fig.savefig('./plots/thesis.pdf', bbox_inches='tight', dpi=150)"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 2",
+ "language": "python",
+ "name": "python2"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.15"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}