{ "cells": [ { "cell_type": "markdown", "id": "6c0bd71b", "metadata": {}, "source": [ "# Base3 lesson (silicon)\n", "\n", "
\n", "

Third (basic) lesson with Abinit and AbiPy

\n", "

Crystalline silicon.

\n", "
\n", "

This lesson aims at showing you how to get the following physical properties, for an insulator:

\n", " \n", "

\n", " You will learn about the use of k-points, as well as the smearing of the plane-wave kinetic energy cut-off.\n", "

\n", "
\n", "\n", "This tutorial is a complement to the standard [ABINIT tutorial on silicon](https://docs.abinit.org/tutorial/base3).\n", "Here, powerful flow and visualisation procedures\n", "will be demonstrated. Still, some basic understanding of the stand-alone working of ABINIT is a prerequisite.\n", "Also, in order to fully benefit from this Abipy tutorial, other more basic Abipy tutorials should have been followed,\n", "as suggested in the [abitutorials index page](../intro)." ] }, { "cell_type": "code", "execution_count": 1, "id": "1f5971ec", "metadata": {}, "outputs": [], "source": [ "# Use this at the beginning of your script so that your code will be compatible with python3\n", "import numpy as np\n", "\n", "import warnings\n", "warnings.filterwarnings(\"ignore\") # Ignore warnings\n", "\n", "from abipy import abilab\n", "abilab.enable_notebook() # This line tells AbiPy we are running inside a notebook\n", "\n", "# This line configures matplotlib to show figures embedded in the notebook.\n", "# Replace `inline` with `notebook` in classic notebook\n", "%matplotlib inline\n", "\n", "# Option available in jupyterlab. See https://github.com/matplotlib/jupyter-matplotlib\n", "#%matplotlib widget" ] }, { "cell_type": "markdown", "id": "e5f51784", "metadata": {}, "source": [ "```{include} ../snippets/plotly_matplotlib_note.md\n", "```" ] }, { "cell_type": "markdown", "id": "90849498", "metadata": {}, "source": [ "## Computing the total energy of silicon at fixed number of k-points\n", "\n", "Our goal is to study the convergence of the total energy of silicon versus the number of **k**-points.\n", "So we start by defining a function that generates a `Flow` of SCF calculations\n", "by looping over a predefined list of {{ngkpt}} values.\n", "The crystalline structure is initialized from a CIF file while other parameters\n", "such as the cutoff energy {{ecut}} are fixed:" ] }, { "cell_type": "code", "execution_count": 2, "id": "aaab682c", "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\n", " \n", " \n", " \n", "\n", "\n", "

\n", "\n", "
def build_ngkpt_flow(options):\n",
       "    """\n",
       "    Crystalline silicon: computation of the total energy\n",
       "    Convergence with respect to the number of k points. Similar to tbase3_3.in\n",
       "\n",
       "    Args:\n",
       "        options: Command line options.\n",
       "\n",
       "    Return:\n",
       "        Abinit Flow object.\n",
       "    """\n",
       "    # Definition of the different grids\n",
       "    ngkpt_list = [(2, 2, 2), (4, 4, 4), (6, 6, 6), (8, 8, 8)]\n",
       "\n",
       "    # These shifts will be the same for all grids\n",
       "    shiftk = [float(s) for s in "0.5 0.5 0.5 0.5 0.0 0.0 0.0 0.5 0.0 0.0 0.0 0.5".split()]\n",
       "\n",
       "    # Build MultiDataset object (container of `ndtset` inputs).\n",
       "    # Structure is initialized from CIF file.\n",
       "    multi = abilab.MultiDataset(structure=abidata.cif_file("si.cif"),\n",
       "                                pseudos=abidata.pseudos("14si.pspnc"), ndtset=len(ngkpt_list))\n",
       "\n",
       "    # These variables are the same in each input.\n",
       "    multi.set_vars(ecut=8, toldfe=1e-6, diemac=12.0, iomode=3)\n",
       "\n",
       "    # Each input has its own value of `ngkpt`. shiftk is constant.\n",
       "    for i, ngkpt in enumerate(ngkpt_list):\n",
       "        multi[i].set_kmesh(ngkpt=ngkpt, shiftk=shiftk)\n",
       "\n",
       "    workdir = options.workdir if (options and options.workdir) else "flow_base3_ngkpt"\n",
       "\n",
       "    # Split the inputs by calling multi.datasets() and pass the list of inputs to Flow.from_inputs.\n",
       "    return flowtk.Flow.from_inputs(workdir, inputs=multi.split_datasets())\n",
       "
\n", "\n", "\n" ], "text/plain": [ "" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from lesson_base3 import build_ngkpt_flow\n", "abilab.print_source(build_ngkpt_flow)" ] }, { "cell_type": "markdown", "id": "e8df8a53", "metadata": {}, "source": [ "Let's call the function to build the flow:" ] }, { "cell_type": "code", "execution_count": 3, "id": "25dd99ef", "metadata": {}, "outputs": [], "source": [ "flow = build_ngkpt_flow(options=None)" ] }, { "cell_type": "markdown", "id": "0d20eea1", "metadata": {}, "source": [ "In total, we have four `ScfTasks` that will be executed in the `flow_base3_ngkpt` directory:" ] }, { "cell_type": "code", "execution_count": 4, "id": "d89f9436", "metadata": {}, "outputs": [ { "data": { "image/svg+xml": [ "\n", "\n", "\n", "\n", "\n", "\n", "flow\n", "\n", "Flow, node_id=23, workdir=flow_base3_ngkpt\n", "\n", "clusterw0\n", "\n", "Work (w0)\n", "\n", "\n", "\n", "w0_t0\n", "\n", "w0_t0\n", "ScfTask\n", "\n", "\n", "\n", "w0_t1\n", "\n", "w0_t1\n", "ScfTask\n", "\n", "\n", "\n", "w0_t2\n", "\n", "w0_t2\n", "ScfTask\n", "\n", "\n", "\n", "w0_t3\n", "\n", "w0_t3\n", "ScfTask\n", "\n", "\n", "\n" ], "text/plain": [ "" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "flow.get_graphviz()" ] }, { "cell_type": "markdown", "id": "d436083b", "metadata": {}, "source": [ "This is the input of the first task `w0_t0`:" ] }, { "cell_type": "code", "execution_count": 5, "id": "4e12a817", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "##############################################
#### SECTION: basic
##############################################
ecut 8
toldfe 1e-06
ngkpt 2 2 2
kptopt 1
nshiftk 4
shiftk
0.5 0.5 0.5
0.5 0.0 0.0
0.0 0.5 0.0
0.0 0.0 0.5
##############################################
#### SECTION: dev
##############################################
iomode 3
##############################################
#### SECTION: files
##############################################
indata_prefix indata/in
tmpdata_prefix tmpdata/tmp
outdata_prefix outdata/out
pseudos /usr/share/miniconda/envs/abipy/lib/python3.12/site-packages/abipy/data/pseudos/14si.pspnc
##############################################
#### SECTION: gstate
##############################################
diemac 12.0
##############################################
#### STRUCTURE
##############################################
natom 2
ntypat 1
typat 1 1
znucl 14
xred
0.0000000000 0.0000000000 0.0000000000
0.2500000000 0.2500000000 0.2500000000
acell 1.0 1.0 1.0
rprim
6.3285005244 0.0000000000 3.6537614813
2.1095001748 5.9665675141 3.6537614813
0.0000000000 0.0000000000 7.3075229627\n", "
" ], "text/plain": [ "" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "flow[0][0].input" ] }, { "cell_type": "markdown", "id": "6fa6498a", "metadata": {}, "source": [ "and these are the {{ngkpt}} divisions of the k-mesh for the four different calculations:" ] }, { "cell_type": "code", "execution_count": 6, "id": "8f3cab12", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "w0_t0 uses ngkpt: (2, 2, 2)\n", "w0_t1 uses ngkpt: (4, 4, 4)\n", "w0_t2 uses ngkpt: (6, 6, 6)\n", "w0_t3 uses ngkpt: (8, 8, 8)\n" ] } ], "source": [ "for task in flow.iflat_tasks():\n", " print(task.pos_str, \"uses ngkpt:\", task.input[\"ngkpt\"])" ] }, { "cell_type": "markdown", "id": "f64aab6f", "metadata": {}, "source": [ "but we can achieve the same goal with:" ] }, { "cell_type": "code", "execution_count": 7, "id": "c3a6c727", "metadata": {}, "outputs": [ { "data": { "text/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", "
ngkptecutclass
w0_t0(2, 2, 2)8ScfTask
w0_t1(4, 4, 4)8ScfTask
w0_t2(6, 6, 6)8ScfTask
w0_t3(8, 8, 8)8ScfTask
\n", "
" ], "text/plain": [ " ngkpt ecut class\n", "w0_t0 (2, 2, 2) 8 ScfTask\n", "w0_t1 (4, 4, 4) 8 ScfTask\n", "w0_t2 (6, 6, 6) 8 ScfTask\n", "w0_t3 (8, 8, 8) 8 ScfTask" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "flow.get_vars_dataframe(\"ngkpt\", \"ecut\")" ] }, { "cell_type": "markdown", "id": "6004b13c", "metadata": {}, "source": [ "At this point, we could run the flow in the notebook by just calling:\n", "\n", " flow.make_scheduler().start()\n", "\n", "or, alternatively, execute the `lesson_base3.py` script to build\n", "the directory with the flow and then use:\n", "\n", " abirun.py flow_base3_ngkpt scheduler\n", "\n", "inside the terminal." ] }, { "cell_type": "markdown", "id": "5b5f92e8", "metadata": {}, "source": [ "## Analysis of the results\n", "\n", "We could use the API provided by the flow to extract the total energies from the GSR files.\n", "Something like:\n", "\n", "```python\n", "nkpt_list, ene_list = [], []\n", "for task in flow.iflat_tasks():\n", " with task.open_gsr() as gsr:\n", " nkpt_list.append(gsr.nkpt)\n", " ene_list.append(gsr.energy)\n", "\n", "# Assuming values are already sorted wrt nkpt\n", "import matplotlib.pyplot as plt\n", "plt.plot(nkpt_list, ene_list, marker=\"o\");\n", "```" ] }, { "cell_type": "markdown", "id": "2368f79a", "metadata": {}, "source": [ "but it is much easier to create a `GsrRobot` that will do the work for us:" ] }, { "cell_type": "code", "execution_count": 8, "id": "19488fe3", "metadata": { "code_folding": [], "run_control": { "marked": true }, "slideshow": { "slide_type": "-" } }, "outputs": [ { "data": { "text/html": [ "
    \n", "
  1. w0/t1/outdata/out_GSR.nc
    2. \n", "
  2. w0/t2/outdata/out_GSR.nc
    3. \n", "
  3. w0/t0/outdata/out_GSR.nc
    4. \n", "
  4. w0/t3/outdata/out_GSR.nc
    5. \n", "
" ], "text/plain": [ "Label Relpath\n", "------------------------ -----------------------------------------\n", "w0/t1/outdata/out_GSR.nc flow_base3_ngkpt/w0/t1/outdata/out_GSR.nc\n", "w0/t2/outdata/out_GSR.nc flow_base3_ngkpt/w0/t2/outdata/out_GSR.nc\n", "w0/t0/outdata/out_GSR.nc flow_base3_ngkpt/w0/t0/outdata/out_GSR.nc\n", "w0/t3/outdata/out_GSR.nc flow_base3_ngkpt/w0/t3/outdata/out_GSR.nc" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "robot_enekpt = abilab.GsrRobot.from_dir(\"flow_base3_ngkpt\")\n", "robot_enekpt" ] }, { "cell_type": "markdown", "id": "0da19eb7", "metadata": {}, "source": [ "In the next lines, we are going to generate a pandas `Dataframe` with\n", "the most important results so that we can show how to use the pandas API to analyze the data:" ] }, { "cell_type": "code", "execution_count": 9, "id": "191c753d", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Index(['formula', 'natom', 'alpha', 'beta', 'gamma', 'a', 'b', 'c', 'volume',\n", " 'abispg_num', 'spglib_symb', 'spglib_num', 'spglib_lattice_type',\n", " 'energy', 'energy_per_atom', 'pressure', 'max_force', 'ecut',\n", " 'pawecutdg', 'tsmear', 'nkpt', 'nsppol', 'nspinor', 'nspden'],\n", " dtype='object')" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "ene_table = robot_enekpt.get_dataframe()\n", "ene_table.keys()" ] }, { "cell_type": "markdown", "id": "9302b1eb", "metadata": {}, "source": [ "The dataframe contains several columns but\n", "we are mainly interested in the number of k-points {{nkpt}} and in the `energy` (given in eV).\n", "Let's massage a bit the data to facilitate the post-processing:" ] }, { "cell_type": "code", "execution_count": 10, "id": "22dc621a", "metadata": {}, "outputs": [], "source": [ "# We are gonna plot f(nkpt) so let's sort the rows first.\n", "ene_table.sort_values(by=\"nkpt\", inplace=True)\n", "\n", "# Add a column with energies in Ha and another column with the difference wrt to the last point.\n", "ene_table[\"energy_Ha\"] = ene_table[\"energy\"] * abilab.units.eV_to_Ha\n", "ene_table[\"ediff_Ha\"] = ene_table[\"energy_Ha\"] - ene_table[\"energy_Ha\"][-1]" ] }, { "cell_type": "markdown", "id": "293cb8f8", "metadata": {}, "source": [ "before printing a subset of the columns with the syntax:" ] }, { "cell_type": "code", "execution_count": 11, "id": "02a9170e", "metadata": {}, "outputs": [ { "data": { "text/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", "
nkptenergyenergy_Haediff_Ha
w0/t0/outdata/out_GSR.nc2-241.251548-8.8658310.006242
w0/t1/outdata/out_GSR.nc10-241.417961-8.8719460.000126
w0/t2/outdata/out_GSR.nc28-241.421160-8.8720640.000009
w0/t3/outdata/out_GSR.nc60-241.421393-8.8720730.000000
\n", "
" ], "text/plain": [ " nkpt energy energy_Ha ediff_Ha\n", "w0/t0/outdata/out_GSR.nc 2 -241.251548 -8.865831 0.006242\n", "w0/t1/outdata/out_GSR.nc 10 -241.417961 -8.871946 0.000126\n", "w0/t2/outdata/out_GSR.nc 28 -241.421160 -8.872064 0.000009\n", "w0/t3/outdata/out_GSR.nc 60 -241.421393 -8.872073 0.000000" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "ene_table[[\"nkpt\", \"energy\", \"energy_Ha\", \"ediff_Ha\"]]" ] }, { "cell_type": "markdown", "id": "cdf7c076", "metadata": {}, "source": [ "If you do not like tables and prefer figures, use:" ] }, { "cell_type": "code", "execution_count": 12, "id": "99d2aa2b", "metadata": {}, "outputs": [ { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "ene_table.plot(x=\"nkpt\", y=[\"energy_Ha\", \"ediff_Ha\", \"pressure\"], style=\"-o\", subplots=True);" ] }, { "cell_type": "markdown", "id": "222d0deb", "metadata": {}, "source": [ "The difference between dataset 3 and dataset 4 is rather small.\n", "Even dataset 2 gives an accuracy of about 0.0001 Ha.\n", "So, our converged value for the total energy (at fixed `acell` and `ecut`) is -8.8726 Ha." ] }, { "cell_type": "markdown", "id": "20233139", "metadata": {}, "source": [ "Now that we have learned a bit how to use pandas `Dataframes`, we can finally reveal\n", "that the AbiPy robots *already* provide methods to perform this kind of convergence studies\n", "so that we do not need to manipulate pandas dataframes explicitly.\n", "For example, we can perform the same analysis with a single line:" ] }, { "cell_type": "code", "execution_count": 13, "id": "c44ed40f", "metadata": {}, "outputs": [ { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "robot_enekpt.plot_gsr_convergence(sortby=\"nkpt\");" ] }, { "cell_type": "markdown", "id": "d6c51087", "metadata": {}, "source": [ "We can also pass a function that will be called by the robot to compute the values along the x-axis\n", "and sort the results.\n", "The docstring of the function is used as label of the x-axis:" ] }, { "cell_type": "code", "execution_count": 14, "id": "0c06ae83", "metadata": {}, "outputs": [ { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "def inv_nkpt(abifile):\n", " r\"\"\"$\\dfrac{1}{nkpt}$\"\"\"\n", " return 1 / abifile.nkpt\n", "\n", "robot_enekpt.plot_gsr_convergence(sortby=inv_nkpt);" ] }, { "cell_type": "code", "execution_count": 15, "id": "f3c71f9c", "metadata": {}, "outputs": [], "source": [ "#robot_enekpt.plot_lattice_convergence(sortby=\"nkpt\");" ] }, { "cell_type": "markdown", "id": "6f1131c8", "metadata": {}, "source": [ "## Determination of the lattice parameters" ] }, { "cell_type": "markdown", "id": "01a787ce", "metadata": {}, "source": [ "At this point, the original Abinit tutorial proceeds with a convergence study for the optimized\n", "lattice parameters as function of the k-point sampling.\n", "In AbiPy, we only need to build different relaxation tasks with a slightly different input\n", "in which only {{ngkpt}} is changed." ] }, { "cell_type": "code", "execution_count": 16, "id": "da54898a", "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\n", " \n", " \n", " \n", "\n", "\n", "

\n", "\n", "
def build_relax_flow(options):\n",
       "    """\n",
       "    Crystalline silicon: computation of the optimal lattice parameter.\n",
       "    Convergence with respect to the number of k points. Similar to tbase3_4.in\n",
       "    """\n",
       "    # Structural relaxation for different k-point samplings.\n",
       "    ngkpt_list = [(2, 2, 2), (4, 4, 4)]\n",
       "\n",
       "    shiftk = [float(s) for s in "0.5 0.5 0.5 0.5 0.0 0.0 0.0 0.5 0.0 0.0 0.0 0.5".split()]\n",
       "\n",
       "    multi = abilab.MultiDataset(structure=abidata.cif_file("si.cif"),\n",
       "                                pseudos=abidata.pseudos("14si.pspnc"), ndtset=len(ngkpt_list))\n",
       "\n",
       "    # Global variables\n",
       "    multi.set_vars(\n",
       "        ecut=8,\n",
       "        tolvrs=1e-9,\n",
       "        optcell=1,\n",
       "        ionmov=3,\n",
       "        ntime=10,\n",
       "        dilatmx=1.05,\n",
       "        ecutsm=0.5,\n",
       "        diemac=12,\n",
       "        iomode=3,\n",
       "    )\n",
       "\n",
       "    for i, ngkpt in enumerate(ngkpt_list):\n",
       "        multi[i].set_kmesh(ngkpt=ngkpt, shiftk=shiftk)\n",
       "\n",
       "    workdir = options.workdir if (options and options.workdir) else "flow_base3_relax"\n",
       "\n",
       "    return flowtk.Flow.from_inputs(workdir, inputs=multi.split_datasets(), task_class=flowtk.RelaxTask)\n",
       "
\n", "\n", "\n" ], "text/plain": [ "" ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from lesson_base3 import build_relax_flow\n", "abilab.print_source(build_relax_flow)" ] }, { "cell_type": "code", "execution_count": 17, "id": "4aba9792", "metadata": {}, "outputs": [ { "data": { "image/svg+xml": [ "\n", "\n", "\n", "\n", "\n", "\n", "flow\n", "\n", "Flow, node_id=29, workdir=flow_base3_relax\n", "\n", "clusterw0\n", "\n", "Work (w0)\n", "\n", "\n", "\n", "w0_t0\n", "\n", "w0_t0\n", "RelaxTask\n", "\n", "\n", "\n", "w0_t1\n", "\n", "w0_t1\n", "RelaxTask\n", "\n", "\n", "\n" ], "text/plain": [ "" ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ "relax_flow = build_relax_flow(options=None)\n", "relax_flow.get_graphviz()" ] }, { "cell_type": "markdown", "id": "4ff4d4c9", "metadata": {}, "source": [ "```{important}\n", "If you want to run the flow from the shell, open lesson_base3.py and change the main function\n", "so that it calls build_relax_flow instead of build_ngkpt_flow.\n", "```" ] }, { "cell_type": "markdown", "id": "c72aa6cf", "metadata": {}, "source": [ "This is our first structural relaxation with AbiPy and this gives us the opportunity to introduce the `HIST.nc` file.\n", "This file stores the history of the relaxation\n", "(energies, forces, stresses, lattice parameters and atomic positions at the different relaxation steps).\n", "\n", "As usual, we use `abiopen` to open an Abinit file object:" ] }, { "cell_type": "code", "execution_count": 18, "id": "aef33ba4", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "================================= File Info =================================\n", "Name: out_HIST.nc\n", "Directory: /home/runner/work/abipy_book/abipy_book/abipy_book/base3/flow_base3_relax/w0/t1/outdata\n", "Size: 4.24 kB\n", "Access Time: Sun Oct 27 17:41:07 2024\n", "Modification Time: Sun Oct 27 17:38:46 2024\n", "Change Time: Sun Oct 27 17:38:46 2024\n", "\n", "============================= Initial Structure =============================\n", "Full Formula (Si2)\n", "Reduced Formula: Si\n", "abc : 3.866975 3.866975 3.866975\n", "angles: 60.000000 60.000000 60.000000\n", "pbc : True True True\n", "Sites (2)\n", " # SP a b c cartesian_forces\n", "--- ---- ---- ---- ---- -----------------------------------------------------------\n", " 0 Si 0 0 0 [ 4.10231609e-27 -5.80155106e-27 -3.31586262e-27] eV ang^-1\n", " 1 Si 0.25 0.25 0.25 [-4.10231609e-27 5.80155106e-27 3.31586262e-27] eV ang^-1\n", "\n", "Number of relaxation steps performed: 4\n", "============================== Final structure ==============================\n", "Full Formula (Si2)\n", "Reduced Formula: Si\n", "abc : 3.822962 3.822962 3.822962\n", "angles: 60.000000 60.000000 60.000000\n", "pbc : True True True\n", "Sites (2)\n", " # SP a b c cartesian_forces\n", "--- ---- ---- ----- ---- -----------------------------------------------------------\n", " 0 Si 0 -0 0 [5.53272690e-28 6.25956593e-27 9.58296409e-28] eV ang^-1\n", " 1 Si 0.25 0.25 0.25 [-5.53272690e-28 -6.25956593e-27 -9.58296409e-28] eV ang^-1\n", "\n", "Volume change in percentage: -3.38%\n", "Percentage lattice parameter changes:\n", "\ta: -1.14%, b: -1.14%, c: -1%\n", "\n", "Stress tensor (Cartesian coordinates in GPa):\n", "[[8.75674654e-03 5.30998779e-11 7.50894518e-11]\n", " [5.30998779e-11 8.75674654e-03 5.30995448e-11]\n", " [7.50894518e-11 5.30995448e-11 8.75674652e-03]]\n", "Pressure: -0.009 [GPa]\n" ] } ], "source": [ "hist = abilab.abiopen(\"flow_base3_relax/w0/t1/outdata/out_HIST.nc\")\n", "print(hist)" ] }, { "cell_type": "markdown", "id": "88a12306", "metadata": {}, "source": [ "To plot the evolution of the most important physical quantities, use:" ] }, { "cell_type": "code", "execution_count": 19, "id": "0e2c3a88", "metadata": {}, "outputs": [ { "data": { "text/html": [ " \n", " " ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.plotly.v1+json": { "config": { "plotlyServerURL": "https://chart-studio.plotly.com", "responsive": true, "showLink": true }, "data": [ { "marker": { "symbol": 0 }, "mode": "lines+markers", "name": "a", "type": "scatter", "x": [ 0, 1, 2, 3 ], "xaxis": "x", "y": [ 3.8669746216878647, 3.854279681180176, 3.8259212912797937, 3.8229616882673327 ], "yaxis": "y" }, { "marker": { "symbol": 0 }, "mode": "lines+markers", "name": "b", "type": "scatter", "x": [ 0, 1, 2, 3 ], "xaxis": "x", "y": [ 3.8669746216823344, 3.854279681174663, 3.8259212912743217, 3.8229616882618647 ], "yaxis": "y" }, { "marker": { "symbol": 0 }, "mode": "lines+markers", "name": "c", "type": "scatter", "x": [ 0, 1, 2, 3 ], "xaxis": "x", "y": [ 3.8669746217045797, 3.854279681196836, 3.8259212912963316, 3.8229616882838573 ], "yaxis": "y" }, { "marker": { "symbol": 0 }, "mode": "lines+markers", "name": "α ", "type": "scatter", "x": [ 0, 1, 2, 3 ], "xaxis": "x2", "y": [ 60.00000000026239, 60.00000000026239, 60.00000000026239, 60.00000000026239 ], "yaxis": "y2" }, { "marker": { "symbol": 0 }, "mode": "lines+markers", "name": "β ", "type": "scatter", "x": [ 0, 1, 2, 3 ], "xaxis": "x2", "y": [ 60.00000000030969, 60.000000000309704, 60.00000000030969, 60.000000000309704 ], "yaxis": "y2" }, { "marker": { "symbol": 0 }, "mode": "lines+markers", "name": "ɣ", "type": "scatter", "x": [ 0, 1, 2, 3 ], "xaxis": "x2", "y": [ 60.000000000420506, 60.00000000042051, 60.000000000420506, 60.00000000042051 ], "yaxis": "y2" }, { "marker": { "symbol": 0 }, "mode": "lines+markers", "name": "Volume", "type": "scatter", "x": [ 0, 1, 2, 3 ], "xaxis": "x3", "y": [ 40.88829184743489, 40.48691433264196, 39.59980943316966, 39.5079812945126 ], "yaxis": "y3" }, { "marker": { "symbol": 0 }, "mode": "lines+markers", "name": "P", "type": "scatter", "x": [ 0, 1, 2, 3 ], "xaxis": "x4", "y": [ -3.219553771466746, -2.3428255558750215, -0.23571583321272574, -0.008756746533999625 ], "yaxis": "y4" }, { "marker": { "symbol": 0 }, "mode": "lines+markers", "name": "min |F|", "type": "scatter", "x": [ 0, 1, 2, 3 ], "xaxis": "x5", "y": [ 7.84104182774146e-27, 1.0076075977210777e-26, 4.529448201456991e-27, 6.356619256521269e-27 ], "yaxis": "y5" }, { "marker": { "symbol": 0 }, "mode": "lines+markers", "name": "max |F|", "type": "scatter", "x": [ 0, 1, 2, 3 ], "xaxis": "x5", "y": [ 7.84104182774146e-27, 1.0076075977210777e-26, 4.529448201456991e-27, 6.356619256521269e-27 ], "yaxis": "y5" }, { "marker": { "symbol": 0 }, "mode": "lines+markers", "name": "mean |F|", "type": "scatter", "x": [ 0, 1, 2, 3 ], "xaxis": "x5", "y": [ 7.84104182774146e-27, 1.0076075977210777e-26, 4.529448201456991e-27, 6.356619256521269e-27 ], "yaxis": "y5" }, { "marker": { "symbol": 0 }, "mode": "lines+markers", "name": "std |F|", "type": "scatter", "x": [ 0, 1, 2, 3 ], "xaxis": "x5", "y": [ 0.0, 0.0, 0.0, 0.0 ], "yaxis": "y5" }, { "marker": { "symbol": 0 }, "mode": "lines+markers", "name": "Energy", "type": "scatter", "x": [ 0, 1, 2, 3 ], "xaxis": "x6", "y": [ -241.41093446379634, -241.41791318245208, -241.4251470981064, -241.42521715456513 ], "yaxis": "y6" } ], "layout": { "hovermode": false, "legend": { "font": { "size": 12 } }, "template": { "data": { "bar": [ { "error_x": { "color": "#f2f5fa" }, "error_y": { "color": "#f2f5fa" }, "marker": { "line": { "color": "rgb(17,17,17)", "width": 0.5 }, "pattern": { "fillmode": "overlay", "size": 10, "solidity": 0.2 } }, "type": "bar" } ], "barpolar": [ { "marker": { "line": { "color": "rgb(17,17,17)", "width": 0.5 }, "pattern": { "fillmode": "overlay", "size": 10, "solidity": 0.2 } }, "type": "barpolar" } ], "carpet": [ { "aaxis": { "endlinecolor": "#A2B1C6", "gridcolor": "#506784", "linecolor": "#506784", "minorgridcolor": "#506784", "startlinecolor": "#A2B1C6" }, "baxis": { "endlinecolor": "#A2B1C6", "gridcolor": "#506784", "linecolor": "#506784", "minorgridcolor": "#506784", "startlinecolor": "#A2B1C6" }, "type": "carpet" } ], "choropleth": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "type": "choropleth" } ], "contour": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0.0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1.0, "#f0f921" ] ], "type": "contour" } ], "contourcarpet": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "type": "contourcarpet" } ], "heatmap": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0.0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1.0, "#f0f921" ] ], "type": "heatmap" } ], "heatmapgl": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0.0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1.0, "#f0f921" ] ], "type": "heatmapgl" } ], "histogram": [ { "marker": { "pattern": { "fillmode": "overlay", "size": 10, "solidity": 0.2 } }, "type": "histogram" } ], "histogram2d": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0.0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1.0, "#f0f921" ] ], "type": "histogram2d" } ], "histogram2dcontour": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0.0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1.0, "#f0f921" ] ], "type": "histogram2dcontour" } ], "mesh3d": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "type": "mesh3d" } ], "parcoords": [ { "line": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "parcoords" } ], "pie": [ { "automargin": true, "type": "pie" } ], "scatter": [ { "marker": { "line": { "color": "#283442" } }, "type": "scatter" } ], "scatter3d": [ { "line": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scatter3d" } ], "scattercarpet": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scattercarpet" } ], "scattergeo": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scattergeo" } ], "scattergl": [ { "marker": { "line": { "color": "#283442" } }, "type": "scattergl" } ], "scattermapbox": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scattermapbox" } ], "scatterpolar": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scatterpolar" } ], "scatterpolargl": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scatterpolargl" } ], "scatterternary": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scatterternary" } ], "surface": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0.0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1.0, "#f0f921" ] ], "type": "surface" } ], "table": [ { "cells": { "fill": { "color": "#506784" }, "line": { "color": "rgb(17,17,17)" } }, "header": { "fill": { "color": "#2a3f5f" }, "line": { "color": "rgb(17,17,17)" } }, "type": "table" } ] }, "layout": { "annotationdefaults": { "arrowcolor": "#f2f5fa", "arrowhead": 0, "arrowwidth": 1 }, "autotypenumbers": "strict", "coloraxis": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "colorscale": { "diverging": [ [ 0, "#8e0152" ], [ 0.1, "#c51b7d" ], [ 0.2, "#de77ae" ], [ 0.3, "#f1b6da" ], [ 0.4, "#fde0ef" ], [ 0.5, "#f7f7f7" ], [ 0.6, "#e6f5d0" ], [ 0.7, "#b8e186" ], [ 0.8, "#7fbc41" ], [ 0.9, "#4d9221" ], [ 1, "#276419" ] ], "sequential": [ [ 0.0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1.0, "#f0f921" ] ], "sequentialminus": [ [ 0.0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1.0, "#f0f921" ] ] }, "colorway": [ "#636efa", "#EF553B", "#00cc96", "#ab63fa", "#FFA15A", "#19d3f3", "#FF6692", "#B6E880", "#FF97FF", "#FECB52" ], "font": { "color": "#f2f5fa" }, "geo": { "bgcolor": "rgb(17,17,17)", "lakecolor": "rgb(17,17,17)", "landcolor": "rgb(17,17,17)", "showlakes": true, "showland": true, "subunitcolor": "#506784" }, "hoverlabel": { "align": "left" }, "hovermode": "closest", "mapbox": { "style": "dark" }, "paper_bgcolor": "rgb(17,17,17)", "plot_bgcolor": "rgb(17,17,17)", "polar": { "angularaxis": { "gridcolor": "#506784", "linecolor": "#506784", "ticks": "" }, "bgcolor": "rgb(17,17,17)", "radialaxis": { "gridcolor": "#506784", "linecolor": "#506784", "ticks": "" } }, "scene": { "xaxis": { "backgroundcolor": "rgb(17,17,17)", "gridcolor": "#506784", "gridwidth": 2, "linecolor": "#506784", "showbackground": true, "ticks": "", "zerolinecolor": "#C8D4E3" }, "yaxis": { "backgroundcolor": "rgb(17,17,17)", "gridcolor": "#506784", "gridwidth": 2, "linecolor": "#506784", "showbackground": true, "ticks": "", "zerolinecolor": "#C8D4E3" }, "zaxis": { "backgroundcolor": "rgb(17,17,17)", "gridcolor": "#506784", "gridwidth": 2, "linecolor": "#506784", "showbackground": true, "ticks": "", "zerolinecolor": "#C8D4E3" } }, "shapedefaults": { "line": { "color": "#f2f5fa" } }, "sliderdefaults": { "bgcolor": "#C8D4E3", "bordercolor": "rgb(17,17,17)", "borderwidth": 1, "tickwidth": 0 }, "ternary": { "aaxis": { "gridcolor": "#506784", "linecolor": "#506784", "ticks": "" }, "baxis": { "gridcolor": "#506784", "linecolor": "#506784", "ticks": "" }, "bgcolor": "rgb(17,17,17)", "caxis": { "gridcolor": "#506784", "linecolor": "#506784", "ticks": "" } }, "title": { "x": 0.05 }, "updatemenudefaults": { "bgcolor": "#506784", "borderwidth": 0 }, "xaxis": { "automargin": true, "gridcolor": "#283442", "linecolor": "#506784", "ticks": "", "title": { "standoff": 15 }, "zerolinecolor": "#283442", "zerolinewidth": 2 }, "yaxis": { "automargin": true, "gridcolor": "#283442", "linecolor": "#506784", "ticks": "", "title": { "standoff": 15 }, "zerolinecolor": "#283442", "zerolinewidth": 2 } } }, "xaxis": { "anchor": "y", "domain": [ 0.0, 0.45 ], "matches": "x5", "showticklabels": false }, "xaxis2": { "anchor": "y2", "domain": [ 0.55, 1.0 ], "matches": "x6", "showticklabels": false }, "xaxis3": { "anchor": "y3", "domain": [ 0.0, 0.45 ], "matches": "x5", "showticklabels": false }, "xaxis4": { "anchor": "y4", "domain": [ 0.55, 1.0 ], "matches": "x6", "showticklabels": false }, "xaxis5": { "anchor": "y5", "domain": [ 0.0, 0.45 ], "title": { "text": "Step" } }, "xaxis6": { "anchor": "y6", "domain": [ 0.55, 1.0 ], "title": { "text": "Step" } }, "yaxis": { "anchor": "x", "domain": [ 0.7, 1.0 ], "title": { "text": "abc (A)" } }, "yaxis2": { "anchor": "x2", "domain": [ 0.7, 1.0 ], "tickformat": ".3r", "title": { "text": "αβɣ (degree) " } }, "yaxis3": { "anchor": "x3", "domain": [ 0.35, 0.6499999999999999 ], "title": { "text": "V (A³)" } }, "yaxis4": { "anchor": "x4", "domain": [ 0.35, 0.6499999999999999 ], "title": { "text": "P (GPa)" } }, "yaxis5": { "anchor": "x5", "domain": [ 0.0, 0.3 ], "title": { "text": "F stats (eV/A)" } }, "yaxis6": { "anchor": "x6", "domain": [ 0.0, 0.3 ], "title": { "text": "Energy (eV)" } } } }, "text/html": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "hist.plotly(template=\"plotly_dark\");" ] }, { "cell_type": "code", "execution_count": 20, "id": "b4e0a733", "metadata": {}, "outputs": [], "source": [ "hist_robot = abilab.HistRobot.from_dir(\"flow_base3_relax\")\n", "\n", "hist_table = hist_robot.get_dataframe()" ] }, { "cell_type": "markdown", "id": "7a1b936a", "metadata": {}, "source": [ "There are several entries in the `DataFrame`:" ] }, { "cell_type": "code", "execution_count": 21, "id": "0d8c8f1b", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Index(['formula', 'natom', 'alpha', 'beta', 'gamma', 'a', 'b', 'c', 'volume',\n", " 'abispg_num', 'spglib_symb', 'spglib_num', 'spglib_lattice_type',\n", " 'num_steps', 'final_energy', 'final_pressure', 'final_fmin',\n", " 'final_fmax', 'final_fmean', 'final_fstd', 'final_drift',\n", " 'initial_fmin', 'initial_fmax', 'initial_fmean', 'initial_fstd',\n", " 'initial_drift'],\n", " dtype='object')" ] }, "execution_count": 21, "metadata": {}, "output_type": "execute_result" } ], "source": [ "hist_table.keys()" ] }, { "cell_type": "markdown", "id": "3f9e389d", "metadata": {}, "source": [ "Let's select some of them with:" ] }, { "cell_type": "code", "execution_count": 22, "id": "2fca5b3c", "metadata": {}, "outputs": [ { "data": { "text/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", "
alphaafinal_energyfinal_pressurenum_steps
w0/t1/outdata/out_HIST.nc60.03.822962-241.425217-0.0087574
w0/t0/outdata/out_HIST.nc60.03.829282-241.255630-0.0132594
\n", "
" ], "text/plain": [ " alpha a final_energy final_pressure \\\n", "w0/t1/outdata/out_HIST.nc 60.0 3.822962 -241.425217 -0.008757 \n", "w0/t0/outdata/out_HIST.nc 60.0 3.829282 -241.255630 -0.013259 \n", "\n", " num_steps \n", "w0/t1/outdata/out_HIST.nc 4 \n", "w0/t0/outdata/out_HIST.nc 4 " ] }, "execution_count": 22, "metadata": {}, "output_type": "execute_result" } ], "source": [ "hist_table[[\"alpha\", \"a\", \"final_energy\", \"final_pressure\", \"num_steps\"]]" ] }, { "cell_type": "markdown", "id": "6188948d", "metadata": {}, "source": [ "and print the evolution of important physical properties extracted from the two files:" ] }, { "cell_type": "code", "execution_count": 23, "id": "b14d474b", "metadata": {}, "outputs": [ { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "hist_robot.gridplot(what_list=[\"energy\", \"abc\", \"pressure\", \"forces\"]);" ] }, { "cell_type": "markdown", "id": "1c5ed2c0", "metadata": {}, "source": [ "We can also compare the two structural relaxations with:" ] }, { "cell_type": "code", "execution_count": 24, "id": "4768a4fb", "metadata": {}, "outputs": [ { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAmEAAAGhCAYAAAAp9WNiAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAAD0KklEQVR4nOydZ3hURReA3y3Z9EpJJUBCDSX0BOlFRaqgqIAoAkEFBMEuCCogoljo0hEUP0CRJiBVakApCYSaUAIhECC97CZb7vdjyZJlE0iFlHl9fLJ778zs3MPs2TPlnCOTJEkiHyQnJ+Ps7JyfogKBQCAQCASCRyDPb8E2bdowatQotm/fTlZWVkn2SSAQCAQCgaDcI8vvSth7773Hnj170Gg02Nvb8/TTT9O7d2+Cg4ORyWQl3U+BQCAQCASCckW+jTAAjUbDrl272LJlCwcPHkSv11OpUiV69uxJz549adiwYUn2VSAQCAQCgaDcUCAjLCfJycls27aNLVu2cPz4cQCqV69O79696dWrF9WqVSvWjgoEAoFAIBCUJwpthOUkLi6OzZs389dff3Hu3DlkMhmBgYH873//K44+CgQCgUAgEJQ7isUIy+bChQvMnj2b3bt3I5PJOHfuXHE1LRAIBAKBQFCuUBa1gdjYWLZs2cKWLVuIjIxEkiSaNm1Kr169iqN/AoFAIBAIBOWSQq2EJSQkmM6DhYWFIUkSfn5+9OrVi169euHj41MSfRUIBAKBQCAoN+TbCMvIyGDnzp1s2bKF0NBQdDodVapUoUePHvTq1YsGDRqUdF8rHJIkYTBY/vNoZVoyZOnGNzmjg9wraifZYyVZlXwHSyESoJfpQCaBJEMhKREBVEAul+U6lioq+ZGHXC4rs+F38tIdaVlq9DaZxje56A6FxhoHlW3Jd7CUIr4n5gh5WFLcuiPfRliTJk3IzMzEzs6OZ555hl69ehEcHIxcnu94r4ICotcbSEhIN7tmwMDPbgtIk6eSq3UhgYPBkdcT3kae/1i85YIo1QUOOOwiTZFquuagd6RdWldqZdV9gj17chgwEGdzAxy1kGqFu8a7wo2LB1Eq5bi62pOYmI5OZ8iznJubPQpF2ZRVbrpDq9cx0/Ad9h4SslweSzJA+k057yvGY6Uo8kmVMkd+x0VFQcjDkpLQHfn+prVu3ZpevXrRpUsXrK2t81tNUMzEWl03MzIskEGaIpVVrouwlexQSAoUKFBICuT3/ipy/JVLChQoUUhyFJISOca/lmXyqJtH2cf9Qx+lusA2pz8trqfJU9nm9CfPpfStcIaYhVHqCA52wii9rrzOdbSgtMJdV3GM0t1RYTi0zXvOLZODg7eB3QfD6Fa3xWPsmUBQccm3EbZgwYI876WmpmJnZ4dCoSiWTgnyJkOe/uhCQIoyiRSSSrYzD0EmyR4w4JQo7hl4ckl+3/BDmauR96DBaHqfi9EnR85ex+33PvjBjgAS7HfYiU+iL1aSFXIUyMr5JqUwSi2p6EbpXU1Svsqd9NjP7esxBFaqTV17P2ykirs9KRCUNIVecz59+jQ//vgjx44dQ6vVsnTpUlq3bk1CQgITJkxgyJAhBAUFFWdfBYCdwT5f5Z5K64irvhJ69BhkevQyHXoM6GU6DPf+6tGjl+nvl8nxXi/ToZcZMGD8q0f3kLLGazmRZBI6dCDTlYQYCoYM0hVpLK48y3TJaAjmWLmT7q3fWaz+yc0MwkeXV9xbTVQ8tF7O+/JcPif7emGMRQMGDjjsMj37g7JAggMOu/BLqF1hVoGEUQqVbVxIzEc5h1pZJHOe/ZxnP6C9aY1TShXq2vtR196PSroqKBATboGgOCiUEXbixAlef/113N3d6d27N+vWrTPdc3NzIy0tjTVr1ggjrATw0lbDQe/4yDNhTdWtHusPrISUw7jLNvbMDbW8jL0Hr+Vq5FkYiPevpcvSSFEmF6i/BpkBAwaQaUtIIsWD3GScyR8w2u4bew+uFmbKMvO1Zb3dcQMOBkdyH0h5XX34ndxLF9yQLHidvJ9BQuK0zcnci1Ugo7RLrSacjN390DNhGXdkaHdWI9nxDg711FSqC1aemag9YwgjhjD2Y8iUoYp3pbqsGrXtauKp8743jgQCQUEplBH2ww8/4O/vz9q1a0lLSzMzwgCCgoL480/LWaeg6MiR0y6tq3FWL5Grh1O7tK6P/cdEhsxkDOTsy+MgxiqaP11+e2S5Xkkv4anzymHoGcyMuft/DbkahA/eN69nMCt//68hV8My+/MfLC/JzAWXbSzqSmD39JLNxeJvtCxyzyiNtbqOj7b6k+5NiWGlUOJ3Nog4jyNIBswMMeneGeOaZ4J4+dmOACQmqjm85gon71zkljIWZc1UvFpJ2LpK6LwSuEQClwgHQJZqQ9UsT/xV1fHUeVNF54EVFdNDWyAoCIUywk6fPs348eNRqVS5umG6u7tz9+7dIndOkDu1suryXEpfS09AQ8U535KT/K4O+mpr3DdOS6nXtSH7Pwvjz2C2Gviw+/GKO4TbHXvkZ9VRN8DJ4JTrPSlPoy93weUtzoILWipgnUeVT1TEE219+ZHt5Pe8ZVnm5UYdWfMPXK53FAev+3JLvynH70IrXm7U0XTN1dWWHp0D6EEAAKmpmfy74wZHoyK5qruG1iMJr1YGqjaWkDtqiOMKcVwxVtbLcMxwo7rCF0+dNx46L5z1ruX+LKZAUFAKZYQplUoMhrzdM+Pi4rCzsyt0pwSPplZWXfwSaovwA5Te1cHCIL/3H9K9r2YhjEUDBi5ZX3ikUfp0Wo8yIZOiEmMVnS8jLL/nLcs6LzfqiFbflr2Hw0glHUfs6eTXBKtGD/85cHS0pktnP7p09gMgI0PL8eM3ObwumvMpl0lxvoNHcz3erSUcPSVSHeOJIJ4IjFvBSq01XgZvPHVeeGi9cdd5Yi3ZlPjzCgSlmUIZYYGBgfz9998MGTLE4l5GRgbr16+nZcuWRe2b4BHIkVNNVx1X7EnUpaOj4sZyEauD9ylPRmlxkN+VUi9ttcfetyeFlUJJ9/qtihQHys7OinbtfGnXzhdoR2amjpMnbxE6J4ajUVe5bX2Tyk20+ARLeDaXwCaTa1zmWg6D2EXrhqfeGw+tF+5aLyrpq1SYcSkQQCGNsDFjxvDqq68yYsQIevToARiTd8fExLB06VISEhIYOXJksXZUIHgUYnXwPsIovY8wSh8P1tZKgoN9CA72AYLRavWcOnWbw3/HcHTadS5nXMe1URbeQRLewQbcakGSVQJJVgmcszkNgNJghbvOA3ed0TDz0HphLzk82QcTCEqQQuWOBAgNDeXzzz8nOjra7Lqvry9Tp06lVatWxdLBikxuUa8fREQ1tkTI5D4iYv59CppRobxFzH+Qx/090esNnDlzh9DQGxw+fJ2wyOs41NXgHWwwGmZBEta5HFF01DvhrvXC4942ZhWdO8rCR1fKE6E3zBHysKQkIuYX2gjL5ty5c1y9ehVJkqhWrRoNGzYss/nWShulUZGWBYRMzBHyuE9BjFJhhJUsBoPEhQvxHD4cw5EjMYQeuY5UKR3vYMn4f5BE1YaW4TTkkpwqOnczw8zJ4FzkQ/9PWh6lDSEPS0qlESYoOcqCIi2NCJmYI+RhTkXNHfkgpW1cSJLE5ctJHD58ncOHYwgNjeFuaipeLbKNMgPewRIO7pZ1bQ12uGs98bi3jemu80Ql5T+9nlgxtqS0jY/SwBPLHXny5EmaNm2av14WY12BQCAQVAxkMhn+/q74+7syeHBjJEni2rUUQkONBtnh1TFERyfhUgPjFua91TKv5hJqqwyuWl/iqvUlY2MSuOkrG8+V3TPMXPWVcjWsKno6K8GTJV8rYY0bNyYwMJABAwbQqVMnbG0fnkssPT2dPXv28L///Y+IiAjCw8OLrcMVibI4my0NCJmYUx7kkZSURHJyEjIZODu74OzsUui2xEqYkbI4LmJjU40G2eEYjhy5QWRkAgprCY8mxtUyn2CJ6m1lOPjoLepaGVS46zzvGWZGb8xYq5j76axycdioCOms8qIsjo+S5omthP3999/MmzePDz/8ECsrKxo3bkxAQAA+Pj44OzsjSRIpKSnExMQQERHBqVOn0Ov19OnTh5kzZ+bv6QqIXq9n2bJl/PPPP0RFRSFJEnXr1mXs2LG0aNEiz3rTpk1j5cqVDBo0iEmTJpmuR0dHs3TpUsLDw4mMjMTPz48tW7bkqy/vv/8+p06d4vbt21hZWVGnTh3efvtt2rZtW+TnFAgqImq1mr17d3HgwD4iIk6RnJxkdt/Z2YWGDRvRrl1HOnXq+siJoaB84OXlyAsv1OeFF+oDcPt2OkeP3uDw4RgO74hh/SxjkHB7dzneQRI+wQb8Oyio2kyP1iaLGFU0Mar7zmSy7KjEFTidleDJUqAzYQkJCWzatIndu3dz+vRpNBqN2X0bGxsaNmxIly5d6NOnD25ubsXe4WzS09Pp2LEjffv25amnnkIul7N27Vr27NljSib+IBcuXGDAgAHIZDL69OljZoTt2rWLKVOmEBgYyJUrV5AkKd9G2NixYwkKCqJGjRpkZmby+++/s3fvXlauXPlQg/BR5DWb1et16PXGxNgKhRwnJ1tSUtTo9WK2AkImD1KW5JGcnMzq1avYsmUjWVlZ+Pn5U6dOXTw9vXB0dESSIC0tlZs3Y7l48QKXL19CpVLRs2cfBg58NV8rZHnLQ4ZSaYVcbvzBFSthZY/ERDVHjtwgNPQGoaExnD59G4NBQiaXqNLAuFpWp4uS6k+BdbXMfLXZN2lAuU5nlRflcXwUlVJ1MF+n03Hz5k0SExMBcHV1xdPTE6Wy+F2Hc0Ov15OWloazs7PZtZ49e1K9enV++uknizqvvvoqrVq1YsOGDXTs2NHMCDMYDCbl+/HHHxMREZFvIyy3vnXp0oV27doxZcqUQrVhbMdckUqSRHz8LTIyHpKcWSAowwwdOhR3d3e6dOlCq1atcHLKPa1SNikpKfz777/s2bOHuLg4li5dWqTPV6msqVq1GnK5XBhh5YCUlEz++y/WdNA/LCzO9KxNhurptdRy2/JBuib1pL62YUl3tdRREcZHQXli25G5d0ZJtWrVqFbtyUSZVigUZgZY9rW6dety7do1i/KbNm0iJiaGxYsXs2HDBov72QZYcfXN0dERrVZbbG0CaLVZZGSk4uTkhq2tAyISiKC88cUX02jZMijf5T08oE6dhrz66lD+++8oHh6+hf7szEwNiYm3uXMnDhcXN6BipDEqzzg5WdOlS026dKkJQHq6lmPHYgkNjeFY/Fkg/pFt7FPtQavIpF5mwwJ5XAoE+eHxLFs9JnQ6HeHh4TRv3tzselpaGt988w2ffvppiZ0dkSQJvV5Pamoq69evJzo6mi+//LLI7SqV941Dvd5oddnZOaBSPTznml5v4MiRG8TFpePubk9wsHeZndULKg5t2nR4LHVDQw/y668ruXr1Munp6VSuXJU2bdrSrdvTHDwYio2NHS+++DyVKpkfqVCr1cyfP5+tW7dy9+5dPDw86Nu3L8OHDzftAsTExNClSxeLzwwMDGTt2rVm106cOMGMGTM4d+4clSpVYsCAAYSEhIhYiyWEvb0VHTpUp0OH6vzxpxvnrm/EyRuLWGQAkgRIoLXLYB87CbXfT31NIxqrm+NicH3sfReUT8qVEbZkyRLi4uIsclrOnTuX6tWr07179xL77N9//52JEycCYGdnxw8//FDk0BxyuQxX1/uz8YwMGTduPLreli2RTJy4l9jYNNM1Ly8Hpk7tRM+etYvUJ4GgtBAff5fdu3fw99/bWLp0VYHqpqSkEBDQgBdffBknJ2euXLnE0qWLuHDhLM8/35fIyChOnTpFp04dzep9+eWX7Nixg/Hjx+Pv709YWBizZ89GrVYzbtw4s7Ljx48nKOj+qp69vfnKWnR0NMOGDaNNmza8++67XLhwgZkzZ6JQKBg2bFiBnkdQcDyqOjBrrJIXf9chGcwNMeneTtOGwQo6dfem+supJCsTCbc7RrjdMapn+hOobo6vtmaRg8QKKjalyghLTU3l9u3bjyxXrVo1VCqV2bVDhw4xZ84cRo4cScOG9/fvIyMj+fXXXy1moMVNly5dqFevHomJiWzfvp13332XuXPn0qFD4Wf2BoNESkqG6X1mpuYhpY1s2RLJsGGbefCk382baQwbtpmlS3sJQ0xQZsnIyGDfvj3s2LGNEyeOYTAY8PLyLnA7zz5rPiFr1qwFMpmM77//hs6dnwEUpKWZn6kyGAxs27aNYcOGMWjQIACCg4O5cuUKf/31l4URVr16dZo0aZJnH5YuXYqrqyvff/89KpWK1q1bk5CQwE8//cTgwYMtdJygeAkO9iZllBO/90/hmR91OOc4WZMSAzveVXL+TzkRq29RfaIT4+c/hX3nW0RbXyba+hLR1pdw0bnRWN2M+pmNxFaloFCUqv2p7du3071790f+f/36dbN6Z86c4Z133qFnz56MHj3a7N7XX39Nt27d8Pb2JiUlhZSUFAwGA1qt1vS6OHBzc6NRo0a0b9+er776ivbt2/Ptt98WuV2dzmD6/0HPNkmSSE/Xmv5PScnk00/3WhhgxrLGvxMm7CUlJdNU52F+GZIk8fHH42nbtgXTpxd9axVg2rTPuXw5qljaAggNPcTbbw/l7beHMW3a54X+9zxx4hhz5/5Y4HqLFs0nMvLiQ8vs2bOLt94aytixb3P7dpxF3Y0b15uVHTCgH8OGDTZrIybmOrNnf1egvuVsNycTJ37IzZuxud67eTOWf/898si2p06dTEpKcr77cuLEMa5di87zfs7nzcjIYPToEQAsXbqQ/fv/Yd++Pbz4Yk+6devItGmfEx19lSZNmlGnTj30ej2vvfYyo0ePYMeO7fnu04M4ORnPmOp0OiRJsvhuSJKETqfD0dHR7LrRa7Pg/k379++nS5cuZsZW9+7dSUlJ4eTJk4V4AkFBUCjkTJ3aiQt/yplb04qVHZWsH6BgZUclc/2suLBBzuuvN8bd3Z7oqymM7X6Mea21BOzsRWBGC6wMKpKUCex33MUyt3nss99JoiLhST+WoIxRqlbC+vfvT//+/QtUJzo6mpCQEJo2bcrUqVMt7l+5coWDBw+yadMms+tr165l7dq1bN26FX9//yL1OzcaNGjA/v37i73dbCRJomfPNfz3X+4/prnXMa6I1ao1z3StVSsvNm9+OdczKPHxxkOrs2f/xOHDB4ve6RKgRYtWtG7dBjAaeKdPnyIwsEme5XN6wRYHUVGRjBgxMs/7Op2ONWt+Ze7cRZw7d4YVK5bw4YcTzOp+/fUU+vTpB0Dz5i1o124Nb7011KydI0cOERzcpkB927TpT1O7+SXbCGvVKjjPMgaDgbS0VJPRkh9OnjxOvXoB+Prm39U/PPwkhw8fYM2a1ajVGbi6uvHyy4P43/9+ISTkbZ57ridgNNTq1QugTZt2+W47G71ej06n4+rVK6xatZzmzZvj4uLK3buWB7YVCgX9+vXjl19+oVmzZvj7+xMeHs7GjRsZOdJyDHz++eeMGzcOFxcXunTpwvvvv4+LiwtgNDRv3ryJn5+fWR0/Pz9kMhmXL18228osDDnPk+ZG9hnRinxW9Pnn66JQyPjkkz1E77t/fMPb25GvvupEr151mDo1iwULjjN79r+cPBnHgGf+5pln/JjwxUD0jWMJsz5GoiKBU3bHOWV3nBpaP5poWlBD51+mtyrF+LCkJGRSKCNs0aJF9OnTB3f3XJJ4PUZu377N0KFD8fT0ZPbs2VhZWVmU+f7778nMNI8HM378eJo0acJrr72Gl5dXifTt+PHjJe45WtJnd2fNmklExCnCw8Po0aM3ALt2/c2aNauRyWQMG/YmgYFN+eyzj/j221lMmTIJH59qvPFGCKNHj2Du3EW5trtmzWpu3bqFs7MzkydPJTk5icmTP0Wv1+Pm5sYXX0zn1q2bTJkyCSsrK6pV8+XDDydw/vxZ5s2bhV6vp23bDgwcONj0b569EuHp6ZnrZw4dOojGjZuSnJzE2LHvM2PGFNLT06lUqTITJ35hVnbOnO+5cOE8mZkaPvxwAv7+tXnvvXd4990PMBgMzJ37IzNnziIxMQE3NzeuXYvmt99+4aOPJjBqVAg9e/ahS5dn+Pjj9xgzZjzVq9e4F+S4CfPmzQIgISEeNzc39u3by7Vr0YwePYLevfvxzDPdcu1/WNhJevXqy+3bcUyb9gU6nRZ//1qMH/8RW7duRq3O4IUXXubQoQOcP38WN7dKpnbfeCMEg8HAggWz8fDwIj7eGNDy0qUofvjhG7RaLXXr1mP8+I/YsOEPIiJOcf78Wb766lu+//4b7t69g16vZ/LkaXh4eHD+/Fnq1jUGy/zf/35h797dyOVy3n33A+rWrcewYYNNZ7SGDRvM/PmL2bZtC/v27WHPnp189tnDV1WXLl3ImTMRjB49AmdnZ9q2bU+rVsFs3/4Xbdq043//+wU7O7uHtnHixDF++eVnrK2tiY29weTJU/Dzq0Vo6EGWL19iii22cOE87twxHoFo1SqIt956k0uXLL2rs5k8eTKTJ082myy++eabvPHGG6b3KpWKAQMG0LZtW5ycnAgPD+enn34iIiKCdevWYWVlRWqqMczMgyE4VCoVtra2JCfnf5UxNx48T/ownJwqdqDb115ryqBBgRw4cI2bN1Px9HSkXTtf0w+tq6s906Z1ZezY1nz55T4WLjzOjh2X2bXrCm+80YTPvxiOxvs2RwglkotctbrMVavLuFGJIIJpSjNseLgjVWmmoo+P3ChOmRTKCPvxxx/58ccfadGiBX369OHZZ5/FwcGh2DqVHzQaDSEhISQmJjJhwgQiIyNN91QqFQEBAQC5nsmwtrbG3d3dbKapVqvZt28fADdu3CAtLY3t241bG61atTIFnn399deJjY1l586dAPzzzz+muGOenp4kJyezZcsWDh48yPfff18izw7GPGubN79MRobOdO3IkRgGDPjzkXV/+60vwcE+ANjZKfP0xBo5cgzz5v1Iv34vcfjwQfR6PatWrWDRohXodFrGjHmbpUtXkZWVhV6vR6vVcuXKZW7fjsPd3SPPzw8IaMgnn0xiwYI5HDy4j6eeascPP8xDqVTy448zOXHiP+LibvHMM8/Rr19/0xbjggVzmTbtW5ycnPjww3F069YdN7dKbN26mV9//Rlv72q4uOTutZSamsqLL76Mj0815s79kRdffIXmzVvyyy8r2L9/r1mQz5CQkdjY2HDx4nlWr17F5MlTef/9T5gxYyoymYyPP/4MmUzG0aOhtGrVGl/f6ly/Hk1WVhaOjo6cPh2Ol5cP9esHkJqagr39/e+GwWCMS5Rdt0OHTqxcuSxPgxUwTSKsra355ZcVDBjwKsHBTzF9+peEhZ3ItU7fvi+yZctGU7sjRgzhxx/nY2Njy4ABxtUxHx8f5sxZeO+ZxnP9+jWef/4FqlZ1Z/TodwH4+OPPsLGxYd++vWzc+AdvvjmKo0dDCQ5+ivj4uxw4sI8FC5YSF3eLGTOm8uOP8y36Ym1tw3PP9XzoalV6epppCzIs7AQqlYrZs3/ixIljpnrp6Wn8+OO393IK5r21mY1er2P69DmEhh7ir782MWrUu/z00zzmz1+Mvb0DBoOBWrXqoNGouXLlMitWLGHmzJn06fNinm3OnDmTf/75h6lTp1KjRg3CwsKYN28eTk5ODB8+HICqVavy+eefm+q0atWK2rVr8+abb7Jz584SdRDK5sHzpLlRloL4Pg6aNXPHyakGKSlqUlLUFvetrGDKlA68/nojpkw5wObNkSxdepLVq08zcmQL3nmnJ21cMgi3Pk6EdTgJsni28Re7pJ0EZDaiSWZz3AyVn8CTFQ4xPizJr0ycnGxLNk7Y3r172bx5M5s3b2bChAlMmTKFTp060adPH9q1a4dCoShMswXi7t27nD9/HoC3337b7J63tzd79uwpUHvx8fGMHTvW7Fr2+5UrV5oMNoPBgF5/P8BftWrVyMrK4rvvviMxMRFXV1fq1q3LqlWraNWqVYGfqyDIZDLs7e+v/nXsWB0vLwdu3kzL9VyYTAaeno507Fi9UMupSUmJuLt7YG1tjbW1NUqlEp1OR+3adTl4cB8eHp7cvh3H8eP/ERiYt2do9ipK/foBXL9+jeTkZL77bjqpqancvXuHunXr0bnz0yxfvoQvvphIq1bBPPdcTy5diuTTT98Hsp044nBzq0T37r3o3r0X3303g/3799K167MWn+no6IiPj3Fl8urVy5w9G8Hy5YvJzMykW7fuZkbY6tUrOXbsXwDTWPb29sHFxRU7Ozs8PY2rp8eOHeXddz8EwMXFlcOHDxAU9BTHj/9HePgJmjRpioODI+np97c55HKFRd1HERZmbAuM4Q/q1w8wyS8m5hoKxf2vcV5nkwwGg2n70N/f6JgRGxvL3Lk/kpmpITb2Bnfv3jGro9frmT9/FpcuRZGZmYmfn3Hb/vz5s7z++jDOnj1DrVq1kcvleHp6kZaWxoPk96yUvb2DyWD89NMPOHDgH9577x3c3T3QaDQ0a9aCF154meDgNrzySl+2bdvC4MFvPLTNWrXqAODu7k5qauq98etuMorlcjm1ahll0bBhY2rV8ick5A3q1TuHlZXlIeuLFy+ybNkyFixYQOfOnQFo2bIlOp2OWbNm8corr+Q5Ge3QoQN2dnacOXOG7t27m86VZa+IZZOVlYVarbaIgVgY8htgU683iGCcOXiUPGrUcGHp0l78918sX3yxn3//jeW7746wYkU4778fzODBHWipassFmwjCbY+TqIwn3OY44TbH8c2qSWN1c2pklZ2tSjE+LClOmRTKCHN3d2f48OEMHz6cixcvsnnzZv766y+2bduGq6sr3bt3p3fv3gQGBhZLJ3PDx8eHCxcuFKpubgZafttbtcrcFd7f35/58y1n/0+C7IOmw4ZtRibDzBDLXuyaOrVjofezXVxciYu7SWZmJjqdFq1Wi1KpJDCwCcuXL2HYsDeJjr7CunX/Y/Jky/N52URGXqBevfqcP3+OevXqs3Pndp56qh29ej3PDz98gyRJKBQKRo0yGsGvvvoSzz7bnVq1ajN16jc4ODig1+uRy+VkZWWZDjbb29tjY5P7sr8sh/959eo1aN++k8lQ1Ol0nDoVBkBychL//XeUBQuWcv78OebO/QEwGkJKpZLk5CQiIy/i71+L9PR0049p48ZNWLlyORMnfs6VK5c4cGAfL774CiqViujoq2i1Ws6fP4u/fy0MBoNZ3UfFhDp69DD9+r0EGMfp2bNnaN26DefOneW553qSlpbK1atXAIiKuu8kkLNduVxOSkoKNjY2JseIDRt+55VXBtGyZRAffTQOSZJQKpWm1brIyIukpaUxb95i/vlnN4cOHSAlJRlHR6d7hpcnkZEXMRgMxMXdMhkgcrmcjAyjZ2FsrDGmSs52H8XEiV/w3nvv0LNnH37+eSlr1vzKn3+uIzj4KQIDm+U7hlbOcpIk4eLiyu3bt8nIyMDOzs7ifKCfXy0UCgWJiQlUrWq5rR0VZZRb/fr1za4HBASQlZVFXFxcvncEjMa8J5cvXza7np0y7cGzYoLSR8uWxvO027dfYsqUA0RFJfLJJ3tZtOgkEya0pVevpjTUNOW6VTSnbI9xRRXFNdUVrqmu4KR3obG6GQGaxlhLZXerUlB0inwwv06dOrz33nu89957HDt2jJ9//pnVq1ezevVqfH196dOnDy+//DKVKlUqjv4KHkHPnrVZurSXRZwwT09Hpk7tWKTwFAqFgkGDhjB6dAgymZyQEOMKZOPGTbh0KZLGjZvg4uLKb7/9QvXqNfJs58KFc+za9TdOTs4MH/4WV65cYsqUSRw6tB9ra+MKxMGD+/njD2NYkaCgYORyOW+99Q4TJhjPZVlZqZg+/Vu2bdvCrl07AKhWzZennnr04ezXXhvKjBnTWLp0IWDcds3G0dEJJycnRo8eQYMGjQDjVvWiRfP5+uvvyczU8MUXExk+/C3q1Qsw1QsMbMqKFUuoWdOfwMCmnDt3xnRu6aWXBvDOO2+iUqmYMOFzzp49Y1a3WbPmfPzxeLp3742DgwM//7yM69evMXbsSD777AtiYq6bVvEGDXqdadM+Z9Wq5fj5+dOkSTM0Gg2//fYL778/hipVqlK5chUAfH2rM2HCB7z88iCGD3+Ld999Gw8PL9NWcZs27Zk16zuqV69uWrHy96/FwoXzmDjxI8aOfY9bt27y7rsjTf+e//57xBTRvlKlyrRt24G33hpqOhMG0K9ff0aODKF+/QamvjRv3pIFC+Zw/Pgx3n33/Uf+GykUCnr06M2tWzfx8vLmwoVzbNmyiX/+MU6gbGxs2bFju8kpI5tZs77jrbdG5dqmXC5nxIiRjB37NjY2NvTo0Ztu3XqY7p87dwa9Xp/nlra3tzEUxpkzZ8zOHkZERCCTyR56vnTv3r1kZGTQqFEj07X27duze/duPvjgA9PZxq1bt+Lk5FTkGIOCx4NMJuO552rx9NN+/PprBN98c5grV5IYPnwLzZt7MGlSe1q3roGvtgbJ8iRO257grE04KYokDjrs4Yj9AeppGhKobo6bvuxsVQqKj0LnjsxJZmYmu3btYvPmzRw8aPSia9OmDVZWVvzzzz9YWVnxzTff8PTTTxe5wxWJB/O/ZWVpuHXrGh4eviJi/hPmzJkIXFxc8Pb2KdG6WVlZhIYepEOHzoXpZrFz9Ggo9erVz1ei7JIgOvoq27f/xa5dO7h1KxaFQkGjRoHMmbOwQO18+ukH1KtXH3//2lhbWxMVdZHVq1fh4GDPwIGvceXKVS5fvsiJE8c5e/YsYNyefemll7h16xZjxozB19eXU6dOMX/+fHr27Mm0adMAY1gcmUxGkyZNcHJy4tSpUyxcuJCaNWuyZs0aU2T96Ohonn/+edq1a8eAAQO4ePEi3377LePGjStysFaRO7LgFIc80tKMnpTz5h0jI8OYtq5bN38mTmxLnTrGhQgtWVywOUO47XESlHdNdX2yqhOobk6NrFrIS0H0KDE+LClVCbwlSeLQoUNs3ryZXbt2kZ6eTkBAAL1796ZXr16mla/bt2/z3nvvERsby+7duwvzURWWohhhpYGffppLRMQp0/uWLYN4/fWSjwT+3ntjzALbDhz4Gk891bbEP1fwaNLS0vj44/Fm10aPHke9evXzqJE34eFh7Ny5jX/+2c2WLbsKVHfVqhXs2bODGzduIEkGPDw8adu2PR06tOXKlRiioqKIijrP8ePHzI4p3Llzh1mzZnH48GHi4+Px8PCgZ8+ehISEmLbC161bx2+//UZ0dDQajQZ3d3e6du3KmDFjLLYrT5w4wddff825c+dwc3Nj0KBBxZK2SBhhBac45REXl8533x1h1apT6PUScrmMQYMa8uGHrXF3N44BCYkbVtcIv7dVKcmMP8VOemcaqZsRoAnE5gluVYrxYUmpMcK++uortm7dSnx8PFWqVKFXr148//zz1K6d+1bXxo0b+eijj0wH6QX5o6wbYQLB40Cn05lWl4pC9vfrzJmLREVF0aJFU3r37lkMPXz8CCOs4JSEPKKiEpg69SBbtxrPE9rZKXnrreaMHt0SB4f7QXpT5Emctj3JGZtwMuXGCaRSsqKupgGB6uZU0lcplv4UBDE+LCkJI6xQa57r1q2jdevWLFmyhH379vHBBx/kaYABNG/enOnTpxfmowSFxICBGKtoLlqfJcYqGgPiSyQo/eRcOc0v2QZYYeoKBCVJrVpurFjRm82bX6ZFC08yMnR8//1RWrVaxrJlYWi1RmcVJ4MLbdI78Ub8KDqnPkclXRV0Mi1nbMNY7baUP51Xc0l1QejxckihVsKyvYsEJUthV8KiVBc44LCLNMV993cHvSPt0rpSK6tuifZZICgKnTu3oUGDhjz//Iu0adMuT2/XbDIyMjh4cD8bN/7B+fNn2b37UKE/W6yEVWxKWh6SJPHXX1FMnXqAy5eTAPDzc2HChLb07Fnb3JsXiVir64TbHuey6qJpq9JR70QjdTMaaAKxkUo2iKoYH5aUmu1IweOhMEZYlOoC25zuBWzNeazk3r/ycyl9hSEmKLXExd1ixYolbN/+F0qlkoCAhtSpUw9PT697ORohNTWFmzdjOX/+rMmjsVu3HrzxRshDgwQ/CmGEVWwelzy0Wj2rVp1m5swj3L1rDKjbooUnkye3JyjIMhl9qjz53lZlGBrTVqWSOve2Kivrq5ZIP8X4sKTUGGGvvfbawxuVybC2tsbDw4OgoCCeffbZYjmzUdF4lBEmIaFDa7pvwMCvbktIl6eRaxxACewNjgxKGGbyvlFilWfQQEmS+OST9zh4cD89evTmk08mFfmZpk37nAEDXsXPr1aR2wJjAu+VK5cCMnx8qvHJJ5MKlRvyxIljHD580BQpPr8sWjSfTp26Urt2nTzL7Nmzi7VrV2Ntbc2ECZ9Ttaq7Wd2zZyNMOR7j4+8ydepkNBo1zz//Is8+a4yuHhNznfXr1zJmzHv57tvGjetzzR05ceKHjBr1rinobE5u3ozl+vVrD80dCcYE3mPGjM93/sgTJ45RuXKVPHNH5kx1lJGRwfjxo+nUqQvr1v2P+Ph4dDrzZPNWVla4uVVCoVCg02lxcHDEycn5oamfHoUwwio2j1seaWlZzJt3jAULjpkynzz3nD8TJ7ajdm03i/I6tFy0OUu47XHuKm+brntnVaOxujl+WXWK1atSjA9LSsIIK5RlJEkScXFxXLt2DWdnZ1P8nBs3bpCcnEz16tVxcHAgPDyctWvXsmjRIpYvX25K/SMoOhISf7j8wk2rG/mvJIN0RSqLqvxouuSp9eGFpEG5GmIigfejKe4E3r/++jMDB75G06bNGTUqhI4du2BtbV3hEngrlUpefnkQaWlp1K5dl+TkJE6ePE7//q/g5OSMnZ09rq7GeF5FSeAtEDwpHBxUfPTRUwwZ0phvvgnl118j2LbtEjt2XObVVxvx/vutcXe/n/9TiRUBmkDqaxoTaxXDKZvjXLK+wA3VdW6oruOgd6KRuikNNIHYSuK4UFmhUL9GY8eOJTk5ma+//prDhw+zfv161q9fz+HDh5k+fTrJycl89tlnHDlyhK+++oqoqKgSzaNYcSnZtBfZCbwnTLifXmfXrr8JCXmdESOGcPRoKBqNhg8+MEa2nzJlEsuXLwYw5QHMjTVrVjN27EgmTfoEvV5PQkI877zzJiNHDmfixA/R6/XcuBHDW28N5Z133uSbb4zxl86fP2sqt3q1cdWkIAm8f/xxJlOmTCIpKYlPPnmPMWPe4osvJpqloQJjAu/Ro0cQEvIakZEXMBgMjBs3iujoq1y5cpn33huDJEmmJNzXrkUzY4axj6NGhbBt2xaysrIYP/4dYmKumyXwvnTJ6CWVWwLvHTu2c+7cGZo3b4lSqaRevfpcuXIJMCbwDgxsyu3bcYwdO5JRo0L4/vsZAGzdupk//lgDwKFDB1i6dCF//vm7qd3jx//jv/+OMnToID799APu3DGmJ7p0KYrRo0fw5ptvmNrasOEP9uzZyejRI0hJSebzzycwevQI3n57GLdu3TL9O+RM4P3mm2/w9tvDuHDB6P08bNhgkyyHDRtMZqaGbdu2sHDhXKZMKfhqqkKhwMvLm4SEeFxd3fD29jEZYHlx4sQxxo9/h08+eZ/XXx9gyhIQGnqQESOGMHr0CLZv/6vAfREIiht3dwe+++5p9u9/jW7d/NHrJX7++RRBQcv49ttQ0tKyzMrLkOGtrcZzqc/zesLbtEhvjY3BljRFCqEO+1heaT67HbZyRxH3hJ5IUBAKtRL2zTff0K9fP55//nmz6wqFgr59+3Lx4kWmT5/OmjVr6NevH2FhYQXO5Sh4ODJkvJA0yGw78obVdTa7rHtk3V5J/fHWGiOwP2w7UiTwfvwJvNetW21aqbO3dyAlJaXCJfDObbWyefOWXL16mUmTPkGjUfPhhxNo2LBxrm1lk58E3gJBaaFOnUqsXNmH0NAYvvhiPydO3OLbb0NZsSKcDz5ozaBBDbGyMs/L7GhwonVGB1pmtCHS2rhVeccqjrO2pzhrewqvLB8aq1vgl1UbBSWf01lQcAplhF24cIE+ffrked/Hx4fVq1eb3jdo0IA///yzMB8leAgyZFhxP9aMr7YmDnpH0uSpeZ4JczA44qutWaizAyKBd8kn8DbmWDQaIenpaTg5OVW4BN4ZGRl8+OG7FmVeeOFlXnjhZaKjr/L111NYsGDpQ9vMTwJvgaC00bq1D9u2DWDLlkimTDnA1avJfPjhbhYtOsHEie147jl/i2C+SpTUz2xMvcxG3FTe4JTtcaKszxOriiFWFYO93pFGmqY0VDcRW5WljEJpoSpVqrB9+/ZcZ5IGg4Ft27ZRufL9PFhJSUk4O+f//IigcMiR0y6tq/HNg7999963S+ta6MObORN4p6enmSXw/vnnZQQGNqVOnbqsW/e/hxphkZHGCOTnz5/Dx6eaKYH33LmLCApqbZbAe/Lkqfz660oMBgO1atXm66+/Z+7cRSxb9gt169YnK+v+Un1BEni/+eYo5s5dxOLFP9Onzwume9kJvOfPX8KYMe+ZjIgHE3g/mIQ7O4F3YGAT3NzcOHBgHw0aNKZaNV9TAu/Tp8MfmcC7Xr0GnDx5HJ1Ox4UL56lZ04+jRw+bzoNlJ/AGOHfuLD4+vjg6OnL7tvGg7qMSeGdlZVkk8J47dxG1a9d5aALvV199HUmS8kzgffNmrEUC74yM9EIl8M6Nu3fvolarAfKdMulhCbwBsRImKLXIZDJ69arDwYNDmD69E5Uq2RIVlciQIZvo1WsN//0Xm3s9ZHjpfOiW2ochCSNpmf4UtgY70hWpHLHfz/JK89jl+Be3lbce8xMJ8qJQK2FvvPEGU6ZMYcCAAfTv3x9fX1/AmAtt3bp1nD59mokTJ5rKb9++ncaNH751ICgeamXV5bmUvpZxwgxFjxMmEniXfALvQYNeZ+rUSSxevIA+ffphbW1TIRN4P8jt27eYM+d7FAoler2OkJDcnSGKksBbIChtqFQKhg1ryksvBTB37jF++uk4//4bS48e/6Nnz9pMmNAWf//cj2A4GBwJzmhPi4yniLQ+xynb49y2usU5m9OcszmNp9abxuoW+GfWsdiqNGDguvI619GC0gp3nXepyGdZHil0nLDVq1cze/ZskpKSTDNO42zThXfeeYdBgwYBxgTEYWFheHt7m7woBfmjKGmLDBiItbpOhjwdO4M9Xtpq4ktUjIgE3i5PuivFjghRUbEpC/K4eTOVb74J5bffzmAwSCiVcgYPbsR77wVTtar9Q+tKSMQpYwm/t1VpkBmf0V7vQCNNUxqom2An2Ytg3w+h1MQJy0ar1RIREUFsrHFp1MvLi4YNG5o81gRFo6znjhQJvAUPUpwJvIsbYYRVbMqSPM6fv8vUqQfZseMyAPb2Vowe3ZK33mqOvf2jf3/T5WlE2JwkwjaMDLlxnMglBZ5aL25YXTcWEsG+LSgVRpharaZjx46EhIQwfPjwglQVFBBLIyyTW7eicXJyw9bWAVnJRqgQCEoFWVmZ7N+/j8jIC6Snp1uc5ZLJZHzwwSdF/pzMTA2JibeJiLjApUuXhBFWwSiL8jh06DpffLGfsDBjOIqqVe356KPWDBjQEKXy0UaAHh1R1hcItz1GnNXNhxe+59j1esLbFXZXpVQEa7W1tUWhUGBrW7J5qwSWWFmpsLNzJCUlgZSUhCfdHYGgxLlz5w5Tp07l7t272NnZkZGRgYODAxkZGRgMBhwdHbG2tubWrWvF8nkZGWo0msxiaUsgKGnatKnG9u0D2bTpIlOnHuTatWTee28XCxcaPSmffdbPwpMyJwqU1M1sQN3MBpyyOcE+xx15f5gM0hSp7HPYgYfWGxvJFluDnfF/yRYrSZVnuCNB3hTqYP4zzzzD33//zcCBAx/6DywoXmQyGZUre6LXV+H06XDCwk7i4eGJjY0SjUaX73AA5R2ZTCZkkoOyLI/169eSlpbG668Pw9XVlR9++Jbevfvi4+PLf/8d5dixf3nxxVc4c+bioxu7R17ykCQJjSYTSZKQJEmEsBCUCeRyGc8/X5fnnvPn559P8f33R7h4MYHXXttIcLA3kye3p3nz3INY58RGyt8RlwjbMCJswyyuKySFySgzN9DssDXYYpPjdXYZYbQV0gjr0aMHX3zxBa+99hr9+/fH29s719AADRo0KHIH80Kv17Ns2TL++ecfoqKikCSJunXrMnbsWFq0aJFnvWnTprFy5UoGDRrEpEn3o3dHR0ezdOlSwsPDiYyMxM/Pjy1bthS4XytWrGD69Ol07NiRhQsXFurZHoVCocTOzp60tHSuXr2Kvb0NmZll7we2pDDmLlUKmdyjLMvj8uVL1K1bH0mCmzeN2yV37txBqVRRrVp1rl2LZtOmDbnGhsuLR8nDYDBgMBhEmjVBmcLaWsmIEc145ZUGzJnzHwsXHufIkRs899xv9O5dh08/bYOfX96ZJuwMDz/Yn021rBrIkKGWZaCWq1HLM9DLdOhletIUqWYH+h+GTJJhI9lic88oy2mgGV/bWdxTFM5kKRZKymO0UE80ePD9tCTHjh2zuC9JEjKZjHPnzhW+Z49Ao9GwaNEi+vbtS0hICHK5nLVr1/Laa6+xdOlSWrdubVHnwoUL/PHHH6Z4RjmJjIxk3759BAYGYjAYCvVjdefOHebNm0elSpUK9UwFoVatOqSmpnH5ciQKhQylUovBULZ+YEsKuVyGtbWVkMk9yrI89Ho9bm6VsLOzw8bGBplMhkwmM4X/8Pb2ITT0oOl9fniUPBQKJY0aNaZ582bF9hwCwePCycmaCRPa8sYbgcyYcZj//e8MmzZdZOvWKIYMacz48cFUrmz5ffHSVstXsO/eyS+ZGR8SEjq0qOX3jTKjgWZ8r8nxWi3LQCPPIFOeiSSTTOUSic/Xs1kZVCYDzdZgm+P1PYPtgXvFtUVq4THqCA52xeMxWijvyPxGv+/bt2+BO5Rf9Ho9aWlpZkFg9Xo9PXv2pHr16vz0008WdV599VVatWrFhg0b6Nixo9lKWM5UKR9//DEREREFXgn78MMPkclkxMbGYmdnV+SVMHG4tnAImZhTluUxcOALdO36LEOHGlMa9evXg65dn2HkSGO+0tmzv2Pnzr/ZvPkhZ1keoCQO15Y2hO4oOOVVHmfO3GHq1APs3n0VMCYOHzOmJSNGNMPOztyTMkp1gW1O937fS9A7Uo8ezT2j7EEDTZ3juiaHUSfJCj6BlGdvkebYHs3NWMu+Zy3ZWKxuFUYmJXowH0rWuMovCoXCIgq/QqGgbt26XLtmeUh306ZNxMTEsHjxYjZs2GBxv6jnP44dO8auXbvYvn077733XpHayi96vYEjR2JIS9Ph4KCkZUuvMvujIRDkRrNmLTl4cJ/JCOvevRerVi0nNTUVg8HA339vFQFXBYKH0KBBFX77rR/791/jyy/3c+rUbb766hDLloXx0UdP8corDUy/GyUZ7DsnChTYGxywxwHykUhDQiJTlmm2ymZuxFmuuulkWgwyPemKVNLJ3xYpEjnOs9liLdly3eqq8d6DC2oyY/kDDrvwS6hd6K3JIm+w3r59m4SEBHx9fQu0JVAS6HQ6wsPDad68udn1tLQ0vvnmGz799NMS8erU6/VMmTKFt956i6pVqxZr23m5GW/efJFPPtlDbOz9fH1eXg5Mn96ZXr3qFGsfyhrZCkUYpEbKsjyGDHmDs2fPYjDoUKlUvPHGMOLj7/LPP7uRyxU888xzjBv3Xr7c8bMpy/IQCApL+/a+7NgxiD//PM/06Ye4di2FceN2snDhCT77rB1du9ZEJpNRK6su1e/4s/dyGKmk44g9nfyaYKV4cuexZMiwkWyw0dvgSv7OampNW6QZaGTqHMZaBup77zU5XmfKNSADjUyNRq4mMX8dI02RSqzVdXy01Qv1bIWW6q5du5g5cybR0dEALFu2jNatW5OQkMDQoUMZNWoUTz/9dGGbLxRLliwhLi6OIUOGmF2fO3cu1atXp3v37iXyuatXr0atVlt8blGRy2W4uloelly//hxDhmziwY3kmzfTGDJkE7///hL9+j354JdPGicnEUYlJ2VRHq6utahfv1aOK/bMnDmjyO3u27ePxYsXExUVRVpaGu7u7nTt2pXRo0ebcnrmhlqtZv78+WzdupW7d+/i4eFB3759GT58OEqlUZ2eOnWK3377jWPHjnH79m3c3d159tlnefvtt80mqnPmzGHu3LkWn/H5558zYMCAIj+jQPAgcrmMF16oT8+etVm+PJzvvz/C+fPxDBq0gTZtfJg0qT03bqQyceLeByb4J5g6tRM9e9Z+gr0vGFZYYWVwxsmQv7zVevQmAyzbWIu2usw529OPrJsd8LYwFMoI27NnD++88w5NmjShZ8+eZorEzc0Nd3d31q9fX2AjLDU11ZSI+GFUq1YNlUpldu3QoUPMmTOHkSNH0rBhQ9P1yMhIfv31V9auXVugvuSX+Ph4Zs+ezYwZMyz6VFQMBomUlAyza3q9gXfe2WphgAFIEshkMGbMNtq396mQM3293sDRo7GkpGTh5KQiKEhs0SoUcpycbElJUaPXl5+zLoVFoZCTlJREvXoB9O37Es7Ozly+HMWSJYs4e/Y8s2fPB4xG64Nj58svv2THjh2MHz8ef39/wsLCmD17Nmq1mnHjxgGwbds2oqOjGT58ODVq1CAqKorZs2cTHh7OypUrzdqzsbHh559/NrtWrVq1Enx6gcDoSfnWW8155ZUGzJ79L4sXn+TQoRiefXZ1ruVv3kxj2LDNLF3aq0wZYgVBgQJ7yQF7/f0tUluDXb6MsPx6luZGoYywefPm0aJFC1atWkViYqLFbK5JkyasWbOmwO1u377dLPF3XmzduhV/f3/T+zNnzvDOO+/Qs2dPRo8ebVb266+/plu3bnh7e5OSkgIYD+FrtVpSUlJwcHAo0nmwWbNmUbduXVq0aGFqX6fTodPpSElJwc7OzjRDLgwPHhA9dOi62QzlQSQJbtxI5eOPdxMQUAVrayU2Nsb/ra0Vub7Ofm9trUQuL7txW7ZsicxlBudQ5mZwJYVebyhXB46LQp8+fWjfvqtJHoGBzVAorPjmm2ncuhVnSjyeE4PBwLZt2xg2bJgpN25wcDBXrlzhr7/+MhlhISEhZuEtgoKCcHJy4v333yciIsJskiiXy2nSpEkJPqlAkDcuLjZMmtSeoUOb8NVXh/j999wjGmRP8CdO/IfnnvOvMBPb/HqMemkLP3EqlHUQGRnJxx9/nOf9ypUrEx+fP5fTnPTv35/+/fsXqE50dDQhISE0bdqUqVOnWty/cuUKBw8eZNOmTWbX165dy9q1ay0MuoJy5coV/vvvP1q2bGlxr2XLlixevJj27dsXuv0HiYvL37Ln0qXhhWo/2xgzGmf3X1tbK7C1VWJtnbsBd/+1ZV0bG4XpnrW18l475gahlZWiUP3NZsuWSIYN25zrFm15n8E9DOG8Yc7D5JHt6KPVanOtK0kSOp3OYrvS0dHRLKRNbvHFAgICAPK10i8QPG58fJwYNKhhnkYYGA2x2NhUBg7cQK1arjg6qnBysjb76+hobXbNzs6qTE/s5chpl9bV6B0pkat3ZLu0rkWKF1YoI8zW1ha1Wp3n/evXr+Pi4lLYPuWb27dvM3ToUDw9PZk9e3auicO///57MjPN05CMHz+eJk2a8Nprr+Hl5VWkPnz66aemFbBsvvrqK2xsbBg/fjx16xZvslN39/wte7ZpUw1HRxUajY7MTB0ajQ6NRm96n5mpR602Xs8ZKykzU09mpp6UlMebukWhkJkZaLkZcHmt6KlUChYuPJHnFi3ARx/tplYtV+zsrLCxUZoMSisrebnN+iBWBs3JXR52fP55O+rXV7B8+RLatm2Pp2fuOkGhUNCvXz9++eUXmjVrhr+/P+Hh4WzcuJGRI0c+9LOPHz8OgJ+fn9l1jUZDcHAwKSkp1KhRgyFDhvDSSy8V8UmNPMpZQTgomFPR5XH3bsajCwF7915l796r+Sork3HPMLM00B404B52TaUq2iS9KNQz1OfkvltE1TmCg9f9H5m0WBm1IoOpF1i/SC6OhaoaFBTEhg0beP311y3u3blzh7Vr19KpU6fC9yofaDQaQkJCSExMZMKECURGRpruqVQq08wzt6V+a2tr3N3dCQoKMl1Tq9Xs27cPgBs3bpCWlsb27dsBaNWqlWl2+/rrrxMbG8vOnTsBqF/f8gC8k5MTdnZ2Zu0XF8HB3nh5OXDzZlquRodMBp6ejvz++wv5ViZardHwMhpq9w00o7FmacCZv75fJ/t19vvMTN29dnKvm5l53zdZr5fIyNCSkZH7KkRRuXMng/btV1pcl8tlOYwy8xW+nIaera3SbLUv+322cXj/vcLMyMuu82D7JW34iZVBc/KSh7X1r8ycuQSAoKCnmDx52kPbmTx5MpMnTzZbsX/zzTd544038qyTkJDAnDlz6NKlCzVq1DBd9/X15f333ycgIIDMzEw2b97MZ599RmpqKsOGDSv4Q+YgL6ee3CiLDhslSUWVR61alfNVLiSkGZUr25GcrCE5OZOUlMwcf43XkpM16PUSkgQpKZn3JvX5DBORC9bWCpydbXByssbZ2drsdd7XbMxeOzioCrUqt379OUa/eBxkSnzbSTh4SqTdlHH9oAzJcByP3/2L5AhXKCPs3Xff5eWXX+bFF1+kW7duyGQyDh48yJEjR1izZg2SJDFq1KhCdyo/3L17l/PnzwPw9ttvm93z9vZmz549BWovPj6esWPHml3Lfr9y5UqTQWUwGNDr8xHYpIRQKORMndqJYcM2I5Nh9qOS/bs+dWrHAs3mrKyM24EODsXrWPAoDAbJZIw9aMDl/jr3Fb2zZ+9w4MD1R36enZ0Sg0FCo7n/72cwlKzxlxd5GXyPNvoUDxh9lkaelZWCjz/e/VDnjQkT9tKpU/U8x0lBbMSCGpQl1XZeRfV6AxMm7M1VHjdudESh0FGlSibR0ZF89NE4fvhhHgpF7jPvmTNn8s8//zB16lRq1KhBWFgY8+bNw8nJieHDh1uU12q1jB8/HjB6PeakT58+Zu87duyIVqtlwYIFvPbaa7mu7OeX3Jx6HkQ4bJhT0eXRsGGlR07wvbwc+eqrR/++SJKEWq0jNTXLZIRlv05NzSQlxfz1g9eyy6anG/VyZqae27fTuX278F6IMpkxUO2jV+CMK3fZ26lvvXXPEU6SEb1PZtFmbo5wuTn15NmvwkTMB+O5sGnTpnH06FGz8xCtWrVi8uTJRTpnJTDysKjXuW+tODJ1ascKtcIBRmeFvn3XPbLcn3/2p02bakiSZLY6l70tm3OLNrd7Go0OtVr7wHvzFcFsAzG3NvT6spUyqKIxb14LZs0az5QpX9OpU1eLqNcXL16kV69eLFiwgM6dO5uuL1iwgPnz5xMaGmqWEk2SJD788EN2797N6tWrqVev3iP7sG3bNt59990in1UVEfMLjpDH/RVjyH2C/7hX0PV6A6mpWWYG3P3X9/9mG3FpaeZGX/b1kv73zP5tyabEI+YD1K5dmxUrVpCcnEx0dDSSJFGtWjWR9PYx0bNnbZ57zp///out8Ieu87tFGxzsfe+9zLTK9DjR6Qwmw83SyNM9cC9/Rt6DK4hqtY6kJM1jP9NXHpDLq6BUKomJicn1flRUFGB5BCEgIICsrCzi4uLMjLAZM2awbds2Fi9enC8DTCB40vTsWZulS3tZTPA9PZ/MBF+hkOPiYoOLi02h25AkCY1Gl6eRdn+1Lou0NPOVuRs3Urh169Grb/l1mMuNIv8KOTs707hx46I2IygECoWctm19K/zsrSS2aEsCpVKOg4OqxLd987syuHr18wQH+1hcL8jieEHX0Uuq7Ye1e/ToDV57bVOe97PJzLyBTqfDy8s71/ve3sbrZ86cwdPT03Q9IiICmUxm5uSzaNEiVqxYwcyZM2ndunV+H4OtW7fi5OSEr69vvusIBMVJeZvgy2QybG2tsLW1yrdjWzb51aUFbTcnhd6O1Ov1HDx4kOvXr5OcnGyhBGUyWYmfCyvvSJJk5rmYFwqFvEKeYXiQjAwtCQlqs20/hUKGm5utRaLa8owxVlzKQ7c/FQoZ3t5OBTqfVVbJTR5TpnxE7dr1qVmzFiqVNVevRrF+/a9UqlSJNWvWolKp+OyziWzYsIGzZ88CRp330ksvcevWLcaMGYOvry+nTp1i/vz59OzZk2nTjIf6N2/ezPvvv0/v3r1N8cSy8fX1Ne0W9OvXj+effx4/Pz80Gg2bN29m+/btfPrpp7k6PRXsmYXuKAxCHuZUdHkUVpfK5bJ8n2ctlBF2+vRpxowZw61bt/KcgcpkMs6dyzvmiEBQEmQvPev1EgqF7LF4IpZG0tOzHrpE7u5uj73943XEeJI8KI+1a1eyb98ubt6MQZIkvL29efbZZxg2bJhpS/Hjjz/mzz//5MKFC6Z6d+7cYdasWRw+fJj4+Hg8PDzo2bMnISEh2NjYmNXLjenTp9OvXz/A6OB06tQp7t69i0wmo06dOgwePJjevXuXlBgEAkEBKWldWigj7MUXX+TGjRtMmzaNFi1a4OTkVOgOCAQCgUAgEFRECnUm7MKFC4wbN87MQ0ggEAgEAoFAkH8KddLOw8OjQAdsBQKBQCAQCATmFMoICwkJYe3ataSl5Z1IWiAQCAQCgUCQN4XajkxPT8fe3p6nn36aHj164OHhYRFhWiaTMWTIkOLoo0AgEAgEAkG5o1AH8/MTeFB4RwoEAoFAIBDkTaGMsBs3buSrXHZwQ4FAIBAIBAKBOYUO1ioQCAQCgUAgKDz5Pph/6tQpkpKS8lX2+vXrbNiwoZBdEggEAoFAICj/5NsIe/nllzlw4IDpfVJSEoGBgfz7778WZU+ePMknn3xSPD0UCAQCgUAgKIfk2wh7cNdSkiQyMzPR6/XF3imBQCAQCASC8k7ZTIsuEAgEAoFAUMYpVJwwweNBkiQMhrz9JiQgSZ+MXCVhyJLhonCm4qWqzh25XPZQ2VU0hDzMyY885HJZmU3+npvuMOkLK4lcFYUEBm3F1iPie2KOkIclxa07hBFWijEYJBIS8s7evulsKNEd9hnfqMBnXxv6BrR7TL0rvSiVclxd7UlJyUCnMzzp7jxxhDzMya883NzsUSjKpjmSl+7YdPa/+zrjQWRQPbQDvQNal3DvSifie2KOkIclJaE7CmSE3bhxgzNnzgCQmpoKQHR0NE5OTmblYmJiCtKsoBAYJANhlQ7jYgDZvU3l6+0O8dWFYzgkVaG2bQ1aedbHTe6GrMLOawUCQU561g9iasRhnOtpkefQ/pIEmckQbx1HWPI5Apz9UaF6ch0VCCoI+Y4TVq9ePYvlNUmScl1yy74uIuYXDb3ekOdKmNkq2EPISlSgvOWCDz40qVSHanIfVJJ1cXe1VJE9W0lMTBczOIQ8HiS/8jDOZsvmsdmi6g6DHrQxNjinVqWevT8BTn64GSqX6wmd+J6YI+RhSUnojnyvhE2fPj2/RQUlTPYqmLMOs9msQQdpMXIywpzAJ5UqjfWoXPXgGk8s8cQSjmQAKc6OyhpP6jv6UV3ui6u+EnLhoyEQVAgeXA0z6CDlqgLFSW9Sne9gX0+Nsy9YV9eg4RphXCOMvejT5VjfcaO60pf6Dn546LyxlWyf9OMIBGWafBthffv2Lcl+CArAlnNHce2gtbguV4JTDQONogPpWS2Ys0fjOHzlPJezrpLhFk/lplpca4LMM4MELnGISxwCJI0Ch6TK+FtXx1deDXetF3aS/eN/MIFAUOLIZXKaxD9FtNK4GiZXQuCNtvTuaDwLlpqayeGNlzh59yJxyliUNVPxaC6hsjegs7/LJe5yiRMAyBLscNd6Uce2Jh56LyrrqqJA8cSeTSAoa4iD+WUM0yqYHuS56DqDHsIqHaanLIiG9TxoWM8DMG4RX76cxMG/o4hIiiLBPg7nBpl4t5JQOehJ94jjFHGcwhh8V5lqj4/kja/cF3etF1V07kK5CgTlhJ71g5gWcRiXhlqSIqwYVT/IdM/R0ZpnnwrgWQIAyMjQ8t/fNzh69SLR+mtoPRLxbKmncj2Q3DK4RRS3iDJW1spxSq9MTavqeOm8cdd54WBwLNfbmAJBURBGWBlDk5WFdVVdrgYYGA0z6yo6NFlZ2FnbmK7LZDL8/V3x928JtESSJK5dS+HwiuucuB7FDVkMNrUz8AmWqNJAQueYzlUucpWLxgZ0ciplVaUaPrjrvPHQeuFocBLKVSAog8hlcponteNk1H6aJ7VD7p73cQQ7Oys6tKtBh3Y1ANBodISF3eLwmiucS71MmstdqjbX4R0kYetmIMXlNuHcJpz/AFBpbPGWfPDS++Cu86Sq1gMrcehfIABEAu9STV6HayNvx3I7PREAhVyOvb016emZ6A3Gg4LuDm7UquJZ4M+LjU0lNDSGI2FXuaS5Bj4peAcb8AmWsKtsWd5Ga4enwWiQeei8qKr1LBUeVeJAqTlCHuZU9IP52RTXuNBq9YSHxxEaGsPJa1e4bR1LpUAt3sES7o0ls3OrABhkVNJVwUvvjfs93eGif/Je3OJ7Yo6QhyUloTuEEVaKeZyKNDdu307nyJEbhIZeJzwmmszK8XgFSfgES7g3kVBYPVBBklFZVwV3nZfJMHPVV3rsylUoD3OEPMwRRpiRkhoXer2BM2fucPhwDEeOX+Nq1nXj0YdgA97BEk7elnVUehs89Pf0htYLd50nNo/50L/4npgj5GGJMMIqGE/aCHuQxEQ1R47c4PDhGP49eZ141W28WhnwDpLwDjbg7GtZR2Wwxl3nec8oM858S9qjSigPc4Q8zBFGmJHHNS4MBonz5+8SGnqD0NAYwq9cw65Ohsko82wuYZWLSnDRueGRY0JXSVe1RL24xffEHCEPS4QRVsEoTYo0N1JSMvnvv1gOH47h8OEYLt25hUdzvVG5Bkl4tZSwsrOs56JzzbFa5k0lXZViPfQvlIc5Qh7mCCPMyJMaF5IkcelSoklvHPnvOoYqqfgES3gHGyd0lWrn0l/JiqpaD5Nhln3ov7gQ3xNzhDwsEUZYBaM0K9LcSE/XcuxYLKGhMYSGxhB26ibOtXVGxXpvtaxyPct6CklJVZ2HaSvCQ+eFg8HJsmA+KU0yKQ0IeZgjjDAjpWVcSJJEdHSyaZX98OEY7qQn4d1KMq2WeQdJ2Dhb1nXQO5l0hrvWi6o6d5Q8eE4ib1LlKajlGQAoFHKcnGxISdGg1xvlYWewK5IuKsuUlvFRmhBGWAWjLCnS3NBodJw8ecukWI8di0Wy0d5XrkESPq0lbFws69rrHfHQeeKhNbq5Gz2q8qdcb9hEc8BxF+1Su+KtqV68D1UGKc1j5EkgjDAjpXlc3LiRaprMhYbGEHUpgcp1MRllPsESVRpKFl7icklOZV3Ve6tlxuMPzgaXXM+l6tGx3G0+akVGnv2w09szJOFtFBUwkEBpHh9PijJthKWkpHDy5EmioqJITExEJpPh6uqKv78/TZo0wdk5l2lOBaesK9IHycq670UVGhrD0aOxpKVnUqk2JqOs2lNQtZEB2QPKVSbJTMrV/d42pove1UK5Skisc11JnPIm7jpP+ie+9sS9rp40ZWmMPA6EEWakLI2LuLh0jh69weHD1wkNjeHcuXis7CW8Wkj3jDIDvm1k2FaxfA4bg63Zapm7zhNryQYJiV/sl5Nke5tcVYQEruqqDEp/o0LqkLI0Ph4XZc4Iy8rKYsuWLfz5558cP34cgyH3Tsvlcpo1a0a/fv3o2bMnKtWTD3NQGihvivRBdLr7XlShoTEcORJDUlImVnbGw7rewRK+T0lUbyvDurLeor6NwYaqupweVV7EKWPZ5LLWVKZ30ktU1/o9zscqdZTlMZJNUlISyclJyGTg7OyCs7NLodsSRpiRsjwuEhLU9zy3jbojIuIOBoMB5+rgHWRcLfNrL6dyYz1yqwd+4iRw01emSqYH6365SOM3s/L8nL9etmfjd29jbS1WwgRlzAj77bffWLBgAYmJibRp04Y2bdrQoEEDqlWrhrOzM5IkkZycTExMDBERERw+fJhDhw7h6urKyJEjeeWVV0qiW2WK8q5IH8RgkDh37q7ZNsTdu2pAwskHk1FWu7MSl/paZCrL51VICnSSHpncmD3Aw+DBS0mvV8iZbDZlcYyo1Wr27t3FgQP7iIg4RXJyktl9Z2cXGjZsRLt2HenUqSu2tvn3uBVGmJGyOC7yIiUlk3//vWGa0IWFxaHXSyhUxnA63kEStTrK8X0KVB6WKd8kCWQ5VIRBB7dOyDj+pjd//z0Imazi6Y/yND6KizJlhHXs2JEhQ4bwwgsv4OiYPw+WtLQ0fv/9d1auXMmePXtKoltlioqmSB9EkiSiohLvKdbrHD4cw61bRnnIrYyBIKs9BQ2eVeHZ0oCiqibXdron98U/q+7j7HqpoiyNkeTkJFatWsHGjevJysrE3782devWx8vL+54ekUhNTSU2NpYLF85x6VIkKpU1ffr049VXh+Di4vLIzxBGmJGyNC4KSlpaFseO3eTIEeN51BMnbpGVZVxNt6tiNMpqd1JQo50MxwYaVLl4cf89Ts644P506VzzMfe+dFCex0dhKVNGmE6nQ6ks3BJuUeqWJyq6In0QSZK4ejXZpFhDQ2O4di0l+y7Dj2txD8wlp6Yko5G6KYGaFrjq3R53t584ZWmMPP10e3x8fOjTpx8dOnTB1dX1oeUTExPZt283mzb9SUxMDDt27HvkZwgjzEhZGhdFRa3WmpyEQkNjOHbsJmq1DgCZ3MCIMB2VAyx1RxWtO4Hq5tTODEBZwQ7nV6TxkV/KlBFWGC5evEidOnWedDdKDUKRPpqYmBTj9kPaWTw+jHpked8sPwLVzame5VdhtijL0hg5ejSUoKDWJVpXGGFGytK4KG6ysvSEhcVx5EgMmzdHkup+k0F/60z3o7bLqNVVBkqjXGwMtjRUN6GRpmmFCVlRkcdHXpRLI+zWrVts2bKFzZs3c/HiRc6dO5fvuvv27WPx4sVERUWRlpaGu7s7Xbt2ZfTo0Q/dAlWr1cyfP5+tW7dy9+5dPDw86Nu3L8OHDzetwMXExNClSxeLuoGBgaxdu9bs2okTJ5gxYwbnzp2jUqVKDBgwgJCQkCKfIxCKNH9ISKx1+Zk4xS1kuYx7yQBKvRV6pdbkBeWic6WRphn1NY2wlmwsK5UjxBgxR6mUc+rUMRYs+IkrVy6Tnp5O5cpVad++A2+8MQIHBwcgd0UqdEf5Q5IknnnmV1osvoFXS4kb/8pYFqTE1VvBiIUeuD4bT7oyFTB6aftn1qWxpjleWp9yPZET48OSkjDCnsj6ampqKtu3b2fTpk0cP34cSZIICAhg1KhRBWonKSmJxo0bM3jwYFxcXIiMjGTOnDlERkaybNmyPOt9+eWX7Nixg/Hjx+Pv709YWBizZ89GrVYzbtw4s7Ljx48nKCjI9N7e3t7sfnR0NMOGDaNNmza8++67XLhwgZkzZ6JQKBg2bFiBnkdQOAzoidclIcsjjJhMDslxWmKm+vPcRDtuuF8kSZnIAYfdHLE7QL3MhjRWN8dNX+nxdlxQJOLj77J79w7+/nsbS5euKlDdpKQkAgIa8sILL+Pk5MyVK5dYtmwRly9f4ocf5uVZT+iO8odMJuOTT9ryySe/8+xsHXs/VVC7diUiIxOY0TOWKu42jFnQhErd47lpfZ0om/NE2Zynsq4qgerm1NEEFChArECQk8dmhGVlZbF37142b97M/v37ycrKQiaTMXjwYIYNG4a7u3uB2+zTp4/Z+6CgIFQqFZ999hlxcXG5tmkwGNi2bRvDhg1j0KBBAAQHB3PlyhX++usvC0VavXp1mjRpkmcfli5diqurK99//z0qlYrWrVuTkJDATz/9xODBg0W4jceAXFKwva8r0XfukNe6bvptGak3rvPnIjlDRjSk10RHLlU5TaIyntO2JzhtewLfrJo0VjenRpZ/uZ7hlmUyMjLYt28PO3Zs48SJYxgMBry8cskI/Qj69OlD+/ZdTbPZZs1aYGWl4ptvpnH37h0qV65iUUfojvJLp07VcZnhyU8N4mja1J1tBwawdeslpk07yKVLiXzW7yx+fi58MLMLLt3ucMHmLHeVt9ntuI1D9v/QQBNII3VTHA0i3qWgYJS4ERYaGsrmzZvZuXMnaWlpNGnShI8++oh69eoxaNAgWrRoUSgDLC+yvaO0Wks3ZDAuPet0OovtSkdHRwqzM7t//36efvppM4XZvXt3Fi5cyMmTJ81mwoKSIStLz6UTau7cyXv5183Nhk6d3Nm7N5ol80/zv5Uq3nmnBT3HVuaCSxhXVFFcU13hmuoKznoXGqmbEaBpXO63KssCOp2OI0cOsWPHdg4fPkBWVhZ+frUYPvwt2rRpj5+ff7F8TnbAaKE7Kh4ymYzPPmvPhAl7+eyz9sjlcnr2rM2zz/rxyy8RfPttKJcvJ/F2vwM0b+7JhKn9sG17m9O2J0hVpHDc7ggnbI/il1WbQHULvLTVxEROkC9K1Ahr3749d+7coX79+rz55pv06NEDT09PAK5du1Zsn6PX69HpdERFRTFv3jw6d+6Mj49PrmUVCgX9+vXjl19+oVmzZvj7+xMeHs7GjRsZOXKkRfnPP/+ccePG4eLiQpcuXXj//fdNhl5GRgY3b97Ez888GKifnx8ymYzLly8XWZEqlQ/fV87edy6rB4iLA6VSxe7drxIfrwZALpfh4GBDWpoGg8H441i5sh3e3o7s33+NyZP3ER4ex/Tph1mxwoGPP27Da4O6csb+JBGqcJIVSRx02MNR+wPUz2xEk8zmVDJYroyUFcrqGAkLO8Hff29jz57dpKQkU69efV54oT+rV//CsGEhdOpkee4qP+SUR7buuHLlMitWLKFduw5UqyZ0R0WkS5ea9O0bQEqK2pQ7UqmUExLSlFdeacDcuf8xb95/HD9+k37PbaB791pMnPQyygYJhFkf47pVNJesL3LJ+iKVdVVoktmCelkN851urbQhxoclJSGTEjXCbt++jY+PDy+88ALdunWjUqWSOXPTqVMn4uLiAGjXrh3ffffdQ8tPnjyZyZMn079/f9O1N998kzfeeMP0XqVSMWDAANq2bYuTkxPh4eH89NNPREREsG7dOqysrEhNNR7WdHIy95ZRqVTY2tqSnJxcpOeSy2W4uto/uiDg5JT/YJXlkfzKqU+f+vTqVY81ayL49NM9XL2axNixf7NoURVmzOjK+92f5RThHCWU27LbnLI5wSmbE/jhTzCtqUNd5JRNpVRWxsh3333HX3/9RWxsLP7+/gwZ8jo9evSgevXqXLt2jdWrf8HBwSbf/+Z54eRkS/v2z5rpjtmzf8TOLpegUfcQuqP8k5s8XF3t+eabZxg3rjWff/4PS5acZOvWKP7++xLDhzfj888HIvNI4yhHCCeMu8o77FIatyqb0YJWBOHKw8OtlFbE+LCkOGVSokbYwoUL2bx5MzNnzuSrr74iKCiIHj168MwzzxTr5yxatAi1Wk1UVBQLFizgrbfeYvny5SgUDwaMMjJz5kz++ecfpk6dSo0aNQgLC2PevHk4OTkxfPhwAKpWrcrnn39uqtOqVStq167Nm2++yc6dO+nevXuxPkNuGAwSKSl5J5cFo0Xu5GRrNnur6ORHJt26+dGpky9Ll4Yxc+YRzpy5Q8+ev9GmjQ9ffNGBgc2GcV0ZTZj1MS5bRXJZdonLXMJJ70KTzOY0yGqMjVQ2lFNZGyOLFy/Gy8ubefMW0axZc9P1xMR0kpON34e0NA2JiQ/3/suLnPKYOXMWGo2ay5cvs3z5EoYPD2H27AUoFAqcnGwtZrxCd5Rf8iMPGxs5X3/dmTfeCGTKlANs3RrFwoXH+eWXU4wa1YJRozrQ0qktEapwwq2Pk6JI5hAHOCwdxE9bmyaZLaimq14mtirF+LAkvzLJTXfkRYkaYR06dKBDhw6o1Wp27NjBli1bmDx5Ml988QWNGzdGJpPlmU+yINSrVw+Apk2b0qhRI/r06cPOnTvp1q2bRdmLFy+ybNkyFixYQOfOnQFo2bIlOp2OWbNm8corr5hc1HN7Hjs7O86cOUP37t1NZ0OyZ7XZZGVloVariyUpeX5dg/V6g3AjfoBHyUShkDNiRDNeeimA2bP/ZfHikxw6FEPXrr/y/PN1+eSTNnSv2Y8UeRKnbU9yxiacFEUS++12c9h2P3U1DQhUN6eSvmxsVZaVMdKxYxcOHz7Au++OomXLILp2fZa2bTtga2uLXm/cXjYYpCI/i15voGbNWgDUr9+IOnXq88YbA9mzZzedOnW1KC90R8UgP/Lw93dlxYreHDkSwxdf7Of48Vt8800oy5eH88EHrRk0qDmNrVpwVXWJcNtjxKiiuaS6yCXVRdx0lQlUN6eupgFWlH7nCzE+LClOmTwW70hbW1v69OlDnz59SEhIMMUFkySJDz74gDVr1tClSxc6duyY51mu/FK3bl2srKzyPHMWFWUM6Fm/fn2z6wEBAWRlZREXF5enIn0QOzs7PD09uXz5stn1K1euIEmSxXkPQenExcWGSZPaM3RoE2bMOMzatWfZsOECf/0VyRtvBDJuXDBtKnWiVXpbLtic4ZTtceKVdzhjG8YZ2zB8snxprG5BzaxaZXarsjQxZcrXZGSks3fvbnbu3M7UqZNRqVQ89VRbGjYMLLE8frVq1UapVBITE5PrfaE7BA8SHOzD1q0D2LIlkqlTD3LlShIffribhQtPMHFiW7p3r4VfVm0SFHc5ZXucczYRJCjvstfxbw7b/0OAJpBG6mY4G1ye9KMInhCP/RfDzc2N1157jXXr1vH3338zYsQIYmNjmTp1Kk8//XSR2w8PD0er1eZpzHl7G93Zz5w5Y3Y9IiICmUyGl5dXnm3v3buXjIwMGjVqZLrWvn17du/ebeZRtXXrVpycnGjatGlRHkXwmPHxcWLOnG7s3j2YTp2qo9UaWLToJK1aLWXWrH/RZkBDTRMGJA6lX9JA/DPrIJNkxKiusdV5PSvdfuKE7VE0MvWTfpQyj52dPT169ObHH+fzxx9/MXTom1y/fp3Zs79DkiTWr/+dHTu2W6wkFYUzZyLQ6XR5hrwQukOQGzKZjF696nDgwOtMn96JypVtuXQpkTfe2EzPnmv4999Y3PSV6Zj2LEPjR9E2rTNOehcy5ZmctPuXlW4/scXpd65ZXUWi1CSwETwmnnjE/GzCw8PZvHkzEydOzHed0aNH07BhQ+rWrYuNjQ3nz59n6dKluLm58fvvv6NSqfj000/ZsGEDZ8+eBYyelC+99BK3bt1izJgx+Pr6curUKebPn0/Pnj2ZNm0aAF9//TUymYwmTZrg5OTEqVOnWLhwITVr1mTNmjWm6NjR0dE8//zztGvXjgEDBnDx4kW+/fZbxo0bV+SAiyLqdeEoLpn88080X365n4iIOwB4ejrw8cdP8dJLAab9/hR5MqdtT3LWJgyN3JhAXCkpqXNvq7KyvmrRH6iIlKcxEh19le3b/2LXrh3cuhWLQqGgUaNA5sxZmO82lEo5n332Ef7+dahZsxbW1tZERV3kt99W4eLixpIlK7GysuL7779i48aNQndUEIpLHqmpmcybd4wFC46b8lP26FGLiRPb4e9vPJxvwEC06jKnbI9zTXXFVNdNV5nG6mbU1TRE9YS3KsX4sKRcpi0qCosWLWLr1q1cu3YNSZLw9vbm6aefZtiwYaZtgY8//pg///yTCxcumOrduXOHWbNmcfjwYeLj4/Hw8KBnz56EhIRgY2OMC7Vu3Tp+++03oqOj0Wg0ppRIY8aMsdhyOHHiBF9//TXnzp3Dzc2NQYMGidQjT5DilInBIPHHH+eYPv0QMTHGVZf69SsxaVJ7OneuYfo31qHlgs1ZTtke567ytqm+d1Y1Gqtb4JdV+4ltVZbXMRIeHsbOndv455/dbNmyK9/1lEo569b9yubNW4iJiUGSDHh4eNKhQ2cGDHgVe3vj93vmzKls2LBB6I4KQnHL4+bNVL79NpTVq89gMEgoFDIGD27M++8HU7Xqfc/VBEU8p2yPc97mNFqZcVVUZbAmQNOYxupmOBuejFelGB+WlCkjbNKkSYSEhFCtWrUC1bt27RpLlizhyy+/LIlulSmEIi0cJSETjUbHsmVh/PDDUZKTMwFo164akya1JzDwfrBhCYlYqxhO2R7jkuoiksz49XLQO9FI3ZQGmkBspbxDIJQE5X2M6HQ60+pSfhAJvI2U93FRUEpKHufP32Xq1IPs2GE8/2dvb8WoUS14663mODjcX+3KlGk4Z3OaUzYnSFYmGi9KUCPLn0B1C6ppazxWr0oxPiwpU0ZYSEgIoaGhBAcH0717d1q3bm0K1PogMTExhIaGsm3bNo4ePUqbNm1YtGhRSXSrTCEUaeEoSZkkJqqZNetfliwJIytLD0C/fvX45JM2VK9u7tGWKk+551UZhkZuPCemkJTU1QTQWN2cKvriyxTxMMrSGImIOEXDho1LtK4wwoyUpXHxOChpeRw+fJ0vvtjPyZPGuHRVq9rz4YetGTiwoVlgXQmJaNVlwm2Pc01133HDRedGoLo59TIbopKsi71/DyLGhyVlyggDOH78OMuWLWPfvn3o9XpcXFzw9vbG2dkZSZJITk4mJiaGlJQUFAoF7du3Z+jQobRo0aKkulSmEIq0cDwOmVy7lszXXx/m99/PAaBSKe55Ugbh5mYeP0yHjkjrs4TbHueOVZzpuleWD43VLfDPqlOiW5VlaYx07tyGBg0a8vzzL9KmTTvTFl9eZGRkcPDgfjZu/IPz58+ye/ehR36GMMKMlKVx8Th4HPKQJIlNmy4ydepBoqONAXlr13Zj4sS2dOvmb7ENnaiI55TNCc7ZnEYrzwKMW5X1NY1orGmGi96tRPoJYnzkRpkzwrJJSEhg7969hIWFcfnyZZKSkgBjnkc/Pz+aNGlCx44dSyyifllFKNLC8Thlcvr0bT7/fD8HDhhDojg5WTN2bCuGD2+Cra15uhIJiZvKG5yyPU6U9fkcW5WONNQ0paG6SYlsVZalMRIXd4sVK5awfftfKJVKAgIaUqdOPTw9ve7laITU1BRu3ozl/PmznDt3Br1eT7duPXjjjRDc3T0e+RnCCDNSlsbF4+BxyiMrS8/PP4fz3XdHSEgwOvQEBXkzeXI7WrSw9LLNkmVyzvo0p2xPkKRMMF2vnulHoLoFvtqaxb5VKcaHJWXWCBMUDqFIC8fjlokkSezda/SkPHv2LgDe3o589NFT9O9fP9cvY5o8lQibk0TYhqGWGyObKyQFdTKNW5VVdY82JvJLWRwjSUlJ/P33Xxw4sI/z58+SmZlpdt/a2pp69QJo27Y9zz7bA1fX/B9eFkaYkbI4LkqSJyGPlJRM5sz5j4ULj6PRGI839OpVmwkT2uLnZzmmJSSuWV0h3PY40daXTNdddK40VjenfmajYtuqFOPDEmGEVTCEIi0cT0omer2B338/z9dfH+LGDaMnZUBAZZMnZW4YtyrPccr2OLetbpmue2p9aKxujn9mHRTknn4rv5T1MaLT6YiLu0VKinH7xsnJGXd3jwIdxs+JMMKMlPVxUdw8SXnExqbyzTeH+e23M0iSsS+vv96Y8eODqVIl99XxJEWCaasyS26cpFgZVNTPbEhjdXNc9UXbWRLjwxJhhFUwhCItHE9aJmq1liVLwpg1619SUozKsX17XyZPbk+jRrnHDZOQuKWMNW1VGmTGftvrHWikaUoDdRPspMIlrH7S8ihtCCPMiBgX5pQGeZw9e4epUw+ya5cxdpiDg4p33mnJiBHNsLe3yrVOliyT89YRnLI9QaIy3nTdN6smgeoWVM/yK9RWZWmQR2lDGGEVDKFIC0dpkUlCgpoffjjK8uXhJk/KF1+szyeftKFaNac86xm3Ko0pkTLkxn9/uaSgTmZ9Gqub467L3cs4L0qLPEoLwggzIsaFOaVJHgcOXOPLLw8QHm505HF3t+ejj57ilVcamHlS5kRC4rrVVcJtj3FVdYlsu8tZ50pjTTPqaxphLT3c0SUnpUkepQVhhFUwhCItHKVNJtHRyUyffoj1688DRk/K4cOb8O67Qbi45K0U9eiItD7PKdvjxFndNF330HoTqG6Of2bdfG1VljZ5PGmEEWZEjAtzSps8DAaJDRsu8NVXB7l2LQWAunUr8dln7Xj66ZoPDeibLE/klO0Jztqcur9VKVlRT9OIxupmuOkrP/LzS5s8SgPCCKtgCEVaOEqrTMLD4/jii/0cPHgdAGdna959N4hhw5pgY/Pw803ZW5WR1udMW5V2envTVqW9lHfi6NIqjyeFMMKMiHFhTmmVR2amjuXLw/nhh6MkJho9KZ96yodJk9rRrNnDV8WzyOKCzRlO2R4nQXnXdL1aVg0C1c2pnuWfZ3ic0iqPJ4kwwioYQpEWjtIsE0mS2LPnKl9+uZ9z54znN3x8HPnkkza88EJ95PKHn91Il6URYRtGhM1JMhTZW5Vyat/bqvTQWbq3l2Z5PAmEEWZEjAtzSrs8kpM1zJ79H4sWnSAz03i84fnn6/LJJ22oWdPloXUlJGKsogm3Pc4VVaRpq9JJ70JjdTMCNI2xlmxIlafc99ZWyHFysiElRYNef2/iZ7DDwZD3UYryTrkwwi5evMi+ffu4ceMGAN7e3rRv3566des+zm6UCYQiLRxlQSZ6vYF164w5KW/eTAOgUaOqTJrUjg4dqj+6Pnqi7m1V3rKKNV1313oSqG5Brcx6pq3KGzbRHHDcRbvUrnhrHt12eUcYYUbKwvfkcVJW5BETk8KMGYdZu/YskgRWVnKGDAlk/PhgKlWyfWT9ZHkSp21PcNYmnMx7W5VKyYo6mgAuW180ZffIDTu9PUMS3kZB4TyTyzpl2gjLyspi0qRJbNy4EUmSkMuNHTQYDMhkMnr16sXUqVNRqZ5s5vjShFCkhaMsySQjQ8uSJSeZNetfUlONEbE7dqzOpEntadiwSr7aiFPeJNz2GJHW5zHIjDNkO4M9DdRNaKhpwlbn9cQpb+Ku86R/4muPNf9cUdHpdGRmakxJtR8kPT0Na2sbkTvyAYTuKDhlTR4REXeYMmU/e/dGA+DoqGLMmFaEhDTFzi53T8qcaMnigs1ZTtkeJ1555/4NCXJVERJU1XnwUtLrZUqHFCdl2gibNm0aq1atYuDAgbz66qv4+voik8mIjo5m1apV/PbbbwwePJgJEyY8ju6UCYQiLRxlUSbx8Wp++OEIy5eHo9UakMmgf/8APv74KXx88rf8nyFLN21VpiuMq2sySWaKzA/QIfUZ/LJqY2uwK3L8scfBzJlfEx5+glWr1uZ6/7XXXqZZs5a8++77+W5TGGFGyuL3pCQpq/LYty+aL788wOnTtwHw9HTg44+f4qWXAvI1fiUkblhdI9z2OJdVF3M3wO7RLfl5amXVFUZYWTTCgoKC6NixIzNmzMj1/gcffMD+/fs5evTo4+hOmUAo0sJRlmVy5UoS06cfYsOGCwBYWysICWnK2LGtcHbOn3u5Hj2XrC8Sbvuf2Vblg6gM1thKttga7LAxGP/aSnbGvwZbbEyv7bCVbLGSVI9d+fbv34du3bozbNibud5ftmwRO3Zs43//+zPfbQojzEhZ/p6UBGVZHgaDxPr155k+/RDXrxs9KevXN3pSdunycE/KnCTLk/jdZZUxNE4eVeSS3KgvpHt6wqQ37usQkz4x2GEj2ZaJCV9+KAnd8dg2dnU6HYGBgXneb9q0KXv37n1c3REISiU1a7qwaFEP3n67OV98sZ/Dh2OYO/cYv/4awbhxQbzxRiDW1g//2iowxhSzNlizySWXFaR72w1Z8kyyyCRZkZSvvikkxX2DLYexlv3a5p6xllP5FtVoi4+/Q5UquQe4BahcuQp37twu0mcIBGUduVzGiy/Wp2fP2ixbFsaPPx7l3Ll4Bg7cQNu21Zg0qR1Nmjw6FZqzwYWuqT1y1RsKgxK9XIdBZiBDkU4GDzfyc2JtsLY00Ex64wF9YrDDitJzLOlBZwU1NqQoNOgpHmeFx2aEtW3bloMHDzJw4MBc7x84cIA2bdo8ru4IBKWapk09+PPP/uzadYUvvzzAhQvxTJq0jyVLTvLJJ23o27feQz0pJSSO2O+32I6USTKq6NzpnfwSGrkatSwDtVyNWp6BWp6BJuf7HK/1Mh16mZ40RSppitR8PYNMkmEt2Zitpt1/bT5bzr734IFfJydnrl2LzvMzoqOv5HleLM86yiv8wi7aKbvirROOCoLyg42NkpEjWzBwYENmzfqXJUtOcvDgdZ55ZjX9+tXlk0/aUr2680Pb8NXWpKrWgzvKOCSZZNIZLyW9jh49GnkGatl9nWHUGzne59AbGpkaZJApzyRTnkkSifl6DqWkzMVAM07sTDojxz1ryaZEVun16FjjsgK1IsP8Rg6bq6jOCiW2HZmUlGT2PiEhgXfffRdfX18GDRqEr68vANHR0fz666/ExMTwww8/4OfnVxLdKZOILYXCUd5kotMZWLPmDDNmHObWLeN4aNy4KpMnt6ddO99c60RbXc59FewevZNeoro2/981LVn3lGxOAy0jhyFn/jrb66qgWBlUZlsbOybt4MyOM4xdPI7adeqa3bt+/jrjRo2iU6eufPrp5Hy1LyGxznVlvhwVxHZkxaI8yuP69RS+/voQv/9+zuRJOXRoE8aNC8LNLW9Pygf1R0H1RTYGDGTKNGYGmiaXSV7O19nORQVBJsnMDTTTMQvLCaCNacL36C1SCYm1Lj9zW3mrQM4KpeJMWL169Sz2obM/Kq/rcrmcs2fPlkR3yiRCkRaO8iqT9HQtixadYM6c/0hLM3pSdulSg88+a0dAwH1PysIqjuJEj958dixX31tlu6dsZRnGGXUOJZxzxS4bdZyanS/uRpOQiXdnL5xqGaegyZHJxO69iY2bDb3/15PK7lXyPNuWc9vjtvIWm13Wmdp/2I+LMMIqFuVZHqdP3+aLL/azf/81AJycrBkzpiUhIU2xtbX0pCzIZKU4kZDQyrLMVtosV+fv6ZN7K3JZhZzwqUxbpJYGWs7V+gRFPLud/sqzndx0SKkwwubMmZPvw4A5GT16dAn0pmwiFGnhKO8yuXs3g++/P8KKFafQ6YyelK+80oCPPnoKLy9H9OhY7jbfcgk9B6Ut3o+ERKYsM8ds+b6xFhd/i7/mbOHCP+fJTLuXgsXBCu+uXjQe1xBb90fHRsrxQUZkmG2z5PYDI4ywikVFkMfevVf58ssDnDljDEnh5eXAxx+3oX//+hZjvazEF9SjM+mK+8ZZhtnKveaBLdLcJnyP5IHQHQ/TH6XCCBMUHaFIC0dFkcnly4l89dUhNm26CICNjYIRI5oxZkwrZC6Z5S7ytSRJJCUZz5S4uLiik+kstkFzrrRZbpFqcm03r9UwYYRVLCqKPPR6A7//fp6vvz7EjRvG850BAZWZNKk9deq4kZBgDNZq1Bu2pKSoTXqjcmU7vLwcn1jfiwMJCU2OLdIHV9o0FqtuGejz2CItDt1Rpo2wffv2sXjxYqKiokhLS8Pd3Z2uXbsyevRoHB3zHihqtZr58+ezdetW7t69i4eHB3379mX48OGmoI+nTp3it99+49ixY9y+fRt3d3eeffZZ3n77bezs7ExtzZkzh7lz51p8xueff86AAQOK9HxCkRaOiiaT48dv8sUX+zlyxJiFws3NhvHjgxkyJBCVSsHBg9eZMGEv06Z1om3bak+4t08GCYk1Lj9z995h49h9Nzm/+AIpUSlo03S4V/agffuOvPHGCBwcjAf9c1OkQneUXyqaPDQaHUuWnOTHH/8lJeXeCrOVHK0272evWtWO48eHP9JDuzwhIZFFFn+4/kKC4q6Fs0JRV9HLtCSTkpJo3LgxgwcPxsXFhcjISObMmUNkZCTLli3Ls96XX37Jjh07GD9+PP7+/oSFhTF79mzUajXjxo0DYNu2bURHRzN8+HBq1KhBVFQUs2fPJjw8nJUrV5q1Z2Njw88//2x2rVq1ivljJ3j8NG/uycaNL/H335eZOvUAFy8mMHHiPyxefJJPP23DTz8d59y5u0yZsp/t2wcW6phAWeea1RXuWN0yvc9KyqJSYzdqD66FtYsK31O12LD4Dy5fvsQPP8zLsx2hOwTlBRsbJaNHt2TgwIb8+OO/LF168qEGmEwGXl6OqFTlI+ZXfpEhwxpr2qR1MjkrSDKJ4PT2xXJOrkwbYX369DF7HxQUhEql4rPPPiMuLg53d3eLOgaDgW3btjFs2DAGDRoEQHBwMFeuXOGvv/4yKdKQkBDc3NzM2nZycuL9998nIiKChg0bmu7J5XKaNGlSAk8oEOQPmUxGt27+dO1ak99+i2DGjFCio5N5882tpjInT8bx/fdHaNPGF0dHFU5O1jg5qXBwUJXZbbf8kB2uI+eZjhp9qucsgFMzO0bIR/HtN19x9+4dKle2TBkldIegPOLmZsuXX3Zg2LAmvPvu3xw6FJNrOUmCF1+sz6VLiTg6WuPoqMLWVllhJnW+2pq46zxNzgq+2prF0m6ZNsJyw8XFBQCtVpvrfUmS0Ol0FtuVjo6O5NyZzalEswkICADg9m0RHFJQOlEq5Qwe3Jh+/eqzYMExZs4MxZBjcjtjRigQalHP3t7KZJhlK1jjaxWOjkZjLfuvg0O2AXf/fmlWyAb0pMpT8k7HIoM0eSpVnb0BoTsEFZPq1Z1Zv74/7dr9zMWLCbmWmTjxH7P3SqX8AR1h1A156Yj7E7/75R0drVEqS+8k8MaNVOLjjedrPSsHkl5Hg+fFQE7fNX6Xi3pOrlwYYXq9Hp1OR1RUFPPmzaNz5874+PjkWlahUNCvXz9++eUXmjVrhr+/P+Hh4WzcuJGRI0c+9HOOHz8OYBHLTKPREBwcTEpKCjVq1GDIkCG89NJLxfJsjxqc2SsY5Xklo6AImYCzszUtW3qZGWDZeHjYo9MZSEnJIivLeOA0PV1LerrWFIesMCiVcpPSze1vfq6VhEJWomJQ6lAy7jkqnDxxkzlz/uOdd1rSOLAqep2eO5du88OKmbRr14Fq1YTuqIgIeRiZNq0T/fv/YXG9WjUnDAaJlJRM0tKykCRjDMPERA2Jibk7veSX7EmgubH2KH1hNOSyr9nZWRX7JDAzU8czz/zKnTsPeprvMb2qWtWO8PARhT4nV6YP5mfTvn174uLiAGjXrh2zZ882OwD7IHq9nsmTJ7Nu3f14QW+++Sbjx4/Ps05CQgJ9+vShUaNGzJ8/33R948aN3L17l4CAADIzM9m8eTNbtmzhww8/ZNiwYUV6LkmSSuXKgqD0I0kSQUFLOHHiJnr9/a+4QiGjWTNPjh4djkwmIzNTR3JyJikpmSQna8xeG/+av87tWmpqJsWpReztrXByssbZ2ebe3+zXqlyuGV9nl89+nZdCzpbLf//F0rKlFzY2q4TuEAhy8KDueFBngDFXZVpaVpH0RkpKJhqNrtj6rVDILPSApY54uN5wdrYxm7xky+L48dhcJ7RyOTRv7mUmm4JSLoyw8+fPo1ariYqKYsGCBfj4+LB8+XIUitwPEM6YMYPNmzczduxYatSoQVhYGPPmzWP06NEMHz7corxWqyUkJIRLly7xxx9/ULVq3rnsAMaMGcPhw4cJDQ3FysoyEF5+0esNpKSoH1omNzfiio6QCezefSXX2Ww269a9QJcuxXOmIVshp6YalXJKSqbp9YPXUlMtr2X/LW6FbD5TNr5OT9dy8OB1U7k5c5rTuLEbly9fZvnyJXh7ezN79gIUCgVOTrYWqyJCd5RfhDzu86D+KE59kZOsLD2pqZmkpGTrAeNr49+cr3O7lq1TsjAYis+MsbVVmq26abUGTp/O+xhBbrLJTXfkRbnYjqxXrx5gTALeqFEj+vTpw86dO+nWrZtF2YsXL7Js2TIWLFhA586dAWjZsiU6nY5Zs2bxyiuvmFzUwWgJf/rpp5w6dYrVq1c/UokCPPfcc/z9999cu3YNf3//Ij1bfl2l9XpDhXCrLggVVSaSJDFt2kFkMnJdoZLJYNq0g7Rv71tsqyV2dlbY2Vnh7m5f6DaysvR5GGtZpKWZK+Ts9w+Wz1bIer1EUpKGpKS8t0nkchlLl8bw99/tqV+/EXXq1OeNNwayZ89uOnXqalFe6I6KgZAHtG/vS9Om7pw8GUfTpu60b+9bIjKRy2X3VqJsCt2GJEmkp2sfMNbMdUi2jshLh6SlZaFWGyeBarUOtVpHXNzDj2YoFDIaNapaZNmUCyMsJ3Xr1sXKyopr167lej8qKgqA+vXrm10PCAggKyuLuLg4M0U6Y8YMtm3bxuLFi03GnkBQmsnK0nPjRmqeW4SSBLGxqWRl6UtVvB+VSkHlynZUrpz3duCjeJhC/u+/WBYtOmkqazBIhIXFsXdvNJ0716BWrdoolUpiYnL3DhO6Q1BRkMlkfPZZeyZM2Mtnn7Uv1VvbMpkMBwejw5CnZ+HbycrSm7ZYHzTajh27yfLl4Wbl9XqJjz9uU2TZlB4NXEyEh4ej1WrzPJjv7W30gDpz5gyeOf7FIiIikMlkeHl5ma4tWrSIFStWMHPmTFq3bp3vPmzduhUnJydTkvLCIpfLcHPL38qCk1MBUrdUECqyTK5fH2e2RC+Xyyzel2aPpKJQqVLu17t1q8NHH7WzuK5SKXBzsyc8PAydTkedOn64udkjl5srV6E7KgZCHkZ6965H374BFX5rFuDNN+HLLzubHJnAqDc8PR1yLf+g7ngYZdoIGz16NA0bNqRu3brY2Nhw/vx5li5dSt26dena1bid8Omnn7JhwwZTYvCGDRvSsGFDJk+eTHx8PL6+vpw6dYpFixbxwgsvYGtr/AJu3ryZ7777jt69e+Pj40NYWJjpc319fU1u6P369eP555/Hz88PjUbD5s2b2bFjB59++mmRznSA0cJXKPL3j1nRPXpyoyLLpCI/e25kZGjNFOiUKR9Ru3Z9atashUplzd2711i1agV169blmWeeRqGQC91RQRHyMEfIw4ibmy23bqWZvS8O2ZRpI6xx48Zs3bqVRYsWIUkS3t7e9O/fn2HDhqFSqQBjgEW9/r7yVSgU/PTTT8yaNYuFCxcSHx+Ph4cHw4cPJyQkxFTu0KFDAGzatIlNmzaZfe706dPp168fYFSqK1as4O7du8hkMurUqcO3335L7969S/rxBQJBPrGzs8LPz9X0vnXrFmzdupXff18ldIdAIHgkD+qQ4qJceEcKBAKBQCAQlDVK3TpjZmYmWVlZT7obAoGgjCF0h0AgKGs88e3Io0ePsnv3bk6cOMGlS5fQaIwu5TY2Nvj7+9O0aVO6du1KUFDQE+6pQCAoTQjdIRAIyjpPZDtSq9WyZs0ali9fzo0bN3B2dqZBgwb4+Pjg7OyMJEmkpKQQExPDmTNnSE5OxsvLi6FDh/Lyyy8X+dCqQCAomwjdIRAIyhNPxAjr1KkTWq2W559/nueee44GDRo8tHxERATbt29nw4YNqFQq9uzZ89DyAoGgfCJ0h0AgKE88ESPsf//7H/369TN5IeWXrKws1q9fzyuvvFJCPRMIBKUZoTsEAkF5QnhHCgQCgUAgEDwBnvjB/JxkZWVx5swZ4uPjadasmSmooUAgEAgEAkF5o9SEqFi5ciVt27Zl4MCBvPPOO1y4cAGAhIQEgoKC+P33359wDwUCQWklKyuLkydPsmvXLhISEp50dwQCgSBflAoj7I8//uCrr76iXbt2TJs2jZw7pG5ubgQHB7N169Yn2EOBQFBaERM4gUBQVikVRtjy5cvp0qUL3333HZ06dbK436BBAyIjI59AzwQCQWlGTOAEAkFZplScCYuOjmbw4MF53ndxcSEpKenxdaiUIEkSBsOj/Sbkclm+ylUkhEzMKa/yWLZsGZ07d+abb74lKSkRAINBQq83ABAQEMAvv/xiep9NfuQhl8uQyfKXBLu0IXRH4RDyMEfIw5Li1h2lwghzcnIiMTExz/tRUVFUqVLlMfaodGAwSCQkpD+0jFIpx9XVnpSUDHQ6w0PLVhSETMwpz/K4du0affu+REJCOsnJGQCkpmpM3xul0pakpCSz71F+5eHmZo9CUTaNMKE7Co6QhzlCHpaUhO4oFduR7du3Z+3ataSkpFjci4yMZN26dXTu3PkJ9EwgEJRmHBwcSU5OyvP+1auXcXOr9Pg6JBAIBAWgVKyEvfvuu7z00kv07NmTTp06IZPJ2LBhA3/88Qc7duygSpUqjBw5ssif8+eff/Lzzz9z6dIl7OzsaNSoEXPnzsXKyoply5bxzz//EBUVhSRJ1K1bl7Fjx9KiRYuHthkTE0OXLl0srgcGBrJ27doi91kgEORNcPBTbNr0J3379re4d/nyJTZv3kCPHr2L/DlCdwgEgpKgVBhh7u7urF+/nu+//55t27YhSRIbN27E3t6eHj168P777xc5ZtiCBQtYvHgxb731Fk2aNCExMZHQ0FD0ej16vZ5FixbRt29fQkJCkMvlrF27ltdee42lS5fSunXrR7Y/fvx4s0TB9vb2ReqvQCB4NCNGjGTEiCG89trLtGnTDplMxrZtW/jrr038888eKlWqzJAhIUX6DKE7BAJBSVEqI+YnJCRgMBhwc3NDLi/6junly5fp1asX8+fPp0OHDhb39Xo9aWlpODs7m13r2bMn1atX56effsqz7ezZ7KxZs+jWrVuR+2reL0O+z3UkJqaLfft7CJmYU97lkZiYwMKF89i3by9paakA2NnZ0aFDZ95++x1cXc0ncPmVh5ubPdHRV4XuqCAIeZgj5GFJQXSHQpE/26VUrIQ9SHFHyl+/fj0+Pj65KlEAhUJhpkSzr9WtW5dr164Va18EAkHx4urqxscff8bHH39GYmIikmTAxcW1WCZwQncIBIKSpFQZYSWVtig8PJw6deowf/58Vq1aRWpqKg0bNuSTTz4hMDAw1zo6nY7w8HCaN2+er8/4/PPPGTduHC4uLnTp0oX3338fFxeXIvddqXz4D0m2tZ1fq7siIGRiTkWQR1ZWFhcunCMxMZHGjQNRqfJWbQWRh9AdFQchD3OEPCwpCZmUGiNs5cqVzJ07l9RU43bCsmXLaN26NQkJCTz33HN88MEHvPjii4Vq+86dO0RERHDx4kUmT56Mra0tP/30E0OHDmXHjh1UqmTpPbVkyRLi4uIYMmTIQ9tWqVQMGDCAtm3b4uTkRHh4OD/99BMRERGsW7cOKyurQvUZjLFGXF3zdz7Eycm20J9TXhEyMae8yiNbd6SkpCCTyVi2bBk1a/o8UnfkRx5Cd1Q8hDzMEfKwpDhlUiqMsOyo1z169KBNmzZ8+umnpns5o14X1giTJImMjAxmzZpFvXr1AKMHUufOnfnll18YO3asWflDhw4xZ84cRo4cScOGDR/adtWqVfn8889N71u1akXt2rV588032blzJ927dy9Un8EY6yclJeOhZRQKOU5OtqSkqC0CUlZUhEzMKc/y2LJlI1999RVPP/0srVoFM23aF6SlaUhMTEcms6Z585Zs3LiZLl2eM9XJrzycnGyF7qhACHmYI+RhSUF0R5k6E5YzbVFuQVsbNGjAqlWrCt2+k5MTLi4uJiUKxij8AQEBREVFmZU9c+YM77zzDj179mT06NGF+rwOHTpgZ2fHmTNniqRIgXwfiNTrDeLw5AMImZhTHuXx66+raNu2A5MmTTXFC9PrJdNz1q5dl99/X5Prc+dHHkJ3VDyEPMwR8rCkOGVSKjZ7o6Ojad++fZ73i5q2qFatWnney8zMNOtHSEgITZs2ZerUqYX+PIFA8Hi4cSOG4OCn8rzv5ORMSkpyodsXukMgEJQkpcIIK+m0RZ06dSIpKYlz586ZriUmJnLmzBkaNGgAwO3btxk6dCienp7Mnj27SOcx9u7dS0ZGBo0aNSp0GwKB4NGUdMR8oTsEAkFJUiq2I7PTFg0cONDiXnbaohdeeKHQ7Xft2pVGjRoxZswYxo0bh7W1NYsWLUKlUjFw4EA0Gg0hISEkJiYyYcIEIiMjTXVVKhUBAQGm9wEBATz//PN89dVXAHz99dfIZDKaNGmCk5MTp06dYuHChTRs2JCuXbsWus8CgeDRlHTEfKE7BAJBSVIqjLCSTlskl8tZtGgR06dPZ9KkSWi1Wlq0aMGvv/5KlSpViImJ4fz58wC8/fbbZnW9vb3Zs2eP6b1er8dguL8X7O/vz2+//cbatWvRaDS4u7vz4osvMmbMGJTKUiFegaDcUtIR84XuEAgEJUmpiZgfHx/P999/z86dO02JvO3t7XnmmWd4//33c3UFL++IqNeFQ8jEnPIuj5KMmF9WYyQJ3VFwhDzMEfKwpCR0xxM3wtRqNYMGDaJ///4MGDAAKP60RWUVoUgLh5CJORVJHvmJmC+MMCMVaVzkByEPc4Q8LCkJ3fHENYytrS0xMTHIZDLTNTc3NypXrlyhDTCBQPBwNBoNQ4e+yoYNv5uuubq64uZWSegOgUBQJigVmqpdu3YcPHjwSXdDIBCUIWxsbLh5MxaQPbKsQCAQlEZKhRE2cuRIrl69ygcffMCxY8eIi4sjKSnJ4n+BQCDISVBQa/7998iT7oZAIBAUilLhgtOjRw/AGA9sy5YteZbLGatHIBAIhgwZzmeffcSUKZ/Ru/cLeHl5YW1tbVHOycn5CfROIBAIHk6pMMJGjRpldiZMIBAI8sPgwS8BcPXqFXbu/DvPcvv3//u4uiQQCAT5plQYYe+8886T7oJAICiDDBkyXEzgBAJBmaVUGGECgUBQGIYNe/NJd0EgEAgKTak4mC8QCAQCgUBQ0SgVK2H16tV75JaCtbU17u7uBAUFMXz4cHx9fR9T7wQCQWmlXbuWj9QdKpWKKlWq0qxZCwYOfI3q1YXuEAgEpYNSYYSNGjWK3bt3ExUVRbt27ahevToAV69e5eDBg9SpU4egoCCuXbvG+vXr+euvv/j111+pV6/eE+65QCB4kgwZMpyDB/dx5cplgoOfwtu7GgAxMdc4ejQUP79aNG/ekpiY62zdupldu/7mp5+W0qpV0yfcc4FAICglRljVqlVJTExk27ZtVKtWzexedHQ0gwcPplatWnz00UdcvXqVl19+me+//55FixYV6HP+/PNPfv75Zy5duoSdnR2NGjVi7ty52NjYALBnzx5+/PFHrly5gpeXFyNGjOCFF154ZLupqalMnz6dXbt2odVqadeuHRMnTqRq1aoF6l9B0ep17IgMI5V0HLGnk18TrBSl4p/0iSFkYk55l0flylVITk7m/+3dd3hTZfvA8W+SprvpgFI6oIPRUlaRUQoFZKkMRQER9AX9yRAVBBS3oiKK+r7KUFYR3DIEFMSCyJANijIEWaWMttAyuktHxvn9EQiEFigtJWl7f66rF805J+c8uUlP7jzzu++WEBgYZLUvOTmJ0aOfIiQklGefHUNS0imeGvl/vPPfSdw/7v9uKR5V7d4hhLAPdnE3njdvHo899lixBAwgODiYxx57jLi4OPr160dISAgDBw7k+++/v6VrzJo1i7lz5zJy5EiioqLIyMhg+/btGI1GAHbt2sWoUaPo378/r732Gjt27OD111/Hzc2N++6774bnHjt2LAkJCbz99ts4OTkxdepUhg8fztKlS3FwqJgQL/rndxIjduLe7srSn3+dXkfYv9E80vTuCrmmvZOYWKsO8Viw4BseeujhYgkYQFBQHfr2fZhvvvmSXr0eYFtmIrXuD+DkisOcbrcdKF08qtq947IVB3awu/YmWqR2pGd4mwq9VmUg8bAm8SiuImJiF0lYamoqGo3muvs1Gg1nzpyxPA4KCqKoqKjU509MTOSzzz5j5syZdOrUybL93nvvtfw+a9YsmjVrxsSJEwFo27YtSUlJTJ8+/YY30t27d7NlyxbmzZtHbGwsAKGhofTs2ZM1a9bQs2fPUpeztBb98ztpd+/A7ZrtbrUV0mrvYNHvVJkP2dKSmFirLvE4e/bsTe8dZ8+mWeLhdc6V40VXFt69WTyq2r3jMpNi4i+vzXjVN/BXwWbuU1qhVlXfcVoSD2sSj+IqKiZ2kYTVr1+fBQsW0KdPH2rWrGm179y5cyxYsID69etbtiUlJRU77kaWLVtGUFCQ1U30akVFRezcuZPx48dbbe/ZsycrV64kOTmZoKDi37QBNm3ahE6no3379pZtYWFhNGrUiE2bNt32G6neaCAxYiduwLX//yo1KCZIjNjJuZy7qlSz043ojQaON9qJKxITqF7xqBscwrIffyCmU2e8vX2s9mWkX2Dpsh+oExxsiUdeSi7ONZ0tx1jiEf4HemNssXhUpXvH1VYe3IlXJz0AXk30LFm/mXvqta6w69m7Ncf+xKuLxOMyiUdx18Zk5cadPBAZU+7z2sUd+OWXX2b48OF0796dbt26WTrmnzx5krVr12IwGHj//fcBKCwsZNmyZXTs2LHU59+7dy8NGzZk5syZfPPNN+Tk5NCkSRNeffVVmjdvzqlTp9Dr9YSFhVk9r169eoD52/D1bqSJiYmEhoYWG6EVFhZGYmJiqct4PQ4O1p+ia47usWpeupZKDe4BCguZWe5rVybX1vhcrTrGpLrEo86bfmwafpT/+7/+BHYLwD3YHYDck7mkrD2NyWAi8qMGuPkrGAuNHF92Ev+Ota3OoVKDe6CJDdv20LORdRNDVbp3XGZSTOytsQ1PBS5fOq3Ldr5he7mvWWkFWz+UeFg/rPbxAKuYmAywt8Y2HtTElLs2zC6SsOjoaBYuXMj06dP57bffKCgoAMzTUsTExDB69GgaN25s2bZly5ZbOv+5c+fYv38/R44c4a233sLFxYXZs2fz5JNPsmbNGrKysgDQ6XRWz7v8+PL+kmRnZ+Ph4VFsu6enJ/v377+lcl5LrVbh7W39cZpDXrnOKURVUiu6Fl0Xdmb/9H9J/i0FY4G5n5bGSYNfTC0aj47Ep7G3ZVufLb2ve64c8or9vVWle8dlC3dtxKuVvlznF6I6UzuYa8N+2/U3A1uVXEteWnaRhAFERkYye/ZsTCYTFy5cAKBGjRqo1eVvc1UUhYsXLzJt2jTLtBbNmzenS5cufPvtt5b+GPbGZFLIzr5otc3jhnUcV4Rs6kjnelEVUCr7s+HYHk503HTT46pLTKpdPDyBN8FkMpGZmQGAl5e35d6xYVPp4uGBGxkZV77k6HQuVereAeZasG3OG9AZzB8klu0GyD6iZYxuJOpqtAyUSVGYlj0bXUO9xAOJR0luFJNtzhvonn5Xsdownc4FjaZ0uYvdJGFg7l9x4MABLly4wF133XVbEjAwfyv18vKymlfMy8uLyMhIEhIS6NWrF2AeLn617OxswPzN9EbnTk1NLbY9Kyvrhs8rLYPBZPW4c1gUf51eh1ttpVh/HzD3b8k7o+a+hm0qfX+f0rqvYRv+d3qzxOSS6hwPXW33YttKG4/OYVHF/t6q0r0DYMW/2y19wa6mdgCvSD2/b9x3W/q5VBYSD2sSj+JuGJMmen7auL1cMbGb4Q5ff/01sbGxDBo0iNGjR3P48GEA0tPTiY6OZsmSJWU+99Wd+q9VWFhI3bp10Wq1xfphXH58bX+Pq4WFhXH8+HEUxbqf1vHjx2/4vLLSahwIOxQNmD88rnb5cdjhqvfheiMSE2vVMR5FRUXs37+PzZt/JzMz02pfeeJRle4dJsXEnhrbMBmvs9+Ief+1QaqiJB7WJB7F3YmY2EUStnTpUt5//306dOjA+++/b3VT8vHxoW3btsTHx5f5/J07dyYzM5ODBw9atmVkZHDgwAEaN26Mo6Mj0dHR/Prrr1bPi4+Pp169etftWAvQsWNHsrKy2L79SqfF48eP8++//97S4IFb8UjTu/H7vS15qdbVwnln1Pj93rZKTD1wqyQm1qpTPH74YSF9+tzHM88M4/XXX+LYsaMAZGZm0qtXV1auXF7meFSle0dBURFOtQyorzOjh1oDTr4GCm5h+p/KTOJhTeJR3J2IiUq59muYDfTu3Zvg4GBmzJhBRkYGMTExfPHFF8TEmKv44uLi+Oabb9i8eXOZzm8ymRgwYABZWVmMGzcOJycn4uLiOHHiBCtXrsTX15ddu3YxZMgQBgwYQI8ePdi5cyczZ85kypQp9OjRw3KuyMhIHnzwQctoTYChQ4dy7NgxXn75ZZycnJgyZQpqtbrcEy4ajSbS06/fEV9vNLAhserOhl4WEhNrVT0ev/yygg8+eJeuXe+hTZu2TJ48kalTZ9KypXk4/ZtvvkJubg5TpswAbi0ePj5uqFRUqXvH0bOnOZtn7jenUatxc3MiL68Qo8n8Td7P3Yf6vv5lvm5lI/GwJvEoriwx8fFxq1x9wi4vTXQ9Xl5exZoYboVarSYuLo7JkyczYcIE9Ho9rVq14rvvvsPX1xeAVq1a8emnnzJ16lSWLFlCQEAAkyZNsrqJAhiNRkwm66rHqVOnWs5tMBiIjY3ljTfeqPAZr7UaB3o2aoO3t7lDcUl9QKobiYm1qh6PhQu/JTa2E2+//R5ZWZnF9oeHR7BkySLL41uNR1W7dzSoFUADAgDzFBZV9X1RWhIPaxKP4io6JnaRhOl0OjIyMq67PyEhwXLDKysfHx/++9//3vCYrl270rVr1xsec7mv2tU8PDx4//33rb7hCiEqXkpKMv37D7zufp3Ok+zs608TURpy7xBCVBS76BPWsWNHFi9ebBlRdLWjR4/yww8/0KVLFxuUTAhhz9zdPUqsAbvsxIlEfHxq3LkCCSHELbCLJGzs2LEYjUZ69+7N1KlTUalU/PTTT4wfP55+/frh4+PDM888Y+tiCiHsTNu27Vix4sdiU0QAJCYe4+effyI2tmIGyAghRHnZRRLm5+fHsmXL6NChA6tWrUJRFJYvX86GDRvo1asXixcvxsfH5+YnEkJUKyNGPIPJZGLIkEeYO3cWKpWKVatWMnHimwwbNgQvLx+eeGK4rYsphBAlsovRkddKT0/HZDLh4+Nz2yZsrYxuNjoSpPNkSSQm1qp6PDIy0pkzZwYbN24gN9dcI+bq6kqnTl14+unRxRb2Lm08bmWEk72Re8etk3hYk3gUVxH3DrvomH8tqfUSQpSWt7cPr7zyJq+88iYZGRkoislq2SIhhLBXdpmECSFEWXh7e9u6CEIIUWo2ScIiIiJQlWER0KtnrRZCVD8dOrQu071j06Y/KqA0QghRPjZJwp599tliN9LffvuNhIQEYmNjCQ0NBczrr23dupUGDRrQrVs3WxRVCGFHnnhiWLF7x6ZNv3P8+DGio2OoUycYgFOnTvDHHzsIC6tHhw5326CkQghxczZJwkaPHm31eNGiRVy4cIGff/652MK1x44d4/HHH6dWrVp3sohCCDs0dOhTVo+XL19GRkY633yziLp1Q6z2nThxnDFjRlKzZvkmehZCiIpiFz1X582bx3/+859iCRhAvXr1eOyxx/j8889tUDIhhD1bsOAb+vUbUCwBAwgJCaVv3wF8//3Xd75gQghRCnaRhKWmpt5wrTQHBwdSU1PvYImEEJXB2bNnb3rvOHv27B0skRBClJ5djI5s0KAB33//Pffffz9+fn5W+1JTU1mwYAENGzYs8/mXLVvGq6++Wmz78OHDGT9+PMnJyddd983R0ZF//vnnuufeuXMnQ4YMKba9Z8+eTJkypcxlFkLcXFhYPX78cQndu9+Hr691l4WzZ9P48ccl1KtXr8znl3uHEKIi2UUS9uqrrzJs2DDuvfdeunXrRnCwuXPtiRMnWLduHYqi8NFHH5X7Op9//jkeHh6Wx5cTvlq1arFo0SKrYxVFYdiwYbRt27ZU5548ebJVc6oMlRei4o0e/TwvvDCKQYP60rFjZwIDgwBITk5i8+bfURSFN998t9zXkXuHEKIi2EUS1qpVKxYvXsy0adNYu3YtBQUFADg7OxMbG8vo0aMJDw8v93UaN25c4kSwjo6OREVFWW3buXMnubm59O7du1TnbtCgAU2bNi13GYUQpde8eRRxcV8yd+5sNm3aQGFhIQBOTk60aRPD0KFPUa9e/XJfR+4dQoiKYBdJGEDDhg2ZMWMGJpOJ9PR0AJsuW7Ry5Urc3d3p0qWLTa4vhCidsLD6TJ78P0wmE5mZGQA2nTFf7h1CiNKymyTsMrVaTc2aNSvk3L179yYjI4OAgAAGDBjAsGHD0Gg0xY7T6/WsWbOG7t274+TkVKpzjxgxgszMTHx9fenVqxdjxozB2dm53GV2cLjxB8nl9akq6xp3FUFiYq36xENNrVo3n46iLPGQe0fVJ/GwJvEoriJiYpMkrGfPnowYMYKePXvi6OhYqucUFRXx888/M2/ePOLj42/per6+vowePZrmzZujUqlYv349U6dOJS0tjQkTJhQ7ftOmTWRmZpaqOcHDw4Nhw4bRunVrnJyc2LFjB/PnzycxMZE5c+bcUjmvpVar8PZ2K9WxOp1Lua5VFUlMrEk8rJUmHnLvqH4kHtYkHsXdzpioFEVRbtvZSmnu3Ll8/vnnmEwmunTpQkxMDI0bNyYoKAgXF/OLu3jxIsnJyezfv59t27axYcMGtFotQ4cOZfjw4eUuw4cffshXX33F77//Xmwi2LFjx/Lnn3+yadOmEr/t3sx3333HxIkT+eGHH2jWrFmZy2g0msjOzr/hMRqNGp3OhezsfIxGWekeJCbXqkrxGDiwH0OG/B/du9+LVqst1XOKiopYs2YV3377NQsXLi11PHQ6lxK/8cq9o2qSeFiTeBRX3ntHSWxSEzZ8+HAGDRrEkiVL+PHHH1m+fLllKZLLNy6j0QiYRxo1aNCA0aNH079/f9zd3W9LGXr06MH8+fM5ePCg1Y00Ly+PDRs28PDDD5fpJnr53BMnTmT//v3lupECGAyle/MbjaZSH1tdSEysVYV49OjRm2nTPuaTT/5LbGxHWrVqQ8OGEQQEBFqa8PLz8zlzJoVDhw6ya9cfbN26Ca1Wy6BBg61ef1njIfeOqk3iYU3iUdztjInN+oS5u7vzxBNP8MQTT5CcnMzu3btJTEwkMzMTAC8vL8LCwoiKiqJOnTp3rFy//fYbBQUF3H///XfsmkKI0nnsscd56KH+rFy5nPj4lfz6a/wNv8CFhdVj6NCn6NXrAdzcbs8XuOuRe4cQ4lbZRcf8oKAggoKC7ug14+Pj0Wg0REZGWm1fuXIldevWpXnz5mU+9y+//AIgw86FqACurm4MGPAoAwY8ypkzp/nnn32cOnWCrKwsADw9PalbN4QmTZoSEBB4268v9w4hxO1iF0lYRRs6dCjR0dGWucbWrVvH4sWLGTJkCL6+V0ZTpaens3379uv2OUtJSaF79+4888wzjBo1CoDx48cTHBxMZGSkpXPtl19+Sbdu3eRGKkQF8/cPwN8/oMLOL/cOIURFqhZJWGhoKEuXLiU1NRWTyURISAivvfYagwcPtjpu1apVGAyG6zYnKIqC0Wjk6rEMDRo04Oeff2b+/Pno9XoCAwMZOXIkI0aMqNDXJISoeHLvEEJUJJuMjhSloygKJtPN/3s0GrWMXrmGxMSaxMNaaeKhVqss/c0qG7l3lI3Ew5rEo7jbfe+QJEwIIYQQwgZkKlwhhBBCCBuwiyRszpw55OXl2boYQgghhBB3jF00R/bq1YuzZ8/y6KOPMnDgQGrUqGG1nNHRo0c5cOAADz74oO0KKYSwC6tXr2bv3r04OTkRHh5O+/bt0el0gHl2/H379uHr60twcLCNSyqEEDdm8yRs586drFu3jo0bN3Ly5EkURUGlUuHs7ExISAiRkZGcPXuWHTt2sH//flsWVQhhY9OnT2fmzJm4uroC5uXNnJ2dGTZsGEOGDOHhhx/m1KlTADRq1IiJEyfSpEkTWxZZCCGuyyZJmF6vZ9GiRXzxxRekpKTg5uZGUVERRUVF132Oq6srL7zwAo888kip14wTQlQtHTt2pEWLFnz88cc4ODhw8OBBPv/8c+Lj4wkNDSU1NZW33noLo9HId999x7Fjx1i8eDENGza0ddGFEKIYmyRhnTt3Rq/X8+CDD9KjRw9efPFFjEYjL7zwAoGB5hmuL1y4QFxcHLt27aJ9+/Y0atSIn376CUdHR9avX3+niyyEsANNmjRhwoQJDBgwwGr7yy+/zIoVK3jyySd58cUXAfOXvUceeYSQkBA++eQTWxRXCCFuyCaTtT711FP07dvX0u8rJSWFl19+mXvuucfquI4dO/Lzzz/zxhtv0Lx5c9avX8+yZctsUWQhhB0IDAxk3759xZKwRx99lOXLl1vNNK/VannggQf4+uuv73QxhRCiVGwyOnLgwIFWHe/r1avHgQMHSjz2/vvvZ/jw4Xz33Xc4OjoycODAO1VMIYSdeeSRR1i6dCmfffYZGRkZlu3h4eE899xz1K9f3+p4Jycnzp07d6eLKYQQpWIXyxYNGzaM559/Hm9vb2JjY8nNzeWuu+7Cx8cHMM/+XFBQYONSCiFs7cknn+TcuXPMmjWLWbNmERYWRnh4OOHh4TRp0gQPDw/LsXq9np9++slqjUchhLAnNh8dedmTTz7J1q1bLY8HDRpEVFQU//zzD99++y1169blt99+s2EJhRD2Ijk5md9++419+/Zx5MgRTp48idFoBMDT05OGDRty/vx5jh8/zsMPP8wrr7xiGVEphBD2wi6SsKVLl/L666/Ttm1bcnJyLFNRXF57ydnZmfDwcBYtWmTLYgoh7JRer+fYsWMcOXKEo0ePcuTIEY4cOcKZM2cA873Ez8+PevXq0aBBA1555RUbl1gIIewkCevduzfBwcHMmDGDjIwMYmJi+OCDDwgODsbDw4P169fzzTffsHnzZlsXVQhRiZhMJvR6fbGfy6OwhRDCluyiT9jJkycZPHiw1TY/Pz9atGgBwN9//01mZqYNSmZbiqJgMt08R1arVaU6rjqRmFirzvFwcNDi4KDFxeXKttL8banVKkttfGVzvdeXW5SP0bnQ/ODql3bpUE2BE+6OLsWeV11U57+Tkkg8iitNTG7l3mEXSZhOp7Ma6XSthISEatm51mRSSE+/8ZqaDg5qvL3dyM6+iMFgukMls28SE2sSD2uljYePjxsaTeVMwkq6d+iNBv5n+hi32gqqa8fFq0AxQV66mvGa59Fq7OKj4Y6SvxNrEo/iKuLeYRcLeHfs2JHFixeTnZ1dbN/Ro0f54Ycf6NKlS7mv8+OPP/Lggw/StGlToqOjGTZsGAUFBRiNRubOnctjjz1GdHQ0bdq0YfDgwezateum50xOTraMzrr659p5jIQQwpbWJezBPaCEBOwSlRrcA018ffxn8si9s4UTopqyi687Y8eOZcCAAfTu3ZvOnTujUqn46aefWLp0KWvWrMHX15dnnnmmXNeYNWsWc+fOZeTIkURFRZGRkcH27dsxGo0YjUbi4uJ46KGHGD58OGq1msWLFzNkyBDmzZtHTEzMTc///PPPEx0dbXns5uZWrvIKIcTtdL4gs1THXYw5zHwOU3hGi2t6Teo5BtPMpyG1TH5o0FRsIYWoZuwiCfPz82PZsmV88sknrFq1CkVRWL58OW5ubvTq1Yvx48db5gwri8TERD777DNmzpxJp06dLNvvvfdeAIxGI2vXrsXT09Oyr3379vTu3ZuvvvqqVElYcHAwUVFRZS6jEEJUpJrOXly/08cVmcfBMxic/PUY/c9whDMcYQemQhWas54EKkE01tUjwBiEu8nj5icUQlyXXSRhADVq1OC9997jvffeIz09HZPJhI+PD2p1+VtMly1bRlBQkFUCdjWNRmOVgF3eFh4ezqlTp8p9fSGEsLWu9aPYfXpdyX3CuNQn7Iyacern2PPrGXadOUSSkoQpMJParU241lBQ6mSSTCbJmKcRIsuJmgW1aegSRoAxEF9DbRzs52NFCLtnl38t5an1KsnevXtp2LAhM2fO5JtvviEnJ4cmTZrw6quv0rx58xKfYzAY2Lt3Ly1btizVNd5++23GjRuHl5cXXbt2Zfz48Xh5eZW77A4ON05CNRq11b9CYnItiYe16hoPrcaBsH+jSau9A8WEVSKmXOpjHHa4De5NnYltFUosoQDo9UZ270xlx5GjHC04wcUa56ndykitZgpqz0LOe57kPCfNJzCocM/1IcQhmEBTEH76AHQmT1RUzgEOQlQ0u5gn7LKioiIOHDjAhQsXrJYtKq/77ruPtLQ0atWqxbhx43BxcWH27NkcOXKENWvWUKNGjWLPmT17NtOnT2fx4sU0adLkuuc+e/YsM2fOJDY2Fp1Ox969e5k9ezZ16tThhx9+QKvVlrnciqJU2iHyQgjbMRpN1x1Zveif30mM2Il7wJVbf26KmrDDbXik6d03PbfBYOKff86yddcJDqQnku6Wim8LPYExCu5+xY/XFjgTqAThbwyktiGAWnp/HHEsfqCNXR75lpGRJ6MBkXiUpLQxMY+OLN2XPLtJwr7++ms+++wzcnJyAJg/fz4xMTGkp6fTo0cPXnzxRfr371+mc997772cOHGC5cuXExERAUBmZiZdunTh8ccfZ8yYMVbHb926lREjRvD0008zatSoW77e77//zlNPPcWUKVPo2bNnmcoM5htpdnb+DY/RaNTodC5kZ+djNMofCkhMriXxsFbaeOh0LpW2tuxGSRiYp6vYkLiHHPLwwI3OYVFlnpbCaDRx4MA5tm5L4q+E45xxSMG7WRFBbRVqt1DQXJtvKSpq6H3NSZk+gNqGALyMPjavLZOkw5rEo7iKSMLsojly6dKlvP/++/Tq1Yv27dvz2muvWfb5+PjQtm1b4uPjy5yE6XQ6vLy8LAkYgJeXF5GRkSQkJFgde+DAAUaPHk3v3r3LlIABdOrUCVdXVw4cOFCuJAwo9ZvfaDTJH8o1JCbWqkM8CgsLUalUODrevKalOsTjerQaB3o2anNbPmQ1GjXNmvnRrJkf0AqTSeHgwfNsX5/M9g9PceziKTwiCwhqqxDY1oRnXYULjme5wFn2u+wGwMnoTG2DOSGrrQ/Ez+CPk+J8m16tEPbLLpKwL774gq5du/Lxxx+XOGlr48aN+eabb8p8/vr161+3g31hYaHl95MnTzJ8+HBatGjBpEmTynw9IcSd8fffu9iyZSP//LOXEyeOW/6enZycCQkJoUmT5nTo0Im77mpl45JWH2q1isaNfWnc2Jdhw1qgKAqHD19g27Zktn+fzN7EUzg3uEhgWxNBbRX8WyngUsBJTSInnRLNJ1HAx1jzUk2ZucbM21gDtX1MbSnEbWMXSVhJyxZdzcvLq1zLFnXu3Jlly5Zx8OBBGjVqBEBGRgYHDhzgiSeeAMx9u5588kn8/f2ZPn16ufpybdiwgYsXL9K0adMyn0MIUTKDwcDy5UtZuPB7UlNPo9PpaNgwgnvu6YGHhw5FUcjJyebMmdOsWRPPkiULqV3bn4EDH6NPn344ONhff6SqTKVSERFRk4iImjz5ZBSKonDsWAbbtiWzbWoyv/2ZhFIrh8C2iqW2zKc+pDucJ93hPP+yDwCtyRE/gz/++kD8DAHU1gfgorja+NUJUT52kYRV9LJF3bp1o2nTpjz33HOMGzcOJycn4uLicHR05NFHH6WgoIDhw4eTkZHB66+/ztGjRy3PdXR0JDIy0vI4MjKSBx98kPfffx+ADz74AJVKRVRUFDqdjn379jFnzhyaNGlCt27dylxmIUTJHnnkQQwGPffd15suXboTHh5xw+MPHTrIhg1r+frrL1iw4Ft++umXO1RSURKVSkX9+j7Ur+/DkCHNUBSFEyey2LYtiW0rkln+ajLphdkERisEtTUR2FYhoI0CHkUkO54k2fGk5VyeBm9LE2ZtQwA1DL4yoayoVOwiCbu8bNGjjz5abN/lZYv69etX5vOr1Wri4uKYPHkyEyZMQK/X06pVK7777jt8fX1JTk7m0KFDADz99NNWzw0MDGT9+vWWx0ajEZPpSv+JevXqsWDBAhYvXkxBQQF+fn7079+f5557DgcHuwivEFXK4MH/R8+e95eq3xdAREQjIiIaMWzYSH75ZUUFl07cKpVKRWioF6GhXjz2mLn14NSpLHPz5fZkNs9N5lRSJr6NFXNtWYw5OavZCLIcMshyyOCw8wEAHBQHaun9LyVm5uTMTXG/aRlMmEhySCIJPTho8TMEStOnuCPsYnRkWloaAwYMQFEUOnfuzOLFi3nggQcwGo2WZYt++OGH2z5/mL272QgnkBEsJZGYWJN4WCvrCKe8vDx69OhBWloaS5Yssepu8MMPP/D5559z+vRpQkNDGTduHJ07d75hOXbu3MmQIUOKbe/ZsydTpkwpwyu7oqrdO1JScti+PdlcW7YtmcTETJy9zDVkQTHmvmV1YsDRs/jHmYdRZ6kpq60PxNdQC81V9Q8JjofZ5L6WPE2OZZub0YOOud2oXxR+R16fPapM7487pcqOjqzoZYuEEKK8Zs6cidFoLLb9l19+4c0332TkyJGWkdyjRo3iu+++K9VSZpMnTyYsLMzy2Nvb+3YWu0oIDPSgf/9G9O9v7tObmpp7KSlLZvuCZDa9kw4qhRoNISjG3IRZr5Maz4YGcjTZ5GiyOcpBANSKhloGP2rrAwAVe1z+RFGwmiAjV5XDKt2P9Mh+qFonYqLi2UUSBhW7bJEQomrIzs7m/PmzhIXVB2DHjm2kpCTRvPld1K/foMKue+zYMb7//ntefvll3nrrLat906dPp1evXowdOxaAtm3bcuTIEWbMmMHcuXNveu4GDRrIIJ5bVLu2Ow89FMFDD5n7A547d5EdO5LZujWJ7duTif/yAgCO7loCWpubMRt21eDf2gQ6A6na06RqT1vOd+2c2Cq1eRWBNZrVhNFAmiZFhbF5Epafn89jjz3Gww8/zKBBg4Dbv2yREKLy27p1M++++yYGg4GWLVvTunU0f/65E6PRyMyZ03n77ffo0OHuCrn2pEmTGDhwIKGhoVbbk5KSOHHiBC+++KLV9p49e/LRRx9RVFRU6r5roux8fV25//6G3H9/QwAuXMhnx45kS23Ztg/OsXUygArvMC2BbU20HKym7n36655TpQajez7JRaeoawy5I69DVD82T8JcXFxITk6W5XmEEDcUFzeTqVNnAjBixBM88shj9O8/EID169fy1VfzKyQJW716NUeOHOHTTz/lwIEDVvsSE83zWl2bnNWrVw+9Xk9SUhL16tW74flHjBhBZmYmvr6+9OrVizFjxuDsXP6JSqvzurN+fm706RNOnz7mpsTMzAJ27Ehhy5ZTbNuWzL6FZ1FMBured/Nz7UjfS0iNkGpXG1aV3x9lVRExsXkSBtChQwe2bNnCwIEDbV0UIYSdSks7Q0SEeboYrVZLixYtLfs6derMRx+9d9uvmZ+fzwcffMC4ceNwdy8+yi4rKwswT7NztcuPL+8viYeHB8OGDaN169Y4OTmxY8cO5s+fT2JiInPmzClXudVqFd7ebqU6VqdzKde1KgNvbzdCQ2swaFAzALKyCpi8YAWw96bPTat/kK9IpQ3R3EVLXKlec5NVh/fHrbqdMbGLJOyZZ55hzJgxvPjiizzyyCPUqVMHJyenYsd5eXnd+cIJIeyCk5MzBoMBBwcHevZ8wKr2vKioqEJq02fNmkWNGjXKNUXO9URGRlrNQRgTE0OtWrWYOHEi+/bto1mzZmU+t8mkkJ198YbHVPc1RdsFNmZd0l50geamx2spJijKBRcnLZlOGaxhNeuVtUQUNaFFQStqmmrd+ULfQdX9/VGSilh31i6SsF69egHmSVlXrlx53eMOHjx4p4okhLAz7dt34PTpFOrWDeaFF1622rdly0YaNGh4W6+XkpLC/PnzmTFjBjk55ukLLl68aPk3Ly8PT09PAHJycqwmlM7Ozgaw7C+tHj16MHHiRPbv31+uJAxk3dmbadM6iA/ecKdrXC6KyToRUy6FY8UTDhT848GouXVxaH+aC9qz7Hfaw36nPQQW1aVZfkvCiqp2x/3q+v64kdsZE7tIwp599lnpEyaEuKGXXnr9uvvatYulffsOt/V6KSkp6PV6RowYUWzfkCFDaN68OR9//DFg7ht29TQTiYmJaLVa6tSpc1vLJG4fjUbN8Pb38tHDy7l3qgHdVf9V2cmwZqwDqRtcyMzMZXznf2nWzJfnp3VDFZPEMccjpDieIsXxFB5GHU3z7yKyoDkuijTdiVtjF0nY6NGjbV0EIUQl5uZ281nRb1VERARff/211baDBw8yefJk3nnnHZo2bUqdOnUICQlh9erVVsuUxcfHExMTc8sjI3/5xbykkkxZcWf07t0A6MOb7dbjUC8Hd3+F3DMqDMd0vDuxM12mhDB37m6mTfuDffvO8UTnc3TuHMyLkwZQFHWKA857yNFks839d3a6bSG8IJJm+S3xNfrZ+qWJSsIukjAhhLA3Op2O6OjoEvc1btyYxo0bA+YvkePHj6du3bpER0cTHx/Pvn37+Pbbby3Hp6Sk0L17d5555hlGjRoFwPjx4wkODiYyMtLSMf/LL7+0rHUr7ozevRvQo0c9/vzzNLm5BtzdHWjdOsDSp2fMmDY89lgTpkzZyZdf7mXDhpP8HnuShx+O5MVXB3MxLJm9Ln9xTpvGvy77+NdlHwFFQTTPb0VYUcMq3VQpys8ukrCIiIibNkc6OTnh5+dHdHQ0w4YNo27duneodEKIyi4lJZnAwKAKOXfv3r3Jz89n7ty5xMXFERoaymeffUaLFi0sxyiKgtFo5OpV4ho0aMDPP//M/Pnz0ev1BAYGMnLkyBKbP0XF0mjUxMbWve6SNDVruvLee50ZNqwFkydv5aefDrN48b8sX36YYcNa8NyYgeTXvMA+l79IcDrEacdkTjsm4270oGn+XTQuaI6LUr1GVYrSsYu1Iz/99FPWrVtHQkICHTp0IDg4GIATJ06wZcsWGjZsSHR0NKdOnWLjxo04OTnx3XffERERcUvX+fHHH/nqq684duwYrq6uNG3alM8++8wyJ8/69euZOnUqx48fJyAggBEjRpRqVFROTg6TJ09m7dq16PV6OnTowBtvvEGtWuUbPXO99d+Onj3N2bwMADRqNW5uTuTlFWK8tLC4n7sP9X39y3XtykZiYq26xuP8+fMkJiZc+jlGYuIxTp48TkFhIR989QVQ+njcyvpv9qaqrR15J9xKPHbvTmXixE1s3ZoMgJeXE2PHRvPkk1EYXPPZ77yb/S57yFebB3JoFA0NCyJpXtASX0PtCn8tt4O8P4qriLUj7SIJW7RoETNnzuTbb78t1pH15MmTDB48mDFjxtCvXz9OnDjBI488QvPmzYmLiyv1NWbNmsXcuXMZOXIkUVFRZGRksH37dl588UXc3NzYtWsXQ4YMoX///vTs2ZMdO3Ywe/Zspk6dyn333XhGv6FDh5KQkMDLL7+Mk5MTU6dORa1Ws3TpUhwcyl7ZWNKN9GJhAZ86TsO11vX/2y6mqRitH4OrU/knfKwMJCbWqkM8cnJySEw8xvHjV5Kt48ePWUYxgrn2PCAgEL/a/qTWSaP1O9cfbVhSPCQJq15uNR6KorBu3XEmTtzMoUPmZZLq1NHxyivt6NevESa1kaNOB9nn8hdntamW5/nrg2ie35KwwoZo0FTY6ykveX8UV2UX8J43bx6PPfZYiSOJgoODeeyxx4iLi6Nfv36EhIQwcOBAvv/++1KfPzExkc8++4yZM2fSqVMny/Z7773X8vusWbNo1qwZEydOBMzrvyUlJTF9+vQbJmG7d+9my5YtzJs3j9jYWMA8e3bPnj1Zs2YNPXv2LHU5S8PZ0ZHCsw4419CjLuHv12SEwnMOONeqPkulSEysVYd49OrVFTB/ELq5uRMSEkpsbCeCg0NxdXXl448/4I033qFTpy6YFBOTzk7BZKy68RB3nkqlolu3MDp3DmHx4n/54INtJCVl8+yzq5k9+2/efLMDd9/dlIjCJqQ6nLY0VZ7RJnNGm4yb0YOmBVE0zo/CVSndxLqi6rGLJCw1NRWN5vrfCDQaDWfOnLE8DgoKoqioqNTnX7ZsGUFBQVYJ2NWKiorYuXMn48ePt9res2dPVq5cSXJyMkFBJfcn2bRpEzqdjvbt21u2hYWF0ahRIzZt2nTbkzC1Sk3UhXac1Gwseb8GIs62Ituj4LZe195FnG1FWpPtJe6rjjGp+vFQUcvPj7EvvEKTZlFWe86cTgEgr7CQzEvzet0sHlEX2qH2q5y1XsK2NBo1gwY1oU+fcD7/3DyS8p9/zjJgwFLuvjuYN9/sQNOmgfjnBNI+rzP7nfdwwGUPeZocdrht5g/XbTQsbESz/Jb4GapeFwFxY3aRhNWvX58FCxbQp08fatasabXv3LlzLFiwgPr161u2JSUlFTvuRvbu3UvDhg2ZOXMm33zzDTk5OTRp0oRXX32V5s2bc+rUKfR6vdU8P4BlzbfExMTrJmGJiYmEhoYWG1gQFhZmWVeuPEpa/+3BpjG8s38bugg96hL+B9O6bOcbSv7AqbKCb7y72sWkisfj3pVd2ffxfl57dSyhfUNoPKoRLrXMczTlqnJRUNjoG8+x4EvL0lwnHiYDZB/SMqZpDOqSpk0XopRcXbU891wbHnusKVOn7mT+/D38/vtJNm48Sf/+jXjllfbUqaOj7cUOtL4Yw1GnQ+xz+Ys07RkOOe/nkPN+ausDaZ7fknqF4XbdVCluH7tIwl5++WWGDx9O9+7d6datm6Vj/smTJ1m7di0Gg4H3338fgMLCQpYtW0bHjh1Lff5z586xf/9+jhw5wltvvYWLiwuzZ8/mySefZM2aNeVa/y07OxsPD49i2z09Pdm/f3+py1iSG63/1i6xM/86rCnX+YWorHT1dMTObMf5v8+z7+P9/HLPaho8Wo+IEbc2WEftAO0KOlPDp/jfsBBlUaOGC+++ezdDh0bxwQdbWbbsMD/8cJAVK44wdGgUY8dG4+XlTERhE6umyqNOB0nVppCqTcHN6E6Tgiia5LeQpsoqzi6SsOjoaBYuXMj06dP57bffKCgwN5M4OTkRExPD6NGjLXPyODk5sWXLlls6v6IoXLx4kWnTpllGVDZv3pwuXbrw7bffWvpy2Zsbrf/WPewutu3fYKkNMxkg+4iWMbqRqKvp6gMmRWFa9mx0DSUmUE3i4Qd8BNu3buGr+XP5beF6OnXpglqlpvOFnsSmXOmCUGI8DmnpHnYXGRnFO7HfyvpvQlwrJMSL2bN7MXJkSyZO3MyWLUnMnPkX3323n7Fjoxk6NApnZwdqGwKonRNA+9zO7HfZw37n3eRpctnptoU/XbfR4FJTZW1DgK1fkqgAdpGEgXkx29mzZ2MymbhwwTzSpEaNGqjV5b8J6nQ6vLy8rKa08PLyIjIykoSEBMvalVePrILSrf+m0+lITU0ttj0rK+uW140ryY1GYDS/0I6TDua+YWoHaH6uHTrf6v2tqfm5dpyMlJhcVl3i0b3zPXTt1I34+J+ZPz8ORVHYv2cvHWI6WM2mXyweF9ph8gMTMvpLVIyoqNosXdqf9etPMHHiZg4ePM8772xi3rzdvPJKe/r3b4RarcJNcSf6YiytLsZwzOkwe112kao9zWHnAxx2PoCfPoDm+S2pXxghTZVViF19zSsqKmLv3r3s3bsXjUZzWxIwwKo/2bUKCwupW7cuWq22WB+uy4+v7St2tbCwMI4fP861M30cP378hs+7HXo3iiZzvxaAzP1aejcqeXbv6kRiYq06xUOtVtO7dx8WLvyRp556lnXr1tCvX29mzfqUCxfOA9UrHsJ+qFQqunYNZf36/zB9+r0EBLiTnJzDqFGr6dr1WzZsOGE5VoOGhoWRPJw5hAEZjxNR0AS1oiFNe5o1up/5ssZMdrpuJk+da7sXJG4bu0nCvv76a2JjYxk0aBCjR4/m8OHDAKSnpxMdHc2SJUvKfO7OnTuTmZnJwYMHLdsyMjI4cOAAjRs3xtHRkejoaH799Ver58XHx1OvXr3rdsoH6NixI1lZWWzffqWT8/Hjx/n3339vqd9aWahValpmdiA7wYGWmR2kYzESk2tVx3g4Ojryn/88weLFy7n//odYsmQhAwb0AcoXj7y8PDp27Eh4eDj//POP1b4ffviBe++9l6ZNm/LAAw+wYcOGUp0zLS2N0aNH06JFC9q0acPrr79Obq58uFZVGo2agQMbs337//HGG7HodE4cOHCORx5ZRv/+S/jnn7NWx/sZ/Ome05v/u/AMbfM64GZ056I6jz/ctvKlz0x+9VhBqkMKCjaf7lOUkV1M1rp06VJef/11evXqRfv27Xnttdf44osviImJAWDMmDHk5OQwf/78Mp3fZDIxYMAAsrKyGDduHE5OTsTFxXHixAlWrlyJr6+vZbLWAQMG0KNHD3bu3MnMmTOZMmUKPXr0sJwrMjKSBx980DJQAMyTtR47dswyWeuUKVMqbLLWa8mEesVJTKxV93ikpaUyb94cXnvtLaDsEy7+97//5aeffuL8+fMsWbLEsr7jL7/8wgsvvMDIkSNp27Yt8fHxLF26lO+++46oqKjrnl+v19O3b18Axo0bR0FBAR9++CERERHMmTOnXK9Z7h23zhbxSE/PZ8qUnXzxxV6KiowA9OsXwauvtqdu3eLdWYwYOeZ0hH0uf3FGm2zZXktfm2b5LWlY2AjNbeplJO+P4ipisla7+Fr8xRdf0LVrVz7++GM6d+5cbH/jxo05evRomc+vVquJi4sjKiqKCRMm8Pzzz+Pu7s53332Hr68vAK1ateLTTz/lr7/+YujQoaxcuZJJkyZZJWAARqMRk8k6+FOnTqVdu3ZMmDCBF154gZCQEOLi4sqVgAkhSvaf/zzMqlUr0ev1pTrez68248e/yi+/rOA//3m4TNc8duwY33//PaNHjy62b/r06fTq1YuxY8fStm1bJk6cSNOmTZkxY8YNz/nrr79y9OhRpk2bRpcuXejZsyfvvfcev//+O/v27StTOUXl4uNjHkm5desT9O1r7rO8dOkh2rX7kgkTNpKRkW91vLmpshH9M//DIxlP0KigKRpFw1ltKmt1v/BFjZnscN1ErjqnpMsJO2QXWcLlpYmux8vLi8zMzHJdw8fHh//+9783PKZr16507dr1hsdcbia9moeHB++//75V7ZgQomL06NGbzz6bwrRpHxMb25FWrdrQsGEEAQGBlnVg8/PzOXMmhUOHDrJr1x9s3boJrVbLoEHXv8/cyKRJkxg4cCChoaFW25OSkjhx4gQvvvii1faePXvy0UcfUVRUhKNjyTPxb9q0ifDwcKu+o+3bt8fLy4uNGzfSrNn1l1kSVUtwsCezZ/fk6adbMnHiJjZvTmL27L9YsGA/zz3XhmHDonBx0Vo9p5ahNt1yelmNqszV5PCn2zb+ct1BvcJwmue3pLYhEBVVZDR0FWQXSZhOpyMjI+O6+xMSEiw1VkKI6u2xxx7noYf6s3LlcuLjV/Lrr/GWyZIvr7xhNJqbdhRFISysHkOHPkWvXg9YjZQsrdWrV3PkyBE+/fRTDhw4YLXv8uCda5OzevXqodfrSUpKskz6fK3ExMRig3dUKhWhoaEVNtHz1S43l8g0HGb2EI+WLf356acBrFt3gnfe2cSBA+d4993NzJ+/h9dea8+AAZHFyueBOzFFsUQXtSNBe5g9TrtI0SZx1PkgR50PUstQm6jCVoQXReJwCx/59hAPe1MRMbGLJKxjx44sXryYRx99tNi+o0eP8sMPP9CvXz8blEwIYY9cXd0YMOBRBgx4lDNnTvPPP/s4deqEZWJlT09P6tYNoUmTpgQEBJb5Ovn5+XzwwQeMGzcOd/fiCVxFTfR8o+eVxo0mer6WTudSrmtVNfYQj4cfbkLfvpF8++0+3nxzg2VNyjlzdvPhh9249956xVZpAahBK6JpxRlOs5Md7GMvZx1SWeOwki1u62lFa1oTjSelnz7JHuJhb25nTOwiCRs7diwDBgygd+/edO7cGZVKxU8//cTSpUtZs2YNvr6+PPPMM7YuphDCDvn7B+DvXzETWc6aNYsaNWpUui+BN5ro+TKNRo1O50J2dj5Go3S8tsd4PPBAA7p3D2Hu3N188slO9u1Lo0eP7+jUqS5vv92J5s39SnyeM5504l7aqDqw33Eve53/IkedzSY2slnZRH19OFGFrQg01LluU6U9xsPWShuTW5no2S6SMD8/P5YtW8Ynn3zCqlWrUBSF5cuX4+bmRq9evRg/fjw+Pj62LqYQohpJSUlh/vz5zJgxwzKR88VLC4JfvHiRvLw8y4TMOTk5Vl0mSjvRc0nTUWRlZeHvX/6FnEs7os1oNMnot6vYWzy0Wg3PPNOKQYMaM3XqH8ybt4eNG0/RufM39O1rHkkZHFzy+0yLMy300TTPa02i41H2uewixTGJo46HOOp4iJqGWjTPb0nDgkgcuNLnzISJNIcUQA8qLX6GQNT2MY7PLtzO94hdJGFgnh3/vffe47333iM9PR2TyYSPj89tm7BVCFF1nD9/jpo1K7afaEpKCnq9nhEjRhTbN2TIEJo3b87HH38MFO/flZiYiFarpU6dOtc9f1hYGEeOHLHapigKx48fp3379rfpVYiqwtvbhXfe6cTQoVFMnryVpUsPsWzZIVauPMr//V9zxo2Lxsen5GYyNWrqF4VTvyic85qz7HX5iyPOBzjvcJZ1HqvY6vY7jQua0zS/BWkOqWx2X0uu5tIISw9wd/WgQ2436heF38FXXD3YZYbj4+NDzZo1JQETQpRo0KC+zJkzg7y8ipvYNCIigq+//trq59VXXwXgnXfe4a233qJOnTqEhISwevVqq+fGx8cTExNz3ZGRYO4Le+jQIU6cOGHZtn37djIzM+nUqdN1nyeqt7p1PZk1qydr1z5Gx451KSoyMmfO37RpM5/p0/8gP//GU7fUNNaia24P/u/Cs7TP7YyHUUeBOp+/XHfwpc8sVul+LDbFRa46h1W6H0lwLD47gCgfyXKEEJVOs2Yt+PbbL3nkkQdZtOi7Us8Zdit0Oh3R0dFWP40aNQLMcxc2btwYgNGjR7Ny5UqmT5/Ozp07eeutt9i3b59VP9aUlBQiIyP57LPPLNvuvfdeGjRowOjRo9mwYQPx8fG89tpr3H333TI9hbipZs38WLKkP4sW9aVxY1+yswuZNGkLMTFfsHDhgZv243JWXLgrP5oh6SPpmdWXwKK6oOLKz9UuPd7svlbWWb3NbNIcGRERUeLIjpu5etkhIUT19fHH09m7dzezZ3/GZ59N5YcfFjJs2Ejuu6/XHS9L7969yc/PZ+7cucTFxREaGspnn31GixYtLMcoioLRaLRaY1ar1fL5558zadIknn/+eRwcHOjevTuvvfbaHX8NovLq3DmETp2CWbLkIJMnbyUlJYfnnvuVWbP+YsKEDnTpEnLDz1s1auoVNcRJceJHx1PXv5AKcjU5xNWYgpvJAxfFBWeTKy4mV1wUF1xMrjibXHBRLm0zmbc5oJV5ym7AJssWffrpp8XeFL/99hsJCQnExsZa5txJTExk69atNGjQgG7dujFq1Kg7XVSbkqVHykZiYq2qx2Pbti3MnTuThISj1K/fgKeeGkXbtu2ue3xFLD1ib+TeceuqQjwKCgzMm7eHqVN3kpVVCEBsbB0mTOhAVFTtGz73iNO//KpbcdvLpFEcriRlyqVEzeR6KVm7lMhdSuJcTK44Kc52OQjAhIk05xTw0EOOFr+C6w9WuJV7h01qwq5d+mPRokVcuHCBn3/+udjkhceOHePxxx+nVq1ad7KIQohKol27WNq1i2Xt2l/5/PM5vPTSWKKi7uKZZ54jIiLS1sUT4o5xdnbg2Wdb8eijjZk27Q8+/3wPW7Ykcc893/PQQ+G8+mp7QkK8Snyuq6l088p1y+6JzuRFvuoi+ep8CtQXLb/nX/q94NLvRpURo8pAriabXE126V6EYm4qvZy4OV9ds3bp9ys1bldq2ypSguPhChusYBcLeN9zzz307duXkSNHlrh/1qxZ/Pjjj6xZs+YOl8y25Nts2UhMrFWneBiNRn75ZQVffTWPc+fO0qlTF0aMeIY6depajpGaMLPq9L4ojaoYj6SkbD74YCtLlhxEUUCrVfPkk1GMHRtNjRrWIylNmPjKZ5a5U35JrYcKuJs8eDz96VLVVCko6NGTr76SlJmTtUvJ26XfC9T5lu2F6sIyvU6torXUsDlflZyZH1/5/XKNm5PiXOom0gTHw6zS/Wh+cPVTLmVOPbIfKpaI2X1N2LVSU1NvuNi1g4MDqampZT7/smXLLKOarjZ8+HDGjx9PcnLyddeMdHR05J9//rnuuXfu3MmQIUOKbe/ZsydTpkwpc5mFELdOo9HwwAMP0aNHb5YtW8y3337FkCGP0KtXH8aPf8XWxRPijqpTR8eMGT0YObIl7767md9/P8mcOX/z/ffmNSmHD2+Bq6u5FkmNmg653cwJh0KJCUeH3G6lbipUocIRRxxNjniavEr1HCNGClT5V5I29UXyVfmXkrUrv+erL1Jw6XeTyoRepUev0ZNTyto2laKyqm0zN5MWr21zMjmz0X3N5Rd07QsExTxYISy9QZmbUO0iCWvQoAHff/89999/P35+1jMAp6amsmDBAho2bFju63z++edWy4RcvlatWrVYtGiR1bGKojBs2DDatm1bqnNPnjzZqinV29u73OUVQty6zMxMTp48jouLK7GxHYmP/5kVK5ZJEiaqraZNa7F4cT9+//0kEyduYv/+c7z33hbmz9/Dyy+345FHzGtS1i8Kp0f2Q9ZNb5hrwO7EPGEaNLgp7rgZ3cF48+MVFIpUhZaELP+qWjXr2rd8S+JWpC5EUSmW48rl0mCF09okgvTBZTqFXSRhr776KsOGDePee++lW7duBAebX8yJEydYt24diqLw0Ucflfs6jRs3LnHmfUdHR6Kioqy27dy5k9zcXHr37l2qczdo0ICmTZuWu4xCiJtTFIXTp1M4deoEJ06cuPTvcZKSTlpmq1cUBa1WS0hIKCEhoTc5oxBV3913B9Ox439YuvQgH3ywjaSkbMaOXcOcOX/xxhsd6NYtlPpF4QSfq8eGxD3kkIcHbnQOi0KrsYt0wYoKFU6KM06KM56m0lV8GDFYkrVrE7UCq5q3fHLU2RSVoon0ovrGTf83YhdRbdWqFYsXL2batGmsXbuWgoICAJydnYmNjWX06NGEh9/ZmXpXrlyJu7s7Xbp0uaPXFULcXNeusRgM5rnBFEXBycmJunVDiI6OITg4lJCQMEJCQgkKqiOTPgtxFbVaxcMPR3L//Q2ZP988kvLgwQs89thPtG8fRJcuocybt5vTp69MhBwQ8DeTJnWmd+8GNiz57aHBAXeTB+543LS2LVl7kh+9Ftz0nKUd1FASu0jCABo2bMiMGTMwmUykp6cD3PZli3r37k1GRgYBAQEMGDCAYcOGodFoih2n1+tZs2YN3bt3x8nJqVTnHjFiBJmZmfj6+tKrVy/GjBmDs7PzbSu7EOKKbt3uuVTDZU62/P0DyjT3oBDVlbOzA88804pHH21yaSTlbrZuTWbr1uRix545k8vQoT8zb979VSIRK60AfR3cjR43HawQoL/+8mQ3YzdJ2GVqtZqaNWve1nP6+voyevRomjdvjkqlYv369UydOpW0tDQmTJhQ7PhNmzaRmZlZqqZIDw8Phg0bRuvWrXFycmLHjh3Mnz+fxMRE5syZU+6yOzjcOAm9PAKjso7iqggSE2tVMR4TJrxT5udWxXgIUVZeXs689VZHnniiGR07fk1+vqHYMZfnUHjppbUEB+vw9nbBw8MRd3fHKv13dLsHK5TEJklYz549GTFiBD179rzh2mpXKyoq4ueff2bevHnEx8ff0vU6dOhAhw4dLI9jY2NxcnLiq6++YuTIkcXmIPv555+pWbMmMTExNz13ZGQkkZFX5iKKiYmhVq1aTJw4kX379pVr+RG1WoW3d+mqOXW6khdurc4kJtYkHtZKE4+NGzcyd+5cEhISyM3Nxc/PzzJx9OVBPoqi8Pnnn7NgwQLOnj1LSEgIzzzzDD179rzp+UvqZlGzZk22bt166y9IiHJITs4pMQG72vnz+XTt+p3VNjc3LR4ejuh0Tnh4OOLh4WR57O7uaLXv8rZrH7u5ae22Jrt+UTi1NrQlMWIn7gFXZvTKPa0i7HA09ZuWr6uUTZKwhx56iMmTJ/Pee+/RpUsXYmJiaNy4MUFBQbi4mG+MFy9eJDk5mf3797Nt2zY2bNiAVqtl6NCht6UMPXr0YP78+Rw8eNAqCcvLy2PDhg08/PDDJTZVlvbcEydOZP/+/eVKwkwmhezsG4/e0GjU6HQuZGfn33StsOpCYmJN4mGttPHQ6VzIzMykWbNmDB48GC8vL44ePcqnn37K0aNHmT9/PmAedT116lSefvppoqKiWL9+Pc8//zzOzs6l6lM6ePBgq1p3rbZiJ54UoiRpaaXrXO7hoaWoyERhoblDVV6enrw8PampZe+crlarLiVw1knc5dq2GyVxVx/j5KS57cncypVHeW7o36ByoG4HBXd/hdwzKpK2qFBMf+M2L7BcTbQ2ScKGDx/OoEGDWLJkCT/++CPLly+3BO5y4mM0mv+DFUWxLHLbv39/3N3dK7Rsv/32GwUFBdx///0Vep3SKu2kgUajqcpMMHi7SEysSTyslSYeffr0sXocHR2No6Mjb775JmlpaXh7ezNr1iwGDx5sWVYtNjaW06dPM3Xq1FIlYf7+/sVGZwtxp/n5la7V5euvH6R9+zoUFhrIySkiO7uQ3Nwiy+85OUXk5BSW+Pjq4y/vMxoVTCaFrKzCS0st5dy0DNej1aqLJWolJXY3SvQ8PBzRai/nISbeeGODuTlWUXFyo3WCp1LBG2/8To8e9crcLGuzPmHu7u488cQTPPHEEyQnJ7N7924SExPJzMwEwMvLi7CwMKKioqhTp+yd3q4nPj4ejUZj1ZQI5lGRdevWpXnz5mU+9y+//AIgU1YIUQV5eXkB5gE8SUlJ5OXl0b59e6tjYmNjeffddzl9+jQBAQE2KKUQt6Zt20ACAtw5cyaXktbRUanA39+Dtm0DAXBycsDJyYGaNV3LfE1FUbh40UBubiHZ2eZk7fK/5kTtyrZrjzEnfld+B9DrTVy4kM+FC/llLhOAi4sDHh5OODiorEaJFi8/nD6dw44dKbRvX7Y8xS465gcFBREUFFRh5x86dCjR0dGW/hfr1q1j8eLFDBkyBF9fX8tx6enpbN++neHDh5d4npSUFLp3784zzzxj+dY7fvx4goODiYyMtHTM//LLL+nWrZskYUJUEUajEYPBQEJCAjNmzKBLly4EBQXx77//AhTr23r58bFjx26ahMXFxfHJJ5/g4uJCbGwsL7300m1J3GRQz62p7vFwcFAzeXIXnnhiBSoVVonY5Ra+yZM74+R0e9MGT08Nnp5OBAaW/Rwmk2KpXbtcw3alFu7y71eSuMu1c9cec7lPXH6+4ab94652/vzFm/69XY9dJGEVLTQ0lKVLl5KamorJZCIkJITXXnuNwYMHWx23atUqDAbDdZsiFUXBaDRy9XKbDRo04Oeff2b+/Pno9XoCAwMZOXIkI0aMqNDXJIS4czp37kxaWhpgHujz8ccfA1C3bl1UKhX79u0jOjracvyePXsAyMrKuuF5H3zwQe6++25q1qzJkSNHmDVrFo8++ijLly/H09OzzOWVQT1lV53jMWRIC9zdnRkzZjXJyVeWAAoK0jF16n307dvIhqW7sRo1yn8Ovd5oSeSysgrZuPEEY8f+etPn1a9fs9R/b9eyiwW8RckUxdxWfjMajVo6XF9DYmJN4mGtNPFQq1WWvqqHDh0iPz+fhIQEZs2aRVBQEF988QUajYaXXnqJjRs38tFHHxEVFcWGDRt46623KCgo4JNPPqFXr16lLtehQ4fo27cv48aNu26NfGmU5t6hUpmnBDKZTCU2P1U3Eg9rhYUGTCZQq7nttV+VSXJyNkbj9d8QGo2KoCCd1bar7x03U30jWwmoVCo0mtL9R1bXKvQbkZhYk3hYu5V4REREANCiRQuaNm1Knz59+O2337jvvvt49dVXOX/+vKX229vbmzFjxvDhhx9adXco7XVCQ0M5cODALT3vWrdy75AVBaxJPMxcXUs3fVRVV7Om6w1Hjtas6Vque6skYUIIcQvCw8PRarWcOnUKMCdd8+fPJy0tjaysLEJCQli3bh1arbbYwB8hROXi5uZIWFjFJaR2kfJv3LjR1kUQQohS2bt3L3q9vthgIj8/Pxo2bIhGo2HBggX07NnzlqfUOXjwIMePH5dBPUJUE3bRJywiIoI2bdowfvz4ck1uKoQQt9OoUaNo0qQJ4eHhODs7c+jQIebNm4ePjw9LlizB0dGRFStWUFhYSN26dTl79iyLFi0iOTmZxYsXW00E3b17dwICAvjqq68AmDdvHqdOnSI6OhofHx+OHj3K7NmzcXJy4qeffkKn012vWEKIKsIumiPnzJnDJ598wiOPPEL37t0ZN24coaGhti6WEKKaa9asGfHx8cTFxaEoCoGBgTz88MMMHTrUMg2FoijMnz+f5ORkXF1d6dSpE//73/+KLYdmNBoxma4MBggNDWXNmjWsWrWKvLw8vL296dSpE2PHjpUETIhqwi5qwi5bvnw5n376KampqfTt25dnn30WPz8/WxdLCCGEEOK2s6skDMyzUH///ffMmTOHixcvMnjwYEaMGGFZLFcIIYQQoiqwuyTssry8PObNm8cXX3yBo6MjI0aMYMCAAZKMCSGEEKJKsKskzGg0kpyczIkTJzhx4gQnT57k77//5tChQ5aJz2rXrk3Dhg1p2LAhL7zwgo1LLIQQQghRNnaRhK1atYoZM2Zw4sQJy7JAarUaPz8/6tatS3BwMHXq1EGr1XL06FGOHDnCsWPH+Pvvv21ddCGEEEKIMrGLJKxt27Z4enoycOBAQkJCqFu3LnXq1Cm2KK4QQgghRFVhF1NUdOvWjfvuu4/Y2FhbF6XMjh07xqRJk9i9ezdubm706dOHsWPHSiIphBBCiBLZRU1YZZeVlUWvXr0ICQnhqaeeIi0tjQ8++IAHHniACRMm2Lp4QgghhLBDdlETVtktXLiQvLw8PvvsM7y8vADzIIN33nmHp556qsxznSmKgsl08xxZrVaV6rjqRGJirbrHI7coH6NzofnB1etaXwqJpsAJd0cXq+eo1SrLgCAhhKgIkoTdBps2bSImJsaSgAH06NGDt956i61bt9K3b98ynddkUkhPv/7q7QAODmq8vd3Izr6IwWC64bHVhcTEWnWPh95o4H+mj3GrraC6drVcFSgmyEtXM17zPFrNlVuij48bGo0kYUKIiiNJ2G2QmJhIv379rLbpdDp8fX1JTEws17kdHG68xrpGo7b6V0hMrmY0mti2LZns7CJ0OkeiowMqdVyMRhPZ2YWXforIyiogO7uIzIt5ZOlzyVVyyVddpECdT5G2AJNzIerAXALvvn4toEoN7oEmNmzbQ89Gbe7gqxFCVHeShN0G2dnZJa715unpSVZWVpnPq1ar8PZ2K9WxOp3LzQ+qZqp7TJYtO8iYMatJTs62bAsK0jFt2n307dvojpdHURRyc4vIyiokK6uAzMyCkn/PyidHf5E88ijU5KN3LDA3JbrqcdAZcPUFV18F15rgGqzg5gtaV/M1HACPSz+3Koe8Uv+9CSHE7VAlkrD09HQyMjJQqVR4e3vj7e1t6yLdFiaTQnb2xRseo9Go0elcyM7Ox2isfk1NJZGYwM8/H+GJJ1aASiG4k4K7v0LuGRVJW7Lo338xX375APff3/CWzllQYCA7u5CsrEJLbdS1v+fkXLu9iOy8fPTaQoxOhbjUUMwJlC+41jT/6+YLrhGXkipfhRo1wbcMdyaTXoUpxwHyHNEUOOKgd8bZ6EJO0UXULVNv+nwP3MjIuNL8r9O5VOpaQyGE/auUSdjFixdZvXo169atY/fu3WRkZFjt9/b2JioqyjL1haura4WWR6fTkZOTU2x7VlYWnp6e5Tp3afvwGI2matnf50aqa0yMRhOvvrqe8AdN3DPNgGedK/uykmDNGAeef/43jEZzzdTVzXvZ2QWX/i28ZnshRUVGALSuVxImcxKl4FLT/K9rhHm7ny+EXkqyXMr4nUhV6ICm0AlHvTPOJhdcFTfcNW54OnjgoXLDWXHFxXTpR3FBqziiQgXOmH8u0RsN/O/0dfqEcalP2Bk1ncOiquX7RQhhO5UqCcvIyCAuLo6FCxdSVFREeHg4Xbt2pU6dOuh0OhRFITs7m+TkZA4cOMCbb77Ju+++y8CBAxk+fDg+Pj4VUq6wsLBifb9ycnI4d+4cYWFhFXJNIa5nx44UdNHZ9F9iKLZPFwj9lxhY0j+PJ5/8GVQKzl5Ykio3X3CtreDaBHx9FYKvbvrztW76uyWKCiejMy4mF1xxw8WSQLlYfne2euyC5trbkwowAUW3dmmtxoGwf6NJq70DxYRVIqZcyrnCDrdB27RS3Q6FEFVApbrrdOnSheDgYF566SXuvffemyZV6enp/PrrryxevJhFixZV2DJHHTt2ZPbs2VZ9w1avXo1araZ9+/YVck0hrif1bC73TDMnYNfW/KjUoCjQd6GBoiwVzj4KKs2tX0OjaCy1UM6Ky1U1UuYEytnyu/mxk+KMGts17T3S9G4W/Q6JETtxD7jSST/vjJqww214pOndNiubEKL6qlSTtW7evJkOHTrc8efezOXJWkNDQ60ma73//vvLNVmr0Wgq9RQVGRl50pRySXWOybFjGbzz9U+0npl2S89zNDnhclUy5XxVDVXxROuqpr9KRm80sCFxDznk4YEbncOirKaluJp5igrpEyaEqDiVKgmzZ8eOHePdd9+1WrZo3Lhx5Vq2SJKwsqmOMblwIZ9PPtnB8m276T5VT1i3m/9Zt83uSCN9U1xMrmgoQ3VYJVXa94ckYUKIilapmiPtWb169fjyyy9tXQxRzRQUGPh83m6W/LWNpk8V8FRc6b9T+ZsCcTeVZTIHIYQQt0OlT8IKCwv59ddf+ffff8nJycFksv5mq1KpeP/9921UOiEqhqIo/LjiIAsPrKfB43n0e/tS8qVAaFF9UrWnyVddpMQWQwXcTR4E6OuUsFMIIcSdUqmTsJSUFIYMGUJKSoplmghPT09ycnIwGo14e3tX+PQUQtxpW/5OZGHCrwQ8lEWHYZc26jU0LWpOVEFrvEzeJDgeZpXuR/PaiCWsldght5tNO8oLIYSo5EnYRx99RG5uLosXLyYoKIh27doxZcoUWrZsyddff813333HvHnzbF1MIW6LfaePsyRlDV53ZxB+r3mbkuVIa1M0LYx34axcWSGgflE4PbIfYrP7WnI1V+awczd50CG3G/WLwu908YUQQlyjUidhO3bsYNCgQTRr1ozMzEzLdkdHR4YNG8axY8d4//33iYuLs10hhSgHBYVD+Qn8krEep+YZ+DY3by884UJHTQdaOje/bqf6+kXhhKU3IM05BTz0kKPFryBQasCEEMJOVOokrKCggMDAQADc3d1RqVRWM9e3aNGCDz/80FbFE6LMjBg5qDnAhsLNUDcHp7rmiUUzdrjR3e1uYgKalGqKCDVq6hiC8caNDEMeBqrHaFEhhKgMKnUS5u/vT1qaeT4kBwcH/Pz82LNnD/fccw8ACQkJODk52bKIQtySAlU++5338IdqJ0a3AgD0F+HUcld6eHXm3lZNbVxCIYQQt0ulTsLatm3LunXrGDVqFAAPPfQQcXFxZGdnYzKZWLFiBX369LFxKYW4uUxNOntcdnFAuw+Tg3m2+5zTcPALZ+6t2ZExfaJkziohhKhiKnUSNmLECP755x+KiopwdHRk5MiRnD17ll9//RW1Wk3v3r159dVXbV1MIUqkoHBam8Rulz857njUMooxdY+Kvz/T0sU3mtlPtcHNTWvbggohhKgQlXbGfKPRSHp6Ojqdrso2OcqM+WVj7zExYiTB6RB7XP7krDbVsv3Izyp2TtHQPqApr7zSHj8/99tyPXuPx50mM+YLIexFpasJUxSFKVOm8O2335Kfn49Go6FTp0689957eHl52bp4QlxXgaqAA8572OvyF3mXpo0w5MOeL9X8MU1DU/8QvnirI40b+9q4pEIIIe6ESpeELVu2jLi4OGrXrk2HDh1ISkpi3bp1mEwmZs2aZeviCVFMljqDPS67OOiyD71KD8DFs2p2TlPx1xw1IbVqMuOdTnTpEmLbggohhLijKl0StmDBAiIjI/n+++9xdnYGYNKkSXz//fekp6fj4+Nj4xIKYe7vdcYhmd2uf5LoeMTS3yv7qJYNk0wcWKimhpc7773ejkGDGkuzlxBCVEOVLglLSkrimWeesSRgAI8++ijffvstJ0+elCRM2JQRI8ecDrPb5U/Oas9Ytmfv8mD5y/mcWA8uLk6MHd2KZ59thbu7ow1LK4QQwpYqXRKWlZVVLNHy9vYGzIt5C2ELhaoCDjjvZa/LX+RqsgHQmDTkbavBt89mcWZfISqVmkGDGvPKK+3w9/ewcYmFEELYWqVLwgBUqpvPFC7EnZClzmSvyy7+dd6HXl0EgIvRFf0Wf2YPS+NMQiYAHTvW5e23O9GkiXS6F0IIYVbppqiIiIjA398fd/crw/dNJhPHjh0jKCgIFxcXq+NVKhUrVqy408W8LWSKirKp6JgoKKQ6pFj6eykq85+Qj6Emmh3BTBt2imOHswAID6/B2293pEuXEJt9eZD3iDWZokIIYS8qXU1Y69atS9wufcFERTNhsvT3StOetmyvWxSGx756TB19lB07/gHA19eVl19ux6OPNsHBQT7IhRBCFFfpkrBvvvnG1kUQ1UyhqoB/nfex12UXOZf7eykawgua4JcYwWcT/mXZso0AuLg48PTTLRk1qrV0uhdCCHFDlS4JE+JOyVJnss9lFweu7u9lcqVp/l0En40k7pP9zJ27gsJCIyoVPPKIudN9QIB0uhdCCHFzVSIJMxqNHDp0qNh2nU5HnTp1bFAiUZmZ+3v9wbFr+ntF5bcmLCeC77/+l8f/u5D09AIAOnSow9tvd6Jp01q2LLYQQohKptIlYRcuXGDQoEE88MADjBo1CoDs7Gz69etXrOOzu7s7q1evpkaNGrYoqqhETJhIdDzCbtc/SdWmWLbXLQol6mJr6hSF8OvqRIZN/J5jxzIAaNjQh7fe6ki3bqEyYlcIIcQtq3RJ2MKFC8nIyOCJJ54otu/JJ5+kfv36gHnE5HvvvcfChQt59tln73ApRWVRpCq09PfK1phHNKoVDREFjWme34qaxlrs2ZPKc2/9wPbt5uSsZk0XXnqpHf/5T1PpdC+EEKLMKl0StnHjRu655x6rKSrAPBVFbGwsMTExlm179+7l999/lyRMFJOtzmKfy18ccN5Lkdo8ya+zyYWm+S1omn8Xboo7SUnZPP1+PEuXmpu6nZ01jBzZktGjW+Ph4WTL4gshhKgCKl0SlpiYyIMPPlhse0nTnTVo0IBVq1ZVaHmMRiPz58/n999/JyEhAUVRCA8PZ8yYMbRq1apCry2KM2EiySGJJPTgoMXPEIiaK7VVqQ6n2ePyJwlOhyz9vbwNNYjKb01EQWMc0JKdXcik6ZuZM+dvCguNADz8cCNeey2WwEDpdC+EEOL2qHRJWEFBAU5O1rUQ3t7e/Pnnn7i6ulptd3FxoaCgoMLLExcXx0MPPcTw4cNRq9UsXryYIUOGMG/ePKuaOVGxEhwPs9l9LbmaHPMGD3B39SA2tysqVOxx/ZMz2mTL8XWKQojKb01wURgqVOj1RuZ/s4f//nc7Fy7kA9C+fRDvvNOJZs38bPGShBBCVGGVLgnz8fEhKSmp2HYPj+I1FMnJyZZ1JSuKs7Mza9euxdPT07Ktffv29O7dm6+++kqSsDskwfEwq3Q/Ftueq85hte4nuNRvXq2oCS9sTPOLrfA1mhMrRVFY/esxJk7cREKCudN9/frevPVWR+65J0w63QshhKgQlS4Ja9GiBfHx8YwaNQoHh+sX32AwEB8fz1133VWh5dFoNFYJ2OVt4eHhnDp1qkKvLcxMmNjsvtb84Np86fJjBVpdjKFZQUvcTFf6E+7dm8bbb29k61ZzDVmNGi68+GIMgwc3RavVVHzhhRBCVFuVLgkbPHgw//nPf3j55ZeZNGlSsbUiwdxE+Prrr5OUlMT7779/x8toMBjYu3cvLVu2LPe5bjb67vLadtV1jTsFhQTt4StNkNejghBTGJ5qHaghOTmb997bwqJF/wLg5KTh6adbMnZsNDpd1ep0X93fI9eSeAgh7EWlS8JatWrF008/zaxZs9i+fTvdunWjQYMGuLq6cvHiRY4ePcratWtJT0/nqaeesknn+M8//5y0tLQSp9G4FWq1Cm9vt1Idq9MVT0arIgMGznCaU5wi6dJPDjdJwC7z0KPJduDDD7fwySc7KCgwAPDYY015770uBAd7VVzB7UB1eY+UlsRDCGFrKqWkYYWVQHx8PNOmTePkyZPF9gUHBzN69Gh69+5dpnPn5ORw9uzZmx5Xp04dHB2t1wfcunUrI0aM4Omnn7ZMJltWRqOJ7Oz8Gx6j0ajR6VzIzs7HaDSV63r26KIqjzMOKZx2SOa0Jpk0hzMYVUarY1SKyjLS8UbcFkfz8ajDnDt3EYB27YJ49927adGidoWU3V5U9ffIrSptPHQ6F6ktE0JUqEqbhF124sQJEhMTyc3Nxc3NjbCwMEJDQ8t1zh9++IE33njjpsfFx8dTr149y+MDBw4wePBgunfvzocffliuMoA5CUtPz7vhMQ4Oary93cjIyMNgqNwfsAoK6ZrznNGmkKpN4YxDMpkOGcWOcza54K8PxF8fhL8+kJqGWnzn8zm56pzifcIARYGLZ9RMqaNBMamoV8+bCRM6cN999apFp/uq9B65HUobDx8fN0nChBAVqtInYfbi5MmTDBo0iEaNGjF79my0Wm25z1nVk7AiikjTnr6UcJkTr8JLE6dezcdQ81LSFUhtQxBeRm9U12Rbi/75nbS7dwCguupzU7kUkiX9HTi70ZUXX4xhyJBm1arTfWV+j1QEScKEEPaiUvUJ2717Ny1atLjjz72Zs2fP8uSTT+Lv78/06dNvSwJW1Sgo5KqzOaNN4Yw2mTMOKZx3OFusGdFB0VJb709tfRD+hkBq6wNxVpxveG6j0cTkwUfQRTtwzzQDnlet2Z6dDGvGOpD8mxO7dj2Bj4/r9U8khBBC3EGVKgl7/PHHad68OYMGDaJz584ljoy8Wl5eHuvXr2fhwoXs37+fvXv33vYyFRQUMHz4cDIyMnj99dc5evSoZZ+joyORkZG3/ZqVgREj5x3OWhKuM9oU8koYwehu1FlqufwNQdQ01LKa4b401q8/wenTuZz+Uc3h5VrqdlBw91fIPaPi1GYVikkF6Dl48ALt20sSJoQQwj5UqiTs119/ZcaMGbz00ktotVqaNWtGZGQkQUFBeHp6oigK2dnZJCcns3//fvbt24fRaKRPnz7873//q5AynT9/nkOHzGsLPv3001b7AgMDWb9+fYVc197kq/LNzYraFFIdkknTnsGgMlgdo1JU+Br8LAlXbX0gHibdLV8rJSWHnTtT+OOPFP744zQHDpyz7FNMKk5uLLmfV1rajZt2hRBCiDupUvYJS09PZ8WKFaxbt45//vmn2NJEzs7ONGnShK5du9KnTx98fHxsVNLysdc+YQoKGZp0Uq+q5cpwuFDsOCeT86V+XIEE6IOopa+NFscSznh9RqOJf/89b0m4/vjjNCkppZyS4ho//vgw7dvXufmBVYz0CbMmfcKEEPaiUiZhVzMYDJw5c4aMDPMoOm9vb/z9/W84m35lYS9JmB49Z7VnLiVcyaRqUyhQF1+T08vgQ4A+iNoGc/Oit7FGsQ70N5ObW8Tff6fyxx8p7Nx5mr/+OkNubpHVMRqNiqZNa9GmTQBt2gTSsmVtevVayJkzuZT0blapwN/fg7/+GlotP1QlCbMmSZgQwl5U+kzFwcGBOnXqUKdO9avhqCi56hyrvlznHdIwqaw/rDSKA356f/wN5mkiausDcFFuvb/VmTM5lhqunTtTOHDgHEajdSbl7u5Iq1b+REcH0qZNAC1a1Mbd3bpGbdKkzgwd+jMqFVaJ2OUZKCZNuls+UIUQQtiVSp+EifIxYTJ3oL+qlitHk13sODeju3leLoN5fq6ahlpouLVpHoxGE4cOXbiUdJmbF5OSil8rKMjDUsvVpk0gjRrVuGkC1bt3A+bNu5833tjA6dO5lu3+/h5MmnQ3vXs3uKWyCiGEEBWt0jdHVmU3a440YSLNOQU89JCjxa8g8KYjCwtVBZc6z5trudK0p9Gr9FbHqBQVNQ21LAnX5Q70t9q0mJenZ/fuM5aarl27zpCdbT0PmFqtonFjX9q0CbDUdAUEeNzSda5mNJr488/T5OYacHd3oHXrgGpfAybNkdakOVIIYS+kJqySSnA8zGb3tVcWrvYAd1cPOuR2o35ROGDuQJ+lybDUcp3RppDucL7YuRxNTpZ+XP76QPz0ATjeYgd6gLS0XEvC9ccfKfzzz7liH3JublpatvS3JF0tW/oXa1osD41GTWxsXUk6hBBC2D1JwiqhBMfDrNL9WGx7rjqHVbofCS9oTJG6iFRtCvnqi8WO8zR4W2q5/PWB+Bhr3nItl8mkcOTIBUtfrj/+OM3Jk1nFjvP3d7fUcLVpE0BkpC8ODlK7IIQQQkgSVsmYMLHZfa35wbV506XHh10OWDZpFA21DP5Xlv3RB+KquN3ydfPz9ezZk2ap5frzz9NkZlo3LapUEBnpa0m42rQJJCjIo1qszyiEEELcqkqZhBUWFrJu3TqSk5Px8vLi7rvvplatWrYu1h1xWpt0pQnyBprkRxFR0JRaBj80ZfhvPnfuotXcXPv2paHXWzftubo60LKlP61bmxOuVq380emcbvlaQgghRHVU6ZKwCxcuMHDgQJKTk7k8psDFxYUZM2bQrl07G5eu4l1Ul27W90B9XfwNgaU6VlEUEhIyLM2Kf/yRQmJiZrHj/PzcrDrQN27sW60WwhZCCCFup0qXhM2cOZOUlBSeeOIJ2rZty8mTJ5k5cyYTJkxg7dq1ti5ehXM1la4p8UbHFRQY2Ls3jZ07zc2Kf/55mvR068lXVSqIiKhB69aBREeba7rq1tVJ06IQQghxm1S6JGzLli306dOHl19+2bKtZs2avPDCCyQmJhIWFmbD0lW8AH0d3I0e5KpzivcJA1DA3eRBgP7K5LUXLuTz559XOtDv3ZtGUZHR6mkuLg60aFHbUtPVqpU/np7OFfxqhBBCiOqr0iVhZ86coWXLllbbWrZsiaIoXLhwoconYWrUuG5sTM7dO0AB1VUDDZVLXbaKltdjUfK/lqQrISGj2Hl8fV0tneejowNo0qQWjo7StCiEEELcKZUuCSsqKsLJybrzt6OjeZ4pg8FgiyLdUUajicmDj6CLduCeaQY8r1qtKTsZ1ox14NCP/wL/Wj0vPLwGbdoEXOpEH0BoqJc0LQohhBA2VOmSMICUlBQOHLgyDUNOjnm04MmTJ9HpdMWOb9y48R0rW0XbsSOF06dzOf2jmsPLtdTtoODur5B7RsWpzSoUkzmxatSoJt27h1pGLfr4uNi45EIIIYS4WqVbtigiIqLEGhxFUYptv7zt4MGDd6p4t1VJyxYtW3aIkSPjb/rc2bN70rdvREUVza7JMj3WJB7WZNkiIYS9qHQ1YZMnT7Z1EWzKz690oyNLe5wQQgghbKPS1YRVJ4qiYDIp12yDlJRsjMbr/7dpNCoCA3VU5y5fGo0ao1FqfS6TeFgrTTzUapX0mxRCVChJwiqhvLwi0tKuP2mrn58bbm63b1FsIYQQQtx+koQJIYQQQtiA9DoVQgghhLABScKEEEIIIWxAkjAhhBBCCBuQJEwIIYQQwgYkCRNCCCGEsAFJwoQQQgghbECSMCGEEEIIG5AkTAghhBDCBiQJE0IIIYSwAUnChBBCCCFsQJIwIYQQQggbkCRMCCGEEMIGHGxdAFE2x44dY9KkSezevRs3Nzf69OnD2LFjcXR0tHXRbOLkyZPMmzePvXv3cvToUcLCwli5cqWti2Uzq1atYsWKFRw4cIDs7GyCg4MZPHgw/fr1Q6VS2bp4NrFx40bmzp1LQkICubm5+Pn50a1bN0aNGoWHh4etiyeEqIYkCauEsrKyePzxxwkJCeHTTz8lLS2NDz74gIKCAiZMmGDr4tnE0aNH2bhxI82bN8dkMqEoiq2LZFNffvklgYGBvPLKK3h7e7Nt2zbefPNNUlNTGTVqlK2LZxOZmZk0a9aMwYMH4+XlxdGjR/n00085evQo8+fPt3XxhBDVkEqp7p9WldCcOXOYPXs2GzZswMvLC4BFixbxzjvvsGHDBvz8/GxbQBswmUyo1ebW9VdeeYX9+/dX65qw9PR0fHx8rLa9+eabxMfH8+eff1piVd0tXryYN998k02bNlXLvxshhG3JnbgS2rRpEzExMZYEDKBHjx6YTCa2bt1qu4LZkCQV1q5NwAAaNWpEbm4uFy9etEGJ7NPlvyG9Xm/bggghqiX55KqEEhMTCQsLs9qm0+nw9fUlMTHRRqUS9u6vv/7Cz88Pd3d3WxfFpoxGI4WFhRw4cIAZM2bQpUsXgoKCbF0sIUQ1JH3CKqHs7Gx0Ol2x7Z6enmRlZdmgRMLe7dq1i/j4eF5++WVbF8XmOnfuTFpaGgAdOnTg448/tnGJhBDVldSECVHFpaamMm7cOKKjoxkyZIiti2NzcXFxLFy4kEmTJpGYmMjIkSMxGo22LpYQohqSmrBKSKfTkZOTU2x7VlYWnp6eNiiRsFfZ2dkMHz4cLy8vPv30U+k7B0RERADQokULmjZtSp8+ffjtt9+47777bFwyIUR1I0lYJRQWFlas71dOTg7nzp0r1ldMVF8FBQU89dRT5OTksGjRIpkLqwTh4eFotVpOnTpl66IIIaoh+VpcCXXs2JFt27aRnZ1t2bZ69WrUajXt27e3YcmEvTAYDIwdO5bExEQ+//xzmX7hOvbu3Yter5eO+UIIm5CasEpo4MCBfPPNNzz77LM89dRTpKWl8dFHHzFw4MBq+2Gbn5/Pxo0bAUhJSSE3N5fVq1cD0KZNmxKnbKjKLs8Z98orr5Cbm8uePXss+yIjI6vlygqjRo2iSZMmhIeH4+zszKFDh5g3bx7h4eF069bN1sUTQlRDMllrJXXs2DHeffddq2WLxo0bVy0/XAGSk5Pp2rVrifu+/vproqOj73CJbKtLly6kpKSUuG/dunXVsuYnLi6O+Ph4Tp06haIoBAYG0r17d4YOHVrtp+0QQtiGJGFCCCGEEDYgfcKEEEIIIWxAkjAhhBBCCBuQJEwIIYQQwgYkCRNCCCGEsAFJwoQQQgghbECSMCGEEEIIG5AkTAghhBDCBiQJE0IIIYSwAUnChBBCCCFsQJIwIYQQQggbkCRMCCGEEMIG/h+Z79oTvuImjAAAAABJRU5ErkJggg==", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "hist_robot.combiplot();" ] }, { "cell_type": "markdown", "id": "cdc359b2", "metadata": {}, "source": [ "Unfortunately the `HIST.nc` file does not have enough metadata.\n", "In particular we would like to have information about the k-point sampling\n", "so that we can analyze the convergence of the optimized lattice parameters wrt {{nkpt}}.\n", "Fortunately the `GSR.nc` has all the information we need and it is just a matter\n", "of replacing the `HistRobot` with a `GsrRobot`:" ] }, { "cell_type": "code", "execution_count": 25, "id": "8608c0b7", "metadata": {}, "outputs": [], "source": [ "with abilab.GsrRobot.from_dir(\"flow_base3_relax\") as relkpt_robot:\n", " relax_table = relkpt_robot.get_dataframe().sort_values(by=\"nkpt\")\n", " dfs = relkpt_robot.get_structure_dataframes()" ] }, { "cell_type": "code", "execution_count": 26, "id": "fb9161d9", "metadata": {}, "outputs": [ { "data": { "text/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", "
energyapressuremax_forcepressure
w0/t0/outdata/out_GSR.nc-241.2556303.829282-0.0132591.913429e-27-0.013259
w0/t1/outdata/out_GSR.nc-241.4252173.822962-0.0087576.356619e-27-0.008757
\n", "
" ], "text/plain": [ " energy a pressure max_force \\\n", "w0/t0/outdata/out_GSR.nc -241.255630 3.829282 -0.013259 1.913429e-27 \n", "w0/t1/outdata/out_GSR.nc -241.425217 3.822962 -0.008757 6.356619e-27 \n", "\n", " pressure \n", "w0/t0/outdata/out_GSR.nc -0.013259 \n", "w0/t1/outdata/out_GSR.nc -0.008757 " ] }, "execution_count": 26, "metadata": {}, "output_type": "execute_result" } ], "source": [ "relax_table[[\"energy\", \"a\", \"pressure\", \"max_force\", \"pressure\"]]" ] }, { "cell_type": "markdown", "id": "382bb99a", "metadata": {}, "source": [ "Plotting the energy, the lattice parameter `a` in Bohr and the pressure in `GPa` vs `nkpt` is really a piece of cake!" ] }, { "cell_type": "code", "execution_count": 27, "id": "2609bb98", "metadata": {}, "outputs": [ { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "relax_table.plot(x=\"nkpt\", y=[\"energy\", \"a\", \"pressure\"], subplots=True);" ] }, { "cell_type": "markdown", "id": "484befaf", "metadata": {}, "source": [ "Alternatively, one can use the `GsrRobot` API:" ] }, { "cell_type": "code", "execution_count": 28, "id": "e05a01c4", "metadata": {}, "outputs": [ { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "relkpt_robot.plot_gsr_convergence(sortby=\"nkpt\");" ] }, { "cell_type": "code", "execution_count": 29, "id": "63c978bd", "metadata": {}, "outputs": [ { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "relkpt_robot.plot_lattice_convergence(what_list=[\"a\"], sortby=\"nkpt\");" ] }, { "cell_type": "markdown", "id": "dde78b08", "metadata": {}, "source": [ "We fix the {{acell}} parameters to the theoretical value of 3*10.216,\n", "and we fix also the grid of k points\n", "(the 4x4x4 FCC grid, equivalent to a 8x8x8 Monkhorst-pack grid).\n", "We will ask for 8 bands (4 valence and 4 conduction)." ] }, { "cell_type": "markdown", "id": "b30b69c0", "metadata": {}, "source": [ "## Computing the band structure\n", "\n", "A band structure can be computed by solving the Kohn-Sham equation for many different k points,\n", "along different lines of the Brillouin zone.\n", "The potential that enters the Kohn-Sham equation must be derived from a previous self-consistent calculation,\n", "and will not vary during the scan of different k-point lines.\n", "\n", "This is our first Flow with dependencies in the sense that the band structure calculation **must be\n", "connected **to a previous SCF run.\n", "Fortunately AbiPy provides a factory function to generate this kind of workflow.\n", "We only need to focus on the definition of the two inputs:" ] }, { "cell_type": "code", "execution_count": 30, "id": "c32958b5", "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\n", " \n", " \n", " \n", "\n", "\n", "

\n", "\n", "
def build_ebands_flow(options):\n",
       "    """\n",
       "    Band structure calculation.\n",
       "    First, a SCF density computation, then a non-SCF band structure calculation.\n",
       "    Similar to tbase3_5.in\n",
       "    """\n",
       "    multi = abilab.MultiDataset(structure=abidata.cif_file("si.cif"),\n",
       "                                pseudos=abidata.pseudos("14si.pspnc"), ndtset=2)\n",
       "    # Global variables\n",
       "    shiftk = [float(s) for s in "0.5 0.5 0.5 0.5 0.0 0.0 0.0 0.5 0.0 0.0 0.0 0.5".split()]\n",
       "    multi.set_vars(ecut=8, diemac=12, iomode=3)\n",
       "\n",
       "    # Dataset 1\n",
       "    multi[0].set_vars(tolvrs=1e-9)\n",
       "    multi[0].set_kmesh(ngkpt=[4, 4, 4], shiftk=shiftk)\n",
       "\n",
       "    # Dataset 2\n",
       "    multi[1].set_vars(tolwfr=1e-15)\n",
       "    multi[1].set_kpath(ndivsm=5)\n",
       "\n",
       "    scf_input, nscf_input = multi.split_datasets()\n",
       "\n",
       "    workdir = options.workdir if (options and options.workdir) else "flow_base3_ebands"\n",
       "\n",
       "    return flowtk.bandstructure_flow(workdir, scf_input=scf_input, nscf_input=nscf_input)\n",
       "
\n", "\n", "\n" ], "text/plain": [ "" ] }, "execution_count": 30, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from lesson_base3 import build_ebands_flow\n", "abilab.print_source(build_ebands_flow)" ] }, { "cell_type": "markdown", "id": "50817dac", "metadata": {}, "source": [ "The `Flow` consists of a single `Work` with two `Tasks`\n", "(`ScfTask` with a **k**-mesh and a `NscfTask` performed on the **k**-path)." ] }, { "cell_type": "code", "execution_count": 31, "id": "91f55948", "metadata": {}, "outputs": [ { "data": { "image/svg+xml": [ "\n", "\n", "\n", "\n", "\n", "\n", "flow\n", "\n", "Flow, node_id=33, workdir=flow_base3_ebands\n", "\n", "clusterw0\n", "\n", "BandStructureWork (w0)\n", "\n", "\n", "\n", "w0_t0\n", "\n", "w0_t0\n", "ScfTask\n", "\n", "\n", "\n", "w0_t1\n", "\n", "w0_t1\n", "NscfTask\n", "\n", "\n", "\n", "w0_t0->w0_t1\n", "\n", "\n", "DEN\n", "\n", "\n", "\n" ], "text/plain": [ "" ] }, "execution_count": 31, "metadata": {}, "output_type": "execute_result" } ], "source": [ "ebands_flow = build_ebands_flow(options=None)\n", "ebands_flow.get_graphviz()" ] }, { "cell_type": "markdown", "id": "d6a181e6", "metadata": {}, "source": [ "```{note}\n", "If you want to run the flow from the shell, open *lesson_base3.py* and change\n", "the main function so that it calls `build_ebands_flow`.\n", "```" ] }, { "cell_type": "markdown", "id": "7d0d79c0", "metadata": {}, "source": [ "Let's extract the band structure from the `GSR.nc` file produced by the `NscfTask`:" ] }, { "cell_type": "code", "execution_count": 32, "id": "706da352", "metadata": {}, "outputs": [], "source": [ "with abilab.abiopen(\"flow_base3_ebands/w0/t1/outdata/out_GSR.nc\") as gsr:\n", " ebands_kpath = gsr.ebands" ] }, { "cell_type": "markdown", "id": "c090d940", "metadata": {}, "source": [ "and plot it with:" ] }, { "cell_type": "code", "execution_count": 33, "id": "50d96e4b", "metadata": {}, "outputs": [ { "data": { "application/vnd.plotly.v1+json": { "config": { "plotlyServerURL": "https://chart-studio.plotly.com", "responsive": true, "showLink": true }, "data": [ { "legendgroup": "", "line": { "color": "black", "width": 2.0 }, "mode": "lines", "name": "", "showlegend": false, "type": "scatter", "x": [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100 ], "y": [ -11.851613445039852, -11.829262546507499, -11.763277586937281, -11.653518784562753, -11.499818752637747, -11.303672784838163, -11.065105789040572, -10.784900153444106, -10.46402896039755, -10.103803186424756, -9.704813330716574, -9.269732619156798, -8.80096606434941, -8.30029060241338, -7.770465816946935, -7.763241578125931, -7.742609888248671, -7.712076592668978, -7.676700589636666, -7.643701158030813, -7.620022143667228, -7.611886989754334, -7.815402926706225, -7.974645817539696, -8.088881272757748, -8.157720333201592, -8.180770328221685, -8.434835077782893, -8.748456785422272, -9.101150890084453, -9.470241909780931, -9.83793835665062, -10.191581875439843, -10.521740693190559, -10.822584099183754, -11.088930019097868, -11.318647158805701, -11.508846872276596, -11.65799194485696, -11.76519980446276, -11.829880423716633, -11.851613445039852, -11.828901344903677, -11.761680471046045, -11.650084601108308, -11.495292457971903, -11.298131195766894, -11.062704080597197, -10.792431633734072, -10.494740482925705, -10.182477994899303, -9.884090789817407, -9.649851486789906, -9.556725550290272, -9.536698945102296, -9.47715632340821, -9.378314780070777, -9.24099057837031, -9.066529106063651, -8.857939766387581, -8.621810965354028, -8.376015999739792, -8.180770328166698, -8.157720333145175, -8.088881272700194, -7.97464581748109, -7.815402926646792, -7.611886989754334, -7.933335050545356, -8.246455483732571, -8.538422451074794, -8.800044043255458, -9.026971122765246, -9.215642668944206, -9.364114935032834, -9.47090005430848, -9.535083175750776, -9.556725550290272, -9.536698945102458, -9.477156323408988, -9.378314780072763, -9.240990578374099, -9.066529106070309, -8.857939766398722, -8.621810965372902, -8.376015999772683, -8.180770328221685, -8.248627108168062, -8.31543595384342, -8.365731396159052, -8.392618338737506, -8.39261833873174, -8.365731396141433, -8.315435953813203, -8.248627108124618, -8.180770328166698, -7.996771832951532, -7.879025362950108, -7.811912967138432, -7.779817588004046, -7.770465816946935 ] }, { "legendgroup": "", "line": { "color": "black", "width": 2.0 }, "mode": "lines", "name": "", "showlegend": false, "type": "scatter", "x": [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100 ], "y": [ -1.6335377495124703e-10, -0.16032698820379743, -0.5636457951166554, -1.09212474143225, -1.6773154842945197, -2.289399990162149, -2.914361827484835, -3.5449307515696202, -4.176451181929831, -4.805790281523441, -5.427689289964074, -6.039193341392819, -6.636376169672958, -7.21465163615954, -7.770465816821671, -7.763241578000309, -7.742609888122045, -7.712076592541063, -7.676700589507842, -7.643701157902436, -7.620022143541795, -7.611886989635335, -7.421374711335846, -7.299854712627417, -7.231093034567854, -7.1978687821403105, -7.188285204247792, -6.933409816359069, -6.633292984974313, -6.289280715718499, -5.90009368490985, -5.466932624806164, -4.991069137133525, -4.474881178196011, -3.919781777304002, -3.327536819015947, -2.7041108333466273, -2.0554800452214876, -1.396703083132917, -0.7604575290559579, -0.23013771779409087, -1.6335377495124703e-10, -0.26620529703147877, -0.8784501465647239, -1.6181584465130672, -2.3945578566803456, -3.1682486139103343, -3.921330316630484, -4.638994639961529, -5.308128391121763, -5.9114859308089756, -6.419868512550031, -6.779883102520867, -6.916275493243097, -6.905755465365838, -6.876303328603695, -6.832943230472041, -6.785214176651248, -6.751038035826356, -6.758244913985018, -6.840508544787537, -7.007460892791007, -7.188285204338305, -7.19786878222963, -7.231093034654421, -7.299854712708667, -7.42137471140827, -7.611886989635335, -7.301869405677406, -7.036209363986135, -6.848777335906148, -6.756628850987542, -6.7440152653999075, -6.777440649106646, -6.826958945905898, -6.8733412683580575, -6.904920301053387, -6.916275493243097, -6.905755465365712, -6.8763033286036315, -6.832943230471622, -6.785214176649349, -6.751038035820505, -6.758244913970187, -6.8405085447560925, -7.007460892733634, -7.188285204247792, -7.111946471075832, -7.031995853958247, -6.969031241749459, -6.935218102137593, -6.935218102147362, -6.96903124177916, -7.031995854008725, -7.111946471147528, -7.188285204338305, -7.397146006609232, -7.559977186599288, -7.677101927235896, -7.7471166931150774, -7.770465816821671 ] }, { "legendgroup": "", "line": { "color": "black", "width": 2.0 }, "mode": "lines", "name": "", "showlegend": false, "type": "scatter", "x": [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100 ], "y": [ -8.334133383414155e-11, -0.09211515515031987, -0.32824727411248933, -0.6354843455953532, -0.9631773430067367, -1.2868497795106428, -1.5917488120541616, -1.8699833250375155, -2.11677200086739, -2.3291545295224263, -2.5037909213476284, -2.6408722380667453, -2.740440421057171, -2.8003751148881233, -2.8203905545038555, -2.8860288266775997, -3.0546901728130798, -3.270200318651442, -3.48261501071111, -3.6568800949279403, -3.770265008381178, -3.8107473700624728, -3.9652867523983035, -4.0900163941103695, -4.180562266201235, -4.235112367525848, -4.253803130533925, -4.362192280919555, -4.345845039371504, -4.2215610063338325, -4.0064177361656155, -3.717533479235718, -3.370725628322197, -2.9758873372138854, -2.544196435673573, -2.0865410091040704, -1.6166404895025357, -1.1528235125847308, -0.7182474423045901, -0.3491040930372957, -0.09293055363501157, -8.334133383414155e-11, -0.03809873573310618, -0.1429488014485587, -0.28742471542663317, -0.4479972131523935, -0.6068650387686665, -0.7553479368493718, -0.8856854923086326, -0.9947007066478415, -1.0801792348909558, -1.1417866347775893, -1.1786793220517104, -1.1921544309391203, -1.3794575138561989, -1.825644345586102, -2.369434218783695, -2.9243278123614713, -3.4385550125135227, -3.8652364322550348, -4.156935732773959, -4.283871621112044, -4.253803130519498, -4.235112367511156, -4.180562266186957, -4.090016394097196, -3.9652867523870174, -3.8107473700624728, -4.007134693668303, -4.09329698299312, -4.030554851546317, -3.803145302957149, -3.42992286752277, -2.9497935995715783, -2.408352500134239, -1.8583358890492825, -1.3926014885726277, -1.1921544309391203, -1.3794575137994745, -1.8256443455318623, -2.3694342187314503, -2.92432781231171, -3.438555012468338, -3.865236432218387, -4.156935732751388, -4.2838716211078065, -4.253803130533925, -4.273514317225932, -4.23884340980823, -4.163788206856713, -4.093693416687977, -4.093693416690762, -4.163788206861114, -4.238843409808835, -4.273514317219683, -4.253803130519498, -4.018734260151437, -3.6815208461149043, -3.2974166712355224, -2.961787548870396, -2.8203905545038555 ] }, { "legendgroup": "", "line": { "color": "black", "width": 2.0 }, "mode": "lines", "name": "", "showlegend": false, "type": "scatter", "x": [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100 ], "y": [ 0.0, -0.09211515504698742, -0.3282472740288691, -0.6354843455286749, -0.9631773429514219, -1.2868497794616625, -1.5917488120078889, -1.8699833249917366, -2.1167720008209514, -2.329154529474871, -2.5037909212987204, -2.6408722380167564, -2.7404404210064457, -2.8003751148369007, -2.8203905544524637, -2.8860288266308487, -3.054690172777407, -3.270200318627115, -3.4826150106888636, -3.6568800948958984, -3.7702650083356892, -3.8107473700038414, -3.577837505726965, -3.244838208497727, -2.8652428266815546, -2.5366929541182444, -2.3990574510867804, -2.2214629443194367, -2.0195348042998416, -1.797493225997051, -1.561755463924979, -1.317366161445312, -1.0741180298982904, -0.8413174918080655, -0.6287781210384527, -0.44437858817602116, -0.2941073014400777, -0.1781910790333603, -0.09506547870692561, -0.04053223612994916, -0.009632704147326088, 0.0, -0.038098735689124474, -0.14294880140758792, -0.2874247153895588, -0.4479972131180334, -0.606865038733801, -0.7553479368102787, -0.8856854922628417, -0.9947007065945579, -1.0801792348307062, -1.1417866347118037, -1.1786793219823508, -1.1921544308687038, -1.228867896098646, -1.3300459374633808, -1.47870080386007, -1.652111383687319, -1.8316823948835745, -2.00430661520324, -2.160024838950893, -2.29321320061289, -2.399057451090166, -2.536692954113345, -2.865242826671942, -3.244838208488802, -3.5778375057242995, -3.8107473700038414, -3.5345497983318137, -3.208169970244198, -2.853818642870846, -2.4897375490238565, -2.137234436321377, -1.8174036791571582, -1.550549151988701, -1.3530913671577975, -1.232217856123289, -1.1921544308687038, -1.2288678961545685, -1.3300459375131126, -1.4787008039013783, -1.652111383719625, -1.8316823949072392, -2.0043066152188804, -2.1600248389594134, -2.2932132006150487, -2.3990574510867804, -2.446692141953893, -2.63163563366671, -2.853804945823167, -3.0105784873298793, -3.010578487324915, -2.8538049458122643, -2.63163563365609, -2.4466921419485868, -2.399057451090166, -2.5478847853783164, -2.6662661059255948, -2.7511129264431946, -2.803014556424606, -2.8203905544524637 ] }, { "legendgroup": "", "line": { "color": "black", "width": 2.0 }, "mode": "lines", "name": "", "showlegend": false, "type": "scatter", "x": [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100 ], "y": [ 2.5122998962024123, 2.4659990593471584, 2.300498242709943, 2.07249175115928, 1.8139821624238675, 1.547901139681355, 1.2932614151436423, 1.0629634354095403, 0.8659627463667237, 0.7058083015123815, 0.592881346241235, 0.5283996162677376, 0.5166806915267141, 0.5585638074771229, 0.6578951423348149, 0.7791898484978423, 1.1158791383818167, 1.6138390186324916, 2.2257662680617756, 2.9169190551276554, 3.656472551200931, 4.2209673810841934, 3.5056460346633163, 2.6470530606189, 1.8971372735474556, 1.3524073521808946, 1.1425072029499486, 1.3489395861198155, 1.5807622702129844, 1.8329315205187688, 2.0948114040784542, 2.352899920500505, 2.583677988477321, 2.760137488600286, 2.862609611797753, 2.8903295781361713, 2.863087850677264, 2.8361320056351875, 2.723552495816225, 2.614020510806002, 2.550680684772594, 2.5122998962024123, 2.5655460423718477, 2.473000865976113, 2.3335052380209316, 2.167275255926123, 1.995520046402028, 1.832029357783112, 1.686643241833675, 1.5636517525829179, 1.469360074491333, 1.398582069139839, 1.356978740567567, 1.3409953340676113, 1.5145510028941738, 1.8722604530378728, 2.092188422387859, 2.0308247644766517, 1.840924139783878, 1.629467596427471, 1.434156843325633, 1.2689557779537504, 1.1425072029457386, 1.3524073521639988, 1.8971372734595677, 2.647053060880973, 3.5056490806367187, 4.2209673810841934, 3.917803514759532, 3.618540214941529, 3.37426750478088, 3.2130468904841276, 2.936786222084285, 2.642637809333662, 2.3154899245457408, 1.9233429563667217, 1.5279439779344806, 1.3409953340676113, 1.5145510029056446, 1.8722604666215537, 2.0921884226177037, 2.0308247646628494, 1.8409241397573108, 1.6294675964089143, 1.4341568433149794, 1.2689557779503104, 1.1425072029499486, 1.3475684269208843, 1.8084646675065548, 2.4433869871103173, 3.1814344039733857, 3.18143354344439, 2.443386986833433, 1.8084646674899005, 1.3475684269101826, 1.1425072029457386, 0.9709439070638091, 0.8348913946576921, 0.7374868785337476, 0.6778521258540584, 0.6578951423348149 ] }, { "marker": { "color": "blue", "line": { "width": 2 }, "opacity": 0.9, "size": 12 }, "mode": "markers", "name": "", "showlegend": false, "type": "scatter", "x": [ 0, 12 ], "y": [ 0.0, 0.5166806915267141 ] }, { "hoverinfo": "none", "line": { "width": 2 }, "marker": { "color": "gray" }, "mode": "lines", "name": "", "showlegend": false, "type": "scatter", "x": [ 0, 12, null, 9.780080750947734, 12, 9.709394669279906, null ], "y": [ 0.0, 0.5166806915267141, null, -0.40127185908093355, 0.5166806915267141, 1.2404248288822766, null ] }, { "marker": { "color": "blue", "line": { "width": 2 }, "opacity": 0.9, "size": 12 }, "mode": "markers", "name": "", "showlegend": false, "type": "scatter", "x": [ 0, 0 ], "y": [ 0.0, 2.5122998962024123 ] }, { "hoverinfo": "none", "line": { "width": 2 }, "marker": { "color": "gray" }, "mode": "lines", "name": "", "showlegend": false, "type": "scatter", "x": [ 0, 0, null, 0.17185143411524234, 0, -0.1718514341152424, null ], "y": [ 0.0, 2.5122998962024123, null, 2.04014196146989, 2.5122998962024123, 2.04014196146989, null ] }, { "marker": { "color": "blue", "line": { "width": 2 }, "opacity": 0.9, "size": 12 }, "mode": "markers", "name": "", "showlegend": false, "type": "scatter", "x": [ 41, 41 ], "y": [ 0.0, 2.5122998962024123 ] }, { "hoverinfo": "none", "line": { "width": 2 }, "marker": { "color": "gray" }, "mode": "lines", "name": "", "showlegend": false, "type": "scatter", "x": [ 41, 41, null, 41.17185143411524, 41, 40.82814856588476, null ], "y": [ 0.0, 2.5122998962024123, null, 2.04014196146989, 2.5122998962024123, 2.04014196146989, null ] } ], "layout": { "annotations": [ { "font": { "size": 12 }, "showarrow": false, "text": "Si₂: direct gap = 2.51, fundamental gap = 0.52 (eV)", "x": 0, "xanchor": "left", "xref": "paper", "y": 1, "yanchor": "bottom", "yref": "paper" } ], "hovermode": false, "template": { "data": { "bar": [ { "error_x": { "color": "#2a3f5f" }, "error_y": { "color": "#2a3f5f" }, "marker": { "line": { "color": "#E5ECF6", "width": 0.5 }, "pattern": { "fillmode": "overlay", "size": 10, "solidity": 0.2 } }, "type": "bar" } ], "barpolar": [ { "marker": { "line": { "color": "#E5ECF6", "width": 0.5 }, "pattern": { "fillmode": "overlay", "size": 10, "solidity": 0.2 } }, "type": "barpolar" } ], "carpet": [ { "aaxis": { "endlinecolor": "#2a3f5f", "gridcolor": "white", "linecolor": "white", "minorgridcolor": "white", "startlinecolor": "#2a3f5f" }, "baxis": { "endlinecolor": "#2a3f5f", "gridcolor": "white", "linecolor": "white", "minorgridcolor": "white", "startlinecolor": "#2a3f5f" }, "type": "carpet" } ], "choropleth": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "type": "choropleth" } ], "contour": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0.0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1.0, "#f0f921" ] ], "type": "contour" } ], "contourcarpet": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "type": "contourcarpet" } ], "heatmap": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0.0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1.0, "#f0f921" ] ], "type": "heatmap" } ], "heatmapgl": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0.0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1.0, "#f0f921" ] ], "type": "heatmapgl" } ], "histogram": [ { "marker": { "pattern": { "fillmode": "overlay", "size": 10, "solidity": 0.2 } }, "type": "histogram" } ], "histogram2d": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0.0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1.0, "#f0f921" ] ], "type": "histogram2d" } ], "histogram2dcontour": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0.0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1.0, "#f0f921" ] ], "type": "histogram2dcontour" } ], "mesh3d": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "type": "mesh3d" } ], "parcoords": [ { "line": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "parcoords" } ], "pie": [ { "automargin": true, "type": "pie" } ], "scatter": [ { "fillpattern": { "fillmode": "overlay", "size": 10, "solidity": 0.2 }, "type": "scatter" } ], "scatter3d": [ { "line": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scatter3d" } ], "scattercarpet": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scattercarpet" } ], "scattergeo": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scattergeo" } ], "scattergl": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scattergl" } ], "scattermapbox": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scattermapbox" } ], "scatterpolar": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scatterpolar" } ], "scatterpolargl": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scatterpolargl" } ], "scatterternary": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scatterternary" } ], "surface": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0.0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1.0, "#f0f921" ] ], "type": "surface" } ], "table": [ { "cells": { "fill": { "color": "#EBF0F8" }, "line": { "color": "white" } }, "header": { "fill": { "color": "#C8D4E3" }, "line": { "color": "white" } }, "type": "table" } ] }, "layout": { "annotationdefaults": { "arrowcolor": "#2a3f5f", "arrowhead": 0, "arrowwidth": 1 }, "autotypenumbers": "strict", "coloraxis": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "colorscale": { "diverging": [ [ 0, "#8e0152" ], [ 0.1, "#c51b7d" ], [ 0.2, "#de77ae" ], [ 0.3, "#f1b6da" ], [ 0.4, "#fde0ef" ], [ 0.5, "#f7f7f7" ], [ 0.6, "#e6f5d0" ], [ 0.7, "#b8e186" ], [ 0.8, "#7fbc41" ], [ 0.9, "#4d9221" ], [ 1, "#276419" ] ], "sequential": [ [ 0.0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1.0, "#f0f921" ] ], "sequentialminus": [ [ 0.0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1.0, "#f0f921" ] ] }, "colorway": [ "#636efa", "#EF553B", "#00cc96", "#ab63fa", "#FFA15A", "#19d3f3", "#FF6692", "#B6E880", "#FF97FF", "#FECB52" ], "font": { "color": "#2a3f5f" }, "geo": { "bgcolor": "white", "lakecolor": "white", "landcolor": "#E5ECF6", "showlakes": true, "showland": true, "subunitcolor": "white" }, "hoverlabel": { "align": "left" }, "hovermode": "closest", "mapbox": { "style": "light" }, "paper_bgcolor": "white", "plot_bgcolor": "#E5ECF6", "polar": { "angularaxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" }, "bgcolor": "#E5ECF6", "radialaxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" } }, "scene": { "xaxis": { "backgroundcolor": "#E5ECF6", "gridcolor": "white", "gridwidth": 2, "linecolor": "white", "showbackground": true, "ticks": "", "zerolinecolor": "white" }, "yaxis": { "backgroundcolor": "#E5ECF6", "gridcolor": "white", "gridwidth": 2, "linecolor": "white", "showbackground": true, "ticks": "", "zerolinecolor": "white" }, "zaxis": { "backgroundcolor": "#E5ECF6", "gridcolor": "white", "gridwidth": 2, "linecolor": "white", "showbackground": true, "ticks": "", "zerolinecolor": "white" } }, "shapedefaults": { "line": { "color": "#2a3f5f" } }, "ternary": { "aaxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" }, "baxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" }, "bgcolor": "#E5ECF6", "caxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" } }, "title": { "x": 0.05 }, "xaxis": { "automargin": true, "gridcolor": "white", "linecolor": "white", "ticks": "", "title": { "standoff": 15 }, "zerolinecolor": "white", "zerolinewidth": 2 }, "yaxis": { "automargin": true, "gridcolor": "white", "linecolor": "white", "ticks": "", "title": { "standoff": 15 }, "zerolinecolor": "white", "zerolinewidth": 2 } } }, "xaxis": { "range": [ 0, 100 ], "tickfont": { "size": 16 }, "ticktext": [ "Γ", "X", "W", "K", "Γ", "L", "U", "W", "L", "K", "U", "X" ], "tickvals": [ 0, 14, 21, 26, 41, 53, 62, 67, 77, 86, 95, 100 ], "title": { "text": "Wave Vector" } }, "yaxis": { "range": [ -7.512299896202412, 7.512299896202412 ], "title": { "text": "Energy (eV)" } } } }, "text/html": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "ebands_kpath.plotly(with_gaps=True);" ] }, { "cell_type": "markdown", "id": "8918cc71", "metadata": {}, "source": [ "Visual inspection reveals that the width of the valence band is ~11.8 eV,\n", "the lowest unoccupied state at X is ~0.5 eV higher than the top of the valence band at $\\Gamma$.\n", "Bulk silicon is described as an indirect band gap material (this is correct), with a band-gap\n", "of about 0.5 eV (this is quantitatively quite wrong:\n", "the experimental value is 1.17 eV at 25 degree Celsius, the famous **DFT band-gap problem**).\n", "The minimum of the conduction band is even slightly displaced with respect to X.\n", "\n", "Unfortunately, it seems that AbiPy does not agree with us:" ] }, { "cell_type": "code", "execution_count": 34, "id": "aa774b9d", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "================================= Structure =================================\n", "Full Formula (Si2)\n", "Reduced Formula: Si\n", "abc : 3.866975 3.866975 3.866975\n", "angles: 60.000000 60.000000 60.000000\n", "pbc : True True True\n", "Sites (2)\n", " # SP a b c\n", "--- ---- ---- ---- ----\n", " 0 Si 0 0 0\n", " 1 Si 0.25 0.25 0.25\n", "\n", "Abinit Spacegroup: spgid: 227, num_spatial_symmetries: 48, has_timerev: True, symmorphic: True\n", "\n", "Number of electrons: 8.0, Fermi level: 5.567 (eV)\n", "nsppol: 1, nkpt: 101, mband: 5, nspinor: 1, nspden: 1\n", "smearing scheme: none (occopt 1), tsmear_eV: 0.272, tsmear Kelvin: 3157.7\n", "Direct gap:\n", " Energy: 2.512 (eV)\n", " Initial state: spin: 0, kpt: $\\Gamma$ [+0.000, +0.000, +0.000], band: 3, eig: 5.567, occ: 2.000\n", " Final state: spin: 0, kpt: $\\Gamma$ [+0.000, +0.000, +0.000], band: 4, eig: 8.080, occ: 0.000\n", "Fundamental gap:\n", " Energy: 0.517 (eV)\n", " Initial state: spin: 0, kpt: $\\Gamma$ [+0.000, +0.000, +0.000], band: 3, eig: 5.567, occ: 2.000\n", " Final state: spin: 0, kpt: [+0.429, +0.000, +0.429], band: 4, eig: 6.084, occ: 0.000\n", "Bandwidth: 11.852 (eV)\n", "Valence maximum located at kpt index 0:\n", " spin: 0, kpt: $\\Gamma$ [+0.000, +0.000, +0.000], band: 3, eig: 5.567, occ: 2.000\n", "Conduction minimum located at kpt index 12:\n", " spin: 0, kpt: [+0.429, +0.000, +0.429], band: 4, eig: 6.084, occ: 0.000\n", "\n", "TIP: Use `--verbose` to print k-point coordinates with more digits\n" ] } ], "source": [ "print(ebands_kpath)" ] }, { "cell_type": "markdown", "id": "31944445", "metadata": {}, "source": [ "The reason is that the Fermi energy in `ebands_kpath` is not completely consistent with the band structure.\n", "The Fermi energy, indeed, has been taken from the previous GS-SCF calculation performed\n", "on a shifted k-mesh, the $\\Gamma$ point was not included and therefore the Fermi energy is underestimated.\n", "\n", "To fix this problem we have to change manually the Fermi energy and set it to the maximum of the valence bands:" ] }, { "cell_type": "code", "execution_count": 35, "id": "0ba5e46b", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "================================= Structure =================================\n", "Full Formula (Si2)\n", "Reduced Formula: Si\n", "abc : 3.866975 3.866975 3.866975\n", "angles: 60.000000 60.000000 60.000000\n", "pbc : True True True\n", "Sites (2)\n", " # SP a b c\n", "--- ---- ---- ---- ----\n", " 0 Si 0 0 0\n", " 1 Si 0.25 0.25 0.25\n", "\n", "Abinit Spacegroup: spgid: 227, num_spatial_symmetries: 48, has_timerev: True, symmorphic: True\n", "\n", "Number of electrons: 8.0, Fermi level: 5.567 (eV)\n", "nsppol: 1, nkpt: 101, mband: 5, nspinor: 1, nspden: 1\n", "smearing scheme: none (occopt 1), tsmear_eV: 0.272, tsmear Kelvin: 3157.7\n", "Direct gap:\n", " Energy: 2.512 (eV)\n", " Initial state: spin: 0, kpt: $\\Gamma$ [+0.000, +0.000, +0.000], band: 3, eig: 5.567, occ: 2.000\n", " Final state: spin: 0, kpt: $\\Gamma$ [+0.000, +0.000, +0.000], band: 4, eig: 8.080, occ: 0.000\n", "Fundamental gap:\n", " Energy: 0.517 (eV)\n", " Initial state: spin: 0, kpt: $\\Gamma$ [+0.000, +0.000, +0.000], band: 3, eig: 5.567, occ: 2.000\n", " Final state: spin: 0, kpt: [+0.429, +0.000, +0.429], band: 4, eig: 6.084, occ: 0.000\n", "Bandwidth: 11.852 (eV)\n", "Valence maximum located at kpt index 0:\n", " spin: 0, kpt: $\\Gamma$ [+0.000, +0.000, +0.000], band: 3, eig: 5.567, occ: 2.000\n", "Conduction minimum located at kpt index 12:\n", " spin: 0, kpt: [+0.429, +0.000, +0.429], band: 4, eig: 6.084, occ: 0.000\n", "\n", "TIP: Use `--verbose` to print k-point coordinates with more digits\n" ] } ], "source": [ "ebands_kpath.set_fermie_to_vbm()\n", "print(ebands_kpath)" ] }, { "cell_type": "markdown", "id": "ca18761a", "metadata": {}, "source": [ "Now the AbiPy results are consistent with our initial analysis:" ] }, { "cell_type": "code", "execution_count": 36, "id": "3574c3a1", "metadata": {}, "outputs": [ { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "ebands_kpath.plot(with_gaps=True);" ] }, { "cell_type": "code", "execution_count": 37, "id": "85e87730", "metadata": {}, "outputs": [], "source": [ "# We can also plot the k-path in the Brillouin zone with:\n", "#ebands_kpath.kpoints.plotly();" ] }, { "cell_type": "markdown", "id": "85e914e7", "metadata": {}, "source": [ "The `GSR` file produced by the first task contains energies on a homogeneous k-mesh.\n", "We can therefore compute the DOS by invoking the `get_edos` method:" ] }, { "cell_type": "code", "execution_count": 38, "id": "74c85048", "metadata": {}, "outputs": [], "source": [ "with abilab.abiopen(\"flow_base3_ebands/w0/t0/outdata/out_GSR.nc\") as gsr:\n", " ebands_kmesh = gsr.ebands\n", "\n", "edos = ebands_kmesh.get_edos()" ] }, { "cell_type": "markdown", "id": "b93b7d25", "metadata": {}, "source": [ "and plot the DOS with:" ] }, { "cell_type": "code", "execution_count": 39, "id": "3958d1ef", "metadata": {}, "outputs": [ { "data": { "application/vnd.plotly.v1+json": { "config": { "plotlyServerURL": "https://chart-studio.plotly.com", "responsive": true, "showLink": true }, "data": [ { "line": { "color": "black", "width": 1.0 }, "mode": "lines", "name": "", "showlegend": false, "type": "scatter", "x": [ -12.44652085384753, -12.396387613682947, -12.346254373518363, -12.29612113335378, -12.245987893189199, -12.195854653024615, -12.14572141286003, -12.09558817269545, -12.045454932530866, -11.995321692366282, -11.9451884522017, -11.895055212037118, -11.844921971872534, -11.794788731707952, -11.74465549154337, -11.694522251378785, -11.644389011214201, -11.594255771049621, -11.544122530885037, -11.493989290720453, -11.44385605055587, -11.393722810391289, -11.343589570226705, -11.293456330062122, -11.24332308989754, -11.193189849732956, -11.143056609568372, -11.092923369403792, -11.042790129239208, -10.992656889074624, -10.942523648910042, -10.89239040874546, -10.842257168580876, -10.792123928416293, -10.741990688251711, -10.691857448087127, -10.641724207922543, -10.591590967757963, -10.541457727593379, -10.491324487428795, -10.441191247264214, -10.39105800709963, -10.340924766935046, -10.290791526770464, -10.240658286605882, -10.190525046441298, -10.140391806276714, -10.090258566112134, -10.04012532594755, -9.989992085782967, -9.939858845618383, -9.889725605453801, -9.839592365289217, -9.789459125124635, -9.739325884960053, -9.689192644795469, -9.639059404630887, -9.588926164466304, -9.53879292430172, -9.488659684137138, -9.438526443972554, -9.388393203807972, -9.338259963643388, -9.288126723478806, -9.237993483314224, -9.18786024314964, -9.137727002985057, -9.087593762820475, -9.037460522655891, -8.987327282491309, -8.937194042326727, -8.887060802162143, -8.836927561997559, -8.786794321832977, -8.736661081668395, -8.68652784150381, -8.636394601339228, -8.586261361174646, -8.536128121010062, -8.48599488084548, -8.435861640680898, -8.385728400516314, -8.33559516035173, -8.28546192018715, -8.235328680022565, -8.185195439857981, -8.1350621996934, -8.084928959528817, -8.034795719364233, -7.984662479199651, -7.934529239035068, -7.884395998870485, -7.8342627587059015, -7.784129518541319, -7.733996278376736, -7.683863038212153, -7.63372979804757, -7.583596557882987, -7.533463317718405, -7.483330077553822, -7.4331968373892385, -7.383063597224655, -7.332930357060073, -7.28279711689549, -7.232663876730907, -7.182530636566324, -7.132397396401741, -7.082264156237159, -7.032130916072576, -6.9819976759079925, -6.931864435743409, -6.881731195578826, -6.831597955414244, -6.781464715249661, -6.731331475085078, -6.681198234920495, -6.631064994755912, -6.5809317545913295, -6.530798514426746, -6.480665274262163, -6.43053203409758, -6.380398793932998, -6.330265553768415, -6.280132313603832, -6.229999073439249, -6.179865833274666, -6.1297325931100834, -6.0795993529455, -6.029466112780917, -5.979332872616334, -5.929199632451751, -5.879066392287169, -5.828933152122586, -5.778799911958003, -5.72866667179342, -5.6785334316288365, -5.628400191464254, -5.578266951299671, -5.528133711135088, -5.478000470970505, -5.427867230805923, -5.37773399064134, -5.327600750476757, -5.2774675103121735, -5.2273342701475904, -5.177201029983008, -5.127067789818425, -5.076934549653842, -5.026801309489259, -4.976668069324676, -4.926534829160094, -4.876401588995511, -4.8262683488309275, -4.776135108666344, -4.726001868501761, -4.675868628337179, -4.625735388172596, -4.575602148008013, -4.52546890784343, -4.475335667678848, -4.4252024275142645, -4.3750691873496805, -4.324935947185098, -4.274802707020516, -4.224669466855932, -4.17453622669135, -4.124402986526768, -4.074269746362184, -4.0241365061976015, -3.9740032660330176, -3.9238700258684354, -3.873736785703853, -3.823603545539269, -3.773470305374687, -3.723337065210103, -3.673203825045521, -3.6230705848809386, -3.5729373447163546, -3.5228041045517724, -3.4726708643871884, -3.422537624222606, -3.372404384058024, -3.32227114389344, -3.272137903728858, -3.222004663564274, -3.1718714233996916, -3.1217381832351094, -3.0716049430705255, -3.0214717029059432, -2.9713384627413593, -2.921205222576777, -2.871071982412195, -2.820938742247611, -2.7708055020830287, -2.7206722619184447, -2.6705390217538625, -2.6204057815892803, -2.5702725414246963, -2.520139301260114, -2.47000606109553, -2.419872820930948, -2.3697395807663657, -2.3196063406017817, -2.2694731004371995, -2.2193398602726173, -2.1692066201080333, -2.119073379943451, -2.068940139778867, -2.018806899614285, -1.9686736594497027, -1.9185404192851188, -1.8684071791205366, -1.8182739389559526, -1.7681406987913704, -1.7180074586267882, -1.6678742184622042, -1.617740978297622, -1.567607738133038, -1.5174744979684558, -1.4673412578038736, -1.4172080176392896, -1.3670747774747074, -1.3169415373101234, -1.2668082971455412, -1.216675056980959, -1.166541816816375, -1.1164085766517928, -1.0662753364872088, -1.0161420963226266, -0.9660088561580444, -0.9158756159934605, -0.8657423758288783, -0.8156091356642943, -0.7654758954997121, -0.7153426553351299, -0.6652094151705459, -0.6150761750059637, -0.5649429348413797, -0.5148096946767975, -0.4646764545122153, -0.4145432143476313, -0.3644099741830491, -0.3142767340184669, -0.2641434938538829, -0.2140102536893007, -0.16387701352471673, -0.11374377336013453, -0.06361053319555232, -0.01347729303096834, 0.036655947133613864, 0.08678918729819785, 0.13692242746278005, 0.18705566762736225, 0.23718890779194624, 0.28732214795652844, 0.3374553881211124, 0.3875886282856946, 0.43772186845027683, 0.4878551086148608, 0.537988348779443, 0.588121588944027, 0.6382548291086092, 0.6883880692731914, 0.7385213094377754, 0.7886545496023576, 0.8387877897669416, 0.8889210299315238, 0.939054270096106, 0.98918751026069, 1.0393207504252722, 1.0894539905898561, 1.1395872307544384, 1.1897204709190206, 1.2398537110836045, 1.2899869512481867, 1.340120191412769, 1.390253431577353, 1.4403866717419351, 1.4905199119065191, 1.5406531520711013, 1.5907863922356835, 1.6409196324002675, 1.6910528725648497, 1.7411861127294337, 1.791319352894016, 1.841452593058598, 1.891585833223182, 1.9417190733877634, 1.9918523135523474, 2.0419855537169314, 2.092118793881512, 2.1422520340460958, 2.1923852742106797, 2.2425185143752637, 2.292651754539844, 2.342784994704428, 2.392918234869012, 2.4430514750335925, 2.4931847151981765, 2.5433179553627605, 2.593451195527341 ], "y": [ 0.0013849526287310467, 0.0054958653360388755, 0.01696227892690954, 0.04071732817047488, 0.07601885126393063, 0.11038507382313577, 0.12466578961212428, 0.10950766669859581, 0.07484775468671932, 0.04003670866899434, 0.01811642297038014, 0.013018598957385205, 0.02889077572904291, 0.07665472824310557, 0.16468882652737912, 0.27599117618347574, 0.35980071245394846, 0.36482609402764093, 0.2877432858839863, 0.17675204850458728, 0.08586544192801782, 0.03894679433560785, 0.03650789397232847, 0.07825596711344804, 0.16474733296326935, 0.2757736083579289, 0.3596859748134788, 0.36494552473587105, 0.2881337393782426, 0.17771884873909444, 0.08878387834279089, 0.04711262430632193, 0.05452618484598633, 0.10882753749420446, 0.20651111975812775, 0.32819817410060065, 0.42923581046086157, 0.45751273817091614, 0.3935791212523022, 0.2728748572839431, 0.16192865233380185, 0.11830896388699873, 0.1755399689152917, 0.339113987512418, 0.5644621151993802, 0.7520655620838338, 0.8128466446424488, 0.7494331934497795, 0.638116644835543, 0.5315330541247103, 0.42157112226872295, 0.29393728417542636, 0.16918389824361008, 0.07956107651129743, 0.038062805553060866, 0.04274447462835719, 0.0935778095935619, 0.1879957861294737, 0.2983052734678146, 0.36879396793245184, 0.35569375668894776, 0.27170999671300755, 0.17925478511626888, 0.1420278638410219, 0.1880894582069963, 0.3040157598453784, 0.4517273136405721, 0.5998276220510339, 0.7364146089380845, 0.8359845550670986, 0.8380054827039869, 0.7025766136706817, 0.4747535850657432, 0.2535715670948274, 0.10608106793916168, 0.0346205596739267, 0.008799054848627133, 0.0017402922775102889, 0.0002677663112353215, 3.204640219607548e-05, 2.9830988653533308e-06, 2.1597855202443396e-07, 1.2161966456431326e-08, 5.326541430950186e-10, 1.8144422949279588e-11, 5.025574151003588e-13, 1.019240953194861e-12, 3.624653569676473e-11, 1.0124594325877899e-09, 2.1998782554597503e-08, 3.7184908936641953e-07, 4.890417850484195e-06, 5.0054330305230174e-05, 0.0003988658033110143, 0.002476202918886383, 0.01198919368876931, 0.04535412900624495, 0.13445125444455247, 0.3139175597425567, 0.5821986853657524, 0.870274386053117, 1.0746688040915813, 1.140483718514341, 1.098339434042364, 1.0121655034361552, 0.9105631457976313, 0.7787698612108, 0.6020124447307209, 0.40099324272135, 0.22214096786942122, 0.0999262704990351, 0.035933318996808856, 0.010241115589531394, 0.0024175262183782024, 0.0011948302519555116, 0.003935461192013182, 0.015341692720869509, 0.04944713955974771, 0.13079895535463523, 0.28395084431875794, 0.5033339430645178, 0.7222865001748214, 0.831061957910788, 0.7600802837549215, 0.548781208659868, 0.3112253646711716, 0.13816071023670035, 0.04789914592200409, 0.012949524909530451, 0.0027275207769784505, 0.00044924875371802806, 7.808055571336837e-05, 0.00017589240814956257, 0.0010733944597281042, 0.005260060830368095, 0.020055917234184283, 0.05947659027616355, 0.13718619047474961, 0.24614580311109227, 0.3437822437066086, 0.3750317973240943, 0.3250695576524678, 0.24211424743703489, 0.19872027607262216, 0.23162671075483526, 0.3130398693372119, 0.3722276702808618, 0.35368181264339077, 0.2627948429489431, 0.15204608123391541, 0.06857910131080179, 0.025080839911206257, 0.01273757471449168, 0.028077486168343845, 0.08998085870104583, 0.23672893985678384, 0.49073699006384575, 0.8017852012447526, 1.0350321883007774, 1.0583309539265415, 0.8590012748869165, 0.5542724348264941, 0.28452621785385745, 0.11639066632245805, 0.039328525960521755, 0.017714219416570115, 0.03219110209075978, 0.09111255614140128, 0.22111624204247032, 0.443348738200705, 0.7433920441323366, 1.0519489887593927, 1.2565112456442087, 1.257729689103178, 1.047559736147274, 0.7368042099981987, 0.4896269224051276, 0.41920108684054685, 0.5229734091773669, 0.6874647418497972, 0.7686305789162479, 0.7126042260237982, 0.605103880380688, 0.5776830518736371, 0.6627469978960403, 0.7571622409301079, 0.7338238984790169, 0.5753211605749752, 0.3869357831935864, 0.2994110676307923, 0.3786998024218264, 0.5963048405814859, 0.8432364973896506, 0.9868575923789872, 0.9555469529576968, 0.786049357777021, 0.5979550764606821, 0.525346497030267, 0.6380848605195061, 0.8790313207649693, 1.0778862693654092, 1.0762928193503578, 0.8662836239035078, 0.5909948904446871, 0.4100616129771773, 0.3795860342480139, 0.44158811810655135, 0.49543975274354507, 0.4858089424469907, 0.4462978040206836, 0.45921163444801805, 0.5625081415597966, 0.6987342713343945, 0.7660284959241608, 0.7176468924353345, 0.5951422299641208, 0.46500469462250293, 0.3539780393211772, 0.26031049743240053, 0.19712605395641863, 0.19356344326824584, 0.2554747440552593, 0.3392812522222545, 0.3760639305799232, 0.3294031995915125, 0.22531155221861635, 0.12077190102585884, 0.05419422442457581, 0.03275181958724257, 0.0514569566867269, 0.1050943467937798, 0.17843981724888847, 0.2370987484584154, 0.24516130352197874, 0.19717082218763765, 0.12333382402351228, 0.06000243381293818, 0.022704006602530212, 0.006681640381932781, 0.0015293632299829144, 0.0002722608182416309, 3.769698892916847e-05, 4.059687541348504e-06, 3.4390704199635805e-07, 9.398149835929526e-08, 1.0306535432902431e-06, 1.1476418494939908e-05, 9.949855746854474e-05, 0.0006709278311943999, 0.0035186963487896144, 0.014352737011807117, 0.045533875919509054, 0.1123521745461226, 0.2156132533059341, 0.32182354354572157, 0.37361178286894914, 0.3374395628631359, 0.2376801049435559, 0.1334877585690587, 0.07131375009918793, 0.06877236511911027, 0.12665309998366023, 0.23038775420409208, 0.33873077484411923, 0.3968508803319188, 0.3798193041309374, 0.3130358367612443, 0.23894813241449753, 0.179089960848818, 0.1396793437616758, 0.1350784637135335, 0.18301741293804208, 0.2741490334777402, 0.3587648034210735, 0.3828401269638318, 0.3478168778992322, 0.3248740482772914, 0.3940062375238725, 0.5597354868100504, 0.7297809569976484, 0.7991590091484838, 0.7675352002925397, 0.7437846370250892, 0.8097114045139737, 0.9104566895602078, 0.9211944558658894, 0.8037214555170098, 0.6436280491201778, 0.5344094467164217, 0.4859680208178584, 0.46923819953031964, 0.49480299796198046, 0.5910161420810977, 0.7189795085741317, 0.7690647782757248, 0.6678902750229337, 0.45726271750973424, 0.24448820286910508, 0.10179663766086482, 0.032977418302567785, 0.008309883637751047 ] } ], "layout": { "hovermode": false, "template": { "data": { "bar": [ { "error_x": { "color": "#2a3f5f" }, "error_y": { "color": "#2a3f5f" }, "marker": { "line": { "color": "#E5ECF6", "width": 0.5 }, "pattern": { "fillmode": "overlay", "size": 10, "solidity": 0.2 } }, "type": "bar" } ], "barpolar": [ { "marker": { "line": { "color": "#E5ECF6", "width": 0.5 }, "pattern": { "fillmode": "overlay", "size": 10, "solidity": 0.2 } }, "type": "barpolar" } ], "carpet": [ { "aaxis": { "endlinecolor": "#2a3f5f", "gridcolor": "white", "linecolor": "white", "minorgridcolor": "white", "startlinecolor": "#2a3f5f" }, "baxis": { "endlinecolor": "#2a3f5f", "gridcolor": "white", "linecolor": "white", "minorgridcolor": "white", "startlinecolor": "#2a3f5f" }, "type": "carpet" } ], "choropleth": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "type": "choropleth" } ], "contour": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0.0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1.0, "#f0f921" ] ], "type": "contour" } ], "contourcarpet": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "type": "contourcarpet" } ], "heatmap": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0.0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1.0, "#f0f921" ] ], "type": "heatmap" } ], "heatmapgl": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0.0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1.0, "#f0f921" ] ], "type": "heatmapgl" } ], "histogram": [ { "marker": { "pattern": { "fillmode": "overlay", "size": 10, "solidity": 0.2 } }, "type": "histogram" } ], "histogram2d": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0.0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1.0, "#f0f921" ] ], "type": "histogram2d" } ], "histogram2dcontour": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0.0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1.0, "#f0f921" ] ], "type": "histogram2dcontour" } ], "mesh3d": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "type": "mesh3d" } ], "parcoords": [ { "line": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "parcoords" } ], "pie": [ { "automargin": true, "type": "pie" } ], "scatter": [ { "fillpattern": { "fillmode": "overlay", "size": 10, "solidity": 0.2 }, "type": "scatter" } ], "scatter3d": [ { "line": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scatter3d" } ], "scattercarpet": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scattercarpet" } ], "scattergeo": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scattergeo" } ], "scattergl": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scattergl" } ], "scattermapbox": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scattermapbox" } ], "scatterpolar": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scatterpolar" } ], "scatterpolargl": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scatterpolargl" } ], "scatterternary": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scatterternary" } ], "surface": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0.0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1.0, "#f0f921" ] ], "type": "surface" } ], "table": [ { "cells": { "fill": { "color": "#EBF0F8" }, "line": { "color": "white" } }, "header": { "fill": { "color": "#C8D4E3" }, "line": { "color": "white" } }, "type": "table" } ] }, "layout": { "annotationdefaults": { "arrowcolor": "#2a3f5f", "arrowhead": 0, "arrowwidth": 1 }, "autotypenumbers": "strict", "coloraxis": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "colorscale": { "diverging": [ [ 0, "#8e0152" ], [ 0.1, "#c51b7d" ], [ 0.2, "#de77ae" ], [ 0.3, "#f1b6da" ], [ 0.4, "#fde0ef" ], [ 0.5, "#f7f7f7" ], [ 0.6, "#e6f5d0" ], [ 0.7, "#b8e186" ], [ 0.8, "#7fbc41" ], [ 0.9, "#4d9221" ], [ 1, "#276419" ] ], "sequential": [ [ 0.0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1.0, "#f0f921" ] ], "sequentialminus": [ [ 0.0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1.0, "#f0f921" ] ] }, "colorway": [ "#636efa", "#EF553B", "#00cc96", "#ab63fa", "#FFA15A", "#19d3f3", "#FF6692", "#B6E880", "#FF97FF", "#FECB52" ], "font": { "color": "#2a3f5f" }, "geo": { "bgcolor": "white", "lakecolor": "white", "landcolor": "#E5ECF6", "showlakes": true, "showland": true, "subunitcolor": "white" }, "hoverlabel": { "align": "left" }, "hovermode": "closest", "mapbox": { "style": "light" }, "paper_bgcolor": "white", "plot_bgcolor": "#E5ECF6", "polar": { "angularaxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" }, "bgcolor": "#E5ECF6", "radialaxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" } }, "scene": { "xaxis": { "backgroundcolor": "#E5ECF6", "gridcolor": "white", "gridwidth": 2, "linecolor": "white", "showbackground": true, "ticks": "", "zerolinecolor": "white" }, "yaxis": { "backgroundcolor": "#E5ECF6", "gridcolor": "white", "gridwidth": 2, "linecolor": "white", "showbackground": true, "ticks": "", "zerolinecolor": "white" }, "zaxis": { "backgroundcolor": "#E5ECF6", "gridcolor": "white", "gridwidth": 2, "linecolor": "white", "showbackground": true, "ticks": "", "zerolinecolor": "white" } }, "shapedefaults": { "line": { "color": "#2a3f5f" } }, "ternary": { "aaxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" }, "baxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" }, "bgcolor": "#E5ECF6", "caxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" } }, "title": { "x": 0.05 }, "xaxis": { "automargin": true, "gridcolor": "white", "linecolor": "white", "ticks": "", "title": { "standoff": 15 }, "zerolinecolor": "white", "zerolinewidth": 2 }, "yaxis": { "automargin": true, "gridcolor": "white", "linecolor": "white", "ticks": "", "title": { "standoff": 15 }, "zerolinecolor": "white", "zerolinewidth": 2 } } }, "xaxis": { "title": { "text": "Energy (eV)" } }, "yaxis": { "title": { "text": "DOS (states/eV)" } } } }, "text/html": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "edos.plotly();" ] }, { "cell_type": "markdown", "id": "67208acf", "metadata": {}, "source": [ "where the zero of the energy axis is set to the Fermi level $\\epsilon_F$ obtained by solving:\n", "\n", "$$\\int_{-\\infty}^{\\epsilon_F} g(\\epsilon)\\,d\\epsilon = N$$\n", "\n", "for $\\epsilon_F$ with $N$ the number of electrons per unit cell.\n", "Note that the DOS is highly sensitive to the sampling of the IBZ and to the value of the broadening,\n", "especially in metallic systems." ] }, { "cell_type": "code", "execution_count": 40, "id": "1abb357d", "metadata": {}, "outputs": [ { "data": { "application/vnd.plotly.v1+json": { "config": { "plotlyServerURL": "https://chart-studio.plotly.com", "responsive": true, "showLink": true }, "data": [ { "legendgroup": "", "line": { "color": "black", "width": 1.0 }, "mode": "lines", "name": "", "showlegend": false, "type": "scatter", "x": [ -12.44652085384753, -12.396387613682947, -12.346254373518363, -12.29612113335378, -12.245987893189199, -12.195854653024615, -12.14572141286003, -12.09558817269545, -12.045454932530866, -11.995321692366282, -11.9451884522017, -11.895055212037118, -11.844921971872534, -11.794788731707952, -11.74465549154337, -11.694522251378785, -11.644389011214201, -11.594255771049621, -11.544122530885037, -11.493989290720453, -11.44385605055587, -11.393722810391289, -11.343589570226705, -11.293456330062122, -11.24332308989754, -11.193189849732956, -11.143056609568372, -11.092923369403792, -11.042790129239208, -10.992656889074624, -10.942523648910042, -10.89239040874546, -10.842257168580876, -10.792123928416293, -10.741990688251711, -10.691857448087127, -10.641724207922543, -10.591590967757963, -10.541457727593379, -10.491324487428795, -10.441191247264214, -10.39105800709963, -10.340924766935046, -10.290791526770464, -10.240658286605882, -10.190525046441298, -10.140391806276714, -10.090258566112134, -10.04012532594755, -9.989992085782967, -9.939858845618383, -9.889725605453801, -9.839592365289217, -9.789459125124635, -9.739325884960053, -9.689192644795469, -9.639059404630887, -9.588926164466304, -9.53879292430172, -9.488659684137138, -9.438526443972554, -9.388393203807972, -9.338259963643388, -9.288126723478806, -9.237993483314224, -9.18786024314964, -9.137727002985057, -9.087593762820475, -9.037460522655891, -8.987327282491309, -8.937194042326727, -8.887060802162143, -8.836927561997559, -8.786794321832977, -8.736661081668395, -8.68652784150381, -8.636394601339228, -8.586261361174646, -8.536128121010062, -8.48599488084548, -8.435861640680898, -8.385728400516314, -8.33559516035173, -8.28546192018715, -8.235328680022565, -8.185195439857981, -8.1350621996934, -8.084928959528817, -8.034795719364233, -7.984662479199651, -7.934529239035068, -7.884395998870485, -7.8342627587059015, -7.784129518541319, -7.733996278376736, -7.683863038212153, -7.63372979804757, -7.583596557882987, -7.533463317718405, -7.483330077553822, -7.4331968373892385, -7.383063597224655, -7.332930357060073, -7.28279711689549, -7.232663876730907, -7.182530636566324, -7.132397396401741, -7.082264156237159, -7.032130916072576, -6.9819976759079925, -6.931864435743409, -6.881731195578826, -6.831597955414244, -6.781464715249661, -6.731331475085078, -6.681198234920495, -6.631064994755912, -6.5809317545913295, -6.530798514426746, -6.480665274262163, -6.43053203409758, -6.380398793932998, -6.330265553768415, -6.280132313603832, -6.229999073439249, -6.179865833274666, -6.1297325931100834, -6.0795993529455, -6.029466112780917, -5.979332872616334, -5.929199632451751, -5.879066392287169, -5.828933152122586, -5.778799911958003, -5.72866667179342, -5.6785334316288365, -5.628400191464254, -5.578266951299671, -5.528133711135088, -5.478000470970505, -5.427867230805923, -5.37773399064134, -5.327600750476757, -5.2774675103121735, -5.2273342701475904, -5.177201029983008, -5.127067789818425, -5.076934549653842, -5.026801309489259, -4.976668069324676, -4.926534829160094, -4.876401588995511, -4.8262683488309275, -4.776135108666344, -4.726001868501761, -4.675868628337179, -4.625735388172596, -4.575602148008013, -4.52546890784343, -4.475335667678848, -4.4252024275142645, -4.3750691873496805, -4.324935947185098, -4.274802707020516, -4.224669466855932, -4.17453622669135, -4.124402986526768, -4.074269746362184, -4.0241365061976015, -3.9740032660330176, -3.9238700258684354, -3.873736785703853, -3.823603545539269, -3.773470305374687, -3.723337065210103, -3.673203825045521, -3.6230705848809386, -3.5729373447163546, -3.5228041045517724, -3.4726708643871884, -3.422537624222606, -3.372404384058024, -3.32227114389344, -3.272137903728858, -3.222004663564274, -3.1718714233996916, -3.1217381832351094, -3.0716049430705255, -3.0214717029059432, -2.9713384627413593, -2.921205222576777, -2.871071982412195, -2.820938742247611, -2.7708055020830287, -2.7206722619184447, -2.6705390217538625, -2.6204057815892803, -2.5702725414246963, -2.520139301260114, -2.47000606109553, -2.419872820930948, -2.3697395807663657, -2.3196063406017817, -2.2694731004371995, -2.2193398602726173, -2.1692066201080333, -2.119073379943451, -2.068940139778867, -2.018806899614285, -1.9686736594497027, -1.9185404192851188, -1.8684071791205366, -1.8182739389559526, -1.7681406987913704, -1.7180074586267882, -1.6678742184622042, -1.617740978297622, -1.567607738133038, -1.5174744979684558, -1.4673412578038736, -1.4172080176392896, -1.3670747774747074, -1.3169415373101234, -1.2668082971455412, -1.216675056980959, -1.166541816816375, -1.1164085766517928, -1.0662753364872088, -1.0161420963226266, -0.9660088561580444, -0.9158756159934605, -0.8657423758288783, -0.8156091356642943, -0.7654758954997121, -0.7153426553351299, -0.6652094151705459, -0.6150761750059637, -0.5649429348413797, -0.5148096946767975, -0.4646764545122153, -0.4145432143476313, -0.3644099741830491, -0.3142767340184669, -0.2641434938538829, -0.2140102536893007, -0.16387701352471673, -0.11374377336013453, -0.06361053319555232, -0.01347729303096834, 0.036655947133613864, 0.08678918729819785, 0.13692242746278005, 0.18705566762736225, 0.23718890779194624, 0.28732214795652844, 0.3374553881211124, 0.3875886282856946, 0.43772186845027683, 0.4878551086148608, 0.537988348779443, 0.588121588944027, 0.6382548291086092, 0.6883880692731914, 0.7385213094377754, 0.7886545496023576, 0.8387877897669416, 0.8889210299315238, 0.939054270096106, 0.98918751026069, 1.0393207504252722, 1.0894539905898561, 1.1395872307544384, 1.1897204709190206, 1.2398537110836045, 1.2899869512481867, 1.340120191412769, 1.390253431577353, 1.4403866717419351, 1.4905199119065191, 1.5406531520711013, 1.5907863922356835, 1.6409196324002675, 1.6910528725648497, 1.7411861127294337, 1.791319352894016, 1.841452593058598, 1.891585833223182, 1.9417190733877634, 1.9918523135523474, 2.0419855537169314, 2.092118793881512, 2.1422520340460958, 2.1923852742106797, 2.2425185143752637, 2.292651754539844, 2.342784994704428, 2.392918234869012, 2.4430514750335925, 2.4931847151981765, 2.5433179553627605, 2.593451195527341 ], "xaxis": "x", "y": [ 0.0, 0.00034495769955658834, 0.0014708572395418353, 0.0043625228347537485, 0.010214885754234664, 0.019559918498245517, 0.031343779885738034, 0.04308365401113366, 0.05232598862708658, 0.05808551901967782, 0.061000923934477196, 0.06256182346631142, 0.06466287621261359, 0.06995421431154127, 0.08205354870502418, 0.10414626511665659, 0.13602057256441044, 0.1723484622834462, 0.20506387973060886, 0.22835053588483956, 0.24151640160411744, 0.24777364342020047, 0.25155643143068596, 0.25730991564071404, 0.26949245844424635, 0.2915772005930302, 0.32343484849104825, 0.35976297348877717, 0.39250395308311925, 0.4158586527644983, 0.4292192979858108, 0.43603222999064567, 0.44112771281992047, 0.4493171642137799, 0.4651261128509882, 0.491932822298242, 0.5299054421550795, 0.5743610201092311, 0.6170290126998169, 0.6504405100644164, 0.6722386188364861, 0.686287838553634, 0.7010194376739174, 0.7268207080731607, 0.7721199058373892, 0.8381217040659481, 0.9165758235622459, 0.9948979738896082, 1.0644603431726947, 1.1230986724391008, 1.1708808730161, 1.2067516277961423, 1.2299693932596616, 1.2424397848187825, 1.2483366511474054, 1.2523877819317872, 1.2592220597464692, 1.2733382564448574, 1.2977181042579395, 1.33116195074067, 1.367482867835407, 1.3989366508848677, 1.4215449765980837, 1.4376519167989728, 1.454201767787695, 1.4788725968705594, 1.5167604458763504, 1.5694783020136305, 1.6364684546978656, 1.7152979196215272, 1.799220464218224, 1.876454836449032, 1.9354782140553017, 1.9719915138264739, 1.990022065754458, 1.9970758942431326, 1.9992526602058454, 1.999781031826498, 1.999881702309992, 1.9998967328927588, 1.9998984890351483, 1.9998986494152649, 1.9998986608526883, 1.9998986614891108, 1.999898661516724, 1.9998986615176588, 1.9998986615177352, 1.9998986615196035, 1.9998986615721785, 1.9998986627258066, 1.9998986824706766, 1.9998989462851688, 1.999901700843424, 1.9999242066642973, 2.000068343175037, 2.0007935403772446, 2.003668346945749, 2.0126825734171727, 2.035160754861124, 2.0800859657925233, 2.152903147114555, 2.2504094511725494, 2.3614622245895323, 2.4737016833826866, 2.5795081342818356, 2.6759007514251976, 2.7605924887835087, 2.829815579742281, 2.880099504757758, 2.9113392417920734, 2.9274855160023434, 2.9342965974312003, 2.936611471449781, 2.9372460901796944, 2.9374271893141817, 2.9376843874472565, 2.9386508136340606, 2.9418988877227674, 2.9509352084878384, 2.9717279598030775, 3.0111970971268858, 3.0726414211584254, 3.150515812466916, 3.2302849286043562, 3.2959023961457614, 3.3390173122296867, 3.361546492249662, 3.370874275703454, 3.373924816731947, 3.37471075782842, 3.3748700195782497, 3.3748964563051653, 3.374909188792758, 3.3749718195913396, 3.3752893362264698, 3.376558508234781, 3.380545730534689, 3.3904050729535093, 3.4096227478507166, 3.4391977523016517, 3.4752342292543177, 3.510332578622908, 3.538767340540922, 3.560867803580871, 3.5824424924255966, 3.6097483928949727, 3.6441030750356385, 3.6804952694808284, 3.711401241711498, 3.7321985613936546, 3.7432592166565235, 3.747954692983607, 3.749850652646681, 3.7518968438962523, 3.7578154912530226, 3.7741945120482447, 3.8106647362245076, 3.8754630616594348, 3.9675486689880035, 4.07249574614897, 4.16861782325137, 4.239469813558725, 4.281521507863277, 4.301620770303725, 4.309427477968682, 4.312287215622319, 4.3147891310909365, 4.3209707430022615, 4.336623784327912, 4.369935566763399, 4.429430727417206, 4.519436990596495, 4.6351675819382425, 4.761214626551557, 4.876786254956514, 4.9662422012096465, 5.027727167715743, 5.073289660571557, 5.120523920857368, 5.181207107387188, 5.254205883805676, 5.328464984021874, 5.394525960987069, 5.453822902325305, 5.516009679917775, 5.587194330799755, 5.661942297008816, 5.727573980664648, 5.775815039126634, 5.810223830635219, 5.84421972574178, 5.893099867671048, 5.965268739294402, 6.057017285820555, 6.154396319388699, 6.241708185504513, 6.311092812194999, 6.367407559756075, 6.425734143419124, 6.5017920932930355, 6.5998987128213376, 6.707894690433446, 6.805282341801155, 6.878340435547659, 6.928526641652025, 6.968114236795763, 7.009282357792702, 7.056258601082939, 7.105451777580109, 7.1521813089598005, 7.19757743110985, 7.248799554021353, 7.312029722812737, 7.385463026407848, 7.459844480978754, 7.525658853337459, 7.578807453717504, 7.61986571180895, 7.650661986552367, 7.6735947630432015, 7.6931812934373465, 7.715693032725504, 7.745510077926211, 7.781372649776209, 7.816740002841312, 7.8445496507166474, 7.861899935595141, 7.870671554383015, 7.8750304412888195, 7.879252100093728, 7.887100524189195, 7.901315010530011, 7.922147305242262, 7.94632456424998, 7.96850010694069, 7.984568043343058, 7.993759283988049, 7.9979056258285555, 7.999378823526219, 7.9997904677422875, 7.999880788993384, 7.9998963281825715, 7.9998984215800615, 7.999898642346526, 7.999898664299297, 7.999898720680896, 7.999899347700943, 7.999904911236065, 7.999943535207237, 8.000153574642452, 8.001049527503204, 8.004051837451932, 8.011967176738564, 8.02840914629875, 8.055352594308598, 8.09021702054668, 8.125864328431616, 8.154696940861143, 8.173304788503996, 8.18357215172413, 8.190595122582092, 8.200392434358365, 8.218292049249927, 8.246823805148816, 8.283700896928417, 8.322637889814766, 8.357372962992379, 8.385045707886066, 8.406003312013581, 8.421984250118715, 8.435758749267965, 8.451705926247502, 8.474625161500853, 8.506355182889589, 8.543534240971814, 8.580164444074548, 8.613888619833093, 8.649928417850745, 8.697742580771763, 8.762390218345352, 8.839040932865384, 8.917584389931754, 8.993351750301496, 9.071233540446704, 9.157471140630376, 9.249297747401755, 9.335773371050827, 9.408333691368892, 9.467392528070553, 9.518547356708979, 9.566434939560395, 9.61476544844283, 9.669201080165912, 9.734875406734771, 9.809475888342947, 9.881515101135681, 9.937922666332222, 9.97310371375929, 9.990464094834934, 9.997220754950504, 9.999290621174426 ], "yaxis": "y" }, { "legendgroup": "", "line": { "color": "black", "width": 1.0 }, "mode": "lines", "name": "", "showlegend": false, "type": "scatter", "x": [ -12.44652085384753, -12.396387613682947, -12.346254373518363, -12.29612113335378, -12.245987893189199, -12.195854653024615, -12.14572141286003, -12.09558817269545, -12.045454932530866, -11.995321692366282, -11.9451884522017, -11.895055212037118, -11.844921971872534, -11.794788731707952, -11.74465549154337, -11.694522251378785, -11.644389011214201, -11.594255771049621, -11.544122530885037, -11.493989290720453, -11.44385605055587, -11.393722810391289, -11.343589570226705, -11.293456330062122, -11.24332308989754, -11.193189849732956, -11.143056609568372, -11.092923369403792, -11.042790129239208, -10.992656889074624, -10.942523648910042, -10.89239040874546, -10.842257168580876, -10.792123928416293, -10.741990688251711, -10.691857448087127, -10.641724207922543, -10.591590967757963, -10.541457727593379, -10.491324487428795, -10.441191247264214, -10.39105800709963, -10.340924766935046, -10.290791526770464, -10.240658286605882, -10.190525046441298, -10.140391806276714, -10.090258566112134, -10.04012532594755, -9.989992085782967, -9.939858845618383, -9.889725605453801, -9.839592365289217, -9.789459125124635, -9.739325884960053, -9.689192644795469, -9.639059404630887, -9.588926164466304, -9.53879292430172, -9.488659684137138, -9.438526443972554, -9.388393203807972, -9.338259963643388, -9.288126723478806, -9.237993483314224, -9.18786024314964, -9.137727002985057, -9.087593762820475, -9.037460522655891, -8.987327282491309, -8.937194042326727, -8.887060802162143, -8.836927561997559, -8.786794321832977, -8.736661081668395, -8.68652784150381, -8.636394601339228, -8.586261361174646, -8.536128121010062, -8.48599488084548, -8.435861640680898, -8.385728400516314, -8.33559516035173, -8.28546192018715, -8.235328680022565, -8.185195439857981, -8.1350621996934, -8.084928959528817, -8.034795719364233, -7.984662479199651, -7.934529239035068, -7.884395998870485, -7.8342627587059015, -7.784129518541319, -7.733996278376736, -7.683863038212153, -7.63372979804757, -7.583596557882987, -7.533463317718405, -7.483330077553822, -7.4331968373892385, -7.383063597224655, -7.332930357060073, -7.28279711689549, -7.232663876730907, -7.182530636566324, -7.132397396401741, -7.082264156237159, -7.032130916072576, -6.9819976759079925, -6.931864435743409, -6.881731195578826, -6.831597955414244, -6.781464715249661, -6.731331475085078, -6.681198234920495, -6.631064994755912, -6.5809317545913295, -6.530798514426746, -6.480665274262163, -6.43053203409758, -6.380398793932998, -6.330265553768415, -6.280132313603832, -6.229999073439249, -6.179865833274666, -6.1297325931100834, -6.0795993529455, -6.029466112780917, -5.979332872616334, -5.929199632451751, -5.879066392287169, -5.828933152122586, -5.778799911958003, -5.72866667179342, -5.6785334316288365, -5.628400191464254, -5.578266951299671, -5.528133711135088, -5.478000470970505, -5.427867230805923, -5.37773399064134, -5.327600750476757, -5.2774675103121735, -5.2273342701475904, -5.177201029983008, -5.127067789818425, -5.076934549653842, -5.026801309489259, -4.976668069324676, -4.926534829160094, -4.876401588995511, -4.8262683488309275, -4.776135108666344, -4.726001868501761, -4.675868628337179, -4.625735388172596, -4.575602148008013, -4.52546890784343, -4.475335667678848, -4.4252024275142645, -4.3750691873496805, -4.324935947185098, -4.274802707020516, -4.224669466855932, -4.17453622669135, -4.124402986526768, -4.074269746362184, -4.0241365061976015, -3.9740032660330176, -3.9238700258684354, -3.873736785703853, -3.823603545539269, -3.773470305374687, -3.723337065210103, -3.673203825045521, -3.6230705848809386, -3.5729373447163546, -3.5228041045517724, -3.4726708643871884, -3.422537624222606, -3.372404384058024, -3.32227114389344, -3.272137903728858, -3.222004663564274, -3.1718714233996916, -3.1217381832351094, -3.0716049430705255, -3.0214717029059432, -2.9713384627413593, -2.921205222576777, -2.871071982412195, -2.820938742247611, -2.7708055020830287, -2.7206722619184447, -2.6705390217538625, -2.6204057815892803, -2.5702725414246963, -2.520139301260114, -2.47000606109553, -2.419872820930948, -2.3697395807663657, -2.3196063406017817, -2.2694731004371995, -2.2193398602726173, -2.1692066201080333, -2.119073379943451, -2.068940139778867, -2.018806899614285, -1.9686736594497027, -1.9185404192851188, -1.8684071791205366, -1.8182739389559526, -1.7681406987913704, -1.7180074586267882, -1.6678742184622042, -1.617740978297622, -1.567607738133038, -1.5174744979684558, -1.4673412578038736, -1.4172080176392896, -1.3670747774747074, -1.3169415373101234, -1.2668082971455412, -1.216675056980959, -1.166541816816375, -1.1164085766517928, -1.0662753364872088, -1.0161420963226266, -0.9660088561580444, -0.9158756159934605, -0.8657423758288783, -0.8156091356642943, -0.7654758954997121, -0.7153426553351299, -0.6652094151705459, -0.6150761750059637, -0.5649429348413797, -0.5148096946767975, -0.4646764545122153, -0.4145432143476313, -0.3644099741830491, -0.3142767340184669, -0.2641434938538829, -0.2140102536893007, -0.16387701352471673, -0.11374377336013453, -0.06361053319555232, -0.01347729303096834, 0.036655947133613864, 0.08678918729819785, 0.13692242746278005, 0.18705566762736225, 0.23718890779194624, 0.28732214795652844, 0.3374553881211124, 0.3875886282856946, 0.43772186845027683, 0.4878551086148608, 0.537988348779443, 0.588121588944027, 0.6382548291086092, 0.6883880692731914, 0.7385213094377754, 0.7886545496023576, 0.8387877897669416, 0.8889210299315238, 0.939054270096106, 0.98918751026069, 1.0393207504252722, 1.0894539905898561, 1.1395872307544384, 1.1897204709190206, 1.2398537110836045, 1.2899869512481867, 1.340120191412769, 1.390253431577353, 1.4403866717419351, 1.4905199119065191, 1.5406531520711013, 1.5907863922356835, 1.6409196324002675, 1.6910528725648497, 1.7411861127294337, 1.791319352894016, 1.841452593058598, 1.891585833223182, 1.9417190733877634, 1.9918523135523474, 2.0419855537169314, 2.092118793881512, 2.1422520340460958, 2.1923852742106797, 2.2425185143752637, 2.292651754539844, 2.342784994704428, 2.392918234869012, 2.4430514750335925, 2.4931847151981765, 2.5433179553627605, 2.593451195527341 ], "xaxis": "x2", "y": [ 0.0027699052574620933, 0.010991730672077751, 0.03392455785381908, 0.08143465634094976, 0.15203770252786125, 0.22077014764627154, 0.24933157922424856, 0.21901533339719162, 0.14969550937343865, 0.08007341733798869, 0.03623284594076028, 0.02603719791477041, 0.05778155145808582, 0.15330945648621114, 0.32937765305475825, 0.5519823523669515, 0.7196014249078969, 0.7296521880552819, 0.5754865717679726, 0.35350409700917457, 0.17173088385603563, 0.0778935886712157, 0.07301578794465693, 0.15651193422689608, 0.3294946659265387, 0.5515472167158578, 0.7193719496269576, 0.7298910494717421, 0.5762674787564852, 0.3554376974781889, 0.17756775668558178, 0.09422524861264386, 0.10905236969197266, 0.21765507498840891, 0.4130222395162555, 0.6563963482012013, 0.8584716209217231, 0.9150254763418323, 0.7871582425046044, 0.5457497145678862, 0.3238573046676037, 0.23661792777399746, 0.3510799378305834, 0.678227975024836, 1.1289242303987603, 1.5041311241676676, 1.6256932892848976, 1.498866386899559, 1.276233289671086, 1.0630661082494206, 0.8431422445374459, 0.5878745683508527, 0.33836779648722015, 0.15912215302259486, 0.07612561110612173, 0.08548894925671438, 0.1871556191871238, 0.3759915722589474, 0.5966105469356292, 0.7375879358649037, 0.7113875133778955, 0.5434199934260151, 0.35850957023253777, 0.2840557276820438, 0.3761789164139926, 0.6080315196907567, 0.9034546272811442, 1.1996552441020678, 1.472829217876169, 1.6719691101341971, 1.6760109654079738, 1.4051532273413634, 0.9495071701314864, 0.5071431341896548, 0.21216213587832336, 0.0692411193478534, 0.017598109697254265, 0.0034805845550205778, 0.000535532622470643, 6.409280439215096e-05, 5.9661977307066616e-06, 4.319571040488679e-07, 2.4323932912862652e-08, 1.0653082861900373e-09, 3.6288845898559175e-11, 1.0051148302007177e-12, 2.038481906389722e-12, 7.249307139352947e-11, 2.0249188651755797e-09, 4.3997565109195006e-08, 7.436981787328391e-07, 9.78083570096839e-06, 0.00010010866061046035, 0.0007977316066220286, 0.004952405837772766, 0.02397838737753862, 0.0907082580124899, 0.26890250888910494, 0.6278351194851134, 1.1643973707315047, 1.740548772106234, 2.1493376081831626, 2.280967437028682, 2.196678868084728, 2.0243310068723104, 1.8211262915952626, 1.5575397224216, 1.2040248894614418, 0.8019864854427, 0.44428193573884245, 0.1998525409980702, 0.07186663799361771, 0.02048223117906279, 0.004835052436756405, 0.002389660503911023, 0.007870922384026363, 0.030683385441739017, 0.09889427911949542, 0.26159791070927046, 0.5679016886375159, 1.0066678861290357, 1.4445730003496429, 1.662123915821576, 1.520160567509843, 1.097562417319736, 0.6224507293423432, 0.2763214204734007, 0.09579829184400818, 0.025899049819060903, 0.005455041553956901, 0.0008984975074360561, 0.00015616111142673675, 0.00035178481629912514, 0.0021467889194562084, 0.01052012166073619, 0.040111834468368565, 0.1189531805523271, 0.27437238094949923, 0.49229160622218454, 0.6875644874132172, 0.7500635946481886, 0.6501391153049356, 0.48422849487406977, 0.3974405521452443, 0.4632534215096705, 0.6260797386744238, 0.7444553405617236, 0.7073636252867815, 0.5255896858978862, 0.30409216246783083, 0.13715820262160358, 0.050161679822412514, 0.02547514942898336, 0.05615497233668769, 0.17996171740209166, 0.4734578797135677, 0.9814739801276915, 1.6035704024895052, 2.0700643766015547, 2.116661907853083, 1.718002549773833, 1.1085448696529883, 0.5690524357077149, 0.2327813326449161, 0.07865705192104351, 0.03542843883314023, 0.06438220418151956, 0.18222511228280255, 0.44223248408494065, 0.88669747640141, 1.4867840882646732, 2.1038979775187854, 2.5130224912884174, 2.515459378206356, 2.095119472294548, 1.4736084199963975, 0.9792538448102552, 0.8384021736810937, 1.0459468183547338, 1.3749294836995944, 1.5372611578324957, 1.4252084520475965, 1.210207760761376, 1.1553661037472742, 1.3254939957920806, 1.5143244818602157, 1.4676477969580337, 1.1506423211499504, 0.7738715663871728, 0.5988221352615846, 0.7573996048436528, 1.1926096811629718, 1.6864729947793011, 1.9737151847579744, 1.9110939059153935, 1.572098715554042, 1.1959101529213643, 1.050692994060534, 1.2761697210390122, 1.7580626415299385, 2.1557725387308184, 2.1525856387007156, 1.7325672478070155, 1.1819897808893742, 0.8201232259543546, 0.7591720684960278, 0.8831762362131027, 0.9908795054870901, 0.9716178848939814, 0.8925956080413672, 0.9184232688960361, 1.1250162831195931, 1.397468542668789, 1.5320569918483216, 1.435293784870669, 1.1902844599282416, 0.9300093892450059, 0.7079560786423544, 0.5206209948648011, 0.39425210791283727, 0.3871268865364917, 0.5109494881105185, 0.678562504444509, 0.7521278611598464, 0.658806399183025, 0.4506231044372327, 0.2415438020517177, 0.10838844884915162, 0.06550363917448514, 0.1029139133734538, 0.2101886935875596, 0.35687963449777693, 0.4741974969168308, 0.49032260704395747, 0.3943416443752753, 0.24666764804702457, 0.12000486762587637, 0.045408013205060424, 0.013363280763865563, 0.0030587264599658288, 0.0005445216364832618, 7.539397785833693e-05, 8.119375082697008e-06, 6.878140839927161e-07, 1.8796299671859052e-07, 2.0613070865804862e-06, 2.2952836989879816e-05, 0.0001989971149370895, 0.0013418556623887997, 0.007037392697579229, 0.028705474023614234, 0.09106775183901811, 0.2247043490922452, 0.4312265066118682, 0.6436470870914431, 0.7472235657378983, 0.6748791257262718, 0.4753602098871118, 0.2669755171381174, 0.14262750019837586, 0.13754473023822053, 0.25330619996732046, 0.46077550840818415, 0.6774615496882385, 0.7937017606638376, 0.7596386082618748, 0.6260716735224886, 0.47789626482899505, 0.358179921697636, 0.2793586875233516, 0.270156927427067, 0.36603482587608416, 0.5482980669554804, 0.717529606842147, 0.7656802539276636, 0.6956337557984644, 0.6497480965545828, 0.788012475047745, 1.1194709736201007, 1.459561913995297, 1.5983180182969676, 1.5350704005850795, 1.4875692740501785, 1.6194228090279474, 1.8209133791204155, 1.8423889117317789, 1.6074429110340196, 1.2872560982403556, 1.0688188934328433, 0.9719360416357168, 0.9384763990606393, 0.9896059959239609, 1.1820322841621953, 1.4379590171482635, 1.5381295565514497, 1.3357805500458675, 0.9145254350194685, 0.48897640573821016, 0.20359327532172963, 0.06595483660513557, 0.016619767275502094 ], "yaxis": "y2" } ], "layout": { "hovermode": false, "template": { "data": { "bar": [ { "error_x": { "color": "#2a3f5f" }, "error_y": { "color": "#2a3f5f" }, "marker": { "line": { "color": "#E5ECF6", "width": 0.5 }, "pattern": { "fillmode": "overlay", "size": 10, "solidity": 0.2 } }, "type": "bar" } ], "barpolar": [ { "marker": { "line": { "color": "#E5ECF6", "width": 0.5 }, "pattern": { "fillmode": "overlay", "size": 10, "solidity": 0.2 } }, "type": "barpolar" } ], "carpet": [ { "aaxis": { "endlinecolor": "#2a3f5f", "gridcolor": "white", "linecolor": "white", "minorgridcolor": "white", "startlinecolor": "#2a3f5f" }, "baxis": { "endlinecolor": "#2a3f5f", "gridcolor": "white", "linecolor": "white", "minorgridcolor": "white", "startlinecolor": "#2a3f5f" }, "type": "carpet" } ], "choropleth": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "type": "choropleth" } ], "contour": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0.0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1.0, "#f0f921" ] ], "type": "contour" } ], "contourcarpet": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "type": "contourcarpet" } ], "heatmap": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0.0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1.0, "#f0f921" ] ], "type": "heatmap" } ], "heatmapgl": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0.0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1.0, "#f0f921" ] ], "type": "heatmapgl" } ], "histogram": [ { "marker": { "pattern": { "fillmode": "overlay", "size": 10, "solidity": 0.2 } }, "type": "histogram" } ], "histogram2d": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0.0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1.0, "#f0f921" ] ], "type": "histogram2d" } ], "histogram2dcontour": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0.0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1.0, "#f0f921" ] ], "type": "histogram2dcontour" } ], "mesh3d": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "type": "mesh3d" } ], "parcoords": [ { "line": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "parcoords" } ], "pie": [ { "automargin": true, "type": "pie" } ], "scatter": [ { "fillpattern": { "fillmode": "overlay", "size": 10, "solidity": 0.2 }, "type": "scatter" } ], "scatter3d": [ { "line": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scatter3d" } ], "scattercarpet": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scattercarpet" } ], "scattergeo": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scattergeo" } ], "scattergl": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scattergl" } ], "scattermapbox": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scattermapbox" } ], "scatterpolar": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scatterpolar" } ], "scatterpolargl": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scatterpolargl" } ], "scatterternary": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scatterternary" } ], "surface": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0.0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1.0, "#f0f921" ] ], "type": "surface" } ], "table": [ { "cells": { "fill": { "color": "#EBF0F8" }, "line": { "color": "white" } }, "header": { "fill": { "color": "#C8D4E3" }, "line": { "color": "white" } }, "type": "table" } ] }, "layout": { "annotationdefaults": { "arrowcolor": "#2a3f5f", "arrowhead": 0, "arrowwidth": 1 }, "autotypenumbers": "strict", "coloraxis": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "colorscale": { "diverging": [ [ 0, "#8e0152" ], [ 0.1, "#c51b7d" ], [ 0.2, "#de77ae" ], [ 0.3, "#f1b6da" ], [ 0.4, "#fde0ef" ], [ 0.5, "#f7f7f7" ], [ 0.6, "#e6f5d0" ], [ 0.7, "#b8e186" ], [ 0.8, "#7fbc41" ], [ 0.9, "#4d9221" ], [ 1, "#276419" ] ], "sequential": [ [ 0.0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1.0, "#f0f921" ] ], "sequentialminus": [ [ 0.0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1.0, "#f0f921" ] ] }, "colorway": [ "#636efa", "#EF553B", "#00cc96", "#ab63fa", "#FFA15A", "#19d3f3", "#FF6692", "#B6E880", "#FF97FF", "#FECB52" ], "font": { "color": "#2a3f5f" }, "geo": { "bgcolor": "white", "lakecolor": "white", "landcolor": "#E5ECF6", "showlakes": true, "showland": true, "subunitcolor": "white" }, "hoverlabel": { "align": "left" }, "hovermode": "closest", "mapbox": { "style": "light" }, "paper_bgcolor": "white", "plot_bgcolor": "#E5ECF6", "polar": { "angularaxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" }, "bgcolor": "#E5ECF6", "radialaxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" } }, "scene": { "xaxis": { "backgroundcolor": "#E5ECF6", "gridcolor": "white", "gridwidth": 2, "linecolor": "white", "showbackground": true, "ticks": "", "zerolinecolor": "white" }, "yaxis": { "backgroundcolor": "#E5ECF6", "gridcolor": "white", "gridwidth": 2, "linecolor": "white", "showbackground": true, "ticks": "", "zerolinecolor": "white" }, "zaxis": { "backgroundcolor": "#E5ECF6", "gridcolor": "white", "gridwidth": 2, "linecolor": "white", "showbackground": true, "ticks": "", "zerolinecolor": "white" } }, "shapedefaults": { "line": { "color": "#2a3f5f" } }, "ternary": { "aaxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" }, "baxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" }, "bgcolor": "#E5ECF6", "caxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" } }, "title": { "x": 0.05 }, "xaxis": { "automargin": true, "gridcolor": "white", "linecolor": "white", "ticks": "", "title": { "standoff": 15 }, "zerolinecolor": "white", "zerolinewidth": 2 }, "yaxis": { "automargin": true, "gridcolor": "white", "linecolor": "white", "ticks": "", "title": { "standoff": 15 }, "zerolinecolor": "white", "zerolinewidth": 2 } } }, "xaxis": { "anchor": "y", "domain": [ 0.0, 1.0 ], "matches": "x2", "showticklabels": false }, "xaxis2": { "anchor": "y2", "domain": [ 0.0, 1.0 ], "title": { "text": "Energy (eV)" } }, "yaxis": { "anchor": "x", "domain": [ 0.6833333333333333, 1.0 ], "title": { "text": "TOT IDOS" } }, "yaxis2": { "anchor": "x2", "domain": [ 0.0, 0.6333333333333333 ], "title": { "text": "TOT DOS" } } } }, "text/html": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "edos.plotly_dos_idos();" ] }, { "cell_type": "markdown", "id": "5b6af286", "metadata": {}, "source": [ "Want to make a nice picture of the band dispersion with a second panel for the DOS?" ] }, { "cell_type": "code", "execution_count": 41, "id": "3bd72b6d", "metadata": {}, "outputs": [ { "data": { "application/vnd.plotly.v1+json": { "config": { "plotlyServerURL": "https://chart-studio.plotly.com", "responsive": true, "showLink": true }, "data": [ { "legendgroup": "", "line": { "color": "black", "width": 2.0 }, "mode": "lines", "name": "", "showlegend": false, "type": "scatter", "x": [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100 ], "xaxis": "x", "y": [ -11.851613445039852, -11.829262546507499, -11.763277586937281, -11.653518784562753, -11.499818752637747, -11.303672784838163, -11.065105789040572, -10.784900153444106, -10.46402896039755, -10.103803186424756, -9.704813330716574, -9.269732619156798, -8.80096606434941, -8.30029060241338, -7.770465816946935, -7.763241578125931, -7.742609888248671, -7.712076592668978, -7.676700589636666, -7.643701158030813, -7.620022143667228, -7.611886989754334, -7.815402926706225, -7.974645817539696, -8.088881272757748, -8.157720333201592, -8.180770328221685, -8.434835077782893, -8.748456785422272, -9.101150890084453, -9.470241909780931, -9.83793835665062, -10.191581875439843, -10.521740693190559, -10.822584099183754, -11.088930019097868, -11.318647158805701, -11.508846872276596, -11.65799194485696, -11.76519980446276, -11.829880423716633, -11.851613445039852, -11.828901344903677, -11.761680471046045, -11.650084601108308, -11.495292457971903, -11.298131195766894, -11.062704080597197, -10.792431633734072, -10.494740482925705, -10.182477994899303, -9.884090789817407, -9.649851486789906, -9.556725550290272, -9.536698945102296, -9.47715632340821, -9.378314780070777, -9.24099057837031, -9.066529106063651, -8.857939766387581, -8.621810965354028, -8.376015999739792, -8.180770328166698, -8.157720333145175, -8.088881272700194, -7.97464581748109, -7.815402926646792, -7.611886989754334, -7.933335050545356, -8.246455483732571, -8.538422451074794, -8.800044043255458, -9.026971122765246, -9.215642668944206, -9.364114935032834, -9.47090005430848, -9.535083175750776, -9.556725550290272, -9.536698945102458, -9.477156323408988, -9.378314780072763, -9.240990578374099, -9.066529106070309, -8.857939766398722, -8.621810965372902, -8.376015999772683, -8.180770328221685, -8.248627108168062, -8.31543595384342, -8.365731396159052, -8.392618338737506, -8.39261833873174, -8.365731396141433, -8.315435953813203, -8.248627108124618, -8.180770328166698, -7.996771832951532, -7.879025362950108, -7.811912967138432, -7.779817588004046, -7.770465816946935 ], "yaxis": "y" }, { "legendgroup": "", "line": { "color": "black", "width": 2.0 }, "mode": "lines", "name": "", "showlegend": false, "type": "scatter", "x": [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100 ], "xaxis": "x", "y": [ -1.6335377495124703e-10, -0.16032698820379743, -0.5636457951166554, -1.09212474143225, -1.6773154842945197, -2.289399990162149, -2.914361827484835, -3.5449307515696202, -4.176451181929831, -4.805790281523441, -5.427689289964074, -6.039193341392819, -6.636376169672958, -7.21465163615954, -7.770465816821671, -7.763241578000309, -7.742609888122045, -7.712076592541063, -7.676700589507842, -7.643701157902436, -7.620022143541795, -7.611886989635335, -7.421374711335846, -7.299854712627417, -7.231093034567854, -7.1978687821403105, -7.188285204247792, -6.933409816359069, -6.633292984974313, -6.289280715718499, -5.90009368490985, -5.466932624806164, -4.991069137133525, -4.474881178196011, -3.919781777304002, -3.327536819015947, -2.7041108333466273, -2.0554800452214876, -1.396703083132917, -0.7604575290559579, -0.23013771779409087, -1.6335377495124703e-10, -0.26620529703147877, -0.8784501465647239, -1.6181584465130672, -2.3945578566803456, -3.1682486139103343, -3.921330316630484, -4.638994639961529, -5.308128391121763, -5.9114859308089756, -6.419868512550031, -6.779883102520867, -6.916275493243097, -6.905755465365838, -6.876303328603695, -6.832943230472041, -6.785214176651248, -6.751038035826356, -6.758244913985018, -6.840508544787537, -7.007460892791007, -7.188285204338305, -7.19786878222963, -7.231093034654421, -7.299854712708667, -7.42137471140827, -7.611886989635335, -7.301869405677406, -7.036209363986135, -6.848777335906148, -6.756628850987542, -6.7440152653999075, -6.777440649106646, -6.826958945905898, -6.8733412683580575, -6.904920301053387, -6.916275493243097, -6.905755465365712, -6.8763033286036315, -6.832943230471622, -6.785214176649349, -6.751038035820505, -6.758244913970187, -6.8405085447560925, -7.007460892733634, -7.188285204247792, -7.111946471075832, -7.031995853958247, -6.969031241749459, -6.935218102137593, -6.935218102147362, -6.96903124177916, -7.031995854008725, -7.111946471147528, -7.188285204338305, -7.397146006609232, -7.559977186599288, -7.677101927235896, -7.7471166931150774, -7.770465816821671 ], "yaxis": "y" }, { "legendgroup": "", "line": { "color": "black", "width": 2.0 }, "mode": "lines", "name": "", "showlegend": false, "type": "scatter", "x": [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100 ], "xaxis": "x", "y": [ -8.334133383414155e-11, -0.09211515515031987, -0.32824727411248933, -0.6354843455953532, -0.9631773430067367, -1.2868497795106428, -1.5917488120541616, -1.8699833250375155, -2.11677200086739, -2.3291545295224263, -2.5037909213476284, -2.6408722380667453, -2.740440421057171, -2.8003751148881233, -2.8203905545038555, -2.8860288266775997, -3.0546901728130798, -3.270200318651442, -3.48261501071111, -3.6568800949279403, -3.770265008381178, -3.8107473700624728, -3.9652867523983035, -4.0900163941103695, -4.180562266201235, -4.235112367525848, -4.253803130533925, -4.362192280919555, -4.345845039371504, -4.2215610063338325, -4.0064177361656155, -3.717533479235718, -3.370725628322197, -2.9758873372138854, -2.544196435673573, -2.0865410091040704, -1.6166404895025357, -1.1528235125847308, -0.7182474423045901, -0.3491040930372957, -0.09293055363501157, -8.334133383414155e-11, -0.03809873573310618, -0.1429488014485587, -0.28742471542663317, -0.4479972131523935, -0.6068650387686665, -0.7553479368493718, -0.8856854923086326, -0.9947007066478415, -1.0801792348909558, -1.1417866347775893, -1.1786793220517104, -1.1921544309391203, -1.3794575138561989, -1.825644345586102, -2.369434218783695, -2.9243278123614713, -3.4385550125135227, -3.8652364322550348, -4.156935732773959, -4.283871621112044, -4.253803130519498, -4.235112367511156, -4.180562266186957, -4.090016394097196, -3.9652867523870174, -3.8107473700624728, -4.007134693668303, -4.09329698299312, -4.030554851546317, -3.803145302957149, -3.42992286752277, -2.9497935995715783, -2.408352500134239, -1.8583358890492825, -1.3926014885726277, -1.1921544309391203, -1.3794575137994745, -1.8256443455318623, -2.3694342187314503, -2.92432781231171, -3.438555012468338, -3.865236432218387, -4.156935732751388, -4.2838716211078065, -4.253803130533925, -4.273514317225932, -4.23884340980823, -4.163788206856713, -4.093693416687977, -4.093693416690762, -4.163788206861114, -4.238843409808835, -4.273514317219683, -4.253803130519498, -4.018734260151437, -3.6815208461149043, -3.2974166712355224, -2.961787548870396, -2.8203905545038555 ], "yaxis": "y" }, { "legendgroup": "", "line": { "color": "black", "width": 2.0 }, "mode": "lines", "name": "", "showlegend": false, "type": "scatter", "x": [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100 ], "xaxis": "x", "y": [ 0.0, -0.09211515504698742, -0.3282472740288691, -0.6354843455286749, -0.9631773429514219, -1.2868497794616625, -1.5917488120078889, -1.8699833249917366, -2.1167720008209514, -2.329154529474871, -2.5037909212987204, -2.6408722380167564, -2.7404404210064457, -2.8003751148369007, -2.8203905544524637, -2.8860288266308487, -3.054690172777407, -3.270200318627115, -3.4826150106888636, -3.6568800948958984, -3.7702650083356892, -3.8107473700038414, -3.577837505726965, -3.244838208497727, -2.8652428266815546, -2.5366929541182444, -2.3990574510867804, -2.2214629443194367, -2.0195348042998416, -1.797493225997051, -1.561755463924979, -1.317366161445312, -1.0741180298982904, -0.8413174918080655, -0.6287781210384527, -0.44437858817602116, -0.2941073014400777, -0.1781910790333603, -0.09506547870692561, -0.04053223612994916, -0.009632704147326088, 0.0, -0.038098735689124474, -0.14294880140758792, -0.2874247153895588, -0.4479972131180334, -0.606865038733801, -0.7553479368102787, -0.8856854922628417, -0.9947007065945579, -1.0801792348307062, -1.1417866347118037, -1.1786793219823508, -1.1921544308687038, -1.228867896098646, -1.3300459374633808, -1.47870080386007, -1.652111383687319, -1.8316823948835745, -2.00430661520324, -2.160024838950893, -2.29321320061289, -2.399057451090166, -2.536692954113345, -2.865242826671942, -3.244838208488802, -3.5778375057242995, -3.8107473700038414, -3.5345497983318137, -3.208169970244198, -2.853818642870846, -2.4897375490238565, -2.137234436321377, -1.8174036791571582, -1.550549151988701, -1.3530913671577975, -1.232217856123289, -1.1921544308687038, -1.2288678961545685, -1.3300459375131126, -1.4787008039013783, -1.652111383719625, -1.8316823949072392, -2.0043066152188804, -2.1600248389594134, -2.2932132006150487, -2.3990574510867804, -2.446692141953893, -2.63163563366671, -2.853804945823167, -3.0105784873298793, -3.010578487324915, -2.8538049458122643, -2.63163563365609, -2.4466921419485868, -2.399057451090166, -2.5478847853783164, -2.6662661059255948, -2.7511129264431946, -2.803014556424606, -2.8203905544524637 ], "yaxis": "y" }, { "legendgroup": "", "line": { "color": "black", "width": 2.0 }, "mode": "lines", "name": "", "showlegend": false, "type": "scatter", "x": [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100 ], "xaxis": "x", "y": [ 2.5122998962024123, 2.4659990593471584, 2.300498242709943, 2.07249175115928, 1.8139821624238675, 1.547901139681355, 1.2932614151436423, 1.0629634354095403, 0.8659627463667237, 0.7058083015123815, 0.592881346241235, 0.5283996162677376, 0.5166806915267141, 0.5585638074771229, 0.6578951423348149, 0.7791898484978423, 1.1158791383818167, 1.6138390186324916, 2.2257662680617756, 2.9169190551276554, 3.656472551200931, 4.2209673810841934, 3.5056460346633163, 2.6470530606189, 1.8971372735474556, 1.3524073521808946, 1.1425072029499486, 1.3489395861198155, 1.5807622702129844, 1.8329315205187688, 2.0948114040784542, 2.352899920500505, 2.583677988477321, 2.760137488600286, 2.862609611797753, 2.8903295781361713, 2.863087850677264, 2.8361320056351875, 2.723552495816225, 2.614020510806002, 2.550680684772594, 2.5122998962024123, 2.5655460423718477, 2.473000865976113, 2.3335052380209316, 2.167275255926123, 1.995520046402028, 1.832029357783112, 1.686643241833675, 1.5636517525829179, 1.469360074491333, 1.398582069139839, 1.356978740567567, 1.3409953340676113, 1.5145510028941738, 1.8722604530378728, 2.092188422387859, 2.0308247644766517, 1.840924139783878, 1.629467596427471, 1.434156843325633, 1.2689557779537504, 1.1425072029457386, 1.3524073521639988, 1.8971372734595677, 2.647053060880973, 3.5056490806367187, 4.2209673810841934, 3.917803514759532, 3.618540214941529, 3.37426750478088, 3.2130468904841276, 2.936786222084285, 2.642637809333662, 2.3154899245457408, 1.9233429563667217, 1.5279439779344806, 1.3409953340676113, 1.5145510029056446, 1.8722604666215537, 2.0921884226177037, 2.0308247646628494, 1.8409241397573108, 1.6294675964089143, 1.4341568433149794, 1.2689557779503104, 1.1425072029499486, 1.3475684269208843, 1.8084646675065548, 2.4433869871103173, 3.1814344039733857, 3.18143354344439, 2.443386986833433, 1.8084646674899005, 1.3475684269101826, 1.1425072029457386, 0.9709439070638091, 0.8348913946576921, 0.7374868785337476, 0.6778521258540584, 0.6578951423348149 ], "yaxis": "y" }, { "legendgroup": "", "line": { "color": "black", "width": 2.0 }, "mode": "lines", "name": "", "showlegend": false, "type": "scatter", "x": [ 0.0027699052574620933, 0.010991730672077751, 0.03392455785381908, 0.08143465634094976, 0.15203770252786125, 0.22077014764627154, 0.24933157922424856, 0.21901533339719162, 0.14969550937343865, 0.08007341733798869, 0.03623284594076028, 0.02603719791477041, 0.05778155145808582, 0.15330945648621114, 0.32937765305475825, 0.5519823523669515, 0.7196014249078969, 0.7296521880552819, 0.5754865717679726, 0.35350409700917457, 0.17173088385603563, 0.0778935886712157, 0.07301578794465693, 0.15651193422689608, 0.3294946659265387, 0.5515472167158578, 0.7193719496269576, 0.7298910494717421, 0.5762674787564852, 0.3554376974781889, 0.17756775668558178, 0.09422524861264386, 0.10905236969197266, 0.21765507498840891, 0.4130222395162555, 0.6563963482012013, 0.8584716209217231, 0.9150254763418323, 0.7871582425046044, 0.5457497145678862, 0.3238573046676037, 0.23661792777399746, 0.3510799378305834, 0.678227975024836, 1.1289242303987603, 1.5041311241676676, 1.6256932892848976, 1.498866386899559, 1.276233289671086, 1.0630661082494206, 0.8431422445374459, 0.5878745683508527, 0.33836779648722015, 0.15912215302259486, 0.07612561110612173, 0.08548894925671438, 0.1871556191871238, 0.3759915722589474, 0.5966105469356292, 0.7375879358649037, 0.7113875133778955, 0.5434199934260151, 0.35850957023253777, 0.2840557276820438, 0.3761789164139926, 0.6080315196907567, 0.9034546272811442, 1.1996552441020678, 1.472829217876169, 1.6719691101341971, 1.6760109654079738, 1.4051532273413634, 0.9495071701314864, 0.5071431341896548, 0.21216213587832336, 0.0692411193478534, 0.017598109697254265, 0.0034805845550205778, 0.000535532622470643, 6.409280439215096e-05, 5.9661977307066616e-06, 4.319571040488679e-07, 2.4323932912862652e-08, 1.0653082861900373e-09, 3.6288845898559175e-11, 1.0051148302007177e-12, 2.038481906389722e-12, 7.249307139352947e-11, 2.0249188651755797e-09, 4.3997565109195006e-08, 7.436981787328391e-07, 9.78083570096839e-06, 0.00010010866061046035, 0.0007977316066220286, 0.004952405837772766, 0.02397838737753862, 0.0907082580124899, 0.26890250888910494, 0.6278351194851134, 1.1643973707315047, 1.740548772106234, 2.1493376081831626, 2.280967437028682, 2.196678868084728, 2.0243310068723104, 1.8211262915952626, 1.5575397224216, 1.2040248894614418, 0.8019864854427, 0.44428193573884245, 0.1998525409980702, 0.07186663799361771, 0.02048223117906279, 0.004835052436756405, 0.002389660503911023, 0.007870922384026363, 0.030683385441739017, 0.09889427911949542, 0.26159791070927046, 0.5679016886375159, 1.0066678861290357, 1.4445730003496429, 1.662123915821576, 1.520160567509843, 1.097562417319736, 0.6224507293423432, 0.2763214204734007, 0.09579829184400818, 0.025899049819060903, 0.005455041553956901, 0.0008984975074360561, 0.00015616111142673675, 0.00035178481629912514, 0.0021467889194562084, 0.01052012166073619, 0.040111834468368565, 0.1189531805523271, 0.27437238094949923, 0.49229160622218454, 0.6875644874132172, 0.7500635946481886, 0.6501391153049356, 0.48422849487406977, 0.3974405521452443, 0.4632534215096705, 0.6260797386744238, 0.7444553405617236, 0.7073636252867815, 0.5255896858978862, 0.30409216246783083, 0.13715820262160358, 0.050161679822412514, 0.02547514942898336, 0.05615497233668769, 0.17996171740209166, 0.4734578797135677, 0.9814739801276915, 1.6035704024895052, 2.0700643766015547, 2.116661907853083, 1.718002549773833, 1.1085448696529883, 0.5690524357077149, 0.2327813326449161, 0.07865705192104351, 0.03542843883314023, 0.06438220418151956, 0.18222511228280255, 0.44223248408494065, 0.88669747640141, 1.4867840882646732, 2.1038979775187854, 2.5130224912884174, 2.515459378206356, 2.095119472294548, 1.4736084199963975, 0.9792538448102552, 0.8384021736810937, 1.0459468183547338, 1.3749294836995944, 1.5372611578324957, 1.4252084520475965, 1.210207760761376, 1.1553661037472742, 1.3254939957920806, 1.5143244818602157, 1.4676477969580337, 1.1506423211499504, 0.7738715663871728, 0.5988221352615846, 0.7573996048436528, 1.1926096811629718, 1.6864729947793011, 1.9737151847579744, 1.9110939059153935, 1.572098715554042, 1.1959101529213643, 1.050692994060534, 1.2761697210390122, 1.7580626415299385, 2.1557725387308184, 2.1525856387007156, 1.7325672478070155, 1.1819897808893742, 0.8201232259543546, 0.7591720684960278, 0.8831762362131027, 0.9908795054870901, 0.9716178848939814, 0.8925956080413672, 0.9184232688960361, 1.1250162831195931, 1.397468542668789, 1.5320569918483216, 1.435293784870669, 1.1902844599282416, 0.9300093892450059, 0.7079560786423544, 0.5206209948648011, 0.39425210791283727, 0.3871268865364917, 0.5109494881105185, 0.678562504444509, 0.7521278611598464, 0.658806399183025, 0.4506231044372327, 0.2415438020517177, 0.10838844884915162, 0.06550363917448514, 0.1029139133734538, 0.2101886935875596, 0.35687963449777693, 0.4741974969168308, 0.49032260704395747, 0.3943416443752753, 0.24666764804702457, 0.12000486762587637, 0.045408013205060424, 0.013363280763865563, 0.0030587264599658288, 0.0005445216364832618, 7.539397785833693e-05, 8.119375082697008e-06, 6.878140839927161e-07, 1.8796299671859052e-07, 2.0613070865804862e-06, 2.2952836989879816e-05, 0.0001989971149370895, 0.0013418556623887997, 0.007037392697579229, 0.028705474023614234, 0.09106775183901811, 0.2247043490922452, 0.4312265066118682, 0.6436470870914431, 0.7472235657378983, 0.6748791257262718, 0.4753602098871118, 0.2669755171381174, 0.14262750019837586, 0.13754473023822053, 0.25330619996732046, 0.46077550840818415, 0.6774615496882385, 0.7937017606638376, 0.7596386082618748, 0.6260716735224886, 0.47789626482899505, 0.358179921697636, 0.2793586875233516, 0.270156927427067, 0.36603482587608416, 0.5482980669554804, 0.717529606842147, 0.7656802539276636, 0.6956337557984644, 0.6497480965545828, 0.788012475047745, 1.1194709736201007, 1.459561913995297, 1.5983180182969676, 1.5350704005850795, 1.4875692740501785, 1.6194228090279474, 1.8209133791204155, 1.8423889117317789, 1.6074429110340196, 1.2872560982403556, 1.0688188934328433, 0.9719360416357168, 0.9384763990606393, 0.9896059959239609, 1.1820322841621953, 1.4379590171482635, 1.5381295565514497, 1.3357805500458675, 0.9145254350194685, 0.48897640573821016, 0.20359327532172963, 0.06595483660513557, 0.016619767275502094 ], "xaxis": "x2", "y": [ -11.950089629336535, -11.899956389171951, -11.849823149007367, -11.799689908842787, -11.749556668678203, -11.699423428513619, -11.649290188349037, -11.599156948184454, -11.54902370801987, -11.498890467855288, -11.448757227690706, -11.398623987526122, -11.34849074736154, -11.298357507196958, -11.248224267032374, -11.19809102686779, -11.147957786703207, -11.097824546538625, -11.047691306374041, -10.997558066209459, -10.947424826044877, -10.897291585880293, -10.84715834571571, -10.797025105551128, -10.746891865386544, -10.69675862522196, -10.646625385057378, -10.596492144892796, -10.546358904728212, -10.49622566456363, -10.446092424399048, -10.395959184234464, -10.345825944069881, -10.2956927039053, -10.245559463740715, -10.195426223576133, -10.145292983411549, -10.095159743246967, -10.045026503082383, -9.9948932629178, -9.944760022753218, -9.894626782588634, -9.844493542424052, -9.79436030225947, -9.744227062094886, -9.694093821930304, -9.64396058176572, -9.593827341601138, -9.543694101436554, -9.493560861271972, -9.44342762110739, -9.393294380942805, -9.343161140778223, -9.293027900613641, -9.242894660449057, -9.192761420284475, -9.142628180119893, -9.092494939955309, -9.042361699790725, -8.992228459626142, -8.94209521946156, -8.891961979296976, -8.841828739132394, -8.791695498967812, -8.741562258803228, -8.691429018638646, -8.641295778474063, -8.59116253830948, -8.541029298144897, -8.490896057980313, -8.440762817815731, -8.390629577651147, -8.340496337486565, -8.290363097321983, -8.240229857157399, -8.190096616992816, -8.139963376828234, -8.08983013666365, -8.039696896499068, -7.989563656334484, -7.939430416169902, -7.889297176005319, -7.839163935840736, -7.7890306956761535, -7.73889745551157, -7.688764215346987, -7.638630975182404, -7.588497735017821, -7.538364494853239, -7.488231254688656, -7.438098014524073, -7.38796477435949, -7.3378315341949065, -7.287698294030324, -7.237565053865741, -7.187431813701158, -7.137298573536575, -7.087165333371992, -7.03703209320741, -6.986898853042827, -6.936765612878244, -6.8866323727136605, -6.836499132549078, -6.786365892384495, -6.736232652219912, -6.686099412055329, -6.635966171890746, -6.585832931726164, -6.535699691561581, -6.4855664513969975, -6.435433211232414, -6.385299971067831, -6.335166730903249, -6.285033490738666, -6.234900250574083, -6.1847670104095, -6.134633770244917, -6.0845005300803345, -6.034367289915751, -5.984234049751168, -5.934100809586585, -5.883967569422003, -5.83383432925742, -5.783701089092837, -5.733567848928254, -5.683434608763671, -5.6333013685990885, -5.583168128434505, -5.533034888269922, -5.482901648105339, -5.432768407940756, -5.382635167776174, -5.332501927611591, -5.282368687447008, -5.232235447282425, -5.1821022071178415, -5.131968966953259, -5.081835726788676, -5.031702486624093, -4.98156924645951, -4.931436006294928, -4.881302766130345, -4.831169525965762, -4.781036285801179, -4.7309030456365955, -4.680769805472013, -4.63063656530743, -4.580503325142847, -4.530370084978264, -4.480236844813681, -4.430103604649099, -4.379970364484516, -4.3298371243199325, -4.279703884155349, -4.229570643990766, -4.179437403826184, -4.129304163661601, -4.079170923497018, -4.029037683332435, -3.9789044431678526, -3.9287712030032695, -3.8786379628386856, -3.8285047226741034, -3.778371482509521, -3.728238242344937, -3.678105002180355, -3.6279717620157728, -3.577838521851189, -3.5277052816866066, -3.4775720415220226, -3.4274388013574404, -3.377305561192858, -3.327172321028274, -3.277039080863692, -3.226905840699108, -3.176772600534526, -3.1266393603699436, -3.0765061202053596, -3.0263728800407774, -2.9762396398761934, -2.9261063997116112, -2.875973159547029, -2.825839919382445, -2.775706679217863, -2.725573439053279, -2.6754401988886967, -2.6253069587241145, -2.5751737185595305, -2.5250404783949483, -2.4749072382303643, -2.424773998065782, -2.3746407579012, -2.324507517736616, -2.2743742775720337, -2.2242410374074497, -2.1741077972428675, -2.1239745570782853, -2.0738413169137013, -2.023708076749119, -1.9735748365845351, -1.923441596419953, -1.8733083562553707, -1.8231751160907868, -1.7730418759262045, -1.7229086357616223, -1.6727753955970384, -1.6226421554324562, -1.5725089152678722, -1.52237567510329, -1.4722424349387078, -1.4221091947741238, -1.3719759546095416, -1.3218427144449576, -1.2717094742803754, -1.2215762341157932, -1.1714429939512092, -1.121309753786627, -1.071176513622043, -1.0210432734574608, -0.9709100332928786, -0.9207767931282946, -0.8706435529637124, -0.8205103127991284, -0.7703770726345462, -0.720243832469964, -0.6701105923053801, -0.6199773521407979, -0.5698441119762139, -0.5197108718116317, -0.46957763164704946, -0.4194443914824655, -0.3693111513178833, -0.3191779111532993, -0.2690446709887171, -0.2189114308241349, -0.1687781906595509, -0.1186449504949687, -0.06851171033038472, -0.01837847016580252, 0.031754769998779686, 0.08188801016336367, 0.13202125032794587, 0.18215449049252808, 0.23228773065711206, 0.28242097082169426, 0.33255421098627824, 0.38268745115086045, 0.43282069131544265, 0.48295393148002663, 0.5330871716446088, 0.5832204118091928, 0.633353651973775, 0.6834868921383572, 0.7336201323029412, 0.7837533724675234, 0.8338866126321074, 0.8840198527966896, 0.9341530929612718, 0.9842863331258558, 1.034419573290438, 1.084552813455022, 1.1346860536196042, 1.1848192937841864, 1.2349525339487704, 1.2850857741133526, 1.3352190142779365, 1.3853522544425187, 1.435485494607101, 1.485618734771685, 1.5357519749362671, 1.5858852151008511, 1.6360184552654333, 1.6861516954300155, 1.7362849355945995, 1.7864181757591817, 1.836551415923764, 1.886684656088348, 1.93681789625293, 1.986951136417514, 2.0370843765820963, 2.0872176167466785, 2.1373508569112625, 2.1874840970758447, 2.2376173372404287, 2.287750577405011, 2.337883817569593, 2.388017057734177, 2.4381502978987584, 2.4882835380633423, 2.5384167782279263, 2.5885500183925068, 2.6386832585570907, 2.6888164987216747, 2.7389497388862587, 2.789082979050839, 2.839216219215423, 2.889349459380007, 2.9394826995445875, 2.9896159397091715, 3.0397491798737555, 3.089882420038336 ], "yaxis": "y2" } ], "layout": { "hovermode": false, "template": { "data": { "bar": [ { "error_x": { "color": "#2a3f5f" }, "error_y": { "color": "#2a3f5f" }, "marker": { "line": { "color": "#E5ECF6", "width": 0.5 }, "pattern": { "fillmode": "overlay", "size": 10, "solidity": 0.2 } }, "type": "bar" } ], "barpolar": [ { "marker": { "line": { "color": "#E5ECF6", "width": 0.5 }, "pattern": { "fillmode": "overlay", "size": 10, "solidity": 0.2 } }, "type": "barpolar" } ], "carpet": [ { "aaxis": { "endlinecolor": "#2a3f5f", "gridcolor": "white", "linecolor": "white", "minorgridcolor": "white", "startlinecolor": "#2a3f5f" }, "baxis": { "endlinecolor": "#2a3f5f", "gridcolor": "white", "linecolor": "white", "minorgridcolor": "white", "startlinecolor": "#2a3f5f" }, "type": "carpet" } ], "choropleth": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "type": "choropleth" } ], "contour": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0.0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1.0, "#f0f921" ] ], "type": "contour" } ], "contourcarpet": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "type": "contourcarpet" } ], "heatmap": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0.0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1.0, "#f0f921" ] ], "type": "heatmap" } ], "heatmapgl": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0.0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1.0, "#f0f921" ] ], "type": "heatmapgl" } ], "histogram": [ { "marker": { "pattern": { "fillmode": "overlay", "size": 10, "solidity": 0.2 } }, "type": "histogram" } ], "histogram2d": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0.0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1.0, "#f0f921" ] ], "type": "histogram2d" } ], "histogram2dcontour": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0.0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1.0, "#f0f921" ] ], "type": "histogram2dcontour" } ], "mesh3d": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "type": "mesh3d" } ], "parcoords": [ { "line": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "parcoords" } ], "pie": [ { "automargin": true, "type": "pie" } ], "scatter": [ { "fillpattern": { "fillmode": "overlay", "size": 10, "solidity": 0.2 }, "type": "scatter" } ], "scatter3d": [ { "line": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scatter3d" } ], "scattercarpet": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scattercarpet" } ], "scattergeo": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scattergeo" } ], "scattergl": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scattergl" } ], "scattermapbox": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scattermapbox" } ], "scatterpolar": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scatterpolar" } ], "scatterpolargl": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scatterpolargl" } ], "scatterternary": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scatterternary" } ], "surface": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0.0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1.0, "#f0f921" ] ], "type": "surface" } ], "table": [ { "cells": { "fill": { "color": "#EBF0F8" }, "line": { "color": "white" } }, "header": { "fill": { "color": "#C8D4E3" }, "line": { "color": "white" } }, "type": "table" } ] }, "layout": { "annotationdefaults": { "arrowcolor": "#2a3f5f", "arrowhead": 0, "arrowwidth": 1 }, "autotypenumbers": "strict", "coloraxis": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "colorscale": { "diverging": [ [ 0, "#8e0152" ], [ 0.1, "#c51b7d" ], [ 0.2, "#de77ae" ], [ 0.3, "#f1b6da" ], [ 0.4, "#fde0ef" ], [ 0.5, "#f7f7f7" ], [ 0.6, "#e6f5d0" ], [ 0.7, "#b8e186" ], [ 0.8, "#7fbc41" ], [ 0.9, "#4d9221" ], [ 1, "#276419" ] ], "sequential": [ [ 0.0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1.0, "#f0f921" ] ], "sequentialminus": [ [ 0.0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1.0, "#f0f921" ] ] }, "colorway": [ "#636efa", "#EF553B", "#00cc96", "#ab63fa", "#FFA15A", "#19d3f3", "#FF6692", "#B6E880", "#FF97FF", "#FECB52" ], "font": { "color": "#2a3f5f" }, "geo": { "bgcolor": "white", "lakecolor": "white", "landcolor": "#E5ECF6", "showlakes": true, "showland": true, "subunitcolor": "white" }, "hoverlabel": { "align": "left" }, "hovermode": "closest", "mapbox": { "style": "light" }, "paper_bgcolor": "white", "plot_bgcolor": "#E5ECF6", "polar": { "angularaxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" }, "bgcolor": "#E5ECF6", "radialaxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" } }, "scene": { "xaxis": { "backgroundcolor": "#E5ECF6", "gridcolor": "white", "gridwidth": 2, "linecolor": "white", "showbackground": true, "ticks": "", "zerolinecolor": "white" }, "yaxis": { "backgroundcolor": "#E5ECF6", "gridcolor": "white", "gridwidth": 2, "linecolor": "white", "showbackground": true, "ticks": "", "zerolinecolor": "white" }, "zaxis": { "backgroundcolor": "#E5ECF6", "gridcolor": "white", "gridwidth": 2, "linecolor": "white", "showbackground": true, "ticks": "", "zerolinecolor": "white" } }, "shapedefaults": { "line": { "color": "#2a3f5f" } }, "ternary": { "aaxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" }, "baxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" }, "bgcolor": "#E5ECF6", "caxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" } }, "title": { "x": 0.05 }, "xaxis": { "automargin": true, "gridcolor": "white", "linecolor": "white", "ticks": "", "title": { "standoff": 15 }, "zerolinecolor": "white", "zerolinewidth": 2 }, "yaxis": { "automargin": true, "gridcolor": "white", "linecolor": "white", "ticks": "", "title": { "standoff": 15 }, "zerolinecolor": "white", "zerolinewidth": 2 } } }, "xaxis": { "anchor": "y", "domain": [ 0.0, 0.6533333333333333 ], "range": [ 0, 100 ], "tickfont": { "size": 16 }, "ticktext": [ "Γ", "X", "W", "K", "Γ", "L", "U", "W", "L", "K", "U", "X" ], "tickvals": [ 0, 14, 21, 26, 41, 53, 62, 67, 77, 86, 95, 100 ], "title": { "text": "Wave Vector" } }, "xaxis2": { "anchor": "y2", "domain": [ 0.6733333333333333, 1.0 ] }, "yaxis": { "anchor": "x", "domain": [ 0.0, 1.0 ], "title": { "text": "Energy (eV)" } }, "yaxis2": { "anchor": "x2", "domain": [ 0.0, 1.0 ], "matches": "y", "showticklabels": false } } }, "text/html": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "ebands_kpath.plotly_with_edos(edos);" ] }, { "cell_type": "markdown", "id": "874c24d6", "metadata": {}, "source": [ "It is important to stress that each panel in the above figure is aligned with respect\n", "to its own Fermi energy and these values are not necessarily equal:" ] }, { "cell_type": "code", "execution_count": 42, "id": "a280fa01", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "5.567493594319245 eV 6.06392481883024\n" ] } ], "source": [ "print(ebands_kpath.fermie, edos.fermie)" ] }, { "cell_type": "markdown", "id": "75388dcb", "metadata": {}, "source": [ "We can always plot the bands and the DOS without setting their Fermi energy to zero by using:" ] }, { "cell_type": "code", "execution_count": 43, "id": "5a21e324", "metadata": {}, "outputs": [ { "data": { "application/vnd.plotly.v1+json": { "config": { "plotlyServerURL": "https://chart-studio.plotly.com", "responsive": true, "showLink": true }, "data": [ { "legendgroup": "", "line": { "color": "black", "width": 2.0 }, "mode": "lines", "name": "", "showlegend": false, "type": "scatter", "x": [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100 ], "xaxis": "x", "y": [ -6.284119850720608, -6.261768952188254, -6.195783992618037, -6.086025190243508, -5.932325158318501, -5.736179190518917, -5.497612194721326, -5.217406559124861, -4.8965353660783055, -4.53630959210551, -4.137319736397329, -3.702239024837553, -3.233472470030164, -2.7327970080941357, -2.2029722226276895, -2.195747983806686, -2.1751162939294257, -2.1445829983497324, -2.109206995317421, -2.0762075637115682, -2.0525285493479832, -2.044393395435089, -2.2479093323869805, -2.407152223220451, -2.521387678438503, -2.5902267388823477, -2.6132767339024396, -2.8673414834636466, -3.1809631911030265, -3.5336572957652073, -3.902748315461685, -4.270444762331374, -4.624088281120597, -4.954247098871313, -5.2550905048645085, -5.5214364247786225, -5.751153564486456, -5.941353277957352, -6.090498350537715, -6.197706210143514, -6.2623868293973874, -6.284119850720608, -6.261407750584433, -6.194186876726801, -6.0825910067890625, -5.927798863652659, -5.730637601447649, -5.4952104862779505, -5.224938039414827, -4.92724688860646, -4.614984400580058, -4.316597195498162, -4.082357892470662, -3.9892319559710265, -3.969205350783051, -3.909662729088964, -3.8108211857515326, -3.673496984051065, -3.499035511744407, -3.2904461720683367, -3.054317371034783, -2.8085224054205478, -2.613276733847453, -2.590226738825929, -2.521387678380948, -2.407152223161844, -2.2479093323275467, -2.044393395435089, -2.365841456226111, -2.6789618894133254, -2.9709288567555485, -3.2325504489362125, -3.4594775284460013, -3.648149074624961, -3.7966213407135894, -3.903406459989234, -3.9675895814315307, -3.9892319559710265, -3.969205350783213, -3.909662729089742, -3.8108211857535172, -3.673496984054853, -3.499035511751064, -3.2904461720794775, -3.054317371053657, -2.808522405453439, -2.6132767339024396, -2.6811335138488177, -2.747942359524175, -2.798237801839807, -2.825124744418261, -2.825124744412496, -2.798237801822187, -2.7479423594939583, -2.681133513805372, -2.613276733847453, -2.4292782386322864, -2.311531768630863, -2.244419372819187, -2.2123239936848007, -2.2029722226276895 ], "yaxis": "y" }, { "legendgroup": "", "line": { "color": "black", "width": 2.0 }, "mode": "lines", "name": "", "showlegend": false, "type": "scatter", "x": [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100 ], "xaxis": "x", "y": [ 5.567493594155891, 5.407166606115448, 5.00384779920259, 4.475368852886995, 3.8901781100247255, 3.278093604157096, 2.6531317668344103, 2.022562842749625, 1.3910424123894138, 0.7617033127958039, 0.13980430435517108, -0.47169974707357376, -1.0688825753537128, -1.6471580418402947, -2.2029722225024257, -2.1957479836810636, -2.1751162938028004, -2.144582998221818, -2.1092069951885963, -2.0762075635831914, -2.05252854922255, -2.0443933953160895, -1.853881117016601, -1.732361118308172, -1.6635994402486087, -1.6303751878210655, -1.6207916099285462, -1.365916222039824, -1.0657993906550676, -0.7217871213992542, -0.3326000905906046, 0.10056096951308081, 0.5764244571857201, 1.092612416123234, 1.6477118170152434, 2.2399567753032983, 2.863382760972618, 3.5120135490977575, 4.170790511186328, 4.807036065263287, 5.337355876525154, 5.567493594155891, 5.301288297287766, 4.689043447754521, 3.949335147806178, 3.1729357376388996, 2.399244980408911, 1.6461632776887614, 0.9284989543577156, 0.25936520319748174, -0.34399233648972993, -0.8523749182307857, -1.212389508201622, -1.3487818989238511, -1.338261871046593, -1.3088097342844507, -1.2654496361527958, -1.2177205823320028, -1.1835444415071112, -1.1907513196657729, -1.2730149504682917, -1.4399672984717617, -1.6207916100190594, -1.6303751879103847, -1.663599440335176, -1.732361118389422, -1.8538811170890248, -2.0443933953160895, -1.7343758113581613, -1.4687157696668902, -1.281283741586903, -1.189135256668297, -1.1765216710806627, -1.209947054787401, -1.2594653515866525, -1.3058476740388119, -1.3374267067341417, -1.3487818989238511, -1.3382618710464673, -1.3088097342843867, -1.2654496361523768, -1.217720582330104, -1.18354444150126, -1.190751319650942, -1.2730149504368475, -1.4399672984143888, -1.6207916099285462, -1.5444528767565875, -1.4645022596390018, -1.4015376474302137, -1.367724507818348, -1.3677245078281168, -1.401537647459914, -1.46450225968948, -1.5444528768282821, -1.6207916100190594, -1.8296524122899869, -1.9924835922800428, -2.1096083329166504, -2.1796230987958323, -2.2029722225024257 ], "yaxis": "y" }, { "legendgroup": "", "line": { "color": "black", "width": 2.0 }, "mode": "lines", "name": "", "showlegend": false, "type": "scatter", "x": [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100 ], "xaxis": "x", "y": [ 5.567493594235904, 5.475378439168925, 5.239246320206756, 4.932009248723892, 4.604316251312508, 4.280643814808602, 3.9757447822650835, 3.6975102692817297, 3.4507215934518554, 3.238339064796819, 3.063702672971617, 2.9266213562525, 2.8270531732620743, 2.767118479431122, 2.7471030398153897, 2.6814647676416454, 2.5128034215061654, 2.297293275667803, 2.0848785836081354, 1.9106134993913046, 1.797228585938067, 1.7567462242567724, 1.6022068419209414, 1.477477200208876, 1.3869313281180102, 1.3323812267933972, 1.3136904637853202, 1.205301313399691, 1.2216485549477407, 1.3459325879854123, 1.5610758581536297, 1.849960115083527, 2.196767965997048, 2.5916062571053597, 3.023297158645672, 3.480952585215175, 3.9508531048167095, 4.414670081734514, 4.849246152014655, 5.2183895012819494, 5.474563040684234, 5.567493594235904, 5.529394858586139, 5.4245447928706865, 5.280068878892612, 5.119496381166852, 4.960628555550579, 4.812145657469873, 4.681808102010613, 4.572792887671404, 4.487314359428289, 4.425706959541656, 4.388814272267535, 4.375339163380125, 4.188036080463046, 3.741849248733143, 3.19805937553555, 2.643165781957774, 2.1289385818057225, 1.7022571620642102, 1.4105578615452867, 1.2836219732072012, 1.3136904637997475, 1.3323812268080892, 1.3869313281322884, 1.4774772002220489, 1.602206841932228, 1.7567462242567724, 1.5603589006509424, 1.4741966113261251, 1.5369387427729275, 1.764348291362096, 2.137570726796475, 2.617699994747667, 3.159141094185006, 3.7091577052699627, 4.1748921057466175, 4.375339163380125, 4.188036080519771, 3.741849248787383, 3.198059375587795, 2.6431657820075354, 2.1289385818509072, 1.702257162100858, 1.4105578615678567, 1.283621973211439, 1.3136904637853202, 1.293979277093313, 1.3286501845110152, 1.4037053874625316, 1.4738001776312684, 1.4738001776284835, 1.4037053874581311, 1.3286501845104097, 1.293979277099562, 1.3136904637997475, 1.5487593341678088, 1.8859727482043411, 2.2700769230837228, 2.605706045448849, 2.7471030398153897 ], "yaxis": "y" }, { "legendgroup": "", "line": { "color": "black", "width": 2.0 }, "mode": "lines", "name": "", "showlegend": false, "type": "scatter", "x": [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100 ], "xaxis": "x", "y": [ 5.567493594319245, 5.475378439272258, 5.239246320290376, 4.93200924879057, 4.604316251367823, 4.280643814857583, 3.9757447823113563, 3.6975102693275086, 3.4507215934982938, 3.238339064844374, 3.063702673020525, 2.9266213563024888, 2.8270531733127995, 2.7671184794823445, 2.7471030398667815, 2.6814647676883965, 2.5128034215418382, 2.2972932756921303, 2.0848785836303816, 1.9106134994233466, 1.797228585983556, 1.7567462243154037, 1.98965608859228, 2.322655385821518, 2.7022507676376906, 3.030800640201001, 3.168436143232465, 3.3460306499998085, 3.5479587900194036, 3.770000368322194, 4.005738130394266, 4.250127432873933, 4.493375564420955, 4.72617610251118, 4.9387154732807925, 5.123115006143224, 5.2733862928791675, 5.389302515285885, 5.47242811561232, 5.526961358189296, 5.557860890171919, 5.567493594319245, 5.529394858630121, 5.424544792911657, 5.280068878929686, 5.119496381201212, 4.960628555585444, 4.8121456575089665, 4.6818081020564035, 4.572792887724687, 4.487314359488539, 4.425706959607441, 4.388814272336894, 4.375339163450541, 4.338625698220599, 4.237447656855864, 4.088792790459175, 3.9153822106319263, 3.7358111994356706, 3.563186979116005, 3.407468755368352, 3.274280393706355, 3.168436143229079, 3.0308006402059, 2.7022507676473033, 2.3226553858304433, 1.9896560885949455, 1.7567462243154037, 2.0329437959874315, 2.359323624075047, 2.7136749514483993, 3.0777560452953887, 3.430259157997868, 3.750089915162087, 4.016944442330544, 4.214402227161448, 4.335275738195956, 4.375339163450541, 4.338625698164677, 4.237447656806133, 4.088792790417867, 3.91538221059962, 3.735811199412006, 3.5631869791003647, 3.4074687553598317, 3.2742803937041964, 3.168436143232465, 3.120801452365352, 2.9358579606525352, 2.713688648496078, 2.556915106989366, 2.5569151069943303, 2.713688648506981, 2.935857960663155, 3.1208014523706584, 3.168436143229079, 3.0196088089409288, 2.9012274883936504, 2.8163806678760506, 2.764479037894639, 2.7471030398667815 ], "yaxis": "y" }, { "legendgroup": "", "line": { "color": "black", "width": 2.0 }, "mode": "lines", "name": "", "showlegend": false, "type": "scatter", "x": [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100 ], "xaxis": "x", "y": [ 8.079793490521658, 8.033492653666404, 7.867991837029188, 7.639985345478525, 7.381475756743113, 7.1153947340006, 6.8607550094628875, 6.6304570297287855, 6.433456340685969, 6.273301895831627, 6.16037494056048, 6.095893210586983, 6.084174285845959, 6.126057401796368, 6.22538873665406, 6.3466834428170875, 6.683372732701062, 7.181332612951737, 7.793259862381021, 8.4844126494469, 9.223966145520176, 9.788460975403439, 9.073139628982561, 8.214546654938145, 7.464630867866701, 6.91990094650014, 6.710000797269194, 6.916433180439061, 7.14825586453223, 7.400425114838014, 7.662304998397699, 7.92039351481975, 8.151171582796566, 8.327631082919531, 8.430103206116998, 8.457823172455416, 8.430581444996509, 8.403625599954433, 8.29104609013547, 8.181514105125247, 8.11817427909184, 8.079793490521658, 8.133039636691093, 8.040494460295358, 7.900998832340177, 7.734768850245368, 7.563013640721273, 7.399522952102357, 7.25413683615292, 7.131145346902163, 7.036853668810578, 6.966075663459084, 6.924472334886812, 6.9084889283868565, 7.082044597213419, 7.439754047357118, 7.659682016707104, 7.598318358795897, 7.408417734103123, 7.196961190746716, 7.001650437644878, 6.8364493722729955, 6.710000797264984, 6.919900946483244, 7.464630867778813, 8.214546655200218, 9.073142674955964, 9.788460975403439, 9.485297109078777, 9.186033809260774, 8.941761099100125, 8.780540484803373, 8.50427981640353, 8.210131403652907, 7.882983518864986, 7.490836550685967, 7.095437572253726, 6.9084889283868565, 7.08204459722489, 7.439754060940799, 7.659682016936949, 7.598318358982095, 7.408417734076556, 7.196961190728159, 7.001650437634225, 6.836449372269556, 6.710000797269194, 6.9150620212401295, 7.3759582618258, 8.010880581429562, 8.748927998292631, 8.748927137763635, 8.010880581152678, 7.375958261809146, 6.915062021229428, 6.710000797264984, 6.538437501383054, 6.402384988976937, 6.304980472852993, 6.245345720173304, 6.22538873665406 ], "yaxis": "y" }, { "legendgroup": "", "line": { "color": "black", "width": 2.0 }, "mode": "lines", "name": "", "showlegend": false, "type": "scatter", "x": [ 0.0027699052574620933, 0.010991730672077751, 0.03392455785381908, 0.08143465634094976, 0.15203770252786125, 0.22077014764627154, 0.24933157922424856, 0.21901533339719162, 0.14969550937343865, 0.08007341733798869, 0.03623284594076028, 0.02603719791477041, 0.05778155145808582, 0.15330945648621114, 0.32937765305475825, 0.5519823523669515, 0.7196014249078969, 0.7296521880552819, 0.5754865717679726, 0.35350409700917457, 0.17173088385603563, 0.0778935886712157, 0.07301578794465693, 0.15651193422689608, 0.3294946659265387, 0.5515472167158578, 0.7193719496269576, 0.7298910494717421, 0.5762674787564852, 0.3554376974781889, 0.17756775668558178, 0.09422524861264386, 0.10905236969197266, 0.21765507498840891, 0.4130222395162555, 0.6563963482012013, 0.8584716209217231, 0.9150254763418323, 0.7871582425046044, 0.5457497145678862, 0.3238573046676037, 0.23661792777399746, 0.3510799378305834, 0.678227975024836, 1.1289242303987603, 1.5041311241676676, 1.6256932892848976, 1.498866386899559, 1.276233289671086, 1.0630661082494206, 0.8431422445374459, 0.5878745683508527, 0.33836779648722015, 0.15912215302259486, 0.07612561110612173, 0.08548894925671438, 0.1871556191871238, 0.3759915722589474, 0.5966105469356292, 0.7375879358649037, 0.7113875133778955, 0.5434199934260151, 0.35850957023253777, 0.2840557276820438, 0.3761789164139926, 0.6080315196907567, 0.9034546272811442, 1.1996552441020678, 1.472829217876169, 1.6719691101341971, 1.6760109654079738, 1.4051532273413634, 0.9495071701314864, 0.5071431341896548, 0.21216213587832336, 0.0692411193478534, 0.017598109697254265, 0.0034805845550205778, 0.000535532622470643, 6.409280439215096e-05, 5.9661977307066616e-06, 4.319571040488679e-07, 2.4323932912862652e-08, 1.0653082861900373e-09, 3.6288845898559175e-11, 1.0051148302007177e-12, 2.038481906389722e-12, 7.249307139352947e-11, 2.0249188651755797e-09, 4.3997565109195006e-08, 7.436981787328391e-07, 9.78083570096839e-06, 0.00010010866061046035, 0.0007977316066220286, 0.004952405837772766, 0.02397838737753862, 0.0907082580124899, 0.26890250888910494, 0.6278351194851134, 1.1643973707315047, 1.740548772106234, 2.1493376081831626, 2.280967437028682, 2.196678868084728, 2.0243310068723104, 1.8211262915952626, 1.5575397224216, 1.2040248894614418, 0.8019864854427, 0.44428193573884245, 0.1998525409980702, 0.07186663799361771, 0.02048223117906279, 0.004835052436756405, 0.002389660503911023, 0.007870922384026363, 0.030683385441739017, 0.09889427911949542, 0.26159791070927046, 0.5679016886375159, 1.0066678861290357, 1.4445730003496429, 1.662123915821576, 1.520160567509843, 1.097562417319736, 0.6224507293423432, 0.2763214204734007, 0.09579829184400818, 0.025899049819060903, 0.005455041553956901, 0.0008984975074360561, 0.00015616111142673675, 0.00035178481629912514, 0.0021467889194562084, 0.01052012166073619, 0.040111834468368565, 0.1189531805523271, 0.27437238094949923, 0.49229160622218454, 0.6875644874132172, 0.7500635946481886, 0.6501391153049356, 0.48422849487406977, 0.3974405521452443, 0.4632534215096705, 0.6260797386744238, 0.7444553405617236, 0.7073636252867815, 0.5255896858978862, 0.30409216246783083, 0.13715820262160358, 0.050161679822412514, 0.02547514942898336, 0.05615497233668769, 0.17996171740209166, 0.4734578797135677, 0.9814739801276915, 1.6035704024895052, 2.0700643766015547, 2.116661907853083, 1.718002549773833, 1.1085448696529883, 0.5690524357077149, 0.2327813326449161, 0.07865705192104351, 0.03542843883314023, 0.06438220418151956, 0.18222511228280255, 0.44223248408494065, 0.88669747640141, 1.4867840882646732, 2.1038979775187854, 2.5130224912884174, 2.515459378206356, 2.095119472294548, 1.4736084199963975, 0.9792538448102552, 0.8384021736810937, 1.0459468183547338, 1.3749294836995944, 1.5372611578324957, 1.4252084520475965, 1.210207760761376, 1.1553661037472742, 1.3254939957920806, 1.5143244818602157, 1.4676477969580337, 1.1506423211499504, 0.7738715663871728, 0.5988221352615846, 0.7573996048436528, 1.1926096811629718, 1.6864729947793011, 1.9737151847579744, 1.9110939059153935, 1.572098715554042, 1.1959101529213643, 1.050692994060534, 1.2761697210390122, 1.7580626415299385, 2.1557725387308184, 2.1525856387007156, 1.7325672478070155, 1.1819897808893742, 0.8201232259543546, 0.7591720684960278, 0.8831762362131027, 0.9908795054870901, 0.9716178848939814, 0.8925956080413672, 0.9184232688960361, 1.1250162831195931, 1.397468542668789, 1.5320569918483216, 1.435293784870669, 1.1902844599282416, 0.9300093892450059, 0.7079560786423544, 0.5206209948648011, 0.39425210791283727, 0.3871268865364917, 0.5109494881105185, 0.678562504444509, 0.7521278611598464, 0.658806399183025, 0.4506231044372327, 0.2415438020517177, 0.10838844884915162, 0.06550363917448514, 0.1029139133734538, 0.2101886935875596, 0.35687963449777693, 0.4741974969168308, 0.49032260704395747, 0.3943416443752753, 0.24666764804702457, 0.12000486762587637, 0.045408013205060424, 0.013363280763865563, 0.0030587264599658288, 0.0005445216364832618, 7.539397785833693e-05, 8.119375082697008e-06, 6.878140839927161e-07, 1.8796299671859052e-07, 2.0613070865804862e-06, 2.2952836989879816e-05, 0.0001989971149370895, 0.0013418556623887997, 0.007037392697579229, 0.028705474023614234, 0.09106775183901811, 0.2247043490922452, 0.4312265066118682, 0.6436470870914431, 0.7472235657378983, 0.6748791257262718, 0.4753602098871118, 0.2669755171381174, 0.14262750019837586, 0.13754473023822053, 0.25330619996732046, 0.46077550840818415, 0.6774615496882385, 0.7937017606638376, 0.7596386082618748, 0.6260716735224886, 0.47789626482899505, 0.358179921697636, 0.2793586875233516, 0.270156927427067, 0.36603482587608416, 0.5482980669554804, 0.717529606842147, 0.7656802539276636, 0.6956337557984644, 0.6497480965545828, 0.788012475047745, 1.1194709736201007, 1.459561913995297, 1.5983180182969676, 1.5350704005850795, 1.4875692740501785, 1.6194228090279474, 1.8209133791204155, 1.8423889117317789, 1.6074429110340196, 1.2872560982403556, 1.0688188934328433, 0.9719360416357168, 0.9384763990606393, 0.9896059959239609, 1.1820322841621953, 1.4379590171482635, 1.5381295565514497, 1.3357805500458675, 0.9145254350194685, 0.48897640573821016, 0.20359327532172963, 0.06595483660513557, 0.016619767275502094 ], "xaxis": "x2", "y": [ -6.382596035017289, -6.332462794852706, -6.282329554688123, -6.232196314523541, -6.1820630743589575, -6.131929834194374, -6.081796594029791, -6.031663353865209, -5.981530113700626, -5.931396873536043, -5.88126363337146, -5.831130393206877, -5.780997153042295, -5.7308639128777115, -5.680730672713128, -5.630597432548545, -5.580464192383962, -5.53033095221938, -5.480197712054797, -5.430064471890214, -5.379931231725631, -5.329797991561048, -5.279664751396465, -5.229531511231882, -5.179398271067299, -5.129265030902716, -5.079131790738133, -5.028998550573551, -4.978865310408968, -4.928732070244385, -4.8785988300798016, -4.8284655899152185, -4.778332349750636, -4.728199109586053, -4.67806586942147, -4.627932629256888, -4.577799389092304, -4.527666148927722, -4.477532908763139, -4.4273996685985555, -4.377266428433973, -4.327133188269389, -4.276999948104807, -4.226866707940224, -4.176733467775641, -4.126600227611059, -4.076466987446475, -4.0263337472818925, -3.9762005071173094, -3.926067266952727, -3.8759340267881437, -3.825800786623561, -3.775667546458978, -3.725534306294395, -3.675401066129812, -3.625267825965229, -3.5751345858006465, -3.5250013456360634, -3.4748681054714803, -3.4247348653068976, -3.3746016251423145, -3.324468384977732, -3.274335144813149, -3.224201904648566, -3.174068664483983, -3.1239354243194, -3.0738021841548173, -3.0236689439902342, -2.9735357038256516, -2.9234024636610685, -2.873269223496486, -2.8231359833319027, -2.7730027431673197, -2.722869503002737, -2.672736262838154, -2.6226030226735713, -2.572469782508988, -2.522336542344405, -2.4722033021798224, -2.4220700620152393, -2.3719368218506567, -2.3218035816860736, -2.2716703415214905, -2.2215371013569083, -2.171403861192325, -2.121270621027742, -2.071137380863159, -2.021004140698576, -1.9708709005339937, -1.9207376603694106, -1.8706044202048275, -1.8204711800402444, -1.7703379398756613, -1.7202046997110791, -1.670071459546496, -1.619938219381913, -1.5698049792173299, -1.5196717390527468, -1.4695384988881646, -1.4194052587235815, -1.3692720185589984, -1.3191387783944153, -1.269005538229833, -1.21887229806525, -1.168739057900667, -1.1186058177360838, -1.0684725775715007, -1.0183393374069185, -0.9682060972423354, -0.9180728570777523, -0.8679396169131692, -0.8178063767485861, -0.7676731365840039, -0.7175398964194208, -0.6674066562548377, -0.6172734160902547, -0.5671401759256716, -0.5170069357610894, -0.46687369559650627, -0.4167404554319232, -0.3666072152673401, -0.3164739751027579, -0.2663407349381748, -0.2162074947735917, -0.1660742546090086, -0.1159410144444255, -0.0658077742798433, -0.015674534115260208, 0.034458706049322885, 0.08459194621390598, 0.13472518637848907, 0.18485842654307127, 0.23499166670765437, 0.28512490687223746, 0.33525814703682055, 0.38539138720140365, 0.43552462736598585, 0.48565786753056894, 0.535791107695152, 0.5859243478597351, 0.6360575880243173, 0.6861908281889004, 0.7363240683534835, 0.7864573085180666, 0.8365905486826497, 0.8867237888472319, 0.936857029011815, 0.9869902691763981, 1.0371235093409812, 1.0872567495055643, 1.1373899896701465, 1.1875232298347296, 1.2376564699993127, 1.2877897101638958, 1.3379229503284789, 1.388056190493061, 1.4381894306576442, 1.4883226708222272, 1.5384559109868103, 1.5885891511513925, 1.6387223913159756, 1.6888556314805596, 1.7389888716451418, 1.789122111809724, 1.839255351974308, 1.8893885921388902, 1.9395218323034724, 1.9896550724680564, 2.0397883126326386, 2.0899215527972226, 2.140054792961805, 2.190188033126387, 2.240321273290971, 2.290454513455553, 2.340587753620137, 2.3907209937847194, 2.4408542339493016, 2.4909874741138855, 2.5411207142784678, 2.5912539544430517, 2.641387194607634, 2.691520434772216, 2.7416536749368, 2.7917869151013823, 2.8419201552659663, 2.8920533954305485, 2.9421866355951307, 2.9923198757597147, 3.042453115924297, 3.092586356088881, 3.142719596253463, 3.1928528364180453, 3.2429860765826293, 3.2931193167472115, 3.3432525569117955, 3.3933857970763777, 3.44351903724096, 3.493652277405544, 3.543785517570126, 3.59391875773471, 3.6440519978992922, 3.6941852380638744, 3.7443184782284584, 3.7944517183930406, 3.844584958557623, 3.894718198722207, 3.944851438886789, 3.994984679051373, 4.045117919215955, 4.095251159380537, 4.145384399545121, 4.195517639709704, 4.245650879874288, 4.29578412003887, 4.345917360203452, 4.396050600368036, 4.446183840532618, 4.496317080697202, 4.546450320861784, 4.596583561026367, 4.6467168011909505, 4.696850041355533, 4.746983281520117, 4.797116521684699, 4.847249761849281, 4.897383002013865, 4.947516242178447, 4.997649482343031, 5.0477827225076135, 5.097915962672196, 5.14804920283678, 5.198182443001362, 5.248315683165946, 5.298448923330528, 5.34858216349511, 5.398715403659694, 5.4488486438242765, 5.4989818839888605, 5.549115124153443, 5.599248364318025, 5.649381604482609, 5.699514844647191, 5.749648084811773, 5.799781324976357, 5.849914565140939, 5.900047805305523, 5.950181045470106, 6.000314285634688, 6.050447525799272, 6.100580765963854, 6.150714006128438, 6.20084724629302, 6.250980486457602, 6.301113726622186, 6.351246966786769, 6.401380206951353, 6.451513447115935, 6.501646687280517, 6.551779927445101, 6.601913167609683, 6.652046407774267, 6.702179647938849, 6.7523128881034316, 6.8024461282680155, 6.852579368432598, 6.902712608597182, 6.952845848761764, 7.002979088926346, 7.05311232909093, 7.103245569255512, 7.153378809420096, 7.2035120495846785, 7.253645289749261, 7.303778529913845, 7.353911770078427, 7.404045010243009, 7.454178250407593, 7.504311490572175, 7.554444730736759, 7.6045779709013415, 7.654711211065924, 7.704844451230508, 7.75497769139509, 7.805110931559674, 7.855244171724256, 7.905377411888838, 7.955510652053422, 8.005643892218004, 8.055777132382588, 8.105910372547172, 8.156043612711752, 8.206176852876336, 8.25631009304092, 8.306443333205504, 8.356576573370084, 8.406709813534668, 8.456843053699252, 8.506976293863833, 8.557109534028417, 8.607242774193, 8.657376014357581 ], "yaxis": "y2" } ], "layout": { "hovermode": false, "template": { "data": { "bar": [ { "error_x": { "color": "#2a3f5f" }, "error_y": { "color": "#2a3f5f" }, "marker": { "line": { "color": "#E5ECF6", "width": 0.5 }, "pattern": { "fillmode": "overlay", "size": 10, "solidity": 0.2 } }, "type": "bar" } ], "barpolar": [ { "marker": { "line": { "color": "#E5ECF6", "width": 0.5 }, "pattern": { "fillmode": "overlay", "size": 10, "solidity": 0.2 } }, "type": "barpolar" } ], "carpet": [ { "aaxis": { "endlinecolor": "#2a3f5f", "gridcolor": "white", "linecolor": "white", "minorgridcolor": "white", "startlinecolor": "#2a3f5f" }, "baxis": { "endlinecolor": "#2a3f5f", "gridcolor": "white", "linecolor": "white", "minorgridcolor": "white", "startlinecolor": "#2a3f5f" }, "type": "carpet" } ], "choropleth": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "type": "choropleth" } ], "contour": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0.0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1.0, "#f0f921" ] ], "type": "contour" } ], "contourcarpet": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "type": "contourcarpet" } ], "heatmap": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0.0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1.0, "#f0f921" ] ], "type": "heatmap" } ], "heatmapgl": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0.0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1.0, "#f0f921" ] ], "type": "heatmapgl" } ], "histogram": [ { "marker": { "pattern": { "fillmode": "overlay", "size": 10, "solidity": 0.2 } }, "type": "histogram" } ], "histogram2d": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0.0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1.0, "#f0f921" ] ], "type": "histogram2d" } ], "histogram2dcontour": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0.0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1.0, "#f0f921" ] ], "type": "histogram2dcontour" } ], "mesh3d": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "type": "mesh3d" } ], "parcoords": [ { "line": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "parcoords" } ], "pie": [ { "automargin": true, "type": "pie" } ], "scatter": [ { "fillpattern": { "fillmode": "overlay", "size": 10, "solidity": 0.2 }, "type": "scatter" } ], "scatter3d": [ { "line": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scatter3d" } ], "scattercarpet": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scattercarpet" } ], "scattergeo": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scattergeo" } ], "scattergl": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scattergl" } ], "scattermapbox": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scattermapbox" } ], "scatterpolar": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scatterpolar" } ], "scatterpolargl": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scatterpolargl" } ], "scatterternary": [ { "marker": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "type": "scatterternary" } ], "surface": [ { "colorbar": { "outlinewidth": 0, "ticks": "" }, "colorscale": [ [ 0.0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1.0, "#f0f921" ] ], "type": "surface" } ], "table": [ { "cells": { "fill": { "color": "#EBF0F8" }, "line": { "color": "white" } }, "header": { "fill": { "color": "#C8D4E3" }, "line": { "color": "white" } }, "type": "table" } ] }, "layout": { "annotationdefaults": { "arrowcolor": "#2a3f5f", "arrowhead": 0, "arrowwidth": 1 }, "autotypenumbers": "strict", "coloraxis": { "colorbar": { "outlinewidth": 0, "ticks": "" } }, "colorscale": { "diverging": [ [ 0, "#8e0152" ], [ 0.1, "#c51b7d" ], [ 0.2, "#de77ae" ], [ 0.3, "#f1b6da" ], [ 0.4, "#fde0ef" ], [ 0.5, "#f7f7f7" ], [ 0.6, "#e6f5d0" ], [ 0.7, "#b8e186" ], [ 0.8, "#7fbc41" ], [ 0.9, "#4d9221" ], [ 1, "#276419" ] ], "sequential": [ [ 0.0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1.0, "#f0f921" ] ], "sequentialminus": [ [ 0.0, "#0d0887" ], [ 0.1111111111111111, "#46039f" ], [ 0.2222222222222222, "#7201a8" ], [ 0.3333333333333333, "#9c179e" ], [ 0.4444444444444444, "#bd3786" ], [ 0.5555555555555556, "#d8576b" ], [ 0.6666666666666666, "#ed7953" ], [ 0.7777777777777778, "#fb9f3a" ], [ 0.8888888888888888, "#fdca26" ], [ 1.0, "#f0f921" ] ] }, "colorway": [ "#636efa", "#EF553B", "#00cc96", "#ab63fa", "#FFA15A", "#19d3f3", "#FF6692", "#B6E880", "#FF97FF", "#FECB52" ], "font": { "color": "#2a3f5f" }, "geo": { "bgcolor": "white", "lakecolor": "white", "landcolor": "#E5ECF6", "showlakes": true, "showland": true, "subunitcolor": "white" }, "hoverlabel": { "align": "left" }, "hovermode": "closest", "mapbox": { "style": "light" }, "paper_bgcolor": "white", "plot_bgcolor": "#E5ECF6", "polar": { "angularaxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" }, "bgcolor": "#E5ECF6", "radialaxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" } }, "scene": { "xaxis": { "backgroundcolor": "#E5ECF6", "gridcolor": "white", "gridwidth": 2, "linecolor": "white", "showbackground": true, "ticks": "", "zerolinecolor": "white" }, "yaxis": { "backgroundcolor": "#E5ECF6", "gridcolor": "white", "gridwidth": 2, "linecolor": "white", "showbackground": true, "ticks": "", "zerolinecolor": "white" }, "zaxis": { "backgroundcolor": "#E5ECF6", "gridcolor": "white", "gridwidth": 2, "linecolor": "white", "showbackground": true, "ticks": "", "zerolinecolor": "white" } }, "shapedefaults": { "line": { "color": "#2a3f5f" } }, "ternary": { "aaxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" }, "baxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" }, "bgcolor": "#E5ECF6", "caxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" } }, "title": { "x": 0.05 }, "xaxis": { "automargin": true, "gridcolor": "white", "linecolor": "white", "ticks": "", "title": { "standoff": 15 }, "zerolinecolor": "white", "zerolinewidth": 2 }, "yaxis": { "automargin": true, "gridcolor": "white", "linecolor": "white", "ticks": "", "title": { "standoff": 15 }, "zerolinecolor": "white", "zerolinewidth": 2 } } }, "xaxis": { "anchor": "y", "domain": [ 0.0, 0.6533333333333333 ], "range": [ 0, 100 ], "tickfont": { "size": 16 }, "ticktext": [ "Γ", "X", "W", "K", "Γ", "L", "U", "W", "L", "K", "U", "X" ], "tickvals": [ 0, 14, 21, 26, 41, 53, 62, 67, 77, 86, 95, 100 ], "title": { "text": "Wave Vector" } }, "xaxis2": { "anchor": "y2", "domain": [ 0.6733333333333333, 1.0 ] }, "yaxis": { "anchor": "x", "domain": [ 0.0, 1.0 ], "title": { "text": "Energy (eV)" } }, "yaxis2": { "anchor": "x2", "domain": [ 0.0, 1.0 ], "matches": "y", "showticklabels": false } } }, "text/html": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "ebands_kpath.plotly_with_edos(edos, e0=0);" ] }, { "cell_type": "markdown", "id": "f2fc3ac5", "metadata": {}, "source": [ "This figure shows that the bands and the DOS are not perfectly aligned.\n", "More specifically we would expect the DOS to be zero at the bottom/top of the conduction.\n", "This problems is essentially due to the use of a relatively large gaussian broadening.\n", "One should therefore compute the DOS with a much denser IBZ mesh and a much smaller broadening\n", "to solve this *alignment issue*." ] } ], "metadata": { "jupytext": { "text_representation": { "extension": ".md", "format_name": "myst", "format_version": 0.13, "jupytext_version": "1.10.3" } }, "kernelspec": { "display_name": "Python 3", "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": "3.12.2" }, "source_map": [ 12, 39, 55, 60, 70, 73, 77, 79, 83, 85, 89, 93, 97, 100, 104, 106, 119, 138, 142, 152, 157, 160, 166, 173, 177, 179, 183, 185, 191, 198, 200, 206, 214, 216, 220, 227, 232, 235, 242, 250, 253, 257, 261, 265, 269, 271, 275, 277, 281, 283, 287, 289, 297, 303, 305, 309, 311, 315, 319, 321, 328, 342, 345, 350, 353, 360, 364, 367, 371, 373, 384, 386, 394, 397, 401, 405, 408, 413, 418, 422, 424, 434, 436, 440, 442, 447, 449, 453, 455 ] }, "nbformat": 4, "nbformat_minor": 5 }