{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "bdf377b8",
   "metadata": {},
   "source": [
    "# Analisi completa della molla 1\n",
    "Tutto quello che c'è da sapere sulla molla 1, possibilmente con la massima chiarezza."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "3a34cc3f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Heavy lifting\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from scipy import stats\n",
    "\n",
    "# Mostrare i dati\n",
    "import ipysheet\n",
    "from IPython.display import display\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "# Calcolo simbolico\n",
    "import sympy as sp\n",
    "\n",
    "\n",
    "G = 9.806\n",
    "uG = 0.004"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0eaece9c",
   "metadata": {},
   "source": [
    "# Analisi dati del calibro"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "960e68a5",
   "metadata": {},
   "source": [
    "## Import dei dati calibro (criterio di Chauvenet)\n",
    "- Primo test di implementazione 1\n",
    "- Scrittura con logica chiara   2\n",
    "- Codice pulito per bene        3 (sono abbastanza soddisfatto)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "1e2fabea",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Blocco funzioni per Chauvenet\n",
    "# Probabilità\n",
    "def p_t_student(valori, err_strumentale):\n",
    "  n   = len(valori)\n",
    "  GdL = n - 1\n",
    "  if n <= 2:\n",
    "    return np.ones(n)\n",
    "\n",
    "  media = valori.mean()\n",
    "  s     = valori.std(ddof=1)\n",
    "  if s == 0:\n",
    "    return np.ones(n)\n",
    "\n",
    "  s = np.sqrt(s**2 + err_strumentale**2)\n",
    "  return 2 * (1 - stats.t.cdf(np.abs(valori - media) / s, df=GdL))\n",
    "\n",
    "# Indice del peggiore outlier o None\n",
    "def trova_outlier(valori, err_strumentale):\n",
    "  n       = len(valori)\n",
    "  soglia  = 1 / (2 * n)\n",
    "  p       = p_t_student(valori, err_strumentale)\n",
    "  idx_min = np.argmin(p)\n",
    "\n",
    "  if p[idx_min] < soglia:\n",
    "      return idx_min\n",
    "  return None\n",
    "\n",
    "# Rimuove outlier\n",
    "def rimuovi_outlier(valori, err_strumentale):\n",
    "  rimossi  = []\n",
    "  campione = valori.copy()\n",
    "\n",
    "  while len(campione) > 2:\n",
    "    idx = trova_outlier(campione, err_strumentale)\n",
    "\n",
    "    if idx is None: # nessun outlier: stop\n",
    "      break\n",
    "\n",
    "    rimossi.append(campione[idx])\n",
    "    campione = np.delete(campione, idx)\n",
    "\n",
    "  return campione, rimossi\n",
    "\n",
    "# return media u rimossi []\n",
    "def stats_riga(valori_raw, err_strumentale):\n",
    "  # caso 0\n",
    "  if len(valori_raw) == 0:\n",
    "    return {\"media\": np.nan, \"u\": np.nan, \"n\": 0, \"rimossi\": []}\n",
    "\n",
    "  # caso 1\n",
    "  if len(valori_raw) == 1:\n",
    "    return {\"media\": valori_raw[0], \"u\": err_strumentale, \"n\": 1, \"rimossi\": []}\n",
    "\n",
    "  # caso n>1\n",
    "  puliti, rimossi = rimuovi_outlier(valori_raw, err_strumentale)\n",
    "\n",
    "  media = puliti.mean()\n",
    "\n",
    "  s = puliti.std(ddof=1)\n",
    "  n = len(puliti)\n",
    "  s = s / np.sqrt(n)\n",
    "  s = np.sqrt(s**2 + err_strumentale**2)\n",
    "\n",
    "  return {\"media\": media, \"u\": s, \"n\": n, \"rimossi\": rimossi}\n",
    "\n",
    "# Calcola la statistica con Criterio di Chauvenet\n",
    "def calcola_stats(df, prefix, err_strumentale):\n",
    "  cols = [col for col in df.columns if col.startswith(prefix)]\n",
    "\n",
    "  for i, row in df.iterrows():\n",
    "    valori = row[cols].dropna().values.astype(float)\n",
    "    ans    = stats_riga(valori, err_strumentale)\n",
    "\n",
    "    df.at[i, prefix]         = ans[\"media\"]\n",
    "    df.at[i, f\"u{prefix}\"]   = ans[\"u\"]\n",
    "    df.at[i, f\"n{prefix}\"]   = int(ans[\"n\"])\n",
    "    df.at[i, f\"out{prefix}\"] = str(ans[\"rimossi\"])\n",
    "\n",
    "  return df\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "a5ff5ff5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "F  = g*m\n",
      "sigma_F = sqrt(g**2*sigma_m**2 + m**2*sigma_g**2)\n",
      "\n",
      "Formula LaTeX:\n",
      "F = g m\n",
      "sigma_F = \\sqrt{g^{2} \\sigma_{m}^{2} + m^{2} \\sigma_{g}^{2}}\n"
     ]
    }
   ],
   "source": [
    "# Blocco funzioni calcolo simbolico la forza\n",
    "# simboli\n",
    "m, x, g = sp.symbols('m x g', positive=True)\n",
    "sigma_m, sigma_x, sigma_g = sp.symbols('sigma_m sigma_x sigma_g', positive=True)\n",
    "\n",
    "F = m * g\n",
    "\n",
    "# derivate parziali\n",
    "dF_dm = sp.diff(F, m)\n",
    "dF_dg = sp.diff(F, g)\n",
    "\n",
    "sigma_F = sp.sqrt((dF_dm * sigma_m)**2 + (dF_dg * sigma_g)**2)\n",
    "\n",
    "print(\"F  =\", F)\n",
    "print(\"sigma_F =\", sigma_F)\n",
    "print(\"\\nFormula LaTeX:\")\n",
    "print(f\"F = {sp.latex(F)}\")\n",
    "print(f\"sigma_F = {sp.latex(sigma_F.simplify())}\")\n",
    "\n",
    "# funzioni numeriche\n",
    "F_fn  = sp.lambdify((m, g),  F,  'numpy')\n",
    "uF_fn = sp.lambdify((m, sigma_m, g, sigma_g), sigma_F, 'numpy')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "e649eddc",
   "metadata": {},
   "outputs": [],
   "source": [
    "dfCalibro = pd.read_csv(r'molla2Calibro.csv')\n",
    "\n",
    "# Costanti strumentali\n",
    "ERR_CALIBRO = 0.02 / np.sqrt(12)\n",
    "ERR_BILANCIA = 0.01 / np.sqrt(12)\n",
    "\n",
    "# Chauvenet e poi statistica di base\n",
    "dfCalibro = calcola_stats(dfCalibro, \"dx\", ERR_CALIBRO)\n",
    "dfCalibro = calcola_stats(dfCalibro, \"m\",  ERR_BILANCIA)\n",
    "\n",
    "# Aggiunta delle forze\n",
    "dfCalibro[\"F\"]  = F_fn(dfCalibro[\"m\"],  G)\n",
    "dfCalibro[\"uF\"] = uF_fn(dfCalibro[\"m\"], dfCalibro[\"um\"], G, uG)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "42ff21d6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "ac92a8cbb63f4b5a9e8b0a61f9c44dc0",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Sheet(cells=(Cell(column_end=0, column_start=0, row_start=0, squeeze_row=False, type='numeric', value=[49.25, …"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sheet = ipysheet.from_dataframe(dfCalibro)\n",
    "\n",
    "display(sheet)\n",
    "# dfCalibro.head(2).to_json(orient=\"records\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c58a6e26",
   "metadata": {},
   "source": [
    "## Regressione lineare Carpi dati del calibro\n",
    "chi² Come persone normali"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "dfab4331",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Blocco di funzione regressione Carpi\n",
    "def sigma_y_equiv(x, y, sigma_x, sigma_y):\n",
    "  # Stima iniziale di A con sola sigma_y\n",
    "  sy2 = sigma_y**2\n",
    "  Sw   = np.sum(1 / sy2)\n",
    "  Sx   = np.sum(x / sy2)\n",
    "  Sxx  = np.sum(x**2 / sy2)\n",
    "  Sy   = np.sum(y / sy2)\n",
    "  Sxy  = np.sum(x * y / sy2)\n",
    "  delta = Sxx * Sw - Sx**2\n",
    "  A_est = (Sxy * Sw - Sx * Sy) / delta\n",
    "\n",
    "  # Propagazione\n",
    "  sigma_eq = np.sqrt(sigma_y**2 + A_est**2 * sigma_x**2)\n",
    "  return sigma_eq\n",
    "\n",
    "\n",
    "def reg_lin(x, y, sigma_x, sigma_y):\n",
    "  x = np.asarray(x, dtype=float)\n",
    "  y = np.asarray(y, dtype=float)\n",
    "  sigma_x = np.asarray(sigma_x, dtype=float)\n",
    "  sigma_y = np.asarray(sigma_y, dtype=float)\n",
    "\n",
    "  # Propagazione errore x → y\n",
    "  sigma_y_eq = sigma_y_equiv(x, y, sigma_x, sigma_y)\n",
    "\n",
    "  # Somme pesate\n",
    "  w    = 1.0 / sigma_y_eq**2\n",
    "  Sw   = np.sum(w)\n",
    "  Sx   = np.sum(w * x)\n",
    "  Sxx  = np.sum(w * x**2)\n",
    "  Sy   = np.sum(w * y)\n",
    "  Sxy  = np.sum(w * x * y)\n",
    "  delta = Sxx * Sw - Sx**2\n",
    "\n",
    "  # Parametri\n",
    "  A      = (Sxy * Sw - Sx * Sy)  / delta\n",
    "  B      = (Sxx * Sy - Sxy * Sx) / delta\n",
    "  sigma_A = np.sqrt(Sw  / delta)\n",
    "  sigma_B = np.sqrt(Sxx / delta)\n",
    "  cov_AB  = -Sx / delta\n",
    "\n",
    "  # Chi quadro\n",
    "  x2  = np.sum((y - A * x - B)**2 / sigma_y_eq**2)\n",
    "  dof = len(x) - 2\n",
    "  P = stats.chi2.sf(x2, dof)\n",
    "\n",
    "  return A, B, sigma_A, sigma_B, cov_AB, x2, P"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5d7ca0a0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Residuo:\n",
      "  r = -A*x - B + y\n",
      "\n",
      "Formula LaTeX:\n",
      "  r       = - A x - B + y\n",
      "  sigma_r = \\sqrt{A^{2} \\sigma_{x}^{2} + 2 cov_{AB} x + \\sigma_{A}^{2} x^{2} + \\sigma_{B}^{2} + \\sigma_{y}^{2}}\n"
     ]
    }
   ],
   "source": [
    "# Blocco calcolo simbolico residui\n",
    "A, B, x, y = sp.symbols('A B x y', real=True)\n",
    "sigma_A, sigma_B, sigma_x, sigma_y = sp.symbols('sigma_A sigma_B sigma_x sigma_y', positive=True)\n",
    "cov_AB = sp.symbols('cov_AB', real=True)\n",
    "\n",
    "# Residuo: r = x - (y/A - B/A)\n",
    "r = y - (A*x + B)\n",
    "\n",
    "# Propagazione errore (con covarianza A,B)\n",
    "dr_dA  = sp.diff(r, A)\n",
    "dr_dB  = sp.diff(r, B)\n",
    "dr_dx  = sp.diff(r, x)\n",
    "dr_dy  = sp.diff(r, y)\n",
    "\n",
    "sigma_r  = sp.sqrt(\n",
    "  (dr_dA * sigma_A)**2 +\n",
    "  (dr_dB * sigma_B)**2 +\n",
    "  (dr_dx * sigma_x)**2 +\n",
    "  (dr_dy * sigma_y)**2 +\n",
    "  2 * dr_dA * dr_dB * cov_AB\n",
    ")\n",
    "\n",
    "# Funzioni numeriche\n",
    "r_fn      = sp.lambdify((x , y , A , B ), r, 'numpy')\n",
    "sigma_r_fn = sp.lambdify(\n",
    "  (x , y , A , B , sigma_x , sigma_y , sigma_A , sigma_B , cov_AB ),\n",
    "  sigma_r , 'numpy'\n",
    ")\n",
    "\n",
    "print(\"Residuo:\")\n",
    "print(f\"  r = {r }\")\n",
    "print(f\"\\nFormula LaTeX:\")\n",
    "print(f\"  r       = {sp.latex(r)}\")\n",
    "print(f\"  sigma_r = {sp.latex(sp.simplify(sigma_r))}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "cd68b201",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ax + B : \n",
      "AC      = 3.2009 ± 0.0034\n",
      "BC      = 1161.4138 ± 0.4687\n",
      "cov_ABC = 0.001385\n",
      "chi²    = 4.3252\n",
      "P(chi², ∞)= 0.1150\n"
     ]
    }
   ],
   "source": [
    "AC, BC, uAC, uBC, covABC, chiC, PC = reg_lin(-dfCalibro[\"dx\"], dfCalibro[\"F\"], dfCalibro[\"udx\"], dfCalibro[\"uF\"])\n",
    "print(\"Ax + B : \")\n",
    "print(f\"AC      = {AC:.4f} ± {uAC:.4f}\")\n",
    "print(f\"BC      = {BC:.4f} ± {uBC:.4f}\")\n",
    "print(f\"cov_ABC = {covABC:.6f}\")\n",
    "print(f\"chi²    = {chiC:.4f}\")\n",
    "print(f\"P(chi², ∞)= {PC:.4f}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "f98a3612",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calcolo numerico residui sul dfCalibro\n",
    "dfCalibro[\"r\"] = r_fn(\n",
    "  -dfCalibro[\"dx\"],\n",
    "  dfCalibro[\"F\"],\n",
    "  AC,\n",
    "  BC\n",
    ")\n",
    "\n",
    "dfCalibro[\"ur\"] = sigma_r_fn(\n",
    "  -dfCalibro[\"dx\"], dfCalibro[\"F\"],\n",
    "  AC, BC,\n",
    "  dfCalibro[\"udx\"], dfCalibro[\"uF\"],\n",
    "  uAC, uBC, covABC\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "89564ae9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Probabilità chi quadro con incertezza residui invece di sigmaY_equiv\n",
      "P(chi², ∞)= 0.1901\n"
     ]
    }
   ],
   "source": [
    "x2  = np.sum(dfCalibro['r']**2 / dfCalibro['ur']**2)\n",
    "dof = 4 - 2\n",
    "P = stats.chi2.sf(x2, dof)\n",
    "print('Probabilità chi quadro con incertezza residui invece di sigmaY_equiv')\n",
    "print(f\"P(chi², ∞)= {P:.4f}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5de53d0e",
   "metadata": {},
   "source": [
    "### Grafici calibro"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "68eb66dc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Fit\n",
    "SCALA = 10\n",
    "fig, ax = plt.subplots(figsize=(8, 5))\n",
    "\n",
    "x_data = -dfCalibro[\"dx\"]\n",
    "y_data =  dfCalibro[\"F\"]\n",
    "\n",
    "x_fit = np.linspace(x_data.min(), x_data.max(), 300)\n",
    "y_fit = AC * x_fit + BC\n",
    "\n",
    "ax.errorbar(\n",
    "    x_data, y_data,\n",
    "    xerr=SCALA * dfCalibro[\"udx\"], yerr=SCALA * dfCalibro[\"uF\"],\n",
    "    fmt='o', color=sns.color_palette()[0],\n",
    "    ecolor='gray', elinewidth=1, capsize=3,\n",
    "    markersize=5, label=f\"Dati (barre errore x{SCALA})\"\n",
    ")\n",
    "ax.plot(\n",
    "    x_fit, y_fit,\n",
    "    color='red', linewidth=1.5,\n",
    "    label=f\"Fit: $A={AC:.3f}\\\\pm{uAC:.3f}$\\n\"\n",
    "          f\"     $B={BC:.2f}\\\\pm{uBC:.2f}$\\n\"\n",
    ")\n",
    "\n",
    "sns.despine(ax=ax)\n",
    "ax.set_xlabel(r\"$- x$  [mm]\")\n",
    "ax.set_ylabel(\"F  [mN]\")\n",
    "ax.set_title(\"Fit lineare — Molla 1 (calibro)\")\n",
    "ax.legend(fontsize=9)\n",
    "ax.grid(True, linestyle=':', linewidth=0.5, alpha=0.7)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "831a4ac6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(8, 5))\n",
    "\n",
    "# Residui con barre d'errore\n",
    "ax.errorbar(\n",
    "    dfCalibro[\"F\"], dfCalibro[\"r\"],\n",
    "    xerr=dfCalibro[\"uF\"], yerr=dfCalibro[\"ur\"],\n",
    "    fmt='o', color=sns.color_palette()[0],\n",
    "    ecolor='gray', elinewidth=1, capsize=3,\n",
    "    markersize=5, label=\"Residui\"\n",
    ")\n",
    "\n",
    "# Linea dello zero\n",
    "ax.axhline(0, color='red', linestyle='--', linewidth=1)\n",
    "\n",
    "# Estetica\n",
    "sns.despine(ax=ax)\n",
    "ax.set_xlabel(\"F  [mN]\")\n",
    "ax.set_ylabel(r\"Residuo $x_i - \\left(\\frac{y_i}{A} - \\frac{B}{A}\\right)$  [mm]\")\n",
    "ax.set_title(\"Residui della regressione — Molla 2 (calibro)\")\n",
    "ax.legend()\n",
    "ax.grid(True, linestyle=':', linewidth=0.5, alpha=0.7)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c5e02e3d",
   "metadata": {},
   "source": [
    "### Sezione non espressamente richiesta\n",
    "Dal grafico dei residui risulta chiaro che tutti i punti sono \"sotto\" mentre uno solo è \"sopra\".\n",
    "Per diletto personale ho voluto vedere cosa sarebbe successo escludendo quel punto.\n",
    "\n",
    "La sezione riguarda solo **Esclusione del punto 1**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "17cbeaea",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fit completo:   chi²=4.33,  P=0.1150\n",
      "Senza punto 1:  chi²=0.007,  P=0.9328\n",
      "\n",
      "A:  3.2009 ± 0.0034  to  3.1995 ± 0.0034\n",
      "B:  1161.4138 ± 0.4687  to  1161.4675 ± 0.4694\n"
     ]
    }
   ],
   "source": [
    "mask = dfCalibro.index != 1\n",
    "dfCalibro_senza1 = dfCalibro.loc[mask]\n",
    "dfCalibro_senza1 = dfCalibro_senza1.copy()\n",
    "\n",
    "AC2, BC2, uAC2, uBC2, covABC2, chiC2, PC2 = reg_lin(-dfCalibro_senza1[\"dx\"], dfCalibro_senza1[\"F\"], dfCalibro_senza1[\"udx\"], dfCalibro_senza1[\"uF\"])\n",
    "\n",
    "print(f\"Fit completo:   chi²={chiC:.2f},  P={PC:.4f}\")\n",
    "print(f\"Senza punto 1:  chi²={chiC2:.3f},  P={PC2:.4f}\")\n",
    "print()\n",
    "print(f\"A:  {AC:.4f} ± {uAC:.4f}  to  {AC2:.4f} ± {uAC2:.4f}\")\n",
    "print(f\"B:  {BC:.4f} ± {uBC:.4f}  to  {BC2:.4f} ± {uBC2:.4f}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "0bc01605",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "dataFrame  CALIBRO\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "c65c6232130744bfb88bee203ff1afe0",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Sheet(cells=(Cell(column_end=0, column_start=0, row_start=0, squeeze_row=False, type='numeric', value=[49.25, …"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "dataFrame  CALIBRO TOLTO DATO 1\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "932691f151f34a228f46544b11b0f080",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Sheet(cells=(Cell(column_end=0, column_start=0, row_end=2, row_start=0, squeeze_row=False, type='numeric', val…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Ricalcolo Residui\n",
    "dfCalibro_senza1[\"r\"] = r_fn(\n",
    "  -dfCalibro_senza1[\"dx\"],\n",
    "   dfCalibro_senza1[\"F\"],\n",
    "   AC2, BC2\n",
    ")\n",
    "\n",
    "dfCalibro_senza1[\"ur\"] = sigma_r_fn(\n",
    "  -dfCalibro_senza1[\"dx\"], dfCalibro_senza1[\"F\"],\n",
    "   AC2, BC2,\n",
    "   dfCalibro_senza1[\"udx\"], dfCalibro_senza1[\"uF\"],\n",
    "   uAC2, uBC2, covABC2\n",
    ")\n",
    "\n",
    "print(\"dataFrame  CALIBRO\")\n",
    "sheet = ipysheet.from_dataframe(dfCalibro)\n",
    "display(sheet)\n",
    "\n",
    "print(\"\\ndataFrame  CALIBRO TOLTO DATO 1\")\n",
    "sheet = ipysheet.from_dataframe(dfCalibro_senza1)\n",
    "display(sheet)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "d2c1a550",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABQkAAAIDCAYAAACnwpgdAAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjgsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvwVt1zgAAAAlwSFlzAAAPYQAAD2EBqD+naQAApnBJREFUeJzs3Xd4VWW69/HfDpBCCsUACRGpCiigDAhiA8eGXVGwHoFRsSEqdp0XxTIcdVQcO3MU7CKKdewKOHZBEHWUZkBID5AeUtf7Byf7sNkJJGHlXknW93NduYRd73zzZM+ah10CjuM4AgAAAAAAAOBbEV4PAAAAAAAAAMBbbBICAAAAAAAAPscmIQAAAAAAAOBzbBICAAAAAAAAPscmIQAAAAAAAOBzbBICAAAAAAAAPscmIQAAAAAAAOBzbBICAAAAAAAAPscmIQAAAAAAAOBzbBICAIAGWbNmjY477jh16NBBgUBAb775ptcjtSi9evXSpEmTdnu5efPmKRAIaP369Q2+j8WLFysQCGjx4sUNvm5LEQgEdMcddwT/vie9mtIVV1yhY489tsluf+f1VNvPfsyYMRo0aFCTzbCjm2++WSNHjjS5LwAA4C42CQEAaIHWrVunSy+9VH369FF0dLQSEhJ02GGH6eGHH1ZpaWmT3vfEiRP1008/6Z577tHzzz+v4cOHN+n97ew///mP7rjjjma3GYT/c8cddygQCCgiIkIbN24MO7+goEAxMTEKBAKaOnWqBxPuXlFRkW6//XaNHTtWnTt3ViAQ0Lx58xp0G6mpqfqf//kf3XrrrU0zZDN0zTXX6Mcff9Tbb7/t9SgAAKCB2no9AAAAaJh//etfGj9+vKKionThhRdq0KBBKi8v1xdffKEbbrhBv/zyi+bMmdMk911aWqqvv/5at912m2ebO//5z380c+ZMjRkzRr169fJkhj2xatUqRUQ07b/THnnkkSotLVVkZGST3s/uREVF6eWXX9aNN94YcvrChQs9mqj+cnNzdeedd2qfffbRgQce2KhnZT788MPq3bu3jjrqKPcHrIPXP/ukpCSddtpp+vvf/65TTz3VkxkAAEDj8ExCAABakNTUVJ1zzjnq2bOn/vOf/+jhhx/WJZdcoiuvvFIvv/yy/vOf/+iAAw5osvvPycmRJHXs2HG3ly0uLm6yOaw0xfcQFRWldu3auX67O4qIiFB0dHSTb0buzoknnqiXX3457PSXXnpJJ510kgcT1V9ycrIyMjK0YcMG3X///Q2+fkVFhV588UVNmDChCaarm9s/+23btqm6urpB15kwYYK++OIL/f77767MAAAAbLBJCABAC3LfffepqKhITz/9tJKTk8PO79evn66++urg3ysrK3XXXXepb9++ioqKUq9evXTrrbeqrKws5Hq9evXSySefrC+++EIjRoxQdHS0+vTpo+eeey54mTvuuEM9e/aUJN1www0KBALBZ/LVvLz0P//5j8477zx16tRJhx9+uOszzJs3T+PHj5ckHXXUUQoEAmHvv/b444/rgAMOUFRUlLp3764rr7xSeXl5u227q+9Bkl544QUNGzZMMTEx6ty5s84555ywl9KuWbNGZ555ppKSkhQdHa29995b55xzjvLz80O+z53fk/CXX37Rn//8Z8XExGjvvffW3XffXevGzM7vw1fXbTaX9yQ877zztGLFCv3222/B0zIzM/XZZ5/pvPPOq/U62dnZuuiii9StWzdFR0frwAMP1LPPPtuo+3/rrbd00kknqXv37oqKilLfvn111113qaqqarfXjYqKUlJSUqPuV5K++OIL5ebm6phjjgk7b9u2bbrjjju03377KTo6WsnJyRo3bpzWrVsXvMzf//53HXroodprr70UExOjYcOG6bXXXtvt/e7qZ79s2TIdeuihiomJUe/evfXkk0/Wet1XXnlFf/3rX5WSkqL27duroKBAkrRgwYLg70BiYqIuuOACpaWlhd1Pzff81ltv7XZeAADQfPByYwAAWpB33nlHffr00aGHHlqvy1988cV69tlnddZZZ+m6667Tt99+q1mzZunXX3/VG2+8EXLZtWvX6qyzztJFF12kiRMn6plnntGkSZM0bNgwHXDAARo3bpw6duyoa6+9Vueee65OPPFExcXFhdzG+PHjte++++pvf/ubHMdxfYYjjzxS06ZN0z/+8Q/deuutGjhwoCQF/3vHHXdo5syZOuaYY3T55Zdr1apVeuKJJ/T999/ryy+/rNcz+Gr7Hu655x79v//3/zRhwgRdfPHFysnJ0SOPPKIjjzxSy5cvV8eOHVVeXq7jjz9eZWVluuqqq5SUlKS0tDS9++67ysvLU4cOHWq9v8zMTB111FGqrKzUzTffrNjYWM2ZM0cxMTH1+Ak3b0ceeaT23ntvvfTSS7rzzjslSfPnz1dcXFytzyQsLS3VmDFjtHbtWk2dOlW9e/fWggULNGnSJOXl5YVsgNfHvHnzFBcXp+nTpysuLk6fffaZZsyYoYKCgkY9O7AhvvrqKwUCAQ0dOjTk9KqqKp188sn69NNPdc455+jqq69WYWGhPv74Y/3888/q27evpO0vVT711FN1/vnnq7y8XK+88orGjx+vd999t1HPwty6datOPPFETZgwQeeee65effVVXX755YqMjNRf/vKXkMveddddioyM1PXXX6+ysjJFRkZq3rx5mjx5sg4++GDNmjVLWVlZevjhh/Xll18GfwdqdOjQQX379tWXX36pa6+9tuHxAACANxwAANAi5OfnO5Kc0047rV6XX7FihSPJufjii0NOv/766x1JzmeffRY8rWfPno4k5/PPPw+elp2d7URFRTnXXXdd8LTU1FRHknP//feH3Obtt9/uSHLOPffcJp9hwYIFjiRn0aJFIbeZnZ3tREZGOscdd5xTVVUVPP3RRx91JDnPPPNMna129T2sX7/eadOmjXPPPfeEnP7TTz85bdu2DZ6+fPlyR5KzYMGCXd5Pz549nYkTJwb/fs011ziSnG+//Tbke+nQoYMjyUlNTQ2eLsm5/fbbd3ubixYtqrWRlZqWOTk5zvXXX+/069cveN7BBx/sTJ482XGc7d/PlVdeGTxv9uzZjiTnhRdeCJ5WXl7ujBo1yomLi3MKCgqCp+/cYu7cuWG9SkpKwma79NJLnfbt2zvbtm2r9/fz/fffO5KcuXPn1vs6F1xwgbPXXnuFnf7MM884kpwHH3ww7Lzq6urgn3eevby83Bk0aJDz5z//OeT0+vzsR48e7UhyHnjggeBpZWVlzkEHHeR07drVKS8vD7lunz59Qu6/vLzc6dq1qzNo0CCntLQ0ePq7777rSHJmzJgR9r0cd9xxzsCBA8NOBwAAzRcvNwYAoIWoeclffHx8vS7/3nvvSZKmT58ecvp1110nafsHoOxo//331xFHHBH8e5cuXdS/f/8Gva/YZZdd5tkMn3zyicrLy3XNNdeEvB/bJZdcooSEhLD7qu/3sHDhQlVXV2vChAnKzc0NfiUlJWnffffVokWLJCn4TMEPP/xQJSUl9bovaXujQw45RCNGjAie1qVLF51//vn1vo3m7LzzztPatWv1/fffB/9b10uN33vvPSUlJencc88NntauXTtNmzZNRUVFWrJkSYPue8dnYxYWFio3N1dHHHGESkpKQl4C3RQ2b96sTp06hZ3++uuvKzExUVdddVXYeYFAIPjnHWffunWr8vPzdcQRR+iHH35o1Dxt27bVpZdeGvx7ZGSkLr30UmVnZ2vZsmUhl504cWLI/S9dulTZ2dm64oorFB0dHTz9pJNO0oABA2r93erUqZNyc3MbNSsAAPAGLzcGAKCFSEhIkLR9s6M+NmzYoIiICPXr1y/k9KSkJHXs2FEbNmwIOX2fffYJu41OnTpp69at9Z6xd+/ens1Qc1v9+/cPOT0yMlJ9+vQJu6/6fg9r1qyR4zjad999a718zUuYe/furenTp+vBBx/Uiy++qCOOOEKnnnqqLrjggjpfalwz98iRI8NO3/n7cFt5ebm2bNnSqOtGRkaqc+fO9brs0KFDNWDAAL300kvq2LGjkpKS9Oc//7nWy27YsEH77rtv2Idu1LycvL4/wxq//PKL/vrXv+qzzz4LbrLX2PF9IpuK878vV9/RunXr1L9/f7Vtu+vD8HfffVd33323VqxYEfL+nTtuJDZE9+7dFRsbG3LafvvtJ0lav369DjnkkODptf0eS7WvyQEDBuiLL74IO91xnEbPCgAAvMEmIQAALURCQoK6d++un3/+uUHXq+//UW/Tpk2tp9e20VGXut5Hz3KGPbXz91BdXa1AIKD333+/1vl2fF/GBx54QJMmTdJbb72ljz76SNOmTdOsWbP0zTffaO+9926ymevzQRw7++qrr3TUUUc16v5Gjx7doA9FOe+88/TEE08oPj5eZ599tsmnLufl5Wn06NFKSEjQnXfeqb59+yo6Olo//PCDbrrppgZ/Ym9D7bXXXg3aYN/Rv//9b5166qk68sgj9fjjjys5OVnt2rXT3Llz9dJLL7k8aTg33g9z69atSkxMdGEaAABghU1CAABakJNPPllz5szR119/rVGjRu3ysj179lR1dbXWrFkTfCaWJGVlZSkvLy/4ScVNqSlmqGvDsea2Vq1apT59+gRPLy8vV2pqaq2fMlsfffv2leM46t27d/CZV7syePBgDR48WH/961/11Vdf6bDDDtOTTz6pu+++u86516xZE3b6qlWrwk7r1KlT2Cc1l5eXKyMjo37fzA4OPPBAffzxxw2+Xs0cDXHeeedpxowZysjI0PPPP1/n5Xr27KmVK1equro6ZCOx5qXBDVkvixcv1ubNm7Vw4UIdeeSRwdNTU1MbNHtjDRgwQC+++KLy8/NDnknat29fffvtt6qoqKjzg3Ref/11RUdH68MPP1RUVFTw9Llz5zZ6nvT0dBUXF4c8m3D16tWSFPyU8rrs+Lu187NAV61aVevPJTU1VQceeGCj5wUAAPZ4T0IAAFqQG2+8UbGxsbr44ouVlZUVdv66dev08MMPS5JOPPFESdLs2bNDLvPggw9KUqM+IbWhmmKGmk2OnTfLjjnmGEVGRuof//hHyDMPn376aeXn5zf6+x03bpzatGmjmTNnhj2j0XEcbd68WdL294ysrKwMOX/w4MGKiIgIebnozk488UR98803+u6774Kn5eTk6MUXXwy7bN++ffX555+HnDZnzpxGPZOwU6dOOuaYYxr1NWzYsAbdV9++fTV79mzNmjUr5L0Xd3biiScqMzNT8+fPD55WWVmpRx55RHFxcRo9enS977PmWZ87/szKy8v1+OOPN2j2xho1apQcxwl7v78zzzxTubm5evTRR8OuUzNrmzZtFAgEQn6u69ev15tvvtnoeSorK/XUU08F/15eXq6nnnpKXbp02e3Pc/jw4eratauefPLJkLX8/vvv69dffw373crPz9e6devq/SnsAACgeeCZhAAAtCB9+/bVSy+9pLPPPlsDBw7UhRdeqEGDBqm8vFxfffWVFixYoEmTJkna/kyxiRMnas6cOcGXXn733Xd69tlndfrppzf6paYN0RQzHHTQQWrTpo3uvfde5efnKyoqSn/+85/VtWtX3XLLLZo5c6bGjh2rU089VatWrdLjjz+ugw8+WBdccEGjvoe+ffvq7rvv1i233KL169fr9NNPV3x8vFJTU/XGG29oypQpuv766/XZZ59p6tSpGj9+vPbbbz9VVlbq+eefV5s2bXTmmWfWefs33nijnn/+eY0dO1ZXX321YmNjNWfOnOCz6nZ08cUX67LLLtOZZ56pY489Vj/++KM+/PDDFvGyzquvvnq3l5kyZYqeeuopTZo0ScuWLVOvXr302muv6csvv9Ts2bPr/aE9knTooYeqU6dOmjhxoqZNm6ZAIKDnn3++QS9df/TRR5WXl6f09HRJ0jvvvKNNmzZJkq666qpdvtfk4Ycfrr322kuffPJJyLPvLrzwQj333HOaPn26vvvuOx1xxBEqLi7WJ598oiuuuEKnnXaaTjrpJD344IMaO3aszjvvPGVnZ+uxxx5Tv379wtZEfXXv3l333nuv1q9fr/3220/z58/XihUrNGfOnDqf0VijXbt2uvfeezV58mSNHj1a5557rrKysvTwww+rV69euvbaa0Mu/8knn8hxHJ122mmNmhUAAHjEi49UBgAAe2b16tXOJZdc4vTq1cuJjIx04uPjncMOO8x55JFHnG3btgUvV1FR4cycOdPp3bu3065dO6dHjx7OLbfcEnIZx3Gcnj17OieddFLY/YwePdoZPXp08O+pqamOJOf+++8Pudztt9/uSHJycnLCbsPtGRzHcf75z386ffr0cdq0aeNIchYtWhQ879FHH3UGDBjgtGvXzunWrZtz+eWXO1u3bg273Z3t6ntwHMd5/fXXncMPP9yJjY11YmNjnQEDBjhXXnmls2rVKsdxHOf33393/vKXvzh9+/Z1oqOjnc6dOztHHXWU88knn4R9nxMnTgw5beXKlc7o0aOd6OhoJyUlxbnrrrucp59+2pHkpKamBi9XVVXl3HTTTU5iYqLTvn175/jjj3fWrl0bdpuLFi0K62Jpdy1rSHKuvPLKkNOysrKcyZMnO4mJiU5kZKQzePBgZ+7cubVe9/bbbw/+fe7cuWG9vvzyS+eQQw5xYmJinO7duzs33nij8+GHH9a7Tc+ePR1JtX7teD91mTZtmtOvX7+w00tKSpzbbrst+DuRlJTknHXWWc66deuCl3n66aedfffd14mKinIGDBjgzJ07N9h15xl397MfPXq0c8ABBzhLly51Ro0a5URHRzs9e/Z0Hn300ZDbqrnuggULav1+5s+f7wwdOtSJiopyOnfu7Jx//vnOpk2bwi539tlnO4cffvhu+wAAgOYl4DiG7wQOAAAA+MTvv/+uAQMG6P3339fRRx/t9TgmMjMz1bt3b73yyis8kxAAgBaGTUIAAACgiVx++eVau3Ztoz8kpqW5+eab9dlnn4W8xyYAAGgZ2CQEAAAAAAAAfI5PNwYAAAAAAAB8jk1CAAAAAAAAwOfYJAQAAAAAAAB8jk1CAAAAAAAAwOfYJAQAAAAAAAB8jk1CAAAAAAAAwOfYJAQAAAAAAAB8jk1CAAAAAAAAwOfYJAQAAAAAAAB8jk1CAAAAAAAAwOfYJAQAAAAAAAB8jk1CAAAAAAAAwOfYJAQAAAAAAAB8jk1CAAAAAAAAwOfYJAQAAAAAAAB8jk1CAAAAAAAAwOfYJAQAAAAAAAB8jk1CAAAAAAAAwOfYJAQAAAAAAAB8jk1CAAAAAAAAwOfYJAQAAAAAAAB8jk1CAAAAAAAAwOfYJAQAAAAAAAB8jk1CAAAAAAAAwOfYJAQAAAAAAAB8jk1CAAAAAAAAwOfYJAQAAAAAAAB8jk1CAAAAAAAAwOfYJAQAAAAAAAB8jk1CAAAAAAAAwOfYJAQAAAAAAAB8jk1CAAAAAAAAwOfYJAQAAAAAAAB8jk1CAAAAAAAAwOfYJAQAAAAAAAB8jk1CAAAAAAAAwOfYJAQAAAAAAAB8jk1CAAAAAAAAwOfYJAQAAAAAAAB8jk1CAAAAAAAAwOfYJAQAAAAAAAB8jk1CAE1m/fr1CgQCmjdvntejmBszZozGjBnj9RhhNm7cqOjoaH355Zdej6JJkyapV69eu71cc21ZX7169dKkSZOCf//ggw8UFxennJwc74YCAMCIn48HAaClYZMQQKPNmzdPgUCg1q+bb7651uu89957uuOOO2wHbWH+9re/6c0332yS277zzjs1cuRIHXbYYcHTXnrpJc2ePXuPbreu20hPT9cdd9yhFStW7NHtN3dfffWV7rjjDuXl5e32smPHjlW/fv00a9asph8MAIAmxvFgy+TG8V9tvvvuO11xxRUaNmyY2rVrp0Ag4Pp9AGg6AcdxHK+HANAyzZs3T5MnT9add96p3r17h5w3aNAgHXjggSorK1O7du3Upk0bSdLUqVP12GOPqbU/9NQ8823x4sUNvm5cXJzOOuss1//FPScnRykpKXr22Wd17rnnBk8/+eST9fPPP2v9+vWNvu26bmPp0qU6+OCDNXfu3JBn00lSRUWFqqurFRUVtcvbLi8vlyRFRkY2er6m9ve//1033HCDUlNTw54dWVZWpoiICLVr1y542hNPPKHrr79emZmZio+PN54WAAD3cDzYMrlx/FebO+64Q3/72980ZMgQFRYWavXq1fycgRakrdcDAGj5TjjhBA0fPrzW86Kjo42nQV1eeOEFtW3bVqeccorXo0hSyKbZrjTnzcH6qG0T9Mwzz9RVV12lBQsW6C9/+YsHUwEA4C6OByFJl19+uW666SbFxMRo6tSpWr16tdcjAWgAXm4MoMns/B40kyZN0mOPPSZJIS9F2Z33339fo0ePVnx8vBISEnTwwQfrpZdeCrnMggULNGzYMMXExCgxMVEXXHCB0tLSQi4zadIkxcXF6Y8//tDJJ5+suLg4paSkBGf66aef9Oc//1mxsbHq2bNn2H3UvJzm888/16WXXqq99tpLCQkJuvDCC7V169bdfh9lZWW6/fbb1a9fP0VFRalHjx668cYbVVZWFrxMIBBQcXGxnn322WCfHZ+Bt3z5cp1wwglKSEhQXFycjj76aH3zzTe7vW9JevPNNzVy5EjFxcUFTxszZoz+9a9/acOGDcH7q3kmXM33u/O/MC9evFiBQCD4LMm6bmPx4sU6+OCDJUmTJ08OnrfjenDzPQkDgYCmTp2qF198Uf3791d0dLSGDRumzz//PORydd3vHXfcEbYea27zzTff1KBBgxQVFaUDDjhAH3zwQcj1brjhBklS7969g99nTbed35NQkrp27aohQ4borbfe2u33BQBAS+bG8eDSpUt1/PHHKzExUTExMerdu3fYP7JVV1dr9uzZOuCAAxQdHa1u3brp0ksvDTtG69Wrl04++WR98cUXGjFihKKjo9WnTx8999xzIZer6yXUO/5v/MqVKzVp0iT16dNH0dHRSkpK0l/+8hdt3rx5t11qjqfmz5+vW2+9VUlJSYqNjdWpp56qjRs3hs2887GEFH6MVHObr776qu655x7tvffeio6O1tFHH621a9eGXK+u4z9Jys7O1kUXXaRu3bopOjpaBx54oJ599tndfk+S1K1bN8XExNTrsgCaH55JCGCP5efnKzc3N+S0xMTEsMtdeumlSk9P18cff6znn3++Xrc9b948/eUvf9EBBxygW265RR07dtTy5cv1wQcf6LzzzgteZvLkyTr44IM1a9YsZWVl6eGHH9aXX36p5cuXq2PHjsHbq6qq0gknnKAjjzxS9913n1588UVNnTpVsbGxuu2223T++edr3LhxevLJJ3XhhRdq1KhRYS+dmTp1qjp27Kg77rhDq1at0hNPPKENGzYED8xqU11drVNPPVVffPGFpkyZooEDB+qnn37SQw89pNWrVwffg/D555/XxRdfrBEjRmjKlCmSpL59+0qSfvnlFx1xxBFKSEjQjTfeqHbt2umpp57SmDFjtGTJEo0cObLOjhUVFfr+++91+eWXh5x+2223KT8/X5s2bdJDDz0kSSGbiPVR120MHDhQd955p2bMmKEpU6boiCOOkCQdeuihDbr9hliyZInmz5+vadOmKSoqSo8//rjGjh2r7777ToMGDWrUbX7xxRdauHChrrjiCsXHx+sf//iHzjzzTP3xxx/aa6+9NG7cOK1evVovv/yyHnrooeDa79Klyy5vd9iwYU323pMAAFhrquPB7OxsHXfccerSpYtuvvlmdezYUevXr9fChQvDbrfmmHDatGlKTU3Vo48+quXLl+vLL78MeQXD2rVrddZZZ+miiy7SxIkT9cwzz2jSpEkaNmyYDjjgAEmqdba//vWvys7ODh4rffzxx/r99981efJkJSUl6ZdfftGcOXP0yy+/6JtvvqnXP4bfc889CgQCuummm5Sdna3Zs2frmGOO0YoVKxq92fbf//3fioiI0PXXX6/8/Hzdd999Ov/88/Xtt99K2vXxX2lpqcaMGaO1a9dq6tSp6t27txYsWKBJkyYpLy9PV199daNmAtBCOADQSHPnznUk1frlOI6TmprqSHLmzp0bvM6VV17p1PehJy8vz4mPj3dGjhzplJaWhpxXXV3tOI7jlJeXO127dnUGDRoUcpl3333XkeTMmDEjeNrEiRMdSc7f/va34Glbt251YmJinEAg4LzyyivB03/77TdHknP77beHfb/Dhg1zysvLg6ffd999jiTnrbfeCp42evRoZ/To0cG/P//8805ERITz73//O+T7ePLJJx1Jzpdffhk8LTY21pk4cWJYj9NPP92JjIx01q1bFzwtPT3diY+Pd4488siwy+9o7dq1jiTnkUceCTvvpJNOcnr27Bl2es33m5qaGnL6okWLHEnOokWLdnsb33//fdgaqDFx4sRar7OznVvWpWbtLV26NHjahg0bnOjoaOeMM87Y7f3efvvtYWtTkhMZGemsXbs2eNqPP/4Y1vL++++vtZXjOE7Pnj1r/Xn+7W9/cyQ5WVlZu/3eAABorpr6ePCNN95wJDnff/99nZf597//7UhyXnzxxZDTP/jgg7DTe/bs6UhyPv/88+Bp2dnZTlRUlHPdddfVeR81x3vPPfdc8LSSkpKwy7388stht1+bmuOplJQUp6CgIHj6q6++6khyHn744ZCZazuW2PkYqeY2Bw4c6JSVlQVPf/jhhx1Jzk8//RQ8ra5jt9mzZzuSnBdeeCF4Wnl5uTNq1CgnLi4uZNbdacjPGUDzwMuNAeyxxx57TB9//HHIlxs+/vhjFRYW6uabbw57L5uaf5ldunSpsrOzdcUVV4Rc5qSTTtKAAQP0r3/9K+x2L7744uCfO3bsqP79+ys2NlYTJkwInt6/f3917NhRv//+e9j1p0yZEvKv0Zdffrnatm2r9957r87vZcGCBRo4cKAGDBig3Nzc4Nef//xnSdKiRYt22aKqqkofffSRTj/9dPXp0yd4enJyss477zx98cUXKigoqPP6NS976dSp0y7vp6UbNWqUhg0bFvz7Pvvso9NOO00ffvihqqqqGnWbxxxzTPDZnJI0ZMgQJSQk1Lo2GqLmZ7Hzsy4AAGiJmup4sOYVIe+++64qKipqvcyCBQvUoUMHHXvssSHHWcOGDVNcXFzYcdb+++8ffIWDtP3Z//3796/zf9sXLVqkW265RVdddZX+67/+K3j6js/027Ztm3Jzc3XIIYdIkn744Yd6fX8XXnhhyIeYnXXWWUpOTt7lceXuTJ48OeQ9nWu+1/ocu7z33ntKSkoK+ZC7du3aadq0aSoqKtKSJUsaPReA5o+XGwPYYyNGjKjzjar3xLp16yRply8T3bBhg6Ttm3o7GzBggL744ouQ06Kjo8NeBtqhQwftvffeYS8J6dChQ63vNbjvvvuG/D0uLk7Jycm7/HS4NWvW6Ndff63zJajZ2dl1Xlfa/snEJSUltX6fAwcOVHV1tTZu3Bh8iUxdnFb+6XI7/2wkab/99lNJSYlycnKUlJTU4NvcZ599wk7r1KlTvd6Hcldqfhb1eSkSAADNXVMdD44ePVpnnnmmZs6cqYceekhjxozR6aefrvPOOy/44WBr1qxRfn6+unbtWutt7Hyc1ZD/bd+0aZPOPvtsHXbYYXrwwQdDztuyZYtmzpypV155Jew+8vPz6/X97XzsEggE1K9fvz361OGdv7+af5isz7HLhg0btO+++yoiIvT5RAMHDgyeD6D1YpMQgK+0adOmQae7talWXV2twYMHhx1c1ujRo4cr91OXvfbaS1L9Dg5r1LV51dhn5DUXDf2+mmpt1Pwsanu/JgAAsF0gENBrr72mb775Ru+8844+/PBD/eUvf9EDDzygb775RnFxcaqurlbXrl314osv1nobO/8jbX3/t728vFxnnXWWoqKi9Oqrr6pt29D/+zxhwgR99dVXuuGGG3TQQQcFZxk7dqyqq6v34LsOtatjl9q+l6Y+rgXQerFJCMBUQ541VfMSz59//ln9+vWr9TI9e/aUJK1atSr40t0aq1atCp7vpjVr1uioo44K/r2oqEgZGRk68cQT67xO37599eOPP+roo4/ebYPazu/SpYvat2+vVatWhZ3322+/KSIiYpcbjfvss49iYmKUmppar/uT/u9fnfPy8kJOr+1fkOu6Detnya1ZsybstNWrV6t9+/bB/4PQqVOnsO9J2rN/GW/M95mamqrExMTdfsAJAACtTWP+d/OQQw7RIYcconvuuUcvvfSSzj//fL3yyiu6+OKL1bdvX33yySc67LDDXP1k3WnTpmnFihX6/PPP1a1bt5Dztm7dqk8//VQzZ87UjBkzgqfXdiyyKztf3nEcrV27VkOGDAmetqtjlx3fhqYh6voZ9OzZUytXrlR1dXXIswl/++234PkAWi/ekxCAqdjYWEnhG0+1Oe644xQfH69Zs2Zp27ZtIefV/Evo8OHD1bVrVz355JMqKysLnv/+++/r119/1UknneTe8P9rzpw5Ie+J88QTT6iyslInnHBCndeZMGGC0tLS9M9//jPsvNLSUhUXFwf/HhsbG9anTZs2Ou644/TWW2+FvPwkKytLL730kg4//HAlJCTUef/t2rXT8OHDtXTp0rDzYmNja31JTM0m7eeffx48raqqSnPmzKn3bTTk5+2Gr7/+OuQ9gDZu3Ki33npLxx13XPBf1fv27av8/HytXLkyeLmMjAy98cYbjb7fxnyfy5Yt06hRoxp9nwAAtFQN+d/NrVu3hj0D7qCDDpKk4LHfhAkTVFVVpbvuuivs+pWVlY06Dpk7d66eeuopPfbYYxoxYkTY+TXHFTvPNnv27Abdz3PPPafCwsLg31977TVlZGSEHFf27dtX33zzjcrLy4Onvfvuu9q4cWOD7mtHdR27nXjiicrMzNT8+fODp1VWVuqRRx5RXFycRo8e3ej7BND88UxCAKZqPlRi2rRpOv7449WmTRudc845tV42ISFBDz30kC6++GIdfPDBOu+889SpUyf9+OOPKikp0bPPPqt27drp3nvv1eTJkzV69Gide+65ysrK0sMPP6xevXrp2muvdf17KC8v19FHH60JEyZo1apVevzxx3X44Yfr1FNPrfM6//Vf/6VXX31Vl112mRYtWqTDDjtMVVVV+u233/Tqq6/qww8/DL6Pz7Bhw/TJJ5/owQcfVPfu3dW7d2+NHDlSd999tz7++GMdfvjhuuKKK9S2bVs99dRTKisr03333bfbuU877TTddtttKigoCNlQHDZsmObPn6/p06fr4IMPVlxcnE455RQdcMABOuSQQ3TLLbdoy5Yt6ty5s1555RVVVlaG3XZdt9G3b1917NhRTz75pOLj4xUbG6uRI0eqd+/ejSi/e4MGDdLxxx+vadOmKSoqSo8//rgkaebMmcHLnHPOObrpppt0xhlnaNq0aSopKdETTzyh/fbbr95vMr6zmnV922236ZxzzlG7du10yimnBP9P0M6ys7O1cuVKXXnllY26PwAAWrKGHA8+++yzevzxx3XGGWeob9++Kiws1D//+U8lJCQEX8UxevRoXXrppZo1a5ZWrFih4447Tu3atdOaNWu0YMECPfzwwzrrrLPqPV9ubq6uuOIK7b///oqKitILL7wQcv4ZZ5yhhIQEHXnkkbrvvvtUUVGhlJQUffTRR7W+amNXOnfurMMPP1yTJ09WVlaWZs+erX79+umSSy4JXubiiy/Wa6+9prFjx2rChAlat26dXnjhhZAPVmuouo7dpkyZoqeeekqTJk3SsmXL1KtXL7322mv68ssvNXv27JAPWanNhg0b9Pzzz0tS8B+n7777bknbn4W44we/AGiGvPpYZQAt39y5cx1Jzvfff1/r+ampqY4kZ+7cucHTKisrnauuusrp0qWLEwgEnPo8DL399tvOoYce6sTExDgJCQnOiBEjnJdffjnkMvPnz3eGDh3qREVFOZ07d3bOP/98Z9OmTSGXmThxohMbGxt2+6NHj3YOOOCAsNN79uzpnHTSSWHf75IlS5wpU6Y4nTp1cuLi4pzzzz/f2bx5c9htjh49OuS08vJy595773UOOOAAJyoqyunUqZMzbNgwZ+bMmU5+fn7wcr/99ptz5JFHOjExMY4kZ+LEicHzfvjhB+f444934uLinPbt2ztHHXWU89VXX+22oeM4TlZWltO2bVvn+eefDzm9qKjIOe+885yOHTs6kpyePXsGz1u3bp1zzDHHOFFRUU63bt2cW2+91fn4448dSc6iRYvqdRtvvfWWs//++ztt27YNWQ8TJ04MuVxdamtZG0nOlVde6bzwwgvOvvvu60RFRTlDhw4NmbPGRx995AwaNMiJjIx0+vfv77zwwgvO7bffHrYea25zZz179gz5uTiO49x1111OSkqKExER4UhyUlNT67zsE0884bRv394pKCjY7fcFAEBz1tTHgz/88INz7rnnOvvss48TFRXldO3a1Tn55JOdpUuXhl12zpw5zrBhw5yYmBgnPj7eGTx4sHPjjTc66enpwcvsfHxXY8fjjZqZ6/qq+d/4TZs2OWeccYbTsWNHp0OHDs748eOd9PR0R5Jz++2377LbokWLHEnOyy+/7Nxyyy1O165dnZiYGOekk05yNmzYEHb5Bx54wElJSXGioqKcww47zFm6dGnYMVLNbS5YsCDkurX9DHZ17JaVleVMnjzZSUxMdCIjI53BgweHXLc+31dtX/U5ngPgrYDj8O6lAFAf8+bN0+TJk/X99983yaf3Wbjooou0evVq/fvf//Z6FNcFAgFdeeWVevTRR70eZbeGDh2qMWPG6KGHHvJ6FAAA4IHFixfrqKOO0oIFCxr0LEcAaEq83BgAfOT222/Xfvvtpy+//FKHHXaY1+P40gcffKA1a9boww8/9HoUAAAAAAhikxAAfGSfffYJ+xAY2Bo7dqyKioq8HgMAAAAAQvDpxgAAAAAAAIDP8Z6EAAAAAAAAgM/xTEIAAAAAAADA59gkBAAAAAAAAHyOTUKXOI6jgoIC8eptAAAAGxx/AQAAuKdVbhJ+/vnnOuWUU9S9e3cFAgG9+eabu73O4sWL9ac//UlRUVHq16+f5s2b16D7LCwsVIcOHVRYWNi4oQ0VFxd7PYKv0NsWvW3R2xa9bdG7+WtJx18Sa8oavW3R2w6tbdHbFr291So3CYuLi3XggQfqscceq9flU1NTddJJJ+moo47SihUrdM011+jiiy/Whx9+2MSTeiMqKsrrEXyF3rbobYvetuhti95wG2vKFr1t0dsOrW3R2xa9vdUqNwlPOOEE3X333TrjjDPqdfknn3xSvXv31gMPPKCBAwdq6tSpOuuss/TQQw818aTeyM3N9XoEX6G3LXrborctetuiN9zGmrJFb1v0tkNrW/S2RW9vtfV6gObg66+/1jHHHBNy2vHHH69rrrmmzuuUlZWprKws+PeCgoKmGs91CQkJXo/gK/S2RW9b9LZFb1v0bn5a8vGXxJqyRm9b9LZDa1v0tkVvb7XKZxI2VGZmprp16xZyWrdu3VRQUKDS0tJarzNr1ix16NAh+NWjRw9J0rZt25Senq7q6mqlpaVJktLS0lReXq7s7GwVFRUpLy9PW7ZsUWlpqTIzM1VZWRly2YqKCmVmZqqkpERbtmzR1q1bVVxcrKysLFVUVIRctqqqSunp6SotLdXmzZuVn5+vwsJC5eTkqKysLOSyjuMoLS1NBQUFysnJUUFBgQoKCpSbm6vS0tJ6z11SUlLr3JWVlWFzFxUV1Tp3dXX1bueumbfmv2VlZcrJyVFhYaHy8/O1efPmOueuqKhQVlaWioqKtHXr1gbNnZeXp6KiImVnZ6u8vLzOuXNzc4MNa5u75jo131dtc1dVVdU6d3FxcdjcOzesmbu0tLTec2/btq3WudPT08PmLisrU3Z2dtjcGRkZu517d2s2IyMjZO7CwsIGzZ2bm1vn71rNbRUWFob8rrk5945rNjs7u9bftfT09OCarc/czekxora56/pdq2nAY0TjHyN2NffOa7amF48RjX+MqPldq89jxM69eYxo+GNEbXPviZZ8/FVWVqbMzEyOv+qYuykeWzMyMjj+kt1ja01vjr84/mopjxEcf3H81VofI+o6jqiPgNPKPw4uEAjojTfe0Omnn17nZfbbbz9NnjxZt9xyS/C09957TyeddJJKSkoUExMTdp3a/iW7R48eys/Pb/Y731u3blWnTp28HsM36G2L3rbobYvetujd/LTk4y+JNWWN3rbobYfWtuhti97e4uXGkpKSkpSVlRVyWlZWlhISEmrdIJS2v5lmS31DzXbt2nk9gq/Q2xa9bdHbFr1t0bv5acnHXxJryhq9bdHbDq1t0dsWvb3Fy40ljRo1Sp9++mnIaR9//LFGjRrl0URNi48Ut0VvW/S2RW9b9LZFb7iNNWWL3rbobYfWtuhti97eapWbhEVFRVqxYoVWrFghSUpNTdWKFSv0xx9/SJJuueUWXXjhhcHLX3bZZfr9999144036rffftPjjz+uV199Vddee60X4ze5zp07ez2Cr9DbFr1t0dsWvW3RG25jTdmity1626G1LXrbore3WuUm4dKlSzV06FANHTpUkjR9+nQNHTpUM2bMkCRlZGQENwwlqXfv3vrXv/6ljz/+WAceeKAeeOAB/c///I+OP/54T+ZvatnZ2V6P4Cv0tkVvW/S2RW9b9IbbWFO26G2L3nZobYvetujtrVb/wSVWCgoK1KFDhxbzxtkAAAAtHcdfAAAA7mmVzyTErtV8NDZs0NsWvW3R2xa9bdEbbmNN2aK3LXrbobUtetuit7d4JqFLWtK/ZFdXVysigv1hK/S2RW9b9LZFb1v0bv5a0vGXxJqyRm9b9LZDa1v0tkVvb1HehzIzM70ewVfobYvetuhti9626A23saZs0dsWve3Q2ha9bdHbW2wS+lCnTp28HsFX6G2L3rbobYvetugNt7GmbNHbFr3t0NoWvW3R21tsEvpQSUmJ1yP4Cr1t0dsWvW3R2xa94TbWlC1626K3HVrborctenurrdcDoH4KCwtVVFRU5/lxcXGKj4+v1221bcuP3RK9bdHbFr1t0dsWveE21pQtetuitx1a26K3LXp7i/otxLJly7RkyZI6zx89erTGjBlTr9viTUBt0dsWvW3R2xa9bdEbbmNN2aK3LXrbobUtetuit7fYJGwhhg0bpv79+0uScnNztXDhQo0bN06JiYmStj+TsL62bdtW72cdYs/R2xa9bdHbFr1t0RtuY03ZorctetuhtS1626K3t9gkbCHi4+PDflESExOVnJzc4NtKSEhwayzUA71t0dsWvW3R2xa94TbWlC1626K3HVrborctenuL53H6UG5urtcj+Aq9bdHbFr1t0dsWveE21pQtetuitx1a26K3LXp7i01CH+revbvXI/gKvW3R2xa9bdHbFr3hNtaULXrborcdWtuity16e4tNQh9KT0/3egRfobctetuity1626I33MaaskVvW/S2Q2tb9LZFb2+xSehD7Mzborctetuity1626I33MaaskVvW/S2Q2tb9LZFb2+xSehD7Mzborctetuity1626I33MaaskVvW/S2Q2tb9LZFb2+xSehDiYmJXo/gK/S2RW9b9LZFb1v0httYU7bobYvedmhti9626O0tNgl9qKCgwOsRfIXetuhti9626G2L3nAba8oWvW3R2w6tbdHbFr29xSahD0VHR3s9gq/Q2xa9bdHbFr1t0RtuY03ZorctetuhtS1626K3t9gk9KHq6mqvR/AVetuity1626K3LXrDbawpW/S2RW87tLZFb1v09habhD5UWVnp9Qi+Qm9b9LZFb1v0tkVvuI01ZYvetuhth9a26G2L3t5ik9CH2rdv7/UIvkJvW/S2RW9b9LZFb7iNNWWL3rbobYfWtuhti97eYpPQh7Zu3er1CL5Cb1v0tkVvW/S2RW+4jTVli9626G2H1rbobYve3mKT0IeSkpK8HsFX6G2L3rbobYvetugNt7GmbNHbFr3t0NoWvW3R21tsEvpQRkaG1yP4Cr1t0dsWvW3R2xa94TbWlC1626K3HVrborctenuLTUIfSklJ8XoEX6G3LXrborctetuiN9zGmrJFb1v0tkNrW/S2RW9vsUnoQ2lpaV6P4Cv0tkVvW/S2RW9b9IbbWFO26G2L3nZobYvetujtLTYJfahr165ej+Ar9LZFb1v0tkVvW/SG21hTtuhti952aG2L3rbo7S02CX1oy5YtXo/gK/S2RW9b9LZFb1v0httYU7bobYvedmhti9626O0tNgl9KDY21usRfIXetuhti9626G2L3nAba8oWvW3R2w6tbdHbFr29xSahD1VUVHg9gq/Q2xa9bdHbFr1t0RtuY03ZorctetuhtS1626K3t9gk9CHHcbwewVfobYvetuhti9626A23saZs0dsWve3Q2ha9bdHbW2wS+lB0dLTXI/gKvW3R2xa9bdHbFr3hNtaULXrborcdWtuity16e4tNQh8qKCjwegRfobctetuity1626I33MaaskVvW/S2Q2tb9LZFb2+xSehDiYmJXo/gK/S2RW9b9LZFb1v0httYU7bobYvedmhti9626O0tNgl9KCsry+sRfIXetuhti9626G2L3nAba8oWvW3R2w6tbdHbFr29xSahD6WkpHg9gq/Q2xa9bdHbFr1t0RtuY03ZorctetuhtS1626K3t9gk9KG0tDSvR/AVetuity1626K3rdbcu7CwUBkZGXV+FRYWej1iq9Sa11RzRG9b9LZDa1v0tkVvb7X1egDY69atm9cj+Aq9bdHbFr1t0dtWa+69bNkyLVmypM7zR48erTFjxtgN5BOteU01R/S2RW87tLZFb1v09habhD6Um5urpKQkr8fwDXrborctetuit63W3HvYsGHq37+/pO3f58KFCzVu3Ljgm4XHxcV5OV6r1ZrXVHNEb1v0tkNrW/S2RW9vsUnoQwkJCV6P4Cv0tkVvW/S2RW9brbl3fHy84uPjQ05LTExUcnKyRxP5Q2teU80RvW3R2w6tbdHbFr29xXsS+tC2bdu8HsFX6G2L3rbobYvetugNt7GmbNHbFr3t0NoWvW3R21tsEvpQRAQ/dkv0tkVvW/S2RW9b9IbbWFO26G2L3nZobYvetujtLV5u7ENt2/Jjt0RvW/S25dfehYWFKioqqvP8uLi4sJdyusGvvb1Cb7iNNWWL3rbobYfWtuhti97eor4PlZSU8Ibkhuhti962/Nrbq0+G9Wtvr9AbbmNN2aK3LXrbobUtetuit7fYJPShjh07ej2Cr9DbFr1t+bW3V58M69feXqE33MaaskVvW/S2Q2tb9LZFb2/xYm8fysnJ8XoEX6G3LXrb8mvv+Ph4JScnKzk5ObgxWPPJsMnJyU3yUmPJv729Qm+4jTVli9626G2H1rbobYve3mKT0IdSUlK8HsFX6G2L3rbobYvetugNt7GmbNHbFr3t0NoWvW3R21tsEvpQWlqa1yP4Cr1t0dsWvW3R2xa94TbWlC1626K3HVrborctenuLTUIfSk5O9noEX6G3LXrborctetuiN9zGmrJFb1v0tkNrW/S2RW9vsUnoQ5mZmV6P4Cv0tkVvW/S2RW9b9IbbWFO26G2L3nZobYvetlp778LCQmVkZNT5VVhY6Ol8fLqxD3Xq1MnrEXyF3rbobYvetuhti95wG2vKFr1t0dsOrW3R21Zr771s2TItWbKkzvNHjx6tMWPG2A20EzYJfai4uFgxMTFej+Eb9LZFb1v0tkVvW/SG21hTtuhti952aG2L3rZae+9hw4apf//+kqTc3FwtXLhQ48aNU2JioiQpLi7Oy/HYJPSjyMhIr0fwFXrborctetuity16w22sKVv0tkVvO7S2RW9brb13fHy84uPjQ05LTExsNu/FyCYhAAAAUIvCwkIVFRXVeX5cXFzYgT4AAEBLxSahD5WVlXk9gq/Q2xa9bdHbFr1t0Rtuv28Qa8oWvW3R2w6tbdHbFr29xSahDyUkJHg9gq/Q2xa9bdHbFr1t0Rtuv28Qa8oWvW3R2w6tbdHbFr29FeH1ALCXm5vr9Qi+Qm9b9LZFb1v0tkVvxMfHKzk5WcnJycGNwZr3DUpOTm7wS41ZU7bobYvedmhti9626O0tNgl9qHv37l6P4Cv0tkVvW/S2RW9b9IbbWFO26G2L3nZobYvetujtLTYJfSg9Pd3rEXyF3rbobYvetuhti95wG2vKFr1t0dsOrW3R2xa9vcUmoQ+lpKR4PYKv0NsWvW3R2xa9bdEbbmNN2aK3LXrbobUtetuit7fYJPShtLQ0r0fwFXrborctetuity16w22sKVv0tkVvO7S2RW9b9PZWq90kfOyxx9SrVy9FR0dr5MiR+u677+q87Lx58xQIBEK+oqOjDae1VfPG27BBb1v0tkVvW/S2RW+4jTVli9626G2H1rbobYve3mqVm4Tz58/X9OnTdfvtt+uHH37QgQceqOOPP17Z2dl1XichIUEZGRnBrw0bNhhObKugoMDrEXyF3rbobYvetuhti95wG2vKFr1t0dsOrW3R2xa9vdUqNwkffPBBXXLJJZo8ebL2339/Pfnkk2rfvr2eeeaZOq8TCASUlJQU/OrWrZvhxLZa87MkmyN626K3LXrborctesNtrClb9LZFbzu0tkVvW/T2VqvbJCwvL9eyZct0zDHHBE+LiIjQMccco6+//rrO6xUVFalnz57q0aOHTjvtNP3yyy+7vJ+ysjIVFBSEfLUU1dXVXo/gK/S2RW9b9LZFb1v0bn5a8vGXxJqyRm9b9LZDa1v0tkVvb7W6TcLc3FxVVVWFPROwW7duyszMrPU6/fv31zPPPKO33npLL7zwgqqrq3XooYdq06ZNdd7PrFmz1KFDh+BXjx49JEnbtm1Tenq6qqurg2+4mZaWpvLycmVnZ6uoqEh5eXnasmWLSktLlZmZqcrKypDLVlRUKDMzUyUlJdqyZYu2bt2q4uJiZWVlqaKiIviy6ezsbFVVVSk9PV2lpaXavHmz8vPzVVhYqJycHJWVlYXcruM4SktLU0lJiXJycoIH17m5uSotLa333CUlJbXOXVlZGTZ3UVFRcO4dL1tdXb3buWvmrflvWVmZcnJyVFhYqPz8fG3evLnOuSsqKpSVlaWioiJt3bq1QXPn5eWpqKhI2dnZKi8vr3Pu3NzcYMPa5q65TmlpaZ1zV1VV1Tp3cXFx2Nw7N6yZu7S0tN5zb9u2rda509PTw+YuKytTdnZ22NwZGRm7nXvnNbvjZauqqpSRkREyd2FhYYPmzs3NrfN3rbS0NDj3jr9rbs6945rNzs6u9XctPT09uGbrM7ebjxE7z93Qx4ja5q7rd23btm2+f4zY8TG5MY8Ru5p75zW7bds2HiP28DGi5mdWn8eInXu31seInJwcSVJeXp7rjxG1zb0nWvLxV1lZWdg65fir6Y6/anpz/GX32FqzTjj+4virpTxGcPzF8ZfXjxHbtm2TtP1Ja019/FVSUqL6CDiO49Trki1Eenq6UlJS9NVXX2nUqFHB02+88UYtWbJE33777W5vo6KiQgMHDtS5556ru+66q9bLlJWVqaysLPj3goIC9ejRQ/n5+UpISNjzb2QXMjIyNGfOHE2ZMkXJyckNvn5paaliYmKaYDLUht626G2L3nv+mNwQ9Lbll96Wa3hPteTjL8k/a6q5oLctetuhtS162/JT7+Z4DNbW6wHclpiYqDZt2igrKyvk9KysLCUlJdXrNtq1a6ehQ4dq7dq1dV4mKipKUVFRezSrV7Zu3eqbX7rmgN626G2L3rbobYvezU9LPv6SWFPW6G2L3nb83LqwsFBFRUV1nh8XF6f4+HhX79PPvb1Ab2+1uk3CyMhIDRs2TJ9++qlOP/10Sdtf0/7pp59q6tSp9bqNqqoq/fTTTzrxxBObcFLvtOYPZWmO6G2L3rbobYvetugNt7GmbNHbFr3t+Ln1smXLtGTJkjrPHz16tMaMGePqffq5txfo7a1Wt0koSdOnT9fEiRM1fPhwjRgxQrNnz1ZxcbEmT54sSbrwwguVkpKiWbNmSZLuvPNOHXLIIerXr5/y8vJ0//33a8OGDbr44ou9/DaaTGZmplJSUrwewzfobYvetuhti9626A23saZs0dsWve34ufWwYcPUv39/Sds/j2DhwoUaN26cEhMTJW1/JqHb/NzbC/T2VqvcJDz77LOVk5OjGTNmKDMzUwcddJA++OCD4I70H3/8oYiI//vMlq1bt+qSSy5RZmamOnXqpGHDhumrr77S/vvv79W30KT4hbNFb1v0tkVvW/S2RW+4jTVli9626G3Hz63j4+PDXk6cmJjYpO/n5ufeXqC3t1rdpxvXmDp1qjZs2KCysjJ9++23GjlyZPC8xYsXa968ecG/P/TQQ8HLZmZm6l//+peGDh3qwdQ2aj71BjbobYvetuhti9626A23saZs0dsWve3Q2ha9bdHbW612kxB169q1q9cj+Aq9bdHbFr1t0dsWveE21pQtetuitx1a26K3LXp7i01CH9qyZYvXI/gKvW3R2xa9bdHbFr3hNtaULXrborcdWtuity16e4tNQh9qijdzRd3obYvetuhti9626A23saZs0dsWve3Q2ha9bdHbW2wS+lB5ebnXI/gKvW3R2xa9bdHbFr3hNtaULXrborcdWtuity16e4tNQh9yHMfrEXyF3rbobYvetuhti95wG2vKFr1t0dsOrW3R2xa9vcUmoQ9FR0d7PYKv0NsWvW3R2xa9bdEbbmNN2aK3LXrbobUtetuit7fYJPShgoICr0fwFXrborctetuity16w22sKVv0tkVvO7S2RW9b9PYWm4Q+tNdee3k9gq/Q2xa9bdHbFr1t0RtuY03ZorctetuhtS1626K3t9gk9KHs7GyvR/AVetuity1626K3LXrDbawpW/S2RW87tLZFb1v09habhD6UkpLi9Qi+Qm9b9LZFb1v0tkVvuI01ZYvetuhth9a26G2L3t5ik9CH0tLSvB7BV+hti9626G2L3rboDbexpmzR2xa97dDaFr1t0dtbbBK2MKm5xXrg47VaXN5bD3y8Vqm5xQ2+jW7dujXBZKgLvW3R2xa9bdHbFr3hNtaULXrborcdWtuity16e4tNwhbk1aUbdfQDi7Xw1wKtr+qshb8W6OgHFmvB0o0Nup3c3NwmmhC1obctetuity1626I33MaaskVvW/S2Q2tb9LZFb2+1bewV33777QZf59hjj1VMTExj79LXUnOLdfPrK1Xt1JwSkPO/f77p9ZU6uFdn9UqMrddtdejQoUlmRO3obYvetuhti9626A23saZs0dsWve3Q2ha9bdHbW43eJDz99NMbdPlAIKA1a9aoT58+jb1LX3t16UYFAgEFdwZ3EAgENH/pRt00dkC9bqu0tJTNWkP0tkVvW/S2RW9b9IbbWFO26G2L3nZobYvetujtrT16uXFmZqaqq6vr9dW+fXu3ZvalTVtL5dSyQShJjuNo09bSet9WRASvMrdEb1v0tkVvW/S2RW+4jTVli9626G2H1rbobYve3mp0/YkTJzZod/eCCy5QQkJCY+/O9/buFLP9mYS1CAQC2rtT/X8Wbds2+gmkaAR626K3LXrborctesNtrClb9LZFbzu0tkVvW/T2VqM3CefOnav4+Ph6X/6JJ55QYmJiY+/O9yYM77HLZxKePbxHvW+rpKTErbFQD/S2RW9b9LZFb1v0httYU7bobYvedmhti9626O0tnsfZQvROjNW9Zw5RRECKCEgBOcE/33vmkHp/aIkkdezYsekGRRh626K3LXrborctesNtrClb9LZFbzu0tkVvW/T2lmvP49y2bZtWrlyp7OxsVVdXh5x36qmnunU3vjZ+eA8d3KuzHn3vBy1blaph/Xtr6ol/atAGoSTl5OQoJSWliabEzuhti9626G2L3rboDbexpmzR2xa97dDaFr1t0dtbrmwSfvDBB7rwwguVm5sbdl4gEFBVVZUbdwNJvRJjdd2x/TQn9TNNOfZYJTdwg1ASv3DG6G2L3rbobYvetugNt7GmbNHbFr3t0NoWvW3R21uuvNz4qquu0vjx45WRkRH2qcZsEDY/aWlpXo/gK/S2RW9b9LZFb1v0httYU7bobYvedmhti9626O0tVzYJs7KyNH36dHXr1s2Nm0MTS05O9noEX6G3LXrborctetuiN9zGmrJFb1v0tkNrW/S2RW9vubJJeNZZZ2nx4sVu3BQMZGZmej2Cr9DbFr1t0dsWvW3RG25jTdmity1626G1LXrbore3XHlPwkcffVTjx4/Xv//9bw0ePFjt2rULOX/atGlu3A1c0rlzZ69H8BV626K3LXrborctesNtrClb9LZFbzu0tkVvW/T2liubhC+//LI++ugjRUdHa/HixQoEAsHzAoEAm4TNTFFRkaKjo70ewzfobYvetuhti9626A23saZs0dsWve3Q2ha9bdHbW65sEt52222aOXOmbr75ZkVEuPIKZjShyMhIr0fwFXrborctetuity16w22sKVv0tkVvO7S2RW9b9PaWKzt65eXlOvvss9kgBAAAAAAAAFogV3b1Jk6cqPnz57txUzBQVlbm9Qi+Qm9b9LZFb1v0tkVvuI01ZYvetuhth9a26G2L3t5y5eXGVVVVuu+++/Thhx9qyJAhYR9c8uCDD7pxN3BJQkKC1yP4Cr1t0dsWvW3R2xa94TbWlC1626K3HVrborctenvLlWcS/vTTTxo6dKgiIiL0888/a/ny5cGvFStWuHEXcNHmzZu9HsFX6G2L3rbobYvetugNt7GmbNHbFr3t0NoWvW3R21uuPJNw0aJFbtwMjCQnJ3s9gq/Q2xa9bfm9d2puseYsXq9vyntrw6vfafrpozSoZ9cmuz+/97ZGb7iNNWWL3rbobYfWtuhti97ecu2TRrZt26bvvvtO7777rt5+++3g1zvvvOPWXcAl6enpXo/gK/S2RW9bfu796tKNOvqBxZq/covWV3XWoow2OvXJ77Vg6cYmu08/9/YCveE21pQtetuitx1a26K3LXp7y5VnEn7wwQf6r//6r1qfFhoIBFRVVeXG3cAlKSkpXo/gK/S2RW9bfu2dmlusm19fqWqn5pSAJMlxpJteX6mDe3VWr8RY1+/Xr729Qm+4jTVli9626G2H1rbobYve3nLlmYRXXXWVJkyYoIyMDFVXV4d8sUHY/KSlpXk9gq/Q2xa9bfm196tLNyoQCNR6XiAQ0PwmejahX3t7hd5wG2vKFr1t0dsOrW3R2xa9veXKJmFWVpamT5+ubt26uXFzaGKJiYlej+Ar9LZFb1t+7b1pa6kcx6n1PMdxtGlraZPcr197e4XecBtryha9bdHbDq1t0dsWvb3lyibhWWedpcWLF7txUzCQn5/v9Qi+Qm9b9Lbl1957d4rZ5TMJ9+4U0yT369feXqE33MaaskVvW/S2Q2tb9LZFb2+58p6Ejz76qMaPH69///vfGjx4sNq1axdy/rRp09y4G7gkJqZp/s8rakdvW/S25dfeE4b30FNL1tV6nuM4Ont4jya5X7/29gq94TbWlC1626K3HVrborctenvLlU3Cl19+WR999JGio6O1ePHikGdXBAIBNgmbmerqaq9H8BV626K3Lb/27p0Yq3vPHKKbXl8pScGXHgcCAd175pAm+dASyb+9vUJvuI01ZYvetuhth9a26G2L3t5yZZPwtttu08yZM3XzzTcrIsKVVzCjCVVWVno9gq/Q2xa9bfm59/jhPXRwr8566uOV+ubnNerdtYOuO32UDujZtcnu08+9vUBvuI01ZYvetuhth9a26G2L3t5yZUevvLxcZ599NhuELUT79u29HsFX6G2L3rb83rtXYqymjemlMZGpumfCiCbdIJTobY3ecBtryha9bdHbDq1t0dsWvb3lyq7exIkTNX/+fDduCgby8vK8HsFX6G2L3rbobYvetugNt7GmbNHbFr3t0NoWvW3R21uuvNy4qqpK9913nz788EMNGTIk7INLHnzwQTfuBi7p2rVpn+mCUPS2RW9b9LZFb1v0httYU7bobYvedmhti9626O0tV55J+NNPP2no0KGKiIjQzz//rOXLlwe/VqxY4cZdwEWZmZlej+Ar9LZFb1v0tkVvW/SG21hTtuhti952aG2L3rbo7S1Xnkm4aNEiN24GRlJSUrwewVfobYvetuhti9626A23saZs0dsWve3Q2ha9bdHbW3zSiA+lpaV5PYKv0NsWvW3R2xa9bdEbbmNN2aK3LXrbobUtetuit7cavUm4cuVKVVdX1/vyv/zyCx9l3UzwGn9b9LZFb1v0tkVvW/SG21hTtuhti952aG2L3rbo7a1GbxIOHTpUmzdvrvflR40apT/++KOxdwcXbdmyxesRfIXetuhti9626G2L3nAba8oWvW3R2w6tbdHbFr291ej3JHQcR//v//0/tW/fvl6XLy8vb+xdwWVxcXFej+Ar9LZFb1v0tkVvW/SG21hTtuhti952aG2L3rbo7a1GbxIeeeSRWrVqVb0vP2rUKMXExDT27uCi8vJyxcbGej2Gb9DbFr1t0dsWvW3RG25jTdmity1626G1LXrbore3Gr1JuHjxYhfHAAAAgLXU3GLNWbxe35T31oZXv9P000dpUE/eCwgAAMCP+HRjH4qMjPR6BF+hty1626K3LXrbau29X126UUc/sFjzV27R+qrOWpTRRqc++b0WLN3o9WitVmtfU80NvW3R2w6tbdHbFr29xSahDxUVFXk9gq/Q2xa9bdHbFr1ttebeqbnFuvn1lap2pGpHchSQo4CqHemm11dqfW6x1yO2Sq15TTVH9LZFbzu0tkVvW/T2FpuEPtS5c2evR/AVetuity1626K3rdbc+9WlGxUIBGo9LxAIaD7PJmwSrXlNNUf0tkVvO7S2RW9b9PYWm4Q+lJ2d7fUIvkJvW/S2RW9b9LbVmntv2loqx3FqPc9xHG3aWmo8kT+05jXVHNHbFr3t0NoWvW3R21tsEvpQSkqK1yP4Cr1t0dsWvW3R21Zr7r13p5hdPpNw704xxhP5Q2teU80RvW3R2w6tbdHbFr29xSahD6WlpXk9gq/Q2xa9bdHbFr1ttebeE4b32OUzCc8e3sN4In9ozWuqOaK3LXrbobUtetuit7fYJPShpKQkr0fwFXrborctetuit63W3Lt3YqzuPXOIIgJSRED/+7EljiIC0r1nDlGvxFivR2yVWvOaao7obYvedmi9/QO4Hvh4rRaX99YDH69VahN+4Ba9bdHbW2wS+hCv8bdFb1v0tkVvW/S21dp7jx/eQ59dN0ZnD+msXm226KjkKr1z2cEaz7MIm0xrX1PNDb1t0duO31u/unSjjn5gsRb+WqD1VZ218NcCHf3AYi1oog/d8ntva/T2FpuEPtSxY0evR/AVetuity1626K3LT/07pUYq2ljemlMZKrumTBCB/Ts6vVIrZof1lRzQm9b9Lbj59apucW6+fWVqnakakdyFAj++abXV2p9Ezyj0M+9vUBvb7XaTcLHHntMvXr1UnR0tEaOHKnvvvtul5dfsGCBBgwYoOjoaA0ePFjvvfee0aT2Skv5xEJL9LZFb1v0tkVvW/SG21hTtuhti952/Nz61aUbd/nBW/Ob4NmEfu7tBXp7q+2eXLmsrEyfffaZPvvsM23atEnZ2dkqLS1Vly5d1LVrVx100EE68cQT1bt3b7fmrZf58+dr+vTpevLJJzVy5EjNnj1bxx9/vFatWqWuXcP/hfyrr77Sueeeq1mzZunkk0/WSy+9pNNPP10//PCDBg0aZDq7hYiIVrs33CzR2xa9bdHbFr1t0RtuY03Zorctetvxc+tNW0t3+cFbm7a6v8Hk595eoLe3GlU/LS1NU6ZM0f77769HHnlEgUBABx54oM4880xddNFFGjNmjHr06KGlS5fqzDPP1IgRI/T666+7PXudHnzwQV1yySWaPHmy9t9/fz355JNq3769nnnmmVov//DDD2vs2LG64YYbNHDgQN11113605/+pEcffdRsZktt2rTxegRfobctetuity1626I3arj1BvmsKVv0tkVvO35uvXenmF0+k3DvTjGu36efe3uB3t5q8DMJ//GPf2jTpk2aMmWK5syZU6/rFBQUaP78+brssst06623ap999mnwoPVVXl6uZcuW6ZZbbgmeFhERoWOOOUZff/11rdf5+uuvNX369JDTjj/+eL355pt13k9ZWZnKysqCfy8oKNj+hxUrpLi4/7tgp05S797Stm3Sf/4TfkN/+tP2/65aJRXvdMDZq5fUubOUkyNt/L+nTbfNyVHnzZu3/6WqSvrxx/DbHTxYatdOWrdOys8POWtbZKTiBw2Stm6VUlNDrxcTIw0cuP3Py5dLO/8rzcCB2y+zYYNUM0ONbt2klBSpsFBasyb0vHbtts8kST/9JFVUhJ6/775SfLyUliZlZYWet9deUs+eUmmp9OuvoecFAtLQodv//Ouv2y+zo969t/8MsrK23/aOOnSQ+vbdPstPPynMgQdKbdps/14KC0PP69FD6tJF2rJFWr8+9LzYWKl//+1//uEHVWzZsv3nWGP//aXo6O3tt24NvW5y8vavggJp7drQ86KipAMO2P7nlSulysrQ8/fbb/va27RJ2vnNXhMTpX32kUpKpN9+Cz0vIkI66KDtf/7Pf7av1R316SN17ChlZkrp6aHndey4/fzycunnnxXmoIO23/7q1VJRUeh5++yzfa7cXOmPP0LPi4vb/v1UV2//ndrZoEFSZKT0++9SXl7IWWU16zsvb/v5O4qO3t5f2n671dWh5w8YILVvv32e3NzQ87p2lfbee/v3sXp16Hlt20pDhmz/8y+/SDs8NkiS+vWTEhKkjIztXztqgscISdt/n/bdt1GPEUpJ2f77XI/HiIrNm0PXtw8fI9r8/ruS0tPVduXK//v5NuAxIswuHiPK2rVT/ODBPEbswWOEuneXkpLq9RhRkZsbur5b6WNE25Urw9ewS48RdR5HNJIXx1+vppbo5u/zJTlynE7a8GuBFv66WPcO76DxvduHXnc33UoDAcVXVnL8ZXD8JSn0GIzjr+2a8LG1NCJC8VVVHH9x/NWkjxEThvbTU0vWhZ0ubX8m4dnDe3D81UwfIzj+UthjRNucnNBjsOZw/OU0wDvvvOP8/vvvDblKiOrqaueVV15xcnNzG30bu5OWluZIcr766quQ02+44QZnxIgRtV6nXbt2zksvvRRy2mOPPeZ07dq1zvu5/fbbHUlhX/nbfxz/93X++c6mTZucsl9+CT39f78yMjKciooKp+xPfwo7b9v//I+zefNmp/i++8LOW9O3r7NixQqncsuWWm835z//cbZt2+aUHHts2Hmlf/ubk52d7RTPmxd2XvXQoc6mTZscx3Gc6sjIsPPzvvzSKS4udorPOy/svKobb3QyMjKc0vffD7/dlJTg7VYmJYWdX/jOO05BQYFTPG1a+HX/8pftDX/4Ify8yEgnLS3NqaqqcsoGDQo7v+S555wtW7Y4xXfdFd7plFOcTZs2ORXp6bU2zF671ikrK3NKR48OO6/swQednJwcp2TOnPCZDjkk+L3WdrtbvvvOKSkpcYrHjQs7r/Kvf3UyMzOd0jffDL/dvn3/r2HnzmHnF3z4oVNYWOgUX3pp+HUvv9xJS0tztn31Vfh58fFOWlqaU11d7ZTvt1/Y+cWvvOLk5eU5RX/9a/j3c9ZZzqZNm5zy33+v9XvN3LDBKS8vd7Ydckh4w8ce276+H344/LqjRzubNm1yqkpKar3dzT/+6JSWljolJ50U/ntz++1OVlaWU/zKK+Hf6/77BxtWxcWFnZ+/aJFTVFTkFE+aFL6+r77aSU9Pd7YtWhR+u4mJwdut6Nkz7Pyi11938vPzneIbbgj/fproMcI57jhn06ZNjXqMqLj3Xh4jVP/HiIJRo8LXdxM9RpTdcguPEdqzx4iKu+7iMULePkbsCevjr987dXd63/C20/Omd8O+et/wtpPaMblB3dLT03ls5fhr+3mt8LE1LS2Nx1aOv7af18SPES9/k+r0vvFtp88Nbzm9b3jrf//7tvPyPf/D8Zea72MEx1+hjxG/d+ru/PeRE52pp9zg/PeRE53fO3Vv8seI+ghs/x1pPdLT05WSkqKvvvpKo0aNCp5+4403asmSJfr222/DrhMZGalnn31W5557bvC0xx9/XDNnzlTWzv9i8r9q+5fsHj16KH/JEiU08TMJc3Jy9Mq//qWzbrlFyV27NvhfqTIiIpR80EE8k9DoX7Kzs7ND3wuTf8neron+lSojEFDy0KE8k9DoX7Kzs7JC17cPHyOyv/xSbzz3nMaNG6cuXbpsP6+JnkmYISn5T3/iMcLoX7KzMzND13crfYzI+eQTLVy4MHQNN4d/ya6F9fHXvf/6RXNWFauqlqPlNgFpSv9Y3TQk4f9O3E23tMpKpbRvz/GX0TMJQ47BOP7argkfW9OqqpQSG8vxF8dfJo8R65f9oic/X60fN2brwB5dddmfUtRr/94cf0nN9jGC4y8FHyNe/W6Dbl74sxxn++Ph9pfQB3TvGQdo/Mhenh5/NckmYZs2bVRVVeX2zdZLeXm52rdvr9dee02nn3568PSJEycqLy9Pb731Vth19tlnH02fPl3XXHNN8LTbb79db775pn6s7cG9FgUFBerQoYPy8/OVkJCw+yvsgYyMDM2ZM0dTpkxRcnJyk94XAGDXeExGS9eS13BTH39d9fJy/WtluqprOVqOCEgnDemuR84d6vr9AgB2ryX/7xf8KzW3WEc/sLjOY4vPrhujXomx9oPVzNAUN+rlkxMjIyM1bNgwffrpp8HTqqur9emnn4Y8s3BHo0aNCrm8JH388cd1Xr6lS9v5X2vQpOhti9626G2L3rboDbffIJ81ZYvetuhth9a26G2rtfd+denGXR5bzF+6sdbzrDR4k7CkpGS3l6nrG7Yyffp0/fOf/9Szzz6rX3/9VZdffrmKi4s1efJkSdKFF14Y8sEmV199tT744AM98MAD+u2333THHXdo6dKlmjp1qlffQpPiX1ls0dsWvW3R2xa9bdEbE4b3qPMfvx3nf98gvwFYU7bobYvedmhti962WnvvTVtLd3lssWlraa3nWWnQJuHUqVPVtWtXHXTQQVq7dq2uuOIKnXXWWXriiSfqvE5WVpYWLVqkxx57TFdeeaXGjBmjbt267fHgu3L22Wfr73//u2bMmKGDDjpIK1as0AcffBC83z/++EMZO7zm/NBDD9VLL72kOXPm6MADD9Rrr72mN998U4MGDWrSOb2SmZnp9Qi+Qm9b9LZFb1v0tkVv9E6M1b1nDlFEYPtLgAJygn++98whDX45EGvKFr1t0dsOrW3R21Zr7+32qxTc1rYhF37//feVm5ur5cuX6/DDD9e0adM0duxYvfzyy0pPT9ddd90lafvu5xFHHKHVq1erY8eO6t+/vwYMGKAFCxbo3Xff1b777tsk38yOpk6dWuczARcvXhx22vjx4zV+/Pgmnqp56Lzjx4mjydHbFr1t0dsWvW3RG5I0fngPHdyrsx597wctW5WqYf17a+qJf2rU+wWxpmzR2xa97dDaFr1ttfbeE4b30FNL1tV6XmNepeC2Bj2TsEOHDoqOjtaoUaPUoUMH3XrrrTr11FP1wgsv6P333w+5bPfu3dW3b1/NmTNHb7/9tu677z7FxsZqxIgR6tSpk6vfBBqmaOdPMEKTorctetuity1626I3avRKjNV1x/bTmMhUXXdsv0a/oThryha9bdHbDq1t0dtWa++946sUAnL2+FUKbmvQJmFOTo7efPNNpaamKjb2/wZv06ZNyGuqA4GA5s+fr6eeekqzZ8/Wcccdp2+//dbz9yrEdpGRkV6P4Cv0tkVvW/S2RW9b9IbbWFO26G2L3nZobYvetvzQe/zwHnrnsoN1VHKVerXZorOHdNZn143ReI+fRSg18OXG06dP1zvvvKNZs2bp999/16GHHqr+/furf//+2rx5c9jlBw8erDfeeENLly7VjBkzlJWVpW+//VYjR4507RsAAAAAAAAAWooDenbVPRNGaM6cOZoy5lgle/wMwhoN2iS89tprQ/6empqqn3/+WT///LMOO+yw4Ok7f1LL8OHD9d577+nLL7/UrbfeqkAgoE8++WQPxsaeKC8v93oEX6G3LXrborctetuiN9zGmrJFb1v0tkNrW/S2RW9vNWiTcGe9e/dW7969dcopp4ScXl1dXevlDzvsMH366adatGjRntwt9lBcXJzXI/gKvW3R2xa9bdHbFr3hNtaULXrborcdWtuity16e6tB70nolqOOOsqLu8X/2rJli9cj+Aq9bdHbFr1t0dsWveE21pQtetuitx1a26K3LXp7y5NNQngrKSnJ6xF8hd626G2L3rbobYvecBtryha9bdHbDq1t0dsWvb3l+ibh6tWrVVlZ6fbNwkUZGRlej+Ar9LZFb1v0tkVvW/SG21hTtuhti952aG2L3rbo7S3XNwkHDhyo33//3e2bhYtSUlK8HsFX6G2L3rbobYvetugNt7GmbNHbFr3t0NoWvW3R21uubxLu/MnGaH7S0tK8HsFX6G2L3rbobYvetugNt7GmbNHbFr3t0NoWvW3R21u8J6EPdenSxesRfIXetuhti9626G2L3nAba8oWvW3R2w6tbdHbFr29xSahD+Xl5Xk9gq/Q2xa9bdHbFr1t0RtuY03ZorctetuhtS1626K3t9gk9KGYmBivR/AVetuity1626K3LXrDbawpW/S2RW87tLZFb1v09habhD5UVVXl9Qi+Qm9b9LZFb1v0tkVvuI01ZYvetuhth9a26G2L3t5ik9CHqqurvR7BV+hti9626G2L3rboDbexpmzR2xa97dDaFr1t0dtbbBL6EE/ftUVvW/S2RW9b9LZFb7iNNWWL3rbobYfWtuhti97ecn2T8KabbtJee+3l9s3CRbwRqC1626K3LXrborctesNtrClb9LZFbzu0tkVvW/T2Vlu3b3DWrFlu3yRc1rVrV69H8BV626K3LXrborctesNtrClb9LZFbzu0tkVvW/T2Fi839qHMzEyvR/AVetuity1626K3LXrDbawpW/S2RW87tLZFb1v09habhD6UkpLi9Qi+Qm9b9LZFb1v0tkVvuI01ZYvetuhth9a26G2L3t5ik9CH0tLSvB7BV+hti9626G2L3rboDbexpmzR2xa97dDaFr1t0dtbTbJJ2KZNm6a4WbiE1/jborctetuity1626I33MaaskVvW/S2Q2tb9LZFb281ySah4zhNcbNwyZYtW7wewVfobYvetuhti9626A23saZs0dsWve3Q2ha9bdHbW436dOO7775b7dq105AhQzRkyJCw14wHAgFXhsP/KSwsVFFRkSQpNzc35L+SFBcXp/j4+HrdVlxcnPsDok70tkVvW/S2RW9b9IbbWFO26G2L3nZobYvetujtrUZtEv71r3/V77//rpUrV+rpp59WWlqannrqqVovm5WVpf/85z/Br19++UW//vqrsrKy9mhwv1m2bJmWLFkSctrChQuDfx49erTGjBlTr9sqLy9XbGysm+NhF+hti9626G2L3rboDbexpmzR2xa97dDaFr1t0dtbDdokvOyyy3TnnXeqa9eu6tOnj/r06aPTTz897HKO4+iII47Q6tWr1bFjR/Xv318DBgzQggUL9O6772rfffd1a37fGDZsmPr371/n+ey2AwAAAAAAoLEatEl4wgkn6MQTT9TJJ5+sG264YZe7u927d1dVVZVmzZql0aNHS5IWLFigESNG7NnEPhUfH1/vlxPvTmRkpCu3g/qhty1626K3LXrbojfcxpqyRW9b9LZDa1v0tkVvbzXog0tOO+00ffvtt+rWrZsOPfRQPfnkk6qurg67XCAQ0Pz58/XUU09p9uzZOu644/Ttt9/yXoXNRM17G8IGvW3R25ZfexcWFiojI0MZGRkh7xNbc1phYWGT3K9fe3uF3nAba8oWvW3R2w6tbdHbFr291eD3JGzTpo1OOukkxcTE6Prrr9fs2bN1//3365RTTgm77ODBg/XGG29o6dKlmjFjhrKysvTtt99q5MiRrgyPxuncubPXI/gKvW3R25Zfe7v5PrEN4dfeXqE33MaaskVvW/S2Q2tb9LZFb281aJNw7Nix+vXXX9WjRw+NGDFCjzzyiPbbbz89/vjj+vTTTzV79uxarzd8+HC99957+vLLL3XrrbcqEAjok08+cWN+NEJ2dnbYJ1Kj6dDbFr1t+bW3V+8T69feXqE33MaaskVvW/S2Q2tb9LZFb281aJPwv//7vzV48GC1adMm5PSnn35aAwYMCP7dcZxar3/YYYfp008/1aJFixoxKtzCL5wtetuity2/9nbzfWIbwq+9vUJvuI01ZYvetuhth9a26G2L3t5q0HsSbt68WZWVlbWe99577wX/XNv7FNb47rvvNGTIkIbcLVyWlpbm9Qi+Qm9b9LZFb1v0tkVvuI01ZYvetuhth9a26G2L3t5q0CbhoYceqttvv13z5s1TcXFxyHl9+vTZ5XWXLVumG264QWVlZdprr70aPilck5SU5PUIvkJvW/S2RW9b9LZFb7iNNWWL3rbobYfWtuhti97eatDLjWNiYvTf//3f+vDDD3XiiScqLi5OBx10kAYPHqzOnTsrISFBkZGRKiwsVEFBgdavX68VK1ZoxYoVOu6443TrrbeqU6dOTfW9oJ6ys7OVnJzs9Ri+QW9b9LZFb1v0tkVvuI01ZYvetuhth9a26G2L3t5q8KcbS9Lxxx+v448/Xj/88IPef/99/fOf/9SmTZuUnZ2t0tJSJSYmqmvXrjrwwAN1wgkn6IEHHlDHjh1dHh2Nxc/CFr1t0dsWvW3R2xa94TbWlC1626K3HVrborctenurUZuENf70pz/pT3/6k2677Ta35oGBkpISxcTEeD2Gb9DbFr1t0dsWvW3RG25jTdmity1626G1LXrbore3GvSehGgd2rbdo71hNBC9bdHbFr1t0dsWveE21pQtetuitx1a26K3LXp7i01CH4qI4Mduid626G2L3rbobYvecBtryha9bdHbDq1t0dsWvb1FfR8qLS31egRfobctetuity1626I33MaaskVvW/S2Q2tb9LZFb2+xSehDHTp08HoEX6G3LXrborctetuiN9zGmrJFb1v0tkNrW/S2RW9vsUnoQ7m5uV6P4Cv0tkVvW/S2RW9b9IbbWFO26G2L3nZobYvetujtLdc3CVevXq3Kykq3bxYuSklJ8XoEX6G3LXrborctetuiN9zGmrJFb1v0tkNrW/S2RW9vub5JOHDgQP3+++9u3yxclJaW5vUIvkJvW/S2RW9b9LZFb7iNNWWL3rbobYfWtuhti97ecv2zpR3Hcfsm4bLu3bt7PYKv0DtcYWGhioqK6jw/Li5O8fHxjbptetuity1626I33MaaskVvW/S2Q2tb9LZFb2+5vkmI5i8jI4NfPEP0Drds2TItWbKkzvNHjx6tMWPGNOq26W2L3rbobYvecBtryha9bdHbDq1t0dsWvb3FJqEP7bXXXl6P4Cv0Djds2DD1799f0vY3pl24cKHGjRunxMRESdufSdhY9LZFb1v0tkVvuI01ZYvetuhth9a26G2L3t7i0419qKCgwOsRfIXe4eLj45WcnKzk5OTgxmBiYmLwtMa+1FiitzV626K3LXrDbawpW/S2RW87tLZFb1v09habhD4UFRXl9Qi+Qm9b9LZFb1v0tkVvuI01ZYvetuhth9a26G2L3t5ikxAAAAAAAADwOTYJfai8vNzrEXyF3rbobYvetuhti95wG2vKFr1t0dsOrW3R2xa9veX6JuFNN93EG002c3vyoRBoOHrborctetuity16w22sKVv0tkVvO7S2RW9b9PaW65uEs2bNYpOwmduyZYvXI/gKvW3R2xa9bdHbFr3hNtaULXrborcdWtuity16e4uXG/tQUlKS1yP4Cr1t0dsWvW3R2xa94TbWlC1626K3HVrborctenuLTUIfysjI8HoEX6G3LXrborctetuiN9zGmrJFb1v0tkNrW/S2RW9vtfV6ANhLSUnxegRfobctetuity1626I33MaaskVvW/S24+fWhYWFKioqkiTl5uaG/Ffa/n528fHxrt6nn3t7gd7ecv2ZhA899JAk6ZdfflFVVZXbNw8XpKWleT2Cr9DbFr1t0dsWvW3RG25jTdmity162/Fz62XLlmnOnDmaM2eOFi5cKElauHBh8LRly5a5fp9+7u0FenvL9WcSHnTQQZKkW2+9Vb/99ptiYmJ0wAEHaPDgwRo0aJBOPvlkt+8SDdSlSxevR/AVetuity1626K3LXrDbawpW/S2RW87fm49bNgw9e/fv87zm+KTcf3c2wv09pYrzyQsLCwM/vmoo46SJL311ltatWqVvvjiC02bNk2JiYn65JNP3Lg77KG8vDyvR/AVetuity1626K3LXrDbawpW/S2RW87fm4dHx+v5OTkOr/cfqmx5O/eXqC3t1x5JuERRxyhDz74oNZPoYmLi9PIkSM1cuRIN+4KLmjfvr3XI/gKvW3R2xa9bdHbFr3hNtaULXrborcdWtuity16e8uVZxIOHTpUI0eO1G+//RZy+ooVK3TiiSe6cRdwUWVlpdcj+Aq9bdHbFr1t0dsWveE21pQtetuitx1a26K3LXp7y5VNwrlz52rSpEk6/PDD9cUXX2j16tWaMGGChg0bpjZt2rhxF/W2ZcsWnX/++UpISFDHjh110UUXBT/9qC5jxoxRIBAI+brsssuMJrZXXV3t9Qi+Qm9b9LZFb1v0tkVvuI01ZYvetuhth9a26G2L3t5y7YNLZs6cqaioKB177LGqqqrS0Ucfra+//lojRoxw6y7q5fzzz1dGRoY+/vhjVVRUaPLkyZoyZYpeeumlXV7vkksu0Z133hn8e2t+imtMTIzXI/gKvW3R2xa9bdHbFr3hNtaULXrborcdWtuity16e8uVZxJmZWXp6quv1t133639999f7dq106RJk8w3CH/99Vd98MEH+p//+R+NHDlShx9+uB555BG98sorSk9P3+V127dvr6SkpOBXQkKC0dT28vPzvR7BV+hti9626G2L3rboDbexpmzR2xa97dDaFr1t0dtbrmwS9u7dW59//rkWLFigZcuW6fXXX9eUKVN0//33u3Hz9fb111+rY8eOGj58ePC0Y445RhEREfr22293ed0XX3xRiYmJGjRokG655RaVlJTs8vJlZWUqKCgI+WopEhMTvR7BV+hti9626G2L3rbo3fy05OMviTVljd626G2H1rbobYve3nJlk/CZZ57R8uXLddJJJ0mSxo4dq0WLFumhhx7SlVde6cZd1EtmZqa6du0aclrbtm3VuXNnZWZm1nm98847Ty+88IIWLVqkW265Rc8//7wuuOCCXd7XrFmz1KFDh+BXjx49JEnbtm1Tenq6qqurlZaWJklKS0tTeXm5srOzVVRUpLy8PG3ZskWlpaXKzMxUZWVlyGUrKiqUmZmpkpISbdmyRVu3blVxcbGysrJUUVERctmqqiqlp6ertLRUmzdvVn5+vgoLC5WTk6OysrKQyzqOo7S0NG3atEk5OTnBg+vc3FyVlpbWe+6SkpJa566srAybu6ioqNa5q6urdzt3zbw1/y0rK1NOTo4KCwuVn5+vzZs31zl3RUWFsrKyVFRUpK1btzZo7ry8PBUVFSk7O1vl5eV1zp2bmxtsWNvcNdep6V3b3FVVVbXOXVxcHDb3zg1r5i4tLa333Nu2bat17vT09LC5y8rKlJ2dHTZ3RkbGbufe3ZrNyMgIzl1YWChp+/uJ1nfu3NzcOn/X0tLSgnPv+Lvm5tw7rtns7Oxaf9fS09ODa7Y+czenx4ja5q7rd62mN48RjX+M2NXcO6/ZtLQ03z1G5OXlBX/X3HiMqPldq89jRHp6ui8eI3JyciRJeXl5rj9G1Db3nvDy+Cs7O1uSlJ2d3ejH1jVr1nD8VcfcTfHYumbNGo6/ZPfYunr1ao6/dpib46/m/xjB8RfHX14/Rmzbtk2SVFRU1OTHX7t7IlyNgOM4Tr0u2Qjr16/XCSecoF9//XWPbufmm2/Wvffeu8vL/Prrr1q4cKGeffZZrVq1KuS8rl27aubMmbr88svrdX+fffaZjj76aK1du1Z9+/at9TJlZWUqKysL/r2goEA9evRQfn5+q36pMuC2jIwMzZkzR1OmTFFycrLX4wCA77Skx2Evj79aUicAAND8NcdjC1eeSViXXr166auvvtrj27nuuuv066+/7vKrT58+SkpKCv4rb43Kykpt2bJFSUlJ9b6/kSNHSpLWrl1b52WioqKUkJAQ8tVS1Owwwwa9bdHbFr1t0dsWvZuflnz8JbGmrNHbFr3t0NoWvW3R21uufbpxXTp16rTHt9GlSxd16dJlt5cbNWqU8vLytGzZMg0bNkzS9mcFVldXBzf+6mPFihWS1Gx2ct2280uy0bTobYvetuhti9626A23saZs0dsWve3Q2ha9bdHbW036TEJrAwcO1NixY3XJJZfou+++05dffqmpU6fqnHPOUffu3SVt35UeMGCAvvvuO0nSunXrdNddd2nZsmVav3693n77bV144YU68sgjNWTIEC+/nSazefNmr0fwFXrborctetuity16w22sKVv0tkVvO7S2RW9b9PZWq9oklLZ/SvGAAQN09NFH68QTT9Thhx+uOXPmBM+vqKjQqlWrgm/aGBkZqU8++UTHHXecBgwYoOuuu05nnnmm3nnnHa++hSbX0l6a09LR2xa9bdHbFr1t0RtuY03ZorctetuhtS1626K3t5r85cbWOnfurJdeeqnO83v16qUdP6ulR48eWrJkicVozca2bdvUvn17r8fwDXrborctetuity16w22sKVv0tkVvO7S2RW9b9PaWa5uEeXl5evrpp4OfZHzAAQfoL3/5izp06ODWXcAlgUDA6xF8hd626G2L3rbobYvecBtryha9bdHbDq1t0dsWvb3lysuNly5dqr59++qhhx7Sli1btGXLFj344IPq27evfvjhBzfuAi6KjIz0egRfobctetuity1622rNvQsLC5WRkaGMjAzl5uZKknJzc4OnFRYWejxh69Sa11RzRG9b9LZDa1v0tkVvb7nyTMJrr71Wp556qv75z3+qbdvtN1lZWamLL75Y11xzjT7//HM37gYuKSoqUmxsrNdj+Aa9bdHbFr1t0dtWa+69bNmysLdbWbhwYfDPo0eP1pgxY4ynav1a85pqjuhti952aG2L3rbo7S1XNgmXLl0askEoSW3bttWNN96o4cOHu3EXcFHnzp29HsFX6G2L3rbobYvetlpz72HDhql///51nh8XF2c4jX+05jXVHNHbFr3t0NoWvW3R21uuvNw4ISFBf/zxR9jpGzduVHx8vBt3ARdlZ2d7PYKv0NsWvW3R2xa9bbXm3vHx8UpOTq7zi+O3ptGa11RzRG9b9LZDa1v0tkVvb7mySXj22Wfroosu0vz587Vx40Zt3LhRr7zyii6++GKde+65btwFXJSSkuL1CL5Cb1v0tkVvW/S2RW+4jTVli9626G2H1rbobYve3nJlk/Dvf/+7xo0bpwsvvFC9evVSz549NWnSJJ111lm699573bgLuCgtLc3rEXyF3rbobYvetuhti95w+wNeWFO26G2L3nZobYvetujtLVfekzAyMlIPP/ywZs2apXXr1kmS+vbtq/bt27tx83BZUlKS1yP4Cr1t0dsWvW3R2xa94fYHvLCmbNHbFr3t0NoWvW3R21uubBLeeeeduzx/xowZbtwNXJKVlaXu3bt7PYZv0NsWvW3R2xa9bdEbbn/AC2vKFr1t0dsOrW3R2xa9veXKJuEbb7wR8veKigqlpqaqbdu26tu3L5uEzUynTp28HsFX6G2L3rbobYvetuiN+Ph4Vz/EhTVli9626G2H1rbobYve3nJlk3D58uVhpxUUFGjSpEk644wz3LgLuKikpEQxMTFej+Eb9LZFb1v0tkVvW/SG21hTtuhti952aG2L3rbo7S1XPrikNgkJCZo5c6b+3//7f011F2iktm1d2RtGPdHbFr1t0dsWvW3RG25jTdmity1626G1LXrbore3mmyTUJLy8/OVn5/flHeBRoiIaNIfO3ZCb1v0tkVvW/S2RW+4jTVli9626G2H1rbobYve3nJli/Yf//hHyN8dx1FGRoaef/55nXDCCW7cBVy0bds2V99fB7tGb1v0tkVvW/S2RW+4jTVli9626G2H1rbobYve3nJlk/Chhx4K+XtERIS6dOmiiRMn6pZbbnHjLuCihIQEr0fwFXrborctetuity16w22sKVv0tkVvO7S2RW9b9PaWK5uEqampbtwMjOTm5iolJcXrMXyD3rbobYvetuhti95wG2vKFr1t0dsOrW3R21Zr711YWKiioiJJ27/XHf8rSXFxcZ4+kzLgOI7j2b23IgUFBerQoYPy8/PZ+QYaICMjQ3PmzNGUKVOUnJzs9TgAgBaE4y8AANCSLF68WEuWLKnz/NGjR2vMmDF2A+2k0c8knD59er0v++CDDzb2btAE0tLSWvXOfHNDb1v0tkVvW/S2RW+4jTVli9626G2H1rbobau19x42bJj69+9f5/lxcXGG04Rr9Cbh8uXLQ/7+ww8/qLKyMvjNrl69Wm3atNGwYcP2bEK4rnv37l6P4Cv0tkVvW/S2RW9b9IbbWFO26G2L3nZobYvetlp77/j4+Gb9wSyN/mzpRYsWBb9OOeUUjR49Wps2bdIPP/ygH374QRs3btRRRx2lk046yc154YL09HSvR/AVetuity1626K3LXrDbawpW/S2RW87tLZFb1v09lajNwl39MADD2jWrFnq1KlT8LROnTrp7rvv1gMPPODGXcBFiYmJXo/gK/S2RW9b9LZFb1v0httYU7bobYvedmhti9626O0tVzYJCwoKlJOTE3Z6Tk6OCgsL3bgLuKigoMDrEXyF3rbobYvetuhti95wG2vKFr1t0dsOrW3R2xa9veXKJuEZZ5yhyZMna+HChdq0aZM2bdqk119/XRdddJHGjRvnxl3ARVFRUV6P4Cv0tkVvW/S2RW9b9IbbWFO26G2L3nZobYvetujtrUZ/cMmOnnzySV1//fU677zzVFFRsf2G27bVRRddpPvvv9+NuwAAAAAAAADQRFzZJGzfvr0ef/xx3X///Vq3bp0kqW/fvoqNjXXj5uGy8vJyr0fwFXrborctetuity16w22sKVv0tkVvO7S2RW9b9PaWK5uENWJjYzVkyBA3bxJNgM1bW/S2RW9b9LZFb1v0httYU7bobYvedmhti9626O2tRm8STp8+XXfddZdiY2M1ffr0XV72wQcfbOzdoAls3bpVMTExXo/hG/S2RW9b9LZFb1v0httYU7bobYvedmhti9626O2tRm8SLl++PPj+g8uXL6/zcoFAoLF3gSaSlJTk9Qi+Qm9b9LZFb1v0tkVvuI01ZYvetuhth9a26G2L3t5q9CbhokWLav0zmr+MjAylpKR4PYZv0NsWvW3R2xa9bdEbbmNN2aK3LXrbobUtetuit7ci3LiR0tJSlZSUBP++YcMGzZ49Wx999JEbNw+X8Qtni9626G2L3rbobYvecBtryha9bdHbDq1t0dsWvb3lyibhaaedpueee06SlJeXpxEjRuiBBx7QaaedpieeeMKNu4CL0tLSvB7BV+hti9626G2L3rboDbexpmzR2xa97dDaFr1t0dtbrmwS/vDDDzriiCMkSa+99pqSkpK0YcMGPffcc/rHP/7hxl3ARV26dPF6BF+hty1626K3LXrbojfcxpqyRW9b9LZDa1v0tkVvb7mySVhSUqL4+HhJ0kcffaRx48YpIiJChxxyiDZs2ODGXcBFeXl5Xo/gK/S2RW9b9LZFb1v0httYU7bobYvedmhti9626O0tVzYJ+/XrpzfffFMbN27Uhx9+qOOOO06SlJ2drYSEBDfuAi5q37691yP4Cr1t0dsWvW3R2xa94TbWlC1626K3HVrborctenvLlU3CGTNm6Prrr1evXr00cuRIjRo1StL2ZxUOHTrUjbuAiyorK70ewVfobYvetuhti9626A23saZs0dsWve3Q2ha9bdHbW23duJGzzjpLhx9+uDIyMnTggQcGTz/66KN1xhlnuHEXcFF1dbXXI/gKvW3R2xa9bdHbFr3hNtaULXrborcdWtuity16e8uVTUJJSkpKUlJSUshpI0aMcOvm4aLo6GivR/AVetuity1626K3LXrDbawpW/S2RW87tLZFb1v09pYrLzeWpH//+9+64IILNGrUqOBHVj///PP64osv3LoLuKSgoMDrEXyF3rbobYvetuhti95wG2vKFr1t0dsOrW3R2xa9veXKJuHrr7+u448/XjExMVq+fLnKysokSfn5+frb3/7mxl3ARYmJiV6P4Cv0tkVvW/S2RW9b9IbbWFO26G2L3nZobYvetujtLVc2Ce+++249+eST+uc//6l27doFTz/ssMP0ww8/uHEXcFFWVpbXI/gKvW3R2xa9bdHbFr3hNtaULXrborcdWtuity16e8uVTcJVq1bpyCOPDDu9Q4cOysvLc+Mu4KKUlBSvR/AVetuity1626K3LXrDbawpW/S2RW87tLZFb1v09pYrm4RJSUlau3Zt2OlffPGF+vTp48ZdwEU17xkJG/S2RW9b9LZFb1v0httYU7bobYvedmhti9626O0tVzYJL7nkEl199dX69ttvFQgElJ6erhdffFHXX3+9Lr/8cjfuAi7q1q2b1yP4Cr1t0dsWvW3R2xa94TbWlC1626K3HVrborctenvLlU3Cm2++Weedd56OPvpoFRUV6cgjj9TFF1+sSy+9VFdddZUbdwEX5ebmej2Cr9DbFr1t0dsWvW3RG25jTdmity1626G1LXrbore32rpxI4FAQLfddptuuOEGrV27VkVFRdp///0VFxen0tJSxcTEuHE3cElCQoLXI/gKvW3R2xa9bdHbFr3hNtaULXrborcdWtuity16e8uVZxLWiIyM1P77768RI0aoXbt2evDBB9W7d2837wIu2LZtm9cj+Aq9bdHbFr1t0dsWveE21pQtetuitx1a26K3LXp7a482CcvKynTLLbdo+PDhOvTQQ/Xmm29KkubOnavevXvroYce0rXXXuvGnHBRIBDwegRfobctetuity1626I33MaaskVvW/S2Q2tb9LZFb2/t0cuNZ8yYoaeeekrHHHOMvvrqK40fP16TJ0/WN998owcffFDjx49XmzZt3JoVLmnXrp3XI/gKvW3R2xa9bdHbFr3hNtaULXrborcdWtuity16e2uPnkm4YMECPffcc3rttdf00UcfqaqqSpWVlfrxxx91zjnnsEHYTBUXF3s9gq/Qu26pucV64OO1WlzeWw98vFapuXveit626G2L3rboDbexpmzR2xa97dDaFr1t0dtbAcdxnMZeOTIyUqmpqUpJSZEkxcTE6LvvvtPgwYNdG7ClKCgoUIcOHZSfn9/s32izoqKC3XlD9K7dq0s36ubXV0qSHMcJPq383jOHaPzwHo2+XXrborctetuid/PXko6/JNaUNXrborcdWtuity16e2uPnklYVVWlyMjI4N/btm2ruLi4PR4KTSs7O9vrEXyF3uFSc4t18+srVe1I1Y7kKBD8802vr9T6PXhGIb1t0dsWvW3RG25jTdmity1626G1LXrbore39uiZhBERETrhhBMUFRUlSXrnnXf05z//WbGxsSGXW7hw4Z5N2QK0tH/JBrx07we/ac7nv6uqOvzhp01EQFOO7KObxg7wYDIAQEvC8RcAAIB79uiZhBMnTlTXrl3VoUMHdejQQRdccIG6d+8e/HvNF5qXtLQ0r0fwFXqH27S1VHX9+4TjONq0tbTRt01vW/S2RW9b9IbbWFO26G2L3nZobYvetujtrT36dOO5c+e6NQcMJScnez2Cr9A73N6dYra/B2EtG4WBQEB7d4pp9G3T2xa9bdHbFr3hNtaULXrborcdWtuity16e2uPnkmIlikzM9PrEXyF3uEmDO+xy2cSnr0HH1xCb1v0tkVvW/SG21hTtuhti952aG2L3rbo7S02CX2oU6dOXo/gK/QO1zsxVveeOUQRASkiIAXkBP9875lD1Csxdvc3Ugd626K3LXrbojfcxpqyRW9b9LZDa1v0tkVvb7FJ6EMlJSVej+Ar9K7d+OE99Nl1YzRuYIJ6tdmicQMT9Nl1YzR+D55FKNHbGr1t0dsWveE21pQtetuitx1a26K3LXp7i01CH2rbdo/eihINRO+69UqM1XXH9tOYyFRdd2y/PXoGYQ1626K3LXrbojfcxpqyRW9b9LZDa1v0tkVvb7FJ6EMREfzYLdHbFr1t0dsWvW3RG25jTdmity1626G1LXrbore3Wl39e+65R4ceeqjat2+vjh071us6juNoxowZSk5OVkxMjI455hitWbOmaQf10LZt27wewVfobYvetuhti9626A23saZs0dsWve3Q2ha9bdHbW61uk7C8vFzjx4/X5ZdfXu/r3HffffrHP/6hJ598Ut9++61iY2N1/PHHt9rFmZCQ4PUIvkJvW/S2RW9b9LZFb7iNNWWL3rbobYfWtuhti97eanWbhDNnztS1116rwYMH1+vyjuNo9uzZ+utf/6rTTjtNQ4YM0XPPPaf09HS9+eabTTusR3Jzc70ewVfobYvetuhti9626A23saZs0dsWve3Q2ha9bdHbW61uk7ChUlNTlZmZqWOOOSZ4WocOHTRy5Eh9/fXXHk7WdLp37+71CL5Cb1v0tkVvW/S2RW+4jTVli9626G2H1rbobYve3vL9JmFmZqYkqVu3biGnd+vWLXhebcrKylRQUBDy1VKkp6d7PYKv0NsWvW3R2xa9bdG7+WnJx18Sa8oavW3R2w6tbdHbFr291SI2CW+++WYFAoFdfv3222+mM82aNUsdOnQIfvXo0UPS9jfZTE9PV3V1tdLS0iRJaWlpKi8vV3Z2toqKipSXl6ctW7aotLRUmZmZqqysDLlsRUWFMjMzVVJSoi1btmjr1q0qLi5WVlaWKioqQi5bVVWl9PR0lZaWavPmzcrPz1dhYaFycnJUVlYWclnHcZSWlqa99tpLOTk5wYPr3NxclZaW1nvukpKSWueurKwMm7uoqKjWuaurq3c7d828Nf8tKytTTk6OCgsLlZ+fr82bN9c5d0VFhbKyslRUVKStW7c2aO68vDwVFRUpOztb5eXldc6dm5sbbFjb3DXXqeld29xVVVW1zl1cXBw2984Na+YuLS2t99zbtm2rde709PSwucvKypSdnR02d0ZGxm7n3t2azcjICM5dWFgoSdqyZUu9587Nza3zdy0xMTE4946/a27OveOazc7OrvV3LT09Pbhm6zN3c3qMqG3uun7XanrzGNH4x4hdzb3zmu3SpYvvHiPy8vKCv2tuPEbU/K7V5zGia9euPEbs4WNEbXPviZZ8/FVWVqbIyEiOv+qYuykeW9u1a8fxl+weW9u2bcvx1x4+RnD8xfFXa36M4PjL2+OvkpIS1UfAcRynXpf0UE5OjjZv3rzLy/Tp00eRkZHBv8+bN0/XXHON8vLydnm933//XX379tXy5ct10EEHBU8fPXq0DjroID388MO1Xq+srExlZWXBvxcUFKhHjx7Kz89v9m+0mZaWppSUFK/H8A1671pGRobmzJmjKVOmKDk5eY9vj9626G2L3rbo3fy05OMviTVljd626G2H1rbobYve3mrr9QD10aVLF3Xp0qVJbrt3795KSkrSp59+GtwkLCgo0LfffrvLT0iOiopSVFRUk8zU1BITE70ewVfobYvetuhti9626N38tOTjL4k1ZY3etuhth9a26G2L3t5qES83bog//vhDK1as0B9//KGqqiqtWLFCK1asUFFRUfAyAwYM0BtvvCFJCgQCuuaaa3T33Xfr7bff1k8//aQLL7xQ3bt31+mnn+7Rd9G0Wtr797R09LZFb1v0tkVvW/SG21hTtuhti952aG2L3rbo7a0W8UzChpgxY4aeffbZ4N+HDh0qSVq0aJHGjBkjSVq1apXy8/ODl7nxxhtVXFysKVOmKC8vT4cffrg++OADRUdHm85upbV+X80VvW3R2xa9bdHbFr3hNtaULXrborcdWtuity16e6vVbRLOmzdP8+bN2+Vldn4bxkAgoDvvvFN33nlnE07WfFRXV3s9gq/Q2xa9bdHbFr1t0RtuY03ZorctetuhtS1626K3t1rdy42xe5WVlV6P4Cv0tkVvW/S2RW9b9IbbWFO26G2L3nZobYvetujtLTYJfah9+/Zej+Ar9LZFb1v0tkVvW/SG21hTtuhti952aG2L3rbo7S02CX1o69atXo/gK/S2RW9b9LZFb1v0httYU7bobYvedmhti9626O0tNgl9KCkpyesRfIXetuhti9626G2L3nAba8oWvW3R2w6tbdHbFr29xSahD2VkZHg9gq/Q2xa9bdHbFr1t0RtuY03ZorctetuhtS1626K3t9gk9KGUlBSvR/AVetuity1626K3LXrDbawpW/S2RW87tLZFb1v09habhD6Ulpbm9Qi+Qm9b9LZFb1v0tkVvuI01ZYvetuhth9a26G2L3t5ik9CHunbt6vUIvkJvW/S2RW9b9LZFb7iNNWWL3rbobYfWtuhti97eYpPQh7Zs2eL1CL5Cb1v0tkVvW/S2RW+4jTVli9626G2H1rbobYve3mKT0IdiY2O9HsFX6G2L3rbobYvetugNt7GmbNHbFr3t0NoWvW3R21tsEvpQRUWF1yP4Cr1t0dsWvW3R2xa94TbWlC1626K3HVrborctenuLTUIfchzH6xF8hd626G2L3rbobYvecBtryha9bdHbDq1t0dsWvb3FJqEPRUdHez2Cr9DbFr1t0dsWvW3RG25jTdmity1626G1LXrbore32CT0oYKCAq9H8BV626K3LXrborctesNtrClb9LZFbzu0tkVvW/T2FpuEPpSYmOj1CL5Cb1v0tkVvW/S2RW+4jTVli9626G2H1rbobYve3mKT0IeysrK8HsFX6G2L3rbobYvetugNt7GmbNHbFr3t0NoWvW3R21tsEvpQSkqK1yP4Cr1t0dsWvW3R2xa94TbWlC1626K3HVrborctenuLTUIfSktL83oEX6G3LXrborctetuiN9zGmrJFb1v0tkNrW/S2RW9vsUnoQ926dfN6BF+hty1626K3LXrbojfcxpqyRW9b9LZDa1v0tkVvb7FJ6EO5ublej+Ar9LZFb1v0tkVvW/SG21hTtuhti952aG2L3rbo7S02CX0oISHB6xF8hd626G2L3rbobYvecBtryha9bdHbDq1t0dsWvb3FJqEPbdu2zesRfIXetuhti9626G2L3nAba8oWvW3R2w6tbdHbFr29xSahD0VE8GO3RG9b9LZFb1v0tkVvuI01ZYvetuhth9a26G2L3t6ivg+1bdvW6xF8hd626G2L3rbobYvecBtryha9bdHbDq1t0dsWvb3FJqEPlZSUeD2Cr9DbFr1t0dsWvW3RG25jTdmity1626G1LXrbore32CT0oY4dO3o9gq/Q2xa9bdHbFr1t0RtuY03ZorctetuhtS1626K3t9gk9KGcnByvR/AVetuity1626K3LXrDbawpW/S2RW87tLZFb1v09habhD6UkpLi9Qi+Qm9b9LZFb1v0tkVvuI01ZYvetuhth9a26G2L3t5ik9CH0tLSvB7BV+hti9626G2L3rboDbexpmzR2xa97dDaFr1t0dtbbBL6UHJystcj+Aq9bdHbFr1t0dsWveE21pQtetuitx1a26K3LXp7i01CH8rMzPR6BF+hty1626K3LXrbojfcxpqyRW9b9LZDa1v0tkVvb7FJ6EOdOnXyegRfobctetuity1626I33MaaskVvW/S2Q2tb9LZFb2+xSehDxcXFXo/gK/S2RW9b9LZFb1v0httYU7bobYvedmhti9626O0tNgl9KDIy0usRfIXetuhti9626G2L3nAba8oWvW3R2w6tbdHbFr29xSYhAAAAAAAA4HNsEvpQWVmZ1yP4Cr1t0dsWvW3R2xa94TbWlC1626K3HVrborctenuLTUIfSkhI8HoEX6G3LXrborctetuiN9zGmrJFb1v0tkNrW/S2RW9vsUnoQ7m5uV6P4Cv0tkVvW/S2RW9b9IbbWFO26G2L3nZobYvetujtLTYJfah79+5ej+Ar9LZFb1v0tkVvW/SG21hTtuhti952aG2L3rbo7S02CX0oPT3d6xF8hd626G2L3rbobYvecBtryha9bdHbDq1t0dsWvb3FJqEPpaSkeD2Cr9DbFr1t0dsWvW3RG25jTdmity1626G1LXrbore32CT0obS0NK9H8BV626K3LXrborctesNtrClb9LZFbzu0tkVvW/T2FpuEPpSYmOj1CL5Cb1v0tkVvW/S2RW+4jTVli9626G2H1rbobYve3mKT0IcKCgq8HsFX6G2L3rbobYvetugNt7GmbNHbFr3t0NoWvW3R21tsEvpQdHS01yP4Cr1t0dsWvW3R2xa94TbWlC1626K3HVrborctenuLTUIfqq6u9noEX6G3LXrborctetuiN9zGmrJFb1v0tkNrW/S2RW9vsUnoQ5WVlV6P4Cv0tkVvW/S2RW9b9IbbWFO26G2L3nZobYvetujtLTYJfah9+/Zej+Ar9LZFb1v0tkVvW/SG21hTtuhti952aG2L3rbo7S02CX1o69atXo/gK/S2RW9b9LZFb1v0httYU7bobYvedmhti9626O0tNgl9qFu3bl6P4Cv0tkVvW/S2RW9b9IbbWFO26G2L3nZobYvetujtLTYJfSgzM9PrEXyF3rbobYvetuhti95wG2vKFr1t0dsOrW3R2xa9vcUmoQ+lpKR4PYKv0NsWvW3R2xa9bdEbbmNN2aK3LXrbobUtetuit7fYJPShtLQ0r0fwFXrborctetuity16w22sKVv0tkVvO7S2RW9b9PYWm4Q+1LVrV69H8BV626K3LXrborctesNtrClb9LZFbzu0tkVvW/T2FpuEPrRlyxavR/AVetuity1626K3LXrDbawpW/S2RW87tLZFb1v09habhD4UFxfn9Qi+Qm9b9LZFb1v0tkVvuI01ZYvetuhth9a26G2L3t5ik9CHysvLvR7BV+hti9626G2L3rboDbexpmzR2xa97dDaFr1t0dtbbBL6kOM4Xo/gK/S2RW9b9LZFb1v0httYU7bobYvedmhti9626O0tNgl9KDo62usRfIXetuhti9626G2L3nAba8oWvW3R2w6tbdHbFr29xSahDxUUFHg9gq/Q2xa9bdHbFr1t0RtuY03ZorctetuhtS1626K3t1rdJuE999yjQw89VO3bt1fHjh3rdZ1JkyYpEAiEfI0dO7ZpB/XQXnvt5fUIvkLvcIWFhcrIyFBGRoZyc3MlSbm5ucHTCgsLG33b9LZFb1v0tkVvuI01ZYvetuhth9a26G2L3t5q6/UAbisvL9f48eM1atQoPf300/W+3tixYzV37tzg36OioppivGYhOztbKSkpXo/hG/QOt2zZMi1ZsiTktIULFwb/PHr0aI0ZM6ZRt01vW/S2RW9b9IbbWFO26G2L3nZobYvetujtrYDTSt8Vct68ebrmmmuUl5e328tOmjRJeXl5evPNNxt9fwUFBerQoYPy8/OVkJDQ6NsB/KCwsFBFRUV1nh8XF6f4+HjDiQAALRHHXwAAAO5pdS83bqzFixera9eu6t+/vy6//HJt3rzZ65GaTFpamtcj+Aq9w8XHxys5ObnOrz3ZIKS3LXrborctesNtrClb9LZFbzu0tkVvW/T2Vqt7uXFjjB07VuPGjVPv3r21bt063XrrrTrhhBP09ddfq02bNrVep6ysTGVlZcG/t6Q31+zWrZvXI/gKvW3R2xa9bdHbFr2bn5Z8/CWxpqzR2xa97dDaFr1t0dtbLeKZhDfffHPYB4vs/PXbb781+vbPOeccnXrqqRo8eLBOP/10vfvuu/r++++1ePHiOq8za9YsdejQIfjVo0cPSdK2bduUnp6u6urq4A54WlqaysvLlZ2draKiIuXl5WnLli0qLS1VZmamKisrQy5bUVGhzMxMlZSUaMuWLdq6dauKi4uVlZWlioqKkMtWVVUpPT1dpaWl2rx5s/Lz81VYWKicnByVlZWFXNZxHKWlpSkjI0M5OTkqKChQQUGBcnNzVVpaWu+5S0pKap27srIybO6ioqJa566urt7t3DXz1vy3rKxMOTk5KiwsVH5+vjZv3lzn3BUVFcrKylJRUZG2bt3aoLnz8vJUVFSk7OxslZeX1zl3bm5usGFtc9dcp6Z3bXNXVVXVOndxcXHY3Ds3rJm7tLS03nNv27at1rnT09PD5i4rK1N2dnbY3BkZGbude3drNiMjI2TuwsLCBs2dm5tb5+9aZmZmcO4df9fcnHvHNZudnV3r71p6enpwzdZn7ub0GFHb3HX9rtX05jGi8Y8Ru5p75zWbmZnJY8QePkbU/K7V5zEiKyuLx4g9fIyobe490ZKPv8rKyrRu3TqOv+qYuykeW9etW8fxl+weW2t6c/zF8VdLeYzg+Ivjr9b6GFHXcUR9tIj3JMzJydnty3/79OmjyMjI4N8b8p6EtenSpYvuvvtuXXrppbWeX9u/ZPfo0aNFvCdOaWmpYmJivB7DN+hti9626G2L3rbo3fy05OMviTVljd626G2H1rbobYve3moRLzfu0qWLunTpYnZ/mzZt0ubNm5WcnFznZaKiolrsJyDzS2eL3rbobYvetuhti97NT0s+/pJYU9bobYvedmhti9626O2tFvFy44b4448/tGLFCv3xxx+qqqrSihUrtGLFipBPUh0wYIDeeOMNSVJRUZFuuOEGffPNN1q/fr0+/fRTnXbaaerXr5+OP/54r76NJhUR0ep+7M0avW3R2xa9bdHbFr3hNtaULXrborcdWtuity16e6tFPJOwIWbMmKFnn302+PehQ4dKkhYtWqQxY8ZIklatWqX8/HxJUps2bbRy5Uo9++yzysvLU/fu3XXcccfprrvuatH/Ur0rbdu2uh97s0ZvW/S2RW9b9LZFb7iNNWWL3rbobYfWtuhti97eanX1582bp3nz5u3yMju+DWNMTIw+/PDDJp6qeSkpKVFcXJzXY/gGvW3R2xa9bdHbFr3hNtaULXrborcdWtuity16e4vncfpQx44dvR7BV+hti9626G2L3rboDbexpmzR2xa97dDaFr1t0dtbbBL6UE5Ojtcj+Aq9bdHbFr1t0dsWveE21pQtetuitx1a26K3LXp7K+Ds+NpbNFpBQYE6dOig/Px8JSQkeD0OAABAq8fxFwAAgHt4JqEPpaWleT2Cr9DbFr1t0dsWvW3RG25jTdmity1626G1LXrbore3eCahS1rSv2RXV1fzseKG6G2L3rbobYvetujd/LWk4y+JNWWN3rbobYfWtuhti97eorwPZWZmej2Cr9DbFr1t0dsWvW3RG25jTdmity1626G1LXrbore32no9QGtR84TMgoICjyfZvbZt27aIOVsLetuity1626K3LXo3nfj4eAUCgT2+nZZ0/CWxpqzR2xa97dDaFr1t0btp7e4YjE1ClxQWFkqSevTo4fEkAAAAzZtbLw/m+AsAAKD+dncMxnsSuqS6ulrp6f+/vXuNjapq2zh+TUtbCkMpAu20hdJyloNYJKlFMA+xEQhBPCE2lXDQEIREqoCVIIeEFAkmBr+AaASNHBQSQG2giIAgWo7hIGpKCxUQW2oslRJObed+P7xhdN7yPPF5mdnTdv6/ZH+Yvdbsvdad1emVNdPObwF7ZzxYrl69qq5du+rixYvN4n/3NHfU21nU21nU21nU21nUO7gClZeaS/6SWFNOo97Oot7OodbOot7Oot7BxycJHRIREaEuXbqEehj/WFxcHD90DqLezqLezqLezqLezqLeTVtzy18Sa8pp1NtZ1Ns51NpZ1NtZ1Dt0+OISAAAAAAAAIMyxSQgAAAAAAACEOTYJw0xMTIwWLVqkmJiYUA8lLFBvZ1FvZ1FvZ1FvZ1FvBBprylnU21nU2znU2lnU21nUO/T44hIAAAAAAAAgzPFJQgAAAAAAACDMsUkIAAAAAAAAhDk2CQEAAAAAAIAwxyZhC7B48WK5XC6/o2/fvr72mzdvaubMmerYsaPcbreeeeYZXb582e8aFy5c0JgxY9SmTRslJCRo7ty5qq+vd3oqzcalS5f0wgsvqGPHjoqNjdXAgQN19OhRX7uZaeHChUpKSlJsbKyys7NVWlrqd43q6mrl5uYqLi5O8fHxevHFF3Xt2jWnp9LkpaWlNVrfLpdLM2fOlMT6DrSGhgYtWLBA6enpio2NVY8ePbRkyRL9/d/Xsr4Dp7a2Vnl5eerWrZtiY2M1dOhQHTlyxNdOre/N/v37NXbsWCUnJ8vlcmnbtm1+7YGq76lTpzR8+HC1bt1aXbt21fLly4M9NTQRZDDnkcGcQwZzDvnLeWSw4CF/NXOGZm/RokXWv39/q6io8B2///67r3369OnWtWtX2717tx09etQefvhhGzp0qK+9vr7eBgwYYNnZ2Xb8+HHbvn27derUyebNmxeK6TR51dXV1q1bN5s8ebIdOnTIzp07Zzt37rSysjJfn2XLlln79u1t27ZtdvLkSXviiScsPT3dbty44eszatQoGzRokB08eNC+/fZb69mzp+Xk5IRiSk1aVVWV39retWuXSbK9e/eaGes70AoKCqxjx45WWFho5eXltnnzZnO73fbuu+/6+rC+A+e5556zfv362b59+6y0tNQWLVpkcXFx9uuvv5oZtb5X27dvt/nz59uWLVtMkm3dutWvPRD1/fPPPy0xMdFyc3Pt9OnTtnHjRouNjbXVq1c7NU2EEBnMWWQwZ5HBnEP+ch4ZLHjIX80bm4QtwKJFi2zQoEF3baupqbGoqCjbvHmz79zPP/9skqy4uNjM/veHOCIiwiorK319Vq1aZXFxcXbr1q2gjr05ys/Pt2HDhv3bdq/Xax6Px95++23fuZqaGouJibGNGzeamdlPP/1kkuzIkSO+Pjt27DCXy2WXLl0K3uBbgFmzZlmPHj3M6/WyvoNgzJgxNnXqVL9zTz/9tOXm5poZ6zuQrl+/bpGRkVZYWOh3fvDgwTZ//nxqHWD/N6QGqr4rV660Dh06+L2e5OfnW58+fYI8IzQFZDBnkcFCiwwWPOQvZ5HBnEP+an74c+MWorS0VMnJyerevbtyc3N14cIFSdKxY8dUV1en7OxsX9++ffsqNTVVxcXFkqTi4mINHDhQiYmJvj4jR47U1atX9eOPPzo7kWbgiy++0JAhQzR+/HglJCQoIyNDH3zwga+9vLxclZWVfjVv3769MjMz/WoeHx+vIUOG+PpkZ2crIiJChw4dcm4yzczt27e1bt06TZ06VS6Xi/UdBEOHDtXu3bt15swZSdLJkyd14MABjR49WhLrO5Dq6+vV0NCg1q1b+52PjY3VgQMHqHWQBaq+xcXFevTRRxUdHe3rM3LkSJWUlOjKlSsOzQahRAZzDhksdMhgwUX+chYZLHTIX00fm4QtQGZmpj766CMVFRVp1apVKi8v1/Dhw1VbW6vKykpFR0crPj7e7zmJiYmqrKyUJFVWVvr98r7TfqcN/s6dO6dVq1apV69e2rlzp15++WW98sor+vjjjyX9VbO71fTvNU9ISPBrb9Wqle677z5q/h9s27ZNNTU1mjx5siSxvoPgjTfe0PPPP6++ffsqKipKGRkZysvLU25uriTWdyC1a9dOWVlZWrJkiX777Tc1NDRo3bp1Ki4uVkVFBbUOskDVl9eY8EYGcxYZLHTIYMFF/nIWGSx0yF9NX6tQDwD37s47TJL0wAMPKDMzU926ddOmTZsUGxsbwpG1TF6vV0OGDNHSpUslSRkZGTp9+rTee+89TZo0KcSja9k+/PBDjR49WsnJyaEeSou1adMmrV+/Xhs2bFD//v114sQJ5eXlKTk5mfUdBJ988ommTp2qlJQURUZGavDgwcrJydGxY8dCPTQA/wAZzFlksNAhgwUX+ct5ZDDg7vgkYQsUHx+v3r17q6ysTB6PR7dv31ZNTY1fn8uXL8vj8UiSPB5Po28iu/P4Th/8JSkpSf369fM7d//99/v+vOhOze5W07/XvKqqyq+9vr5e1dXV1PzfOH/+vL7++mu99NJLvnOs78CbO3eu793sgQMHauLEiXr11Vf11ltvSWJ9B1qPHj20b98+Xbt2TRcvXtThw4dVV1en7t27U+sgC1R9eY3B35HBgosMFhpksOAjfzmPDBYa5K+mj03CFujatWs6e/askpKS9NBDDykqKkq7d+/2tZeUlOjChQvKysqSJGVlZemHH37w+0HctWuX4uLiGgUxSI888ohKSkr8zp05c0bdunWTJKWnp8vj8fjV/OrVqzp06JBfzWtqavzeqdqzZ4+8Xq8yMzMdmEXzs3btWiUkJGjMmDG+c6zvwLt+/boiIvx/NURGRsrr9UpifQdL27ZtlZSUpCtXrmjnzp0aN24ctQ6yQNU3KytL+/fvV11dna/Prl271KdPH3Xo0MGh2aCpIIMFFxksNMhgwUf+Ch0ymLPIX81AqL85Bfdu9uzZ9s0331h5ebl99913lp2dbZ06dbKqqiozM5s+fbqlpqbanj177OjRo5aVlWVZWVm+59fX19uAAQPs8ccftxMnTlhRUZF17tzZ5s2bF6opNWmHDx+2Vq1aWUFBgZWWltr69eutTZs2tm7dOl+fZcuWWXx8vH3++ed26tQpGzdu3F2/1j0jI8MOHTpkBw4csF69evl9rTv+0tDQYKmpqZafn9+ojfUdWJMmTbKUlBQrLCy08vJy27Jli3Xq1Mlef/11Xx/Wd+AUFRXZjh077Ny5c/bVV1/ZoEGDLDMz027fvm1m1Ppe1dbW2vHjx+348eMmyd555x07fvy4nT9/3swCU9+amhpLTEy0iRMn2unTp+3TTz+1Nm3a2OrVqx2fL5xHBnMWGcx5ZDBnkL+cRwYLHvJX88YmYQswYcIES0pKsujoaEtJSbEJEyZYWVmZr/3GjRs2Y8YM69Chg7Vp08aeeuopq6io8LvGL7/8YqNHj7bY2Fjr1KmTzZ492+rq6pyeSrPx5Zdf2oABAywmJsb69u1r77//vl+71+u1BQsWWGJiosXExNhjjz1mJSUlfn3++OMPy8nJMbfbbXFxcTZlyhSrra11chrNxs6dO01Soxqasb4D7erVqzZr1ixLTU211q1bW/fu3W3+/Pl269YtXx/Wd+B89tln1r17d4uOjjaPx2MzZ860mpoaXzu1vjd79+41SY2OSZMmmVng6nvy5EkbNmyYxcTEWEpKii1btsypKSLEyGDOI4M5iwzmDPKX88hgwUP+at5cZmah+AQjAAAAAAAAgKaB/0kIAAAAAAAAhDk2CQEAAAAAAIAwxyYhAAAAAAAAEObYJAQAAAAAAADCHJuEAAAAAAAAQJhjkxAAAAAAAAAIc2wSAgAAAAAAAGGOTUIAAAAAAAAgzLFJCADNmMvlksvlUnx8vGP3XLx4se++K1ascOy+AAAATQUZDEBLxCYhAITI5MmTfUHv70dZWdl/dZ21a9fqzJkz9zyetLQ0uVwuHTx40O98Xl6e/vWvf/kez5kzRxUVFerSpcs93xMAAMBpZDAAuDs2CQEghEaNGqWKigq/Iz09/b+6Rnx8vBISEgIyntatWys/P/8/9nG73fJ4PIqMjAzIPQEAAJxGBgOAxtgkBIAQiomJkcfj8TvuNfgtXrxYDz74oNasWaPU1FS53W7NmDFDDQ0NWr58uTwejxISElRQUNDoudOmTdPBgwe1ffv2exoDAABAU0YGA4DGWoV6AACAwDt79qx27NihoqIinT17Vs8++6zOnTun3r17a9++ffr+++81depUZWdnKzMz0/e89PR0TZ8+XfPmzdOoUaMUEcF7SQAAAP8UGQxAc8YrDwCEUGFhodxut+8YP358QK7r9Xq1Zs0a9evXT2PHjtWIESNUUlKiFStWqE+fPpoyZYr69OmjvXv3Nnrum2++qfLycq1fvz4gYwEAAGhqyGAA0BifJASAEBoxYoRWrVrle9y2bduAXDctLU3t2rXzPU5MTFRkZKTfu9KJiYmqqqpq9NzOnTtrzpw5WrhwoSZMmBCQ8QAAADQlZDAAaIxPEgJACLVt21Y9e/b0HUlJSQG5blRUlN9jl8t113Ner/euz3/ttdd048YNrVy5MiDjAQAAaErIYADQGJuEAIBG3G63FixYoIKCAtXW1oZ6OAAAAGGBDAYglNgkBADc1bRp09S+fXtt2LAh1EMBAAAIG2QwAKHCJiEA4K6ioqK0ZMkS3bx5M9RDAQAACBtkMACh4jIzC/UgAAD/Py6XS1u3btWTTz7p+L3T0tKUl5envLw8x+8NAAAQSmQwAC0RnyQEgGYuJydHXbp0cex+S5culdvt1oULFxy7JwAAQFNDBgPQ0vBJQgBoxsrKyiRJkZGRSk9Pd+Se1dXVqq6uliR17txZ7du3d+S+AAAATQUZDEBLxCYhAAAAAAAAEOb4c2MAAAAAAAAgzLFJCAAAAAAAAIQ5NgkBAAAAAACAMMcmIQAAAAAAABDm2CQEAAAAAAAAwhybhAAAAAAAAECYY5MQAAAAAAAACHNsEgIAAAAAAABhjk1CAAAAAAAAIMz9DxWOTAcceTj0AAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 1300x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Grafico ringraziate Cloude per l'idea super compatta di questo codice\n",
    "# WARNING: non intuitivo, ma molto molto figo\n",
    "fig, axes = plt.subplots(1, 2, figsize=(13, 5), sharey=True)\n",
    "\n",
    "for ax, (r_col, ur_col, f_col, uf_col, df_plot, titolo) in zip(axes, [\n",
    "  (\"r\",  \"ur\",  \"F\", \"uF\", dfCalibro, \"Fit completo (tutti i punti)\"),\n",
    "  (\"r\", \"ur\", \"F\", \"uF\",   dfCalibro_senza1,  \"Fit senza punto 1\"),\n",
    "]):\n",
    "  ax.errorbar(\n",
    "    df_plot[f_col], df_plot[r_col],\n",
    "    xerr=df_plot[uf_col], yerr=df_plot[ur_col],\n",
    "    fmt='o', color=sns.color_palette()[0],\n",
    "    ecolor='gray', elinewidth=1, capsize=3,\n",
    "    markersize=5, label=\"Residui\"\n",
    "  )\n",
    "  ax.axhline(0, color='red', linestyle='--', linewidth=1)\n",
    "  sns.despine(ax=ax)\n",
    "  ax.set_xlabel(\"F  [mN]\")\n",
    "  ax.set_title(titolo)\n",
    "  ax.grid(True, linestyle=':', linewidth=0.5, alpha=0.7)\n",
    "\n",
    "axes[0].set_ylabel(r\"Residuo $x_i - \\left(\\frac{y_i}{A} - \\frac{B}{A}\\right)$  [mm]\")\n",
    "fig.suptitle(\"Confronto residui — Molla 1 (calibro)\", y=1.02)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "8f79348f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Fit senza un dato\n",
    "SCALA = 10\n",
    "fig, ax = plt.subplots(figsize=(8, 5))\n",
    "\n",
    "x_data = -dfCalibro_senza1[\"dx\"]\n",
    "y_data =  dfCalibro_senza1[\"F\"]\n",
    "\n",
    "x_fit = np.linspace(x_data.min(), x_data.max(), 300)\n",
    "y_fit = AC2 * x_fit + BC2\n",
    "\n",
    "ax.errorbar(\n",
    "    x_data, y_data,\n",
    "    xerr=SCALA * dfCalibro_senza1[\"udx\"], yerr=SCALA * dfCalibro_senza1[\"uF\"],\n",
    "    fmt='o', color=sns.color_palette()[0],\n",
    "    ecolor='gray', elinewidth=1, capsize=3,\n",
    "    markersize=5, label=f\"Dati (barre errore x{SCALA})\"\n",
    ")\n",
    "ax.plot(\n",
    "    x_fit, y_fit,\n",
    "    color='red', linewidth=1.5,\n",
    "    label=f\"Fit: $A={AC2:.3f}\\\\pm{uAC2:.3f}$\\n\"\n",
    "          f\"     $B={BC2:.2f}\\\\pm{uBC2:.2f}$\\n\"\n",
    ")\n",
    "\n",
    "sns.despine(ax=ax)\n",
    "ax.set_xlabel(r\"$- x$  [mm]\")\n",
    "ax.set_ylabel(\"F  [mN]\")\n",
    "ax.set_title(\"Fit lineare — Molla 1 (calibro tolto dato 1)\")\n",
    "ax.legend(fontsize=9)\n",
    "ax.grid(True, linestyle=':', linewidth=0.5, alpha=0.7)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b952c206",
   "metadata": {},
   "source": [
    "# Analisi dati sonar"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8e347644",
   "metadata": {},
   "source": [
    "## Import dei dati sonar (semidispersioni)\n",
    "- masse, $\\omega$, c trattati come prima"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "d6195b96",
   "metadata": {},
   "outputs": [],
   "source": [
    "dfSonar = pd.read_csv(r'molla2Sonar.csv')\n",
    "\n",
    "ERR_OMEGA = 0.000001\n",
    "ERR_C = 0.000001\n",
    "ERR_CRONOMETRO = 0.01\n",
    "\n",
    "# Bilancia trattata esattamente come prima\n",
    "dfSonar = calcola_stats(dfSonar, \"m\",  ERR_BILANCIA)\n",
    "dfSonar = calcola_stats(dfSonar, \"w\",  ERR_OMEGA)\n",
    "dfSonar = calcola_stats(dfSonar, \"c\",  ERR_C)\n",
    "dfSonar = calcola_stats(dfSonar, \"t\",  ERR_CRONOMETRO)\n",
    "\n",
    "# Aggiunta delle forze\n",
    "dfSonar[\"F\"]  = F_fn(dfSonar[\"m\"],  G)\n",
    "dfSonar[\"uF\"] = uF_fn(dfSonar[\"m\"], dfSonar[\"um\"], G, uG)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "02e2d183",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "f3c0753abf4145cf8e63b1c692bcf464",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Sheet(cells=(Cell(column_end=0, column_start=0, row_end=4, row_start=0, squeeze_row=False, type='numeric', val…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sheet = ipysheet.from_dataframe(dfSonar)\n",
    "\n",
    "display(sheet)\n",
    "# dfSonar.head(4).to_json(orient=\"records\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4e12f76c",
   "metadata": {},
   "source": [
    "## Regressione lineare Carpi dati del sonar Caso statico\n",
    "chi² Come persone normali"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "06f9ccef",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ax + B : \n",
      "AS      = 3.2192 ± 0.0027\n",
      "BS      = 2042.5203 ± 1.0326\n",
      "cov_ABS = 0.002760\n",
      "chi²    = 9.0319\n",
      "P(chi², ∞)= 0.0289\n"
     ]
    }
   ],
   "source": [
    "AS, BS, uAS, uBS, covABS, chiS, PS = reg_lin(-dfSonar[\"c\"], dfSonar[\"F\"], dfSonar[\"uc\"], dfSonar[\"uF\"])\n",
    "print(\"Ax + B : \")\n",
    "print(f\"AS      = {AS:.4f} ± {uAS:.4f}\")\n",
    "print(f\"BS      = {BS:.4f} ± {uBS:.4f}\")\n",
    "print(f\"cov_ABS = {covABS:.6f}\")\n",
    "print(f\"chi²    = {chiS:.4f}\")\n",
    "print(f\"P(chi², ∞)= {PS:.4f}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "09445aac",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calcolo numerico residui sul dfSonar\n",
    "dfSonar[\"r\"] = r_fn(\n",
    "  -dfSonar[\"c\"],\n",
    "  dfSonar[\"F\"],\n",
    "  AS,\n",
    "  BS\n",
    ")\n",
    "\n",
    "dfSonar[\"ur\"] = sigma_r_fn(\n",
    "  -dfSonar[\"c\"], dfSonar[\"F\"],\n",
    "  AS, BS,\n",
    "  dfSonar[\"uc\"], dfSonar[\"uF\"],\n",
    "  uAS, uBS, covABS\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f6641e08",
   "metadata": {},
   "source": [
    "### Grafici sonar valori statici"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "75653d7a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Fit\n",
    "SCALA = 10\n",
    "fig, ax = plt.subplots(figsize=(8, 5))\n",
    "\n",
    "x_data = -dfSonar[\"c\"]\n",
    "y_data =  dfSonar[\"F\"]\n",
    "\n",
    "x_fit = np.linspace(x_data.min(), x_data.max(), 300)\n",
    "y_fit = AS * x_fit + BS\n",
    "\n",
    "ax.errorbar(\n",
    "    x_data, y_data,\n",
    "    xerr=SCALA * dfSonar[\"uc\"], yerr=SCALA * dfSonar[\"uF\"],\n",
    "    fmt='o', color=sns.color_palette()[0],\n",
    "    ecolor='gray', elinewidth=1, capsize=3,\n",
    "    markersize=5, label=f\"Dati (barre errore x{SCALA})\"\n",
    ")\n",
    "ax.plot(\n",
    "    x_fit, y_fit,\n",
    "    color='red', linewidth=1.5,\n",
    "    label=f\"Fit: $A={AS:.3f}\\\\pm{uAS:.3f}$\\n\"\n",
    "          f\"     $B={BS:.2f}\\\\pm{uBS:.2f}$\\n\"\n",
    ")\n",
    "\n",
    "sns.despine(ax=ax)\n",
    "ax.set_xlabel(r\"$- x$  [mm]\")\n",
    "ax.set_ylabel(\"F  [mN]\")\n",
    "ax.set_title(\"Fit lineare — Molla 1 (sonar)\")\n",
    "ax.legend(fontsize=9)\n",
    "ax.grid(True, linestyle=':', linewidth=0.5, alpha=0.7)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "1ecf9ab2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Grafico Residui\n",
    "fig, ax = plt.subplots(figsize=(8, 5))\n",
    "\n",
    "# Residui con barre d'errore\n",
    "ax.errorbar(\n",
    "    dfSonar[\"F\"], dfSonar[\"r\"],\n",
    "    xerr=dfSonar[\"uF\"], yerr=dfSonar[\"ur\"],\n",
    "    fmt='o', color=sns.color_palette()[0],\n",
    "    ecolor='gray', elinewidth=1, capsize=3,\n",
    "    markersize=5, label=\"Residui\"\n",
    ")\n",
    "\n",
    "# Linea dello zero\n",
    "ax.axhline(0, color='red', linestyle='--', linewidth=1)\n",
    "\n",
    "# Estetica\n",
    "sns.despine(ax=ax)\n",
    "ax.set_xlabel(\"F  [mN]\")\n",
    "ax.set_ylabel(r\"Residuo $x_i - \\left(\\frac{y_i}{A} - \\frac{B}{A}\\right)$  [mm]\")\n",
    "ax.set_title(\"Residui della regressione — Molla 2 (sonar statico)\")\n",
    "ax.legend()\n",
    "ax.grid(True, linestyle=':', linewidth=0.5, alpha=0.7)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4eebafaf",
   "metadata": {},
   "source": [
    "### Sezione non espressamente richiesta\n",
    "La velocità del suono è chiaramente un fattore moltiplicativo che viene ignorato.\n",
    "\n",
    "Formula di Cramer 1993"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "4088453c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "c = 0.049862877088008*c_raw*v0/sqrt(T + 273.15)\n",
      "sigma_c = v0*sqrt(0.000621576627873448*c_raw**2*sigma_T**2 + 0.00248630651149379*sigma_c_raw**2*(T + 273.15)**2)/(T + 273.15)**(3/2)\n",
      "\n",
      "Formula LaTeX:\n",
      "c = \\frac{0.049862877088008 c_{raw} v_{0}}{\\sqrt{T + 273.15}}\n",
      "sigma_c = \\frac{v_{0} \\sqrt{0.000621576627873448 c_{raw}^{2} \\sigma_{T}^{2} + 0.00248630651149379 \\sigma_{c raw}^{2} \\left(T + 273.15\\right)^{2}}}{\\left(T + 273.15\\right)^{\\frac{3}{2}}}\n"
     ]
    }
   ],
   "source": [
    "# propagazione dell'errore con la temperatura\n",
    "# simboli\n",
    "v0, T, c_raw = sp.symbols('v0 T c_raw', positive=True)\n",
    "sigma_T, sigma_c_raw = sp.symbols('sigma_T sigma_c_raw', positive=True)\n",
    "\n",
    "# velocità corretta e posizione\n",
    "# v = 331.3 * sp.sqrt(1 + T / 273.15)\n",
    "v = 20.055 * sp.sqrt(T + 273.15)\n",
    "c = c_raw * v0 / v\n",
    "\n",
    "# derivate parziali\n",
    "dc_dcraw = sp.diff(c, c_raw)\n",
    "dc_dT    = sp.diff(c, T)\n",
    "\n",
    "sigma_c = sp.sqrt((dc_dcraw * sigma_c_raw)**2 + (dc_dT * sigma_T)**2)\n",
    "\n",
    "print(\"c =\", c)\n",
    "print(\"sigma_c =\", sigma_c.simplify())\n",
    "print(\"\\nFormula LaTeX:\")\n",
    "print(f\"c = {sp.latex(c)}\")\n",
    "print(f\"sigma_c = {sp.latex(sigma_c.simplify())}\")\n",
    "\n",
    "# funzioni numeriche\n",
    "c_fn  = sp.lambdify((c_raw, T, v0), c, 'numpy')\n",
    "uc_fn = sp.lambdify((c_raw, sigma_c_raw, T, sigma_T, v0), sigma_c, 'numpy')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "1584a5d4",
   "metadata": {},
   "outputs": [],
   "source": [
    "Temperatura = (23.6+21.2) / 2\n",
    "Temperatura1 = 21.2\n",
    "Temperatura2 = 23.6\n",
    "uTemperatura = (23.6-21.2) / np.sqrt(12)\n",
    "Velocita_impostata = 343.0\n",
    "\n",
    "dfSonarCorrezione = dfSonar.copy()\n",
    "\n",
    "dfSonarCorrezione['c']  =  c_fn(dfSonarCorrezione['c'], Temperatura, Velocita_impostata)\n",
    "dfSonarCorrezione['uc'] = uc_fn(dfSonarCorrezione['c'], dfSonarCorrezione['uc'],\n",
    "                      Temperatura, uTemperatura,\n",
    "                      Velocita_impostata)\n",
    "dfSonarCorrezione['cA']  =  c_fn(dfSonarCorrezione['c'], Temperatura1, Velocita_impostata)\n",
    "dfSonarCorrezione['cB']  =  c_fn(dfSonarCorrezione['c'], Temperatura2, Velocita_impostata)\n",
    "dfSonarCorrezione['vecchioC'] = dfSonar['c']\n",
    "dfSonarCorrezione['vecchioUc'] = dfSonar['uc']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "ac4860fa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "8215c947eed74d85be6c835c01f9e689",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Sheet(cells=(Cell(column_end=0, column_start=0, row_end=4, row_start=0, squeeze_row=False, type='numeric', val…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sheet = ipysheet.from_dataframe(dfSonarCorrezione)\n",
    "\n",
    "display(sheet)\n",
    "# dfSonar.head(4).to_json(orient=\"records\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "8917049c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fit completo:   chi²=9.03,  P=0.0289\n",
      "Temperatura :  chi²=0.952,  P=0.8129\n",
      "\n",
      "A:  3.2192 ± 0.0027  to  3.2390 ± 0.0076\n",
      "B:  2042.5203 ± 1.0326  to  2043.7514 ± 2.5703\n"
     ]
    }
   ],
   "source": [
    "AS2, BS2, uAS2, uBS2, covABS2, chiS2, PS2 = reg_lin(-dfSonarCorrezione[\"c\"], dfSonarCorrezione[\"F\"], dfSonarCorrezione[\"uc\"], dfSonarCorrezione[\"uF\"])\n",
    "\n",
    "\n",
    "print(f\"Fit completo:   chi²={chiS:.2f},  P={PS:.4f}\")\n",
    "print(f\"Temperatura :  chi²={chiS2:.3f},  P={PS2:.4f}\")\n",
    "print()\n",
    "print(f\"A:  {AS:.4f} ± {uAS:.4f}  to  {AS2:.4f} ± {uAS2:.4f}\")\n",
    "print(f\"B:  {BS:.4f} ± {uBS:.4f}  to  {BS2:.4f} ± {uBS2:.4f}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "e35a9456",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calcolo numerico residui sul dfSonar\n",
    "dfSonarCorrezione[\"r\"] = r_fn(\n",
    "  -dfSonarCorrezione[\"c\"],\n",
    "  dfSonarCorrezione[\"F\"],\n",
    "  AS2,\n",
    "  BS2\n",
    ")\n",
    "\n",
    "dfSonarCorrezione[\"ur\"] = sigma_r_fn(\n",
    "  -dfSonarCorrezione[\"c\"], dfSonarCorrezione[\"F\"],\n",
    "  AS2, BS2,\n",
    "  dfSonarCorrezione[\"uc\"], dfSonarCorrezione[\"uF\"],\n",
    "  uAS2, uBS2, covABS2\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "d5646b8c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Fit\n",
    "SCALA = 10\n",
    "fig, ax = plt.subplots(figsize=(8, 5))\n",
    "\n",
    "x_data = -dfSonarCorrezione[\"c\"]\n",
    "y_data =  dfSonarCorrezione[\"F\"]\n",
    "\n",
    "x_fit = np.linspace(x_data.min(), x_data.max(), 300)\n",
    "y_fit = AS2 * x_fit + BS2\n",
    "\n",
    "ax.errorbar(\n",
    "    x_data, y_data,\n",
    "    xerr=SCALA * dfSonarCorrezione[\"uc\"], yerr=SCALA * dfSonarCorrezione[\"uF\"],\n",
    "    fmt='o', color=sns.color_palette()[0],\n",
    "    ecolor='gray', elinewidth=1, capsize=3,\n",
    "    markersize=5, label=f\"Dati (barre errore x{SCALA})\"\n",
    ")\n",
    "ax.plot(\n",
    "    x_fit, y_fit,\n",
    "    color='red', linewidth=1.5,\n",
    "    label=f\"Fit: $A={AS2:.3f}\\\\pm{uAS2:.3f}$\\n\"\n",
    "          f\"     $B={BS2:.2f}\\\\pm{uBS2:.2f}$\\n\"\n",
    ")\n",
    "\n",
    "sns.despine(ax=ax)\n",
    "ax.set_xlabel(r\"$- x$  [mm]\")\n",
    "ax.set_ylabel(\"F  [mN]\")\n",
    "ax.set_title(\"Fit lineare — Molla 1 (sonar Correzione della temperatura)\")\n",
    "ax.legend(fontsize=9)\n",
    "ax.grid(True, linestyle=':', linewidth=0.5, alpha=0.7)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "8de2a48e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Grafico Residui\n",
    "fig, ax = plt.subplots(figsize=(8, 5))\n",
    "\n",
    "# Residui con barre d'errore\n",
    "ax.errorbar(\n",
    "    dfSonarCorrezione[\"F\"], dfSonarCorrezione[\"r\"],\n",
    "    xerr=dfSonarCorrezione[\"uF\"], yerr=dfSonarCorrezione[\"ur\"],\n",
    "    fmt='o', color=sns.color_palette()[0],\n",
    "    ecolor='gray', elinewidth=1, capsize=3,\n",
    "    markersize=5, label=\"Residui\"\n",
    ")\n",
    "\n",
    "# Linea dello zero\n",
    "ax.axhline(0, color='red', linestyle='--', linewidth=1)\n",
    "\n",
    "# Estetica\n",
    "sns.despine(ax=ax)\n",
    "ax.set_xlabel(\"F  [mN]\")\n",
    "ax.set_ylabel(r\"Residuo $x_i - \\left(\\frac{y_i}{A} - \\frac{B}{A}\\right)$  [mm]\")\n",
    "ax.set_title(\"Residui della regressione — Molla 2 (sonar statico corretto)\")\n",
    "ax.legend()\n",
    "ax.grid(True, linestyle=':', linewidth=0.5, alpha=0.7)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c9c20bd0",
   "metadata": {},
   "source": [
    "## Analisi dati sonar dinamica\n",
    "Ancora non abbiamo il parametro $\\alpha$, quindi useremo $\\alpha = \\frac 1 3$. Lo imposto nel csv così è più facile da cambiare con il metodo della molla"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "af6143df",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Massa molla = 29.8933 ± 0.0044\n"
     ]
    }
   ],
   "source": [
    "# Calcolo della massa della molla per bene\n",
    "dfMasse = pd.DataFrame([[29.90, 29.89, 29.89]], columns=[\"m1\", \"m2\", \"m3\"])\n",
    "dfMasse = calcola_stats(dfMasse, \"m\",  ERR_BILANCIA)\n",
    "\n",
    "massaMolla  = dfMasse.m[0]\n",
    "umassaMolla = dfMasse.um[0]\n",
    "print(f\"Massa molla = {massaMolla:.4f} ± {umassaMolla:.4f}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "a1e69bd3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Meq = 1000/(alp*m_molla + m_osc)\n",
      "sigma_Meq = 1000*sqrt(alp**2*sigma_m_molla**2 + m_molla**2*sigma_alp**2 + sigma_m_osc**2)/(alp*m_molla + m_osc)**2\n",
      "\n",
      "Formula LaTeX:\n",
      "Meq = \\frac{1000}{alp m_{molla} + m_{osc}}\n",
      "sigma_Meq = \\frac{1000 \\sqrt{alp^{2} \\sigma_{m molla}^{2} + m_{molla}^{2} \\sigma_{alp}^{2} + \\sigma_{m osc}^{2}}}{\\left(alp m_{molla} + m_{osc}\\right)^{2}}\n"
     ]
    }
   ],
   "source": [
    "#massa della molla equivalente\n",
    "# simboli\n",
    "m_osc, alp, m_molla = sp.symbols('m_osc alp m_molla', positive=True)\n",
    "sigma_m_osc, sigma_alp, sigma_m_molla = sp.symbols('sigma_m_osc sigma_alp sigma_m_molla', positive=True)\n",
    "\n",
    "# massa equivalente\n",
    "Meq = 1 / (m_osc + alp * m_molla) * 1000\n",
    "\n",
    "# derivate parziali\n",
    "dMeq_dm_osc   = sp.diff(Meq, m_osc)\n",
    "dMeq_dalp     = sp.diff(Meq, alp)\n",
    "dMeq_dm_molla = sp.diff(Meq, m_molla)\n",
    "\n",
    "sigma_Meq = sp.sqrt(\n",
    "    (dMeq_dm_osc   * sigma_m_osc  )**2 +\n",
    "    (dMeq_dalp     * sigma_alp    )**2 +\n",
    "    (dMeq_dm_molla * sigma_m_molla)**2\n",
    ")\n",
    "\n",
    "print(\"Meq =\", Meq)\n",
    "print(\"sigma_Meq =\", sigma_Meq.simplify())\n",
    "print(\"\\nFormula LaTeX:\")\n",
    "print(f\"Meq = {sp.latex(Meq)}\")\n",
    "print(f\"sigma_Meq = {sp.latex(sigma_Meq.simplify())}\")\n",
    "\n",
    "# funzioni numeriche\n",
    "Meq_fn  = sp.lambdify((m_osc, alp, m_molla), Meq, 'numpy')\n",
    "uMeq_fn = sp.lambdify((m_osc, sigma_m_osc, alp, sigma_alp, m_molla, sigma_m_molla), sigma_Meq, 'numpy')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "56679fc4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "w2 = w**2\n",
      "sigma_w2 = 2*sigma_w*w\n",
      "\n",
      "Formula LaTeX:\n",
      "w2 = w^{2}\n",
      "sigma_w2 = 2 \\sigma_{w} w\n"
     ]
    }
   ],
   "source": [
    "# w in w^2\n",
    "# simboli\n",
    "w = sp.symbols('w', positive=True)\n",
    "sigma_w = sp.symbols('sigma_w', positive=True)\n",
    "\n",
    "# omega^2\n",
    "w2 = w**2\n",
    "\n",
    "# derivata parziale\n",
    "dw2_dw = sp.diff(w2, w)\n",
    "\n",
    "sigma_w2 = sp.sqrt((dw2_dw * sigma_w)**2)\n",
    "\n",
    "print(\"w2 =\", w2)\n",
    "print(\"sigma_w2 =\", sigma_w2.simplify())\n",
    "print(\"\\nFormula LaTeX:\")\n",
    "print(f\"w2 = {sp.latex(w2)}\")\n",
    "print(f\"sigma_w2 = {sp.latex(sigma_w2.simplify())}\")\n",
    "\n",
    "# funzioni numeriche\n",
    "w2_fn  = sp.lambdify((w), w2, 'numpy')\n",
    "uw2_fn = sp.lambdify((w, sigma_w), sigma_w2, 'numpy')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "455271a9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "a17da393c1ea463caee2c3891f98037a",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Sheet(cells=(Cell(column_end=0, column_start=0, row_end=4, row_start=0, squeeze_row=False, type='numeric', val…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dfSonar['Meq'] = Meq_fn(dfSonar['m'], dfSonar['alp'], massaMolla)\n",
    "dfSonar['uMeq']= uMeq_fn(dfSonar['m'], dfSonar['um'], dfSonar['alp'], dfSonar['ualp'], massaMolla, umassaMolla)\n",
    "\n",
    "dfSonar['Omega2'] = w2_fn(dfSonar['w'])\n",
    "dfSonar['uOmega2']= uw2_fn(dfSonar['w'], dfSonar['uw'])\n",
    "\n",
    "\n",
    "sheet = ipysheet.from_dataframe(dfSonar)\n",
    "display(sheet)\n",
    "# dfSonar.head(4).to_json(orient=\"records\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5dda09cd",
   "metadata": {},
   "source": [
    "## Regressione lineare Carpi dati del sonar Caso Dinamico"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "02119d66",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ax + B : \n",
      "AD      = 3.5059 ± 0.0010\n",
      "BD      = -1.1685 ± 0.0099\n",
      "cov_ABD = -0.000009\n",
      "chi²    = 3294.6334\n",
      "P(chi², ∞)= 0.0000\n"
     ]
    }
   ],
   "source": [
    "AD, BD, uAD, uBD, covABD, chiD, PD = reg_lin( dfSonar[\"Meq\"], dfSonar[\"Omega2\"], dfSonar[\"uMeq\"], dfSonar[\"uOmega2\"])\n",
    "\n",
    "print(\"Ax + B : \")\n",
    "print(f\"AD      = {AD:.4f} ± {uAD:.4f}\")\n",
    "print(f\"BD      = {BD:.4f} ± {uBD:.4f}\")\n",
    "print(f\"cov_ABD = {covABD:.6f}\")\n",
    "print(f\"chi²    = {chiD:.4f}\")\n",
    "print(f\"P(chi², ∞)= {PD:.4f}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "96f12fe6",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calcolo numerico residui sul dfSonar caso dinamico\n",
    "dfSonar[\"R\"] = r_fn(\n",
    "  dfSonar[\"Meq\"],\n",
    "  dfSonar[\"Omega2\"],\n",
    "  AD,\n",
    "  BD\n",
    ")\n",
    "\n",
    "dfSonar[\"uR\"] = sigma_r_fn(\n",
    "  dfSonar[\"Meq\"], dfSonar[\"Omega2\"],\n",
    "  AD, BD,\n",
    "  dfSonar[\"uMeq\"], dfSonar[\"uOmega2\"],\n",
    "  uAD, uBD, covABD\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "de571f32",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Fit\n",
    "SCALA = 10\n",
    "fig, ax = plt.subplots(figsize=(8, 5))\n",
    "\n",
    "x_data =  dfSonar[\"Meq\"]\n",
    "y_data =  dfSonar[\"Omega2\"]\n",
    "\n",
    "x_fit = np.linspace(0, x_data.max(), 300)\n",
    "y_fit = AD * x_fit + BD\n",
    "\n",
    "ax.errorbar(\n",
    "    x_data, y_data,\n",
    "    xerr=SCALA * dfSonar[\"uMeq\"], yerr=SCALA * dfSonar[\"uOmega2\"],\n",
    "    fmt='o', color=sns.color_palette()[0],\n",
    "    ecolor='gray', elinewidth=1, capsize=3,\n",
    "    markersize=5, label=f\"Dati (barre errore x{SCALA})\"\n",
    ")\n",
    "ax.plot(\n",
    "    x_fit, y_fit,\n",
    "    color='red', linewidth=1.5,\n",
    "    label=f\"Fit: $A={AD:.3f}\\\\pm{uAD:.3f}$\\n\"\n",
    "          f\"     $B={BD:.2f}\\\\pm{uBD:.2f}$\\n\"\n",
    ")\n",
    "\n",
    "\n",
    "plt.xlim(left=0)\n",
    "plt.ylim(bottom=0)\n",
    "\n",
    "sns.despine(ax=ax)\n",
    "ax.set_xlabel(r\"Meq  [Kg$^{-1}$]\")\n",
    "ax.set_ylabel(r\"$\\omega^2$  [s$^{-2}$]\")\n",
    "ax.set_title(\"Fit lineare — Molla 1 (sonar Dinamico)\")\n",
    "ax.legend(fontsize=9)\n",
    "ax.grid(True, linestyle=':', linewidth=0.5, alpha=0.7)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "c87033e0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Grafico Residui\n",
    "fig, ax = plt.subplots(figsize=(8, 5))\n",
    "\n",
    "# Residui con barre d'errore\n",
    "ax.errorbar(\n",
    "    dfSonar[\"Omega2\"], dfSonar[\"R\"],\n",
    "    xerr=dfSonar[\"uOmega2\"], yerr=dfSonar[\"uR\"],\n",
    "    fmt='o', color=sns.color_palette()[0],\n",
    "    ecolor='gray', elinewidth=1, capsize=3,\n",
    "    markersize=5, label=\"Residui\"\n",
    ")\n",
    "\n",
    "# Linea dello zero\n",
    "ax.axhline(0, color='red', linestyle='--', linewidth=1)\n",
    "\n",
    "# Estetica\n",
    "sns.despine(ax=ax)\n",
    "ax.set_xlabel(r\"$\\omega^2$  [s$^{-2}$]\")\n",
    "ax.set_ylabel(r\"Residuo $x_i - \\left(\\frac{y_i}{A} - \\frac{B}{A}\\right)$  [Kg$^{-1}$]\")\n",
    "ax.set_title(\"Residui della regressione — Molla 2 (sonar dinamico)\")\n",
    "ax.legend()\n",
    "ax.grid(True, linestyle=':', linewidth=0.5, alpha=0.7)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d35498c5",
   "metadata": {},
   "source": [
    "# Analisi dati Cronometro"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "97921cfc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "wt = 40*pi/w\n",
      "w2t = 1600*pi**2/w**2\n",
      "sigma_w2t = 3200*pi**2*sigma_t/w**3\n",
      "\n",
      "Formula LaTeX:\n",
      "w2t = \\frac{1600 \\pi^{2}}{w^{2}}\n",
      "sigma_w2t = \\frac{3200 \\pi^{2} \\sigma_{t}}{w^{3}}\n"
     ]
    }
   ],
   "source": [
    "# t/20 to w\n",
    "# simboli\n",
    "t = sp.symbols('w', positive=True)\n",
    "sigma_t = sp.symbols('sigma_t', positive=True)\n",
    "\n",
    "# omega^2\n",
    "wt = (2 * sp.pi) / (t/20)\n",
    "w2t = wt**2\n",
    "\n",
    "# derivata parziale\n",
    "dw2t_dt = sp.diff(w2t, t)\n",
    "\n",
    "sigma_w2t = sp.sqrt((dw2t_dt * sigma_t)**2)\n",
    "\n",
    "print(\"wt =\", wt)\n",
    "print(\"w2t =\", w2t)\n",
    "print(\"sigma_w2t =\", sigma_w2t.simplify())\n",
    "print(\"\\nFormula LaTeX:\")\n",
    "print(f\"w2t = {sp.latex(w2t)}\")\n",
    "print(f\"sigma_w2t = {sp.latex(sigma_w2t.simplify())}\")\n",
    "\n",
    "# funzioni numeriche\n",
    "w2t_fn  = sp.lambdify((t), w2t, 'numpy')\n",
    "uw2t_fn = sp.lambdify((t, sigma_t), sigma_w2t, 'numpy')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "0b3f8a4e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "1cc80fabe1b5423099a66eb4124d84c8",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Sheet(cells=(Cell(column_end=0, column_start=0, row_end=4, row_start=0, squeeze_row=False, type='numeric', val…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dfSonar['Omega2t'] = w2t_fn(dfSonar['t'])\n",
    "dfSonar['uOmega2t']= uw2t_fn(dfSonar['t'], dfSonar['ut'])\n",
    "\n",
    "sheet = ipysheet.from_dataframe(dfSonar)\n",
    "display(sheet)\n",
    "# dfSonar.head(4).to_json(orient=\"records\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "0421b1cb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ax + B : \n",
      "ACr      = 3.8380 ± 0.0526\n",
      "BCr      = -1.0200 ± 0.5757\n",
      "cov_ABCr = -0.029589\n",
      "chi²    = 2.0359\n",
      "P(chi², ∞)= 0.5650\n"
     ]
    }
   ],
   "source": [
    "ACr, BCr, uACr, uBCr, covABCr, chiCr, PCr = reg_lin( dfSonar[\"Meq\"], dfSonar[\"Omega2t\"], dfSonar[\"uMeq\"], dfSonar[\"uOmega2t\"])\n",
    "\n",
    "print(\"Ax + B : \")\n",
    "print(f\"ACr      = {ACr:.4f} ± {uACr:.4f}\")\n",
    "print(f\"BCr      = {BCr:.4f} ± {uBCr:.4f}\")\n",
    "print(f\"cov_ABCr = {covABCr:.6f}\")\n",
    "print(f\"chi²    = {chiCr:.4f}\")\n",
    "print(f\"P(chi², ∞)= {PCr:.4f}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "2fb7140a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calcolo numerico residui sul dfSonar caso dinamico\n",
    "dfSonar[\"Rc\"] = r_fn(\n",
    "  dfSonar[\"Meq\"],\n",
    "  dfSonar[\"Omega2t\"],\n",
    "  ACr,\n",
    "  BCr\n",
    ")\n",
    "\n",
    "dfSonar[\"uRc\"] = sigma_r_fn(\n",
    "  dfSonar[\"Meq\"], dfSonar[\"Omega2t\"],\n",
    "  ACr, BCr,\n",
    "  dfSonar[\"uMeq\"], dfSonar[\"uOmega2t\"],\n",
    "  uACr, uBCr, covABCr\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "739c2c88",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Fit\n",
    "SCALA = 10\n",
    "fig, ax = plt.subplots(figsize=(8, 5))\n",
    "\n",
    "x_data =  dfSonar[\"Meq\"]\n",
    "y_data =  dfSonar[\"Omega2t\"]\n",
    "\n",
    "x_fit = np.linspace(0, x_data.max(), 300)\n",
    "y_fit = ACr * x_fit + BCr\n",
    "\n",
    "ax.errorbar(\n",
    "    x_data, y_data,\n",
    "    xerr=SCALA * dfSonar[\"uMeq\"], yerr=SCALA * dfSonar[\"uOmega2t\"],\n",
    "    fmt='o', color=sns.color_palette()[0],\n",
    "    ecolor='gray', elinewidth=1, capsize=3,\n",
    "    markersize=5, label=f\"Dati (barre errore x{SCALA})\"\n",
    ")\n",
    "ax.plot(\n",
    "    x_fit, y_fit,\n",
    "    color='red', linewidth=1.5,\n",
    "    label=f\"Fit: $A={ACr:.3f}\\\\pm{uACr:.3f}$\\n\"\n",
    "          f\"     $B={BCr:.2f}\\\\pm{uBCr:.2f}$\\n\"\n",
    ")\n",
    "\n",
    "\n",
    "plt.xlim(left=0)\n",
    "plt.ylim(bottom=0)\n",
    "\n",
    "sns.despine(ax=ax)\n",
    "ax.set_xlabel(r\"Meq  [Kg$^{-1}$]\")\n",
    "ax.set_ylabel(r\"$\\omega^2$  [s$^{-2}$]\")\n",
    "ax.set_title(\"Fit lineare — Molla 1 (cronometro)\")\n",
    "ax.legend(fontsize=9)\n",
    "ax.grid(True, linestyle=':', linewidth=0.5, alpha=0.7)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "b44b497b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Grafico Residui\n",
    "fig, ax = plt.subplots(figsize=(8, 5))\n",
    "\n",
    "# Residui con barre d'errore\n",
    "ax.errorbar(\n",
    "    dfSonar[\"Omega2t\"], dfSonar[\"Rc\"],\n",
    "    xerr=dfSonar[\"uOmega2t\"], yerr=dfSonar[\"uRc\"],\n",
    "    fmt='o', color=sns.color_palette()[0],\n",
    "    ecolor='gray', elinewidth=1, capsize=3,\n",
    "    markersize=5, label=\"Residui\"\n",
    ")\n",
    "\n",
    "# Linea dello zero\n",
    "ax.axhline(0, color='red', linestyle='--', linewidth=1)\n",
    "\n",
    "# Estetica\n",
    "sns.despine(ax=ax)\n",
    "ax.set_xlabel(r\"$\\omega^2$  [s$^{-2}$]\")\n",
    "ax.set_ylabel(r\"Residuo $x_i - \\left(\\frac{y_i}{A} - \\frac{B}{A}\\right)$  [Kg$^{-1}$]\")\n",
    "ax.set_title(\"Residui della regressione — Molla 2 (cronometro)\")\n",
    "ax.legend()\n",
    "ax.grid(True, linestyle=':', linewidth=0.5, alpha=0.7)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b5ca1727",
   "metadata": {},
   "source": [
    "# Raccolta finale di tutti i dati"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "e87e24b7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Calibro\n",
      "AC      = 3.2009 ± 0.0034\n",
      "BC      = 1161.4138 ± 0.4687\n",
      "cov_ABC = 0.001385\n",
      "chi²    = 4.3252\n",
      "GdL     = 4\n",
      "P(chi², ∞)= 0.1150\n",
      "[AC-2uAC; AC+2uAC]     = [3.1942; 3.2076]\n",
      "\n",
      "Sonar caso statico corretto\n",
      "AS      = 3.2390 ± 0.0076\n",
      "BS      = 2043.7514 ± 2.5703\n",
      "cov_ABS = 0.018946\n",
      "chi²    = 0.9520\n",
      "GdL     = 5\n",
      "P(chi², ∞)= 0.8129\n",
      "[AS-2uAS; AS+2uAS]     = [3.2238; 3.2542]\n",
      "\n",
      "Sonar caso statico non corretto\n",
      "AS      = 3.2192 ± 0.0027\n",
      "BS      = 2042.5203 ± 1.0326\n",
      "cov_ABS = 0.002760\n",
      "chi²    = 9.0319\n",
      "GdL     = 5\n",
      "P(chi², ∞)= 0.0289\n",
      "[AS-2uAS; AS+2uAS]     = [3.2138; 3.2247]\n",
      "\n",
      "Sonar caso Dinamico\n",
      "AD      = 3.5059 ± 0.0010\n",
      "BD      = -1.1685 ± 0.0099\n",
      "cov_ABD = -0.000009\n",
      "chi²    = 3294.6334\n",
      "GdL     = 5\n",
      "P(chi², ∞)= 0.0000\n",
      "[AD-2uAD; AD+2uAD]     = [3.5040; 3.5079]\n",
      "\n",
      "Cronometro\n",
      "ACr      = 3.8380 ± 0.0526\n",
      "BCr      = -1.0200 ± 0.5757\n",
      "cov_ABCr = -0.029589\n",
      "chi²    = 2.0359\n",
      "P(chi², ∞)= 0.5650\n",
      "[ACr-2uACr; ACr+2uACr] = [3.7328; 3.9432]\n"
     ]
    }
   ],
   "source": [
    "print(\"Calibro\")\n",
    "print(f\"AC      = {AC:.4f} ± {uAC:.4f}\")\n",
    "print(f\"BC      = {BC:.4f} ± {uBC:.4f}\")\n",
    "print(f\"cov_ABC = {covABC:.6f}\")\n",
    "print(f\"chi²    = {chiC:.4f}\")\n",
    "print(f\"GdL     = {len(dfCalibro)}\")\n",
    "print(f\"P(chi², ∞)= {PC:.4f}\")\n",
    "print(f\"[AC-2uAC; AC+2uAC]     = [{AC - 2*uAC:.4f}; {AC + 2*uAC:.4f}]\")\n",
    "\n",
    "print(\"\\nSonar caso statico corretto\")\n",
    "print(f\"AS      = {AS2:.4f} ± {uAS2:.4f}\")\n",
    "print(f\"BS      = {BS2:.4f} ± {uBS2:.4f}\")\n",
    "print(f\"cov_ABS = {covABS2:.6f}\")\n",
    "print(f\"chi²    = {chiS2:.4f}\")\n",
    "print(f\"GdL     = {len(dfSonar)}\")\n",
    "print(f\"P(chi², ∞)= {PS2:.4f}\")\n",
    "print(f\"[AS-2uAS; AS+2uAS]     = [{AS2 - 2*uAS2:.4f}; {AS2 + 2*uAS2:.4f}]\")\n",
    "\n",
    "print(\"\\nSonar caso statico non corretto\")\n",
    "print(f\"AS      = {AS:.4f} ± {uAS:.4f}\")\n",
    "print(f\"BS      = {BS:.4f} ± {uBS:.4f}\")\n",
    "print(f\"cov_ABS = {covABS:.6f}\")\n",
    "print(f\"chi²    = {chiS:.4f}\")\n",
    "print(f\"GdL     = {len(dfSonar)}\")\n",
    "print(f\"P(chi², ∞)= {PS:.4f}\")\n",
    "print(f\"[AS-2uAS; AS+2uAS]     = [{AS - 2*uAS:.4f}; {AS + 2*uAS:.4f}]\")\n",
    "\n",
    "print(\"\\nSonar caso Dinamico\")\n",
    "print(f\"AD      = {AD:.4f} ± {uAD:.4f}\")\n",
    "print(f\"BD      = {BD:.4f} ± {uBD:.4f}\")\n",
    "print(f\"cov_ABD = {covABD:.6f}\")\n",
    "print(f\"chi²    = {chiD:.4f}\")\n",
    "print(f\"GdL     = {len(dfSonar)}\")\n",
    "print(f\"P(chi², ∞)= {PD:.4f}\")\n",
    "print(f\"[AD-2uAD; AD+2uAD]     = [{AD - 2*uAD:.4f}; {AD + 2*uAD:.4f}]\")\n",
    "\n",
    "print(\"\\nCronometro\")\n",
    "print(f\"ACr      = {ACr:.4f} ± {uACr:.4f}\")\n",
    "print(f\"BCr      = {BCr:.4f} ± {uBCr:.4f}\")\n",
    "print(f\"cov_ABCr = {covABCr:.6f}\")\n",
    "print(f\"chi²    = {chiCr:.4f}\")\n",
    "print(f\"P(chi², ∞)= {PCr:.4f}\")\n",
    "print(f\"[ACr-2uACr; ACr+2uACr] = [{ACr - 2*uACr:.4f}; {ACr + 2*uACr:.4f}]\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "0bc96952",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA9oAAAJwCAYAAAB25xl7AAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjgsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvwVt1zgAAAAlwSFlzAAAPYQAAD2EBqD+naQAAbhhJREFUeJzt3Xl8VNX9//H3nZnMZE8IkI0dRPbFImKkCiqCggsVrVoqWK1bQRFcKIoK2IrFDa2K2qrY71dqq19xV0RU/CmIiqIIlAqioBCCINkgy8y9vz8mM2QgAQKTe8n19Xw8psk9986dz0xuMe+cc88xLMuyBAAAAAAA4sLjdAEAAAAAALgJQRsAAAAAgDgiaAMAAAAAEEcEbQAAAAAA4oigDQAAAABAHBG0AQAAAACII4I2AAAAAABxRNAGAAAAACCOCNoAAAAAAMQRQRsAgCPI119/raFDhyojI0OGYejFF190uqRGNW3aNBmGEddzvvfeezIMQ++9915czwsAwMEiaAMAsJf169fryiuvVMeOHZWYmKj09HQNHDhQDzzwgHbv3t2orz127FitXLlSf/7zn/U///M/OvbYYxv19fa2evVqTZs2Td9++62tr3soHnnkEc2dO9fpMgAA2IfP6QIAADiSvPbaazr//PMVCAQ0ZswY9ezZU1VVVfrggw904403atWqVXr88ccb5bV3796tpUuX6pZbbtH48eMb5TUOZPXq1Zo+fboGDx6s9u3bO1LDwXrkkUfUokULXXLJJTHtJ510knbv3i2/3+9MYQCAnz2CNgAANTZs2KALL7xQ7dq10zvvvKO8vLzovnHjxmndunV67bXXGu31t23bJknKzMw84LHl5eVKSUlptFqaMo/Ho8TERKfLAAD8jDF0HACAGrNmzVJZWZmeeOKJmJAdcdRRR2nChAnR7WAwqDvuuEOdOnVSIBBQ+/btdfPNN6uysjLmee3bt9eZZ56pDz74QMcdd5wSExPVsWNH/eMf/4geM23aNLVr106SdOONN8owjGiPcuQ+5tWrV+s3v/mNmjVrpl/+8pdxr2Hu3Lk6//zzJUknn3yyDMPY517nRx55RD169FAgEFB+fr7GjRunnTt3HtTn+8EHH6h///5KTExUp06d9Nhjj9V53FNPPaVTTjlF2dnZCgQC6t69u+bMmbPP+1m1apUWL14crXPw4MGSuEcbAOA8erQBAKjxyiuvqGPHjjrhhBMO6vjf//73evrpp3Xeeefp+uuv17JlyzRz5kytWbNG8+fPjzl23bp1Ou+883TZZZdp7NixevLJJ3XJJZeoX79+6tGjh84991xlZmZq4sSJuuiiizR8+HClpqbGnOP8889X586ddeedd8qyrLjXcNJJJ+naa6/Vgw8+qJtvvlndunWTpOjXadOmafr06RoyZIiuvvpqrV27VnPmzNEnn3yiDz/8UAkJCfV+VitXrtTQoUPVsmVLTZs2TcFgULfffrtycnL2OXbOnDnq0aOHzj77bPl8Pr3yyiv6wx/+INM0NW7cOEnS7Nmzdc011yg1NVW33HKLJNV5LgAAHGEBAACruLjYkmSdc845B3X8ihUrLEnW73//+5j2G264wZJkvfPOO9G2du3aWZKs999/P9pWVFRkBQIB6/rrr4+2bdiwwZJk3X333THnvP322y1J1kUXXdToNTz33HOWJOvdd9+NOWdRUZHl9/utoUOHWqFQKNr+0EMPWZKsJ598st7PyrIsa+TIkVZiYqL13XffRdtWr15teb1ea+9fR3bt2rXP84cNG2Z17Ngxpq1Hjx7WoEGD9jn23XffrfM9AABgF4aOAwAgqaSkRJKUlpZ2UMe//vrrkqRJkybFtF9//fWStM+93N27d9eJJ54Y3W7ZsqW6dOmib7755qBrvOqqqxyr4e2331ZVVZWuu+46eTx7fn24/PLLlZ6evt9710OhkBYsWKCRI0eqbdu20fZu3bpp2LBh+xyflJQU/b64uFg//vijBg0apG+++UbFxcUHrBUAAKcRtAEAkJSeni5JKi0tPajjv/vuO3k8Hh111FEx7bm5ucrMzNR3330X0147YEY0a9ZMP/3000HX2KFDB8dqiJyrS5cuMe1+v18dO3bc57Vq27Ztm3bv3q3OnTvvs2/v80nShx9+qCFDhiglJUWZmZlq2bKlbr75ZkkiaAMAmgTu0QYAQOGgnZ+fr6+++qpBzzMM46CO83q9dbZbNfdaH4zaPb1O1dDY1q9fr1NPPVVdu3bVfffdpzZt2sjv9+v111/X/fffL9M0nS4RAIADokcbAIAaZ555ptavX6+lS5ce8Nh27drJNE19/fXXMe1bt27Vzp07ozOIN6bGqKG+0B4519q1a2Paq6qqtGHDhv2+VsuWLZWUlLRPnXWd75VXXlFlZaVefvllXXnllRo+fLiGDBlS5x8ZDvYPDAAA2I2gDQBAjZtuukkpKSn6/e9/r61bt+6zf/369XrggQckScOHD5cUnv26tvvuu0+SNGLEiMYttpFqiKzNvfeSXUOGDJHf79eDDz4Y0wP+xBNPqLi4eL+v5fV6NWzYML344ovauHFjtH3NmjVasGDBPsdKsb3sxcXFeuqpp+qs9WCXFgMAwE4MHQcAoEanTp00b948XXDBBerWrZvGjBmjnj17qqqqSkuWLNFzzz2nSy65RJLUp08fjR07Vo8//rh27typQYMG6eOPP9bTTz+tkSNH6uSTT270ehujhr59+8rr9eovf/mLiouLFQgEomtaT5kyRdOnT9fpp5+us88+W2vXrtUjjzyi/v3767e//e1+zzt9+nS9+eabOvHEE/WHP/xBwWBQf/3rX9WjRw99+eWX0eOGDh0qv9+vs846S1deeaXKysr0t7/9TdnZ2dqyZUvMOfv166c5c+boT3/6k4466ihlZ2frlFNOafB7BgAg3gjaAADUcvbZZ+vLL7/U3XffrZdeeklz5sxRIBBQ7969de+99+ryyy+PHvv3v/9dHTt21Ny5czV//nzl5uZqypQpuv32222rN9415Obm6tFHH9XMmTN12WWXKRQK6d1331V2dramTZumli1b6qGHHtLEiROVlZWlK664Qnfeeed+19CWpN69e2vBggWaNGmSbrvtNrVu3VrTp0/Xli1bYoJ2ly5d9Pzzz2vq1Km64YYblJubq6uvvlotW7bUpZdeGnPO2267Td99951mzZql0tJSDRo0iKANADgiGNaRNAMKAAAAAABNHPdoAwAAAAAQRwRtAAAAAADiiKANAAAAAEAcEbQBAAAAAIgjgjYAAAAAAHFE0AYAAAAAII6a5Drapmlq8+bNSktLk2EYTpcDAAAAAHA5y7JUWlqq/Px8eTz777NukkF78+bNatOmjdNlAAAAAAB+ZjZt2qTWrVvv95gmGbTT0tIkhd9genq6w9UAAAAAANyupKREbdq0iebR/WmSQTsyXDw9PZ2gDQAAAACwzcHcvsxkaAAAAAAAxBFBGwAAAACAOCJoAwAAAAAQR03yHm0AAAAAPx+WZSkYDCoUCjldClzM6/XK5/PFZQlpgjYAAACAI1ZVVZW2bNmiXbt2OV0KfgaSk5OVl5cnv99/WOchaAMAAAA4IpmmqQ0bNsjr9So/P19+vz8uvY3A3izLUlVVlbZt26YNGzaoc+fO8ngO/U5rgjYAAACAI1JVVZVM01SbNm2UnJzsdDlwuaSkJCUkJOi7775TVVWVEhMTD/lcTIYGAAAA4Ih2OD2LQEPE61rjigUAAAAAII4I2gAAAAAAxBFBGwAAAAAQ45JLLtHIkSOj24MHD9Z1113nWD21GYahF1980eky9ovJ0AAAAAAA+/XCCy8oISHB6TIkSVu2bFGzZs2cLmO/CNoAAAAA8DNQVVV1yOtDZ2VlxbmaQ5ebm+t0CQfE0HEAAAAAiLPnn39evXr1UlJSkpo3b64hQ4aovLxcUnh98BkzZqh169YKBALq27ev3nzzzehzv/32WxmGoRdeeEEnn3yykpOT1adPHy1dujR6zPbt23XRRRepVatWSk5OVq9evfTPf/4zpobBgwdr/Pjxuu6669SiRQsNGzaszlpDoZAmTZqkzMxMNW/eXDfddJMsy9rnXLWHjrdv31533nmnLr30UqWlpalt27Z6/PHHY54zefJkHX300UpOTlbHjh116623qrq6Orp/2rRp6tu3r5588km1bdtWqamp+sMf/qBQKKRZs2YpNzdX2dnZ+vOf/xxz3r2Hjn///fe66KKLlJWVpZSUFB177LFatmxZdP+cOXPUqVMn+f1+denSRf/zP/9T5+cQT/RoAwAAAGhSqqtC2lm4y/bXzcxNVoLfe8DjtmzZoosuukizZs3Sr371K5WWlur//b//Fw2vDzzwgO6991499thjOuaYY/Tkk0/q7LPP1qpVq9S5c+foeW655Rbdc8896ty5s2655RZddNFFWrdunXw+nyoqKtSvXz9NnjxZ6enpeu2113TxxRerU6dOOu6446LnePrpp3X11Vfrww8/rLfee++9V3PnztWTTz6pbt266d5779X8+fN1yimn7Pd93nvvvbrjjjt088036/nnn9fVV1+tQYMGqUuXLpKktLQ0zZ07V/n5+Vq5cqUuv/xypaWl6aabboqeY/369XrjjTf05ptvav369TrvvPP0zTff6Oijj9bixYu1ZMkSXXrppRoyZIgGDBiwTw1lZWUaNGiQWrVqpZdfflm5ubn67LPPZJqmJGn+/PmaMGGCZs+erSFDhujVV1/V7373O7Vu3Vonn3zyAX+Wh8qw9v5TRRNQUlKijIwMFRcXKz093elyAAAAADSCiooKbdiwQR06dFBiYmK0fdvGUv37zk9sr+fXN/dXy7ZpBzzus88+U79+/fTtt9+qXbt2++xv1aqVxo0bp5tvvjnadtxxx6l///56+OGH9e2336pDhw76+9//rssuu0yStHr1avXo0UNr1qxR165d63zdM888U127dtU999wjKdwLXVJSos8++2y/9ebn52vixIm68cYbJUnBYFAdOnRQv379oj3HgwcPVt++fTV79mxJ4R7tE088Mdo7bFmWcnNzNX36dF111VV1vs4999yjZ599Vp9++qmkcI/23XffrcLCQqWlhT/X008/XWvXrtX69euja1p37dpVl1xyif74xz9KCvdoz58/XyNHjtTjjz+uG264Qd9++22dw9sHDhyoHj16xPS2//rXv1Z5eblee+21fY6v75qTGpZD6dEGAAAA0KRk5ibr1zf3d+R1D0afPn106qmnqlevXho2bJiGDh2q8847T82aNVNJSYk2b96sgQMHxjxn4MCB+uKLL2LaevfuHf0+Ly9PklRUVKSuXbsqFArpzjvv1L///W/98MMPqqqqUmVlpZKTY2vs16/ffmstLi7Wli1bYnqLfT6fjj322H2Gj++tdn2GYSg3N1dFRUXRtn/961968MEHtX79epWVlSkYDO4TUNu3bx8N2ZKUk5Mjr9cbDdmRttrnrW3FihU65phj6r2HfM2aNbriiiti2gYOHKgHHnhgv+/tcBG0AQAAADQpCX7vQfUsO8Xr9WrhwoVasmSJ3nrrLf31r3/VLbfcomXLlql58+YHfZ7as3wbhiFJ0SHRd999tx544AHNnj1bvXr1UkpKiq677jpVVVXFnCMlJSUO7+jA9UVqjNS3dOlSjR49WtOnT9ewYcOUkZGhZ599Vvfee+8Bz7G/8+4tKSnpcN9Go2AyNAAAAACIM8MwNHDgQE2fPl2ff/65/H6/5s+fr/T0dOXn5+9zz/SHH36o7t27H/T5P/zwQ51zzjn67W9/qz59+qhjx47673//2+A6MzIylJeXFzN5WDAY1PLlyxt8rtqWLFmidu3a6ZZbbtGxxx6rzp0767vvvjusc9ald+/eWrFihXbs2FHn/m7duh32Z30o6NEGAAAAgDhatmyZFi1apKFDhyo7O1vLli3Ttm3b1K1bN0nSjTfeqNtvv12dOnVS37599dRTT2nFihV65plnDvo1OnfurOeff15LlixRs2bNdN9992nr1q2HFCAnTJigu+66S507d1bXrl113333aefOnQ0+z971bdy4Uc8++6z69++v1157TfPnzz+sc9bloosu0p133qmRI0dq5syZysvL0+eff678/HwVFBToxhtv1K9//Wsdc8wxGjJkiF555RW98MILevvtt+NeS20EbQAAAACIo/T0dL3//vuaPXu2SkpK1K5dO917770644wzJEnXXnutiouLdf3116uoqEjdu3fXyy+/HDPj+IFMnTpV33zzjYYNG6bk5GRdccUVGjlypIqLixtc7/XXX68tW7Zo7Nix8ng8uvTSS/WrX/3qkM4VcfbZZ2vixIkaP368KisrNWLECN16662aNm3aIZ+zLn6/X2+99Zauv/56DR8+XMFgUN27d9fDDz8sSRo5cqQeeOAB3XPPPZowYYI6dOigp556SoMHD45rHXtj1nEAAAAAR6T9zQANNIZ4zTrOPdoOqKoIavO6nU6XAQAAAABoBARtB3z1/g968d7PVPZThdOlAAAAAADijKDtgIqyalmWtKu46sAHAwAAAACaFIK2E2ruijeb3u3xAAAAAIADIGg7IDL/XBOchw4AAAAAcAAEbQdEg3aIoA0AAAAAbkPQdoDP75UkBZJZxhwAAAAA3Iag7QB/Yjhgp2SwFiAAAAAAuA1B2wHB6pCk8HraAAAAAAB3IWg7YHdJtSRp59ZdDlcCAAAAAIi3wwrad911lwzD0HXXXRdtq6io0Lhx49S8eXOlpqZq1KhR2rp1a8zzNm7cqBEjRig5OVnZ2dm68cYbFQz+fHp3I5OhmSaToQEAAABwh/bt22v27NlOl3FEOOSg/cknn+ixxx5T7969Y9onTpyoV155Rc8995wWL16szZs369xzz43uD4VCGjFihKqqqrRkyRI9/fTTmjt3rm677bZDfxdNDMt7AQAAAKiturra6RJsEQqFZJqm02U0ukMK2mVlZRo9erT+9re/qVmzZtH24uJiPfHEE7rvvvt0yimnqF+/fnrqqae0ZMkSffTRR5Kkt956S6tXr9b//u//qm/fvjrjjDN0xx136OGHH1ZVVVV83tURLpKvrZCzdQAAAABoPKZpatasWTrqqKMUCATUtm1b/fnPf9a3334rwzD0r3/9S4MGDVJiYqKeeeYZmaapGTNmqHXr1goEAurbt6/efPPN6Pkiz3vhhRd08sknKzk5WX369NHSpUtjXvf//u//1KNHDwUCAbVv31733ntvzP727dvrT3/6k8aMGaPU1FS1a9dOL7/8srZt26ZzzjlHqamp6t27tz799NOY533wwQc68cQTlZSUpDZt2ujaa69VeXm5JGnw4MH67rvvNHHiRBmGIcMwJElz585VZmamXn75ZXXv3l2BQEAbN27UTz/9pDFjxqhZs2ZKTk7WGWecoa+//roxfgyOOKSgPW7cOI0YMUJDhgyJaV++fLmqq6tj2rt27aq2bdtGf/hLly5Vr169lJOTEz1m2LBhKikp0apVq+p8vcrKSpWUlMQ83MASPdoAAABAQ4VCu1VS+pXtj1Bod4PqnDJliu666y7deuutWr16tebNmxeTg/74xz9qwoQJWrNmjYYNG6YHHnhA9957r+655x59+eWXGjZsmM4+++x9Augtt9yiG264QStWrNDRRx+tiy66KHor7vLly/XrX/9aF154oVauXKlp06bp1ltv1dy5c2POcf/992vgwIH6/PPPNWLECF188cUaM2aMfvvb3+qzzz5Tp06dNGbMmOgo3PXr1+v000/XqFGj9OWXX+pf//qXPvjgA40fP16S9MILL6h169aaMWOGtmzZoi1btkRfa9euXfrLX/6iv//971q1apWys7N1ySWX6NNPP9XLL7+spUuXyrIsDR8+3DU9+w1eyPnZZ5/VZ599pk8++WSffYWFhfL7/crMzIxpz8nJUWFhYfSY2hdXZH9kX11mzpyp6dOnN7TUI1ZSql+SlJmd7HAlAAAAQNNTvmu9PvnkHNtft3//l5Se1vOgji0tLdUDDzyghx56SGPHjpUkderUSb/85S/17bffSpKuu+66mNts77nnHk2ePFkXXnihJOkvf/mL3n33Xc2ePVsPP/xw9LgbbrhBI0aMkCRNnz5dPXr00Lp169S1a1fdd999OvXUU3XrrbdKko4++mitXr1ad999ty655JLoOYYPH64rr7xSknTbbbdpzpw56t+/v84//3xJ0uTJk1VQUKCtW7cqNzdXM2fO1OjRo6Pzc3Xu3FkPPvigBg0apDlz5igrK0ter1dpaWnKzc2N+Syqq6v1yCOPqE+fPpKkr7/+Wi+//LI+/PBDnXDCCZKkZ555Rm3atNGLL74YraEpa1DQ3rRpkyZMmKCFCxcqMdG+NaCnTJmiSZMmRbdLSkrUpk0b214/3pgMDQAAADh0Kcmd1L//S4687sFas2aNKisrdeqpp9Z7zLHHHhv9vqSkRJs3b9bAgQNjjhk4cKC++OKLmLba82Tl5eVJkoqKitS1a1etWbNG55xzzj7nmD17tkKhkLxe7z7niHR89urVa5+2oqIi5ebm6osvvtCXX36pZ555JnqMZVkyTVMbNmxQt27d6n2ffr8/5vXWrFkjn8+nAQMGRNuaN2+uLl26aM2aNfWepylpUNBevny5ioqK9Itf/CLaFgqF9P777+uhhx7SggULVFVVpZ07d8b0akf+CiJJubm5+vjjj2POG5mVfO+/fEQEAgEFAoGGlHpE210Svhe9uGiXWrZJc7gaAAAAoGnxepMOumfZKUlJSQc8JiUl5ZDOnZCQEP0+ci90QycYq+sc+ztvWVmZrrzySl177bX7nKtt27b7fa2kpKTo+X4uGnSP9qmnnqqVK1dqxYoV0cexxx6r0aNHR79PSEjQokWLos9Zu3atNm7cqIKCAklSQUGBVq5cqaKiougxCxcuVHp6urp37x6nt3VkC4XCPdnVVe6fbQ8AAAD4OercubOSkpJistH+pKenKz8/Xx9++GFM+4cfftignNStW7c6z3H00UdHe7MPxS9+8QutXr1aRx111D4Pvz98a6zf71codOAZn7t166ZgMKhly5ZF27Zv3661a9e6JhM2qEc7LS1NPXvG/uUoJSVFzZs3j7ZfdtllmjRpkrKyspSenq5rrrlGBQUFOv744yVJQ4cOVffu3XXxxRdr1qxZKiws1NSpUzVu3DhX9VrvT3R5L4aOAwAAAK6UmJioyZMn66abbpLf79fAgQO1bds2rVq1qt7h5DfeeKNuv/12derUSX379tVTTz2lFStWxAzXPpDrr79e/fv31x133KELLrhAS5cu1UMPPaRHHnnksN7P5MmTdfzxx2v8+PH6/e9/r5SUFK1evVoLFy7UQw89JCk8m/n777+vCy+8UIFAQC1atKjzXJ07d9Y555yjyy+/XI899pjS0tL0xz/+Ua1atdpn2HtT1eDJ0A7k/vvvl8fj0ahRo1RZWalhw4bF/FC9Xq9effVVXX311SooKFBKSorGjh2rGTNmxLuUI1ckX7OONgAAAOBat956q3w+n2677TZt3rxZeXl5uuqqq+o9/tprr1VxcbGuv/56FRUVqXv37nr55ZfVuXPng37NX/ziF/r3v/+t2267TXfccYfy8vI0Y8aMmInQDkXv3r21ePFi3XLLLTrxxBNlWZY6deqkCy64IHrMjBkzdOWVV6pTp06qrKyMdjDW5amnntKECRN05plnqqqqSieddJJef/31mOHrTZlh7e/dH6FKSkqUkZGh4uJipaenO11Og735+Eqt/2ybBv3maPU8qbXT5QAAAABHpIqKCm3YsEEdOnSwdTJm/Hzt75prSA49pHW0cXgSAuF7I5LT/A5XAgAAAACIN4K2Azze8MfuTTj0yQgAAAAAAEcmgrYDqiuCkqTdZVUOVwIAAAAAiDeCtgOqK8NT3u8urXa4EgAAAABAvBG0HRCZfo7lvQAAAIADa4LzN6OJite1RtB2QHQdbf7BAAAAAOoVWepp165dDleCn4vItXa4y4zFfR1tHFgkX5shgjYAAABQH6/Xq8zMTBUVFUmSkpOTZRiGw1XBjSzL0q5du1RUVKTMzEx5vYc3cTVB2wEeT/gfB18CAwoAAACA/cnNzZWkaNgGGlNmZmb0mjscBG0H+PzhgB1IObzhCAAAAIDbGYahvLw8ZWdnq7qayYTReBISEg67JzuCoO0AMxgeMh6qNh2uBAAAAGgavF5v3EIQ0NgYu+yAyt3hdbTLfqpwuBIAAAAAQLwRtB3A8l4AAAAA4F4EbQdElvUyCdoAAAAA4DoEbSdE1tHmFm0AAAAAcB2CtgMiQ8YjPdsAAAAAAPcgaDvAFwjPlpiU5ne4EgAAAABAvBG0nRCZDI0ObQAAAABwHYK2A6orQ5Kk3SVVDlcCAAAAAIg3grYDzFC4KztYHXK4EgAAAABAvBG0HWAx6zgAAAAAuBZB2wGRe7NNbtIGAAAAANchaDsguryXSdAGAAAAALchaDvA4zUkST4/Hz8AAAAAuA1JzwlGOGh7vXz8AAAAAOA2JD0HmMHwLGhVlcw6DgAAAABuQ9B2QKgmaFfvDjpcCQAAAAAg3gjaDmDWcQAAAABwL4K2AyL52goRtAEAAADAbQjaDogu70XOBgAAAADXIWg7wSBhAwAAAIBbEbQdYBiRdbS9DlcCAAAAAIg3grYDIkPHzZDpcCUAAAAAgHgjaDsgsrxX5S6W9wIAAAAAtyFoOyA66zizoQEAAACA6xC0nRBZR5vlvQAAAADAdQjaDjDNSJe2s3UAAAAAAOKPoO2gaOAGAAAAALgGQdsBkXuzvT7D4UoAAAAAAPFG0HZEOGAzFxoAAAAAuA9B2wFWzfrZwaqQw5UAAAAAAOKNoO0As6YrOxSkSxsAAAAA3Iag7QTT6QIAAAAAAI2FoO2AyL3Z3KMNAAAAAO5D0LaZVTtdk7QBAAAAwHUI2jaLZGuf3yPDw/JeAAAAAOA2BG2bRXq0/Uk+GeRsAAAAAHAdgrbdaiZCM4OmLJOh4wAAAADgNgRtm0WW9qooDyoUImgDAAAAgNsQtG1WuxfbYjI0AAAAAHAdgrbNYrI1ORsAAAAAXIegbTPuywYAAAAAd2tQ0J4zZ4569+6t9PR0paenq6CgQG+88UZ0/+DBg2UYRszjqquuijnHxo0bNWLECCUnJys7O1s33nijgsFgfN5NExAZLu71eejRBgAAAAAX8jXk4NatW+uuu+5S586dZVmWnn76aZ1zzjn6/PPP1aNHD0nS5ZdfrhkzZkSfk5ycHP0+FAppxIgRys3N1ZIlS7RlyxaNGTNGCQkJuvPOO+P0lo5sVs2s41n5KSovrnS2GAAAAABA3DUoaJ911lkx23/+8581Z84cffTRR9GgnZycrNzc3Dqf/9Zbb2n16tV6++23lZOTo759++qOO+7Q5MmTNW3aNPn9/kN8G01HpEfb4zXo0QYAAAAAFzrke7RDoZCeffZZlZeXq6CgINr+zDPPqEWLFurZs6emTJmiXbt2RfctXbpUvXr1Uk5OTrRt2LBhKikp0apVq+p9rcrKSpWUlMQ8mqpIj3bRtyUKBU1niwEAAAAAxF2DerQlaeXKlSooKFBFRYVSU1M1f/58de/eXZL0m9/8Ru3atVN+fr6+/PJLTZ48WWvXrtULL7wgSSosLIwJ2ZKi24WFhfW+5syZMzV9+vSGlnpEivRos7IXAAAAALhTg4N2ly5dtGLFChUXF+v555/X2LFjtXjxYnXv3l1XXHFF9LhevXopLy9Pp556qtavX69OnTodcpFTpkzRpEmTotslJSVq06bNIZ/PSTHraNOhDQAAAACu0+Ch436/X0cddZT69eunmTNnqk+fPnrggQfqPHbAgAGSpHXr1kmScnNztXXr1phjItv13dctSYFAIDrTeeTRVNXuyba4SRsAAAAAXOew19E2TVOVlXXPnr1ixQpJUl5eniSpoKBAK1euVFFRUfSYhQsXKj09PTr83O1YRxsAAAAA3K1BQ8enTJmiM844Q23btlVpaanmzZun9957TwsWLND69es1b948DR8+XM2bN9eXX36piRMn6qSTTlLv3r0lSUOHDlX37t118cUXa9asWSosLNTUqVM1btw4BQKBRnmDR5rIPdp5R2Xqx+9LHa4GAAAAABBvDQraRUVFGjNmjLZs2aKMjAz17t1bCxYs0GmnnaZNmzbp7bff1uzZs1VeXq42bdpo1KhRmjp1avT5Xq9Xr776qq6++moVFBQoJSVFY8eOjVl32+0iQ8eTUhNkOFsKAAAAAKARNChoP/HEE/Xua9OmjRYvXnzAc7Rr106vv/56Q17WVSJDx3/8vkwmU48DAAAAgOsc9j3aaJhIti75cTezjgMAAACACxG0bRYzGRo92gAAAADgOgRtm1m1wjUxGwAAAADch6Bts5jh4iRtAAAAAHAdgrbNIj3azVulyCJpAwAAAIDrELRtFhk5nt+5mQyLBb4AAAAAwG0I2jaLTIa2u7SK5b0AAAAAwIUatI42Dl9k6Pi65UUOVwIAAAAAaAz0aNuMTmwAAAAAcDeCtt32StoWyRsAAAAAXIWgbbN9YjU5GwAAAABchaBtt5p1tH3+8EdPzgYAAAAAdyFo2yyydvYvhrWraSBqAwAAAICbELTtVpOrDSO8hjY5GwAAAADchaBts0iwXrFoY02Dc7UAAAAAAOKPoG2zyCzjleXB8DZJGwAAAABchaDtMIaOAwAAAIC7ELTttnewJmgDAAAAgKsQtG1m7dWFvfc2AAAAAKBpI2jbLJKrew5qVdPgXC0AAAAAgPgjaDukeatUSeRsAAAAAHAbgrbNIkPFv135Y3jbJGoDAAAAgJsQtO1Wk6u/W7nd2ToAAAAAAI2CoG2zfeY+o0MbAAAAAFyFoO0wZh0HAAAAAHchaNts3+W9HCoEAAAAANAoCNp2qwnWuZ0ynK0DAAAAANAoCNo2s2qSdu+TW4e36dIGAAAAAFchaNvMMsNfd5dW1TQ4VwsAAAAAIP4I2g75f//6WhI92gAAAADgNgRtuzEZGgAAAAC4GkHbZgRrAAAAAHA3grbN9g7alknyBgAAAAA3IWjbjmANAAAAAG5G0LZZpEf77Al9Y7YBAAAAAO5A0LZbTbA2PEZ4k6QNAAAAAK5C0LZZJFi//+zamgYHiwEAAAAAxB1B2yE/bdnldAkAAAAAgEZA0LaZZUkyam/TpQ0AAAAAbkLQtptl1c7ZTIYGAAAAAC5D0LYZPdoAAAAA4G4EbScYUv8R7cPfk7MBAAAAwFUI2jazLEsej0dtezZ3uhQAAAAAQCMgaNvMssL/s/6zbTXbdGkDAAAAgJsQtO1Wk6tXLNwY3iRnAwAAAICrELRtZlmWDKP2bGjO1QIAAAAAiD+CthOYdRwAAAAAXIugbTNyNQAAAAC4G0HbbpZkGIZyO6aHN02H6wEAAAAAxBVB22aWZcnjNTToN13D29ykDQAAAACuQtB2gCVLwapQZAMAAAAA4CIEbZtZliWZhv5v1vKabYcLAgAAAADEVYOC9pw5c9S7d2+lp6crPT1dBQUFeuONN6L7KyoqNG7cODVv3lypqakaNWqUtm7dGnOOjRs3asSIEUpOTlZ2drZuvPFGBYPB+LybJsCyJMOzVwMAAAAAwDUaFLRbt26tu+66S8uXL9enn36qU045Reecc45WrVolSZo4caJeeeUVPffcc1q8eLE2b96sc889N/r8UCikESNGqKqqSkuWLNHTTz+tuXPn6rbbbovvuzqSWfvdBAAAAAA0cYZ1mAs5Z2Vl6e6779Z5552nli1bat68eTrvvPMkSf/5z3/UrVs3LV26VMcff7zeeOMNnXnmmdq8ebNycnIkSY8++qgmT56sbdu2ye/3H9RrlpSUKCMjQ8XFxUpPTz+c8m336esbtGLRJlWWh3vxf3X9Mcrv3MzhqgAAAAAA+9OQHHrI92iHQiE9++yzKi8vV0FBgZYvX67q6moNGTIkekzXrl3Vtm1bLV26VJK0dOlS9erVKxqyJWnYsGEqKSmJ9orXpbKyUiUlJTGPpsqyJGOvbQAAAACAezQ4aK9cuVKpqakKBAK66qqrNH/+fHXv3l2FhYXy+/3KzMyMOT4nJ0eFhYWSpMLCwpiQHdkf2VefmTNnKiMjI/po06ZNQ8s+YliW5PEaGjW5X3QbAAAAAOAeDQ7aXbp00YoVK7Rs2TJdffXVGjt2rFavXt0YtUVNmTJFxcXF0cemTZsa9fUalWXJ8HiUlJoQ3QYAAAAAuIevoU/w+/066qijJEn9+vXTJ598ogceeEAXXHCBqqqqtHPnzphe7a1btyo3N1eSlJubq48//jjmfJFZySPH1CUQCCgQCDS01COSJckyLb33zNroNgAAAADAPQ57HW3TNFVZWal+/fopISFBixYtiu5bu3atNm7cqIKCAklSQUGBVq5cqaKiougxCxcuVHp6urp37364pTQNVngt7e//81N423S2HAAAAABAfDWoR3vKlCk644wz1LZtW5WWlmrevHl67733tGDBAmVkZOiyyy7TpEmTlJWVpfT0dF1zzTUqKCjQ8ccfL0kaOnSounfvrosvvlizZs1SYWGhpk6dqnHjxrmmx/pALMuSYeyZDs2iTxsAAAAAXKVBQbuoqEhjxozRli1blJGRod69e2vBggU67bTTJEn333+/PB6PRo0apcrKSg0bNkyPPPJI9Pler1evvvqqrr76ahUUFCglJUVjx47VjBkz4vuujmSW9pp23KlCAAAAAACN4bDX0XZCU15He+mL67X2oy0q31klSTpzfB+169nc4aoAAAAAAPtjyzraOESWJcPr0bHD29dsNrm/cwAAAAAA9oOgbTPLkrweQz0HtXK6FAAAAABAIyBo261m1vFvv/wxvEmHNgAAAAC4CkHbZpZlyTQVXUebpA0AAAAA7kLQtpklqdbqXuRsAAAAAHAZgrbd9g7WBG0AAAAAcBWCtt32WkfbImkDAAAAgKsQtG1mWZY8hqHmrVLC26bDBQEAAAAA4oqgbTNLks/v0a+u/4XTpQAAAAAAGgFB226WJBkyamZEs5gNDQAAAABchaBtM8uyFKwO6Ykb/l9Ng7P1AAAAAADii6BtNyu8vJcZsmo2SdoAAAAA4CYEbZuFR47vmXacydAAAAAAwF0I2nbjnmwAAAAAcDWCts0sK2YZbYI3AAAAALgMQdtuliWf36tf39I/sgkAAAAAcBGCts0sSR6voaz8lPA2QRsAAAAAXIWgbTPLkkLVpt57Zm2kxdF6AAAAAADxRdC2m2XJsqT/LNkS2QQAAAAAuAhB225WzOpedGgDAAAAgMsQtG22d6626NIGAAAAAFchaNvM2mt9L3I2AAAAALgLQdtuluT1efSLYe32WlAbAAAAAOAGBG2bWZbkS/Co4Fed5DEMWSZd2gAAAADgJgRtu1mWTMvSD2t/ksVMaAAAAADgOgRtm1kKr6P94v2fyzAM7tEGAAAAAJchaNutdrA2mHUcAAAAANyGoG2z2pOOGxLraAMAAACAyxC07WZZklETtQ2mHQcAAAAAtyFo28ySZHiklMyADDF0HAAAAADchqBtN0vyJybokrsGyuNlMjQAAAAAcBuCts0sy9ozYtww6NEGAAAAAJchaNvMsqTqyqDm/vHDcMgmZwMAAACAqxC0HWBZhsp3VjpdBgAAAACgERC07VZrqLghho4DAAAAgNsQtG1We3UvGWIyNAAAAABwGYK2zfZZRpugDQAAAACuQtC2naWERK9GTjxGhpeh4wAAAADgNgRtm1mW5PV61KpLM3k8xoGfAAAAAABoUgjadrMsBatNLZ2/XpZpyTLp0QYAAAAANyFo28yypFDI1GcLvhPLaAMAAACA+xC0HcRkaAAAAADgPgRtm1mWpeid2YaYDA0AAAAAXIagbTdL0fW9DBn0aAMAAACAyxC0bWZZki/Bo24D8+TxGuRsAAAAAHAZgrbNLCu8jvYpF3eTx2uEkzcAAAAAwDUI2g6wLGn75jJZImcDAAAAgNsQtO1mSdW7g3p2xseyQqzvBQAAAABuQ9C2WUwPtmEw6zgAAAAAuAxB22aWZe2ZdZxJxwEAAADAdQjaTjBqfW86VgUAAAAAoBE0KGjPnDlT/fv3V1pamrKzszVy5EitXbs25pjBgwfLMIyYx1VXXRVzzMaNGzVixAglJycrOztbN954o4LB4OG/mybAssI52+MzFF5Gmz5tAAAAAHCTBgXtxYsXa9y4cfroo4+0cOFCVVdXa+jQoSovL4857vLLL9eWLVuij1mzZkX3hUIhjRgxQlVVVVqyZImefvppzZ07V7fddlt83tGRzrKUlObX1Q+drAS/l7HjAAAAAOAyvoYc/Oabb8Zsz507V9nZ2Vq+fLlOOumkaHtycrJyc3PrPMdbb72l1atX6+2331ZOTo769u2rO+64Q5MnT9a0adPk9/sP4W00HZal6NBxg2W0AQAAAMB1Duse7eLiYklSVlZWTPszzzyjFi1aqGfPnpoyZYp27doV3bd06VL16tVLOTk50bZhw4appKREq1atqvN1KisrVVJSEvNoyqp2B/WvP3+sYLVF0gYAAAAAl2lQj3Ztpmnquuuu08CBA9WzZ89o+29+8xu1a9dO+fn5+vLLLzV58mStXbtWL7zwgiSpsLAwJmRLim4XFhbW+VozZ87U9OnTD7XUI4plWbJCln7cVKbMnCRGjgMAAACAyxxy0B43bpy++uorffDBBzHtV1xxRfT7Xr16KS8vT6eeeqrWr1+vTp06HdJrTZkyRZMmTYpul5SUqE2bNodWuMNCQVPbt4TvaTdDlrZuKFF5caVSMgIOVwYAAAAAiIdDGjo+fvx4vfrqq3r33XfVunXr/R47YMAASdK6deskSbm5udq6dWvMMZHt+u7rDgQCSk9Pj3k0VWbQ0s7C8FB605K2bSzVruIqh6sCAAAAAMRLg4K2ZVkaP3685s+fr3feeUcdOnQ44HNWrFghScrLy5MkFRQUaOXKlSoqKooes3DhQqWnp6t79+4NKaeJ2jNY3NjPUQAAAACApqlBQ8fHjRunefPm6aWXXlJaWlr0nuqMjAwlJSVp/fr1mjdvnoYPH67mzZvryy+/1MSJE3XSSSepd+/ekqShQ4eqe/fuuvjiizVr1iwVFhZq6tSpGjdunAIB9w+fNrwete6aqaOPy9WKtzepdZdMpTVPdLosAAAAAECcNKhHe86cOSouLtbgwYOVl5cXffzrX/+SJPn9fr399tsaOnSounbtquuvv16jRo3SK6+8Ej2H1+vVq6++Kq/Xq4KCAv32t7/VmDFjNGPGjPi+syOUYRjKyk9VtxPylRDwKq1FkhJTEpwuCwAAAAAQJw3q0bYOsBRVmzZttHjx4gOep127dnr99dcb8tKuYQZNbd1Qoo9f3aDqqqC2/1CmXSVVSk539/rhAAAAAPBzccizjuPQmGZ4pvGtG0qU0TJRO37YpfKdlQRtAAAAAHCJQ5p1HIeu9qAAw2A6NAAAAABwG4K23Q4w/B4AAAAA0LQRtO1GzgYAAAAAV+MebbsZllKzAspomazdpVVKyfTLn+R1uioAAAAAQJzQo20zj9ejo/vnauTEY5SUmqD8zs2U0TLZ6bIAAAAAAHFC0LaZaVqqrgyqbGeFTMtSsCqkUMh0uiwAAAAAQJwwdNxmZtDSyvd+0Mr3flCzvGRt+bpYO34oV8u2aU6XBgAAAACIA3q0bWYx6zgAAAAAuBpB20Gsow0AAAAA7kPQtlntDm1iNgAAAAC4D0HbdiRtAAAAAHAzgrbNDMPQL4a11WX3nqjkDL/a9cxS89apTpcFAAAAAIgTZh23m2EoIeBVYkqCPF6PDMOQx0PXNgAAAAC4BUHbZmbI1Kr/t1kbV+2QaVoq3rZbO7fuUmZOstOlAQAAAADigKHjNrNMqeynSm1ZX6xQtamKsmpVV4acLgsAAAAAECcEbbvVXkabEeMAAAAA4DoEbZtZtZI2y2gDAAAAgPsQtJ1E0AYAAAAA12EyNAe07ZGl/M6Z+uE/PykzN1mpzQJOlwQAAAAAiBN6tG1mSGrdNUv9Tm8vf3KC0poFlJTmd7osAAAAAECcELRtZlqWCr8p1lfv/6DqyqDKdlaqorza6bIAAAAAAHHC0HGbWab0zefb9M3n25TTPk0/bdml0u0VSkxJcLo0AAAAAEAc0KNtN6vW+l5MOw4AAAAArkPQBgAAAAAgjgjaNovp0ObTBwAAAADX4R5tm1mylJLpV2KqX16vRwkBr3x+EjcAAAAAuAVB22aGDPU7vb16DW6tt+eulhmy1Cw3xemyAAAAAABxQleq3aw9c6AZRuxQcgAAAABA00fQtplpWlr8z//q4aveUfG2ChV+U6xtG0udLgsAAAAAECcEbQAAAAAA4oig7SCW0QYAAAAA9yFo28ja+4ZsgjYAAAAAuA5B205752yCNgAAAAC4Dst72SiSs487q706HpOtz9/epGa5VWqWl+xoXQAAAACA+KFH2041Q8dTmyWpeX6qEnweeRM88iV4HS4MAAAAABAv9GjbKHKL9pfvbtKGL7ZJkkq2V6jkx91Kb5HkYGUAAAAAgHihR9tONUH7x01l2vDFj6quCqlqV1CVu4LO1gUAAAAAiBuCto2svWdDAwAAAAC4DkHbRnuv7sXyXgAAAADgPgRtO+2zjDZJGwAAAADchsnQbGTVdGm37ZmlZrkp2lVapcQUn5Iz/A5XBgAAAACIF3q0HdD1+Dz98rzOSknzKzHVr5SMgNMlAQAAAADihB5tG0Xu0d76bYk8XkNVlSFVVQRVtTsofxI/CgAAAABwA3q07VSTtL94e5PefOwrle+s1K7iKhVv2+1wYQAAAACAeCFo22jvWceZCg0AAAAA3IegbSeW0QYAAAAA1yNo28giaQMAAACA6zEDl51qcnZiik8+v1cenyHDI3l8DCIHAAAAALcgaNsoco/2KWO6qUOfllr28jcq+rZUzfNTnS0MAAAAABA3DB23kRVJ2kZND7ax7wRpAAAAAICmjR5tB7z196/k9XnUumszlRdX6sfvy9SiNb3aAAAAAOAGDerRnjlzpvr376+0tDRlZ2dr5MiRWrt2bcwxFRUVGjdunJo3b67U1FSNGjVKW7dujTlm48aNGjFihJKTk5Wdna0bb7xRwWDw8N/Nka6m9zpYZapyVzDcw21Jlkm3NgAAAAC4RYOC9uLFizVu3Dh99NFHWrhwoaqrqzV06FCVl5dHj5k4caJeeeUVPffcc1q8eLE2b96sc889N7o/FAppxIgRqqqq0pIlS/T0009r7ty5uu222+L3ro5QFuPEAQAAAMD1DOsw0t+2bduUnZ2txYsX66STTlJxcbFatmypefPm6bzzzpMk/ec//1G3bt20dOlSHX/88XrjjTd05plnavPmzcrJyZEkPfroo5o8ebK2bdsmv99/wNctKSlRRkaGiouLlZ6efqjl2650R4X+cfOS6HanY1po/ec/6tc391fLtmkOVgYAAAAA2J+G5NDDmgytuLhYkpSVlSVJWr58uaqrqzVkyJDoMV27dlXbtm21dOlSSdLSpUvVq1evaMiWpGHDhqmkpESrVq2q83UqKytVUlIS82iK9vmbhsGyXgAAAADgNocctE3T1HXXXaeBAweqZ8+ekqTCwkL5/X5lZmbGHJuTk6PCwsLoMbVDdmR/ZF9dZs6cqYyMjOijTZs2h1q2s2pydsGvOunsCX2VkZ0kf6JXGdlJztYFAAAAAIibQw7a48aN01dffaVnn302nvXUacqUKSouLo4+Nm3a1Oiv2RgiHdrZ7dLUpluW/Ik+GV5D/kQmfwcAAAAAtzikhDd+/Hi9+uqrev/999W6detoe25urqqqqrRz586YXu2tW7cqNzc3eszHH38cc77IrOSRY/YWCAQUCAQOpdQjSmTo+Iq3N+rrT7bKk+BRsDKksp8qlNos0eHqAAAAAADx0KAebcuyNH78eM2fP1/vvPOOOnToELO/X79+SkhI0KJFi6Jta9eu1caNG1VQUCBJKigo0MqVK1VUVBQ9ZuHChUpPT1f37t0P570c+Wp6tL/7aodWf7hFFWXVCgUt7S6tdrYuAAAAAEDcNKhHe9y4cZo3b55eeuklpaWlRe+pzsjIUFJSkjIyMnTZZZdp0qRJysrKUnp6uq655hoVFBTo+OOPlyQNHTpU3bt318UXX6xZs2apsLBQU6dO1bhx41zRa70/+06G5kwdAAAAAIDG06CgPWfOHEnS4MGDY9qfeuopXXLJJZKk+++/Xx6PR6NGjVJlZaWGDRumRx55JHqs1+vVq6++qquvvloFBQVKSUnR2LFjNWPGjMN7J00QORsAAAAA3KdBQftgltxOTEzUww8/rIcffrjeY9q1a6fXX3+9IS/tCpbpdAUAAAAAgMbGdNc2smpu0m7bI0tJqX75U3wyPFJiaoLDlQEAAAAA4oWgbaeaAQH9R3RQbscMffHOJnm8HqVlMeM4AAAAALgFQdtGkZH3238ok2VZqq4MyjItVVeFlOD3OlscAAAAACAuCNo2itzj/t4zayVJXY7PlRmytLNwl1q2TXOyNAAAAABAnDRoHW0cpgPPJQcAAAAAaOII2jbae9Z2g/W9AAAAAMB1CNoAAAAAAMQR92jbKLKOttdnyPCEH5IkerYBAAAAwDUI2jaKrKN9/pT+at4qVas/2Kw1H25Ri9apDlcGAAAAAIgXho7bae/J0Ix62gEAAAAATRY92jaKzIX2ykNfyOvzqF2PLEnS9i3latGKXm0AAAAAcAOCto0is46X/1QpSQoFwzdth6pCjtUEAAAAAIgvho7bqZ6h44wcBwAAAAD3IGjbaO91tPfssLcOAAAAAEDjIWjbaa9AbdR0aVskbQAAAABwDe7RtlGkR3vgeZ2UnB7QrpIqSVJaVpKTZQEAAAAA4ogebRtF+q079s3W0cflKjnDL0kKJPH3DgAAAABwCxKencKTjOuztzYqkOxTINErSSovrlRmdrKDhQEAAAAA4oWgbaPIvdir3v9BktRrcCtJ0q6dBG0AAAAAcAuGjtton0nHjchkaAAAAAAAtyBo26m+1b1I2gAAAADgGgRtG9W7jjYAAAAAwDW4R9tONTk7v0umfD6PklITJEn+mknRAAAAAABNH0HbRpEe7WGX9VRyul/frNgmSUrLSnSyLAAAAABAHBG0bRQZOV66Y7eqK4MKVQclScFq08GqAAAAAADxRNC2U03Qfv6u5ZKkPkNaS5J+KiynVxsAAAAAXILJ0Gxk7TXtuOFQHQAAAACAxkPQtpG19wjxSNJmMnIAAAAAcA2CtoOMmqTNsl8AAAAA4B4EbRvVF6jJ2QAAAADgHkyGZqeaQP27WQPlD/j0/dc79PnCTcrKS3G2LgAAAABA3BC0bRTp0U5I9Mnn98rr8TpcEQAAAAAg3gjaNooMEZ9/z3IZHkMd+7aUJJX8uFvpLZIcrAwAAAAAEC/co22nmqS9bWOZir4tVVVFUJJUVRlysioAAAAAQBwRtG2075xnRn07AAAAAABNFEHbRnuvo22wjjYAAAAAuA5B21axiTqas1nfCwAAAABcg8nQbBTJ0yeM6iTDYygpxS9JSs7wO1gVAAAAACCeCNo2ssxw0j7mtHaSpC3rdkqSAskJTpUEAAAAAIgzgrYDVry9UTKk5LSAJKmivEpSirNFAQAAAADigqBto8jQ8Q+fXydJ6j+ivSSpfGeVQxUBAAAAAOKNydDsZFl7ZhqX9syGBgAAAABwDYK2jSxLdYZrZh0HAAAAAPcgaNvIsiSjVpc262gDAAAAgPtwj7aNLMuSDCm7XZpkSIGk8GzjvgSvw5UBAAAAAOKFoG0nS/J4DJ0/pb8kadvGUklSalbAyaoAAAAAAHFE0LZR5F7sYGVIkmRaZkw7AAAAAKDpI2g74LEJiyVJA87pIEn6acsu5bTPcLIkAAAAAECcMBmajSxTqmt9L/qzAQAAAMA9CNo2shS7jjazjgMAAACA+xC07bR3oDbqbgYAAAAANF0NDtrvv/++zjrrLOXn58swDL344osx+y+55BIZhhHzOP3002OO2bFjh0aPHq309HRlZmbqsssuU1lZ2WG9kabAsiwZqr2OdiRpE7UBAAAAwC0aPBlaeXm5+vTpo0svvVTnnntuncecfvrpeuqpp6LbgUDs8lWjR4/Wli1btHDhQlVXV+t3v/udrrjiCs2bN6+h5TQpliV5fNJv7zheklSxq1qSlN480cmyAAAAAABx1OCgfcYZZ+iMM87Y7zGBQEC5ubl17luzZo3efPNNffLJJzr22GMlSX/96181fPhw3XPPPcrPz29oSU2HFe7FzmiZLEkyC8slSR6vsb9nAQAAAACakEa5R/u9995Tdna2unTpoquvvlrbt2+P7lu6dKkyMzOjIVuShgwZIo/Ho2XLltV5vsrKSpWUlMQ8miLLsmRZ0it/XaFX/rpCW78Nv4+ynyodrgwAAAAAEC9xD9qnn366/vGPf2jRokX6y1/+osWLF+uMM85QKBSSJBUWFio7OzvmOT6fT1lZWSosLKzznDNnzlRGRkb00aZNm3iXbSNLG1ft0MZVO7S7NDx0vKoi5HBNAAAAAIB4afDQ8QO58MILo9/36tVLvXv3VqdOnfTee+/p1FNPPaRzTpkyRZMmTYpul5SUNMmwbZmWpNrre0X3OFANAAAAAKAxNPryXh07dlSLFi20bt06SVJubq6KiopijgkGg9qxY0e993UHAgGlp6fHPJoiS6pzHW1iNgAAAAC4R6MH7e+//17bt29XXl6eJKmgoEA7d+7U8uXLo8e88847Mk1TAwYMaOxynLVXh3aUaXchAAAAAIDG0uCh42VlZdHeaUnasGGDVqxYoaysLGVlZWn69OkaNWqUcnNztX79et1000066qijNGzYMElSt27ddPrpp+vyyy/Xo48+qurqao0fP14XXnihu2ccV3gyNI/Ho1+c3laSoWY54dnHAylxH8EPAAAAAHBIgxPep59+qpNPPjm6Hbl3euzYsZozZ46+/PJLPf3009q5c6fy8/M1dOhQ3XHHHTFraT/zzDMaP368Tj31VHk8Ho0aNUoPPvhgHN7Okc2yJK/PUMHIoyRJpTsqJEmJyQlOlgUAAAAAiKMGB+3BgwfLsuq/q3jBggUHPEdWVpbmzZvX0Jdu+qzwhGj//Tg8u3p6i0RJzDoOAAAAAG7CmGUbWZYly5QWPrlaknTiBZ0lSeXFFU6WBQAAAACIo0afDA217D0ZmlGrHQAAAADgCgRtG1mWFbu+V6TdgVoAAAAAAI2DoG2jvdfRjnZpk7QBAAAAwDW4R9tOpmQYhtJbJEmG5E/0SpIMT12LawMAAAAAmiKCto0sWfL5PbrotgGSpN1lVZKktGaJTpYFAAAAAIgjho7baO9btI2aDYux4wAAAADgGvRo28mSglWmHrv2PUnSL38dXt6reNtuB4sCAAAAAMQTQdtGlmXJ8ITDdrhBsV8BAAAAAE0eQ8fttFegji6jbZG0AQAAAMAtCNo22mcd7WjSdqQcAAAAAEAjIGjbyNKebC0pGrqZDA0AAAAA3IN7tO1kWvL5vTr3xl9IklKbBSRJyekBJ6sCAAAAAMQRQdtGliSP11Bep0xJUrAqJEny+hhYAAAAAABuQdC2kWVJZsjUwqdWyZChbifkSZIqSqscrgwAAAAAEC8EbTtZlixT+u+yrZKkVl2bSZIqK4JOVgUAAAAAiCPGLNto71W8ohOjMRcaAAAAALgGQdtOe087XvM9y2gDAAAAgHsQtG1k7ZWojXqOAwAAAAA0XdyjbSPLknwJHnUbmCdDUkZOkiQpIeB1tjAAAAAAQNwQtO1kWfImeHXKxd1imgPJ/BgAAAAAwC1IeDayrPDw8e//s0OWJWXlp0iSglWmw5UBAAAAAOKFoG0jy5JCVSG9NHuFJOm0S7tLknaxjjYAAAAAuAaTodnJsmQY+06BZplMOw4AAAAAbkHQtpElMdU4AAAAALgcQdtGlmlJdfRoiw5tAAAAAHAN7tG2mWFI/iSfDEPyeGv+zkEvNwAAAAC4BkHbRpYlBZITdPn9J0XbFj3tUUpGwMGqAAAAAADxxNBxO1l1jBE3DFl1tQMAAAAAmiR6tG1kWVKwKqi5Uz6UIenECzorWBnSruJKp0sDAAAAAMQJQdtGliXJksp/CgfrYJUpSQqF6NEGAAAAALdg6LidLKvuScfJ2QAAAADgGgRtG7GONgAAAAC4H0HbRvWuow0AAAAAcA3u0baZP9Gr06/sKUnKaZ+uhIBXgWR+DAAAAADgFiQ8G1mWJa/Pq07HZEfbfH6PvD4GFgAAAACAWxC07WRJwaqQPnjuv5JhqMuAXFVXhlS1u9rpygAAAAAAcULQtpFlSaGQqS8WfS9Jym6bpmCVqardIYcrAwAAAADEC2OWbWRZlgymHQcAAAAAVyNo26meScctFtIGAAAAANcgaNvIslRn0iZmAwAAAIB7cI+2jcKzjhvq0KeFJCklMyCf3yMfs44DAAAAgGsQtG0WSPLp5Iu7RbcTUxPkT+LHAAAAAABuQcKzkWVaMi1p+w9lkhHu0bZClswgg8cBAAAAwC0I2jar2l2tZ+/4WJJ02qXdVV5cpd1lVQ5XBQAAAACIF24OtlF4cvE6JkOjQxsAAAAAXIOgbSPLsupZ3sv+WgAAAAAAjYOgbSPLqqs/m3W0AQAAAMBNCNp2siR56ho6TtAGAAAAALdgMjQbWZal5DS/xj16SrTtswXfKSnV72BVAAAAAIB4okfbZsbeN2kbhiyTHm0AAAAAcAt6tG1kmZYqdlXr2TuWSYahgpEdVVy0S81yk50uDQAAAAAQJw3u0X7//fd11llnKT8/X4Zh6MUXX4zZb1mWbrvtNuXl5SkpKUlDhgzR119/HXPMjh07NHr0aKWnpyszM1OXXXaZysrKDuuNNBWWaWn7D+Xa/n2ZKncFFawyFQqaTpcFAAAAAIiTBgft8vJy9enTRw8//HCd+2fNmqUHH3xQjz76qJYtW6aUlBQNGzZMFRUV0WNGjx6tVatWaeHChXr11Vf1/vvv64orrjj0d9FEWJZU1/pezIUGAAAAAO7R4KHjZ5xxhs4444w691mWpdmzZ2vq1Kk655xzJEn/+Mc/lJOToxdffFEXXnih1qxZozfffFOffPKJjj32WEnSX//6Vw0fPlz33HOP8vPzD+PtHNnqW0dbBG0AAAAAcI24Toa2YcMGFRYWasiQIdG2jIwMDRgwQEuXLpUkLV26VJmZmdGQLUlDhgyRx+PRsmXL6jxvZWWlSkpKYh5NkWXV2aHN8l4AAAAA4CJxnQytsLBQkpSTkxPTnpOTE91XWFio7Ozs2CJ8PmVlZUWP2dvMmTM1ffr0eJbqDMuSP8mnQb/pIknK6ZCuzJxk+fxM/g4AAAAAbtEkEt6UKVNUXFwcfWzatMnpkg6JZUkJfq96ntRKPU9qpYyWyUrJ8MvjaRI/BgAAAADAQYhrj3Zubq4kaevWrcrLy4u2b926VX379o0eU1RUFPO8YDCoHTt2RJ+/t0AgoEAgEM9SnWFJwWpTy9/8VpLUoU9LlRdXyp/EKmsAAAAA4BZx7Urt0KGDcnNztWjRomhbSUmJli1bpoKCAklSQUGBdu7cqeXLl0ePeeedd2SapgYMGBDPco44lmWpqiKoj178Rh+9+I1+3FSqnVt3q7oy5HRpAAAAAIA4aXBXallZmdatWxfd3rBhg1asWKGsrCy1bdtW1113nf70pz+pc+fO6tChg2699Vbl5+dr5MiRkqRu3brp9NNP1+WXX65HH31U1dXVGj9+vC688EJXzzgewWRoAAAAAOBuDQ7an376qU4++eTo9qRJkyRJY8eO1dy5c3XTTTepvLxcV1xxhXbu3Klf/vKXevPNN5WYmBh9zjPPPKPx48fr1FNPlcfj0ahRo/Tggw/G4e0c2Syz7mnHLdOBYgAAAAAAjaLBQXvw4MH77YE1DEMzZszQjBkz6j0mKytL8+bNa+hLN3mWpDqX0aZDGwAAAABcg1m4bGRZki/Bo9xOGTIkJaYmKCk1QQaTjgMAAACAaxC07WRZSkzza9SN/aJNeUdlKljNZGgAAAAA4BYEbRuFh4hbqiivliT5Al5ZlinTZOw4AAAAALgFQdtOlrSrpFpPXP//JEmnXdpdG77Yruz2aQ4XBgAAAACIF+4OtlF9k8ixvBcAAAAAuAdB20aWVc+s4yzvBQAAAACuQdC2U71J2/ZKAAAAAACNhKBtI9OSPJ59kzYjxwEAAADAPZgMzUaWaSmlWUCX3HWCLEn+ZJ86989W8bbdTpcGAAAAAIgTgraNLNOS1+tRSmZitC3B72XoOAAAAAC4CEHbRpYZXkP7xfs/lyQdO7ydNq3ZoYQAPwYAAAAAcAvu0baJZVmyLMkMWvph7U/6Ye1P2lVcpdIdlTJNph0HAAAAALcgaNskMuGZUccnzvJeAAAAAOAeBG2bWJGkXVfQZtpxAAAAAHANgrZNLDMcpo06FtImZwMAAACAezALl00iw8MT0xLU/8z2kgw1b5Wq/M6ZKvup0snSAAAAAABxRNC2SaRHOzE5Qb1Oah1tz2mfrvKd25wqCwAAAAAQZwRtm5g1QTtUbWrNki2SLOV3ztTOol0yQ8yGBgAAAABuQdC2SWTCs91l1Vryf+skSadd2l0bvvhRyel+J0sDAAAAAMQRk6HZJHKPdp3LezEbGgAAAAC4BkHbJtFZx/eddJygDQAAAAAuQtC2SSRMG3UmbZuLAQAAAAA0Gu7RtklkMjRfgleZuckyJCUk+pSc4VeomsnQAAAAAMAtCNo2idyjnd4iUaOnHR9t37G5tVYs3ORQVQAAAACAeGPouE2i92h7YoeOG4bBPdoAAAAA4CL0aNskEqaLt+3WSw98LkOGTh3bTR+9tF5eH3/vAAAAAAC3IGjbxDT3TIZmhSSrZgY0yxSToQEAAACAi9CVapPoOtos7wUAAAAArkbQtkl0ea86PnFyNgAAAAC4B0HbJpZZ/zra9GgDAAAAgHtwj7ZNost7tUzWeVOOlSEpvXmijh3eXp++/q2TpQEAAAAA4oigbZNIr3VCwKPm+anR9tRmAadKAgAAAAA0AoK2TSKzju8uqdKC11ZKMtTr5NZau6xQUnho+d5rbAMAAAAAmh6Ctk0i92hX7Q5p3fJtkqQOfVpoy7ri8H7LkiGCNgAAAAA0dUyGZpNI0K7vE2c+NAAAAABwB4K2TSJBuq51tKVaQRwAAAAA0KQRtG2yv+W9JHq0AQAAAMAtuEfbJpHJ0JLT/eo5qJUkKSM7WR36tNCGL36kRxsAAAAAXIKgbZNIj3Vqs0QNuqhLtP3o43LDQZsubQAAAABwBYK2TSI91sGqoL5dWSJJatEmVTsKy2r2O1YaAAAAACCOCNo2iQTtku2Veu3hLyVJp13aXZ+88m14Pz3aAAAAAOAKTIZmk8g92p76Zh0nZwMAAACAKxC07RJZ3quepM1kaAAAAADgDgRtm0R6tFVvjzZBGwAAAADcgHu0bRIJ0l6fR0lpCdHvE1MSVFFevSeIAwAAAACaNIK2TSJDw1u0SdOld58Ybfcn+/Ty7BXRoeUAAAAAgKaNoeM2iSzfZew1dNyoaaBHGwAAAADcgR5tm5imJcOQdmwu10uzP5ckDbqoi96btzZ8ADkbAAAAAFyBoG0Ty7RkeAyZIUu7S6slSaGgqYqy8PdMhgYAAAAA7sDQcZtYVv1Le0kMHQcAAAAAtyBo28SqGTpe/wG2lQIAAAAAaERxD9rTpk2TYRgxj65du0b3V1RUaNy4cWrevLlSU1M1atQobd26Nd5lHHEsy6JHGwAAAAB+BhqlR7tHjx7asmVL9PHBBx9E902cOFGvvPKKnnvuOS1evFibN2/Wueee2xhlHFFM05LHYygjO0kjxvXWiHG9lX90pgaP7hI+gJwNAAAAAK7QKJOh+Xw+5ebm7tNeXFysJ554QvPmzdMpp5wiSXrqqafUrVs3ffTRRzr++OMbo5wjQnjouCF/ok/te7WItme3Tw/vZzI0AAAAAHCFRunR/vrrr5Wfn6+OHTtq9OjR2rhxoyRp+fLlqq6u1pAhQ6LHdu3aVW3bttXSpUvrPV9lZaVKSkpiHk2NZUqGRyr7qVKL/7lWi/+5Vlu/LdHKd7+XxNBxAAAAAHCLuAftAQMGaO7cuXrzzTc1Z84cbdiwQSeeeKJKS0tVWFgov9+vzMzMmOfk5OSosLCw3nPOnDlTGRkZ0UebNm3iXXaji9yjvbu0Sl8t/kFfLf5BxUW7tGbJlpoDnK0PAAAAABAfcR86fsYZZ0S/7927twYMGKB27drp3//+t5KSkg7pnFOmTNGkSZOi2yUlJU0ubFs192jXhx5tAAAAAHCHRl/eKzMzU0cffbTWrVun3NxcVVVVaefOnTHHbN26tc57uiMCgYDS09NjHk2NZUna7/JeBG0AAAAAcINGD9plZWVav3698vLy1K9fPyUkJGjRokXR/WvXrtXGjRtVUFDQ2KU4yjxgj7aNxQAAAAAAGk3ch47fcMMNOuuss9SuXTtt3rxZt99+u7xery666CJlZGTosssu06RJk5SVlaX09HRdc801KigocPWM49KeWccDKT4d1a+lJEOpWYk6ql+21i0vYtZxAAAAAHCJuAft77//XhdddJG2b9+uli1b6pe//KU++ugjtWzZUpJ0//33y+PxaNSoUaqsrNSwYcP0yCOPxLuMI45lhidDS2+epGGX94q2pzYLaN3yIokebQAAAABwhbgH7WeffXa/+xMTE/Xwww/r4YcfjvdLH9HCy3sZClaFtH1LuQxJ6c0TVVy0W5Jk0qMNAAAAAK4Q96CNupmWJY9H+qlwl56f+akk6bRLu2vhk6slhXu8AQAAAABNX6NPhoawyNDxeveTswEAAADAFQjaNrEsyTD2E7Tp0QYAAAAAVyBo2yQ86/h+9tOlDQAAAACuQNC2Se2h44ZX8njD30e+Wsw6DgAAAACuwGRoNrFMSx6PoZZt0/SHh0+Jtrfv1UJ/m/g+PdoAAAAA4BL0aNvEtOqZDK2miaANAAAAAO5Aj7ZNwutoSzu2lOuNx1bKkFRw7lH6+OVvovsBAAAAAE0fQdsm4cnQDIWqTe0s3CVJqq4I6sfvy8L76dEGAAAAAFdg6LhNrPqGjtcwQwRtAAAAAHADgrZNLHP/62gTtAEAAADAHQjaNjFNS556Pm2Pz5AZ4iZtAAAAAHAD7tG2iWWFl/dKa56oU8Z0k2Qpp0O6hl3eU+/8Y7VCQXq0AQAAAMANCNo2sUxLhs+jxJQEdTshL9qe0TJZi/+5lh5tAAAAAHAJgrZNIrOO7yqp0lfvfy/JUKdjWmrTmh3yGFKomqANAAAAAG5A0LaJaUoej1S+s1KfvPqtJCkzO0kfPr9OKZl+hZgMDQAAAABcgcnQ7GJZUj2zjhsej8wgPdoAAAAA4AYEbZuEZx2vO2h7vaJHGwAAAABcgqBtE8uUjHo+bcNLjzYAAAAAuAX3aNvEsiwZHkP+JK9adWkmSUrO8Kt97xYq+6lCIYI2AAAAALgCQdsmZig8dDyjZbJGTjwm2t66S5ZevO8z1tEGAAAAAJcgaNskFDTlS/AqFDJVUVolS5I/2adQpSnDa7CONgAAAAC4BEHbJsFqU94Ej3b8UK5/3/mJJOm0S7tr4ZOrlXdUhkIJ9GgDAAAAgBswGZpNQjVBuy4eerQBAAAAwDUI2jYJVZvy+upe3svj9TAZGgAAAAC4BEHbJsGae7Tr4vUaMpkMDQAAAABcgaBtk/0NHTe8Bj3aAAAAAOASTIZmAzNkyjIteX0eNW+dqsvuPVGS5At4dXmvFlo6f51KfqxwuEoAAAAAQDwQtG0QrA73VvsSPPJ4DCWmJOzZ6fPIm+CVSY82AAAAALgCQdsGkfuvvQke7dy6S4v+sUaGpGNHtNeKtzcpLSuRoeMAAAAA4BLco22DSI+2N8Gj6sqQCtcXa8v6YlWUVWvT6h2yZMkMMRkaAAAAALgBQdsGoWBIkuTz1f1xez0s7wUAAAAAbkHQtkHtHu26GF6DHm0AAAAAcAmCtg1CBwjaXh/LewEAAACAWzAZmg1CtWYdT0xJ0PEjO0qSWrRJ00kXHq3qqpBCQXq0AQAAAMANCNo2CNb0Vnt9HiWl+dXv9PbRfVl5KVr94WZZpiXTtOTxGA5VCQAAAACIB4K2DWoPHa8or9a65UWSpDbdmqnwm5Lo/dlmyJTH43WsTgAAAADA4eMebRtEg7bPo9LtFVo8b60Wz1urrRtK9PZTq1W5q1rSnvW2AQAAAABNF0HbBsFa92jXxeMNt4dCTIgGAAAAAE0dQdsGoVr3aNfF6w3flx2qpkcbAAAAAJo6grYNQtWmPD5DRj0TnRm+cLtJjzYAAAAANHlMhmaDYLUpX01vts/vUfNWKZJhKJDsU06HdPkD4R8Da2kDAAAAQNNH0LZBqNqUt+b+7Ga5Kbrw1gHRfe16ttDWDSWSFJ19HAAAAADQdDF03Aah4J6gXRdPzdBxerQBAAAAoOmjR9sGoWpTvoTw+tjbNpbq33d+Ikk67dLuWvjkap1xZS9JUnVFyLEaAQAAAADxQdC2QTBo1jvjuCQFUsI/hl2lVXaVBAAA6mFZlkyzUqZZoZBZITMU/t40K2VZQZlmUJYVeYRkWdUyrZAss7pmOyjTCn8vq+Gj1QzDJ8PwyvD4ZBg+eQyfDCMh2uaJfG/4ZHgS5DF88ngC8ngS5fEmyutJDH/v4dc8AHAK/wLboPY92nVJCHjl9Xm0m6ANAMBBs6yQgsFyhUJlCobKFQqWKxQqVzBUVvP9rpr2mv01xwRDZTJDNSE6GqQr92yblXGozqgJx/uuOGJZliwrVBOW995vybJMWVbw8CswfDWBOyCvNxy+vZ5EebzhUO71JsvnTZHXlyKvN6Xm+9Tw15p2nzc1vK/mGK83VR6Pv873BQDYg6Btg+rKkBL89QdtwzCUlJ6gXSUEbQDAz4dlmQqFylVdXaxgsETVwfDXYHXJXtule76v2V8dLJFp7t7v+Q0joVZITJbXmxoNln5/8z0hNNoTvHevcCD8qLUdDq+1epRrPTyemp5oI0GGUf9/90tKv9Inn5yjY499QelpPev5bKyYHvNwL3ntXvNqmZH9ZpVCZqXMUMU+vfDh7yPtNT3zNX9kCIV2q6Jyi0LlNX+cCJUrGCw/iM/VJ683VQm+dPkS0uXzhR+1txN8GTXtaUpIyIge4/Oly+tNPPDFAQBNHEHbBmU7KpTeImm/xySn+bWboA0AaGIsy1IoVKbq6p3hR7BYwerimq/htmCwNCZEVwdLFAwWKxgslVT3ihvhgBwJb+GglpzUbk9gS0gP97b6Umr1wO7pjfX5UuTxBOz9MOLIMMI94lKCJHuDqWWFwqMBgjXhu2ZUQCSIh7+WRf/wUV3zs6ys3BL9o0kwWFJvr7zH468VvDOU4Eur+RlnRH/eCb4M+RLSleDLrNkOH+v1JtObDqBJIGjboGR7hVp1aSZJapaXrAtvPU4ypJTMgEbPOF6pzQJKTvdrV2m1w5UCAH6uTLMqHIBrh+WY4LwzHKKqd6o6WFIToItVXV0sqa77kD1KSMgMh+WaoJyQkKXk5A57AnStEJ1Qq8fT50t39f3FKcmdVXD8IgUCeU6XUifD8MrnS5PPl3bI5wjf57675poqqRXKSxSMhvHS6PVVWVmk8vKvo0E9FCqvpzZfrWsqo9YfYuoK6TXtNdeY15tCSAdgG/f+V+wIEQqaKi+uVFrz8F+jfQleNW+VGt2fmJwgSUpK82v75rr/owIAwMEI37Ncq6cx2rMc28NcO1CHA3P9wcbjSVJCNLxkKiEhQymBnJq2mt7GhMya/eG2hIQMeb2phJp6eL0BJSe3d7qMRmUYRs1w/WQpkNvg55tmdcx1HPmjTrQHvbo4OjIiHNLXRdtCobJ6avLtGeYe/QNPxp4e8+h1TEgHcPgI2o2s7KcKyVI0aJf8uFsfPPe1JKnPqW20+oPNGnB2RyWl+7X7Pz85WSoAwGGmWanqYKlCwdI9PYGh0lo9gqU1j0hvYGx7fQFDMqLhIhKO/f4WSk45qlaIjoTkSC90Zs1Q3djh17t3b9I339yv1q1+q6SkNo3/obhQ5DPs2HEin2E9PJ4E+f3N5fc3r/eYyOfYudvNMZ+jaQZr/n9RfOCQXrVN5bvWxyGkZ0TDeWxQT+ePTsDPlKNB++GHH9bdd9+twsJC9enTR3/961913HHHOVlS3JVsr5AkpWWFg3blrqA2fPGjJOmoftn678db1XdIWyWn+bWrtEqWZfGPMQA0EaYZVCi0a59Zr2PuZY3e37qr1szXe2bBDkafUybTrH+ujvBQ3vSYr0lJrWPaEnzp8vrSaoZhp9X8op8pny9tv5NzNUR1sFiFW19Sm7aXKkmExEPBZxgf9X2OHo9Pfn+W/P6sBp8zJqTXDHMPh/NIW3HNPAPFqqr6UeW7vokG+fpDurdmxvaUmBnc98z4niqfNzl2pvfacw/EzPqeUjMpH78rAkc6x4L2v/71L02aNEmPPvqoBgwYoNmzZ2vYsGFau3atsrOznSor7kq3V0iGlNZs/xOZpGQGFKo2VfZTZTSUAwAOjmWZMs1qWVaVTHPPw7Kq69iuWcYptLtmpubdCoV2R5d2CoV211r6abdCocixkdmad9ccVyHL2v/cGuHZmev4hdqXoiR/871+oU6OuUc5Gp4TIsNW4xOUAdTvcEN6KFRa6/aMPcE8/Me4XTFLzIVC5ara/dOeP9bV/NHNNCsO8EpGzfJsSTUz5ifVLN+WtGcGfW+SvJ6kmhnzk6LHeD1JNc+NzKrvl+Hxy+Pxy2PUfPX4ZdT6fk+b99A+VOBnyrGgfd999+nyyy/X7373O0nSo48+qtdee01PPvmk/vjHPzpVVlxZpqW1HxWqWU7yftfRlqQ23bPkT/Rqxdsb9cvzO7v6L5WWVfcMs3sddbBni+Nrxv91D76+gzydY/XZ/zM7WEf+zzb+rxs+pynLMuvYNmu2LVkyJcuUJavmq1lzsVm1jjVr6jT3OqdZ6xx7zhV5vfB2qGaZoeCeZYZqfzX32o75um+baVXvu8+slmlVhUO0WVXzfXg7HJxr9h0g8NbHMLzhX04jv6RG1hr27vmFNcGXKc8+7TVfPYny+pLrnPU63PPEesPAz4XH45PH00wJCc0O6zx7RsrsPSqmXMHQrj1/8Iv5uucPgqHQblVVbotpixwb/gPhoa1yE166bt8A7jEiYT2h1nJ34eXvPLW3PbX3hZfI8+x1fO1j9t4nw5Ahj2R4ZMgT/uNj7e+jX43wHwUMjwwZNV+9Nccbe76XUdPmrXVc7XNF/u02oo/Yf88NqWbbqHVMzYclI/pc1XquUUdbrfPFtMUeH27eu23vc9b3s+O/Q04wrIP/LTBuqqqqlJycrOeff14jR46Mto8dO1Y7d+7USy+9FHN8ZWWlKisro9vFxcVq27atNm3apPT0dLvKbrAvlz6v7bv/LMNb6/80liUzFP7IDa8hK2TV7A8H87j8NIz4/kiNOJ8PgDtZpkeWZUiWV5bpkeSVZXlkWV7J9Ei19lmWV7I8skxvzfdG+DlW+DnSnuMs0yvL9IUfId+e761Ie4KskFcya+0zfbWel7DXtk9W0C/TTJAspippqEDGJrU5aZY2vX+TKosZ9nwo+Azjg8/xEBkheTzVMjxBGd6ar56gDE9Ihqdahjcow6jdFpS81dHvjchza297a443LMkww/uMkKRa3xvWnu89IRmGKRkhGZ7wPnnM8OsaZvgcNfsMT12rGsAOlnUYAf0QnusPnqeBp91y6K9pg5KSErVp00Y7d+5URkbGfo915DeMH3/8UaFQSDk5OTHtOTk5+s9//rPP8TNnztT06dP3aW/Thn9UAQCw3T2S9Aenq2ja+Azjg88RcJFZNY8jX2lp6ZEZtBtqypQpmjRpUnTbNE3t2LFDzZs3P+KGQkT+ynGk97aj6eNag1241mAHrjPYhWsNduFacx/LslRaWqr8/PwDHutI0G7RooW8Xq+2bt0a075161bl5u671mIgEFAgELu8SGZmZmOWeNjS09P5PxRswbUGu3CtwQ5cZ7AL1xrswrXmLgfqyY5wZApTv9+vfv36adGiRdE20zS1aNEiFRQUOFESAAAAAABx4djQ8UmTJmns2LE69thjddxxx2n27NkqLy+PzkIOAAAAAEBT5FjQvuCCC7Rt2zbddtttKiwsVN++ffXmm2/uM0FaUxMIBHT77bfvM9QdiDeuNdiFaw124DqDXbjWYBeutZ83R5b3AgAAAADArRy5RxsAAAAAALciaAMAAAAAEEcEbQAAAAAA4oigDQAAAABAHBG0G2DOnDnq3bt3dNH5goICvfHGG/UeP3fuXBmGEfNITEy0sWI0VQ291iRp586dGjdunPLy8hQIBHT00Ufr9ddft6liNFUNvdYGDx68z79rhmFoxIgRNlaNpuZQ/k2bPXu2unTpoqSkJLVp00YTJ05URUWFTRWjqWrotVZdXa0ZM2aoU6dOSkxMVJ8+ffTmm2/aWDHc4q677pJhGLruuuv2e9xzzz2nrl27KjExUb169eJ3NRdzbHmvpqh169a666671LlzZ1mWpaefflrnnHOOPv/8c/Xo0aPO56Snp2vt2rXRbcMw7CoXTVhDr7Wqqiqddtppys7O1vPPP69WrVrpu+++U2Zmpv3Fo0lp6LX2wgsvqKqqKrq9fft29enTR+eff76dZaOJaeh1Nm/ePP3xj3/Uk08+qRNOOEH//e9/dckll8gwDN13330OvAM0FQ291qZOnar//d//1d/+9jd17dpVCxYs0K9+9SstWbJExxxzjAPvAE3RJ598oscee0y9e/fe73FLlizRRRddpJkzZ+rMM8/UvHnzNHLkSH322Wfq2bOnTdXCNhYOS7Nmzay///3vde576qmnrIyMDHsLgmvt71qbM2eO1bFjR6uqqsrmquBG+7vW9nb//fdbaWlpVllZWSNXBbfZ33U2btw465RTTolpmzRpkjVw4EA7SoPL7O9ay8vLsx566KGYtnPPPdcaPXq0HaXBBUpLS63OnTtbCxcutAYNGmRNmDCh3mN//etfWyNGjIhpGzBggHXllVc2cpVwAkPHD1EoFNKzzz6r8vJyFRQU1HtcWVmZ2rVrpzZt2uicc87RqlWrbKwSbnAw19rLL7+sgoICjRs3Tjk5OerZs6fuvPNOhUIhm6tFU3aw/67V9sQTT+jCCy9USkpKI1cHtziY6+yEE07Q8uXL9fHHH0uSvvnmG73++usaPny4naWiiTuYa62ysnKf2/qSkpL0wQcf2FEiXGDcuHEaMWKEhgwZcsBjly5dus9xw4YN09KlSxurPDiIoeMNtHLlShUUFKiiokKpqamaP3++unfvXuexXbp00ZNPPqnevXuruLhY99xzj0444QStWrVKrVu3trlyNDUNuda++eYbvfPOOxo9erRef/11rVu3Tn/4wx9UXV2t22+/3ebK0dQ05Fqr7eOPP9ZXX32lJ554woYq0dQ15Dr7zW9+ox9//FG//OUvZVmWgsGgrrrqKt188802V42mqCHX2rBhw3TffffppJNOUqdOnbRo0SK98MIL/KEaB+XZZ5/VZ599pk8++eSgji8sLFROTk5MW05OjgoLCxujPDiMHu0G6tKli1asWKFly5bp6quv1tixY7V69eo6jy0oKNCYMWPUt29fDRo0SC+88IJatmypxx57zOaq0RQ15FozTVPZ2dl6/PHH1a9fP11wwQW65ZZb9Oijj9pcNZqihlxrtT3xxBPq1auXjjvuOBuqRFPXkOvsvffe05133qlHHnlEn332mV544QW99tpruuOOO2yuGk1RQ661Bx54QJ07d1bXrl3l9/s1fvx4/e53v5PHw6/I2L9NmzZpwoQJeuaZZ5jsGHUyLMuynC6iKRsyZIg6dep00OH5/PPPl8/n0z//+c9Grgxus79rbdCgQUpISNDbb78dbXvjjTc0fPhwVVZWyu/321kqmriD+XetvLxc+fn5mjFjhiZMmGBjdXCL/V1nJ554oo4//njdfffd0bb//d//1RVXXKGysjJCEBrkYP5Nq6io0Pbt25Wfn68//vGPevXVV7ndD/v14osv6le/+pW8Xm+0LRQKyTAMeTweVVZWxuyTpLZt22rSpEkxM5PffvvtevHFF/XFF1/YVTpswn+pDpNpmqqsrDyoY0OhkFauXKm8vLxGrgputL9rbeDAgVq3bp1M04y2/fe//1VeXh4hGw12MP+uPffcc6qsrNRvf/tbm6qC2+zvOtu1a9c+YTryCyv9A2iog/k3LTExUa1atVIwGNT//d//6ZxzzrGpOjRVp556qlauXKkVK1ZEH8cee6xGjx6tFStW7BOypfBo10WLFsW0LVy48KDnRUHTwj3aDTBlyhSdccYZatu2rUpLSzVv3jy99957WrBggSRpzJgxatWqlWbOnClJmjFjho4//ngdddRR2rlzp+6++2599913+v3vf+/k20AT0NBr7eqrr9ZDDz2kCRMm6JprrtHXX3+tO++8U9dee62TbwNNQEOvtYgnnnhCI0eOVPPmzZ0oG01MQ6+zs846S/fdd5+OOeYYDRgwQOvWrdOtt96qs846q85fXoGIhl5ry5Yt0w8//KC+ffvqhx9+0LRp02Sapm666SYn3waagLS0tH2W5EpJSVHz5s2j7XtfbxMmTNCgQYN07733asSIEXr22Wf16aef6vHHH7e9fjQ+gnYDFBUVacyYMdqyZYsyMjLUu3dvLViwQKeddpokaePGjTF/gf/pp590+eWXq7CwUM2aNVO/fv20ZMmSg5pkCD9vDb3W2rRpowULFmjixInq3bu3WrVqpQkTJmjy5MlOvQU0EQ291iRp7dq1+uCDD/TWW285UTKaoIZeZ1OnTpVhGJo6dap++OEHtWzZUmeddZb+/Oc/O/UW0EQ09FqrqKjQ1KlT9c033yg1NVXDhw/X//zP/ygzM9OhdwA32ft6O+GEEzRv3jxNnTpVN998szp37qwXX3yRNbRdinu0AQAAAACII+7RBgAAAAAgjgjaAAAAAADEEUEbAAAAAIA4ImgDAAAAABBHBG0AAAAAAOKIoA0AAAAAQBwRtAEAAAAAiCOCNgAAAAAAcUTQBgDgZ2Dw4MG67rrrnC4DAICfBYI2AAAAAABxRNAGAAAAACCOCNoAAPwMvfbaa8rIyNAzzzzjdCkAALiOz+kCAACAvebNm6errrpK8+bN05lnnul0OQAAuA492gAA/Iw8/PDD+sMf/qBXXnmFkA0AQCOhRxsAgJ+J559/XkVFRfrwww/Vv39/p8sBAMC16NEGAOBn4phjjlHLli315JNPyrIsp8sBAMC1CNoAAPxMdOrUSe+++65eeuklXXPNNU6XAwCAazF0HACAn5Gjjz5a7777rgYPHiyfz6fZs2c7XRIAAK5D0AYA4GemS5cueueddzR48GB5vV7de++9TpcEAICrGBY3aQEAAAAAEDfcow0AAAAAQBwRtAEAAAAAiCOCNgAAAAAAcUTQBgAAAAAgjgjaAAAAAADEEUEbAAAAAIA4ImgDAAAAABBHBG0AAAAAAOKIoA0AAAAAQBwRtAEAAAAAiCOCNgAAAAAAcfT/AfSCrWb5kd/1AAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 1200x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot gaussiane\n",
    "\n",
    "# Parametri gaussiane\n",
    "# (media, deviazione standard, colore, nome)\n",
    "gaussiane = [\n",
    "    # (AC, uAC, 1, 'calibro'),\n",
    "    # (AS2, uAS2, 2, 'sonar statico'),\n",
    "    (AD, uAD, 4, 'sonar dinamico'),\n",
    "    (ACr, uACr, 8, 'cronometro')\n",
    "]\n",
    "\n",
    "# Creazione figura\n",
    "plt.figure(figsize=(12, 7))\n",
    "\n",
    "# Creazione asse x\n",
    "xMin = float('inf')\n",
    "xMax = float('-inf')\n",
    "for mu, sigma, _, _ in gaussiane:\n",
    "    minimoLocale = mu - 4 * sigma\n",
    "    massimoLocale = mu + 4 * sigma\n",
    "    \n",
    "    if minimoLocale < xMin:\n",
    "        xMin = minimoLocale\n",
    "    \n",
    "    if massimoLocale > xMax:\n",
    "        xMax = massimoLocale\n",
    "x = np.linspace(xMin, xMax, 1000)\n",
    "\n",
    "# Ciclo gaussiane\n",
    "for mu, sigma, colore, etichetta in gaussiane:\n",
    "    \n",
    "    y = stats.norm.pdf(x, mu, sigma)\n",
    "    plt.plot(x, y, color=sns.color_palette()[colore], linewidth=1, label=etichetta)\n",
    "    \n",
    "    puntiLinee = [mu - sigma, mu, mu + sigma]\n",
    "    for px in puntiLinee:\n",
    "        py = stats.norm.pdf(px, mu, sigma) \n",
    "        plt.vlines(x=px, ymin=0, ymax=py, colors=sns.color_palette()[colore], linestyles='dashed', linewidth=1)\n",
    "        \n",
    "# Dettagli estetici finali\n",
    "plt.ylim(bottom=0)\n",
    "plt.title('Confronto dati')\n",
    "plt.xlabel('k')\n",
    "plt.legend()\n",
    "\n",
    "# Mostriamo il grafico\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "d4af85a1",
   "metadata": {},
   "outputs": [],
   "source": [
    "def p_t_student_compatibilita(x, ux, gx, y, uy, gy):\n",
    "  GdL = gx + gy - 2\n",
    "  s2 = ( (gx - 1) * ux**2  +  (gy - 1) * uy**2 ) / GdL\n",
    "  sigma2 = ( s2 / gx )  + ( s2 / gy )\n",
    "  t = abs(x - y) / np.sqrt( sigma2 )\n",
    "\n",
    "  return {\"p\": 2 * (1 - stats.t.cdf(abs(t), df=GdL)), \"t\": t}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "57de948b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Compatibilità: Calibro vs Sonar statico\n",
      "Sigma             t    p-value\n",
      "------------------------------\n",
      "1σ           6.8052     0.0065\n",
      "2σ           3.4026     0.0424\n",
      "3σ           2.2684     0.1081\n",
      "\n",
      "\n",
      "Compatibilità: Calibro vs Sonar statico corretto\n",
      "Sigma             t    p-value\n",
      "------------------------------\n",
      "1σ           6.4288     0.0076\n",
      "2σ           3.2144     0.0488\n",
      "3σ           2.1429     0.1215\n",
      "\n",
      "\n",
      "Compatibilità: Calibro corretto vs Sonar statico corretto\n",
      "Sigma             t    p-value\n",
      "------------------------------\n",
      "1σ           4.5101     0.0458\n",
      "2σ           2.2551     0.1528\n",
      "3σ           1.5034     0.2716\n",
      "\n",
      "\n",
      "Compatibilità: Calibro vs Sonar dinamico\n",
      "Sigma             t    p-value\n",
      "------------------------------\n",
      "1σ         159.7965     0.0000\n",
      "2σ          79.8982     0.0000\n",
      "3σ          53.2655     0.0000\n",
      "\n",
      "\n",
      "Compatibilità: Calibro corretto vs Sonar dinamico\n",
      "Sigma             t    p-value\n",
      "------------------------------\n",
      "1σ         273.1973     0.0000\n",
      "2σ         136.5986     0.0001\n",
      "3σ          91.0658     0.0001\n",
      "\n",
      "\n",
      "Compatibilità: Sonar Dinamico vs Sonar statico\n",
      "Sigma             t    p-value\n",
      "------------------------------\n",
      "1σ         171.4131     0.0000\n",
      "2σ          85.7065     0.0000\n",
      "3σ          57.1377     0.0000\n",
      "\n",
      "\n",
      "Compatibilità: Sonar Dinamico vs cronometro\n",
      "Sigma             t    p-value\n",
      "------------------------------\n",
      "1σ          10.9307     0.0004\n",
      "2σ           5.4654     0.0055\n",
      "3σ           3.6436     0.0219\n"
     ]
    }
   ],
   "source": [
    "# Ringraziate Cloude per questo incredibile print\n",
    "print(\"Compatibilità: Calibro vs Sonar statico\")\n",
    "print(f\"{'Sigma':<10} {'t':>8} {'p-value':>10}\")\n",
    "print(\"-\" * 30)\n",
    "for n in [1, 2, 3]:\n",
    "    res = p_t_student_compatibilita(AC, uAC*n, len(dfCalibro)-2,\n",
    "                                    AS,  uAS*n, len(dfSonar)-2)\n",
    "    print(f\"{n}σ         {res['t']:>8.4f} {res['p']:>10.4f}\")\n",
    "\n",
    "print(\"\\n\\nCompatibilità: Calibro vs Sonar statico corretto\")\n",
    "print(f\"{'Sigma':<10} {'t':>8} {'p-value':>10}\")\n",
    "print(\"-\" * 30)\n",
    "for n in [1, 2, 3]:\n",
    "    res = p_t_student_compatibilita(AC, uAC*n, len(dfCalibro)-2,\n",
    "                                    AS2,  uAS2*n, len(dfSonar)-2)\n",
    "    print(f\"{n}σ         {res['t']:>8.4f} {res['p']:>10.4f}\")\n",
    "\n",
    "print(\"\\n\\nCompatibilità: Calibro corretto vs Sonar statico corretto\")\n",
    "print(f\"{'Sigma':<10} {'t':>8} {'p-value':>10}\")\n",
    "print(\"-\" * 30)\n",
    "for n in [1, 2, 3]:\n",
    "    res = p_t_student_compatibilita(AC2, uAC2*n, len(dfCalibro_senza1)-2,\n",
    "                                    AS2,  uAS2*n, len(dfSonar)-2)\n",
    "    print(f\"{n}σ         {res['t']:>8.4f} {res['p']:>10.4f}\")\n",
    "\n",
    "print(\"\\n\\nCompatibilità: Calibro vs Sonar dinamico\")\n",
    "print(f\"{'Sigma':<10} {'t':>8} {'p-value':>10}\")\n",
    "print(\"-\" * 30)\n",
    "for n in [1, 2, 3]:\n",
    "    res = p_t_student_compatibilita(AC, uAC*n, len(dfCalibro)-2,\n",
    "                                    AD,  uAD*n,  len(dfSonar)-2)\n",
    "    print(f\"{n}σ         {res['t']:>8.4f} {res['p']:>10.4f}\")\n",
    "\n",
    "print(\"\\n\\nCompatibilità: Calibro corretto vs Sonar dinamico\")\n",
    "print(f\"{'Sigma':<10} {'t':>8} {'p-value':>10}\")\n",
    "print(\"-\" * 30)\n",
    "for n in [1, 2, 3]:\n",
    "    res = p_t_student_compatibilita(AC2, uAC2*n, len(dfCalibro_senza1)-2,\n",
    "                                    AD,  uAD*n,  len(dfSonar)-2)\n",
    "    print(f\"{n}σ         {res['t']:>8.4f} {res['p']:>10.4f}\")\n",
    "\n",
    "print(\"\\n\\nCompatibilità: Sonar Dinamico vs Sonar statico\")\n",
    "print(f\"{'Sigma':<10} {'t':>8} {'p-value':>10}\")\n",
    "print(\"-\" * 30)\n",
    "for n in [1, 2, 3]:\n",
    "    res = p_t_student_compatibilita(AD,  uAD*n,  len(dfSonar)-2,\n",
    "                                    AS, uAS*n, len(dfSonar)-2)\n",
    "    print(f\"{n}σ         {res['t']:>8.4f} {res['p']:>10.4f}\")\n",
    "\n",
    "print(\"\\n\\nCompatibilità: Sonar Dinamico vs cronometro\")\n",
    "print(f\"{'Sigma':<10} {'t':>8} {'p-value':>10}\")\n",
    "print(\"-\" * 30)\n",
    "for n in [1, 2, 3]:\n",
    "    res = p_t_student_compatibilita(AD,  uAD*n,  len(dfSonar)-2,\n",
    "                                    ACr, uACr*n, len(dfSonar)-2)\n",
    "    print(f\"{n}σ         {res['t']:>8.4f} {res['p']:>10.4f}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b66ccc91",
   "metadata": {},
   "source": [
    "# Note finali\n",
    "SI VEDE LA RISONANZA E LA DEFORMAZIONE DELLE MASSE EQUIVALENTI (NON È LINEARE)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "base",
   "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": "3.13.11"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}