Lab1/mollaDefinitiva/molla-1/molla1.ipynb

{
 "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": 1,
   "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": 2,
   "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": 3,
   "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": 4,
   "id": "e649eddc",
   "metadata": {},
   "outputs": [],
   "source": [
    "dfCalibro = pd.read_csv(r'molla1Calibro.csv')\n",
    "\n",
    "# Costanti strumentali\n",
    "ERR_CALIBRO = 0.02 / np.sqrt(24)\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": 5,
   "id": "42ff21d6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "1cc893b29be14f7ca0499d657f9f656d",
       "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(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": 6,
   "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": 7,
   "id": "5d7ca0a0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Residuo:\n",
      "  r = x + B/A - y/A\n",
      "\n",
      "Formula LaTeX:\n",
      "  r       = x + \\frac{B}{A} - \\frac{y}{A}\n",
      "  sigma_r = \\sqrt{\\frac{A^{4} \\sigma_{x}^{2} + A^{2} \\left(\\sigma_{B}^{2} + \\sigma_{y}^{2}\\right) - 2 A cov_{AB} \\left(B - y\\right) + \\sigma_{A}^{2} \\left(B - y\\right)^{2}}{A^{4}}}\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 = x - (y / A - B / A)\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": 8,
   "id": "cd68b201",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ax + B : \n",
      "AC      = 23.9432 ± 0.0422\n",
      "BC      = 2719.8356 ± 2.8402\n",
      "cov_ABC = 0.118646\n",
      "chi²    = 56.2014\n",
      "P(chi², ∞)= 0.0000\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": 9,
   "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": "markdown",
   "id": "5de53d0e",
   "metadata": {},
   "source": [
    "### Grafici calibro"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "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": 11,
   "id": "831a4ac6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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NmuS4Xzz00ENYsGABfv75Z7Rq1QpBQUH46aefsHXrVnz77bfYsGEDVq9ejf/7v//Djz/+qNo7QVW3n6ofWOtymy60a9euS34b1OTk5Dq9/eqdd96Jt99+G6Ghobj99tsb5G2V8/PzkZycjLCwMDz77LNo27YtAgMDsX//fjz++ON1fqejumrevDny8vIu6bJqfL9JuPterau8vDxERUWpMA1Rw+DCgojg6+uLBQsWYMiQIXjzzTcxe/ZstGnTBsC539a6e0eWC0VGRmLy5MmYPHkyioqKMGjQIMyfP7/ahUXr1q1ht9sdv3mscvToUZdtmzVr5vYdm+r6m9fzr3vz5s0oKipy+qHxwuuua4OL+eqrrxAYGIgffvjB6ejQhx9+KNpv27Zt8euvv2Lo0KE1/nazqnlaWprTb+ePHTtWp+tSFAVJSUmO39TWpGvXrujatSuefvpp7Nq1C9dccw2WL1+O559/HsC5t/UcOnQohg4disWLF+PFF1/EU089ha1bt7pt3rp1awDu7yd//PEHoqKiXH6jrPZtOl/37t2d3v2sLtw9xacmd955J+bOnYuMjAx8+umn1W7XunVrHDx4EHa73WnxUfW0paqGtbFt2zbk5ORg7dq1GDRokOP0tLS0Os1+qTp16oTPP/8cBQUFjiNdwLl/sz179qC8vLzaI0r18f2Wnp7uckTszz//BAC371x3vvPvuxcebTp69Kjbf5e0tDR07979kuclamh8jQURATj3VqZ9+vTB0qVLUVpaipiYGAwePBjvvPMOMjIyXLbPzs52/DknJ8fpvJCQELRr187lrU7Pd9111wEAXn/9dafTly5d6rJt27ZtUVBQgIMHDzpOy8jIwNdff12r23ah66+/HhUVFXj77bcdp1VWVuKNN95w2q4uDWrD19cXBoPB6UjLyZMnnd616VKMGzcORqMR7777rst5VqvV8fkTVUdd3nrrLadtLrzdNRk9ejR8fX3xzDPPuDxFRVEUx32hsLAQFRUVTud37doVPj4+jvuFu6cQ9ejRAwCqve+0aNECPXr0wMcff+y02Dx06BB+/PFHXH/99bW+LXW9Te40a9YMw4YNu6SvXr161WnOtm3bYunSpViwYAH69OlT7XbXX389MjMzsXr1asdpFRUVeOONNxASEoLk5ORaX2fVEZzzu5SVlbnch+pLv379oCiKy+sXxowZA7PZjDfffNPlMlWz1sf3W0VFBd555x3H38vKyvDOO+8gOjr6ov+evXv3RkxMDJYvX+50//7+++9x5MgRl3epKigowPHjx9G/f/9LnpeoofGIBRE5PProoxg7diw++ugjTJs2DcuWLcOAAQPQtWtX3HfffWjTpg2ysrKwe/dunD17Fr/++isAoEuXLhg8eDB69eqFyMhI7Nu3D19++SWmT59e7XX16NED48ePx1tvvYWCggL0798fmzdvdvvb8zvuuAOPP/44br31Vjz00EMoKSnB22+/jQ4dOlzSizBvuukmXHPNNZg9ezZOnjyJLl26YO3atW6fL17bBrVxww03YPHixRg5ciTuvPNOmEwmLFu2DO3atXNaNNXV3XffjS+++ALTpk3D1q1bcc0116CyshJ//PEHvvjiC/zwww/o3bs3evXqhTFjxmDp0qXIyclxvN1s1W9ca/Nc7rZt2+L555/HE088gZMnT2LUqFEIDQ1FWloavv76a0ydOhWzZs3Cli1bMH36dIwdOxYdOnRARUUFPv30U/j6+mLMmDEAzn36+08//YQbbrgBrVu3hslkwltvvYVWrVo5fWbGhV555RVcd9116NevH6ZMmeJ4u9nw8HCnz+KordreJk9Qm7eKnTp1Kt555x1MmjQJKSkpSExMxJdffomdO3di6dKlCA0NrfX19e/fH82aNcPEiRPx0EMPwWAw4NNPP3X7uofqvPnmm8jPz0d6ejoA4D//+Y/j82oefPBBpyMRFxowYACaN2+OTZs2Of2W/5577sEnn3yCmTNnYu/evRg4cCCKi4uxadMm/OMf/8Att9xSL99vLVu2xMKFC3Hy5El06NABq1evRmpqKlasWHHRD+Zs0qQJFi5ciMmTJyM5ORnjx493vN1sYmKiy1vKbtq0yfHW2ES60dBvQ0VE2qp6O8lffvnF5bzKykqlbdu2Stu2bZWKigpFURTl+PHjyj333KPExcUpTZo0UeLj45Ubb7xR+fLLLx2Xe/7555U+ffooERERSlBQkNKpUyflhRdecLz9oqK4f2tYq9WqPPTQQ0rz5s2V4OBg5aabblLOnDnj8haYiqIoP/74o3LFFVco/v7+SseOHZXPPvvskt9uVlEUJScnR7n77ruVsLAwJTw8XLn77rsdb5F64dth1qZBbd9u9v3331fat2+vBAQEKJ06dVI+/PBDt7fDneTkZOXyyy93e15ZWZmycOFC5fLLL1cCAgKUZs2aKb169VKeeeYZpaCgwLFdcXGx8sADDyiRkZFKSEiIMmrUKOXo0aMKAOWll15ybHf+W52689VXXykDBgxQgoODleDgYKVTp07KAw88oBw9elRRFEU5ceKE8re//U1p27atEhgYqERGRipDhgxRNm3a5NjH5s2blVtuuUVp2bKl4u/vr7Rs2VIZP3688ueffzq2cfd2s4qiKJs2bVKuueYaJSgoSAkLC1Nuuukm5ffff3faprrb4O4tVWtzmxraxf4NquCCt5tVFEXJyspSJk+erERFRSn+/v5K165d3b7N64Xfa+7a7Ny5U7n66quVoKAgpWXLlspjjz2m/PDDDy739+q0bt1aAeD268J/A3ceeughp7farVJSUqI89dRTSlJSktKkSRMlLi5Oue2225Tjx487tqnt91tt32728ssvV/bt26f069dPCQwMVFq3bq28+eabTvuqumx1b7W8evVqpWfPnkpAQIASGRmpTJgwQTl79qzLdrfffrsyYMCAi/Yh8iQGRanDrx2IiMjrpKamomfPnvjss88wYcIErcchcnLixAl06tQJ33//PYYOHar1OA0iMzMTSUlJWLVqFY9YkK7wNRZERI2I1Wp1OW3p0qXw8fFxenEukado06YNpkyZgpdeeknrURrM0qVL0bVrVy4qSHd4xIKIqBF55plnkJKSgiFDhsDPzw/ff/89vv/+e8fz8omIiC4VFxZERI3Ixo0b8cwzz+D3339HUVERLrvsMtx999146qmnLvphY0RERDXhwoKIiIiIiMT4GgsiIiIiIhLjwoKIiIiIiMS8dmGxbNkyJCYmIjAwEH379sXevXur3fbdd9/FwIED0axZM8enqF64vaIomDt3Llq0aIGgoCAMGzYMf/31V63nURQFhYWFdfpQISIiIiIivfDKhcXq1asxc+ZMzJs3D/v370f37t0xYsQImEwmt9tv27YN48ePx9atW7F7924kJCRg+PDhMBqNjm1efvllvP7661i+fDn27NmD4OBgjBgxAqWlpbWayWKxIDw8HBaLRZXb6EnKysq0HkHX2E+G/eTYUIb9ZNhPhv1k2E9dXvni7b59++Kqq67Cm2++CQCw2+1ISEjAgw8+iNmzZ1/08pWVlWjWrBnefPNN3HPPPVAUBS1btsQjjzyCWbNmAQAKCgoQGxuLjz76CHfcccdF91lYWIjw8HAUFBQgLCxMdgM9jNVqRVBQkNZj6Bb7ybCfHBvKsJ8M+8mwnwz7qcvrjliUlZUhJSUFw4YNc5zm4+ODYcOGYffu3bXaR0lJCcrLyxEZGQkASEtLQ2ZmptM+w8PD0bdv31rv05uVlJRoPYKusZ8M+8mxoQz7ybCfDPvJsJ+6vO5Ny81mMyorKxEbG+t0emxsLP74449a7ePxxx9Hy5YtHQuJzMxMxz4u3GfVeRey2Wyw2WyOvxcWFtb6NugN3/tehv1k2E+ODWXYT4b9ZNhPhv3U5XVHLKReeuklrFq1Cl9//TUCAwMveT8LFixAeHi44yshIQEAUFpaivT0dNjtdsdrOIxGI8rKymAymVBUVIT8/Hzk5ubCarUiMzMTFRUVTtuWl5cjMzMTJSUlyM3NRV5eHoqLi5GVlYXy8nKnbSsrK5Geng6r1YqcnBwUFBTAYrEgOzsbNpvNaVtFUWA0GmGz2ZCdnY3CwkIUFhbCbDbDarVWO3deXp7T3CUlJW7nrqiocJm7qKjI7dx2u/2ic1fNe+HcFosFBQUFyMnJqXbu8vJyZGVloaioCHl5eXWaOz8/H0VFRTCZTCgrK6t2brPZ7Gjobu7z91/d3JWVlW7nLi4udpn7woZVc1ut1lrPXVpa6nbu9PR0l7ltNhtMJpPL3BkZGRed+2L32YyMDKe5LRZLtXObzWaXuatOq+l7zWKxOH2vqTn3+fdZk8nk9nstPT3d7feaFo8RVf929fUYceHc3vYYoShKvT5G1DS3NzxGZGdn1+tjhLu5vekxwsfHR/c/R2j5GJGdna37nyMa4jGitrzuNRZlZWVo2rQpvvzyS4waNcpx+sSJE5Gfn49vvvmm2su++uqreP7557Fp0yb07t3bcfqJEyfQtm1bHDhwAD169HCcnpycjB49euC1115z2Ze7IxYJCQle+RqL7OxsREdHaz2GbrGfDPvJsaEM+8mwnwz7ybCfurzu+I+/vz969eqFzZs3OxYWdrsdmzdvxvTp06u93Msvv4wXXngBP/zwg9OiAgCSkpIQFxeHzZs3OxYWhYWF2LNnD+6//363+wsICEBAQIAqt8nTedtCqaGxnwz7ybGhDPvJsJ+MN/SrrKxEeXm5JtcdEBBQ63f49FZNmjSBr6+vKvvyuoUFAMycORMTJ05E79690adPHyxduhTFxcWYPHkyAOCee+5BfHw8FixYAABYuHAh5s6di5UrVyIxMdHxuomQkBCEhITAYDBgxowZeP7559G+fXskJSVhzpw5aNmypdNRkcbKbDYjPj5e6zF0i/1k2E+ODWXYT4b9ZPTcr+pphPn5+ZrNUFFRwddZAIiIiEBcXBwMBoNoP15Z8vbbb0d2djbmzp2LzMxM9OjRAxs2bHC8+Pr06dPw8fnfy0vefvttlJWV4bbbbnPaz7x58zB//nwAwGOPPYbi4mJMnToV+fn5GDBgADZs2CB6HYa30OsDmqdgPxn2k2NDGfaTYT8ZPferWlTExMSgadOm4h9qqe4URUFJSYnjs95atGgh2p/XvcbCU3nz51gYjUZdP7Bpjf1k2E+ODWXYT4b9ZPTar7KyEn/++SdiYmLQvHlzzeYoKyuDv7+/ZtfvKXJycmAymdChQwfR06L4rlAk1rJlS61H0DX2k2E/OTaUYT8Z9pPRa7+q11Q0bdpU0zmaNGmi6fV7iqp/B+lrXbiwILH09HStR9A19pNhPzk2lGE/GfaT0Xs/ydOfLBYLMjIyqv2yWCwX3YdWLxr3NGo9Dc0rX2NBDSsqKkrrEXSN/WTYT44NZdhPhv1kGnO/lJQUbN++vdrzk5OTMXjw4Br3wRduq4s1SaywsJDvAS3AfjLsJ8eGMuwnw34yjblfr1690LFjRwDn3h1r7dq1GD16tGOxFRISctF9VFZWOr2hj9ZOnjyJpKQkl89OO9+2bdswZMgQ5OXlISIiolb7nTRpEvLz87Fu3TrVZnWHCwsSayyf11Ff2E+G/eTYUIb9ZNhPpjH3Cw0NRWhoqNNpUVFRdXpno0tZVEyaNAkff/wxgHNHPFq1aoWxY8fi2WefFb9baEJCAjIyMlQ/EvXaa6+hId6vyXOWaERERERE1bBYLNi2bZvLayfSzMV4a6cR28qS8NZOI9LMxRe9jNTIkSORkZGBEydOYMmSJXjnnXcwb9488X59fX0RFxen+lO0wsPDa310Q4ILCxIrKyvTegRdYz8Z9pNjQxn2k2E/mcbUr6ioCNu3b0dRUZHjtC/2ncHQRduwMiULJysjsTIlC0MXbcOafWeqvcz57Hb7Jc0SEBCAuLg4JCQkYNSoURg2bBg2btzo2OeCBQuQlJSEoKAgdO/eHV9++aXjsnl5eZgwYQKio6MRFBSE9u3b48MPPwRw7qlQBoMBqampju2/++47dOjQAUFBQRgyZAhOnjzpNMv8+fNdnja1dOlSJCYmOv4+adKkBvlQZz4VisSCg4O1HkHX2E+G/eTYUIb9ZNhPpjH3SzMXY/ZXB2F3PMPHgMr//+fHvzqIqxIjcbEnikk+s6HKoUOHsGvXLrRu3RoAsGDBAnz22WdYvnw52rdvj59++gl33XUXoqOjkZycjDlz5uD333/H999/j6ioKBw7dgxWq9Xtvs+cOYPRo0fjgQcewNSpU7Fv3z488sgj4pnrCxcWJJaXl4egoCCtx9AtvfezWCzV/iYIOPfiuQufA6smvffzBGwow34y7CfTGPuZzWYAwAc7jajpTVLf33YE4zrWvLSoqKi4pA/IW79+PUJCQlBRUQGbzQYfHx+8+eabsNlsePHFF7Fp0yb069cPANCmTRvs2LED77zzDpKTk3H69Gn07NkTvXv3BgCnIwsXevvtt9G2bVssWrQIANCxY0f89ttvWLhwYZ1nbghcWJBYXFyc1iPomt77qfF2fxJ67+cJ2FCG/WTYT6Yx9lu7di0AYEdZEuxKJOBmeaEoCnYc+B1+h9Nq3NelfkDekCFD8Pbbb6O4uBhLliyBn58fxowZg8OHD6OkpATXXnut0/ZlZWXo2bMnAOD+++/HmDFjsH//fgwfPhyjRo1C//793V7PkSNH0LdvX6fTqhYsnogLCxLLyMhAfHy81mPolt77qfF2fxJ67+cJ2FCG/WTYT6Yx9qv6f0zFTiNOp2Q5nv50PoPBgAE9u2B0x56OhYg75eXll3TEIjg4GO3atQMAfPDBB+jevTvef/99XHHFFQCAb7/91uXfpeodvK677jqcOnUK3333HTZu3IihQ4figQcewKuvvlrnOYBz72x14Ts+afXBf1xYkFhje0BTm977qfF2fxJ67+cJ2FCG/WTYT6Yx9qv6f8zfBofh85SsarebMrgzAsoLa9zXpSwqLuTj44Mnn3wSM2fOxJ9//omAgACcPn0aycnJ1V4mOjoaEydOxMSJEzFw4EA8+uijbhcWnTt3xr///W+n037++WeXfWVmZkJRFMcnaJ//4u+GxHeFIjGj0aj1CLrGfjLsJ8eGMuwnw34yjblfUlQwFo7pBh8D4GsADFDgYwB8DMDCMd2QGHXxF7ar9a5aY8eOha+vL9555x3MmjULDz/8MD7++GMcP34c+/fvxxtvvOH47Iu5c+fim2++wbFjx3D48GGsX78enTt3drvfadOm4a+//sKjjz6Ko0ePYuXKlfjoo4+cthk8eDCys7Px8ssv4/jx41i2bBm+//57VW5XXXFhQWKN9RM/1cJ+Muwnx4Yy7CfDfjKNqV9ISAiSk5OdnmI7tncCtjwyGHf2ikWiby4m9IrFlkcGY2zvhGovcz61Pi/Cz88P06dPx8svv4wnnngCc+bMwYIFC9C5c2eMHDkS3377LZKSkgCcO0ryxBNPoFu3bhg0aBB8fX2xatUqt/u97LLL8NVXX2HdunXo3r07li9fjhdffNFpm86dO+Ott97CsmXL0L17d+zduxezZs1S5XbVlUFpiI/hIxQWFiI8PBwFBQUICwvTehxVmUwmxMTEaD2GbnlTv4yMDKxYsQJTp05tsKdCeVM/rbChDPvJsJ+MXvuVlpYiLS0NSUlJ4k+rBi79/z/l5eWX/AJub6LWvwdfY0FiTZs21XoEXWM/GfaTY0MZ9pNhP5nG3O/8tzuvegvaqv8CtXu7cx8fPnlHTVxYkFhFRYXWI+ga+8mwnxwbyrCfDPvJNOZ+7t7u/Px3gKrN253ziTvq4sKCxOx2u9Yj6Br7ybCfHBvKsJ8M+8k05n7nv925O/X9dufkigsLElPjuZGNGfvJsJ8cG8qwnwz7yTTmfu7e7ryuqt6eldTBJ5aRWGFhze8RTTVjPxn2k2NDGfaTYT8Z9pNpzEd86gMXFiRW9QnLdGnYT4b95NhQhv1k2E9G7/20/sFerbeb1Tu1/h1Yk8SysrIa5Sd/qoX9ZNhPjg1l2E+G/WT02s/f3x8+Pj5IT09HdHQ0/P39NXlaUllZmSqfvq1XiqKgrKwM2dnZ8PHxEbfgwoLE9PiA5knYT4b95NhQhv1k2E9Gr/18fHyQlJSEjIwMpKenaz1Oo9e0aVNcdtll4rff5cKCxIxGo24f2DwB+8mwnxwbyrCfDPvJ6Lmfv78/LrvsMlRUVKCyslKTGbKyshAbG6vJdXsKX19f+Pn5qXLEiAsLEmvs35BS7CfDfnJsKMN+Muwno/d+BoMBTZo00ezTr+Pj4/k6CxXxxdskdv6nXFLdsZ8M+8mxoQz7ybCfDPvJsJ+6uLAgsbCwMK1H0DX2k2E/OTaUYT8Z9pNhPxn2UxcXFiRWWlqq9Qi6xn4y7CfHhjLsJ8N+Muwnw37q4sKCxPiplTLsJ8N+cmwow34y7CfDfjLspy4uLEhMqxdceQv2k2E/OTaUYT8Z9pNhPxn2UxcXFiRWXFys9Qi6xn4y7CfHhjLsJ8N+Muwnw37q4sKCxCIjI7UeQdfYT4b95NhQhv1k2E+G/WTYT11cWJCYyWTSegRdYz8Z9pNjQxn2k2E/GfaTYT91cWFBYnr9xE9PwX4y7CfHhjLsJ8N+Muwnw37q4sKCxIxGo9Yj6Br7ybCfHBvKsJ8M+8mwnwz7qYsLCxJr0aKF1iPoGvvJsJ8cG8qwnwz7ybCfDPupiwsLEsvMzNR6BF1jPxn2k2NDGfaTYT8Z9pNhP3VxYUFizZo103oEXfOWfmnmYry+7SS2lSXhqS/24tCphnlBnLf00xIbyrCfDPvJsJ8M+6mLCwsSKykp0XoEXfOGfl/sO4Ohi7Zh9cFcnKyMxNYMX9y8/Bes2Xem3q/bG/ppjQ1l2E+G/WTYT4b91MWFBYn5+flpPYKu6b1fmrkYs786CLsC2BVAgQEKDLArwONfHcRJc/1++JDe+3kCNpRhPxn2k2E/GfZTFxcWJObjw7uRhN77fbHvDAwGg9vzDAYDVtfzUQu99/MEbCjDfjLsJ8N+MuynLq+tuWzZMiQmJiIwMBB9+/bF3r17q9328OHDGDNmDBITE2EwGLB06VKXbebPnw+DweD01alTp3q8BfpRWlqq9Qi6pvd+Z/OsUBTF7XmKouBsnrVer1/v/TwBG8qwnwz7ybCfDPupyysXFqtXr8bMmTMxb9487N+/H927d8eIESOq/XTFkpIStGnTBi+99BLi4uKq3e/ll1+OjIwMx9eOHTvq6yboSlhYmNYj6Jre+7VqFlTjEYtWzYLq9fr13s8TsKEM+8mwnwz7ybCfurxyYbF48WLcd999mDx5Mrp06YLly5ejadOm+OCDD9xuf9VVV+GVV17BHXfcgYCAgGr36+fnh7i4OMdXVFRUfd0EXTGbzVqPoGt67zeud0KNRyxu751Qr9ev936egA1l2E+G/WTYT4b91OV1C4uysjKkpKRg2LBhjtN8fHwwbNgw7N69W7Tvv/76Cy1btkSbNm0wYcIEnD59utptbTYbCgsLnb68VcuWLbUeQdf03i8pKhgLx3SDjwHwMeD/v3RbgY8BWDimGxKjguv1+vXezxOwoQz7ybCfDPvJsJ+6vG5hYTabUVlZidjYWKfTY2NjRR+C0rdvX3z00UfYsGED3n77baSlpWHgwIGwWCxut1+wYAHCw8MdXwkJ535rW1paivT0dNjtdsfHyBuNRpSVlcFkMqGoqAj5+fnIzc2F1WpFZmYmKioqnLYtLy9HZmYmSkpKkJubi7y8PBQXFyMrKwvl5eVO21ZWViI9PR1WqxU5OTkoKCiAxWJBdnY2bDab07aKosBoNMJmsyE7O9uxIDKbzbBardXOfeTIEae5S0pK3M5dUVHhMndRUZHbue12+0Xnrpr3wrktFgsKCgqQk5NT7dzl5eXIyspCUVER8vLy6jR3fn4+ioqKYDKZUFZWVu3cZrPZ0dDd3FWXOXXqVLVzV1ZWup27uLjYZe4LG1bNbbVaaz13aWmp27nT09Nd5rbZbDCZTLBYLBjePgxrp/TAmC7hSPTNxZC4SnxwWyLG9k5wO/fF7rMZGRlOc1sslmrnPnTokMvcZrP5ot9rFovF6XstIyPjor1rO/f591mTyeT2ey09Pd3t95oWjxGHDx+u18eIC+f2tseIM2fO1OtjRE1z6+Ux4vy5L/xeO3ToUL0+Rrib25seI9LT03X/c4SWjxGHDh3S/c8RDfEYUVsGpbrnMOhUeno64uPjsWvXLvTr189x+mOPPYbt27djz549NV4+MTERM2bMwIwZM2rcLj8/H61bt8bixYsxZcoUl/NtNhtsNpvj74WFhUhISEBBQYHXPZ9PUZRqn2NPF+dN/TIyMrBixQpMnToVLVq0aJDr9KZ+WmFDGfaTYT8Z9pNhP3V53RGLqKgo+Pr6Iisry+n0rKysGl+YXVcRERHo0KEDjh075vb8gIAAhIWFOX15q/T0dK1H0DX2k2E/OTaUYT8Z9pNhPxn2U5fXLSz8/f3Rq1cvbN682XGa3W7H5s2bnY5gSBUVFeH48eMN9ltZT8YXscuwnwz7ybGhDPvJsJ8M+8mwn7q8bmEBADNnzsS7776Ljz/+GEeOHMH999+P4uJiTJ48GQBwzz334IknnnBsX1ZWhtTUVKSmpjqe65aamup0NGLWrFnYvn07Tp48iV27duHWW2+Fr68vxo8f3+C3z9N48wvTGwL7ybCfHBvKsJ8M+8mwnwz7qcsrP8f89ttvR3Z2NubOnYvMzEz06NEDGzZscLyg+/Tp006ftJieno6ePXs6/v7qq6/i1VdfRXJyMrZt2wYAOHv2LMaPH4+cnBxER0djwIAB+PnnnxEdHd2gt80TBQYGaj2CrrGfDPvJsaEM+8mwnwz7ybCfurxyYQEA06dPx/Tp092eV7VYqJKYmFjt+/BXWbVqlVqjeR273a71CLrGfjLsJ8eGMuwnw34y7CfDfuryyqdCUcOqqKjQegRdYz8Z9pNjQxn2k2E/GfaTYT91cWFBYk2bNtV6BF1jPxn2k2NDGfaTYT8Z9pNhP3VxYUFieXl5Wo+ga+wnw35ybCjDfjLsJ8N+MuynLi4sSEzNzwdpjNhPhv3k2FCG/WTYT4b9ZNhPXVxYkFhGRobWI+ga+8mwnxwbyrCfDPvJsJ8M+6mLCwsSi4+P13oEXWM/GfaTY0MZ9pNhPxn2k2E/dXFhQWJGo1HrEXSN/WTYT44NZdhPhv1k2E+G/dTFhQWJxcTEaD2CrrGfDPvJsaEM+8mwnwz7ybCfuriwILHc3FytR9A19pNhPzk2lGE/GfaTYT8Z9lMXFxYkFhwcrPUIusZ+Muwnx4Yy7CfDfjLsJ8N+6uLCgsTKy8u1HkHX2E+G/eTYUIb9ZNhPhv1k2E9dXFiQmKIoWo+ga+wnw35ybCjDfjLsJ8N+MuynLi4sSCwwMFDrEXSN/WTYT44NZdhPhv1k2E+G/dTFhQWJFRYWaj2CrrGfDPvJsaEM+8mwnwz7ybCfuriwILGoqCitR9A19pNhPzk2lGE/GfaTYT8Z9lMXFxYklpWVpfUIusZ+Muwnx4Yy7CfDfjLsJ8N+6uLCgsTi4+O1HkHX2E+G/eTYUIb9ZNhPhv1k2E9dXFiQmNFo1HoEXWM/GfaTY0MZ9pNhPxn2k2E/dXFhQWKxsbFaj6Br7CfDfnJsKMN+Muwnw34y7KcuLixIzGw2az2CrrGfDPvJsaEM+8mwnwz7ybCfuriwILGwsDCtR9A19pNhPzk2lGE/GfaTYT8Z9lMXFxYkVlpaqvUIuqb3fhaLBRkZGcjIyHD85sdsNjtOs1gs9Xr9eu/nCdhQhv1k2E+G/WTYT11+Wg9A+ufjw/WphN77paSkYPv27U6nrV271vHn5ORkDB48uN6uX+/9PAEbyrCfDPvJsJ8M+6mLCwsS8/Pj3UhC7/169eqFjh07Vnt+SEhIvV6/3vt5AjaUYT8Z9pNhPxn2UxdrklhJSUm9//DozfTeLzQ0FKGhoZpdv977eQI2lGE/GfaTYT8Z9lMXj/+QWEREhNYj6Br7ybCfHBvKsJ8M+8mwnwz7qYsLCxLLzs7WegRdYz8Z9pNjQxn2k2E/GfaTYT91GRRFUbQeojEoLCxEeHg4CgoK+NZmREREROR1eMSCxIxGo9Yj6Br7ybCfHBvKsJ8M+8mwnwz7qYtHLBqINx+xsNvtfLs2AfaTYT85NpRhPxn2k2E/GfZTF0uSWGZmptYj6Br7ybCfHBvKsJ8M+8mwnwz7qYsLCxJr1qyZ1iPoGvvJsJ8cG8qwnwz7ybCfDPupiwsLEisuLtZ6BF1jPxn2k2NDGfaTYT8Z9pNhP3VxYUFi/v7+Wo+ga+wnw35ybCjDfjLsJ8N+MuynLi4siIiIiIhIjAsLErPZbFqPoGvsJ8N+cmwow34y7CfDfjLspy4uLEjM294+t6Gxnwz7ybGhDPvJsJ8M+8mwn7q4sCAxs9ms9Qi6xn4y7CfHhjLsJ8N+Muwnw37q4gfkNRBv/oA8RVFgMBi0HkO32E+G/eTYUIb9ZNhPhv1k2E9dPGJBYunp6VqPoGvsJ8N+cmwow34y7CfDfjLspy6vXVgsW7YMiYmJCAwMRN++fbF3795qtz18+DDGjBmDxMREGAwGLF26VLzPxiQ+Pl7rEXSN/WTYT44NZdhPhv1k2E+G/dTllQuL1atXY+bMmZg3bx7279+P7t27Y8SIETCZTG63LykpQZs2bfDSSy8hLi5OlX02JkajUesRdI39ZNhPjg1l2E+G/WTYT4b91OWVr7Ho27cvrrrqKrz55psAALvdjoSEBDz44IOYPXt2jZdNTEzEjBkzMGPGDNX2CXj3ayxsNhsCAgK0HkO32E+G/eTYUIb9ZNhPhv1k2E9dXnfEoqysDCkpKRg2bJjjNB8fHwwbNgy7d+/2mH16k8LCQq1H0DX2k2E/OTaUYT8Z9pNhPxn2U5ef1gOozWw2o7KyErGxsU6nx8bG4o8//miwfdpsNqcPXfHmO25gYKDWI+ga+8mwnxwbyrCfDPvJsJ8M+6nL645YeIoFCxYgPDzc8ZWQkAAAKC0tRXp6Oux2u+N5fUajEWVlZTCZTCgqKkJ+fj5yc3NhtVqRmZmJiooKp23Ly8uRmZmJkpIS5ObmIi8vD8XFxcjKykJ5ebnTtpWVlUhPT4fVakVOTg4KCgpgsViQnZ0Nm83mtK2iKDAajbDZbMjOzkZhYSEKCwthNpthtVqrndtsNjvNXVJS4nbuiooKl7mLiorczm232y86d9W8F85tsVhQUFCAnJycaucuLy9HVlYWioqKkJeXV6e58/PzUVRUBJPJhLKysmrnNpvNjobu5q66TGlpabVzV1ZWup27uLjYZe4LG1bNbbVaaz13aWmp27nT09Nd5rbZbDCZTC5zZ2RkXHTui91nMzIynOa2WCzVzp2Zmekyt9lsvuj3msVicfpeU3Pu8++zJpPJ7fdaenq62+81LR4jsrKy6vUx4sK5ve0x4sLeaj9G1DS3NzxGVM1WX48R7ub2pseIqv/q+ecILR8jMjMzdf9zREM8RtSW173GoqysDE2bNsWXX36JUaNGOU6fOHEi8vPz8c0339R4eXevsbiUfbo7YpGQkOCVr7HIyclB8+bNtR5Dt9hPhv3k2FCG/WTYT4b9ZNhPXV53xMLf3x+9evXC5s2bHafZ7XZs3rwZ/fr1a7B9BgQEICwszOnLWzVt2lTrEXSN/WTYT44NZdhPhv1k2E+G/dTlda+xAICZM2di4sSJ6N27N/r06YOlS5eiuLgYkydPBgDcc889iI+Px4IFCwCcOyLx+++/O/5sNBqRmpqKkJAQtGvXrlb7bMzy8vIQFBSk9Ri6xX4y7CfHhjLsJ8N+Muwnw37q8rqnQlV588038corryAzMxM9evTA66+/jr59+wIABg8ejMTERHz00UcAgJMnTyIpKcllH8nJydi2bVut9nkx3vx2s5WVlfD19dV6DN1iPxn2k2NDGfaTYT8Z9pNhP3Vd8sLi3//+d50vc+211zbaVaE3LyyMRiM/uVKA/WTYT44NZdhPhv1k2E+G/dR1yQsLH5+6vTzDYDDgr7/+Qps2bS7l6nTPmxcWRERERESiF29nZmbCbrfX6osvjvFeVW9NRpeG/WTYT44NZdhPhv1k2E+G/dR1yQuLiRMn1ulpTXfddRd/U++lYmJitB5B19hPhv3k2FCG/WTYT4b9ZNhPXZe8sPjwww8RGhpa6+3ffvttREVFXerVkQfLzc3VegRdYz8Z9pNjQxn2k2E/GfaTYT91ed3nWFDDCwkJ0XoEXWM/GfaTY0MZ9pNhPxn2k2E/dan2ORalpaU4ePAgTCYT7Ha703k333yzWldDHqisrAzBwcFaj6Fb7CfDfnJsKMN+Muwnw34y7KcuVRYWGzZswD333AOz2exynsFgQGVlpRpXQx7KSz8KpcGwnwz7ybGhDPvJsJ8M+8mwn7pUeSrUgw8+iLFjxyIjI8Pl3aC4qPB+gYGBWo+ga+wnw35ybCjDfjLsJ8N+MuynLlUWFllZWZg5cyZiY2PV2B3pTGFhodYj6Br7ybCfHBvKsJ8M+8mwnwz7qUuVhcVtt92Gbdu2qbEr0qHmzZtrPYKusZ8M+8mxoQz7ybCfDPvJsJ+6LvmTt89XUlKCsWPHIjo6Gl27dkWTJk2czn/ooYekV6F73vzJ20ajEfHx8VqPoVvsJ8N+cmwow34y7CfDfjLspy5VFhbvv/8+pk2bhsDAQDRv3hwGg+F/V2Aw4MSJE9Kr0D1vXlgQEREREanyVKinnnoKzzzzDAoKCnDy5EmkpaU5vrio8H5Go1HrEXSN/WTYT44NZdhPhv1k2E+G/dSlyhGLyMhI/PLLL2jbtq0aM3klbz5iUVFRAT8/1T4SpdFhPxn2k2NDGfaTYT8Z9pNhP3WpcsRi4sSJWL16tRq7Ih1y9/klVHvsJ8N+cmwow34y7CfDfjLspy5VlmiVlZV4+eWX8cMPP6Bbt24uL95evHixGldDHio8PFzrEXSN/WTYT44NZdhPhv1k2E+G/dSlysLit99+Q8+ePQEAhw4dcjrv/Bdyk3eyWq0ICgrSegzdYj8Z9pNjQxn2k2E/GfaTYT91qbKw2Lp1qxq7IZ3y8VHlGXWNFvvJsJ8cG8qwnwz7ybCfDPupS7VXq5SWluLgwYMwmUyw2+2O0w0GA2666Sa1roY8EF/0JMN+Muwnx4Yy7CfDfjLsJ8N+6lKl5oYNG3D33XcjJyfH5TyDwYDKyko1roY8VElJCUJCQrQeQ7fYT4b95NhQhv1k2E+G/WTYT12qHP958MEHMW7cOGRkZMButzt9cVHh/SIiIrQeQdfYT4b95NhQhv1k2E+G/WTYT12qLCyysrIwc+ZMxMbGqrE70pns7GytR9A19pNhPzk2lGE/GfaTYT8Z9lOXKh+Q97e//Q3XXHMNpkyZosZMXsmbPyCPiIiIiEiVhUVJSQnGjh2L6OhodO3a1eVzLB566CHpVeieNy8sjEYj4uPjtR5Dt9hPhv3k2FCG/WTYT4b9ZNhPXaosLN5//31MmzYNgYGBaN68udNnVxgMBpw4cUJ6FbrnzQsLu93Ot2sTYD8Z9pNjQxn2k2E/GfaTYT91qVLyqaeewjPPPIOCggKcPHkSaWlpji8uKrxfZmam1iPoGvvJsJ8cG8qwnwz7ybCfDPupS5WFRVlZGW6//Xau+BqpyMhIrUfQNfaTYT85NpRhPxn2k2E/GfZTlyorgYkTJ2L16tVq7Ip0qKioSOsRdI39ZNhPjg1l2E+G/WTYT4b91KXKB+RVVlbi5Zdfxg8//IBu3bq5vHh78eLFalwNeSh/f3+tR9A19pNhPzk2lGE/GfaTYT8Z9lOXKguL3377DT179gQAHDp0yOm881/ITURERERE3kmVhcXWrVvV2A3plM1m03oEXWM/GfaTY0MZ9pNhPxn2k2E/dfHV1iTmbW+f29DYT4b95NhQhv1k2E+G/WTYT12XvLA4ePAg7HZ7rbc/fPgwKioqLvXqyIPl5ORoPYKusZ8M+8mxoQz7ybCfDPvJsJ+6LvkD8nx9fZGZmYno6OhabR8WFobU1FS0adPmUq5O97z5A/IUReFraQTYT4b95NhQhv1k2E+G/WTYT12X/BoLRVEwZ84cNG3atFbbl5WVXepVkYdLT09HfHy81mPoFvvJsJ8cG8qwnwz7ybCfDPup65KPWAwePLjOK7yVK1eiRYsWl3J1uufNRyyIiIiIiC55YUF1480LC6PRyNW+APvJsJ8cG8qwnwz7ybCfDPupi+8KRWJRUVFaj6Br7CfDfnJsKMN+Muwnw34y7KcuLixIrKCgQOsRdI39ZNhPjg1l2E+G/WTYT4b91MWFBYkFBQVpPYKusZ8M+8mxoQz7ybCfDPvJsJ+6uLAgsbp8ngm5Yj8Z9pNjQxn2k2E/GfaTYT91ee3CYtmyZUhMTERgYCD69u2LvXv31rj9mjVr0KlTJwQGBqJr16747rvvnM6fNGkSDAaD09fIkSPr8yboBj/4UIb9ZNhPjg1l2E+G/WTYT4b91OWVC4vVq1dj5syZmDdvHvbv34/u3btjxIgRMJlMbrfftWsXxo8fjylTpuDAgQMYNWoURo0ahUOHDjltN3LkSGRkZDi+/vWvfzXEzfF4tf0sE3KP/WTYT44NZdhPhv1k2E+G/dTllQuLxYsX47777sPkyZPRpUsXLF++HE2bNsUHH3zgdvvXXnsNI0eOxKOPPorOnTvjueeew5VXXok333zTabuAgADExcU5vpo1a9YQN8fj5efnaz2CrrGfDPvJsaEM+8mwnwz7ybCfurxuYVFWVoaUlBQMGzbMcZqPjw+GDRuG3bt3u73M7t27nbYHgBEjRrhsv23bNsTExKBjx464//77kZOTU+0cNpsNhYWFTl/eKiYmRusRdI39ZNhPjg1l2E+G/WTYT4b91OV1Cwuz2YzKykrExsY6nR4bG4vMzEy3l8nMzLzo9iNHjsQnn3yCzZs3Y+HChdi+fTuuu+46VFZWut3nggULEB4e7vhKSEgAAJSWliI9PR12ux1GoxHAuQ9nKSsrg8lkQlFREfLz85Gbmwur1YrMzExUVFQ4bVteXo7MzEyUlJQgNzcXeXl5KC4uRlZWFsrLy522raysRHp6OqxWK3JyclBQUACLxYLs7GzYbDanbRVFgdFohM1mQ3Z2tmNBZDabYbVaq5376NGjTnOXlJS4nbuiosJl7qKiIrdz2+32i85dNe+Fc1ssFhQUFCAnJ6faucvLy5GVlYWioiLk5eXVae78/HwUFRXBZDKhrKys2rnNZrOjobu5qy5z5syZaueurKx0O3dxcbHL3Bc2rJrbarXWeu7S0lK3c6enp7vMbbPZYDKZXObOyMi46NwXu89mZGQ4zW2xWKqd+/fff3eZ22w2X/R7zWKxOH2vqTn3+fdZk8nk9nstPT3d7feaFo8RR44cqdfHiAvn9rbHCKPRWK+PETXN7Q2PEb///nu9Pka4m9ubHiMyMzN1/3OElo8Rv//+u+5/jmiIx4ja8rpP3k5PT0d8fDx27dqFfv36OU5/7LHHsH37duzZs8flMv7+/vj4448xfvx4x2lvvfUWnnnmGWRlZbm9nhMnTqBt27bYtGkThg4d6nK+zWaDzWZz/L2wsBAJCQle+cnbRERERER+kgvbbDZs2bIFW7ZswdmzZ2EymWC1WhEdHY2YmBj06NED119/PZKSktSa96KioqLg6+vrsiDIyspCXFyc28vExcXVaXsAaNOmDaKionDs2DG3C4uAgAAEBARcwi3QH6PRiPj4eK3H0C32k2E/OTaUYT8Z9pNhPxn2U9clPRXKaDRi6tSp6NKlC9544w0YDAZ0794dY8aMwZQpUzB48GAkJCRg3759GDNmDPr06YOvvvpK7dnd8vf3R69evbB582bHaXa7HZs3b3Y6gnG+fv36OW0PABs3bqx2ewA4e/YscnJy0KJFC3UG1zE+P1GG/WTYT44NZdhPhv1k2E+G/dRV5yMWr7/+Os6ePYupU6dixYoVtbpMYWEhVq9ejWnTpuHJJ5/EZZddVudB62LmzJmYOHEievfujT59+mDp0qUoLi7G5MmTAQD33HMP4uPjsWDBAgDAP//5TyQnJ2PRokW44YYbsGrVKuzbt89x+4qKivDMM89gzJgxiIuLw/Hjx/HYY4+hXbt2GDFiRL3eFj3Izc11eY0K1R77ybCfHBvKsJ8M+8mwnwz7qatOC4v169fjpptuqvNTm8LCwnDffffh3nvvxRdffIHg4GA0b968Tvuoi9tvvx3Z2dmYO3cuMjMz0aNHD2zYsMFxxzl9+jR8fP53sKZ///5YuXIlnn76aTz55JNo37491q1bhyuuuAIA4Ovri4MHD+Ljjz9Gfn4+WrZsieHDh+O5555rNE93qklISIjWI+ga+8mwnxwbyrCfDPvJsJ8M+6nL61687akKCwsRHh7ulS/ezsvL42d6CLCfDPvJsaEM+8mwnwz7ybCfuurl7WZ9fX3rY7dEREREROSh6mVhwYMgjYu/v7/WI+ga+8mwnxwbyrCfDPvJsJ8M+6mrzguLkpKSi25jMBguaRjSp6KiIq1H0DX2k2E/OTaUYT8Z9pNhPxn2U1edXrw9ffp0fPTRR2jXrh2+/PJLLF68GCaTCUOHDsX999/v9jJZWVn4/fffHV+HDx/GkSNHqv3gOdKfyMhIrUfQNfaTYT85NpRhPxn2k2E/GfZTV52OWHz//fcwm814++23MWDAALRq1Qr33HMPfvrpJ8yZM8exnaIoGDhwIGJjYzFo0CAsWbIEp06dwpo1a/Dyyy/jjz/+UP2GkHZMJpPWI+ga+8mwnxwbyrCfDPvJsJ8M+6mrTu8KdeWVV2L//v0AgI4dO+Lo0aMAgMrKSvTt2xf79u0DAPj4+GDs2LE4c+YMFixYgOTkZABAUlIS0tLS1L4NuuDN7wpFRERERFSnIxbZ2dlYt24d0tLSEBwc7Djd19fX6QXbBoMBq1evxjvvvIOlS5di+PDh2LNnD1974aWMRqPWI+ga+8mwnxwbyrCfDPvJsJ8M+6mrTkcslixZgkOHDuHQoUM4evQounTpgo4dO6Jjx45Yvnw5Tp48CeDcQqOystJxuX379mHu3LnYvn07tmzZgr59+6p+QzydNx+xqKys5FsMC7CfDPvJsaEM+8mwnwz7ybCfukQfkJeWluZYaBw6dAiff/45gHNPhbLb7S7b79y5E3PnzoXBYMCmTZsufWod8uaFRUZGBlq0aKH1GLrFfjLsJ8eGMuwnw34y7CfDfurS5JO3t27diiFDhjT01WrKmxcWVqsVQUFBWo+hW+wnw35ybCjDfjLsJ8N+Muynrnr5gLyLaWyLCm9ntVq1HkHX2E+G/eTYUIb9ZNhPhv1k2E9ddfocCyJ3fHw0WZ96DfaTYT85NpRhPxn2k2E/GU/tZ7FYavzwvpCQEISGhjbgRLWj+sLizz//RJs2beDnxzVLY8EXPcmwnwz7ybGhDPvJsJ8M+8l4ar+UlBRs37692vOTk5MxePDghhuollT/6b9z5844cuQIOnTooPauyUNZrVaPXDXrBfvJsJ8cG8qwnwz7ybCfjKf269WrFzp27AgAMJvNWLt2LUaPHo2oqCgA545YeCLVFxYavBacNBYREaH1CLrGfjLsJ8eGMuwnw34y7Cfjqf1CQ0NdFjxRUVEe/w5WnvnEMtKV7OxsrUfQNfaTYT85NpRhPxn2k2E/GfZTFxcWJBYfH6/1CLrGfjLsJ8eGMuwnw34y7CfDfuriwoLEjEaj1iPoGvvJsJ8cG8qwnwz7ybCfDPupiwsLEvP05/t5OvaTYT85NpRhPxn2k2E/GfZTFxcWJJaZman1CLrGfjLsJ8eGMuwnw34y7CfDfuriwoLEIiMjtR5B19hPhv3k2FCG/WTYT4b9ZNhPXaovLB5//HE0b95c7d2SB6vpkyHp4thPhv3k2FCG/WTYT4b9ZNhPXap/jsWCBQvU3iV5OH9/f61H0DX2k2E/OTaUYT8Z9pNhPxn2UxefCkVERERERGJcWJBYWVmZ1iPoGvvJsJ8cG8qwnwz7ybCfDPupiwsLEgsJCdF6BF1jPxn2k2NDGfaTYT8Z9pNhP3XVy8LC19e3PnZLHio3N1frEXSN/WTYT44NZdhPhv1k2E+G/dRVLwsLRVHqY7fkoeLi4rQeQdfYT4b95NhQhv1k2E+G/WTYT12X9K5Qzz//PJo0aYJu3bqhW7duiI+PdzrfYDCoMhzpQ0ZGhst9gGqP/WTYT06PDS0WS41vExkSEoLQ0NAGmUWP/TwJ+8mwnwz7qcugXOLhhRMnTuDgwYM4ePAgjEYj3nnnHcd5vr6+qKysBABkZWXh999/d3wdPnwYR44cQVZWljq3QCcKCwsRHh6OgoIChIWFaT0OEZGubdu2Ddu3b6/2/OTkZAwePLjhBiIiqicZGRlYsWIFpk6dihYtWmg9To3qdMRi2rRpePbZZxETE4M2bdqgTZs2GDVqlMt2iqJg4MCB+PPPPxEREYGOHTuiU6dOWLNmDdavX4/27durNT95AKPRyNW+APvJsJ+cHhv26tULHTt2BACYzWasXbsWo0ePRlRUFICGfUGmHvt5EvaTYT8Z9lNXnRYW1113Ha6//nrceOONePTRRxEcHFztti1btkRlZSUWLFiA5ORkAMCaNWvQp08f2cTkcaKjo7UeQdfYT4b95PTYMDQ01OWpTlFRUZr8Nk+P/TwJ+8mwnwz7qatOL96+5ZZbsGfPHsTGxqJ///5Yvnw57Ha7y3YGgwGrV6/GO++8g6VLl2L48OHYs2cPX3vhpfLz87UeQdfYT4b95NhQhv1k2E+G/WTYT111flcoX19f3HDDDXj44Yfx9NNPo0uXLvjPf/7jdtuuXbvi66+/xosvvohnnnkGWVlZ2LNnj3ho8ixBQUFaj6Br7CfDfnJsKMN+Muwnw34y7KeuOj0VauTIkThy5AgSEhLQp08fvPHGG+jQoQPeeustbN68GUuXLnV7ud69e+O7777Dzp078eSTT8JgMGDTpk1qzE8eoOqF+nRp2E+G/eTYUIb9ZNhPhv1k2E9ddVpYvPTSS+jatavLB+C9//776NSpk+Pv1b3R1DXXXIPNmzdj69atlzAqeSp3T4ej2mM/GfaTY0MZ9pNhPxn2k2E/ddXpqVA5OTmoqKhwe953333n+HNN/0h79+5Ft27d6nK15OF4GFGG/WTYT44NZdhPhv1k2E+G/dRVp4VF//79MW/ePHz00UcoLi52Oq9NmzY1XjYlJQWPPvoobDYbmjdvXvdJyWPxhU8y7CfDfnJsKMN+Muwnw34y7KeuOj0VKigoCC+99BJ++OEHXH/99QgJCUGPHj3QtWtXREZGIiwsDP7+/rBYLCgsLMTJkyeRmpqK1NRUDB8+HE8++SSaNWtWX7eFNBITE6P1CLrGfjLsJ8eGMuwnw34y7CfDfuqq08KiyogRIzBixAjs378f33//Pd59912cPXsWJpMJVqsVUVFRiImJQffu3XHddddh0aJFiIiIUHl08hSZmZn8cBkB9pNhPzk2lGE/GfaTYT8Z9lPXJS0sqlx55ZW48sor8dRTT6k1D+kQvyFl2E+G/eTYUIb9ZNhPhv1k2E9ddf4cC71YtmwZEhMTERgYiL59+2Lv3r01br9mzRp06tQJgYGB6Nq1q9OL0YFz73Q1d+5ctGjRAkFBQRg2bBj++uuv+rwJumE0GrUeQdfYT4b95NhQhv1k2E+G/WTYT11eubBYvXo1Zs6ciXnz5mH//v3o3r07RowYAZPJ5Hb7Xbt2Yfz48ZgyZQoOHDiAUaNGYdSoUTh06JBjm5dffhmvv/46li9fjj179iA4OBgjRoxAaWlpQ90sj8XnJ8qwnwz7ybGhDPvJsJ8M+8mwn7q8cmGxePFi3HfffZg8eTK6dOmC5cuXo2nTpvjggw/cbv/aa69h5MiRePTRR9G5c2c899xzuPLKK/Hmm28COHe0YunSpXj66adxyy23oFu3bvjkk0+Qnp6OdevWNeAt80y5ublaj6Br7CfDfnJsKMN+Muwnw34y7Kcu0WssPFFZWRlSUlLwxBNPOE7z8fHBsGHDsHv3breX2b17N2bOnOl02ogRIxyLhrS0NGRmZmLYsGGO88PDw9G3b1/s3r0bd9xxh8s+bTYbbDab4++FhYXn/pCaCoSE/G/DZs2ApCSgtBT4/XfX4a688tx/jx4FLniLXyQmApGRQHY2cOaM83mhoUD79kBlJfDrr6777doVaNIEOH4cKChwPi8+HoiNBfLygLQ05/OCgoDOnc/9+cABQFEQZrUCVYcSO3c+t82pU0BOjvNlY2PP7dtiAS58GlmTJudmAoDffgPKy53Pb9/+3G0yGoGsLOfzmjcHWrcGrFbgyBHn8wwGoGfPc38+cuTcNudLSjr3b5CV9b/bUCU8HGjb9twsv/0GF927A76+526LxeJ8XkICEB0N5OYCJ086nxccDHTseO7P+/c79wOALl2AwMBz7fPynC/bosW5r8JC4Ngx5/MCAoDLLz/354MHgQs/c6ZDh3P3vbNngQuP3kVFAZddBpSUAH/84Xyejw/Qo8e5P//++7n76vnatAEiIoDMTCA93fm8iIhz55eVAecdAXTo0ePc/v/8Eygqcj7vssvOzWU2A6dPO58XEnLu9tjtCDt2zPXf7oorAH9/4MQJ4MK3EmzZEoiLO3f6iRPO5wUGnusPnPtevfAzeTp1Apo2PTeP2ex8XkwM0KrVudvx55/O5/n5AVWf33P4MHDeYwMAoF07ICwMyMg493W+BniMcNtQxccIJ/XwGOGXnQ3/qqYaPEaEBAQA+/fDhUqPES687DEiJDa2Xh8jkJrqul8veowIDQg4972j458jnDTwzxFhVuu5dh78c4TfwYOIS0+H38GD5/79tXiMqLofXYziZYxGowJA2bVrl9Ppjz76qNKnTx+3l2nSpImycuVKp9OWLVumxMTEKIqiKDt37lQAKOnp6U7bjB07Vhk3bpzbfc6bN08B4PJVcO5b6H9fEyYoZ8+eVWyHDzuf/v+/MjIylPLycsV25ZUu55W+956Sk5OjFL/8sutlhw9Xzp49q1Tk5rrdb/bvvyulpaVKybXXupxXvnChYjKZlOKPPnI5z96zp3L27FlFURTF7u/vcn7+zp1KcXGxUnznnS7nVT72mJKRkaFYv//edb/x8Y79VsTFuZxv+c9/lMLCQqX4oYdcL/u3v51ruH+/63n+/orRaFQqKysV2xVXuJxf8sknSm5urlL83HOunW66STl79qxSnp7utqHp2DHFZrMp1uRkl/Nsixcr2dnZSsmKFa4zXX2147a622/u3r1KSUmJUjx6tMt5FU8/rWRmZirWdetc99u27f8aRka6nF/4ww+KxWJRiv/+d9fL3n+/YjQaldJdu1zPCw1VjEajYrfblbIOHVzOL161SsnPz1eKnn7a9fbcdpty9uxZpezECbe3NfPUKaWsrEwpvfpq14bLlp27f7/2mutlk5OVs2fPKpUlJW73m/Prr4rValVKbrjB9f793HNKVlaWUrxqlett7dLF0bAyJMTl/IKtW5WioiKleNIk1/v3P/+ppKenK6Vbt7ruNyrKsd/y1q1dzi/66iuloKBAKX70Udfbw8eIc/u9yGPEhxMnKn/99ZcmjxHmI0fcNuRjRO0eI/744w8+RggeI0rHjuVjBPhzxPlf9fIYUUuGczOp588//0SbNm3g56fNwZD09HTEx8dj165d6Nevn+P0xx57DNu3b8eePXtcLuPv74+PP/4Y48ePd5z21ltv4ZlnnkFWVhZ27dqFa665Bunp6WjRooVjm3HjxsFgMGD16tUu+3R3xCIhIQEF27cjzMuOWBQWFiIsLOzcaTxicU4dfhvp1A/wut9G1vcRi8KffnLuB3jVbyMb4jGi8L//dW2oo99GZmdn473t2zHpwQfRwm5v8MeIPJMJzc6ehQsesTjnIo8Rec2aoVlwMI9YXOJjRIGPD8J79ND1zxFOGvjniMLCQoQlJXn0zxHZv/yCtWvXYvTo0YiOjvboIxaqLyx8fX1x5MgRdOjQQc3d1lpZWRmaNm2KL7/8EqNGjXKcPnHiROTn5+Obb75xucxll12GmTNnYsaMGY7T5s2bh3Xr1uHXX3/FiRMn0LZtWxw4cAA9qh48ASQnJ6NHjx547bXXLjpXYWEhwsPDUVBQ4Po/cJ0rLi5GcHCw1mPoFvvJsJ+c3htmZGRgxYoVmDp1qtMvfxqK3vtpjf1k2E9GD/20foyrC9VfvK3yOqXO/P390atXL2zevNlxmt1ux+bNm52OYJyvX79+TtsDwMaNGx3bJyUlIS4uzmmbwsJC7Nmzp9p9NiZFF/4WieqE/WTYT44NZdhPhv1k2E+G/dTldS/eBoCZM2di4sSJ6N27N/r06YOlS5eiuLgYkydPBgDcc889iI+Px4IFCwAA//znP5GcnIxFixbhhhtuwKpVq7Bv3z6sWLECAGAwGDBjxgw8//zzaN++PZKSkjBnzhy0bNnS6ahIYxUZGan1CLrGfjLsJ8eGMuwnw34y7CfDfuryyrebvf322/Hqq69i7ty56NGjB1JTU7FhwwbExsYCAE6fPo2M856j2L9/f6xcuRIrVqxA9+7d8eWXX2LdunW44oorHNs89thjePDBBzF16lRcddVVKCoqwoYNGxAYGNjgt8/TVPf5IFQ77CfDfnJsKMN+Muwnw34y7Kcu1V9j4ePjgz/++EOz11h4Km9+jQURkZb09PxjIqK60tNjnFcesaCGZbzwXRCoTthPhv3k2FCG/WTYT4b9ZNhPXVxYkFhcXJzWI+ga+8mwnxwbyrCfDPvJsJ8M+6mLCwsS4/MTZdhPhv3k2FCG/WTYT4b9ZNhPXaovLB5//HE0b95c7d2SB4uIiNB6BF1jPxn2k2NDGfaTYT8Z9pNhP3WpvrBYsGABFxaNTElJidYj6Br7ybCfHBvKsJ8M+8mwnwz7qYtPhSIxPz+v/DiUBsN+Muwnx4Yy7CfDfjLsJ8N+6uLCgsR8fHg3kmA/GfaTY0MZ9pNhPxn2k2E/dbEmiVmtVq1H0DX2k2E/OTaUYT8Z9pNhPxn2U5fqC4slS5YAAA4fPozKykq1d08eKDw8XOsRdI39ZNhPjg1l2E+G/WTYT4b91KX6wqJHjx4AgCeffBJdunRBjx49MGHCBLz00ktYv3692ldHHsBsNms9gq6xnwz7ybGhDPvJsJ8M+8mwn7pUecWKxWJBaGgoAGDIkCEAgG+++QYAUFRUhMOHD+O3337Dpk2bcOONN6pxleRB4uPjtR5B19hPhv3k2FCG/WTYT4b9ZNhPXaocsRg4cCAyMzPdnhcSEoK+ffvi3nvvxdKlS9W4OvIwRqNR6xF0jf1k2E+ODWXYT4b9ZNhPhv3UpcrComfPnujbty/++OMPp9NTU1Nx/fXXq3EV5MFatmyp9Qi6xn4y7CfHhjLsJ8N+Muwnw37qUmVh8eGHH2LSpEkYMGAAduzYgT///BPjxo1Dr1694Ovrq8ZVkAfLyMjQegRdYz8Z9pNjQxn2k2E/GfaTYT91qfapIM888wwCAgJw7bXXorKyEkOHDsXu3bvRp08fta6CPBQ/aV2G/WTYT44NZdhPhv1k2E+G/dSlyhGLrKws/POf/8Tzzz+PLl26oEmTJpg0aRIXFY1EYWGh1iPoGvvJsJ8cG8qwnwz7ybCfDPupS5WFRVJSEn766SesWbMGKSkp+OqrrzB16lS88sorauyePFxAQIDWI+ga+8mwnxwbyrCfDPvJsJ8M+6lLladCffDBB7jjjjscfx85ciS2bt2KG2+8ESdPnsSyZcvUuBoiIiIiIvJQqhyxOH9RUeXKK6/Erl27sGXLFjWugjxYWVmZ1iPoGvvJsJ8cG8qwnwz7ybCfDPupS/VP3j5fYmIidu3aVZ9XQR4gJCRE6xF0jf1k2E+ODWXYT4b9ZNhPhv3UVa8LCwBo1qxZfV8FaSw3N1frEXSN/WTYT44NZdhPhv1k2E+G/dRV7wsL8n5xcXFaj6Br7CfDfnJsKMN+Muwnw34y7KcuLixIjB8uI8N+Muwnp+eGh06Z8NQXe7GtLAmvbzuJNHNxg8+g536egP1k2E+G/dTFhQWJxcfHaz2CrrGfDPvJ6bXhF/vO4Oblv2Brhi9OVkZi9cFcDF20DWv2nWnQOfTaz1Ownwz7ybCfulRbWOTn52PRokW49957ce+992LJkiUoKChQa/fkwYxGo9Yj6Br7ybCfnB4bppmLMfurg7ArgAIDFBhgVwC7Ajz+1UGcbMAjF3rs50nYT4b9ZNhPXaosLPbt24e2bdtiyZIlyM3NRW5uLhYvXoy2bdti//79alwFebDo6GitR9A19pNhPzk9Nvxi3xkYDAa35xkMBqxuwKMWeuznSdhPhv1k2E9dqiwsHn74Ydx88804efIk1q5di7Vr1yItLQ033ngjZsyYocZVkAfLz8/XegRdYz8Z9pPTY8OzeVYoiuL2PEVRcDbP2mCz6LGfJ2E/GfaTYT91qfLJ2/v27cO7774LP7//7c7Pzw+PPfYYevfurcZVkAdr2rSp1iPoGvvJsJ+cHhu2ahZ07oiFm8WFwWBAq2ZBDTaLHvt5Ek/vZ7FYUFRUVO35ISEhCA0NbcCJnHl6P0/HfupSZWERFhaG06dPo1OnTk6nnzlzRtNvNmoYFRUVWo+ga+wnw35yemw4rncC3tl+3O15iqLg9t4JDTaLHvt5Ek/vl5KSgu3bt1d7fnJyMgYPHtxwA13A0/t5OvZTlyoLi9tvvx1TpkzBq6++iv79+wMAdu7ciUcffRTjx49X4yrIg9ntdq1H0DX2k2E/OT02TIoKxsIx3fD4VwcdT4mqes3FwjHdkBgV3GCz6LGfJ/H0fr169ULHjh0BAGazGWvXrsXo0aMRFRUFQPtPbvb0fp6O/dSlysLi1VdfhcFgwD333IOKigooigJ/f3/cf//9eOmll9S4CvJgQUEN95QDb8R+Muwnp9eGY3snoEt0ABat2400UwGuvqI9/n5twy4qAP328xSe3i80NNTl2RdRUVFo0aKFRhM58/R+no791KXKi7f9/f3x2muvIS8vD6mpqfj111+Rm5uLJUuWICAgQI2rIA/GtxWWYT8Z9pPTc8PLW8fghXF9MNg/DQ8NTmzwRQWg736egP1k2E+G/dSlyhGLZ599tsbz586dq8bVkIeqOhxMl4b9ZNhPjg1l2E+G/WTYT4b91KXKwuLrr792+nt5eTnS0tLg5+eHtm3bcmHh5bKysvjJlQLsJ8N+cmwow34y7CfDfjLspy5VFhYHDhxwOa2wsBCTJk3CrbfeqsZVkAfjN6QM+8mwnxwbyrCfDPvJsJ8M+6lLlddYuBMWFoZnnnkGc+bMqa+rIA9hNBq1HkHX2E+G/eTYUIb9ZNhPhv1k2E9d9bawAM69IIYvivF+MTExWo+ga+wnw35ybCjDfjLsJ8N+MuynLlWeCvX66687/V1RFGRkZODTTz/Fddddp8ZVkAfLyclBXFyc1mPoFvvJsJ8cG8qwnwz7ybCfDPupS5WFxZIlS5z+7uPjg+joaEycOBFPPPGEGldBHiwsLEzrEXSN/WTYT44NZdhPhv1k2E+G/dSlysIiLS1Njd2QTpWWlqJp06Zaj6Fb7CfDfnJsKMN+Muwnw34y7Keuen2NhRZyc3MxYcIEhIWFISIiAlOmTEFRUVGNlyktLcUDDzyA5s2bIyQkBGPGjEFWVpbTNgaDweVr1apV9XlTdMNgMGg9gq6xnwz7ybGhDPvJsJ8M+8mwn7ou+YjFzJkza73t4sWLL/Vq6mzChAnIyMjAxo0bUV5ejsmTJ2Pq1KlYuXJltZd5+OGH8e2332LNmjUIDw/H9OnTMXr0aOzcudNpuw8//BAjR450/D0iIqK+boau+Pv7az2CrrGfDPvJsaEM+8mwnwz7ybCfui55YXHhZ1fs378fFRUV6NixIwDgzz//hK+vL3r16iWbsA6OHDmCDRs24JdffkHv3r0BAG+88Qauv/56vPrqq2jZsqXLZQoKCvD+++9j5cqV+L//+z8A5xYQnTt3xs8//4yrr77asW1ERARf4ONGUVERgoODtR5Dt9hPhv3k2FCG/WTYT4b9ZNhPXZf8VKitW7c6vm666SYkJyfj7Nmz2L9/P/bv348zZ85gyJAhuOGGG9Sct0a7d+9GRESEY1EBAMOGDYOPjw/27Nnj9jIpKSkoLy/HsGHDHKd16tQJl112GXbv3u207QMPPICoqCj06dMHH3zwARRFqZ8bojORkZFaj6Br7CfDfnJsKMN+Muwnw34y7KcuVV5jsWjRIixYsADNmjVznNasWTM8//zzWLRokRpXUSuZmZku70fs5+eHyMhIZGZmVnsZf39/l6c1xcbGOl3m2WefxRdffIGNGzdizJgx+Mc//oE33nij2llsNhsKCwudvryVyWTSegRdYz8Z9pNjQxn2k2E/GfaTYT91qbKwKCwsRHZ2tsvp2dnZsFgs4v3Pnj3b7Yunz//6448/xNdTkzlz5uCaa65Bz5498fjjj+Oxxx7DK6+8Uu32CxYsQHh4uOMrISEBwLkXiqenp8Nutzs+7dFoNKKsrAwmkwlFRUXIz89Hbm4urFYrMjMzUVFR4bRteXk5MjMzUVJSgtzcXOTl5aG4uBhZWVkoLy932rayshLp6emwWq3IyclBQUEBLBYLsrOzYbPZnLZVFAVGoxE2mw3Z2dmOBZHZbIbVaq127iZNmjjNXVJS4nbuiooKl7mLiorczm232y86d9W8F85tsVhQUFCAnJycaucuLy9HVlYWioqKkJeXV6e58/PzUVRUBJPJhLKysmrnNpvNjobu5q66TFRUVLVzV1ZWup27uLjYZe4LG1bNbbVaaz13aWmp27nT09Nd5rbZbDCZTC5zZ2RkXHTui91nMzIynOa2WCzVzm0wGFzmNpvNF/1es1gsTt9ras59/n3WZDK5/V5LT093+72mxWOEwWCo18eIC+dW+zEiPz8fAFBcXKzJY0TVL6Lq6zGiprm94TECQL0+RribW/IYUcVTHiPi4+N1/3NEfT9G1PRzBACP/zmi6k2IqrbV4jGitgyKCs/nueeee/Df//4XixYtQp8+fQAAe/bswaOPPoqBAwfi448/Fu0/OzsbOTk5NW7Tpk0bfPbZZ3jkkUeQl5fnOL2iogKBgYFYs2YNbr31VpfLbdmyBUOHDkVeXp7TUYvWrVtjxowZePjhh91e37fffosbb7wRpaWlCAgIcDnfZrPBZrM5/l5YWIiEhAQUFBR43XsmVz2w0aVhPxn2k9N7w4yMDKxYsQJTp05FixYtGvz69d5Pa3rqp/V9zR099fNEeujnife76qjyORbLly/HrFmzcOedd6K8vPzcjv38MGXKlBp/q19b0dHRiI6Ovuh2/fr1Q35+PlJSUhwvGt+yZQvsdjv69u3r9jK9evVCkyZNsHnzZowZMwYAcPToUZw+fRr9+vWr9rpSU1PRrFkzt4sKAAgICKj2PG/DF7TLsJ8M+8mxoQz7ybCfDPvJsJ+6VHkqVNOmTfHWW28hJycHBw4cwIEDB5Cbm4u33nqrQV9p37lzZ4wcORL33Xcf9u7di507d2L69Om44447HO8IZTQa0alTJ+zduxcAEB4ejilTpmDmzJnYunUrUlJSMHnyZPTr18/xjlD/+c9/8N577+HQoUM4duwY3n77bbz44ot48MEHG+y2ebILP/OD6ob9ZNhPjg1l2E+G/WTYT4b91KXKEYsqwcHB6Natm5q7rLPPP/8c06dPx9ChQ+Hj44MxY8bg9ddfd5xfXl6Oo0ePoqSkxHHakiVLHNvabDaMGDECb731luP8Jk2aYNmyZXj44YehKAratWuHxYsX47777mvQ2+apzn/RPtUd+8mwnxwbyrCfDPvJsJ8M+6lL9AF5zz33HIKDgy/6YXkN+QF5kZGRNX4YXmJiosvbxAYGBmLZsmVYtmyZ28uMHDnS6YPxyFlJSQmCgoK0HkO32E+G/eTYUIb9ZNhPhv1k2E9dog/Iq3o9xYUflnc+flS69/PzU/XAV6PDfjLsJ8eGMuwnw34y7CfDfuq65Jpbt251+2dqfHx8VHmpTqPFfjLsJ8eGMuwnw34y7CfDfupSpabVanV6zcKpU6ewdOlS/Pjjj2rsnjxcaWmp1iPoGvvJsJ8cG8qwnwz7ybCfDPupS5WFxS233IJPPvkEAJCfn48+ffpg0aJFuOWWW/D222+rcRXkwbztczkaGvvJsJ8cG8qwnwz7ybCfjKf3SzMX4/VtJ7GtLAlPfbEXh0559ieFq7Kw2L9/PwYOHAgA+PLLLxEXF4dTp07hk08+cXpHJvJOZrNZ6xF0jf1k2E+ODWXYT4b9ZNhPxpP7fbHvDIYu2obVB3NxsjISWzN8cfPyX7Bm3xmtR6uWKguLkpIShIaGAgB+/PFHjB49Gj4+Prj66qtx6tQpNa6CPJinf2Klp2M/GfaTY0MZ9pNhPxn2k/HUfmnmYsz+6iDsCmBXAAUGKDDArgCPf3UQJ83FWo/olioLi3bt2mHdunU4c+YMfvjhBwwfPhwAYDKZPP4QE8kZjUatR9A19pNhPzk2lGE/GfaTYT8ZT+33xb4z1b6zqsFgwGoPPWqhysJi7ty5mDVrFhITE9G3b1/069cPwLmjFz179lTjKsiDVX2qOV0a9pNhPzk2lGE/GfaTYT8ZT+13Ns/q8rlrVRRFwdk8awNPVDuqLCxuu+02nD59Gvv27cOGDRscpw8dOhRLlixR4yrIg6Wnp2s9gq6xnwz7ybGhDPvJsJ8M+8l4ar9WzYJqPGLRqplnfqifap8KEhcXh7i4OKfT+vTpo9buyYNFRUVpPYKusZ8M+8mxoQz7ybCfDPvJeGq/cb0T8M72427PUxQFt/dOaOCJake1TwX573//i7vuugv9+vVzPF/t008/xY4dO9S6CvJQhYWFWo+ga+wnw35ybCjDfjLsJ8N+Mp7aLykqGAvHdIOPAfAx4P+/dFuBjwFYOKYbEqOCtR7RLVUWFl999RVGjBiBoKAgHDhwADabDQBQUFCAF198UY2rIA8WEBCg9Qi6xn4y7CfHhjLsJ8N+Muwn48n9xvZOwJZHBuP2bpFI9M3FkBaV+M+0qzDWQ49WACotLJ5//nksX74c7777Lpo0aeI4/ZprrsH+/fvVuAoiIiIiokYlMSoYDw1OxGD/NLwwrg8ubx2j9Ug1UmVhcfToUQwaNMjl9PDwcOTn56txFeTBysrKtB5B19hPhv3k2FCG/WTYT4b9ZNhPXaosLOLi4nDs2DGX03fs2IE2bdqocRXkwYKDPfN5fnrBfjLsJ8eGMuwnw34y7CfDfupSZWFx33334Z///Cf27NkDg8GA9PR0fP7555g1axbuv/9+Na6CPFheXp7WI+ga+8mwnxwbyrCfDPvJsJ8M+6lLlbebnT17Nux2O4YOHYqSkhIMGjQIAQEBmDVrFh588EE1roI82IVvM0x1w34y7CfHhjLsJ8N+Muwnw37qUuWIhcFgwFNPPYXc3FwcOnQIP//8M7Kzs/Hcc8/BavXMTwYk9WRkZGg9gq6xnwz7ybGhDPvJsJ8M+8mwn7pU+xwLAPD390eXLl3Qp08fNGnSBIsXL0ZSUpKaV0EeKD4+XusRdI39ZNhPjg1l2E+G/WTYT4b91CVaWNhsNjzxxBPo3bs3+vfvj3Xr1gEAPvzwQyQlJWHJkiV4+OGH1ZiTPFjVByLSpWE/GfaTY0MZ9pNhPxn2k2E/dYleYzF37ly88847GDZsGHbt2oWxY8di8uTJ+Pnnn7F48WKMHTsWvr6+as1KHio6OlrrEXSN/WTYT44NZdhPhv1k2E+G/dQlOmKxZs0afPLJJ/jyyy/x448/orKyEhUVFfj1119xxx13cFHRSPCzSmTYT4b95NhQhv1k2E+G/WTYT12iIxZnz55Fr169AABXXHEFAgIC8PDDD8NgMKgyHOlD06ZNtR5B19hPhv3k9NjQYrGgqKgIAGA2m53+CwAhISEIDQ1tkFn02M+TsJ8M+8mwn7pEC4vKykr4+/v/b2d+fggJCREPRfpSUVGh9Qi6xn4y7Cenx4YpKSnYvn2702lr1651/Dk5ORmDBw9ukFn02M+TsJ8M+8mwn7pECwtFUTBp0iQEBAQAAEpLSzFt2jSXTzE8/8GevI/dbtd6BF1jPxn2k9Njw169eqFjx47Vnt+Qv+TSYz9Pwn4y7CfDfuoSLSwmTpzo9Pe77rpLNAzpU2BgoNYj6Br7ybCfnB4bhoaGNthTnS5Gj/08iV76HTplwuJ1e5FWloTSbScx9dowJEUFX/yC9Uwv/TwV+6lLtLD48MMP1ZqDdKywsJDPURRgPxn2k2NDGfaT0UO/L/adweyvDkJRfAFE4tTBXKw+uA0Lx3TD2N4Jms6mh36ejP3UpeoH5FHjFBUVpfUIusZ+Muwnx4Yy7Cfj6f3SzMWY/dVB2BVAgQEKDLArgF0BHv/qIE6aizWdz9P7eTr2UxcXFiSWlZWl9Qi6xn4y7CfHhjLsJ+Pp/b7Yd6bad7s0GAxYve9MA0/kzNP7eTr2UxcXFiQWHx+v9Qi6xn4y7CfHhjLsJ+Pp/c7mWaEoitvzFEXB2TxrA0/kzNP7eTr2UxcXFiRmNBq1HkHX2E+G/eTYUIb9ZDy9X6tmQTUesWjVLKiBJ3Lm6f08HfupiwsLEouNjdV6BF1jPxn2k2NDGfaT8fR+43on1HjE4naNX7zt6f08HfupiwsLEjv/026p7thPhv3k2FCG/WQ8vV9SVDAWjukGHwP+/0u3FfgYAB8DsHBMNyRq/Jaznt7P07GfukRvN0sEAGFhYVqPoGvsJ8N+cmwow34yeug3tncCukQHYNG63UgzFeDqK9rj79dqv6gA9NHPk7GfunjEgsRKS0u1HkHX2E+G/eTYUIb9ZPTS7/LWMXhhXB8M9k/DQ4MTPWJRAeinn6diP3VxYUFi1b2ojWqH/WTYT44NZdhPhv1k2E+G/dTFp0J5MYvFgqKiomrPDwkJQWhoqPh6mjRpIt5HY8Z+Muwnx4Yy7CfDfjLsJ8N+6uLCwoulpKRg+/bt1Z6fnJyMwYMHi6+nuLgYISEh4v00Vuwnw35ybCjDfjLsJ8N+MuynLi4svFivXr3QsWNHAOfe9WDt2rUYPXq04+Pr1fpGioyMVGU/jRX7ybCfHBvKsJ8M+8mwnwz7qYuvsfBioaGhaNGiBVq0aOFYTERFRTlOU+NpUABgMplU2U9jxX4y7CfHhjLsJ8N+Muwnw37q4sKCxOLj47UeQdfYT4b95NhQhv1k2E+G/WTYT11et7DIzc3FhAkTEBYWhoiICEyZMqXGFzADwIoVKzB48GCEhYXBYDAgPz9flf02FkajUesRdI39ZNhPjg1l2E+G/WTYT4b91OV1C4sJEybg8OHD2LhxI9avX4+ffvoJU6dOrfEyJSUlGDlyJJ588klV99tYtGjRQusRdI39ZNhPjg1l2E+G/WTYT4b91OVVC4sjR45gw4YNeO+999C3b18MGDAAb7zxBlatWoX09PRqLzdjxgzMnj0bV199tar7bSwyMzO1HkHX2E+G/eTYUIb9ZNhPhv1k2E9dXrWw2L17NyIiItC7d2/HacOGDYOPjw/27NnToPu12WwoLCx0+vJWzZo103oEXWM/GfaTY0MZ9pNhPxn2k2E/dXnVwiIzMxMxMTFOp/n5+SEyMlK0Ir2U/S5YsADh4eGOr4SEBADnPjo+PT0ddrvd8bw+o9GIsrIymEwmFBUVIT8/H7m5ubBarcjMzERFRYXTtuXl5cjMzERJSQlyc3ORl5eH4uJiZGVloby83GnbyspKpKenOz6yvqioCBaLBdnZ2bDZbE7bKooCo9EIm82G7Oxsx4LIbDbDarVWO7fRaHSau6SkxO3cFRUVLnMXFRW5ndtutyM9PR1WqxU5OTkoKChwmbtq3gvntlgsKCgoQE5OTrVzl5eXIysrC0VFRcjLy6vT3Pn5+SgqKoLJZHLcfndzm81mR0N3c1ddpqCgoNq5Kysr3c5dXFzsMveFDavmtlqttZ67tLTU7dzp6ekuc9tsNphMJpe5MzIyLjr3xe6zGRkZTnNbLJZq5z59+rTL3Gaz+aLfaxaLxel7Tc25z7/Pmkwmt99r6enpbr/XtHiMOH36dI3fa9LHiAvn9rbHCIvFUq+PETXN7Q2PEadOnarXxwh3c0seI6p4ymNESUlJg/wc4a2PEadOnfL4nyOqXtNbta0WjxG1ZVAURan11hqZPXs2Fi5cWOM2R44cwdq1a/Hxxx/j6NGjTufFxMTgmWeewf3331/jPrZt24YhQ4YgLy8PERERjtNffPHFOu/XZrPBZrM5/l5YWIiEhAQUFBQgLCysxjnqQ0ZGBlasWIGpU6eq/nzCgoIChIeHq7rPxoT9ZNhPjg1l2E9GT/3q8/+ll0pP/TyRHvp54v2uOrr4gLxHHnkEkyZNqnGbNm3aIC4uzuX9iCsqKpCbm4u4uLhLvv5L2W9AQAACAgIu+Tr1xMfHqw58NTj2k2E/OTaUYT8Z9pNhPxn2U5cuFhbR0dGIjo6+6Hb9+vVDfn4+UlJS0KtXLwDAli1bYLfb0bdv30u+/vrar7coLS1V7cP2GiP2k2E/OTaUYT8Z9pNhPxn2U5dXLdM6d+6MkSNH4r777sPevXuxc+dOTJ8+HXfccQdatmwJ4Nxzxjp16oS9e/c6LpeZmYnU1FQcO3YMAPDbb78hNTUVubm5td5vY6bFU7u8CfvJsJ8cG8qwnwz7ybCfDPupy6sWFgDw+eefo1OnThg6dCiuv/56DBgwACtWrHCcX15ejqNHj6KkpMRx2vLly9GzZ0/cd999AIBBgwahZ8+e+Pe//13r/TZmZrNZ6xF0jf1k2E+ODWXYT4b9ZNhPhv3UpYunQtVFZGQkVq5cWe35iYmJuPD16vPnz8f8+fNF+23MeNRGhv1k2E+ODWXYT4b9ZNhPhv3U5XVHLKjh8UMCZdhPhv3k2FCG/WTYT4b9ZNhPXVxYkBhX+zLsJ8N+cmwow34y7CfDfjLspy4uLEiMq30Z9pNhPzk2lGE/GfaTYT8Z9lMXFxYkFhUVpfUIusZ+Muwnx4Yy7CfDfjLsJ8N+6uLCgsQKCwu1HkHX2E+G/eTYUIb9ZNhPhv1k2E9dXFiQWGBgoNYj6Br7ybCfHBvKsJ8M+8mwnwz7qYsLCxKz2+1aj6Br7CfDfnJsKMN+Muwnw34y7KcuLixIrKKiQusRdI39ZNhPjg1l2E+G/WTYT4b91MWFBYk1bdpU6xF0jf1k2E+ODWXYT4b9ZNhPhv3UxYUFieXl5Wk9gq6xnwz7ybGhDPvJsJ8M+8mwn7q4sCCxuLg4rUfQNfaTYT85NpRhPxn2k2E/GfZTFxcWJJaRkaH1CLrGfjLsJ8eGMuwnw34y7CfDfuriwoLE4uPjtR5B19hPhv3k2FCG/WTYT4b9ZNhPXVxYkJjRaNR6BF1jPxn2k2NDGfaTYT8Z9pNhP3VxYUFiMTExWo+ga+wnw35ybCjDfjLsJ8N+MuynLi4sSCw3N1frEXSN/WTYT44NZdhPhv1k2E+G/dTFhQWJBQcHaz2CrrGfDPvJsaEM+8mwnwz7ybCfuriwILHy8nKtR9A19pNhPzk2lGE/GfaTYT8Z9lMXFxYkpiiK1iPoGvvJsJ8cG8qwnwz7ybCfDPupiwsLEgsMDNR6BF1jPxn2k2NDGfaTYT8Z9pNhP3VxYUFihYWFWo+ga+wnw35ybCjDfjLsJ8N+MuynLi4sSCwqKkrrEXSN/WTYT44NZdhPhv1k2E+G/dTFhUUjkGYuxqKNx7CtLAmLNh5DmrlY1f1nZWWpur/Ghv1k2E+ODWXYT4b9ZNhPhv3U5af1AFS/vth3BrO/OggAUJRInDpSiLVHtmHhmG4Y2ztBleuIj49XZT+NFfvJsJ8cG8qwnwz7ybCfDPupi0csvFiauRizvzoIuwLYFUCBwfHnx786iJMqHbkwGo2q7KexYj8Z9pNjQxn2k2E/GfaTYT91cWHhxb7YdwYGg8HteQaDAav3nVHlemJjY1XZT2PFfjLsJ8eGMuwnw34y7CfDfuriwsKLnc2zVvv+zIqi4GyeVZXrMZvNquynsWI/GfaTY0MZ9pNhPxn2k2E/dXFh4cVaNQuq8YhFq2ZBqlxPWFiYKvtprNhPhv3k2FCG/WTYT4b9ZNhPXVxYeLFxvRNqPGJxu0ov3i4tLVVlP40V+8mwnxwbyrCfjKf3s1gsyMjIQEZGhuO322az2XGaxWLRdD5P7+fp2E9dfFcoL5YUFYyFY7rhcce7QimOIxgLx3RDYlSwKtfj48P1qQT7ybCfHBvKsJ+Mp/dLSUnB9u3bnU5bu3at48/JyckYPHhwA0/1P57ez9Oxn7q4sPByY3sn4KrESLz53X6kHE1Dr45JmH79laotKgDAz493Iwn2k2E/OTaUYT8ZT+/Xq1cvdOzYsdrzQ0JCGnAaV57ez9Oxn7pYsxFIjArGI9e2w4q0LZh67bVooeKiAgBKSko0f2DVM/aTYT85NpRhPxlP7xcaGorQ0FCtx6iWp/fzdOynLh7/IbGIiAitR9A19pNhPzk2lGE/GfaTYT8Z9lMXFxYklp2drfUIusZ+Muwnx4Yy7CfDfjLsJ8N+6uLCgsTi4+O1HkHX2E+G/eTYUIb9ZNhPhv1k2E9dXFiQmNFo1HoEXWM/GfaTY0MZ9pNhPxn2k2E/dXFhQWItWrTQegRdYz8Z9pNjQxn2k2E/GfaTYT91cWFBYpmZmVqPoGvsJ8N+cmwow34y7CfDfjLspy4uLEisWbNmWo+ga+wnw35ybCjDfjLsJ8N+MuynLi4sSKy4uFjrEXSN/WTYT44NZdhPhv1k2E+G/dTldQuL3NxcTJgwAWFhYYiIiMCUKVNQVFRU42VWrFiBwYMHIywsDAaDAfn5+S7bJCYmwmAwOH299NJL9XQr9MXf31/rEXSN/WTYT44NZdhPhv1k2E+G/dTldQuLCRMm4PDhw9i4cSPWr1+Pn376CVOnTq3xMiUlJRg5ciSefPLJGrd79tlnkZGR4fh68MEH1RydiIiIiEi3/LQeQE1HjhzBhg0b8Msvv6B3794AgDfeeAPXX389Xn31VbRs2dLt5WbMmAEA2LZtW437Dw0NRVxcnJojewWbzab1CLrGfjLsJ8eGMuwnw34y7CfDfuryqiMWu3fvRkREhGNRAQDDhg2Dj48P9uzZI97/Sy+9hObNm6Nnz5545ZVXUFFRId6nNwgLC9N6BF1jPxn2k2NDGfaTYT8Z9pNhP3V51cIiMzMTMTExTqf5+fkhMjJS/HZiDz30EFatWoWtW7fi73//O1588UU89thj1W5vs9lQWFjo9OWtzGaz1iPoGvvJsJ8cG8qwnwz7ybCfDPupSxcLi9mzZ7u8cPrCrz/++KNeZ5g5cyYGDx6Mbt26Ydq0aVi0aBHeeOONag+hLViwAOHh4Y6vhIQEAEBpaSnS09Nht9sdn/ZoNBpRVlYGk8mEoqIi5OfnIzc3F1arFZmZmaioqHDatry8HJmZmSgpKUFubi7y8vJQXFyMrKwslJeXO21bWVmJ9PR0lJaWAgCKiopgsViQnZ0Nm83mtK2iKDAajbDZbMjOznYsiMxmM6xWa7Vz+/n5Oc1dUlLidu6KigqXuYuKitzObbfbkZ6eDqvVipycHBQUFLjMXTXvhXNbLBYUFBQgJyen2rnLy8uRlZWFoqIi5OXl1Wnu/Px8FBUVwWQyoaysrNq5zWazo6G7uasu07x582rnrqysdDt3cXGxy9wXNqya22q11nru0tJSt3Onp6e7zG2z2WAymVzmzsjIuOjcF7vPZmRkOM1tsViqnbvq++r8uc1m80W/1ywWi9P3mppzn3+fNZlMbr/X0tPT3X6vafEYYTAYavxekz5GXDi3tz1GxMTE1OtjRE1ze8NjhKIo9foY4W5ub3qMaNmyZYP8HOGtjxFVX578c0TVmxBVbavFY0RtGRRFUWq9tUays7ORk5NT4zZt2rTBZ599hkceeQR5eXmO0ysqKhAYGIg1a9bg1ltvrXEf27Ztw5AhQ5CXl4eIiIgatz18+DCuuOIK/PHHH+jYsaPL+TabzWnRUVhYiISEBBQUFGhy2C0jIwMrVqzA1KlTVf+USaPRiPj4eFX32Ziwnwz7ybGhDPvJsJ8M+8nooV99/gynNl28eDs6OhrR0dEX3a5fv37Iz89HSkoKevXqBQDYsmUL7HY7+vbtq+pMqamp8PHxcXnqVZWAgAAEBASoep2eytO/IT0d+8mwnxwbyrCfDPvJsJ8M+6lLF0+Fqq3OnTtj5MiRuO+++7B3717s3LkT06dPxx133OF4Ryij0YhOnTph7969jstlZmYiNTUVx44dAwD89ttvSE1NRW5uLoBzLwpfunQpfv31V5w4cQKff/45Hn74Ydx11138xEbAcdiMLg37ybCfHBvKsJ8M+8mwnwz7qcurFhYA8Pnnn6NTp04YOnQorr/+egwYMAArVqxwnF9eXo6jR4+ipKTEcdry5cvRs2dP3HfffQCAQYMGoWfPnvj3v/8N4NzRh1WrViE5ORmXX345XnjhBTz88MNO+23MoqKitB5B19hPhv3k2FCG/WTYT4b9ZNhPXbp4KlRdREZGYuXKldWen5iYiAtfVjJ//nzMnz+/2stceeWV+Pnnn9Ua0esUFhbW6qlq5B77ybCfHBvKsJ8M+8mwnwz7qcvrjlhQwwsMDNR6BF1jPxn2k2NDGfaTYT8Z9pNhP3VxYUFiVW/5SZeG/WTYT44NZdhPhv1k2E+G/dTldU+FoobHTyCXYT8Z9pNjQxn2k2E/GfaT8dR+FovF8fkVVR/id/6H+YWEhCA0NFST2WrChQWJNW3aVOsRdI39ZNhPjg1l2E+G/WTYT8ZT+6WkpGD79u1Op61du9bx5+TkZAwePLiBp7o4LixILC8vD0FBQVqPoVvsJ8N+cmwow34y7CfDfjKe2q9Xr15uP4C5SkhISANOU3tcWJBYbGys1iPoGvvJsJ8cG8qwnwz7ybCfjKf2Cw0N9cinOl0MX7xNYpmZmVqPoGvsJ8N+cmwow34y7CfDfjLspy4uLEgsPj5e6xF0jf1k2E+ODWXYT4b9ZNhPhv3UxYUFiRmNRq1H0DX2k2E/OTaUYT8Z9pNhPxn2UxcXFiQWExOj9Qi6xn4y7CfHhjLsJ8N+Muwnw37q4sKCxHJzc7UeQdfYT4b95NhQhv1k2E+G/WTYT11cWJCYp77lmV6wnwz7ybGhDPvJsJ8M+8mwn7q4sCCxsrIyrUfQNfaTYT85NpRhPxn2k2E/GfZTFxcWJKYoitYj6Br7ybCfHBvKsJ8M+8mwnwz7qYsfkOfFLBYLioqKAABms9npv8C5w39qfPhKYGCgeB+NGfvJsJ8cG8qwnwz7ybCfDPupiwsLL5aSkoLt27c7nbZ27VrHn5OTkzF48GDx9RQWFqJp06bi/TRW7CfDfnJsKMN+Muwnw34y7Kcug8JjQA2isLAQ4eHhKCgoQFhYWINc5/lHLNxR64hFeXk5mjRpIt5PY8V+Muwnx4Yy7CfDfjLsJ8N+6uJrLLxYaGgoWrRoUe2XGosKADCZTKrsp7FiPxn2k2NDGfaTYT8Z9pNhP3XxiEUD0eKIBRERERFRQ+ERCxIzGo1aj6Br7CfDfnJsKMN+Muwnw34y7KcuHrFoIN58xKKiogJ+fnwfgEvFfjLsJ8eGMuwnw34y7CfDfuriEQsSO/8tbKnu2E+G/eTYUIb9ZNhPhv1k2E9dXFiQWHh4uNYj6Br7ybCfHBvKsJ8M+8mwnwz7qYsLCxKzWq1aj6Br7CfDfnJsKMN+Muwnw34y7KcuLixIzMeHdyMJ9pNhPzk2lGE/GfaTYT8Z9lMXa5IYX/Qkw34y7CfHhjLsJ8N+Muwnw37q4sKCxEpKSrQeQdfYT4b95NhQhv1k2E+G/WTYT11cWJBYRESE1iPoGvvJsJ8cG8qwnwz7ybCfDPupiwsLEsvOztZ6BF1jPxn2k2NDGfaTYT8Z9pNhP3XxA/IaiDd/QB4REREREY9YkJjRaNR6BF1jPxn2k2NDGfaTYT8Z9pNhP3XxiEUD8eYjFna7nW/XJsB+Muwnx4Yy7CfDfjLsJ8N+6mJJEsvMzNR6BF1jPxn2k2NDGfaTYT8Z9pNhP3XxzXsbSNWBocLCQo0nUZ+fn59X3q6Gwn4y7CfHhjLsJ8N+Muwnw361FxoaCoPBUOM2XFg0EIvFAgBISEjQeBIiIiIiorqpzdP5+RqLBmK325Genl6r1Z6eFBYWIiEhAWfOnPG61440BPaTYT85NpRhPxn2k2E/GfarGx6x8CA+Pj5o1aqV1mPUm7CwMH5TCrCfDPvJsaEM+8mwnwz7ybCfevjibSIiIiIiEuPCgoiIiIiIxLiwIJGAgADMmzcPAQEBWo+iS+wnw35ybCjDfjLsJ8N+MuynPr54m4iIiIiIxHjEgoiIiIiIxLiwICIiIiIiMS4siIiIiIhIjAsLcstisWDGjBlo3bo1goKC0L9/f/zyyy+O8xVFwdy5c9GiRQsEBQVh2LBh+Ouvv5z2kZubiwkTJiAsLAwRERGYMmUKioqKGvqm1LuffvoJN910E1q2bAmDwYB169Y5na9Wq4MHD2LgwIEIDAxEQkICXn755fq+aQ3iYv3Wrl2L4cOHo3nz5jAYDEhNTXXZR2lpKR544AE0b94cISEhGDNmDLKyspy2OX36NG644QY0bdoUMTExePTRR1FRUVGPt6zh1NSwvLwcjz/+OLp27Yrg4GC0bNkS99xzD9LT0532wftg9ffB+fPno1OnTggODkazZs0wbNgw7Nmzx2kb9qu+3/mmTZsGg8GApUuXOp3OftX3mzRpEgwGg9PXyJEjnbZhv5rvf0eOHMHNN9+M8PBwBAcH46qrrsLp06cd5zf2/4eoiQsLcuvee+/Fxo0b8emnn+K3337D8OHDMWzYMBiNRgDAyy+/jNdffx3Lly/Hnj17EBwcjBEjRqC0tNSxjwkTJuDw4cPYuHEj1q9fj59++glTp07V6ibVm+LiYnTv3h3Lli1ze74arQoLCzF8+HC0bt0aKSkpeOWVVzB//nysWLGi3m9ffbtYv+LiYgwYMAALFy6sdh8PP/ww/vOf/2DNmjXYvn070tPTMXr0aMf5lZWVuOGGG1BWVoZdu3bh448/xkcffYS5c+eqfnu0UFPDkpIS7N+/H3PmzMH+/fuxdu1aHD16FDfffLPTdrwPVn8f7NChA95880389ttv2LFjBxITEzF8+HBkZ2c7tmG/6vtV+frrr/Hzzz+jZcuWLuexX839Ro4ciYyMDMfXv/71L6fz2a/6fsePH8eAAQPQqVMnbNu2DQcPHsScOXMQGBjo2Kax/z9EVQrRBUpKShRfX19l/fr1TqdfeeWVylNPPaXY7XYlLi5OeeWVVxzn5efnKwEBAcq//vUvRVEU5ffff1cAKL/88otjm++//14xGAyK0WhsmBuiAQDK119/7fi7Wq3eeustpVmzZorNZnNs8/jjjysdO3as51vUsC7sd760tDQFgHLgwAGn0/Pz85UmTZooa9ascZx25MgRBYCye/duRVEU5bvvvlN8fHyUzMxMxzZvv/22EhYW5tTUG9TUsMrevXsVAMqpU6cUReF98Hy16VdQUKAAUDZt2qQoCvudr7p+Z8+eVeLj45VDhw4prVu3VpYsWeI4j/3+x12/iRMnKrfccku1l2G//3HX7/bbb1fuuuuuai/D/4eoi0csyEVFRQUqKyudVvMAEBQUhB07diAtLQ2ZmZkYNmyY47zw8HD07dsXu3fvBgDs3r0bERER6N27t2ObYcOGwcfHx+UpBN5MrVa7d+/GoEGD4O/v79hmxIgROHr0KPLy8hro1nimlJQUlJeXOzXu1KkTLrvsMqfGXbt2RWxsrGObESNGoLCwEIcPH27wmbVWUFAAg8GAiIgIALwP1kVZWRlWrFiB8PBwdO/eHQD7XYzdbsfdd9+NRx99FJdffrnL+ex3cdu2bUNMTAw6duyI+++/Hzk5OY7z2K96drsd3377LTp06IARI0YgJiYGffv2dXq6FP8foi4uLMhFaGgo+vXrh+eeew7p6emorKzEZ599ht27dyMjIwOZmZkA4PQNVvX3qvMyMzMRExPjdL6fnx8iIyMd2zQGarXKzMx0u4/zr6OxyszMhL+/v+OH5CoXNma/c0pLS/H4449j/PjxCAsLA8D7YG2sX78eISEhCAwMxJIlS7Bx40ZERUUBYL+LWbhwIfz8/PDQQw+5PZ/9ajZy5Eh88skn2Lx5MxYuXIjt27fjuuuuQ2VlJQD2q4nJZEJRURFeeukljBw5Ej/++CNuvfVWjB49Gtu3bwfA/4eozU/rAcgzffrpp/jb3/6G+Ph4+Pr64sorr8T48eORkpKi9WhEdInKy8sxbtw4KIqCt99+W+txdGXIkCFITU2F2WzGu+++i3HjxmHPnj0uP9CRs5SUFLz22mvYv38/DAaD1uPo0h133OH4c9euXdGtWze0bdsW27Ztw9ChQzWczPPZ7XYAwC233IKHH34YANCjRw/s2rULy5cvR3JyspbjeSUesSC32rZti+3bt6OoqAhnzpzB3r17UV5ejjZt2iAuLg4AXN4xISsry3FeXFwcTCaT0/kVFRXIzc11bNMYqNUqLi7O7T7Ov47GKi4uDmVlZcjPz3c6/cLGjb1f1aLi1KlT2Lhxo+NoBcD7YG0EBwejXbt2uPrqq/H+++/Dz88P77//PgD2q8l///tfmEwmXHbZZfDz84Ofnx9OnTqFRx55BImJiQDYr67atGmDqKgoHDt2DAD71SQqKgp+fn7o0qWL0+mdO3d2vCsU/x+iLi4sqEbBwcFo0aIF8vLy8MMPP+CWW25BUlIS4uLisHnzZsd2hYWF2LNnD/r16wcA6NevH/Lz852OcGzZsgV2ux19+/Zt8NuhFbVa9evXDz/99BPKy8sd22zcuBEdO3ZEs2bNGujWeKZevXqhSZMmTo2PHj2K06dPOzX+7bffnP7nW/XD9YX/w/FGVYuKv/76C5s2bULz5s2dzud9sO7sdjtsNhsA9qvJ3XffjYMHDyI1NdXx1bJlSzz66KP44YcfALBfXZ09exY5OTlo0aIFAParib+/P6666iocPXrU6fQ///wTrVu3BsD/h6hO61ePk2fasGGD8v333ysnTpxQfvzxR6V79+5K3759lbKyMkVRFOWll15SIiIilG+++UY5ePCgcssttyhJSUmK1Wp17GPkyJFKz549lT179ig7duxQ2rdvr4wfP16rm1RvLBaLcuDAAeXAgQMKAGXx4sXKgQMHHO+4o0ar/Px8JTY2Vrn77ruVQ4cOKatWrVKaNm2qvPPOOw1+e9V2sX45OTnKgQMHlG+//VYBoKxatUo5cOCAkpGR4djHtGnTlMsuu0zZsmWLsm/fPqVfv35Kv379HOdXVFQoV1xxhTJ8+HAlNTVV2bBhgxIdHa088cQTDX5760NNDcvKypSbb75ZadWqlZKamqpkZGQ4vs5/NxPeB933KyoqUp544gll9+7dysmTJ5V9+/YpkydPVgICApRDhw459sF+1X8PX+jCd4VSFParrp/FYlFmzZql7N69W0lLS1M2bdqkXHnllUr79u2V0tJSxz7Yr/r739q1a5UmTZooK1asUP766y/ljTfeUHx9fZX//ve/jn009v+HqIkLC3Jr9erVSps2bRR/f38lLi5OeeCBB5T8/HzH+Xa7XZkzZ44SGxurBAQEKEOHDlWOHj3qtI+cnBxl/PjxSkhIiBIWFqZMnjxZsVgsDX1T6t3WrVsVAC5fEydOVBRFvVa//vqrMmDAACUgIECJj49XXnrppYa6ifXqYv0+/PBDt+fPmzfPsQ+r1ar84x//UJo1a6Y0bdpUufXWW50WHoqiKCdPnlSuu+46JSgoSImKilIeeeQRpby8vAFvaf2pqWHV2/S6+9q6datjH7wPuu9ntVqVW2+9VWnZsqXi7++vtGjRQrn55puVvXv3Ou2D/ar/Hr6Qu4UF+7nvV1JSogwfPlyJjo5WmjRporRu3Vq57777nN72VFHY72L3v/fff19p166dEhgYqHTv3l1Zt26d0z4a+/9D1GRQFEVR8wgIERERERE1PnyNBRERERERiXFhQUREREREYlxYEBERERGRGBcWREREREQkxoUFERERERGJcWFBRERERERiXFgQEREREZEYFxZERERERCTGhQUREemCwWCAwWBAREREg13n/PnzHde7dOnSBrteIiI94sKCiIjq3aRJkxw/oJ//dezYsTrt58MPP8Sff/4pnicxMREGgwE///yz0+kzZszA4MGDHX+fNWsWMjIy0KpVK/F1EhF5Oy4siIioQYwcORIZGRlOX0lJSXXaR0REBGJiYlSZJzAwEI8//niN24SEhCAuLg6+vr6qXCcRkTfjwoKIiBpEQEAA4uLinL6kP7DPnz8fPXr0wAcffIDLLrsMISEh+Mc//oHKykq8/PLLiIuLQ0xMDF544QWXy06dOhU///wzvvvuO9EMRER0jp/WAxAREUkcP34c33//PTZs2IDjx4/jtttuw4kTJ9ChQwds374du3btwt/+9jcMGzYMffv2dVwuKSkJ06ZNwxNPPIGRI0fCx4e/ayMikuCjKBERNYj169cjJCTE8TV27FhV9mu32/HBBx+gS5cuuOmmmzBkyBAcPXoUS5cuRceOHTF58mR07NgRW7dudbns008/jbS0NHz++eeqzEJE1JjxiAURETWIIUOG4O2333b8PTg4WJX9JiYmIjQ01PH32NhY+Pr6Oh2BiI2NhclkcrlsdHQ0Zs2ahblz5+L2229XZR4iosaKRyyIiKhBBAcHo127do6vFi1aqLLfJk2aOP3dYDC4Pc1ut7u9/MyZM2G1WvHWW2+pMg8RUWPFhQURETVqISEhmDNnDl544QVYLBatxyEi0i0uLIiIqNGbOnUqwsPDsXLlSq1HISLSLS4siIio0WvSpAmee+45lJaWaj0KEZFuGRRFUbQegoiI6GIMBgO+/vprjBo1qsGvOzExETNmzMCMGTMa/LqJiPSCRyyIiEg3xo8fj1atWjXY9b344osICQnB6dOnG+w6iYj0ikcsiIhIF44dOwYA8PX1RVJSUoNcZ25uLnJzcwGce2va8PDwBrleIiI94sKCiIiIiIjE+FQoIiIiIiIS48KCiIiIiIjEuLAgIiIiIiIxLiyIiIiIiEiMCwsiIiIiIhLjwoKIiIiIiMS4sCAiIiIiIjEuLIiIiIiISIwLCyIiIiIiEvt/MHRSttzr/+wAAAAASUVORK5CYII=",
      "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 1 (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": 12,
   "id": "17cbeaea",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fit completo:   chi²=56.20,  P=0.0000\n",
      "Senza punto 1:  chi²=1.811,  P=0.4044\n",
      "\n",
      "A:  23.9432 ± 0.0422  to  23.8834 ± 0.0429\n",
      "B:  2719.8356 ± 2.8402  to  2718.1321 ± 2.8464\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": 13,
   "id": "0bc01605",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "dataFrame  CALIBRO\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "a5260403df9c4a96ab08fa1c2cf5b6b0",
       "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"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "dataFrame  CALIBRO TOLTO DATO 1\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "9f06c0d4d33e47f880fcc0b33229c9d6",
       "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=[88.97, …"
      ]
     },
     "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": 14,
   "id": "d2c1a550",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "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": 15,
   "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 trattate come prima\n",
    "- $\\omega$, c trattati con semidispersione"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "d6195b96",
   "metadata": {},
   "outputs": [],
   "source": [
    "dfSonar = pd.read_csv(r'molla1Sonar.csv')\n",
    "\n",
    "# Bilancia trattata esattamente come prima\n",
    "dfSonar = calcola_stats(dfSonar, \"m\",  ERR_BILANCIA)\n",
    "\n",
    "# Semidispersioni su w e uw\n",
    "dfSonar['w']  = (dfSonar['w1'] + dfSonar['w2']) / 2\n",
    "dfSonar['uw'] = np.maximum((dfSonar['w1'] - dfSonar['w2']).abs() / 2,\n",
    "                            np.sqrt(dfSonar['uw1']**2 + dfSonar['uw2']**2))\n",
    "\n",
    "# Semidispersione su c e uc\n",
    "dfSonar['c']  = (dfSonar['c1'] + dfSonar['c2']) / 2\n",
    "dfSonar['uc'] = np.maximum((dfSonar['c1'] - dfSonar['c2']).abs() / 2,\n",
    "                            np.sqrt(dfSonar['uc1']**2 + dfSonar['uc2']**2))\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": 17,
   "id": "02e2d183",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "df2bc11f953c400c8b820daa87af2178",
       "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=[108.61,…"
      ]
     },
     "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": 18,
   "id": "06f9ccef",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ax + B : \n",
      "AS      = 23.5225 ± 0.0853\n",
      "BS      = 7371.9487 ± 21.4728\n",
      "cov_ABS = 1.830281\n",
      "chi²    = 3.8872\n",
      "P(chi², ∞)= 0.1432\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": 19,
   "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": 20,
   "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": 21,
   "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 1 (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": 22,
   "id": "4088453c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "c = 0.00301841231512225*c_raw*v0/sqrt(0.00366099212886692*T + 1)\n",
      "sigma_c = v0*sqrt(3.05277451303515e-11*c_raw**2*sigma_T**2 + 9.11081290408163e-6*sigma_c_raw**2*(0.00366099212886692*T + 1)**2)/(0.00366099212886692*T + 1)**(3/2)\n",
      "\n",
      "Formula LaTeX:\n",
      "c = \\frac{0.00301841231512225 c_{raw} v_{0}}{\\sqrt{0.00366099212886692 T + 1}}\n",
      "sigma_c = \\frac{v_{0} \\sqrt{3.05277451303515 \\cdot 10^{-11} c_{raw}^{2} \\sigma_{T}^{2} + 9.11081290408163 \\cdot 10^{-6} \\sigma_{c raw}^{2} \\left(0.00366099212886692 T + 1\\right)^{2}}}{\\left(0.00366099212886692 T + 1\\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",
    "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": 23,
   "id": "1584a5d4",
   "metadata": {},
   "outputs": [],
   "source": [
    "Temperatura = 22.6\n",
    "uTemperatura = 0.7 / 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)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "ac4860fa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "31a0e5a6b1c44157b5e5ac5348c72645",
       "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=[108.61,…"
      ]
     },
     "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": 25,
   "id": "8917049c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fit completo:   chi²=3.89,  P=0.1432\n",
      "Temperatura :  chi²=1.632,  P=0.4422\n",
      "\n",
      "A:  23.5225 ± 0.0853  to  23.6160 ± 0.1404\n",
      "B:  7371.9487 ± 21.4728  to  7365.6372 ± 35.4592\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": 26,
   "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": 27,
   "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": 40,
   "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 1 (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": 29,
   "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": 30,
   "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": 31,
   "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": 32,
   "id": "455271a9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "3b51a0edcf7047c0ab2e16af0a3de188",
       "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=[108.61,…"
      ]
     },
     "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": 33,
   "id": "02119d66",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ax + B : \n",
      "AD      = 23.8854 ± 0.0133\n",
      "BD      = 1.5710 ± 0.0856\n",
      "cov_ABD = -0.001129\n",
      "chi²    = 27.0310\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": 34,
   "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": 35,
   "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": 36,
   "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 1 (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": "b5ca1727",
   "metadata": {},
   "source": [
    "# Raccolta finale di tutti i dati"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "e87e24b7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Calibro Con tutti i dati\n",
      "AC      = 23.9432 ± 0.0422\n",
      "BC      = 2719.8356 ± 2.8402\n",
      "cov_ABC = 0.118646\n",
      "chi²    = 56.2014\n",
      "GdL     = 5\n",
      "P(chi², ∞)= 0.0000\n",
      "\n",
      "Calibro tolto il dato 1\n",
      "AC      = 23.8834 ± 0.0429\n",
      "BC      = 2718.1321 ± 2.8464\n",
      "cov_ABC = 0.120249\n",
      "chi²    = 1.8108\n",
      "GdL     = 4\n",
      "P(chi², ∞)= 0.4044\n",
      "\n",
      "Sonar caso statico (temperatura non considerata)\n",
      "AS      = 23.5225 ± 0.0853\n",
      "BS      = 7371.9487 ± 21.4728\n",
      "cov_ABS = 1.830281\n",
      "chi²    = 3.8872\n",
      "GdL     = 4\n",
      "P(chi², ∞)= 0.1432\n",
      "\n",
      "Sonar caso statico (temperatura considerata)\n",
      "AS      = 23.6160 ± 0.1404\n",
      "BS      = 7365.6372 ± 35.4592\n",
      "cov_ABS = 4.976670\n",
      "chi²    = 1.6321\n",
      "GdL     = 4\n",
      "P(chi², ∞)= 0.4422\n",
      "\n",
      "Sonar caso Dinamico\n",
      "AD      = 23.8854 ± 0.0133\n",
      "BD      = 1.5710 ± 0.0856\n",
      "cov_ABD = -0.001129\n",
      "chi²    = 27.0310\n",
      "GdL     = 4\n",
      "P(chi², ∞)= 0.0000\n"
     ]
    }
   ],
   "source": [
    "print(\"Calibro Con tutti i dati\")\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",
    "\n",
    "print(\"\\nCalibro tolto il dato 1\")\n",
    "print(f\"AC      = {AC2:.4f} ± {uAC2:.4f}\")\n",
    "print(f\"BC      = {BC2:.4f} ± {uBC2:.4f}\")\n",
    "print(f\"cov_ABC = {covABC2:.6f}\")\n",
    "print(f\"chi²    = {chiC2:.4f}\")\n",
    "print(f\"GdL     = {len(dfCalibro_senza1)}\")\n",
    "print(f\"P(chi², ∞)= {PC2:.4f}\")\n",
    "\n",
    "print(\"\\nSonar caso statico (temperatura non considerata)\")\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",
    "\n",
    "print(\"\\nSonar caso statico (temperatura considerata)\")\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",
    "\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}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "dc913446",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "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",
    "]\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": 38,
   "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": 57,
   "id": "3005eb0f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "2 * (1 - stats.t.cdf(abs(2.6076), df=6))\n",
    "len(dfCalibro)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "57de948b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Compatibilità: Calibro vs Sonar statico (T considerata)\n",
      "Sigma             t    p-value\n",
      "------------------------------\n",
      "1σ           5.0132     0.0015\n",
      "2σ           2.5066     0.0406\n",
      "3σ           1.6711     0.1386\n",
      "\n",
      "\n",
      "Compatibilità: Calibro vs Sonar dinamico\n",
      "Sigma             t    p-value\n",
      "------------------------------\n",
      "1σ           2.6076     0.0350\n",
      "2σ           1.3038     0.2335\n",
      "3σ           0.8692     0.4135\n",
      "\n",
      "\n",
      "Compatibilità: Sonar Dinamico vs Sonar statico (T considerata)\n",
      "Sigma             t    p-value\n",
      "------------------------------\n",
      "1σ           3.8197     0.0088\n",
      "2σ           1.9098     0.1047\n",
      "3σ           1.2732     0.2500\n"
     ]
    }
   ],
   "source": [
    "# Ringraziate Cloude per questo incredibile print\n",
    "print(\"Compatibilità: Calibro vs Sonar statico (T considerata)\")\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),\n",
    "                                    AS2,  uAS2*n, len(dfSonar))\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),\n",
    "                                    AD,  uAD*n,  len(dfSonar))\n",
    "    print(f\"{n}σ         {res['t']:>8.4f} {res['p']:>10.4f}\")\n",
    "\n",
    "print(\"\\n\\nCompatibilità: Sonar Dinamico vs Sonar statico (T considerata)\")\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),\n",
    "                                    AS2, uAS2*n, len(dfSonar))\n",
    "    print(f\"{n}σ         {res['t']:>8.4f} {res['p']:>10.4f}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b66ccc91",
   "metadata": {},
   "source": [
    "# Note finali\n",
    "Chiaramente i dati presi con il sonar statico soffrono di altri errori che dovremmo discutere come introdurre, sicuramente soffrono della precisione con cui abbiamo puntato il sonar.\n",
    "\n",
    "La temperatura sfortunatamente è stata presa con troppa poca attenzione e questo fa perdere di integrità hai nostri dati, ma altro per ora non mi viene su 2 piedi.\n",
    "\n",
    "Abbiamo almeno una buona basa su cui poter ragionare."
   ]
  }
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