Planck.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "3020493b",
   "metadata": {},
   "source": [
    "### Legge di Planck"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "c7d33afb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Flusso (dalla legge di Stefan): 6.2624e+07 W/m^2\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Programma Python per il calcolo dello spettro\n",
    "# di emissione di un corpo che si trova alla \n",
    "# temperatura T (spettro di \"corpo nero\")\n",
    "\n",
    "# librerie da importare nell'ambiente Python\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Costanti \"a\" e \"b\" della legge di Planck\n",
    "a=3.7469543e+20\n",
    "b=14397733.98663405\n",
    "c=299000000\n",
    "\n",
    "# Costante di Stefan\n",
    "sigma=5.6225e-8\n",
    "\n",
    "#-------- Sezione di input ---------\n",
    "\n",
    "# Temperatura (in K) per la quale effettuare il calcolo\n",
    "Temp=5777.\n",
    "\n",
    "# Valori minimo e massimo (in nm) dell'intervallo di lunghezze \n",
    "# d'onda su cui effettuare il calcolo\n",
    "lam_min=50.\n",
    "lam_max=2500.\n",
    "\n",
    "\n",
    "# \"Risoluzione\": res=5. significa che il calcolo viene\n",
    "# effettuato per lunghezze d'onda intervallate di 5 nm\n",
    "# a partire da lam_min, fino a lam_max \n",
    "res=5.\n",
    "\n",
    "#---- Fine della sezione di input -------\n",
    "\n",
    "# Numero di valori di lunghezze \n",
    "npoint=int((lam_max-lam_min)/res)\n",
    "\n",
    "# Generazione della lista di valori delle \n",
    "# lunghezze d'onda\n",
    "lam_list=np.linspace(lam_min, lam_max, npoint)\n",
    "\n",
    "# Funzione di Planck\n",
    "# La funzione riceve come argomenti un valore di lunghezza\n",
    "# d'onda (lam) e un valore di temperatura (tt)\n",
    "def planck(lam,tt):\n",
    "    f1=np.exp(b/(lam*tt)) - 1\n",
    "    denom=f1*lam**5\n",
    "    return a/denom\n",
    "\n",
    "# Applicazione della funzione planck su tutti i valori\n",
    "# di lunghezza d'onda contenuti nella lista lam_list:\n",
    "    \n",
    "# Inizializzazione di una lista che conterra' i risultati\n",
    "power_list=np.array([])\n",
    "\n",
    "# Ciclo su tutti i valori contenuti in lam_list\n",
    "for il in lam_list:\n",
    "    p_l=planck(il, Temp)\n",
    "    power_list=np.append(power_list, p_l) \n",
    "    \n",
    "    \n",
    "Int_tot=sigma*Temp**4\n",
    "\n",
    "\n",
    "print(\"\\nFlusso (dalla legge di Stefan): %5.4e W/m^2\" % Int_tot)  \n",
    "\n",
    "# Parte grafica\n",
    "plt.figure()\n",
    "plt.plot(lam_list, power_list,\"k-\")\n",
    "plt.xlabel(\"Lunghezza d'onda (nm)\")\n",
    "plt.ylabel(\"Power (W/nm m^2)\")\n",
    "plt.title(\"T=\" + str(Temp))\n",
    "plt.ylim(0)\n",
    "plt.xlim(0)\n",
    "# \n",
    "# plt.savefig('filename.png', dpi=600)\n",
    "plt.show()"
   ]
  }
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