example_analytic_erlang_c_ext.ipynb

{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Extended Erlang C (M/M/c/K+M model)\n",
    "\n",
    "This is an Erlang C model with impatient clients."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Importing modules"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Erlang module\n",
    "from queuesim.analytic import erlang_c_ext_table\n",
    "\n",
    "# Plotting modules\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.ticker as formater\n",
    "import seaborn as sns\n",
    "\n",
    "# Defining general plot style\n",
    "sns.set()\n",
    "percent_formater = formater.PercentFormatter(xmax=1, decimals=0)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Mean waiting time as a function of &rho;"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>lambda</th>\n",
       "      <th>mu</th>\n",
       "      <th>nu</th>\n",
       "      <th>a</th>\n",
       "      <th>c</th>\n",
       "      <th>K</th>\n",
       "      <th>rho_offered</th>\n",
       "      <th>rho_real</th>\n",
       "      <th>P(blocked)</th>\n",
       "      <th>P(A)</th>\n",
       "      <th>E[N_Q]</th>\n",
       "      <th>E[N]</th>\n",
       "      <th>E[W]</th>\n",
       "      <th>E[V]</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.025000</td>\n",
       "      <td>0.001667</td>\n",
       "      <td>0.001111</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>10</td>\n",
       "      <td>20</td>\n",
       "      <td>1.500000</td>\n",
       "      <td>0.990567</td>\n",
       "      <td>0.093936</td>\n",
       "      <td>0.271157</td>\n",
       "      <td>5.527938</td>\n",
       "      <td>15.433612</td>\n",
       "      <td>221.117501</td>\n",
       "      <td>617.344480</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.023810</td>\n",
       "      <td>0.001667</td>\n",
       "      <td>0.001111</td>\n",
       "      <td>14.285714</td>\n",
       "      <td>10</td>\n",
       "      <td>20</td>\n",
       "      <td>1.428571</td>\n",
       "      <td>0.986145</td>\n",
       "      <td>0.074228</td>\n",
       "      <td>0.254351</td>\n",
       "      <td>5.045798</td>\n",
       "      <td>14.907245</td>\n",
       "      <td>211.923524</td>\n",
       "      <td>626.104299</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.022727</td>\n",
       "      <td>0.001667</td>\n",
       "      <td>0.001111</td>\n",
       "      <td>13.636364</td>\n",
       "      <td>10</td>\n",
       "      <td>20</td>\n",
       "      <td>1.363636</td>\n",
       "      <td>0.980407</td>\n",
       "      <td>0.057849</td>\n",
       "      <td>0.236889</td>\n",
       "      <td>4.565157</td>\n",
       "      <td>14.369230</td>\n",
       "      <td>200.866901</td>\n",
       "      <td>632.246130</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.021739</td>\n",
       "      <td>0.001667</td>\n",
       "      <td>0.001111</td>\n",
       "      <td>13.043478</td>\n",
       "      <td>10</td>\n",
       "      <td>20</td>\n",
       "      <td>1.304348</td>\n",
       "      <td>0.973246</td>\n",
       "      <td>0.044505</td>\n",
       "      <td>0.219091</td>\n",
       "      <td>4.095784</td>\n",
       "      <td>13.828240</td>\n",
       "      <td>188.406086</td>\n",
       "      <td>636.099019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.020833</td>\n",
       "      <td>0.001667</td>\n",
       "      <td>0.001111</td>\n",
       "      <td>12.500000</td>\n",
       "      <td>10</td>\n",
       "      <td>20</td>\n",
       "      <td>1.250000</td>\n",
       "      <td>0.964613</td>\n",
       "      <td>0.033838</td>\n",
       "      <td>0.201283</td>\n",
       "      <td>3.646344</td>\n",
       "      <td>13.292474</td>\n",
       "      <td>175.024500</td>\n",
       "      <td>638.038749</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.020000</td>\n",
       "      <td>0.001667</td>\n",
       "      <td>0.001111</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>10</td>\n",
       "      <td>20</td>\n",
       "      <td>1.200000</td>\n",
       "      <td>0.954530</td>\n",
       "      <td>0.025460</td>\n",
       "      <td>0.183777</td>\n",
       "      <td>3.223770</td>\n",
       "      <td>12.769071</td>\n",
       "      <td>161.188509</td>\n",
       "      <td>638.453569</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.019231</td>\n",
       "      <td>0.001667</td>\n",
       "      <td>0.001111</td>\n",
       "      <td>11.538462</td>\n",
       "      <td>10</td>\n",
       "      <td>20</td>\n",
       "      <td>1.153846</td>\n",
       "      <td>0.943078</td>\n",
       "      <td>0.018984</td>\n",
       "      <td>0.166850</td>\n",
       "      <td>2.832960</td>\n",
       "      <td>12.263737</td>\n",
       "      <td>147.313923</td>\n",
       "      <td>637.714312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.018519</td>\n",
       "      <td>0.001667</td>\n",
       "      <td>0.001111</td>\n",
       "      <td>11.111111</td>\n",
       "      <td>10</td>\n",
       "      <td>20</td>\n",
       "      <td>1.111111</td>\n",
       "      <td>0.930385</td>\n",
       "      <td>0.014048</td>\n",
       "      <td>0.150723</td>\n",
       "      <td>2.476755</td>\n",
       "      <td>11.780606</td>\n",
       "      <td>133.744791</td>\n",
       "      <td>636.152738</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.017857</td>\n",
       "      <td>0.001667</td>\n",
       "      <td>0.001111</td>\n",
       "      <td>10.714286</td>\n",
       "      <td>10</td>\n",
       "      <td>20</td>\n",
       "      <td>1.071429</td>\n",
       "      <td>0.916615</td>\n",
       "      <td>0.010332</td>\n",
       "      <td>0.135561</td>\n",
       "      <td>2.156156</td>\n",
       "      <td>11.322309</td>\n",
       "      <td>120.744762</td>\n",
       "      <td>634.049301</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.017241</td>\n",
       "      <td>0.001667</td>\n",
       "      <td>0.001111</td>\n",
       "      <td>10.344828</td>\n",
       "      <td>10</td>\n",
       "      <td>20</td>\n",
       "      <td>1.034483</td>\n",
       "      <td>0.901949</td>\n",
       "      <td>0.007562</td>\n",
       "      <td>0.121473</td>\n",
       "      <td>1.870668</td>\n",
       "      <td>10.890161</td>\n",
       "      <td>108.498762</td>\n",
       "      <td>631.629311</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0.016667</td>\n",
       "      <td>0.001667</td>\n",
       "      <td>0.001111</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>10</td>\n",
       "      <td>20</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.886573</td>\n",
       "      <td>0.005514</td>\n",
       "      <td>0.108511</td>\n",
       "      <td>1.618693</td>\n",
       "      <td>10.484422</td>\n",
       "      <td>97.121595</td>\n",
       "      <td>629.065339</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0.016129</td>\n",
       "      <td>0.001667</td>\n",
       "      <td>0.001111</td>\n",
       "      <td>9.677419</td>\n",
       "      <td>10</td>\n",
       "      <td>20</td>\n",
       "      <td>0.967742</td>\n",
       "      <td>0.870667</td>\n",
       "      <td>0.004011</td>\n",
       "      <td>0.096688</td>\n",
       "      <td>1.397905</td>\n",
       "      <td>10.104571</td>\n",
       "      <td>86.670098</td>\n",
       "      <td>626.483407</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0.015625</td>\n",
       "      <td>0.001667</td>\n",
       "      <td>0.001111</td>\n",
       "      <td>9.375000</td>\n",
       "      <td>10</td>\n",
       "      <td>20</td>\n",
       "      <td>0.937500</td>\n",
       "      <td>0.854398</td>\n",
       "      <td>0.002913</td>\n",
       "      <td>0.085980</td>\n",
       "      <td>1.205566</td>\n",
       "      <td>9.749545</td>\n",
       "      <td>77.156215</td>\n",
       "      <td>623.970885</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0.015152</td>\n",
       "      <td>0.001667</td>\n",
       "      <td>0.001111</td>\n",
       "      <td>9.090909</td>\n",
       "      <td>10</td>\n",
       "      <td>20</td>\n",
       "      <td>0.909091</td>\n",
       "      <td>0.837917</td>\n",
       "      <td>0.002114</td>\n",
       "      <td>0.076338</td>\n",
       "      <td>1.038776</td>\n",
       "      <td>9.417948</td>\n",
       "      <td>68.559235</td>\n",
       "      <td>621.584583</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>0.014706</td>\n",
       "      <td>0.001667</td>\n",
       "      <td>0.001111</td>\n",
       "      <td>8.823529</td>\n",
       "      <td>10</td>\n",
       "      <td>20</td>\n",
       "      <td>0.882353</td>\n",
       "      <td>0.821356</td>\n",
       "      <td>0.001534</td>\n",
       "      <td>0.067700</td>\n",
       "      <td>0.894651</td>\n",
       "      <td>9.108208</td>\n",
       "      <td>60.836274</td>\n",
       "      <td>619.358155</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>0.014286</td>\n",
       "      <td>0.001667</td>\n",
       "      <td>0.001111</td>\n",
       "      <td>8.571429</td>\n",
       "      <td>10</td>\n",
       "      <td>20</td>\n",
       "      <td>0.857143</td>\n",
       "      <td>0.804825</td>\n",
       "      <td>0.001114</td>\n",
       "      <td>0.059990</td>\n",
       "      <td>0.770438</td>\n",
       "      <td>8.818691</td>\n",
       "      <td>53.930691</td>\n",
       "      <td>617.308368</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>0.013889</td>\n",
       "      <td>0.001667</td>\n",
       "      <td>0.001111</td>\n",
       "      <td>8.333333</td>\n",
       "      <td>10</td>\n",
       "      <td>20</td>\n",
       "      <td>0.833333</td>\n",
       "      <td>0.788419</td>\n",
       "      <td>0.000810</td>\n",
       "      <td>0.053130</td>\n",
       "      <td>0.663590</td>\n",
       "      <td>8.547780</td>\n",
       "      <td>47.778498</td>\n",
       "      <td>615.440145</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>0.013514</td>\n",
       "      <td>0.001667</td>\n",
       "      <td>0.001111</td>\n",
       "      <td>8.108108</td>\n",
       "      <td>10</td>\n",
       "      <td>20</td>\n",
       "      <td>0.810811</td>\n",
       "      <td>0.772213</td>\n",
       "      <td>0.000590</td>\n",
       "      <td>0.047042</td>\n",
       "      <td>0.571797</td>\n",
       "      <td>8.293925</td>\n",
       "      <td>42.313007</td>\n",
       "      <td>613.750450</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      lambda        mu        nu          a   c   K  rho_offered  rho_real  \\\n",
       "0   0.025000  0.001667  0.001111  15.000000  10  20     1.500000  0.990567   \n",
       "1   0.023810  0.001667  0.001111  14.285714  10  20     1.428571  0.986145   \n",
       "2   0.022727  0.001667  0.001111  13.636364  10  20     1.363636  0.980407   \n",
       "3   0.021739  0.001667  0.001111  13.043478  10  20     1.304348  0.973246   \n",
       "4   0.020833  0.001667  0.001111  12.500000  10  20     1.250000  0.964613   \n",
       "5   0.020000  0.001667  0.001111  12.000000  10  20     1.200000  0.954530   \n",
       "6   0.019231  0.001667  0.001111  11.538462  10  20     1.153846  0.943078   \n",
       "7   0.018519  0.001667  0.001111  11.111111  10  20     1.111111  0.930385   \n",
       "8   0.017857  0.001667  0.001111  10.714286  10  20     1.071429  0.916615   \n",
       "9   0.017241  0.001667  0.001111  10.344828  10  20     1.034483  0.901949   \n",
       "10  0.016667  0.001667  0.001111  10.000000  10  20     1.000000  0.886573   \n",
       "11  0.016129  0.001667  0.001111   9.677419  10  20     0.967742  0.870667   \n",
       "12  0.015625  0.001667  0.001111   9.375000  10  20     0.937500  0.854398   \n",
       "13  0.015152  0.001667  0.001111   9.090909  10  20     0.909091  0.837917   \n",
       "14  0.014706  0.001667  0.001111   8.823529  10  20     0.882353  0.821356   \n",
       "15  0.014286  0.001667  0.001111   8.571429  10  20     0.857143  0.804825   \n",
       "16  0.013889  0.001667  0.001111   8.333333  10  20     0.833333  0.788419   \n",
       "17  0.013514  0.001667  0.001111   8.108108  10  20     0.810811  0.772213   \n",
       "\n",
       "    P(blocked)      P(A)    E[N_Q]       E[N]        E[W]        E[V]  \n",
       "0     0.093936  0.271157  5.527938  15.433612  221.117501  617.344480  \n",
       "1     0.074228  0.254351  5.045798  14.907245  211.923524  626.104299  \n",
       "2     0.057849  0.236889  4.565157  14.369230  200.866901  632.246130  \n",
       "3     0.044505  0.219091  4.095784  13.828240  188.406086  636.099019  \n",
       "4     0.033838  0.201283  3.646344  13.292474  175.024500  638.038749  \n",
       "5     0.025460  0.183777  3.223770  12.769071  161.188509  638.453569  \n",
       "6     0.018984  0.166850  2.832960  12.263737  147.313923  637.714312  \n",
       "7     0.014048  0.150723  2.476755  11.780606  133.744791  636.152738  \n",
       "8     0.010332  0.135561  2.156156  11.322309  120.744762  634.049301  \n",
       "9     0.007562  0.121473  1.870668  10.890161  108.498762  631.629311  \n",
       "10    0.005514  0.108511  1.618693  10.484422   97.121595  629.065339  \n",
       "11    0.004011  0.096688  1.397905  10.104571   86.670098  626.483407  \n",
       "12    0.002913  0.085980  1.205566   9.749545   77.156215  623.970885  \n",
       "13    0.002114  0.076338  1.038776   9.417948   68.559235  621.584583  \n",
       "14    0.001534  0.067700  0.894651   9.108208   60.836274  619.358155  \n",
       "15    0.001114  0.059990  0.770438   8.818691   53.930691  617.308368  \n",
       "16    0.000810  0.053130  0.663590   8.547780   47.778498  615.440145  \n",
       "17    0.000590  0.047042  0.571797   8.293925   42.313007  613.750450  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Arrival rate range\n",
    "l_range = [1 / mean_i for mean_i in range(40, 75, 2)]\n",
    "\n",
    "# Service rate\n",
    "mu = 1 / 600\n",
    "\n",
    "# Waiting cancelation rate\n",
    "nu = 1 / 900\n",
    "\n",
    "# Number of operators\n",
    "c = 10\n",
    "\n",
    "# System size\n",
    "K = 20\n",
    "\n",
    "# Erlang C results for different values of lambda\n",
    "results = erlang_c_ext_table([(l, mu, nu, c, K) for l in l_range])\n",
    "\n",
    "# Display results table\n",
    "results"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Optional: Interactive diagram mode\n",
    "# Run \"pip install ipympl\" first\n",
    "# %matplotlib ipympl"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x27ad1398b50>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1600x900 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(16, 9))\n",
    "\n",
    "line1 = ax.plot(results[\"rho_offered\"], results[\"E[W]\"], 'b', label=\"E[W]\")\n",
    "ax.tick_params(axis='y', labelcolor='b')\n",
    "ax.set_xlabel(\"Offered utilization\")\n",
    "ax.set_ylabel(\"E[W]\", color='b')\n",
    "ax.xaxis.set_major_formatter(percent_formater)\n",
    "lines1, labels1 = ax.get_legend_handles_labels()\n",
    "\n",
    "ax = ax.twinx()\n",
    "line2 = ax.plot(results[\"rho_offered\"], results[\"P(A)\"], 'r', label=\"P(A) (waiting cancelations)\")\n",
    "line3 = ax.plot(results[\"rho_offered\"], results[\"P(blocked)\"], 'r--', label=\"P(blocked) (blocked clients)\")\n",
    "line4 = ax.plot(results[\"rho_offered\"], results[\"rho_real\"], 'g', label=\"$\\\\rho$ (real utilization)\")\n",
    "ax.set_ylabel(\"P(A) and $\\\\rho$\")\n",
    "ax.yaxis.set_major_formatter(percent_formater)\n",
    "lines2, labels2 = ax.get_legend_handles_labels()\n",
    "\n",
    "ax.set_title(\"Extended Erlang C model at different utilizations\")\n",
    "ax.legend(lines1 + lines2, labels1 + labels2)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.0"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}