module3/exo3/exercice.ipynb

parent 5531fa3e
......@@ -2,7 +2,7 @@
"cells": [
{
"cell_type": "code",
"execution_count": 54,
"execution_count": 64,
"metadata": {},
"outputs": [],
"source": [
......@@ -15,7 +15,7 @@
},
{
"cell_type": "code",
"execution_count": 55,
"execution_count": 65,
"metadata": {},
"outputs": [],
"source": [
......@@ -33,7 +33,7 @@
},
{
"cell_type": "code",
"execution_count": 56,
"execution_count": 66,
"metadata": {},
"outputs": [
{
......@@ -1060,7 +1060,7 @@
"[794 rows x 11 columns]"
]
},
"execution_count": 56,
"execution_count": 66,
"metadata": {},
"output_type": "execute_result"
}
......@@ -1075,7 +1075,7 @@
},
{
"cell_type": "code",
"execution_count": 57,
"execution_count": 67,
"metadata": {},
"outputs": [
{
......@@ -1155,7 +1155,7 @@
"1 [ppm] [ppm] [ppm] NaN "
]
},
"execution_count": 57,
"execution_count": 67,
"metadata": {},
"output_type": "execute_result"
}
......@@ -1167,7 +1167,7 @@
},
{
"cell_type": "code",
"execution_count": 58,
"execution_count": 68,
"metadata": {},
"outputs": [
{
......@@ -2194,7 +2194,7 @@
"[792 rows x 11 columns]"
]
},
"execution_count": 58,
"execution_count": 68,
"metadata": {},
"output_type": "execute_result"
}
......@@ -2209,7 +2209,7 @@
},
{
"cell_type": "code",
"execution_count": 59,
"execution_count": 69,
"metadata": {},
"outputs": [],
"source": [
......@@ -2218,7 +2218,7 @@
},
{
"cell_type": "code",
"execution_count": 60,
"execution_count": 70,
"metadata": {},
"outputs": [
{
......@@ -2245,28 +2245,28 @@
},
{
"cell_type": "code",
"execution_count": 61,
"execution_count": 71,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/opt/conda/lib/python3.6/site-packages/ipykernel_launcher.py:14: SettingWithCopyWarning: \n",
"/opt/conda/lib/python3.6/site-packages/ipykernel_launcher.py:13: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
" \n"
" del sys.path[0]\n"
]
},
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x7f47673520f0>"
"<matplotlib.axes._subplots.AxesSubplot at 0x7f14c6eadc18>"
]
},
"execution_count": 61,
"execution_count": 71,
"metadata": {},
"output_type": "execute_result"
},
......@@ -2318,7 +2318,7 @@
},
{
"cell_type": "code",
"execution_count": 23,
"execution_count": 72,
"metadata": {},
"outputs": [
{
......@@ -2350,7 +2350,7 @@
}
],
"source": [
"dates = data[\" Yr\"] # Colonne des dates\n",
"dates = data[\" Yr\"] # Colonne des datess\n",
"co2_concentration_series = data[\" CO2\"].astype(float) # Colonne de concentration de CO2 (avant ajustement saisonnier)\n",
"\n",
"# Appliquer la transformation de Fourier pour identifier les composantes périodiques\n",
......@@ -2383,7 +2383,7 @@
},
{
"cell_type": "code",
"execution_count": 27,
"execution_count": 73,
"metadata": {},
"outputs": [
{
......@@ -2426,7 +2426,7 @@
},
{
"cell_type": "code",
"execution_count": 45,
"execution_count": 74,
"metadata": {},
"outputs": [
{
......@@ -2491,12 +2491,92 @@
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Prévision de 2024 et 2025:"
]
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 75,
"metadata": {},
"outputs": [],
"source": []
"outputs": [
{
"data": {
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\n",
"text/plain": [
"<Figure size 1080x432 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"from numpy.fft import fft\n",
"from scipy.signal import find_peaks\n",
"from scipy.optimize import curve_fit\n",
"import matplotlib.pyplot as plt\n",
"# Extraire la colonne des dates et de CO2\n",
"dates = year\n",
"dates = np.append(dates, [2024, 2025])\n",
"\n",
"co2_data = yearly_CO2\n",
"#.astype(float).values\n",
"#co2_data = np.pad(co2_data, (0, 2), 'constant', constant_values=(0, 0))\n",
"\n",
"\n",
"# Utilisez le modèle linéaire et les paramètres estimés pour faire la prédiction\n",
"prediction_2024 = linear_model(68 + 2024 - 1958, *popt)\n",
"prediction_2025 = linear_model(68 + 2025 - 1958, *popt)\n",
"\n",
"# Ajoutez ces prévisions à co2_data\n",
"co2_data = np.append(co2_data, [prediction_2024, prediction_2025])\n",
"\n",
"\n",
"\n",
"# Appliquer la transformation de Fourier aux données pour identifier l'oscillation périodique\n",
"co2_fft = fft(co2_data)\n",
"frequencies = np.fft.fftfreq(len(co2_data))\n",
"amplitudes = np.abs(co2_fft)\n",
"\n",
"# Trouver les fréquences principales (les périodes des oscillations)\n",
"peaks, _ = find_peaks(amplitudes)\n",
"periods = 1 / frequencies[peaks]\n",
"\n",
"# Créer un modèle simple pour la contribution lente: une régression linéaire\n",
"def linear_model(x, a, b):\n",
" return a * x + b\n",
"\n",
"# Adapter le modèle aux données pour estimer les paramètres a et b\n",
"popt, _ = curve_fit(linear_model, np.arange(len(co2_data)), co2_data)\n",
"\n",
"# Créer un graphique pour visualiser l'oscillation périodique\n",
"plt.figure(figsize=(15, 6))\n",
"plt.subplot(2, 1, 1)\n",
"plt.plot(dates, co2_data)\n",
"plt.title('Concentration de CO2 avec Oscillation Périodique')\n",
"\n",
"# Extrapoler la tendance lente jusqu'à 2025\n",
"years = np.arange(1958, 2026)\n",
"extrapolated_data = linear_model(len(co2_data)+ years - 1958, *popt)\n",
"\n",
"# Créer un graphique pour visualiser la contribution lente et l'extrapolation\n",
"plt.subplot(2, 1, 2)\n",
"plt.plot(dates, co2_data, label='Données originales')\n",
"plt.plot(dates, extrapolated_data, label='Extrapolation', linestyle='--', color='red')\n",
"plt.title('Contribution Lente et Extrapolation jusqu\\'à 2025')\n",
"plt.xlabel('Année')\n",
"plt.ylabel('Concentration de CO2')\n",
"plt.legend()\n",
"\n",
"plt.tight_layout()\n",
"plt.show()"
]
}
],
"metadata": {
......
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