# Predict CO2 concentration using exponential model
-y_train_exp = exp_model(x_train, *exp_par[0])
+
+
# Predict CO2 concentration using exponential model for train and test sets
+y_train_exp = exp_model(x_train, *exp_par[0])
+y_test_exp = exp_model(x_test, *exp_par[0])
-
+
# Define lambda function for the mean absolute error formulamae_fn =lambda obs,pred: np.mean(np.abs(obs - pred))
-# Compute MAE between observed and predicted carbon dioxide using the expoential model
+# Compute MAE between observed and predicted carbon dioxide using the exponetial modelmae_train_exp = mae_fn(y_train, y_train_exp)
-print('MAE using the exponential model is:',np.round(mae_train_exp, 2), 'ppm')
+print('Exponential model MAE for train dataset:',np.round(mae_train_exp, 2), 'ppm')
+
+mae_test_exp = mae_fn(y_test, y_test_exp)
+print('Exponential model MAE for test dataset:',np.round(mae_test_exp, 2), 'ppm')
-
MAE using the exponential model is: 1.87 ppm
+
Exponential model MAE for train dataset: 1.87 ppm
+Exponential model MAE for test dataset: 2.06 ppm
# Check if residuals approach a zero meanprint('Mean residuals (ppm):', np.mean(residuals_exp_fit))
@@ -1172,27 +1177,26 @@
Deter
To determine the seasonality of the data we will use the de-trended residuals.
y(t) = A \ sin[2 \pi (m + phi) ]
t is time since March, 1958 (the start of the data set) A is amplitude of the wave m is the fractional month (Jan is zero and Dec is 1) phi is the phase constant (an offset to align the sine wave)
# Generate timeseries using sinusoidal-exponential modely_train_sin = sin_model(x_train, *sin_par[0])
-
+
# Visualize residuals of the exponential fit and the fitted sinusoidal modelplt.figure(figsize=(10,4))plt.scatter(df_train['decimal_date'], residuals_exp_fit, facecolor='w', edgecolor='k')
@@ -1203,7 +1207,7 @@
Deter
-
+
# Close up view for a shorter time span of 50 monthszoom_range =range(0,50)plt.figure(figsize=(10,4))
@@ -1217,7 +1221,7 @@
Deter
Althought we can still some minor differences, overall the sinnusoidal model seems to capture the main trend of the residuals. We could compute the residuals of this fit to inspect if there still is a trend that we can exploit to include in our model. In this exercise we will stop here, since this is probably sufficient for most practical applications, but before we move on, let’s plot the residuals of the sinusoidal fit. You will see that slowly the residuals are looking more random.
It seems that there might still be some additional information that can be exploited in the residuals. However, it is unclear whether the trend will persist over time. For this tutorial we will stop here. Note that the pattern in the residuals may be attributed to local variations in the exponential fit (the main trend we fitted first). So the right course of action may be to first evaluate if a better trend model can better capture annual trends in atmospheric carbon dioxide. Also note that the residuals oscillate between +2 and -2 ppm, which is probably good for most practical applications.
Combine trend and seasonal models
Now that we have an exponential and a sinusoidal model, let’s combine them to have a full deterministic model that we can use to predict and forecast the atmospheric carbon dioxide concentration. The combined model is:
y(t) = a + b \ exp \bigg(\frac{c \ t}{d}\bigg) + A \ sin(2 \pi [m + phi] )
-
+
# Define the exponential-sinusoidal model as the sum of both modelsexp_sin_model =lambda t,a,b,c,d,A,phi: exp_model(t,a,b,c,d) + sin_model(t,A,phi)
-
+
# Recall that the parameters for the exponential and sinnusoidal models are:print(exp_par[0])print(sin_par[0])
# Compute MAE of combined model against the training setmae_train_exp_sin = mae_fn(y_train, y_train_exp_sin)
-print('MAE using the exponential-sinusoidal model is:',np.round(mae_train_exp_sin, 2), 'ppm')
+print('Exponential-Sinusoidal model MAE for train set:',np.round(mae_train_exp_sin, 2), 'ppm')
-
MAE using the exponential-sinusoidal model is: 1.05 ppm
Exponential-Sinusoidal model MAE for train set: 0.79 ppm
Full model against test set
-
-
# Predict the time series using the full model
-y_test_exp_sin = exp_sin_model(x_test, *exp_sin_par)
-
-# Compute MAE of combined model against the test set
-mae_test_exp_sin = mae_fn(y_test, y_test_exp_sin)
-print('MAE using the exponential-sinusoidal model is:',np.round(mae_test_exp_sin, 2), 'ppm')
+
+
# Predict the time series using the full model
+y_test_exp_sin = exp_sin_model(x_test, *exp_sin_par)
+
+# Compute MAE of combined model against the test set
+mae_test_exp_sin = mae_fn(y_test, y_test_exp_sin)
+print('MAE using the exponential-sinusoidal model is:',np.round(mae_test_exp_sin, 2), 'ppm')
-
MAE using the exponential-sinusoidal model is: 1.16 ppm
+
MAE using the exponential-sinusoidal model is: 0.8 ppm
# Forecast of concentration in July 2030 (relative date)
-y_2030 = exp_sin_model(2030.5- start_date, *exp_sin_par)
-print('Carbon dioxide concentration in 2050 is estimated to be:', np.round(y_2030),'ppm')
+
+
# Forecast of concentration in July 2030 (relative date)
+y_2030 = exp_sin_model(2030- start_date, *exp_sin_par)
+print('Carbon dioxide concentration in 2030 is estimated to be:', np.round(y_2030),'ppm')
-
Carbon dioxide concentration in 2050 is estimated to be: 443.0 ppm
+
Carbon dioxide concentration in 2030 is estimated to be: 438.0 ppm
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diff --git a/docs/search.json b/docs/search.json
index 789704e..4e05ed2 100644
--- a/docs/search.json
+++ b/docs/search.json
@@ -2010,35 +2010,35 @@
"href": "exercises/atmospheric_carbon_dioxide.html#determine-trend-of-time-series",
"title": "68 Atmospheric carbon dioxide",
"section": "Determine trend of time series",
- "text": "Determine trend of time series\nTo capture the main trend of carbon dioxide concentration over time we will fit the following exponential model:\ny(t) = a + b \\ exp \\bigg(\\frac{c \\ t}{d}\\bigg)\nt is time since March, 1958 (the start of the data set) a, b, c, and d are unknown parameters.\n\n# Define lambda function\nexp_model = lambda t,a,b,c,d: a + b*np.exp(c*t/d)\n\n\n# Fit exponential model\nexp_par = curve_fit(exp_model, x_train, y_train)\n\n# Display parameters\nprint('a:', exp_par[0][0])\nprint('b:', exp_par[0][1])\nprint('c:', exp_par[0][2])\nprint('d:', exp_par[0][3])\n\na: 255.96961561849702\nb: 57.671516523308355\nc: 0.016585403165490224\nd: 1.0298254042563226\n\n\n\n# Predict CO2 concentration using exponential model\ny_train_exp = exp_model(x_train, *exp_par[0])\n\n\n# Define lambda function for the mean absolute error formula\nmae_fn = lambda obs,pred: np.mean(np.abs(obs - pred))\n\n# Compute MAE between observed and predicted carbon dioxide using the expoential model\nmae_train_exp = mae_fn(y_train, y_train_exp)\nprint('MAE using the exponential model is:',np.round(mae_train_exp, 2), 'ppm')\n\nMAE using the exponential model is: 1.87 ppm\n\n\n\n# Overlay obseved and predicted carbon dioxide\nplt.figure(figsize=(6,4))\nplt.plot(df_train['decimal_date'], y_train, '-k', label='Observed')\nplt.plot(df_train['decimal_date'], y_train_exp, '-r', label='Predicted')\nplt.title('Mauna Loa, HI')\nplt.xlabel('Time')\nplt.ylabel('Atmospheric carbon dioxide (ppm)')\nplt.legend()\nplt.show()\n\n\n\n\n\nExamine residuals of exponential fit\n\n# Compute residuals\nresiduals_exp_fit = y_train - y_train_exp\n\n# Generate scatter plot.\n# We will also add a line plot to better see any temporal trends\nplt.figure(figsize=(10,4))\nplt.scatter(df_train['decimal_date'],residuals_exp_fit, facecolor='w', edgecolor='k')\nplt.plot(df_train['decimal_date'],residuals_exp_fit, color='k')\nplt.title('Residuals')\nplt.ylabel('Atmospheric carbon dioxide (ppm)')\nplt.show()\n\n\n\n\n\n# Check if residuals approach a zero mean\nprint('Mean residuals (ppm):', np.mean(residuals_exp_fit))\n\nMean residuals (ppm): -4.931054212049981e-06\n\n\nResiduals exhibit a mean close to zero and a sinusoidal pattern. This suggests that a model involving sine or cosine terms could be used to add to improve the exponential model predictions."
+ "text": "Determine trend of time series\nTo capture the main trend of carbon dioxide concentration over time we will fit the following exponential model:\ny(t) = a + b \\ exp \\bigg(\\frac{c \\ t}{d}\\bigg)\nt is time since March, 1958 (the start of the data set) a, b, c, and d are unknown parameters.\n\n# Define lambda function\nexp_model = lambda t,a,b,c,d: a + b*np.exp(c*t/d)\n\n\n# Fit exponential model\nexp_par = curve_fit(exp_model, x_train, y_train)\n\n# Display parameters\nprint('a:', exp_par[0][0])\nprint('b:', exp_par[0][1])\nprint('c:', exp_par[0][2])\nprint('d:', exp_par[0][3])\n\na: 255.96961561849702\nb: 57.671516523308355\nc: 0.016585403165490224\nd: 1.0298254042563226\n\n\n\n# Predict CO2 concentration using exponential model for train and test sets\ny_train_exp = exp_model(x_train, *exp_par[0])\ny_test_exp = exp_model(x_test, *exp_par[0])\n\n\n# Define lambda function for the mean absolute error formula\nmae_fn = lambda obs,pred: np.mean(np.abs(obs - pred))\n\n# Compute MAE between observed and predicted carbon dioxide using the exponetial model\nmae_train_exp = mae_fn(y_train, y_train_exp)\nprint('Exponential model MAE for train dataset:',np.round(mae_train_exp, 2), 'ppm')\n\nmae_test_exp = mae_fn(y_test, y_test_exp)\nprint('Exponential model MAE for test dataset:',np.round(mae_test_exp, 2), 'ppm')\n\nExponential model MAE for train dataset: 1.87 ppm\nExponential model MAE for test dataset: 2.06 ppm\n\n\n\n# Overlay obseved and predicted carbon dioxide\nplt.figure(figsize=(6,4))\nplt.plot(df_train['decimal_date'], y_train, '-k', label='Observed')\nplt.plot(df_train['decimal_date'], y_train_exp, '-r', label='Predicted')\nplt.title('Mauna Loa, HI')\nplt.xlabel('Time')\nplt.ylabel('Atmospheric carbon dioxide (ppm)')\nplt.legend()\nplt.show()\n\n\n\n\n\nExamine residuals of exponential fit\n\n# Compute residuals\nresiduals_exp_fit = y_train - y_train_exp\n\n# Generate scatter plot.\n# We will also add a line plot to better see any temporal trends\nplt.figure(figsize=(10,4))\nplt.scatter(df_train['decimal_date'],residuals_exp_fit, facecolor='w', edgecolor='k')\nplt.plot(df_train['decimal_date'],residuals_exp_fit, color='k')\nplt.title('Residuals')\nplt.ylabel('Atmospheric carbon dioxide (ppm)')\nplt.show()\n\n\n\n\n\n# Check if residuals approach a zero mean\nprint('Mean residuals (ppm):', np.mean(residuals_exp_fit))\n\nMean residuals (ppm): -4.931054212049981e-06\n\n\nResiduals exhibit a mean close to zero and a sinusoidal pattern. This suggests that a model involving sine or cosine terms could be used to add to improve the exponential model predictions."
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"title": "68 Atmospheric carbon dioxide",
"section": "Determine seasonality of time series",
- "text": "Determine seasonality of time series\nTo determine the seasonality of the data we will use the de-trended residuals.\ny(t) = A \\ sin[2 \\pi (m + phi) ]\nt is time since March, 1958 (the start of the data set) A is amplitude of the wave m is the fractional month (Jan is zero and Dec is 1) phi is the phase constant (an offset to align the sine wave)\n\n# Define the sinusoidal model\nsin_model = lambda t,A,phi: A*np.sin(2*np.pi*((t-np.floor(t)) + phi))\n\n# Fit sinusoidal-exponential model\np0 = [-3, -10]\nsin_par = curve_fit(sin_model, x_train, y_train, p0)\n\n# Display parameters\nprint('A:', sin_par[0][0])\nprint('phi:', sin_par[0][1])\n\nA: 2.9614562555902526\nphi: -9.921208441996372\n\n\n\n# Generate timeseries using sinusoidal-exponential model\ny_train_sin = sin_model(x_train, *sin_par[0])\n\n\n# Visualize residuals of the exponential fit and the fitted sinusoidal model\nplt.figure(figsize=(10,4))\nplt.scatter(df_train['decimal_date'], residuals_exp_fit, facecolor='w', edgecolor='k')\nplt.plot(df_train['decimal_date'], y_train_sin, '-k')\nplt.ylabel('Atmospheric carbon dioxide (ppm)')\nplt.show()\n\n\n\n\n\n# Close up view for a shorter time span of 50 months\nzoom_range = range(0,50)\nplt.figure(figsize=(10,4))\nplt.scatter(x_train[zoom_range], residuals_exp_fit[zoom_range],\n facecolor='w', edgecolor='k')\nplt.plot(x_train[zoom_range], y_train_sin[zoom_range], '-k')\nplt.ylabel('Atmospheric carbon dioxide (ppm)')\nplt.show()\n\n\n\n\nAlthought we can still some minor differences, overall the sinnusoidal model seems to capture the main trend of the residuals. We could compute the residuals of this fit to inspect if there still is a trend that we can exploit to include in our model. In this exercise we will stop here, since this is probably sufficient for most practical applications, but before we move on, let’s plot the residuals of the sinusoidal fit. You will see that slowly the residuals are looking more random.\n\n# Calculate residuals\nresiduals_sin_fit = residuals_exp_fit - y_train_sin\n\n# Plot\nplt.figure(figsize=(10,4))\nplt.scatter(df_train['decimal_date'], residuals_sin_fit, facecolor='w', edgecolor='k')\nplt.title('Residuals')\nplt.ylabel('Atmospheric carbon dioxide (ppm)')\nplt.show()"
+ "text": "Determine seasonality of time series\nTo determine the seasonality of the data we will use the de-trended residuals.\ny(t) = A \\ sin[2 \\pi (m + phi) ]\nt is time since March, 1958 (the start of the data set) A is amplitude of the wave m is the fractional month (Jan is zero and Dec is 1) phi is the phase constant (an offset to align the sine wave)\n\n# Define the sinusoidal model\nsin_model = lambda t,A,phi: A*np.sin(2*np.pi*((t-np.floor(t)) + phi))\n\n# Fit sinusoidal-exponential model\nsin_par = curve_fit(sin_model, x_train, residuals_exp_fit)\n\n# Display parameters\nprint('A:', sin_par[0][0])\nprint('phi:', sin_par[0][1])\n\nA: 2.824752471828899\nphi: 1.1443361257709888\n\n\n\n# Generate timeseries using sinusoidal-exponential model\ny_train_sin = sin_model(x_train, *sin_par[0])\n\n\n# Visualize residuals of the exponential fit and the fitted sinusoidal model\nplt.figure(figsize=(10,4))\nplt.scatter(df_train['decimal_date'], residuals_exp_fit, facecolor='w', edgecolor='k')\nplt.plot(df_train['decimal_date'], y_train_sin, '-k')\nplt.ylabel('Atmospheric carbon dioxide (ppm)')\nplt.show()\n\n\n\n\n\n# Close up view for a shorter time span of 50 months\nzoom_range = range(0,50)\nplt.figure(figsize=(10,4))\nplt.scatter(x_train[zoom_range], residuals_exp_fit[zoom_range],\n facecolor='w', edgecolor='k')\nplt.plot(x_train[zoom_range], y_train_sin[zoom_range], '-k')\nplt.ylabel('Atmospheric carbon dioxide (ppm)')\nplt.show()\n\n\n\n\nAlthought we can still some minor differences, overall the sinnusoidal model seems to capture the main trend of the residuals. We could compute the residuals of this fit to inspect if there still is a trend that we can exploit to include in our model. In this exercise we will stop here, since this is probably sufficient for most practical applications, but before we move on, let’s plot the residuals of the sinusoidal fit. You will see that slowly the residuals are looking more random.\n\n# Calculate residuals\nresiduals_sin_fit = residuals_exp_fit - y_train_sin\n\n# Plot\nplt.figure(figsize=(10,4))\nplt.scatter(df_train['decimal_date'], residuals_sin_fit, facecolor='w', edgecolor='k')\nplt.title('Residuals')\nplt.ylabel('Atmospheric carbon dioxide (ppm)')\nplt.show()\n\n\n\n\nIt seems that there might still be some additional information that can be exploited in the residuals. However, it is unclear whether the trend will persist over time. For this tutorial we will stop here. Note that the pattern in the residuals may be attributed to local variations in the exponential fit (the main trend we fitted first). So the right course of action may be to first evaluate if a better trend model can better capture annual trends in atmospheric carbon dioxide. Also note that the residuals oscillate between +2 and -2 ppm, which is probably good for most practical applications."
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"href": "exercises/atmospheric_carbon_dioxide.html#combine-trend-and-seasonal-models",
"title": "68 Atmospheric carbon dioxide",
"section": "Combine trend and seasonal models",
- "text": "Combine trend and seasonal models\nNow that we have an exponential and a sinusoidal model, let’s combine them to have a full deterministic model that we can use to predict and forecast the atmospheric carbon dioxide concentration. The combined model is:\ny(t) = a + b \\ exp \\bigg(\\frac{c \\ t}{d}\\bigg) + A \\ sin(2 \\pi [m + phi] )\n\n# Define the exponential-sinusoidal model as the sum of both models\nexp_sin_model = lambda t,a,b,c,d,A,phi: exp_model(t,a,b,c,d) + sin_model(t,A,phi)\n\n\n# Recall that the parameters for the exponential and sinnusoidal models are:\nprint(exp_par[0])\nprint(sin_par[0])\n\n[2.55969616e+02 5.76715165e+01 1.65854032e-02 1.02982540e+00]\n[ 2.96145626 -9.92120844]\n\n\n\n# So the combined parameters for both models are\nexp_sin_par = np.concatenate((exp_par[0], sin_par[0]))\n\n\n# Predict the time series using the full model\ny_train_exp_sin = exp_sin_model(x_train, *exp_sin_par)\n\n\n# Create figure of combined models\nplt.figure(figsize=(6,4))\nplt.plot(df_train['decimal_date'], y_train, '-k', label='Observed')\nplt.plot(df_train['decimal_date'], y_train_exp_sin, \n color='tomato', alpha=0.75, label='Predicted')\nplt.title('Mauna Loa, HI')\nplt.xlabel('Time')\nplt.ylabel('Atmospheric carbon dioxide (ppm)')\nplt.legend()\nplt.show()\n\n\n\n\n\n# Compute MAE of combined model against the training set\nmae_train_exp_sin = mae_fn(y_train, y_train_exp_sin)\nprint('MAE using the exponential-sinusoidal model is:',np.round(mae_train_exp_sin, 2), 'ppm')\n\nMAE using the exponential-sinusoidal model is: 1.05 ppm\n\n\n\n# Compute residuals\nresiduals_exp_sin = y_train - y_train_exp_sin\n\n# Plot residuals\nplt.figure(figsize=(6,4))\nplt.scatter(df_train['decimal_date'], residuals_exp_sin, s=10)\nplt.xlabel('Time')\nplt.ylabel('Atmospheric carbon dioxide (ppm)')\n\nText(0, 0.5, 'Atmospheric carbon dioxide (ppm)')"
+ "text": "Combine trend and seasonal models\nNow that we have an exponential and a sinusoidal model, let’s combine them to have a full deterministic model that we can use to predict and forecast the atmospheric carbon dioxide concentration. The combined model is:\ny(t) = a + b \\ exp \\bigg(\\frac{c \\ t}{d}\\bigg) + A \\ sin(2 \\pi [m + phi] )\n\n# Define the exponential-sinusoidal model as the sum of both models\nexp_sin_model = lambda t,a,b,c,d,A,phi: exp_model(t,a,b,c,d) + sin_model(t,A,phi)\n\n\n# Recall that the parameters for the exponential and sinnusoidal models are:\nprint(exp_par[0])\nprint(sin_par[0])\n\n[2.55969616e+02 5.76715165e+01 1.65854032e-02 1.02982540e+00]\n[2.82475247 1.14433613]\n\n\n\n# So the combined parameters for both models are\nexp_sin_par = np.concatenate((exp_par[0], sin_par[0]))\n\n\n# Predict the time series using the full model for the train and test datasets\ny_train_exp_sin = exp_sin_model(x_train, *exp_sin_par)\n\n\n# Create figure of combined models\nplt.figure(figsize=(6,4))\nplt.plot(df_train['decimal_date'], y_train, '-k', label='Observed')\nplt.plot(df_train['decimal_date'], y_train_exp_sin, \n color='tomato', alpha=0.75, label='Predicted')\nplt.title('Mauna Loa, HI')\nplt.xlabel('Time')\nplt.ylabel('Atmospheric carbon dioxide (ppm)')\nplt.legend()\nplt.show()\n\n\n\n\n\n# Compute MAE of combined model against the training set\nmae_train_exp_sin = mae_fn(y_train, y_train_exp_sin)\nprint('Exponential-Sinusoidal model MAE for train set:',np.round(mae_train_exp_sin, 2), 'ppm')\n\nExponential-Sinusoidal model MAE for train set: 0.79 ppm"
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"title": "68 Atmospheric carbon dioxide",
"section": "Full model against test set",
- "text": "Full model against test set\n\n# Predict the time series using the full model\ny_test_exp_sin = exp_sin_model(x_test, *exp_sin_par)\n\n# Compute MAE of combined model against the test set\nmae_test_exp_sin = mae_fn(y_test, y_test_exp_sin)\nprint('MAE using the exponential-sinusoidal model is:',np.round(mae_test_exp_sin, 2), 'ppm')\n\nMAE using the exponential-sinusoidal model is: 1.16 ppm\n\n\n\n# Create figure of combined models\nplt.figure(figsize=(6,4))\nplt.plot(df_test['decimal_date'], y_test, '-k', label='Observed')\nplt.plot(df_test['decimal_date'], y_test_exp_sin, color='tomato', alpha=0.75, label='Predicted')\nplt.title('Mauna Loa, HI')\nplt.xlabel('Time')\nplt.ylabel('Atmospheric carbon dioxide (ppm)')\nplt.legend()\nplt.show()"
+ "text": "Full model against test set\n\n# Predict the time series using the full model\ny_test_exp_sin = exp_sin_model(x_test, *exp_sin_par)\n\n# Compute MAE of combined model against the test set\nmae_test_exp_sin = mae_fn(y_test, y_test_exp_sin)\nprint('MAE using the exponential-sinusoidal model is:',np.round(mae_test_exp_sin, 2), 'ppm')\n\nMAE using the exponential-sinusoidal model is: 0.8 ppm\n\n\n\n# Create figure of combined models\nplt.figure(figsize=(6,4))\nplt.plot(df_test['decimal_date'], y_test, '-k', label='Observed')\nplt.plot(df_test['decimal_date'], y_test_exp_sin, color='tomato', alpha=0.75, label='Predicted')\nplt.title('Mauna Loa, HI')\nplt.xlabel('Time')\nplt.ylabel('Atmospheric carbon dioxide (ppm)')\nplt.legend()\nplt.show()"
},
{
"objectID": "exercises/atmospheric_carbon_dioxide.html#generate-2030-forecast",
"href": "exercises/atmospheric_carbon_dioxide.html#generate-2030-forecast",
"title": "68 Atmospheric carbon dioxide",
"section": "Generate 2030 forecast",
- "text": "Generate 2030 forecast\n\n# Forecast of concentration in July 2030 (relative date)\ny_2030 = exp_sin_model(2030.5 - start_date, *exp_sin_par)\nprint('Carbon dioxide concentration in 2050 is estimated to be:', np.round(y_2030),'ppm')\n\nCarbon dioxide concentration in 2050 is estimated to be: 443.0 ppm\n\n\n\nlast_date = df['decimal_date'].iloc[-1]\nx_forecast = np.arange(last_date, 2030, 0.1) - start_date\ny_forecast = exp_sin_model(x_forecast, *exp_sin_par)\n\n# Figure with projection\nplt.figure(figsize=(6,4))\nplt.plot(df['decimal_date'], df['monthly_avg_co2'], '-k', label='Observed')\nplt.plot(start_date+x_forecast, y_forecast, color='tomato', alpha=0.75, label='Forecast')\nplt.title('Mauna Loa, HI')\nplt.xlabel('Time')\nplt.ylabel('Atmospheric carbon dioxide (ppm)')\nplt.legend()\nplt.show()"
+ "text": "Generate 2030 forecast\n\n# Forecast of concentration in July 2030 (relative date)\ny_2030 = exp_sin_model(2030 - start_date, *exp_sin_par)\nprint('Carbon dioxide concentration in 2030 is estimated to be:', np.round(y_2030),'ppm')\n\nCarbon dioxide concentration in 2030 is estimated to be: 438.0 ppm\n\n\n\nlast_date = df['decimal_date'].iloc[-1]\nx_forecast = np.arange(last_date, 2030, 0.1) - start_date\ny_forecast = exp_sin_model(x_forecast, *exp_sin_par)\n\n# Figure with projection\nplt.figure(figsize=(6,4))\nplt.plot(df['decimal_date'], df['monthly_avg_co2'], '-k', label='Observed')\nplt.plot(start_date+x_forecast, y_forecast, color='tomato', alpha=0.75, label='Forecast')\nplt.title('Mauna Loa, HI')\nplt.xlabel('Time')\nplt.ylabel('Atmospheric carbon dioxide (ppm)')\nplt.legend()\nplt.show()"
},
{
"objectID": "exercises/atmospheric_carbon_dioxide.html#practice",
diff --git a/exercises/atmospheric_carbon_dioxide.ipynb b/exercises/atmospheric_carbon_dioxide.ipynb
index 3c322aa..d8d5d15 100644
--- a/exercises/atmospheric_carbon_dioxide.ipynb
+++ b/exercises/atmospheric_carbon_dioxide.ipynb
@@ -329,7 +329,7 @@
},
{
"cell_type": "code",
- "execution_count": 6,
+ "execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
@@ -339,7 +339,7 @@
},
{
"cell_type": "code",
- "execution_count": 7,
+ "execution_count": 6,
"metadata": {},
"outputs": [
{
@@ -366,24 +366,26 @@
},
{
"cell_type": "code",
- "execution_count": 8,
+ "execution_count": 14,
"metadata": {},
"outputs": [],
"source": [
- "# Predict CO2 concentration using exponential model\n",
- "y_train_exp = exp_model(x_train, *exp_par[0])\n"
+ "# Predict CO2 concentration using exponential model for train and test sets\n",
+ "y_train_exp = exp_model(x_train, *exp_par[0])\n",
+ "y_test_exp = exp_model(x_test, *exp_par[0])\n"
]
},
{
"cell_type": "code",
- "execution_count": 9,
+ "execution_count": 16,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
- "MAE using the exponential model is: 1.87 ppm\n"
+ "Exponential model MAE for train dataset: 1.87 ppm\n",
+ "Exponential model MAE for test dataset: 2.06 ppm\n"
]
}
],
@@ -391,14 +393,17 @@
"# Define lambda function for the mean absolute error formula\n",
"mae_fn = lambda obs,pred: np.mean(np.abs(obs - pred))\n",
"\n",
- "# Compute MAE between observed and predicted carbon dioxide using the expoential model\n",
+ "# Compute MAE between observed and predicted carbon dioxide using the exponetial model\n",
"mae_train_exp = mae_fn(y_train, y_train_exp)\n",
- "print('MAE using the exponential model is:',np.round(mae_train_exp, 2), 'ppm')\n"
+ "print('Exponential model MAE for train dataset:',np.round(mae_train_exp, 2), 'ppm')\n",
+ "\n",
+ "mae_test_exp = mae_fn(y_test, y_test_exp)\n",
+ "print('Exponential model MAE for test dataset:',np.round(mae_test_exp, 2), 'ppm')\n"
]
},
{
"cell_type": "code",
- "execution_count": 10,
+ "execution_count": 17,
"metadata": {},
"outputs": [
{
@@ -433,7 +438,7 @@
},
{
"cell_type": "code",
- "execution_count": 11,
+ "execution_count": 18,
"metadata": {},
"outputs": [
{
@@ -463,7 +468,7 @@
},
{
"cell_type": "code",
- "execution_count": 12,
+ "execution_count": 19,
"metadata": {},
"outputs": [
{
@@ -505,15 +510,15 @@
},
{
"cell_type": "code",
- "execution_count": 14,
+ "execution_count": 20,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
- "A: 2.9614562555902526\n",
- "phi: -9.921208441996372\n"
+ "A: 2.824752471828899\n",
+ "phi: 1.1443361257709888\n"
]
}
],
@@ -522,8 +527,7 @@
"sin_model = lambda t,A,phi: A*np.sin(2*np.pi*((t-np.floor(t)) + phi))\n",
"\n",
"# Fit sinusoidal-exponential model\n",
- "p0 = [-3, -10]\n",
- "sin_par = curve_fit(sin_model, x_train, y_train, p0)\n",
+ "sin_par = curve_fit(sin_model, x_train, residuals_exp_fit)\n",
"\n",
"# Display parameters\n",
"print('A:', sin_par[0][0])\n",
@@ -532,7 +536,7 @@
},
{
"cell_type": "code",
- "execution_count": 15,
+ "execution_count": 21,
"metadata": {},
"outputs": [],
"source": [
@@ -542,12 +546,12 @@
},
{
"cell_type": "code",
- "execution_count": 16,
+ "execution_count": 28,
"metadata": {},
"outputs": [
{
"data": {
- "image/png": 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\n",
+ "image/png": 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\n",
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