MAINT: Replace polyfit/polyval with Polynomial class.

The Polynomial class is recommended over the poly* functional interface
for new code.

Author: rossbar

content/tutorial-ma.md

@@ -268,21 +268,20 @@ Finally, we can use the [numpy.polyfit](https://numpy.org/devdocs/reference/gene
 
 ```{code-cell}
 t = np.arange(len(china_total))
-params = np.polyfit(t[~china_total.mask], valid, 3)
-cubic_fit = np.polyval(params, t)
+model = np.polynomial.Polynomial.fit(t[~china_total.mask], valid, 3)
 plt.plot(t, china_total)
-plt.plot(t, cubic_fit, "--")
+plt.plot(t, model(t), "--")
 ```
 
 This plot is not so readable since the lines seem to be over each other, so let's summarize in a more elaborate plot. We'll plot the real data when
 available, and show the cubic fit for unavailable data, using this fit to compute an estimate to the observed number of cases on January 28th 2020, 7 days after the beginning of the records:
 
 ```{code-cell}
 plt.plot(t, china_total)
-plt.plot(t[china_total.mask], cubic_fit[china_total.mask], "--", color="orange")
-plt.plot(7, np.polyval(params, 7), "r*")
+plt.plot(t[china_total.mask], model(t)[china_total.mask], "--", color="orange")
+plt.plot(7, model(7), "r*")
 plt.xticks([0, 7, 13], dates[[0, 7, 13]])
-plt.yticks([0, np.polyval(params, 7), 10000, 17500])
+plt.yticks([0, model(7), 10000, 17500])
 plt.legend(["Mainland China", "Cubic estimate", "7 days after start"])
 plt.title(
     "COVID-19 cumulative cases from Jan 21 to Feb 3 2020 - Mainland China\n"