HACKTOBERFEST: Approximation of pi and plotting example

README.md

@@ -111,6 +111,25 @@ Directly prints results if run directly.
 May also be imported, yielding results one by one.
 
 
+### Approximating *pi*
+
+This script is useful to show a way to approximate the value of pi using a Monte Carlo method. It is also optimized using the `@jit` (*just-in-time*) decorator from the [numba](https://numba.pydata.org/) library.
+
+To see different approximations you just need to modify the argument passed to the main function.
+
+```bash
+python pi.py
+```
+
+
+### Plotting a function
+
+This script contains an example of plotting a function using [`matplotlib`](http://matplotlib.org/). Feel free to modify the value of `y` to obtain different functions that depend on `x`.
+
+```bash
+python plot_example.py
+```
+
 ## Release History
 
 * 0.0.1
@@ -141,4 +160,4 @@ The following people helped in creating the above content.
 * <a href="https://github.com/KayvanMazaheri" target="_blank">Kayvan Mazaheri</a>
 * <a href="https://github.com/kalbhor" target="_blank">Lakshay Kalbhor</a>
 * <a href="https://github.com/Pradhvan">Pradhvan Bisht</a>
-* <a href="https://github.com/toonarmycaptain" target="_blank">David Antonini</a>
+* <a href="https://github.com/toonarmycaptain" target="_blank">David Antonini</a>

pi.py

@@ -0,0 +1,15 @@
+import numpy as np
+from numba import jit
+
+@jit
+def aprox_pi(N):
+	points = 2 * np.random.rand(N, 2) - 1
+	M = 0
+
+	for k in range(N):
+		if points[k,0]**2 + points[k,1]**2 < 1.:
+			M += 1
+
+	return 4.*M/N
+
+print(aprox_pi(1e8))

plot_example.py

@@ -0,0 +1,8 @@
+import numpy as np
+import matplotlib.pyplot as plt
+
+x = np.linspace(-3, 3, 100)
+y = x**2
+
+plt.plot(x, y)
+plt.show()