import numpy as np                     # Load the library

a = np.linspace(-np.pi, np.pi, 100)    # Create even grid from -π to π
b = np.cos(a)                          # Apply cosine to each element of a
c = np.sin(a)                          # Apply sin to each element of a

b @ c

from scipy.stats import norm
from scipy.integrate import quad

ϕ = norm()
value, error = quad(ϕ.pdf, -2, 2)  # Integrate using Gaussian quadrature
value

%matplotlib inline
import networkx as nx
import matplotlib.pyplot as plt
plt.rcParams['figure.figsize'] = (10,6)
np.random.seed(1234)

# Generate a random graph
p = dict((i, (np.random.uniform(0, 1), np.random.uniform(0, 1)))
         for i in range(200))
g = nx.random_geometric_graph(200, 0.12, pos=p)
pos = nx.get_node_attributes(g, 'pos')

# Find node nearest the center point (0.5, 0.5)
dists = [(x - 0.5)**2 + (y - 0.5)**2 for x, y in list(pos.values())]
ncenter = np.argmin(dists)

# Plot graph, coloring by path length from central node
p = nx.single_source_shortest_path_length(g, ncenter)
plt.figure()
nx.draw_networkx_edges(g, pos, alpha=0.4)
nx.draw_networkx_nodes(g,
                       pos,
                       nodelist=list(p.keys()),
                       node_size=120, alpha=0.5,
                       node_color=list(p.values()),
                       cmap=plt.cm.jet_r)
plt.show()