use a list of tuples to store data points

master
neingeist 11 years ago
parent ae646e457e
commit e290f8c248

@ -9,14 +9,13 @@ b1 = Symbol('b1')
b2 = Symbol('b2')
# Data points
xn = [1, 2, 3, 4, 5, 7, 9]
yn = [6, 5, 7, 10, 11, 12, 14]
data = [(1,14), (2, 13), (3, 12), (4, 10), (5,9), (7,8), (9,5)]
# S is the function to minimize:
#
# For each data point the vertical error/residual is x*b1 + b2 - y. We want to
# minimize the sum of the squared residuals (least squares).
S = sum((xn[i] * b1 + b2 - yn[i]) ** 2 for i in range(0, len(xn)))
S = sum((p[0] * b1 + b2 - p[1]) ** 2 for p in data)
print("Function to minimize: S = {}".format(S))
# Minimize S by setting its partial derivatives to zero.
@ -32,9 +31,10 @@ print("Fitted line: y = {}".format(fitted_line))
# Construct something we can plot with matplotlib
fitted_line_func = lambdify(x, fitted_line, modules=['numpy'])
x_plot = np.linspace(min(xn), max(xn), 100)
x_plot = np.linspace(min(p[0] for p in data),
max(p[0] for p in data), 100)
# Plot data points and fitted line
plt.scatter(xn, yn, marker="+")
plt.scatter([p[0] for p in data], [p[1] for p in data], marker="+")
plt.plot(x_plot, fitted_line_func(x_plot), 'r')
plt.show()

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