Hi James,
2008/12/8 James james@fmnmedia.co.uk:
I have a very simple plot, and the lines join point to point, however i would like to add a line of best fit now onto the chart, i am really new to python etc, and didnt really understand those links!
Can anyone help me :)
It sounds like the second link, about linear regression, is a good place to start, and I've made a very simple example based on that:
----------------------------------------------- import numpy as np import matplotlib.pyplot as plt
x = np.linspace(0, 10, 11) #1 data_y = np.random.normal(size=x.shape, loc=x, scale=2.5) #2 plt.plot(x, data_y, 'bo') #3
coefs = np.lib.polyfit(x, data_y, 1) #4 fit_y = np.lib.polyval(coefs, x) #5 plt.plot(x, fit_y, 'b--') #6 ------------------------------------------------
Line 1 creates an array with the x values I have. Line 2 creates some random "data" I want to fit, which, in this case happens to be normally distributed around the unity line y=x. The raw data is plotted (assuming you have matplotlib installed as well - I suggest you do) by line 3, with blue circles.
Line 4 calculates the coefficients giving the least-squares best fit to a first degree polynomial (i.e. a straight line y = c0 * x + c1). So the values of coefs are c0 and c1 in the previous equation.
Line 5 calculates the y values on the fitted polynomial, at given x values, from the coefficients calculated in line 4, and line 6 simply plots these fitted y values, using a dotted blue line.
I hope that helps get you started. Keep posting questions on specific issues as they arise, and we'll see what we can do to help.
Angus.