A preliminary study of scientific calculation using Python

Take a look at Python's scientific computing power today after setting up the Django Framework blog.

The scientific calculation of Python has three musketeers: Numpy,scipy,matplotlib.

NumPy is responsible for numerical calculation, matrix operation and so on;

SCIPY is responsible for common mathematical algorithms, interpolation, fitting and so on;

Matplotlib is responsible for drawing.

First of all, Baidu top three, followed by installation.

May consider using pyhton34/script/easy-install tools; easy-insatll-m matplotlib;

Try the code to fit the example;

1 #-*-Coding:utf-8-*-
2 Import NumPy as NP
3 from scipy.optimize import leastsq
4 Import Pylab as pl
5
6 def func (x, p):
7 # "" "
8 # Functions used for data fitting: A*sin (2*pi*k*x + theta)
9 # "" "
Ten A, k, theta = P
Return A*np.sin (2*np.pi*k*x+theta)
12
def residuals (p, y, x):
14 # "" "
15 # The difference between the experimental data x, Y, and the Fit function, p is the coefficient to be found for fit
16 # "" "
Y-func return (x, p)
18
x = Np.linspace (0, -2*np.pi, 100)
A, k, theta = ten, 0.34, NP.PI/6 # function parameters of real data
Y0 = func (x, [A, K, Theta]) # Real data
Y1 = y0 + 2 * NP.RANDOM.RANDN (len (x)) # Experiment data after adding noise
23
P0 = [7, 0.2, 0] # First guessing function fitting parameters
25
26 # Call LEASTSQ for data fitting
# residuals as a function of calculating errors
# P0 is the initial value of the fitting parameter
# args is the experimental data that needs to be fitted
PLSQ = LEASTSQ (residuals, P0, args= (y1, x))
31
# Print (U "true parameter:")
Print ([A, K, Theta])
# Print (U "Fit Parameters")
Print (plsq[0]) # parameters after fitting the experimental data
36
PNS Pl.plot (x, y0, label=u "real data")
Pl.plot (x, y1, label=u "data with noisy")
Pl.plot (x, func (x, plsq[0]), label=u "Nihe data")
Pl.legend ()
Pl.show ()

Run prompt error, missing third-party packages, such as six,dateutil,pyparsing, and so on, what is missing, third-party packages are mostly directly dragged into the D:\python34\lib directory can be, very convenient.

All mounted upon, running successfully;

Http://www.cnblogs.com/javajava/p/4792791.html

Using Python to do scientific Computing (GO)