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-*-
2ImportNumPy as NP
3 fromScipy.optimizeImportLeastsq
4ImportPylab as Pl
5
6defFunc (x, p):
7# """
8#functions used for data fitting: A*sin (2*pi*k*x + theta)
9# """
TenA, k, theta = P
OnereturnA*np.sin (2*np.pi*k*x+theta)
A
-defResiduals (p, y, x):
-# """
the#the difference between the experimental data x, Y, and the fitting function, p is the coefficient to be found for fitting
-# """
-returnY-func (x, p)
-
+x = Np.linspace (0, -2*np.pi, 100)
-A, k, theta = ten, 0.34, NP.PI/6#function parameters for real data
+Y0 = func (x, [A, K, Theta])#Real Data
AY1 = y0 + 2 * NP.RANDOM.RANDN (len (x))#experimental data after adding noise
at
-P0 = [7, 0.2, 0]#function fitting parameters for the first guess
-
-#call LEASTSQ for data fitting
-#residuals as a function of calculating errors
-#P0 is the initial value of the fitting parameter
in#args is the experimental data that needs to be fitted
-PLSQ = LEASTSQ (residuals, P0, args= (y1, x))
to
+#Print (U "true parameter:")
-Print([A, K, Theta])
the#Print (U "fit parameter")
*Print(Plsq[0])#parameters after fitting the experimental data
$
Panax NotoginsengPl.plot (x, y0, Label=u"Real Data")
-Pl.plot (x, y1, Label=u"data with noisy")
thePl.plot (x, func (x, plsq[0]), Label=u"Nihe Data")
+Pl.legend ()
APl.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;

A preliminary study of scientific calculation using Python