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http://www.cnblogs.com/Vonng/p/4239822.html
在Python中直接调用Matlab,看上去真不错,转一个
Python调用Matlab2014b引擎
用惯Python的你,是不是早已无法忍受matplotlib那丑陋无比的图以及蛋疼无比部署依赖?
当当当当,Matlab2014b的Python Engine API现已加入豪华午餐。【看上去2015a应该也支持了】
上次写了一篇文章,讲用C++调用Matlab的绘图引擎,不过呢有句话怎么说来着?人生苦短,我用Python。
这次就说一说怎么用Python调用Matlab的引擎。Python大法好,这个可比C++要容易太多了。
过程非常简单,第一步是安装,假设Matlabroot是Matlab的安装根目录
找到你的Matlab安装根目录,然后Shell进入matlabroot\extern\engines\python目录中,执行
python setup.py install
完事了。注意,一定要用管理员权限执行。
不用管理员权限的安装方法稍微复杂一点点:
cd "matlabroot\extern\engines\python"
python setup.py build --build-base builddir install --install-base installdir
将installdir添加到Python的包搜索路径中,再加入到PYTHONPATH环境变量中即可。
Matlab的Python引擎怎么用呢? 更简单了:
import matlab.engine 就可以开始了。
然后是一段测试用的Python脚本:
import matlab
import matlab.engine
import timedef basic_test(eng):print "Basic Testing Begin"print "eng.power(100,2) = %d"%eng.power(100,2)print "eng.max(100,200) = %d"%eng.max(100,200)print "eng.rand(5,5) = "print eng.rand(5,5)print "eng.randi(matlab.double([1,100]),matlab.double([3,4]))"%\eng.randi(matlab.double([1,100]),matlab.double([3,4]))print "Basic Testing Begin"def plot_test(eng):print "Plot Testing Begin"eng.workspace['data'] = \eng.randi(matlab.double([1,100]),matlab.double([30,2]))eng.eval("plot(data(:,1),'ro-')")eng.hold('on',nargout=0)eng.eval("plot(data(:,2),'bx--')")print "Plot testing end"def audio_test(eng,freq,length):print "Audio Testing Begin"eval_str = "f = %d;t=%d;"%(freq,length)eng.eval(eval_str,nargout = 0)eng.eval('fs = 44100;T=1/fs;t=(0:T:t);',nargout = 0)eng.eval('y = sin(2 * pi * f * t);',nargout = 0)eng.eval('sound(y,fs);',nargout = 0)time.sleep(length)print "Audio Testing End"def fourier_test(eng):passdef demo(eng):basic_test(eng)plot_test(eng)audio_test(eng,680,1)if __name__ == "__main__":print "Initializing Matlab Engine"eng = matlab.engine.start_matlab()print "Initializing Complete!"demo(eng)print "Exiting Matlab Engine"print "Press Any Key to Exit"raw_input();eng.quit()print "Bye-Bye"
比起C++ Engine的API,Python Engine的最牛逼之处就是可以直接以原生的形式调用Matlab内建函数,而不是用Eval方法。当然,如果你想用也是一点问题都没有的。同时,变量的存取再也不用和一堆mxArray以及它们的ADT打交道了,直接以字典的形式对engine.workspace进行存取即可。显然比C++的调用方式更为科学。
下面的可以做一个备忘Sheet
###Matlab Engine for Python
#Call Matlab Function from Python------------------------------
##Step 1: Installation#Install with Administrator Privilegescd "matlabroot\extern\engines\python"python setup.py install#Install without Administrator Privilegescd "matlabroot\extern\engines\python"python setup.py build --build-base builddir install --install-base installdirInclude 'installdir' in the search path for Python packagesAdd 'installdir' to the PYTHONPATH environment variavle------------------------------
##Step 2: Using Matlab Engine#Start and quitimport matlab.engineeng = matlab.engine.start_matlab()eng.quit()#Call Matlab Functions:#Just call with form eng.xxx()#the function xxx should in the namespace of matlab.#Asynchronously Callimport matlab.engineeng = matlab.engine.start_matlab()future = eng.sqrt(4.0,async=True)ret = future.result()print(ret)#WorkSpace Usage:import matlab.engineeng = matlab.engine.start_matlab()eng.workspace['y'] = xa = eng.eval('sqrt(y)')print(a)#Skills for unsupported features in python#eng.eval()import matlab.engineeng = matlab.engine.start_matlab()eng.eval("T = readtable('patients.dat');",nargout=0)#Plot With Matlab:import matlab.engineeng = matlab.engine.start_matlab()data = eng.peaks(100)eng.mesh(data)
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