用慣Python的你,是不是早已無法忍受matplotlib那丑陋無比的圖以及蛋疼無比部署依賴?
當當當當,Matlab2014b的Python Engine API現已加入豪華午餐。
上次寫了一篇文章,講用C++調用Matlab的繪圖引擎,不過呢有句話怎么說來着?人生苦短,我用Python。
這次就說一說怎么用Python調用Matlab的引擎。Python大法好,這個可比C++要容易太多了。
過程非常簡單,第一步是安裝,假設Matlabroot是Matlab的安裝根目錄
找到你的Matlab安裝根目錄,然后Shell進入matlabroot\extern\engines\python目錄中,執行
python setup.py install
完事了。注意,一定要用管理員權限執行。
不用管理員權限的安裝方法稍微復雜一點點:
cd "matlabroot\extern\engines\python"
python setup.py build --build-base builddir install --install-base installdir
將installdir添加到Python的包搜索路徑中,再加入到PYTHONPATH環境變量中即可。
Matlab的Python引擎怎么用呢? 更簡單了:
import matlab.engine 就可以開始了。
然后是一段測試用的Python腳本:
import matlab import matlab.engine import time def 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): pass def 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的最牛逼之處就是可以直接以原生的形式調用Matlab內建函數,而不是用Eval方法。當然,如果你想用也是一點問題都沒有的。同時,變量的存取再也不用和一堆mxArray以及它們的ADT打交道了,直接以字典的形式對engine.workspace進行存取即可。顯然比C++的調用方式更為科學。
下面的可以做一個備忘Sheet
###Matlab Engine for Python #Call Matlab Function from Python ------------------------------ ##Step 1: Installation #Install with Administrator Privileges cd "matlabroot\extern\engines\python" python setup.py install #Install without Administrator Privileges cd "matlabroot\extern\engines\python" python setup.py build --build-base builddir install --install-base installdir Include 'installdir' in the search path for Python packages Add 'installdir' to the PYTHONPATH environment variavle ------------------------------ ##Step 2: Using Matlab Engine #Start and quit import matlab.engine eng = 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 Call import matlab.engine eng = matlab.engine.start_matlab() future = eng.sqrt(4.0,async=True) ret = future.result() print(ret) #WorkSpace Usage: import matlab.engine eng = matlab.engine.start_matlab() eng.workspace['y'] = x a = eng.eval('sqrt(y)') print(a) #Skills for unsupported features in python #eng.eval() import matlab.engine eng = matlab.engine.start_matlab() eng.eval("T = readtable('patients.dat');",nargout=0) #Plot With Matlab: import matlab.engine eng = matlab.engine.start_matlab() data = eng.peaks(100) eng.mesh(data) ------------------------------