Refer to the official documentation:
Http://cn.mathworks.com/help/matlab/matlab_external/get-started-with-matlab-engine-for-python.html
Usage documentation for MATLAB Engine API:
Http://cn.mathworks.com/help/matlab/matlab-engine-for-python.html
Raw materials:
1, MATLAB 2015a 32-bit
2, Python 2.7.13 32-bit
Installation:
1, run cmd, switch to the directory of MATLAB:
C:\Program Files (x86) \matlab\matlab Production Server\r2015a\extern\engines\python
Since this folder is in the C drive, there may be a problem with write permissions at the time of installation. If Write permission appears, you can give the current user Full control by right-clicking the folder, choosing Properties---security--edit.
> Python setup.py Install
To complete the installation.
2. Examples of API calls to Matlab in Python:
#coding =utf-8import Matlab.engineif __name__ = = ' __main__ ': eng = Matlab.engine.start_matlab (' matlab_r2015a ') A = ENG.SQRT (4.0) print type (a), a eng.quit () Pass
Creating an array of matlab in Python
1. Create a 1XN array
Import Matlab.enginea = Matlab.int8 ([1,2,3,4,5]) print type (A), a.size,a# output: <class ' Matlab.mlarray.int8 ' > (1, 5) [ [1,2,3,4,5]]
Attribute or Method |
Purpose |
size
|
Size of array returned as atuple |
reshape(size)
|
Reshape array as specified by sequencesize |
2. Creating multidimensional arrays
Import Matlab.enginea = Matlab.double ([[[1,2,3,4,5], [6,7,8,9,10]]) print (A)
3. Index the MATLAB array in python
The MATLAB array index here is not the same as in the MATLAB IDE, MATLAB is starting from 1, and in Python is starting from 0 index
Import Matlab.enginea = Matlab.int8 ([1,2,3,4,5]) print (a[0]) #输出: [1,2,3,4,5]
Because A is a 1x5 matrix, a[0] is [1,2,3,4,5], and if you want to index 4 in a, you need to enter:
Print A[0][3]
4. Slicing the MATLAB array in python
There's not much difference between the syntax and Python, just use it.
Import Matlab.enginea = Matlab.int8 ([1,2,3,4,5]) print (A[0][1:4]) #输出: [2,3,4]
Slice assignment or you can assign a value from one MATLAB array to another MATLAB array:
A = Matlab.double ([[1,2,3,4],[5,6,7,8]]); A[0] = [10,20,30,40]print (A) #输出: [[10.0,20.0,30.0,40.0],[5.0,6.0,7.0,8.0]]a = Matlab.int8 ([1,2,3,4,5,6,7,8]); A[0][2:4] = [30,40]a[0][6:8] = [70,80]print (A) #输出: [[1,2,30,40,5,6,70,80]]
Attention:
Note: slicing MATLAB arrays behaves differently from slicing a Python list. Slicing a MATLAB array returns a view instead of a shallow copy. Given a MATLAB array and a Python list with the same values, assigning a slice results in different results as shown by th E following code. A = Matlab.int32 ([[1,2],[3,4],[5,6]]) L = [[1,2],[3,4],[5,6]]a[0] = a[0][::-1]l[0] = L[0][::-1]print (a) [[2,2],[3,4],[ 5,6]]print (L) [[2, 1], [3, 4], [5, 6]]
Array reshape
Import Matlab.enginea = Matlab.int8 ([1,2,3,4,5,6,7,8,9]) A.reshape ((3,3)) print (A) [[1,4,7],[2,5,8],[3,6,9]]
data types supported by MATLAB in Python:
matlab Class
|
Constructor Call in Python |
matlab.double
|
matlab.double(initializer=None, size=None, is_complex=False)
|
matlab.single
|
matlab.single(initializer=None, size=None, is_complex=False)
|
matlab.int8
|
matlab.int8(initializer=None, size=None, is_complex=False)
|
matlab.int16
|
matlab.int16(initializer=None, size=None, is_complex=False)
|
matlab.int32
|
matlab.int32(initializer=None, size=None, is_complex=False)
|
matlab.int64 A
|
matlab.int64(initializer=None, size=None, is_complex=False)
|
matlab.uint8
|
matlab.uint8(initializer=None, size=None, is_complex=False)
|
matlab.uint16
|
matlab.uint16(initializer=None, size=None, is_complex=False)
|
matlab.uint32
|
matlab.uint32(initializer=None, size=None, is_complex=False)
|
matlab.uint64 [b]
|
matlab.uint64(initializer=None, size=None, is_complex=False)
|
matlab.logical
|
matlab.logical(initializer=None, size=None) C
|
matlab.object
|
No constructor. When a-function returns a handle to a MATLAB object, the engine returns a to matlab.object Python. |
[A] in Python 2.7 on Windows, was converted to in matlab.int64 int32 MATLAB. Also, MATLAB cannot return an int64 array to Python. [b] in Python 2.7 on Windows, are converted to in matlab.uint64 uint32 MATLAB. Also, MATLAB cannot return a uint64 array to Python. [C] logicals cannot be made to an array of complex numbers. |
Examples of singular value decomposition:
#coding =utf-8import matlab.enginefrom numpy import *if __name__ = = ' __main__ ': eng = Matlab.engine.start_matlab (' matlab_r2015a ') A = matlab.double ([[[1,2],[5,6]]) print type (a), A.size,a print Eng.eig (a) eng.quit ( ) Pass
Examples and how To
Install MATLAB Engine API for Python
To start the MATLAB engine within a Python session, your first must install the engine API as a python package.
Install MATLAB Engine API for Python in nondefault Locations
By default, the installer builds the engine API for Python in the matlabroot
\extern\engines\python
folder. The installer installs the engine in the default Python folder.
Start and Stop MATLAB Engine for Python
Options for starting the MATLAB Engine for Python.
Connect Python to Running MATLAB Session
How to connect the MATLAB Engine for Python to a shared MATLAB session, which is already running on your local machine.
Call MATLAB Functions from Python
How to return the output argument from a MATLAB function. How to read multiple outputs from a function. What does when is the MATLAB function does not return an output argument.
Call MATLAB Functions asynchronously from Python
This example shows how to call the MATLAB sqrt
function asynchronously from Python and retrieve the square root later.
Call User Script and Function from Python
This example shows how to call a MATLAB script to compute the area of a triangle from Python.
Redirect Standard Output and Error to Python
This example shows how to redirect standard output and standard error from a MATLAB function to Python StringIO
objects.
Use of MATLAB Engine Workspace in Python
This example shows what to add variables to the MATLAB engine workspace in Python.
Use of MATLAB Handle Objects in Python
This example shows what to create an object from a MATLAB handle class and call its methods in Python.
Use of MATLAB Arrays in Python
This example shows what to create a MATLAB array in Python and pass it as the input argument to the MATLAB sqrt
function.
Sort and Plot MATLAB Data from Python
This example shows what to sort data about patients into lists of smokers and nonsmokers in Python and plot blood pressure Readings for the patients with MATLAB.
Get Help for MATLAB Functions from Python
From Python, you can access the supporting documentation for all MATLAB functions.
Concepts
Get Started with MATLAB Engine API for Python
The Matlab Engine API for Python provides a python package named this enables you-call matlab
MATLAB functions from Pyth Mnl
System Requirements for MATLAB Engine API for Python
What are need to write and build MATLAB engine applications.
Pass Data to MATLAB from Python
When your pass Python data as input arguments to MATLAB functions, the MATLAB Engine for Python Converts the data into Equi Valent MATLAB data types.
Handle Data returned from MATLAB to Python
When MATLAB functions return output arguments, the Matlab Engine API for Python converts the data into equivalent Python D ATA types.
MATLAB Arrays as Python Variables
The matlab
Python package provides arrays classes to represent arrays of MATLAB numeric types as Python variables so that MA Tlab arrays can be passed between Python and MATLAB.
Default Numeric Types in MATLAB and Python
MATLAB stores all numeric values as double-precision floating point numbers by default.
Troubleshooting
Limitations to MATLAB Engine API for Python
The engine cannot start or connect to MATLAB in a remote machine.
Troubleshoot MATLAB Errors in Python
When a MATLAB function raises an error, the MATLAB Engine for Python stops the function and catches the exception raised B Y MATLAB.
[Python-matlab] API for invoking MATLAB in Python