The matlab Python® package provides array
classes to represent arrays of MATLAB® numeric types as Python variables.
You can create MATLAB numeric arrays in a Python session
by calling constructors from the matlab Python package
(for example, matlab.double, matlab.int32).
The name of the constructor indicates the MATLAB numeric type.
You can pass MATLAB arrays as input arguments to MATLAB functions
called from Python. When a MATLAB function returns a numeric
array as an output argument, the array is returned to Python.
You can initialize the array with an optional initializer input
argument that contains numbers. The initializer argument
must be a Python sequence type such as a list or a tuple. The
optional size input argument sets the size of the
initialized array. To create multidimensional arrays, specify initializer to
contain multiple sequences of numbers, or specify size to
be multidimensional. You can create a MATLAB array of complex
numbers by setting the optional is_complex keyword
argument to True. The mlarray module
provides the MATLAB array constructors listed in the table.
Class from | Constructor Call in Python | MATLAB Numeric Type |
|---|---|---|
| matlab.double( initializer=None, size=None, is_complex=False) | Double precision |
| matlab.single( initializer=None, size=None, is_complex=False) | Single precision |
| matlab.int8( initializer=None, size=None, is_complex=False) | 8-bit signed integer |
| matlab.int16( initializer=None, size=None, is_complex=False) | 16-bit signed integer |
| matlab.int32( initializer=None, size=None, is_complex=False) | 32-bit signed integer |
| matlab.int64( initializer=None, size=None, is_complex=False) | 64-bit signed integer |
| matlab.uint8( initializer=None, size=None, is_complex=False) | 8-bit unsigned integer |
| matlab.uint16( initializer=None, size=None, is_complex=False) | 16-bit unsigned integer |
| matlab.uint32( initializer=None, size=None, is_complex=False) | 32-bit unsigned integer |
| matlab.uint64( initializer=None, size=None, is_complex=False) | 64-bit unsigned integer |
| matlab.logical( initializer=None, size=None)[c] | Logical |
[a] In Python
2.7 on Windows, [b] In Python
2.7 on Windows, [c] Logicals cannot be made into an array of complex numbers. | ||
When you create an array with N elements,
the size is 1-by-N because it is a MATLAB array.
import matlab A = matlab.int8([1,2,3,4,5]) print(A.size) (1, 5)
The initializer is a Python list containing five numbers.
The MATLAB array size is 1-by-5, indicated by the tuple (1,5).
All MATLAB arrays created with matlab package
constructors have the attributes and methods listed in the table below:
Attribute or Method | Purpose |
|---|---|
| Size of array returned as a tuple |
| Reshape the array as specified by the sequence |
In Python, you can create multidimensional MATLAB arrays of any numeric type. Use two Python lists of floats to create a 2-by-5 MATLAB array of doubles.
import matlab A = matlab.double([[1,2,3,4,5], [6,7,8,9,10]]) print(A) [[1.0,2.0,3.0,4.0,5.0],[6.0,7.0,8.0,9.0,10.0]]
The size attribute of A shows
it is a 2-by-5 array.
print(A.size) (2, 5)
You can index into MATLAB arrays just as you can index into Python lists and tuples.
import matlab A = matlab.int8([1,2,3,4,5]) print(A[0]) [1,2,3,4,5]
The size of the MATLAB array is (1,5);
therefore, A[0] is [1,2,3,4,5].
Index into the array to get 3.
print(A[0][2]) 3
Python indexing is zero-based. When you access elements of MATLAB arrays in a Python session, use zero-based indexing.
This example shows how to index into a multidimensional MATLAB array.
A = matlab.double([[1,2,3,4,5], [6,7,8,9,10]]) print(A[1][2]) 8.0
You can slice MATLAB arrays just as you can slice Python lists and tuples.
import matlab A = matlab.int8([1,2,3,4,5]) print(A[0][1:4]) [2,3,4]
You can assign data to a slice. This example shows an assignment from a Python list to the array.
A = matlab.double([[1,2,3,4],[5,6,7,8]]) A[0] = [10,20,30,40] print(A) [[10.0,20.0,30.0,40.0],[5.0,6.0,7.0,8.0]]
You can assign data from another MATLAB array, or from any Python iterable that contains numbers.
You can specify slices for assignment, as shown in this example.
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) [[1,2,30,40,5,6,70,80]]
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. >>>mlarray = matlab.int32([[1,2],[3,4],[5,6]]) >>>py_list = [[1,2],[3,4],[5,6]] >>>mlarray[0] = mlarray[0][::-1] >>>py_list[0] = py_list[0][::-1] >>>mlarray[0] matlab.int32([[2,2],[3,4],[5,6]]) >>>py_list [[2,1],[3,4],[5,6]] |
You can reshape a MATLAB array in Python with the reshape method.
The input argument, size, must be a sequence that
does not change the number of elements in the array. Use reshape to
change a 1-by-9 MATLAB array to 3-by-3.
import matlab A = 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]]