Pass matlab array to python

Pass Scalar Values to Python

MATLAB Input Argument Type —
Scalar Values Only

Resulting Python py. Type

Examples

z = complex[1,2];
py.cmath.polar[z]

ans = 
  Python tuple with no properties.

    [2.23606797749979, 1.1071487177940904]

py.list[{string[missing],'Value'}]

ans = 
  Python list with no properties.

    [None, 'Value']

Pass Vectors to Python

MATLAB Input Argument Type —
1-by-N Vector

Resulting Python Type

Pass Matrices and Multidimensional Arrays to Python

The Python language provides a protocol for accessing memory buffers like the data stored in a MATLAB array. MATLAB implements this Python buffer protocol for MATLAB arrays so that you can read MATLAB arrays directly from Python code, running in the same process as MATLAB, without copying data.

Many Python functions directly use the MATLAB array from Python without converting it to a native Python type. Some functions might require a specific type, such as numpy.ndarray, or might modify data in the array. These functions might accept the MATLAB array and copy the data into the required type. Other functions might display an error if you do not pass the required type. To pass data to these functions, first create the required Python type from the MATLAB data, then pass it to the Python function. For example, to create array p to pass to a Python function that requires data of type numpy.array, type:

p = py.numpy.array[magic[3]]

p = 

  Python ndarray:

     8     1     6
     3     5     7
     4     9     2

    Use details function to view the properties of the Python object.

    Use double function to convert to a MATLAB array.

MATLAB sparse arrays are not supported in Python. See Unsupported MATLAB Types.

a = [1 2; 3 4];
py.pyfunc[a]

py.pyfunc[numpy.ndarray[a]]

Automatically Convert Python Types to MATLAB Types

MATLAB automatically converts these data types returned from Python functions into MATLAB types. To convert other types, see Explicitly Convert Python Types to MATLAB Types.

Python Return Type, as Displayed in Python

Resulting MATLAB Type — Scalar

Explicitly Convert Python Types to MATLAB Types

If the output of a Python function implements the Python buffer protocol, such as numpy.ndarray, and it is numeric or logical, then MATLAB displays:

• The actual Python type

• The underlying data

• The corresponding MATLAB conversion function. Use this function to fully convert the Python object to a MATLAB array.

Use these MATLAB functions to convert Python data types to MATLAB types.

Python Return Type or Protocol, as Displayed in MATLAB

MATLAB Conversion Function

Examples

py.help['datetime.date.__str__']

Help on wrapper_descriptor in datetime.date:

datetime.date.__str__ = __str__[self, /]
    Return str[self].

d = py.datetime.date[...
    int32[2020],int32[3],int32[4]];
char[d]

ans = '2020-3-04'

For example, a Python function returns this array p:

p = 

  Python ndarray:

     8     1     6
     3     5     7
     4     9     2

    Use details function to view the properties of the Python object.

    Use double function to convert to a MATLAB array.

You can convert it to a MATLAB matrix P by typing:

P = 3×3    
     8     1     6
     3     5     7
     4     9     2

If you need specific information about the Python properties of p, type:

    py.numpy.ndarray handle with properties:

           T: [1×1 py.numpy.ndarray]
        base: [1×1 py.NoneType]
      ctypes: [1×1 py.numpy.core._internal._ctypes]
        data: [1×3 py.memoryview]
       dtype: [1×1 py.numpy.dtype[float64]]
       flags: [1×1 py.numpy.flagsobj]
        flat: [1×1 py.numpy.flatiter]
        imag: [1×1 py.numpy.ndarray]
    itemsize: [1×1 py.int]
      nbytes: [1×1 py.int]
        ndim: [1×1 py.int]
        real: [1×1 py.numpy.ndarray]
       shape: [1×2 py.tuple]
        size: [1×1 py.int]
     strides: [1×2 py.tuple]

  Methods, Events, Superclasses

If the Python module provides content in its __doc__ attribute, then MATLAB links to that information.

Unsupported MATLAB Types

These MATLAB types are not supported in Python.

• Multidimensional char or cell arrays

• Structure arrays

• Sparse arrays

• categorical,
  table,
  containers.Map,
  datetime types

• MATLAB objects

• meta.class [py.class]