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Use Python Numeric Variables in MATLAB

This example shows how to use Python® numeric types in MATLAB®.

Use Python Numeric Types in MATLAB

When calling a Python function that takes a numeric input argument, MATLAB converts double values into types that best represent the data to the Python language. For example, to call trigonometry functions in the Python math module, pass a MATLAB double value.

pynum = py.math.radians(90)
pynum = 1.5708

For functions that return Python float types, MATLAB automatically converts this type to double.

class(pynum)
ans = 
'double'

For Python functions returning integer types, MATLAB automatically converts this type to int64. For example, the bit_length function returns the number of bits necessary to represent an integer in binary as an int value.

py.int(intmax).bit_length
ans = 
  Python int with properties:

    denominator: [1×1 py.int]
           imag: [1×1 py.int]
      numerator: [1×1 py.int]
           real: [1×1 py.int]

    31

Call Python Methods with Numeric iterable Arguments

The Python math.fsum function sums floating-point values in an iterable input argument. You can pass a MATLAB vector to this function. For example, open the MATLAB patients.mat data file and read the numeric array Height.

load patients.mat
class(Height)
ans = 
'double'
size(Height)
ans = 1×2

   100     1

When you pass this argument to Python, MATLAB automatically converts the numeric values to Python numeric values and Python iterates over the vector values.

py.math.fsum(Height)
ans = 6707

Use Python array Types in MATLAB

Suppose that you have a Python function that returns the following Python array.array of type double.

P = py.array.array('d', 1:5)
P = 
  Python array:

     1     2     3     4     5

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

    Use double function to convert to a MATLAB array.

To pass P to the MATLAB function sum, convert P to a MATLAB array of type double.

sum(double(P))
ans = 15

Use Python Integer array Types in MATLAB

Suppose that you have a Python array of 8-byte signed integers. Call the Python reverse function on the array, then convert the result to a MATLAB array.

arr = py.array.array('q',[int64(5),int64(1),int64(-5)])
arr = 
  Python array:

    5    1   -5

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

    Use int64 function to convert to a MATLAB array.

arr.reverse
A = int64(arr)
A = 1×3 int64 row vector

   -5    1    5

Default Numeric Types

By default, a number in MATLAB is a double type. By default, a number (without a fractional part) in Python is an integer type. This difference can cause confusion when passing numbers to Python functions.

For example, when you pass these MATLAB numbers to the Python datetime function, Python reads them as float types and displays an error:

d = py.datetime.date(2014,12,31)

Python Error: TypeError: integer argument expected, got float

To correct the error, explicitly convert each number to an integer type:

d = py.datetime.date(int32(2014),int32(12),int32(31))
d = 
  Python date with properties:

      day: [1×1 py.int]
    month: [1×1 py.int]
     year: [1×1 py.int]

    2014-12-31

Why Do I See Properties When I Display a Number?

MATLAB displays all Python types as objects, which includes a list of object properties. For numeric types, MATLAB displays the expected output value on the last line.

py.int(5)
ans = 
  Python int with properties:

    denominator: [1×1 py.int]
           imag: [1×1 py.int]
      numerator: [1×1 py.int]
           real: [1×1 py.int]

    5