# Evaluate a 3-D Chebyshev series on the Cartesian product of x, y and z with 2d array of coefficient

In this article, we will discuss how to evaluate a 3-D Chebyshev series on the Cartesian product of x, y, and z with a 2d array of coefficients in Python and NumPy.

**Example**

Input:[[0 1] [2 3]]Output:[[17. 28.] [28. 46.]]Explanation:A 3-D Chebyshev series on the Cartesian product.

With the help of **NumPy.polynomial.Chebyshev.****chebgrid3d()** method, we can get the array of coefficients after evaluating the Chebyshev series on the cartesian product of x, y, and z by using the np.chebgrid3d() method. Here, x, y, and z are tuples or lists, they are converted to arrays. These elements must be capable of multiplication and addition among themselves as well as with the constituents of c. If the shape of the **c** has fewer than three dimensions, ones are implicitly added to make it three-dimensional.

Syntax:numpy.polynomial.chebyshev.chebgrid3d()

Parameters:

x,y,z: array like objects.The points in the Cartesian product of x, y, and z are used to assess the three-dimensional series.c:The coefficients for terms of degree i,j are contained in c[i,j].

Returns:values: array like object

**Example 1:**

Here, the NumPy package is imported and np.array() is used to create a 2-d array the **.shape** attribute is used to find the shape of the array, the **.ndim** attribute is used to find the dimensions of the array, the **.dtype** attribute is used to find the data type of the array and **numpy.polynomial.chebyshev.chebgrid3d()** is used to evaluate the 3-d Chebyshev series.

## Python3

`# import packages` `import` `numpy as np` `from` `numpy.polynomial ` `import` `chebyshev as Chev` ` ` `# array of coefficients` `c ` `=` `np.array([[` `2` `,` `2` `],[` `3` `,` `3` `]])` `print` `(c)` ` ` `# shape of the array is` `print` `(` `"Shape of the array is : "` `,c.shape)` ` ` `# dimension of the array` `print` `(` `"The dimension of the array is : "` `,c.ndim)` ` ` `# Datatype of the array` `print` `(` `"Datatype of our Array is : "` `,c.dtype)` ` ` `#evaluating Chebyshev series` `print` `(Chev.chebgrid3d([` `1` `,` `2` `],[` `3` `,` `4` `],[` `5` `,` `6` `],c))` |

**Output:**

[[2 2] [3 3]] Shape of the array is : (2, 2) The dimension of the array is : 2 Datatype of our Array is : int64 [[180. 212.] [225. 265.]]

### Example 2:

In this example, we are using a 1-D array to evaluate a 3-D Chebyshev series on the Cartesian product series.

## Python3

`# import packages` `import` `numpy as np` `from` `numpy.polynomial ` `import` `chebyshev as Chev` ` ` `# array of coefficients` `c ` `=` `np.array([` `2` `,` `2` `,` `3` `])` `print` `(c)` ` ` `# shape of the array is` `print` `(` `"Shape of the array is : "` `,c.shape)` ` ` `# dimension of the array` `print` `(` `"The dimension of the array is : "` `,c.ndim)` ` ` `# Datatype of the array` `print` `(` `"Datatype of our Array is : "` `,c.dtype)` ` ` `#evaluating Chebyshev series` `print` `(Chev.chebgrid3d([` `1` `,` `2` `],[` `3` `,` `4` `],[` `5` `,` `6` `],c))` |

**Output:**

[2 2 3] Shape of the array is : (3,) The dimension of the array is : 1 Datatype of our Array is : int32 [663. 778.]