Ndarray Indexing

Description

ndarray objects use a similar indexing system to iterable Python data types. To access an element of a multidimensional array, we use an "outside-in" approach. For instance, to access the location of the number 7 in the following 3 dimensional array a:

[[[1 2]
  [3 4]]

 [[5 6]
  [7 8]]]

we would call the index of the 2-dimensional array containing [5 6] and [7 8], then the index of 7 in the 1-dimensional array containing 7 like so: a[1, 1, 0]

Sage Cell

Code

a = np.array([[[1, 2], [3, 4]], [[5, 6], [7, 8]]])
print(a[1, 1, 0])

Options

Slicing Arrays

We can take multiple items at once by passing a range of indices instead of only one using :. For instance, if we wanted all items in an array b from index 0 to index 5, we would use 0:6. We can also tell the program to simply get everything to the end of the array by leaving the range unbounded, like so: 0:. Note the last number in the given range is excluded. As an example, the following cell shows how to get the first item in every 1 -dimensional array stored in 3 dimensional array a.

Code

a = np.array([[[1, 2], [3, 4]], [[5, 6], [7, 8]]])
print(a[0:, 0:, 0])

Tags

Primary Tags:

Secondary Tags:

A list of possible tags can be found at The WeBWorK Open Problem Library. For linear algebra tags see the Curated Courses Project.

Related Cells

Any related cells go here. Provide a link to the page containing the information about the cell.

Attribute

Permalink:

Author:

Date: 06 Apr 2019 19:08

Submitted by: Zane Corbiere

Unless otherwise stated, the content of this page is licensed under Creative Commons Attribution-ShareAlike 3.0 License