Title: Theory / Important / CS / Programming / Python / SciPy / NumPy

Name: Broadcasting
Definition: assuming \(i<i'\), replace the first array such that its shape is \((1,\dots,1,foo_i,\dots,foo_1)\) so that they have the same length
Page: https://www.numpy.org/devdocs/user/basics.broadcasting.html
Definition2: for each dimension such that \(foo_k=1\) and \(foo'_k>1\), copy the array \(foo'_k\) times in dimension \(k\) (and similarly when inversing \(foo\) and \(foo'\))
Conjdef: Given two compatible shapes \((foo_i,\dots,foo_1)\) and \((foo_{i'}',\dots,foo_1')\), changing as follows
Intuition: how numpy treats arrays with different shapes during arithmetic operations.

Name: compatible dimensions
Definition: equal
Page: https://www.numpy.org/devdocs/user/basics.broadcasting.html
Context: ndarray
Definition2: one is 1
Conjdef: either
DefType: Dimensions

Page: https://www.numpy.org/devdocs/user/basics.broadcasting.html
Definition: Relation on shapes \((foo_i,\dots,foo_1)\) and \((foo_j',\dots,foo_1')\) such that \(foo_k\) is a compatiable dimension with \(foo_k'\) for \(k\le\min(i,j)\)
Name: compatible shape
Context: ndarray