@@ -141,10 +141,12 @@ column vectors.
141141
142142The set of all $n$-vectors is denoted by $\mathbb R^n$.
143143
144- For example,
144+ ``` {prf:example}
145+ :label: le_ex_dim
145146
146147* $\mathbb R^2$ is the plane --- the set of pairs $(x_1, x_2)$.
147148* $\mathbb R^3$ is 3 dimensional space --- the set of vectors $(x_1, x_2, x_3)$.
149+ ```
148150
149151Often vectors are represented visually as arrows from the origin to the point.
150152
@@ -185,7 +187,8 @@ multiplication, which we now describe.
185187
186188When we add two vectors, we add them element-by-element.
187189
188- For example,
190+ ``` {prf:example}
191+ :label: le_ex_add
189192
190193$$
191194\begin{bmatrix}
208211 1
209212\end{bmatrix}.
210213$$
214+ ```
211215
212216In general,
213217
@@ -273,7 +277,8 @@ plt.show()
273277
274278Scalar multiplication is an operation that multiplies a vector $x$ with a scalar elementwise.
275279
276- For example,
280+ ``` {prf:example}
281+ :label: le_ex_mul
277282
278283$$
279284-2
292297 14
293298\end{bmatrix}.
294299$$
300+ ```
295301
296302More generally, it takes a number $\gamma$ and a vector $x$ and produces
297303
@@ -429,7 +435,8 @@ matrices.
429435
430436Scalar multiplication and addition are generalizations of the vector case:
431437
432- Here is an example of scalar multiplication
438+ ``` {prf:example}
439+ :label: le_ex_asm
433440
434441$$
4354423
443450 0 & 15
444451\end{bmatrix}.
445452$$
453+ ```
446454
447455In general for a number $\gamma$ and any matrix $A$,
448456
461469\end{bmatrix}.
462470$$
463471
472+ ``` {prf:example}
473+ :label: le_ex_ma
474+
464475Consider this example of matrix addition,
465476
466477$$
479490 7 & 12
480491\end{bmatrix}.
481492$$
493+ ```
482494
483495In general,
484496
@@ -518,6 +530,9 @@ $j$-th column of $B$.
518530If $A$ is $n \times k$ and $B$ is $j \times m$, then to multiply $A$ and $B$
519531we require $k = j$, and the resulting matrix $A B$ is $n \times m$.
520532
533+ ``` {prf:example}
534+ :label: le_ex_2dmul
535+
521536Here's an example of a $2 \times 2$ matrix multiplied by a $2 \times 1$ vector.
522537
523538$$
536551 a_{21}x_1 + a_{22}x_2
537552\end{bmatrix}
538553$$
554+ ```
539555
540556As an important special case, consider multiplying $n \times k$
541557matrix $A$ and $k \times 1$ column vector $x$.
@@ -839,6 +855,8 @@ In matrix form, the system {eq}`la_se` becomes
839855 \end{bmatrix}.
840856```
841857
858+ ``` {prf:example}
859+ :label: le_ex_gls
842860For example, {eq}`n_eq_sys_la` has this form with
843861
844862$$
848866 \quad \text{and} \quad
849867 x = p.
850868$$
851-
869+ ```
852870
853871When considering problems such as {eq}` la_gf ` , we need to ask at least some of
854872the following questions
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