rm WeaveSupport

quarto/differentiable_vector_calculus/plots_plotting.qmd

@@ -14,17 +14,6 @@ using LinearAlgebra
 using ForwardDiff
 ```
 
-```{julia}
-#| echo: false
-#| results: "hidden"
-using CalculusWithJulia.WeaveSupport
-frontmatter = (
-    title = "2D and 3D plots in Julia with Plots",
-    description = "Calculus with Julia: 2D and 3D plots in Julia with Plots",
-    tags = ["CalculusWithJulia", "differentiable_vector_calculus", "2d and 3d plots in julia with plots"],
-);
-nothing
-```
 
 ---
 
@@ -121,10 +110,10 @@ for t in ts
 end
 ```
 
-```{julia}
-#| echo: false
-note("""Adding many arrows this way would be inefficient.""")
-```
+:::{.callout-note}
+## Note
+Adding many arrows this way would be inefficient.
+:::
 
 ### Setting a viewing angle for 3D plots
 
@@ -381,10 +370,10 @@ zs = [Z(1, theta, phi) for theta in thetas, phi in phis]
 surface(xs, ys, zs)
 ```
 
-```{julia}
-#| echo: false
-note("The above may not work with all backends for `Plots`, even if those that support 3D graphics.")
-```
+:::{.callout-note}
+## Note
+The above may not work with all backends for `Plots`, even if those that support 3D graphics.
+    :::
 
 For convenience, the `plot_parametric` function from `CalculusWithJulia` can produce these plots using interval notation, `a..b`,  and a function:
 
@@ -419,4 +408,3 @@ a,b = 1,3
 f(x,y,z) = (x^2+((1+b)*y)^2+z^2-1)^3-x^2*z^3-a*y^2*z^3
 CalculusWithJulia.plot_implicit_surface(f, xlim=-2..2, ylim=-1..1, zlim=-1..2)
 ```
-

quarto/differentiable_vector_calculus/polar_coordinates.qmd

@@ -14,21 +14,6 @@ using Roots
 using QuadGK
 ```
 
-```{julia}
-#| echo: false
-#| results: "hidden"
-using CalculusWithJulia.WeaveSupport
-
-frontmatter = (
-        title = "Polar Coordinates and Curves",
-        description = "Calculus with Julia: Polar Coordinates and Curves",
-        tags = ["CalculusWithJulia", "differentiable_vector_calculus", "polar coordinates and curves"],
-);
-using LaTeXStrings
-
-nothing
-```
-
 ---
 
 
@@ -785,4 +770,3 @@ r(theta) = sqrt(cos(2theta) * sec(theta)^4)
 val, _ = quadgk(t -> sqrt(D(r)(t)^2 + r(t)^2), -pi/4, pi/4)
 numericq(val)
 ```
-

quarto/differentiable_vector_calculus/scalar_functions.qmd

@@ -26,15 +26,7 @@ import Contour: contours, levels, level, lines, coordinates
 ```{julia}
 #| echo: false
 #| results: "hidden"
-using CalculusWithJulia.WeaveSupport
 using CSV, DataFrames
-
-const frontmatter = (
-        title = "Scalar functions",
-        description = "Calculus with Julia: Scalar functions",
-        tags = ["CalculusWithJulia", "differentiable_vector_calculus", "scalar functions"],
-);
-
 nothing
 ```
 
@@ -2436,4 +2428,3 @@ What equation does the function $f(x,y) = \cos(x) + \sin(y)$ satisfy?
 answ = 5
 radioq(ode_choices, answ, keep_order=true)
 ```
-

quarto/differentiable_vector_calculus/scalar_functions_applications.qmd

@@ -20,19 +20,6 @@ And the following from the `Contour` package:
 import Contour: contours, levels, level, lines, coordinates
 ```
 
-```{julia}
-#| echo: false
-#| results: "hidden"
-using CalculusWithJulia.WeaveSupport
-
-const frontmatter = (
-        title = "Applications with scalar functions",
-        description = "Calculus with Julia: Applications with scalar functions",
-        tags = ["CalculusWithJulia", "differentiable_vector_calculus", "applications with scalar functions"],
-);
-
-nothing
-```
 
 This section presents different applications of scalar functions.
 
@@ -2309,4 +2296,3 @@ ts = fzeros(fn, 0, 2pi)
 val = maximum((f∘r).(ts))
 numericq(val)
 ```
-

quarto/differentiable_vector_calculus/vector_fields.qmd

@@ -14,19 +14,6 @@ using ForwardDiff
 using LinearAlgebra
 ```
 
-```{julia}
-#| echo: false
-#| results: "hidden"
-using CalculusWithJulia.WeaveSupport
-
-const frontmatter = (
-        title = "Functions ``R^n \\rightarrow R^m``",
-        description = "Calculus with Julia: Functions ``R^n \\rightarrow R^m``",
-        tags = ["CalculusWithJulia", "differentiable_vector_calculus", "functions ``R^n \\rightarrow R^m``"],
-);
-
-nothing
-```
 
 For a scalar function $f: R^n \rightarrow R$, the gradient of $f$, $\nabla{f}$, is a function from $R^n \rightarrow R^n$. Specializing to $n=2$, a function that for each point, $(x,y)$, assigns a vector $\vec{v}$. This is an example of vector field. More generally, we  could have a [function](https://en.wikipedia.org/wiki/Multivariable_calculus) $f: R^n \rightarrow R^m$, of which we have discussed many already:
 
@@ -1123,5 +1110,3 @@ radioq(choices, answ)
 ```
 
 (The latter is of interest, as only when the expression is $0$ will the vector field be the gradient of a scalar function.)
-
-

quarto/differentiable_vector_calculus/vector_valued_functions.qmd

@@ -23,18 +23,6 @@ import DifferentialEquations
 import DifferentialEquations: ODEProblem, Tsit5
 ```
 
-```{julia}
-#| echo: false
-#| results: "hidden"
-using CalculusWithJulia.WeaveSupport
-frontmatter = (
-    title = "Vector-valued functions, ``f:R \\rightarrow R^n``",
-    description = "Calculus with Julia: Vector-valued functions, ``f:R \\rightarrow R^n``",
-    tags = ["CalculusWithJulia", "differentiable_vector_calculus", "vector-valued functions, ``f:R \\rightarrow r^n``"],
-);
-
-nothing
-```
 
 ---
 
@@ -2795,4 +2783,3 @@ choices = [
 answ = 1
 radioq(choices, answ)
 ```
-

quarto/differentiable_vector_calculus/vectors.qmd

@@ -13,19 +13,6 @@ using LinearAlgebra
 using SymPy
 ```
 
-```{julia}
-#| echo: false
-#| results: "hidden"
-using CalculusWithJulia.WeaveSupport
-
-const frontmatter = (
-        title = "Vectors and matrices",
-        description = "Calculus with Julia: Vectors and matrices",
-        tags = ["CalculusWithJulia", "differentiable_vector_calculus", "vectors and matrices"],
-);
-
-nothing
-```
 
 ---
 
@@ -716,13 +703,10 @@ and
 ```{julia}
 [𝓊'; 𝓋']
 ```
-
-```{julia}
-#| echo: false
-note("""
+:::{.callout-note}
+## Note
 The adjoint is defined *recursively* in `Julia`. In the `CalculusWithJulia` package, we overload the `'` notation for *functions* to yield a univariate derivative found with automatic differentiation. This can lead to problems: if we have a matrix of functions, `M`, and took the transpose with `M'`, then the entries of `M'` would be the derivatives of the functions in `M` - not the original functions. This is very much likely to not be what is desired. The `CalculusWithJulia` package commits **type piracy** here *and* abuses the generic idea for `'` in Julia. In general type piracy is very much frowned upon, as it can change expected behaviour. It is defined in `CalculusWithJulia`, as that package is intended only to act as a means to ease users into the wider package ecosystem of `Julia`.
-""")
-```
+:::
 
 ---
 
@@ -768,12 +752,11 @@ $$
 \vec{u} \times \vec{v} =  \| \vec{u} \| \| \vec{v} \| \sin(\theta) \hat{n}.
 $$
 
-```{julia}
-#| echo: false
-note("""
+:::{callout-note}
+## Note
 The right-hand rule is also useful to understand how standard household screws will behave when twisted with a screwdriver. If the right hand fingers curl in the direction of the twisting screwdriver, then the screw will go in or out following the direction pointed to by the thumb.
-""")
-```
+
+:::
 
 The right-hand rule depends on the order of consideration of the vectors. If they are reversed, the opposite direction is determined. A consequence is that the cross product is **anti**-commutative, unlike multiplication:
 
@@ -1519,4 +1502,3 @@ choices = [
 answ = 1
 radioq(choices, answ)
 ```
-