some typos.

This commit is contained in:
Fang Liu
2025-06-14 09:27:53 +08:00
parent e7684ac2f7
commit 95429d26f9
2 changed files with 5 additions and 5 deletions

View File

@@ -409,7 +409,7 @@ p = [γ => 0.0,
prob = ODEProblem(sys, u0, TSPAN, p, jac=true) prob = ODEProblem(sys, u0, TSPAN, p, jac=true)
sol = solve(prob,Tsit5()) sol = solve(prob,Tsit5())
plot(t -> sol(t)[3], t -> sol(t)[4], TSPAN..., legend=false) plot(t -> sol(t)[1], t -> sol(t)[3], TSPAN..., legend=false)
``` ```
The toolkit will automatically generate fast functions and can perform transformations (such as is done by `ode_order_lowering`) before passing along to the numeric solves. The toolkit will automatically generate fast functions and can perform transformations (such as is done by `ode_order_lowering`) before passing along to the numeric solves.

View File

@@ -340,7 +340,7 @@ The first-order initial value equations we have seen can be described generally
$$ $$
\begin{align*} \begin{align*}
y'(x) &= F(y,x),\\ y'(x) &= F(y,x),\\
y(x_0) &= x_0. y(x_0) &= y_0.
\end{align*} \end{align*}
$$ $$
@@ -375,7 +375,7 @@ $$
u'(x) = a u(1-u), \quad a > 0 u'(x) = a u(1-u), \quad a > 0
$$ $$
Before beginning, we look at the form of the equation. When $u=0$ or $u=1$ the rate of change is $0$, so we expect the function might be bounded within that range. If not, when $u$ gets bigger than $1$, then the slope is negative and when $u$ gets less than $0$, the slope is positive, so there will at least be a drift back to the range $[0,1]$. Let's see exactly what happens. We define a parameter, restricting `a` to be positive: Before beginning, we look at the form of the equation. When $u=0$ or $u=1$ the rate of change is $0$, so we expect the function might be bounded within that range. If not, when $u$ gets bigger than $1$, then the slope is negative and though the slope is negative too when $u<0$, but for a realistic problem, it always be $u\ge0$. so we focus $u$ on the range $[0,1]$. Let's see exactly what happens. We define a parameter, restricting `a` to be positive:
```{julia} ```{julia}
@@ -403,7 +403,7 @@ To finish, we call `dsolve` to find a solution (if possible):
out = dsolve(eqn) out = dsolve(eqn)
``` ```
This answer - to a first-order equation - has one free constant, `C_1`, which can be solved for from an initial condition. We can see that when $a > 0$, as $x$ goes to positive infinity the solution goes to $1$, and when $x$ goes to negative infinity, the solution goes to $0$ and otherwise is trapped in between, as expected. This answer - to a first-order equation - has one free constant, `C`, which can be solved for from an initial condition. We can see that when $a > 0$, as $x$ goes to positive infinity the solution goes to $1$, and when $x$ goes to negative infinity, the solution goes to $0$ and otherwise is trapped in between, as expected.
The limits are confirmed by investigating the limits of the right-hand: The limits are confirmed by investigating the limits of the right-hand:
@@ -420,7 +420,7 @@ We can confirm that the solution is always increasing, hence trapped within $[0,
diff(rhs(out),x) diff(rhs(out),x)
``` ```
Suppose that $u(0) = 1/2$. Can we solve for $C_1$ symbolically? We can use `solve`, but first we will need to get the symbol for `C_1`: Suppose that $u(0) = 1/2$. Can we solve for $C_1$ symbolically? We can use `solve`, but first we will need to get the symbol for `C`:
```{julia} ```{julia}