From b2bf43bf1669e7eecbd84b5eebae433a9202105b Mon Sep 17 00:00:00 2001 From: shaowu Date: Thu, 5 Oct 2023 20:49:37 -0400 Subject: [PATCH] second update JOSS --- docs/JOSS/paper.md | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/docs/JOSS/paper.md b/docs/JOSS/paper.md index 0b13bc2..1f28bb3 100644 --- a/docs/JOSS/paper.md +++ b/docs/JOSS/paper.md @@ -181,7 +181,10 @@ Xnext = np.vstack(Xnext) ``` We plot `X` in Fig. \ref{fig:example-edmd}, while `Xnext` is omitted for brevity. -Now we start using `pykoopman` to learn Koopman operator from the above system. To begin with, we can create an observable function and an appropriate regressor. These two objects will then serve as input for the `pykoopman.Koopman` class. For instance, we can employ EDMD to approximate the slow manifold dynamics as shown in Fig. \ref{eq:slow_manifold}. +Now we start using `pykoopman` to learn Koopman operator from the above system. +To begin with, we can create an observable function and an appropriate regressor. +These two objects will then serve as input for the `pykoopman.Koopman` class. +For instance, we can employ EDMD to approximate the slow manifold dynamics as shown in Fig. \ref{eq:example-edmd}. ```python from pykoopman import Koopman