From 308a163a4a604288460ef9b8b6fc5f694b541159 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Ole=20Sch=C3=BCtt?= <ole.schuett@cp2k.org>
Date: Fri, 20 Dec 2024 12:34:05 +0100
Subject: [PATCH] Docs: Also look for keyword mentions in other subdirs

---
 docs/generate_input_reference.py       | 7 ++++---
 docs/technologies/eigensolvers/dlaf.md | 4 ++--
 2 files changed, 6 insertions(+), 5 deletions(-)

diff --git a/docs/generate_input_reference.py b/docs/generate_input_reference.py
index bda3a34849..fa36eff4be 100755
--- a/docs/generate_input_reference.py
+++ b/docs/generate_input_reference.py
@@ -386,9 +386,10 @@ def render_keyword(
 def find_all_mentions() -> Dict[str, Set[Path]]:
     root_dir = Path(__file__).resolve().parent
     mentions = defaultdict(set)
-    for fn in (root_dir / "methods").glob("**/*.md"):
-        for xref in re.findall(r"\(#(CP2K_INPUT\..*)\)", fn.read_text()):
-            mentions[xref].add(fn.relative_to(root_dir))
+    for subdir in "getting-started", "methods", "technologies":
+        for fn in (root_dir / subdir).glob("**/*.md"):
+            for xref in re.findall(r"\(#(CP2K_INPUT\..*)\)", fn.read_text()):
+                mentions[xref].add(fn.relative_to(root_dir))
     return mentions
 
 
diff --git a/docs/technologies/eigensolvers/dlaf.md b/docs/technologies/eigensolvers/dlaf.md
index 5939a1b8bf..3747eece3e 100644
--- a/docs/technologies/eigensolvers/dlaf.md
+++ b/docs/technologies/eigensolvers/dlaf.md
@@ -25,7 +25,7 @@ and optional dependencies.
 ## CP2K Input File
 
 [DLA-Future] can be selected in the CP2K input file with the
-[`PREFERRED_DIAG_LIBRARY`](#CP2K_INPUT.GLOBAL.PREFERRED_DIAG_LIBRARY) keyword:
+[PREFERRED_DIAG_LIBRARY](#CP2K_INPUT.GLOBAL.PREFERRED_DIAG_LIBRARY) keyword:
 
 ```
 &GLOBAL
@@ -35,7 +35,7 @@ and optional dependencies.
 &END GLOBAL
 ```
 
-The [`DLAF_NEIGVEC_MIN`](#CP2K_INPUT.GLOBAL.DLAF_NEIGVEC_MIN) indicates the minimum matrix size for
+The [DLAF_NEIGVEC_MIN](#CP2K_INPUT.GLOBAL.DLAF_NEIGVEC_MIN) indicates the minimum matrix size for
 which DLA-Future is used instead of ScaLAPACK. DLA-Future is optimized for large matrices on GPUs,
 and might be slower than ScaLAPACK for small matrices or CPU matrices.