From 85deee78430845ec3a7d6dc7af3484057001f5d3 Mon Sep 17 00:00:00 2001
From: Jake Pullen <hello@jake-is.me>
Date: Tue, 9 Dec 2025 18:23:17 +0000
Subject: [PATCH] =?UTF-8?q?fix:=20=F0=9F=9A=91=EF=B8=8F=20Updated=20docume?=
 =?UTF-8?q?ntation=20and=20small=20tweaks=20to=20tidy=20up?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 README.MD      |  5 -----
 main.py        | 20 ++++++++++----------
 pyproject.toml |  2 +-
 uv.lock        |  2 +-
 4 files changed, 12 insertions(+), 17 deletions(-)

diff --git a/README.MD b/README.MD
index c234d8e..85db07c 100644
--- a/README.MD
+++ b/README.MD
@@ -9,7 +9,6 @@ The project consists of a main pipeline workflow that processes multiple modules
 - `main.py`: Main pipeline orchestrator that calls on the modules as needed
 - `batch_nimrod.py`: Module for batch processing multiple NIMROD files with configurable bounding boxes
 - `generate_timeseries.py`: Module for extracting cropped rain data and creating rainfall timeseries
-- `combine_timeseries.py`: Module for combining grouped timeseries CSVs into consolidated datasets
 
 ## Features
 
@@ -31,10 +30,6 @@ The project consists of a main pipeline workflow that processes multiple modules
 - Extract cropped rain data based on specified locations
 - Create rainfall timeseries CSVs for each location
 - Parse datetime from filename and create proper datetime index
-
-### combine_timeseries.py
-
-- Combine multiple timeseries CSV files into grouped datasets
 - Group locations by specified output groups
 - Create consolidated CSV files for each group
 
diff --git a/main.py b/main.py
index d244034..b038ccc 100644
--- a/main.py
+++ b/main.py
@@ -12,6 +12,16 @@ logging.basicConfig(
     level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s"
 )
 
+def process_pipeline(dat_file):
+    # 1. Process DAT to ASC
+    asc_file = batch._process_single_file(dat_file)
+    if not asc_file:
+        return None
+
+    # 2. Extract data from ASC
+    file_results = timeseries.process_asc_file(asc_file, locations)
+    return file_results
+
 if __name__ == "__main__":
     os.makedirs(Path(Config.ASC_TOP_FOLDER), exist_ok=True)
     os.makedirs(Path(Config.COMBINED_FOLDER), exist_ok=True)
@@ -45,16 +55,6 @@ if __name__ == "__main__":
     # Initialize results structure
     results = {loc[0]: {"dates": [], "values": []} for loc in locations}
 
-    def process_pipeline(dat_file):
-        # 1. Process DAT to ASC
-        asc_file = batch._process_single_file(dat_file)
-        if not asc_file:
-            return None
-
-        # 2. Extract data from ASC
-        file_results = timeseries.process_asc_file(asc_file, locations)
-        return file_results
-
     # Get list of DAT files
     dat_files = [
         f for f in os.listdir(Path(Config.DAT_TOP_FOLDER)) if not f.startswith(".")
diff --git a/pyproject.toml b/pyproject.toml
index c3ecfef..1f10b49 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [project]
 name = "met-office"
-version = "1.1.0"
+version = "1.1.1"
 description = "Convert .dat nimrod files to .asc files"
 readme = "README.md"
 requires-python = ">=3.14"
diff --git a/uv.lock b/uv.lock
index a0b486f..127efef 100644
--- a/uv.lock
+++ b/uv.lock
@@ -4,7 +4,7 @@ requires-python = ">=3.14"
 
 [[package]]
 name = "met-office"
-version = "1.1.0"
+version = "1.1.1"
 source = { virtual = "." }
 dependencies = [
     { name = "numpy" },