From c97b681fb0a8d339af0198b62f63b3d7f951af36 Mon Sep 17 00:00:00 2001
From: alessandrofelder <alessandrofelder@users.noreply.github.com>
Date: Fri, 15 Sep 2023 16:41:36 +0100
Subject: [PATCH] scripts -> workflows

---
 README.md                                     |  2 +-
 .../__init__.py                               |  0
 brainglobe_workflows/registration_script.py   | 54 +++++++++++++++++++
 pyproject.toml                                |  4 +-
 4 files changed, 57 insertions(+), 3 deletions(-)
 rename {brainglobe_scripts => brainglobe_workflows}/__init__.py (100%)
 create mode 100644 brainglobe_workflows/registration_script.py

diff --git a/README.md b/README.md
index 48477139..e3bf3ae6 100644
--- a/README.md
+++ b/README.md
@@ -1 +1 @@
-# brainglobe-scripts
+# brainglobe-workflows
diff --git a/brainglobe_scripts/__init__.py b/brainglobe_workflows/__init__.py
similarity index 100%
rename from brainglobe_scripts/__init__.py
rename to brainglobe_workflows/__init__.py
diff --git a/brainglobe_workflows/registration_script.py b/brainglobe_workflows/registration_script.py
new file mode 100644
index 00000000..a60b10cb
--- /dev/null
+++ b/brainglobe_workflows/registration_script.py
@@ -0,0 +1,54 @@
+import os
+from pathlib import Path
+import subprocess
+import json
+from typing import Dict, Union
+
+Pathlike = Union[str, bytes, os.PathLike]
+# TODO: use pydantic or attrs, and/or a dataclass, for this??
+def _default_config():
+	defaults = {
+        "sample_data_path"
+    }
+
+def _validate_config(config_dict: Dict[str]):
+	expected_keys = [
+		"sample_data_path",
+		"output_path",
+		"voxel size",
+		"orientation"
+		"atlas"
+		]
+	expected_types = [
+		Pathlike,
+    ]
+	for key, type in zip(expected_keys, expected_types):
+        assert key in config_dict.keys()
+
+
+def example_workflow():
+	input_config_path = Path(os.environ("BRAINGLOBE_REGISTRATION_CONFIG_PATH"))
+	if input_config_path.exists():
+		config = json.loads(input_config_path)
+	else:
+		config = _default_config()
+	input_data = read_from_config(config)
+	preprocessed_data = process(input_data) # if required
+	results = run_main_tool(prepocessed_data)
+	save(results)
+
+if __name__ == "__main__":
+	example_workflow()
+
+"""
+To run brainreg, you need to pass:
+    * The path to the sample data
+    * The path to the directory to save the results
+    * The voxel sizes
+    * The orientation
+    * The atlas to use
+
+We put this all together in a single command:
+
+brainreg test_brain brainreg_output -v 50 40 40  --orientation psl --atlas allen_mouse_50um
+"""
diff --git a/pyproject.toml b/pyproject.toml
index f55d6f89..ec5c3257 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,7 +1,7 @@
 [project]
-name = "brainglobe-scripts"
+name = "brainglobe-workflows"
 authors = [{name = "BrainGlobe developers", email= "a.felder@ucl.ac.uk"}]
-description = "A place to keep scripts to use as benchmarks, end-to-end tests and for tutorials"
+description = "A place to keep scripts to use as benchmarks, user-examples end-to-end tests and for tutorials"
 readme = "README.md"
 requires-python = ">=3.8.0"
 dynamic = ["version"]