From d006204850058fc6a9b47b9168e9f020c18bc956 Mon Sep 17 00:00:00 2001
From: jhennies <julianhennies@hotmail.de>
Date: Fri, 13 Feb 2026 14:22:55 +0100
Subject: [PATCH] example for creating mobie collection table

---
 .../code/create_mobie_collection_table.py     | 108 ++++++++++++++++++
 tutorials/mobie_collection_table.md           |   5 +
 2 files changed, 113 insertions(+)
 create mode 100644 tutorials/code/create_mobie_collection_table.py

diff --git a/tutorials/code/create_mobie_collection_table.py b/tutorials/code/create_mobie_collection_table.py
new file mode 100644
index 0000000..a348f2b
--- /dev/null
+++ b/tutorials/code/create_mobie_collection_table.py
@@ -0,0 +1,108 @@
+import os
+import pandas as pd
+
+
+def normalize_mobie_table_entry_dict(entries, use_abs_path=False, table_filepath=None):
+
+    def _normalize_uri(uri):
+        if use_abs_path:
+            uri = os.path.abspath(uri)
+        else:
+            assert table_filepath is not None
+            uri = os.path.relpath(uri, os.path.split(table_filepath)[0])
+        return uri
+
+    def _normalize_affine(affine):
+        return ','.join([str(x) for x in affine])
+
+    def _normalize_exclusive(exclusive):
+        if type(exclusive) is not str:
+            return 'true' if exclusive else 'false'
+        return exclusive
+
+    def _normalize_contrast_limits(contrast_limits):
+        return ','.join(f'{x:.1f}' if isinstance(x, int) or x == int(x) else str(x) for x in contrast_limits)
+
+    # Let's make sure everything is a list!
+    for k, v in entries.items():
+        assert type(v) == list, 'Entries have to be given as as list even if only one element is added!'
+
+    # First pass to determine the number of entries or check that the length of the arrays matches the given entry count
+    entry_count = max([len(v) for _, v in entries.items()])
+
+    for k, v in entries.items():
+
+        assert len(v) == entry_count or len(v) == 1, 'The number of elements in an entry must match the entry count or be of len = 1'
+        if len(v) == 1:
+            entries[k] = v * entry_count
+
+    # Now we can make sure that everything is properly readable by MoBIE
+    for k, v in entries.items():
+
+        for idx, item in enumerate(v):
+            if k == 'uri':
+                v[idx] = _normalize_uri(item)
+            elif k == 'name':
+                pass
+            elif k == 'type':
+                pass
+            elif k == 'view':
+                pass
+            elif k == 'group':
+                pass
+            elif k == 'affine':
+                v[idx] = _normalize_affine(item)
+            elif k == 'blend':
+                pass
+            elif k == 'exclusive':
+                v[idx] = _normalize_exclusive(item)
+            elif k == 'contrast_limits':
+                v[idx] = _normalize_contrast_limits(item)
+            else:
+                pass
+
+        entries[k] = v
+
+    return entries
+
+
+# Inputs are automatically obtained from microscope project metadata
+map_filepaths = ['path/to/image1.tif', 'path/to/image2.tif']
+affine_transforms = [[1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0], [1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0]]  # Scaling is done from image meta data and not from here!
+names = ['Image1', 'Image1']
+contrast_limits = [[10, 230], [50, 255]]
+view_name = 'View1'
+group_name = 'Group1'
+
+# Set up a dictionary that contains all entries
+entries=dict(
+    uri=map_filepaths,
+    type=['intensities'],
+    view=[view_name],
+    group=[group_name],
+    affine=affine_transforms,
+    name=names,
+    blend=['alpha'],
+    exclusive=[True],
+    contrast_limits=contrast_limits
+)
+
+# Translate the dictionary entries into a MoBIE-readable format, e.g. concatenating the affine transform to a single string
+entries = normalize_mobie_table_entry_dict(entries, use_abs_path=True)
+
+# Where to save the resulting table
+table_filepath = 'test_mobie_table.tsv'
+
+# Create the table
+new_table_data = pd.DataFrame(entries)
+new_table_data.to_csv(table_filepath, index=False, sep='\t')
+
+# # Append the table (Use this instead of the above if you need to add to an existing table)
+# table_data = pd.DataFrame()
+# if os.path.exists(table_filepath):
+#     table_data = pd.read_csv(table_filepath, sep='\t')
+# new_table_data = pd.concat([table_data, pd.DataFrame(entries)], ignore_index=True, sort=False)
+# new_table_data = new_table_data.fillna('')
+# new_table_data.to_csv(table_filepath, index=False, sep='\t')
+
+
diff --git a/tutorials/mobie_collection_table.md b/tutorials/mobie_collection_table.md
index 13a17a1..1d9e67d 100644
--- a/tutorials/mobie_collection_table.md
+++ b/tutorials/mobie_collection_table.md
@@ -148,6 +148,11 @@ Here are some Google Sheet collection tables that are pointing to remotely hoste
     - Practically, you can "remove" a column by giving it a name that MoBIE does not recognise, e.g. renaming `affine` (recognised) to `x_affine` (not recognised).
 - For local image data, you can use `Plugins > MoBIE > Create > Create MoBIE Collection Table...` to get started and then modify or add columns
 
+#### Setting up a collection table using python
+
+[Here](code/create_mobie_collection_table.py) is a simple example of how to create a MoBIE collection table using pandas in python. 
+The example is intended as an inspiration and does not cover every situation. Feel free to copy and adjust to your needs!
+
 ### Quick start
 
 Make sure to have [MoBIE installed on your computer](installation.md).