Write per-TIFF quantification outputs instead of single merged file

imc quantify now processes each TIFF individually and writes output
files next to the input TIFF by default (e.g. *_quantification.h5ad).
The -o flag accepts an output directory to override the default location.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

Author: jkim810

imc/scripts/__init__.py

@@ -636,11 +636,12 @@ def find_h5ad() -> tp.Optional[Path]:
                 },
             },
             {
-                "args": ["--output"],
+                "args": ["-o", "--output"],
                 "kwargs": {
                     "dest": "output",
-                    "help": "Output file with quantification. "
-                    "Default is 'processed/quantification.csv'.",
+                    "type": Path,
+                    "help": "Output directory for quantification files. "
+                    "Default is to write next to each input TIFF.",
                 },
             },
             {

imc/scripts/quantify.py

@@ -14,6 +14,26 @@
 from imc.ops.quant import quantify_cells_rois
 from imc.scripts import build_cli, find_tiffs
 
+def _make_anndata(quant, morphology):
+    """Convert a quantification DataFrame to an AnnData object."""
+    v = len(str(quant["obj_id"].max()))
+    idx = quant["roi"] + "-" + quant["obj_id"].astype(str).str.zfill(v)
+    quant.index = idx
+
+    cols = [
+        "sample", "roi", "obj_id", "X_centroid", "Y_centroid", "layer",
+        "area", "perimeter", "minor_axis_length", "major_axis_length",
+        "eccentricity", "solidity"
+    ]
+    cols = [c for c in cols if c in quant.columns]
+    ann = anndata.AnnData(
+        quant.drop(cols, axis=1, errors="ignore").astype(float), obs=quant[cols]
+    )
+    if "X_centroid" in ann.obs.columns:
+        ann.obsm["spatial"] = ann.obs[["Y_centroid", "X_centroid"]].values
+    return ann
+
+
 def main(cli: tp.Sequence[str] = None) -> int:
     parser = build_cli("quantify")
     args = parser.parse_args(cli)
@@ -45,44 +65,39 @@ def main(cli: tp.Sequence[str] = None) -> int:
         error = f"Not all cell masks exist! Missing:\n\t- {m}"
         raise ValueError(error)
 
-    quant = quantify_cells_rois(
-        rois, args.layers.split(","), morphology=args.morphology
-    ).reset_index()
-
-    # reorder columns for nice effect
-    ext = ["roi", "obj_id"] + (["X_centroid", "Y_centroid"] if args.morphology else [])
-    rem = [x for x in quant.columns if x not in ext]
-    quant = quant[ext + rem]
-
-    if args.output is None:
-        f = Path("processed").mkdir() / "quantification.csv.gz"
-    else:
-        f = args.output
-    quant.to_csv(f, index=False)
-    print(f"Wrote CSV file to '{f.absolute()}'.")
-
-    if args.output_h5ad:
-        v = len(str(quant["obj_id"].max()))
-        idx = quant["roi"] + "-" + quant["obj_id"].astype(str).str.zfill(v)
-        quant.index = idx
-
-        # cols = ["sample", "roi", "obj_id", "X_centroid", "Y_centroid", "layer"]
-        cols = [
-            "sample", "roi", "obj_id", "X_centroid", "Y_centroid", "layer",
-            "area", "perimeter", "minor_axis_length", "major_axis_length",
-            "eccentricity", "solidity"
-        ]
-        cols = [c for c in cols if c in quant.columns]
-        ann = anndata.AnnData(
-            quant.drop(cols, axis=1, errors="ignore").astype(float), obs=quant[cols]
-        )
-        if "X_centroid" in ann.obs.columns:
-            ann.obsm["spatial"] = ann.obs[["Y_centroid", "X_centroid"]].values
-        f = f.replace_(".csv.gz", ".h5ad")
-        ann.write(f)
-        print(f"Wrote h5ad file to '{f.absolute()}'.")
-        ann2 = anndata.read_h5ad(f)
-        assert np.allclose(ann.X, ann2.X)
+    # Process each TIFF individually so each gets its own output file
+    for tiff, roi in zip(args.tiffs, rois):
+        print(f"Quantifying '{roi.name}'...")
+        quant = quantify_cells_rois(
+            [roi], args.layers.split(","), morphology=args.morphology
+        ).reset_index()
+
+        # reorder columns for nice effect
+        ext = ["roi", "obj_id"] + (["X_centroid", "Y_centroid"] if args.morphology else [])
+        rem = [x for x in quant.columns if x not in ext]
+        quant = quant[ext + rem]
+
+        # Determine output path
+        if args.output is not None:
+            # -o flag: use as output directory, write <roi_name>_quantification files there
+            out_dir = Path(args.output).mkdir()
+            stem = tiff.stem.replace("_full", "")
+            csv_path = out_dir / f"{stem}_quantification.csv.gz"
+        else:
+            # Default: write next to the input TIFF
+            stem = tiff.stem.replace("_full", "")
+            csv_path = tiff.parent / f"{stem}_quantification.csv.gz"
+
+        quant.to_csv(csv_path, index=False)
+        print(f"Wrote CSV file to '{csv_path.absolute()}'.")
+
+        if args.output_h5ad:
+            ann = _make_anndata(quant, args.morphology)
+            h5ad_path = csv_path.replace_(".csv.gz", ".h5ad")
+            ann.write(h5ad_path)
+            print(f"Wrote h5ad file to '{h5ad_path.absolute()}'.")
+            ann2 = anndata.read_h5ad(h5ad_path)
+            assert np.allclose(ann.X, ann2.X)
 
     print("Finished quantification step.")
     return 0