diff --git a/CITATION.cff b/CITATION.cff
index 3d24c7b..0f817e8 100644
--- a/CITATION.cff
+++ b/CITATION.cff
@@ -3,7 +3,7 @@ message: "If you use this software, please cite it as below."
 
 title: "de:code"
 abstract: "DESHIMA code for data analysis"
-version: 2.9.0
+version: 2.9.1
 date-released: 2023-11-25
 license: "MIT"
 doi: "10.5281/zenodo.3384216"
diff --git a/README.md b/README.md
index fc2b423..6b561b2 100644
--- a/README.md
+++ b/README.md
@@ -11,5 +11,5 @@ DESHIMA code for data analysis
 ## Installation
 
 ```shell
-pip install decode==2.9.0
+pip install decode==2.9.1
 ```
diff --git a/decode/__init__.py b/decode/__init__.py
index 3277d48..e4f640e 100644
--- a/decode/__init__.py
+++ b/decode/__init__.py
@@ -10,7 +10,7 @@
     "select",
     "utils",
 ]
-__version__ = "2.9.0"
+__version__ = "2.9.1"
 
 
 # submodules
diff --git a/decode/qlook.py b/decode/qlook.py
index e5cec6c..53649f2 100644
--- a/decode/qlook.py
+++ b/decode/qlook.py
@@ -162,7 +162,7 @@ def raster(
     da_sub = da_on - da_base.values
 
     # make continuum series
-    weight = calc_chan_weight(da_off, method=chan_weight, pwv=pwv)
+    weight = get_chan_weight(da_off, method=chan_weight, pwv=pwv)
     series = da_sub.weighted(weight.fillna(0)).mean("chan")
 
     # make continuum map
@@ -174,7 +174,7 @@ def raster(
     cont = cube.weighted(weight.fillna(0)).mean("chan")
 
     # save result
-    filename = Path(dems).with_suffix(f".pswsc.{format}").name
+    filename = Path(dems).with_suffix(f".raster.{format}").name
 
     if format in DATA_FORMATS:
         return save_qlook(cont, Path(outdir) / filename)
@@ -251,7 +251,7 @@ def skydip(
     # make continuum series
     da_on = select.by(da, "state", include="SCAN")
     da_off = select.by(da, "state", exclude="SCAN")
-    weight = calc_chan_weight(da_off, method=chan_weight, pwv=pwv)
+    weight = get_chan_weight(da_off, method=chan_weight, pwv=pwv)
     series = da_on.weighted(weight.fillna(0)).mean("chan")
 
     # save result
@@ -321,7 +321,7 @@ def still(
 
     # make continuum series
     da_off = select.by(da, "state", exclude=["ON", "SCAN"])
-    weight = calc_chan_weight(da_off, method=chan_weight, pwv=pwv)
+    weight = get_chan_weight(da_off, method=chan_weight, pwv=pwv)
     series = da.weighted(weight.fillna(0)).mean("chan")
 
     # save result
@@ -392,10 +392,10 @@ def zscan(
     # make continuum series
     da_on = select.by(da, "state", include="ON")
     da_off = select.by(da, "state", exclude="ON")
-    weight = calc_chan_weight(da_off, method=chan_weight, pwv=pwv)
+    weight = get_chan_weight(da_off, method=chan_weight, pwv=pwv)
     series = da_on.weighted(weight.fillna(0)).mean("chan")
 
-    # save output
+    # save result
     filename = Path(dems).with_suffix(f".zscan.{format}").name
 
     if format in DATA_FORMATS:
@@ -417,7 +417,31 @@ def zscan(
     return save_qlook(fig, Path(outdir) / filename)
 
 
-def calc_chan_weight(
+def mean_in_time(dems: xr.DataArray) -> xr.DataArray:
+    """Similar to DataArray.mean but keeps middle time."""
+    middle = dems[len(dems) // 2 : len(dems) // 2 + 1]
+    return xr.zeros_like(middle) + dems.mean("time")
+
+
+def subtract_per_scan(dems: xr.DataArray) -> xr.DataArray:
+    """Apply source-sky subtraction to a single-scan DEMS."""
+    if len(states := np.unique(dems.state)) != 1:
+        raise ValueError("State must be unique.")
+
+    if (state := states[0]) == "ON":
+        src = select.by(dems, "beam", include="A")
+        sky = select.by(dems, "beam", include="B")
+        return src.mean("time") - sky.mean("time").data
+
+    if state == "OFF":
+        src = select.by(dems, "beam", include="B")
+        sky = select.by(dems, "beam", include="A")
+        return src.mean("time") - sky.mean("time").data
+
+    raise ValueError("State must be either ON or OFF.")
+
+
+def get_chan_weight(
     dems: xr.DataArray,
     /,
     *,
@@ -459,30 +483,6 @@ def calc_chan_weight(
     raise ValueError("Method must be either uniform, std, or std/tx.")
 
 
-def mean_in_time(dems: xr.DataArray) -> xr.DataArray:
-    """Similar to DataArray.mean but keeps middle time."""
-    middle = dems[len(dems) // 2 : len(dems) // 2 + 1]
-    return xr.zeros_like(middle) + dems.mean("time")
-
-
-def subtract_per_scan(dems: xr.DataArray) -> xr.DataArray:
-    """Apply source-sky subtraction to a single-scan DEMS."""
-    if len(states := np.unique(dems.state)) != 1:
-        raise ValueError("State must be unique.")
-
-    if (state := states[0]) == "ON":
-        src = select.by(dems, "beam", include="A")
-        sky = select.by(dems, "beam", include="B")
-        return src.mean("time") - sky.mean("time").data
-
-    if state == "OFF":
-        src = select.by(dems, "beam", include="B")
-        sky = select.by(dems, "beam", include="A")
-        return src.mean("time") - sky.mean("time").data
-
-    raise ValueError("State must be either ON or OFF.")
-
-
 def get_robust_lim(da: xr.DataArray) -> tuple[float, float]:
     """Calculate a robust limit for plotting."""
     sigma = SIGMA_OVER_MAD * utils.mad(da)
diff --git a/pyproject.toml b/pyproject.toml
index edde958..360c19a 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "decode"
-version = "2.9.0"
+version = "2.9.1"
 description = "DESHIMA code for data analysis"
 authors = ["Akio Taniguchi <taniguchi@a.phys.nagoya-u.ac.jp>"]
 keywords = [