#233 Merge pull request from deshima-dev/astropenguin/issue232

Remove deprecated data type (numpy.float_)

Author: astropenguin

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: 2025.4.0
+version: 2025.4.1
 date-released: 2025-04-17
 license: "MIT"
 doi: "10.5281/zenodo.3384216"

README.md

@@ -11,7 +11,7 @@ DESHIMA code for data analysis
 ## Installation
 
 ```shell
-pip install decode==2025.4.0
+pip install decode==2025.4.1
 ```
 
 ## Quick look

decode/__init__.py

@@ -10,7 +10,7 @@
     "select",
     "utils",
 ]
-__version__ = "2025.4.0"
+__version__ = "2025.4.1"
 
 
 # submodules

decode/fit.py

@@ -19,7 +19,7 @@ def baseline(
     *,
     order: int = 0,
     model: str = "LinearRegression",
-    weight: Optional[Union[NDArray[np.float_], float]] = None,
+    weight: Optional[Union[NDArray[np.float64], float]] = None,
     **options: Any,
 ) -> xr.DataArray:
     """Fit baseline by polynomial and atmospheric models.
@@ -67,7 +67,7 @@ def baseline(
     else:
         model.fit(X, y)  # type: ignore
 
-    coeff: NDArray[np.float_] = model.coef_  # type: ignore
+    coeff: NDArray[np.float64] = model.coef_  # type: ignore
 
     # create baseline
     baseline = xr.zeros_like(dems)
@@ -80,7 +80,7 @@ def baseline(
     return baseline
 
 
-def dtau_dpwv(freq: NDArray[np.float_]) -> xr.DataArray:
+def dtau_dpwv(freq: NDArray[np.float64]) -> xr.DataArray:
     """Calculate dtau/dpwv as a function of frequency.
 
     Args:

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "decode"
-version = "2025.4.0"
+version = "2025.4.1"
 description = "DESHIMA code for data analysis"
 authors = [
     "Akio Taniguchi <taniguchi.akio@gmail.com>",

tests/test_assign.py

@@ -8,7 +8,7 @@
 
 # constants
 DEMS_DIR = Path(__file__).parents[1] / "data" / "dems"
-DEMS = load.dems(DEMS_DIR / "dems_20171111110002.nc.gz")
+DEMS = load.dems(DEMS_DIR / "dems_20171111110002.nc.gz").compute()
 
 
 def test_assign_scan() -> None: