#117 Merge pull request from deshima-dev/astropenguin/issue116

Update make module

CITATION.cff

@@ -3,8 +3,8 @@ message: "If you use this software, please cite it as below."
 
 title: "de:code"
 abstract: "DESHIMA code for data analysis"
-version: 2.5.2
-date-released: 2023-11-06
+version: 2.5.3
+date-released: 2023-11-07
 license: "MIT"
 doi: "10.5281/zenodo.3384216"
 url: "https://github.com/deshima-dev/decode"

README.md

@@ -11,5 +11,5 @@ DESHIMA code for data analysis
 ## Installation
 
 ```shell
-pip install decode==2.5.2
+pip install decode==2.5.3
 ```

decode/__init__.py

@@ -8,7 +8,7 @@
     "plot",
     "select",
 ]
-__version__ = "2.5.2"
+__version__ = "2.5.3"
 
 
 # submodules

decode/make.py

@@ -9,57 +9,105 @@
 # dependencies
 import numpy as np
 import xarray as xr
-from astropy.units import Quantity
-from xarray_dataclasses import AsDataArray, Coord, Data
+from astropy.units import Quantity, Unit
+from xarray_dataclasses import AsDataArray, Attr, Coordof, Data
+from . import convert
 
 
 # type hints
-Angle = Union[Quantity, str]
-Chan = Literal["chan"]
-Lat = Literal["lat"]
-Lon = Literal["lon"]
-_ = Tuple[()]
+QuantityLike = Union[Quantity, str]
+UnitLike = Union[Unit, str]
+Ln = Literal["lon"]
+Lt = Literal["lat"]
+Ch = Literal["chan"]
+
+
+@dataclass
+class Weight:
+    data: Data[Tuple[Ln, Lt, Ch], float]
+    long_name: Attr[str] = "Data weights"
+
+
+@dataclass
+class Lon:
+    data: Data[Ln, float]
+    long_name: Attr[str] = "Sky longitude"
+    units: Attr[str] = "deg"
+
+
+@dataclass
+class Lat:
+    data: Data[Lt, float]
+    long_name: Attr[str] = "Sky latitude"
+    units: Attr[str] = "deg"
+
+
+@dataclass
+class Chan:
+    data: Data[Ch, int]
+    long_name: Attr[str] = "Channel ID"
+
+
+@dataclass
+class Frame:
+    data: Data[Tuple[()], str]
+    long_name: Attr[str] = "Sky coordinate frame"
+
+
+@dataclass
+class D2MkidID:
+    data: Data[Ch, int]
+    long_name: Attr[str] = "[DESHIMA 2.0] MKID ID"
+
+
+@dataclass
+class D2MkidType:
+    data: Data[Ch, str]
+    long_name: Attr[str] = "[DESHIMA 2.0] MKID type"
+
+
+@dataclass
+class D2MkidFrequency:
+    data: Data[Ch, float]
+    long_name: Attr[str] = "[DESHIMA 2.0] MKID center frequency"
+    units: Attr[str] = "Hz"
 
 
 @dataclass
 class Cube(AsDataArray):
     """Cube of DESHIMA 2.0."""
 
-    data: Data[Tuple[Lon, Lat, Chan], Any]
-    lon: Coord[Lon, float] = 0.0
-    lat: Coord[Lat, float] = 0.0
-    frame: Coord[_, str] = "altaz"
-    d2_mkid_frequency: Coord[Chan, float] = 0.0
-    d2_mkid_id: Coord[Chan, int] = 0
-    d2_mkid_type: Coord[Chan, str] = ""
+    data: Data[Tuple[Ln, Lt, Ch], Any]
+    weight: Coordof[Weight] = 1.0
+    lon: Coordof[Lon] = 0.0
+    lat: Coordof[Lat] = 0.0
+    chan: Coordof[Chan] = 0
+    frame: Coordof[Frame] = "altaz"
+    d2_mkid_frequency: Coordof[D2MkidFrequency] = 0.0
+    d2_mkid_id: Coordof[D2MkidID] = 0.0
+    d2_mkid_type: Coordof[D2MkidType] = ""
 
 
 def cube(
     dems: xr.DataArray,
     /,
     *,
-    gridsize_lon: Angle = "3 arcsec",
-    gridsize_lat: Angle = "3 arcsec",
+    skycoord_grid: QuantityLike = "6 arcsec",
+    skycoord_units: UnitLike = "arcsec",
 ) -> xr.DataArray:
     """Make a cube from DEMS.
 
     Args:
-        dems: Input DEMS DataArray.
-        gridsize_lon: Grid size of the longitude axis.
-        gridsize_lat: Grid size of the latitude axis.
+        dems: Input DEMS DataArray to be converted.
+        skycoord_grid: Grid size of the sky coordinate axes.
+        skycoord_units: Units of the sky coordinate axes.
 
     Returns:
         Cube DataArray.
 
     """
-    dems = dems.copy()
-    cos = np.cos(np.deg2rad(dems["lat"]))
-    dems["lon"] -= dems["lon_origin"]
-    dems["lat"] -= dems["lat_origin"]
-    dems["lon"] *= cos
-
-    dlon = Quantity(gridsize_lon).to("deg").value
-    dlat = Quantity(gridsize_lat).to("deg").value
+    dlon = Quantity(skycoord_grid).to(dems.lon.attrs["units"]).values
+    dlat = Quantity(skycoord_grid).to(dems.lat.attrs["units"]).values
     lon_min = np.floor(dems.lon.min() / dlon) * dlon
     lon_max = np.ceil(dems.lon.max() / dlon) * dlon
     lat_min = np.floor(dems.lat.min() / dlat) * dlat
@@ -73,15 +121,15 @@ def cube(
     j = np.abs(dems.lat - lat).argmin("grid")
     index = (i + n_lon * j).compute()
 
-    dems = dems.copy()
+    dems = dems.copy(data=dems.data)
     dems.coords.update({"index": index})
     grid = dems.groupby("index").mean("time")
 
     temp = np.full([n_lat * n_lon, n_chan], np.nan)
     temp[grid.index.values] = grid.values
     data = temp.reshape((n_lat, n_lon, n_chan)).swapaxes(0, 1)
 
-    return Cube.new(
+    cube = Cube.new(
         data=data,
         lon=lon.values,
         lat=lat.values,
@@ -90,3 +138,6 @@ def cube(
         d2_mkid_frequency=dems.d2_mkid_frequency.values,
         d2_mkid_type=dems.d2_mkid_type.values,
     )
+    cube = convert.units(cube, "lon", skycoord_units)
+    cube = convert.units(cube, "lat", skycoord_units)
+    return cube

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "decode"
-version = "2.5.2"
+version = "2.5.3"
 description = "DESHIMA code for data analysis"
 authors = ["Akio Taniguchi <taniguchi@a.phys.nagoya-u.ac.jp>"]
 keywords = [