chore: remove quite unnecessary constants.py

cinrad/calc.py

@@ -7,7 +7,7 @@
 from functools import wraps
 
 import numpy as np
-from xarray import DataArray, Dataset, merge
+from xarray import DataArray, Dataset
 
 try:
     from pykdtree.kdtree import KDTree
@@ -17,7 +17,6 @@
 from cinrad.utils import *
 from cinrad.grid import grid_2d, resample
 from cinrad.projection import height, get_coordinate
-from cinrad.constants import deg2rad
 from cinrad.error import RadarCalculationError
 from cinrad._typing import Volume_T
 from cinrad.common import get_dtype
@@ -364,12 +363,13 @@ def get_section(
             stlon = self.rl[0].site_longitude
             stp = np.round(
                 get_coordinate(
-                    start_polar[0], start_polar[1] * deg2rad, 0, stlon, stlat
+                    start_polar[0], np.deg2rad(start_polar[1]), 0, stlon, stlat
                 ),
                 2,
             )
             enp = np.round(
-                get_coordinate(end_polar[0], end_polar[1] * deg2rad, 0, stlon, stlat), 2
+                get_coordinate(end_polar[0], np.deg2rad(end_polar[1]), 0, stlon, stlat),
+                2,
             )
         elif start_cart and end_cart:
             stp = start_cart

cinrad/grid.py

@@ -10,7 +10,6 @@
 except ImportError:
     from scipy.spatial import KDTree
 
-from cinrad.constants import deg2rad
 from cinrad._typing import Number_T
 
 
@@ -61,7 +60,7 @@ def resample(
     """
     # Target grid
     Rrange = np.arange(d_reso, distance.max() + d_reso, d_reso)
-    Trange = np.linspace(0, 360, a_reso + 1) * deg2rad
+    Trange = np.linspace(0, np.pi * 2, a_reso + 1)
     dist, theta = np.meshgrid(Rrange, Trange)
     # Original grid
     d, t = np.meshgrid(distance, azimuth)

cinrad/hca.py

@@ -6,7 +6,7 @@
 
 import numpy as np
 
-from cinrad.constants import MODULE_DIR
+from cinrad.utils import MODULE_DIR
 from cinrad._typing import Boardcast_T
 
 PARAMS = np.load(os.path.join(MODULE_DIR, "data", "hca_params.npy"))

cinrad/io/base.py

@@ -10,7 +10,7 @@
 
 import numpy as np
 
-from cinrad.constants import MODULE_DIR
+from cinrad.utils import MODULE_DIR
 from cinrad._typing import Number_T
 
 with open(os.path.join(MODULE_DIR, "data", "radar_station.json"), "r") as buf:

cinrad/io/level2.py

@@ -10,7 +10,6 @@
 import numpy as np
 import xarray as xr
 
-from cinrad.constants import deg2rad, con
 from cinrad.projection import get_coordinate, height
 from cinrad.error import RadarDecodeError
 from cinrad.io.base import RadarBase, prepare_file
@@ -162,6 +161,7 @@ def __init__(
         f.close()
 
     def _SAB_reader(self, f: Any, dtype: str = "SAB"):
+        ANGLE_CONVERSION = (180 / 4096) * 0.125
         _header_size = 128
         if dtype == "SAB":
             radar_dtype = SAB_dtype
@@ -181,8 +181,8 @@ def _SAB_reader(self, f: Any, dtype: str = "SAB"):
         self.Rreso = data["gate_length_r"][0] / 1000
         self.Vreso = data["gate_length_v"][0] / 1000
         boundary = np.where(data["radial_num"] == 1)[0]
-        self.el = data["elevation"][boundary] * con
-        self.azimuth = data["azimuth"] * con * deg2rad
+        self.el = data["elevation"][boundary] * ANGLE_CONVERSION
+        self.azimuth = np.deg2rad(data["azimuth"] * ANGLE_CONVERSION)
         dv = data["v_reso"][0]
         self.nyquist_v = data["nyquist_vel"][boundary] / 100
         self.task_name = "VCP{}".format(data["vcp_mode"][0])
@@ -360,7 +360,7 @@ def _CC2_reader(self, f: Any):
             other_info = np.frombuffer(f.read(CC2_other.itemsize), CC2_other)
             self.task_name = other_info["sScanName"][0].decode()
             data_block = np.frombuffer(f.read(), CC2_data)
-            raw_azimuth = data_block["usAzimuth"] / 100 * deg2rad
+            raw_azimuth = np.deg2rad(data_block["usAzimuth"] / 100)
             raw_dbz = np.ma.masked_equal(data_block["ucCorZ"].astype(int), 0)
             dbz = (raw_dbz - 64) / 2
             zdr = np.ma.masked_equal(data_block["siZDR"].astype(int), -32768) * 0.01
@@ -402,20 +402,20 @@ def get_azimuth_angles(self, scans: Optional[int] = None) -> np.ndarray:
                 return self.data[scans]["azimuth"]
         elif self.radartype == "CC":
             if scans is None:
-                return (
-                    np.array(np.linspace(0, 360, 512).tolist() * self.get_nscans())
-                    * deg2rad
+                return np.array(
+                    np.linspace(0, np.pi * 2, 512).tolist() * self.get_nscans()
                 )
+
             else:
-                return np.array(np.linspace(0, 360, 512).tolist()) * deg2rad
+                return np.linspace(0, np.pi * 2, 512)
         elif self.radartype in ["SC", "CD"]:
             if scans is None:
-                return (
-                    np.array(np.linspace(0, 360, 360).tolist() * self.get_nscans())
-                    * deg2rad
+                return np.array(
+                    np.linspace(0, np.pi * 2, 360).tolist() * self.get_nscans()
                 )
+
             else:
-                return np.array(np.linspace(0, 360, 360).tolist()) * deg2rad
+                return np.linspace(0, np.pi * 2, 360)
 
     def get_elevation_angles(
         self, scans: Optional[int] = None
@@ -871,7 +871,7 @@ def get_data(self, tilt: int, drange: Number_T, dtype: str) -> xr.Dataset:
             start_lon = self.stationlon
             start_lat = self.stationlat
             end_lon, end_lat = get_coordinate(
-                self.drange, azimuth * deg2rad, 0, self.stationlon, self.stationlat
+                self.drange, np.deg2rad(azimuth), 0, self.stationlon, self.stationlat
             )
             ds = xr.Dataset(
                 {dtype: da},
@@ -897,7 +897,7 @@ def get_data(self, tilt: int, drange: Number_T, dtype: str) -> xr.Dataset:
 
     def projection(self, reso: float) -> tuple:
         r = self.get_range(self.drange, reso)
-        theta = np.array(self.aux[self.tilt]["azimuth"]) * deg2rad
+        theta = np.deg2rad(self.aux[self.tilt]["azimuth"])
         lonx, latx = get_coordinate(
             r, theta, self.elev, self.stationlon, self.stationlat
         )

cinrad/io/level3.py

@@ -12,7 +12,6 @@
 from xarray import Dataset, DataArray
 
 from cinrad.projection import get_coordinate, height
-from cinrad.constants import deg2rad
 from cinrad._typing import Boardcast_T
 from cinrad.io.base import RadarBase, prepare_file, _get_radar_info
 from cinrad.io._dtype import *
@@ -89,7 +88,7 @@ def __init__(self, file: Any):
             az = np.linspace(0, 360, data.shape[0])
             az += start_az
             az[az > 360] -= 360
-            self.az = az * deg2rad
+            self.az = np.deg2rad(az)
             self.reso = self.max_range / data.shape[1]
             self.rng = np.arange(self.reso, self.max_range + self.reso, self.reso)
         else:
@@ -324,7 +323,7 @@ def current(self, storm_id: str) -> tuple:
         curpos = self.info[storm_id]["current storm position"]
         dist, az = xy2polar(*curpos)
         lonlat = get_coordinate(
-            dist, az * deg2rad, 0, self.handler.lon, self.handler.lat, h_offset=False
+            dist, np.deg2rad(az), 0, self.handler.lon, self.handler.lat, h_offset=False
         )
         return lonlat
 
@@ -348,7 +347,7 @@ def track(self, storm_id: str, tracktype: str) -> Optional[tuple]:
         for dis, azi in zip(pol_pos[0], pol_pos[1]):
             pos_tup = get_coordinate(
                 dis,
-                azi * deg2rad,
+                np.deg2rad(azi),
                 0,
                 self.handler.lon,
                 self.handler.lat,
@@ -394,7 +393,7 @@ def get_hail_param(self, storm_id: str) -> dict:
         xy = out.get("current storm position")
         dist, az = xy2polar(*xy)
         lonlat = get_coordinate(
-            dist, az * deg2rad, 0, self.handler.lon, self.handler.lat, h_offset=False
+            dist, np.deg2rad(az), 0, self.handler.lon, self.handler.lat, h_offset=False
         )
         out["position"] = tuple(lonlat)
         return out
@@ -568,7 +567,7 @@ def _parse_radial_fmt(self):
         az = np.linspace(0, 360, raw.shape[0])
         az += azi[0]
         az[az > 360] -= 360
-        azi = az * deg2rad
+        azi = np.deg2rad(az)
         # self.azi = np.deg2rad(azi)
         dist = np.arange(start_range // reso + 1, end_range // reso + 1, 1) * reso
         lon, lat = get_coordinate(
@@ -618,7 +617,7 @@ def _parse_raster_fmt(self):
         max_range = int(nx / 2 * reso)
         y = np.linspace(max_range, max_range * -1, ny) / 111 + self.stationlat
         x = (
-            np.linspace(max_range * -1, max_range, nx) / (111 * np.cos(y * deg2rad))
+            np.linspace(max_range * -1, max_range, nx) / (111 * np.cos(np.deg2rad(y)))
             + self.stationlon
         )
         lon, lat = np.meshgrid(x, y)
@@ -676,7 +675,7 @@ def _parse_cappi_fmt(self):
                 az = np.linspace(0, 360, raw.shape[0])
                 az += azi0[0]
                 az[az > 360] -= 360
-                azi = az * deg2rad
+                azi = np.deg2rad(az)
                 dist = np.arange(start_range + reso, end_range + reso, reso)
         raw = np.vstack(data).astype(int)
         raw = np.ma.masked_less(raw, 5)
@@ -760,7 +759,7 @@ def _parse_swp_fmt(self):
         swp_percent = DataArray(swp["swp"])
         lon, lat = get_coordinate(
             swp_range / 1000,
-            swp_azimuth * deg2rad,
+            np.deg2rad(swp_azimuth),
             self.params["elevation"],
             self.stationlon,
             self.stationlat,
@@ -794,7 +793,7 @@ def _parse_hail_fmt(self):
         hail_severe_possibility = DataArray(hail_table["hail_severe_possibility"])
         lon, lat = get_coordinate(
             hail_range / 1000,
-            hail_azimuth * deg2rad,
+            np.deg2rad(hail_azimuth),
             self.params["elevation"],
             self.stationlon,
             self.stationlat,
@@ -832,7 +831,7 @@ def _parse_meso_fmt(self):
         meso_range = np.array(meso_table["meso_range"])[:, np.newaxis]
         lon, lat = get_coordinate(
             meso_range / 1000,
-            meso_azimuth * deg2rad,
+            np.deg2rad(meso_azimuth),
             self.params["elevation"],
             self.stationlon,
             self.stationlat,
@@ -871,7 +870,7 @@ def _parse_tvs_fmt(self):
         tvs_range = np.array(tvs_table["tvs_range"])[:, np.newaxis]
         lon, lat = get_coordinate(
             tvs_range / 1000,
-            tvs_azimuth * deg2rad,
+            np.deg2rad(tvs_azimuth),
             self.params["elevation"],
             self.stationlon,
             self.stationlat,
@@ -910,7 +909,7 @@ def _parse_sti_fmt(self):
         curr_direction = sti_current["direction"]
         curr_lon, curr_lat = get_coordinate(
             curr_range / 1000,
-            curr_azimuth * deg2rad,
+            np.deg2rad(curr_azimuth),
             self.params["elevation"],
             self.stationlon,
             self.stationlat,
@@ -929,7 +928,7 @@ def _parse_sti_fmt(self):
             fore_range = np.array(forecast_positon["range"])[:, np.newaxis]
             fore_lon, fore_lat = get_coordinate(
                 fore_range / 1000,
-                fore_azimuth * deg2rad,
+                np.deg2rad(fore_azimuth),
                 self.params["elevation"],
                 self.stationlon,
                 self.stationlat,
@@ -948,7 +947,7 @@ def _parse_sti_fmt(self):
             his_range = np.array(history_positon["range"])[:, np.newaxis]
             his_lon, his_lat = get_coordinate(
                 his_range / 1000,
-                his_azimuth * deg2rad,
+                np.deg2rad(his_azimuth),
                 self.params["elevation"],
                 self.stationlon,
                 self.stationlat,
@@ -1009,7 +1008,7 @@ def _parse_uam_fmt(self):
         uam_deg = DataArray(uam_table["deg"])
         lon, lat = get_coordinate(
             uam_range / 1000,
-            uam_azimuth * deg2rad,
+            np.deg2rad(uam_azimuth),
             self.params["elevation"],
             self.stationlon,
             self.stationlat,

cinrad/projection.py

@@ -4,9 +4,10 @@
 
 import numpy as np
 
-from cinrad.constants import deg2rad, rm
 from cinrad._typing import Boardcast_T, Number_T
 
+RM = 8500
+
 
 def height(
     distance: Boardcast_T, elevation: Union[int, float], radarheight: Number_T
@@ -27,9 +28,10 @@ def height(
     -------
     height
     """
+
     return (
-        distance * np.sin(elevation * deg2rad)
-        + distance**2 / (2 * rm)
+        distance * np.sin(np.deg2rad(elevation))
+        + distance**2 / (2 * RM)
         + radarheight / 1000
     )
 
@@ -67,13 +69,13 @@ def get_coordinate(
     """
     elev = elevation if h_offset else 0
     if isinstance(azimuth, np.ndarray):
-        deltav = np.cos(azimuth[:, np.newaxis]) * distance * np.cos(elev * deg2rad)
-        deltah = np.sin(azimuth[:, np.newaxis]) * distance * np.cos(elev * deg2rad)
+        deltav = np.cos(azimuth[:, np.newaxis]) * distance * np.cos(np.deg2rad(elev))
+        deltah = np.sin(azimuth[:, np.newaxis]) * distance * np.cos(np.deg2rad(elev))
     else:
-        deltav = np.cos(azimuth) * distance * np.cos(elev * deg2rad)
-        deltah = np.sin(azimuth) * distance * np.cos(elev * deg2rad)
+        deltav = np.cos(azimuth) * distance * np.cos(np.deg2rad(elev))
+        deltah = np.sin(azimuth) * distance * np.cos(np.deg2rad(elev))
     deltalat = deltav / 111
     actuallat = deltalat + centerlat
-    deltalon = deltah / (111 * np.cos(actuallat * deg2rad))
+    deltalon = deltah / (111 * np.cos(np.deg2rad(actuallat)))
     actuallon = deltalon + centerlon
     return actuallon, actuallat