refactor: implicit import of arguments

tsutterley · Jan 11, 2024 · c1b7c7e · c1b7c7e
1 parent 964a887
commit c1b7c7e
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Showing 3 changed files with 22 additions and 17 deletions.
diff --git a/doc/source/api_reference/arguments.rst b/doc/source/api_reference/arguments.rst
@@ -11,18 +11,18 @@ Calling Sequence
 .. code-block:: python
 
     import pyTMD.arguments
-    pu,pf,G = pyTMD.arguments(MJD, constituents,
+    pu,pf,G = pyTMD.arguments.arguments(MJD, constituents,
         deltat=DELTAT, corrections=CORRECTIONS)
 
 `Source code`__
 
 .. __: https://github.com/tsutterley/pyTMD/blob/main/pyTMD/arguments.py
 
-.. autofunction:: pyTMD.arguments
+.. autofunction:: pyTMD.arguments.arguments
 
-.. autofunction:: pyTMD.minor_arguments
+.. autofunction:: pyTMD.arguments.minor_arguments
 
-.. autofunction:: pyTMD.doodson_number
+.. autofunction:: pyTMD.arguments.doodson_number
 
 .. autofunction:: pyTMD.arguments._arguments_table
 

diff --git a/pyTMD/__init__.py b/pyTMD/__init__.py
@@ -11,6 +11,7 @@
 
 Documentation is available at https://pytmd.readthedocs.io
 """
+import pyTMD.arguments
 import pyTMD.astro
 import pyTMD.eop
 import pyTMD.interpolate
@@ -22,11 +23,6 @@
 import pyTMD.utilities
 import pyTMD.version
 from pyTMD import io
-from pyTMD.arguments import (
-    arguments, 
-    minor_arguments, 
-    doodson_number
-)
 from pyTMD.check_points import check_points
 from pyTMD.compute_tide_corrections import (
     compute_corrections,

diff --git a/pyTMD/predict.py b/pyTMD/predict.py
@@ -45,8 +45,8 @@
 from __future__ import annotations
 
 import numpy as np
+import pyTMD.arguments
 import pyTMD.astro
-from pyTMD.arguments import arguments, minor_arguments
 from pyTMD.constants import constants
 
 # PURPOSE: Predict tides at single times
@@ -90,8 +90,11 @@ def map(t: float | np.ndarray,
     npts, nc = np.shape(hc)
     # load the nodal corrections
     # convert time to Modified Julian Days (MJD)
-    pu, pf, G = arguments(t + 48622.0, constituents,
-        deltat=deltat, corrections=corrections)
+    pu, pf, G = pyTMD.arguments.arguments(t + 48622.0,
+        constituents,
+        deltat=deltat,
+        corrections=corrections
+    )
     # allocate for output tidal elevation
     ht = np.ma.zeros((npts))
     ht.mask = np.zeros((npts), dtype=bool)
@@ -152,8 +155,11 @@ def drift(t: float | np.ndarray,
     nt = len(t)
     # load the nodal corrections
     # convert time to Modified Julian Days (MJD)
-    pu, pf, G = arguments(t + 48622.0, constituents,
-        deltat=deltat, corrections=corrections)
+    pu, pf, G = pyTMD.arguments.arguments(t + 48622.0,
+        constituents,
+        deltat=deltat,
+        corrections=corrections
+    )
     # allocate for output time series
     ht = np.ma.zeros((nt))
     ht.mask = np.zeros((nt), dtype=bool)
@@ -214,8 +220,11 @@ def time_series(t: float | np.ndarray,
     nt = len(t)
     # load the nodal corrections
     # convert time to Modified Julian Days (MJD)
-    pu, pf, G = arguments(t + 48622.0, constituents,
-        deltat=deltat, corrections=corrections)
+    pu, pf, G = pyTMD.arguments.arguments(t + 48622.0,
+        constituents,
+        deltat=deltat,
+        corrections=corrections
+    )
     # allocate for output time series
     ht = np.ma.zeros((nt))
     ht.mask = np.zeros((nt), dtype=bool)
@@ -354,7 +363,7 @@ def infer_minor(
 
     # load the nodal corrections for minor constituents
     # convert time to Modified Julian Days (MJD)
-    pu, pf, G = minor_arguments(t + 48622.0,
+    pu, pf, G = pyTMD.arguments.minor_arguments(t + 48622.0,
         deltat=kwargs['deltat'],
         corrections=kwargs['corrections']
     )