refactor: make offsets to convert to MJD variables

pyTMD/astro.py

@@ -17,6 +17,7 @@
 
 UPDATE HISTORY:
     Updated 07/2024: made a wrapper function for normalizing angles
+        make number of days to convert JD to MJD a variable
     Updated 04/2024: use wrapper to importlib for optional dependencies
     Updated 01/2024: refactored lunisolar ephemerides functions
     Updated 12/2023: refactored phase_angles function to doodson_arguments
@@ -63,6 +64,9 @@
 # default JPL Spacecraft and Planet ephemerides kernel
 _default_kernel = get_data_path(['data','de440s.bsp'])
 
+# number of days between the Julian day epoch and MJD
+_jd_mjd = 2400000.5
+
 # PURPOSE: calculate the sum of a polynomial function of time
 def polynomial_sum(coefficients: list | np.ndarray, t: np.ndarray):
     """
@@ -796,7 +800,7 @@ def gast(T: float | np.ndarray):
     # create timescale from centuries relative to 2000-01-01T12:00:00
     ts = timescale.time.Timescale(MJD=T*36525.0 + 51544.5)
     # convert dynamical time to modified Julian days
-    MJD = ts.tt - 2400000.5
+    MJD = ts.tt - _jd_mjd
     # estimate the mean obliquity
     epsilon = mean_obliquity(MJD)
     # estimate the nutation in longitude and obliquity
@@ -840,7 +844,7 @@ def itrs(T: float | np.ndarray):
     # create timescale from centuries relative to 2000-01-01T12:00:00
     ts = timescale.time.Timescale(MJD=T*36525.0 + 51544.5)
     # convert dynamical time to modified Julian days
-    MJD = ts.tt - 2400000.5
+    MJD = ts.tt - _jd_mjd
     # estimate the mean obliquity
     epsilon = mean_obliquity(MJD)
     # estimate the nutation in longitude and obliquity
@@ -990,7 +994,7 @@ def _nutation_angles(T: float | np.ndarray):
     # create timescale from centuries relative to 2000-01-01T12:00:00
     ts = timescale.time.Timescale(MJD=T*36525.0 + 51544.5)
     # convert dynamical time to modified Julian days
-    MJD = ts.tt - 2400000.5
+    MJD = ts.tt - _jd_mjd
     # get the fundamental arguments in radians
     l, lp, F, D, Om = delaunay_arguments(MJD)
     # non-polynomial terms in the equation of the equinoxes

pyTMD/compute.py

@@ -61,6 +61,7 @@
 
 UPDATE HISTORY:
     Updated 07/2024: assert that data type is a known value
+        make number of days to convert JD to MJD a variable
     Updated 06/2024: use np.clongdouble instead of np.longcomplex
     Updated 04/2024: use wrapper to importlib for optional dependencies
     Updated 02/2024: changed class name for ellipsoid parameters to datum
@@ -125,6 +126,9 @@
 # attempt imports
 pyproj = pyTMD.utilities.import_dependency('pyproj')
 
+# number of days between the Julian day epoch and MJD
+_jd_mjd = 2400000.5
+
 # PURPOSE: wrapper function for computing values
 def corrections(
         x: np.ndarray, y: np.ndarray, delta_time: np.ndarray,
@@ -828,7 +832,7 @@ def LPT_displacements(
             epoch=EPOCH, standard=TIME)
 
     # convert dynamic time to Modified Julian Days (MJD)
-    MJD = ts.tt - 2400000.5
+    MJD = ts.tt - _jd_mjd
     # convert Julian days to calendar dates
     Y,M,D,h,m,s = timescale.time.convert_julian(ts.tt, format='tuple')
     # calculate time in year-decimal format
@@ -1008,7 +1012,7 @@ def OPT_displacements(
             epoch=EPOCH, standard=TIME)
 
     # convert dynamic time to Modified Julian Days (MJD)
-    MJD = ts.tt - 2400000.5
+    MJD = ts.tt - _jd_mjd
     # convert Julian days to calendar dates
     Y,M,D,h,m,s = timescale.time.convert_julian(ts.tt, format='tuple')
     # calculate time in year-decimal format

pyTMD/predict.py

@@ -21,6 +21,7 @@
 
 UPDATE HISTORY:
     Updated 07/2024: use normalize_angle from pyTMD astro module
+        make number of days to convert tide time to MJD a variable
     Updated 02/2024: changed class name for ellipsoid parameters to datum
     Updated 01/2024: moved minor arguments calculation into new function
         moved constituent parameters function from predict to arguments
@@ -52,6 +53,9 @@
 import pyTMD.astro
 from pyTMD.crs import datum
 
+# number of days between MJD and the tide epoch (1992-01-01T00:00:00)
+_mjd_tide = 48622.0
+
 # PURPOSE: Predict tides at single times
 def map(t: float | np.ndarray,
         hc: np.ndarray,
@@ -93,7 +97,7 @@ 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 = pyTMD.arguments.arguments(t + 48622.0,
+    pu, pf, G = pyTMD.arguments.arguments(t + _mjd_tide,
         constituents,
         deltat=deltat,
         corrections=corrections
@@ -159,7 +163,7 @@ def drift(t: float | np.ndarray,
     nt = len(t)
     # load the nodal corrections
     # convert time to Modified Julian Days (MJD)
-    pu, pf, G = pyTMD.arguments.arguments(t + 48622.0,
+    pu, pf, G = pyTMD.arguments.arguments(t + _mjd_tide,
         constituents,
         deltat=deltat,
         corrections=corrections
@@ -225,7 +229,7 @@ def time_series(t: float | np.ndarray,
     nt = len(t)
     # load the nodal corrections
     # convert time to Modified Julian Days (MJD)
-    pu, pf, G = pyTMD.arguments.arguments(t + 48622.0,
+    pu, pf, G = pyTMD.arguments.arguments(t + _mjd_tide,
         constituents,
         deltat=deltat,
         corrections=corrections
@@ -369,7 +373,7 @@ def infer_minor(
 
     # load the nodal corrections for minor constituents
     # convert time to Modified Julian Days (MJD)
-    pu, pf, G = pyTMD.arguments.minor_arguments(t + 48622.0,
+    pu, pf, G = pyTMD.arguments.minor_arguments(t + _mjd_tide,
         deltat=kwargs['deltat'],
         corrections=kwargs['corrections']
     )
@@ -535,7 +539,7 @@ def solid_earth_tide(
     # number of input coordinates
     nt = len(np.atleast_1d(t))
     # convert time to Modified Julian Days (MJD)
-    MJD = t + 48622.0
+    MJD = t + _mjd_tide
     # scalar product of input coordinates with sun/moon vectors
     radius = np.sqrt(XYZ[:,0]**2 + XYZ[:,1]**2 + XYZ[:,2]**2)
     solar_radius = np.sqrt(SXYZ[:,0]**2 + SXYZ[:,1]**2 + SXYZ[:,2]**2)