Merge pull request #21 from tsutterley/interpolation

replaced griddata with scipy regular grid interpolators

.gitignore

@@ -37,6 +37,8 @@ wheels/
 *.egg-info/
 .installed.cfg
 *.egg
+.pytest_cache
+pythonenv*/
 # OS generated files #
 ######################
 .DS_Store

doc/source/conf.py

@@ -22,7 +22,7 @@
 author = 'Tyler C. Sutterley'
 
 # The full version, including alpha/beta/rc tags
-release = '1.0.2.10'
+release = '1.0.2.11'
 
 
 # -- General configuration ---------------------------------------------------

doc/source/user_guide/compute_tide_corrections.md

@@ -35,7 +35,7 @@ tide = compute_tide_corrections(x, y, delta_time, DIRECTORY=DIRECTORY,
  - `METHOD`: interpolation method
      * `bilinear`: quick bilinear interpolation
      * `spline`: scipy bivariate spline interpolation (default)
-     * `linear`, `cubic`, `nearest`: scipy griddata interpolations
+     * `linear`, `nearest`: scipy regular grid interpolations
  - `FILL_VALUE`: output invalid value
 
 #### Outputs

doc/source/user_guide/read_FES_model.md

@@ -31,7 +31,7 @@ amp,ph = read_FES_model(ilon,ilat,directory,model_files,TYPE=type,
  - `METHOD`: interpolation method
     * `'bilinear'`: quick bilinear interpolation
     * `'spline'`: scipy bivariate spline interpolation
-    * `'linear'`, `'cubic'`, `'nearest'`: scipy griddata interpolations
+    * `'linear'`, `'nearest'`: scipy regular grid interpolations
  - `GZIP`: input files are compressed
  - `SCALE`: scaling factor for converting to output units
 

doc/source/user_guide/read_GOT_model.md

@@ -21,7 +21,7 @@ amp,ph = read_GOT_model(ilon,ilat,directory,model_files,METHOD='spline')
  - `METHOD`: interpolation method
     * `'bilinear'`: quick bilinear interpolation
     * `'spline'`: scipy bivariate spline interpolation
-    * `'linear'`, `'cubic'`, `'nearest'`: scipy griddata interpolations
+    * `'linear'`, `'nearest'`: scipy regular grid interpolations
  - `GZIP`: input files are compressed
  - `SCALE`: scaling factor for converting to output units
 

doc/source/user_guide/read_netcdf_model.md

@@ -32,7 +32,7 @@ amp,ph,D,c = read_netcdf_model(ilon,ilat,directory,model_files,type,METHOD='spli
  - `METHOD`: interpolation method
     * `'bilinear'`: quick bilinear interpolation
     * `'spline'`: scipy bivariate spline interpolation
-    * `'linear'`, `'cubic'`, `'nearest'`: scipy griddata interpolations
+    * `'linear'`, `'nearest'`: scipy regular grid interpolations
  - `GZIP`: input netCDF4 files are compressed
  - `SCALE`: scaling factor for converting to output units
 

doc/source/user_guide/read_ocean_pole_tide.md

@@ -7,15 +7,19 @@ read_ocean_pole_tide.py
 
 #### Calling Sequence
 ```python
+from pyTMD.utilities import get_data_path
 from pyTMD.read_ocean_pole_tide import read_ocean_pole_tide
-ht = read_ocean_pole_tide(input_file)
+ocean_pole_tide_file = get_data_path(['data','opoleloadcoefcmcor.txt.gz'])
+ur,un,ue,glon,glat = read_ocean_pole_tide(ocean_pole_tide_file)
 ```
 [Source code](https://github.com/tsutterley/pyTMD/blob/master/pyTMD/read_ocean_pole_tide.py)
 
 #### Inputs
   1. `input_file`: [IERS 0.5x0.5 map of ocean pole tide coefficients](ftp://maia.usno.navy.mil/conventions/2010/2010_update/chapter7/additional_info/opoleloadcoefcmcor.txt.gz)
 
 #### Outputs
- - `ur`: ocean pole tide coefficients
+ - `ur`: radial ocean pole tide coefficients
+ - `un`: north ocean pole tide coefficients
+ - `ue`: east ocean pole tide coefficients
  - `glon`: grid longitude
  - `glat`: grid latitude

doc/source/user_guide/read_tide_model.md

@@ -29,7 +29,7 @@ amp,ph,D,c = read_tide_model(ilon, ilat, grid_file, model_file, EPSG,
  - `METHOD`: interpolation method
     * `'bilinear'`: quick bilinear interpolation
     * `'spline'`: scipy bivariate spline interpolation
-    * `'linear'`, `'cubic'`, `'nearest'`: scipy griddata interpolations
+    * `'linear'`, `'nearest'`: scipy regular grid interpolations
  - `GRID`: binary file type to read
     * `'ATLAS'`: reading a global solution with high-resolution local solutions
     * `'OTIS'`: combined global solution

notebooks/Plot Antarctic Tidal Currents.ipynb

@@ -74,6 +74,7 @@
     "import ipywidgets as widgets\n",
     "from IPython.display import HTML\n",
     "\n",
+    "import pyTMD.time\n",
     "from pyTMD.calc_delta_time import calc_delta_time\n",
     "from pyTMD.read_tide_model import extract_tidal_constants\n",
     "from pyTMD.read_netcdf_model import extract_netcdf_constants\n",
@@ -280,10 +281,8 @@
    "source": [
     "#-- convert from calendar date to days relative to Jan 1, 1992 (48622 MJD)\n",
     "YMD = datepick.value\n",
-    "tide_time = 367.0*YMD.year - \\\n",
-    "    np.floor(7.0*(YMD.year + np.floor((YMD.month+9.0)/12.0))/4.0) - \\\n",
-    "    np.floor(3.0*(np.floor((YMD.year + (YMD.month - 9.0)/7.0)/100.0) + 1.0)/4.0) + \\\n",
-    "    np.floor(275.*YMD.month/9.0) + YMD.day + np.arange(24)/24.0 - 727594.0\n",
+    "tide_time = pyTMD.time.convert_calendar_dates(YMD.year, YMD.month,\n",
+    "    YMD.day, hour=np.arange(24))\n",
     "\n",
     "#-- save tide currents\n",
     "tide = {}\n",

notebooks/Plot Ross Ice Shelf Map.ipynb

@@ -77,6 +77,7 @@
     "import ipywidgets as widgets\n",
     "from IPython.display import HTML\n",
     "\n",
+    "import pyTMD.time\n",
     "from pyTMD.calc_delta_time import calc_delta_time\n",
     "from pyTMD.read_tide_model import extract_tidal_constants\n",
     "from pyTMD.read_netcdf_model import extract_netcdf_constants\n",
@@ -287,10 +288,8 @@
    "source": [
     "#-- convert from calendar date to days relative to Jan 1, 1992 (48622 MJD)\n",
     "YMD = datepick.value\n",
-    "tide_time = 367.0*YMD.year - \\\n",
-    "    np.floor(7.0*(YMD.year + np.floor((YMD.month+9.0)/12.0))/4.0) - \\\n",
-    "    np.floor(3.0*(np.floor((YMD.year + (YMD.month - 9.0)/7.0)/100.0) + 1.0)/4.0) + \\\n",
-    "    np.floor(275.*YMD.month/9.0) + YMD.day + np.arange(24)/24.0 - 727594.0\n",
+    "tide_time = pyTMD.time.convert_calendar_dates(YMD.year, YMD.month,\n",
+    "    YMD.day, hour=np.arange(24))\n",
     "\n",
     "#-- read tidal constants and interpolate to grid points\n",
     "if model_format in ('OTIS','ATLAS'):\n",

notebooks/Plot Tide Forecasts.ipynb

@@ -75,6 +75,7 @@
     "import ipywidgets as widgets\n",
     "import ipyleaflet as leaflet\n",
     "\n",
+    "import pyTMD.time\n",
     "from pyTMD.calc_delta_time import calc_delta_time\n",
     "from pyTMD.infer_minor_corrections import infer_minor_corrections\n",
     "from pyTMD.predict_tidal_ts import predict_tidal_ts\n",
@@ -182,11 +183,9 @@
     "\n",
     "#-- convert from calendar date to days relative to Jan 1, 1992 (48622 MJD)\n",
     "YMD = datepick.value\n",
-    "TIME = np.arange(7*1440)/1440.0\n",
-    "tide_time = 367.0*YMD.year - \\\n",
-    "    np.floor(7.0*(YMD.year + np.floor((YMD.month+9.0)/12.0))/4.0) - \\\n",
-    "    np.floor(3.0*(np.floor((YMD.year + (YMD.month - 9.0)/7.0)/100.0) + 1.0)/4.0) + \\\n",
-    "    np.floor(275.*YMD.month/9.0) + YMD.day + TIME - 727594.0\n",
+    "#-- calculate a weeks forecast every minute\n",
+    "tide_time = pyTMD.time.convert_calendar_dates(YMD.year, YMD.month,\n",
+    "    YMD.day, minute=np.arange(7*1440))\n",
     "\n",
     "#-- select between tide models\n",
     "if (TIDE_MODEL == 'CATS0201'):\n",

pyTMD/compute_equilibrium_tide.py

@@ -1,8 +1,8 @@
 """
 compute_equilibrium_tide.py (08/2020)
 Calculates the long-period equilibrium ocean tides
-Fifteen tidal spectral lines from the Cartwright-Tayler-Edden
-    tables are summed over to compute the long-period tides
+Uses the summation of fifteen tidal spectral lines from the
+    Cartwright-Tayler-Edden tables to compute the long-period tides
 
 INPUTS:
     t: days relative to Jan 1, 1992 (48622 MJD)
@@ -14,6 +14,10 @@
 REFERENCES:
     Cartwright & Tayler, Geophys. J. R.A.S., 23, 45, 1971.
     Cartwright & Edden, Geophys. J. R.A.S., 33, 253, 1973.
+
+UPDATE HISTORY:
+    Updated 08/2020: use Load love number value of 0.693 for gamma_2
+    Written 08/2020
 """
 import numpy as np
 
@@ -25,16 +29,17 @@ def compute_equilibrium_tide(t, lat):
     PHC = np.array([290.21,280.12,274.35,343.51])
     DPD = np.array([13.1763965,0.9856473,0.1114041,0.0529539])
 
-    #-- convert time from days relative to 1992-01-01 to 1987-01-01
-    #-- Compute 4 principal mean longitudes in radians at delta time
+    #-- number of input points
     npts = len(t)
+    #-- compute 4 principal mean longitudes in radians at delta time (SHPN)
     SHPN = np.zeros((4,npts))
     for N in range(4):
+        #-- convert time from days relative to 1992-01-01 to 1987-01-01
         ANGLE = PHC[N] + (t + 1826.0)*DPD[N]
         SHPN[N,:] = np.pi*np.mod(ANGLE, 360.0)/180.0
 
-    #-- Assemble long-period tide potential from 15 CTE terms > 1 mm.
-    #-- Nodal term is included but not the constant term.
+    #-- assemble long-period tide potential from 15 CTE terms greater than 1 mm
+    #-- nodal term is included but not the constant term.
     PH = np.zeros((npts))
     Z = np.zeros((npts))
     Z += 2.79*np.cos(SHPN[3,:]) - 0.49*np.cos(SHPN[1,:] - \
@@ -51,6 +56,9 @@ def compute_equilibrium_tide(t, lat):
         0.53*np.cos(PH - SHPN[2,:] + SHPN[3,:]) - \
         0.24*np.cos(PH - 2.0*SHPN[1,:] + SHPN[2,:])
 
-    #-- Multiply by gamma_2 * sqrt(5/4 pi) * P20(lat)
-    lpet = 0.437*Z*(1.5*np.sin(lat*np.pi/180.0)**2 - 0.5)/100.0
+    #-- Multiply by gamma_2 * normalization * P20(lat)
+    gamma_2 = 0.693
+    P20 = 0.5*(3.0*np.sin(lat*np.pi/180.0)**2 - 1.0)
+    #-- calculate long-period equilibrium tide and convert to meters
+    lpet = gamma_2*np.sqrt((4.0 + 1.0)/(4.0*np.pi))*P20*(Z/100.0)
     return lpet

pyTMD/compute_tide_corrections.py

@@ -32,7 +32,7 @@
     METHOD: interpolation method
         bilinear: quick bilinear interpolation
         spline: scipy bivariate spline interpolation
-        linear, cubic, nearest: scipy griddata interpolations
+        linear, nearest: scipy regular grid interpolations
     FILL_VALUE: output invalid value (default NaN)
 
 PYTHON DEPENDENCIES:
@@ -125,7 +125,7 @@ def compute_tide_corrections(x, y, delta_time, DIRECTORY=None, MODEL=None,
     METHOD: interpolation method
         bilinear: quick bilinear interpolation
         spline: scipy bivariate spline interpolation
-        linear, cubic, nearest: scipy griddata interpolations
+        linear, nearest: scipy regular grid interpolations
     FILL_VALUE: output invalid value (default NaN)
 
     Returns
@@ -174,7 +174,7 @@ def compute_tide_corrections(x, y, delta_time, DIRECTORY=None, MODEL=None,
             'h_m4_tpxo9_atlas_30_v2.nc.gz','h_ms4_tpxo9_atlas_30_v2.nc.gz',
             'h_mn4_tpxo9_atlas_30_v2.nc.gz','h_2n2_tpxo9_atlas_30_v2.nc.gz']
         model_format = 'netcdf'
-        TYPE = 'z'
+        model_type = 'z'
         SCALE = 1.0/1000.0
     elif (MODEL == 'TPXO9.1'):
         grid_file = os.path.join(DIRECTORY,'TPXO9.1','DATA','grid_tpxo9')