Added new CDD interpolation modes with parameters

.gitignore

@@ -5,7 +5,7 @@
 /build
 pyg2p.egg-info
 /dist
-
+*.nbc
 /.python-version
 .coverage
 .coverage.*

README.md

@@ -671,15 +671,38 @@ Attributes p, leafsize and eps for the kd tree algorithm are default in scipy li
 
 #### ADW
 It's the Angular Distance Weighted (ADW) algorithm by Shepard et al. 1968, with scipy.kd_tree using 11 neighbours.
-If @adw_broadcasting is set to true, computations will run in full broadcasting mode but requires more memory
+If @use_broadcasting is set to true, computations will run in full broadcasting mode but requires more memory
 
 ```json
 {
 "Interpolation": {
   "@latMap": "/dataset/maps/europe5km/lat.map",
   "@lonMap": "/dataset/maps/europe5km/long.map",
   "@mode": "adw",
-  "@adw_broadcasting": false}
+  "@use_broadcasting": false}
+}
+```
+
+#### CDD
+It's the Correlation Distance Decay (CDD) modified implementation of the Angular Distance Weighted algorithm, with scipy.kd_tree using 11 neighbours. It needs a map of CDD values for each point, to be specified in the field @cdd_map
+@cdd_mode can be one of the following values: "Hofstra", "NewEtAl" or "MixHofstraShepard"
+In case of mode "MixHofstraShepard", @cdd_options allows to customize the parameters of Hofstra and Shepard algorithm.
+If @use_broadcasting is set to true, computations will run in full broadcasting mode but requires more memory
+
+```json
+{
+"Interpolation": {
+  "@latMap": "/dataset/maps/europe5km/lat.map",
+  "@lonMap": "/dataset/maps/europe5km/long.map",
+  "@mode": "cdd",
+  "@cdd_map": "/dataset/maps/europe5km/cdd_map.nc",
+  "@cdd_mode": "MixHofstraShepard",
+  "@cdd_options": {
+    "m_const": 4,
+    "min_num_of_station": 4,
+    "radius_ratio": 0.3333333333333333
+  },
+  "@use_broadcasting": false}
 }
 ```
 

src/pyg2p/main/api.py

@@ -168,6 +168,9 @@ def _define_exec_params(self):
         self._vars['outMaps.clone'] = self.api_conf['OutMaps']['cloneMap']
         interpolation_conf = self.api_conf['OutMaps']['Interpolation']
         self._vars['interpolation.mode'] = interpolation_conf.get('mode', self.default_values['interpolation.mode'])
+        self._vars['interpolation.cdd_map'] = interpolation_conf.get('cdd_map', '')
+        self._vars['interpolation.cdd_mode'] = interpolation_conf.get('cdd_mode', '')
+        self._vars['interpolation.cdd_options'] = interpolation_conf.get('cdd_options', None)
         self._vars['interpolation.use_broadcasting'] = interpolation_conf.get('use_broadcasting', False)
         self._vars['interpolation.rotated_target'] = interpolation_conf.get('rotated_target', False)
         if not self._vars['interpolation.dir'] and self.api_conf.get('intertableDir'):

src/pyg2p/main/context.py

@@ -360,7 +360,10 @@ def _define_exec_params(self):
         self._vars['outMaps.clone'] = exec_conf['OutMaps']['@cloneMap']
         interpolation_conf = exec_conf['OutMaps']['Interpolation']
         self._vars['interpolation.mode'] = interpolation_conf.get('@mode', self.default_values['interpolation.mode'])
-        self._vars['interpolation.adw_broadcasting'] = interpolation_conf.get('@adw_broadcasting', False)
+        self._vars['interpolation.cdd_map'] = interpolation_conf.get('@cdd_map', '')
+        self._vars['interpolation.cdd_mode'] = interpolation_conf.get('@cdd_mode', '')
+        self._vars['interpolation.cdd_options'] = interpolation_conf.get('@cdd_options', None)
+        self._vars['interpolation.use_broadcasting'] = interpolation_conf.get('@use_broadcasting', False)
         self._vars['interpolation.rotated_target'] = interpolation_conf.get('@rotated_target', False)
         if not self._vars['interpolation.dir'] and interpolation_conf.get('@intertableDir'):
             # get from JSON

src/pyg2p/main/interpolation/__init__.py

@@ -20,7 +20,7 @@
 class Interpolator(Loggable):
     _LOADED_INTERTABLES = {}
     _prefix = 'I'
-    scipy_modes_nnear = {'nearest': 1, 'invdist': 4, 'adw': 11, 'cdd': 10, 'bilinear': 4, 'triangulation': 3, 'bilinear_delaunay': 4}
+    scipy_modes_nnear = {'nearest': 1, 'invdist': 4, 'adw': 11, 'cdd': 11, 'bilinear': 4, 'triangulation': 3, 'bilinear_delaunay': 4}
     suffixes = {'grib_nearest': 'grib_nearest', 'grib_invdist': 'grib_invdist',
                 'nearest': 'scipy_nearest', 'invdist': 'scipy_invdist', 'adw': 'scipy_adw', 'cdd': 'scipy_cdd',
                 'bilinear': 'scipy_bilinear', 'triangulation': 'scipy_triangulation', 'bilinear_delaunay': 'scipy_bilinear_delaunay'}
@@ -31,7 +31,10 @@ def __init__(self, exec_ctx, mv_input):
         self._mv_grib = mv_input
         self.interpolate_with_grib = exec_ctx.is_with_grib_interpolation
         self._mode = exec_ctx.get('interpolation.mode')
-        self._adw_broadcasting = exec_ctx.get('interpolation.adw_broadcasting')
+        self._cdd_map = exec_ctx.get('interpolation.cdd_map')
+        self._cdd_mode = exec_ctx.get('interpolation.cdd_mode')
+        self._cdd_options = exec_ctx.get('interpolation.cdd_options')
+        self._use_broadcasting = exec_ctx.get('interpolation.use_broadcasting')
         self._source_filename = pyg2p.util.files.filename(exec_ctx.get('input.file'))
         self._suffix = self.suffixes[self._mode]
         self._intertable_dirs = exec_ctx.get('interpolation.dirs')
@@ -227,7 +230,9 @@ def interpolate_scipy(self, latgrib, longrib, v, grid_id, grid_details=None):
             self._log('\nInterpolating table not found\n Id: {}\nWill create file: {}'.format(intertable_id, intertable_name), 'WARN')
             scipy_interpolation = ScipyInterpolation(longrib, latgrib, grid_details, v.ravel(), nnear, self.mv_out,
                                           self._mv_grib, target_is_rotated=self._rotated_target_grid,
-                                          parallel=self.parallel, mode=self._mode, use_broadcasting=self._adw_broadcasting)
+                                          parallel=self.parallel, mode=self._mode, 
+                                          cdd_map=self._cdd_map, cdd_mode=self._cdd_mode, cdd_options = self._cdd_options,
+                                          use_broadcasting=self._use_broadcasting)
             _, weights, indexes = scipy_interpolation.interpolate(lonefas, latefas)
             result = self._interpolate_scipy_append_mv(v, weights, indexes, nnear)