Merge pull request #32 from ecmwf/develop

Develop

README.md

@@ -80,6 +80,24 @@ encoder = Covjsonkit().encode("CoverageCollection", "BoundingBox")
 res = encoder.from_polytope(polytope_output)
 ```
 
+### Config
+
+Covjsonkit uses a config to determine what parameter metadata to use, an example can be found in [example_config.json](example_config.json). This will automatically be loaded at runtime to point to the correct parameter metadata files. 
+
+The example config has to be stored in one of the following places:
+
+1. System-wide configuration in /etc/covjsonkit/config.json (and yaml)
+2. User configuration in ~/.covjsonkit.json (and yaml)
+
+Users can add their own parameter metadata in the [data directory](covjsonkit/data/) by add ing a new directory containing a param.json, param_id.json, and units.json in a format the same as can be found in [ecmwf directory](covjsonkit/data/ecmwf/). Then edit the config to point to your newly named directory.
+
+If users want to pass in their own config tehy can do this as a python dictioanry in the following way:
+
+```Python
+encoder = Covjsonkit(cf).encode("CoverageCollection", "BoundingBox")
+```
+
+Where `cf` is a valid covjsonkit config.
 ## Testing
 
 Python unit tests can be run with pytest:

covjsonkit/api.py

@@ -1,3 +1,5 @@
+from conflator import Conflator
+
 import covjsonkit.decoder.BoundingBox
 import covjsonkit.decoder.Frame
 import covjsonkit.decoder.Path
@@ -13,6 +15,8 @@
 import covjsonkit.encoder.VerticalProfile
 import covjsonkit.encoder.Wkt
 
+from .config import CovjsonKitConfig
+
 features_encoder = {
     "pointseries": covjsonkit.encoder.TimeSeries.TimeSeries,
     "verticalprofile": covjsonkit.encoder.VerticalProfile.VerticalProfile,
@@ -34,16 +38,21 @@
 
 
 class Covjsonkit:
-    def __init__(self):
-        pass
+    def __init__(self, config=None):
+        # If no config check default locations
+        if config is None:
+            self.conf = Conflator(app_name="covjsonkit", model=CovjsonKitConfig).load()
+        # else initialise with provided config
+        else:
+            self.conf = CovjsonKitConfig.model_validate(config)
 
     def encode(self, type, domaintype):
         if domaintype == "timeseries":
             domaintype = "PointSeries"
         elif domaintype == "trajectory":
             domaintype = "path"
         feature = self._feature_factory(domaintype.lower(), "encoder")
-        return feature(type, domaintype)
+        return feature(self.conf, domaintype)
 
     def decode(self, covjson):
         requesttype = covjson["domainType"]

covjsonkit/config.py

@@ -0,0 +1,5 @@
+from conflator import ConfigModel
+
+
+class CovjsonKitConfig(ConfigModel):
+    param_db: str = "ecmwf"

covjsonkit/decoder/BoundingBox.py

@@ -45,10 +45,12 @@ def to_xarray(self):
         # Get coordinates
         x = []
         y = []
+        z = []
         datetimes = []
         for coord in self.get_coordinates()["composite"]["values"]:
             x.append(float(coord[0]))
             y.append(float(coord[1]))
+            z.append(float(coord[2]))
         for datetime in self.get_coordinates()["t"]["values"]:
             datetimes.append(datetime)
 
@@ -112,6 +114,7 @@ def to_xarray(self):
                 points=(["points"], list(range(0, len(x)))),
                 x=(["points"], x),
                 y=(["points"], y),
+                z=(["points"], z),
             ),
         )
         for mars_metadata in self.mars_metadata[0]:

covjsonkit/decoder/TimeSeries.py

@@ -95,7 +95,7 @@ def to_xarray(self):
                                 param_values[parameter][i][j] = coverage["ranges"][parameter]["values"]
 
         for parameter in self.parameters:
-            param_coords = {"x": x, "y": y, "z": [z], "number": nums, "datetime": datetime, "t": steps}
+            param_coords = {"x": x, "y": y, "z": z, "number": nums, "datetime": datetime, "t": steps}
             dataarray = xr.DataArray(
                 [[[param_values[parameter]]]],
                 dims=dims,

covjsonkit/encoder/BoundingBox.py

@@ -81,16 +81,16 @@ def from_xarray(self, dataset):
     def from_polytope(self, result):
 
         coords = {}
-        # coords['composite'] = []
         mars_metadata = {}
         range_dict = {}
         lat = 0
         param = 0
         number = [0]
         step = 0
         dates = [0]
+        levels = [0]
 
-        self.walk_tree(result, lat, coords, mars_metadata, param, range_dict, number, step, dates)
+        self.walk_tree(result, lat, coords, mars_metadata, param, range_dict, number, step, dates, levels)
 
         self.add_reference(
             {
@@ -102,18 +102,51 @@ def from_polytope(self, result):
             }
         )
 
+        combined_dict = {}
+
+        for date in range_dict:
+            if date not in combined_dict:
+                combined_dict[date] = {}
+            for level in range_dict[date]:
+                for num in range_dict[date][level]:
+                    if num not in combined_dict[date]:
+                        combined_dict[date][num] = {}
+                    for para in range_dict[date][level][num]:
+                        if para not in combined_dict[date][num]:
+                            combined_dict[date][num][para] = {}
+                        for s, value in range_dict[date][level][num][para].items():
+                            if s not in combined_dict[date][num][para]:
+                                combined_dict[date][num][para][s] = value
+                            else:
+                                # Cocatenate arrays
+                                combined_dict[date][num][para][s] += value
+
+        levels = []
         for date in range_dict.keys():
-            for num in range_dict[date].keys():
+            for level in range_dict[date].keys():
+                levels.append(level)
+            break
+
+        for date in coords.keys():
+            coord = coords[date]["composite"]
+            coords[date]["composite"] = []
+            for level in levels:
+                for cor in coord:
+                    coords[date]["composite"].append([cor[0], cor[1], level])
+
+        for date in combined_dict.keys():
+            for num in combined_dict[date].keys():
                 val_dict = {}
-                for step in range_dict[date][num][self.parameters[0]].keys():
+                for step in combined_dict[date][num][self.parameters[0]].keys():
                     val_dict[step] = {}
-                for para in range_dict[date][num].keys():
-                    for step in range_dict[date][num][para].keys():
-                        val_dict[step][para] = range_dict[date][num][para][step]
+                for para in combined_dict[date][num].keys():
+                    for step in combined_dict[date][num][para].keys():
+                        val_dict[step][para] = combined_dict[date][num][para][step]
                 for step in val_dict.keys():
                     mm = mars_metadata.copy()
                     mm["number"] = num
                     mm["step"] = step
+                    mm["Forecast date"] = date
                     self.add_coverage(mm, coords[date], val_dict[step])
 
         # self.add_coverage(mars_metadata, coords, range_dict)

covjsonkit/encoder/Frame.py

@@ -81,16 +81,16 @@ def from_xarray(self, dataset):
     def from_polytope(self, result):
 
         coords = {}
-        # coords['composite'] = []
         mars_metadata = {}
         range_dict = {}
         lat = 0
         param = 0
         number = [0]
         step = 0
         dates = [0]
+        levels = [0]
 
-        self.walk_tree(result, lat, coords, mars_metadata, param, range_dict, number, step, dates)
+        self.walk_tree(result, lat, coords, mars_metadata, param, range_dict, number, step, dates, levels)
 
         self.add_reference(
             {
@@ -102,18 +102,51 @@ def from_polytope(self, result):
             }
         )
 
+        combined_dict = {}
+
+        for date in range_dict:
+            if date not in combined_dict:
+                combined_dict[date] = {}
+            for level in range_dict[date]:
+                for num in range_dict[date][level]:
+                    if num not in combined_dict[date]:
+                        combined_dict[date][num] = {}
+                    for para in range_dict[date][level][num]:
+                        if para not in combined_dict[date][num]:
+                            combined_dict[date][num][para] = {}
+                        for s, value in range_dict[date][level][num][para].items():
+                            if s not in combined_dict[date][num][para]:
+                                combined_dict[date][num][para][s] = value
+                            else:
+                                # Cocatenate arrays
+                                combined_dict[date][num][para][s] += value
+
+        levels = []
         for date in range_dict.keys():
-            for num in range_dict[date].keys():
+            for level in range_dict[date].keys():
+                levels.append(level)
+            break
+
+        for date in coords.keys():
+            coord = coords[date]["composite"]
+            coords[date]["composite"] = []
+            for level in levels:
+                for cor in coord:
+                    coords[date]["composite"].append([cor[0], cor[1], level])
+
+        for date in combined_dict.keys():
+            for num in combined_dict[date].keys():
                 val_dict = {}
-                for step in range_dict[date][num][self.parameters[0]].keys():
+                for step in combined_dict[date][num][self.parameters[0]].keys():
                     val_dict[step] = {}
-                for para in range_dict[date][num].keys():
-                    for step in range_dict[date][num][para].keys():
-                        val_dict[step][para] = range_dict[date][num][para][step]
+                for para in combined_dict[date][num].keys():
+                    for step in combined_dict[date][num][para].keys():
+                        val_dict[step][para] = combined_dict[date][num][para][step]
                 for step in val_dict.keys():
                     mm = mars_metadata.copy()
                     mm["number"] = num
                     mm["step"] = step
+                    mm["Forecast date"] = date
                     self.add_coverage(mm, coords[date], val_dict[step])
 
         # self.add_coverage(mars_metadata, coords, range_dict)

covjsonkit/encoder/Shapefile.py

@@ -81,16 +81,16 @@ def from_xarray(self, dataset):
     def from_polytope(self, result):
 
         coords = {}
-        # coords['composite'] = []
         mars_metadata = {}
         range_dict = {}
         lat = 0
         param = 0
         number = [0]
         step = 0
         dates = [0]
+        levels = [0]
 
-        self.walk_tree(result, lat, coords, mars_metadata, param, range_dict, number, step, dates)
+        self.walk_tree(result, lat, coords, mars_metadata, param, range_dict, number, step, dates, levels)
 
         self.add_reference(
             {
@@ -102,18 +102,51 @@ def from_polytope(self, result):
             }
         )
 
+        combined_dict = {}
+
+        for date in range_dict:
+            if date not in combined_dict:
+                combined_dict[date] = {}
+            for level in range_dict[date]:
+                for num in range_dict[date][level]:
+                    if num not in combined_dict[date]:
+                        combined_dict[date][num] = {}
+                    for para in range_dict[date][level][num]:
+                        if para not in combined_dict[date][num]:
+                            combined_dict[date][num][para] = {}
+                        for s, value in range_dict[date][level][num][para].items():
+                            if s not in combined_dict[date][num][para]:
+                                combined_dict[date][num][para][s] = value
+                            else:
+                                # Cocatenate arrays
+                                combined_dict[date][num][para][s] += value
+
+        levels = []
         for date in range_dict.keys():
-            for num in range_dict[date].keys():
+            for level in range_dict[date].keys():
+                levels.append(level)
+            break
+
+        for date in coords.keys():
+            coord = coords[date]["composite"]
+            coords[date]["composite"] = []
+            for level in levels:
+                for cor in coord:
+                    coords[date]["composite"].append([cor[0], cor[1], level])
+
+        for date in combined_dict.keys():
+            for num in combined_dict[date].keys():
                 val_dict = {}
-                for step in range_dict[date][num][self.parameters[0]].keys():
+                for step in combined_dict[date][num][self.parameters[0]].keys():
                     val_dict[step] = {}
-                for para in range_dict[date][num].keys():
-                    for step in range_dict[date][num][para].keys():
-                        val_dict[step][para] = range_dict[date][num][para][step]
+                for para in combined_dict[date][num].keys():
+                    for step in combined_dict[date][num][para].keys():
+                        val_dict[step][para] = combined_dict[date][num][para][step]
                 for step in val_dict.keys():
                     mm = mars_metadata.copy()
                     mm["number"] = num
                     mm["step"] = step
+                    mm["Forecast date"] = date
                     self.add_coverage(mm, coords[date], val_dict[step])
 
         # self.add_coverage(mars_metadata, coords, range_dict)