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129 fix coverages not conforming to ogc specification #135

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Merged
awarde96 merged 11 commits into from
Oct 12, 2026
Merged

129 fix coverages not conforming to ogc specification #135

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7144ddc
Add updated covjson output for vertical profile and position for enco…
awarde96 Sep 3, 2026
a2a3340
Update composite axis features (bbox, frame, shapefile) to align with…
awarde96 Sep 4, 2026
ac810c8
Update path to comply with ogc spec
awarde96 Sep 4, 2026
a48a5b3
ALign grid with ogc spec
awarde96 Sep 4, 2026
9358566
Fix bug when converting grid feature to_xarray
awarde96 Sep 4, 2026
46f98f6
Convert all t values in coverages to be valid_time, remove forecast_d…
awarde96 Sep 7, 2026
24e1f26
Merge develop with timeseries spec fix
awarde96 Oct 7, 2026
2b4be3e
Align position and vertical profile with timeseries
awarde96 Oct 7, 2026
4d6017a
Update encoders to calculate valid time correctly
awarde96 Oct 8, 2026
54a2c9f
Align decoders with new outputs
awarde96 Oct 8, 2026
4b5bebf
Update tests
awarde96 Oct 8, 2026
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92 changes: 58 additions & 34 deletions covjsonkit/decoder/BoundingBox.py
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Original file line number Diff line number Diff line change
Expand Up @@ -17,6 +17,25 @@ def __init__(self, covjson):
super().__init__(covjson)
self.domains = self.get_domains()
self.ranges = self.get_ranges()
# Backwards-compatible composite ordering: derive the position of the
# longitude (x), latitude (y) and optional vertical (z) components from
# the ``composite`` axis's ``coordinates`` labels. This reads both
# spec-compliant coverages (labels x/y[/z], values [lon, lat[, level]])
# and legacy coverages (labels latitude/longitude/levelist, values
# [lat, lon[, level]]).
labels = self.domains[0]["axes"]["composite"]["coordinates"]
self.x_idx = self._label_index(labels, ("x", "longitude"))
self.y_idx = self._label_index(labels, ("y", "latitude"))
self.z_idx = self._label_index(labels, ("z", "levelist"), required=False)

@staticmethod
def _label_index(labels, names, required=True):
for name in names:
if name in labels:
return labels.index(name)
if required:
raise ValueError(f"None of {names} found in composite coordinates {labels}")
return None

def get_domains(self):
domains = []
Expand Down Expand Up @@ -51,9 +70,9 @@ def to_geotiff(self, output_file="multipoint", resolution=0.01):
if rasterio is None:
raise ImportError("Please install 'rasterio' to use this feature: pip install covjsonkit[geo]")
coords = self.covjson["coverages"][0]["domain"]["axes"]["composite"]["values"]
x = [c[1] for c in coords] # longitude
y = [c[0] for c in coords] # latitude
# z = [c[2] for c in coords] # height/time/etc (not used yet)
x = [c[self.x_idx] for c in coords] # longitude
y = [c[self.y_idx] for c in coords] # latitude
# z = [c[self.z_idx] for c in coords] # height/time/etc (not used yet)

# Define grid
x_min, x_max = min(x), max(x)
Expand Down Expand Up @@ -119,10 +138,13 @@ def to_geojson(self):
param_vals["datetime"] = datetime
if "mars:metadata" in coverage:
param_vals["mars:metadata"] = mars_metadata
geom_coords = [lonlat[self.x_idx], lonlat[self.y_idx]]
if self.z_idx is not None:
geom_coords.append(lonlat[self.z_idx])
features.append(
{
"type": "Feature",
"geometry": {"type": "Point", "coordinates": [lonlat[1], lonlat[0], lonlat[2]]},
"geometry": {"type": "Point", "coordinates": geom_coords},
"properties": param_vals,
}
)
Expand All @@ -135,14 +157,15 @@ def to_xarray(self):
dataarraydict = {}

# Get coordinates
x = []
y = []
z = []
longitude = []
latitude = []
levelist = []
datetimes = []
for coord in self.get_coordinates()["composite"]["values"]:
x.append(float(coord[0]))
y.append(float(coord[1]))
z.append(float(coord[2]))
longitude.append(float(coord[self.x_idx]))
latitude.append(float(coord[self.y_idx]))
if self.z_idx is not None:
levelist.append(float(coord[self.z_idx]))
for datetime in self.get_coordinates()["t"]["values"]:
datetimes.append(datetime)

Expand All @@ -160,21 +183,16 @@ def to_xarray(self):
if "step" not in coverage["mars:metadata"]:
coverage["mars:metadata"]["step"] = 0
steps.append(coverage["mars:metadata"]["step"])
datetimes.append(coverage["domain"]["axes"]["t"]["values"][0])
# ``t`` is the valid time (date + step); the datetimes dimension is
# the forecast reference so that datetimes x steps stays dense.
datetime = self.forecast_reference(coverage)
datetimes.append(datetime)
number = coverage["mars:metadata"]["number"]
step = coverage["mars:metadata"]["step"]
for parameter in self.parameters:
# values[parameter].append(coverage["ranges"][parameter]["values"])
if coverage["domain"]["axes"]["t"]["values"][0] not in values[parameter]:
values[parameter][coverage["domain"]["axes"]["t"]["values"][0]] = {}
if (
coverage["mars:metadata"]["number"]
not in values[parameter][coverage["domain"]["axes"]["t"]["values"][0]]
):
values[parameter][coverage["domain"]["axes"]["t"]["values"][0]][
coverage["mars:metadata"]["number"]
] = {}
values[parameter][coverage["domain"]["axes"]["t"]["values"][0]][coverage["mars:metadata"]["number"]][
coverage["mars:metadata"]["step"]
] = coverage["ranges"][parameter]["values"]
values[parameter].setdefault(datetime, {}).setdefault(number, {})[step] = coverage["ranges"][parameter][
"values"
]

datetimes = sorted(list(set(datetimes)))
numbers = sorted(list(set(numbers)))
Expand All @@ -188,7 +206,10 @@ def to_xarray(self):
for j, number in enumerate(numbers):
new_values[parameter][i].append([])
for k, step in enumerate(steps):
new_values[parameter][i][j].append(values[parameter][datetime][number][step])
cell = values[parameter].get(datetime, {}).get(number, {}).get(step)
if cell is None:
cell = [None] * len(longitude)
new_values[parameter][i][j].append(cell)

for parameter in self.parameters:
dataarray = xr.DataArray(new_values[parameter], dims=dims)
Expand All @@ -197,17 +218,20 @@ def to_xarray(self):
dataarray.attrs["long_name"] = self.get_parameter_metadata(parameter)["observedProperty"]["id"]
dataarraydict[dataarray.attrs["long_name"]] = dataarray

coords_dict = dict(
datetimes=(["datetimes"], datetimes),
number=(["number"], numbers),
steps=(["steps"], steps),
points=(["points"], list(range(0, len(longitude)))),
latitude=(["points"], latitude),
longitude=(["points"], longitude),
)
if self.z_idx is not None:
coords_dict["levelist"] = (["points"], levelist)

ds = xr.Dataset(
dataarraydict,
coords=dict(
datetimes=(["datetimes"], datetimes),
number=(["number"], numbers),
steps=(["steps"], steps),
points=(["points"], list(range(0, len(x)))),
latitude=(["points"], x),
longitude=(["points"], y),
levelist=(["points"], z),
),
coords=coords_dict,
)
for mars_metadata in self.mars_metadata[0]:
ds.attrs[mars_metadata] = self.mars_metadata[0][mars_metadata]
Expand Down
85 changes: 54 additions & 31 deletions covjsonkit/decoder/Circle.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -9,6 +9,24 @@ def __init__(self, covjson):
super().__init__(covjson)
self.domains = self.get_domains()
self.ranges = self.get_ranges()
# Backwards-compatible composite ordering: derive the position of the
# longitude (x), latitude (y) and optional vertical (z) components from
# the ``composite`` axis's ``coordinates`` labels. Reads both spec
# coverages (x/y[/z], values [lon, lat[, level]]) and legacy coverages
# (latitude/longitude/levelist, values [lat, lon[, level]]).
labels = self.domains[0]["axes"]["composite"]["coordinates"]
self.x_idx = self._label_index(labels, ("x", "longitude"))
self.y_idx = self._label_index(labels, ("y", "latitude"))
self.z_idx = self._label_index(labels, ("z", "levelist"), required=False)

@staticmethod
def _label_index(labels, names, required=True):
for name in names:
if name in labels:
return labels.index(name)
if required:
raise ValueError(f"None of {names} found in composite coordinates {labels}")
return None

def get_domains(self):
domains = []
Expand Down Expand Up @@ -61,10 +79,13 @@ def to_geojson(self):
param_vals["datetime"] = datetime
if "mars:metadata" in coverage:
param_vals["mars:metadata"] = mars_metadata
geom_coords = [lonlat[self.x_idx], lonlat[self.y_idx]]
if self.z_idx is not None:
geom_coords.append(lonlat[self.z_idx])
features.append(
{
"type": "Feature",
"geometry": {"type": "Point", "coordinates": [lonlat[1], lonlat[0], lonlat[2]]},
"geometry": {"type": "Point", "coordinates": geom_coords},
"properties": param_vals,
}
)
Expand All @@ -77,14 +98,15 @@ def to_xarray(self):
dataarraydict = {}

# Get coordinates
x = []
y = []
z = []
longitude = []
latitude = []
levelist = []
datetimes = []
for coord in self.get_coordinates()["composite"]["values"]:
x.append(float(coord[0]))
y.append(float(coord[1]))
z.append(float(coord[2]))
longitude.append(float(coord[self.x_idx]))
latitude.append(float(coord[self.y_idx]))
if self.z_idx is not None:
levelist.append(float(coord[self.z_idx]))
for datetime in self.get_coordinates()["t"]["values"]:
datetimes.append(datetime)

Expand All @@ -102,21 +124,16 @@ def to_xarray(self):
if "step" not in coverage["mars:metadata"]:
coverage["mars:metadata"]["step"] = 0
steps.append(coverage["mars:metadata"]["step"])
datetimes.append(coverage["domain"]["axes"]["t"]["values"][0])
# ``t`` is the valid time (date + step); the datetimes dimension is
# the forecast reference so that datetimes x steps stays dense.
datetime = self.forecast_reference(coverage)
datetimes.append(datetime)
number = coverage["mars:metadata"]["number"]
step = coverage["mars:metadata"]["step"]
for parameter in self.parameters:
# values[parameter].append(coverage["ranges"][parameter]["values"])
if coverage["domain"]["axes"]["t"]["values"][0] not in values[parameter]:
values[parameter][coverage["domain"]["axes"]["t"]["values"][0]] = {}
if (
coverage["mars:metadata"]["number"]
not in values[parameter][coverage["domain"]["axes"]["t"]["values"][0]]
):
values[parameter][coverage["domain"]["axes"]["t"]["values"][0]][
coverage["mars:metadata"]["number"]
] = {}
values[parameter][coverage["domain"]["axes"]["t"]["values"][0]][coverage["mars:metadata"]["number"]][
coverage["mars:metadata"]["step"]
] = coverage["ranges"][parameter]["values"]
values[parameter].setdefault(datetime, {}).setdefault(number, {})[step] = coverage["ranges"][parameter][
"values"
]

datetimes = sorted(list(set(datetimes)))
numbers = sorted(list(set(numbers)))
Expand All @@ -130,7 +147,10 @@ def to_xarray(self):
for j, number in enumerate(numbers):
new_values[parameter][i].append([])
for k, step in enumerate(steps):
new_values[parameter][i][j].append(values[parameter][datetime][number][step])
cell = values[parameter].get(datetime, {}).get(number, {}).get(step)
if cell is None:
cell = [None] * len(longitude)
new_values[parameter][i][j].append(cell)

for parameter in self.parameters:
dataarray = xr.DataArray(new_values[parameter], dims=dims)
Expand All @@ -139,17 +159,20 @@ def to_xarray(self):
dataarray.attrs["long_name"] = self.get_parameter_metadata(parameter)["observedProperty"]["id"]
dataarraydict[dataarray.attrs["long_name"]] = dataarray

coords_dict = dict(
datetimes=(["datetimes"], datetimes),
number=(["number"], numbers),
steps=(["steps"], steps),
points=(["points"], list(range(0, len(longitude)))),
latitude=(["points"], latitude),
longitude=(["points"], longitude),
)
if self.z_idx is not None:
coords_dict["levelist"] = (["points"], levelist)

ds = xr.Dataset(
dataarraydict,
coords=dict(
datetimes=(["datetimes"], datetimes),
number=(["number"], numbers),
steps=(["steps"], steps),
points=(["points"], list(range(0, len(x)))),
latitude=(["points"], x),
longitude=(["points"], y),
levelist=(["points"], z),
),
coords=coords_dict,
)
for mars_metadata in self.mars_metadata[0]:
ds.attrs[mars_metadata] = self.mars_metadata[0][mars_metadata]
Expand Down
25 changes: 22 additions & 3 deletions covjsonkit/decoder/Frame.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -8,6 +8,22 @@ def __init__(self, covjson):
super().__init__(covjson)
self.domains = self.get_domains()
self.ranges = self.get_ranges()
# Backwards-compatible composite ordering: derive x/y/z positions from
# the ``composite`` axis's ``coordinates`` labels (reads both x/y[/z]
# and legacy latitude/longitude/levelist labels).
labels = self.domains[0]["axes"]["composite"]["coordinates"]
self.x_idx = self._label_index(labels, ("x", "longitude"))
self.y_idx = self._label_index(labels, ("y", "latitude"))
self.z_idx = self._label_index(labels, ("z", "levelist"), required=False)

@staticmethod
def _label_index(labels, names, required=True):
for name in names:
if name in labels:
return labels.index(name)
if required:
raise ValueError(f"None of {names} found in composite coordinates {labels}")
return None

def get_domains(self):
domains = []
Expand Down Expand Up @@ -57,12 +73,15 @@ def to_geojson(self):
param_vals["datetime"] = datetime
if "mars:metadata" in coverage:
param_vals["mars:metadata"] = mars_metadata
geom_coords = [lonlat[self.x_idx], lonlat[self.y_idx]]
if self.z_idx is not None:
geom_coords.append(lonlat[self.z_idx])
features.append(
{
"type": "Feature",
"geometry": {
"type": "Point",
"coordinates": [lonlat[1], lonlat[0], lonlat[2]],
"coordinates": geom_coords,
},
"properties": param_vals,
}
Expand Down Expand Up @@ -91,8 +110,8 @@ def to_xarray(self):
times.append(domain["axes"]["t"]["values"][0])
if i == 0:
for coord in domain["axes"]["composite"]["values"]:
x.append(float(coord[0]))
y.append(float(coord[1]))
x.append(float(coord[self.x_idx]))
y.append(float(coord[self.y_idx]))

n_points = len(x)

Expand Down
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