def get_elevation(dataset_name, methods=["GET", "OPTIONS", "HEAD"]):
"""Calculate the elevation for the given locations.
Args:
dataset_name: String matching a dataset in the config file.
Returns:
Response.
"""
try:
# Parse inputs.
interpolation = _parse_interpolation(request.args.get("interpolation"))
nodata_value = _parse_nodata_value(request.args.get("nodata_value"))
lats, lons = _parse_locations(
request.args.get("locations"),
_load_config()["max_locations_per_request"])
# Get the z values.
dataset = _get_dataset(dataset_name)
elevations = backend.get_elevation(lats, lons, dataset, interpolation)
elevations = utils.fill_na(elevations, nodata_value)
# Build response.
results = []
for z, lat, lon in zip(elevations, lats, lons):
results.append({
"elevation": z,
"location": {
"lat": lat,
"lng": lon
}
})
data = {"status": "OK", "results": results}
return jsonify(data)
except (ClientError, backend.InputError) as e:
return jsonify({"status": "INVALID_REQUEST", "error": str(e)}), 400
except config.ConfigError as e:
return (
jsonify({
"status": "SERVER_ERROR",
"error": "Config Error: {}".format(e)
}),
500,
)
except Exception as e:
if app.debug:
raise e
app.logger.error(e)
msg = "Server error, please retry request."
return jsonify({"status": "SERVER_ERROR", "error": msg}), 500
def _get_elevation_for_single_dataset(lats,
lons,
dataset,
interpolation="nearest",
nodata_value=None):
"""Read elevations from a dataset.
A dataset may consist of multiple files, so need to determine which
locations lies in which file, then loop over the files.
Args:
lats, lons: Arrays of latitudes/longitudes.
dataset: config.Dataset object.
interpolation: method name string.
Returns:
elevations: List of elevations, same length as lats/lons.
"""
# Which paths we need results from.
lats = np.array(lats)
lons = np.array(lons)
paths = dataset.location_paths(lats, lons)
# Store mapping of tile path to point so we can merge back together later.
elevations_by_path = {}
path_to_point_index = collections.defaultdict(list)
for i, path in enumerate(paths):
path_to_point_index[path].append(i)
# Batch results by path.
for path, indices in path_to_point_index.items():
if path is None:
elevations_by_path[None] = [None] * len(indices)
continue
batch_lats = lats[path_to_point_index[path]]
batch_lons = lons[path_to_point_index[path]]
elevations_by_path[path] = _get_elevation_from_path(
batch_lats, batch_lons, path, interpolation)
# Put the results back again.
elevations = [None] * len(paths)
for path, path_elevations in elevations_by_path.items():
for i_path, i_original in enumerate(path_to_point_index[path]):
elevations[i_original] = path_elevations[i_path]
elevations = utils.fill_na(elevations, nodata_value)
return elevations
def test_replacement(self):
na_value = -9999
values = [np.nan, float("nan"), 0]
replaced_values = [na_value, na_value, 0]
assert utils.fill_na(values, na_value) == replaced_values
def test_no_replacement(self):
a = [-12.5, None, 9, "string", True, False, 0, 1, "NaN"]
assert a == utils.fill_na(a, "na_value")