def geo_row_to_geojson(row, _, __):
"""Convert a geopandas dataframe row to a geojson format object. Converts all datetimes to epoch seconds.
geo_properties and precision inputs are ignored
"""
# Let pandas handle json serialization, except for the geojson object
shapely_geo_object = row['geometry']
row_json = json.loads(row.drop('geometry').to_json(date_format='epoch', date_unit='s'))
# Convert shapely object to a geojson object
geometry = geojson.GeoJSON(shapely.geometry.mapping(shapely_geo_object))
return geojson.Feature(geometry=geometry,
properties={key: row_json[key] for key in row_json.keys()})
async def test_geo_result(connection, universal_access_token, flowapi_url):
query = flowclient.joined_spatial_aggregate(
connection=connection(url=flowapi_url, token=universal_access_token),
**{
"locations": flowclient.daily_location_spec(
date="2016-01-01", aggregation_unit="admin3", method="last"
),
"metric": flowclient.handset_spec(
start_date="2016-01-01",
end_date="2016-01-02",
characteristic="brand",
method="last",
),
"method": "distr",
},
)
try:
result = await query.get_result(format="geojson")
except TypeError:
result = query.get_result(format="geojson")
assert geojson.GeoJSON(result).is_valid
def _read_geometries(
shape: Union[str, Path],
crs: Optional[Union[str, int, dict]] = None
) -> Tuple[List[geojson.geometry.Geometry], rasterio.crs.CRS]:
"""
A decorator to perform a check to verify a geometry is valid. Returns the function with geom set to
the shapely Shape object.
"""
try:
if shape is None:
raise ValueError
except (KeyError, ValueError):
logging.exception("No shape provided.")
raise
geom = list()
geometry_types = list()
try:
with fiona.open(shape) as fio:
logging.info("Vector read OK.")
if crs:
shape_crs = rasterio.crs.CRS.from_user_input(crs)
else:
shape_crs = rasterio.crs.CRS(fio.crs or 4326)
for i, feat in enumerate(fio):
g = geojson.GeoJSON(feat)
geom.append(g["geometry"])
geometry_types.append(g["geometry"]["type"])
except fiona.errors.DriverError:
logging.exception("Unable to read shape.")
raise
if len(geom):
logging.info("Shapes found are {}.".format(", ".join(
set(geometry_types))))
return geom, shape_crs
else:
raise RuntimeError("No geometries found.")
def test_GeoJSON(self):
self.assertEqual(None, geojson.GeoJSON().__geo_interface__)
self.assertEqual({"type": "GeoJSON"}, to_mapping(geojson.GeoJSON()))
def generate_areal_stats(self, areal_option, query_object, wbpm_calc):
"""Calculates several statistics for the Water Productivity calculated raster for a chosen dataset / name
Args:
areal_option (TYPE): Description
query_object (TYPE): Description
wbpm_calc (TYPE): Description
Returns:
TYPE: Description
"""
num_areas = 0
if areal_option == 'c':
try:
calculation_area = WaterProductivityCalc._COUNTRIES.filter(
ee.Filter.eq('iso3', query_object))
num_areas = calculation_area.size().getInfo()
geom = calculation_area.geometry()
finally:
error = Exception('no country')
elif areal_option == 'w':
try:
calculation_area = WaterProductivityCalc._WSHEDS.filter(
ee.Filter.eq('MAJ_NAME', query_object))
num_areas = calculation_area.size().getInfo()
geom = calculation_area.geometry()
finally:
error = Exception('no watershed')
elif areal_option == 'g':
try:
geojson_raw = {"type": "FeatureCollection",
"crs": {"type": "name", "properties": {"name": "urn:ogc:def:crs:OGC:1.3:CRS84"}},
"features": [{"type": "Feature",
"properties": {"area": "user_defined"},
"geometry": {"type": "Polygon",
"coordinates": [[[8.72, 12.28],
[29.34,
0.92],
[20.63, -6.24],
[8.72, 12.28]]]}
}
]
}
# from IPython import embed
# embed()
if isinstance(geojson.GeoJSON(query_object), geojson.GeoJSON):
if query_object['type'] == 'FeatureCollection':
data = geojson.FeatureCollection(
query_object['features'])
geom = data['features'][0]['geometry']
if len(geom) > 0:
num_areas = 1
finally:
error = Exception('User defined area seems empty')
if num_areas > 0:
means = wbpm_calc.reduceRegion(
reducer=ee.Reducer.mean(),
geometry=geom,
scale=self.scale_calc,
maxPixels=1e9
)
mean = means.getInfo()
reducers_min_max_sum = ee.Reducer.minMax().combine(
reducer2=ee.Reducer.sum(),
sharedInputs=True
)
# Use the combined reducer to get the min max and SD of the image.
stats = wbpm_calc.reduceRegion(
reducer=reducers_min_max_sum,
bestEffort=True,
geometry=geom,
scale=self.scale_calc
)
min_max_sum = stats.getInfo()
statistics_for_chosen_area = {}
statistics_for_chosen_area['response'] = {}
statistics_for_chosen_area['response']['name'] = query_object
if areal_option == 'c':
statistics_for_chosen_area['response']['iso3'] = calculation_area.getInfo()[
'features'][0]['properties']['iso3']
statistics_for_chosen_area['response']['gaul_code'] = calculation_area.getInfo()[
'features'][0]['properties']['gaul_code']
elif areal_option == 'w':
statistics_for_chosen_area['response']['wshed_code'] = int(
calculation_area.getInfo()['features'][0]['properties']['MAJ_BAS'])
statistics_for_chosen_area['response']['wapor_code'] = calculation_area.getInfo()[
'features'][0]['properties']['WaPOR_bas']
statistics_for_chosen_area['response']['stats'] = {}
statistics_for_chosen_area['response']['stats']['min'] = min_max_sum.pop(
'b1_min')
statistics_for_chosen_area['response']['stats']['sum'] = min_max_sum.pop(
'b1_sum')
statistics_for_chosen_area['response']['stats']['max'] = min_max_sum.pop(
'b1_max')
statistics_for_chosen_area['response']['stats']['mean'] = mean.pop(
'b1')
return statistics_for_chosen_area
else:
self.L1_logger.error("Error: %s named %s" % (error, query_object))
return error
#!/usr/bin/env python3
import geojson
import json
import sys
from geojson_rewind import rewind
with open(sys.argv[1]) as json_file:
data = json.load(json_file)
if 'crs' in data:
del data['crs']
data = rewind(data)
widget = geojson.GeoJSON(data)
widget.is_valid
widget.errors()
print(widget)