def test_get_position_pandas_datetime_series():
df = pd.DataFrame({'date': [date] * 3, 'lat': [lat] * 3, 'lng': [lng] * 3})
pos = pd.DataFrame(get_position(df['date'], df['lng'], df['lat']))
assert pos.shape == (3, 2)
assert all(x in pos.columns for x in ['azimuth', 'altitude'])
assert pos.dtypes['azimuth'] == np.dtype('float64')
assert pos.dtypes['altitude'] == np.dtype('float64')
assert np.isclose(pos['azimuth'].iloc[0], -2.5003175907168385)
assert np.isclose(pos['altitude'].iloc[0], -0.7000406838781611)
def create_stac_items(scenes_list: str,
grid_geom: str,
collection: int = 1,
level: int = 1):
"""Create STAC Items from scene_list and WRS2 grid."""
# Read WRS2 Grid geometries
with open(grid_geom, "r") as f:
wrs_grid_list = [json.loads(line) for line in f.readlines()]
pr = [x["properties"]["PR"] for x in wrs_grid_list]
wrs_grid = dict(zip(pr, wrs_grid_list))
for pr in wrs_grid.keys():
wrs_grid[pr]["geometry"] = _reduce_precision(
wrs_grid[pr]["geometry"])
# Open list of scenes
with open(scenes_list, "r") as f:
reader = csv.DictReader(f)
for value in reader:
# LC08_L1GT_070235_20180607_20180608_01_RT
product_id = value["productId"]
productid_info = product_id.split("_")
path_row = productid_info[2]
collection_number = productid_info[-2]
collection_category = productid_info[-1]
sat_number = int(productid_info[0][2:4])
sensor = productid_info[0][1]
_level = int(value["processingLevel"][1])
if _level != level:
continue
if int(collection_number) != collection:
continue
grid_cell = wrs_grid[path_row]
scene_time = grid_cell["properties"]["PERIOD"]
geom = grid_cell["geometry"]
if sensor == "C":
instruments = ["oli", "tirs"]
elif sensor == "O":
instruments = ["oli"]
elif sensor == "T" and sat_number >= 8:
instruments = ["tirs"]
elif sensor == "E":
instruments = ["etm"]
elif sensor == "T" and sat_number <= 8:
instruments = ["tm"]
elif sensor == "M":
instruments = ["mss"]
path = int(value["path"])
row = int(value["row"])
# we remove the milliseconds because it's missing for some entry
d = value["acquisitionDate"].split(".")
if len(d) == 1:
date_info = datetime.strptime(
value["acquisitionDate"],
"%Y-%m-%d %H:%M:%S").replace(tzinfo=timezone.utc)
else:
date_info = datetime.strptime(
value["acquisitionDate"],
"%Y-%m-%d %H:%M:%S.%f").replace(tzinfo=timezone.utc)
center_lat = (float(value["min_lat"]) +
float(value["max_lat"])) / 2
center_lon = (float(value["min_lon"]) +
float(value["max_lon"])) / 2
pos = get_position(date_info, center_lon, center_lat)
sun_azimuth = math.degrees(pos["azimuth"] + math.pi) % 360
sun_elevation = math.degrees(pos["altitude"])
collection_name = f"aws-landsat-c{collection}l{level}"
stac_item = {
"type":
"Feature",
"stac_extensions":
[eo_extension, landsat_extension, view_extension],
"id":
product_id,
"collection":
collection_name,
"bbox":
feature_bounds(geom),
"geometry":
geom,
"properties": {
"datetime": date_info.strftime("%Y-%m-%dT%H:%M:%S.%fZ"),
"platform": f"LANDSAT_{sat_number}",
"instruments": instruments,
"gsd": 30,
"view:sun_azimuth": round(sun_azimuth, 6),
"view:sun_elevation": round(sun_elevation, 6),
"landsat:wrs_type": 2,
"landsat:wrs_row": row,
"landsat:wrs_path": path,
"landsat:scene_id": value["entityId"],
"landsat:day_or_night": scene_time.lower(),
"landsat:processing_level": value["processingLevel"],
"landsat:collection_category": collection_category,
"landsat:collection_number": collection_number,
"landsat:cloud_cover_land": float(value["cloudCover"]),
"eo:cloud_cover": float(value["cloudCover"]),
},
"links": [{
"title": "AWS Public Dataset page for Landsat-8",
"rel": "about",
"type": "text/html",
"href": "https://registry.opendata.aws/landsat-8",
}],
}
prefix = f"https://landsat-pds.s3.us-west-2.amazonaws.com/c{int(collection_number)}/L{sat_number}/{path:03}/{row:03}/{product_id}/{product_id}"
stac_item["assets"] = create_assets(prefix)
yield stac_item
def sun_positions(arr_utc: np.ndarray, lon: float, lat: float) -> Tuple[np.ndarray, np.ndarray]:
sc = suncalc.get_position(arr_utc, lon, lat)
return sc['azimuth'], sc['altitude']
def test_get_position_pandas_single_timestamp():
ts_date = pd.Timestamp(date)
pos = get_position(ts_date, lng, lat)
assert np.isclose(pos['azimuth'], -2.5003175907168385)
assert np.isclose(pos['altitude'], -0.7000406838781611)
def test_get_position():
"""getPosition returns azimuth and altitude for the given time and location
"""
pos = get_position(date, lng, lat)
assert np.isclose(pos['azimuth'], -2.5003175907168385)
assert np.isclose(pos['altitude'], -0.7000406838781611)