def flip_quadkey(q, flip):
lng, lat = quadkey_to_centroid(q)
z = len(q)
if flip[0]: lng = -lng
if flip[1]: lat = -lat
tile = mercantile.tile(lng, lat, z)
return mercantile.quadkey(tile)
def quadkey(ctx, input):
"""Takes [x, y, z] tiles or quadkeys as input and writes
quadkeys or a [x, y, z] tiles to stdout, respectively.
Input may be a compact newline-delimited sequences of JSON or
a pretty-printed ASCII RS-delimited sequence of JSON (like
https://tools.ietf.org/html/rfc8142 and
https://tools.ietf.org/html/rfc7159).
$ echo "[486, 332, 10]" | mercantile quadkey
Output:
0313102310
$ echo "0313102310" | mercantile quadkey
Output:
[486, 332, 10]
"""
src = normalize_input(input)
try:
for line in iter_lines(src):
if line[0] == '[':
tile = json.loads(line)[:3]
output = mercantile.quadkey(tile)
else:
tile = mercantile.quadkey_to_tile(line)
output = json.dumps(tile)
click.echo(output)
except ValueError:
raise click.BadParameter(
"{0}".format(input), param=input, param_hint='input')
def cl_post_prediction(self, payload: Dict[str, Any], chips: List[dict], prediction_id: str, inferences: List[str]) -> Dict[str, Any]:
payload = json.dumps(payload)
r = requests.post(self.prediction_endpoint + ":predict", data=payload)
r.raise_for_status()
preds = r.json()["predictions"]
pred_list = [];
for i in range(len(chips)):
pred_dict = {}
for j in range(len(preds[i])):
pred_dict[inferences[j]] = preds[i][j]
body = {
"geom": shapely.geometry.mapping(box(*chips[i].get('bounds'))),
"predictions": pred_dict,
"prediction_id": prediction_id
}
if chips[i].get('x') is not None and chips[i].get('y') is not None and chips[i].get('z') is not None:
body['quadkey'] = mercantile.quadkey(chips[i].get('x'), chips[i].get('y'), chips[i].get('z'))
pred_list.append(body)
return {
"predictionId": prediction_id,
"predictions": pred_list
}
def quadkey(ctx, input):
"""Takes a [x, y, z] tile or a quadkey as input and writes a
quadkey or a [x, y, z] tile to stdout, respectively.
$ echo "[486, 332, 10]" | mercantile quadkey
Output:
0313102310
$ echo "0313102310" | mercantile quadkey
Output:
[486, 332, 10]
"""
src = normalize_input(input)
try:
for line in iter_lines(src):
if line[0] == '[':
tile = json.loads(line)[:3]
output = mercantile.quadkey(tile)
else:
tile = mercantile.quadkey_to_tile(line)
output = json.dumps(tile)
click.echo(output)
except ValueError:
raise click.BadParameter("{0}".format(input),
param=input,
param_hint='input')
def polyfill(self, input_gdf, zoom_level):
check_package('mercantile', is_optional=True)
import mercantile
if not hasattr(input_gdf, 'geometry'):
raise ValueError('This dataframe has no valid geometry.')
geometry_name = input_gdf.geometry.name
dfs = []
for _, row in input_gdf.iterrows():
input_geometry = row[geometry_name]
bounds = input_geometry.bounds
tiles = mercantile.tiles(bounds[0], bounds[1], bounds[2],
bounds[3], zoom_level)
new_rows = []
for tile in tiles:
new_row = row.copy()
new_geometry = box(*mercantile.bounds(tile))
if new_geometry.intersects(input_geometry):
new_row[geometry_name] = new_geometry
new_row['quadkey'] = mercantile.quadkey(tile)
new_rows.append(new_row)
dfs.append(DataFrame(new_rows))
df = concat(dfs).reset_index(drop=True)
return GeoDataFrame(df, geometry=geometry_name, crs='epsg:4326')
def cl_post_prediction(self, payload: Dict[str, Any], tiles: List[Tile],
prediction_id: str,
inferences: List[str]) -> Dict[str, Any]:
payload = json.dumps(payload)
r = requests.post(self.prediction_endpoint + ":predict", data=payload)
r.raise_for_status()
preds = r.json()["predictions"]
pred_list = []
for i in range(len(tiles)):
pred_dict = {}
for j in range(len(preds[i])):
pred_dict[inferences[j]] = preds[i][j]
pred_list.append({
"quadkey":
mercantile.quadkey(tiles[i].x, tiles[i].y, tiles[i].z),
"predictions":
pred_dict,
"prediction_id":
prediction_id
})
return {"predictionId": prediction_id, "predictions": pred_list}
def quadkey(ctx, input):
"""Takes a [x, y, z] tile or a quadkey as input and writes a
quadkey or a [x, y, z] tile to stdout, respectively.
$ echo "[486, 332, 10]" | mercantile quadkey
Output:
0313102310
$ echo "0313102310" | mercantile quadkey
Output:
[486, 332, 10]
"""
src = normalize_input(input)
try:
for line in iter_lines(src):
if line[0] == '[':
tile = json.loads(line)[:3]
output = mercantile.quadkey(tile)
else:
tile = mercantile.quadkey_to_tile(line)
output = json.dumps(tile)
click.echo(output)
except ValueError:
raise click.BadParameter(
"{0}".format(input), param=input, param_hint='input')
def quadkey(ctx, input):
"""Takes [x, y, z] tiles or quadkeys as input and writes
quadkeys or a [x, y, z] tiles to stdout, respectively.
Input may be a compact newline-delimited sequences of JSON or
a pretty-printed ASCII RS-delimited sequence of JSON (like
https://tools.ietf.org/html/rfc8142 and
https://tools.ietf.org/html/rfc7159).
Examples:
\b
echo "[486, 332, 10]" | mercantile quadkey
0313102310
\b
echo "0313102310" | mercantile quadkey
[486, 332, 10]
"""
src = normalize_input(input)
try:
for line in iter_lines(src):
if line[0] == "[":
tile = json.loads(line)[:3]
output = mercantile.quadkey(tile)
else:
tile = mercantile.quadkey_to_tile(line)
output = json.dumps(tile)
click.echo(output)
except mercantile.QuadKeyError:
raise click.BadParameter("{0}".format(input),
param=input,
param_hint="input")
def get_assets(url: str, x: int, y: int, z: int) -> Tuple[str]:
"""Get assets."""
mosaic_def = fetch_mosaic_definition(url)
min_zoom = mosaic_def["minzoom"]
max_zoom = mosaic_def["maxzoom"]
if z > max_zoom or z < min_zoom:
return [] # return empty asset
mercator_tile = mercantile.Tile(x=x, y=y, z=z)
quadkey_zoom = mosaic_def.get("quadkey_zoom", min_zoom) # 0.0.2
# get parent
if mercator_tile.z > quadkey_zoom:
depth = mercator_tile.z - quadkey_zoom
for i in range(depth):
mercator_tile = mercantile.parent(mercator_tile)
quadkey = [mercantile.quadkey(*mercator_tile)]
# get child
elif mercator_tile.z < quadkey_zoom:
depth = quadkey_zoom - mercator_tile.z
mercator_tiles = [mercator_tile]
for i in range(depth):
mercator_tiles = sum([mercantile.children(t) for t in mercator_tiles], [])
mercator_tiles = list(filter(lambda t: t.z == quadkey_zoom, mercator_tiles))
quadkey = [mercantile.quadkey(*tile) for tile in mercator_tiles]
else:
quadkey = [mercantile.quadkey(*mercator_tile)]
assets = list(
itertools.chain.from_iterable(
[mosaic_def["tiles"].get(qk, []) for qk in quadkey]
)
)
# check if we have a mosaic in the url (.json/.gz)
return list(
itertools.chain.from_iterable(
[
get_assets(asset, x, y, z)
if os.path.splitext(asset)[1] in [".json", ".gz"]
else [asset]
for asset in assets
]
)
)
def quadkeys_to_poly(quadkeys):
quadkeys = sorted(set(quadkeys))
tiles = [mercantile.quadkey_to_tile(qk) for qk in quadkeys]
tiles = mercantile.simplify(tiles)
quadkeys = [mercantile.quadkey(t) for t in tiles]
polys = quadkeys_to_polys(quadkeys)
poly = shapely.ops.unary_union(polys)
return poly
def bbox_to_quadkeys(bbox: list, zoom: int):
""" Find all quadkeys in a bbox """
tiles = mercantile.tiles(bbox[0], bbox[1], bbox[2], bbox[3], int(zoom))
quadkeys = []
for tile in tiles:
quadkeys.append(mercantile.quadkey(tile))
return quadkeys
def create_tiles_gdf(bounds: List[float],
quadkey_zoom: int) -> gpd.GeoDataFrame:
"""Create GeoDataFrame of all tiles within bounds at quadkey_zoom
"""
features = [
mercantile.feature(tile, props={'quadkey': mercantile.quadkey(tile)})
for tile in mercantile.tiles(*bounds, quadkey_zoom)
]
return gpd.GeoDataFrame.from_features(features, crs='EPSG:4326')
def __init__(self, *tile):
if len(tile) == 1:
tile = tile[0]
else:
tile = Tile(*tile)
quadkey = mercantile.quadkey(tile)
self.url_fmt = f'http://t0.tiles.virtualearth.net/tiles/a{quadkey}.jpeg?g=854&mkt=en-US&token='
def get_tile(self, tile):
#========================
surface = skia.Surface(*self.__tile_size) ## In pixels...
canvas = surface.getCanvas()
canvas.clear(skia.Color4f(0xFFFFFFFF))
canvas.translate(self.__pixel_offset[0] + (self.__tile_origin[0] - tile.x)*self.__tile_size[0],
self.__pixel_offset[1] + (self.__tile_origin[1] - tile.y)*self.__tile_size[1])
quadkey = mercantile.quadkey(tile)
self.__svg_drawing.draw_element(canvas, self.__tile_bboxes.get(quadkey))
image = surface.makeImageSnapshot()
return image.toarray(colorType=skia.kBGRA_8888_ColorType)
def find_quadkeys(mercator_tile: mercantile.Tile,
quadkey_zoom: int) -> List[str]:
"""
Find quadkeys at desired zoom for tile
Attributes
----------
mercator_tile: mercantile.Tile
Input tile to use when searching for quadkeys
quadkey_zoom: int
Zoom level
Returns
-------
list
List[str] of quadkeys
"""
# get parent
if mercator_tile.z > quadkey_zoom:
depth = mercator_tile.z - quadkey_zoom
for i in range(depth):
mercator_tile = mercantile.parent(mercator_tile)
return [mercantile.quadkey(*mercator_tile)]
# get child
elif mercator_tile.z < quadkey_zoom:
depth = quadkey_zoom - mercator_tile.z
mercator_tiles = [mercator_tile]
for i in range(depth):
mercator_tiles = sum(
[mercantile.children(t) for t in mercator_tiles], [])
mercator_tiles = list(
filter(lambda t: t.z == quadkey_zoom, mercator_tiles))
return [mercantile.quadkey(*tile) for tile in mercator_tiles]
else:
return [mercantile.quadkey(*mercator_tile)]
def __init__(self, raster_layer, tile_set):
self.__svg = etree.parse(raster_layer.source_data).getroot()
if 'viewBox' in self.__svg.attrib:
self.__size = tuple(
float(x) for x in self.__svg.attrib['viewBox'].split()[2:])
else:
self.__size = (length_as_pixels(self.__svg.attrib['width']),
length_as_pixels(self.__svg.attrib['height']))
self.__scaling = (tile_set.pixel_rect.width / self.__size[0],
tile_set.pixel_rect.height / self.__size[1])
self.__definitions = DefinitionStore()
defs = self.__svg.find(SVG_NS('defs'))
if defs is not None:
self.__definitions.add_definitions(defs)
self.__style_matcher = StyleMatcher(self.__svg.find(SVG_NS('style')))
self.__first_scan = True
# Transform from SVG pixels to tile pixels
transform = Transform([[self.__scaling[0], 0.0, 0.0],
[0.0, self.__scaling[1], 0.0], [0.0, 0.0, 1.0]])
self.__path_list = []
self.__draw_svg(transform, self.__path_list)
# Transform from SVG pixels to world coordinates
self.__image_to_world = (Transform([
[WORLD_METRES_PER_PIXEL / self.__scaling[0], 0, 0],
[0, WORLD_METRES_PER_PIXEL / self.__scaling[1], 0], [0, 0, 1]
]) @ np.array([[1, 0, -self.__scaling[0] * self.__size[0] / 2.0],
[0, -1, self.__scaling[1] * self.__size[1] / 2.0],
[0, 0, 1.0]]))
self.__tile_size = tile_set.tile_size
self.__tile_origin = tile_set.start_coords
self.__pixel_offset = tuple(tile_set.pixel_rect)[0:2]
path_bounding_boxes = [(path, paint,
shapely.geometry.box(*tuple(path.getBounds())))
for (path, paint) in self.__path_list]
self.__tile_paths = {}
for tile in tile_set:
tile_set.tile_coords_to_pixels.transform_point((tile.x, tile.y))
x0 = (tile.x - self.__tile_origin[0]
) * self.__tile_size[0] - self.__pixel_offset[0]
y0 = (tile.y - self.__tile_origin[1]
) * self.__tile_size[1] - self.__pixel_offset[1]
tile_bbox = shapely.prepared.prep(
shapely.geometry.box(x0, y0, x0 + self.__tile_size[0],
y0 + self.__tile_size[0]))
self.__tile_paths[mercantile.quadkey(tile)] = list(
filter(lambda ppb: tile_bbox.intersects(ppb[2]),
path_bounding_boxes))
def children(quadkeys, levels=1):
if not type(quadkeys) is list:
quadkeys = [
quadkeys,
]
for level in range(levels):
childrenKeys = []
for qk in quadkeys:
childrenKeys.extend([
mercantile.quadkey(t) \
for t in mercantile.children(mercantile.quadkey_to_tile(qk))
])
quadkeys = childrenKeys
return quadkeys
def get_tile(self, tile):
#========================
surface = skia.Surface(*self.__tile_size)
canvas = surface.getCanvas()
canvas.translate(
self.__pixel_offset[0] +
(self.__tile_origin[0] - tile.x) * self.__tile_size[0],
self.__pixel_offset[1] +
(self.__tile_origin[1] - tile.y) * self.__tile_size[1])
quadkey = mercantile.quadkey(tile)
for path, paint, bbox in self.__tile_paths.get(quadkey, []):
canvas.drawPath(path, paint)
image = surface.makeImageSnapshot()
return image.toarray(colorType=skia.kBGRA_8888_ColorType)
def od_post_prediction(self, payload: str, chips: List[dict], prediction_id: str) -> Dict[str, Any]:
pred_list = [];
for i in range(len(chips)):
r = requests.post(self.prediction_endpoint + ":predict", data=json.dumps({
"instances": [ payload["instances"][i] ]
}))
r.raise_for_status()
# We only post a single chip for od detection
preds = r.json()["predictions"][0]
if preds["num_detections"] == 0.0:
continue
# Create lists of num_detections length
scores = preds['detection_scores'][:int(preds["num_detections"])]
bboxes = preds['detection_boxes'][:int(preds["num_detections"])]
bboxes_256 = []
for bbox in bboxes:
bboxes_256.append([c * 256 for c in bbox])
for j in range(len(bboxes_256)):
bbox = geojson.Feature(
geometry=self.tf_bbox_geo(bboxes_256[j], chips[i].get('bounds')),
properties={}
).geometry
score = preds["detection_scores"][j]
body = {
"geom": bbox,
"predictions": {
"default": score
},
"prediction_id": prediction_id
}
if chips[i].get('x') is not None and chips[i].get('y') is not None and chips[i].get('z') is not None:
body['quadkey'] = mercantile.quadkey(chips[i].get('x'), chips[i].get('y'), chips[i].get('z'))
pred_list.append(body)
return {
"predictionId": prediction_id,
"predictions": pred_list
}
def od_post_prediction(self, payload: str, tiles: List[Tile],
prediction_id: str) -> Dict[str, Any]:
pred_list = []
for i in range(len(tiles)):
r = requests.post(self.prediction_endpoint + ":predict",
data=json.dumps(
{"instances": [payload["instances"][i]]}))
r.raise_for_status()
# We only post a single chip for od detection
preds = r.json()["predictions"][0]
if preds["num_detections"] == 0.0:
continue
# Create lists of num_detections length
scores = preds['detection_scores'][:int(preds["num_detections"])]
bboxes = preds['detection_boxes'][:int(preds["num_detections"])]
bboxes_256 = []
for bbox in bboxes:
bboxes_256.append([c * 256 for c in bbox])
print("BOUND: " + str(len(bboxes_256)) + " for " +
str(tiles[i].x) + "/" + str(tiles[i].y) + "/" +
str(tiles[i].z))
for j in range(len(bboxes_256)):
bbox = geojson.Feature(geometry=self.tf_bbox_geo(
bboxes_256[j], tiles[i]),
properties={}).geometry
score = preds["detection_scores"][j]
pred_list.append({
"quadkey":
mercantile.quadkey(tiles[i].x, tiles[i].y, tiles[i].z),
"quadkey_geom":
bbox,
"predictions": {
"default": score
},
"prediction_id":
prediction_id
})
return {"predictionId": prediction_id, "predictions": pred_list}
def __init__(self, xtile, ytile, zoom, uri=None):
super(Syncher, self).__init__()
self.uri = uri or get_uri(xtile, ytile, zoom)
self.tile = {'x': xtile, 'y': ytile, 'z': zoom}
tile_bounds = mc.bounds(mc.quadkey_to_tile(mc.quadkey(xtile, ytile, zoom)))
keys = ('w', 's', 'e', 'n',)
self.bbox = dict(zip(keys, map(str, (
tile_bounds.west,
tile_bounds.south,
tile_bounds.east,
tile_bounds.north,
)))) # minx, miny, maxx, maxy
self.base_query = {
'query': [[{"k": "qwertyuiop", "modv": "not", "regv": "."}]],
'bbox': self.bbox,
'gtypes': ['node', 'way', 'relation'],
}
def __init__(self, raster_layer, tile_set):
self.__bbox = shapely.geometry.box(*extent_to_bounds(raster_layer.extent))
self.__svg = etree.parse(raster_layer.source_data).getroot()
self.__source = raster_layer.source_params.get('source')
if 'viewBox' in self.__svg.attrib:
self.__size = tuple(float(x)
for x in self.__svg.attrib['viewBox'].split()[2:])
else:
self.__size = (length_as_pixels(self.__svg.attrib['width']),
length_as_pixels(self.__svg.attrib['height']))
self.__scaling = (tile_set.pixel_rect.width/self.__size[0],
tile_set.pixel_rect.height/self.__size[1])
self.__definitions = DefinitionStore()
self.__style_matcher = StyleMatcher(self.__svg.find(SVG_NS('style')))
self.__clip_paths = ObjectStore()
# Transform from SVG pixels to tile pixels
svg_to_tile_transform = Transform([[self.__scaling[0], 0.0, 0.0],
[ 0.0, self.__scaling[1], 0.0],
[ 0.0, 0.0, 1.0]])
self.__svg_drawing = self.__draw_svg(svg_to_tile_transform)
# Transform from SVG pixels to world coordinates
self.__image_to_world = (Transform([
[WORLD_METRES_PER_PIXEL/self.__scaling[0], 0, 0],
[ 0, WORLD_METRES_PER_PIXEL/self.__scaling[1], 0],
[ 0, 0, 1]])
@np.array([[1, 0, -self.__scaling[0]*self.__size[0]/2.0],
[0, -1, self.__scaling[1]*self.__size[1]/2.0],
[0, 0, 1.0]]))
self.__tile_size = tile_set.tile_size
self.__tile_origin = tile_set.start_coords
self.__pixel_offset = tuple(tile_set.pixel_rect)[0:2]
self.__tile_bboxes = {}
for tile in tile_set:
tile_set.tile_coords_to_pixels.transform_point((tile.x, tile.y))
x0 = (tile.x - self.__tile_origin[0])*self.__tile_size[0] - self.__pixel_offset[0]
y0 = (tile.y - self.__tile_origin[1])*self.__tile_size[1] - self.__pixel_offset[1]
tile_bbox = shapely.geometry.box(x0, y0,
x0 + self.__tile_size[0],
y0 + self.__tile_size[0])
self.__tile_bboxes[mercantile.quadkey(tile)] = tile_bbox
def save_to_db(self, tiles:List[Tile], results:List[Any], result_wrapper:Optional[Callable]=None) -> None:
db = urlparse(self.db)
conn = pg8000.connect(
user=db.username,
password=db.password,
host=db.hostname,
database=db.path[1:],
port=db.port
)
cursor = conn.cursor()
for i, output in enumerate(results):
quadkey = quadkey(tiles[i])
# centroid = db.Column(Geometry('POINT', srid=4326))
predictions = pg8000.PGJsonb(output)
cursor.execute("INSERT INTO mlenabler VALUES (null, %s, %s, %s) ON CONFLICT (id) DO UPDATE SET output = %s", (self.prediction_id, quadkey, predictions, predictions))
conn.commit()
conn.close()
def soil_hi():
with open('E:/project_use/geodata/soil_liq_hi.txt', 'r',
encoding='utf-8') as f:
t = json.load(f)
'''把所有的物件只挑要的撈出來，另存成item'''
item1 = []
for iii, it in enumerate(t['features']):
area = it['properties']['area']
grade = it['properties']['分級']
codi = []
for jjj, it1 in enumerate(it['geometry']['coordinates']):
for kkk, it2 in enumerate(it1):
long = it2[0]
lat = it2[1]
codi.append((long, lat))
js = {'area': area, 'grade': grade, 'coodinates': codi}
item1.append(js)
# print(item)
'''將經緯度轉換成quadkey值並存進原本的dict'''
for mmm, each in enumerate(item1):
each_tiles = []
for nnn, each_pt in enumerate(each['coodinates']):
zoom_num = 16
aaa = mercantile.tile(each_pt[0], each_pt[1], zoom_num)
each_tiles.append(aaa)
# print(list(set(each_tiles)))
each_tile = list(set(each_tiles))
each_quad = []
for o in range(len(each_tile)):
b = mercantile.quadkey(each_tile[o])
each_quad.append(b)
each['quad'] = each_quad
'''把最終高潛勢的quadkey值append成一個list'''
level_hi_quad = []
for ppp in range(len(item1)):
each_quads = item1[ppp]['quad']
for rrr in range(len(each_quads)):
ccc = each_quads[rrr]
level_hi_quad.append(ccc)
set(level_hi_quad)
return list(set(level_hi_quad))
def missing_quadkeys(mosaic: Dict,
shp_path: str,
bounds: List[float] = None,
simplify: bool = True) -> Dict:
"""Find quadkeys over land missing from mosaic
Args:
- mosaic: mosaic definition
- shp_path: path to Natural Earth shapefile of land boundaries
- bounds: force given bounds
- simplify: reduce size of the tileset as much as possible by merging leaves into parents
Returns:
- GeoJSON FeatureCollection of missing tiles
"""
bounds = bounds or mosaic['bounds']
top_tile = mercantile.bounding_tile(*bounds)
gdf = gpd.read_file(shp_path)
quadkey_zoom = mosaic.get('quadkey_zoom', mosaic['minzoom'])
# Remove null island
# Keep the landmasses that are visible at given zoom
gdf = gdf[gdf['max_zoom'] <= quadkey_zoom]
land_tiles = find_child_land_tiles(top_tile, gdf, quadkey_zoom)
quadkeys = {mercantile.quadkey(tile) for tile in land_tiles}
mosaic_quadkeys = set(mosaic['tiles'].keys())
not_in_mosaic = quadkeys.difference(mosaic_quadkeys)
not_in_mosaic = [mercantile.quadkey_to_tile(qk) for qk in not_in_mosaic]
if simplify:
not_in_mosaic = mercantile.simplify(not_in_mosaic)
features = [mercantile.feature(tile) for tile in not_in_mosaic]
return {'type': 'FeatureCollection', 'features': features}
def lnglat_to_Num(lon, lat, zoom):
try:
lat_deg = float(lat)
lon_deg = float(lon)
lat_rad = math.radians(lat_deg)
n = 2.0**zoom
xtile = int((lon_deg + 180.0) / 360.0 * n)
ytile = int(
(1.0 - math.log(math.tan(lat_rad) +
(1 / math.cos(lat_rad))) / math.pi) / 2.0 * n)
qk = mercantile.quadkey(xtile, ytile, zoom)
number = 0
for i, digit in enumerate(qk):
number |= int(digit)
if i != len(qk) - 1:
number = number << 2
return number
except ValueError, e:
print "error", e
return None
def _create_mosaic(
cls,
features: Sequence[Dict],
minzoom: int,
maxzoom: int,
quadkey_zoom: Optional[int] = None,
accessor: Callable[[Dict], str] = default_accessor,
asset_filter: Callable = default_filter,
version: str = "0.0.2",
quiet: bool = True,
**kwargs,
):
"""Create mosaic definition content.
Attributes:
features (list): List of GeoJSON features.
minzoom (int): Force mosaic min-zoom.
maxzoom (int): Force mosaic max-zoom.
quadkey_zoom (int): Force mosaic quadkey zoom (optional).
accessor (callable): Function called on each feature to get its identifier (default is feature["properties"]["path"]).
asset_filter (callable): Function to filter features.
version (str): mosaicJSON definition version (default: 0.0.2).
quiet (bool): Mask processing steps (default is True).
kwargs (any): Options forwarded to `asset_filter`
Returns:
mosaic_definition (MosaicJSON): Mosaic definition.
Examples:
>>> MosaicJSON._create_mosaic([], 12, 14)
"""
quadkey_zoom = quadkey_zoom or minzoom
if not quiet:
click.echo(f"Get quadkey list for zoom: {quadkey_zoom}", err=True)
# If Pygeos throws an error, fall back to non-vectorized operation
# Ref: https://github.com/developmentseed/cogeo-mosaic/issues/81
try:
dataset_geoms = polygons(
[feat["geometry"]["coordinates"][0] for feat in features]
)
except TypeError:
dataset_geoms = [
polygons(feat["geometry"]["coordinates"][0]) for feat in features
]
bounds = tuple(total_bounds(dataset_geoms))
tiles = burntiles.burn(features, quadkey_zoom)
tiles = [mercantile.Tile(*tile) for tile in tiles]
mosaic_definition: Dict[str, Any] = dict(
mosaicjson=version,
minzoom=minzoom,
maxzoom=maxzoom,
quadkey_zoom=quadkey_zoom,
bounds=bounds,
center=((bounds[0] + bounds[2]) / 2, (bounds[1] + bounds[3]) / 2, minzoom),
tiles={},
version="1.0.0",
)
if not quiet:
click.echo("Feed Quadkey index", err=True)
# Create tree and find assets that overlap each tile
tree = STRtree(dataset_geoms)
fout = os.devnull if quiet else sys.stderr
with click.progressbar( # type: ignore
tiles, file=fout, show_percent=True, label="Iterate over quadkeys"
) as bar:
for tile in bar:
quadkey = mercantile.quadkey(tile)
tile_geom = polygons(
mercantile.feature(tile)["geometry"]["coordinates"][0]
)
# Find intersections from rtree
intersections_idx = sorted(
tree.query(tile_geom, predicate="intersects")
)
if len(intersections_idx) == 0:
continue
intersect_dataset, intersect_geoms = zip(
*[(features[idx], dataset_geoms[idx]) for idx in intersections_idx]
)
dataset = asset_filter(
tile, intersect_dataset, intersect_geoms, **kwargs
)
if dataset:
mosaic_definition["tiles"][quadkey] = [accessor(f) for f in dataset]
return cls(**mosaic_definition)
def stac_to_mosaicJSON(
query: Dict,
minzoom: int = 7,
maxzoom: int = 12,
optimized_selection: bool = True,
maximum_items_per_tile: int = 20,
stac_collection_limit: int = 500,
seasons: Tuple = ["spring", "summer", "autumn", "winter"],
stac_url: str = os.environ.get("SATAPI_URL",
"https://sat-api.developmentseed.org"),
) -> Dict:
"""
Create a mosaicJSON from a stac request.
Attributes
----------
query : str
sat-api query.
minzoom : int, optional, (default: 7)
Mosaic Min Zoom.
maxzoom : int, optional (default: 12)
Mosaic Max Zoom.
optimized_selection : bool, optional (default: true)
Limit one Path-Row scene per quadkey.
maximum_items_per_tile : int, optional (default: 20)
Limit number of scene per quadkey. Use 0 to use all items.
stac_collection_limit : int, optional (default: None)
Limits the number of items returned by sat-api
stac_url : str, optional (default: from ENV)
Returns
-------
out : dict
MosaicJSON definition.
"""
if stac_collection_limit:
query.update(limit=stac_collection_limit)
logger.debug(json.dumps(query))
def fetch_sat_api(query):
headers = {
"Content-Type": "application/json",
"Accept-Encoding": "gzip",
"Accept": "application/geo+json",
}
url = f"{stac_url}/stac/search"
data = requests.post(url, headers=headers, json=query).json()
error = data.get("message", "")
if error:
raise Exception(f"SAT-API failed and returned: {error}")
meta = data.get("meta", {})
if not meta.get("found"):
return []
logger.debug(json.dumps(meta))
features = data["features"]
if data["links"]:
curr_page = int(meta["page"])
query["page"] = curr_page + 1
query["limit"] = meta["limit"]
features = list(itertools.chain(features, fetch_sat_api(query)))
return features
features = fetch_sat_api(query)
if not features:
raise Exception(f"No asset found for query '{json.dumps(query)}'")
logger.debug(f"Found: {len(features)} scenes")
features = list(
filter(
lambda x: _get_season(x["properties"]["datetime"],
max(x["bbox"][1], x["bbox"][3])) in seasons,
features,
))
if optimized_selection:
dataset = []
prs = []
for item in features:
pr = item["properties"]["eo:column"] + "-" + item["properties"][
"eo:row"]
if pr not in prs:
prs.append(pr)
dataset.append(item)
else:
dataset = features
if query.get("bbox"):
bounds = query["bbox"]
else:
bounds = burntiles.find_extrema(dataset)
for i in range(len(dataset)):
dataset[i]["geometry"] = shape(dataset[i]["geometry"])
tiles = burntiles.burn([bbox_to_geojson(bounds)], minzoom)
tiles = list(set(["{2}-{0}-{1}".format(*tile.tolist()) for tile in tiles]))
logger.debug(f"Number tiles: {len(tiles)}")
mosaic_definition = dict(
mosaicjson="0.0.1",
minzoom=minzoom,
maxzoom=maxzoom,
bounds=bounds,
center=[(bounds[0] + bounds[2]) / 2, (bounds[1] + bounds[3]) / 2,
minzoom],
tiles={},
)
for tile in tiles:
z, x, y = list(map(int, tile.split("-")))
tile = mercantile.Tile(x=x, y=y, z=z)
quadkey = mercantile.quadkey(*tile)
geometry = box(*mercantile.bounds(tile))
intersect_dataset = list(
filter(lambda x: geometry.intersects(x["geometry"]), dataset))
if len(intersect_dataset):
# We limit the item per quadkey to 20
if maximum_items_per_tile:
intersect_dataset = intersect_dataset[0:maximum_items_per_tile]
mosaic_definition["tiles"][quadkey] = [
scene["properties"]["landsat:product_id"]
for scene in intersect_dataset
]
return mosaic_definition
def point_to_polygon(point, zoom):
tile = mercantile.tile(*np.array(point), zoom)
quadkey = mercantile.quadkey(tile)
poly = quadkey_to_poly(quadkey)
return poly
def get_quadkeys(totalBounds, zoom):
allTiles = mercantile.tiles(*totalBounds, zoom)
for tile in allTiles:
yield mercantile.quadkey(tile)
def test_quadkey():
tile = mercantile.Tile(486, 332, 10)
expected = "0313102310"
assert mercantile.quadkey(tile) == expected
def do_GET(self):
url = urlparse(self.path)
if url.path == '/tile':
query_components = parse_qs(urlparse(self.path).query)
dataset = query_components["dataset"][0]
level = query_components["level"][0]
x = query_components["x"][0]
y = query_components["y"][0]
time_from = transToStamp(query_components["time_from"][0])
time_to = transToStamp(query_components["time_to"][0])
# start = time.time()
tile_quadkey = mercantile.quadkey(int(x), int(y), int(level))
tile_id = quadkey_to_num(tile_quadkey)
print tile_id, str(time_from), str(time_to)
jpype.attachThreadToJVM()
hbase_response = cp.spatialSum("nycTaxi", tile_id, str(time_from),
str(time_to))
print hbase_response
# end = time.time()
# print "query_time" + ": " + str(end - start)
#
#
# q_time1.append(end - start)
self.send_response(200)
self.send_header('Content-type', 'application/json')
self.send_header('Access-Control-Allow-Origin', '*')
self.end_headers()
self.wfile.write(hbase_response)
# if len(q_time1) == 20:
# print "hundred"
# plt.plot(range(len(q_time1)), q_time1)
# plt.ylabel('tile query time')
# plt.axis([1, 20, 0, 2])
# print float(sum(q_time1)) / len(q_time1)
# plt.show()
return
if url.path == '/time_series':
query_components = parse_qs(urlparse(self.path).query)
dataset = query_components["dataset"][0]
level = query_components["level"][0]
bounds = query_components["bounds"][0]
bounds = bounds.split(",")
time_from = transToStamp(query_components["time_from"][0])
time_to = transToStamp(query_components["time_to"][0])
start = time.time()
new_bounds = check_bounds(bounds)
tiles = mercantile.tiles(new_bounds[0],new_bounds[1],new_bounds[2], \
new_bounds[3], [int(level), ])
tile_numbers = []
for tile in list(tiles):
t_quadkey = mercantile.quadkey(tile)
t_num = quadkey_to_num(t_quadkey)
tile_numbers.append(t_num)
tile_numbers = ' '.join(str(x) for x in tile_numbers)
jpype.attachThreadToJVM()
res = cp.timeSeriesCount(dataset, tile_numbers, str(time_from),
str(time_to))
end = time.time()
print "query_time" + ": " + str(end - start)
# q_time2.append(end - start)
self.send_response(200)
self.send_header('Content-type', 'application/json')
self.send_header('Access-Control-Allow-Origin', '*')
self.end_headers()
self.wfile.write(res)
# if len(q_time2) == 20:
# print "hundred"
# plt.plot(range(len(q_time2)), q_time2)
# plt.ylabel('timeseries query time')
# plt.axis([1, 20, 0, 1])
# print float(sum(q_time2)) / len(q_time2)
# plt.show()
return
def _create_mosaic(
cls,
features: Sequence[Dict],
minzoom: int,
maxzoom: int,
quadkey_zoom: Optional[int] = None,
accessor: Callable[[Dict], str] = default_accessor,
asset_filter: Callable = default_filter,
version: str = "0.0.2",
quiet: bool = True,
**kwargs,
):
"""
Create mosaic definition content.
Attributes
----------
features : List, required
List of GeoJSON features.
minzoom: int, required
Force mosaic min-zoom.
maxzoom: int, required
Force mosaic max-zoom.
quadkey_zoom: int, optional
Force mosaic quadkey zoom.
accessor: callable, required
Function called on each feature to get its identifier (default is feature["properties"]["path"]).
asset_filter: callable, required
Function to filter features.
version: str, optional
mosaicJSON definition version (default: 0.0.2).
quiet: bool, optional (default: True)
Mask processing steps.
kwargs: any
Options forwarded to `asset_filter`
Returns
-------
mosaic_definition : MosaicJSON
Mosaic definition.
"""
quadkey_zoom = quadkey_zoom or minzoom
if not quiet:
click.echo(f"Get quadkey list for zoom: {quadkey_zoom}", err=True)
# Find dataset geometries
dataset_geoms = polygons(
[feat["geometry"]["coordinates"][0] for feat in features])
bounds = list(total_bounds(dataset_geoms))
tiles = burntiles.burn(features, quadkey_zoom)
tiles = [mercantile.Tile(*tile) for tile in tiles]
mosaic_definition: Dict[str, Any] = dict(
mosaicjson=version,
minzoom=minzoom,
maxzoom=maxzoom,
quadkey_zoom=quadkey_zoom,
bounds=bounds,
center=((bounds[0] + bounds[2]) / 2, (bounds[1] + bounds[3]) / 2,
minzoom),
tiles={},
version="1.0.0",
)
if not quiet:
click.echo(f"Feed Quadkey index", err=True)
# Create tree and find assets that overlap each tile
tree = STRtree(dataset_geoms)
for tile in tiles:
quadkey = mercantile.quadkey(tile)
tile_geom = polygons(
mercantile.feature(tile)["geometry"]["coordinates"][0])
# Find intersections from rtree
intersections_idx = sorted(
tree.query(tile_geom, predicate="intersects"))
if len(intersections_idx) == 0:
continue
intersect_dataset, intersect_geoms = zip(
*[(features[idx], dataset_geoms[idx])
for idx in intersections_idx])
dataset = asset_filter(tile, intersect_dataset, intersect_geoms,
**kwargs)
if dataset:
mosaic_definition["tiles"][quadkey] = [
accessor(f) for f in dataset
]
return cls(**mosaic_definition)