def union(inputtiles, parsenames):
tiles = sutils.tile_parser(inputtiles, parsenames)
xmin, xmax, ymin, ymax = sutils.get_range(tiles)
zoom = sutils.get_zoom(tiles)
# make an array of shape (xrange + 3, yrange + 3)
burn = sutils.burnXYZs(tiles, xmin, xmax, ymin, ymax, 0)
nw = mercantile.xy(*mercantile.ul(xmin, ymin, zoom))
se = mercantile.xy(*mercantile.ul(xmax + 1, ymax + 1, zoom))
aff = Affine(((se[0] - nw[0]) / float(xmax - xmin + 1)), 0.0, nw[0],
0.0, -((nw[1] - se[1]) / float(ymax - ymin + 1)), nw[1])
unprojecter = sutils.Unprojecter()
unionedTiles = [
{
'geometry': unprojecter.unproject(feature),
'properties': {},
'type': 'Feature'
} for feature, shapes in features.shapes(np.asarray(np.flipud(np.rot90(burn)).astype(np.uint8), order='C'), transform=aff) if shapes == 1
]
return unionedTiles
def findedges(inputtiles, parsenames):
tiles = sutils.tile_parser(inputtiles, parsenames)
xmin, xmax, ymin, ymax = sutils.get_range(tiles)
zoom = sutils.get_zoom(tiles)
# zoom = inputtiles[0, -1]
# make an array of shape (xrange + 3, yrange + 3)
burn = sutils.burnXYZs(tiles, xmin, xmax, ymin, ymax)
# Create the indixes for rolling
idxs = sutils.get_idx()
# Using the indices to roll + stack the array, find the minimum along the rolled / stacked axis
xys_edge = (np.min(np.dstack((
np.roll(np.roll(burn, i[0], 0), i[1], 1) for i in idxs
)), axis=2) - burn)
# Set missed non-tiles to False
xys_edge[burn == False] = False
# Recreate the tile xyzs, and add the min vals
xys_edge = np.dstack(np.where(xys_edge))[0]
xys_edge[:, 0] += xmin - 1
xys_edge[:, 1] += ymin - 1
# Return the edge array
return np.append(xys_edge, np.zeros((xys_edge.shape[0], 1), dtype=np.uint8) + zoom, axis=1)
def findedges(inputtiles, parsenames):
tiles = sutils.tile_parser(inputtiles, parsenames)
xmin, xmax, ymin, ymax = sutils.get_range(tiles)
zoom = sutils.get_zoom(tiles)
# zoom = inputtiles[0, -1]
# make an array of shape (xrange + 3, yrange + 3)
burn = sutils.burnXYZs(tiles, xmin, xmax, ymin, ymax)
# Create the indixes for rolling
idxs = sutils.get_idx()
# Using the indices to roll + stack the array, find the minimum along the rolled / stacked axis
xys_edge = (np.min(np.dstack(
(np.roll(np.roll(burn, i[0], 0), i[1], 1) for i in idxs)),
axis=2) - burn)
# Set missed non-tiles to False
xys_edge[burn == False] = False
# Recreate the tile xyzs, and add the min vals
xys_edge = np.dstack(np.where(xys_edge))[0]
xys_edge[:, 0] += xmin - 1
xys_edge[:, 1] += ymin - 1
# Return the edge array
return np.append(xys_edge,
np.zeros((xys_edge.shape[0], 1), dtype=np.uint8) + zoom,
axis=1)
def union(inputtiles, parsenames):
tiles = sutils.tile_parser(inputtiles, parsenames)
xmin, xmax, ymin, ymax = sutils.get_range(tiles)
zoom = sutils.get_zoom(tiles)
# make an array of shape (xrange + 3, yrange + 3)
burn = sutils.burnXYZs(tiles, xmin, xmax, ymin, ymax, 0)
nw = mercantile.xy(*mercantile.ul(xmin, ymin, zoom))
se = mercantile.xy(*mercantile.ul(xmax + 1, ymax + 1, zoom))
aff = Affine(
((se[0] - nw[0]) / float(xmax - xmin + 1)),
0.0,
nw[0],
0.0,
-((nw[1] - se[1]) / float(ymax - ymin + 1)),
nw[1],
)
unprojecter = sutils.Unprojecter()
unionedTiles = [
{
"geometry": unprojecter.unproject(feature),
"properties": {},
"type": "Feature",
}
for feature, shapes in features.shapes(
np.asarray(np.flipud(np.rot90(burn)).astype(np.uint8), order="C"),
transform=aff,
)
if shapes == 1
]
return unionedTiles