def get_valid_versions(self, group_by=None, **kwargs):
if 'layers' not in kwargs:
return []
else:
p = Pyramid.objects(name=layers[0]).first()
qs = Tile.objects(pyramid=p)
if 'filter' in kwargs:
qs = qs.filter(**kwargs['filter'])
return qs.distinct('version')
def get_valid_times(self, **kwargs):
if 'layers' not in kwargs:
return []
else:
p = Pyramid.objects(name=layers[0]).first()
qs = Tile.objects(pyramid=p)
if 'filter' in kwargs:
qs = qs.filter(**kwargs['filter'])
return qs.distinct('time')
def get_valid_versions(self, group_by=None, **kwargs):
if "layers" not in kwargs:
return []
else:
p = Pyramid.objects(name=layers[0]).first()
qs = Tile.objects(pyramid=p)
if "filter" in kwargs:
qs = qs.filter(**kwargs["filter"])
return qs.distinct("version")
def get_valid_times(self, **kwargs):
if "layers" not in kwargs:
return []
else:
p = Pyramid.objects(name=layers[0]).first()
qs = Tile.objects(pyramid=p)
if "filter" in kwargs:
qs = qs.filter(**kwargs["filter"])
return qs.distinct("time")
def get_2d_dataset(self,
layers,
srs,
bbox,
width,
height,
styles=None,
bgcolor=None,
transparent=False,
time=None,
elevation=None,
v=None,
filter=None,
**kwargs):
pyramid = Pyramid.objects(name=layers[0]).first()
minx, miny, maxx, maxy = bbox
# see if we need to transform the dataset
default_srid = Pyramid.objects(name=layers[0]).first().srs
s_srs = djgdal.SpatialReference(default_srid.decode('ascii'))
print srs
if not srs:
t_srs = djgdal.SpatialReference(default_srid.decode('ascii'))
else:
t_srs = djgdal.SpatialReference(srs)
#print t_srs, s_srs
s_mins = Point(minx, miny, srid=t_srs.wkt)
s_maxs = Point(maxx, maxy, srid=t_srs.wkt)
s_mins.transform(s_srs.srid)
s_maxs.transform(s_srs.srid)
# figure out the pixel size. if we're only after one pixel, like for GetFeatureInfo,
# it's likely that pxsize will be 0. In that case, set the pixel size to be the
# smallest available.
tminx, tminy, tmaxx, tmaxy = bbox
minx = s_mins.x
maxx = s_maxs.x
miny = s_mins.y
maxy = s_maxs.y
pxsize = (maxx - minx) / width
# case of only looking for one pixel
if pxsize == 0:
pxsize = pyramid.pxsize_at_levels[-1]
maxx = maxx + pxsize
maxy = maxy + pxsize
# start with the furthest zoomed out tiles and work our way in, searching for the
# nearest level to the query
l = 0
p = 999999999
for level, px in enumerate(pyramid.pxsize_at_levels):
if abs(px - pxsize) < p:
l = level
p = abs(px - pxsize)
# open the index for that level, filter it by our bounding box.
dataset = ogr.Open(pyramid.indices[l].encode('ascii'))
index = dataset.GetLayer(0)
index.ResetReading()
index.SetSpatialFilterRect(minx, miny, maxx, maxy)
f = index.GetNextFeature()
# retrieve tiles
tiles = []
while f:
Tile.objects.ensure_index('tile_name')
Tile.objects.ensure_index('pyramid', 'tile_name')
t = Tile.objects(pyramid=pyramid, level=l,
tile_name=f.location).first()
fl = gdal.FileFromMemBuffer('/vsimem/' + t.tile_name, t.data)
tiles.append(gdal.Open('/vsimem/' + t.tile_name))
f = index.GetNextFeature()
del index # close the index
# create our output dataset and stitch tiles into it by projecting them in.
output = gdal.GetDriverByName('MEM').Create("TEMP", width, height,
pyramid.raster_count,
pyramid.data_type, [])
output.SetGeoTransform([
tminx, (tmaxx - tminx) / width, 0, tmaxy, 0,
(tminy - tmaxy) / height
])
output.SetProjection(t_srs.wkt)
#print output.GetGeoTransform()
for tile in tiles:
#print tile.GetGeoTransform()
#print tile.GetProjection()
#print output.GetProjection()
gdal.ReprojectImage(tile, output, None, None, gdal.GRA_Bilinear)
return output
def get_2d_dataset(
self,
layers,
srs,
bbox,
width,
height,
styles=None,
bgcolor=None,
transparent=False,
time=None,
elevation=None,
v=None,
filter=None,
**kwargs
):
pyramid = Pyramid.objects(name=layers[0]).first()
minx, miny, maxx, maxy = bbox
# see if we need to transform the dataset
default_srid = Pyramid.objects(name=layers[0]).first().srs
s_srs = djgdal.SpatialReference(default_srid.decode("ascii"))
print srs
if not srs:
t_srs = djgdal.SpatialReference(default_srid.decode("ascii"))
else:
t_srs = djgdal.SpatialReference(srs)
# print t_srs, s_srs
s_mins = Point(minx, miny, srid=t_srs.wkt)
s_maxs = Point(maxx, maxy, srid=t_srs.wkt)
s_mins.transform(s_srs.srid)
s_maxs.transform(s_srs.srid)
# figure out the pixel size. if we're only after one pixel, like for GetFeatureInfo,
# it's likely that pxsize will be 0. In that case, set the pixel size to be the
# smallest available.
tminx, tminy, tmaxx, tmaxy = bbox
minx = s_mins.x
maxx = s_maxs.x
miny = s_mins.y
maxy = s_maxs.y
pxsize = (maxx - minx) / width
# case of only looking for one pixel
if pxsize == 0:
pxsize = pyramid.pxsize_at_levels[-1]
maxx = maxx + pxsize
maxy = maxy + pxsize
# start with the furthest zoomed out tiles and work our way in, searching for the
# nearest level to the query
l = 0
p = 999999999
for level, px in enumerate(pyramid.pxsize_at_levels):
if abs(px - pxsize) < p:
l = level
p = abs(px - pxsize)
# open the index for that level, filter it by our bounding box.
dataset = ogr.Open(pyramid.indices[l].encode("ascii"))
index = dataset.GetLayer(0)
index.ResetReading()
index.SetSpatialFilterRect(minx, miny, maxx, maxy)
f = index.GetNextFeature()
# retrieve tiles
tiles = []
while f:
Tile.objects.ensure_index("tile_name")
Tile.objects.ensure_index("pyramid", "tile_name")
t = Tile.objects(pyramid=pyramid, level=l, tile_name=f.location).first()
fl = gdal.FileFromMemBuffer("/vsimem/" + t.tile_name, t.data)
tiles.append(gdal.Open("/vsimem/" + t.tile_name))
f = index.GetNextFeature()
del index # close the index
# create our output dataset and stitch tiles into it by projecting them in.
output = gdal.GetDriverByName("MEM").Create("TEMP", width, height, pyramid.raster_count, pyramid.data_type, [])
output.SetGeoTransform([tminx, (tmaxx - tminx) / width, 0, tmaxy, 0, (tminy - tmaxy) / height])
output.SetProjection(t_srs.wkt)
# print output.GetGeoTransform()
for tile in tiles:
# print tile.GetGeoTransform()
# print tile.GetProjection()
# print output.GetProjection()
gdal.ReprojectImage(tile, output, None, None, gdal.GRA_Bilinear)
return output
