def generate_hibed_tiles(tileset, tile_ids):
'''
Generate tiles from a hibed file.
Parameters
----------
tileset: tilesets.models.Tileset object
The tileset that the tile ids should be retrieved from
tile_ids: [str,...]
A list of tile_ids (e.g. xyx.0.0.1) identifying the tiles
to be retrieved
Returns
-------
generated_tiles: [(tile_id, tile_data),...]
A list of tile_id, tile_data tuples
'''
generated_tiles = []
for tile_id in tile_ids:
tile_id_parts = tile_id.split('.')
tile_position = list(map(int, tile_id_parts[1:3]))
dense = hdft.get_discrete_data(h5py.File(tileset.datafile.path),
tile_position[0], tile_position[1])
tile_value = {
'discrete':
list([list([x.decode('utf-8') for x in d]) for d in dense])
}
generated_tiles += [(tile_id, tile_value)]
return generated_tiles
def generate_tile(tile_id, request):
'''
Create a tile. The tile_id specifies the dataset as well
as the position.
This function will look at the filetype and determine what type
of tile to retrieve (e..g cooler -> 2D dense, hitile -> 1D dense,
elasticsearch -> anything)
Args:
tile_id (str): The id of a tile, consisting of the tileset id,
followed by the tile position (e.g. PIYqJpdyTCmAZGmA6jNHJw.4.0.0)
request (django.http.HTTPRequest): The request that included this tile.
Returns:
(string, dict): A tuple containing the tile ID tile data
'''
tile_id_parts = tile_id.split('.')
tile_position = map(int, tile_id_parts[1:])
tileset_uuid = tile_id_parts[0]
tileset = tm.Tileset.objects.get(uuid=tileset_uuid)
if tileset.private and request.user != tileset.owner:
# dataset is not public return an empty set
return (tileset_uuid, {'error': "Forbidden"})
tile_value = rdb.get(tile_id)
if tile_value is not None:
tile_value = pickle.loads(tile_value)
return (tile_id, tile_value)
if tileset.filetype == "hitile":
dense = hdft.get_data(
h5py.File(
get_datapath(tileset.datafile)
),
tile_position[0],
tile_position[1]
)
tile_value = {'dense': base64.b64encode(dense)}
elif tileset.filetype == 'beddb':
tile_value = cdt.get_tile(
get_datapath(tileset.datafile),
tile_position[0],
tile_position[1]
)
elif tileset.filetype == 'bed2ddb':
tile_value = cdt.get_2d_tile(
get_datapath(tileset.datafile),
tile_position[0],
tile_position[1],
tile_position[2]
)
elif tileset.filetype == 'hibed':
dense = hdft.get_discrete_data(
h5py.File(
get_datapath(tileset.datafile)
),
tile_position[0],
tile_position[1]
)
tile_value = {'discrete': list([list(d) for d in dense])}
elif tileset.filetype == "elasticsearch":
response = urllib.urlopen(
tileset.datafile + '/' + '.'.join(map(str, tile_position))
)
tile_value = json.loads(response.read())["_source"]["tile_value"]
else:
tile_value = make_cooler_tile(
get_datapath(tileset.datafile), tile_position
)
if tile_value is None:
return None
rdb.set(tile_id, pickle.dumps(tile_value))
return (tile_id, tile_value)