| import tiledb.cc as lt |
|
|
|
|
| class Aggregation: |
| """ |
| Proxy object returned by Query.agg to calculate aggregations. |
| """ |
|
|
| def __init__(self, query=None, attr_to_aggs={}): |
| if query is None: |
| raise ValueError("must pass in a query object") |
|
|
| self.query = query |
| self.attr_to_aggs = attr_to_aggs |
|
|
| def __getitem__(self, selection): |
| from .main import PyAgg |
| from .subarray import Subarray |
|
|
| array = self.query.array |
| order = self.query.order |
|
|
| layout = ( |
| lt.LayoutType.UNORDERED if array.schema.sparse else lt.LayoutType.ROW_MAJOR |
| ) |
| if order is None or order == "C": |
| layout = lt.LayoutType.ROW_MAJOR |
| elif order == "F": |
| layout = lt.LayoutType.COL_MAJOR |
| elif order == "G": |
| layout = lt.LayoutType.GLOBAL_ORDER |
| elif order == "U": |
| layout = lt.LayoutType.UNORDERED |
| else: |
| raise ValueError( |
| "order must be 'C' (TILEDB_ROW_MAJOR), " |
| "'F' (TILEDB_COL_MAJOR), " |
| "'G' (TILEDB_GLOBAL_ORDER), " |
| "or 'U' (TILEDB_UNORDERED)" |
| ) |
|
|
| q = PyAgg(array._ctx_(), array, layout, self.attr_to_aggs) |
|
|
| from .libtiledb import ( |
| index_as_tuple, |
| index_domain_subarray, |
| replace_ellipsis, |
| replace_scalars_slice, |
| ) |
|
|
| selection = index_as_tuple(selection) |
| dom = array.schema.domain |
| idx = replace_ellipsis(dom.ndim, selection) |
| idx, drop_axes = replace_scalars_slice(dom, idx) |
| dim_ranges = index_domain_subarray(array, dom, idx) |
|
|
| subarray = Subarray(array, array._ctx_()) |
| subarray.add_ranges([list([x]) for x in dim_ranges]) |
| q.set_subarray(subarray) |
|
|
| cond = self.query.cond |
| if cond is not None and cond != "": |
| from .query_condition import QueryCondition |
|
|
| if isinstance(cond, str): |
| q.set_cond(QueryCondition(cond)) |
| else: |
| raise TypeError("`cond` expects type str.") |
|
|
| result = q.get_aggregate() |
|
|
| |
| if len(result) == 1: |
| result = result[list(result.keys())[0]] |
|
|
| |
| if len(result) == 1: |
| result = result[list(result.keys())[0]] |
|
|
| return result |
|
|
| @property |
| def multi_index(self): |
| """Apply Array.multi_index with query parameters.""" |
| from .multirange_indexing import MultiRangeAggregation |
|
|
| return MultiRangeAggregation(self.query.array, query=self) |
|
|
| @property |
| def df(self): |
| raise NotImplementedError(".df indexer not supported for Aggregations") |
|
|
