File size: 2,837 Bytes
2c3c408 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 | 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 there was only one attribute, just show the aggregate results
if len(result) == 1:
result = result[list(result.keys())[0]]
# If there was only one aggregate, just show the value
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")
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