def decode(cls, encoding, spec, df):
binners = encoding.decode_list('binner', spec['binners'])
task = cls(df, binners)
aggs = encoding.decode_list('aggregation', spec['aggregations'])
for agg in aggs:
agg._prepare_types(df)
task.add_aggregation_operation(agg)
return task
def decode(cls, encoding, spec, df, nthreads):
# aggs = [vaex.agg._from_spec(agg_spec) for agg_spec in spec['aggregations']]
aggs = encoding.decode_list('aggregation', spec['aggregations'])
dtypes = encoding.decode_dict('dtype', spec['dtypes'])
grid = encoding.decode_list('binner-cpu', spec['binners'], nthreads=nthreads)
values = encoding.decode_list2('ndarray', spec['values']) if 'values' in spec else None
# dtypes = {expr: _deserialize_type(type_spec) for expr, type_spec in spec['dtypes'].items()}
for agg in aggs:
agg._prepare_types(df)
return cls(df, grid, aggs, dtypes, initial_values=values, nthreads=nthreads)
def decode(cls, encoding, spec, df):
grid = encoding.decode('grid', spec['grid'])
task = cls(df, grid)
aggs = encoding.decode_list('aggregation', spec['aggregations'])
for agg in aggs:
agg._prepare_types(df)
task.add_aggregation_operation(agg)
return task
def decode(cls, encoding, spec, df):
# aggs = [vaex.agg._from_spec(agg_spec) for agg_spec in spec['aggregations']]
aggs = encoding.decode_list('aggregation', spec['aggregations'])
dtypes = encoding.decode_dict('dtype', spec['dtypes'])
grid = encoding.decode('grid', spec['grid'])
# dtypes = {expr: _deserialize_type(type_spec) for expr, type_spec in spec['dtypes'].items()}
for agg in aggs:
agg._prepare_types(df)
return cls(df, grid, aggs, dtypes)
def decode(cls, encoding, spec, df):
binners = tuple(encoding.decode_list('binner', spec['binners']))
agg = encoding.decode('aggregation', spec['aggregation'])
task = cls(df, binners, agg)
return task
