from ..filters import ArrayPredicate, NotNullFilter, NullFilter, NumExprFilter
from ..mixins import (
AliasedMixin,
CustomTermMixin,
DownsampledMixin,
LatestMixin,
PositiveWindowLengthMixin,
RestrictedDTypeMixin,
SingleInputMixin,
StandardOutputs,
)
string_classifiers_only = restrict_to_dtype(
dtype=categorical_dtype,
message_template=(
"{method_name}() is only defined on Classifiers producing strings"
" but it was called on a Classifier of dtype {received_dtype}."))
class Classifier(RestrictedDTypeMixin, ComputableTerm):
"""
A Pipeline expression computing a categorical output.
Classifiers are most commonly useful for describing grouping keys for
complex transformations on Factor outputs. For example, Factor.demean() and
Factor.zscore() can be passed a Classifier in their ``groupby`` argument,
indicating that means/standard deviations should be computed on assets for
which the classifier produced the same label.
"""
# Used by RestrictedDTypeMixin
dtype=float64_dtype,
)
else:
return NumExprFactor(
"{func}(x_0)".format(func=func),
(self,),
dtype=float64_dtype,
)
return mathfunc
# Decorators for Factor methods.
if_not_float64_tell_caller_to_use_isnull = restrict_to_dtype(
dtype=float64_dtype,
message_template=(
"{method_name}() was called on a factor of dtype {received_dtype}.\n"
"{method_name}() is only defined for dtype {expected_dtype}."
"To filter missing data, use isnull() or notnull()."
)
)
float64_only = restrict_to_dtype(
dtype=float64_dtype,
message_template=(
"{method_name}() is only defined on Factors of dtype {expected_dtype},"
" but it was called on a Factor of dtype {received_dtype}."
)
)
FACTOR_DTYPES = frozenset([datetime64ns_dtype, float64_dtype, int64_dtype])
from ..filters import ArrayPredicate, NotNullFilter, NullFilter, NumExprFilter
from ..mixins import (
CustomTermMixin,
DownsampledMixin,
LatestMixin,
PositiveWindowLengthMixin,
RestrictedDTypeMixin,
SingleInputMixin,
StandardOutputs,
)
string_classifiers_only = restrict_to_dtype(
dtype=categorical_dtype,
message_template=(
"{method_name}() is only defined on Classifiers producing strings"
" but it was called on a Factor of dtype {received_dtype}."
)
)
class Classifier(RestrictedDTypeMixin, ComputableTerm):
"""
A Pipeline expression computing a categorical output.
Classifiers are most commonly useful for describing grouping keys for
complex transformations on Factor outputs. For example, Factor.demean() and
Factor.zscore() can be passed a Classifier in their ``groupby`` argument,
indicating that means/standard deviations should be computed on assets for
which the classifier produced the same label.
"""
dtype=float64_dtype,
)
else:
return NumExprFactor(
"{func}(x_0)".format(func=func),
(self, ),
dtype=float64_dtype,
)
return mathfunc
# Decorators for Factor methods.
if_not_float64_tell_caller_to_use_isnull = restrict_to_dtype(
dtype=float64_dtype,
message_template=(
"{method_name}() was called on a factor of dtype {received_dtype}.\n"
"{method_name}() is only defined for dtype {expected_dtype}."
"To filter missing data, use isnull() or notnull()."))
float64_only = restrict_to_dtype(
dtype=float64_dtype,
message_template=(
"{method_name}() is only defined on Factors of dtype {expected_dtype},"
" but it was called on a Factor of dtype {received_dtype}."))
FACTOR_DTYPES = frozenset([datetime64ns_dtype, float64_dtype, int64_dtype])
class Factor(RestrictedDTypeMixin, ComputableTerm):
"""
Pipeline API expression producing a numerical or date-valued output.
