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349: Implemented round() function #359

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349: Implemented round() function #359

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9e1affb
implemented round() function
VidhyaVarshanyJS Jan 30, 2024
b64b224
added test cases for round in test_unary.py
VidhyaVarshanyJS Feb 3, 2024
94ab060
made changes in few files
VidhyaVarshanyJS Feb 26, 2024
f357b6b
Merge branch 'main' into vidhya
VidhyaVarshanyJS Mar 4, 2024
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32 changes: 32 additions & 0 deletions temporian/core/event_set_ops.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1501,6 +1501,38 @@ def abs(

return abs(self)

def __round__(self):
from temporian.core.operators.unary import round

return round(input=self)

def round(
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self: EventSetOrNode,
) -> EventSetOrNode:
"""Rounds the values of an [`EventSet`][temporian.EventSet]'s features to the nearest integer.

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Add another line specifying that only float types are allowed, and the output type will always be the same as the input's

Example:
```python
>>> a = tp.event_set(
... timestamps=[1, 2, 3],
... features={"M": [1.4, 2.6, 3.1], "N": [-1.9, -3.5, 5.8]},
... )
>>> a.round()
indexes: ...
'M': [1, 3, 3]
'N': [-2, -4, 6]
...

```

Returns:
EventSet with rounded feature values.
"""
from temporian.core.operators.unary import round

return round(self)


def add_index(
self: EventSetOrNode, indexes: Union[str, List[str]]
) -> EventSetOrNode:
Expand Down
47 changes: 47 additions & 0 deletions temporian/core/operators/test/test_unary.py
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Expand Up @@ -99,6 +99,53 @@ def test_correct_notnan(self) -> None:
)
assertOperatorResult(self, evset.notnan(), expected)

def test_round_single_feature(self):
evset = event_set(
timestamps=[1, 2, 3],
features={"f": [1.1, -2.5, -3.9]},
)
expected = event_set(
timestamps=[1, 2, 3],
features={"f": [1.0, -3.0, -4.0]},
same_sampling_as=evset,
)
assertOperatorResult(self, evset.round(), expected)
assertOperatorResult(self, round(evset), expected) # __round__ magic

def test_round_multiple_features(self):
evset = event_set(
timestamps=[1, 2],
features={"a": [10.5, 11.7], "b": [1.2, 2.9]},
)
expected = event_set(
timestamps=[1, 2],
features={"a": [11, 12], "b": [1, 3]},
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I don't think these will pass, since a list of ints will yield an eventset with int features, which won't be equal to the float results of round(). Ensure your new tests are passing by running bazel test //temporian/core/operators/test:test_unary --config=macos --test_output=errors or bazel test //temporian/core/operators/test:test_unary --config=linux --test_output=errors depending on your OS

same_sampling_as=evset,
)
assertOperatorResult(self, evset.round(), expected)
assertOperatorResult(self, round(evset), expected) # __round__ magic

def test_round_non_accepted_types(self):
evset = event_set(
timestamps=[1, 2],
features={"a": ["10.5", 11.7], "b": [1, 2]},
)
with self.assertRaises(TypeError):
_ = evset
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missing calling round() on the evset here - this shouldn't be raising anything? did you manage to run the tests locally to ensure they pass?


def test_round_float32_and_float64_features(self):
evset = event_set(
timestamps=[1, 2],
features={"a": [10.5, 11.7], "b": [1.2, 2.9]},
)
expected = event_set(
timestamps=[1, 2],
features={"a": [11.0, 12.0], "b": [1.0, 3.0]},
same_sampling_as=evset,
)
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which of these are being defined as f32 and which as f64? see the f64 and f32 methods in temporian/test/utils.py to explicitly create an eventset with the desired feature types

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I need a clarification. Can I use the numpy for specifying the float32 and float64 separately as

float32

def test_round_float32(self):
    evset = event_set(
        timestamps=[1, 2],
        features={"a": np.array([10.5, 11.7], dtype=np.float32), "b": np.array([1.2, 2.9], dtype=np.float32)},
    )
    expected = event_set(
        timestamps=[1, 2],
        features={"a": np.array([11.0, 12.0], dtype=np.float32), "b": np.array([1.0, 3.0], dtype=np.float32)},
        same_sampling_as=evset,
    )
    assertOperatorResult(self, evset.round(), expected)
    assertOperatorResult(self, round(evset), expected)  # __round__ magic

float64

def test_round_float64(self):
    evset = event_set(
        timestamps=[1, 2],
        features={"a": np.array([10.5, 11.7], dtype=np.float64), "b": np.array([1.2, 2.9], dtype=np.float64)},
    )
    expected = event_set(
        timestamps=[1, 2],
        features={"a": np.array([11.0, 12.0], dtype=np.float64), "b": np.array([1.0, 3.0], dtype=np.float64)},
        same_sampling_as=evset,
    )
    assertOperatorResult(self, evset.round(), expected)
    assertOperatorResult(self, round(evset), expected)  # __round__ magic

assertOperatorResult(self, evset.round(), expected)
assertOperatorResult(self, round(evset), expected) # __round__ magic


if __name__ == "__main__":
absltest.main()
31 changes: 31 additions & 0 deletions temporian/core/operators/unary.py
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Original file line number Diff line number Diff line change
Expand Up @@ -182,11 +182,31 @@ def get_output_dtype(cls, feature_dtype: DType) -> DType:
return feature_dtype


class RoundOperator(BaseUnaryOperator):
@classmethod
def op_key_definition(cls) -> str:
return "ROUND"

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unnecessary empty line

@classmethod
def allowed_dtypes(cls) -> List[DType]:
return [
DType.FLOAT32,
DType.FLOAT64,
DType.INT32,
DType.INT64,
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ints shouldn't be allowed

]

@classmethod
def get_output_dtype(cls, feature_dtype: DType) -> DType:
return feature_dtype


operator_lib.register_operator(InvertOperator)
operator_lib.register_operator(IsNanOperator)
operator_lib.register_operator(NotNanOperator)
operator_lib.register_operator(AbsOperator)
operator_lib.register_operator(LogOperator)
operator_lib.register_operator(RoundOperator)

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extra newline here too


@compile
Expand Down Expand Up @@ -242,3 +262,14 @@ def log(
return LogOperator(
input=input,
).outputs["output"]


@compile
def round(
input: EventSetOrNode,
) -> EventSetOrNode:
assert isinstance(input, EventSetNode)

return RoundOperator(
input=input,
).outputs["output"]
9 changes: 9 additions & 0 deletions temporian/implementation/numpy/operators/unary.py
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Expand Up @@ -10,6 +10,7 @@
NotNanOperator,
IsNanOperator,
LogOperator,
RoundOperator,
)
from temporian.implementation.numpy import implementation_lib
from temporian.implementation.numpy.data.event_set import IndexData
Expand Down Expand Up @@ -77,6 +78,11 @@ def _do_operation(self, feature: np.ndarray) -> np.ndarray:
return np.log(feature)


class RoundNumpyImplementation(BaseUnaryNumpyImplementation):
def _do_operation(self, feature: np.ndarray) -> np.ndarray:
return np.round(feature)


implementation_lib.register_operator_implementation(
AbsOperator, AbsNumpyImplementation
)
Expand All @@ -92,3 +98,6 @@ def _do_operation(self, feature: np.ndarray) -> np.ndarray:
implementation_lib.register_operator_implementation(
LogOperator, LogNumpyImplementation
)
implementation_lib.register_operator_implementation(
RoundOperator, RoundNumpyImplementation
)