380: Initial implementation of moving_product operation (google#383)

* WIP: Initial implementation of moving_product operation * Remove the wrong use of override keyword at Reset Method in the MovingProductAccumulator class * Implement On-Demand Product Calculation in MovingProductAccumulator Key Changes: - Start and end indices (`start_idx` and `end_idx`) introduced to track the window. - `Add` and `Remove` methods updated to adjust the window indices without affecting the product. - `Result` method now calculates the product on-demand, considering zeros and ignoring NaN values for accuracy. - Added a TODO comment to explore future optimizations for the Result method to enhance calculation efficiency. * add test and doc for moving_product * Optimize moving_product logic to directly return zero for windows with zero values * fix(docs): Update docs and adjust example values for clarity in event_set_ops.py fix(moving_product): Update the moving_product logic to return NaN when the input only contains NaN. * feat(window_op): Add cumprod operator * style: format cumprod related files with Black * docs: remove un-wanted function description from moving_product at event_set_ops.py * fix(test): Pass the correct dtype at docstring example for moving_product in event_set_ops.py * fix(test_moving_product): Correct calculation errors in test_with_sampling and test_with_variable_winlen_same_sampling.
check-spelling-sandbox · Mar 7, 2024 · 9ccd08f · 9ccd08f
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diff --git a/docs/src/reference/index.md b/docs/src/reference/index.md
@@ -45,13 +45,13 @@ Check the index on the left for a more detailed description of any symbol.
 | [`tp.combine()`][temporian.combine]                                                                        | Combines events from [`EventSets`][temporian.EventSet] with different samplings.                               |
 | [`tp.glue()`][temporian.glue]                                                                              | Concatenates features from [`EventSets`][temporian.EventSet] with the same sampling.                           |
 | [`EventSet.abs()`][temporian.EventSet.abs]                                                                 | Computes the absolute value of the features.                                                                   |
-| [`EventSet.add_index()`][temporian.EventSet.add_index]                                                     | Adds indexes to an [`EventSet`][temporian.EventSet].
-| [`EventSet.arccos()`][temporian.EventSet.arccos]                                                           | Computes the inverse cosine of the features.
-| [`EventSet.arcsin()`][temporian.EventSet.arcsin]                                                           | Computes the inverse sine of the features.
-| [`EventSet.arctan()`][temporian.EventSet.arctan]                                                           | Computes the inverse tangent of the features.                                                     |
+| [`EventSet.add_index()`][temporian.EventSet.add_index]                                                     | Adds indexes to an [`EventSet`][temporian.EventSet].                                                           |
+| [`EventSet.arccos()`][temporian.EventSet.arccos]                                                           | Computes the inverse cosine of the features.                                                                   |
+| [`EventSet.arcsin()`][temporian.EventSet.arcsin]                                                           | Computes the inverse sine of the features.                                                                     |
+| [`EventSet.arctan()`][temporian.EventSet.arctan]                                                           | Computes the inverse tangent of the features.                                                                  |
 | [`EventSet.begin()`][temporian.EventSet.begin]                                                             | Generates a single timestamp at the beginning of the input.                                                    |
-| [`EventSet.cast()`][temporian.EventSet.cast]                                                               | Casts the dtype of features.
-| [`EventSet.cos()`][temporian.EventSet.cos]                                                                 | Computes the cosine of the features.                                                                                    |
+| [`EventSet.cast()`][temporian.EventSet.cast]                                                               | Casts the dtype of features.                                                                                   |
+| [`EventSet.cos()`][temporian.EventSet.cos]                                                                 | Computes the cosine of the features.                                                                           |
 | [`EventSet.drop_index()`][temporian.EventSet.drop_index]                                                   | Removes indexes from an [`EventSet`][temporian.EventSet].                                                      |
 | [`EventSet.end()`][temporian.EventSet.end]                                                                 | Generates a single timestamp at the end of the input.                                                          |
 | [`EventSet.enumerate()`][temporian.EventSet.enumerate]                                                     | Creates an ordinal feature enumerating the events according to their timestamp.                                |
@@ -72,10 +72,10 @@ Check the index on the left for a more detailed description of any symbol.
 | [`EventSet.resample()`][temporian.EventSet.resample]                                                       | Resamples an [`EventSet`][temporian.EventSet] at each timestamp of another [`EventSet`][temporian.EventSet].   |
 | [`EventSet.select()`][temporian.EventSet.select]                                                           | Selects a subset of features from an [`EventSet`][temporian.EventSet].                                         |
 | [`EventSet.select_index_values()`][temporian.EventSet.select_index_values]                                 | Selects a subset of index values from an [`EventSet`][temporian.EventSet].                                     |
-| [`EventSet.set_index()`][temporian.EventSet.set_index]                                                     | Replaces the indexes in an [`EventSet`][temporian.EventSet].
-| [`EventSet.sin()`][temporian.EventSet.sin]                                                                 | Computes the sine of the features.                                                    |
-| [`EventSet.since_last()`][temporian.EventSet.since_last]                                                   | Computes the amount of time since the last distinct timestamp.
-| [`EventSet.tan()`][temporian.EventSet.tan]                                                                 | Computes the tangent of the features.                                                  |
+| [`EventSet.set_index()`][temporian.EventSet.set_index]                                                     | Replaces the indexes in an [`EventSet`][temporian.EventSet].                                                   |
+| [`EventSet.sin()`][temporian.EventSet.sin]                                                                 | Computes the sine of the features.                                                                             |
+| [`EventSet.since_last()`][temporian.EventSet.since_last]                                                   | Computes the amount of time since the last distinct timestamp.                                                 |
+| [`EventSet.tan()`][temporian.EventSet.tan]                                                                 | Computes the tangent of the features.                                                                          |
 | [`EventSet.tick()`][temporian.EventSet.tick]                                                               | Generates timestamps at regular intervals in the range of a guide.                                             |
 | [`EventSet.tick_calendar()`][temporian.EventSet.tick]                                                      | Generates timestamps at the specified calendar date-time events.                                               |
 | [`EventSet.timestamps()`][temporian.EventSet.timestamps]                                                   | Creates a feature from the events timestamps (`float64`).                                                      |
@@ -91,9 +91,9 @@ Check the index on the left for a more detailed description of any symbol.
 
 ### Window operators
 
-| Symbols                                                                                                                                                                                                                                                                                                                                                                                                                                                        | Description                                                                           |
-| -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------- |
-| [`EventSet.simple_moving_average()`][temporian.EventSet.simple_moving_average] [`EventSet.moving_standard_deviation()`][temporian.EventSet.moving_standard_deviation] [`EventSet.cumsum()`][temporian.EventSet.cumsum] [`EventSet.moving_sum()`][temporian.EventSet.moving_sum] [`EventSet.moving_count()`][temporian.EventSet.moving_count] [`EventSet.moving_min()`][temporian.EventSet.moving_min] [`EventSet.moving_max()`][temporian.EventSet.moving_max] | Compute an operation on the values in a sliding window over an EventSet's timestamps. |
+| Symbols                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            | Description                                                                           |
+| ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------- |
+| [`EventSet.simple_moving_average()`][temporian.EventSet.simple_moving_average] [`EventSet.moving_standard_deviation()`][temporian.EventSet.moving_standard_deviation] [`EventSet.cumsum()`][temporian.EventSet.cumsum] [`EventSet.moving_sum()`][temporian.EventSet.moving_sum] [`EventSet.moving_count()`][temporian.EventSet.moving_count] [`EventSet.moving_min()`][temporian.EventSet.moving_min] [`EventSet.moving_max()`][temporian.EventSet.moving_max] [`EventSet.cumprod()`][temporian.EventSet.cumprod] [`EventSet.moving_product()`][temporian.EventSet.moving_product] | Compute an operation on the values in a sliding window over an EventSet's timestamps. |
 
 ### Python operators
 

diff --git a/docs/src/reference/temporian/operators/window/cumprod.md b/docs/src/reference/temporian/operators/window/cumprod.md
@@ -0,0 +1 @@
+::: temporian.EventSet.cumprod
diff --git a/docs/src/reference/temporian/operators/window/moving_product.md b/docs/src/reference/temporian/operators/window/moving_product.md
@@ -0,0 +1 @@
+::: temporian.EventSet.moving_product
diff --git a/temporian/core/event_set_ops.py b/temporian/core/event_set_ops.py
@@ -2133,6 +2133,78 @@ def cast(
 
         return cast(self, target=target, check_overflow=check_overflow)
 
+    def cumprod(
+        self: EventSetOrNode,
+        sampling: Optional[EventSetOrNode] = None,
+    ) -> EventSetOrNode:
+        """Computes the cumulative product of values over each feature in an
+        [`EventSet`][temporian.EventSet].
+
+        This operation only supports floating-point features.
+
+        Missing (NaN) values are not accounted for. The output will be NaN until
+        the input contains at least one numeric value.
+
+        Warning: The `cumprod` function leverages an infinite window length for
+        its calculations, which may lead to considerable computational overhead
+        with increasing dataset sizes.
+
+        Example:
+            ```python
+            >>> a = tp.event_set(
+            ...     timestamps=[0, 1, 2, 3],
+            ...     features={"value": [1.0, 2.0, 10.0, 12.0]},
+            ... )
+
+            >>> b = a.cumprod()
+            >>> b
+            indexes: ...
+                (4 events):
+                    timestamps: [0. 1. 2. 3.]
+                    'value': [  1.   2.  20. 240.]
+            ...
+
+            ```
+
+        Examples with sampling:
+            ```python
+            >>> a = tp.event_set(
+            ...     timestamps=[0, 1, 2, 5, 6, 7],
+            ...     features={"value": [1, 2, 10, 12, np.nan, 2]},
+            ... )
+
+            >>> # Cumulative product at 5 and 10
+            >>> b = tp.event_set(timestamps=[5, 10])
+            >>> c = a.cumprod(sampling=b)
+            >>> c
+            indexes: ...
+                (2 events):
+                    timestamps: [ 5. 10.]
+                    'value': [240. 480.]
+            ...
+
+            >>> # Product all values in the EventSet
+            >>> c = a.cumprod(sampling=a.end())
+            >>> c
+            indexes: ...
+                (1 events):
+                    timestamps: [7.]
+                    'value': [480.]
+            ...
+
+            ```
+
+        Args:
+            sampling: Timestamps to sample the sliding window's value at. If not
+                provided, timestamps in the input are used.
+
+        Returns:
+            Cumulative product of each feature.
+        """
+        from temporian.core.operators.window.moving_product import cumprod
+
+        return cumprod(self, sampling=sampling)
+
     def cumsum(
         self: EventSetOrNode,
         sampling: Optional[EventSetOrNode] = None,
@@ -3171,6 +3243,68 @@ def moving_standard_deviation(
             self, window_length=window_length, sampling=sampling
         )
 
+    def moving_product(
+        self: EventSetOrNode,
+        window_length: WindowLength,
+        sampling: Optional[EventSetOrNode] = None,
+    ) -> EventSetOrNode:
+        """Computes the product of values in a sliding window over an
+        [`EventSet`][temporian.EventSet].
+
+        This operation only supports floating-point features.
+
+        For each t in sampling, and for each feature independently, returns at
+        time t the product of non-zero and non-NaN values for the feature in the window
+        (t - window_length, t].
+
+        `sampling` can't be specified if a variable `window_length` is
+        specified (i.e., if `window_length` is an EventSet).
+
+        If `sampling` is specified or `window_length` is an EventSet, the moving
+        window is sampled at each timestamp in them, else it is sampled on the
+        input's.
+
+        Zeros result in the accumulator's result being 0 for the window. NaN values are ignored in the
+        calculation of the product. If the window does not contain any NaN, zero or any non-zero values (e.g.,
+        all values are missing), the output for that window is an empty array.
+
+        Example:
+            ```python
+            >>> a = tp.event_set(
+            ...     timestamps=[0, 1, 2],
+            ...     features={"value": [np.nan, 1, 5]},
+            ... )
+
+            >>> b = a.moving_product(tp.duration.seconds(1))
+            >>> b
+            indexes: ...
+                (3 events):
+                    timestamps: [0. 1. 2.]
+                    'value': [nan 1. 5.]
+            ...
+
+            ```
+
+        See [`EventSet.moving_count()`][temporian.EventSet.moving_count] for
+        examples of moving window operations with external sampling and indices.
+
+        Args:
+            window_length: Sliding window's length.
+            sampling: Timestamps to sample the sliding window's value at. If not
+                provided, timestamps in the input are used.
+
+        Returns:
+            EventSet containing the moving product of each feature in the input,
+            considering non-zero and non-NaN values only.
+        """
+        from temporian.core.operators.window.moving_product import (
+            moving_product,
+        )
+
+        return moving_product(
+            self, window_length=window_length, sampling=sampling
+        )
+
     def moving_sum(
         self: EventSetOrNode,
         window_length: WindowLength,

diff --git a/temporian/core/operators/window/BUILD b/temporian/core/operators/window/BUILD
@@ -17,6 +17,7 @@ py_library(
         ":moving_standard_deviation",
         ":moving_sum",
         ":simple_moving_average",
+        ":moving_product",
     ],
 )
 
@@ -126,3 +127,18 @@ py_library(
         "//temporian/core/data:schema",
     ],
 )
+
+py_library(
+    name = "moving_product",
+    srcs = ["moving_product.py"],
+    srcs_version = "PY3",
+    deps = [
+        ":base",
+        "//temporian/core:compilation",
+        "//temporian/core:operator_lib",
+        "//temporian/core:typing",
+        "//temporian/core/data:dtype",
+        "//temporian/core/data:node",
+        "//temporian/core/data:schema",
+    ],
+)
diff --git a/temporian/core/operators/window/__init__.py b/temporian/core/operators/window/__init__.py
@@ -25,3 +25,5 @@
 from temporian.core.operators.window.moving_count import moving_count
 from temporian.core.operators.window.moving_min import moving_min
 from temporian.core.operators.window.moving_max import moving_max
+from temporian.core.operators.window.moving_product import cumprod
+from temporian.core.operators.window.moving_product import moving_product
diff --git a/temporian/core/operators/window/moving_product.py b/temporian/core/operators/window/moving_product.py
@@ -0,0 +1,85 @@
+# Copyright 2021 Google LLC.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     https://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""Moving Product operator class and public API function definition.."""
+
+from typing import Optional
+
+import numpy as np
+
+from temporian.core import operator_lib
+from temporian.core.compilation import compile
+from temporian.core.data.dtype import DType
+from temporian.core.data.node import EventSetNode
+from temporian.core.data.schema import FeatureSchema
+from temporian.core.operators.window.base import BaseWindowOperator
+from temporian.utils.typecheck import typecheck
+from temporian.core.typing import EventSetOrNode, WindowLength
+
+
+class MovingProductOperator(BaseWindowOperator):
+    """
+    Window operator to compute the moving product.
+    """
+
+    @classmethod
+    def operator_def_key(cls) -> str:
+        return "MOVING_PRODUCT"
+
+    def get_feature_dtype(self, feature: FeatureSchema) -> DType:
+        if not feature.dtype.is_float:
+            raise ValueError(
+                "moving_product requires the input EventSet to contain"
+                " floating point features only, but received feature"
+                f" {feature.name!r} with type {feature.dtype}. Note: You can"
+                " cast features e.g. `.cast(tp.float32)`"
+            )
+        return (
+            DType.FLOAT32 if feature.dtype == DType.FLOAT32 else DType.FLOAT64
+        )
+
+
+operator_lib.register_operator(MovingProductOperator)
+
+
+@typecheck
+@compile
+def moving_product(
+    input: EventSetOrNode,
+    window_length: WindowLength,
+    sampling: Optional[EventSetOrNode] = None,
+) -> EventSetOrNode:
+    assert isinstance(input, EventSetNode)
+    if sampling is not None:
+        assert isinstance(sampling, EventSetNode)
+
+    return MovingProductOperator(
+        input=input,
+        window_length=window_length,
+        sampling=sampling,
+    ).outputs["output"]
+
+
+@compile
+def cumprod(
+    input: EventSetOrNode,
+    sampling: Optional[EventSetOrNode] = None,
+) -> EventSetOrNode:
+    assert isinstance(input, EventSetNode)
+    if sampling is not None:
+        assert isinstance(sampling, EventSetNode)
+
+    return MovingProductOperator(
+        input=input, window_length=np.inf, sampling=sampling
+    ).outputs["output"]