sma.py

# 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.
"""Basic profiling script for temporian.

The script creates a node, applies an sma to it, and runs the graph.
"""

import numpy as np
import pandas as pd
import temporian as tp
from temporian.implementation.numpy.data.event_set import EventSet

# Make results reproducible
np.random.seed(0)

# Control size of benchmark , N = 300000 takes about 5s to run
N = 300000

STORE, PRODUCT, TIMESTAMP, SALES, COSTS = (
    "store_id",
    "product_id",
    "timestamp",
    "sales",
    "costs",
)


def main():
    print(f"Running lag benchmark with N={N}...")

    # Integer ids from 0 to 9
    ids = list(range(int(10)))

    timestamps = np.sort(np.random.randn(N) * 100)
    product_ids = np.random.choice(ids, N)
    store_ids = np.random.choice(ids, N)

    evset = tp.from_pandas(
        pd.DataFrame(
            {
                STORE: store_ids,
                PRODUCT: product_ids,
                TIMESTAMP: timestamps,
                SALES: np.random.randn(N) * 100,
            }
        ),
        indexes=[STORE, PRODUCT],
    )

    node = evset.node()

    sma = node.simple_moving_average(window_length=10)

    res: EventSet = tp.run(
        sma,
        input={node: evset},
        check_execution=False,
    )

    # Print output's first row, useful to check reproducibility
    print(res)


if __name__ == "__main__":
    main()