Time Series Generator
Project description
Time Series Generator
Description
Emulates Teras Tensorflow TimeSeriesGenerator functionality
Instalation
pip install time-series-generator
Usage
import numpy as np
from time_series_generator import TimeseriesGenerator
data = np.array([[i] for i in range(50)])
targets = np.array([[i] for i in range(50)])
data_gen = TimeSeriesGenerator(data, targets,
length=10, sampling_rate=2,
batch_size=2)
assert len(data_gen) == 20
batch_0 = data_gen[0]
x, y = batch_0
assert np.array_equal(x,
np.array([[[0], [2], [4], [6], [8]],
[[1], [3], [5], [7], [9]]]))
assert np.array_equal(y,
np.array([[10], [11]]))
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Close
Hashes for time_series_generator-0.0.3.tar.gz
Algorithm | Hash digest | |
---|---|---|
SHA256 | f1a32ebedb0bdb0fae891df52ddc17e0ff5c0a95d3f8b7202a8e41c86e164b19 |
|
MD5 | 9a76f27440fbeacc62c4489c218092ee |
|
BLAKE2b-256 | 1f4b64549cfa4bd3423bbabbf171d20003426a4d6928dc871c65e768a1206542 |
Close
Hashes for time_series_generator-0.0.3-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 7094a68dfcaad42d2dbbfa18e1d2440674a52282b9823f5b48ff0021c4afa89d |
|
MD5 | d77cd592ff715d538b4baabbb376bc39 |
|
BLAKE2b-256 | 55b3e1232aefb3816d6c9d3030c32fea5c598955cfdf9171e88d9a31d973adaa |