import numpy as np
import pandas as pd
from torch_timeseries.core import Freq, TimeSeriesDataset, TimeSeriesStaticGraphDataset
[docs]class Dummy(TimeSeriesDataset):
"""
Dummy dataset for testing purposes.
Attributes:
name (str): Name of the dataset.
num_features (int): Number of features in the dataset.
freq (Freq): Frequency of the data points.
length (int): Length of the dataset.
Methods:
download():
Placeholder method for downloading data.
_load():
Loads the dataset into a NumPy array.
"""
name: str = 'dummy'
num_features:int = 2
freq : Freq = Freq.minutes
length : int = 1440
[docs] def download(self):
pass
[docs] def _load(self):
dates = pd.date_range(start='2022-01-01', end='2022-01-02', freq='t')
data = np.random.rand(len(dates), 2)
self.df = pd.DataFrame({'date': dates, 'data1': data[:, 0],'data2': data[:, 1]})
self.dates = pd.DataFrame({'date':self.df.date})
self.data = self.df.drop('date', axis=1).values
return self.data