Noise
class
rackio_AI.Noise()Encapsulates method to work with noise
add(self, df, win_size=30, method='rhinehardt', cols=None, std_factor=0.001)Add gaussian noise over subsequence windows based on some method
Parameters
- :param df: (pandas.DataFrame)
- :param win_size: (int) window size to apply gaussian noise
- :param method: (str) method to base gaussian noise
- rhinehardt or rh
- :param cols: (list) column names to add gaussian noise.
returns
- df (pandas.DataFrame) noise added
**Snippet code
>>> import matplotlib.pyplot as plt
>>> from rackio_AI import Noise
>>> df = pd.DataFrame(np.random.randn(100,2), columns=["a", "b"])
>>> noise = Noise()
>>> df_noisy = noise.add(df, win_size=10)
>>> ax = plt.plot(df.index, df["a"], '-r', df.index, df["b"], '-b', df_noisy.index, df_noisy["a"], '--r', df_noisy.index, df_noisy["b"], '--b')
>>> ax = plt.legend(["a", "b", "noisy a", "noisy b"])
>>> plt.show()

rhinehardt(self, x, std_factor=1)Add noise to variable x based on Box-Muller transform
Parameters
- :param x: (pandas.DataFrame)