Module timexseries_clustering.timeseries_container
Expand source code
from pandas import DataFrame
class TimeSeriesContainer:
"""
A TimeSeriesContainer collect all the relevant information useful to characterizethe time-series coming from
the ingested dataset.
Parameters
----------
timeseries_data : DataFrame
Historical time-series data, in the form of a DataFrame with an index and more than one data column.
approach : str
Approach used to cluster time-series data.
models : dict
Dictionary of ModelResult objects, all trained on these time-series.
best_model : dict
Dictionary with the information of the best clustering for all the metrics and corresponding model.
xcorr : dict
Cross-correlation between the data of this time-series and all the other ones.
"""
def __init__(self, timeseries_data: DataFrame, approach: str, models: dict, best_model: dict, xcorr: dict):
self.timeseries_data = timeseries_data
self.approach = approach
self.models = models
self.xcorr = xcorr
self.best_model = best_modelClasses
class TimeSeriesContainer (timeseries_data: pandas.core.frame.DataFrame, approach: str, models: dict, best_model: dict, xcorr: dict)-
A TimeSeriesContainer collect all the relevant information useful to characterizethe time-series coming from the ingested dataset.
Parameters
timeseries_data:DataFrame- Historical time-series data, in the form of a DataFrame with an index and more than one data column.
approach:str- Approach used to cluster time-series data.
models:dict- Dictionary of ModelResult objects, all trained on these time-series.
best_model:dict- Dictionary with the information of the best clustering for all the metrics and corresponding model.
xcorr:dict- Cross-correlation between the data of this time-series and all the other ones.
Expand source code
class TimeSeriesContainer: """ A TimeSeriesContainer collect all the relevant information useful to characterizethe time-series coming from the ingested dataset. Parameters ---------- timeseries_data : DataFrame Historical time-series data, in the form of a DataFrame with an index and more than one data column. approach : str Approach used to cluster time-series data. models : dict Dictionary of ModelResult objects, all trained on these time-series. best_model : dict Dictionary with the information of the best clustering for all the metrics and corresponding model. xcorr : dict Cross-correlation between the data of this time-series and all the other ones. """ def __init__(self, timeseries_data: DataFrame, approach: str, models: dict, best_model: dict, xcorr: dict): self.timeseries_data = timeseries_data self.approach = approach self.models = models self.xcorr = xcorr self.best_model = best_model