tsfresh enforces a strict naming of the created features, which you have to follow whenever you create new feature calculators. This is due to the tsfresh.feature_extraction.settings.from_columns() method which needs to deduce the following information from the feature name:

the time series that was used to calculate the feature

the feature calculator method that was used to derive the feature

all parameters that have been used to calculate the feature (optional)

Hence, to enable the tsfresh.feature_extraction.settings.from_columns() to deduce all the necessary conditions, the features should be named in the following format:

{time_series_name}__{feature_name}__{parameter name 1}_{parameter value 1}__[..]__{parameter name k}_{parameter value k}

Here, we assumed that {feature_name} has k parameters.

So for example the following feature name:

temperature_1__quantile__q_0.6

is the value of the feature tsfresh.feature_extraction.feature_calculators.quantile() for the time series `temperature_1` and a parameter value of q=0.6. On the other hand, the feature named:

Pressure 5__cwt_coefficients__widths_(2, 5, 10, 20)__coeff_14__w_5

denotes the value of the feature tsfresh.feature_extraction.feature_calculators.cwt_coefficients() for the time series `Pressure 5` under parameter values of widths=(2, 5, 10, 20), coeff=14 and w=5.