method normalize(data, a, b) Normalize the series to a optional range, usualy within `(-1, 1)` or `(0, 1)`. Namespace types: array<float> Parameters: data (array<float>): Sample data to normalize. a (float): Minimum target range value, `default=-1.0`. b (float): Minimum target range value, `default= 1.0`. Returns: Normalized array within new range. ___
Reference: *Time Series Classification: A review of Algorithms and Implementations*.
normalize_series(source, length, a, b) Normalize the series to a optional range, usualy within `(-1, 1)` or `(0, 1)`.\ *Note that this may provide a different result than the array version due to rolling range*. Parameters: source (float): Series to normalize. length (int): Number of bars to sample the range. a (float): Minimum target range value, `default=-1.0`. b (float): Minimum target range value, `default= 1.0`. Returns: Normalized series within new range.
method polar(data) Turns a normalized sample array into polar coordinates. Namespace types: array<float> Parameters: data (array<float>): Sampled data values. Returns: Converted array into polar coordinates.
polar_series(source) Turns a normalized series into polar coordinates. Parameters: source (float): Source series. Returns: Converted series into polar coordinates.
method gasf(data) Gramian Angular Summation Field *`GASF`*. Namespace types: array<float> Parameters: data (array<float>): Sampled data values. Returns: Matrix with *`GASF`* values.
method gasf_id(data) Trig. identity of Gramian Angular Summation Field *`GASF`*. Namespace types: array<float> Parameters: data (array<float>): Sampled data values. Returns: Matrix with *`GASF`* values. Reference: *Time Series Classification: A review of Algorithms and Implementations*.
method gadf(data) Gramian Angular Difference Field *`GADF`*. Namespace types: array<float> Parameters: data (array<float>): Sampled data values. Returns: Matrix with *`GADF`* values.
method gadf_id(data) Trig. identity of Gramian Angular Difference Field *`GADF`*. Namespace types: array<float> Parameters: data (array<float>): Sampled data values. Returns: Matrix with *`GADF`* values. Reference: *Time Series Classification: A review of Algorithms and Implementations*.
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