datamod package¶
Submodules¶
Module contents¶
Data handling module.
The aim of the datamod package is to handle the data.
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class
datamod.get_data(file)¶ Bases:
objectImport data from an external file.
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dim_in¶ Number of input dimensions.
Type: int
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col_names¶ Names of columns.
Type: list
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dim_out¶ Number of output dimensions.
Type: int
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coordinates¶ Samples coordinates.
Type: np.array
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response¶ Sample response.
Type: np.array
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input¶ Normalized input samples.
Type: np.array
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output¶ Normalized output samples.
Type: np.array
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norm_in¶ Input normalization factors.
Type: np.array
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norm_out¶ Output normalization factors.
Type: np.array
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range_in¶ Range of the input data.
Type: np.array
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range_out¶ Range of the output data.
Type: np.array
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datamod.get_range(data)¶ Determine the range of the data.
Parameters: data (np.array) – Data to analyze. Returns: Ranges of the given data. Return type: ranges (np.array)
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datamod.load_problem(name)¶ Load a pre-defined benchmark problem.
Parameters: name (str) – Name of the desired problem. Returns: Benchmark problem. range_in (np.array): Input parameter allowable ranges. dim_in (int): Number of input dimensions. dim_out (int): Number of output dimensions. n_constr (int): Number of constraints. Return type: problem ()
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datamod.normalize(data)¶ Normalize the data to the [-1,1] range.
Parameters: data (np.array) – Data to normalize.
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datamod.scale(data, ranges)¶ Scale data from [-1,1] range to original range.
Parameters: - data (np.array) – Data to scale.
- ranges (np.array) – Normalization ranges.
- Returns (np.array):
- data_scale: Scaled data.