src package

Submodules

src.compare_references module

This script compares different reference systems against each other.

src.compare_references.detect_outlier(data, column, reference_column, z_threshold=3, maximum_deviation=0.25)

Detect outliers based on z-score and maximum deviation.

Parameters

  • data (DataFrame) – DataFrame with the data

  • column (str) – name of the column under consideration

  • reference_column (str) – name of the reference column matching the data column

  • z_threshold (float) – cutoff value for z-score

  • maximum_deviation (float) – cutoff value for deviation between systems

Returns

boolean vector indicating outliers

Return type

np.array

src.compare_references.draw_reg_line_and_info(data, outlier, column, reference_column, axis)

Plot regression line and parameters.

Parameters

  • data (DataFrame) – DataFrame with actual data

  • outliers (np.array) – Boolean array, indicating if the row is an outlier

  • column (str) – name of the column under consideration

  • reference_column (str) – name of the reference column matching the data column

  • axis (matplotlib.axis) – axis to plot on

Returns

None

src.compare_references.reg_line(x, y)

Calculate regression line for data.

Parameters

  • x (list[float]) – data x values

  • y (list[float]) – data y values

Returns

x values of the regression line, y values of the regression line, calculated regression line parameters (gradient, intercept, r_value, p_value, std_err, rmse, mae), p-values of the statistical model, confidence interval

Return type

tuple(list[float], ..)

src.pipeline_playground module

This script is meant to demonstrate the usage of the pipeline. Please note inline documentation.