qmmd.qmcalc.visAnalysis.plotFigs
Attributes
Functions
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Plot linear regression line and its equation/R2. |
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Plot benchmarking statistical measures. |
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Plot elimination barriers. |
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Plot various regression analyses. |
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Internal helper to plot a single regression analysis. |
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Internal helper to plot multiple charge correlations. |
Module Contents
- qmmd.qmcalc.visAnalysis.plotFigs.lin_reg(m: float, c: float, r2: float, xlimit: Tuple[float, float], leg_loc: str, font_size: str = 'x-small') None
Plot linear regression line and its equation/R2.
- Parameters:
m (float) – Slope.
c (float) – Intercept.
r2 (float) – R-squared value.
xlimit (Tuple[float, float]) – X-axis limits.
leg_loc (str) – Legend location.
font_size (str, optional) – Font size for the legend.
- qmmd.qmcalc.visAnalysis.plotFigs.plot_benchmarking_bar(save_path: str = 'Benchmarking Statistical Measures.png') None
Plot benchmarking statistical measures.
- Parameters:
save_path (str, optional) – Path to save the plot.
- qmmd.qmcalc.visAnalysis.plotFigs.plot_barriers_bar(save_path: str = 'Elimination Barrier for Different Mechanisms.png') None
Plot elimination barriers.
- Parameters:
save_path (str, optional) – Path to save the plot.
- qmmd.qmcalc.visAnalysis.plotFigs.plot_regression_analysis(data_path: str = '.', combination: str = 'outputs/CombinationI') None
Plot various regression analyses.
- Parameters:
data_path (str, optional) – Path to the data directory.
combination (str, optional) – Combination ID.
- qmmd.qmcalc.visAnalysis.plotFigs._plot_single_regression(df: pandas.DataFrame, config_dict: Dict[str, Any], x_col: str, y_col: str, x_label: str, y_label: str, save_path: str) None
Internal helper to plot a single regression analysis.
- qmmd.qmcalc.visAnalysis.plotFigs._plot_charge_correlations(df: pandas.DataFrame, prop_dict: Dict[str, Any], combination: str) None
Internal helper to plot multiple charge correlations.
- qmmd.qmcalc.visAnalysis.plotFigs.parser