utility functions

Utils

class SeqMetrics.utils.plot_metrics(metrics: dict, ranges: tuple = ((0.0, 1.0), (1.0, 10), (10, 1000)), exclude: list | None = None, plot_type: str = 'bar', max_metrics_per_fig: int = 15, show: bool = True, save: bool = False, save_path: str = '', **kwargs)[source]

Plots the metrics given as dictionary as radial or bar plot between specified ranges.

Parameters:

  • metrics – dictionary whose keys are names are erros and values are error values.

  • ranges – tuple of tuples defining range of errors to plot in one plot

  • exclude – List of metrics to be excluded from plotting.

  • max_metrics_per_fig – maximum number of metrics to show in one figure.

  • plot_type – either of radial or bar.

  • show – If, then figure will be shown/drawn

  • save – if True, the figure will be saved.

  • save_path – if given, the figure will the saved at this location.

  • kwargs – keyword arguments for plotting

Examples

>>> import numpy as np
>>> from SeqMetrics import RegressionMetrics
>>> from SeqMetrics import plot_metrics
>>> t = np.random.random((20, 1))
>>> p = np.random.random((20, 1))
>>> er = RegressionMetrics(t, p)
>>> all_errors = er.calculate_all()
>>> plot_metrics(all_errors, plot_type='bar', max_metrics_per_fig=50)
>>> # or draw the radial plot
>>> plot_metrics(all_errors, plot_type='radial', max_metrics_per_fig=50)

```

_images/reg1.png _images/reg2.png
SeqMetrics.utils.treat_arrays(true, predicted, remove_nan: bool = True, remove_inf: bool = True, replace_nan: int | float | None = None, remove_zero=None, remove_neg=None, replace_inf: int | float | None = None)[source]

processes the true and predicted arrays.

Parameters:

  • true (array_like) – array of true/actual/measured/observed values

  • predicted (array_like) – array of predicted/simulated/calculated values

  • remove_nan (bool, default True) – if True, remove the NaN values from (both) the arrays

  • remove_inf (bool, default True) – if True, remove the infinite values from (both) the arrays

  • replace_nan (float, default None) – if provided, replace the NaN values with this value in both arrays. If given, remove_nan will have no effect.

  • remove_zero (bool, default None) – if True, remove the zero values from (both) the arrays

  • remove_neg (bool, default None) – if True, remove the negative values from (both) the arrays

  • replace_inf (float, default None) – if provided, replace the infinite values with this value in both arrays. If given, remove_inf will have no effect.