`elasticai.preprocessor._plot_helper`#

Module Contents#

`get_textsize_paper`	Getting the fontsize (best practice) for publishing in papers
`get_plot_color_inactive`	Getting the color for plotting non-spike activity in transient plots
`get_plot_color`	Getting the color string
`get_plot_marker`	Getting the marker for plotting
`cm_to_inch`	Translation figure size
`save_figure`	Saving figure in given format Args: fig: Matplot which will be saved path: Path for saving the figure name: Name of the plot formats: List with data formats for saving the figures Returns: None
`extract_minmax_for_logarithmic_limits`	Function for extracting the min-max value of given data for defining the logarithmic limits
`scale_auto_value`	Getting the scaling value and corresponding string notation for unit scaling in plots Args: data: Array or value for calculating the SI scaling value Returns: Tuple with [0] = scaling value and [1] = SI pre-unit
`translate_unit_to_scale_value`	Translating the unit of a value from string to float

elasticai.preprocessor._plot_helper.get_textsize_paper() → int[source]#: Getting the fontsize (best practice) for publishing in papers

elasticai.preprocessor._plot_helper.get_plot_color_inactive() → str[source]#: Getting the color for plotting non-spike activity in transient plots

elasticai.preprocessor._plot_helper.get_plot_color(idx: int) → str[source]#: Getting the color string

elasticai.preprocessor._plot_helper.get_plot_marker(idx: int) → str[source]#: Getting the marker for plotting

elasticai.preprocessor._plot_helper.cm_to_inch(value: float) → float[source]#: Translation figure size

elasticai.preprocessor._plot_helper.save_figure(fig, path: str, name: str, formats: list = ['pdf', 'svg']) → None[source]#: Saving figure in given format Args: fig: Matplot which will be saved path: Path for saving the figure name: Name of the plot formats: List with data formats for saving the figures Returns: None

elasticai.preprocessor._plot_helper.extract_minmax_for_logarithmic_limits(data: numpy.ndarray) → tuple[float, float][source]#

Function for extracting the min-max value of given data for defining the logarithmic limits

elasticai.preprocessor._plot_helper.scale_auto_value(data: float | numpy.ndarray) → tuple[float, str][source]#: Getting the scaling value and corresponding string notation for unit scaling in plots Args: data: Array or value for calculating the SI scaling value Returns: Tuple with [0] = scaling value and [1] = SI pre-unit

elasticai.preprocessor._plot_helper.translate_unit_to_scale_value(unit_str: str, pos: int) → float[source]#

Translating the unit of a value from string to float

Parameters:

Returns:

Scaled value