upxo.viz.dataviz module

upxo.viz.dataviz.see_distr(self, gsdim=2, vis='hist', prop_data_format='dataframe', prop_df=None, prop_names=['area', 'perimeter', 'orientation', 'solidity'], props={'area': [], 'orientation': [], 'perimeter': [], 'solidity': []}, prop_units={'area': 'μm²', 'orientation': 'degrees', 'perimeter': 'μm', 'solidity': ''}, probability_density=False, nbins_values={'area': 30, 'orientation': 30, 'perimeter': 30, 'solidity': 30}, bw_adjust_values={'area': None, 'orientation': None, 'perimeter': None, 'solidity': None}, alpha_values={'area': 0.7, 'orientation': 0.7, 'perimeter': 0.7, 'solidity': 0.7}, color_values={'area': 'blue', 'orientation': 'blue', 'perimeter': 'blue', 'solidity': 'blue'}, edgecolor_values={'area': 'black', 'orientation': 'black', 'perimeter': 'black', 'solidity': 'black'}, binsize=30, alpha=0.7, color='blue', edgecolor='black', ncolumns=3, ylabel='count')[source]

Plot distributions of multiple grain properties in subplots

Parameters:

  • gsdim (int, optional) – Dimensionality of the grain structure data (2 for 2D, 3 for 3D). Default is 2.

  • vis (str, optional) – Visualization type: ‘hist’ for histogram, ‘kde’ for kernel density estimate, or ‘hist_kde’ for both overlaid. Default is ‘hist’.

  • prop_data_format (str, optional) – Format of the property data source. Options are ‘dataframe’ or ‘dict’. Default is ‘dataframe’.

  • prop_df (pandas.DataFrame, optional) – DataFrame containing grain properties if prop_data_format is ‘dataframe’. Default is None.

  • prop_names (list of str, optional) – List of grain property names to plot distributions for. Default includes ‘area’, ‘perimeter’, ‘orientation’, and ‘solidity’.

  • props (dict, optional) – Dictionary of grain properties if prop_data_format is ‘dict’. Default is empty dict.

  • prop_units (dict, optional) – Dictionary mapping property names to their units for labeling axes. Default units are provided for common properties.

  • probability_density (bool, optional) – If True, normalize distributions to form a probability density. Default is False.

  • nbins_values (dict, optional) – Dictionary specifying number of bins for each property. Default is 30 bins for each.

  • bw_adjust_values (dict, optional) – Dictionary specifying bandwidth adjustment for KDE plots. If None for a property, optimal bandwidth is calculated automatically using Scott’s rule. Default is None for all.

  • alpha_values (dict, optional) – Dictionary specifying transparency (alpha) for each property distribution. Default is 0.7.

  • color_values (dict, optional) – Dictionary specifying fill color for each property distribution. Default is ‘blue’.

  • edgecolor_values (dict, optional) – Dictionary specifying edge color for each property distribution. Default is ‘black’.

  • binsize (int, optional) – Default number of bins to use if not specified in nbins_values. Default is 30

  • alpha (float, optional) – Default transparency (alpha) to use if not specified in alpha_values. Default is 0

  • color (str, optional) – Default fill color to use if not specified in color_values. Default is ‘blue’.

  • edgecolor (str, optional) – Default edge color to use if not specified in edgecolor_values. Default is ‘black’.

  • ncolumns (int, optional) – Number of columns in the subplot grid. Default is 3.

  • ylabel (str, optional) – Label for the y-axis. Default is ‘count’.

Return type:

None

Notes

This function creates distributions for specified grain properties in a grid of subplots. It supports data input as either a pandas DataFrame or a dictionary of properties.

Usage

from upxo.viz.dataviz import see_distr