upxo.viz.gbviz module

gbviz.py

Grain-boundary segment visualization for UPXO: plotting labeled grain-boundary segment images, isolating a single segment by ID, and overlaying junction-point markers styled by junction order.

upxo.viz.gbviz.see_all_gbsegs(gbsegImage, figsize=(5, 5), dpi=75, cmap='nipy_spectral', title='GB segments', xlabel='X-axis, um', ylabel='Y-axis, um', cbarLabel='Segment ID (float)')[source]

Visualize the GB segments in the given image.

Parameters:

  • gbsegImage (2D array-like) – The image containing the GB segments, where each segment is represented by a unique ID (float).

  • figsize (tuple of float, optional) – Matplotlib figure size in inches. Default (5, 5).

  • dpi (int, optional) – Figure resolution. Default 75.

  • cmap (str, optional) – Matplotlib colormap name for the segment-ID image. Default ‘nipy_spectral’.

  • title (str, optional) – Plot title. Default “GB segments”.

  • xlabel (str, optional) – X-axis label. Default “X-axis, um”.

  • ylabel (str, optional) – Y-axis label. Default “Y-axis, um”.

  • cbarLabel (str, optional) – Colorbar label. Default “Segment ID (float)”.

  • Usage

  • -----

  • gbViz (import upxo.viz.gbviz as)

  • as (Use)

upxo.viz.gbviz.see_gbsegs_fid(gbsegImage, fid, figsize=(5, 5), dpi=75, cmap='nipy_spectral', title='GB segments', xlabel='X-axis, um', ylabel='Y-axis, um', cbarLabel='Segment ID (float)')[source]

import upxo.viz.gbviz as gbViz Use as: gbViz.see_gbsegs_fid

upxo.viz.gbviz.see_gbsegs_jp_by_jpo(gbsegs, jps_by_order, style_by_order=None, default_style=None, figsize=(5, 5), dpi=80, legend_anchor=(1.02, 1.0), ms2=4, ms3=4, ms4=4, ms5=4, legend_loc='upper left', legend_title='Junction point data', legend_frameon=True, hide_axis=True, cmap='rainbow')[source]

Import import upxo.viz.gbviz as gbViz Use as: gbViz.plot_gbsegs_by_order