plotting

Module Contents

Classes

individual_plotter
ind_list_plotter
comparison_plotter
combo_plotter

Functions

get_logger
plot_2d_map
plot_1d_profile	Plot a 1D intensity profile.
reset_plots
plot_i07_list
plot_chi_profile	Plot a 1D intensity profile versus chi.
plot_contour
plot_i07_list_colab	Colab-friendly version: - Avoids %matplotlib widget/ipympl - Uses ipywidgets.Output() for reliable redraws - Avoids wg.interact auto-display (returns a VBox you can display()) - Observes changes from Text/Dropdown/Checkbox instead of using interact
view_2D_image
remove_colorbars
remove_axes

API

plotting.get_logger(folderpath, name)

plotting.plot_2d_map(loaded_data, loaded_axis, filename, fig: matplotlib.figure.Figure, ax: matplotlib.axes.Axes, logscale, axlabels) → matplotlib.figure.Figure

plotting.plot_1d_profile(loaded_data, loaded_axis, filename, fig: matplotlib.figure.Figure, ax: matplotlib.axes.Axes, logscale, axlabels, label=None) → matplotlib.figure.Figure

Plot a 1D intensity profile.

plotting.reset_plots()

class plotting.individual_plotter(datafolder: str)

Initialization

plot_list_data()

class plotting.ind_list_plotter(folderpath)

Initialization

get_files()

returns a list of files in the folderpath that match the scantype and have .hdf5 extension, sorted by the date part of the filename split by underscores. filenames are of the format: <scantype>_<scannumber>_<date>_<time>.hdf5

set_plot_callback()

set_dataloader()

set_scantype(scantype, heatmap)

_plot_chimap(data_result: giwaxs_toolbox.processing.result2d, filename: str, fig: matplotlib.figure.Figure, ax: matplotlib.axes.Axes, logscale: bool) → matplotlib.figure.Figure

_plot_qmap(data_result: giwaxs_toolbox.processing.result2d, filename: str, fig: matplotlib.figure.Figure, ax: matplotlib.axes.Axes, logscale: bool) → matplotlib.figure.Figure

_plot_exitmap(data_result: giwaxs_toolbox.processing.result2d, filename: str, fig: matplotlib.figure.Figure, ax: matplotlib.axes.Axes, logscale: bool) → matplotlib.figure.Figure

_plot_ivsq(data_result: giwaxs_toolbox.processing.result1d, filename, fig: matplotlib.figure.Figure, ax: matplotlib.axes.Axes, logscale: bool) → matplotlib.figure.Figure

_plot_ivsq_heatmap(data_result: giwaxs_toolbox.processing.result1d, filename, fig: matplotlib.figure.Figure, ax: matplotlib.axes.Axes, logscale) → matplotlib.figure.Figure

_plot_ivschi(data_result: giwaxs_toolbox.processing.result1d, filename, fig: matplotlib.figure.Figure, ax: matplotlib.axes.Axes, logscale: bool) → matplotlib.figure.Figure

create_plot()

class plotting.comparison_plotter(datafolder: str)

Initialization

plot_files(filenames: list, index1vals: numpy.ndarray | None = None, index2vals: numpy.ndarray | None = None, logscale=False)

class plotting.combo_plotter(datafolder: str)

Initialization

plot_files(filenames: list, index1vals: numpy.ndarray | None = None, index2vals: numpy.ndarray | None = None, logscale=False)

plot_ivsq(filenames: list, index1vals: numpy.ndarray | None = None, index2vals: numpy.ndarray | None = None, logscale: bool = False)

plot_ivschi(filenames: list, index1vals: numpy.ndarray | None = None, index2vals: numpy.ndarray | None = None, logscale: bool = False)

plot_exitmap(filenames: list, index1vals: numpy.ndarray | None = None, index2vals: numpy.ndarray | None = None, logscale: bool = False)

plot_qmap(filenames: list, index1vals: numpy.ndarray | None = None, index2vals: numpy.ndarray | None = None, logscale: bool = False)

plot_chimap(filenames: list, index1vals: numpy.ndarray | None = None, index2vals: numpy.ndarray | None = None, logscale: bool = False)

plotting.plot_i07_list(dirpath: pathlib.Path, scantype: str, title=None)

plotting.plot_chi_profile(chi, intensity, chi_min=None, chi_max=None, logscale=False, title='Chi Profile', label=None)

Plot a 1D intensity profile versus chi.

plotting.plot_contour(csv_file, outfile, cmap='viridis', levels=100, figsize=(10, 6))

plotting.plot_i07_list_colab(dirpath: pathlib.Path, scantype: str, title=None)

Colab-friendly version: - Avoids %matplotlib widget/ipympl - Uses ipywidgets.Output() for reliable redraws - Avoids wg.interact auto-display (returns a VBox you can display()) - Observes changes from Text/Dropdown/Checkbox instead of using interact

plotting.view_2D_image(img_data, cmap='viridis', flip_vertical=False, flip_horizontal=False)

plotting.remove_colorbars(fig)

plotting.remove_axes(fig)