topostats.plottingfuncs

Plotting data.

Module Contents

Classes

Images

Plots image arrays.

Functions

add_pixel_to_nm_to_plotting_config(→ dict)	Add the pixel to nanometre scaling factor to plotting configs.
dilate_binary_image(→ numpy.typing.NDArray)	Dilate a supplied binary image a given number of times.
load_mplstyle(→ None)	Load the Matplotlibrc parameter file.
add_bounding_boxes_to_plot(→ tuple)	Add the bounding boxes to a plot.
set_n_ticks(→ None)	Set the number of ticks along the y and x axes and lets matplotlib assign the values.

Attributes

LOGGER

topostats.plottingfuncs.LOGGER

topostats.plottingfuncs.add_pixel_to_nm_to_plotting_config(plotting_config: dict, pixel_to_nm_scaling: float) → dict

Add the pixel to nanometre scaling factor to plotting configs.

Ensures plots are in nanometres and not pixels.

Parameters:

• plotting_config (dict) – TopoStats plotting configuration dictionary.

• pixel_to_nm_scaling (float) – Pixel to nanometre scaling factor for the image.

Returns:

Updated plotting config with the pixel to nanometre scaling factor applied to all the image configurations.

Return type:

dict

topostats.plottingfuncs.dilate_binary_image(binary_image: numpy.typing.NDArray, dilation_iterations: int) → numpy.typing.NDArray

Dilate a supplied binary image a given number of times.

Parameters:

• binary_image (npt.NDArray) – Binary image to be dilated.

• dilation_iterations (int) – Number of dilation iterations to be performed.

Returns:

Dilated binary image.

Return type:

npt.NDArray

topostats.plottingfuncs.load_mplstyle(style: str | pathlib.Path) → None

Load the Matplotlibrc parameter file.

Parameters:

style (str | Path) – Path to a Matplotlib Style file.

class topostats.plottingfuncs.Images(data: numpy.array, output_dir: str | pathlib.Path, filename: str, style: str | pathlib.Path = None, pixel_to_nm_scaling: float = 1.0, masked_array: numpy.array = None, title: str = None, image_type: str = 'non-binary', image_set: str = 'core', core_set: bool = False, pixel_interpolation: str | None = None, cmap: str | None = None, mask_cmap: str = 'jet_r', region_properties: dict = None, zrange: list = None, colorbar: bool = True, axes: bool = True, num_ticks: tuple[int | None] = (None, None), save: bool = True, savefig_format: str | None = None, histogram_log_axis: bool = True, histogram_bins: int | None = None, savefig_dpi: str | float | None = None)

Plots image arrays.

Parameters:

• data (np.array) – Numpy array to plot.

• output_dir (Union[str, Path]) – Output directory to save the file to.

• filename (Union[str, Path]) – Filename to save image as.

• style (dict) – Filename of matploglibrc Params.

• pixel_to_nm_scaling (float) – The scaling factor showing the real length of 1 pixel, in nm.

• masked_array (npt.NDArray) – Optional mask array to overlay onto an image.

• title (str) – Title for plot.

• image_type (str) – The image data type - binary or non-binary.

• image_set (str) – The set of images to process - core or all.

• core_set (bool) – Flag to identify image as part of the core image set or not.

• pixel_interpolation (str | None) – Interpolation to use (default: None).

• cmap (str) – Colour map to use (default ‘nanoscope’, ‘afmhot’ also available).

• mask_cmap (str) – Colour map to use for the secondary (masked) data (default ‘jet_r’, ‘blu’ proivides more contrast).

• region_properties (dict) – Dictionary of region properties, adds bounding boxes if specified.

• zrange (list) – Lower and upper bound to clip core images to.

• colorbar (bool) – Optionally add a colorbar to plots, default is False.

• axes (bool) – Optionally add/remove axes from the image.

• num_ticks (tuple[int | None]) – The number of x and y ticks to display on the image.

• save (bool) – Whether to save the image.

• savefig_format (str) – Format to save the image as.

• histogram_log_axis (bool) – Optionally use a logarithmic y axis for the histogram plots.

• histogram_bins (int) – Number of bins for histograms to use.

• savefig_dpi (str | float | None) – The resolution of the saved plot (default ‘figure’).

plot_histogram_and_save() → tuple | None

Plot and save a histogram of the height map.

Returns:

Matplotlib.pyplot figure object and Matplotlib.pyplot axes object.

Return type:

tuple | None

plot_and_save()

Plot and save the image.

Returns:

Matplotlib.pyplot figure object and Matplotlib.pyplot axes object.

Return type:

tuple

save_figure()

Save figures as plt.savefig objects.

Returns:

Matplotlib.pyplot figure object and Matplotlib.pyplot axes object.

Return type:

tuple

topostats.plottingfuncs.add_bounding_boxes_to_plot(fig, ax, shape: tuple, region_properties: list, pixel_to_nm_scaling: float) → tuple

Add the bounding boxes to a plot.

Parameters:

• fig (plt.figure.Figure) – Matplotlib.pyplot figure object.

• ax (plt.axes._subplots.AxesSubplot) – Matplotlib.pyplot axes object.

• shape (tuple) – Tuple of the image-to-be-plot’s shape.

• region_properties (list) – Region properties to add bounding boxes from.

• pixel_to_nm_scaling (float) – The scaling factor from px to nm.

Returns:

Matplotlib.pyplot figure object and Matplotlib.pyplot axes object.

Return type:

tuple

topostats.plottingfuncs.set_n_ticks(ax: matplotlib.pyplot.Axes.axes, n_xy: list[int | None, int | None]) → None

Set the number of ticks along the y and x axes and lets matplotlib assign the values.

Parameters:

• ax (plt.Axes.axes) – The axes to add ticks to.

• n_xy (list[int, int]) – The number of ticks.

Returns:

The axes with the new ticks.

Return type:

plt.Axes.axes