topostats.plottingfuncs#

Plotting data.

Attributes#

LOGGER

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.ndarray)

Dilate a supplied binary image a given number of times.

add_bounding_boxes_to_plot(→ None)

Add the bounding boxes to a plot.

Module Contents#

topostats.plottingfuncs.LOGGER#
topostats.plottingfuncs.add_pixel_to_nm_to_plotting_config(plotting_config: dict, pixel_to_nm_scaling: float) → dict[source]#

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:

plotting_config – 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.ndarray, dilation_iterations: int) → numpy.ndarray[source]#

Dilate a supplied binary image a given number of times.

Parameters:

  • binary_image (np.ndarray) – Binary image to be dilated

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

Returns:

binary_image – Dilated binary image

Return type:

np.ndarray

class topostats.plottingfuncs.Images(data: numpy.array, output_dir: str | pathlib.Path, filename: str, 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 = 'nanoscope', mask_cmap: str = 'jet_r', region_properties: dict = None, zrange: list = None, colorbar: bool = True, axes: bool = True, save: bool = True, save_format: str = 'png', histogram_log_axis: bool = True, histogram_bins: int = 200, dpi: str | float = 'figure')[source]#

Plots image arrays.

data#
output_dir#
filename#
pixel_to_nm_scaling#
masked_array#
title#
image_type#
image_set#
core_set#
interpolation#
cmap#
mask_cmap#
region_properties#
zrange#
colorbar#
axes#
save#
save_format#
histogram_log_axis#
histogram_bins#
dpi#
plot_histogram_and_save()[source]#

Plot and save a histogram of the height map.

Returns:

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

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

plot_and_save()[source]#

Plot and save the images with savefig or imsave depending on config file parameters.

Returns:

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

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

save_figure()[source]#

Save figures as plt.savefig objects.

Returns:

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

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

save_array_figure() → None[source]#

Save the image array as an image using plt.imsave().

topostats.plottingfuncs.add_bounding_boxes_to_plot(fig, ax, shape, region_properties: list, pixel_to_nm_scaling: float) → None[source]#

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 – Region properties to add bounding boxes from.

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

Returns:

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

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