topostats.plottingfuncs#
Plotting data.
Attributes#
Classes#
Plots image arrays. |
Functions#
Add the pixel to nanometre scaling factor to plotting configs. |
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Dilate a supplied binary image a given number of times. |
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Load the Matplotlibrc parameter file. |
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Add the bounding boxes to a plot. |
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Set the number of ticks along the y and x axes and lets matplotlib assign the values. |
Module Contents#
- 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:
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 #
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
- topostats.plottingfuncs.load_mplstyle(style: str | pathlib.Path) None #
Load the Matplotlibrc parameter file.
- Parameters:
style (str | Path) – Path to a Matplotlib Style file.
- Returns:
Only loads the style file.
- Return type:
None
- 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: list[int | None, 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.
- 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#
- num_ticks#
- save#
- savefig_format#
- histogram_log_axis#
- histogram_bins#
- savefig_dpi#
- plot_histogram_and_save()#
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()#
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()#
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 #
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 #
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.
- 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