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Add distance summary plots #48
Commits on Dec 6, 2023
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Add connectome summary plotting functionality
This commit adds the functionality to generate a summary plot of AFID distances on a connectome using nilearn.plotting to do so. In doing so, a complete set of AfidSet distances are provided as an argument, and coloured based on their distance from "expected" (ground-truth). Approporiate unit tests are also added in to make sure plots are generated and of the correct type. During development, generated plots were visually assessed to ensure generated plots are as expected. Note: a `pyright: ignore` has been temporarily added to line 230 in plotting.py until other plot_types are implemented in order to bypass the pyright error being thrown.
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Add histogram summary plotting functionality
This commit adds the functionality to generate a summary histogram plot of AFID distances using `plotly`. In doing so, an optional argument has been added - `afid_labels` for labelling the histogram. If not provided, `afid_labels`, indices are used to label the histogram. Appropriate unit tests are also added. During development, generated plots were visually assessed. Note: `pyright: ignore` have been added where `afid_labels` is not expected to be None. Also added type stubs for plotly.
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Take actual value of distances (instead of abs)
Knowing if the "distance" is negative can provide some insight - this is mostly for plotting distances along specific spatial components (e.g. x, y, z). These distances will be automatically set in the histogram and upcoming scatter plots. For the connectome plot, the minimum node value is set by either taking the smallest value (if negative) or 0 (if positive).
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Add scatter summary plotting functionality
This commit adds functionality to generate a summary scatter plot of AFID distances using `plotly`. Similar to generating a histogram plot, this also makes use of the new `afid_labels` argument to label the markers. If not porvided, indices are used to label the scatter plot. Appropriate unit tests are alos added, with generated plots visually assessed during development.
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Add callable helper for slow data generation
Some tests may fail a HealthCheck due to slow data generation - namely any tests that try to generate an entire AfidSet. This commit adds a function to the helpers that disables this check.
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This commit adds the slow_generation decorator where appropriate to disable the health checks for tests where data generation is slow. Additionally, delete the view that is created from plot_ortho for memory considerations (`close()` is not a valid command for these views).
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