Implementing Histograms
Self-similarity histograms are needed to give user more information on the homogeneity of their sample.
To achieve this:
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Added a function which calculates the self-similarity metrics, the mean and std for the required dataset - calculate_self_similarity(). This function works out the KS scores between all gridsquares within the dataset.
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Added a function which plots the self-similarity metrics as a histogram. The mean and std values are also displayed on the graph - plot_self_sim_results(). These histograms are displayed on the website, alongside a self-sim hist interpretation guide.