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| # Overlay 2 histograms to compare them | |
| def overlaid_histogram(data1, data2, n_bins = 0, data1_name="", data1_color="#539caf", data2_name="", data2_color="#7663b0", x_label="", y_label="", title=""): | |
| # Set the bounds for the bins so that the two distributions are fairly compared | |
| max_nbins = 10 | |
| data_range = [min(min(data1), min(data2)), max(max(data1), max(data2))] | |
| binwidth = (data_range[1] - data_range[0]) / max_nbins | |
| if n_bins == 0 | |
| bins = np.arange(data_range[0], data_range[1] + binwidth, binwidth) | |
| else: | |
| bins = n_bins | |
| # Create the plot | |
| _, ax = plt.subplots() | |
| ax.hist(data1, bins = bins, color = data1_color, alpha = 1, label = data1_name) | |
| ax.hist(data2, bins = bins, color = data2_color, alpha = 0.75, label = data2_name) | |
| ax.set_ylabel(y_label) | |
| ax.set_xlabel(x_label) | |
| ax.set_title(title) | |
| ax.legend(loc = 'best') |
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