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import os |
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import json |
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import numpy as np |
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import seaborn as sns |
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from scipy.stats import boxcox |
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from pycirclize import Circos |
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import matplotlib.pyplot as plt |
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base_dir = 'metadata' |
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with open(os.path.join(base_dir,'hierarchy.json'), 'r') as f: |
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hierarchy_data = json.load(f) |
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with open(os.path.join(base_dir,'target_counts.json'), 'r') as f: |
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target_counts = json.load(f) |
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with open(os.path.join(base_dir,'modality_counts.json'), 'r') as f: |
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modality_counts = json.load(f) |
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sectors = {k: len(v) for k,v in modality_counts.items()} |
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name2color = { |
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"MRI": "#005A9E", |
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"CT": "#FF7F00", |
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"pathology": "#984EA3", |
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"ultrasound": "#7BC8F6", |
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"X-Ray": "#999999", |
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"fundus": "#76B041", |
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"dermoscopy": "#FDBF6F", |
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"endoscope": "#C0392B", |
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"OCT": "#33A02C", |
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} |
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def generate_shades(base_color, n): |
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return sns.light_palette(base_color, n + 2)[1:-1] |
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color_schemes = {} |
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for sector in sectors: |
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child_colors = generate_shades(name2color[sector], len(modality_counts[sector])) |
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color_schemes[sector] = child_colors |
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parent_track_ratio = (72, 85) |
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middle_track_ratio = (85, 100) |
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bar_track_ratio = (45, 70) |
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parent_track_font_size = 7 |
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middle_track_font_size = 5.5 |
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bar_track_font_size = 7 |
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circos = Circos(sectors, space=6) |
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for sector in circos.sectors: |
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track = sector.add_track(parent_track_ratio) |
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track.axis(fc=name2color[sector.name], lw=0) |
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track.text(sector.name.capitalize().replace('Mri', 'MRI').replace('Ct', 'CT').replace('Oct', 'OCT').replace('Dermoscopy', "DS"), color="white", size=parent_track_font_size) |
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track1 = sector.add_track(middle_track_ratio, r_pad_ratio=0.1) |
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sect_start = 0 |
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color_idx = 0 |
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for k,v in modality_counts[sector.name].items(): |
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sect_size = 1 |
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track1.rect(sect_start, sect_start+sect_size, r_lim=(middle_track_ratio[0], middle_track_ratio[1]-1) , ec="black", lw=0,fc=color_schemes[sector.name][color_idx]) |
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color_idx += 1 |
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track1.text(k.capitalize(), sect_start+sect_size/2, color="black", size=middle_track_font_size) |
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sect_start += sect_size |
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x = np.linspace(sector.start+0.5, sector.end-0.5, int(sector.size)) |
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y = [v for k,v in modality_counts[sector.name].items()] |
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y_box = boxcox(y, 0.35) |
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track2 = sector.add_track(bar_track_ratio, r_pad_ratio=0.1) |
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track2.axis() |
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track2.yticks([1.14, 2.29, 3.43, 4.58], ["10$^2$", "10$^3$", "10$^4$", "10$^5$"], label_size=bar_track_font_size-1) |
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track2.bar(x, y_box, color=name2color[sector.name], alpha=0.5, align="center", lw=0) |
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fig = circos.plotfig() |
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fig.savefig('plots/data_target_modality.pdf') |
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plt.show() |
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