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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: 0 for k in hierarchy_data.keys()} |
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for sector_name in hierarchy_data: |
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for k,v in hierarchy_data[sector_name]['child'].items(): |
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sectors[sector_name] += len(v['child']) |
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sectors[sector_name] += 1 |
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name2color = {"organ": "#E41A1C", "abnormality": "#377EB8", "histology": "#4DAF4A"} |
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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(hierarchy_data[sector]['child'])) |
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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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outer_track_font_size = 9 |
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circos = Circos(sectors, space=8.8) |
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for sector in circos.sectors: |
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idx2label = {} |
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idx = 1 |
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for k,v in hierarchy_data[sector.name.lower()]['child'].items(): |
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for k1,v1 in v['child'].items(): |
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idx2label[idx] = k1 |
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idx += 1 |
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idx2label[idx] = '' |
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idx2label[0] = '' |
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track_outer = sector.add_track((100, 101)) |
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track_outer.xticks_by_interval( |
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1, |
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tick_length=0, |
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outer=True, |
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show_bottom_line=False, |
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label_orientation="vertical", |
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label_formatter=lambda v: idx2label[int(v)], |
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label_size=outer_track_font_size, |
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show_endlabel=True |
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) |
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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 i, (k,v) in enumerate(hierarchy_data[sector.name.lower()]['child'].items()): |
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sect_size = len(v['child']) if i != len(hierarchy_data[sector.name.lower()]['child'])-1 else len(v['child'])+1 |
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if i == 0: |
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sect_size += 0.5 |
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if i == len(hierarchy_data[sector.name.lower()]['child'])-1: |
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sect_size -= 0.5 |
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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.replace('abnormality', 'abn.').replace(' anatomies', '').replace(' disturbance', '').replace('other abn.', 'Other').replace('liver', '').replace('pancreas', '').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+1 , sector.end-1 , int(sector.size)-1) |
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y = [target_counts[idx2label[i+1]] for i in range(0,len(x))] |
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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/figure_1a.pdf') |
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plt.show() |
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