plot legend with titles
This commit is contained in:
Luis Aleixo
parent
158320e522
commit
0350b1e8e6
1 changed files with 48 additions and 21 deletions
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@ -2,6 +2,7 @@ from dataclasses import field
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import numpy as np
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import matplotlib.pyplot as plt
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import matplotlib.lines as mlines
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from matplotlib.patches import Rectangle
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import pandas as pd
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import csv
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@ -11,6 +12,7 @@ from cara.monte_carlo.data import activity_distributions
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from tqdm import tqdm
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from scipy.spatial import ConvexHull
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def get_enclosure_points(x_coordinates, y_coordinates):
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df = pd.DataFrame({'x': x_coordinates, 'y': y_coordinates})
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@ -19,12 +21,13 @@ def get_enclosure_points(x_coordinates, y_coordinates):
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hull = ConvexHull(points)
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# get x and y coordinates
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# repeat last point to close the polygon
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x_hull = np.append(points[hull.vertices,0],
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points[hull.vertices,0][0])
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y_hull = np.append(points[hull.vertices,1],
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points[hull.vertices,1][0])
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x_hull = np.append(points[hull.vertices, 0],
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points[hull.vertices, 0][0])
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y_hull = np.append(points[hull.vertices, 1],
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points[hull.vertices, 1][0])
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return x_hull, y_hull
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SAMPLE_SIZE = 50000
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fig = plt.figure()
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@ -89,9 +92,10 @@ ax.fill_between(viral_loads, lower_percentiles,
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ax.set_yscale('log')
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############# Coleman #############
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coleman_etal_vl = [np.log10(821065925.4), np.log10(1382131207), np.log10(81801735.96), np.log10(487760677.4), np.log10(2326593535), np.log10(1488879159), np.log10(884480386.5)]
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coleman_etal_vl = [np.log10(821065925.4), np.log10(1382131207), np.log10(81801735.96), np.log10(
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487760677.4), np.log10(2326593535), np.log10(1488879159), np.log10(884480386.5)]
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coleman_etal_er = [127, 455.2, 281.8, 884.2, 448.4, 1100.6, 621]
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plt.scatter(coleman_etal_vl, coleman_etal_er, label='Coleman et al')
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plt.scatter(coleman_etal_vl, coleman_etal_er)
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x_hull, y_hull = get_enclosure_points(coleman_etal_vl, coleman_etal_er)
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# plot shape
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plt.fill(x_hull, y_hull, '--', c='orange', alpha=0.2)
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@ -101,20 +105,21 @@ markers = ['*', 'v', 's']
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############# Milton et al #############
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milton_vl = [np.log10(8.30E+04), np.log10(4.20E+05), np.log10(1.80E+06)]
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milton_er = [22, 220, 1120] # removed first and last due to its dimensions
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plt.scatter(milton_vl[0], milton_er[0], marker=markers[0], color='red', label = ' Milton et al 25th')
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plt.scatter(milton_vl[1], milton_er[1], marker=markers[1], color='red', label = ' Milton et al Mean')
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plt.scatter(milton_vl[2], milton_er[2], marker=markers[2], color='red', label = ' Milton et al 75th')
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milton_er = [22, 220, 1120] # removed first and last due to its dimensions
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plt.scatter(milton_vl[0], milton_er[0], marker=markers[0], color='red')
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plt.scatter(milton_vl[1], milton_er[1], marker=markers[1], color='red')
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plt.scatter(milton_vl[2], milton_er[2], marker=markers[2], color='red')
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x_hull, y_hull = get_enclosure_points(milton_vl, milton_er)
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# plot shape
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plt.fill(x_hull, y_hull, '--', c='red', alpha=0.2)
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############# Yan et al #############
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yan_vl = [np.log10(7.86E+07), np.log10(2.23E+09), np.log10(1.51E+10)] # removed first and last due to its dimensions
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# removed first and last due to its dimensions
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yan_vl = [np.log10(7.86E+07), np.log10(2.23E+09), np.log10(1.51E+10)]
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yan_er = [8396.78166, 45324.55964, 400054.0827]
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plt.scatter(yan_vl[0], yan_er[0], marker=markers[0], color='green', label = ' Yan et al 25th')
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plt.scatter(yan_vl[1], yan_er[1], marker=markers[1], color='green', label = ' Yan et al Mean')
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plt.scatter(yan_vl[2], yan_er[2], marker=markers[2], color='green', label = ' Yan et al 75th')
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plt.scatter(yan_vl[0], yan_er[0], marker=markers[0], color='green')
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plt.scatter(yan_vl[1], yan_er[1], marker=markers[1], color='green')
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plt.scatter(yan_vl[2], yan_er[2], marker=markers[2], color='green')
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x_hull, y_hull = get_enclosure_points(yan_vl, yan_er)
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# plot shape
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@ -151,13 +156,35 @@ plt.fill(x_hull, y_hull, '--', c='green', alpha=0.2)
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# box plot aligned with the viral load value of 9.34786
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############ Legend ############
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# min = mlines.Line2D([], [], color='gray', marker='_', linestyle='None', label = 'Min')
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# first_quantile = mlines.Line2D([], [], color='gray', marker='*', linestyle='None', label = '25th quantile')
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# second_quantile = mlines.Line2D([], [], color='gray', marker='v', linestyle='None', label = 'Mean')
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# third_quantile = mlines.Line2D([], [], color='gray', marker='s', linestyle='None', label = '75th quantile')
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# max = mlines.Line2D([], [], color='gray', marker='+', linestyle='None', label = 'Max')
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# plt.legend(handles=[min, first_quantile, second_quantile, third_quantile, max])
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ax.legend()
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result_from_model = mlines.Line2D(
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[], [], color='blue', marker='_', linestyle='None')
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coleman = mlines.Line2D([], [], color='orange', marker='o', linestyle='None')
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milton_mean = mlines.Line2D(
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[], [], color='red', marker='v', linestyle='None') # mean
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milton_25 = mlines.Line2D(
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[], [], color='red', marker='*', linestyle='None') # 25
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milton_75 = mlines.Line2D(
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[], [], color='red', marker='s', linestyle='None') # 75
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yann_mean = mlines.Line2D([], [], color='green',
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marker='v', linestyle='None') # mean
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yann_25 = mlines.Line2D([], [], color='green',
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marker='*', linestyle='None') # 25
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yann_75 = mlines.Line2D([], [], color='green',
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marker='s', linestyle='None') # 75
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title_proxy = Rectangle((0, 0), 0, 0, color='w')
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titles = ["$\\bf{CARA \, (SARS-CoV-2)}$", "$\\bf{Coleman \, et \, al. \, (SARS-CoV-2)}$",
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"$\\bf{Milton \, et \, al. \,(Influenza)}$", "$\\bf{Yann \, et \, al. \,(Influenza)}$"]
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leg = plt.legend([title_proxy, result_from_model, title_proxy, coleman, title_proxy, milton_mean, milton_25, milton_75, title_proxy, yann_mean, yann_25, yann_75],
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[titles[0], "Result from model", titles[1], "Dataset", titles[2], "Mean", "25th per.", "75th per.", titles[3], "Mean", "25th per.", "75th per."])
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# Move titles to the left
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for item, label in zip(leg.legendHandles, leg.texts):
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if label._text in titles:
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width = item.get_window_extent(fig.canvas.get_renderer()).width
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label.set_ha('left')
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label.set_position((-3*width, 0))
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############ Plot ############
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plt.title('Exhaled virions while breathing for 1h', fontsize=14)
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