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47 lines
1.1 KiB
Python
47 lines
1.1 KiB
Python
# TRAINS - Example of Matplotlib and Seaborn integration and reporting
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#
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import numpy as np
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import matplotlib.pyplot as plt
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import seaborn as sns
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from trains import Task
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task = Task.init(project_name='examples', task_name='Matplotlib example')
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# create plot
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N = 50
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x = np.random.rand(N)
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y = np.random.rand(N)
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colors = np.random.rand(N)
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area = (30 * np.random.rand(N))**2 # 0 to 15 point radii
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plt.scatter(x, y, s=area, c=colors, alpha=0.5)
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plt.show()
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# create another plot - with a name
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x = np.linspace(0, 10, 30)
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y = np.sin(x)
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plt.plot(x, y, 'o', color='black')
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plt.show()
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# create image plot
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m = np.eye(256, 256, dtype=np.uint8)
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plt.imshow(m)
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plt.show()
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# create image plot - with a name
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m = np.eye(256, 256, dtype=np.uint8)
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plt.imshow(m)
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plt.title('Image Title')
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plt.show()
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sns.set(style="darkgrid")
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# Load an example dataset with long-form data
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fmri = sns.load_dataset("fmri")
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# Plot the responses for different events and regions
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sns.lineplot(x="timepoint", y="signal",
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hue="region", style="event",
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data=fmri)
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plt.show()
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print('This is a Matplotlib & Seaborn example')
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