File:ICC-example1.svg
Summary
Description |
English: Dot plot illustrating the intraclass correlation coefficient |
Date | |
Source |
Own work |
Author | Skbkekas |
SVG development | |
Source code | Python codefrom __future__ import division
import numpy as np
import matplotlib.pyplot as plt
def ICC(X):
K = X.shape[1]
m = X.mean(1)-X.mean()
A = (m**2).mean()/X.var()
A *= K/(K-1)
A -= 1/(K-1)
return A
def genplot(X, fname):
n = X.shape[0]
plt.clf()
for i in range(1,n+1):
plt.plot((i,i), (-2,2), '-', color='grey')
plt.hold(True)
for k in range(X.shape[1]):
plt.plot(np.arange(1,n+1), X[:,k], 'o', color='blue')
plt.xlim(0,n+1)
plt.xlabel("Group number")
plt.ylabel("Data value")
icc = ICC(X)
plt.title("ICC=%.2f" % icc)
plt.xticks(range(1,n+1,2))
plt.savefig(fname + ".png")
plt.savefig(fname + ".svg")
X = np.random.uniform(low=-2, high=2, size=(20,4))
genplot(X, "ICC-example1")
V = np.random.uniform(low=-2, high=2, size=20)
X = np.zeros((20,4))
for i in range(len(V)):
e = min(min(V[i]+2,2-V[i]),0.7)
X[i,:] = np.random.uniform(low=V[i]-e, high=V[i]+e, size=4)
genplot(X, "ICC-example2")
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Licensing
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