import numpy as np
import matplotlib.pyplot as plt
import scipy.special as sp

## Simulate test statistic values.                                              
T = np.random.normal(size=200)
T[0:20] = np.random.normal(size=20)+2
T = np.sort(T)

## Standard normal quantiles.                                                   
P = np.arange(1, 201, dtype=np.float64)/201
Q = sp.ndtri(P)

plt.clf()
plt.grid(True)
plt.plot([-4,4], [-4,4], '-', color='grey')
plt.hold(True)
plt.plot(T, Q, 'o', color='black', ms=3)

print T[196],Q[196]
print T[4],Q[4]

plt.plot((T[196],), (Q[196],), 'o', color='red')
plt.plot((T[4],), (Q[4],), 'o', color='blue')

plt.xlabel("Observed test statistic quantiles")
plt.ylabel("Standard normal quantiles")
plt.savefig("quantile_meta_test.png")
plt.savefig("quantile_meta_test.svg")