Merge pull request #5 from jdtuck/fix_main

remove main from package

pyBASS/pyBASS.py

@@ -894,50 +894,4 @@ def bassPCA(xx, y, npc=None, percVar=99.9, ncores=1, center=True, scale=False, *
     return BassBasis(xx, y, basis, newy, setup.y_mean, setup.y_sd, trunc_error, ncores, **kwargs)
 
 
-######################################################
-## test it out
 
-if __name__ == '__main__':
-
-    if False:
-        def f(x):
-            return (10 * np.sin(2 * np.pi * x[:, 0] * x[:, 1]) +
-                    20 * (x[:, 2] - .5) ** 2 +
-                    10 * x[:, 3] + 5 * x[:, 4])
-
-        n, p = 500, 10
-        x = np.random.rand(n, p)
-        xx = np.random.rand(1000, p)
-        y = f(x) + np.random.normal(size=n)
-
-        mod = bass(x, y, nmcmc=10000, nburn=9000)
-        pred = mod.predict(xx, mcmc_use=np.array([1, 100]), nugget=True)
-
-        mod.plot()
-
-        print(np.var(mod.predict(xx).mean(axis=0)-f(xx)))
-
-    if False:
-        def f2(x):
-            return (10 * np.sin(np.pi * tt * x[1]) +
-                    20 * (x[2] - .5) ** 2 +
-                    10 * x[3] + 5 * x[4])
-
-        tt = np.linspace(0, 1, 50)
-        n, p = 500, 9
-        x = np.random.rand(n, p) - .5
-        xx = np.random.rand(1000, p) - .5
-        e = np.random.normal(size=n * len(tt))
-        y = np.apply_along_axis(f2, 1, x)  # + e.reshape(n,len(tt))
-
-        modf = bassPCA(x, y, ncores=2, percVar=99.99)
-        modf.plot()
-
-        pred = modf.predict(xx, mcmc_use=np.array([1,100]), nugget=True)
-
-        ind = 11
-        plt.plot(pred[:,ind,:].T)
-        plt.plot(f2(xx[ind,]),'bo')
-
-        plt.plot(np.apply_along_axis(f2, 1, xx), np.mean(pred,axis=0))
-        abline(1,0)