Try out paralleled `numpy` computations¶

dat = readRDS('/home/gaow/Documents/GTExV8/Thyroid.Lung.FMO2.filled.rds')
attach(dat)

%get X Y --from R
Y = Y.as_matrix()

Loading required package: feather

from libgaow.regression_data import MASH
import numpy as np

model = MASH(X=X,Y=Y)
model.set_prior({'identity': np.identity(2), 
                 'single_1': np.array([[1,0],[0,0]]), 
                 'single_2': np.array([[0,0], [0,1]]), 
                 'all_in': np.ones((2,2))}, 
                [0.5,1], 
                [0.9,0.01,0.01,0.01,0.01,0.01,0.01,0.02,0.02])

from time import time
t0 = time()
model.fit()
t1 = time()

t1 - t0

19.080756664276123

model.post_mean_mat

array([[ -1.49884347e-04,  -6.36060586e-04,  -9.44192821e-04, ...,
          1.24769557e-04,   1.71446659e-05,   1.49532499e-04],
       [ -1.28376438e-04,  -5.37549875e-04,  -1.19440242e-03, ...,
          2.34743878e-05,   1.51444262e-04,   3.88329156e-05]])

Try out paralleled numpy computations¶

Try out paralleled `numpy` computations¶