I would like to be able to basically pass a column into the np.random.normal()
function.
I have the following;
def calc_z(w,S,a1,a2,yt1,yt2):
mu = w * S
print 'Mu' , mu
sigma = mt.sqrt(0.5)
z = np.array(np.random.normal(mu,sigma))
u = [a1,a2,z]
yt = [yt1,yt2,1]
thetaset = np.random.rand(len(u))
m = [i for i in range(len(u))]
max_iter = 30
#Calculate E-step
for i in range(max_iter):
print 'Iteration:', i
print 'z:', z
print 'thetaset', thetaset
devLz = eq6(var,w,S,z,yt,u,thetaset,m)
dev2Lz2 = eq9(var,thetaset,u)
#Calculate M-Step
z = z - (devLz / dev2Lz2)
w = lambdaw * z
for i in range(len(thetaset)):
devLTheta = eq7(yt,u,thetaset,lambdatheta)
dev2LTheta2 = eq10(thetaset,u,lambdatheta)
thetaset = thetaset - (devLTheta / dev2LTheta2)
return float(z)
calc_z_udf = udf(calc_z,FloatType())
data.show()
data = data.withColumn('z', calc_z(data['w'],data['Org_Depth_Diff_S'],data['proximity_rank_a1'],data['cotravel_count_a2'],data['cotravel_yt1'],data['proximity_yt2']))
But when I pass S
in, the np.random.normal
function doesn't like being passed a column and gives me the following error;
Traceback (most recent call last):
File "/home/taylorr2/PySparkLatent3.py", line 125, in <module>
data = data.withColumn('z', calc_z(data['w'],data['Org_Depth_Diff_S'],data['proximity_rank_a1'],data['cotravel_count_a2'],data['cotravel_yt1'],data['proximity_yt2']))
File "/home/taylorr2/PySparkLatent3.py", line 90, in calc_z
z = np.array(np.random.normal(mu,sigma))
File "mtrand.pyx", line 1282, in mtrand.RandomState.normal (numpy/random/mtrand/mtrand.c:6920)
ValueError: setting an array element with a sequence.
I am trying to think of a way to get this function to accept this value or do this a different way.
Thanks!
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