drugv = cmb.combination(drugv)
if drugv == False:
break
i = i + 1
drugv = (df_drug.as_matrix()).astype(np.int32)
outsize = 7
thlen = len(faultv) / 2
kernel = kernel % {"outsize": outsize}
mod = compiler.SourceModule(kernel)
results = mod.get_function("encode")
for i in range(len(drugv)):
print "Drug vector:", i + 1, list(drugv[i]), "started."
for j in range(len(faultv)):
outlist = [0, 0, 0, 0, 0, 0, 0]
drugpath.pathway(faultv[j], drugv[i], inpv, pathv, outlist)
outv[j] = outlist
inpv = [0, 0, 0, 0, 1]
output_drugthree.loc[i] = " ".join(map(str, drugv[i]))
outv_gpu = gpuarray.to_gpu((np.array(outv[:thlen])).astype(np.int32))
env_gpu = gpuarray.empty(thlen, np.int32)
results(outv_gpu, env_gpu, block=(thlen, 1, 1))
output_drugthree.iloc[i, 1:thlen + 1] = env_gpu.get()
outv_gpu = gpuarray.to_gpu((np.array(outv[thlen:])).astype(np.int32))
env_gpu = gpuarray.empty(thlen, np.int32)
results(outv_gpu, env_gpu, block=(thlen, 1, 1))
output_drugthree.iloc[i, thlen + 1:] = env_gpu.get()
print "Drug vector:", i + 1, list(drugv[i]), "ended."
ofile = "outs/output_drugthree_p.csv"
output_drugthree.to_csv(ofile)
df_drug.columns=["drugs"]
df_drug["values"]=[0] * len(df_drug.index)
drugv=list(df_drug["values"])
#creating output file
cols=["drug vector"] + [i for i in range(28)]
output_drugone=pd.DataFrame(columns=cols)
j=0
start_time=time.clock()
while True:
encoded=[]
print("Drug scenario:",drugv,"starts")
for i in range(28):
drugpath.pathway([i],drugv,inpv,pathv,outv)
encoded.append(float(en.encode(outv)))
inpv=unq
print("%0.3f"%(time.clock()-start_time),"Drug scenario:",drugv,"ends")
output_drugone.loc[j,"drug vector"]=' '.join(map(str,drugv))
output_drugone.iloc[j,1:]=encoded
drugv=cmb.combination(drugv)
if drugv==False:
break
j=j+1
print("Execution time: ","%0.3f"%(time.clock()-start_time)," seconds")
#print(output_drugone)
#write to output_drugone.csv
output_drugone.to_csv("outs/output_drugone.csv")