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")