diff --git a/R/ALPACA.R b/R/ALPACA.R
index c4c6ad00..6b0d4e6e 100644
--- a/R/ALPACA.R
+++ b/R/ALPACA.R
@@ -70,19 +70,22 @@ alpaca <- function(net.table,file.stem,verbose=FALSE)
     louv.Bscores <- NULL
     for (i in seq_len(max(louv.memb)))
     {
+      print(i)
         this.comm <- names(louv.memb)[louv.memb==i]
         this.tfs <- this.comm[grep("_A$",this.comm)]
         this.genes <- this.comm[grep("_B$",this.comm)]
     if (length(this.tfs)>=1){
         if (length(this.tfs)>1){
-            tf.sums <- apply(dwbm[this.tfs,this.genes],1,sum)
-            gene.sums <- apply(dwbm[this.tfs,this.genes],2,sum)
+            if (length(this.genes)==1){
+                gene.sums <- sum(dwbm[this.tfs,this.genes])
+                tf.sums <- dwbm[this.tfs,this.genes]
+            }else if (length(this.genes)>1){
+                tf.sums <- apply(dwbm[this.tfs,this.genes],1,sum)
+                gene.sums <- apply(dwbm[this.tfs,this.genes],2,sum)
+            }
         } else if (length(this.tfs)==1) {
             tf.sums <- sum(dwbm[this.tfs,this.genes])
             gene.sums <- dwbm[this.tfs,this.genes]
-        } else if (length(this.genes)==1){
-            gene.sums <- sum(dwbm[this.tfs,this.genes])
-            tf.sums <- dwbm[this.tfs,this.genes]
         }
       this.denom <- sum(dwbm[this.tfs,this.genes])
       louv.Ascores <- c(louv.Ascores,tf.sums/this.denom)
diff --git a/inst/extdata/panda.py b/inst/extdata/panda.py
index ae4a7685..4f534239 100644
--- a/inst/extdata/panda.py
+++ b/inst/extdata/panda.py
@@ -4,6 +4,7 @@
 import pandas as pd
 from scipy.stats import zscore
 import numpy as np
+import os
 
 # this scirpt is derived from https://github.com/netZoo/netZooPy/blob/master/netZooPy/panda/panda.py
 # and https://github.com/netZoo/netZooPy/blob/master/netZooPy/panda/timer.py
@@ -91,9 +92,9 @@ def __init__(self, expression_file, motif_file, ppi_file, computing='cpu',precis
         if save_tmp:
             with Timer('Saving expression matrix and normalized networks ...'):
                 if self.expression_data is not None:
-                    np.save('/tmp/expression.npy', self.expression_data.values)
-                np.save('/tmp/motif.normalized.npy', self.motif_matrix)
-                np.save('/tmp/ppi.normalized.npy', self.ppi_matrix)
+                    np.save('expression.npy', self.expression_data.values)
+                np.save('motif.normalized.npy', self.motif_matrix)
+                np.save('ppi.normalized.npy', self.ppi_matrix)
 
         # delete expression data
         del self.expression_data