diff --git a/bin/createModel.py b/bin/createModel.py
index e2182ae9..3c793e77 100755
--- a/bin/createModel.py
+++ b/bin/createModel.py
@@ -50,7 +50,7 @@
 volumes = []
 
 # Create/write compartments
-compartment_sheet = np.array([np.array(line.strip().split("\t")) for line in open('Compartments.txt')])
+compartment_sheet = np.array([np.array(line.strip().split("\t")) for line in open('Compartments.txt')], dtype=object)
 
 #read in each line minus the header row
 for row in compartment_sheet[1:]:
@@ -65,7 +65,7 @@
 fileModel.write("\n")
 
 # Write species and assign compartments
-species_sheet = np.array([np.array(line.strip().split("\t")) for line in open('Species.txt', encoding='latin-1')])
+species_sheet = np.array([np.array(line.strip().split("\t")) for line in open('Species.txt', encoding='latin-1')], dtype=object)
 
 species_compartments = []
 for row in species_sheet[1:]:
@@ -84,7 +84,7 @@
 fileModel.write("\n\n  # Reactions:\n")
 
 #reads in file from excel and gets rid of first row and column (they're data labels)
-stoic_sheet = np.array([np.array(line.strip().split("\t")) for line in open('StoicMat.txt')])
+stoic_sheet = np.array([np.array(line.strip().split("\t")) for line in open('StoicMat.txt')], dtype=object)
 
 #gets first column minus blank space at the beginning
 stoic_columnnames = stoic_sheet[0]
@@ -92,8 +92,8 @@
 stoic_data = np.array([line[1:] for line in stoic_sheet[1:]])
 
 
-ratelaw_sheet = np.array([np.array(line.strip().split("\t")) for line in open('Ratelaws.txt')])
-ratelaw_data = np.array([line[1:] for line in ratelaw_sheet[1:]])
+ratelaw_sheet = np.array([np.array(line.strip().split("\t")) for line in open('Ratelaws.txt')], dtype=object)
+ratelaw_data = np.array([line[1:] for line in ratelaw_sheet[1:]], dtype=object)
 
 paramnames = []
 paramvals = []
diff --git a/bin/modules/RunSPARCED.py b/bin/modules/RunSPARCED.py
index b6278fd4..97c9e168 100644
--- a/bin/modules/RunSPARCED.py
+++ b/bin/modules/RunSPARCED.py
@@ -22,7 +22,7 @@ def RunSPARCED(flagD,th,spdata,genedata,sbml_file,model):
     splist = list(model.getStateIds())
     if len(spdata)==0: # if no initial condition values are supplied, use the input file information
         spdata0 = pd.read_csv('Species.txt',header=0,index_col=0,sep="\t")
-        spdata = np.float(spdata0.values[:,1])  
+        spdata = np.float64(spdata0.values[:,1])  
     
     # calculate 
     genedata, GenePositionMatrix, AllGenesVec, kTCmaxs, kTCleak, kGin_1, kGac_1, kTCd, TARs0, tcnas, tcnrs, tck50as, tck50rs, spIDs = RunPrep(flagD,Vn,model)