diff --git a/Packages/PyLOOS/cluster-structures.py b/Packages/PyLOOS/cluster-structures.py
index 940aa338d..ae6eac5e9 100755
--- a/Packages/PyLOOS/cluster-structures.py
+++ b/Packages/PyLOOS/cluster-structures.py
@@ -153,7 +153,7 @@
 
 minima = numpy.full_like(numpy.arange(args.num_means),
                          1.e10,
-                         dtype=numpy.float)
+                         dtype=float)
 minima_indices = numpy.zeros([args.num_means], dtype=numpy.int)
 
 for i in range(len(idx)):
diff --git a/Packages/PyLOOS/contact_distance.py b/Packages/PyLOOS/contact_distance.py
index 1cad0cb7b..42794fd5a 100755
--- a/Packages/PyLOOS/contact_distance.py
+++ b/Packages/PyLOOS/contact_distance.py
@@ -127,7 +127,7 @@
         traj.append(t)
 
 num_pairs = len(residues) * (len(residues)-1) // 2
-contacts = numpy.zeros((len(traj), num_pairs), numpy.float)
+contacts = numpy.zeros((len(traj), num_pairs), float)
 
 default_box = loos.GCoord(10000., 10000., 10000.)
 frame_number = 0
diff --git a/Packages/PyLOOS/packing_score_per_res.py b/Packages/PyLOOS/packing_score_per_res.py
index a4036adc7..8ea04b08d 100755
--- a/Packages/PyLOOS/packing_score_per_res.py
+++ b/Packages/PyLOOS/packing_score_per_res.py
@@ -167,7 +167,7 @@ def __call__(self, parser, namespace, values, option_string = None):
     vtraj.append(traj)
 
 # pre-allocate storage as a numpy array
-scores = numpy.zeros([len(residues), len(probes), len(vtraj)], numpy.float)
+scores = numpy.zeros([len(residues), len(probes), len(vtraj)], float)
 
 frame_index = 0
 for frame in vtraj:
diff --git a/Packages/PyLOOS/rare-event-detection.py b/Packages/PyLOOS/rare-event-detection.py
index 5fe72277a..d2422f7ff 100755
--- a/Packages/PyLOOS/rare-event-detection.py
+++ b/Packages/PyLOOS/rare-event-detection.py
@@ -144,7 +144,7 @@ def LowerTriIndex(row, col, n):
     if args.no_backbone:
         residues = list([loos.selectAtoms(r, "!backbone") for r in residues])
 
-    fc = numpy.zeros([int((len(residues)-1)*len(residues)/2), len(traj)], numpy.float64)
+    fc = numpy.zeros([int((len(residues)-1)*len(residues)/2), len(traj)], float64)
 
 
     for (frame, frame_id) in zip(traj, range(len(traj))):
diff --git a/Tools/potential_profile.py b/Tools/potential_profile.py
index 14d096179..edc91d84e 100755
--- a/Tools/potential_profile.py
+++ b/Tools/potential_profile.py
@@ -104,7 +104,7 @@ def read_file(filename):
     #      dielectric   charge density        integrated distance
     units = 1/eps0 * e_to_C/(ang_to_m**3) * ang_to_m**2
 
-    pot = numpy.zeros(data.shape, numpy.float)
+    pot = numpy.zeros(data.shape, float)
     # compute the potential, uncorrected for periodicity
     for i in range(len(data)):
         for j in range(i+1, len(data)):
diff --git a/loos/src/loos/Voronoi/area_per_molecule.py b/loos/src/loos/Voronoi/area_per_molecule.py
index 50a2d9ca2..e1a16b34f 100755
--- a/loos/src/loos/Voronoi/area_per_molecule.py
+++ b/loos/src/loos/Voronoi/area_per_molecule.py
@@ -109,7 +109,7 @@ def main():
         """)
         sys.exit(0)
 
-    histograms = numpy.zeros([len(selection_strings[1:]), num_bins], numpy.float)
+    histograms = numpy.zeros([len(selection_strings[1:]), num_bins], float)
 
     print("# ", " ".join(sys.argv))
 
diff --git a/loos/src/loos/Voronoi/lipid_lifetime.py b/loos/src/loos/Voronoi/lipid_lifetime.py
index 761482839..abada0d9e 100755
--- a/loos/src/loos/Voronoi/lipid_lifetime.py
+++ b/loos/src/loos/Voronoi/lipid_lifetime.py
@@ -133,7 +133,7 @@ def main():
     protein_centroid.append(loos.Atom())
 
     # set up space to hold the neigbor time series
-    neighbor_timeseries = numpy.zeros([len(target_lipids), len(traj)], numpy.float)
+    neighbor_timeseries = numpy.zeros([len(target_lipids), len(traj)], float)
 
     for frame in traj:
         # Use the centroid of the protein slice to represent the protein