diff --git a/examples/applications/plot_tomography_l1_reconstruction.py b/examples/applications/plot_tomography_l1_reconstruction.py
index dc0a1265e27bd..24996e5568e2e 100644
--- a/examples/applications/plot_tomography_l1_reconstruction.py
+++ b/examples/applications/plot_tomography_l1_reconstruction.py
@@ -34,6 +34,7 @@ class :class:`sklearn.linear_model.Lasso`, that uses the coordinate descent
 the circular artifact separating the pixels in the corners, that have
 contributed to fewer projections than the central disk.
 """
+from __future__ import division
 
 print(__doc__)
 
@@ -50,7 +51,7 @@ class :class:`sklearn.linear_model.Lasso`, that uses the coordinate descent
 
 def _weights(x, dx=1, orig=0):
     x = np.ravel(x)
-    floor_x = np.floor((x - orig) / dx)
+    floor_x = np.floor((x - orig) / dx).astype(np.int64)
     alpha = (x - orig - floor_x * dx) / dx
     return np.hstack((floor_x, floor_x + 1)), np.hstack((1 - alpha, alpha))
 
@@ -112,7 +113,7 @@ def generate_synthetic_data():
 
 # Generate synthetic images, and projections
 l = 128
-proj_operator = build_projection_operator(l, l / 7.)
+proj_operator = build_projection_operator(l, l // 7)
 data = generate_synthetic_data()
 proj = proj_operator * data.ravel()[:, np.newaxis]
 proj += 0.15 * np.random.randn(*proj.shape)