nest · heplesser · Aug 17, 2018 · Aug 13, 2018 · Aug 14, 2018 · Aug 16, 2018
diff --git a/doc/model_details/HillTononiModels.ipynb b/doc/model_details/HillTononiModels.ipynb
diff --git a/pynest/examples/brunel_alpha_evolution_strategies.py b/pynest/examples/brunel_alpha_evolution_strategies.py
@@ -64,6 +64,7 @@
 
 '''
 
+from __future__ import print_function
 print('Statistics after optimization:', end=' ') 
 print('Statistics after optimization:', end=' ') 
 import matplotlib.pyplot as plt
 from matplotlib.patches import Ellipse
 import numpy as np
@@ -404,7 +405,7 @@ def optimize(func, mu, sigma, learning_rate_mu=None, learning_rate_sigma=None,
     while True:
 
         # create new population using the search distribution
-        s = np.random.normal(0, 1, size=(population_size, *np.shape(mu)))
+        s = np.random.normal(0, 1, size=(population_size,) + np.shape(mu))
         z = mu + sigma * s
 
         # add mirrored perturbations if enabled

diff --git a/pynest/examples/hh_psc_alpha.py b/pynest/examples/hh_psc_alpha.py
@@ -56,7 +56,7 @@
 
 
 # Simulation loop
-n_data = dcto / float(dcstep)
+n_data = int(dcto / float(dcstep))
 amplitudes = np.zeros(n_data)
 event_freqs = np.zeros(n_data)
 for i, amp in enumerate(range(dcfrom, dcto, dcstep)):

diff --git a/pynest/examples/sinusoidal_gamma_generator.py b/pynest/examples/sinusoidal_gamma_generator.py
@@ -204,7 +204,7 @@ def plot_hist(spikes):
 t = 1000
 n = 1000
 dt = 1.0
-steps = t / dt
+steps = int(t / dt)
 offset = t / 1000. * 2 * np.pi
 
 '''