Merge pull request #433 from AurelienJaquier/fix-lfpy

Fix parameterscalers

Author: wvangeit

bluepyopt/deapext/tools/selIBEA.py

@@ -63,7 +63,7 @@ def _calc_fitness_components(population, kappa):
     population_matrix = numpy.fromiter(
         iter(-x for individual in population
              for x in individual.fitness.wvalues),
-        dtype=numpy.float)
+        dtype=numpy.float64)
     pop_len = len(population)
     feat_len = len(population[0].fitness.wvalues)
     population_matrix = population_matrix.reshape((pop_len, feat_len))

bluepyopt/ephys/efeatures.py

@@ -563,7 +563,7 @@ def _filter_response(response, fcut=[0.5, 6000], order=2, filt_type="lfilter"):
 
     trace = response["voltage"]
 
-    if isinstance(fcut, (float, int, np.float, np.integer)):
+    if isinstance(fcut, (float, int, np.floating, np.integer)):
         btype = "highpass"
         band = fcut / fn
     else:

bluepyopt/ephys/extra_features_utils.py

@@ -1,3 +1,24 @@
+"""Extra features functions"""
+
+"""
+Copyright (c) 2016-2020, EPFL/Blue Brain Project
+
+ This file is part of BluePyOpt <https://github.com/BlueBrain/BluePyOpt>
+
+ This library is free software; you can redistribute it and/or modify it under
+ the terms of the GNU Lesser General Public License version 3.0 as published
+ by the Free Software Foundation.
+
+ This library is distributed in the hope that it will be useful, but WITHOUT
+ ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
+ FOR A PARTICULAR PURPOSE.  See the GNU Lesser General Public License for more
+ details.
+
+ You should have received a copy of the GNU Lesser General Public License
+ along with this library; if not, write to the Free Software Foundation, Inc.,
+ 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
+"""
+
 import numpy as np
 
 all_1D_features = [
@@ -278,7 +299,7 @@ def repolarization_slope(waveforms, sampling_frequency, return_idx=False):
 
     rslope = np.empty(waveforms.shape[0])
     rslope[:] = np.nan
-    return_to_base_idx = np.empty(waveforms.shape[0], dtype=np.int)
+    return_to_base_idx = np.empty(waveforms.shape[0], dtype=np.int_)
     return_to_base_idx[:] = 0
 
     time = np.arange(0, waveforms.shape[1]) * (1 / sampling_frequency)  # in s

bluepyopt/ephys/parameterscalers.py

@@ -178,7 +178,7 @@ def scale(self, values, segment, sim=None):
 
         # find section
         target_sec = None
-        for sec in sim.neuron.h.allsec():
+        for sec in segment.sec.wholetree():
             if "." in sec.name():  # deal with templates
                 sec_name = sec.name().split(".")[1]
             else:

bluepyopt/ipyp/bpopt_tasksdb.py

@@ -98,7 +98,7 @@ def plot_duration_histogram(tasks):
     durations = np.fromiter((t['duration']
                              for task_list in tasks.values()
                              for t in task_list),
-                            dtype=np.float)
+                            dtype=np.float64)
     plt.hist(durations, 100)
 
     plt.xlabel('Duration (s)')