bugfix, further python 3.12 fix

Exploration/HelperFunctions/Synapses_And_Weights.py

@@ -118,7 +118,8 @@ def get_combined_syn_mats(synapses, neuron_id=None, attr='W'):
             shapes[key] = (base_src.height, base_src.width)
         try:
             syn_mat = eval('s.' + attr)
-            if type(syn_mat) is not bool:
+
+            if type(syn_mat)!=bool:
                 w = s.ignore_transpose_mode(syn_mat)
             else:
                 w = syn_mat

Exploration/Network_UI/Basic_Tabs/sidebar_fast_forward_module.py

@@ -32,7 +32,11 @@ def fast_forward(self, steps, Network_UI):
     def initialize(self, Network_UI):
 
         self.iteration_display_label=Network_UI.sidebar.add_widget(QLabel())
-        self.iteration_display_label.setMaximumHeight(10)
+        #self.iteration_display_label.setMaximumHeight(20)
+
+        font_metrics = QFontMetrics(self.iteration_display_label.font())
+        text_height = font_metrics.height()
+        self.iteration_display_label.setFixedHeight(text_height)
 
         def start_pause_click(event):
             Network_UI.pause = not Network_UI.pause

Exploration/Network_UI/Sequence_Activation_Tabs/reconstruction_tab.py

@@ -11,7 +11,7 @@ def add_recorder_variables(self, neuron_group, Network_UI):
         return
 
     def initialize(self, Network_UI):
-        if Network_UI.network['TextActivator', 0] and Network_UI.network['TextGenerator', 0] is not None:
+        if Network_UI.network['TextActivator', 0] is not None and Network_UI.network['TextGenerator', 0] is not None:
             self.reconstruction_tab = Network_UI.add_tab(title=self.title) #Network_UI.Next_Tab(self.title)
 
             self.grid = QGridLayout()
@@ -70,7 +70,7 @@ def initialize(self, Network_UI):
 
 
     def update(self, Network_UI):
-        if Network_UI.network['TextActivator', 0] is not None and self.reconstruction_tab.isVisible():
+        if Network_UI.network['TextActivator', 0] is not None and Network_UI.network['TextGenerator', 0] is not None and self.reconstruction_tab.isVisible():
             group=Network_UI.selected_neuron_group()
 
             '''

Exploration/Network_UI/Sequence_Activation_Tabs/sidebar_grammar_module.py

@@ -66,14 +66,16 @@ def initialize(self, Network_UI):
     def update(self, Network_UI):
 
         if Network_UI.network['TextGenerator', 0] is not None and Network_UI.network['TextActivator', 0] is not None:
-            if Network_UI.network['TextActivator', 0].behavior_enabled:
-                inp_text = Network_UI.network['TextGenerator', 0].history[-self.text_length:]
+            if Network_UI.network['TextGenerator', 0].behavior_enabled and Network_UI.network['TextActivator', 0].behavior_enabled:
+                inp_text = Network_UI.network['TextGenerator', 0].get_str_history()[-self.text_length:]
             else:
                 inp_text = 'deactivated'
+            inp_text=inp_text.replace('\n', '<break>')
             self.inp_text_label.setText(inp_text)
 
         if Network_UI.network['TextReconstructor', 0] is not None:
             recon_text = Network_UI.network['TextReconstructor', 0].reconstruction_history[-self.text_length:]
+            recon_text=recon_text.replace('\n', '<break>')
             self.recon_text_label.setText(recon_text)
 '''
 

Exploration/Network_UI/Sequence_Activation_Tabs/sun_gravity_plot_tab.py

@@ -156,10 +156,10 @@ def draw_neurons(self, painter, group, neuron_size=1, selected_neurons=None):
 
         painter.setPen(0)
 
-        inactive = group.output <= 0
+        inactive = group.spike <= 0
         active = np.invert(inactive)
 
-        for c in unique(color, axis=0):
+        for c in np.unique(color, axis=0):
             mask = np.all(color == c[None,:], axis=1) * inactive #(color == c) np.all(a == b, axis=1)
             painter.setBrush(pg.mkBrush(color=c))
             for x, y in zip(group.buffer_posx[mask], group.buffer_posy[mask]):

NetworkBehavior/Structure/Partition.py

@@ -32,7 +32,7 @@ def partition(self, synapses, dst_group_masks):  # todo:auto receptive field ext
 
             syn_sub_groups.append(synapses.get_sub_synapse_group(src_mask, dst_mask))
 
-        print('partitioned into', len(syn_sub_groups), 'SynapseGroups')
+        print('partitioned into', len(syn_sub_groups), 'SynapseGroups', str(int(rf_x)), 'x', str(int(rf_y)), 'x', str(int(rf_z)))
 
         # add sub Groups
         for sg in syn_sub_groups:

NetworkCore/Base_Attachable_Modules.py

@@ -3,6 +3,9 @@
 from numpy.random import *
 from numpy import *
 from functools import wraps
+import builtins
+
+bool = builtins.bool
 
 def lognormal_real_mean(mean=1.0, sigma=1.0, size=1):
     mu = -np.power(sigma, 2) + np.log(mean)
@@ -40,7 +43,7 @@ def __init__(self, tag, network, behavior):
         self.behavior = {}#behavior
 
         if type(behavior) == list:
-            self.behavior = dict(zip(range(len(self.behavior)), self.behavior))
+            behavior = dict(zip(range(len(behavior)), behavior))
 
         for k,b in behavior.items():
             self.add_behavior(k, b, initialize=False)
@@ -266,4 +269,6 @@ def deactivate_behaviours(self, tag):
 
     @deprecated_warning("activate_behaviours function will be removed in coming versions. Please use activate_behaviors instead.")
     def activate_behaviours(self,tag):
-        return self.activate_behaviors(tag)
+        return self.activate_behaviors(tag)
+
+__all__ = ['lognormal_real_mean', 'lognormal_rm', 'uniform_gap', 'is_number', 'deprecated_warning', 'NetworkObjectBase'] # numpy functions are only accessible inside this file

NetworkCore/Neuron_Group.py

@@ -32,28 +32,24 @@ def __init__(self, net, size, behavior, tag=None, color=None):
             size = -1#will be overwritten by size-behavior
 
         self.size = size
+        self.BaseNeuronGroup = self#used for subgroup reconstruction
+        self.afferent_synapses = {} #set by SynapseGroup
+        self.efferent_synapses = {}
+        self.mask = True#np.array([True for _ in range(size)]).astype(bool)#True#used for subgroup reconstruction
+        self.id = np.arange(self.size)
+
+        if color is not None:
+            self.color = color
 
         super().__init__(tag, net, behavior)
         self.add_tag('ng')
 
-        self.BaseNeuronGroup = self#used for subgroup reconstruction
-
         if net is not None:
             net.NeuronGroups.append(self)
             for tag in self.tags:
                 if not hasattr(net, tag):
                     setattr(net, tag, self)
 
-        self.afferent_synapses = {} #set by SynapseGroup
-        self.efferent_synapses = {}
-
-        self.mask = True#np.array([True for _ in range(size)]).astype(bool)#True#used for subgroup reconstruction
-
-        self.id = np.arange(self.size)
-
-        if color is not None:
-            self.color = color
-
     def synapses(self, mode, tag='All'):#afferent=0, efferent=1
         if mode==afferent:
             return self.afferent_synapses[tag]

NetworkCore/Synapse_Group.py

@@ -194,3 +194,5 @@ def ignore_transpose_mode(self, W):# always returns DxS matrix
         else:
             return W
 
+
+

test_pymoNNto.py

@@ -48,6 +48,17 @@ def get_sample_network():
 
     return My_Network, My_Neurons, My_Synapses, sm
 
+def get_sample_network_list():
+    My_Network = Network()
+    My_Neurons = NeuronGroup(net=My_Network, tag='my_neurons', size=100, behavior=[
+        Counter(inc='[2#I]'),
+        Recorder('count')
+    ])
+    My_Synapses = SynapseGroup(net=My_Network, src=My_Neurons, dst=My_Neurons, tag='GLUTAMATE')
+    sm = StorageManager('test', random_nr=False, print_msg=False)
+    My_Network.initialize(storage_manager=sm)
+
+    return My_Network, My_Neurons, My_Synapses, sm
 
 def test_basics():
     net = Network()
@@ -113,40 +124,40 @@ def test_behavior_and_tagging():
 
     # basic network
     set_genome({'I': 1})
-    My_Network, My_Neurons, My_Synapses, sm = get_sample_network()
+    for My_Network, My_Neurons, My_Synapses, sm in [get_sample_network(), get_sample_network_list()]:
 
-    My_Network.simulate_iterations(1000)
+        My_Network.simulate_iterations(1000)
 
-    My_Network.deactivate_behaviors('Counter')
-    My_Network.simulate_iterations(10)
+        My_Network.deactivate_behaviors('Counter')
+        My_Network.simulate_iterations(10)
 
-    My_Network.activate_behaviors('Counter')
-    My_Network.simulate_iterations(20)
+        My_Network.activate_behaviors('Counter')
+        My_Network.simulate_iterations(20)
 
-    My_Network.recording_off()
-    My_Network.simulate_iterations(30)
+        My_Network.recording_off()
+        My_Network.simulate_iterations(30)
 
-    assert My_Network.iteration == 1000+10+20+30
-    assert np.mean(My_Neurons.count) == 1000+20+30
+        assert My_Network.iteration == 1000+10+20+30
+        assert np.mean(My_Neurons.count) == 1000+20+30
 
-    assert My_Synapses.src == My_Neurons
-    assert My_Synapses.dst == My_Neurons
+        assert My_Synapses.src == My_Neurons
+        assert My_Synapses.dst == My_Neurons
 
-    assert My_Neurons.synapses(afferent, 'GLUTAMATE') == [My_Synapses]
+        assert My_Neurons.synapses(afferent, 'GLUTAMATE') == [My_Synapses]
 
-    assert len(My_Network.all_objects()) == 3
+        assert len(My_Network.all_objects()) == 3
 
-    #tagging system
-    assert My_Network['my_neurons'] == [My_Neurons]
-    assert len(My_Network['count', 0]) == My_Network.iteration-30
+        #tagging system
+        assert My_Network['my_neurons'] == [My_Neurons]
+        assert len(My_Network['count', 0]) == My_Network.iteration-30
 
-    My_Network.clear_recorder()
-    assert len(My_Neurons['count', 0]) == 0
+        My_Network.clear_recorder()
+        assert len(My_Neurons['count', 0]) == 0
 
-    assert My_Network.tag_shortcuts['my_neurons'] == My_Network['my_neurons']
+        assert My_Network.tag_shortcuts['my_neurons'] == My_Network['my_neurons']
 
-    if os.path.isdir(folder+'test/'):
-        shutil.rmtree(folder+'test/')
+        if os.path.isdir(folder+'test/'):
+            shutil.rmtree(folder+'test/')