General module updated

src/Modules/General/callbacks.py

@@ -231,7 +231,6 @@ class callbacks(callbacksOp):
                         treemap visualization
                     """
                     try:
-
                         if data != None:
                             super.Max = data[1]
                             super.Label = data[0]
@@ -435,7 +434,7 @@ class callbacks(callbacksOp):
                         content of the graph that contains general information on the network activity
                     """
                     if generalGraphSwitchIsOn:
-                        labelData = getNetworkInput(int(sliderValue)*float(updateInterval), g.updateInterval)
+                        labelData = getNetworkInput(int(sliderValue)*float(updateInterval), g.updateInterval, False)
                         if labelData != None:
                             labelData = (labelData[1] // InputPerEpoch)+1 if (labelData[1] % InputPerEpoch) != 0 else (labelData[1] // InputPerEpoch)
                         else:
@@ -490,7 +489,7 @@ class callbacks(callbacksOp):
                     if labelGraphSwitchIsOn:
 
                         labelData = getNetworkInput(
-                            int(sliderValue)*float(updateInterval), g.updateInterval)
+                            int(sliderValue)*float(updateInterval), g.updateInterval, False)
                         if(not super.visStopped):
 
                             if labelData == [None]:
@@ -581,7 +580,7 @@ class callbacks(callbacksOp):
                         elements = super.generate2DView(g,Layer2DViewFilter)
                         matrix = {}
                         indices = {}
-                        labelData = getNetworkInput(int(sliderValue)*float(updateInterval), g.updateInterval)
+                        labelData = getNetworkInput(int(sliderValue)*float(updateInterval), g.updateInterval, True)
                         if callback_context.triggered[0]['prop_id'].split('.')[0] in ["v-step","vis-update"]:
                             super.SpikesActivityPerInput = {i["layer"]:[[0 for _ in range(g.ClassNbr)] for _ in range(g.Layer_Neuron[i["layer"]])] for i in g.LayersNeuronsInfo}
                             for element in elements:
@@ -707,7 +706,7 @@ class callbacks(callbacksOp):
                 
             def make_SpikeActivityPerInput(layer,dataLabel,Layer2DViewFilter):
                 fig = make_subplots(rows=5, cols=1, shared_xaxes=True, vertical_spacing=0.08, specs=[[{'rowspan': 4}],[None],[None],[None],[{'rowspan': 1}]])
-                fig.add_trace(go.Heatmap(z=super.SpikesActivityPerInput[layer] if layer in Layer2DViewFilter else [], colorscale= 'Reds' if sum([item for row in super.SpikesActivityPerInput[layer] for item in row]) > 0 else "gray", zmin=0, hovertemplate=('Class: %{x} <br>Neuron: %{y} <br>Spikes: %{z} <extra></extra>'),xgap=4,ygap=4),row=1, col=1)
+                fig.add_trace(go.Heatmap(z=super.SpikesActivityPerInput[layer] if layer in Layer2DViewFilter else [], colorscale= 'Reds', zmin=0, hovertemplate=('Class: %{x} <br>Neuron: %{y} <br>Spikes: %{z} <extra></extra>'),xgap=4,ygap=4),row=1, col=1)
                 fig.update_layout({"xaxis":dict(title="Class",tickmode="array",zeroline = False,tickvals=[i for i in range(g.ClassNbr)]),"yaxis":dict(title="Neuron",zeroline = False),"margin":{'l': 0, 'r': 0, 't': 5, 'b': 0},"uirevision":'no reset of zoom'})
                 if (dataLabel == None) or (layer not in Layer2DViewFilter):
                     fig.add_trace(go.Bar(x=[],y=[],hovertemplate=('Label: %{x} <br>Nbr: %{y} <extra></extra>')),row=5, col=1)
@@ -719,12 +718,13 @@ class callbacks(callbacksOp):
             # MongoDB operations
             # ---------------------------------------------------------
 
-            def getNetworkInput(timestamp, interval):
+            def getNetworkInput(timestamp, interval, full):
                 """ Get network input for a given timestamp and interval.
 
                 Args:
                     timestamp (int): timestamp value
                     interval (int): interval value
+                    full (bool): get info for all Inputs or just the existing ones in that period
 
                 Returns:
                     array contains totale processed inputs and current inputs
@@ -751,10 +751,14 @@ class callbacks(callbacksOp):
                 if not labels:
                     return None
 
-                L = dict({i: 0 for i in range(g.ClassNbr)})
+                if (full):
+                    L = dict({i: 0 for i in range(g.ClassNbr)})
 
-                for l in labels:
-                    L[l["_id"]] = l["C"]
+                    for l in labels:
+                        L[l["_id"]] = l["C"]
+                else:
+                    L = dict({l["_id"]: l["C"] for l in labels})
+                
                 return [L, Max]
 
             def getSpike(timestamp, interval, layer, perNeuron):

src/Modules/General/spark.py

@@ -65,7 +65,7 @@ class spark(sparkOp):
                 if ('labels' in self.g.db.list_collection_names()):
                     self.g.labelsExistance = True
                     M = max(M, pymongo.collection.Collection(self.g.db, 'labels').find_one(sort=[("T", -1)])["T"])
-                    self.g.ClassNbr = int(max(M, pymongo.collection.Collection(self.g.db, 'labels').find_one(sort=[("L", -1)])["L"]))+1
+                    self.g.ClassNbr = int(pymongo.collection.Collection(self.g.db, 'labels').find_one(sort=[("L", -1)])["L"])+1
                 else:
                     print("No labels")