Merge branch 'CSNG-MFF:master' into master

.github/workflows/fast-model-mpi-explosion.yml

@@ -20,7 +20,7 @@ jobs:
         pip3 install pytest pytest-cov pytest-randomly coverage black
         # TODO: Remove fixed numpy and pynn versions after the PyNN pull request
         # https://github.com/NeuralEnsemble/PyNN/pull/762 is accepted
-        pip3 install numpy==1.23.5 scipy mpi4py matplotlib quantities lazyarray interval Pillow param==1.5.1 parameters neo cython pynn==0.10.0 psutil future requests elephant pytest-xdist pytest-timeout junitparser numba
+        pip3 install numpy==1.23.5 scipy mpi4py matplotlib quantities lazyarray interval Pillow param==1.5.1 parameters neo==0.12.0 cython pynn==0.10.0 psutil future requests elephant pytest-xdist pytest-timeout junitparser numba
     - name: Download and install imagen
       run: |
         git clone https://github.com/antolikjan/imagen.git

.github/workflows/fast-model-mpi.yml

@@ -20,7 +20,7 @@ jobs:
         pip3 install pytest pytest-cov pytest-randomly coverage black
         # TODO: Remove fixed numpy and pynn versions after the PyNN pull request
         # https://github.com/NeuralEnsemble/PyNN/pull/762 is accepted
-        pip3 install numpy==1.23.5 scipy mpi4py matplotlib quantities lazyarray interval Pillow param==1.5.1 parameters neo cython pynn==0.10.0 psutil future requests elephant pytest-xdist pytest-timeout junitparser numba
+        pip3 install numpy==1.23.5 scipy mpi4py matplotlib quantities lazyarray interval Pillow param==1.5.1 parameters neo==0.12.0 cython pynn==0.10.0 psutil future requests elephant pytest-xdist pytest-timeout junitparser numba
     - name: Download and install imagen
       run: |
         git clone https://github.com/antolikjan/imagen.git

.github/workflows/fast-model-stepcurrentmodule.yml

@@ -19,7 +19,7 @@ jobs:
         pip3 install pytest pytest-cov pytest-randomly coverage black
         # TODO: Remove fixed numpy and pynn versions after the PyNN pull request
         # https://github.com/NeuralEnsemble/PyNN/pull/762 is accepted
-        pip3 install numpy==1.23.5 scipy mpi4py matplotlib quantities lazyarray interval Pillow param==1.5.1 parameters neo cython psutil future requests elephant pytest-xdist pytest-timeout junitparser numba
+        pip3 install numpy==1.23.5 scipy mpi4py matplotlib quantities lazyarray interval Pillow param==1.5.1 parameters neo==0.12.0 cython psutil future requests elephant pytest-xdist pytest-timeout junitparser numba
 
     - name: Download and install imagen
       run: |

.github/workflows/fast-model.yml

@@ -19,7 +19,7 @@ jobs:
         pip3 install pytest pytest-cov pytest-randomly coverage black
         # TODO: Remove fixed numpy and pynn versions after the PyNN pull request
         # https://github.com/NeuralEnsemble/PyNN/pull/762 is accepted
-        pip3 install numpy==1.23.5 scipy mpi4py matplotlib quantities lazyarray interval Pillow param==1.5.1 parameters neo cython pynn==0.10.0 psutil future requests elephant pytest-xdist pytest-timeout junitparser numba
+        pip3 install numpy==1.23.5 scipy mpi4py matplotlib quantities lazyarray interval Pillow param==1.5.1 parameters neo==0.12.0 cython pynn==0.10.0 psutil future requests elephant pytest-xdist pytest-timeout junitparser numba
 
     - name: Download and install imagen
       run: |

.github/workflows/lsv1m-model.yml

@@ -19,7 +19,7 @@ jobs:
         pip3 install pytest pytest-cov pytest-randomly coverage black
         # TODO: Remove fixed numpy and pynn versions after the PyNN pull request
         # https://github.com/NeuralEnsemble/PyNN/pull/762 is accepted
-        pip3 install numpy==1.23.5 scipy mpi4py matplotlib quantities lazyarray interval Pillow param==1.5.1 parameters neo cython pynn==0.10.0 psutil future requests elephant pytest-xdist pytest-timeout junitparser numba
+        pip3 install numpy==1.23.5 scipy mpi4py matplotlib quantities lazyarray interval Pillow param==1.5.1 parameters neo==0.12.0 cython pynn==0.10.0 psutil future requests elephant pytest-xdist pytest-timeout junitparser numba
 
     - name: Download and install imagen
       run: |

.github/workflows/unit-tests.yml

@@ -19,7 +19,7 @@ jobs:
         pip3 install pytest pytest-cov pytest-randomly coverage black
         # TODO: Remove fixed numpy and pynn versions after the PyNN pull request
         # https://github.com/NeuralEnsemble/PyNN/pull/762 is accepted
-        pip3 install numpy==1.23.5 scipy mpi4py matplotlib quantities lazyarray interval Pillow param==1.5.1 parameters neo cython pynn==0.10.0 psutil future requests elephant pytest-xdist pytest-timeout junitparser numba
+        pip3 install numpy==1.23.5 scipy mpi4py matplotlib quantities lazyarray interval Pillow param==1.5.1 parameters neo==0.12.0 cython pynn==0.10.0 psutil future requests elephant pytest-xdist pytest-timeout junitparser numba
 
     - name: Download and install imagen
       run: |

README.rst

@@ -51,7 +51,7 @@ ____________
 
 Now you can install all other dependencies in this protected environment::
 
-  pip3 install numpy==1.23.5 scipy mpi4py matplotlib quantities lazyarray interval Pillow param==1.5.1 parameters neo cython psutil future requests elephant pytest-xdist pytest-timeout junitparser numba
+  pip3 install numpy==1.23.5 scipy mpi4py matplotlib quantities lazyarray interval Pillow param==1.5.1 parameters neo==0.12.0 cython psutil future requests elephant pytest-xdist pytest-timeout junitparser numba
 
 Next we will manually install several packages. It is probably the best if you create a separate directory in an appropriate
 place, where you will download and install the packages from.
@@ -60,14 +60,14 @@ First install the *imagen* package::
 
   git clone https://github.com/CSNG-MFF/imagen.git
   cd imagen
-  python setup.py install
+  pip install .
 
 Then install the *PyNN* package from the PyNNStepCurrentModule branch::
 
   git clone https://github.com/CSNG-MFF/PyNN.git
   cd PyNN
   git checkout PyNNStepCurrentModule
-  python setup.py install
+  pip install .
 
 Next install the *Nest* simulator (always in the virtual environment):
 
@@ -125,7 +125,7 @@ And, finally, Mozaik::
     
     git clone https://github.com/CSNG-MFF/mozaik.git
     cd mozaik
-    python setup.py install
+    pip install .
     
 
 .. _ref-run:

mozaik/experiments/optogenetic.py

@@ -232,12 +232,12 @@ def stimulating_signal_function(sheet, coor_x, coor_y, update_interval, paramete
 
     def __init__(self, model, parameters):
         CorticalStimulationWithOptogeneticArray.__init__(self, model, parameters)
-        self.parameters.stimulator_array_parameters[
-            "stimulating_signal"
-        ] = self.parameters.stimulating_signal
-        self.parameters.stimulator_array_parameters[
-            "stimulating_signal_parameters"
-        ] = self.parameters.stimulating_signal_parameters
+        self.parameters.stimulator_array_parameters["stimulating_signal"] = (
+            self.parameters.stimulating_signal
+        )
+        self.parameters.stimulator_array_parameters["stimulating_signal_parameters"] = (
+            self.parameters.stimulating_signal_parameters
+        )
 
         self.append_direct_stim(model, self.parameters.stimulator_array_parameters)
 
@@ -333,9 +333,9 @@ class OptogeneticArrayStimulusCircles(CorticalStimulationWithOptogeneticArray):
     def __init__(self, model, parameters):
         CorticalStimulationWithOptogeneticArray.__init__(self, model, parameters)
         sap = self.parameters.stimulator_array_parameters
-        sap[
-            "stimulating_signal"
-        ] = "mozaik.sheets.direct_stimulator.stimulating_pattern_flash"
+        sap["stimulating_signal"] = (
+            "mozaik.sheets.direct_stimulator.stimulating_pattern_flash"
+        )
         sap["stimulating_signal_parameters"] = ParameterSet(
             {
                 "shape": "circle",
@@ -457,9 +457,9 @@ class OptogeneticArrayStimulusHexagonalTiling(CorticalStimulationWithOptogenetic
     def __init__(self, model, parameters):
         CorticalStimulationWithOptogeneticArray.__init__(self, model, parameters)
         sap = self.parameters.stimulator_array_parameters
-        sap[
-            "stimulating_signal"
-        ] = "mozaik.sheets.direct_stimulator.stimulating_pattern_flash"
+        sap["stimulating_signal"] = (
+            "mozaik.sheets.direct_stimulator.stimulating_pattern_flash"
+        )
         sap["stimulating_signal_parameters"] = ParameterSet(
             {
                 "shape": "hexagon",
@@ -621,9 +621,9 @@ class OptogeneticArrayImageStimulus(CorticalStimulationWithOptogeneticArray):
     def __init__(self, model, parameters):
         CorticalStimulationWithOptogeneticArray.__init__(self, model, parameters)
         sap = self.parameters.stimulator_array_parameters
-        sap[
-            "stimulating_signal"
-        ] = "mozaik.sheets.direct_stimulator.stimulating_pattern_flash"
+        sap["stimulating_signal"] = (
+            "mozaik.sheets.direct_stimulator.stimulating_pattern_flash"
+        )
         sap["stimulating_signal_parameters"] = ParameterSet(
             {
                 "shape": "image",
@@ -741,9 +741,9 @@ def __init__(self, model, parameters):
         self.parameters["sheet_intensity_scaler"] = [1 for s in sl]
         self.parameters["sheet_transfection_proportion"] = [1 for s in sl]
         sap = self.parameters.stimulator_array_parameters
-        sap[
-            "stimulating_signal"
-        ] = "mozaik.sheets.direct_stimulator.stimulating_pattern_flash"
+        sap["stimulating_signal"] = (
+            "mozaik.sheets.direct_stimulator.stimulating_pattern_flash"
+        )
         sap["stimulating_signal_parameters"] = ParameterSet(
             {
                 "shape": "or_map",
@@ -885,9 +885,9 @@ def __init__(self, model, parameters):
         self.parameters["sheet_intensity_scaler"] = [1 for s in sl]
         self.parameters["sheet_transfection_proportion"] = [1 for s in sl]
         sap = self.parameters.stimulator_array_parameters
-        sap[
-            "stimulating_signal"
-        ] = "mozaik.sheets.direct_stimulator.stimulating_pattern_flash"
+        sap["stimulating_signal"] = (
+            "mozaik.sheets.direct_stimulator.stimulating_pattern_flash"
+        )
         sap["stimulating_signal_parameters"] = ParameterSet(
             {
                 "shape": "or_map",

mozaik/visualization/plotting.py

@@ -58,7 +58,7 @@
 from neo.core.analogsignal import AnalogSignal as NeoAnalogSignal
 from neo.core.spiketrain import SpikeTrain as NeoSpikeTrain
 from .simple_plot import StandardStyleLinePlot, SpikeRasterPlot, \
-                        SpikeHistogramPlot, ConductancesPlot, PixelMovie, \
+                        SpikeHistogramPlot, ConductancePlot, ConductancesPlot, PixelMovie, \
                         ScatterPlotMovie, ScatterPlot, ConnectionPlot, SimplePlot, HistogramPlot, CorticalColumnSpikeRasterPlot, OrderedAnalogSignalListPlot
 from .plot_constructors import LinePlot, PerStimulusPlot, PerStimulusADSPlot, ADSGridPlot, MultipleFilesPlot
 
@@ -712,51 +712,60 @@ class GSynPlot(Plotting):
     
     spontaneous : bool
                 Whether to also show the spontaneous activity the preceded the stimulus.
-    """
     
+    separated : bool
+                Whether the excitatory and inhibitory conductances should be plotted separately.
+    """
+
     required_parameters = ParameterSet({
         'neuron': int,  # we can only plot one neuron - which one ?
         'sheet_name': str,
         'spontaneous' : bool, # whether to also show the spontaneous activity the preceded the stimulus
+        'separated': bool, # Whether the excitatory and inhibitory conductances should be plotted separately
     })
 
     def subplot(self, subplotspec):
         dsv = queries.param_filter_query(self.datastore,sheet_name=self.parameters.sheet_name)
         return PerStimulusPlot(dsv, function=self._ploter, title_style="Standard"
                                         ).make_line_plot(subplotspec)
-    
+
     @staticmethod
     def concat_asl(asl1,asl2):
         assert asl1.sampling_period == asl2.sampling_period
         assert asl1.units == asl2.units
-        
+
         return NeoAnalogSignal(numpy.concatenate((asl1.magnitude,asl2.magnitude)),t_start=-asl1.t_stop,
                             sampling_period=asl1.sampling_period,
                             units=asl1.units)
 
 
-    def _ploter(self, dsv,gs):
+    def _ploter(self, dsv, subplotspec):
+        if self.parameters.separated:
+            gs = gridspec.GridSpecFromSubplotSpec(2, 1, subplot_spec=subplotspec,hspace=0.3, wspace=0.45)
+        else:
+            gs = gridspec.GridSpecFromSubplotSpec(1, 1, subplot_spec=subplotspec)
+
         segs = sorted(dsv.get_segments(),key = lambda x : MozaikParametrized.idd(x.annotations['stimulus']).trial)
         gsyn_es = [s.get_esyn(self.parameters.neuron) for s in segs]
         gsyn_is = [s.get_isyn(self.parameters.neuron) for s in segs]
         params = OrderedDict()
-        
+
         if self.parameters.spontaneous:
            segs = sorted(dsv.get_segments(null=True),key = lambda x : MozaikParametrized.idd(x.annotations['stimulus']).trial)
-           spont_gsyn_es = [s.get_esyn(self.parameters.neuron) for s in segs] 
-           spont_gsyn_is = [s.get_isyn(self.parameters.neuron) for s in segs] 
-           
-           gsyn_es = [GSynPlot.concat_asl(s,n) for n,s in zip(gsyn_es,spont_gsyn_es)] 
-           gsyn_is = [GSynPlot.concat_asl(s,n) for n,s in zip(gsyn_is,spont_gsyn_is)] 
+           spont_gsyn_es = [s.get_esyn(self.parameters.neuron) for s in segs]
+           spont_gsyn_is = [s.get_isyn(self.parameters.neuron) for s in segs]
+
+           gsyn_es = [GSynPlot.concat_asl(s,n) for n,s in zip(gsyn_es,spont_gsyn_es)]
+           gsyn_is = [GSynPlot.concat_asl(s,n) for n,s in zip(gsyn_is,spont_gsyn_is)]
            t_start = - spont_gsyn_es[0].t_stop.magnitude
            t_stop = gsyn_es[0].t_stop.magnitude
            params = {'x_ticks' : [t_start,0, t_stop/2, t_stop]}
-        
-        return [("ConductancesPlot",ConductancesPlot(gsyn_es, gsyn_is),gs,params)]
-
-
-
-
+
+        if self.parameters.separated:
+            return [("ConductancePlotExc",ConductancePlot(gsyn_es,'exc'),gs[0,0],params),
+                    ("ConductancePlotInh",ConductancePlot(gsyn_is,'inh'),gs[1,0],params)]
+        else:
+            return [("ConductancesPlot",ConductancesPlot(gsyn_es, gsyn_is),gs[0,0],params)]
 
 
 
@@ -820,7 +829,7 @@ def _ploter(self, dsv,subplotspec):
 
                  ("Conductance_plot",GSynPlot(dsv,
                    ParameterSet({'sheet_name': self.parameters.sheet_name,'spontaneous' : self.parameters.spontaneous,
-                               'neuron': self.parameters.neuron})
+                               'separated' : False, 'neuron': self.parameters.neuron})
                  ),gs[1 + offset, 0], {'x_label' : None, 'x_tick_style' : 'Custom' , 'x_tick_labels' : None, 'title' : None}),
 
                  ("Vm_plot",VmPlot(dsv,
@@ -1186,6 +1195,9 @@ class PerNeuronValuePlot(Plotting):
     cortical_view : bool  
                 Whether to show cortical view or histogram (see class description for full detail.)
                 
+    neuron_ids : list  
+                List of neurons to plot 
+                
     Notes
     -----
     So far doesn't support the situation where several types of PerNeuronValue analysys data structures are present in the supplied
@@ -1194,6 +1206,7 @@ class PerNeuronValuePlot(Plotting):
 
     required_parameters = ParameterSet({
           'cortical_view': bool,  #Whether to show cortical view or histogram (see class description for full detail.)
+          'neuron_ids': list,
     })
 
     def __init__(self, datastore, parameters, plot_file_name=None,
@@ -1215,9 +1228,9 @@ def _ploter(self, dsv, gs):
             assert len(pnvs) <= 1, logger.error("We can only display single stimulus parametrization in cortical view, but you have suplied multiple in datastore.")
             pnv = pnvs[0]
             pos = self.dsv.get_neuron_positions()[pnv.sheet_name]                            
-            posx = pos[0,self.datastore.get_sheet_indexes(pnv.sheet_name,pnv.ids)]
-            posy = pos[1,self.datastore.get_sheet_indexes(pnv.sheet_name,pnv.ids)]
-            values = pnv.values
+            posx = pos[0,self.datastore.get_sheet_indexes(pnv.sheet_name,self.parameters.neuron_ids)]
+            posy = pos[1,self.datastore.get_sheet_indexes(pnv.sheet_name,self.parameters.neuron_ids)]
+            values = pnv.get_value_by_id(self.parameters.neuron_ids)
             if pnv.period != None:
                 periodic = True
                 period = pnv.period
@@ -1240,9 +1253,9 @@ def _ploter(self, dsv, gs):
             a = sorted([(','.join([p + ' : ' + str(getattr(MozaikParametrized.idd(pnv.stimulus_id),p)) for p in varying_stim_parameters]),pnv) for pnv in pnvs],key=lambda x: x[0])
 
             if len(a) > 1:
-                return [("HistogramPlot",HistogramPlot([z[1].values for z in a],labels=[z[0] for z in a]),gs,params)]
+                return [("HistogramPlot",HistogramPlot([z[1].get_value_by_id(self.parameters.neuron_ids) for z in a],labels=[z[0] for z in a]),gs,params)]
             else:
-                return [("HistogramPlot",HistogramPlot([pnvs[0].values]),gs,params)]
+                return [("HistogramPlot",HistogramPlot([pnvs[0].get_value_by_id(self.parameters.neuron_ids)]),gs,params)]