Merge pull request #801 from suny-downstate-medical-center/development

Merge latest development to nml branch

CHANGES.md

@@ -16,6 +16,8 @@
 
 - Fixed loading netParams in some scenarios (bug caused by srting functions pre-processing)
 
+- Fix of `plotRaster` pops coloring if ordered not by gid
+
 # Version 1.0.5
 
 **New features**

netpyne/analysis/spikes.py

@@ -375,6 +375,8 @@ def prepareSpikeData(
         'orderBy': orderBy,
         'axisArgs': axisArgs,
         'legendLabels': legendLabels,
+        'cellGids': df['pop'].index.tolist(),
+        'cellPops': df['pop'].tolist(),
     }
 
     if colorbyPhase:

netpyne/plotting/plotRaster.py

@@ -228,6 +228,8 @@ def plotRaster(
     if type(rasterData) == str:
         rasterData = loadData(rasterData)
 
+    popsOfCellsByGid = zip([], [])
+
     # If input is a dictionary, pull the data out of it
     if type(rasterData) == dict:
 
@@ -245,6 +247,10 @@ def plotRaster(
         axisArgs = rasterData.get('axisArgs')
         legendLabels = rasterData.get('legendLabels')
 
+        popsOfCellsByGid = zip( # ordered the same
+            rasterData.get('cellGids', []),
+            rasterData.get('cellPops', []))
+
     # If input is a list or tuple, the first item is spike times, the second is spike indices
     elif type(rasterData) == list or type(rasterData) == tuple:
         spkTimes = rasterData[0]
@@ -288,32 +294,13 @@ def plotRaster(
             + ') must be the same size'
         )
 
-    # Create a dictionary with the color for each pop
-    if not colorList:
-        from .plotter import colorList
-    popColorsTemp = {popLabel: colorList[ipop % len(colorList)] for ipop, popLabel in enumerate(popLabels)}
-    if popColors:
-        popColorsTemp.update(popColors)
-    popColors = popColorsTemp
-
-    # Create a list to link cell indices to their populations
-    indPop = []
-    for popLabel, popNumCell in zip(popLabels, popNumCells):
-        indPop.extend(int(popNumCell) * [popLabel])
-
-    # Create a dictionary to link cells to their population color
-    cellInds = list(set(spkInds))
-    indColors = {cellInd: popColors[indPop[int(cellInd)]] for cellInd in cellInds}
-
-    # Create a list of spkColors to be fed into the scatter plot
-    spkColors = [indColors[spkInd] for spkGid, spkInd in zip(spkGids, spkInds)]
-
     # Set the time range appropriately
     if 'timeRange' in kwargs:
         timeRange = kwargs['timeRange']
     elif 'timeRange' in rasterData:
         timeRange = rasterData['timeRange']
     else:
+        import numpy as np
         timeRange = [0, np.ceil(max(spkTimes))]
 
     # Set features for raster plot colored by phase
@@ -325,6 +312,33 @@ def plotRaster(
         if 'pop_background' in colorbyPhase:
             if colorbyPhase['pop_background'] == True:
                 kwargs['background'] = {'popLabels': popLabels, 'popNumCells': popNumCells, 'timeRange': timeRange}
+    else:
+        # Create a dictionary with the color for each pop
+        if not colorList:
+            from .plotter import colorList
+        popColorsTemp = {popLabel: colorList[ipop % len(colorList)] for ipop, popLabel in enumerate(popLabels)}
+        if popColors:
+            popColorsTemp.update(popColors)
+        popColors = popColorsTemp
+
+        if orderBy == 'gid':
+            # Create a list to link cell indices to their populations
+            indPop = []
+            for popLabel, popNumCell in zip(popLabels, popNumCells):
+                indPop.extend(int(popNumCell) * [popLabel])
+
+            def color(_, ind):
+                return popColors[indPop[int(ind)]]
+        else:
+            popByGid = {gid: pop for (gid, pop) in popsOfCellsByGid}
+            def color(gid, _):
+                pop = popByGid.get(gid)
+                if not pop:
+                    return [.0, .0, .0] # default to black
+                return popColors.get(pop)
+
+        # Create a list of spkColors to be fed into the scatter plot
+        spkColors = [color(gid, ind) for gid, ind in zip(spkGids, spkInds)]
 
     # Create a dictionary with the inputs for a scatter plot
     scatterData = {}

netpyne/specs/netParams.py

@@ -846,5 +846,5 @@ def setNestedParam(self, paramLabel, paramVal):
     def setCfgMapping(self, cfg):
         if hasattr(self, 'mapping'):
             for k, v in self.mapping.items():
-                if getattr(cfg, k, None):
+                if hasattr(cfg, k):
                     self.setNestedParam(v, getattr(cfg, k))

netpyne/tutorials/README.md

@@ -6,20 +6,19 @@ We don't want to affect your system in any way, so we will operate from a virtua
 
 You can open a terminal and enter the following at the prompt:
 
-    mkdir netpyne_tuts && cd netpyne_tuts && export PATH=/bin:/usr/bin && python3 -m venv env && source env/bin/activate && python3 -m pip install --upgrade pip && python3 -m pip install --upgrade ipython && python3 -m pip install --upgrade ipykernel && python3 -m pip install --upgrade jupyter && ipython kernel install --user --name=env && python3 -m pip install --upgrade neuron && git clone https://github.com/Neurosim-lab/netpyne.git && python3 -m pip install -e netpyne && cp -r netpyne/netpyne/tutorials . && cd tutorials && jupyter notebook
+    mkdir netpyne_tuts && cd netpyne_tuts && export PATH=/bin:/usr/bin && python3 -m venv env && source env/bin/activate && python3 -m pip install --upgrade pip && python3 -m pip install --upgrade ipython && python3 -m pip install --upgrade ipykernel && python3 -m pip install --upgrade jupyter && ipython kernel install --user --name=env && python3 -m pip install --upgrade neuron && git clone --depth 1 https://github.com/suny-downstate-medical-center/netpyne.git && python3 -m pip install -e netpyne && cp -r netpyne/netpyne/tutorials . && cd tutorials && jupyter notebook
 
 ## Installation option two
 
-You can execute **netpyne_tut0.py** by opening a terminal and entering:
+You can execute **install_tuts.py** by downloading it, opening a terminal and entering:
 
-    python3 netpyne_tut0.py
+    python3 install_tuts.py
 
 ## Installation option three
 
-You can execute **netpyne_tut0.sh** by opening a terminal and entering:
+You can execute **install_tuts.sh** by downloading it, opening a terminal and entering:
 
-    chmod u+x netpyne_tut0.sh
-    ./netpyne_tut0.sh
+    sh install_tuts.sh
 
 ## Installation summary
 
@@ -31,15 +30,15 @@ Either of these options will do the same thing.  They will:
 - Activate (enter) the virtual environment
 - Upgrade pip and install necessary packages
 - Create a Jupyter kernel out of **env**
-- Clone the NetPyNE GitHub repository
+- Clone the NetPyNE GitHub repository (using shallow cloning)
 - Install NetPyNE using pip 
 - Copy the NetPyNE **tutorials** directory into **netpyne_tuts**
 - Change into the **tutorials** directory
 - Start Jupyter Notebook
 
 ## Future use
 
-This installation step only needs to be performed once.  To re-enter the virtual environment in the future, change to the **netpyne_tuts** directory and execute the following:
+This installation step only needs to be performed once. To re-enter the virtual environment in the future, change to the **netpyne_tuts** directory and execute the following:
 
     source env/bin/activate
     jupyter notebook