Su 202503

.gitignore

@@ -46,8 +46,10 @@ barrel_cortex/*
 getting_started/example_data/**/metadata.json
 getting_started/biophysical_constraints/86_CDK_20041214_BAC_run5_soma_Hay2013_C2center_apic_rec.param
 getting_started/functional_constraints/network.param
-getting_started/example_simulation_data/C2_evoked_UpState_INH_PW_1.0_SuW_0.5_C2center/20150815-1530_20240/20240_network_model.param
-getting_started/example_simulation_data/C2_evoked_UpState_INH_PW_1.0_SuW_0.5_C2center/20150815-1530_20240/20240_neuron_model.param
+getting_started/example_data/biophysical_constraints/86_CDK_20041214_BAC_run5_soma_Hay2013_C2center_apic_rec.param
+getting_started/example_data/functional_constraints/network.param
+getting_started/example_data/simulation_data/C2_evoked_UpState_INH_PW_1.0_SuW_0.5_C2center/20150815-1530_20240/20240_network_model.param
+getting_started/example_data/simulation_data/C2_evoked_UpState_INH_PW_1.0_SuW_0.5_C2center/20150815-1530_20240/20240_neuron_model.param
 getting_started/radii/data/neuron1/output**
 
 # Ignore example param files generated from templates, but don't ignore templates themselves

Interface/__init__.py

@@ -260,7 +260,7 @@ def print_module_versions():
     logger.info("Loaded modules with __version__ attribute are:\n" + ', '.join(module_versions))
 
 
-def get_client(ip=None, client_port=38786, timeout=120):
+def get_client(ip=None, client_port=38786, timeout=120, cluster=None):
     """
     Gets the distributed.client object if dask has been setup
 
@@ -288,7 +288,10 @@ def get_client(ip=None, client_port=38786, timeout=120):
             hostname
         )  # fetches the ip of the current host
     logger.info("Getting dask client with ip {}".format(ip))
-    c = Client(ip + ':' + client_port, timeout=timeout)
+    if cluster:
+        c = cluster.get_client()
+    else:
+        c = Client(ip + ':' + client_port, timeout=timeout)
     logger.info("Got dask client {}".format(c))
     logger.debug("Making mechanisms visible on client side")
     local_pythonpath = os.environ.get('PYTHONPATH', '')

README.md

@@ -31,7 +31,7 @@ Installation instructions can be found [here](https://mpinb.github.io/in_silico_
 
 ISF is available for Linux, Windows and macOS.
 For installation and environment management, ISF uses [pixi](https://pixi.sh/latest/). 
-Please follow the installation instructions on the [`pixi` documentation](https://pixi.sh/latest/#installation)
+Please follow the installation instructions on the [pixi documentation](https://pixi.sh/latest/#installation)
 
 To install ISF with pixi, simply:
 

biophysics_fitting/L5tt_parameter_setup.py

@@ -187,15 +187,15 @@ def get_L5tt_template():
                             'spatial': 'uniform'
                         },
                         'Ca_HVA': {
-                            'begin': 900.0,
-                            'end': 1100.0,
+                            'begin': None,
+                            'end': None,
                             'gCa_HVAbar': None,
                             'outsidescale': 0.1,
                             'spatial': 'uniform_range'
                         },
                         'Ca_LVAst': {
-                            'begin': 900.0,
-                            'end': 1100.0,
+                            'begin': None,
+                            'end': None,
                             'gCa_LVAstbar': None,
                             'outsidescale': 0.01,
                             'spatial': 'uniform_range'
@@ -391,6 +391,7 @@ def get_L5tt_template_v2():
     return NTParameterSet(p['neuron'])
 
 
+
 def set_morphology(cell_param, filename=None):
     """Add the morphology to a cell parameter object.
 

pyproject.toml

@@ -38,9 +38,9 @@ requires = ["hatchling"]
 cmasher = ">=1.6.3,<2"
 cython = ">=3.0.11,<4"
 dash = ">=2.18.1,<3"
-dask = "2.30.0.*"
+dask = ">=2022.6"
 fasteners = ">=0.17.3,<0.18"
-flask = "==1.1.4"
+flask = ">=2.3"
 ipywidgets = ">=8.1.5,<9"
 jupyterlab = ">=3.5.3,<4"
 jupyter-scatter = ">=0.19.1,<0.20"
@@ -59,6 +59,8 @@ seaborn = ">=0.12.2,<0.13"
 scipy = "1.5.2.*"
 wheel = ">=0.45.1,<0.46"
 zarr = ">=2.15.0,<3"
+dask-gateway = ">=2023.1.1,<2024"
+async-timeout = ">=4.0.3,<5"
 
 [tool.pixi.pypi-dependencies]
 bluepyopt = "==1.9.126"
@@ -70,15 +72,15 @@ blenderspike-py = { git = "https://github.com/ArtemKirsanov/BlenderSpike.git" }
 
 # OS specific dependencies
 [tool.pixi.target.osx]
-pypi-dependencies = { neuron = ">=8.2", "distributed"= ">=2.30.0"}
+pypi-dependencies = { neuron = ">=8.2", distributed = ">=2022.6"}
 dependencies = { numpy = "==1.21", pytables = ">=3.7.0,<4" }
 
 [tool.pixi.target.linux]
-dependencies = { neuron = "==7.8.2", numpy = "==1.19.2", distributed = "==2.30.0", gcc = "<15" }
+dependencies = { neuron = "==7.8.2", numpy = "==1.19.2", distributed = ">=2022.6", gcc = "<15" }
 pypi-dependencies = { tables = ">=3.8.0,<4" }
 
 [tool.pixi.target.win]
-dependencies = { numpy = "==1.19.2", distributed = "==2.30.0"}
+dependencies = { numpy = "==1.19.2", distributed = ">=2022.6"}
 pypi-dependencies = { tables = ">=3.8.0,<4" }
 
 # Docs does not inherit the default dependencies

single_cell_parser/cell_parser.py

@@ -431,7 +431,7 @@ def insert_range_mechanisms(self, label, mechs):
                                 h.pop_section()
 
             elif mech.spatial == 'linear':
-                ''' spatially linear distribution with negative slope'''
+                ''' spatially linear distribution with slope'''
                 maxDist = self.cell.max_distance(label)
                 #                set origin to 0 of first branch with this label
                 if label == 'Soma':
@@ -459,8 +459,11 @@ def insert_range_mechanisms(self, label, mechs):
                             dist = self.cell.distance_to_soma(sec, seg.x)
                             if relDistance:
                                 dist = dist / maxDist
-                            #rangeVarVal = mech[param]*(dist*slope + offset)
-                            rangeVarVal = max(mech[param] * (dist * slope + 1),
+                            if slope > 0: # positive slope
+                                rangeVarVal = min(mech[param] * (dist * slope + 1),
+                                              mech[param] * offset)
+                            else: 
+                                rangeVarVal = max(mech[param] * (dist * slope + 1),
                                               mech[param] * offset)
                             s = param + '=' + str(rangeVarVal)
                             paramStrings.append(s)

visualize/cell_morphology_visualizer.py

@@ -1487,6 +1487,7 @@ def interactive_app(
             port=5050,
             host=self.dash_ip)
 
+
 def get_3d_plot_morphology(
     lookup_table=None,
     colors="grey",
@@ -1502,7 +1503,9 @@ def get_3d_plot_morphology(
     synapse_legend=True,
     legend=None,
     return_figax = True,
-    proj_type="ortho"
+    proj_type="ortho",
+    fig = None,  
+    ax = None
     ):
     """Constructs a 3d matplotlib plot of a cell morphology, overlayed with some scalar data.
 
@@ -1528,21 +1531,25 @@ def get_3d_plot_morphology(
         synapse_legend (bool): Whether the synapse activations legend should appear in the plot
         legend (bool): Whether the legend for scalar data (e.g. membrane voltage) should appear in the plot
         return_figax (bool): Whether to return the figure and axis objects. Default: True
-        proj_type (str): Projection type for the 3D plot. Default: "ortho"
+        proj_type (str): Projection type for the 3D plot, ignored if fig and ax are provided. Default: "ortho"
+        fig (matplotlib.figure.Figure): Figure object to plot on. If None, a new figure and axes will be created.
+        ax (matplotlib.axes._subplots.Axes3DSubplot): Axes object. Ignored if fig is None. Note that it must be created as a 3D axes with the intended projection type.
 
     Returns:
         tuple | None: fig and ax object if :paramref:`return_figax` is True. None otherwise.
     """
     #----------------- Generic axes setup
-    fig = plt.figure(
-        figsize=(15, 15), 
-        dpi=dpi,
-        num=str(time_point) if time_point is not None else None)
-    ax = plt.axes(projection='3d', proj_type=proj_type)
+    if not fig: 
+        assert not ax, "If no figure is given, ax argument is ignored!"
+        fig = plt.figure(
+            figsize=(15, 15), 
+            dpi=dpi,
+            num=str(time_point) if time_point is not None else None)
+        ax = plt.axes(projection='3d', proj_type=proj_type)
     ax.set_xticks([])
     ax.set_yticks([])
     ax.set_zticks([])
-    plt.axis('off')
+    ax.axis('off')
     ax.set_xlabel('x')
     ax.set_ylabel('y')
     ax.set_zlabel('z')

visualize/utils.py

@@ -65,8 +65,8 @@ def write_video_from_images(
     Returns:
         None. Writes the video to the specified path.
     '''
-    try:
-        subprocess.check_output(["module load", "ffmpeg"])
+    try: 
+        subprocess.check_output(["module load", "ffmpeg"], shell = True)
     except Exception as e:
         raise EnvironmentError("Could not load ffmpeg") from e