Support visualisation of morphology only files

pyneuroml/plot/PlotMorphology.py

@@ -18,7 +18,7 @@
 import matplotlib
 import numpy
 from matplotlib import pyplot as plt
-from neuroml import Cell, NeuroMLDocument, SegmentGroup
+from neuroml import Cell, Morphology, NeuroMLDocument, SegmentGroup
 from neuroml.neuro_lex_ids import neuro_lex_ids
 
 from pyneuroml.pynml import read_neuroml2_file
@@ -301,6 +301,7 @@ def plot_2D(
     if verbose:
         print("Plotting %s" % nml_file)
 
+    # if it's a file, load it first
     if isinstance(nml_file, str):
         # load without optimization for older HDF5 API
         # TODO: check if this is required: must for MultiscaleISN
@@ -315,38 +316,43 @@ def plot_2D(
                 optimized=True,
             )
             load_minimal_morphplottable__model(nml_model, nml_file)
+            # note that from this point, the model object is not necessarily valid,
+            # because we've removed lots of bits.
+    else:
+        nml_model = nml_file
 
+    # if it isn't a NeuroMLDocument, create one
+    if isinstance(nml_model, Cell):
+        logger.info("Got a cell")
+        plottable_nml_model = NeuroMLDocument(id="newdoc")
+        plottable_nml_model.add(nml_model)
+        logger.info(f"plottable cell model is: {plottable_nml_model.cells[0]}")
         if title is None:
-            try:
-                title = f"{nml_model.networks[0].id} from {nml_file}"
-            except IndexError:
-                title = f"{nml_model.cells[0].id} from {nml_file}"
-
-    elif isinstance(nml_file, Cell):
-        nml_model = NeuroMLDocument(id="newdoc")
-        nml_model.add(nml_file)
+            title = f"{plottable_nml_model.cells[0].id}"
+
+    # if it's only a cell, add it to an empty cell in a document
+    elif isinstance(nml_model, Morphology):
+        logger.info("Received morph, adding to a dummy cell")
+        plottable_nml_model = NeuroMLDocument(id="newdoc")
+        nml_cell = plottable_nml_model.add(
+            Cell, id=nml_model.id, morphology=nml_model, validate=False
+        )
+        plottable_nml_model.add(nml_cell)
+        logger.info(f"plottable cell model is: {plottable_nml_model.cells[0]}")
         if title is None:
-            title = f"{nml_model.cells[0].id}"
-
-    elif isinstance(nml_file, NeuroMLDocument):
-        nml_model = nml_file
+            title = f"{plottable_nml_model.cells[0].id}"
+    elif isinstance(nml_model, NeuroMLDocument):
+        plottable_nml_model = nml_model
         if title is None:
-            try:
-                title = f"{nml_model.networks[0].id} from {nml_file.id}"
-            except IndexError:
-                title = f"{nml_model.cells[0].id} from {nml_file.id}"
-    else:
-        raise TypeError(
-            "Passed model is not a NeuroML file path, nor a neuroml.Cell, nor a neuroml.NeuroMLDocument"
-        )
+            title = f"{plottable_nml_model.id}"
 
     (
         cell_id_vs_cell,
         pop_id_vs_cell,
         positions,
         pop_id_vs_color,
         pop_id_vs_radii,
-    ) = extract_position_info(nml_model, verbose)
+    ) = extract_position_info(plottable_nml_model, verbose)
 
     if verbose:
         logger.debug(f"positions: {positions}")

pyneuroml/plot/PlotMorphologyVispy.py

@@ -17,7 +17,7 @@
 
 import numpy
 import progressbar
-from neuroml import Cell, NeuroMLDocument, SegmentGroup
+from neuroml import Cell, Morphology, NeuroMLDocument, SegmentGroup
 from neuroml.neuro_lex_ids import neuro_lex_ids
 from scipy.spatial.transform import Rotation
 
@@ -302,7 +302,7 @@ def vispy_on_key_press(event):
 
 
 def plot_interactive_3D(
-    nml_file: typing.Union[str, Cell, NeuroMLDocument],
+    nml_file: typing.Union[str, Cell, Morphology, NeuroMLDocument],
     min_width: float = DEFAULTS["minWidth"],
     verbose: bool = False,
     plot_type: str = "constant",
@@ -335,8 +335,10 @@ def plot_interactive_3D(
 
 
     :param nml_file: path to NeuroML cell file or
-        :py:class:`neuroml.NeuroMLDocument` or :py:class:`neuroml.Cell` object
-    :type nml_file: str or neuroml.NeuroMLDocument or neuroml.Cell
+        :py:class:`neuroml.NeuroMLDocument` or :py:class:`neuroml.Cell`
+        or :py:class:`neuroml.Morphology` object
+    :type nml_file: str or neuroml.NeuroMLDocument or neuroml.Cell or
+        neuroml.Morphology
     :param min_width: minimum width for segments (useful for visualising very
         thin segments): default 0.8um
     :type min_width: float
@@ -449,6 +451,7 @@ def plot_interactive_3D(
     if verbose:
         logger.info(f"Visualising {nml_file}")
 
+    # if it's a file, load it first
     if isinstance(nml_file, str):
         # load without optimization for older HDF5 API
         # TODO: check if this is required: must for MultiscaleISN
@@ -463,38 +466,43 @@ def plot_interactive_3D(
                 optimized=True,
             )
             load_minimal_morphplottable__model(nml_model, nml_file)
+            # note that from this point, the model object is not necessarily valid,
+            # because we've removed lots of bits.
+    else:
+        nml_model = nml_file
 
+    # if it isn't a NeuroMLDocument, create one
+    if isinstance(nml_model, Cell):
+        logger.info("Got a cell")
+        plottable_nml_model = NeuroMLDocument(id="newdoc")
+        plottable_nml_model.add(nml_model)
+        logger.info(f"plottable cell model is: {plottable_nml_model.cells[0]}")
         if title is None:
-            try:
-                title = f"{nml_model.networks[0].id} from {nml_file}"
-            except IndexError:
-                title = f"{nml_model.cells[0].id} from {nml_file}"
-
-    elif isinstance(nml_file, Cell):
-        nml_model = NeuroMLDocument(id="newdoc")
-        nml_model.add(nml_file)
+            title = f"{plottable_nml_model.cells[0].id}"
+
+    # if it's only a cell, add it to an empty cell in a document
+    elif isinstance(nml_model, Morphology):
+        logger.info("Received morph, adding to a dummy cell")
+        plottable_nml_model = NeuroMLDocument(id="newdoc")
+        nml_cell = plottable_nml_model.add(
+            Cell, id=nml_model.id, morphology=nml_model, validate=False
+        )
+        plottable_nml_model.add(nml_cell)
+        logger.info(f"plottable cell model is: {plottable_nml_model.cells[0]}")
         if title is None:
-            title = f"{nml_model.cells[0].id}"
-
-    elif isinstance(nml_file, NeuroMLDocument):
-        nml_model = nml_file
+            title = f"{plottable_nml_model.cells[0].id}"
+    elif isinstance(nml_model, NeuroMLDocument):
+        plottable_nml_model = nml_model
         if title is None:
-            try:
-                title = f"{nml_model.networks[0].id} from {nml_file.id}"
-            except IndexError:
-                title = f"{nml_model.cells[0].id} from {nml_file.id}"
-    else:
-        raise TypeError(
-            "Passed model is not a NeuroML file path, nor a neuroml.Cell, nor a neuroml.NeuroMLDocument"
-        )
+            title = f"{plottable_nml_model.id}"
 
     (
         cell_id_vs_cell,
         pop_id_vs_cell,
         positions,
         pop_id_vs_color,
         pop_id_vs_radii,
-    ) = extract_position_info(nml_model, verbose)
+    ) = extract_position_info(plottable_nml_model, verbose)
 
     logger.debug(f"positions: {positions}")
     logger.debug(f"pop_id_vs_cell: {pop_id_vs_cell}")
@@ -726,7 +734,7 @@ def plot_interactive_3D(
                     f"More meshes than threshold ({len(meshdata.keys())}/{precision[1]}), reducing precision to {precision[0]} and re-calculating."
                 )
                 plot_interactive_3D(
-                    nml_file=nml_model,
+                    nml_file=plottable_nml_model,
                     min_width=min_width,
                     verbose=verbose,
                     plot_type=plot_type,

pyneuroml/utils/__init__.py

@@ -25,13 +25,13 @@
 
 import neuroml
 import numpy
-import pyneuroml.utils.misc
 from lems.model.model import Model
 from neuroml.loaders import read_neuroml2_file
+
+import pyneuroml.utils.misc
 from pyneuroml.errors import UNKNOWN_ERR
 from pyneuroml.utils.plot import get_next_hex_color
 
-
 logger = logging.getLogger(__name__)
 logger.setLevel(logging.INFO)
 
@@ -86,12 +86,20 @@ def extract_position_info(
     pop_id_vs_color = {}
     pop_id_vs_radii = {}
 
+    morph_elements = []
     cell_elements = []
     popElements = []
 
     cell_elements.extend(nml_model.cells)
     cell_elements.extend(nml_model.cell2_ca_poolses)
 
+    # handle morphology elements by adding them into dummy cells
+    ctr = 1
+    morph_elements.extend(nml_model.morphology)
+    for m in morph_elements:
+        cell_elements.append(neuroml.Cell(id=f"Dummy cell {ctr}", morphology=m))
+        ctr += 1
+
     # if the model does not include a network, plot all the cells in the
     # model in new dummy populations
     if len(nml_model.networks) == 0:

pyneuroml/utils/plot.py

@@ -352,6 +352,7 @@ def load_minimal_morphplottable__model(
     required_members = [
         "id",
         "cells",
+        "morphology",
         "cell2_ca_poolses",
         "networks",
         "populations",
@@ -360,6 +361,7 @@ def load_minimal_morphplottable__model(
     for m in model_members:
         if m not in required_members:
             setattr(nml_model, m, None)
+            logger.debug(f"Dropped {m}")
 
     # if the model contains a network, use it
     if len(nml_model.networks) > 0:
@@ -385,11 +387,13 @@ def load_minimal_morphplottable__model(
                         acell.biophysical_properties = None
                         nml_model.add(acell)
     else:
-        # add any included cells to the main document
+        # add any included cells or morphologies to the main document
         for inc in nml_model.includes:
             incl_loc = os.path.abspath(os.path.join(base_path, inc.href))
             if os.path.isfile(incl_loc):
                 inc = read_neuroml2_file(incl_loc)
                 for acell in inc.cells:
                     acell.biophysical_properties = None
                     nml_model.add(acell)
+                for morph in inc.morphology:
+                    nml_model.add(morph)