For 1.1.3 release

docs/source/pyneuroml.plot.rst

@@ -31,3 +31,18 @@ pyneuroml.plot.PlotMorphology module
    :show-inheritance:
    :exclude-members:  set, add_line, plot_from_console, main, process_args, LineDataUnits
 
+pyneuroml.plot.PlotMorphologyVispy module
+------------------------------------------
+
+.. automodule:: pyneuroml.plot.PlotMorphologyVispy
+   :members:
+   :undoc-members:
+   :show-inheritance:
+
+pyneuroml.plot.PlotMorphologyPlotly module
+------------------------------------------
+
+.. automodule:: pyneuroml.plot.PlotMorphologyPlotly
+   :members:
+   :undoc-members:
+   :show-inheritance:

pyneuroml/__init__.py

@@ -8,7 +8,7 @@
     __version__ = importlib_metadata.version("pyNeuroML")
 
 
-JNEUROML_VERSION = "0.12.4"
+JNEUROML_VERSION = "0.13.0"
 
 # Define a logger for the package
 logging.basicConfig(

pyneuroml/analysis/ChannelDensityPlot.py

@@ -564,7 +564,7 @@ def plot_channel_densities(
     show_plots_already: bool = True,
     morph_plot_type: str = "constant",
     morph_min_width: float = 2.0,
-    target_directory=None
+    target_directory=None,
 ):
     """Plot channel densities on a Cell on morphology plots.
 
@@ -601,11 +601,13 @@ def plot_channel_densities(
     :param colormap_name: name of matplotlib colormap to use for morph plot.
         Note that if there's only one overlay value, the colormap is modified
         to only show the max value of the colormap to indicate this.
+
+        See: https://matplotlib.org/stable/users/explain/colors/colormaps.html
     :type colormap_name: str
     :returns: None
     """
-    tgt_dir = target_directory+'/' if target_directory else './'
-    
+    tgt_dir = target_directory + "/" if target_directory else "./"
+
     if channel_density_ids is not None and ion_channels is not None:
         raise ValueError(
             "Only one of channel_density_ids or ions channels may be provided"

pyneuroml/plot/PlotMorphology.py

@@ -9,33 +9,31 @@
 
 
 import argparse
+import logging
 import os
-import sys
 import random
-
+import sys
 import typing
-import logging
 
-import numpy
 import matplotlib
+import numpy
 from matplotlib import pyplot as plt
-
+from neuroml import Cell, NeuroMLDocument, Segment, SegmentGroup
+from neuroml.neuro_lex_ids import neuro_lex_ids
 from pyneuroml.pynml import read_neuroml2_file
-from pyneuroml.utils.cli import build_namespace
 from pyneuroml.utils import extract_position_info
+from pyneuroml.utils.cli import build_namespace
 from pyneuroml.utils.plot import (
-    add_text_to_matplotlib_2D_plot,
-    get_next_hex_color,
+    DEFAULTS,
     add_box_to_matplotlib_2D_plot,
-    get_new_matplotlib_morph_plot,
-    autoscale_matplotlib_plot,
-    add_scalebar_to_matplotlib_plot,
     add_line_to_matplotlib_2D_plot,
-    DEFAULTS,
+    add_scalebar_to_matplotlib_plot,
+    add_text_to_matplotlib_2D_plot,
+    autoscale_matplotlib_plot,
+    get_new_matplotlib_morph_plot,
+    get_next_hex_color,
+    load_minimal_morphplottable__model,
 )
-from neuroml import SegmentGroup, Cell, Segment, NeuroMLDocument
-from neuroml.neuro_lex_ids import neuro_lex_ids
-
 
 logger = logging.getLogger(__name__)
 logger.setLevel(logging.INFO)
@@ -144,7 +142,7 @@ def plot_from_console(a: typing.Optional[typing.Any] = None, **kwargs: str):
     :param kwargs: other arguments
     """
     a = build_namespace(DEFAULTS, a, **kwargs)
-    print(a)
+    logger.debug(a)
     if a.interactive3d:
         from pyneuroml.plot.PlotMorphologyVispy import plot_interactive_3D
 
@@ -251,21 +249,27 @@ def plot_2D(
     if verbose:
         print("Plotting %s" % nml_file)
 
-    # do not recursive read the file, the extract_position_info function will
-    # do that for us, from a copy of the model
     if type(nml_file) is str:
-        nml_model = read_neuroml2_file(
-            nml_file,
-            include_includes=False,
-            check_validity_pre_include=False,
-            verbose=False,
-            optimized=True,
-        )
+        # load without optimization for older HDF5 API
+        # TODO: check if this is required: must for MultiscaleISN
+        if nml_file.endswith(".h5"):
+            nml_model = read_neuroml2_file(nml_file)
+        else:
+            nml_model = read_neuroml2_file(
+                nml_file,
+                include_includes=False,
+                check_validity_pre_include=False,
+                verbose=False,
+                optimized=True,
+            )
+            load_minimal_morphplottable__model(nml_model, nml_file)
+
         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)
@@ -290,9 +294,7 @@ def plot_2D(
         positions,
         pop_id_vs_color,
         pop_id_vs_radii,
-    ) = extract_position_info(
-        nml_model, verbose, nml_file if type(nml_file) is str else ""
-    )
+    ) = extract_position_info(nml_model, verbose)
 
     if verbose:
         logger.debug(f"positions: {positions}")