Merge pull request #172 from BlueBrain/fix-plotting

Fix plotting

.pylintrc

@@ -12,7 +12,8 @@
 #W0622 - redefined-builti
 #C0325 - superfluous-parens
 #R0205 - useless-object-inheritance
-disable=C0103,R0904,R0903,W0511,R0801,R0401,I0013,W0622,C0325,R0205,C0302,C0415,E1133,C0112,C0116,W0221,W1514,C0413,W0105
+#R0917 - too-many-positional-arguments
+disable=C0103,R0904,R0903,W0511,R0801,R0401,I0013,W0622,C0325,R0205,C0302,C0415,E1133,C0112,C0116,W0221,W1514,C0413,W0105,R0917
 
 [FORMAT]
 # Maximum number of characters on a single line.

bluepyemodel/emodel_pipeline/emodel_pipeline.py

@@ -245,7 +245,7 @@ def validation(self, preselect_for_validation=False):
             preselect_for_validation=preselect_for_validation,
         )
 
-    def plot(self, only_validated=False, load_from_local=False):
+    def plot(self, only_validated=False, load_from_local=False, seeds=None):
         """Plot the results of the optimisation in a subfolder called "figures".
 
         Args:
@@ -254,6 +254,7 @@ def plot(self, only_validated=False, load_from_local=False):
             load_from_local (bool): if True, loads responses of the e-models from local files
                 instead of recomputing them. Responses are automatically saved locally when
                 plotting currentscapes.
+            seeds (list): list of seeds to use for plot. If None, all emodels will be plotted.
         """
         pp_settings = self.access_point.pipeline_settings
 
@@ -306,7 +307,7 @@ def plot(self, only_validated=False, load_from_local=False):
         return plotting.plot_models(
             access_point=self.access_point,
             mapper=self.mapper,
-            seeds=None,
+            seeds=seeds,
             figures_dir=pathlib.Path("./figures") / self.access_point.emodel_metadata.emodel,
             plot_distributions=True,
             plot_scores=True,

bluepyemodel/emodel_pipeline/plotting.py

@@ -861,11 +861,12 @@ def plot_bAP(
     apical_distances, apical_values = apical_feature.get_distances_feature_values(responses)
     basal_distances, basal_values = basal_feature.get_distances_feature_values(responses)
 
-    if 0 in apical_distances:
-        apical_x_fit, apical_y_fit = bAP_fit(apical_feature, apical_distances, apical_values)
-    if 0 in basal_distances:
-        basal_x_fit, basal_y_fit = bAP_fit(basal_feature, basal_distances, basal_values)
-
+    if apical_values is None or basal_values is None:
+        logger.warning(
+            "Cannot plot figure for bAP because dendrite feature could not be computed. "
+            "This can happen when the emodel is bad and cannot even compute curent threshold."
+        )
+        return fig, ax
     if len(apical_distances) != len(apical_values) or len(basal_distances) != len(basal_values):
         logger.warning(
             "Cannot plot figure for bAP because of mismatch between "
@@ -874,6 +875,11 @@ def plot_bAP(
         )
         return fig, ax
 
+    if 0 in apical_distances:
+        apical_x_fit, apical_y_fit = bAP_fit(apical_feature, apical_distances, apical_values)
+    if 0 in basal_distances:
+        basal_x_fit, basal_y_fit = bAP_fit(basal_feature, basal_distances, basal_values)
+
     ax.scatter(
         apical_distances,
         apical_values,
@@ -1667,6 +1673,18 @@ def plot_sinespec(
     current_key = f"{prot_name}.iclamp.i"
     voltage_key = f"{prot_name}.soma.v"
 
+    fig, axs = plt.subplots(3, figsize=(6, 12))
+
+    if voltage_key not in responses or current_key not in responses:
+        logger.warning(
+            "Could not find sinespec responses %s for emodel with seed %s. "
+            "This is most probably due to a bad model unable to compute threshold. "
+            "Skipping Sinespec plot.",
+            model.emodel_metadata.emodel,
+            model.seed,
+        )
+        return fig, axs
+
     freq, smooth_Z = get_impedance(
         responses[voltage_key]["time"],
         responses[voltage_key]["voltage"],
@@ -1676,9 +1694,8 @@ def plot_sinespec(
         efel_settings,
     )
     if freq is None or smooth_Z is None:
-        return None, None
+        return fig, axs
 
-    fig, axs = plt.subplots(3, figsize=(6, 12))
     # current trace
     axs[0].plot(responses[current_key]["time"], responses[current_key]["voltage"])
     axs[0].set_xlabel("Time (ms)")

bluepyemodel/emodel_pipeline/plotting_utils.py

@@ -385,14 +385,22 @@ def get_simulated_FI_curve_for_plotting(evaluator, responses, prot_name):
             protocol_name = get_protocol_name(val)
             amp_temp = float(protocol_name.split("_")[-1])
             if "mean_frequency" in val:
-                simulated_freq.append(values[val])
+                mean_freq = values[val]
+                # Expects a one-sized array or None.
+                # If list is a mix of arrays and Nones, matplotlib will raise an error when trying
+                # to turn the list into a numpy array.
+                # -> turn one-sized array into number
+                mean_freq = mean_freq[0] if mean_freq is not None else None
+                simulated_freq.append(mean_freq)
                 if "bpo_threshold_current" in responses:
                     simulated_amp_rel.append(amp_temp)
                     simulated_amp.append(rel_to_abs_amplitude(amp_temp, responses))
                 else:
                     simulated_amp_rel.append(numpy.nan)
                     simulated_amp.append(amp_temp)
 
+    # turn Nones into NaNs
+    simulated_freq = numpy.asarray(simulated_freq, dtype=float)
     return simulated_amp_rel, simulated_amp, simulated_freq
 
 
@@ -514,6 +522,8 @@ def get_sinespec_evaluator(evaluator, sinespec_settings, efel_settings):
             FixedDtRecordingCustom(f"{prot_name}.soma.v", location=soma_loc, variable="v"),
             FixedDtRecordingStimulus(f"{prot_name}.iclamp.i", location=None, variable="i"),
         ],
+        # with constant Vm change, cvode would actually take longer to compute than fixed dt
+        cvode_active=False,
     )
     new_prots[prot_name] = sinespec_prot
 

bluepyemodel/model/model.py

@@ -56,11 +56,27 @@ def multi_locations(section_name, additional_multiloc_map):
     if additional_multiloc_map is not None:
         multiloc_map.update(additional_multiloc_map)
 
-    return [
+    seclist_locations = [
         ephys.locations.NrnSeclistLocation(sec, seclist_name=sec)
         for sec in multiloc_map.get(section_name, [section_name])
     ]
 
+    for sec_loc in seclist_locations:
+        # all and myelinated are also accepted
+        if (
+            sec_loc.seclist_name not in multiloc_map["allact"]
+            and sec_loc.seclist_name != "all"
+            and sec_loc.seclist_name != "myelinated"
+        ):
+            logger.warning(
+                "Section location %s not in expected locations %s. "
+                "This might make the cell crash at run time.",
+                sec_loc.seclist_name,
+                multiloc_map["allact"],
+            )
+
+    return seclist_locations
+
 
 def define_distributions(distributions_definition, morphology=None):
     """Create a list of ParameterScaler from a the definition of channel distributions

bluepyemodel/tasks/luigi_tools.py

@@ -63,7 +63,7 @@ def __init__(self, *args, **kwargs):
             species=self.species,
             brain_region=self.brain_region,
             iteration_tag=self.iteration_tag,
-            **EmodelAPIConfig().api_args
+            **EmodelAPIConfig().api_args,
         )
 
     def get_mapper(self):
@@ -112,7 +112,7 @@ def __init__(
             species=species,
             brain_region=brain_region,
             iteration_tag=iteration_tag,
-            **EmodelAPIConfig().api_args
+            **EmodelAPIConfig().api_args,
         )
 
 

pyproject.toml

@@ -0,0 +1,94 @@
+[build-system]
+requires = ["setuptools >= 64", "setuptools_scm"]
+build-backend = "setuptools.build_meta"
+
+[project]
+name = "bluepyemodel"
+authors = [
+    {name = "Blue Brain Project, EPFL"},
+]
+description="Blue Brain Python Electrical Modeling Pipeline"
+readme = "README.rst"
+license = {file = "LICENSE.txt"}
+requires-python = ">= 3.9"
+dynamic = ["version"]
+dependencies = [
+    "numpy",
+    "scipy",
+    "pandas",
+    "ipyparallel>=6.3",
+    "tqdm",
+    "pyyaml",
+    "gitpython",
+    "bluepyopt>=1.14.10",
+    "bluepyefe>=2.2.0",
+    "neurom>=3.0",
+    "efel>=5.5.5",
+    "configparser",
+    "neuron>=8.0",
+    "morph_tool>=2.8",
+    "morphio",
+    "fasteners>=0.16",
+    "jinja2>=3.0.3",
+    "currentscape>=0.0.11",
+]
+keywords=[
+    "computational neuroscience",
+    "simulation",
+    "analysis",
+    "parameters",
+    "Blue Brain Project",
+]
+classifiers=[
+    "Development Status :: 5 - Production/Stable",
+    "Environment :: Console",
+    "License :: OSI Approved :: Apache Software License",
+    "Operating System :: POSIX",
+    "Topic :: Scientific/Engineering",
+    "Programming Language :: Python :: 3",
+    "Topic :: Utilities",
+]
+
+[project.optional-dependencies]
+luigi = [
+    "luigi>=3.0",
+    "luigi-tools>=0.0.12",
+]
+docs = [
+    "graphviz",
+    "sphinx",
+    "sphinx-bluebrain-theme",
+    "luigi>=3.0",
+    "luigi-tools>=0.0.12",
+]
+test = [
+    "pytest>=6.2",
+    "dictdiffer>=0.8",
+]
+nexus = [
+    "nexusforge>=0.8.2",
+    "entity_management>=1.2",
+    "pyJWT>=2.1.0",
+]
+all = [
+    "luigi>=3.0",
+    "luigi-tools>=0.0.12",
+    "nexusforge>=0.8.2",
+    "entity_management>=1.2",
+    "pyJWT>=2.1.0",
+    "pytest>=6.2",
+    "dictdiffer>=0.8",
+]
+
+[project.urls]
+Homepage = "https://github.com/BlueBrain/BluePyEModel"
+
+[tool.setuptools]
+include-package-data = true
+
+[tool.setuptools.packages.find]
+exclude = ["tests",]
+
+[tool.setuptools_scm]
+version_scheme = "python-simplified-semver"
+local_scheme = "no-local-version"