add settings for customisable plots

bluepyemodel/emodel_pipeline/emodel_pipeline.py

@@ -262,16 +262,16 @@ def plot(self, only_validated=False, load_from_local=False, seeds=None):
             mapper=self.mapper,
             seeds=seeds,
             figures_dir=pathlib.Path("./figures") / self.access_point.emodel_metadata.emodel,
-            plot_optimisation_progress=True,
+            plot_optimisation_progress=pp_settings.plot_optimisation_progress,
             optimiser=pp_settings.optimiser,
-            plot_parameter_evolution=True,
-            plot_distributions=True,
-            plot_scores=True,
-            plot_traces=True,
-            plot_thumbnail=True,
+            plot_parameter_evolution=pp_settings.plot_parameter_evolution,
+            plot_distributions=pp_settings.plot_distributions,
+            plot_scores=pp_settings.plot_scores,
+            plot_traces=pp_settings.plot_traces,
+            plot_thumbnail=pp_settings.plot_thumbnail,
             plot_currentscape=pp_settings.plot_currentscape,
-            plot_dendritic_ISI_CV=True,
-            plot_dendritic_rheobase=True,
+            plot_dendritic_ISI_CV=pp_settings.plot_dendritic_ISI_CV,
+            plot_dendritic_rheobase=pp_settings.plot_dendritic_rheobase,
             plot_bAP_EPSP=pp_settings.plot_bAP_EPSP,
             plot_IV_curve=pp_settings.plot_IV_curves,
             plot_FI_curve_comparison=pp_settings.plot_FI_curve_comparison,

bluepyemodel/emodel_pipeline/emodel_settings.py

@@ -18,7 +18,7 @@
 
 import logging
 
-# pylint: disable=too-many-arguments,too-many-locals,too-many-instance-attributes
+# pylint: disable=too-many-arguments,too-many-locals,too-many-instance-attributes, unused-argument
 # pylint: disable=too-many-statements
 
 logger = logging.getLogger(__name__)
@@ -60,7 +60,6 @@ def __init__(
         use_stagnation_criterion=True,
         validation_function="max_score",
         validation_threshold=5.0,
-        plot_optimisation=True,
         use_ProbAMPANMDA_EMS=False,
         compile_mechanisms=False,
         n_model=3,
@@ -71,8 +70,16 @@ def __init__(
         name_rmp_protocol=None,
         validation_protocols=None,
         name_gene_map=None,
-        plot_currentscape=True,
+        plot_optimisation=True,
+        plot_optimisation_progress=True,
         plot_parameter_evolution=True,
+        plot_distributions=True,
+        plot_scores=True,
+        plot_traces=True,
+        plot_thumbnail=True,
+        plot_currentscape=True,
+        plot_dendritic_ISI_CV=True,
+        plot_dendritic_rheobase=True,
         plot_bAP_EPSP=False,
         plot_IV_curves=False,
         plot_FI_curve_comparison=False,
@@ -235,8 +242,6 @@ def __init__(
                 Nexus access_point and the IC-selector.
             n_model (int): minimum number of models to pass validation to consider the e-model
                 building task done. Only used by the Luigi workflow.
-            plot_optimisation (bool): should the e-models scores and traces be plotted. Only used
-                by the Luigi workflow.
             use_ProbAMPANMDA_EMS (bool): True to link ProbAMPANMDA_EMS in EMC on nexus,
                 and download ProbAMPANMDA from nexus along with other mechanisms.
             compile_mechanisms (bool): should the mod files be copied in the local
@@ -260,10 +265,18 @@ def __init__(
             validation_protocols (list of str): name of the protocols to be used for validation
                 only. E.g. ``["APWaveform_300"]``. These protocols will not be used during
                 optimisation.
-            plot_currentscape (bool): during the plotting, should the currentscapes be
-                plotted for the recordings.
+            plot_optimisation (bool): legacy parameter, is not used anymore.
+            plot_optimisation_progress (bool): True to plot the optimisation progress
+                from checkpoint.
             plot_parameter_evolution (bool): during the plotting, should the evolution of the
                 parameters be plotted.
+            plot_distributions (bool): True to plot the parameters distributions.
+            plot_scores (bool): True to plot the scores
+            plot_traces (bool): True to plot the traces
+            plot_thumbnail (bool): True to plot a trace that can be used as thumbnail
+            plot_currentscape (bool): during the plotting, should the currentscapes be
+                plotted for the recordings.
+            plot_dendritic_rheobase (bool): True to plot dendritic rheobase (if present)
             plot_bAP_EPSP (bool): during the plotting, should ready-to-use back-propagating AP
                 and EPSP protocols be run and plotted.
                 Should be True only for pyramidal cells,
@@ -419,7 +432,13 @@ def __init__(
         self.name_gene_map = name_gene_map
 
         # Settings specific to the analysis (figure plotting)
-        self.plot_optimisation = plot_optimisation
+        self.plot_optimisation_progress = plot_optimisation_progress
+        self.plot_distributions = plot_distributions
+        self.plot_scores = plot_scores
+        self.plot_traces = plot_traces
+        self.plot_thumbnail = plot_thumbnail
+        self.plot_dendritic_ISI_CV = plot_dendritic_ISI_CV
+        self.plot_dendritic_rheobase = plot_dendritic_rheobase
         self.plot_currentscape = plot_currentscape
         self.currentscape_config = currentscape_config
         self.plot_parameter_evolution = plot_parameter_evolution

bluepyemodel/tasks/emodel_creation/optimisation.py

@@ -530,8 +530,11 @@ class Validation(WorkflowTaskRequiringMechanisms, IPyParallelTask):
     def requires(self):
         """ """
 
-        plot_optimisation = self.access_point.pipeline_settings.plot_optimisation
         compile_mechanisms = self.access_point.pipeline_settings.compile_mechanisms
+        plot_parameter_evolution = self.access_point.pipeline_settings.plot_parameter_evolution
+        plot_distributions = self.access_point.pipeline_settings.plot_distributions
+        plot_traces = self.access_point.pipeline_settings.plot_traces
+        plot_scores = self.access_point.pipeline_settings.plot_scores
 
         to_run = [
             StoreBestModels(
@@ -558,7 +561,7 @@ def requires(self):
                 )
             )
 
-        if plot_optimisation:
+        if any((plot_parameter_evolution, plot_distributions, plot_scores, plot_traces)):
             to_run.append(
                 PlotModels(
                     emodel=self.emodel,
@@ -1096,21 +1099,6 @@ def requires(self):
             )
         ]
 
-        plot_optimisation = self.access_point.pipeline_settings.plot_optimisation
-
-        if plot_optimisation:
-            to_run.append(
-                PlotValidatedDistributions(
-                    emodel=self.emodel,
-                    etype=self.etype,
-                    ttype=self.ttype,
-                    mtype=self.mtype,
-                    species=self.species,
-                    brain_region=self.brain_region,
-                    iteration_tag=self.iteration_tag,
-                )
-            )
-
         return to_run
 
 
@@ -1249,7 +1237,13 @@ def requires(self):
     def run(self):
         """ """
 
-        plot_optimisation = self.access_point.pipeline_settings.plot_optimisation
+        plot_parameter_evolution = self.access_point.pipeline_settings.plot_parameter_evolution
+        plot_distributions = self.access_point.pipeline_settings.plot_distributions
+        plot_traces = self.access_point.pipeline_settings.plot_traces
+        plot_scores = self.access_point.pipeline_settings.plot_scores
+        plot_thumbnail = self.access_point.pipeline_settings.plot_thumbnail
+        plot_dendritic_ISI_CV = self.access_point.pipeline_settings.plot_dendritic_ISI_CV
+        plot_dendritic_rheobase = self.access_point.pipeline_settings.plot_dendritic_rheobase
         plot_currentscape = self.access_point.pipeline_settings.plot_currentscape
         plot_bAP_EPSP = self.access_point.pipeline_settings.plot_bAP_EPSP
         plot_IV_curves = self.access_point.pipeline_settings.plot_IV_curves
@@ -1271,13 +1265,13 @@ def run(self):
             figures_dir=Path("./figures") / self.emodel,
             # False because already done in PlotOptimisation task
             plot_optimisation_progress=False,
-            plot_parameter_evolution=plot_optimisation,
-            plot_distributions=plot_optimisation,
-            plot_traces=plot_optimisation,
-            plot_scores=plot_optimisation,
-            plot_thumbnail=plot_optimisation,
-            plot_dendritic_ISI_CV=plot_optimisation,
-            plot_dendritic_rheobase=plot_optimisation,
+            plot_parameter_evolution=plot_parameter_evolution,
+            plot_distributions=plot_distributions,
+            plot_traces=plot_traces,
+            plot_scores=plot_scores,
+            plot_thumbnail=plot_thumbnail,
+            plot_dendritic_ISI_CV=plot_dendritic_ISI_CV,
+            plot_dendritic_rheobase=plot_dendritic_rheobase,
             plot_currentscape=plot_currentscape,
             plot_bAP_EPSP=plot_bAP_EPSP,
             plot_IV_curve=plot_IV_curves,
@@ -1299,30 +1293,36 @@ def output(self):
         """ """
 
         batch_size = self.access_point.pipeline_settings.optimisation_batch_size
-        plot_optimisation = self.access_point.pipeline_settings.plot_optimisation
+        plot_parameter_evolution = self.access_point.pipeline_settings.plot_parameter_evolution
+        plot_distributions = self.access_point.pipeline_settings.plot_distributions
+        plot_traces = self.access_point.pipeline_settings.plot_traces
+        plot_scores = self.access_point.pipeline_settings.plot_scores
 
         outputs = []
-        if plot_optimisation:
+        if plot_parameter_evolution:
             # parameter evolution
             for seed in range(self.seed, self.seed + batch_size):
                 fname = self.access_point.emodel_metadata.as_string(seed=seed)
                 fname += "__evo_parameter_density.pdf"
                 fpath = Path("./figures") / self.emodel / "parameter_evolution" / fname
                 outputs.append(luigi.LocalTarget(fpath))
 
+        if plot_distributions:
             # distribution
             fname = self.access_point.emodel_metadata.as_string()
             fname += "__parameters_distribution.pdf"
             fpath = Path("./figures") / self.emodel / "distributions" / "all" / fname
             outputs.append(luigi.LocalTarget(fpath))
 
+        if plot_scores:
             # scores
             for seed in range(self.seed, self.seed + batch_size):
                 fname = self.access_point.emodel_metadata.as_string(seed)
                 fname += "__scores.pdf"
                 fpath = Path("./figures") / self.emodel / "scores" / "all" / fname
                 outputs.append(luigi.LocalTarget(fpath))
 
+        if plot_traces:
             # traces
             for seed in range(self.seed, self.seed + batch_size):
                 fname = self.access_point.emodel_metadata.as_string(seed)