Merge pull request #105 from BlueBrain/images-readme

use raw version of image in readme to make it fetchable in PyPi

README.rst

@@ -274,7 +274,7 @@ Copyright (c) 2020-2022 Blue Brain Project/EPFL
                 :target: https://pypi.org/project/EModelRunner/
                 :alt: Latest Release
 
-.. |GUI_screenshot| image:: doc/source/images/GUI_screenshot.png
+.. |GUI_screenshot| image:: https://raw.githubusercontent.com/BlueBrain/EModelRunner/main/doc/source/images/GUI_screenshot.png
 
 .. |banner| image:: https://raw.githubusercontent.com/BlueBrain/EModelRunner/main/doc/source/logo/BBP-eModelRunner.jpg
 

doc/source/conf.py

@@ -74,6 +74,10 @@
 # to be able to put multiple return variables in the docstrings
 # napoleon_custom_sections = [("Returns", "params_style")]
 
+suppress_warnings = [
+    'autosummary.import_cycle',
+]
+
 
 # -- Options for HTML output -------------------------------------------------
 

emodelrunner/create_hoc_tools.py

@@ -227,8 +227,7 @@ def get_step_hoc(self, prot):
         if isinstance(step_definitions, dict):
             step_definitions = [step_definitions]
         for i, step in enumerate(step_definitions):
-            if i + 1 > self.max_steps:
-                self.max_steps = i + 1
+            self.max_steps = max(self.max_steps, i + 1)
 
             if step["amp"] is None:
                 amp = f"{step['thresh_perc'] / 100.} * threshold_current"

emodelrunner/factsheets/ion_channel_mechanisms.py

@@ -85,22 +85,26 @@ def get_channel_and_equations(
     elif len(split_name) == 2:
         biophys = split_name[0]
         channel = split_name[1]
+    else:
+        raise ValueError(
+            f"Could not extract channel and parameter name from name {name}"
+        )
 
     # type
     if "dist" in param_config:
-        if param_config["dist"] == "exp":
-            type_ = "exponential"
-            value = exp_fun.format(distance="x", value=value)
-            latex, plot = edit_dist_func(value)
-        elif param_config["dist"] == "decay":
+        if param_config["dist"] == "decay":
             type_ = "decay"
             value = decay_fun.format(distance="x", value=value, constant=decay_cst)
             latex, plot = edit_dist_func(value)
         else:
-            logger.warning(
-                "dist is set to %s. Expected 'exp' or 'decay'. Set type to exponential anyway.",
-                param_config["dist"],
-            )
+            type_ = "exponential"
+            value = exp_fun.format(distance="x", value=value)
+            latex, plot = edit_dist_func(value)
+            if param_config["dist"] != "exp":
+                logger.warning(
+                    "dist is set to %s. Expected 'exp' or 'decay'. Set type to exponential anyway.",
+                    param_config["dist"],
+                )
     else:
         type_ = "uniform"
         latex = value

emodelrunner/protocols/thalamus_protocols.py

@@ -311,7 +311,6 @@ def run(self, cell_model, param_values, sim, rmp=None):
             rin_noholding = self.rin_efeature_dep.calculate_feature(
                 rin_noholding_response
             )
-
         elif self.name.endswith("_hyp"):
             rin_noholding_protocol = self.create_rin_protocol_hyp(holdi=0)
             rin_noholding_response = rin_noholding_protocol.run(
@@ -320,6 +319,8 @@ def run(self, cell_model, param_values, sim, rmp=None):
             rin_noholding = self.rin_efeature_hyp.calculate_feature(
                 rin_noholding_response
             )
+        else:
+            raise ValueError("Rin protocol should end with either '_dep' or '_hyp'.")
 
         logger.info("Rin without holdi is %s", rin_noholding)
 
@@ -512,6 +513,10 @@ def voltage_base(self, current, cell_model, param_values, sim=None):
             )
 
             voltage_base = feature.calculate_feature(response)
+
+        else:
+            raise ValueError("Rin protocol should end with either '_dep' or '_hyp'.")
+
         return voltage_base
 
     def generate_current(self, threshold_current=None, holding_current=None, dt=0.1):
@@ -709,6 +714,10 @@ def detect_spike(
                 exp_mean=1,
                 exp_std=0.1,
             )
+        else:
+            raise ValueError(
+                "Threshold detection protocol should end with either '_dep' or '_hyp'."
+            )
 
         spike_count = feature.calculate_feature(response)
         logger.debug("%s spikes with I = %s", spike_count, step_current)

emodelrunner/run.py

@@ -39,7 +39,7 @@ def main(config_path):
         config_path (str): path to config file
             The config file should have '.ini' suffix
     """
-    # pylint: disable=too-many-locals
+    # pylint: disable=too-many-locals, possibly-used-before-assignment
     config = load_config(config_path=config_path)
 
     cell = create_cell_using_config(config)

emodelrunner/synapses/mechanism.py

@@ -105,6 +105,11 @@ def get_cell_section_for_synapse(synapse, icell):
             section = icell.apic[synapse["sectionlist_index"]]
         elif synapse["sectionlist_id"] == 3:
             section = icell.axon[synapse["sectionlist_index"]]
+        else:
+            raise ValueError(
+                f"Unrecognized sectionlist_id: {synapse['sectionlist_id']}. "
+                "Should be 0, 1,, 2 or 3."
+            )
 
         return section
 

tests/unit_tests/data/hippocampus_morphometrics.json

@@ -33,7 +33,7 @@
         },
         {
             "name": "average diameter, all",
-            "value": 0.539696595209174,
+            "value": 0.5396965962874053,
             "unit": "\u00b5m"
         },
         {
@@ -93,7 +93,7 @@
         },
         {
             "name": "average diameter, axon",
-            "value": 0.39878087863997674,
+            "value": 0.3987808603270087,
             "unit": "\u00b5m"
         },
         {
@@ -153,7 +153,7 @@
         },
         {
             "name": "average diameter, apical",
-            "value": 0.922797184065503,
+            "value": 0.9227971437728758,
             "unit": "\u00b5m"
         },
         {
@@ -213,7 +213,7 @@
         },
         {
             "name": "average diameter, basal",
-            "value": 0.678468805386857,
+            "value": 0.6784688144013714,
             "unit": "\u00b5m"
         },
         {

tests/unit_tests/test_morphology_features.py

@@ -78,7 +78,7 @@ def test_thalamus_morphology_factsheet_builder():
 
 def test_average_diameter():
     """Test average diameter feature."""
-    morphology = nm.load_neuron(test_morph)
+    morphology = nm.load_morphology(test_morph)
     feature = morphology_features.AverageDiameter(
         morphology, "basal_dendrite", NeuriteType.basal_dendrite
     )
@@ -90,7 +90,7 @@ def test_average_diameter():
 
 def test_total_length():
     """Test total length morphology feature."""
-    morphology = nm.load_neuron(test_morph)
+    morphology = nm.load_morphology(test_morph)
     feature = morphology_features.TotalLength(morphology, "axon", NeuriteType.axon)
     feature_dict = feature.to_dict()
     assert feature_dict["name"] == "total length, axon"
@@ -100,7 +100,7 @@ def test_total_length():
 
 def test_total_height():
     """Test total height feature."""
-    morphology = nm.load_neuron(test_morph)
+    morphology = nm.load_morphology(test_morph)
     feature = morphology_features.TotalHeight(morphology, "axon", NeuriteType.axon)
     feature_dict = feature.to_dict()
     assert feature_dict["name"] == "total height, axon"
@@ -110,7 +110,7 @@ def test_total_height():
 
 def test_total_width():
     """Test total width feature."""
-    morphology = nm.load_neuron(test_morph)
+    morphology = nm.load_morphology(test_morph)
     feature = morphology_features.TotalWidth(morphology, "axon", NeuriteType.axon)
     feature_dict = feature.to_dict()
     assert feature_dict["name"] == "total width, axon"
@@ -120,7 +120,7 @@ def test_total_width():
 
 def test_total_depth():
     """Test total depth feature."""
-    morphology = nm.load_neuron(test_morph)
+    morphology = nm.load_morphology(test_morph)
     feature = morphology_features.TotalDepth(morphology, "axon", NeuriteType.axon)
     feature_dict = feature.to_dict()
     assert feature_dict["name"] == "total depth, axon"
@@ -130,7 +130,7 @@ def test_total_depth():
 
 def test_total_area():
     """Test the total area feature."""
-    morphology = nm.load_neuron(test_morph)
+    morphology = nm.load_morphology(test_morph)
     feature = morphology_features.TotalArea(morphology, "axon", NeuriteType.axon)
     feature_dict = feature.to_dict()
     assert feature_dict["name"] == "total area, axon"
@@ -140,7 +140,7 @@ def test_total_area():
 
 def test_total_volume():
     """Test the total volume feature."""
-    morphology = nm.load_neuron(test_morph)
+    morphology = nm.load_morphology(test_morph)
     feature = morphology_features.TotalVolume(morphology, "axon", NeuriteType.axon)
     feature_dict = feature.to_dict()
     assert feature_dict["name"] == "total volume, axon"
@@ -150,7 +150,7 @@ def test_total_volume():
 
 def test_number_of_sections():
     """Test number of sections feature."""
-    morphology = nm.load_neuron(test_morph)
+    morphology = nm.load_morphology(test_morph)
     feature = morphology_features.NumberOfSections(
         morphology, "basal_dendrite", NeuriteType.basal_dendrite
     )
@@ -162,7 +162,7 @@ def test_number_of_sections():
 
 def test_mean_neurite_volumes():
     """Test neurite volumes feature."""
-    morphology = nm.load_neuron(test_morph)
+    morphology = nm.load_morphology(test_morph)
     feature = morphology_features.MeanNeuriteVolumes(
         morphology, "axon", NeuriteType.axon
     )
@@ -174,7 +174,7 @@ def test_mean_neurite_volumes():
 
 def test_max_branch_order():
     """Test max branch order feature."""
-    morphology = nm.load_neuron(test_morph)
+    morphology = nm.load_morphology(test_morph)
     feature = morphology_features.MaxBranchOrder(
         morphology, "apical_dendrite", NeuriteType.apical_dendrite
     )
@@ -186,7 +186,7 @@ def test_max_branch_order():
 
 def test_max_section_length():
     """Test max section length feature."""
-    morphology = nm.load_neuron(test_morph)
+    morphology = nm.load_morphology(test_morph)
     feature = morphology_features.MaxSectionLength(
         morphology, "basal_dendrite", NeuriteType.basal_dendrite
     )
@@ -198,7 +198,7 @@ def test_max_section_length():
 
 def test_soma_diameter():
     """Test the some diameter feature."""
-    morphology = nm.load_neuron(test_morph)
+    morphology = nm.load_morphology(test_morph)
     feature = morphology_features.SomaDiamater(morphology)
     feature_dict = feature.to_dict()
     assert feature_dict["name"] == "soma diameter"
@@ -208,7 +208,7 @@ def test_soma_diameter():
 
 def test_soma_surface_area():
     """Test the soma surface area feature."""
-    morphology = nm.load_neuron(test_morph)
+    morphology = nm.load_morphology(test_morph)
     feature = morphology_features.SomaSurfaceArea(morphology)
     feature_dict = feature.to_dict()
     assert feature_dict["name"] == "soma surface area"
@@ -218,7 +218,7 @@ def test_soma_surface_area():
 
 def test_soma_volume():
     """Test the soma volume feature."""
-    morphology = nm.load_neuron(test_morph)
+    morphology = nm.load_morphology(test_morph)
     feature = morphology_features.SomaVolume(morphology)
     feature_dict = feature.to_dict()
     assert feature_dict["name"] == "soma volume"