thumbnail plotting in validation (#27)

Author: AurelienJaquier

bluecellulab/analysis/analysis.py

@@ -350,7 +350,6 @@ def validate(self, soma_amp, dend_amps, dend_dist, apic_amps, apic_dist):
         validated = True
         notes = ""
         popt_dend, popt_apic = self.fit(soma_amp, dend_amps, dend_dist, apic_amps, apic_dist)
-        logging.warning(popt_dend)
         if dend_amps is not None:
             plt.cla()
             plt.plot([0], soma_amp, '.')

bluecellulab/validation/validation.py

@@ -25,6 +25,7 @@
 from bluecellulab.analysis.inject_sequence import run_multirecordings_stimulus
 from bluecellulab.analysis.inject_sequence import run_stimulus
 from bluecellulab.cell.core import Cell
+from bluecellulab.simulation.neuron_globals import NeuronGlobals
 from bluecellulab.stimulus.factory import IDRestTimings
 from bluecellulab.stimulus.factory import StimulusFactory
 from bluecellulab.tools import calculate_input_resistance
@@ -33,15 +34,17 @@
 logger = logging.getLogger(__name__)
 
 
-def plot_trace(recording, out_dir, fname, title):
+def plot_trace(recording, out_dir, fname, title, plot_current=True):
     """Plot a trace with inout current given a recording."""
     outpath = out_dir / fname
     fig, ax1 = plt.subplots(figsize=(10, 6))
     plt.plot(recording.time, recording.voltage, color="black")
-    current_axis = ax1.twinx()
-    current_axis.plot(recording.time, recording.current, color="gray", alpha=0.6)
-    current_axis.set_ylabel("Stimulus Current [nA]")
-    fig.suptitle(title)
+    if plot_current:
+        current_axis = ax1.twinx()
+        current_axis.plot(recording.time, recording.current, color="gray", alpha=0.6)
+        current_axis.set_ylabel("Stimulus Current [nA]")
+    if title:
+        fig.suptitle(title)
     ax1.set_xlabel("Time [ms]")
     ax1.set_ylabel("Voltage [mV]")
     fig.tight_layout()
@@ -410,20 +413,61 @@ def fi_test(template_params, rheobase, out_dir, spike_threshold_voltage=-30.):
     }
 
 
+def thumbnail_test(template_params, rheobase, out_dir):
+    """Thumbnail test: creating a thumbnail."""
+    stim_factory = StimulusFactory(dt=1.0)
+    step_stimulus = stim_factory.idrest(threshold_current=rheobase, threshold_percentage=130)
+    recording = run_stimulus(
+        template_params,
+        step_stimulus,
+        "soma[0]",
+        0.5,
+        add_hypamp=True,
+    )
+
+    # plotting
+    outpath = plot_trace(
+        recording,
+        out_dir,
+        fname="thumbnail.pdf",
+        title="",
+        plot_current=False
+    )
+
+    return {
+        "name": "thumbnail",
+        "passed": True,
+        "validation_details": "",
+        "figures": [outpath],
+    }
+
+
 def run_validations(
-    cell, cell_name, spike_threshold_voltage=-30, output_dir="./memodel_validation_figures"
+    cell,
+    cell_name,
+    spike_threshold_voltage=-30,
+    v_init=-80.0,
+    celsius=34.0,
+    output_dir="./memodel_validation_figures"
 ):
     """Run all the validations on the cell.
 
     Args:
         cell (Cell): The cell to validate.
         cell_name (str): The name of the cell, used in the output directory.
         spike_threshold_voltage (float): The voltage threshold for spike detection.
+        v_init: Initial membrane potential. Default is -80.0 mV.
+        celsius: Temperature in Celsius. Default is 34.0.
         output_dir (str): The directory to save the validation figures.
     """
     out_dir = pathlib.Path(output_dir) / cell_name
     out_dir.mkdir(parents=True, exist_ok=True)
 
+    # set initial voltage and temperature
+    neuron_globals = NeuronGlobals.get_instance()
+    neuron_globals.temperature = celsius
+    neuron_globals.v_init = v_init
+
     # get me-model properties
     holding_current = cell.hypamp if cell.hypamp else 0.0
     if cell.threshold:
@@ -473,6 +517,9 @@ def run_validations(
     # Validation 9: FI Test
     fi_test_result = fi_test(cell.template_params, rheobase, out_dir, spike_threshold_voltage)
 
+    # Validation 10: Thumbnail Test
+    thumbnail_result = thumbnail_test(cell.template_params, rheobase, out_dir)
+
     return {
         "memodel_properties": {
             "holding_current": holding_current,
@@ -487,4 +534,5 @@ def run_validations(
         "rin_test": rin_result,
         "iv_test": iv_test_result,
         "fi_test": fi_test_result,
+        "thumbnail_test": thumbnail_result,
     }

tests/test_validation/test_validation.py

@@ -406,6 +406,24 @@ def test_fi_test(mock_Cell, mock_compute, dummy_template_params, dummy_out_dir):
     )
 
 
+@patch("bluecellulab.validation.validation.plot_trace")
+@patch("bluecellulab.validation.validation.run_stimulus")
+def test_thumnail_test(
+    mock_run_stimulus, mock_plot_trace, dummy_template_params, dummy_out_dir
+):
+    # passed case
+    rec = MagicMock()
+    rec.spike = [1]
+    mock_run_stimulus.return_value = rec
+    mock_plot_trace.return_value = dummy_out_dir / "thumbnail.pdf"
+    result = validation.thumbnail_test(dummy_template_params, 1.0, dummy_out_dir)
+    assert result["passed"] is True
+    assert len(result["figures"]) == 1
+    assert result["figures"][0] == dummy_out_dir / "thumbnail.pdf"
+    assert result["validation_details"] == ""
+    assert result["name"] == "thumbnail"
+
+
 @patch("bluecellulab.validation.validation.calculate_rheobase")
 @patch("bluecellulab.validation.validation.calculate_input_resistance")
 @patch("bluecellulab.validation.validation.spiking_test")
@@ -416,7 +434,9 @@ def test_fi_test(mock_Cell, mock_compute, dummy_template_params, dummy_out_dir):
 @patch("bluecellulab.validation.validation.rin_test")
 @patch("bluecellulab.validation.validation.iv_test")
 @patch("bluecellulab.validation.validation.fi_test")
+@patch("bluecellulab.validation.validation.thumbnail_test")
 def test_run_validations(
+    mock_thumbnail,
     mock_fi,
     mock_iv,
     mock_rin,
@@ -447,6 +467,7 @@ def test_run_validations(
     mock_rin.return_value = {"passed": True}
     mock_iv.return_value = {"passed": True}
     mock_fi.return_value = {"passed": True}
+    mock_thumbnail.return_value = {"passed": True}
     result = validation.run_validations(cell, "cellname")
     assert result["spiking_test"]["passed"] is True
     assert result["depolarization_block_test"]["passed"] is True