GH AllenInstitute#533 - Default to vm_delta_mv if autobias_v is None

If autobias_v is None for a given sweep, then default to previous method
of measuring delta between pre and post-stimulus baselines as vm_delta_mv.

ipfx/qc_feature_evaluator.py

@@ -169,10 +169,13 @@ def qc_current_clamp_sweep(sweep, is_ramp, qc_criteria=None):
         fail_tags.append("slow noise: %.3f above threshold: %.3f" % (sweep["slow_noise_rms_mv"], qc_criteria["slow_noise_rms_mv_max"]) )
 
     if sweep["pre_vm_delta_mv"] is not None and sweep["pre_vm_delta_mv"] > qc_criteria["vm_delta_mv_max"]:
-        fail_tags.append("pre Vm delta: %.3f above threshold:%.3f" % (sweep["pre_vm_delta_mv"], qc_criteria["vm_delta_mv_max"]))
+        fail_tags.append("pre Vm delta: %.3f above threshold: %.3f" % (sweep["pre_vm_delta_mv"], qc_criteria["vm_delta_mv_max"]))
 
     if sweep["post_vm_delta_mv"] is not None and sweep["post_vm_delta_mv"] > qc_criteria["vm_delta_mv_max"]:
-        fail_tags.append("post Vm delta: %.3f above threshold:%.3f" % (sweep["post_vm_delta_mv"], qc_criteria["vm_delta_mv_max"]))
+        fail_tags.append("post Vm delta: %.3f above threshold: %.3f" % (sweep["post_vm_delta_mv"], qc_criteria["vm_delta_mv_max"]))
+
+    if sweep["vm_delta_mv"] is not None and sweep["vm_delta_mv"] > qc_criteria["vm_delta_mv_max"]:
+        fail_tags.append("Vm delta: %.3f above threshold: %.3f" % (sweep["vm_delta_mv"], qc_criteria["vm_delta_mv_max"]))
 
     if fail_tags:
         logging.info("sweep: {}, {}, {}".format(sweep["sweep_number"], sweep["stimulus_name"], fail_tags))

ipfx/qc_feature_extractor.py

@@ -379,9 +379,14 @@ def current_clamp_sweep_qc_features(sweep, is_ramp):
     qc_features["pre_vm_mv"] = mean_first_stability_epoch
     qc_features["slow_vm_mv"] = mean_first_stability_epoch
     qc_features["slow_noise_rms_mv"] = rms_first_stability_epoch
-
-    qc_features["pre_vm_delta_mv"] = qcf.measure_vm_delta(mean_first_stability_epoch, autobias_v)
-    qc_features["post_vm_delta_mv"] = qcf.measure_vm_delta(mean_last_stability_epoch, autobias_v)
+    if autobias_v != None:
+        qc_features["pre_vm_delta_mv"] = qcf.measure_vm_delta(mean_first_stability_epoch, autobias_v)
+        qc_features["post_vm_delta_mv"] = qcf.measure_vm_delta(mean_last_stability_epoch, autobias_v)
+        qc_features["vm_delta_mv"] = None
+    else:
+        qc_features["vm_delta_mv"] = qcf.measure_vm_delta(mean_first_stability_epoch, mean_last_stability_epoch)
+        qc_features["pre_vm_delta_mv"] = None
+        qc_features["post_vm_delta_mv"] = None
 
     return qc_features
 

ipfx/qc_features.py

@@ -39,6 +39,22 @@ def measure_vm(vals):
 
 
 def measure_vm_delta(mean_baseline, target_v):
+    """Measure delta between mean baseline and autobias target voltage,
+       or if autobias is not available then measure delta between
+       pre and post stimulus baselines.
+    
+    
+    Parameters
+    ----------
+        mean_baseline : float mean baseline membrane voltage 
+        target_v : float autobias taget voltage or post-stimulus 
+                   mean baseline membrane voltage
+    
+    Returns
+    -------
+        delta: absolute voltage diff 
+    
+    """
 
     if mean_baseline is not None and target_v is not None:
         delta = abs(mean_baseline - target_v)