Metric or Physio returning optimization

phys2denoise/metrics/cardiac.py

@@ -17,7 +17,7 @@ def _cardiac_metrics(
     peaks=None,
     window=6,
     central_measure="mean",
-    return_physio=False,
+    **kwargs,
 ):
     """
     Compute cardiac metrics.
@@ -154,7 +154,7 @@ def _cardiac_metrics(
 @due.dcite(references.CHANG_CUNNINGHAM_GLOVER_2009)
 @return_physio_or_metric()
 @physio.make_operation()
-def heart_rate(data, fs=None, peaks=None, window=6, central_measure="mean"):
+def heart_rate(data, fs=None, peaks=None, window=6, central_measure="mean", **kwargs):
     """
     Compute average heart rate (HR) in a sliding window.
 
@@ -213,6 +213,7 @@ def heart_rate(data, fs=None, peaks=None, window=6, central_measure="mean"):
         peaks=peaks,
         window=window,
         central_measure=central_measure,
+        **kwargs,
     )
 
     return data, hr
@@ -221,7 +222,9 @@ def heart_rate(data, fs=None, peaks=None, window=6, central_measure="mean"):
 @due.dcite(references.PINHERO_ET_AL_2016)
 @return_physio_or_metric()
 @physio.make_operation()
-def heart_rate_variability(data, fs=None, peaks=None, window=6, central_measure="mean"):
+def heart_rate_variability(
+    data, fs=None, peaks=None, window=6, central_measure="mean", **kwargs
+):
     """
     Compute average heart rate variability (HRV) in a sliding window.
 
@@ -278,6 +281,7 @@ def heart_rate_variability(data, fs=None, peaks=None, window=6, central_measure=
         peaks=peaks,
         window=window,
         central_measure=central_measure,
+        **kwargs,
     )
 
     return data, hrv
@@ -286,7 +290,9 @@ def heart_rate_variability(data, fs=None, peaks=None, window=6, central_measure=
 @due.dcite(references.CHEN_2020)
 @return_physio_or_metric()
 @physio.make_operation()
-def heart_beat_interval(data, fs=None, peaks=None, window=6, central_measure="mean"):
+def heart_beat_interval(
+    data, fs=None, peaks=None, window=6, central_measure="mean", **kwargs
+):
     """
     Compute average heart beat interval (HBI) in a sliding window.
 
@@ -336,14 +342,15 @@ def heart_beat_interval(data, fs=None, peaks=None, window=6, central_measure="me
         peaks=peaks,
         window=window,
         central_measure=central_measure,
+        **kwargs,
     )
 
     return data, hbi
 
 
 @return_physio_or_metric()
 @physio.make_operation()
-def cardiac_phase(data, slice_timings, n_scans, t_r, fs=None, peaks=None):
+def cardiac_phase(data, slice_timings, n_scans, t_r, fs=None, peaks=None, **kwargs):
     """Calculate cardiac phase from cardiac peaks.
 
     Assumes that timing of cardiac events are given in same units

phys2denoise/metrics/chest_belt.py

@@ -16,7 +16,7 @@
 @return_physio_or_metric()
 @physio.make_operation()
 def respiratory_variance_time(
-    data, fs=None, peaks=None, troughs=None, lags=(0, 4, 8, 12)
+    data, fs=None, peaks=None, troughs=None, lags=(0, 4, 8, 12), **kwargs
 ):
     """
     Implement the Respiratory Variance over Time (Birn et al. 2006).
@@ -113,7 +113,7 @@ def respiratory_variance_time(
 @due.dcite(references.POWER_2018)
 @return_physio_or_metric()
 @physio.make_operation()
-def respiratory_pattern_variability(data, window):
+def respiratory_pattern_variability(data, window, **kwargs):
     """Calculate respiratory pattern variability.
 
     Parameters
@@ -161,7 +161,7 @@ def respiratory_pattern_variability(data, window):
 @due.dcite(references.POWER_2020)
 @return_physio_or_metric()
 @physio.make_operation()
-def env(data, fs=None, window=10):
+def env(data, fs=None, window=10, **kwargs):
     """Calculate respiratory pattern variability across a sliding window.
 
     Parameters
@@ -245,7 +245,7 @@ def _respiratory_pattern_variability(data, window):
 @due.dcite(references.CHANG_GLOVER_2009)
 @return_physio_or_metric()
 @physio.make_operation()
-def respiratory_variance(data, fs=None, window=6):
+def respiratory_variance(data, fs=None, window=6, **kwargs):
     """Calculate respiratory variance.
 
     Parameters
@@ -310,7 +310,7 @@ def respiratory_variance(data, fs=None, window=6):
 
 @return_physio_or_metric()
 @physio.make_operation()
-def respiratory_phase(data, n_scans, slice_timings, t_r, fs=None):
+def respiratory_phase(data, n_scans, slice_timings, t_r, fs=None, **kwargs):
     """Calculate respiratory phase from respiratory signal.
 
     Parameters

phys2denoise/metrics/multimodal.py

@@ -20,6 +20,7 @@ def retroicor(
     physio_type=None,
     fs=None,
     cardiac_peaks=None,
+    **kwargs,
 ):
     """Compute RETROICOR regressors.
 

phys2denoise/metrics/utils.py

@@ -360,8 +360,9 @@ def wrapper(*args, **kwargs):
                 physio._computed_metrics[func.__name__] = dict(
                     metric=metric, args=kwargs
                 )
-                if return_physio:
-                    return physio, metric
+                return_physio_value = kwargs.get("return_physio", return_physio)
+                if return_physio_value:
+                    return physio
                 else:
                     return metric
             else:

phys2denoise/tests/test_metrics_cardiac.py

@@ -50,12 +50,28 @@ def test_cardiac_phase_smoke_physio_obj():
     data = np.zeros(peaks.shape)
     phys = physio.Physio(data, sample_rate, physio_type="cardiac")
     phys._metadata["peaks"] = peaks
-    phys, card_phase = cardiac.cardiac_phase(
+
+    # Test where the physio object is returned
+    phys = cardiac.cardiac_phase(
         phys,
         slice_timings=slice_timings,
         n_scans=n_scans,
         t_r=t_r,
     )
     assert phys.history[0][0] == "phys2denoise.metrics.cardiac.cardiac_phase"
+    assert phys.computed_metrics["cardiac_phase"]["metric"].ndim == 2
+    assert phys.computed_metrics["cardiac_phase"]["metric"].shape == (
+        n_scans,
+        slice_timings.size,
+    )
+
+    # Test where the metric is returned
+    card_phase = cardiac.cardiac_phase(
+        phys,
+        slice_timings=slice_timings,
+        n_scans=n_scans,
+        t_r=t_r,
+        return_physio=False,
+    )
     assert card_phase.ndim == 2
     assert card_phase.shape == (n_scans, slice_timings.size)