entropy_sample: return phi in info dict

neuropsychology · Aug 31, 2023 · a12ce58 · a12ce58
1 parent 1570a10
commit a12ce58
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Showing 3 changed files with 13 additions and 12 deletions.
diff --git a/neurokit2/complexity/entropy_multiscale.py b/neurokit2/complexity/entropy_multiscale.py
@@ -391,13 +391,14 @@ def _entropy_multiscale(
     # Get coarse-grained signal
     coarse = complexity_coarsegraining(signal, scale=scale, method=coarsegraining)
 
-    # Get delay
-    delay = 1  # If non-overlapping
-    if coarsegraining in ["rolling", "interpolate"]:
-        delay = scale
-
     # For 1D coarse-graining
     if coarse.ndim == 1:
+        # Get delay
+        delay = 1  # If non-overlapping
+        if coarsegraining in ["rolling", "interpolate"]:
+            delay = scale
+
+        # Compute entropy
         return algorithm(
             coarse,
             delay=delay,
@@ -414,7 +415,7 @@ def _entropy_multiscale(
                 [
                     algorithm(
                         coarse[i],
-                        delay=delay,
+                        delay=1,
                         dimension=dimension,
                         tolerance=tolerance,
                         **kwargs,
@@ -428,7 +429,7 @@ def _entropy_multiscale(
                 [
                     _phi(
                         coarse[i],
-                        delay=delay,
+                        delay=1,
                         dimension=dimension,
                         tolerance=tolerance,
                         approximate=False,

diff --git a/neurokit2/complexity/entropy_sample.py b/neurokit2/complexity/entropy_sample.py
@@ -81,13 +81,13 @@ def entropy_sample(signal, delay=1, dimension=2, tolerance="sd", **kwargs):
     }
 
     # Compute phi
-    phi = _phi(
+    info["phi"], _ = _phi(
         signal,
         delay=delay,
         dimension=dimension,
         tolerance=info["Tolerance"],
         approximate=False,
         **kwargs
-    )[0]
+    )
 
-    return _phi_divide(phi), info
+    return _phi_divide(info["phi"]), info
diff --git a/neurokit2/complexity/utils_complexity_coarsegraining.py b/neurokit2/complexity/utils_complexity_coarsegraining.py
@@ -201,14 +201,14 @@ def complexity_coarsegraining(
         raise ValueError("Unknown `method`: {}".format(method))
 
     if show is True:
-        _complexity_show(signal[0:n], coarse, method=method)
+        _complexity_coarsegraining_show(signal[0:n], coarse, method=method)
     return coarse
 
 
 # =============================================================================
 # Utils
 # =============================================================================
-def _complexity_show(signal, coarse, method="nonoverlapping"):
+def _complexity_coarsegraining_show(signal, coarse, method="nonoverlapping"):
     plt.plot(signal, linewidth=1.5)
     if method == "nonoverlapping":
         plt.plot(