[Fix] Forward custom amplitude_min through eda_process (#1197)

NEWS.rst

@@ -1,6 +1,14 @@
 News
 =====
 
+0.2.14
+-------------------
+Fixes
++++++++++++++
+
+* ``eda_process()`` now forwards a custom ``amplitude_min`` to ``eda_peaks()``
+  instead of hardcoding ``0.1`` (#1197).
+
 0.2.8
 -------------------
 New Features
@@ -230,6 +238,3 @@ Fixes
 -------------------
 
 * First release on PyPI.
-
-
-

neurokit2/eda/eda_methods.py

@@ -64,13 +64,13 @@ def eda_methods(
     method_phasic = str(method).lower() if method_phasic == "default" else str(method_phasic).lower()
     method_peaks = str(method).lower() if method_peaks == "default" else str(method_peaks).lower()
 
-    # Create dictionary with all inputs
+    # Unpack user kwargs so get_kwargs() can forward them (same pattern as rsp_methods).
     report_info = {
         "sampling_rate": sampling_rate,
         "method_cleaning": method_cleaning,
         "method_phasic": method_phasic,
         "method_peaks": method_peaks,
-        "kwargs": kwargs,
+        **kwargs,
     }
 
     # Get arguments to be passed to underlying functions

neurokit2/eda/eda_process.py

@@ -28,8 +28,10 @@ def eda_process(eda_signal, sampling_rate=1000, method="neurokit", report=None,
         should be generated. Defaults to ``None``. Can also be ``"text"`` to
         just print the text in the console without saving anything.
     **kwargs
-        Other arguments to be passed to specific methods. For more information,
-        see :func:`.rsp_methods`.
+        Other arguments to be passed to specific methods. This includes
+        ``amplitude_min`` (relative SCR amplitude threshold, default ``0.1``)
+        forwarded to :func:`.eda_peaks`. For more information, see
+        :func:`.eda_methods`.
 
     Returns
     -------
@@ -96,12 +98,12 @@ def eda_process(eda_signal, sampling_rate=1000, method="neurokit", report=None,
             **methods["kwargs_phasic"],
         )
 
-    # Find peaks
+    # Find peaks. amplitude_min defaults to 0.1 inside eda_peaks(); a custom
+    # value passed via **kwargs is forwarded through methods["kwargs_peaks"].
     peak_signal, info = eda_peaks(
         eda_decomposed["EDA_Phasic"].values,
         sampling_rate=sampling_rate,
         method=methods["method_peaks"],
-        amplitude_min=0.1,
         **methods["kwargs_peaks"],
     )
     info["sampling_rate"] = sampling_rate  # Add sampling rate in dict info

tests/tests_eda.py

@@ -144,6 +144,36 @@ def test_eda_process():
     assert peaks.shape == onsets.shape == recovery.shape == (5,)
 
 
+def test_eda_process_custom_amplitude_min():
+    """Custom amplitude_min must reach eda_peaks through eda_process (#1197)."""
+    from neurokit2.eda.eda_methods import eda_methods
+
+    methods = eda_methods(amplitude_min=0.03)
+    assert methods["kwargs_peaks"]["amplitude_min"] == 0.03
+
+    sampling_rate = 250
+    eda = nk.eda_simulate(
+        duration=30,
+        scr_number=5,
+        drift=0.1,
+        noise=0,
+        sampling_rate=sampling_rate,
+        random_state=42,
+    )
+
+    signals_default, _ = nk.eda_process(eda, sampling_rate=sampling_rate)
+    signals_strict, _ = nk.eda_process(eda, sampling_rate=sampling_rate, amplitude_min=0.9)
+    signals_loose, _ = nk.eda_process(eda, sampling_rate=sampling_rate, amplitude_min=0.01)
+
+    n_default = int(np.sum(signals_default["SCR_Peaks"] == 1))
+    n_strict = int(np.sum(signals_strict["SCR_Peaks"] == 1))
+    n_loose = int(np.sum(signals_loose["SCR_Peaks"] == 1))
+
+    assert n_strict <= n_default
+    assert n_loose >= n_default
+    assert n_strict < n_loose
+
+
 def test_eda_plot():
     sampling_rate = 1000
     eda = nk.eda_simulate(