fix ptp deprecation and tests

Author: zm711

src/spikeinterface/core/sparsity.py

@@ -21,8 +21,7 @@
         * "snr" : threshold based on template signal-to-noise ratio. Use the "threshold" argument
                  to specify the SNR threshold (in units of noise levels) and the "amplitude_mode" argument
                  to specify the mode to compute the amplitude of the templates.
-        * "amplitude" : threshold based on the amplitude values on every channels. Use the "threshold" argument
-                     to specify the ptp threshold (in units of amplitude) and the "amplitude_mode" argument
+        * "amplitude" : threshold based on the amplitude values on every channels. Use the "amplitude_mode" argument
                      to specify the mode to compute the amplitude of the templates.
         * "energy" : threshold based on the expected energy that should be present on the channels,
                     given their noise levels. Use the "threshold" argument to specify the energy threshold
@@ -38,7 +37,7 @@
     radius_um : float
         Radius in um for "radius" method.
     threshold : float
-        Threshold for "snr", "energy" (in units of noise levels) and "ptp" methods (in units of amplitude).
+        Threshold for "snr" and "energy" (in units of noise levels) (in units of amplitude).
         For the "snr" method, the template amplitude mode is controlled by the "amplitude_mode" argument.
     amplitude_mode : "extremum" | "at_index" | "peak_to_peak"
         Mode to compute the amplitude of the templates for the "snr", "amplitude", and "best_channels" methods.
@@ -607,9 +606,7 @@ def create_dense(cls, sorting_analyzer):
 def compute_sparsity(
     templates_or_sorting_analyzer: "Templates | SortingAnalyzer",
     noise_levels: np.ndarray | None = None,
-    method: (
-        "radius" | "best_channels" | "closest_channels" | "snr" | "amplitude" | "energy" | "by_property" | "ptp"
-    ) = "radius",
+    method: "radius" | "best_channels" | "closest_channels" | "snr" | "amplitude" | "energy" | "by_property" = "radius",
     peak_sign: "neg" | "pos" | "both" = "neg",
     num_channels: int | None = 5,
     radius_um: float | None = 100.0,
@@ -644,7 +641,13 @@ def compute_sparsity(
         # to keep backward compatibility
         templates_or_sorting_analyzer = templates_or_sorting_analyzer.sorting_analyzer
 
-    if method in ("best_channels", "closest_channels", "radius", "snr", "amplitude", "ptp"):
+    if method in (
+        "best_channels",
+        "closest_channels",
+        "radius",
+        "snr",
+        "amplitude",
+    ):
         assert isinstance(
             templates_or_sorting_analyzer, (Templates, SortingAnalyzer)
         ), f"compute_sparsity(method='{method}') need Templates or SortingAnalyzer"
@@ -687,14 +690,6 @@ def compute_sparsity(
         sparsity = ChannelSparsity.from_property(
             templates_or_sorting_analyzer.sorting, templates_or_sorting_analyzer.recording, by_property
         )
-    elif method == "ptp":
-        # TODO: remove after deprecation
-        assert threshold is not None, "For the 'ptp' method, 'threshold' needs to be given"
-        sparsity = ChannelSparsity.from_ptp(
-            templates_or_sorting_analyzer,
-            threshold,
-            noise_levels=noise_levels,
-        )
     else:
         raise ValueError(f"compute_sparsity() method={method} does not exists")
 
@@ -710,7 +705,7 @@ def estimate_sparsity(
     num_spikes_for_sparsity: int = 100,
     ms_before: float = 1.0,
     ms_after: float = 2.5,
-    method: "radius" | "best_channels" | "closest_channels" | "amplitude" | "snr" | "by_property" | "ptp" = "radius",
+    method: "radius" | "best_channels" | "closest_channels" | "amplitude" | "snr" | "by_property" = "radius",
     peak_sign: "neg" | "pos" | "both" = "neg",
     radius_um: float = 100.0,
     num_channels: int = 5,
@@ -759,9 +754,9 @@ def estimate_sparsity(
     # Can't be done at module because this is a cyclic import, too bad
     from .template import Templates
 
-    assert method in ("radius", "best_channels", "closest_channels", "snr", "amplitude", "by_property", "ptp"), (
+    assert method in ("radius", "best_channels", "closest_channels", "snr", "amplitude", "by_property"), (
         f"method={method} is not available for `estimate_sparsity()`. "
-        "Available methods are 'radius', 'best_channels', 'snr', 'amplitude', 'by_property', 'ptp' (deprecated)"
+        "Available methods are 'radius', 'best_channels', 'snr', 'amplitude', 'by_property'"
     )
 
     if recording.get_probes() == 1:
@@ -838,14 +833,6 @@ def estimate_sparsity(
             sparsity = ChannelSparsity.from_amplitude(
                 templates, threshold, amplitude_mode=amplitude_mode, peak_sign=peak_sign
             )
-        elif method == "ptp":
-            # TODO: remove after deprecation
-            assert threshold is not None, "For the 'ptp' method, 'threshold' needs to be given"
-            assert noise_levels is not None, (
-                "For the 'snr' method, 'noise_levels' needs to be given. You can use the "
-                "`get_noise_levels()` function to compute them."
-            )
-            sparsity = ChannelSparsity.from_ptp(templates, threshold, noise_levels=noise_levels)
         else:
             raise ValueError(f"compute_sparsity() method={method} does not exists")
     else:

src/spikeinterface/core/tests/test_sparsity.py

@@ -268,24 +268,8 @@ def test_estimate_sparsity():
         progress_bar=True,
         n_jobs=1,
     )
-    # ptp: just run it
     print(noise_levels)
 
-    with pytest.warns(DeprecationWarning):
-        sparsity = estimate_sparsity(
-            sorting,
-            recording,
-            num_spikes_for_sparsity=50,
-            ms_before=1.0,
-            ms_after=2.0,
-            method="ptp",
-            threshold=5,
-            noise_levels=noise_levels,
-            chunk_duration="1s",
-            progress_bar=True,
-            n_jobs=1,
-        )
-
 
 def test_compute_sparsity():
     recording, sorting = get_dataset()
@@ -310,8 +294,6 @@ def test_compute_sparsity():
     sparsity = compute_sparsity(sorting_analyzer, method="amplitude", threshold=5, amplitude_mode="peak_to_peak")
     sparsity = compute_sparsity(sorting_analyzer, method="energy", threshold=5)
     sparsity = compute_sparsity(sorting_analyzer, method="by_property", by_property="group")
-    with pytest.warns(DeprecationWarning):
-        sparsity = compute_sparsity(sorting_analyzer, method="ptp", threshold=5)
 
     # using object Templates
     templates = sorting_analyzer.get_extension("templates").get_data(outputs="Templates")
@@ -322,9 +304,6 @@ def test_compute_sparsity():
     sparsity = compute_sparsity(templates, method="amplitude", threshold=5, amplitude_mode="peak_to_peak")
     sparsity = compute_sparsity(templates, method="closest_channels", num_channels=2)
 
-    with pytest.warns(DeprecationWarning):
-        sparsity = compute_sparsity(templates, method="ptp", noise_levels=noise_levels, threshold=5)
-
 
 if __name__ == "__main__":
     # test_ChannelSparsity()