Merge pull request #1970 from h-mayorquin/change_default_in_generate_recording

Some additions to generate.py after #1948

Author: alejoe91

src/spikeinterface/core/generate.py

@@ -2,6 +2,7 @@
 import warnings
 import numpy as np
 from typing import Union, Optional, List, Literal
+import warnings
 
 
 from .numpyextractors import NumpyRecording, NumpySorting
@@ -31,7 +32,7 @@ def generate_recording(
     set_probe: Optional[bool] = True,
     ndim: Optional[int] = 2,
     seed: Optional[int] = None,
-    mode: Literal["lazy", "legacy"] = "legacy",
+    mode: Literal["lazy", "legacy"] = "lazy",
 ) -> BaseRecording:
     """
     Generate a recording object.
@@ -51,10 +52,10 @@ def generate_recording(
         The number of dimensions of the probe, by default 2. Set to 3 to make 3 dimensional probes.
     seed : Optional[int]
         A seed for the np.ramdom.default_rng function
-    mode: str ["lazy", "legacy"] Default "legacy".
+    mode: str ["lazy", "legacy"] Default "lazy".
         "legacy": generate a NumpyRecording with white noise.
-                  This mode is kept for backward compatibility and will be deprecated in next release.
-        "lazy": return a NoiseGeneratorRecording
+                This mode is kept for backward compatibility and will be deprecated version 0.100.0.
+        "lazy": return a NoiseGeneratorRecording instance.
 
     Returns
     -------
@@ -64,6 +65,10 @@ def generate_recording(
     seed = _ensure_seed(seed)
 
     if mode == "legacy":
+        warnings.warn(
+            "generate_recording() : mode='legacy' will be deprecated in version 0.100.0. Use mode='lazy' instead.",
+            DeprecationWarning,
+        )
         recording = _generate_recording_legacy(num_channels, sampling_frequency, durations, seed)
     elif mode == "lazy":
         recording = NoiseGeneratorRecording(
@@ -538,7 +543,7 @@ def synthetize_spike_train_bad_isi(duration, baseline_rate, num_violations, viol
 
 class NoiseGeneratorRecording(BaseRecording):
     """
-    A lazy recording that generates random samples if and only if `get_traces` is called.
+    A lazy recording that generates white noise samples if and only if `get_traces` is called.
 
     This done by tiling small noise chunk.
 
@@ -555,7 +560,7 @@ class NoiseGeneratorRecording(BaseRecording):
         The sampling frequency of the recorder.
     durations : List[float]
         The durations of each segment in seconds. Note that the length of this list is the number of segments.
-    noise_level: float, default 5:
+    noise_level: float, default 1:
         Std of the white noise
     dtype : Optional[Union[np.dtype, str]], default='float32'
         The dtype of the recording. Note that only np.float32 and np.float64 are supported.
@@ -581,7 +586,7 @@ def __init__(
         num_channels: int,
         sampling_frequency: float,
         durations: List[float],
-        noise_level: float = 5.0,
+        noise_level: float = 1.0,
         dtype: Optional[Union[np.dtype, str]] = "float32",
         seed: Optional[int] = None,
         strategy: Literal["tile_pregenerated", "on_the_fly"] = "tile_pregenerated",
@@ -647,7 +652,7 @@ def __init__(
         if self.strategy == "tile_pregenerated":
             rng = np.random.default_rng(seed=self.seed)
             self.noise_block = (
-                rng.standard_normal(size=(self.noise_block_size, self.num_channels)).astype(self.dtype) * noise_level
+                rng.standard_normal(size=(self.noise_block_size, self.num_channels), dtype=self.dtype) * noise_level
             )
         elif self.strategy == "on_the_fly":
             pass
@@ -664,35 +669,35 @@ def get_traces(
         start_frame = 0 if start_frame is None else max(start_frame, 0)
         end_frame = self.num_samples if end_frame is None else min(end_frame, self.num_samples)
 
-        start_frame_mod = start_frame % self.noise_block_size
-        end_frame_mod = end_frame % self.noise_block_size
+        start_frame_within_block = start_frame % self.noise_block_size
+        end_frame_within_block = end_frame % self.noise_block_size
         num_samples = end_frame - start_frame
 
         traces = np.empty(shape=(num_samples, self.num_channels), dtype=self.dtype)
 
-        start_block_index = start_frame // self.noise_block_size
-        end_block_index = end_frame // self.noise_block_size
+        first_block_index = start_frame // self.noise_block_size
+        last_block_index = end_frame // self.noise_block_size
 
         pos = 0
-        for block_index in range(start_block_index, end_block_index + 1):
+        for block_index in range(first_block_index, last_block_index + 1):
             if self.strategy == "tile_pregenerated":
                 noise_block = self.noise_block
             elif self.strategy == "on_the_fly":
                 rng = np.random.default_rng(seed=(self.seed, block_index))
-                noise_block = rng.standard_normal(size=(self.noise_block_size, self.num_channels)).astype(self.dtype)
+                noise_block = rng.standard_normal(size=(self.noise_block_size, self.num_channels), dtype=self.dtype)
                 noise_block *= self.noise_level
 
-            if block_index == start_block_index:
-                if start_block_index != end_block_index:
-                    end_first_block = self.noise_block_size - start_frame_mod
-                    traces[:end_first_block] = noise_block[start_frame_mod:]
+            if block_index == first_block_index:
+                if first_block_index != last_block_index:
+                    end_first_block = self.noise_block_size - start_frame_within_block
+                    traces[:end_first_block] = noise_block[start_frame_within_block:]
                     pos += end_first_block
                 else:
                     # special case when unique block
-                    traces[:] = noise_block[start_frame_mod : start_frame_mod + traces.shape[0]]
-            elif block_index == end_block_index:
-                if end_frame_mod > 0:
-                    traces[pos:] = noise_block[:end_frame_mod]
+                    traces[:] = noise_block[start_frame_within_block : start_frame_within_block + num_samples]
+            elif block_index == last_block_index:
+                if end_frame_within_block > 0:
+                    traces[pos:] = noise_block[:end_frame_within_block]
             else:
                 traces[pos : pos + self.noise_block_size] = noise_block
                 pos += self.noise_block_size
@@ -710,7 +715,7 @@ def get_traces(
 
 def generate_recording_by_size(
     full_traces_size_GiB: float,
-    num_channels: int = 1024,
+    num_channels: int = 384,
     seed: Optional[int] = None,
     strategy: Literal["tile_pregenerated", "on_the_fly"] = "tile_pregenerated",
 ) -> NoiseGeneratorRecording:
@@ -719,15 +724,15 @@ def generate_recording_by_size(
     This is a convenience wrapper around the NoiseGeneratorRecording class where only
     the size in GiB (NOT GB!) is specified.
 
-    It is generated with 1024 channels and a sampling frequency of 1 Hz. The duration is manipulted to
+    It is generated with 384 channels and a sampling frequency of 1 Hz. The duration is manipulted to
     produced the desired size.
 
     Seee GeneratorRecording for more details.
 
     Parameters
     ----------
     full_traces_size_GiB : float
-        The size in gibibyte (GiB) of the recording.
+        The size in gigabytes (GiB) of the recording.
     num_channels: int
         Number of channels.
     seed : int, optional
@@ -740,7 +745,7 @@ def generate_recording_by_size(
 
     dtype = np.dtype("float32")
     sampling_frequency = 30_000.0  # Hz
-    num_channels = 1024
+    num_channels = 384
 
     GiB_to_bytes = 1024**3
     full_traces_size_bytes = int(full_traces_size_GiB * GiB_to_bytes)