[pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

Author: pre-commit-ci[bot]

strax/context.py

@@ -18,7 +18,6 @@
 import strax
 from strax import CutList
 
-
 export, __all__ = strax.exporter()
 __all__.extend(["RUN_DEFAULTS_KEY"])
 
@@ -1443,8 +1442,8 @@ def _add_saver(
         target_plugin: strax.Plugin,
         combining: bool = False,
     ):
-        """Adds savers to already existing savers. Checks if data_type can be stored in any storage
-        frontend.
+        """Adds savers to already existing savers. frontend. Checks if data_type can be stored in
+        any storage.
 
         :param savers: Dictionary of already existing savers.
         :param d_to_save: String of the data_type to be saved.
@@ -1559,7 +1558,6 @@ def to_absolute_time_range(
         :param full_range: If True returns full time_range of the run.
 
         """
-
         selection = (
             (time_range is None)
             + (seconds_range is None)
@@ -1820,9 +1818,9 @@ def make(
         combining=False,
         **kwargs,
     ) -> None:
-        """Compute target for run_id. Returns nothing (None).
+        """Compute target for run_id.
 
-        {get_docs}
+        Returns nothing (None).         {get_docs}
 
         """
         kwargs.setdefault("progress_bar", False)
@@ -2018,8 +2016,8 @@ def get_zarr(
         overwrite=True,
         **kwargs,
     ):
-        """Get persistent arrays using zarr. This is useful when loading large amounts of data that
-        cannot fit in memory zarr is very compatible with dask. Targets are loaded into separate
+        """Get persistent arrays using zarr. cannot fit in memory zarr is very compatible with dask.
+        Targets are loaded into separate This is useful when loading large amounts of data that
         arrays and runs are merged. the data is added to any existing data in the storage location.
 
         :param run_ids: (Iterable) run ids you wish to load.
@@ -2070,9 +2068,9 @@ def get_zarr(
         return group
 
     def key_for(self, run_id, target, chunk_number=None, combining=False):
-        """Get the DataKey for a given run and a given target plugin. The DataKey is inferred from
-        the plugin lineage. The lineage can come either from the _fixed_plugin_cache or computed on
-        the fly.
+        """Get the DataKey for a given run and a given target plugin. the plugin lineage. The
+        lineage can come either from the _fixed_plugin_cache or computed on The DataKey is inferred
+        from the fly.
 
         :param run_id: run id to get
         :param target: data type to get
@@ -2487,7 +2485,6 @@ def merge_per_chunk_storage(
         check_is_stored: bool = True,
     ):
         """Merge the per-chunked data from the per-chunked dependency into the target storage."""
-
         if check_is_stored and self.is_stored(run_id, target):
             raise ValueError(f"Data {target} for {run_id} already exists.")
 
@@ -2871,7 +2868,6 @@ def tree_levels(self):
         'class': 'Peaks', 'index': 0, 'order': 1}}
 
         """
-
         context_hash = self._context_hash()
         if self._fixed_level_cache is not None and context_hash in self._fixed_level_cache:
             return self._fixed_level_cache[context_hash]

strax/dtypes.py

@@ -1,8 +1,7 @@
 """Fundamental dtypes for use in strax.
 
-Note that if you change the dtype titles (comments), numba will crash if
-there is an existing numba cache. Clear __pycache__ and restart.
-TODO: file numba issue.
+Note that if you change the dtype titles (comments), numba will crash if there is an existing numba
+cache. Clear __pycache__ and restart. TODO: file numba issue.
 
 """
 
@@ -12,7 +11,6 @@
 import numba  # noqa: F401
 import strax
 
-
 __all__ = (
     "interval_dtype raw_record_dtype record_dtype hit_dtype peak_dtype "
     "DIGITAL_SUM_WAVEFORM_CHANNEL DEFAULT_RECORD_LENGTH "
@@ -134,8 +132,9 @@ def hitlet_dtype():
 
 
 def hitlet_with_data_dtype(n_samples=2):
-    """Hitlet dtype with data field. Required within the plugins to compute hitlet properties.
+    """Hitlet dtype with data field.
 
+    Required within the plugins to compute hitlet properties.
     :param n_samples: Buffer length of the data field. Make sure it can hold the longest hitlet.
 
     """
@@ -246,8 +245,8 @@ def peak_dtype(
 def copy_to_buffer(
     source: np.ndarray, buffer: np.ndarray, func_name: str, field_names: Optional[Tuple[str]] = None
 ):
-    """Copy the data from the source to the destination e.g. raw_records to records. To this end, we
-    dynamically create the njitted function with the name 'func_name' (should start with "_").
+    """Copy the data from the source to the destination e.g. raw_records to records. dynamically
+    create the njitted function with the name 'func_name' (should start with "_"). To this end, we.
 
     :param source: array of input
     :param buffer: array of buffer to fill with values from input

strax/plugins/plugin.py

@@ -411,8 +411,8 @@ def source_finished(self):
         raise RuntimeError("source_finished called on a regular plugin")
 
     def _fetch_chunk(self, d, iters, check_end_not_before=None):
-        """Add a chunk of the datatype d to the input buffer. Return True if this succeeded, False
-        if the source is exhausted.
+        """Add a chunk of the datatype d to the input buffer. if the source is exhausted. Return
+        True if this succeeded, False.
 
         :param d: data type to fetch
         :param iters: iterators that produce data

strax/processing/general.py

@@ -123,8 +123,8 @@ class NoBreakFound(Exception):
 @export
 @numba.njit(nogil=True, cache=True)
 def _find_break_i(data, safe_break, not_before):
-    """Return first index of element right of the first gap larger than safe_break in data. Assumes
-    all x have the same length and are sorted!
+    """Return first index of element right of the first gap larger than safe_break in data. all x
+    have the same length and are sorted! Assumes.
 
     :param tolerant: if no break found, yield an as good as possible break anyway.
 
@@ -211,8 +211,8 @@ def _fc_in(a_starts, b_starts, a_ends, b_ends, result):
 
 @export
 def split_by_containment(things, containers):
-    """Return list of thing-arrays contained in each container. Result is returned as a
-    numba.typed.List or list if containers are empty.
+    """Return list of thing-arrays contained in each container. numba.typed.List or list if
+    containers are empty. Result is returned as a.
 
     Assumes everything is sorted, and containers are non-overlapping.
 

strax/processing/peak_building.py

@@ -157,7 +157,6 @@ def store_downsampled_waveform(
         waveform in the peak.
 
     """
-
     n_samples = len(p["data"])
 
     p_length = p["length"]
@@ -255,8 +254,8 @@ def sum_waveform(
     store_data_start=False,
     select_peaks_indices=None,
 ):
-    """Compute sum waveforms for all peaks in peaks. Only builds summed waveform other regions in
-    which hits were found. This is required to avoid any bias due to zero-padding and baselining.
+    """Compute sum waveforms for all peaks in peaks. which hits were found. This is required to
+    avoid any bias due to zero-padding and baselining. Only builds summed waveform other regions in
     Will downsample sum waveforms if they do not fit in per-peak buffer.
 
     :param peaks: Peaks for which the summed waveform should be build.
@@ -401,8 +400,8 @@ def sum_waveform(
 
 @numba.njit(cache=True, nogil=True)
 def _build_hit_waveform(hit, record, hit_waveform):
-    """Adds information for overlapping record and hit to hit_waveform. Updates hit_waveform
-    inplace. Result is still in ADC counts.
+    """Adds information for overlapping record and hit to hit_waveform. inplace. Result is still in
+    ADC counts. Updates hit_waveform.
 
     :return: Boolean if record saturated within the hit.
 
@@ -477,8 +476,8 @@ def find_hit_integration_bounds(
     n_channels,
     allow_bounds_beyond_records=False,
 ):
-    """Update (lone) hits to include integration bounds. Please note that time and length of the
-    original hit are not changed!
+    """Update (lone) hits to include integration bounds. original hit are not changed! Please note
+    that time and length of the.
 
     :param hits: Hits or lone hits which should be extended by integration bounds.
     :param excluded_intervals: Regions in which hits should not extend to. E.g. Peaks for lone hits.

strax/processing/peak_merging.py

@@ -36,7 +36,6 @@ def merge_peaks(
         constituent peaks, it being too time-consuming to revert to records/hits.
 
     """
-
     new_peaks, endtime = _merge_peaks(
         peaks,
         start_merge_at,

strax/processing/peak_properties.py

@@ -77,7 +77,6 @@ def compute_widths(peaks):
     :param peaks: single strax peak(let) or other data-bearing dtype
 
     """
-
     desired_widths = np.linspace(0, 1, len(peaks[0]["width"]))
     # 0% are width is 0 by definition, and it messes up the calculation below
     desired_widths = desired_widths[1:]
@@ -137,8 +136,8 @@ def compute_area_fraction_top(peaks, n_top_channels):
 
 @export
 def compute_properties(peaks, n_top_channels=0, select_peaks_indices=None):
-    """Compute properties: median_time, width, area_decile_from_midpoint,
-    center_time, and area_fraction_top for peaks.
+    """Compute properties: median_time, width, area_decile_from_midpoint, center_time, and
+    area_fraction_top for peaks.
 
     :param peaks: single strax peak(let) or other data-bearing dtype
     :param select_peaks_indices: array of integers informing which peaks to compute default to None

strax/processing/pulse_processing.py

@@ -20,8 +20,8 @@
 def baseline(
     records, baseline_samples=40, flip=True, allow_sloppy_chunking=False, fallback_baseline=16000
 ):
-    """Determine baseline as the average of the first baseline_samples of each pulse. Subtract the
-    pulse data from int(baseline), and store the baseline mean and rms.
+    """Determine baseline as the average of the first baseline_samples of each pulse. pulse data
+    from int(baseline), and store the baseline mean and rms. Subtract the.
 
     :param baseline_samples: number of samples at start of pulse to average to determine the
         baseline.
@@ -165,8 +165,8 @@ def find_hits(
     min_amplitude: ty.Union[int, np.ndarray] = 15,
     min_height_over_noise: ty.Union[int, np.ndarray] = 0,
 ):
-    """Return hits (intervals >= threshold) found in records. Hits that straddle record boundaries
-    are split (perhaps we should fix this?)
+    """Return hits (intervals >= threshold) found in records. are split (perhaps we should fix
+    this?) Hits that straddle record boundaries.
 
     NB: returned hits are NOT sorted yet!
 
@@ -316,8 +316,8 @@ def _waveforms_to_float(wv, bl):
 
 @export
 def filter_records(r, ir):
-    """Apply filter with impulse response ir over the records r. Assumes the filter origin is at the
-    impulse response maximum.
+    """Apply filter with impulse response ir over the records r. impulse response maximum. Assumes
+    the filter origin is at the.
 
     :param ws: Waveform matrix, must be float
     :param ir: Impulse response, must have odd length. Will normalize.
@@ -338,8 +338,8 @@ def filter_records(r, ir):
 
 @export
 def filter_waveforms(ws, ir, prev_r, next_r):
-    """Convolve filter with impulse response ir over each row of ws. Assumes the filter origin is at
-    the impulse response maximum.
+    """Convolve filter with impulse response ir over each row of ws. the impulse response maximum.
+    Assumes the filter origin is at.
 
     :param ws: Waveform matrix, must be float
     :param ir: Impulse response, must have odd length.

strax/run_selection.py

@@ -26,7 +26,6 @@ def list_available(self, target, runs=None, **kwargs) -> list:
     :param runs: Runs to check. If None, check all runs.
 
     """
-
     if len(kwargs):
         # noinspection PyMethodFirstArgAssignment
         self = self.new_context(**kwargs)
@@ -53,8 +52,8 @@ def list_available(self, target, runs=None, **kwargs) -> list:
 def keys_for_runs(
     self, target: str, run_ids: ty.Union[np.ndarray, list, tuple, str]
 ) -> ty.List[strax.DataKey]:
-    """Get the data-keys for a multitude of runs. If use_per_run_defaults is False which it
-    preferably is (#246), getting many keys should be fast as we only compute the lineage once.
+    """Get the data-keys for a multitude of runs. preferably is (#246), getting many keys should be
+    fast as we only compute the lineage once. If use_per_run_defaults is False which it.
 
     :param run_ids: Runs to get datakeys for
     :param target: datatype requested
@@ -467,8 +466,8 @@ def available_for_run(
     exclude_targets: ty.Union[None, list, tuple, str] = None,
     pattern_type: str = "fnmatch",
 ) -> pd.DataFrame:
-    """For a given single run, check all the targets if they are stored. Excludes the target if
-    never stored anyway.
+    """For a given single run, check all the targets if they are stored. never stored anyway.
+    Excludes the target if.
 
     :param run_id: requested run
     :param include_targets: targets to include e.g. raw_records, raw_records* or *_nv. If multiple

strax/storage/files.py

@@ -17,10 +17,10 @@
 
 @export
 class DataDirectory(StorageFrontend):
-    """Simplest registry: single directory with FileStore data
-    sitting in subdirectories.
+    """Simplest registry: single directory with FileStore data sitting in subdirectories.
 
     Run-level metadata is stored in loose json files in the directory.
+
     """
 
     can_define_runs = True