subset docstring edit (#364)

* subset docstring edit

* black v24

---------

Co-authored-by: Philippe Miron <[email protected]>

Author: selipot

clouddrift/adapters/gdp1h.py

@@ -601,11 +601,11 @@ def to_raggedarray(
     )
 
     # set dynamic global attributes
-    ra.attrs_global[
-        "time_coverage_start"
-    ] = f"{datetime(1970,1,1) + timedelta(seconds=int(np.min(ra.coords['time']))):%Y-%m-%d:%H:%M:%SZ}"
-    ra.attrs_global[
-        "time_coverage_end"
-    ] = f"{datetime(1970,1,1) + timedelta(seconds=int(np.max(ra.coords['time']))):%Y-%m-%d:%H:%M:%SZ}"
+    ra.attrs_global["time_coverage_start"] = (
+        f"{datetime(1970,1,1) + timedelta(seconds=int(np.min(ra.coords['time']))):%Y-%m-%d:%H:%M:%SZ}"
+    )
+    ra.attrs_global["time_coverage_end"] = (
+        f"{datetime(1970,1,1) + timedelta(seconds=int(np.max(ra.coords['time']))):%Y-%m-%d:%H:%M:%SZ}"
+    )
 
     return ra

clouddrift/adapters/gdp6h.py

@@ -488,11 +488,11 @@ def to_raggedarray(
     )
 
     # update dynamic global attributes
-    ra.attrs_global[
-        "time_coverage_start"
-    ] = f"{datetime(1970,1,1) + timedelta(seconds=int(np.min(ra.coords['time']))):%Y-%m-%d:%H:%M:%SZ}"
-    ra.attrs_global[
-        "time_coverage_end"
-    ] = f"{datetime(1970,1,1) + timedelta(seconds=int(np.max(ra.coords['time']))):%Y-%m-%d:%H:%M:%SZ}"
+    ra.attrs_global["time_coverage_start"] = (
+        f"{datetime(1970,1,1) + timedelta(seconds=int(np.min(ra.coords['time']))):%Y-%m-%d:%H:%M:%SZ}"
+    )
+    ra.attrs_global["time_coverage_end"] = (
+        f"{datetime(1970,1,1) + timedelta(seconds=int(np.max(ra.coords['time']))):%Y-%m-%d:%H:%M:%SZ}"
+    )
 
     return ra

clouddrift/adapters/glad.py

@@ -13,6 +13,7 @@
 ---------
 Özgökmen, Tamay. 2013. GLAD experiment CODE-style drifter trajectories (low-pass filtered, 15 minute interval records), northern Gulf of Mexico near DeSoto Canyon, July-October 2012. Distributed by: Gulf of Mexico Research Initiative Information and Data Cooperative (GRIIDC), Harte Research Institute, Texas A&M University–Corpus Christi. doi:10.7266/N7VD6WC8
 """
+
 from clouddrift.adapters.utils import download_with_progress
 from io import BytesIO
 import numpy as np

clouddrift/adapters/mosaic.py

@@ -18,6 +18,7 @@
 >>> from clouddrift.adapters import mosaic
 >>> ds = mosaic.to_xarray()
 """
+
 from datetime import datetime
 from io import BytesIO
 import numpy as np

clouddrift/datasets.py

@@ -4,6 +4,7 @@
 they will be downloaded from their upstream repositories and stored for later access 
 (~/.clouddrift for UNIX-based systems).
 """
+
 from io import BufferedReader, BytesIO
 from clouddrift import adapters
 import os

clouddrift/pairs.py

@@ -1,6 +1,7 @@
 """
 Functions to analyze pairs of contiguous data segments.
 """
+
 from clouddrift import ragged, sphere
 from concurrent.futures import as_completed, ThreadPoolExecutor
 import itertools

clouddrift/ragged.py

@@ -558,17 +558,17 @@ def subset(
     Parameters
     ----------
     ds : xr.Dataset
-        Dataset stored as ragged arrays
+        Dataset stored as ragged arrays.
     criteria : dict
-        dictionary containing the variables (as keys) and the ranges/values/functions (as values) to subset
+        Dictionary containing the variables (as keys) and the ranges/values/functions (as values) to subset.
     id_var_name : str, optional
-        Name of the variable containing the ID of the trajectories (default is "id")
+        Name of the variable with dimension `traj_dim_name` containing the ID of the trajectories (default is "id").
     rowsize_var_name : str, optional
-        Name of the variable containing the number of observations per trajectory (default is "rowsize")
+        Name of the variable containing the number of observations per trajectory (default is "rowsize").
     traj_dim_name : str, optional
-        Name of the trajectory dimension (default is "traj")
+        Name of the trajectory dimension (default is "traj").
     obs_dim_name : str, optional
-        Name of the observation dimension (default is "obs")
+        Name of the observation dimension (default is "obs").
     full_trajectories : bool, optional
         If True, it returns the complete trajectories (rows) where at least one observation
         matches the criteria, rather than just the segments where the criteria are satisfied.

clouddrift/raggedarray.py

@@ -3,6 +3,7 @@
 structure used by CloudDrift to process custom Lagrangian datasets to Xarray
 Datasets and Awkward Arrays.
 """
+
 import awkward as ak
 from clouddrift.ragged import rowsize_to_index
 import xarray as xr

clouddrift/wavelet.py

@@ -429,8 +429,7 @@ def morse_wavelet(
         if normalization == "energy":
             with np.errstate(divide="ignore"):
                 waveletzero = np.exp(
-                    beta * np.log(norm_radian_frequency)
-                    - norm_radian_frequency**gamma
+                    beta * np.log(norm_radian_frequency) - norm_radian_frequency**gamma
                 )
         elif normalization == "bandpass":
             if beta == 0:
@@ -800,11 +799,7 @@ def morse_amplitude(
     if normalization == "energy":
         r = (2 * beta + 1) / gamma
         amp = (
-            2
-            * np.pi
-            * gamma
-            * (2**r)
-            * np.exp(_lgamma(order) - _lgamma(order + r - 1))
+            2 * np.pi * gamma * (2**r) * np.exp(_lgamma(order) - _lgamma(order + r - 1))
         ) ** 0.5
     elif normalization == "bandpass":
         fm, _, _ = morse_freq(gamma, beta)