Version 0.14.1

docs/conf.py

@@ -221,7 +221,7 @@
 intersphinx_mapping = {
     "python": ("https://docs.python.org/dev", None),
     "numpy": ("https://numpy.org/doc/stable/", None),
-    "scipy": ("https://docs.scipy.org/doc/scipy/reference", None),
+    "scipy": ('https://docs.scipy.org/doc/scipy', None),
     "pandas": ("https://pandas.pydata.org/pandas-docs/stable", None),
 }
 

docs/ref/index.rst

@@ -10,10 +10,10 @@ SKDH Reference
     io
     preprocessing
     features
+    context
     sleep
     activity
     gait
     gait_old
     sit2stand
     utility
-    ambulation

docs/src/research.rst

@@ -2,7 +2,7 @@ Peer Reviewed Journal Articles Using SKDH
 =========================================
 
 - W. Lin et al., “Can Gait Characteristics Be Represented by Physical Activity Measured with Wrist-Worn Accelerometers?,” Sensors, vol. 23, no. 20, Art. no. 20, Jan. 2023, doi: 10.3390/s23208542.
-- W. Lin et al., "SciKit Digital Health Package for Accelerometry-Measured Physical Activity: Comparisons to Existing Solutions and Investigations of Age Effects in Healthy Adults", In Preperation
+- W. Lin et al., "SciKit Digital Health Package for Accelerometry-Measured Physical Activity: Comparisons to Existing Solutions and Investigations of Age Effects in Healthy Adults", Front. Digit. Health, 26 Nov. 2023, doi: 10.3389/fdgth.2023.1321086
 - J. Di et al., "Wearable Accelerometers as An Innovative Approach to Monitor Physical Activity and Gait in Children and Adolescents", In Preparation
 - P. Sheriff et al., "In-Clinic and Natural Gait Observations (I-CAN-GO) an Observational Low-Interventional Master Protocol to Validate Gait and Physical Activity in Adults", In Preparation
 - N. Camerlingo et al., "Measuring gait parameters from a chest-worn accelerometer in healthy individuals: a validation study", In Preparation

meson.build

@@ -1,7 +1,7 @@
 project(
     'scikit-digital-health',
     'c',
-    version: '0.14.0',
+    version: '0.14.1',
     license: 'MIT',
     meson_version: '>=1.1',
 )

pyproject.toml

@@ -33,8 +33,6 @@ classifiers = [
     "Development Status :: 4 - Beta",
     "License :: OSI Approved :: MIT License",
     "Programming Language :: Python",
-    "Programming Language :: Python :: 3.6",
-    "Programming Language :: Python :: 3.7",
     "Programming Language :: Python :: 3.8",
     "Programming Language :: Python :: 3.9",
     "Programming Language :: Python :: 3.10",
@@ -51,7 +49,7 @@ classifiers = [
 requires-python = ">=3.6"
 dependencies = [
     "numpy>=1.17.2",
-    "scipy>=1.3.1",
+    "scipy>=1.12.0",
     "pandas>=1.0.0",
     "lightgbm>=2.3.0",
     "pywavelets",

requirements.txt

@@ -1,5 +1,5 @@
 numpy>=1.17.2
-scipy>=1.3.1
+scipy>=1.12.0
 pandas>=0.23.4
 lightgbm>=2.3.0
 pywavelets

src/skdh/activity/metrics.py

@@ -4,6 +4,8 @@
 Lukas Adamowicz
 Copyright (c) 2021. Pfizer Inc. All rights reserved.
 """
+import warnings
+
 from numpy import maximum, abs, repeat, arctan, sqrt, pi
 from numpy.linalg import norm
 from scipy.signal import butter, sosfiltfilt
@@ -38,9 +40,11 @@ def metric_anglez(accel, wlen, *args, **kwargs):
     anglez : numpy.ndarray
         (N, ) array of angles between accelerometer z axis and horizontal plane in degrees.
     """
-    anglez = arctan(accel[:, 2] / sqrt(accel[:, 0] ** 2 + accel[:, 1] ** 2)) * (
-        180 / pi
-    )
+    with warnings.catch_warnings():
+        warnings.filterwarnings("ignore", message="divide by zero encountered in divide")
+        anglez = arctan(accel[:, 2] / sqrt(accel[:, 0] ** 2 + accel[:, 1] ** 2)) * (
+            180 / pi
+        )
     return moving_mean(anglez, wlen, wlen)
 
 

src/skdh/gait/__init__.py

@@ -4,7 +4,7 @@
 
 .. currentmodule:: skdh.gait
 
-Pipeline gait processing
+Pipeline Gait Processing
 ------------------------
 
 .. autosummary::

src/skdh/gait/core.py

@@ -77,7 +77,7 @@ class GaitLumbar(BaseProcess):
         - `btype`: band
         - `output`: sos - NOTE that this will always be set/overriden
 
-        See :scipy-signal:func:`scipy.signal.butter` for full options.
+        See :func:`scipy.signal.butter` for full options.
     ic_prom_factor : float, optional
         [:meth:`skdh.gaitv3.substeps.ApCwtGaitEvents`] Factor multiplied by the
         standard deviation of the CWT coefficients to obtain a minimum prominence

src/skdh/gait/substeps/s1_preprocessing.py

@@ -54,7 +54,7 @@ class PreprocessGaitBout(BaseProcess):
         - `btype`: band
         - `output`: sos - NOTE that this will always be set/overriden
 
-        See :scipy-signal:func:`scipy.signal.butter` for full options.
+        See :func:`scipy.signal.butter` for full options.
     """
 
     def __init__(

src/skdh/io/apdm.py

@@ -24,6 +24,9 @@ class ReadApdmH5(BaseProcess):
     sensor_location : str
         Sensor location to get data from. Looks at the `Label 0` key to find the
         desired sensor.
+    localize_timestamps : bool, optional
+        Convert timestamps to local time from UTC. Default is True. Uses APDM's 
+        timezone offset attribute for the sensor being extracted.
     gravity_acceleration : float, optional
         Acceleration due to gravity. Used to convert values to units of `g`.
         Default is 9.81 m/s^2.
@@ -46,10 +49,11 @@ class ReadApdmH5(BaseProcess):
     - Sternum
     """
 
-    def __init__(self, sensor_location, gravity_acceleration=9.81, ext_error="warn"):
+    def __init__(self, sensor_location, localize_timestamps=True, gravity_acceleration=9.81, ext_error="warn"):
         super().__init__(
             # kwargs
             sensor_location=sensor_location,
+            localize_timestamps=localize_timestamps,
             gravity_acceleration=gravity_acceleration,
             ext_error=ext_error,
         )
@@ -59,6 +63,7 @@ def __init__(self, sensor_location, gravity_acceleration=9.81, ext_error="warn")
         else:
             raise ValueError("`ext_error` must be one of 'raise', 'warn', 'skip'.")
 
+        self.localize_time = localize_timestamps
         self.sens = sensor_location
         self.g = gravity_acceleration
 
@@ -113,4 +118,12 @@ def predict(self, *, file, **kwargs):
             res[self._gyro] = f["Sensors"][sid]["Gyroscope"][()]
             res[self._temp] = f["Sensors"][sid]["Temperature"][()]
 
+            # if we are converting to local time
+            if self.localize_time:
+                offset_hours = float(f['Sensors'][sid]['Configuration'].attrs["Timezone Offset"])
+                # convert to seconds
+                offset_sec = offset_hours * 3600.0
+
+                res[self._time] += offset_sec
+
         return res

src/skdh/io/axivity.py

@@ -91,7 +91,7 @@ def predict(self, *, file, **kwargs):
         super().predict(expect_days=False, expect_wear=False, file=file, **kwargs)
 
         # read the file
-        fs, n_bad_samples, imudata, ts, temperature = read_axivity(file)
+        fs, n_bad_samples, imudata, ts, temperature = read_axivity(str(file))
 
         # end = None if n_bad_samples == 0 else -n_bad_samples
         end = None

src/skdh/io/csv.py

@@ -81,7 +81,7 @@ def handle_timestamp_inconsistency(df, fill_gaps, accel_col_names, accel_in_g, g
         t_delta = to_timedelta(t_delta, unit="s")
 
         # add the time delta so that we have unique timestamps
-        df["_datetime_"] += t_delta
+        df.loc[:, "_datetime_"] += t_delta
 
     # check if we are filling gaps or not
     if fill_gaps:

src/skdh/io/geneactiv.py

@@ -79,7 +79,7 @@ def predict(self, *, file, **kwargs):
         super().predict(expect_days=False, expect_wear=False, file=file, **kwargs)
 
         # read the file
-        n_max, fs, acc, time, light, temp = read_geneactiv(file)
+        n_max, fs, acc, time, light, temp = read_geneactiv(str(file))
 
         results = {
             self._time: time[:n_max],

tests/io/conftest.py

@@ -48,7 +48,7 @@ def predict(self, *, test_input=None, **kwargs):
 
 @fixture
 def gnactv_file(path_tests):
-    return str(path_tests / "io" / "data" / "gnactv_sample.bin")
+    return path_tests / "io" / "data" / "gnactv_sample.bin"
 
 
 @fixture
@@ -63,7 +63,7 @@ def gnactv_truth(path_tests):
 
 @fixture
 def ax3_file(path_tests):
-    return str(path_tests / "io" / "data" / "ax3_sample.cwa")
+    return path_tests / "io" / "data" / "ax3_sample.cwa"
 
 
 @fixture
@@ -78,7 +78,7 @@ def ax3_truth(path_tests):
 
 @fixture
 def ax6_file(path_tests):
-    return str(path_tests / "io" / "data" / "ax6_sample.cwa")
+    return path_tests / "io" / "data" / "ax6_sample.cwa"
 
 
 @fixture
@@ -93,7 +93,7 @@ def ax6_truth(path_tests):
 
 @fixture
 def apdm_file(path_tests):
-    return str(path_tests / "io" / 'data' / "apdm_sample.h5")
+    return path_tests / "io" / 'data' / "apdm_sample.h5"
 
 
 @fixture

tests/io/test_apdm.py

@@ -10,12 +10,12 @@
 
 class TestApdmReader:
     def test(self, apdm_file):
-        res = ReadApdmH5("Lumbar", gravity_acceleration=9.81).predict(file=apdm_file)
+        res = ReadApdmH5("Lumbar", localize_timestamps=True, gravity_acceleration=9.81).predict(file=apdm_file)
 
         lumbar_sens = "XI-010284"
         with h5py.File(apdm_file) as f:
             acc = f["Sensors"][lumbar_sens]["Accelerometer"][()] / 9.81
-            time = f["Sensors"][lumbar_sens]["Time"][()] / 1e6  # to seconds
+            time = f["Sensors"][lumbar_sens]["Time"][()] / 1e6 - 4 * 3600  # to seconds, convert to local
             gyro = f["Sensors"][lumbar_sens]["Gyroscope"][()]
             temp = f["Sensors"][lumbar_sens]["Temperature"][()]