Feature/nsrr

pyActigraphy/__init__.py

@@ -41,4 +41,4 @@
     "viz"
 ]
 
-__version__ = '1.2.2'
+__version__ = '1.2.3'

pyActigraphy/io/__init__.py

@@ -19,6 +19,7 @@
 from .dqt import read_raw_dqt
 from .mesa import read_raw_mesa
 from .mtn import read_raw_mtn
+from .nsrr import read_raw_nsrr
 from .rpx import read_raw_rpx
 from .tal import read_raw_tal
 
@@ -32,6 +33,7 @@
     "read_raw_dqt",
     "read_raw_mesa",
     "read_raw_mtn",
+    "read_raw_nsrr"
     "read_raw_rpx",
     "read_raw_tal"
 ]

pyActigraphy/io/nsrr/__init__.py

@@ -0,0 +1,11 @@
+"""Module to read generic NSRR files."""
+
+# Author: Grégory Hammad <gregory.hammad@uliege.be>
+#
+# License: BSD (3-clause)
+
+from .nsrr import RawNSRR
+
+from .nsrr import read_raw_nsrr
+
+__all__ = ["RawNSRR", "read_raw_nsrr"]

pyActigraphy/io/nsrr/nsrr.py

@@ -0,0 +1,238 @@
+import pandas as pd
+import os
+import warnings
+
+from ..base import BaseRaw
+from pyActigraphy.light import LightRecording
+
+
+class RawNSRR(BaseRaw):
+    r"""Raw object from generic NSRR files
+
+    Parameters
+    ----------
+    input_fname: str
+        Path to the NSRR file.
+    time_origin: datetime-like
+        Time origin of the timestamps.
+        Required as the NSRR files do not contain date informations.
+        Default is '2000-01-01'
+    start_time: datetime-like, optional
+        Read data from this time.
+        Default is None.
+    period: str, optional
+        Length of the read data.
+        Cf. #timeseries-offset-aliases in
+        <https://pandas.pydata.org/pandas-docs/stable/timeseries.html>.
+        Default is None (i.e all the data).
+    intervals: dict, optional
+        Map manually annotated periods to specific scores.
+        If set to None, the names of the annotated periods is returned instead.
+        Default is {'EXCLUDED': -1, 'ACTIVE': 1, 'REST': 0.5, 'REST-S': 0}.
+    check_dayofweek: bool, optional
+        If set to True, check if the day of the week reported in the original
+        recoring is aligned with the reconstructed index.
+        Default is False.
+    """
+
+    def __init__(
+        self,
+        input_fname,
+        time_origin='2000-01-01',
+        start_time=None,
+        period=None,
+        intervals={'EXCLUDED': -1, 'ACTIVE': 1, 'REST': 0.5, 'REST-S': 0},
+        check_dayofweek=False
+    ):
+
+        # get absolute file path
+        input_fname = os.path.abspath(input_fname)
+
+        # read file
+        data = pd.read_csv(input_fname, index_col='line')
+
+        # extract informations from the header
+        name = data.iloc[1, 0]
+
+        # set additional informations manually
+        uuid = None
+        freq = pd.Timedelta(30, unit='s')
+
+        # day of the week
+        self.__dayofweek = data['dayofweek']
+
+        # reconstruct NSRR datetime index
+        date = pd.to_datetime(
+            data['daybymidnight'] - 1 + data.loc[1, 'dayofweek'],
+            unit='D',
+            origin=time_origin
+        ).astype(str)
+        time = data['linetime']
+
+        index = pd.DatetimeIndex(date + ' ' + time, freq='infer')
+
+        data.set_index(index, inplace=True)
+
+        if check_dayofweek:
+            # Shift day of the week to match Pandas' convention (0=Monday, etc)
+            dw = self.__dayofweek - 2
+            if (data.index.dayofweek - dw.where(dw >= 0, dw + 7)).sum() != 0:
+                warnings.warn((
+                    "Specified time_origin is such that the day of the week in"
+                    " the reconstructed time index is *not* aligned with the"
+                    " day of the week reported in the recording."
+                ))
+
+        # set start and stop times
+        if start_time is not None:
+            start_time = pd.to_datetime(start_time)
+        else:
+            start_time = data.index[0]
+
+        if period is not None:
+            period = pd.Timedelta(period)
+            stop_time = start_time+period
+        else:
+            stop_time = data.index[-1]
+            period = stop_time - start_time
+
+        data = data[start_time:stop_time]
+
+        # no wear indicator
+        self.__nowear = data['offwrist']
+
+        # event marker indicator
+        self.__marker = data['marker']
+
+        # LIGHT
+        self.__white_light = data['whitelight']
+        self.__red_light = data['redlight']
+        self.__green_light = data['greenlight']
+        self.__blue_light = data['bluelight']
+
+        # wake indicator
+        self.__wake = data['wake']
+
+        # intervals
+        if intervals is not None:
+            self.__intervals = data['interval'].map(intervals)
+        else:
+            self.__intervals = data['interval']
+
+        # call __init__ function of the base class
+        super().__init__(
+            fpath=input_fname,
+            name=name,
+            uuid=uuid,
+            format='NSRR',
+            axial_mode='tri-axial',
+            start_time=start_time,
+            period=period,
+            frequency=freq,
+            data=data['activity'],
+            light=LightRecording(
+                name=name,
+                uuid=uuid,
+                data=data.loc[:, [
+                    'whitelight', 'redlight', 'greenlight', 'bluelight'
+                    ]
+                ],
+                frequency=data.index.freq
+            )
+        )
+
+    @property
+    def marker(self):
+        r"""Event marker indicator."""
+        return self.__marker
+
+    @property
+    def wake(self):
+        r"""Awake indicator."""
+        return self.__wake
+
+    @property
+    def nowear(self):
+        r"""Off-wrist indicator."""
+        return self.__nowear
+
+    @property
+    def intervals(self):
+        r"""Interval type (manual rest-activty scoring)."""
+        return self.__intervals
+
+    @property
+    def dayofweek(self):
+        r"""Day of the week (1=Sunday, 2=Monday, etc)."""
+        return self.__dayofweek
+
+    @property
+    def white_light(self):
+        r"""Value of the white light illuminance in lux."""
+        return self.__white_light
+
+    @property
+    def red_light(self):
+        r"""Value of the light intensity in µw/cm²."""
+        return self.__red_light
+
+    @property
+    def green_light(self):
+        r"""Value of the light intensity in µw/cm²."""
+        return self.__green_light
+
+    @property
+    def blue_light(self):
+        r"""Value of the light intensity in µw/cm²."""
+        return self.__blue_light
+
+
+def read_raw_nsrr(
+    input_fname,
+    time_origin='2000-01-01',
+    start_time=None,
+    period=None,
+    intervals={'EXCLUDED': -1, 'ACTIVE': 1, 'REST': 0.5, 'REST-S': 0},
+    check_dayofweek=False
+):
+    r"""Reader function for generic NSRR files
+
+    Parameters
+    ----------
+    input_fname: str
+        Path to the ActTrust file.
+    time_origin: datetime-like
+        Time origin of the timestamps.
+        Required as the NSRR files do not contain date informations.
+        Default is '2000-01-01'
+    start_time: datetime-like, optional
+        Read data from this time.
+        Default is None.
+    period: str, optional
+        Length of the read data.
+        Cf. #timeseries-offset-aliases in
+        <https://pandas.pydata.org/pandas-docs/stable/timeseries.html>.
+        Default is None (i.e all the data).
+    intervals: dict, optional
+        Map manually annotated periods to specific scores.
+        If set to None, the names of the annotated periods is returned instead.
+        Default is {'EXCLUDED': -1, 'ACTIVE': 1, 'REST': 0.5, 'REST-S': 0}.
+    check_dayofweek: bool, optional
+        If set to True, check if the day of the week reported in the original
+        recoring is aligned with the reconstructed index.
+        Default is False.
+
+    Returns
+    -------
+    raw : Instance of RawNSRR
+        An object containing raw NSRR data
+    """
+
+    return RawNSRR(
+        input_fname=input_fname,
+        time_origin=time_origin,
+        start_time=start_time,
+        period=period,
+        intervals=intervals,
+        check_dayofweek=check_dayofweek
+    )

pyActigraphy/io/reader/reader.py

@@ -13,6 +13,7 @@
 from ..dqt import read_raw_dqt
 from ..mesa import read_raw_mesa
 from ..mtn import read_raw_mtn
+from ..nsrr import read_raw_nsrr
 from ..rpx import read_raw_rpx
 from ..tal import read_raw_tal
 from pyActigraphy.log import read_sst_log
@@ -238,6 +239,7 @@ def read_raw(
         * DQT (Daqtometers, Daqtix)
         * MESA (MESA dataset, NSRR)
         * MTN (MotionWatch8, CamNtech)
+        * NSRR (generic file, NSRR)
         * RPX (Actiwatch, Respironics)
         * TAL (Tempatilumi, CE Brasil)
 
@@ -262,7 +264,7 @@ def read_raw(
     """
 
     supported_types = [
-        'AGD', 'ATR', 'AWD', 'BBA', 'DQT', 'MESA', 'MTN', 'RPX', 'TAL'
+        'AGD', 'ATR', 'AWD', 'BBA', 'DQT', 'MESA', 'MTN', 'NSRR', 'RPX', 'TAL'
     ]
     if reader_type not in supported_types:
         raise ValueError(
@@ -302,6 +304,9 @@ def parallel_reader(
         'MTN': lambda files: parallel_reader(
             n_jobs, read_raw_mtn, files, prefer, verbose, **kwargs
         ),
+        'NSRR': lambda files: parallel_reader(
+            n_jobs, read_raw_nsrr, files, prefer, verbose, **kwargs
+        ),        
         'RPX': lambda files: parallel_reader(
             n_jobs, read_raw_rpx, files, prefer, verbose, **kwargs
         ),