Merge pull request #125 from ghammad/fix/bba

En route to v1.2.1

docs/source/changelog.rst

@@ -8,6 +8,17 @@ What's new
 
 *************
 
+v1.2.1 ("No worries", April 2023)
+-------------------------------------------
+
+This release aims to fix:
+
+* Biobank Accelerometer Analysis file format: support file paths containing numerical characters and/or whitespaces;
+* Actiwatch (CamNtech) file format: fix `issue #123 <https://github.com/ghammad/pyActigraphy/issues/123>`_ by upper casing the UUID.
+* Batch reader: add missing types, 'BBA' and 'MESA'.
+
+*************
+
 v1.2 ("Let's go 3D", March 2023)
 -------------------------------------------
 

docs/source/pyActigraphy-Intro.ipynb

@@ -78,9 +78,12 @@
     "* agd (Actigraph)\n",
     "* atr (ActTrust)\n",
     "* awd (Actiwatch)\n",
+    "* bba (Axivity or GeneActiv via the Biobankaccelerometer package)\n",
     "* dqt (DaqTix)\n",
+    "* mesa (MESA dataset, hosted by the NSRR)\n",
     "* mtn (MotionWatch8)\n",
-    "* rpx (Respironics)\n"
+    "* rpx (Respironics)\n",
+    "* tal (Tempatilumi)\n"
    ]
   },
   {
@@ -92,9 +95,12 @@
     "* read_raw_agd\n",
     "* read_raw_atr\n",
     "* read_raw_awd\n",
+    "* read_raw_bba\n",
     "* read_raw_dqt\n",
+    "* read_raw_mesa\n",
     "* read_raw_mtn\n",
-    "* read_raw_rpx\n"
+    "* read_raw_rpx\n",
+    "* read_raw_tal\n"
    ]
   },
   {

pyActigraphy/__init__.py

@@ -41,4 +41,4 @@
     "viz"
 ]
 
-__version__ = '1.2'
+__version__ = '1.2.1'

pyActigraphy/io/awd/awd.py

@@ -217,7 +217,7 @@ def __extract_awd_model(uuid):
         )
         match = re.match(pattern=r'^([A-Za-z])[0-9a-fA-F]+', string=uuid)
         if match:  # check if UUID matches the expected pattern
-            dcode = match.groups()[0]
+            dcode = match.groups()[0].upper()
             if dcode in RawAWD.device_code.keys():
                 return dcode
             else:

pyActigraphy/io/bba/bba.py

@@ -274,7 +274,7 @@ def __read_baa_metadata_json(input_fname, metadata_fname):
         # - INPUT DATA: input_fname = 'basename'-timeSeries.csv[.gz]
 
         match_basename = re.match(
-            pattern=r'^(\w*)-timeSeries.csv(\.gz)?',
+            pattern=r'^(.+?)-timeSeries.csv(\.gz)?',
             string=os.path.basename(input_fname)
         )
         if match_basename:
@@ -287,7 +287,7 @@ def __read_baa_metadata_json(input_fname, metadata_fname):
 
         if not re.match(
             pattern=r'{}.(cwa|CWA)(\.gz)?'.format(input_basename),
-            string=meta_data['file-name']
+            string=os.path.basename(meta_data['file-name'])
         ):
             raise ValueError(
                 'Attempting to read a metadata file referring to another '

pyActigraphy/io/reader/reader.py

@@ -9,7 +9,9 @@
 from ..agd import read_raw_agd
 from ..atr import read_raw_atr
 from ..awd import read_raw_awd
+from ..bba import read_raw_bba
 from ..dqt import read_raw_dqt
+from ..mesa import read_raw_mesa
 from ..mtn import read_raw_mtn
 from ..rpx import read_raw_rpx
 from ..tal import read_raw_tal
@@ -231,8 +233,10 @@ def read_raw(
 
         * AGD ((w)GT3X(+)), ActiGraph)
         * ATR (ActTrust, Condor Instruments)
-        * AWD (ActiWatch 4, CamNtech)
+        * AWD (ActiWatch 4/7/L/L-Plus/T, CamNtech)
+        * BBA (Biobankaccelerometer)
         * DQT (Daqtometers, Daqtix)
+        * MESA (MESA dataset, NSRR)
         * MTN (MotionWatch8, CamNtech)
         * RPX (Actiwatch, Respironics)
         * TAL (Tempatilumi, CE Brasil)
@@ -257,7 +261,9 @@ def read_raw(
         An object containing raw data
     """
 
-    supported_types = ['AGD', 'ATR', 'AWD', 'DQT', 'MTN', 'RPX', 'TAL']
+    supported_types = [
+        'AGD', 'ATR', 'AWD', 'BBA', 'DQT', 'MESA', 'MTN', 'RPX', 'TAL'
+    ]
     if reader_type not in supported_types:
         raise ValueError(
             'Type {0} unsupported. Supported types: {1}'.format(
@@ -284,9 +290,15 @@ def parallel_reader(
         'AWD': lambda files: parallel_reader(
             n_jobs, read_raw_awd, files, prefer, verbose, **kwargs
         ),
+        'BBA': lambda files: parallel_reader(
+            n_jobs, read_raw_bba, files, prefer, verbose, **kwargs
+        ),
         'DQT': lambda files: parallel_reader(
             n_jobs, read_raw_dqt, files, prefer, verbose, **kwargs
         ),
+        'MESA': lambda files: parallel_reader(
+            n_jobs, read_raw_mesa, files, prefer, verbose, **kwargs
+        ),
         'MTN': lambda files: parallel_reader(
             n_jobs, read_raw_mtn, files, prefer, verbose, **kwargs
         ),