refactor(reader): extract qc code out of _read_device into own function

src/actipy/reader.py

@@ -59,15 +59,20 @@ def read_device(input_file,
     # NOTE: Using process() increases data ref count by 1, which increases
     # memory. So instead we just do everything here.
 
-    sample_rate = info['SampleRate']
+    # Basic quality control
+    timer.start("Quality control...")
+    data, info_qc = qc(data, info['SampleRate'])
+    info_qc['ReadErrors'] += info['ReadErrors']
+    info.update(info_qc)
+    timer.stop()
 
     if len(data) == 0:
         print("File is empty. No data to process.")
         return data, info
 
     if lowpass_hz not in (None, False):
         timer.start("Lowpass filter...")
-        data, info_lowpass = P.lowpass(data, sample_rate, lowpass_hz)
+        data, info_lowpass = P.lowpass(data, info['SampleRate'], lowpass_hz)
         info.update(info_lowpass)
         timer.stop()
 
@@ -86,7 +91,7 @@ def read_device(input_file,
     if resample_hz not in (None, False):
         timer.start("Resampling...")
         if resample_hz in ('uniform', True):
-            data, info_resample = P.resample(data, sample_rate)
+            data, info_resample = P.resample(data, info['SampleRate'])
         else:
             data, info_resample = P.resample(data, resample_hz)
         info.update(info_resample)
@@ -164,6 +169,54 @@ def process(data, sample_rate,
     return data, info
 
 
+def qc(data, sample_rate):
+    """ Basic quality control. Returns a dict with general info. Also checks and
+    corrects for non-increasing timestamps.
+    """
+
+    info = {}
+
+    if len(data) == 0:
+        info['NumTicks'] = 0
+        info['StartTime'] = None
+        info['EndTime'] = None
+        info['WearTime(days)'] = 0
+        info['NumInterrupts'] = 0
+        info['ReadErrors'] = 0
+        return info
+
+    # Start/end times, wear time, interrupts
+    tol = pd.Timedelta('1s')
+    tdiff = data.index.diff()
+    total_wear = tdiff[tdiff < tol].sum().total_seconds()
+    num_interrupts = (tdiff > tol).sum()
+    time_format = "%Y-%m-%d %H:%M:%S"
+    info['NumTicks'] = len(data)
+    info['StartTime'] = data.index[0].strftime(time_format)
+    info['EndTime'] = data.index[-1].strftime(time_format)
+    info['WearTime(days)'] = total_wear / (60 * 60 * 24)
+    info['NumInterrupts'] = num_interrupts
+
+    # Check for non-increasing timestamps. This is rare but can happen with
+    # buggy devices. TODO: Parser should do this.
+    errs = (tdiff <= pd.Timedelta(0)).sum()
+    del tdiff  # we're done with this
+    if errs > 0:
+        print("Found non-increasing data timestamps. Fixing...")
+        data = data[data
+                    .index
+                    .to_series()
+                    .cummax()
+                    .diff()
+                    .fillna(pd.Timedelta(1))
+                    .gt(pd.Timedelta(0))]
+        info['ReadErrors'] = int(np.ceil(errs / sample_rate))
+    else:
+        info['ReadErrors'] = 0
+
+    return data, info
+
+
 def _read_device(input_file, verbose=True):
     """ Internal function that interfaces with the Java parser to read the
     device file. Returns parsed data as a pandas dataframe, and a dict with
@@ -204,44 +257,7 @@ def _read_device(input_file, verbose=True):
         data_mmap = np.load(os.path.join(tmpdir, "data.npy"), mmap_mode='r')
         data = {c: np.asarray(data_mmap[c]) for c in data_mmap.dtype.names}
         data = pd.DataFrame(data, copy=False)
-
-        if len(data) == 0:
-            info['NumTicks'] = 0
-            info['StartTime'] = None
-            info['EndTime'] = None
-            info['WearTime(days)'] = 0
-            info['NumInterrupts'] = 0
-            data.set_index('time', inplace=True)
-            timer.stop()
-            return data, info
-
-        # Check for non-increasing timestamps. This is rare but can happen with
-        # buggy devices. TODO: Parser should do this.
-        errs = (data['time'].diff() <= pd.Timedelta(0)).sum()
-        if errs > 0:
-            print("Found non-increasing data timestamps. Fixing...")
-            data = data[data['time']
-                        .cummax()
-                        .diff()
-                        .fillna(pd.Timedelta(1))
-                        > pd.Timedelta(0)]
-            info['ReadErrors'] += int(np.ceil(errs / info['SampleRate']))
-
-        # Start/end times, wear time, interrupts
-        t = data['time']
-        tol = pd.Timedelta('1s')
-        total_wear = (t.diff().pipe(lambda x: x[x < tol].sum()).total_seconds())
-        num_interrupts = (t.diff() > tol).sum()
-        strftime = "%Y-%m-%d %H:%M:%S"
-        info['NumTicks'] = len(data)
-        info['StartTime'] = t.iloc[0].strftime(strftime)
-        info['EndTime'] = t.iloc[-1].strftime(strftime)
-        info['WearTime(days)'] = total_wear / (60 * 60 * 24)
-        info['NumInterrupts'] = num_interrupts
-        del t
-
         data.set_index('time', inplace=True)
-
         timer.stop()
 
         return data, info