Fix to take into account real acquisition times when calculating framerate instead of the set interval (which is sometimes inaccurate)

nd2reader/raw_metadata.py

@@ -3,6 +3,7 @@ from nd2reader.common import read_chunk, read_array, read_metadata, parse_date,
 import xmltodict
 import six
 import numpy as np
+import warnings
 
 
 class RawMetadata(object):
@@ -434,6 +435,12 @@ class RawMetadata(object):
         if interval is None or interval <= 0:
             # Use a fallback if it is still not found
             interval = get_from_dict_if_exists('dAvgPeriodDiff', loop)
+        else:
+            avg_interval = get_from_dict_if_exists('dAvgPeriodDiff', loop)
+            if round(avg_interval) != round(interval):
+                warnings.warn("Reported average frame interval (%.1f ms) doesn't match the set interval (%.1f ms). Using the average now." % (avg_interval, interval), RuntimeWarning)
+                interval = avg_interval
+
         if interval is None or interval <= 0:
             # In some cases, both keys are not saved. Then try to calculate it.
             interval = RawMetadata._guess_sampling_from_loops(duration, loop)

nd2reader/reader.py

@@ -177,26 +177,9 @@ class ND2Reader(FramesSequenceND):
             np.ndarray: an array of times in milliseconds.
 
         """
-        if self._timesteps is not None and len(timesteps) > 0:
+        if self._timesteps is not None and len(self._timesteps) > 0:
             return self._timesteps
 
-        timesteps = np.array([])
-        current_time = 0.0
-
-        for loop in self.metadata['experiment']['loops']:
-            if loop['stimulation']:
-                continue
-
-            if loop['sampling_interval'] == 0:
-                # This is a loop were no data is acquired
-                current_time += loop['duration']
-                continue
-
-            timesteps = np.concatenate(
-                (timesteps, np.arange(current_time, current_time + loop['duration'], loop['sampling_interval'])))
-            current_time += loop['duration']
-
-        # if experiment did not finish, number of timesteps is wrong. Take correct amount of leading timesteps.
-        self._timesteps = timesteps[:self.metadata['num_frames']]
+        self._timesteps = np.array(list(self._parser._raw_metadata.acquisition_times), dtype=np.float) * 1000.0
 
         return self._timesteps