Location
src/fastcs_catio/utils.py - average() function (lines 107-110)
Current Implementation
The average() function iterates over each field in a numpy structured array and computes the mean individually:
mean_array = np.empty(1, dtype=array.dtype)
for field in array.dtype.fields:
mean_array[field] = np.mean(array[field])
return mean_array
Suggested Improvements
1. Vectorize the averaging operation
The current loop-based approach could be replaced with a single numpy call to improve performance. Consider using numpy.mean() with structured array views or np.lib.recfunctions utilities.
2. Async exception reporting
Investigate and implement proper exception reporting for async tasks that use this function. Currently, exceptions may be silently swallowed.
References
See TODO comments at lines 108-109 in utils.py
Location
src/fastcs_catio/utils.py -
average()function (lines 107-110)Current Implementation
The
average()function iterates over each field in a numpy structured array and computes the mean individually:Suggested Improvements
1. Vectorize the averaging operation
The current loop-based approach could be replaced with a single numpy call to improve performance. Consider using
numpy.mean()with structured array views ornp.lib.recfunctionsutilities.2. Async exception reporting
Investigate and implement proper exception reporting for async tasks that use this function. Currently, exceptions may be silently swallowed.
References
See TODO comments at lines 108-109 in utils.py