This PR introduces a suite of unit tests for accum(), scan(), scan_by_key(), and where() located within the within the vector algorithms directory. This PR also resolves issues from the inclusive_scan_operations.py file, specifically with calling particular functions, which spilled up to C++ resolution for scan_by_key.
Bug Resolution: Fixed c_type calling for the methods themselves. Scan_by_key was calling scan.name incorrectly, similar issue with the where() function. Additionally, the specific error raised by scan_by_key had to be resolved in the c++ origin file.
General Functionality: Tests confirm that the library accurately handles tests across various array shapes and dimensions, ensuring these operations perform correctly from scalars up to four-dimensional arrays. This encompasses verifying the maintenance of result dimensions in accordance with input shapes.
Data Type and Edge Case Handling: The library's robustness is tested against a comprehensive set of data types including integers, floating-points, and complex numbers (where applicable), affirming operation compatibility and precision. Additionally, scenarios involving shape mismatches, negative dimensions, and zero-sized arrays are explored (granted these cause segfaults), expecting runtime errors to prevent undefined behaviors.
This PR introduces a suite of unit tests for accum(), scan(), scan_by_key(), and where() located within the within the vector algorithms directory. This PR also resolves issues from the inclusive_scan_operations.py file, specifically with calling particular functions, which spilled up to C++ resolution for scan_by_key.
Bug Resolution: Fixed c_type calling for the methods themselves. Scan_by_key was calling scan.name incorrectly, similar issue with the where() function. Additionally, the specific error raised by scan_by_key had to be resolved in the c++ origin file.
General Functionality: Tests confirm that the library accurately handles tests across various array shapes and dimensions, ensuring these operations perform correctly from scalars up to four-dimensional arrays. This encompasses verifying the maintenance of result dimensions in accordance with input shapes.
Data Type and Edge Case Handling: The library's robustness is tested against a comprehensive set of data types including integers, floating-points, and complex numbers (where applicable), affirming operation compatibility and precision. Additionally, scenarios involving shape mismatches, negative dimensions, and zero-sized arrays are explored (granted these cause segfaults), expecting runtime errors to prevent undefined behaviors.