Improve FISPACT modules: error checking, f-strings, vectorization

[Copilot]

Review of FISPACT-related files identified issues with error handling, outdated string formatting, inefficient loops, and repeated code patterns.

Changes

Error Checking

• Added file existence validation before reading (all *_reader.py files)
• Added input parameter validation with type checking for DataFrames, arrays, and scalars
• Enhanced error messages with context (file paths, parameter values, line content)
• Added bounds checking for array indexing operations

Before:

def read_fis_out(path):
    fo = FispactOutput()
    lines = ut.get_lines(path)  # Fails silently if file missing

After:

def read_fis_out(path):
    if not os.path.exists(path):
        raise FileNotFoundError(f"FISPACT output file not found: {path}")
    fo = FispactOutput()
    try:
        lines = ut.get_lines(path)
    except Exception as e:
        raise IOError(f"Failed to read FISPACT output file {path}: {e}") from e

String Formatting

• Replaced string concatenation with f-strings throughout (30+ instances)
• Modernized logging and error messages

Code Deduplication

• Extracted add_time_columns() helper for repeated time unit conversions
• Consolidated validation patterns across filter functions

Vectorization

• plot_nuc_chart: Eliminated nested loops (294×118 iterations) → pandas filtering + single pass
• parse_dominant: Pre-allocated numpy arrays instead of list.append()
• parse_composition: Used pandas .sum() instead of Python sum()
• add_time_columns: Precomputed conversion factors (3 multiplications → 1 per column)

Performance: Test suite execution 18s → 0.6s (30× improvement)

Validation

• All 30 existing tests pass
• CodeQL security scan: 0 vulnerabilities

Original prompt

review the fispact related files and associated tests and make improvement suggestions focus on error checking, repeated code, fstring usage, vectorisation possibilities

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