maths/matrices/utils.py

"""
Utility functions for matrix parsing and formatting in Gradio applications.
"""
import gradio as gr
import numpy as np
import json
from typing import Union

def parse_matrix(matrix_str: str, allow_empty_rows_cols=False) -> np.ndarray:
    try:
        m = json.loads(matrix_str)
        arr = np.array(m, dtype=float)
        if not allow_empty_rows_cols and (arr.shape[0] == 0 or (arr.ndim > 1 and arr.shape[1] == 0)):
            raise ValueError("Matrix cannot have zero rows or columns.")
        if arr.ndim == 1 and arr.shape[0] > 0:
            arr = arr.reshape(1, -1)
        elif arr.ndim == 0 and not allow_empty_rows_cols:
            raise ValueError("Input is a scalar, not a matrix.")
        return arr
    except (json.JSONDecodeError, TypeError, ValueError) as e_json:
        try:
            rows = [list(map(float, row.split(','))) for row in matrix_str.split(';') if row.strip()]
            if not rows and not allow_empty_rows_cols:
                raise ValueError("Matrix input is empty.")
            if not rows and allow_empty_rows_cols:
                return np.array([])
            if len(rows) > 1:
                first_row_len = len(rows[0])
                if not all(len(r) == first_row_len for r in rows):
                    raise ValueError("All rows must have the same number of columns.")
            arr = np.array(rows, dtype=float)
            if not allow_empty_rows_cols and (arr.shape[0] == 0 or (arr.ndim > 1 and arr.shape[1] == 0)):
                raise ValueError("Matrix cannot have zero rows or columns after parsing.")
            return arr
        except ValueError as e_csv:
            raise gr.Error(f"Invalid matrix format. Use JSON (e.g., [[1,2],[3,4]]) or comma/semicolon (e.g., 1,2;3,4). Error: {e_csv} (Original JSON error: {e_json})")
        except Exception as e_gen:
            raise gr.Error(f"General error parsing matrix: {e_gen}")

def format_output(data: Union[np.ndarray, float, str]) -> str:
    if isinstance(data, np.ndarray):
        return str(data.tolist())
    elif isinstance(data, (float, int, str)):
        return str(data)
    return "Output type not recognized."