Normalizes a 1D array, between ranges 0-cap. Args: array: List containing values to be normalized between cap range. cap: Maximum cap amount for normalization. Returns: return 1D numpy array, corresponding to limited range array Examples: >>> normalize_a
(array: np.ndarray, cap: float = 1)
| 50 | |
| 51 | |
| 52 | def normalize_array(array: np.ndarray, cap: float = 1) -> np.ndarray: |
| 53 | """Normalizes a 1D array, between ranges 0-cap. |
| 54 | |
| 55 | Args: |
| 56 | array: List containing values to be normalized between cap range. |
| 57 | cap: Maximum cap amount for normalization. |
| 58 | Returns: |
| 59 | return 1D numpy array, corresponding to limited range array |
| 60 | |
| 61 | Examples: |
| 62 | >>> normalize_array(np.array([2, 3, 5, 7])) |
| 63 | array([0. , 0.2, 0.6, 1. ]) |
| 64 | >>> normalize_array(np.array([[5], [7], [11], [13]])) |
| 65 | array([[0. ], |
| 66 | [0.25], |
| 67 | [0.75], |
| 68 | [1. ]]) |
| 69 | """ |
| 70 | diff = np.max(array) - np.min(array) |
| 71 | return (array - np.min(array)) / (1 if diff == 0 else diff) * cap |
| 72 | |
| 73 | |
| 74 | def grayscale(image: np.ndarray) -> np.ndarray: |