| 32 | |
| 33 | |
| 34 | class OptimalityTestMatrix(object): |
| 35 | def __init__(self, ivs=None, verbose=False): |
| 36 | """ |
| 37 | Initilize a test matrix. To run it, see run(). |
| 38 | :param ivs: A dictionary mapping each test name to its |
| 39 | iterable of Intervals. |
| 40 | :type ivs: None or dict of [str, list of Interval] |
| 41 | :param verbose: Whether to print the structure of the trees |
| 42 | :type verbose: bool |
| 43 | """ |
| 44 | self.verbose = verbose |
| 45 | |
| 46 | # set test_tupes |
| 47 | self.test_types = {} |
| 48 | # all methods beginning with "test_" |
| 49 | test_names = [ |
| 50 | name for name in self.__class__.__dict__ |
| 51 | if |
| 52 | callable(getattr(self, name)) and |
| 53 | name.startswith('test_') |
| 54 | ] |
| 55 | for test_name in test_names: |
| 56 | key = test_name[len('test_'):] |
| 57 | key = ' '.join(key.split('_')) |
| 58 | test_function = getattr(self, test_name) |
| 59 | self.test_types[key] = test_function |
| 60 | |
| 61 | # set ivs |
| 62 | self.ivs = { |
| 63 | key: [Interval(*tup) for tup in value.data] |
| 64 | for key, value in data.__dict__.items() |
| 65 | if 'copy_structure' not in key and hasattr(value, 'data') |
| 66 | } |
| 67 | |
| 68 | # initialize result matrix |
| 69 | self.result_matrix = { |
| 70 | 'ivs name': {}, |
| 71 | 'test type': {} |
| 72 | } |
| 73 | for name in self.ivs: |
| 74 | self.result_matrix['ivs name'][name] = {} |
| 75 | for name in self.test_types: |
| 76 | self.result_matrix['test type'][name] = {} |
| 77 | self.summary_matrix = deepcopy(self.result_matrix) |
| 78 | |
| 79 | def test_init(self, ivs): |
| 80 | t = IntervalTree(ivs) |
| 81 | return t |
| 82 | |
| 83 | def test_add_ascending(self, ivs): |
| 84 | if self.verbose: |
| 85 | pbar = ProgressBar(len(ivs)) |
| 86 | t = IntervalTree() |
| 87 | for iv in sorted(ivs): |
| 88 | t.add(iv) |
| 89 | if self.verbose: pbar() |
| 90 | return t |
| 91 |
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