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How to use get_example method in hypothesis

Best Python code snippet using hypothesis

dataset.py

Source:dataset.py

...24        self.return_domain = return_domain25        self.src = src26    def __len__(self):27        return len(self.data)28    def get_example(self, i, r=None):29        x, y = self.data[i]30        if r is None:31            r = np.random.randint(self.n_domain)32        x = imrotate(np.tile(x, (3, 1, 1)), self.rotate[r]).transpose(2, 0, 1)[[0]]33        if self.return_domain:34            return x, y, r35        else:36            return x.astype(np.float32), y.astype(np.int8)37class SVHNDataset(dataset_mixin.DatasetMixin):38    img_size = (28, 28)39    def __init__(self, root=os.path.join(dataset_path, 'SVHN_MNIST'), src='train', size=999999999, k=None):40        if src == 'train':41            mat = io.loadmat(os.path.join(root, 'train_32x32.mat'))42        elif src == 'test':43            mat = io.loadmat(os.path.join(root, 'test_32x32.mat'))44        else:45            raise ValueError46        matx = mat['X'].transpose(2, 3, 0, 1).mean(axis=0)47        maty = mat['y'][:, 0].astype(np.int8)48        if k is None:49            self.x = []50            for x in matx[:size]:51                self.x.append(imresize(x, self.img_size)[np.newaxis, ...])52            self.x = np.array(self.x, dtype=np.float32)53            self.y = maty[:size]54        else:55            self.x, self.y = [], []56            counter = defaultdict(int)57            n, i = 0, 058            while n < k * 10:59                x = imresize(matx[n], self.img_size)[np.newaxis, ...]60                y = maty[n]61                if counter[y] < k:62                    self.x.append(x)63                    self.y.append(y)64                    n += 165                i += 166            self.x = np.array(self.x, dtype=np.float32)67    def __len__(self):68        return 11000#len(self.x)69    def get_example(self, i):70        i = i % len(self.x)71        return self.x[i], self.y[i]72class USPSDataset(dataset_mixin.DatasetMixin):73    img_size = (28, 28)74    n_classes = 1075    def __init__(self):76        mat = io.loadmat('./datasets/usps_all.mat')77        self.data = mat['data']78    def __len__(self):79        return 1100 * 1080    def get_example(self, i):81        ix = i // 1082        y = i % 1083        x = imresize(self.data[:, ix, y].reshape(16, 16), self.img_size)[np.newaxis, ...]84        return x, y85class MNIST_MDataset(dataset_mixin.DatasetMixin):86    img_size = (28, 28)87    n_classes = 1088    def __init__(self, data_root=os.path.join(dataset_path, 'mnist_m'), src='train', transform=None):89        self.transform = transform90        if src == 'train':91            data_list = os.path.join(data_root, 'mnist_m_train_labels.txt')92            self.root = os.path.join(data_root, 'mnist_m_train')93        elif src == 'test':94            data_list = os.path.join(data_root, 'mnist_m_test_labels.txt')95            self.root = os.path.join(data_root, 'mnist_m_test')96        else:97            raise ValueError98        f = open(data_list, 'r')99        data_list = f.readlines()100        f.close()101        self.n_data = len(data_list)102        self.img_paths = []103        self.img_labels = []104        for data in data_list:105            self.img_paths.append(data[:-3])106            self.img_labels.append(data[-2])107    def get_example(self, item):108        img_paths, labels = self.img_paths[item], self.img_labels[item]109        imgs = Image.open(os.path.join(self.root, img_paths)).convert('RGB')110        img = imresize(np.array(imgs), self.img_size).transpose(2, 0, 1).astype(np.float32)111        # nch 3 -> 1112        img = img.mean(axis=0)[np.newaxis, ...]113        if self.transform is not None:114            img = self.transform(img)115        labels = int(labels)116        return img, labels117    def __len__(self):118        return self.n_data119class CrossDomainDigitDataset(dataset_mixin.DatasetMixin):120    img_size = (28, 28)121    n_classes = 10122    def __init__(self, datasets, return_domain=True):123        self.n_domain = len(datasets)124        self.datasets = datasets125        self.return_domain = return_domain126    def get_example(self, i, r=None):127        if r is None:128            r = np.random.randint(self.n_domain)129        x, y = self.datasets[r][i]130        if self.return_domain:131            return x.astype(np.float32), y, r132        else:133            return x.astype(np.float32), y134    def __len__(self):135        return min(map(len, self.datasets))136if __name__ == '__main__':137    # m = RotateMnistDataset()138    # x, y, r = m.get_example(0, r=0)139    # imsave('./png/0.png', np.tile(x.transpose(1, 2, 0), (1, 1, 3)))140    # x, y, r = m.get_example(0, r=1)141    # imsave('./png/1.png', np.tile(x.transpose(1, 2, 0), (1, 1, 3)))142    # x, y, r = m.get_example(0, r=4)143    # imsave('./png/4.png', np.tile(x.transpose(1, 2, 0), (1, 1, 3)))144    mnist_train, test = get_mnist(ndim=3)145    mnist_m = MNIST_MDataset()146    svhn = SVHNDataset()147    usps = USPSDataset()148    digits = CrossDomainDigitDataset(datasets=[mnist_train, mnist_m, svhn, usps])149    print(len(digits))150    x, y, r = digits.get_example(0, r=0)151    print(x.shape, y, r)152    x, y, r = digits.get_example(1, r=1)153    print(x.shape, y, r)154    x, y, r = digits.get_example(2, r=2)155    print(x.shape, y, r)156    x, y, r = digits.get_example(3, r=3)...

metrics_tests.py

Source:metrics_tests.py

...11    averaged_r_squared,12    overall_censored_mape,13    averaged_censored_mape14)15def get_example() -> pd.DataFrame():16    """17    Get example of DataFrame with actual values and predictions.18    :return:19        example DataFrame20    """21    df = pd.DataFrame(22        [[1, 2, 3],23         [1, 4, 5],24         [2, 10, 8],25         [2, 8, 10]],26        columns=['key', 'actual_value', 'prediction']27    )28    return df29class TestMetrics(unittest.TestCase):30    """31    Tests of evaluational metrics.32    """33    def test_overall_r_squared(self) -> type(None):34        """35        Test `overall_r_squared` function.36        :return:37            None38        """39        df = get_example()40        score = overall_r_squared(df)41        self.assertEquals(score, 0.75)42    def test_averaged_r_squared(self) -> type(None):43        """44        Test `averaged_r_squared` function.45        :return:46            None47        """48        df = get_example()49        score = averaged_r_squared(df, ['key'])50        self.assertEquals(score, -1.5)51    def test_overall_censored_mape(self) -> type(None):52        """53        Test `overall_censored_mape` function.54        :return:55            None56        """57        df = get_example()58        score = overall_censored_mape(df)59        self.assertEquals(score, 30)60    def test_overall_censored_mape_with_zeros(self) -> type(None):61        """62        Test correct work of `overall_censored_mape` function63        with zero forecasts made for zero actual values.64        :return:65            None66        """67        first_df = get_example()68        second_df = pd.DataFrame(69            [[3, 0, 0],70             [3, 0, 0],71             [4, 0, 0],72             [4, 0, 0]],73            columns=['key', 'actual_value', 'prediction']74        )75        df = pd.concat([first_df, second_df])76        score = overall_censored_mape(df)77        self.assertEquals(score, 15)78    def test_overall_censored_mape_with_missings(self) -> type(None):79        """80        Test correct work of `overall_censored_mape` function81        with some values missed.82        :return:83            None84        """85        df = get_example()86        df.loc[0, 'prediction'] = None87        df.loc[1, 'actual_value'] = np.nan88        score = overall_censored_mape(df)89        self.assertEquals(score, 22.5)90    def test_averaged_censored_mape(self) -> type(None):91        """92        Test `averaged_r_censored_mape` function.93        :return:94            None95        """96        df = get_example()97        score = averaged_censored_mape(df, ['key'])98        self.assertEquals(score, 30)99    def test_averaged_censored_mape_with_empty_series(self) -> type(None):100        """101        Test correct work of `overall_censored_mape` function102        with DataFrame that contains an empty time series.103        :return:104            None105        """106        df = get_example()107        df.loc[0, 'prediction'] = None108        df.loc[1, 'actual_value'] = np.nan109        score = averaged_censored_mape(df, ['key'])110        self.assertEquals(score, 22.5)111def main():112    test_loader = unittest.TestLoader()113    suites_list = []114    testers = [115        TestMetrics()116    ]117    for tester in testers:118        suite = test_loader.loadTestsFromModule(tester)119        suites_list.append(suite)120    overall_suite = unittest.TestSuite(suites_list)...

dataset_mixin.py

Source:dataset_mixin.py

...29           ...     def __init__(self, values):30           ...         self.values = values31           ...     def __len__(self):32           ...         return len(self.values)33           ...     def get_example(self, i):34           ...         return self.values[i]35           ...36           >>> ds = SimpleDataset([0, 1, 2, 3, 4, 5])37           >>> ds[1]   # Access by int38           139           >>> ds[1:3]  # Access by slice40           [1, 2]41           >>> ds[[4, 0]]  # Access by one-dimensional integer list42           [4, 0]43           >>> index = numpy.arange(3)44           >>> ds[index]  # Access by one-dimensional integer numpy.ndarray45           [0, 1, 2]46        """47        if isinstance(index, slice):48            current, stop, step = index.indices(len(self))49            return [self.get_example(i) for i in50                    six.moves.range(current, stop, step)]51        elif isinstance(index, list) or isinstance(index, numpy.ndarray):52            return [self.get_example(i) for i in index]53        else:54            return self.get_example(index)55    def __len__(self):56        """Returns the number of data points."""57        raise NotImplementedError58    def get_example(self, i):59        """Returns the i-th example.60        Implementations should override it. It should raise :class:`IndexError`61        if the index is invalid.62        Args:63            i (int): The index of the example.64        Returns:65            The i-th example.66        """...

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