How to use get_example method in hypothesis

Best Python code snippet using hypothesis

dataset.py

Source: dataset.py Github

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...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)...

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metrics_tests.py

Source: metrics_tests.py Github

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...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)...

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dataset_mixin.py

Source: dataset_mixin.py Github

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...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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