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Identical blocks of code found in 2 locations. Consider refactoring.
Open

        with self.test_session() as sess:
            sess.run(tf.global_variables_initializer())

            self.assertEqual(len(outputs), 2)
            self.assertEqual(outputs[0].eval().shape, (4, 3))
Severity: Major
Found in lib/layer/embedded_gcnn_test.py and 1 other location - About 1 hr to fix
lib/layer/embedded_gcnn_test.py on lines 152..159

Duplicated Code

Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

Tuning

This issue has a mass of 135.

We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

Refactorings

Further Reading

Identical blocks of code found in 2 locations. Consider refactoring.
Open

        with self.test_session() as sess:
            sess.run(tf.global_variables_initializer())

            self.assertEqual(len(outputs), 2)
            self.assertEqual(outputs[0].eval().shape, (4, 3))
Severity: Major
Found in lib/layer/embedded_gcnn_test.py and 1 other location - About 1 hr to fix
lib/layer/embedded_gcnn_test.py on lines 110..117

Duplicated Code

Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

Tuning

This issue has a mass of 135.

We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

Refactorings

Further Reading

Function test_coarsen_adj_with_efficient_pooling has 36 lines of code (exceeds 25 allowed). Consider refactoring.
Open

    def test_coarsen_adj_with_efficient_pooling(self):
        adj = [[0, 1, 1, 0, 0], [1, 0, 0, 1, 0], [1, 0, 0, 1, 0],
               [0, 1, 1, 0, 1], [0, 0, 0, 1, 0]]
        adj = sp.coo_matrix(adj)
        points = np.array([[1, 1], [3, 2], [3, 0], [4, 1], [8, 3]])
Severity: Minor
Found in lib/graph/coarsening_test.py - About 1 hr to fix

    Function __init__ has a Cognitive Complexity of 12 (exceeds 5 allowed). Consider refactoring.
    Open

        def __init__(self, data_dir, dataset, preprocess_algorithm):
        self._data_dir = data_dir
        self.epochs_completed = 0
        self._index_in_epoch = 0
    Severity: Minor
    Found in lib/pipeline/dataset.py - About 1 hr to fix

    Cognitive Complexity

    Cognitive Complexity is a measure of how difficult a unit of code is to intuitively understand. Unlike Cyclomatic Complexity, which determines how difficult your code will be to test, Cognitive Complexity tells you how difficult your code will be to read and comprehend.

    A method's cognitive complexity is based on a few simple rules:

    • Code is not considered more complex when it uses shorthand that the language provides for collapsing multiple statements into one
    • Code is considered more complex for each "break in the linear flow of the code"
    • Code is considered more complex when "flow breaking structures are nested"

    Further reading

    Function __init__ has a Cognitive Complexity of 12 (exceeds 5 allowed). Consider refactoring.
    Open

        def __init__(self,
                 dataset,
                 preprocess_algorithm,
                 augment,
                 batch_size,
    Severity: Minor
    Found in lib/datasets/queue.py - About 1 hr to fix

    Cognitive Complexity

    Cognitive Complexity is a measure of how difficult a unit of code is to intuitively understand. Unlike Cyclomatic Complexity, which determines how difficult your code will be to test, Cognitive Complexity tells you how difficult your code will be to read and comprehend.

    A method's cognitive complexity is based on a few simple rules:

    • Code is not considered more complex when it uses shorthand that the language provides for collapsing multiple statements into one
    • Code is considered more complex for each "break in the linear flow of the code"
    • Code is considered more complex when "flow breaking structures are nested"

    Further reading

    Function test_conv_K2_P4 has 32 lines of code (exceeds 25 allowed). Consider refactoring.
    Open

        def test_conv_K2_P4(self):
        features = [[1, 2], [3, 4], [5, 6], [7, 8]]
        features = tf.constant(features, dtype=tf.float32)

        adj_dist = [[0, 2, 1, 0], [2, 0, 0, 1], [1, 0, 0, 2], [0, 1, 2, 0]]
    Severity: Minor
    Found in lib/layer/embedded_gcnn_test.py - About 1 hr to fix

      Function train has 10 arguments (exceeds 4 allowed). Consider refactoring.
      Open

      def train(model,
      Severity: Major
      Found in lib/model/train.py - About 1 hr to fix

        Function test_coarsen_adj has 29 lines of code (exceeds 25 allowed). Consider refactoring.
        Open

            def test_coarsen_adj(self):
        adj = [[0, 1, 1, 0, 0], [1, 0, 0, 1, 0], [1, 0, 0, 1, 0],
               [0, 1, 1, 0, 1], [0, 0, 0, 1, 0]]
        adj = sp.coo_matrix(adj)
        points = np.array([[1, 1], [3, 2], [3, 0], [4, 1], [8, 3]])
        Severity: Minor
        Found in lib/graph/coarsening_test.py - About 1 hr to fix

          Function __init__ has 9 arguments (exceeds 4 allowed). Consider refactoring.
          Open

              def __init__(self,
          Severity: Major
          Found in lib/layer/var_layer.py - About 1 hr to fix

            Function test_coarsen_clustered_adj has 27 lines of code (exceeds 25 allowed). Consider refactoring.
            Open

                def test_coarsen_clustered_adj(self):
        adj = [[0, 1, 0, 1, 0], [1, 0, 1, 0, 0], [0, 1, 0, 1, 0],
               [1, 0, 1, 0, 1], [0, 0, 0, 1, 0]]
        adj = sp.coo_matrix(adj)
        points = np.array([[1, 1], [3, 1], [3, 3], [1, 3], [0, 8]])
            Severity: Minor
            Found in lib/graph/coarsening_test.py - About 1 hr to fix

              Similar blocks of code found in 2 locations. Consider refactoring.
              Open

                      expected_adj = [
            [0, 1, 1, 1, 0, 0, 0, 0, 1, 0],
            [1, 0, 1, 1, 1, 1, 0, 0, 0, 0],
            [1, 1, 0, 1, 0, 1, 0, 0, 1, 1],
            [1, 1, 1, 0, 0, 0, 0, 0, 0, 0],
              Severity: Major
              Found in lib/segmentation/adjacency_test.py and 1 other location - About 1 hr to fix
              lib/segmentation/adjacency_test.py on lines 39..49

              Duplicated Code

              Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

              Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

              When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

              Tuning

              This issue has a mass of 126.

              We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

              The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

              If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

              See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

              Refactorings

              Further Reading

              Similar blocks of code found in 2 locations. Consider refactoring.
              Open

                      expected_adj = [
            [0, 1, 1, 1, 0, 0, 0, 0, 1, 0],
            [1, 0, 1, 1, 1, 1, 0, 0, 0, 0],
            [1, 1, 0, 1, 0, 1, 0, 0, 1, 0],
            [1, 1, 1, 0, 0, 0, 0, 0, 0, 0],
              Severity: Major
              Found in lib/segmentation/adjacency_test.py and 1 other location - About 1 hr to fix
              lib/segmentation/adjacency_test.py on lines 86..96

              Duplicated Code

              Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

              Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

              When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

              Tuning

              This issue has a mass of 126.

              We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

              The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

              If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

              See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

              Refactorings

              Further Reading

              Function coarsen_adj has 7 arguments (exceeds 4 allowed). Consider refactoring.
              Open

              def coarsen_adj(adj,
              Severity: Major
              Found in lib/graph/coarsening.py - About 50 mins to fix

                Function __init__ has 7 arguments (exceeds 4 allowed). Consider refactoring.
                Open

                    def __init__(self,
                Severity: Major
                Found in lib/model/model.py - About 50 mins to fix

                  Function _coarsen_adj has 7 arguments (exceeds 4 allowed). Consider refactoring.
                  Open

                  def _coarsen_adj(adj,
                  Severity: Major
                  Found in lib/graph/coarsening.py - About 50 mins to fix

                    Function preprocess_spatial_fixed has 7 arguments (exceeds 4 allowed). Consider refactoring.
                    Open

                    def preprocess_spatial_fixed(
                    Severity: Major
                    Found in mnist_spatial.py - About 50 mins to fix

                      Function __init__ has 7 arguments (exceeds 4 allowed). Consider refactoring.
                      Open

                          def __init__(self,
                      Severity: Major
                      Found in lib/layer/embedded_gcnn.py - About 50 mins to fix

                        Function preprocess_pipeline has 7 arguments (exceeds 4 allowed). Consider refactoring.
                        Open

                        def preprocess_pipeline(image,
                        Severity: Major
                        Found in lib/pipeline/preprocess.py - About 50 mins to fix

                          Function __init__ has 7 arguments (exceeds 4 allowed). Consider refactoring.
                          Open

                              def __init__(self,
                          Severity: Major
                          Found in lib/datasets/queue.py - About 50 mins to fix

                            Function receptive_fields has 6 arguments (exceeds 4 allowed). Consider refactoring.
                            Open

                            def receptive_fields(points,
                            Severity: Minor
                            Found in lib/graph/spatial.py - About 45 mins to fix
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