Showing 59 of 59 total issues
File graph.py
has 488 lines of code (exceeds 250 allowed). Consider refactoring. Open
## graph.py## Copyright (c) 2016-2023 Junpei Kawamoto#
Function psi
has a Cognitive Complexity of 24 (exceeds 5 allowed). Consider refactoring. Open
def psi(u_label: UserLabel, p_label: ProductLabel, r_label: ReviewLabel, epsilon: float) -> float: """Likelihood of a pair of user and product. The likelihood is dependent on the review of the user gives the product. The review is one of {+, -}. We defined constant representing "+" and "-",
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Cyclomatic complexity is too high in function psi. (15) Open
def psi(u_label: UserLabel, p_label: ProductLabel, r_label: ReviewLabel, epsilon: float) -> float: """Likelihood of a pair of user and product. The likelihood is dependent on the review of the user gives the product. The review is one of {+, -}. We defined constant representing "+" and "-",
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Cyclomatic complexity is too high in method update. (10) Open
def update(self) -> float: """Update reviewers' anomalous scores and products' summaries. For each user :math:`u`, update messages to every product :math:`p` the user reviews. The message function :math:`m_{u\\rightarrow p}`
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Function update
has a Cognitive Complexity of 18 (exceeds 5 allowed). Consider refactoring. Open
def update(self) -> float: """Update reviewers' anomalous scores and products' summaries. For each user :math:`u`, update messages to every product :math:`p` the user reviews. The message function :math:`m_{u\\rightarrow p}`
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Function add_review
has 5 arguments (exceeds 4 allowed). Consider refactoring. Open
def add_review(self, reviewer: Reviewer, product: Product, rating: float, *_args: Any, **_kwargs: Any) -> Review:
Avoid too many return
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return epsilon
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return 2 * epsilon
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return 1 - 2 * epsilon
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return 1 - epsilon
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:data:`ReviewLabel.PLUS<fraud_eagle.labels.ReviewLabel.PLUS>` is returned.
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where :math:`u` and :math:`p` is the user and the product, respectively.
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diffs.append(abs(np.exp(review.user_to_product(p_label)) - np.exp(updated)))
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message_to_user[u_label] = self._update_product_to_user(reviewer, product, u_label)
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"""Compute an updated message from a user to a product with a product label.
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\\phi_{i}^{\\cal{U}}: \\cal{L}_{\\cal{U}} \\rightarrow \\mathbb{R}_{\\geq 0},
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diffs.append(abs(np.exp(review.product_to_user(u_label)) - np.exp(updated)))
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\\phi_{j}^{\\cal{P}}: \\cal{L}_{\\cal{P}} \\rightarrow \\mathbb{R}_{\\geq 0},
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where :math:`u` and :math:`p` is the user and the product, respectively.
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def add_review(self, reviewer: Reviewer, product: Product, rating: float, *_args: Any, **_kwargs: Any) -> Review:
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