Fix Codacy Warnings (#477)
--------- Co-authored-by: Dario Coscia <dariocos99@gmail.com>
This commit is contained in:
committed by
Nicola Demo
parent
e3790e049a
commit
4177bfbb50
@@ -1,11 +1,11 @@
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"""Module for AbstractProblem class"""
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from abc import ABCMeta, abstractmethod
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from copy import deepcopy
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from ..utils import check_consistency
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from ..domain import DomainInterface, CartesianDomain
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from ..condition.domain_equation_condition import DomainEquationCondition
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from copy import deepcopy
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from .. import LabelTensor
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from ..label_tensor import LabelTensor
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from ..utils import merge_tensors
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@@ -20,7 +20,12 @@ class AbstractProblem(metaclass=ABCMeta):
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"""
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def __init__(self):
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"""
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TODO
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:return: _description_
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:rtype: _type_
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"""
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self._discretised_domains = {}
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# create collector to manage problem data
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@@ -42,16 +47,33 @@ class AbstractProblem(metaclass=ABCMeta):
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@property
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def batching_dimension(self):
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"""
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TODO
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:return: _description_
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:rtype: _type_
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"""
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return self._batching_dimension
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@batching_dimension.setter
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def batching_dimension(self, value):
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"""
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TODO
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:return: _description_
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:rtype: _type_
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"""
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self._batching_dimension = value
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# TODO this should be erase when dataloading will interface collector,
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# kept only for back compatibility
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# back compatibility 0.1
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@property
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def input_pts(self):
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"""
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TODO
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:return: _description_
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:rtype: _type_
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"""
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to_return = {}
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for cond_name, cond in self.conditions.items():
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if hasattr(cond, "input"):
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@@ -62,6 +84,12 @@ class AbstractProblem(metaclass=ABCMeta):
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@property
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def discretised_domains(self):
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"""
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TODO
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:return: _description_
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:rtype: _type_
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"""
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return self._discretised_domains
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def __deepcopy__(self, memo):
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@@ -90,10 +118,7 @@ class AbstractProblem(metaclass=ABCMeta):
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:rtype: bool
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"""
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return all(
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[
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domain in self.discretised_domains
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for domain in self.domains.keys()
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]
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domain in self.discretised_domains for domain in self.domains
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)
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@property
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@@ -127,7 +152,6 @@ class AbstractProblem(metaclass=ABCMeta):
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"""
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The output variables of the problem.
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"""
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pass
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@property
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@abstractmethod
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@@ -153,7 +177,7 @@ class AbstractProblem(metaclass=ABCMeta):
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chebyshev sampling, ``chebyshev``; grid sampling ``grid``.
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:param variables: variable(s) to sample, defaults to 'all'.
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:type variables: str | list[str]
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:param domains: problem's domain from where to sample, defaults to 'all'.
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:param domains: Domain from where to sample, defaults to 'all'.
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:type domains: str | list[str]
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:Example:
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@@ -162,11 +186,12 @@ class AbstractProblem(metaclass=ABCMeta):
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>>> pinn.discretise_domain(n=10, mode='grid', variables=['x'])
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.. warning::
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``random`` is currently the only implemented ``mode`` for all geometries, i.e.
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``EllipsoidDomain``, ``CartesianDomain``, ``SimplexDomain`` and the geometries
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compositions ``Union``, ``Difference``, ``Exclusion``, ``Intersection``. The
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modes ``latin`` or ``lh``, ``chebyshev``, ``grid`` are only implemented for
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``CartesianDomain``.
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``random`` is currently the only implemented ``mode`` for all
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geometries, i.e. ``EllipsoidDomain``, ``CartesianDomain``,
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``SimplexDomain`` and the geometries compositions ``Union``,
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``Difference``, ``Exclusion``, ``Intersection``. The
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modes ``latin`` or ``lh``, ``chebyshev``, ``grid`` are only
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implemented for ``CartesianDomain``.
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"""
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# check consistecy n, mode, variables, locations
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