folivo/PINA
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

Fix Codacy Warnings (#477)

Browse Source 
---------

Co-authored-by: Dario Coscia <dariocos99@gmail.com>
This commit is contained in:
Filippo Olivo
2025-03-10 15:38:45 +01:00
committed by Nicola Demo
parent e3790e049a
commit 4177bfbb50
157 changed files with 3473 additions and 3839 deletions
Download Patch File Download Diff File Expand all files Collapse all files

33
pina/domain/cartesian.py
View File

@@ -1,4 +1,5 @@
import torch
"""Module for CartesianDomain class."""
import torch
from .domain_interface import DomainInterface
@@ -46,7 +47,8 @@ class CartesianDomain(DomainInterface):
def update(self, new_domain):
"""Adding new dimensions on the ``CartesianDomain``
:param CartesianDomain new_domain: A new ``CartesianDomain`` object to merge
:param CartesianDomain new_domain: A new ``CartesianDomain`` object
to merge
:Example:
>>> spatial_domain = CartesianDomain({'x': [0, 1], 'y': [0, 1]})
@@ -78,7 +80,7 @@ class CartesianDomain(DomainInterface):
"""
dim = bounds.shape[0]
if mode in ["chebyshev", "grid"] and dim != 1:
raise RuntimeError("Something wrong in Span...")
raise RuntimeError("Something wrong in Cartesian...")
if mode == "random":
pts = torch.rand(size=(n, dim))
@@ -89,11 +91,10 @@ class CartesianDomain(DomainInterface):
# elif mode == 'lh' or mode == 'latin':
elif mode in ["lh", "latin"]:
pts = torch_lhs(n, dim)
else:
raise ValueError("Invalid mode")
pts *= bounds[:, 1] - bounds[:, 0]
pts += bounds[:, 0]
return pts
return pts * (bounds[:, 1] - bounds[:, 0]) + bounds[:, 0]
def sample(self, n, mode="random", variables="all"):
"""Sample routine.
@@ -121,7 +122,8 @@ class CartesianDomain(DomainInterface):
are sampled all together, and the final number of points
.. warning::
The extrema values of Span are always sampled only for ``grid`` mode.
The extrema values of Span are always sampled only for ``grid``
mode.
:Example:
>>> spatial_domain = Span({'x': [0, 1], 'y': [0, 1]})
@@ -153,7 +155,7 @@ class CartesianDomain(DomainInterface):
"""Sample independentely the variables and cross the results"""
tmp = []
for variable in variables:
if variable in self.range_.keys():
if variable in self.range_:
bound = torch.tensor([self.range_[variable]])
pts_variable = self._sample_range(n, mode, bound)
pts_variable = pts_variable.as_subclass(LabelTensor)
@@ -166,7 +168,7 @@ class CartesianDomain(DomainInterface):
result = result.append(i, mode="cross")
for variable in variables:
if variable in self.fixed_.keys():
if variable in self.fixed_:
value = self.fixed_[variable]
pts_variable = torch.tensor([[value]]).repeat(
result.shape[0], 1
@@ -201,7 +203,7 @@ class CartesianDomain(DomainInterface):
result.labels = keys
for variable in variables:
if variable in self.fixed_.keys():
if variable in self.fixed_:
value = self.fixed_[variable]
pts_variable = torch.tensor([[value]]).repeat(
result.shape[0], 1
@@ -224,7 +226,7 @@ class CartesianDomain(DomainInterface):
"""
tmp = []
for variable in variables:
if variable in self.fixed_.keys():
if variable in self.fixed_:
value = self.fixed_[variable]
pts_variable = torch.tensor([[value]]).repeat(n, 1)
pts_variable = pts_variable.as_subclass(LabelTensor)
@@ -244,15 +246,14 @@ class CartesianDomain(DomainInterface):
if self.fixed_ and (not self.range_):
return _single_points_sample(n, variables)
if isinstance(variables, str) and variables in self.fixed_.keys():
if isinstance(variables, str) and variables in self.fixed_:
return _single_points_sample(n, variables)
if mode in ["grid", "chebyshev"]:
return _1d_sampler(n, mode, variables).extract(variables)
elif mode in ["random", "lh", "latin"]:
if mode in ["random", "lh", "latin"]:
return _Nd_sampler(n, mode, variables).extract(variables)
else:
raise ValueError(f"mode={mode} is not valid.")
raise ValueError(f"mode={mode} is not valid.")
def is_inside(self, point, check_border=False):
"""Check if a point is inside the ellipsoid.