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This commit is contained in:
ndem0
2024-02-09 11:25:00 +00:00
committed by Nicola Demo
parent 591aeeb02b
commit cbb43a5392
64 changed files with 1323 additions and 955 deletions
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44
pina/geometry/cartesian.py
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@@ -72,17 +72,17 @@ class CartesianDomain(Location):
:rtype: torch.Tensor
"""
dim = bounds.shape[0]
if mode in ['chebyshev', 'grid'] and dim != 1:
raise RuntimeError('Something wrong in Span...')
if mode in ["chebyshev", "grid"] and dim != 1:
raise RuntimeError("Something wrong in Span...")
if mode == 'random':
if mode == "random":
pts = torch.rand(size=(n, dim))
elif mode == 'chebyshev':
pts = chebyshev_roots(n).mul(.5).add(.5).reshape(-1, 1)
elif mode == 'grid':
elif mode == "chebyshev":
pts = chebyshev_roots(n).mul(0.5).add(0.5).reshape(-1, 1)
elif mode == "grid":
pts = torch.linspace(0, 1, n).reshape(-1, 1)
# elif mode == 'lh' or mode == 'latin':
elif mode in ['lh', 'latin']:
elif mode in ["lh", "latin"]:
pts = torch_lhs(n, dim)
pts *= bounds[:, 1] - bounds[:, 0]
@@ -90,7 +90,7 @@ class CartesianDomain(Location):
return pts
def sample(self, n, mode='random', variables='all'):
def sample(self, n, mode="random", variables="all"):
"""Sample routine.
:param n: Number of points to sample, see Note below
@@ -145,7 +145,7 @@ class CartesianDomain(Location):
"""
def _1d_sampler(n, mode, variables):
""" Sample independentely the variables and cross the results"""
"""Sample independentely the variables and cross the results"""
tmp = []
for variable in variables:
if variable in self.range_.keys():
@@ -158,17 +158,18 @@ class CartesianDomain(Location):
result = tmp[0]
for i in tmp[1:]:
result = result.append(i, mode='cross')
result = result.append(i, mode="cross")
for variable in variables:
if variable in self.fixed_.keys():
value = self.fixed_[variable]
pts_variable = torch.tensor([[value]
]).repeat(result.shape[0], 1)
pts_variable = torch.tensor([[value]]).repeat(
result.shape[0], 1
)
pts_variable = pts_variable.as_subclass(LabelTensor)
pts_variable.labels = [variable]
result = result.append(pts_variable, mode='std')
result = result.append(pts_variable, mode="std")
return result
@@ -197,12 +198,13 @@ class CartesianDomain(Location):
for variable in variables:
if variable in self.fixed_.keys():
value = self.fixed_[variable]
pts_variable = torch.tensor([[value]
]).repeat(result.shape[0], 1)
pts_variable = torch.tensor([[value]]).repeat(
result.shape[0], 1
)
pts_variable = pts_variable.as_subclass(LabelTensor)
pts_variable.labels = [variable]
result = result.append(pts_variable, mode='std')
result = result.append(pts_variable, mode="std")
return result
def _single_points_sample(n, variables):
@@ -226,22 +228,22 @@ class CartesianDomain(Location):
result = tmp[0]
for i in tmp[1:]:
result = result.append(i, mode='std')
result = result.append(i, mode="std")
return result
if self.fixed_ and (not self.range_):
return _single_points_sample(n, variables)
if variables == 'all':
if variables == "all":
variables = list(self.range_.keys()) + list(self.fixed_.keys())
if mode in ['grid', 'chebyshev']:
if mode in ["grid", "chebyshev"]:
return _1d_sampler(n, mode, variables)
elif mode in ['random', 'lh', 'latin']:
elif mode in ["random", "lh", "latin"]:
return _Nd_sampler(n, mode, 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.