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

preliminary modifications for N-S

Browse Source
This commit is contained in:
Anna Ivagnes
2022-05-05 17:12:31 +02:00
parent d152fe67e3
commit 8130912926
13 changed files with 213 additions and 162 deletions
Download Patch File Download Diff File Expand all files Collapse all files

43
pina/span.py
View File

@@ -20,9 +20,27 @@ class Span(Location):
else:
raise TypeError
def sample(self, n, mode='random'):
def sample(self, n, mode='random', variables='all'):
bounds = np.array(list(self.range_.values()))
if variables=='all':
spatial_range_ = list(self.range_.keys())
spatial_fixed_ = list(self.fixed_.keys())
bounds = np.array(list(self.range_.values()))
fixed = np.array(list(self.fixed_.values()))
else:
bounds = []
spatial_range_ = []
spatial_fixed_ = []
fixed = []
for variable in variables:
if variable in self.range_.keys():
spatial_range_.append(variable)
bounds.append(list(self.range_[variable]))
elif variable in self.fixed_.keys():
spatial_fixed_.append(variable)
fixed.append(int(self.fixed_[variable]))
fixed = torch.Tensor(fixed)
bounds = np.array(bounds)
if mode == 'random':
pts = np.random.uniform(size=(n, bounds.shape[0]))
elif mode == 'chebyshev':
@@ -41,23 +59,24 @@ class Span(Location):
from scipy.stats import qmc
sampler = qmc.LatinHypercube(d=bounds.shape[0])
pts = sampler.random(n)
# Scale pts
pts *= bounds[:, 1] - bounds[:, 0]
pts += bounds[:, 0]
pts = pts.astype(np.float32)
pts = torch.from_numpy(pts)
fixed = torch.Tensor(list(self.fixed_.values()))
pts_fixed_ = torch.ones(pts.shape[0], len(self.fixed_),
dtype=pts.dtype) * fixed
pts_range_ = LabelTensor(pts, list(self.range_.keys()))
pts_fixed_ = LabelTensor(pts_fixed_, list(self.fixed_.keys()))
pts_range_ = LabelTensor(pts, spatial_range_)
if not len(spatial_fixed_)==0:
pts_fixed_ = torch.ones(pts.shape[0], len(spatial_fixed_),
dtype=pts.dtype) * fixed
pts_fixed_ = LabelTensor(pts_fixed_, spatial_fixed_)
pts_range_ = pts_range_.append(pts_fixed_)
return pts_range_
if self.fixed_:
return pts_range_.append(pts_fixed_)
else:
return pts_range_
def meshgrid(self, n):
pts = np.array([