| from torch import nn,tensor |
| import numpy as np |
| import seaborn as sns |
| class PINNd_p(nn.Module): |
| """ $d \mapsto P$ |
| |
| |
| """ |
| def __init__(self): |
| super(PINNd_p,self).__init__() |
| weights = tensor([60.,0.5]) |
| self.weights = nn.Parameter(weights) |
| def forward(self,x): |
| |
| c,b = self.weights |
| x1 = (x[0]/(c*x[1]))**0.5 |
| return x1 |
| |
| class PINNhd_ma(nn.Module): |
| """ $h,d \mapsto m_a $ |
| |
| |
| """ |
| def __init__(self): |
| super(PINNhd_ma,self).__init__() |
| weights = tensor([0.01]) |
| self.weights = nn.Parameter(weights) |
| def forward(self,x): |
| c, = self.weights |
| x1 = c*x[0]*x[1] |
| return x1 |
| |
| class PINNT_ma(nn.Module): |
| """$ m_a, U \mapsto T$ |
| |
| |
| """ |
| def __init__(self): |
| super(PINNT_ma,self).__init__() |
| weights = tensor([0.01]) |
| self.weights = nn.Parameter(weights) |
| def forward(self,x): |
| c, = self.weights |
| x1 = c*x[0]*x[1]**0.5 |
| return x1 |
| |
| |
| |
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