add B in the nn parameter

pinnicle/parameter.py

@@ -193,6 +193,7 @@ def set_default(self):
         self.fft = False
         self.num_fourier_feature = 10
         self.sigma = 1.0
+        self.B = None
 
         # parallel neural network
         self.is_parallel = False
@@ -207,6 +208,9 @@ def check_consistency(self):
         if self.fft:
             if self.input_size != self.num_fourier_feature*2:
                 raise ValueError("'input_size' does not match the number of fourier feature")
+            if self.B is not None:
+                if self.B.shape[1] != self.num_fourier_feature:
+                    raise ValueError("Number of columns of 'B' matrix does not match the number of fourier feature")
         else:
             # input size of nn equals to dependent in physics
             if self.input_size != len(self.input_variables):

tests/test_parameters.py

@@ -1,4 +1,5 @@
 import pytest
+import numpy as np
 import pinnicle as pinn
 from pinnicle.parameter import DataParameter, SingleDataParameter, NNParameter, DomainParameter, PhysicsParameter, Parameters, EquationParameter, TrainingParameter
 from pinnicle.physics import SSAEquationParameter, DummyEquationParameter
@@ -67,17 +68,26 @@ def test_nn_parameter():
     d.input_lb = 1
     d.input_ub = 10
     assert d.is_input_scaling()
-
     assert not d.is_output_scaling()
+
     d.output_lb = 1
     d.output_ub = 10
     assert d.is_output_scaling()
+
     d = NNParameter({"num_neurons":[1,2,3]})
     assert d.num_layers == 3
     assert d.input_size == 0
+
     d = NNParameter({"fft":True})
     assert d.input_size == 2*d.num_fourier_feature
     assert d.is_input_scaling()
+    assert d.B is None
+
+    d = NNParameter({"fft":True, "num_fourier_feature":4, "B":np.array([[1,2,3,4]])})
+    assert d.B is not None
+    with pytest.raises(Exception):
+        d = NNParameter({"fft":True, "num_fourier_feature":4, "B":np.array([[1,2]])})
+        d = NNParameter({"fft":True, "num_fourier_feature":4, "B":1})
 
 def test_parameters():
     p = Parameters()