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Fix for incompatibility of numpy2.* in the finite difference routines #595

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Fix for incompatibility of numpy2.* in the finite difference routines #595

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12 changes: 9 additions & 3 deletions pysindy/differentiation/finite_difference.py
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Original file line number Diff line number Diff line change
Expand Up @@ -109,7 +109,13 @@ def _coefficients(self, t):
matrices = dt_endpoints[:, "power", :] ** pows
b = AxesArray(np.zeros((1, self.n_stencil)), {"ax_time": 0, "ax_power": 1})
b[0, self.d] = factorial(self.d)
return np.linalg.solve(matrices, b)
# as of numpy 2.0:
# solve requires that the 'b' matrix has shape (M,) or (..., M, K)
# with corresponding output (..., M) or (..., M, K),
# so add axis K = 1 then squeeze that axis away
# This change also propagates to all other _coefficients functions
# and is compatible with numpy 1.*
return np.squeeze(np.linalg.solve(matrices, b[..., np.newaxis]), axis=2)

def _coefficients_boundary_forward(self, t):
# use the same stencil for each boundary point,
Expand Down Expand Up @@ -145,7 +151,7 @@ def _coefficients_boundary_forward(self, t):

b = np.zeros(self.stencil_inds.shape).T
b[:, self.d] = factorial(self.d)
return np.linalg.solve(matrices, b)
return np.squeeze(np.linalg.solve(matrices, b[..., np.newaxis]), axis=2)

def _coefficients_boundary_periodic(self, t):
# use centered periodic stencils
Expand Down Expand Up @@ -198,7 +204,7 @@ def _coefficients_boundary_periodic(self, t):

b = np.zeros(self.stencil_inds.shape).T
b[:, self.d] = factorial(self.d)
return np.linalg.solve(matrices, b)
return np.squeeze(np.linalg.solve(matrices, b[..., np.newaxis]), axis=2)

def _constant_coefficients(self, dt):
pows = np.arange(self.n_stencil)[:, np.newaxis]
Expand Down
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