__init__(self, coeffs, prefactor=None, shift=None, stack_dim=0): 

__repr__(self): 

@classmethod
from_tensors(cls, tensors, prefactor=None, shift=None, rescale=True): 

@property
shape(self): 

@property
scaling(self): 

@property
coeffs(self) -> 'np.ndarray|SparseArray': 

@property
coordinate_dim(self): 

__mul__(self, other) -> 'DensePolynomial': 

__add__(self, other) -> 'DensePolynomial': 

shift(self, shift) -> 'DensePolynomial': 

@classmethod
compute_shifted_coeffs(cls, poly_coeffs, shift, stack_dim=0): 

@classmethod
fill_tensors(self, tensors, idx, value, stack_dim, pcache, permute, rescale): 

@classmethod
extract_tensors(cls, coeffs, stack_dim=None, permute=True, rescale=True, cutoff=1e-15): 

@classmethod
condense_tensors(cls, tensors, rescale=True, allow_sparse=True): 

@property
coefficient_tensors(self): 

@property
unscaled_coefficient_tensors(self): 

transform(self, lin_transf): 

outer(self, other): 

deriv(self, coord): 

grad(self): 

clip(self, threshold=1e-15): 

make_sparse_backed(self, threshold=1e-15):