def _repr_(self):
if self._approximation.length() >= 0:
from printing import repr_matrix
coeffs = [ [ self[i,j] for j in range(self.ncols()) ] for i in range(self.nrows()) ]
return repr_matrix(coeffs)
else:
return Element_inexact._repr_(self)
def __init__(self, parent, function, starting_workprec=None, **kwargs):
if isinstance(function, list):
nrows = parent.nrows()
ncols = parent.ncols()
if len(function) > nrows*ncols:
raise ValueError("list too long")
coeffs = function + ([0] * (nrows*ncols-len(function)))
coeffs = [ coeffs[i*ncols:(i+1)*ncols] for i in range(nrows) ]
from printing import repr_matrix
self.repr = lambda: repr_matrix(coeffs)
LazyApproximation.__init__(self, parent, function, starting_workprec, **kwargs)
def __repr__(self):
from printing import repr_matrix
return repr_matrix([ [ self[i,j] for j in range(self.ncols()) ] for i in range(self.nrows()) ])
