Perfect. The following solution seems to work for me. Thanks!
class log(Function):
def _eval_evalf(self,prec):
pass
def doit(self, **hints):
from sympy import log as sympy_log
return sympy_log(self.args[0]).doit(**hints)
On Saturday, September 6, 2014 2:20:12 PM UTC-5, Aaron Meurer wrote:
>
> SymPy automatically defines evaluation based on mpmath function names.
> I think you can get around it by defining an empty _eval_evalf(self,
> prec) function.
>
> Aaron Meurer
>
> On Sat, Sep 6, 2014 at 1:50 PM, Duane Nykamp <[email protected]
> <javascript:>> wrote:
> > I really like the evaluate=False flag on parse_expr. But, since
> log(0.1)
> > automatically evaluates to a float, I'm trying to create an unevaluated
> > version of log. However, I'm getting strange results where log is
> > implicitly defined.
> >
> > As shown below, once I define a function log that does nothing, sympy
> > somehow implicitly defines it to be the usual log function.
> >
> > Am I missing how this works or is this aberrant behavior?
> >
> > My eventual plan is to have log.doit() return the original sympy
> function.
> >
> > If I call the function something else, like llog, then I don't run into
> the
> > behavior. But, I'm not sure how to make printers display my llog
> function
> > as log.
> >
> > Thanks,
> > Duane
> >
> >
> >
> > In [1]: from sympy import Function
> >
> > In [2]: log
> >
> ---------------------------------------------------------------------------
> > NameError Traceback (most recent call
> last)
> > <ipython-input-2-9a115ebc25a0> in <module>()
> > ----> 1 log
> >
> > NameError: name 'log' is not defined
> >
> > In [3]: class log(Function):
> > ...: pass
> > ...:
> >
> > In [4]: log
> > Out[4]: __main__.log
> >
> > In [5]: log(0.1)
> > Out[5]: -2.30258509299405
> >
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