I just started using sympy a couple of days ago and am playing with an
example from the R documentation for the uniroot routine.

http://stat.ethz.ch/R-manual/R-patched/library/stats/html/uniroot.html

The second example tries to find the smallest x for which exp(x) is
computationally positive. So, here it goes in sympy...


Python 2.5.4 console for SymPy 0.6.5

These commands were executed:
>>> from __future__ import division
>>> from sympy import *
>>> x, y, z = symbols('xyz')
>>> k, m, n = symbols('kmn', integer=True)
>>> f, g, h = map(Function, 'fgh')

Documentation can be found at http://sympy.org/

In [1]: F = Eq(1e80*exp(x) - 1e-300)

In [2]: F
Out[2]:
                     x
-1.0e-300 + 1.0e+80*e  = 0

In [3]: tsolve(F,x)
Out[3]: [log(1.0e-380)]


Is there a way to specify the domain to search over? It looks like I
can do this with solve (without an effect though) but can't with
tsolve...

In [5]: solve(F,x, domain=[-1000,0])
Out[5]: [log(1.0e-380)]

In [6]: tsolve(F,x, domain=[-1000,0])
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call
last)

TypeError: tsolve() got an unexpected keyword argument 'domain'


Thanks!

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