Add Python 3.4 to .travis.yml

I don't know if Travis actually supports it yet. I guess we'll find out.

For the slow tests, we only tested on the most recent version of Python 2 and
Python 3, so change them from 3.3 to 3.4.

This is a lot of Pythons now. We should probably think about dropping 3.2
support...
Fix for the bug #7343
Fix for the issue #7342
Fix for the bug #7343

Corrected the bug by adding solutions returned from
each individual equation to the `sols` set. Previous
error was due to replacing the last solution in `sols`
by the new solution rather than appending it to the `sols`.
Fix for the issue #7342

Change the return type of `diop_solve()` to a tuple in the univariable
case. Also added the checks to ensure that only  `Add`, `Mul` or a
`Symbol` is processed in the `classify_diop()` function. Raised an
error in the other cases.
Replace `==` by `is`
Fixed merge conflicts.

Conflicts:
	sympy/solvers/diophantine.py
Use the shortened version of `isinstance`. Replaced
`isinstance(eq, Add) or isinstance(eq, Mull) or ....` by
`isinstance(eq, (Add, Mul, ...))

Replaced the search for `None` using a for loop by using
`in`.
Use iterators in `merge_solution` instead of using counter
variables to keep track of the next element to be taken out
from `params` and `solution`.
Makes IndexedBase consistent with Symbol wrt to latex printing
Adds test extra test for latex of IndexedBase
Added files and docs for primary field functionality
Merge branch 'master' of https://github.com/sympy/sympy into fielddocs
Added documentation for fieldfunctions, rectified errors
Made changes suggested by @smichr
Merge branch 'master' of https://github.com/sympy/sympy into fielddocs
Changed the `diophantine()` function so that it now respects the assumptions
imposed on the symbols. Originally the issue was raised in a so question found
in

http://stackoverflow.com/questions/23301941/how-can-i-declare-natural-symbols-with-sympy

and reported as SymPy issue #7444 by Aaron.

A similar approach as in `solve` is carried out to check for the assumptions.
Each symbol's assumptions are tested against the value returned by the
`diop_solve()` for that variable using `check_assumptions()`.
Remove an unnecessary blank line
Correct nth-order linear ode constants

- use a complex-conjugate accounting to avoid adding extra constants
- test nth-order constants without simplification
- remove XFAIL, now that we fix #6247
- remove XFAIL, now that we also fix #7081
Fix for Issue 7140: plot.append