Add summaries for variables over one dimension

Starting with commit 92f2212, `pymc.summary` gave a warning for
variables over 1d (instead of throwing an uncaught NumPy error) because
there wasn't anything in place to deal with displaying the additional
dimensions.

This commit addresses that by grouping the output in the summary table
to reflect the different dimensions. For example, a 2d variable x would
have a 3d MCMC trace, and the summary statistics for x would have a
shape corresponding to the original variable.

    >>> trace['x'].shape
    (3000, 2, 3)
    >>> trace['x'].mean(0).shape
    (2, 3)

To display this in the summary table, the indices for the stats array
are grouped by indices for all dimensions except the rightmost. In the
summary output, the left indices are separated by blank row, while the
rightmost index is shown as rows within a group.

    (0, 0)
    (0, 1)
    (0, 2)

    (1, 0)
    (1, 1)
    (1, 2)

This scheme isn't great visually for variables over 2d because then
there is more than one left index and a blank row is inserted regardless
of which left index is incremented. It'd be possible to extend this by
displaying the current left indices instead of a blank row for variables
over 2d.

Also, this commit changes the naming in the summary tests to refer to
variable dimensions in a consistent way (0d, 1d, 2d, ...). These are
always meant to refer to the original variable dimensions, not the MCMC
trace dimensions.
Added Weibull and half-Cauchy distributions
Merge branch 'distributions' of github.com:pymc-devs/pymc into distributions
Add index labels in summaries

For variables above 1d, label each group of rows in the summary with the
corresponding NumPy index.
Merge pull request #516 from kyleam/summary-over-1d

Add summaries for variables over one dimension
Added ChiSquared, HalfNormal and Wald distributions
Merge pull request #519 from pymc-devs/distributions

Three More Distributions
add discrete step method tests

Tests for discrete step methods were missing.
guess the scaling for only our variables

Nuts was guessing the scaling for all the variables, not just the ones
we care about.
got discrete step test passing
add support for variables > 1d in traceplot

traceplot would generate an error if a trace of a more than 1-d
variable was.

Now we ravel the dimensions after the first.

We should support for this in forestplot and autocorrplot.
Revert "BLD: Remove broken nose-timer."

This reverts commit 079a0c30e277e5776f4125f6b737394d34127162.
remote timer-verbose arg from travis commands
import checks with dot to avoid error in py 3.3
import models with .models for py 3.3
Fix for missing Deterministics in psample trace for #522
Merge pull request #521 from pymc-devs/timer

Misc: add back nose-timer, support multidimensional variables in traceplot, test discrete step methods
Merge branch 'psample_fix'

Conflicts:
	pymc/tests/models.py
Minor fix to half-Cauchy docstring
Added Pareto and Inverse Gamma