Rsmtool

This is primarily a bug fix release but it also has some improvements.

Bugfixes
- The notebooks are fixed so that any plots are now shown in their assigned places (this was broken in v5.5.1 due to the underlying `matplotlib` dependency being upgraded to v2.0).

Improvements
- The widths of the subgroup plots is now more intelligently determined. No more plots with really wide bars when there are only a few groups.
- Many of the unnecessary warnings that popped up in the reports and on the terminal are now suppressed and handled in code where appropriate.

This is a minor bugfix release.

What's new?
- Update [SKLL](http://github.com/EducationalTestingService/skll) requirement to v1.3. This allows us to streamline the RSMTool conda recipe into a single recipe (using the MKL backend instead of OpenBLAS on macOS/Linux)
- Update all other conda packages to their latest versions.
- Minor fixes and updates to tests.

This is a major release.

What's new?
- New tool: `rsmsummarize` which can [summarize](http://rsmtool.readthedocs.io/en/latest/advanced_usage.html#rsmsummarize-compare-multiple-scoring-models) any number of `rsmtool` experiments and produce a summary report.
- All input files can now be in any tabular format (CSV/TSV/XLS/XLSX). This is an improvement over previous releases where input files were required to be CSV files. For more details, see the [documentation](http://rsmtool.readthedocs.io/en/latest/pipeline.html#input-file-format). This includes the [feature description file](http://rsmtool.readthedocs.io/en/latest/usage_rsmtool.html#fine-grained-column-selection) although the old JSON format is still supported for backwards compatibility (you will get a `DeprecationWarning` when using that format).
- `rsmtool` now includes a new model `ScoreWeightedLR` which estimates feature coefficients using weighted least squares regression. The weights are computed as an inverse proportion of total number of responses with a given score level.
- `rsmtool` now produces the `feature` sub-directory as part of its [output](http://rsmtool.readthedocs.io/en/latest/usage_rsmtool.html#output) for _all_ experiments. Previously, this sub-directory was only produced for experiments with some form of feature selection.
- `rsmcompare` now requires the user to specify a "comparison ID" instead of generating one automatically from the experiment IDs of the two experiments being compared.

Improvements
- Improved CSS for HTML report printing.
- Several updates and fixes to documentation.
- Fix errors in PCA computation when the number of components was smaller than the total number of features.
- Use `skll` API to convert featureset to data frame instead of writing our own function.
- Separate the file reading and processing functions in `rsmpredict` for more modularity.
- Wrap longer labels on box plots automatically.
- Update package dependencies to latest releases.
- Increase report generation timeout to be 60 minutes instead of 10 minutes. This is useful for experiments with very large data files.
- Fix bug that had system and human scores reversed in the confusion matrix.
- Limit the length of experiment IDs where appropriate such that we don't encounter "filename is too long" OS errors.

This is a minor release that fixes a bug in how some javascript was loaded in the Jupyter notebooks.

This release has minor features and bug fixes.
1. `rsmcompare` now includes extra checks to make sure the experiment paths and ids specified by the user actually exist.
2. Factored out `rsmcompare` code from the header notebook and moved to `comparison.py`.
3. Factored out the float formatting functions from the `rsmtool`/`rsmcompare` header notebooks and moved them to `utils.py`.
4. Added new tests for `comparison.py` and the float formatting and highlighting functions in `utils.py`.
5. Fixed the bug in `rsmcompare` which seemed to ignore zero scores in confusion matrices.
6. Fixed a bug in `rsmcompare` that prevented the score distribution table from being displayed correctly if the score levels differed between the two models.

This is a minor bugfix release.
1. Previously, if `rsmpredict` was given a model requiring a transformation that could yield `Inf`/`NaN` values for new data (e.g. `sqrt(-1)`), it would raise an error and terminate. Now, it simply excludes such responses and displays a warning.
2. Updated various `conda` files to use newer versions of the `ipython` and `notebook` packages since there seem to have been some updates that broke older recipes and requirements files.