This baseline commit brings in the file that has been used in the
exploratory repo of https://github.com/tallamjr/plasticc/pipeline.py

Although one expects the code in this file to change a lot, PEP8 linting
was carried out to encourage the consistent style.

Comments added to areas of code which need further discussion or will
indeed be adapted further

File mode changed to 644 from 755. This puts all files in the same
permissions bracket to allow for consistency across the files.

Renaming to be in line with code style conventions

Updating with doctrings and examples. Also including helper function to
obtain git revision hash to include in analysis folder name

Certain options would be better served as defaults in the script and the
user can change these as they wish in the source file

These files may still have merit for processing the data but as the
pipeline is being developed it is felt they are better served in a
seperate folder

Removed code to add to sys path as this is no longer necessary as
pipeline script now resides in snmachine main repo

Several functions have been updated with doctrings and examples for how
to run such functions

Renaming of files to make it easier to follow how the modern workflow
takes place. Put old run_pipeline.py file in archive as this is no
longer used

gps.py defines variable names for the kernel parameters and number of
points for the GPs. This change updates the configuration file and
pipeline to be in line with that file

Reducing the number of PCA components from 200 to 10 as it is required
that number of components be less than or equal to the number of
objects. Thus for the dataset used here "training_set_snia.pickle" 10 is
appropriate.

This should fix this error:

    Running PCA...
    The condition number in the SVD is 1.02688179587e+23 and the normalized
    one is 5.00036575467e+22
    Traceback (most recent call last):
      File "plasticc_pipeline.py", line 469, in <module>
        tol=None, pca_path=None, save_output=True,
    output_root=dirs.get("intermediate_files_directory"))
      File
    "/home/tallam/.conda/envs/snmachine/lib/python3.6/site-packages/snmachine/snfeatures.py",
    line 2005, in extract_pca
        normalize_variance=normalize_variance)
      File
    "/home/tallam/.conda/envs/snmachine/lib/python3.6/site-packages/snmachine/snfeatures.py",
    line 1873, in _pca
        return self.pca_SVD(dataMatrix, ncomp, tol, normalize_variance)
      File
    "/home/tallam/.conda/envs/snmachine/lib/python3.6/site-packages/snmachine/snfeatures.py",
    line 1714, in pca_SVD
        assert isinstance(tol, np.float)
    AssertionError

If one attempts to call the "method_directory" parameter from the
dictionary but it does not exist, a None type return will occur

This function is used to determine the last modified time of the
configuration file that is being used and to place this in the name of
the analysis run.

This function now displays the confusion matrix as ASCII table in
console as well as returning seaborn figure

Removal of Log Loss function call as well as stripping unused functions
within 'create_classifier'

Previously one would prepend the hash and timestamp to the folder, but
this became too verbose

Adding checks if analysis name already created

This should see if the user has already defined an existing analysis
name already and check to see if they want to overwrite the results in
that folder, or create a new one.

Sending stderr to /dev/null if folder overwritten

This function should be able to convert to either numpy or astropy.Table
to a pandas.DataFrame.

Also updating docstrings

Due to a conditional check if a directory exists or not, it became
apparent that if there was not a directory, no new ones were being
created. This change fixes that.

Do not track log files in utils folder

Removing ROC and AUC metrics

Instead of an Astropy Table, return as a pandas DataFrame to processing
later in the pipeline

Required updating sklearn version

Also functionality save classifier and confusion matrix plot

Fixes #149

The recent HTTP 404 error discovered in the CI suggests that a recent
change to sncosmo might be the reason for failing to find salt2 models

Latest version = 1.8.0, which is where the error occurs, bumping down to
1.7.1 (previous release) to test outcome

…he classifier and confusion matrix

With the inclusion of this feature set, although not fully complete,
a MINOR bump is felt necessary.