Tidy up ingested files

After image ingestion, move the data file and metadata file to
a temporary "ingested" folder. (Idea being we can sweep this
directory offline and delete anything over a certain age)
A check is done to see if the geotiff file exists before
moving the files.

The tidyup method needs to know the name of the metadata file,
so add that as an instance attribute.

Also add unit test for the new method (using mock so it doesn't
actually move anything)
More flexible file readers

Add checks to the file readers, such that default values are
used for wavelengths, variable names etc only if they are
not present in the metadata file. So allows users to specify
different settings if required. Default position is to read
reflectance for AATSR & VIIRS, radiance for MERIS (doesn't
have reflectance).
Refactor regridding method to speed it up

Regridding method was very slow, leading to the unit tests taking
a long time.

The problem was the check for whether a point is inside the region
of interest which was done inside the for loops, ie it is evalulated
separately at each grid point. Move outside the for loops and generate
a logical array instead, so it is only done once.

Unit tests now run ~10x quicker.
Fix bug in tidy up

Tidy up method was broken due to the metadata filename variable
containing the path as well as filename, so when we tried to join
the new "ingested" path it created a non existant path. Use
os.path.basemap to strip out the filename before generating
the new path.

(Unit test didn't pick this up as it did the same thing)
Add MeasurementType to Image

Add MeasurementType field to the Image model. Currently uses
units_and_name from ingest.py, to fill the required long_name
and units fields.

Also change the API to allow images to be filtered by
measurement type.