V1.6.1

See merge request !201

Small fix requiring a length-1 list to be indexed

See merge request !200

Writing unit tests for Controller configurations is tricky, so I
didn't do it, and this tiny-but-impactful bug slipped in. I did
test this on the stagin server this time, and the processing pipe-
line should work after this is deployed.

Now process inchannels, not outchannels

See merge request !199

The original version of AverageAlgorithm.py seemed to be written
to process the Controller's `--outchannels`. It "worked" for several
years because `--outchannels` defaulted to `--inchannels`. But what
we actually always wanted was to process `--inchannels`.

Mostly this was just a matter of semantics, but when I recently added
the ability to average fewer than the full complement of inputs, it
was also necessary to change the `can_produce_data()` method to check
for "any" instead of "all" channels, which in turn required that the
AverageAlgorithm class properly instantiate its `_inchannels` and
`_outchannels` class variables, instead of just set them to `None`.

To briefly explain the different changes in this commit:

- added `Algorithm.__init__(self, inchannels=[channel])` to ensure that
  can_produce_data() would work when run via programmatic interface.
- added `Algorithm.configure(self, arguments)` to AverageAlgorithm.configure()
  to ensure that can_produce_data() would work when run via Controller.py.
- changed all variations of `outchannel` to `inchannel`
- cleaned up where class variables were modified inside process() method

Make AverageAlgorithm require **any** inputs

See merge request !198

The method TimeseriesUtility.get_stream_gaps() would over-write gaps[channel] if
there were multiple Traces in a stream that were the same channel, but different
observatories. This is a typical situation when using the AverageAlgorithm.

Recent attempts to change the AverageAlgorithm to allow fewer than the full
complement of inputs when calculating a mutli-station average were thwarted
by the default can_produce_data() method in the parent Algorithm class, which
required all inputs to be present, when what we now want is **any** inputs to
be present.

Updating the version number to 1.6.0

See merge request !197

Add spreadsheet factory functionality to copy_absolutes.py

See merge request !192

Imported Enum to define a CLI parameter with a predefined set of values to choose from. Created a spreadsheets_dir option and factory option.

specify interval over which min_count is applied to AverageAlgorithm

See merge request !196

Previously use the number of traces in the input Stream. This could
be fewer than the number of desired observatories if a given input's
data was completely missing.

The recently added `min_count` option to AverageAlgorithm.py leads to some
undesirable behavior when realtime data, with asynchronous inputs, are being
processed. By adding the ability to specify an interval over which `min_count`
is applied, some of this undesirable behavior can be mitigated.

In particular, if the `realtime` option is specified via the controller, and
`min_count` is defined, the minimum number of inputs will be allowed only for
time steps prior to `(UTCDateTime.now() - realtime)`; the full complement of
inputs will be required to calculate averages more recent than that. One
drawback is that if an input observatory goes offline for an extended period,
the Dst index will be calculated with a persistent lag `realtime` seconds long.

A user can always override this admittedly ad-hoc default behavior using the
`min_count_start` and `min_count_end` options.

A "feature" in obspy is that the stats.npts metadata object is not
automatically calculated if a Trace is created by passing in a Stats
object (instead of a simple dictionary). The Trace still contained
the data array, which is probably why this issue wasn't discovered
sooner, but something as simple as trace.times() is broken if npts
is not specified. It's amazing this wasn't discovered sooner, given
how many times traces get "created" throughout geomag-algoriothms.
Probably, we should survey the codebase to make sure this isn't a
problem elsewhere.

Add --average-min-count option to AverageAlgorithm

See merge request !195

- added a `min_count` keyword to the AvergeAlgorithm's __init__() method;
- added a --average-min-count option via the add_arguments() classmethod;
- set `self.min_count = arguments.average_min_count` in configure() method;
- refactored process() method to respect `min_count`, but now it defaults
  to a requirement that all inputs be valid (this modified a recent merge
  by @awernle that only required that any inputs be valid;
- modified AverageAlgorithm_test.py to properly assess things in light
  of the change to default behavior just mentioned.

Changed dst_tot to calculate average regardless of nan values and added a new count

Closes #78

See merge request !194

Renamed variables and put into paragraphs. Asserted that the count correctly shows where there are fewer input data.

Changed dst_tot to calculate average regardless of nan values and added a new stream that counts available observatories pertimestep

Api hotfix sqlalchemy

See merge request !193

Pipeline updates

See merge request !188