Add mock units table

[h-mayorquin]

Motivation

Add a quick method to create mock units table
Is this something that would be of interest or useful to have?

How to test the behavior?

Should we have tests for the mock methods?

from pynwb.testing.mock.ecephys import mock_Units


units_table = mock_Units()
units_table.to_dataframe()

Produces the following output.

id	unit_name	spike_times
0	unit_0	[0.6369616873214543, 0.9067484010853246, 0.9477219250215193]
1	unit_1	[0.8158535541215322, 0.8185920542916802, 1.6759963308792496, 1.709581906184714, 2.439237352614658]
2	unit_2	[0.028319671145462966, 0.1526029476450269, 0.8232273623386572]
3	unit_3	[0.6884467305709401, 1.0773681545500438, 1.212464659572455]
4	unit_4	[0.5715298307297609, 0.8933992218057031, 1.4876992520053998, 1.825610477512533, 2.2172294780406943, 3.1075038300454865, 3.3346614235788663, 3.9578485682649087, 4.041863911847294]
5	unit_5	[0.7870983074886834, 1.0264677504816355, 1.9029519812923392, 1.9615200160975337, 2.297637076643194, 2.447916543538033, 2.89825591018732, 3.694580180474614]
6	unit_6	[0.4045518398215282, 0.6030648843307835]
7	unit_7	[0.6291081515397092, 1.5562627046075765, 1.9966398593233605, 2.9512303530140978, 3.4511261667017448, 3.8763547915508205, 4.496568243566198, 5.491664748801522, 6.440608423739287]
8	unit_8	[0.7577288453082914, 1.2551515407959104, 1.784463700992681, 2.5702494017064885, 2.9849052510621594, 3.7193888228508887, 4.430531700840638, 5.3625913874540165, 5.477524020734922]
9	unit_9	[0.9274239286245599, 1.8953501185492063, 1.9100564235145756]

Checklist

• Did you update CHANGELOG.md with your changes?
• Have you checked our Contributing document?
• Have you ensured the PR clearly describes the problem and the solution?
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• Have you included the relevant issue number using "Fix #XXX" notation where XXX is the issue number? By including "Fix #XXX" you allow GitHub to close issue #XXX when the PR is merged.

[oruebel]

Should we have tests for the mock methods?

Since pynwb.testing is part of the main pynwb package (not just the test harness), I do think that having at least a basic set of unit tests that generate a mock instance and then check that the contents are as expected would be very useful, in particular since downstream testing depends on it. Also, to keep our test coverage up.

[oruebel]

Should we have tests for the mock methods?

Correction of my previous comment. Tests for the mock classes are here https://github.com/NeurodataWithoutBorders/pynwb/blob/dev/tests/unit/test_mock.py

[h-mayorquin]

Thanks @oruebel. I will take care of this.

[codecov]

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 91.81%. Comparing base (faa8884) to head (18d55b1).

Additional details and impacted files

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##              dev    #1875   +/-   ##
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  Coverage   91.81%   91.81%           
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  Files          27       27           
  Lines        2627     2627           
  Branches      688      688           
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  Hits         2412     2412           
  Misses        142      142           
  Partials       73       73           

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integration	72.47% <ø> (ø)
unit	83.82% <ø> (ø)

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[rly]

Thank you for the contribution, @h-mayorquin !