Napari-time-series-plotter

Introducing the Inspector

This update is a small one, adding the TSPInspector widget. This widget allows to inspect the currently plotted time series in as a table. Time series data saved in the Inspector can be copied to the clipboard or directly exported to a CSV file.
New additions
- TSPInspector widget
- DataTableModel

Further changes
- clean up of background functions
- doc strings improvements
- figure legend repositioned

Additional information
- Due to API changes we require napari-matplotlib < v1.
- This will be the last release before version 0.1.0.
v0.1.0 will bring some major changes to the plotting modes and hopefully some performance gains, as well as the migration to napari-matplotlib >= v1 or a different canvas.

The Plotting Modes Update
With this update, we add two new plotting modes and some more options for title and axe customization!
You can select the plotting mode in the options tab. The default plotting mode is Voxel plotting.

ROI plotting
ROI plotting uses an automatically added `Shapes` layer (`ROI selection`) to define one or multiple regions on the current slice. All voxels inside of these are combined (combination modes: mean, median, std, sum, min, max; select in options tab; default: mean) and plotted per ROI and selected layer.

ROI plotting does, due to current limitations on the `napari` viewer, only work on layers without any scale, translate, rotate, or affine information.
If a layer has such parameters a warning for the problematic layer will be sent.</br>
ROI plotting does not work properly in grid mode, as grid mode does not work consistently with `Shapes` layers.

Multi-voxel plotting
Multi-voxel plotting works similarly to the previous voxel plotting, but with a `Points` layer for voxel selection. By adding points to the `Voxel selection` layer the user can select multiple voxels simultaneously to plot and compare them.
Multi-voxel plotting should work in all scenarios.

New options
- Plot title customization
- X-axis label customization
- Y-axis label customization
- Scaling factor for the X-axis

Minor fixes
- Blocked RGB images due to strange behavior (if you would need/like RGB image support write an issue)
- Axis limits now allow float values
- Readme update

The GUI update

Complete rework of the back-end and major rework of the front-end GUI. Now with better usability, access to plotting options and the ability to save your plots.

Reworked and newly added widgets:
- `LayerSelector`
Switched from basic `QWidget` with custom `QCheckbox` subwidgets to `QListView` / custom `QStandardItemModel` approach.
This offers better handling of the underlying data and events.
- `VoxelPlotter`
Switched from vanilla `matplotlib.backends.backend_qt5agg.FigureCanvas` to `napari_matplotlib.base.NapariMPLWidget`.
This offered better event handling and the inclusion of a nicely formated mpl toolbar.
Options for axe autoscaling and label truncation added.
- `TSPExplorer`
New dock widget for the `napariViewer`.
As a result an additional `QObject` for signal management is no longer needed, all events are connected via this one main widget. It is no longer needed to activate two widgets in the viewer for full functionality.
- `OptionsManager`
New widget for options control. With the update of `VoxelPlotter` user changeable options were added, this widget allows control of these. The widget is located in a tab next to the `VoxelPlotter` for easy access.

Further changes
- new structure of the submodules
Clear differentiation between docked widget, subwidgets and utility functions and classes
- new dependencies with napari_matplotlib but no longer direct dependencies on napari or pytest (added extra section for test requirements)
- complete rework of the tests to match the new design