Patterncoordinator errata + new Sweeper

This pull request addresses several issues in PatternCoordinator. Furthermore, a new PatternGenerator "Sweeper" for motion is introduced.

## Addressed issues in PatternCoordinator
### Change inherent_features from a dict to a list
Here, inherent_features has been changed from a dict to a list. If a feature is listed in inherent_features, the corresponding feature coordinator is not added to _feature_coordinators_to_apply. This avoids confusion about the former value of inherent_features, which was only meaningful in PatternCoordinatorImages, but not in PatternCoordinator itself.
In PatternCoordinatorImages, a new variable placeholder_mapping has been introduced. This maps a placeholder in the filename_template to its replacement.

### Allow supplying a path to a dataset
Rather than supplying a JSON file which specifies an image dataset, this pull request adds the possibility for providing a path to a dataset. By default, all png files within the provided directory are then used.
Furthermore, filename_template can now contain glob elements such as * which are evaluated.

### Change to FeatureCoordinators
Rather than modifying an existing PatternGenerator, the implementation of FeatureCoordinators has been changed to return a new PatternGenerator. In practise, a copy of the supplied PatternGenerator is made and then modified and returned.
This change is neccessary to allow the supplied PatternGenerator to be passed through another PatternGenerator, e.g. a MotionCoordinator might use Sweeper with the supplied PatternGenerator passed to the Sweeper.

### Introduce names to numbergen objects for time_dependent=True
When time_dependent=True, the numbergen objects must get passed a name. This has been done here for the present FeatureCoordinators.

### Bugfix: use get_value_generator when overwriting parameters
So far, parameters of the PatternGenerators were set as follows:
pattern.x += numbergen.UniformRandom(...)
This evaluates to
pattern.x = pattern.x + numbergen.UniformRandom(...)

However, pattern.x never returns a numbergen object, but always float (even if it is set to a numbergen object).

The correct way to set parameters is instead:
pattern.x = pattern.get_value_generator('x') + numbergen.UniformRandom(...)

## Sweeper
Sweeper is a more correct implementation of Translator. E.g. if you have a numbergen randomly setting orientation of a Gaussian and you pass it into a Translator, the orientation will keep changing during each sweep phase! This is clearly not what one wants to achieve. Sweeper however allows this behavior. It does so by setting a new time_fn on the supplied pattern generator, which is "slowed down" by dividing by reset_period.
Documentation will be added later.
Wait...surely featuremapper uses Translator vs Sweeper for the old motion model vs new motion model in measurement? Or whatever way round those two classes are used (yes, it is confusing!)