[README] Add gitter badge & trim whitespace
[test data] add TS with data jsons
[test data] fix name of timestream data json
Correctly load image_data & new test case for this

We now correctly load ts.data and ts.image_data, and test that these are
loaded correctly. We also make ts.iter_by_whatever set the resulting
image.data to the data for that timepoint from ts.image_data, if that
timepoint is in the image_data dict. There's a new test case for this
too.
[ts/init.py] flake8 changes
Use spc-testimages as data folder
update test data
Update tests to use latest datasets
Speed up iter_by_timepoints
Add flake8 to travis script
Put getFeatures and calcComplexity in the parent class.

* timestream/manipulate/plantSegmenter.py: We put them in the parent
class as they might be used by other subclasses.
Make normRange a method of class PotSegmenter

* timestream/manipulate/plantSegmenter.py (normRange) : New method that
will normalize a dimension value to range from [0,1]
(getFeatures): Take normRange out of getFeatures.
Change name of FeatureCalculator to StatParamCalculator

* timestream/manipulate/pipecomponents.py: The StatParam calculates statistical
parameters not features.
* timestream/manipulate/plantSegmenter.py: Likewise
Put feature calculation in a separate class

* timestream/manipulate/plantSegmenter.py(FeatureCalculator): New class that
calculates features. It allows the generation of any combination of features.
Add additional simple segmentation code

We name it method1.
* timestream/manipulate/plantSegmenter.py(FeatureCalculator.G4mB3mR1): New
feature that calculates 4*G-3*B-1*R.
(PotSegmenter_Method1): New class with new method for segmenting plants. We
follow these setps:
1. Get feature G4mB3mR1
2. Apply a median filter
3. Apply a hard threshold.
4. Remove all blobs greater than self.blobMinSize
(segmentingMethods): added PotSegmenter_Method1 as "method1"
(YAML): this is the argument line in the yaml file
methargs: { threshold : 0.6, kSize : 5, blobMinSize : 50 }
* timestream/manipulate/pipecomponents.py: Added a FIXME comments so I can
remember to check for pipecomponent arguments.