2. save gram matrices and relative data when using function cross_validation_pre_computed, before cross validation step, in case that something goes wrong with CV. Parameter read_gm_from_file can be used to choose whether to read gram matrices from file.
3. add some test code to check if a gram matrix is symmetric and positive semi-definite.

2. apply part of the Fast Computation of Shortest Path Kernel (FCSP) to speed up the sp kernel.

2. modify model_selection_precomputed so that all results are written into memory and then to a file at last section of code, in case that on cpu/disk seperated systems the IO takes too much time.
3. correct utils.floyd_warshall_numpy function. DONNOT use the last version.

2. model_selection_precomputed can now save all results as human readable text.
3. modify pygraph.utils.utils.floydTransformation and pygraph.utils.graphdataset.get_dataset_attributes.

MOD modify tree pattern kernel, remove tottering.
MOD save output in function model_selection_precpmputed.

modifié :         notebooks/run_cyclicpatternkernel.ipynb
	modifié :         notebooks/run_marginalizedkernel_acyclic.ipynb
	modifié :         notebooks/run_pathkernel_acyclic.ipynb
	modifié :         notebooks/run_spkernel_acyclic.ipynb
	modifié :         notebooks/run_treeletkernel_acyclic.ipynb
	modifié :         notebooks/run_treepatternkernel.ipynb
	modifié :         notebooks/run_untildpathkernel_acyclic.ipynb
	nouveau fichier : notebooks/run_untilnwalkkernel.ipynb
	modifié :         notebooks/run_weisfeilerLehmankernel_acyclic.ipynb
	modifié :         pygraph/kernels/treePatternKernel.py
	modifié :         pygraph/kernels/untildPathKernel.py
	nouveau fichier : pygraph/kernels/untilnWalkKernel.py
	nouveau fichier : pygraph/utils/model_selection_precomputed.py
	modifié :         pygraph/utils/utils.py