Dhollander RF estimation

[rutgerfick]

Includes:

• Introduction of tissue_response_models.
• Dhollander16 three tissue response estimation
• Includes classic Tournier07 wm-tissue response estimation based on FA.

Will not include / for next pull request:

• Allowing models to have non-unity S0 response during fitting.
• Tournier12 wm-tissue response estimation

[coveralls]

Pull Request Test Coverage Report for Build 259

• 50 of 58 (86.21%) changed or added relevant lines in 6 files are covered.
• 11 unchanged lines in 5 files lost coverage.
• Overall coverage decreased (-0.5%) to 82.861%

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Changes Missing Coverage	Covered Lines	Changed/Added Lines	%
dmipy/core/modeling_framework.py	42	50	84.0%

Files with Coverage Reduction	New Missed Lines	%
dmipy/distributions/tests/test_bingham.py	1	91.78%
dmipy/signal_models/gaussian_models.py	2	96.79%
dmipy/data/saved_acquisition_schemes.py	2	83.33%
dmipy/data/saved_data.py	2	70.94%
dmipy/utils/tests/test_spherical_convolution.py	4	88.37%

Totals
Change from base Build 237:	-0.5%
Covered Lines:	3967
Relevant Lines:	4661

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💛 - Coveralls

[codecov-io]

Codecov Report

Merging #17 into master will decrease coverage by 0.3%.
The diff coverage is 82.75%.

@@            Coverage Diff             @@
##           master      #17      +/-   ##
==========================================
- Coverage   82.52%   82.21%   -0.31%     
==========================================
  Files          52       52              
  Lines        4680     4661      -19     
  Branches      542      534       -8     
==========================================
- Hits         3862     3832      -30     
- Misses        675      685      +10     
- Partials      143      144       +1

Impacted Files	Coverage Δ
...ipy/optimizers_fod/construct_observation_matrix.py	90.47% <0%> (ø)	⬆️
dmipy/optimizers_fod/csd_cvxpy.py	100% <100%> (ø)	⬆️
dmipy/core/acquisition_scheme.py	75.93% <100%> (ø)	⬆️
dmipy/core/fitted_modeling_framework.py	63.81% <100%> (+0.11%)	⬆️
dmipy/optimizers_fod/csd_tournier.py	96.29% <100%> (-0.58%)	⬇️
dmipy/core/modeling_framework.py	68.11% <82%> (-0.24%)	⬇️
dmipy/utils/tests/test_spherical_convolution.py	87.8% <0%> (-12.2%)	⬇️
dmipy/distributions/tests/test_bingham.py	98.5% <0%> (+4.47%)	⬆️

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[rutgerfick]

refactor convolution kernel construction for optimizers_fod into MultiCompartmentSphericalHarmonicsModel. Change call to use this function so the signal generation works properly.