Merge bed5c10 into f68892b

glotaran · Nov 11, 2019 · 8d84a04 · 8d84a04
2 parents f68892b + bed5c10
commit 8d84a04
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diff --git a/glotaran/builtin/models/kinetic_spectrum/test/test_kinetic_spectrum_model.py b/glotaran/builtin/models/kinetic_spectrum/test/test_kinetic_spectrum_model.py
@@ -344,149 +344,11 @@ class ThreeComponentSequential:
     axis = {"time": time, "spectral": spectral}
 
 
-class IrfDispersion:
-    model = KineticSpectrumModel.from_dict({
-        'initial_concentration': {
-            'j1': {
-                'compartments': ['s1', 's2', 's3', 's4'],
-                'parameters': ['j.1', 'j.0', 'j.0', 'j.0']
-            },
-        },
-        'megacomplex': {
-            'mc1': {'k_matrix': ['k1']},
-        },
-        'k_matrix': {
-            "k1": {'matrix': {
-                ("s2", "s1"): 'kinetic.1',
-                ("s3", "s2"): 'kinetic.2',
-                ("s4", "s3"): 'kinetic.3',
-                ("s4", "s4"): 'kinetic.4',
-            }}
-        },
-        'irf': {
-            'irf1': {
-                'type': 'spectral-multi-gaussian',
-                'center': ['irf.center'],
-                'width': ['irf.width'],
-                'dispersion_center': 'irf.dispcenter',
-                'center_dispersion': ['irf.centerdisp'],
-            },
-        },
-        'dataset': {
-            'dataset1': {
-                'initial_concentration': 'j1',
-                'irf': 'irf1',
-                'megacomplex': ['mc1'],
-            },
-        },
-    })
-    sim_model = KineticSpectrumModel.from_dict({
-        'initial_concentration': {
-            'j1': {
-                'compartments': ['s1', 's2', 's3', 's4'],
-                'parameters': ['j.1', 'j.0', 'j.0', 'j.0']
-            },
-        },
-        'megacomplex': {
-            'mc1': {'k_matrix': ['k1']},
-        },
-        'k_matrix': {
-            "k1": {'matrix': {
-                ("s2", "s1"): 'kinetic.1',
-                ("s3", "s2"): 'kinetic.2',
-                ("s4", "s3"): 'kinetic.3',
-                ("s4", "s4"): 'kinetic.4',
-            }}
-        },
-        'shape': {
-            'sh1': {
-                'type': "gaussian",
-                'amplitude': "shape.amps.1",
-                'location': "shape.locs.1",
-                'width': "shape.width.1",
-            },
-            'sh2': {
-                'type': "gaussian",
-                'amplitude': "shape.amps.2",
-                'location': "shape.locs.2",
-                'width': "shape.width.2",
-            },
-            'sh3': {
-                'type': "gaussian",
-                'amplitude': "shape.amps.3",
-                'location': "shape.locs.3",
-                'width': "shape.width.3",
-            },
-            'sh4': {
-                'type': "gaussian",
-                'amplitude': "shape.amps.4",
-                'location': "shape.locs.4",
-                'width': "shape.width.4",
-            },
-        },
-        'irf': {
-            'irf1': {
-                'type': 'spectral-multi-gaussian',
-                'center': ['irf.center'],
-                'width': ['irf.width'],
-                'dispersion_center': 'irf.dispcenter',
-                'center_dispersion': ['irf.centerdisp'],
-            },
-        },
-        'dataset': {
-            'dataset1': {
-                'initial_concentration': 'j1',
-                'irf': 'irf1',
-                'megacomplex': ['mc1'],
-                'shape': {'s1': 'sh1', 's2': 'sh2', 's3': 'sh3', 's4': 'sh4'}
-            },
-        },
-    })
-
-    initial = ParameterGroup.from_dict({
-        'j': [
-            ['1', 1, {'vary': False, 'non-negative': False}],
-            ['0', 0, {'vary': False, 'non-negative': False}],
-        ],
-        'kinetic': [
-            ["1", 1],
-            ["2", 0.4],
-            ["3", 0.05],
-            ["4", 0.009],
-            {'non-negative': True}
-        ],
-        'irf': [['center', 0.3],
-                ['width', 0.1],
-                ['dispcenter', 400, {'vary': False}],
-                ['centerdisp', 0.25]],
-    })
-    wanted = ParameterGroup.from_dict({
-        'j': [
-            ['1', 1, {'vary': False, 'non-negative': False}],
-            ['0', 0, {'vary': False, 'non-negative': False}],
-        ],
-        'kinetic': [
-            ["1", 1],
-            ["2", 0.4],
-            ["3", 0.05],
-            ["4", 0.009],
-        ],
-
-        'shape': {'amps': [2, 4, 5, 8], 'locs': [320, 380, 420, 460], 'width': [30, 20, 10, 40]},
-        'irf': [['center', 0.3], ['width', 0.1], ['dispcenter', 400], ['centerdisp', 0.25]],
-    })
-
-    time = np.arange(-1, 30, 0.01)
-    spectral = np.arange(300, 500, 25)
-    axis = {"time": time, "spectral": spectral}
-
-
 @pytest.mark.parametrize("suite", [
     OneComponentOneChannel,
     OneComponentOneChannelGaussianIrf,
     ThreeComponentParallel,
     ThreeComponentSequential,
-    IrfDispersion,
 ])
 @pytest.mark.parametrize("nnls", [True, False])
 def test_kinetic_model(suite, nnls):