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DrPaulSharpDrPaulSharp
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Reformats tutorials (#47)
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‎source/tutorial/bayes.rst‎

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@@ -81,7 +81,7 @@ You can give the prior (alongside :math:`mu`, and :math:`sigma` if relevant) whe
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.. code-block:: Python
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problem.parameters.append(name='My new param', min=1, value=2, max=3, prior_type="gaussian", mu=0, sigma=1)
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problem.parameters.append(name='My new param', min=1, value=2, max=3, fit=True, prior_type="gaussian", mu=0, sigma=1)
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problem.parameters.append(name='My scale param', min=10, value=20, max=30, fit=True, prior_type="jeffreys")
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‎source/tutorial/customModels.rst‎

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@@ -144,13 +144,17 @@ First, we add our seven parameters (remember that Substrate Roughness is always
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.. code-block:: Python
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problem.parameters.append(name='Oxide thick', min=5.0, value=20.0, max=60.0, fit=True)
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problem.parameters.append(name='Oxide Hydration', min=0, value=0.2, max=0.5, fit=True)
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problem.parameters.append(name='Lipid APM', min=45.0, value=55.0, max=65.0, fit=True)
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problem.parameters.append(name='Head Hydration', min=0, value=0.2, max=0.5, fit=True)
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problem.parameters.append(name='Bilayer Hydration', min=0, value=0.1, max=0.2, fit=True)
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problem.parameters.append(name='Bilayer Roughness', min=2.0, value=4.0, max=8.0, fit=True)
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problem.parameters.append(name='Water Thickness', min=0, value=2.0, max=10.0, fit=True)
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parameters = [['Oxide thick', 5.0, 20.0, 60.0, True],
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['Oxide Hydration', 0, 0.2, 0.5, True],
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['Lipid APM', 45.0, 55.0, 65.0, True],
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['Head Hydration', 0, 0.2, 0.5, True],
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['Bilayer Hydration', 0, 0.1, 0.2, True],
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['Bilayer Roughness', 2.0, 4.0, 8.0, True],
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['Water Thickness', 0, 2.0, 10.0, True]]
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for param in pGroup:
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problem.parameters.append(name=param[0], min=param[1], value=param[2], max=param[3], fit=param[4])
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For this tutorial, we will show our custom model both in MATLAB and Python. You may run custom models

‎source/tutorial/project.rst‎

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@@ -151,11 +151,12 @@ To avoid having to make a whole load of statements for large projects with many
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.. code-block:: Python
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pGroup = [RAT.models.Parameter(name='Layer thick', min=10, value=20, max=30, fit=True),
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RAT.models.Parameter(name='Layer SLD', min=1e-6, value=3e-6, max=5e-6, fit=True),
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RAT.models.Parameter(name='Layer rough', min=5, value=7, max=10, fit=True)]
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problem.parameters.extend(pGroup)
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pGroup = [['Layer thick', 10, 20, 30, True,],
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['Layer SLD', 1e-6, 3e-6, 5e-6, True,],
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['Layer rough', 5, 7, 10, True]]
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for param in pGroup:
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problem.parameters.append(name=param[0], min=param[1], value=param[2], max=param[3], fit=param[4])
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The resulting parameters block looks like this:
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@@ -185,8 +186,8 @@ The resulting parameters block looks like this:
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problem.parameters.append(name='My new param', min=1, value=2, max=3)
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problem.parameters.append(name='My other new param', min=10, value=20, max=30, fit=False)
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pGroup = [RAT.models.Parameter(name='Layer thick', min=10, value=20, max=30, fit=True),
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RAT.models.Parameter(name='Layer SLD', min=1e-6, value=3e-6, max=5e-6, fit=True),
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RAT.models.Parameter(name='Layer rough', min=5, value=7, max=10, fit=True)]
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RAT.models.Parameter(name='Layer SLD', min=1e-6, value=3e-6, max=5e-6, fit=True),
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RAT.models.Parameter(name='Layer rough', min=5, value=7, max=10, fit=True)]
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problem.parameters.extend(pGroup)
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print(problem.parameters)
@@ -379,13 +380,15 @@ Start by making a new project, and adding the parameters we will need:
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problem = RAT.Project(name='Layers Example')
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params = [RAT.models.Parameter(name='Layer Thickness', min=10, value=20, max=30, fit=False),
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RAT.models.Parameter(name='H SLD', min=-6e-6, value=-4e-6, max=-1e-6, fit=False),
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RAT.models.Parameter(name='D SLD', min=5e-6, value=7e-6, max=9e-6, fit=True),
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RAT.models.Parameter(name='Layer rough', min=3, value=5, max=7, fit=True),
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RAT.models.Parameter(name='Layer hydr', min=0, value=10, max=20, fit=True)]
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params = [['Layer Thickness', 10, 20, 30, False],
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['H SLD', -6e-6, -4e-6, -1e-6, False],
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['D SLD', 5e-6, 7e-6, 9e-6, True],
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['Layer rough', 3, 5, 7, True],
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['Layer hydr', 0, 10, 20, True]]
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problem.parameters.extend(params)
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for param in params:
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problem.parameters.append(name=param[0], min=param[1], value=param[2], max=param[3], fit=param[4])
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A layer is defined in terms of a name, thickness, SLD, roughness and (optional) hydration, along with details of which bulk phase is hydrating the layer.
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The easiest way to define these is to group the parameters into cell arrays, and then add them to the project as a layers group:
@@ -441,10 +444,10 @@ Our two layers now appear in the ``layers`` block of the project:
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problem = RAT.Project(name='Layers Example')
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params = [RAT.models.Parameter(name='Layer Thickness', min=10, value=20, max=30, fit=False),
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RAT.models.Parameter(name='H SLD', min=-6e-6, value=-4e-6, max=-1e-6, fit=False),
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RAT.models.Parameter(name='D SLD', min=5e-6, value=7e-6, max=9e-6, fit=True),
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RAT.models.Parameter(name='Layer rough', min=3, value=5, max=7, fit=True),
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RAT.models.Parameter(name='Layer hydr', min=0, value=10, max=20, fit=True)]
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RAT.models.Parameter(name='H SLD', min=-6e-6, value=-4e-6, max=-1e-6, fit=False),
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RAT.models.Parameter(name='D SLD', min=5e-6, value=7e-6, max=9e-6, fit=True),
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RAT.models.Parameter(name='Layer rough', min=3, value=5, max=7, fit=True),
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RAT.models.Parameter(name='Layer hydr', min=0, value=10, max=20, fit=True)]
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problem.parameters.extend(params)
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problem.layers.append(name='H Layer', thickness='Layer Thickness', SLD='H SLD',
@@ -977,18 +980,20 @@ Then we need to define the parameters we need. We'll do this by making a paramet
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.. code-block:: Python
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parameters = [
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RAT.models.Parameter(name='Tails Thickness', min=10, value=20, max=30, fit=True),
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RAT.models.Parameter(name='Heads Thickness', min=3, value=11, max=16, fit=True),
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RAT.models.Parameter(name='Tails Roughness', min=2, value=5, max=9, fit=True),
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RAT.models.Parameter(name='Heads Roughness', min=2, value=5, max=9, fit=True),
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RAT.models.Parameter(name='Deuterated Tails SLD', min=4e-6, value=6e-6, max=2e-5, fit=True),
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RAT.models.Parameter(name='Hydrogenated Tails SLD', min=-0.6e-6, value=-0.4e-6, max=0, fit=True),
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RAT.models.Parameter(name='Deuterated Heads SLD', min=1e-6, value=3e-6, max=8e-6, fit=True),
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RAT.models.Parameter(name='Hydrogenated Heads SLD', min=0.1e-6, value=1.4e-6, max=3e-6, fit=True),
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RAT.models.Parameter(name='Heads Hydration', min=0, value=0.3, max=0.5, fit=True)
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['Tails Thickness', 10, 20, 30, True],
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['Heads Thickness', 3, 11, 16, True],
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['Tails Roughness', 2, 5, 9, True],
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['Heads Roughness', 2, 5, 9, True],
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['Deuterated Tails SLD', 4e-6, 6e-6, 2e-5, True],
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['Hydrogenated Tails SLD', -0.6e-6, -0.4e-6, 0, True],
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['Deuterated Heads SLD', 1e-6, 3e-6, 8e-6, True],
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['Hydrogenated Heads SLD', 0.1e-6, 1.4e-6, 3e-6, True],
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['Heads Hydration', 0, 0.3, 0.5, True]
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]
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problem.parameters.extend(parameters)
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for param in params:
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problem.parameters.append(name=param[0], min=param[1], value=param[2], max=param[3], fit=param[4])
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Next we need to group the parameters into our layers. We need four layers in all, representing deuterated and hydrogenated versions of the heads and tails:
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