Fix documentation issues.

Author: collijk

docs/source/tutorials/disease_model.rst

@@ -91,12 +91,12 @@ initial population of simulants. It also notes that there is a
 `'population_size'` key. This key has a default value set by  Vivarium's
 population management system.
 
-Where's the ``__init__()``?
-+++++++++++++++++++++++++++
+The ``__init__()`` method
++++++++++++++++++++++++++
 
 Though Vivarium components are represented are represented by Python
 `classes <https://docs.python.org/3/tutorial/classes.html>`_ you'll notice
-that many of the classes we write lack the typical ``__init__`` constructor.
+that many of the classes have very sparse ``__init__`` methods.
 Due to the way the simulation bootstraps itself, the ``__init__`` method is
 usually only used to assign names to generic components and muck with
 the ``configuration_defaults`` a bit. We'll see more of this later.
@@ -108,7 +108,7 @@ Instead of the ``__init__`` method, most of the component initialization
 takes place in the ``setup`` method.
 
 .. literalinclude:: ../../../src/vivarium/examples/disease_model/population.py
-   :lines: 28, 40-59
+   :lines: 31, 43-62
    :dedent: 4
    :linenos:
 
@@ -154,7 +154,7 @@ Line 2 simply grabs a copy of the simulation
 a dictionary that supports ``.``-access notation.
 
 .. literalinclude:: ../../../src/vivarium/examples/disease_model/population.py
-   :lines: 40
+   :lines: 43
    :dedent: 4
    :linenos:
    :lineno-start: 2
@@ -169,7 +169,7 @@ it easier to perform counterfactual analysis. It's not important to have a full
 grasp of this system at this point.
 
 .. literalinclude:: ../../../src/vivarium/examples/disease_model/population.py
-   :lines: 42-47
+   :lines: 45-50
    :dedent: 4
    :linenos:
    :lineno-start: 4
@@ -210,7 +210,7 @@ The next thing we do is grab actual
 from the framework.
 
 .. literalinclude:: ../../../src/vivarium/examples/disease_model/population.py
-   :lines: 49-51
+   :lines: 52-54
    :dedent: 4
    :linenos:
    :lineno-start: 11
@@ -241,7 +241,7 @@ know that it is responsible for generating the ``'age'``, ``'sex'``,
 ``'alive'``, and ``'entrance_time'`` columns in the population state table.
 
 .. literalinclude:: ../../../src/vivarium/examples/disease_model/population.py
-   :lines: 53-55
+   :lines: 56-58
    :dedent: 4
    :linenos:
    :lineno-start: 15
@@ -261,7 +261,7 @@ know that it is responsible for generating the ``'age'``, ``'sex'``,
 Next we get a view into the population table.
 
 .. literalinclude:: ../../../src/vivarium/examples/disease_model/population.py
-   :lines: 57
+   :lines: 60
    :dedent: 4
    :linenos:
    :lineno-start: 19
@@ -280,7 +280,7 @@ simulation. Any time the ``'time_step'`` event is called, the ``age_simulants``
 method will be called as well.
 
 .. literalinclude:: ../../../src/vivarium/examples/disease_model/population.py
-   :lines: 59
+   :lines: 62
    :dedent: 4
    :linenos:
    :lineno-start: 21
@@ -304,7 +304,7 @@ describe where in the simulation life-cycle they occur. This helps me think
 more clearly about what's going on and helps debugging.
 
 .. literalinclude:: ../../../src/vivarium/examples/disease_model/population.py
-   :lines: 61, 87-111
+   :lines: 64, 90-114
    :dedent: 4
    :linenos:
 
@@ -348,7 +348,7 @@ we specified an ``'age_start'`` and ``'age_end'``.  Here we use these
 to generate the age distribution of our initial population.
 
 .. literalinclude:: ../../../src/vivarium/examples/disease_model/population.py
-   :lines: 87-95
+   :lines: 90-98
    :dedent: 4
    :linenos:
    :lineno-start: 2
@@ -388,7 +388,7 @@ These ``key_columns`` are what the randomness system uses to uniquely
 identify simulants across simulations.
 
 .. literalinclude:: ../../../src/vivarium/examples/disease_model/population.py
-   :lines: 97-102
+   :lines: 100-105
    :dedent: 4
    :linenos:
    :lineno-start: 2
@@ -408,7 +408,7 @@ If we're not using CRN, we can just generate the full set of simulant
 attributes straightaway.
 
 .. literalinclude:: ../../../src/vivarium/examples/disease_model/population.py
-   :lines: 103-109
+   :lines: 106-112
    :dedent: 4
    :linenos:
    :lineno-start: 2
@@ -434,7 +434,7 @@ The last piece of our population component is the ``'time_step'`` listener
 method ``age_simulants``.
 
 .. literalinclude:: ../../../src/vivarium/examples/disease_model/population.py
-   :lines: 113, 123-125
+   :lines: 116, 126-128
    :dedent: 4
    :linenos:
 
@@ -585,7 +585,7 @@ Many of the tools we explored in the ``BasePopulation`` component are
 used again here. There are two new things to look at.
 
 .. literalinclude:: ../../../src/vivarium/examples/disease_model/mortality.py
-   :lines: 25, 37-43
+   :lines: 28, 40-46
    :dedent: 4
    :linenos:
 
@@ -629,7 +629,7 @@ a ``pandas.Series`` that assigns each individual the mortality rate
 specified in the configuration.
 
 .. literalinclude:: ../../../src/vivarium/examples/disease_model/mortality.py
-   :lines: 45, 58
+   :lines: 48, 61
    :dedent: 4
    :linenos:
 
@@ -646,7 +646,7 @@ Like our aging method in the population component, our ``determine_deaths``
 method responds to ``'time_step'`` events.
 
 .. literalinclude:: ../../../src/vivarium/examples/disease_model/mortality.py
-   :lines: 60, 70-74
+   :lines: 63, 73-77
    :dedent: 4
    :linenos:
 
@@ -659,7 +659,7 @@ steps we're taking.
 
 In lines 3-5, we determine who died this time step.  We turn our mortality rate
 into a probability of death in the given time step by assuming deaths are
-`exponentially distributed`__ and using the inverse distribution function.
+`exponentially distributed`_ and using the inverse distribution function.
 We then draw a uniformly distributed random number for each person and
 determine who died by comparing that number to the computed probability of
 death for the individual.