Minor improvement suggestions

content/04_111_model.ipynb

@@ -102,21 +102,21 @@
     "    Simulates the service process for a call operator\n",
     "\n",
     "    1. request and wait for a call operator\n",
-    "    2. phone triage (triangular)\n",
+    "    2. phone triage (triangular distribution)\n",
     "    3. exit system\n",
     "    \n",
     "    Params:\n",
     "    ------\n",
     "    \n",
     "    identifier: int \n",
-    "        A unique identifer for this caller\n",
+    "        A unique identifier for this caller\n",
     "        \n",
     "    operators: simpy.Resource\n",
     "        The pool of call operators that answer calls\n",
     "        These are shared across resources.\n",
     "        \n",
     "    env: simpy.Environment\n",
-    "        The current environent the simulation is running in\n",
+    "        The current environment the simulation is running in\n",
     "        We use this to pause and restart the process after a delay.\n",
     "\n",
     "    service_rng: numpy.random.Generator\n",

content/05_basic_results.ipynb

@@ -142,21 +142,21 @@
     "    Simulates the service process for a call operator\n",
     "\n",
     "    1. request and wait for a call operator\n",
-    "    2. phone triage (triangular)\n",
+    "    2. phone triage (triangular distribution)\n",
     "    3. exit system\n",
     "    \n",
     "    Params:\n",
     "    ------\n",
     "    \n",
     "    identifier: int \n",
-    "        A unique identifer for this caller\n",
+    "        A unique identifier for this caller\n",
     "        \n",
     "    operators: simpy.Resource\n",
     "        The pool of call operators that answer calls\n",
     "        These are shared across resources.\n",
     "        \n",
     "    env: simpy.Environment\n",
-    "        The current environent the simulation is running in\n",
+    "        The current environment the simulation is running in\n",
     "        We use this to pause and restart the process after a delay.\n",
     "\n",
     "    service_rng: numpy.random.Generator\n",

content/06a_basic_results_exercise.ipynb

@@ -154,14 +154,14 @@
     "    ------\n",
     "    \n",
     "    identifier: int \n",
-    "        A unique identifer for this caller\n",
+    "        A unique identifier for this caller\n",
     "        \n",
     "    operators: simpy.Resource\n",
     "        The pool of call operators that answer calls\n",
     "        These are shared across resources.\n",
     "        \n",
     "    env: simpy.Environment\n",
-    "        The current environent the simulation is running in\n",
+    "        The current environment the simulation is running in\n",
     "        We use this to pause and restart the process after a delay.\n",
     "    \n",
     "    '''\n",

content/06b_basic_results_solutions.ipynb

@@ -150,14 +150,14 @@
     "    ------\n",
     "    \n",
     "    identifier: int \n",
-    "        A unique identifer for this caller\n",
+    "        A unique identifier for this caller\n",
     "        \n",
     "    operators: simpy.Resource\n",
     "        The pool of call operators that answer calls\n",
     "        These are shared across resources.\n",
     "        \n",
     "    env: simpy.Environment\n",
-    "        The current environent the simulation is running in\n",
+    "        The current environment the simulation is running in\n",
     "        We use this to pause and restart the process after a delay.\n",
     "    \n",
     "    '''\n",

content/07_experiments.ipynb

@@ -19,7 +19,7 @@
     "\n",
     "All of these approaches work well and it really is a matter of judgement on what you prefer. One downside of a python `dict` and a custom class is that they are both mutable (although a class can have custom properties where users can only access 'viewable' attributes).  A dataclass can easily be made immutable and requires less code than a custom class, but has the downside that its syntax is a little less pythonic. Here we will build a parameter class called `Experiment`.  \n",
     "\n",
-    "> ☺️ We will also use this re-organisation of code to elimiate our global variables!"
+    "> ☺️ We will also use this re-organisation of code to eliminate our global variables!"
    ]
   },
   {
@@ -75,7 +75,7 @@
     "N_STREAMS = 2\n",
     "DEFAULT_RND_SET = 0\n",
     "\n",
-    "# Boolean switch to simulation results as the model runs\n",
+    "# Boolean switch to display simulation results as the model runs\n",
     "TRACE = False\n",
     "\n",
     "# run variables\n",
@@ -217,7 +217,7 @@
     "    An Experiment:\n",
     "    1. Contains a list of parameters that can be left as defaults or varied\n",
     "    2. Provides a place for the experimentor to record results of a run \n",
-    "    3. Controls the set & streams of psuedo random numbers used in a run.\n",
+    "    3. Controls the set & streams of pseudo random numbers used in a run.\n",
     "    \n",
     "    \"\"\"\n",
     "\n",
@@ -442,10 +442,10 @@
     "    ------\n",
     "\n",
     "    identifier: int\n",
-    "        A unique identifer for this caller\n",
+    "        A unique identifier for this caller\n",
     "\n",
     "    env: simpy.Environment\n",
-    "        The current environent the simulation is running in\n",
+    "        The current environment the simulation is running in\n",
     "        We use this to pause and restart the process after a delay.\n",
     "\n",
     "    args: Experiment\n",

content/08_full_model.ipynb

@@ -95,7 +95,7 @@
     "DEFAULT_RND_SET = 0\n",
     "# ##############################################################################\n",
     "\n",
-    "# Boolean switch to simulation results as the model runs\n",
+    "# Boolean switch to display simulation results as the model runs\n",
     "TRACE = False\n",
     "\n",
     "# run variables\n",
@@ -349,7 +349,7 @@
     "    An Experiment:\n",
     "    1. Contains a list of parameters that can be left as defaults or varied\n",
     "    2. Provides a place for the experimentor to record results of a run\n",
-    "    3. Controls the set & streams of psuedo random numbers used in a run.\n",
+    "    3. Controls the set & streams of pseudo random numbers used in a run.\n",
     "\n",
     "    \"\"\"\n",
     "\n",
@@ -566,10 +566,10 @@
     "    Params:\n",
     "    ------\n",
     "    identifier: int\n",
-    "        A unique identifer for this caller\n",
+    "        A unique identifier for this caller\n",
     "\n",
     "    env: simpy.Environment\n",
-    "        The current environent the simulation is running in\n",
+    "        The current environment the simulation is running in\n",
     "        We use this to pause and restart the process after a delay.\n",
     "\n",
     "    args: Experiment\n",

content/09_time_weighted_calcs.ipynb

@@ -95,7 +95,7 @@
     "DEFAULT_RND_SET = 0\n",
     "# ##############################################################################\n",
     "\n",
-    "# Boolean switch to simulation results as the model runs\n",
+    "# Boolean switch to display simulation results as the model runs\n",
     "TRACE = False\n",
     "\n",
     "# run variables\n",
@@ -423,7 +423,7 @@
     "    An Experiment:\n",
     "    1. Contains a list of parameters that can be left as defaults or varied\n",
     "    2. Provides a place for the experimentor to record results of a run\n",
-    "    3. Controls the set & streams of psuedo random numbers used in a run.\n",
+    "    3. Controls the set & streams of pseudo random numbers used in a run.\n",
     "\n",
     "    \"\"\"\n",
     "\n",
@@ -648,10 +648,10 @@
     "    Params:\n",
     "    ------\n",
     "    identifier: int\n",
-    "        A unique identifer for this caller\n",
+    "        A unique identifier for this caller\n",
     "\n",
     "    env: simpy.Environment\n",
-    "        The current environent the simulation is running in\n",
+    "        The current environment the simulation is running in\n",
     "        We use this to pause and restart the process after a delay.\n",
     "\n",
     "    args: Experiment\n",

content/10_multiple_arrival_processes.ipynb

@@ -67,7 +67,7 @@
     "N_STREAMS = 4\n",
     "DEFAULT_RND_SET = 0\n",
     "\n",
-    "# Boolean switch to simulation results as the model runs\n",
+    "# Boolean switch to display simulation results as the model runs\n",
     "TRACE = False\n",
     "\n",
     "# run variables (units = hours)\n",
@@ -79,7 +79,7 @@
    "id": "5f2a4ad9-6d5e-480d-850f-84d4882a738b",
    "metadata": {},
    "source": [
-    "## 2. Helper classes and functions"
+    "## 3. Helper classes and functions"
    ]
   },
   {
@@ -153,7 +153,7 @@
    "id": "5a8c050c-4bb6-408f-a805-3a4aaab56916",
    "metadata": {},
    "source": [
-    "## 3. Experiment class"
+    "## 4. Experiment class"
    ]
   },
   {
@@ -257,7 +257,7 @@
    "id": "de8990c2-a330-4c02-ac77-26c30d3e0a41",
    "metadata": {},
    "source": [
-    "## 4. A function per arrival source\n",
+    "## 5. A function per arrival source\n",
     "\n",
     "The first approach we will use is creating an arrival generator per source.  There will be some code redundancy, but it will a clear design for others to understand."
    ]
@@ -392,7 +392,7 @@
    "id": "6058571e-9fdb-4961-be27-8a3b8c2fe26e",
    "metadata": {},
    "source": [
-    "## 5. Single run function"
+    "## 6. Single run function"
    ]
   },
   {

content/11_blocking.ipynb

@@ -82,7 +82,7 @@
     "N_STREAMS = 3\n",
     "DEFAULT_RND_SET = 0\n",
     "\n",
-    "# Boolean switch to simulation results as the model runs\n",
+    "# Boolean switch to display simulation results as the model runs\n",
     "TRACE = False\n",
     "\n",
     "# run variables (units = days)\n",
@@ -94,7 +94,7 @@
    "id": "5f2a4ad9-6d5e-480d-850f-84d4882a738b",
    "metadata": {},
    "source": [
-    "## 2. Helper classes and functions"
+    "## 3. Helper classes and functions"
    ]
   },
   {
@@ -122,7 +122,7 @@
    "id": "5a8c050c-4bb6-408f-a805-3a4aaab56916",
    "metadata": {},
    "source": [
-    "## 3. Experiment class"
+    "## 4. Experiment class"
    ]
   },
   {
@@ -229,7 +229,7 @@
    "id": "94f0f9c5-22cb-493a-9f1f-4e2a8325beaa",
    "metadata": {},
    "source": [
-    "## 4. Pathway process logic\n",
+    "## 5. Pathway process logic\n",
     "\n",
     "The key things to recognise are \n",
     "\n",
@@ -317,7 +317,7 @@
    "id": "de8990c2-a330-4c02-ac77-26c30d3e0a41",
    "metadata": {},
    "source": [
-    "## 4. Arrivals generator\n",
+    "## 6. Arrivals generator\n",
     "\n",
     "This is a standard arrivals generator. We create stroke arrivals according to their distribution."
    ]
@@ -362,7 +362,7 @@
    "id": "6058571e-9fdb-4961-be27-8a3b8c2fe26e",
    "metadata": {},
    "source": [
-    "## 5. Single run function"
+    "## 7. Single run function"
    ]
   },
   {

content/12_arrival_classes.ipynb

@@ -92,7 +92,7 @@
     "N_STREAMS = 4\n",
     "DEFAULT_RND_SET = 0\n",
     "\n",
-    "# Boolean switch to simulation results as the model runs\n",
+    "# Boolean switch to display simulation results as the model runs\n",
     "TRACE = False\n",
     "\n",
     "# run variables (units = minutes)\n",

content/13_warm_up.ipynb

@@ -91,7 +91,7 @@
     "N_STREAMS = 2\n",
     "DEFAULT_RND_SET = 0\n",
     "\n",
-    "# Boolean switch to simulation results as the model runs\n",
+    "# Boolean switch to display simulation results as the model runs\n",
     "TRACE = False\n",
     "\n",
     "# run variables (units = days)\n",

content/14_initial_conditions.ipynb

@@ -124,7 +124,7 @@
     "N_STREAMS = 3\n",
     "DEFAULT_RND_SET = 0\n",
     "\n",
-    "# Boolean switch to simulation results as the model runs\n",
+    "# Boolean switch to display simulation results as the model runs\n",
     "TRACE = False\n",
     "\n",
     "# run variables (units = days)\n",

content/basic_model.py

@@ -142,7 +142,7 @@ class Experiment:
     An Experiment:
     1. Contains a list of parameters that can be left as defaults or varied
     2. Provides a place for the experimentor to record results of a run 
-    3. Controls the set & streams of psuedo random numbers used in a run.
+    3. Controls the set & streams of pseudo random numbers used in a run.
     """
 
     def __init__(
@@ -261,10 +261,10 @@ def service(identifier, env, args):
     Params:
     ------
     identifier: int
-        A unique identifer for this caller
+        A unique identifier for this caller
 
     env: simpy.Environment
-        The current environent the simulation is running in
+        The current environment the simulation is running in
         We use this to pause and restart the process after a delay.
 
     args: Experiment

content/distributions.py

@@ -1,5 +1,5 @@
 """
-Distribution and utility classes avilable to these examples.
+Distribution and utility classes available to these examples.
 """
 
 import numpy as np
@@ -142,50 +142,6 @@ def sample(self, size=None):
         """
         return self.rand.exponential(self.mean, size=size)
 
-
-class Bernoulli:
-    """
-    Convenience class for the Bernoulli distribution.
-    packages up distribution parameters, seed and random generator.
-
-    The Bernoulli distribution is a special case of the binomial distribution
-    where a single trial is conducted
-
-    Use the Bernoulli distribution to sample success or failure.
-    """
-
-    def __init__(self, p, random_seed=None):
-        """
-        Constructor
-
-        Params:
-        ------
-        p: float
-            probability of drawing a 1
-
-        random_seed: int | SeedSequence, optional (default=None)
-            A random seed to reproduce samples.  If set to none then a unique
-            sample is created.
-        """
-        self.rand = np.random.default_rng(seed=random_seed)
-        self.p = p
-
-    def sample(self, size=None):
-        """
-        Generate a sample from the exponential distribution
-
-        Params:
-        -------
-        size: int, optional (default=None)
-            the number of samples to return.  If size=None then a single
-            sample is returned.
-
-        Returns:
-        -------
-        float or np.ndarray (if size >=1)
-        """
-        return self.rand.binomial(n=1, p=self.p, size=size)
-
 class DiscreteEmpirical:
     """
     DiscreteEmpirical distribution implementation.