Overhaul docs #105
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Overhaul docs #105
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Hi @drvinceknight would really appreciate your thoughts on this. (doctests failing due to some Python2 / Python3 printing differences, I'm thinking about this) |
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I'm thinking: Only run doctests on Python3. Run all other tests on both. Make a note in docs that output assumes Python3 although Python2 is also supported? |
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Yeah I was going to suggest that. You can setup matrices of different runs
on Travis.
You could say "whilst python 2 is currently supported, python 3 is
recommended and assumed in the documentation".
…On Tue, 21 Mar 2017, 14:48 Geraint Palmer, ***@***.***> wrote:
I'm thinking: Only run doctests on Python3. Run all other tests on both.
Make a note in docs that output assumes Python3 although Python2 is also
supported?
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drvinceknight
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Mar 21, 2017
docs/index.rst
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| Ciw is a discrete event simulation library for open queueing networks. It's core features include the capability to simulate networks of queues, multiple customer classes, and implementation of Type I blocking for restricted networks. A number of other features are also implemented, including priorities, baulking, schedules, and deadlock detection. | ||
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| The documentation contains a two part tutortial that guides the user through some key concepts and core features of the library. A series of How-to guides instruct on the use and implementation of Ciw's numerous features, and reference pages and background information is available to ensure ease of use and understanding. |
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Remove this paragraph (not needed).
docs/index.rst
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| The documentation contains a two part tutortial that guides the user through some key concepts and core features of the library. A series of How-to guides instruct on the use and implementation of Ciw's numerous features, and reference pages and background information is available to ensure ease of use and understanding. | ||
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| Please note that Ciw is currently supported for and regularly tested on Python versions 2.7, 3.4 and 3.5. However, for the documentation we assume Python 3 is used. |
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Possibly put this sentence in brackets.
docs/Reference/parameters.rst
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| 'Baulking_functions': {'Class 0': [my_baulking_function]} | ||
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Some rst syntax is broken in this file.
docs/index.rst
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| citation.rst | ||
| changelog.rst | ||
| glossary.rst |
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I suggest you move this to reference.
docs/index.rst
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| .. toctree:: | ||
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| citation.rst |
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I suggest you move this to a how to.
docs/Tutorial-II/tutorial_v.rst
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| Ciw's real power comes when modelling networks of queues. That is many service nodes, such that when customers finish service, there is a probability of joining another node, rejoining the current node, or leaving the system. These types of systems arise naturally in communications, manufacturing, and service industries. | ||
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| Imagine a café that sells both hot and cold food. Customer arrive and can take a few routes: |
docs/Tutorial-II/tutorial_v.rst
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| A transition matrix is an :math:`n \times n` matrix (where :math:`n` is the number of nodes in the network) such that the :math:`(i,j)\text{th}` element corresponds to the probability of transitioning to node :math:`j` after service at node :math:`i`. In Python, we write this matrix as a list of lists. The transition matrix for the café system looks like this:: | ||
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| [[0.0, 0.3, 0.7], |
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Write this in maths display mode.
docs/Tutorial-II/tutorial_v.rst
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| Notice the Service distributions: an average cold food service time of 1 minute is equivalent to a rate of 1/1 = 1 service per minute; an average hot food service time of 2.5 minutes is equivalent to 1/2.5 = 0.4 services per minute; and an average till service time of 2 minutes is equivalent to 0.5 services per minute. | ||
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| Let's simulate this for one shift of lunchtime of 3 hours (180 mins). At the beginning of lunchtime he café opens, and thus begins from an empty system. Therefore no war-mup time is required. We'll use 20 minutes of cool-down time. We'll run 10 trials, to get a resume of the average number of customers that pass through the system. To find the average number of customers that pass through the system, we can count the number of data records that have passed through Node 3 (the Till):: |
docs/Tutorial-II/tutorial_v.rst
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| We can now get the average number of customers that have passed through the system:: | ||
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| >>> sum(completed_custs)/len(completed_custs) |
docs/Tutorial-II/tutorial_v.rst
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| Notice the Service distributions: an average cold food service time of 1 minute is equivalent to a rate of 1/1 = 1 service per minute; an average hot food service time of 2.5 minutes is equivalent to 1/2.5 = 0.4 services per minute; and an average till service time of 2 minutes is equivalent to 0.5 services per minute. | ||
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| Let's simulate this for one shift of lunchtime of 3 hours (180 mins). At the beginning of lunchtime he café opens, and thus begins from an empty system. Therefore no war-mup time is required. We'll use 20 minutes of cool-down time. We'll run 10 trials, to get a resume of the average number of customers that pass through the system. To find the average number of customers that pass through the system, we can count the number of data records that have passed through Node 3 (the Till):: |
This was referenced Mar 22, 2017
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