Autumn School Dynamic MSM16-18 November 2015 | L-Esch-sur-Alzette Slide 1 4. Basic concepts, a rudimentary model, and input data (demo01.yml)

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Autumn School Dynamic MSM16-18 November 2015 | L-Esch-sur-Alzette Slide 1 4. Basic concepts, a rudimentary model, and input data (demo01.yml)

Autumn School Dynamic MSM16-18 November 2015 | L-Esch-sur-Alzette Slide 2  Import - other model (parts) to include in the simulation  Globals - time series and other external data  e.g. macroeconomic context  Entities – which unit is modelled?  e.g. person, household, enterprise, …  Simulation - how do we run that? Model structure - Top level concepts

Autumn School Dynamic MSM16-18 November 2015 | L-Esch-sur-Alzette Slide 3  A model file can (optionally) import (an)other model file(s)  This can be used to simply split a large model file into smaller files  or (more interestingly) to create simulation variants without having to duplicate the common parts. Import

Autumn School Dynamic MSM16-18 November 2015 | L-Esch-sur-Alzette Slide 4  Globals are variables (aka. parameters) that do not relate to any particular entity defined in the model  They can be used in any entity  Two kinds of globals: tables and multi-dimensional arrays  Globals can be loaded from either.csv files during the simulation, or from the HDF5 input file, along with the entities data  Periodic globals have a special status. They can have a different value for each period Globals

Autumn School Dynamic MSM16-18 November 2015 | L-Esch-sur-Alzette Slide 5  Fields: entity characteristics  what do we (want to) know about an individual?  Links: interaction between entities  same entity: e.g. who is the mother?  different entities: e.g. in what household does the person live?  Macros: make the model more readable  Processes: how do entities evolve over time?  the model definition (transformations, regressions, alignments,...) Entities

Autumn School Dynamic MSM16-18 November 2015 | L-Esch-sur-Alzette Slide 6  Types of fields:  bool: boolean (True or False)  int: integer  float: real number  Two implicit fields that do not have to be defined:  id: the unique identifier of the item  period: the current period in the run of the program  Two options for the definition of fields  initialdata: False when the field is not present in the input dataset  output: False when we don’t want the field in the output dataset Entities - Fields

Autumn School Dynamic MSM16-18 November 2015 | L-Esch-sur-Alzette Slide 7  The processes define how individuals of each entity evolve over time.  Expressions:  Arithmetic operators: +, -, *, /, ** (exponent), % (modulo)  Comparison operators: =, >  Boolean operators: and, or, not  Assignments:  - variable_name: expression  Example: - age: age + 1  Functions: processes are grouped in functions Entities - Processes

Autumn School Dynamic MSM16-18 November 2015 | L-Esch-sur-Alzette Slide 8 entities: person: fields: # period and id are implicit - age: int - gender: bool - agegroup: {type: int, initialdata: False} processes: ageing: - age: age + 1 Entities - example

Autumn School Dynamic MSM16-18 November 2015 | L-Esch-sur-Alzette Slide 9  processes: what happens to the entities and in what order?  init: processes executed in the period before start_period  input: which input file to use?  output: where is the output?  start_period: first period to simulate  periods: how many periods do we want to simulate? Simulation

Autumn School Dynamic MSM16-18 November 2015 | L-Esch-sur-Alzette Slide 10  This block defines which processes are executed and in what order  They will be executed for each period starting from start_period for periods times  Since processes are defined on specific entities, you have to specify the entity before each list of processes  You can execute the same process more than once during a simulation and you can alternate between entities in the simulation of a period  Example: simulation: processes: - person: [ageing, birth, death] - household: [clean_empty] - person: [get_a_life] - person: [csv_output] - household: [csv_output] Simulation - processes

Autumn School Dynamic MSM16-18 November 2015 | L-Esch-sur-Alzette Slide 11  The initial (observed) data is read from the file specified in the input entry  Specifying the path is optional. If it is omitted, it defaults to the directory where the simulation file is located  The hdf5-file format can be browsed with vitables (F9) or another hdf5- browser available on the net Simulation - input

Autumn School Dynamic MSM16-18 November 2015 | L-Esch-sur-Alzette Slide 12  The simulation result is stored in the file specified in the output entry  Only the variables defined at the entity level are stored. Temporary variables are not saved.  Specifying the path is optional. If it is omitted, it defaults to the directory where the simulation file is located. Simulation - output

Autumn School Dynamic MSM16-18 November 2015 | L-Esch-sur-Alzette Slide 13  Random_seed  Skip_shows: True | False (default)  Default_entity  Logging  level: periods | functions (default) | processes  timings: True (default) | False  Assertions  Autodump  Autodiff Simulation - options