Spatial Microsimulation Urban Metabolism (SMUM)¶
Author: | Dr. M. Esteban Munoz H. <emunozh@gmail.com> or <esteban.munoz@un.org> |
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Version: | 0.2.0 |
Date: | 2018-06-12 |
Note
This documentation is generated automatically from the main github repository. The build of the documentation is not always successful and you might end up reading a documentation of an outdated version of the model. Please always verify the version of the model you are running. This simulation library is under development and we are constantly changing the simulation libraries.
This is the main documentation for the Spatial Microsimulation Urban Metabolism model. This model combines two powerful approaches for the simulation of resource flows within cities. The first approach is Urban Metabolism (UM). This approach describes the metabolic performance of cities by quantifying and balancing all resource inputs and outputs from a predefined city-system. The second component of the simulation model is the Spatial Microsimulation (SM) model. This component of the simulation library constructs a synthetic population for the specific city-system and allocates consumption values to the individual city agents. The simulation library benchmarks this synthetic sample to the aggregated consumption values from the UM model.
The aim of this documentation is twofold:
- Describe the methodological approach of the simulation model; and
- Explain how to use the components of the library and present some simulation examples.
This simulation library is build on top of some well know python libraries as well as some specific python an R libraries.
Python libraries | Use |
pandas | Data library for python |
numpy | Numerical model in python |
scipy | Scientific python |
statsmodels | Statistical models |
Theano | Compiled numerical computation library. |
jupyterhub | Used as main UI |
matplotlib | De facto python plotting library |
seaborn | Statistical plots |
pymc3 | Bayesian Statistics, MCMC |
ipfn | Iterative Proportional Fitting |
XlsxWriter | Create excel files |
R libraries | Use |
GREGWT | Sample reweighting library |