Re: [UrbanSim-Users] land price estimation and RPy

From: Brian Miles <Brian.Miles_at_uvm.edu>
Date: Thu, 4 Oct 2007 11:22:43 -0400

Hi Hana,

We're currently running version 857 of Opus (from the zip file). I
pulled down the latest from SVN, but it appears that I am missing at
least one library that the latest version expects:

   File "C:\opusworkspace-svn\opus_core\database_management
\database_server.py",
line 17, in ?
     from sqlalchemy.schema import MetaData
ImportError: No module named sqlalchemy.schema

Do you have a document that lists all of the libraries required by
the latest version of Opus?

Thanks,

Brian

On Oct 3, 2007, at 4:50 PM, Hana Sevcikova wrote:

> Brian,
>
> You're right, changing the estimation procedure is not very well
> supported. I have done some changes today, so please update from
> SVN. Then you can add an argument
>
> estimation_procedure = "opus_core.estimate_linear_regression_r"
>
> to the land_price_model controller in urbansim/configs/
> general_configuration.py (in the LandPriceModelConfigurationCreator
> call) and the estimation should call that module.
>
> We haven't kept code that uses rpy up to date since our conversion
> to numpy, so yes, the module will be probably broken. But the
> suggested change should do what I understand you want to do.
>
> Let me know if you need this also for other models. We are in the
> process of changing the system of configurations, so in the future
> it should be much easier to specify these non-standard settings.
> Sorry for the inconvenience.
>
> Hana
>
>
> Brian Miles wrote:
>> Hello,
>> We are trying to configure the land price model to estimate using
>> RPy so that we can use R's AIC and plotting features.
>> I see from urbansim.models.LandPriceModel.estimate() that the
>> default estimation procedure used is that defined in
>> opus_core.estimate_linear_regression. I see that there exists
>> another potential land price estimation procedure in
>> opus_core.estimate_linear_regression_r. In theory, we would use
>> an estimation procedure something like this one to take advantage
>> of R's AIC calculation and plot generation.
>> However, I don't understand how to configure the
>> urbansim.models.LandPriceModel to use something other than the
>> default estimation procedure. Taking my cue from the
>> documentation in opus_core.RegressionModel.estimate(), I tried
>> adding the key 'estimation' with the value
>> 'opus_core.estimate_linear_regression_r' to my estimation config.
>> This doesn't work however, because LandPriceModel (a subclass of
>> RegressionModel) specifies a procedure, and the logic in
>> RegressionModel.estimate() only looks to the estimation
>> configuration for the estimation procedure if there is no estimate
>> procedure specified.
>> I temporarily--for testing purposes--modified
>> RegressionModel.estimate() to look first to the config. However
>> the things I'm setting in my estimation config (e.g. estimation,
>> cache_directory) aren't in the estimation config that
>> RegressionModel.estimate() is seeing.
>> I'm unsure of what the best way is to do what I'm trying to do
>> (specify an estimation procedure other than that which is hard
>> coded in LandPriceModel.estimate()).
>> I may not be properly specifying the estimation procedure that I
>> have to run; how should this be done? (I didn't see any specific
>> advise on this in the Opus user guide.) Or perhaps I should copy
>> the LandPriceModel into a models directory within my own package
>> and modify that? (note: I modified urbansim.models.LandPriceModel,
>> as a test, to run opus_core.estimate_linear_regression_r, and it
>> did, only this estimation procedure appears to be broken.
>> However, this is a moot point until I have an acceptable/"correct"
>> way of specifying estimation procedures to models).
>> Whether one of these or something else, what's the best way to
>> proceed?
>> Thanks,
>> Brian Miles
>> Graduate Assistant
>> Spatial Analysis Lab - Rubenstein School of Environment and
>> Natural Resources
>> University of Vermont
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Received on Thu Oct 04 2007 - 08:22:56 PDT

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