ui framework for distributed fitting service paul kienzle wenwu chen, ziwen fu reflectometry group,...

UI Framework for Distributed Fitting Service

Paul KienzleWenwu Chen, Ziwen Fu

Reflectometry Group,NIST

Software Infrastructure of PARK: the distributed fitting service

Job Server

ServiceService

ServiceService

Working Nodes

User Interface

Scientist (Application)

View Developer (UI)Reduce Service Developer (Reduce)

Data reduction

Theory Developer (Map)

Data simulation

Data presentation

Model buildingData View

Distributed Computing Environmentloose coupled server/client pattern (map/reduce)

Service ServerMaster Node

User

Cluster

Working Nodes

User/Client

ServiceServerManagement

WorkingServer

User User User User

UI Overview

• High Level– Job Work flow– Job History, Redo, Undo– ……

• Low level (UI/GUI*)– Model building (dataset, reduction, model)– Job request– Viewer of Job reply

Data Structure & UI for Fitting(1)

FittingConstrain

Data Structure & UI for Fitting(2)

FittingModelBuilder

FittingDatasetViewer/EditorFittingResultsViewer

Developed GUI for Fitting Service

• TraitsUI– Easy for simple applications– Less-controllable of the widgets– Compatible, complexity, speed

• wx AUI + matplotlib– Dataset orientated (works now, version 0.3)– Job orientated (in developing, version 0.4)– wx.plot now, changed to matplotlib later

• Future?

GUI Framework

FittingConstrain

FittingModelBuilderFittingDatasetViewer

FittingDatasetEditor

FittingModelPage

Dataset event

Dataset event

Model event

Model event Model events:1. The whole model is updated2. The parameter value is changed

FittingViewer

Network event

Models

• Dataset UI

– DatasetViewer : FittingDatasetViewer– DatasetEditor : FittingDatasetEditor– DatasetMetadataViewer : FittingDatasetMetaViewer

Data Structure– Dataset : XmlDataset (data reduction)– Data : XmlData (read/write data)– MetaData : XmlMetaData (read/write data)– Parameter : XmlParameter (parameters for model)

Models

• ModelBuilder UI

– ModelPage : FittingModelPage– ModelBuilder : FittingModelBuilder– ModelResultViewer: FittingViewer (optional)– ModelParameterViewer:

FittingParameterViewer (optional)

Theory– ModelTheory: Theory

Available Models: Gaussian Fitting, Reflectometry for NCNR and SNS~/park/parkClient/builder/gauss, NCNRRefl, refl

Examples: Gaussian Fitting

• Theory (Theory developer)– GaussTheory

• Data structure (Theory & UI developer)– GaussXmlDataset, GaussXmlData– GaussParameter

• Dataset (UI developer)– GaussDatasetViewer, GaussDatasetEditor– GaussDatasetMeta, GaussDatasetPanel

• Model Builder (UI developer)– GaussModelPage, GaussModelBuilder

Examples: SNS Refl Fitting

• Theory – ReflTheory*

• Data structure – ReflSNSDataset, ReflSNSData– ReflParameter*

• Dataset – reflDatasetViewer, reflDatasetEditor– reflDatasetMeta, reflDatasetPanel

• Model Builder – ReflModelPage, ReflModelBuilder

Examples: NCNR Refl Fitting

• Theory – ReflTheory*

• Data structure – NCNRDataset, NCNRData– ReflParameter*

• Dataset – NCNRDatasetViewer, NCNRDatasetEditor– NCNRDatasetMeta, NCNRDatasetPanel

• Model Builder – ReflModelPage, ReflModelBuilder

Shared with SNS Refl Fitting

Download PARK

Source code:

svn co svn://svn@danse.us/park

Windows executable files:

http://chemnuc-20.umd.edu/~DANSE/ download/index.html

Data Structure & UI for Fitting(1)

XmlMultiplexor

Data Structure & UI for Fitting(2)

Fitting• doFitting()

– Return the object representing the fitting results• getOptimizer()

– Return a real optimizer object• getXmlOptimizer()

– return the object that is the xml representation of the optimizer• setXmlOptimizer(optimizer)

– set the object that is the xml representation of the optimizer• getXmlMultiplexor()

– get the object that is the xml representation of the multiplexor• setXmlMultiplexor(xor)

– set the object that is the xml representation of the multiplexor

XmlMultiplexor

• getVariables() – Return a list of variable definitions– Variable attributes:

• Name: read only, model_name.parameter_name.attribute_name• Flag: ‘optimized’ | ‘fixed’ | ‘constrains’• Value: initial value• Range: [value0, value1]

• getConstrains()– Return a list of variable constrains– Constrain attributes:

• Target: model_name.parameter_name.attribute_name• Constrain expression: string representation of constrain• evaluate(): evaluate and set the parameter’s value

• getModels() – Return a list of models

Model

• getDataSet()– Return the data set object representing the experimental

data and meta data

• getWeight() / setWeight(weight)– Get/set the weight

• getTheory() / setTheoryName(string name)– Return /set the theory object to calculate the theoretical

data.

• getParameters() / addParameter()– Return the parameters representing the model

Dataset• addData(data)

– Add a data• removeData(data)

– Remove a data• getData()

– Return a list of data• getReductionData()

– Return the joined experimental data in order of (x, y, dy)*– x, y, dy are data objects

• setTheoryData(data)– Set the theoretical data associated with the dataset

• getTheoryData()– Return the theory data associated with the dataset

• getDataSourceType()– Return the data source type

• setDataSourceType(dstype)– Set the data source type

– XML format for dataset<dataset>

<data> … </data>* <reduction> [<array> array_data </array> <matrix> </matrix> <narray> </narray>]* reduction_data</reduction> <theory> [<array> array_data </array> <matrix> </matrix> <narray> </narray>]* theory_data </theory>

</dataset>

Data• getReductionData() / getRawData()

– Return the reduction/raw data in order of(x, y, dy)*

• getMetaData()– Return the meta data associated with this data

• getDataSourceType()– Return the data source type

• setDataSourceType(dstype)– Set the data source type

• _readData ()– Read the data from the data source

• _writeData ()– Write the data to the data source

DataSourceType:– ‘Local’, ‘Imbed’, ‘Reply’, ‘URL’, ‘USER’

MetaData / Parametermetadata.para_name = para_valueparameter.attr_name = attr_value

Theory• getDataset() / setDataset(dataset)

– Return the dataset / set the dataset object• getParameters()

– Return a list of parameters• getTheoryData()

– Return the theoretical data object• getObjectiveFx()

– Return the objective function for optimizer• has1stDerivate / has2ndDerivate (parameter_name) /

– Return the true if the given parameter has the 1st or 2nd derivative

Optimizer

optimizer.para_name = para_value

Optimize()do the optimization

<fitting> <multiplexor> <model modelType="gauss" name="M0“

theory="gaussTheory.GaussTheory" weight="1.0"> <dataset classname="gaussXmlDataSource.GaussXmlDataset" srctype="local"> <data classname="gaussXmlDataSource.GaussXmlData“ file="C:\ gauss\gauss1.dat" srctype="local"> <gauss scale="0.500000015926"/> </data>

<data classname="gaussXmlDataSource.GaussXmlData" file="C:\gauss\gauss1.dat" srctype="local"> <gauss scale="0.500000015926"/> </data> </dataset> <param a0="39.0" name="g0" sigma="1.0" x0="0.0"/> </model> <optimizer classname=‘scipy.sciopt‘ funcname=‘fmin’

xtol='1e-005' ftol='1e-005' maxiter='1000'/> </multiplexor></fitting>

<fitting> <multiplexor> <model name='M0' theory=‘reflTheory' weight='1.0'>

<dataset classname=‘NCNRReflDataset.NCNRDataset' name='Dataset1' srctype='local'>

<data srctype='local' classname='shannonDataset.ShannonData' file='C:\Documents and Settings\UMCP\park-0.3.8\du53.dat'>

<NCNR wavelength='14.85' scale='1.0' divergence='10' offset2='2.0'

offset='2.0' wavelengthdivergence='0.021' angulardivergence='0.007' background='1e-010'/>

</data> </dataset> <profile> … </profile></model><constrains></constrains><variables></variables></multiplexor><optimizer classname='boxmin' xtol='1e-005' ftol='1e-005' maxiter='1000'/></fitting>

<profile script='profile.py'>from parseReflModelNb import *M1 = ReflModel("M1", file="inline", magnetic=False)M1.incident('Air', phi=0)M1.interface(8)M1.layer('dPS', depth=[80,90], rho=[5, 6, 9], mu=0)M1.interface(5)M1.layer('P2VP', depth=[10, 30], rho=[1, 1.8, 3], mu=0)M1.interface(5)M1.layer('SiOx', depth=[14, 20.4], rho=3.80, mu=0)M1.interface(5)M1.substrate('Si', rho=2.07, mu=0 )fit = ParkFit([M1])

</profile>