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matlab.io.datastore.SimulationDatastore class

Package:matlab.io.datastore

Datastore for inputs and outputs of金宝appmodels

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Description

Amatlab.io.datastore.SimulationDatastoreobject enables a Simulink®model to interact with big data. You can load big data as simulation input and log big output data from a simulation. To simulate models with big data, you store the data in a MAT-file and refer to the data through aSimulationDatastoreobject. SeeWork with Big Data for Simulations.

ASimulationDatastoreobject refers to big simulation data (which a MAT-file stores) for one signal. If the MAT-file stores simulation data for a bus signal, aSimulationDatastoreobject refers to the data for one leaf signal element in the bus. You can use the datastore object to inspect and access the data and, through a parent object such asSimulink.SimulationData.Signal, simulate a Simulink model with the data.

To analyze the datastore data, you can use the methods and properties of theSimulationDatastoreobject as well as MATLAB®tools such as thetallfunction. For more information about the MATLAB tools, seeGetting Started with Datastore.

Construction

After you store big simulation data in aSimulink.SimulationData.Datasetobject in a MAT-file, a signal element in theDatasetobject points to the big data. To create amatlab.io.datastore.SimulationDatastoreobject that refers to the big data:

  1. At the command prompt or in a script, create aSimulink.SimulationData.DatasetRefobject that refers to theDatasetobject in the MAT-file.

  2. Use one of these techniques:

    • Use one-based, curly-brace indexing (for example,{1}) to return an object that represents the target signal element, such asSimulink.SimulationData.SignalorSimulink.SimulationData.State. For example, for aDatasetRefobject namedlogsout_ref, to create aSignalobject that refers to the second signal element, use this code:

      myLoggedSig = logsout_ref{2}

    • Use thegetAsDatastoremethod of theDatasetRefobject to return an object that represents the target signal element. For more information, seegetAsDatastore.

TheSimulationDatastoreobject resides in theValuesproperty of the returned object.

Properties

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Name and path of the file that contains the big data, returned as a character vector. This property is read-only.

Data Types:char

Total number of samples (time steps) in the datastore, returned as an integer. Thereadallmethod extracts this many samples from the big data. This property is read-only.

Data Types:uint64

Amount of data to read at a time, in number of samples (time steps), specified as a scalar double. Thereadmethod extracts this many samples from the big data.

Data Types:double

Methods

hasdata Determine if data is available to read
isPartitionable Determine whether datastore is partitionable
isShuffleable Determine whether datastore is shuffleable
preview Return subset of data from datastore
progress Return percentage of data that you have read from a datastore
read Read data in datastore
readall Read all data in datastore
reset Reset datastore to initial state

Copy Semantics

Handle. To learn how handle classes affect copy operations, seeCopying Objects.

Limitations

  • SimulationDatastoredoes not support using a parallel pool with Parallel Computing Toolbox™ installed. To analyze data using tall arrays or run MapReduce algorithms, set the global execution environment to be the local MATLAB session usingmapreduce. Enter this code:

    mapreduce(0)
    For information about controlling parallel resources, seeRun mapreduce on a Parallel Pool(Parallel Computing Toolbox).

  • You cannot use a MATLAB tall variable as simulation input data.

Examples

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Open Script

This example shows how to log big data from a simulation and inspect and analyze portions of that data by interacting with amatlab.io.datastore.SimulationDatastoreobject.

Log Big Data from Model

Open the example modelsldemo_fuelsys.

open_system('sldemo_fuelsys')

SelectConfiguration Parameters > Data Import/Export > Log Dataset data to file.

set_param('sldemo_fuelsys','LoggingToFile','on')

Simulate the model.

sim('sldemo_fuelsys')

The MAT-fileout.matappears in your current folder. The file contains data for logged signals such asfuel(which is at the root level of the model).

At the command prompt, create aDatasetRef对象是指记录变量的名字,sldemo_fuelsys_output.

DSRef = Simulink.SimulationData.DatasetRef('out.mat','sldemo_fuelsys_output');

Preview Big Data

Use curly braces ({and}) to extract the signal elementfuel, which is the tenth element inDSRef, as aSimulink.SimulationData.Signalobject that contains aSimulationDatastoreobject.

SimDataSig = DSRef{10};

To more easily interact with theSimulationDatastoreobject that resides in theValuesproperty of theSignalobject, store a handle in a variable namedDStore.

DStore = SimDataSig.Values;

Use thepreviewmethod to inspect the first five samples of logged data for thefuelsignal.

preview(DStore)
ans = 10x1 timetable Time Data ______________ ______ 0 sec 1.209 0.00056199 sec 1.209 0.0033719 sec 1.209 0.01 sec 1.1729 0.02 sec 1.1409 0.03 sec 1.1124 0.04 sec 1.0873 0.05 sec 1.0652 0.055328 sec 1.0652 0.055328 sec 1.0652

Inspect Specific Sample

Inspect the 603rd sample of loggedfueldata.

Set theReadSizeproperty ofDStoreto a number that, considering memory resources, your computer can tolerate. For example, setReadSizeto200.

DStore.ReadSize = 200;

Read from the datastore three times. Each read operation advances the reading position by 200 samples.

read(DStore); read(DStore); read(DStore);

Now that you are very close to the 603rd sample, setReadSizeto a smaller number. For example, setReadSizeto5.

DStore.ReadSize = 5;

Read from the datastore again.

read(DStore)
ans = 5x1 timetable Time Data ________ ______ 5.79 sec 1.6097 5.8 sec 1.6136 5.81 sec 1.6003 5.82 sec 1.5904 5.83 sec 1.5832

The third sample of read data is the 603rd sample in the datastore.

Inspect Earlier Sample

Inspect the 403rd sample of loggedfueldata. Due to previous read operations, the datastore now reads starting from the 606th sample, so you must reset the datastore. Then, you can read from the first sample up to the 403rd sample.

Use theresetmethod to resetDStore.

reset(DStore);

SetReadSizeto200again.

DStore.ReadSize = 200;

Read from the datastore twice to advance the read position to the 401st sample.

read(DStore); read(DStore);

SetReadSizeto5again.

DStore.ReadSize = 5;

Read from the datastore.

read(DStore)
ans = 5x1 timetable Time Data ________ _______ 3.85 sec 0.999 3.86 sec 0.99219 3.87 sec 0.98538 3.88 sec 0.97858 3.89 sec 0.97179

Extract Multiple Samples

Extract samples 1001 through 1020 (a total of 20 samples).

Reset the datastore.

reset(DStore)

Advance to sample 1001.

DStore.ReadSize = 200;fori = 1:5 read(DStore);end

Prepare to extract 20 samples from the datastore.

DStore.ReadSize = 20;

Extract samples 1001 through 1020. Store the extracted data in a variable namedtargetSamples.

targetSamples = read(DStore)
targetSamples = 20x1 timetable Time Data ________ ______ 9.7 sec 1.5828 9.71 sec 1.5733 9.72 sec 1.5664 9.73 sec 1.5614 9.74 sec 1.5579 9.75 sec 1.5553 9.76 sec 1.5703 9.77 sec 1.582 9.78 sec 1.5913 9.79 sec 1.5988 9.8 sec 1.605 9.81 sec 1.6101 9.82 sec 1.6145 9.83 sec 1.6184 9.84 sec 1.6049 9.85 sec 1.595 9.86 sec 1.5877 9.87 sec 1.5824 9.88 sec 1.5785 9.89 sec 1.5757

Find Maximum Value of Data in Datastore

Reset the datastore.

reset(DStore)

Write awhileloop, using thehasdatamethod, to incrementally analyze the data in chunks of 200 samples.

DStore.ReadSize = 200; runningMax = [];whilehasdata(DStore) tt = read(DStore); rawChunk = tt.Data; runningMax = max([rawChunk; runningMax]);end

Now, the variablerunningMaxstores the maximum value in the entire datastore.

runningMax
runningMax = 1.6423

Version History

Introduced in R2017a

See Also

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