BCIgui/Masterarbeit/openvibe/extras-master/plugins/processing/riemannian/bci-examples/0.2-Riemann-Classic-NOISE-Training.xml

<OpenViBE-Scenario>
	<FormatVersion>2</FormatVersion>
	<Creator>OpenViBE Designer</Creator>
	<CreatorVersion>2.2.0</CreatorVersion>
	<Settings>
		<Setting>
			<Identifier>(0x004d2731, 0x8fa767ea)</Identifier>
			<TypeIdentifier>(0x79a9edeb, 0x245d83fc)</TypeIdentifier>
			<Name>Directory</Name>
			<DefaultValue>${Player_ScenarioDirectory}/</DefaultValue>
			<Value>${Player_ScenarioDirectory}</Value>
		</Setting>
		<Setting>
			<Identifier>(0x0002ec8d, 0xace742b6)</Identifier>
			<TypeIdentifier>(0x330306dd, 0x74a95f98)</TypeIdentifier>
			<Name>Model Filename</Name>
			<DefaultValue>Classification-Riemann-Classic-Training-Model.xml</DefaultValue>
			<Value>Riemann-Classic-Training-Model.xml</Value>
		</Setting>
		<Setting>
			<Identifier>(0x001828e2, 0x99ca3842)</Identifier>
			<TypeIdentifier>(0x330306dd, 0x74a95f98)</TypeIdentifier>
			<Name>LWF Mean</Name>
			<DefaultValue>Mean-Riemann-LWF.csv</DefaultValue>
			<Value>Mean-Riemann-LWF.csv</Value>
		</Setting>
		<Setting>
			<Identifier>(0x001e2b6a, 0x511e6a8e)</Identifier>
			<TypeIdentifier>(0x330306dd, 0x74a95f98)</TypeIdentifier>
			<Name>COR Mean</Name>
			<DefaultValue>Mean-Riemann-COR.csv</DefaultValue>
			<Value>Mean-Riemann-COR.csv</Value>
		</Setting>
		<Setting>
			<Identifier>(0x004939a9, 0xe3c4dec6)</Identifier>
			<TypeIdentifier>(0x007deef9, 0x2f3e95c6)</TypeIdentifier>
			<Name>Log Level</Name>
			<DefaultValue>Information</DefaultValue>
			<Value>Information</Value>
		</Setting>
	</Settings>
	<Inputs></Inputs>
	<Outputs></Outputs>
	<Boxes>
		<Box>
			<Identifier>(0x0000241d, 0x0000786a)</Identifier>
			<Name>LWF</Name>
			<AlgorithmClassIdentifier>(0x9a93af80, 0x6449c826)</AlgorithmClassIdentifier>
			<Inputs>
				<Input>
					<TypeIdentifier>(0x5ba36127, 0x195feae1)</TypeIdentifier>
					<Name>Input Signal</Name>
				</Input>
			</Inputs>
			<Outputs>
				<Output>
					<TypeIdentifier>(0x544a003e, 0x6dcba5f6)</TypeIdentifier>
					<Name>Output Covariance Matrix</Name>
				</Output>
			</Outputs>
			<Settings>
				<Setting>
					<TypeIdentifier>(0x5261636b, 0x45535449)</TypeIdentifier>
					<Name>Estimator</Name>
					<DefaultValue>Covariance</DefaultValue>
					<Value>Ledoit and Wolf</Value>
					<Modifiability>false</Modifiability>
				</Setting>
				<Setting>
					<TypeIdentifier>(0x2cdb2f0b, 0x12f231ea)</TypeIdentifier>
					<Name>Center Data</Name>
					<DefaultValue>true</DefaultValue>
					<Value>true</Value>
					<Modifiability>false</Modifiability>
				</Setting>
				<Setting>
					<TypeIdentifier>(0xa88b3667, 0x0871638c)</TypeIdentifier>
					<Name>Log Level</Name>
					<DefaultValue>Information</DefaultValue>
					<Value>$var{Log Level}</Value>
					<Modifiability>false</Modifiability>
				</Setting>
			</Settings>
			<Attributes>
				<Attribute>
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		</Box>
		<Box>
			<Identifier>(0x0000241d, 0x0000786b)</Identifier>
			<Name>COR</Name>
			<AlgorithmClassIdentifier>(0x9a93af80, 0x6449c826)</AlgorithmClassIdentifier>
			<Inputs>
				<Input>
					<TypeIdentifier>(0x5ba36127, 0x195feae1)</TypeIdentifier>
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				</Input>
			</Inputs>
			<Outputs>
				<Output>
					<TypeIdentifier>(0x544a003e, 0x6dcba5f6)</TypeIdentifier>
					<Name>Output Covariance Matrix</Name>
				</Output>
			</Outputs>
			<Settings>
				<Setting>
					<TypeIdentifier>(0x5261636b, 0x45535449)</TypeIdentifier>
					<Name>Estimator</Name>
					<DefaultValue>Covariance</DefaultValue>
					<Value>Pearson Correlation</Value>
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				</Setting>
				<Setting>
					<TypeIdentifier>(0x2cdb2f0b, 0x12f231ea)</TypeIdentifier>
					<Name>Center Data</Name>
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				</Setting>
				<Setting>
					<TypeIdentifier>(0xa88b3667, 0x0871638c)</TypeIdentifier>
					<Name>Log Level</Name>
					<DefaultValue>Information</DefaultValue>
					<Value>$var{Log Level}</Value>
					<Modifiability>false</Modifiability>
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			<Identifier>(0x00003577, 0x00001a8d)</Identifier>
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			<Inputs>
				<Input>
					<TypeIdentifier>(0x544a003e, 0x6dcba5f6)</TypeIdentifier>
					<Name>Input Stream</Name>
				</Input>
			</Inputs>
			<Outputs>
				<Output>
					<TypeIdentifier>(0x6f752dd0, 0x082a321e)</TypeIdentifier>
					<Name>Output Stimulations</Name>
				</Output>
			</Outputs>
			<Settings>
				<Setting>
					<TypeIdentifier>(0x007deef9, 0x2f3e95c6)</TypeIdentifier>
					<Name>Timeout delay</Name>
					<DefaultValue>5</DefaultValue>
					<Value>20</Value>
					<Modifiability>false</Modifiability>
				</Setting>
				<Setting>
					<TypeIdentifier>(0x2c132d6e, 0x44ab0d97)</TypeIdentifier>
					<Name>Output Stimulation</Name>
					<DefaultValue>OVTK_StimulationId_Label_00</DefaultValue>
					<Value>OVTK_StimulationId_Train</Value>
					<Modifiability>false</Modifiability>
				</Setting>
			</Settings>
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			<Identifier>(0x00004173, 0x000028f8)</Identifier>
			<Name>Simple DSP</Name>
			<AlgorithmClassIdentifier>(0x00e26fa1, 0x1dbab1b2)</AlgorithmClassIdentifier>
			<Inputs>
				<Input>
					<TypeIdentifier>(0x5ba36127, 0x195feae1)</TypeIdentifier>
					<Name>Input - A</Name>
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			</Inputs>
			<Outputs>
				<Output>
					<TypeIdentifier>(0x5ba36127, 0x195feae1)</TypeIdentifier>
					<Name>Output</Name>
				</Output>
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			<Settings>
				<Setting>
					<TypeIdentifier>(0x79a9edeb, 0x245d83fc)</TypeIdentifier>
					<Name>Equation</Name>
					<DefaultValue>x</DefaultValue>
					<Value>(x+1)*10</Value>
					<Modifiability>false</Modifiability>
				</Setting>
			</Settings>
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			<Name>Tangent Space</Name>
			<AlgorithmClassIdentifier>(0x7c265dba, 0x202c1f70)</AlgorithmClassIdentifier>
			<Inputs>
				<Input>
					<TypeIdentifier>(0x544a003e, 0x6dcba5f6)</TypeIdentifier>
					<Name>Input Covariance Matrix</Name>
				</Input>
			</Inputs>
			<Outputs>
				<Output>
					<TypeIdentifier>(0x17341935, 0x152ff448)</TypeIdentifier>
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				</Output>
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			<Settings>
				<Setting>
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				<Setting>
					<TypeIdentifier>(0x330306dd, 0x74a95f98)</TypeIdentifier>
					<Name>Filename to Reference Matrix (CSV, empty for Identity)</Name>
					<DefaultValue>${Player_ScenarioDirectory}/Mean.csv</DefaultValue>
					<Value>$var{Directory}/$var{LWF Mean}</Value>
					<Modifiability>false</Modifiability>
				</Setting>
				<Setting>
					<TypeIdentifier>(0xa88b3667, 0x0871638c)</TypeIdentifier>
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				<Output>
					<TypeIdentifier>(0x17341935, 0x152ff448)</TypeIdentifier>
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				<Setting>
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				<Setting>
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					<DefaultValue>Information</DefaultValue>
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			</Source>
			<Target>
				<BoxIdentifier>(0x00004173, 0x000028f8)</BoxIdentifier>
				<BoxInputIndex>0</BoxInputIndex>
			</Target>
		</Link>
		<Link>
			<Identifier>(0x000046df, 0x00001885)</Identifier>
			<Source>
				<BoxIdentifier>(0x00003577, 0x00001a8d)</BoxIdentifier>
				<BoxOutputIndex>0</BoxOutputIndex>
			</Source>
			<Target>
				<BoxIdentifier>(0x00005062, 0x000009d6)</BoxIdentifier>
				<BoxInputIndex>0</BoxInputIndex>
			</Target>
		</Link>
		<Link>
			<Identifier>(0x00004966, 0x0000478e)</Identifier>
			<Source>
				<BoxIdentifier>(0x000044b9, 0x00003dae)</BoxIdentifier>
				<BoxOutputIndex>0</BoxOutputIndex>
			</Source>
			<Target>
				<BoxIdentifier>(0x000078f6, 0x0000791c)</BoxIdentifier>
				<BoxInputIndex>0</BoxInputIndex>
			</Target>
		</Link>
		<Link>
			<Identifier>(0x00004acb, 0x000025a9)</Identifier>
			<Source>
				<BoxIdentifier>(0x000044b9, 0x00003dac)</BoxIdentifier>
				<BoxOutputIndex>0</BoxOutputIndex>
			</Source>
			<Target>
				<BoxIdentifier>(0x00005062, 0x000009d6)</BoxIdentifier>
				<BoxInputIndex>2</BoxInputIndex>
			</Target>
		</Link>
		<Link>
			<Identifier>(0x000065fa, 0x000032fe)</Identifier>
			<Source>
				<BoxIdentifier>(0x000044b9, 0x00003dad)</BoxIdentifier>
				<BoxOutputIndex>0</BoxOutputIndex>
			</Source>
			<Target>
				<BoxIdentifier>(0x000078f6, 0x0000791b)</BoxIdentifier>
				<BoxInputIndex>0</BoxInputIndex>
			</Target>
		</Link>
		<Link>
			<Identifier>(0x000068c9, 0x00003f16)</Identifier>
			<Source>
				<BoxIdentifier>(0x0000241d, 0x0000786a)</BoxIdentifier>
				<BoxOutputIndex>0</BoxOutputIndex>
			</Source>
			<Target>
				<BoxIdentifier>(0x000044b9, 0x00003dab)</BoxIdentifier>
				<BoxInputIndex>0</BoxInputIndex>
			</Target>
		</Link>
		<Link>
			<Identifier>(0x00006fb3, 0x00007389)</Identifier>
			<Source>
				<BoxIdentifier>(0x00004173, 0x000028f8)</BoxIdentifier>
				<BoxOutputIndex>0</BoxOutputIndex>
			</Source>
			<Target>
				<BoxIdentifier>(0x0000241d, 0x0000786a)</BoxIdentifier>
				<BoxInputIndex>0</BoxInputIndex>
			</Target>
		</Link>
		<Link>
			<Identifier>(0x00007539, 0x00000593)</Identifier>
			<Source>
				<BoxIdentifier>(0x000044b9, 0x00003dac)</BoxIdentifier>
				<BoxOutputIndex>0</BoxOutputIndex>
			</Source>
			<Target>
				<BoxIdentifier>(0x000078f6, 0x0000791a)</BoxIdentifier>
				<BoxInputIndex>0</BoxInputIndex>
			</Target>
		</Link>
		<Link>
			<Identifier>(0x00007b2f, 0x00001c30)</Identifier>
			<Source>
				<BoxIdentifier>(0x000044b9, 0x00003dab)</BoxIdentifier>
				<BoxOutputIndex>0</BoxOutputIndex>
			</Source>
			<Target>
				<BoxIdentifier>(0x00005062, 0x000009d6)</BoxIdentifier>
				<BoxInputIndex>1</BoxInputIndex>
			</Target>
		</Link>
	</Links>
	<Comments>
		<Comment>
			<Identifier>(0x000054d7, 0x00005adf)</Identifier>
			<Text>Compute Feature 
(Need to run previous scenario)</Text>
			<Attributes>
				<Attribute>
					<Identifier>(0x473d9a43, 0x97fc0a97)</Identifier>
					<Value>160</Value>
				</Attribute>
				<Attribute>
					<Identifier>(0x7234b86b, 0x2b8651a5)</Identifier>
					<Value>304</Value>
				</Attribute>
			</Attributes>
		</Comment>
		<Comment>
			<Identifier>(0x000054d7, 0x00005ae0)</Identifier>
			<Text>Input Signal</Text>
			<Attributes>
				<Attribute>
					<Identifier>(0x473d9a43, 0x97fc0a97)</Identifier>
					<Value>160</Value>
				</Attribute>
				<Attribute>
					<Identifier>(0x7234b86b, 0x2b8651a5)</Identifier>
					<Value>144</Value>
				</Attribute>
			</Attributes>
		</Comment>
		<Comment>
			<Identifier>(0x000054d7, 0x00005ae1)</Identifier>
			<Text>Compute Covariance</Text>
			<Attributes>
				<Attribute>
					<Identifier>(0x473d9a43, 0x97fc0a97)</Identifier>
					<Value>160</Value>
				</Attribute>
				<Attribute>
					<Identifier>(0x7234b86b, 0x2b8651a5)</Identifier>
					<Value>224</Value>
				</Attribute>
			</Attributes>
		</Comment>
		<Comment>
			<Identifier>(0x000054d7, 0x00005ae2)</Identifier>
			<Text>Display</Text>
			<Attributes>
				<Attribute>
					<Identifier>(0x473d9a43, 0x97fc0a97)</Identifier>
					<Value>176</Value>
				</Attribute>
				<Attribute>
					<Identifier>(0x7234b86b, 0x2b8651a5)</Identifier>
					<Value>368</Value>
				</Attribute>
			</Attributes>
		</Comment>
		<Comment>
			<Identifier>(0x000054d7, 0x00005ae3)</Identifier>
			<Text>Classify</Text>
			<Attributes>
				<Attribute>
					<Identifier>(0x473d9a43, 0x97fc0a97)</Identifier>
					<Value>176</Value>
				</Attribute>
				<Attribute>
					<Identifier>(0x7234b86b, 0x2b8651a5)</Identifier>
					<Value>480</Value>
				</Attribute>
			</Attributes>
		</Comment>
	</Comments>
	<Metadata>
		<Entry>
			<Identifier>(0x05377d7e, 0x41751bb3)</Identifier>
			<Type>(0x3bcce5d2, 0x43f2d968)</Type>
			<Data>[{"boxIdentifier":"(0xffffffff, 0xffffffff)","childCount":1,"height":592,"identifier":"(0x00001f6c, 0x000012a7)","name":"Display","parentIdentifier":"(0xffffffff, 0xffffffff)","type":1,"width":831},{"boxIdentifier":"(0xffffffff, 0xffffffff)","childCount":1,"identifier":"(0x00003bf6, 0x000002ba)","index":0,"name":"Default tab","parentIdentifier":"(0x00001f6c, 0x000012a7)","type":2},{"boxIdentifier":"(0xffffffff, 0xffffffff)","childCount":2,"dividerPosition":271,"identifier":"(0x00001ce3, 0x000060d0)","index":0,"maxDividerPosition":547,"name":"Vertical split","parentIdentifier":"(0x00003bf6, 0x000002ba)","type":4},{"boxIdentifier":"(0xffffffff, 0xffffffff)","childCount":2,"dividerPosition":125,"identifier":"(0x000075ce, 0x00003e67)","index":0,"maxDividerPosition":255,"name":"Vertical split","parentIdentifier":"(0x00001ce3, 0x000060d0)","type":4},{"boxIdentifier":"(0xffffffff, 0xffffffff)","childCount":2,"dividerPosition":128,"identifier":"(0x00001e51, 0x000013a9)","index":1,"maxDividerPosition":255,"name":"Vertical split","parentIdentifier":"(0x00001ce3, 0x000060d0)","type":4},{"boxIdentifier":"(0x000078f6, 0x00007919)","childCount":0,"identifier":"(0x00006d43, 0x000076f1)","index":0,"parentIdentifier":"(0x000075ce, 0x00003e67)","type":3},{"boxIdentifier":"(0x000078f6, 0x0000791a)","childCount":0,"identifier":"(0x00003dc4, 0x00004b7c)","index":1,"parentIdentifier":"(0x000075ce, 0x00003e67)","type":3},{"boxIdentifier":"(0x000078f6, 0x0000791b)","childCount":0,"identifier":"(0x00006429, 0x00003b15)","index":0,"parentIdentifier":"(0x00001e51, 0x000013a9)","type":3},{"boxIdentifier":"(0x000078f6, 0x0000791c)","childCount":0,"identifier":"(0x00001547, 0x000040e0)","index":1,"parentIdentifier":"(0x00001e51, 0x000013a9)","type":3}]</Data>
		</Entry>
	</Metadata>
	<Attributes>
		<Attribute>
			<Identifier>(0x079d1f09, 0x667c7871)</Identifier>
			<Value></Value>
		</Attribute>
		<Attribute>
			<Identifier>(0x4c90d4ad, 0x7a2554ec)</Identifier>
			<Value>320</Value>
		</Attribute>
		<Attribute>
			<Identifier>(0x60bc58ab, 0x7a1b4d83)</Identifier>
			<Value></Value>
		</Attribute>
		<Attribute>
			<Identifier>(0x790d75b8, 0x3bb90c33)</Identifier>
			<Value>Thibaut Monseigne</Value>
		</Attribute>
		<Attribute>
			<Identifier>(0x7a3a1558, 0xf12c63c2)</Identifier>
			<Value></Value>
		</Attribute>
		<Attribute>
			<Identifier>(0x7b814cca, 0x271df6dd)</Identifier>
			<Value>475</Value>
		</Attribute>
		<Attribute>
			<Identifier>(0x84009d7c, 0x3c4e763b)</Identifier>
			<Value></Value>
		</Attribute>
		<Attribute>
			<Identifier>(0x8c1fc55b, 0x7b433dc2)</Identifier>
			<Value>1.0</Value>
		</Attribute>
		<Attribute>
			<Identifier>(0x9f5c4075, 0x4a0d3666)</Identifier>
			<Value>Classification Riemann Classic Training Example</Value>
		</Attribute>
		<Attribute>
			<Identifier>(0xf36a1567, 0xd13c53da)</Identifier>
			<Value></Value>
		</Attribute>
		<Attribute>
			<Identifier>(0xf6b2e3fa, 0x7bd43926)</Identifier>
			<Value>bci-examples</Value>
		</Attribute>
		<Attribute>
			<Identifier>(0xf8034a49, 0x8b3f37cc)</Identifier>
			<Value>Inria</Value>
		</Attribute>
	</Attributes>
</OpenViBE-Scenario>