org.knime.core.node.workflow
Enum WorkflowPersistor.LoadResultEntry.LoadResultEntryType
java.lang.Object
java.lang.Enum<WorkflowPersistor.LoadResultEntry.LoadResultEntryType>
org.knime.core.node.workflow.WorkflowPersistor.LoadResultEntry.LoadResultEntryType
- All Implemented Interfaces:
- Serializable, Comparable<WorkflowPersistor.LoadResultEntry.LoadResultEntryType>
- Enclosing class:
- WorkflowPersistor.LoadResultEntry
public static enum WorkflowPersistor.LoadResultEntry.LoadResultEntryType
- extends Enum<WorkflowPersistor.LoadResultEntry.LoadResultEntryType>
Ok
public static final WorkflowPersistor.LoadResultEntry.LoadResultEntryType Ok
Warning
public static final WorkflowPersistor.LoadResultEntry.LoadResultEntryType Warning
Error
public static final WorkflowPersistor.LoadResultEntry.LoadResultEntryType Error
DataLoadError
public static final WorkflowPersistor.LoadResultEntry.LoadResultEntryType DataLoadError
values
public static WorkflowPersistor.LoadResultEntry.LoadResultEntryType[] values()
- Returns an array containing the constants of this enum type, in
the order they are declared. This method may be used to iterate
over the constants as follows:
for (WorkflowPersistor.LoadResultEntry.LoadResultEntryType c : WorkflowPersistor.LoadResultEntry.LoadResultEntryType.values())
System.out.println(c);
- Returns:
- an array containing the constants of this enum type, in
the order they are declared
valueOf
public static WorkflowPersistor.LoadResultEntry.LoadResultEntryType valueOf(String name)
- Returns the enum constant of this type with the specified name.
The string must match exactly an identifier used to declare an
enum constant in this type. (Extraneous whitespace characters are
not permitted.)
- Parameters:
name
- the name of the enum constant to be returned.
- Returns:
- the enum constant with the specified name
- Throws:
IllegalArgumentException
- if this enum type has no constant
with the specified name
NullPointerException
- if the argument is null
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University of Konstanz, Germany.
Chair for Bioinformatics and Information Mining, Prof. Dr. Michael R. Berthold.
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