Scalar¶
A Scalar is represented either by an OperationNode, or the derived class Scalar.
Scalar can contain strings, ints, floats.
Although it is possible to generate Scalars with the function calls or object construction specified below,
the recommended way is to use the methods defined on SystemDSContext.
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class
systemds.operator.Scalar(sds_context: SystemDSContext, operation: str, unnamed_input_nodes: Iterable[Union[DAGNode, str, int, float, bool]] = None, named_input_nodes: Dict[str, Union[DAGNode, str, int, float, bool]] = None, output_type: systemds.script_building.dag.OutputType = <OutputType.DOUBLE: 1>, assign: bool = False)¶ -
__init__(sds_context: SystemDSContext, operation: str, unnamed_input_nodes: Iterable[Union[DAGNode, str, int, float, bool]] = None, named_input_nodes: Dict[str, Union[DAGNode, str, int, float, bool]] = None, output_type: systemds.script_building.dag.OutputType = <OutputType.DOUBLE: 1>, assign: bool = False) → Scalar¶ Create general OperationNode
- Parameters
sds_context – The SystemDS context for performing the operations
operation – The name of the DML function to execute
unnamed_input_nodes – inputs identified by their position, not name
named_input_nodes – inputs with their respective parameter name
output_type – type of the output in DML (double, matrix etc.)
is_python_local_data – if the data is local in python e.g. Numpy arrays
number_of_outputs – If set to other value than 1 then it is expected that this operation node returns multiple values. If set remember to set the output_types value as well.
output_types – The types of output in a multi output scenario. Default is None, and means every multi output is a matrix.
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abs() → systemds.operator.nodes.scalar.Scalar¶ Calculate absolute.
- Returns
Scalar representing operation
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acos() → systemds.operator.nodes.scalar.Scalar¶ Calculate arccos.
- Returns
Scalar representing operation
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asin() → systemds.operator.nodes.scalar.Scalar¶ Calculate arcsin.
- Returns
Scalar representing operation
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atan() → systemds.operator.nodes.scalar.Scalar¶ Calculate arctan.
- Returns
Scalar representing operation
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code_line(var_name: str, unnamed_input_vars: Sequence[str], named_input_vars: Dict[str, str]) → str¶ Generates the DML code line equal to the intended action of this node.
- Parameters
var_name – Name of DML-variable this nodes result should be saved in
unnamed_input_vars – all strings representing the unnamed parameters
named_input_vars – all strings representing the named parameters (name value pairs)
- Returns
the DML code line that is equal to this operation
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compute(verbose: bool = False, lineage: bool = False)¶ Get result of this operation. Builds the dml script and executes it in SystemDS, before this method is called all operations are only building the DAG without actually executing (lazy evaluation).
- Parameters
verbose – Can be activated to print additional information such as created DML-Script
lineage – Can be activated to print lineage trace till this node
- Returns
the output as an python builtin data type or numpy array
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cos() → systemds.operator.nodes.scalar.Scalar¶ Calculate cos.
- Returns
Scalar representing operation
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cosh() → systemds.operator.nodes.scalar.Scalar¶ Calculate cos.
- Returns
Scalar representing operation
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pass_python_data_to_prepared_script(sds, var_name: str, prepared_script: py4j.java_gateway.JavaObject) → None¶ Passes data from python to the prepared script object.
- Parameters
jvm – the java virtual machine object
var_name – the variable name the data should get in java
prepared_script – the prepared script
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sin() → systemds.operator.nodes.scalar.Scalar¶ Calculate sin.
- Returns
Scalar representing operation
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sinh() → systemds.operator.nodes.scalar.Scalar¶ Calculate sin.
- Returns
Scalar representing operation
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tan() → systemds.operator.nodes.scalar.Scalar¶ Calculate tan.
- Returns
Scalar representing operation
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tanh() → systemds.operator.nodes.scalar.Scalar¶ Calculate tan.
- Returns
Scalar representing operation
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