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
.
- class systemds.operator.Scalar(sds_context, operation: str, unnamed_input_nodes: Iterable[DAGNode | str | int | float | bool] = None, named_input_nodes: Dict[str, DAGNode | str | int | float | bool] = None, assign: bool = False)
- __init__(sds_context, operation: str, unnamed_input_nodes: Iterable[DAGNode | str | int | float | bool] = None, named_input_nodes: Dict[str, DAGNode | str | int | float | bool] = None, 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
is_python_local_data – if the data is local in python e.g. Numpy arrays that this operation node returns multiple values. If set remember to set the output_types value as well.
- ceil() Scalar
Return the ceiling of the input, element-wise.
- Returns:
Scalar representing operation
- 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
- 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
- floor() Scalar
Return the floor of the input, element-wise.
- Returns:
Scalar representing operation
- isInf() Scalar
Computes a boolean indicator matrix of the same shape as the input, indicating where Inf (positive or negative infinity) values are located. :return: the OperationNode representing this operation
- isNA() Scalar
Computes a boolean indicator matrix of the same shape as the input, indicating where NA (not available) values are located. Currently, NA is only capturing NaN values.
- Returns:
the OperationNode representing this operation
- isNaN() Scalar
Computes a boolean indicator matrix of the same shape as the input, indicating where NaN (not a number) values are located.
- Returns:
the OperationNode representing this operation
- pass_python_data_to_prepared_script(sds, var_name: str, prepared_script: 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