<reponame>TheGoldfish01/pydpf-core
"""
identical_fc
============
"""
from ansys.dpf.core.dpf_operator import Operator
from ansys.dpf.core.inputs import Input, _Inputs
from ansys.dpf.core.outputs import Output, _Outputs, _modify_output_spec_with_one_type
from ansys.dpf.core.operators.specification import PinSpecification, Specification

"""Operators from Ans.Dpf.Native plugin, from "logic" category
"""

class identical_fc(Operator):
    """Check if two fields container are identical.

      available inputs:
        - fields_containerA (FieldsContainer)
        - fields_containerB (FieldsContainer)
        - tolerance (float)
        - small_value (float)

      available outputs:
        - boolean (bool)
        - message (str)

      Examples
      --------
      >>> from ansys.dpf import core as dpf

      >>> # Instantiate operator
      >>> op = dpf.operators.logic.identical_fc()

      >>> # Make input connections
      >>> my_fields_containerA = dpf.FieldsContainer()
      >>> op.inputs.fields_containerA.connect(my_fields_containerA)
      >>> my_fields_containerB = dpf.FieldsContainer()
      >>> op.inputs.fields_containerB.connect(my_fields_containerB)
      >>> my_tolerance = float()
      >>> op.inputs.tolerance.connect(my_tolerance)
      >>> my_small_value = float()
      >>> op.inputs.small_value.connect(my_small_value)

      >>> # Instantiate operator and connect inputs in one line
      >>> op = dpf.operators.logic.identical_fc(fields_containerA=my_fields_containerA,fields_containerB=my_fields_containerB,tolerance=my_tolerance,small_value=my_small_value)

      >>> # Get output data
      >>> result_boolean = op.outputs.boolean()
      >>> result_message = op.outputs.message()"""
    def __init__(self, fields_containerA=None, fields_containerB=None, tolerance=None, small_value=None, config=None, server=None):
        super().__init__(name="AreFieldsIdentical_fc", config = config, server = server)
        self._inputs = InputsIdenticalFc(self)
        self._outputs = OutputsIdenticalFc(self)
        if fields_containerA !=None:
            self.inputs.fields_containerA.connect(fields_containerA)
        if fields_containerB !=None:
            self.inputs.fields_containerB.connect(fields_containerB)
        if tolerance !=None:
            self.inputs.tolerance.connect(tolerance)
        if small_value !=None:
            self.inputs.small_value.connect(small_value)

    @staticmethod
    def _spec():
        spec = Specification(description="""Check if two fields container are identical.""",
                             map_input_pin_spec={
                                 0 : PinSpecification(name = "fields_containerA", type_names=["fields_container"], optional=False, document=""""""), 
                                 1 : PinSpecification(name = "fields_containerB", type_names=["fields_container"], optional=False, document=""""""), 
                                 2 : PinSpecification(name = "tolerance", type_names=["double"], optional=False, document="""Double relative tolerance. Maximum tolerance gap between to compared values: values within relative tolerance are considered identical (v1-v2)/v2 < relativeTol (default is 0.001)."""), 
                                 3 : PinSpecification(name = "small_value", type_names=["double"], optional=False, document="""Double positive small value.Smallest value which will be considered during the comparison step : all the abs(values) in field less than this value is considered as null, (default value:1.0e-14).""")},
                             map_output_pin_spec={
                                 0 : PinSpecification(name = "boolean", type_names=["bool"], optional=False, document="""bool (true if identical...)"""), 
                                 1 : PinSpecification(name = "message", type_names=["string"], optional=False, document="""""")})
        return spec


    @staticmethod
    def default_config():
        return Operator.default_config(name = "AreFieldsIdentical_fc")

    @property
    def inputs(self):
        """Enables to connect inputs to the operator

        Returns
        --------
        inputs : InputsIdenticalFc 
        """
        return super().inputs


    @property
    def outputs(self):
        """Enables to get outputs of the operator by evaluationg it

        Returns
        --------
        outputs : OutputsIdenticalFc 
        """
        return super().outputs


#internal name: AreFieldsIdentical_fc
#scripting name: identical_fc
class InputsIdenticalFc(_Inputs):
    """Intermediate class used to connect user inputs to identical_fc operator

      Examples
      --------
      >>> from ansys.dpf import core as dpf

      >>> op = dpf.operators.logic.identical_fc()
      >>> my_fields_containerA = dpf.FieldsContainer()
      >>> op.inputs.fields_containerA.connect(my_fields_containerA)
      >>> my_fields_containerB = dpf.FieldsContainer()
      >>> op.inputs.fields_containerB.connect(my_fields_containerB)
      >>> my_tolerance = float()
      >>> op.inputs.tolerance.connect(my_tolerance)
      >>> my_small_value = float()
      >>> op.inputs.small_value.connect(my_small_value)
    """
    def __init__(self, op: Operator):
        super().__init__(identical_fc._spec().inputs, op)
        self._fields_containerA = Input(identical_fc._spec().input_pin(0), 0, op, -1) 
        self._inputs.append(self._fields_containerA)
        self._fields_containerB = Input(identical_fc._spec().input_pin(1), 1, op, -1) 
        self._inputs.append(self._fields_containerB)
        self._tolerance = Input(identical_fc._spec().input_pin(2), 2, op, -1) 
        self._inputs.append(self._tolerance)
        self._small_value = Input(identical_fc._spec().input_pin(3), 3, op, -1) 
        self._inputs.append(self._small_value)

    @property
    def fields_containerA(self):
        """Allows to connect fields_containerA input to the operator

        Parameters
        ----------
        my_fields_containerA : FieldsContainer, 

        Examples
        --------
        >>> from ansys.dpf import core as dpf

        >>> op = dpf.operators.logic.identical_fc()
        >>> op.inputs.fields_containerA.connect(my_fields_containerA)
        >>> #or
        >>> op.inputs.fields_containerA(my_fields_containerA)

        """
        return self._fields_containerA

    @property
    def fields_containerB(self):
        """Allows to connect fields_containerB input to the operator

        Parameters
        ----------
        my_fields_containerB : FieldsContainer, 

        Examples
        --------
        >>> from ansys.dpf import core as dpf

        >>> op = dpf.operators.logic.identical_fc()
        >>> op.inputs.fields_containerB.connect(my_fields_containerB)
        >>> #or
        >>> op.inputs.fields_containerB(my_fields_containerB)

        """
        return self._fields_containerB

    @property
    def tolerance(self):
        """Allows to connect tolerance input to the operator

        - pindoc: Double relative tolerance. Maximum tolerance gap between to compared values: values within relative tolerance are considered identical (v1-v2)/v2 < relativeTol (default is 0.001).

        Parameters
        ----------
        my_tolerance : float, 

        Examples
        --------
        >>> from ansys.dpf import core as dpf

        >>> op = dpf.operators.logic.identical_fc()
        >>> op.inputs.tolerance.connect(my_tolerance)
        >>> #or
        >>> op.inputs.tolerance(my_tolerance)

        """
        return self._tolerance

    @property
    def small_value(self):
        """Allows to connect small_value input to the operator

        - pindoc: Double positive small value.Smallest value which will be considered during the comparison step : all the abs(values) in field less than this value is considered as null, (default value:1.0e-14).

        Parameters
        ----------
        my_small_value : float, 

        Examples
        --------
        >>> from ansys.dpf import core as dpf

        >>> op = dpf.operators.logic.identical_fc()
        >>> op.inputs.small_value.connect(my_small_value)
        >>> #or
        >>> op.inputs.small_value(my_small_value)

        """
        return self._small_value

class OutputsIdenticalFc(_Outputs):
    """Intermediate class used to get outputs from identical_fc operator
      Examples
      --------
      >>> from ansys.dpf import core as dpf

      >>> op = dpf.operators.logic.identical_fc()
      >>> # Connect inputs : op.inputs. ...
      >>> result_boolean = op.outputs.boolean()
      >>> result_message = op.outputs.message()
    """
    def __init__(self, op: Operator):
        super().__init__(identical_fc._spec().outputs, op)
        self._boolean = Output(identical_fc._spec().output_pin(0), 0, op) 
        self._outputs.append(self._boolean)
        self._message = Output(identical_fc._spec().output_pin(1), 1, op) 
        self._outputs.append(self._message)

    @property
    def boolean(self):
        """Allows to get boolean output of the operator


        - pindoc: bool (true if identical...)

        Returns
        ----------
        my_boolean : bool, 

        Examples
        --------
        >>> from ansys.dpf import core as dpf

        >>> op = dpf.operators.logic.identical_fc()
        >>> # Connect inputs : op.inputs. ...
        >>> result_boolean = op.outputs.boolean() 
        """
        return self._boolean

    @property
    def message(self):
        """Allows to get message output of the operator


        Returns
        ----------
        my_message : str, 

        Examples
        --------
        >>> from ansys.dpf import core as dpf

        >>> op = dpf.operators.logic.identical_fc()
        >>> # Connect inputs : op.inputs. ...
        >>> result_message = op.outputs.message() 
        """
        return self._message


"""
identical_fc
============
"""
from ansys.dpf.core.dpf_operator import Operator
from ansys.dpf.core.inputs import Input, _Inputs
from ansys.dpf.core.outputs import Output, _Outputs, _modify_output_spec_with_one_type
from ansys.dpf.core.operators.specification import PinSpecification, Specification

"""Operators from Ans.Dpf.Native plugin, from "logic" category
"""

class identical_fc(Operator):
    """Check if two fields container are identical.

      available inputs:
        - fields_containerA (FieldsContainer)
        - fields_containerB (FieldsContainer)
        - tolerance (float)
        - small_value (float)

      available outputs:
        - boolean (bool)
        - message (str)

      Examples
      --------
      >>> from ansys.dpf import core as dpf

      >>> # Instantiate operator
      >>> op = dpf.operators.logic.identical_fc()

      >>> # Make input connections
      >>> my_fields_containerA = dpf.FieldsContainer()
      >>> op.inputs.fields_containerA.connect(my_fields_containerA)
      >>> my_fields_containerB = dpf.FieldsContainer()
      >>> op.inputs.fields_containerB.connect(my_fields_containerB)
      >>> my_tolerance = float()
      >>> op.inputs.tolerance.connect(my_tolerance)
      >>> my_small_value = float()
      >>> op.inputs.small_value.connect(my_small_value)

      >>> # Instantiate operator and connect inputs in one line
      >>> op = dpf.operators.logic.identical_fc(fields_containerA=my_fields_containerA,fields_containerB=my_fields_containerB,tolerance=my_tolerance,small_value=my_small_value)

      >>> # Get output data
      >>> result_boolean = op.outputs.boolean()
      >>> result_message = op.outputs.message()"""
    def __init__(self, fields_containerA=None, fields_containerB=None, tolerance=None, small_value=None, config=None, server=None):
        super().__init__(name="AreFieldsIdentical_fc", config = config, server = server)
        self._inputs = InputsIdenticalFc(self)
        self._outputs = OutputsIdenticalFc(self)
        if fields_containerA !=None:
            self.inputs.fields_containerA.connect(fields_containerA)
        if fields_containerB !=None:
            self.inputs.fields_containerB.connect(fields_containerB)
        if tolerance !=None:
            self.inputs.tolerance.connect(tolerance)
        if small_value !=None:
            self.inputs.small_value.connect(small_value)

    @staticmethod
    def _spec():
        spec = Specification(description="""Check if two fields container are identical.""",
                             map_input_pin_spec={
                                 0 : PinSpecification(name = "fields_containerA", type_names=["fields_container"], optional=False, document=""""""), 
                                 1 : PinSpecification(name = "fields_containerB", type_names=["fields_container"], optional=False, document=""""""), 
                                 2 : PinSpecification(name = "tolerance", type_names=["double"], optional=False, document="""Double relative tolerance. Maximum tolerance gap between to compared values: values within relative tolerance are considered identical (v1-v2)/v2 < relativeTol (default is 0.001)."""), 
                                 3 : PinSpecification(name = "small_value", type_names=["double"], optional=False, document="""Double positive small value.Smallest value which will be considered during the comparison step : all the abs(values) in field less than this value is considered as null, (default value:1.0e-14).""")},
                             map_output_pin_spec={
                                 0 : PinSpecification(name = "boolean", type_names=["bool"], optional=False, document="""bool (true if identical...)"""), 
                                 1 : PinSpecification(name = "message", type_names=["string"], optional=False, document="""""")})
        return spec


    @staticmethod
    def default_config():
        return Operator.default_config(name = "AreFieldsIdentical_fc")

    @property
    def inputs(self):
        """Enables to connect inputs to the operator

        Returns
        --------
        inputs : InputsIdenticalFc 
        """
        return super().inputs


    @property
    def outputs(self):
        """Enables to get outputs of the operator by evaluationg it

        Returns
        --------
        outputs : OutputsIdenticalFc 
        """
        return super().outputs


#internal name: AreFieldsIdentical_fc
#scripting name: identical_fc
class InputsIdenticalFc(_Inputs):
    """Intermediate class used to connect user inputs to identical_fc operator

      Examples
      --------
      >>> from ansys.dpf import core as dpf

      >>> op = dpf.operators.logic.identical_fc()
      >>> my_fields_containerA = dpf.FieldsContainer()
      >>> op.inputs.fields_containerA.connect(my_fields_containerA)
      >>> my_fields_containerB = dpf.FieldsContainer()
      >>> op.inputs.fields_containerB.connect(my_fields_containerB)
      >>> my_tolerance = float()
      >>> op.inputs.tolerance.connect(my_tolerance)
      >>> my_small_value = float()
      >>> op.inputs.small_value.connect(my_small_value)
    """
    def __init__(self, op: Operator):
        super().__init__(identical_fc._spec().inputs, op)
        self._fields_containerA = Input(identical_fc._spec().input_pin(0), 0, op, -1) 
        self._inputs.append(self._fields_containerA)
        self._fields_containerB = Input(identical_fc._spec().input_pin(1), 1, op, -1) 
        self._inputs.append(self._fields_containerB)
        self._tolerance = Input(identical_fc._spec().input_pin(2), 2, op, -1) 
        self._inputs.append(self._tolerance)
        self._small_value = Input(identical_fc._spec().input_pin(3), 3, op, -1) 
        self._inputs.append(self._small_value)

    @property
    def fields_containerA(self):
        """Allows to connect fields_containerA input to the operator

        Parameters
        ----------
        my_fields_containerA : FieldsContainer, 

        Examples
        --------
        >>> from ansys.dpf import core as dpf

        >>> op = dpf.operators.logic.identical_fc()
        >>> op.inputs.fields_containerA.connect(my_fields_containerA)
        >>> #or
        >>> op.inputs.fields_containerA(my_fields_containerA)

        """
        return self._fields_containerA

    @property
    def fields_containerB(self):
        """Allows to connect fields_containerB input to the operator

        Parameters
        ----------
        my_fields_containerB : FieldsContainer, 

        Examples
        --------
        >>> from ansys.dpf import core as dpf

        >>> op = dpf.operators.logic.identical_fc()
        >>> op.inputs.fields_containerB.connect(my_fields_containerB)
        >>> #or
        >>> op.inputs.fields_containerB(my_fields_containerB)

        """
        return self._fields_containerB

    @property
    def tolerance(self):
        """Allows to connect tolerance input to the operator

        - pindoc: Double relative tolerance. Maximum tolerance gap between to compared values: values within relative tolerance are considered identical (v1-v2)/v2 < relativeTol (default is 0.001).

        Parameters
        ----------
        my_tolerance : float, 

        Examples
        --------
        >>> from ansys.dpf import core as dpf

        >>> op = dpf.operators.logic.identical_fc()
        >>> op.inputs.tolerance.connect(my_tolerance)
        >>> #or
        >>> op.inputs.tolerance(my_tolerance)

        """
        return self._tolerance

    @property
    def small_value(self):
        """Allows to connect small_value input to the operator

        - pindoc: Double positive small value.Smallest value which will be considered during the comparison step : all the abs(values) in field less than this value is considered as null, (default value:1.0e-14).

        Parameters
        ----------
        my_small_value : float, 

        Examples
        --------
        >>> from ansys.dpf import core as dpf

        >>> op = dpf.operators.logic.identical_fc()
        >>> op.inputs.small_value.connect(my_small_value)
        >>> #or
        >>> op.inputs.small_value(my_small_value)

        """
        return self._small_value

class OutputsIdenticalFc(_Outputs):
    """Intermediate class used to get outputs from identical_fc operator
      Examples
      --------
      >>> from ansys.dpf import core as dpf

      >>> op = dpf.operators.logic.identical_fc()
      >>> # Connect inputs : op.inputs. ...
      >>> result_boolean = op.outputs.boolean()
      >>> result_message = op.outputs.message()
    """
    def __init__(self, op: Operator):
        super().__init__(identical_fc._spec().outputs, op)
        self._boolean = Output(identical_fc._spec().output_pin(0), 0, op) 
        self._outputs.append(self._boolean)
        self._message = Output(identical_fc._spec().output_pin(1), 1, op) 
        self._outputs.append(self._message)

    @property
    def boolean(self):
        """Allows to get boolean output of the operator


        - pindoc: bool (true if identical...)

        Returns
        ----------
        my_boolean : bool, 

        Examples
        --------
        >>> from ansys.dpf import core as dpf

        >>> op = dpf.operators.logic.identical_fc()
        >>> # Connect inputs : op.inputs. ...
        >>> result_boolean = op.outputs.boolean() 
        """
        return self._boolean

    @property
    def message(self):
        """Allows to get message output of the operator


        Returns
        ----------
        my_message : str, 

        Examples
        --------
        >>> from ansys.dpf import core as dpf

        >>> op = dpf.operators.logic.identical_fc()
        >>> # Connect inputs : op.inputs. ...
        >>> result_message = op.outputs.message() 
        """
        return self._message
identical_fc ============ Operators from Ans.Dpf.Native plugin, from "logic" category Check if two fields container are identical.        available inputs:         - fields_containerA (FieldsContainer)         - fields_containerB (FieldsContainer)         - tolerance (float)         - small_value (float)        available outputs:         - boolean (bool)         - message (str)        Examples       --------       >>> from ansys.dpf import core as dpf        >>> # Instantiate operator       >>> op = dpf.operators.logic.identical_fc()        >>> # Make input connections       >>> my_fields_containerA = dpf.FieldsContainer()       >>> op.inputs.fields_containerA.connect(my_fields_containerA)       >>> my_fields_containerB = dpf.FieldsContainer()       >>> op.inputs.fields_containerB.connect(my_fields_containerB)       >>> my_tolerance = float()       >>> op.inputs.tolerance.connect(my_tolerance)       >>> my_small_value = float()       >>> op.inputs.small_value.connect(my_small_value)        >>> # Instantiate operator and connect inputs in one line       >>> op = dpf.operators.logic.identical_fc(fields_containerA=my_fields_containerA,fields_containerB=my_fields_containerB,tolerance=my_tolerance,small_value=my_small_value)        >>> # Get output data       >>> result_boolean = op.outputs.boolean()       >>> result_message = op.outputs.message() Check if two fields container are identical. Double relative tolerance. Maximum tolerance gap between to compared values: values within relative tolerance are considered identical (v1-v2)/v2 < relativeTol (default is 0.001). Double positive small value.Smallest value which will be considered during the comparison step : all the abs(values) in field less than this value is considered as null, (default value:1.0e-14). bool (true if identical...) Enables to connect inputs to the operator          Returns         --------         inputs : InputsIdenticalFc Enables to get outputs of the operator by evaluationg it          Returns         --------         outputs : OutputsIdenticalFc #internal name: AreFieldsIdentical_fc #scripting name: identical_fc Intermediate class used to connect user inputs to identical_fc operator        Examples       --------       >>> from ansys.dpf import core as dpf        >>> op = dpf.operators.logic.identical_fc()       >>> my_fields_containerA = dpf.FieldsContainer()       >>> op.inputs.fields_containerA.connect(my_fields_containerA)       >>> my_fields_containerB = dpf.FieldsContainer()       >>> op.inputs.fields_containerB.connect(my_fields_containerB)       >>> my_tolerance = float()       >>> op.inputs.tolerance.connect(my_tolerance)       >>> my_small_value = float()       >>> op.inputs.small_value.connect(my_small_value) Allows to connect fields_containerA input to the operator          Parameters         ----------         my_fields_containerA : FieldsContainer,           Examples         --------         >>> from ansys.dpf import core as dpf          >>> op = dpf.operators.logic.identical_fc()         >>> op.inputs.fields_containerA.connect(my_fields_containerA)         >>> #or         >>> op.inputs.fields_containerA(my_fields_containerA) Allows to connect fields_containerB input to the operator          Parameters         ----------         my_fields_containerB : FieldsContainer,           Examples         --------         >>> from ansys.dpf import core as dpf          >>> op = dpf.operators.logic.identical_fc()         >>> op.inputs.fields_containerB.connect(my_fields_containerB)         >>> #or         >>> op.inputs.fields_containerB(my_fields_containerB) Allows to connect tolerance input to the operator          - pindoc: Double relative tolerance. Maximum tolerance gap between to compared values: values within relative tolerance are considered identical (v1-v2)/v2 < relativeTol (default is 0.001).          Parameters         ----------         my_tolerance : float,           Examples         --------         >>> from ansys.dpf import core as dpf          >>> op = dpf.operators.logic.identical_fc()         >>> op.inputs.tolerance.connect(my_tolerance)         >>> #or         >>> op.inputs.tolerance(my_tolerance) Allows to connect small_value input to the operator          - pindoc: Double positive small value.Smallest value which will be considered during the comparison step : all the abs(values) in field less than this value is considered as null, (default value:1.0e-14).          Parameters         ----------         my_small_value : float,           Examples         --------         >>> from ansys.dpf import core as dpf          >>> op = dpf.operators.logic.identical_fc()         >>> op.inputs.small_value.connect(my_small_value)         >>> #or         >>> op.inputs.small_value(my_small_value) Intermediate class used to get outputs from identical_fc operator       Examples       --------       >>> from ansys.dpf import core as dpf        >>> op = dpf.operators.logic.identical_fc()       >>> # Connect inputs : op.inputs. ...       >>> result_boolean = op.outputs.boolean()       >>> result_message = op.outputs.message() Allows to get boolean output of the operator           - pindoc: bool (true if identical...)          Returns         ----------         my_boolean : bool,           Examples         --------         >>> from ansys.dpf import core as dpf          >>> op = dpf.operators.logic.identical_fc()         >>> # Connect inputs : op.inputs. ...         >>> result_boolean = op.outputs.boolean() Allows to get message output of the operator           Returns         ----------         my_message : str,           Examples         --------         >>> from ansys.dpf import core as dpf          >>> op = dpf.operators.logic.identical_fc()         >>> # Connect inputs : op.inputs. ...         >>> result_message = op.outputs.message()