"""
fft_eval
========
"""
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.Math plugin, from "math" category
"""

class fft_eval(Operator):
    """Evaluate the fast fourier transforms at a given set of fields.

      available inputs:
        - field_t (Field)
        - time_scoping (Scoping) (optional)

      available outputs:
        - field (Field)
        - offset (Field)

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

      >>> # Instantiate operator
      >>> op = dpf.operators.math.fft_eval()

      >>> # Make input connections
      >>> my_field_t = dpf.Field()
      >>> op.inputs.field_t.connect(my_field_t)
      >>> my_time_scoping = dpf.Scoping()
      >>> op.inputs.time_scoping.connect(my_time_scoping)

      >>> # Instantiate operator and connect inputs in one line
      >>> op = dpf.operators.math.fft_eval(field_t=my_field_t,time_scoping=my_time_scoping)

      >>> # Get output data
      >>> result_field = op.outputs.field()
      >>> result_offset = op.outputs.offset()"""
    def __init__(self, field_t=None, time_scoping=None, config=None, server=None):
        super().__init__(name="fft_eval", config = config, server = server)
        self._inputs = InputsFftEval(self)
        self._outputs = OutputsFftEval(self)
        if field_t !=None:
            self.inputs.field_t.connect(field_t)
        if time_scoping !=None:
            self.inputs.time_scoping.connect(time_scoping)

    @staticmethod
    def _spec():
        spec = Specification(description="""Evaluate the fast fourier transforms at a given set of fields.""",
                             map_input_pin_spec={
                                 0 : PinSpecification(name = "field_t", type_names=["field"], optional=False, document="""field of values to evaluate"""), 
                                 1 : PinSpecification(name = "time_scoping", type_names=["scoping"], optional=True, document="""if specified only the results at these set ids are used""")},
                             map_output_pin_spec={
                                 0 : PinSpecification(name = "field", type_names=["field"], optional=False, document=""""""), 
                                 2 : PinSpecification(name = "offset", type_names=["field"], optional=False, document="""""")})
        return spec


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

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

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


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

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


#internal name: fft_eval
#scripting name: fft_eval
class InputsFftEval(_Inputs):
    """Intermediate class used to connect user inputs to fft_eval operator

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

      >>> op = dpf.operators.math.fft_eval()
      >>> my_field_t = dpf.Field()
      >>> op.inputs.field_t.connect(my_field_t)
      >>> my_time_scoping = dpf.Scoping()
      >>> op.inputs.time_scoping.connect(my_time_scoping)
    """
    def __init__(self, op: Operator):
        super().__init__(fft_eval._spec().inputs, op)
        self._field_t = Input(fft_eval._spec().input_pin(0), 0, op, -1) 
        self._inputs.append(self._field_t)
        self._time_scoping = Input(fft_eval._spec().input_pin(1), 1, op, -1) 
        self._inputs.append(self._time_scoping)

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

        - pindoc: field of values to evaluate

        Parameters
        ----------
        my_field_t : Field, 

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

        >>> op = dpf.operators.math.fft_eval()
        >>> op.inputs.field_t.connect(my_field_t)
        >>> #or
        >>> op.inputs.field_t(my_field_t)

        """
        return self._field_t

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

        - pindoc: if specified only the results at these set ids are used

        Parameters
        ----------
        my_time_scoping : Scoping, 

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

        >>> op = dpf.operators.math.fft_eval()
        >>> op.inputs.time_scoping.connect(my_time_scoping)
        >>> #or
        >>> op.inputs.time_scoping(my_time_scoping)

        """
        return self._time_scoping

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

      >>> op = dpf.operators.math.fft_eval()
      >>> # Connect inputs : op.inputs. ...
      >>> result_field = op.outputs.field()
      >>> result_offset = op.outputs.offset()
    """
    def __init__(self, op: Operator):
        super().__init__(fft_eval._spec().outputs, op)
        self._field = Output(fft_eval._spec().output_pin(0), 0, op) 
        self._outputs.append(self._field)
        self._offset = Output(fft_eval._spec().output_pin(2), 2, op) 
        self._outputs.append(self._offset)

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


        Returns
        ----------
        my_field : Field, 

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

        >>> op = dpf.operators.math.fft_eval()
        >>> # Connect inputs : op.inputs. ...
        >>> result_field = op.outputs.field() 
        """
        return self._field

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


        Returns
        ----------
        my_offset : Field, 

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

        >>> op = dpf.operators.math.fft_eval()
        >>> # Connect inputs : op.inputs. ...
        >>> result_offset = op.outputs.offset() 
        """
        return self._offset


"""
fft_eval
========
"""
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.Math plugin, from "math" category
"""

class fft_eval(Operator):
    """Evaluate the fast fourier transforms at a given set of fields.

      available inputs:
        - field_t (Field)
        - time_scoping (Scoping) (optional)

      available outputs:
        - field (Field)
        - offset (Field)

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

      >>> # Instantiate operator
      >>> op = dpf.operators.math.fft_eval()

      >>> # Make input connections
      >>> my_field_t = dpf.Field()
      >>> op.inputs.field_t.connect(my_field_t)
      >>> my_time_scoping = dpf.Scoping()
      >>> op.inputs.time_scoping.connect(my_time_scoping)

      >>> # Instantiate operator and connect inputs in one line
      >>> op = dpf.operators.math.fft_eval(field_t=my_field_t,time_scoping=my_time_scoping)

      >>> # Get output data
      >>> result_field = op.outputs.field()
      >>> result_offset = op.outputs.offset()"""
    def __init__(self, field_t=None, time_scoping=None, config=None, server=None):
        super().__init__(name="fft_eval", config = config, server = server)
        self._inputs = InputsFftEval(self)
        self._outputs = OutputsFftEval(self)
        if field_t !=None:
            self.inputs.field_t.connect(field_t)
        if time_scoping !=None:
            self.inputs.time_scoping.connect(time_scoping)

    @staticmethod
    def _spec():
        spec = Specification(description="""Evaluate the fast fourier transforms at a given set of fields.""",
                             map_input_pin_spec={
                                 0 : PinSpecification(name = "field_t", type_names=["field"], optional=False, document="""field of values to evaluate"""), 
                                 1 : PinSpecification(name = "time_scoping", type_names=["scoping"], optional=True, document="""if specified only the results at these set ids are used""")},
                             map_output_pin_spec={
                                 0 : PinSpecification(name = "field", type_names=["field"], optional=False, document=""""""), 
                                 2 : PinSpecification(name = "offset", type_names=["field"], optional=False, document="""""")})
        return spec


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

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

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


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

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


#internal name: fft_eval
#scripting name: fft_eval
class InputsFftEval(_Inputs):
    """Intermediate class used to connect user inputs to fft_eval operator

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

      >>> op = dpf.operators.math.fft_eval()
      >>> my_field_t = dpf.Field()
      >>> op.inputs.field_t.connect(my_field_t)
      >>> my_time_scoping = dpf.Scoping()
      >>> op.inputs.time_scoping.connect(my_time_scoping)
    """
    def __init__(self, op: Operator):
        super().__init__(fft_eval._spec().inputs, op)
        self._field_t = Input(fft_eval._spec().input_pin(0), 0, op, -1) 
        self._inputs.append(self._field_t)
        self._time_scoping = Input(fft_eval._spec().input_pin(1), 1, op, -1) 
        self._inputs.append(self._time_scoping)

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

        - pindoc: field of values to evaluate

        Parameters
        ----------
        my_field_t : Field, 

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

        >>> op = dpf.operators.math.fft_eval()
        >>> op.inputs.field_t.connect(my_field_t)
        >>> #or
        >>> op.inputs.field_t(my_field_t)

        """
        return self._field_t

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

        - pindoc: if specified only the results at these set ids are used

        Parameters
        ----------
        my_time_scoping : Scoping, 

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

        >>> op = dpf.operators.math.fft_eval()
        >>> op.inputs.time_scoping.connect(my_time_scoping)
        >>> #or
        >>> op.inputs.time_scoping(my_time_scoping)

        """
        return self._time_scoping

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

      >>> op = dpf.operators.math.fft_eval()
      >>> # Connect inputs : op.inputs. ...
      >>> result_field = op.outputs.field()
      >>> result_offset = op.outputs.offset()
    """
    def __init__(self, op: Operator):
        super().__init__(fft_eval._spec().outputs, op)
        self._field = Output(fft_eval._spec().output_pin(0), 0, op) 
        self._outputs.append(self._field)
        self._offset = Output(fft_eval._spec().output_pin(2), 2, op) 
        self._outputs.append(self._offset)

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


        Returns
        ----------
        my_field : Field, 

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

        >>> op = dpf.operators.math.fft_eval()
        >>> # Connect inputs : op.inputs. ...
        >>> result_field = op.outputs.field() 
        """
        return self._field

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


        Returns
        ----------
        my_offset : Field, 

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

        >>> op = dpf.operators.math.fft_eval()
        >>> # Connect inputs : op.inputs. ...
        >>> result_offset = op.outputs.offset() 
        """
        return self._offset


fft_eval ======== Operators from Ans.Dpf.Math plugin, from "math" category Evaluate the fast fourier transforms at a given set of fields.        available inputs:         - field_t (Field)         - time_scoping (Scoping) (optional)        available outputs:         - field (Field)         - offset (Field)        Examples       --------       >>> from ansys.dpf import core as dpf        >>> # Instantiate operator       >>> op = dpf.operators.math.fft_eval()        >>> # Make input connections       >>> my_field_t = dpf.Field()       >>> op.inputs.field_t.connect(my_field_t)       >>> my_time_scoping = dpf.Scoping()       >>> op.inputs.time_scoping.connect(my_time_scoping)        >>> # Instantiate operator and connect inputs in one line       >>> op = dpf.operators.math.fft_eval(field_t=my_field_t,time_scoping=my_time_scoping)        >>> # Get output data       >>> result_field = op.outputs.field()       >>> result_offset = op.outputs.offset() Evaluate the fast fourier transforms at a given set of fields. field of values to evaluate if specified only the results at these set ids are used Enables to connect inputs to the operator          Returns         --------         inputs : InputsFftEval Enables to get outputs of the operator by evaluationg it          Returns         --------         outputs : OutputsFftEval #internal name: fft_eval #scripting name: fft_eval Intermediate class used to connect user inputs to fft_eval operator        Examples       --------       >>> from ansys.dpf import core as dpf        >>> op = dpf.operators.math.fft_eval()       >>> my_field_t = dpf.Field()       >>> op.inputs.field_t.connect(my_field_t)       >>> my_time_scoping = dpf.Scoping()       >>> op.inputs.time_scoping.connect(my_time_scoping) Allows to connect field_t input to the operator          - pindoc: field of values to evaluate          Parameters         ----------         my_field_t : Field,           Examples         --------         >>> from ansys.dpf import core as dpf          >>> op = dpf.operators.math.fft_eval()         >>> op.inputs.field_t.connect(my_field_t)         >>> #or         >>> op.inputs.field_t(my_field_t) Allows to connect time_scoping input to the operator          - pindoc: if specified only the results at these set ids are used          Parameters         ----------         my_time_scoping : Scoping,           Examples         --------         >>> from ansys.dpf import core as dpf          >>> op = dpf.operators.math.fft_eval()         >>> op.inputs.time_scoping.connect(my_time_scoping)         >>> #or         >>> op.inputs.time_scoping(my_time_scoping) Intermediate class used to get outputs from fft_eval operator       Examples       --------       >>> from ansys.dpf import core as dpf        >>> op = dpf.operators.math.fft_eval()       >>> # Connect inputs : op.inputs. ...       >>> result_field = op.outputs.field()       >>> result_offset = op.outputs.offset() Allows to get field output of the operator           Returns         ----------         my_field : Field,           Examples         --------         >>> from ansys.dpf import core as dpf          >>> op = dpf.operators.math.fft_eval()         >>> # Connect inputs : op.inputs. ...         >>> result_field = op.outputs.field() Allows to get offset output of the operator           Returns         ----------         my_offset : Field,           Examples         --------         >>> from ansys.dpf import core as dpf          >>> op = dpf.operators.math.fft_eval()         >>> # Connect inputs : op.inputs. ...         >>> result_offset = op.outputs.offset()