|
| 1 | +""" |
| 2 | +quantization |
| 3 | +
|
| 4 | +Autogenerated DPF operator classes. |
| 5 | +""" |
| 6 | + |
| 7 | +from __future__ import annotations |
| 8 | + |
| 9 | +from warnings import warn |
| 10 | +from ansys.dpf.core.dpf_operator import Operator |
| 11 | +from ansys.dpf.core.inputs import Input, _Inputs |
| 12 | +from ansys.dpf.core.outputs import Output, _Outputs |
| 13 | +from ansys.dpf.core.operators.specification import PinSpecification, Specification |
| 14 | +from ansys.dpf.core.config import Config |
| 15 | +from ansys.dpf.core.server_types import AnyServerType |
| 16 | + |
| 17 | + |
| 18 | +class quantization(Operator): |
| 19 | + r"""Applies scaling to precision to all the values from field input, then |
| 20 | + rounding to the unit. |
| 21 | +
|
| 22 | +
|
| 23 | + Parameters |
| 24 | + ---------- |
| 25 | + input_field: Field |
| 26 | + Input field |
| 27 | + threshold: float |
| 28 | + Threshold (precision) desired. |
| 29 | +
|
| 30 | + Returns |
| 31 | + ------- |
| 32 | + output_field: Field |
| 33 | + Scaled and rounded field |
| 34 | +
|
| 35 | + Examples |
| 36 | + -------- |
| 37 | + >>> from ansys.dpf import core as dpf |
| 38 | +
|
| 39 | + >>> # Instantiate operator |
| 40 | + >>> op = dpf.operators.compression.quantization() |
| 41 | +
|
| 42 | + >>> # Make input connections |
| 43 | + >>> my_input_field = dpf.Field() |
| 44 | + >>> op.inputs.input_field.connect(my_input_field) |
| 45 | + >>> my_threshold = float() |
| 46 | + >>> op.inputs.threshold.connect(my_threshold) |
| 47 | +
|
| 48 | + >>> # Instantiate operator and connect inputs in one line |
| 49 | + >>> op = dpf.operators.compression.quantization( |
| 50 | + ... input_field=my_input_field, |
| 51 | + ... threshold=my_threshold, |
| 52 | + ... ) |
| 53 | +
|
| 54 | + >>> # Get output data |
| 55 | + >>> result_output_field = op.outputs.output_field() |
| 56 | + """ |
| 57 | + |
| 58 | + def __init__(self, input_field=None, threshold=None, config=None, server=None): |
| 59 | + super().__init__(name="quantization", config=config, server=server) |
| 60 | + self._inputs = InputsQuantization(self) |
| 61 | + self._outputs = OutputsQuantization(self) |
| 62 | + if input_field is not None: |
| 63 | + self.inputs.input_field.connect(input_field) |
| 64 | + if threshold is not None: |
| 65 | + self.inputs.threshold.connect(threshold) |
| 66 | + |
| 67 | + @staticmethod |
| 68 | + def _spec() -> Specification: |
| 69 | + description = r"""Applies scaling to precision to all the values from field input, then |
| 70 | +rounding to the unit. |
| 71 | +""" |
| 72 | + spec = Specification( |
| 73 | + description=description, |
| 74 | + map_input_pin_spec={ |
| 75 | + 0: PinSpecification( |
| 76 | + name="input_field", |
| 77 | + type_names=["field"], |
| 78 | + optional=False, |
| 79 | + document=r"""Input field""", |
| 80 | + ), |
| 81 | + 1: PinSpecification( |
| 82 | + name="threshold", |
| 83 | + type_names=["double"], |
| 84 | + optional=False, |
| 85 | + document=r"""Threshold (precision) desired.""", |
| 86 | + ), |
| 87 | + }, |
| 88 | + map_output_pin_spec={ |
| 89 | + 0: PinSpecification( |
| 90 | + name="output_field", |
| 91 | + type_names=["field"], |
| 92 | + optional=False, |
| 93 | + document=r"""Scaled and rounded field""", |
| 94 | + ), |
| 95 | + }, |
| 96 | + ) |
| 97 | + return spec |
| 98 | + |
| 99 | + @staticmethod |
| 100 | + def default_config(server: AnyServerType = None) -> Config: |
| 101 | + """Returns the default config of the operator. |
| 102 | +
|
| 103 | + This config can then be changed to the user needs and be used to |
| 104 | + instantiate the operator. The Configuration allows to customize |
| 105 | + how the operation will be processed by the operator. |
| 106 | +
|
| 107 | + Parameters |
| 108 | + ---------- |
| 109 | + server: |
| 110 | + Server with channel connected to the remote or local instance. When |
| 111 | + ``None``, attempts to use the global server. |
| 112 | +
|
| 113 | + Returns |
| 114 | + ------- |
| 115 | + config: |
| 116 | + A new Config instance equivalent to the default config for this operator. |
| 117 | + """ |
| 118 | + return Operator.default_config(name="quantization", server=server) |
| 119 | + |
| 120 | + @property |
| 121 | + def inputs(self) -> InputsQuantization: |
| 122 | + """Enables to connect inputs to the operator |
| 123 | +
|
| 124 | + Returns |
| 125 | + -------- |
| 126 | + inputs: |
| 127 | + An instance of InputsQuantization. |
| 128 | + """ |
| 129 | + return super().inputs |
| 130 | + |
| 131 | + @property |
| 132 | + def outputs(self) -> OutputsQuantization: |
| 133 | + """Enables to get outputs of the operator by evaluating it |
| 134 | +
|
| 135 | + Returns |
| 136 | + -------- |
| 137 | + outputs: |
| 138 | + An instance of OutputsQuantization. |
| 139 | + """ |
| 140 | + return super().outputs |
| 141 | + |
| 142 | + |
| 143 | +class InputsQuantization(_Inputs): |
| 144 | + """Intermediate class used to connect user inputs to |
| 145 | + quantization operator. |
| 146 | +
|
| 147 | + Examples |
| 148 | + -------- |
| 149 | + >>> from ansys.dpf import core as dpf |
| 150 | + >>> op = dpf.operators.compression.quantization() |
| 151 | + >>> my_input_field = dpf.Field() |
| 152 | + >>> op.inputs.input_field.connect(my_input_field) |
| 153 | + >>> my_threshold = float() |
| 154 | + >>> op.inputs.threshold.connect(my_threshold) |
| 155 | + """ |
| 156 | + |
| 157 | + def __init__(self, op: Operator): |
| 158 | + super().__init__(quantization._spec().inputs, op) |
| 159 | + self._input_field = Input(quantization._spec().input_pin(0), 0, op, -1) |
| 160 | + self._inputs.append(self._input_field) |
| 161 | + self._threshold = Input(quantization._spec().input_pin(1), 1, op, -1) |
| 162 | + self._inputs.append(self._threshold) |
| 163 | + |
| 164 | + @property |
| 165 | + def input_field(self) -> Input: |
| 166 | + r"""Allows to connect input_field input to the operator. |
| 167 | +
|
| 168 | + Input field |
| 169 | +
|
| 170 | + Returns |
| 171 | + ------- |
| 172 | + input: |
| 173 | + An Input instance for this pin. |
| 174 | +
|
| 175 | + Examples |
| 176 | + -------- |
| 177 | + >>> from ansys.dpf import core as dpf |
| 178 | + >>> op = dpf.operators.compression.quantization() |
| 179 | + >>> op.inputs.input_field.connect(my_input_field) |
| 180 | + >>> # or |
| 181 | + >>> op.inputs.input_field(my_input_field) |
| 182 | + """ |
| 183 | + return self._input_field |
| 184 | + |
| 185 | + @property |
| 186 | + def threshold(self) -> Input: |
| 187 | + r"""Allows to connect threshold input to the operator. |
| 188 | +
|
| 189 | + Threshold (precision) desired. |
| 190 | +
|
| 191 | + Returns |
| 192 | + ------- |
| 193 | + input: |
| 194 | + An Input instance for this pin. |
| 195 | +
|
| 196 | + Examples |
| 197 | + -------- |
| 198 | + >>> from ansys.dpf import core as dpf |
| 199 | + >>> op = dpf.operators.compression.quantization() |
| 200 | + >>> op.inputs.threshold.connect(my_threshold) |
| 201 | + >>> # or |
| 202 | + >>> op.inputs.threshold(my_threshold) |
| 203 | + """ |
| 204 | + return self._threshold |
| 205 | + |
| 206 | + |
| 207 | +class OutputsQuantization(_Outputs): |
| 208 | + """Intermediate class used to get outputs from |
| 209 | + quantization operator. |
| 210 | +
|
| 211 | + Examples |
| 212 | + -------- |
| 213 | + >>> from ansys.dpf import core as dpf |
| 214 | + >>> op = dpf.operators.compression.quantization() |
| 215 | + >>> # Connect inputs : op.inputs. ... |
| 216 | + >>> result_output_field = op.outputs.output_field() |
| 217 | + """ |
| 218 | + |
| 219 | + def __init__(self, op: Operator): |
| 220 | + super().__init__(quantization._spec().outputs, op) |
| 221 | + self._output_field = Output(quantization._spec().output_pin(0), 0, op) |
| 222 | + self._outputs.append(self._output_field) |
| 223 | + |
| 224 | + @property |
| 225 | + def output_field(self) -> Output: |
| 226 | + r"""Allows to get output_field output of the operator |
| 227 | +
|
| 228 | + Scaled and rounded field |
| 229 | +
|
| 230 | + Returns |
| 231 | + ------- |
| 232 | + output: |
| 233 | + An Output instance for this pin. |
| 234 | +
|
| 235 | + Examples |
| 236 | + -------- |
| 237 | + >>> from ansys.dpf import core as dpf |
| 238 | + >>> op = dpf.operators.compression.quantization() |
| 239 | + >>> # Get the output from op.outputs. ... |
| 240 | + >>> result_output_field = op.outputs.output_field() |
| 241 | + """ |
| 242 | + return self._output_field |
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