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ENH: GeneratePythonFilter-Crashing fixed, Generation Fixed, headers s…
…plit (#877) Signed-off-by: Michael Jackson <[email protected]>
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40
src/Plugins/SimplnxCore/src/SimplnxCore/utils/PythonPluginSourceTemplate.in.hpp
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| #pragma once | ||
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| /** | ||
| * This file is auto-generated during CMake time. Any changes made to the generated file | ||
| * will be over written the next time CMake runs a configure. | ||
| */ | ||
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| #include <string> | ||
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| namespace nx::core | ||
| { | ||
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| // clang-format off | ||
| static const char k_PythonFilterTemplateCharArray[] = {@PYTHON_FILTER_TEMPLATE@}; | ||
| // clang-format on | ||
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| inline const std::string PythonFilterTemplate() | ||
| { | ||
| return {k_PythonFilterTemplateCharArray}; | ||
| } | ||
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| // clang-format off | ||
| static const char k_PluginPythonFileCharArray[] = {@PYTHON_PLUGIN_TEMPLATE@}; | ||
| // clang-format on | ||
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| inline const std::string PluginPythonFile() | ||
| { | ||
| return {k_PluginPythonFileCharArray}; | ||
| } | ||
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| // clang-format off | ||
| static const char k_PluginInitPythonFileCharArray[] = {@PYTHON_PLUGIN_INIT_TEMPLATE@}; | ||
| // clang-format on | ||
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| inline const std::string PluginInitPythonFile() | ||
| { | ||
| return {k_PluginInitPythonFileCharArray}; | ||
| } | ||
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| }; // namespace nx::core |
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97
wrapping/python/plugins/DataAnalysisToolkit/NPSortArray.py
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,97 @@ | ||
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| from typing import List | ||
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| import simplnx as nx | ||
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| import numpy as np | ||
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| class NPSortArray: | ||
| """ | ||
| This section should contain the 'keys' that store each parameter. The value of the key should be snake_case. The name | ||
| of the value should be ALL_CAPITOL_KEY | ||
| """ | ||
| INPUT_ARRAY_KEY = 'input_array_path' | ||
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| def uuid(self) -> nx.Uuid: | ||
| """This returns the UUID of the filter. Each filter has a unique UUID value | ||
| :return: The Filter's Uuid value | ||
| :rtype: string | ||
| """ | ||
| return nx.Uuid('ae37de34-4ead-4202-9a49-6c222cbd88a8') | ||
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| def human_name(self) -> str: | ||
| """This returns the name of the filter as a user of DREAM3DNX would see it | ||
| :return: The filter's human name | ||
| :rtype: string | ||
| """ | ||
| return 'Sort Data Array (Numpy)' | ||
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| def class_name(self) -> str: | ||
| """The returns the name of the class that implements the filter | ||
| :return: The name of the implementation class | ||
| :rtype: string | ||
| """ | ||
| return 'NPSortArray' | ||
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| def name(self) -> str: | ||
| """The returns the name of filter | ||
| :return: The name of the filter | ||
| :rtype: string | ||
| """ | ||
| return 'NPSortArray' | ||
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| def default_tags(self) -> List[str]: | ||
| """This returns the default tags for this filter | ||
| :return: The default tags for the filter | ||
| :rtype: list | ||
| """ | ||
| return ['python'] | ||
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| def clone(self): | ||
| """Clones the filter | ||
| :return: A new instance of the filter | ||
| :rtype: NPSortArray | ||
| """ | ||
| return NPSortArray() | ||
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| def parameters(self) -> nx.Parameters: | ||
| """This function defines the parameters that are needed by the filter. Parameters collect the values from the user | ||
| or through a pipeline file. | ||
| """ | ||
| params = nx.Parameters() | ||
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| params.insert(nx.ArraySelectionParameter(NPSortArray.INPUT_ARRAY_KEY, 'Input Data Array', 'The input array to sort.', nx.DataPath(), nx.get_all_data_types())) | ||
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| return params | ||
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| def preflight_impl(self, data_structure: nx.DataStructure, args: dict, message_handler: nx.IFilter.MessageHandler, should_cancel: nx.AtomicBoolProxy) -> nx.IFilter.PreflightResult: | ||
| """This method preflights the filter and should ensure that all inputs are sanity checked as best as possible. Array | ||
| sizes can be checked if the arrays are actually know at preflight time. Some filters will not be able to report output | ||
| array sizes during preflight (segmentation filters for example). | ||
| :returns: | ||
| :rtype: nx.IFilter.PreflightResult | ||
| """ | ||
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| # message_handler(nx.IFilter.Message(nx.IFilter.Message.Type.Info, f'Preflight: {value}')) | ||
| return nx.IFilter.PreflightResult() | ||
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| def execute_impl(self, data_structure: nx.DataStructure, args: dict, message_handler: nx.IFilter.MessageHandler, should_cancel: nx.AtomicBoolProxy) -> nx.IFilter.ExecuteResult: | ||
| """ This method actually executes the filter algorithm and reports results. | ||
| :returns: | ||
| :rtype: nx.IFilter.ExecuteResult | ||
| """ | ||
| # Extract the DataPath from the arguments | ||
| input_data_arr_path: nx.DataPath = args[NPSortArray.INPUT_ARRAY_KEY] | ||
| # Use the DataPath to get a numpy view of the DataArray at that DataPath | ||
| input_array_view = data_structure[input_data_arr_path].npview() | ||
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| # Treat the view like a single dimensional array | ||
| # The entire array is sorted from first element to last element. | ||
| input_array_view = input_array_view.reshape(-1) | ||
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| # Sort the actual Data Array in place | ||
| input_array_view.sort() | ||
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| return nx.Result() | ||
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| Original file line number | Diff line number | Diff line change |
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| @@ -1,10 +1,17 @@ | ||
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| from DataAnalysisToolkit.Plugin import DataAnalysisToolkit | ||
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| from DataAnalysisToolkit.CalculateHistogramFilter import CalculateHistogramFilter | ||
| from DataAnalysisToolkit.InterpolateGridDataFilter import InterpolateGridDataFilter | ||
| from DataAnalysisToolkit.CliReaderFilter import CliReaderFilter | ||
| from DataAnalysisToolkit.ContourDetectionFilter import ContourDetectionFilter | ||
| from DataAnalysisToolkit.NPSortArray import NPSortArray | ||
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| # FILTER_INCLUDE_INSERT | ||
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| def get_plugin(): | ||
| return DataAnalysisToolkit() | ||
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| __all__ = ['DataAnalysisToolkit', 'CalculateHistogramFilter', 'InterpolateGridDataFilter', 'CliReaderFilter', 'ContourDetectionFilter', 'get_plugin'] | ||
| __all__ = ['DataAnalysisToolkit','CalculateHistogramFilter', 'InterpolateGridDataFilter', 'CliReaderFilter', 'get_plugin', 'ContourDetectionFilter', 'NPSortArray'] # FILTER_NAME_INSERT | ||
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