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cleaning before weekend
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Elias Vitali authored and Elias Vitali committed Jun 9, 2023
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{
"cells": [
{
"cell_type": "code",
"execution_count": 17,
"id": "4cd9e531",
"metadata": {},
"outputs": [],
"source": [
"acquisition_metadata = {\n",
"'acquisition.genericMetadata.program.programName': 'Auto Slice & View 4',\n",
" 'acquisition.genericMetadata.program.programVersion': '4.2.1.1982',\n",
" 'acquisition.genericMetadata.applicationId.identifierValue': 'ASV',\n",
" 'acquisition.genericMetadata.fileVersion': '1.2',\n",
" 'acquisition.genericMetadata.projectName': '20200818_AlSi13 XRM tomo2',\n",
" 'acquisition.genericMetadata.numberOfCuts': '719',\n",
"}\n",
"\n",
"dataset_metadata = [\n",
" {\n",
" 'acquisition.dataset.rows': '1',\n",
" 'acquisition.dataset.columns': '1',\n",
" },\n",
" {\n",
" 'acquisition.dataset.rows': '1',\n",
" 'acquisition.dataset.columns': '1',\n",
" },\n",
"]\n",
"\n",
"image_metadata = [\n",
" [\n",
" {\n",
" 'acquisition.dataset.images.creationTime': '18.08.2020 17:51:07',\n",
" 'acquisition.dataset.images.stage.workingDistance.value': '0.00403678',\n",
" },\n",
" {\n",
" 'acquisition.dataset.images.creationTime': '18.08.2020 18:09:06',\n",
" 'acquisition.dataset.images.stage.workingDistance.value': '0.00403773',\n",
" }\n",
" ],\n",
" [\n",
" {\n",
" 'acquisition.dataset.images.creationTime': '18.08.2020 17:51:07',\n",
" 'acquisition.dataset.images.stage.workingDistance.value': '0.00403678',\n",
" },\n",
" {\n",
" 'acquisition.dataset.images.creationTime': '18.08.2020 18:09:06',\n",
" 'acquisition.dataset.images.stage.workingDistance.value': '0.00403773',\n",
" }\n",
" ]\n",
"]"
]
},
{
"cell_type": "code",
"execution_count": 75,
"id": "1c57c08f",
"metadata": {},
"outputs": [],
"source": [
"def combineMetadata(acquisition_metadata, dataset_metadata, image_metadata): \n",
" metadata = {}\n",
" # Combine acquisition metadata\n",
" for key, value in acquisition_metadata.items():\n",
" nested_keys = key.split('.')\n",
" current_dict = metadata\n",
"\n",
" for nested_key in nested_keys[:-1]:\n",
" if nested_key not in current_dict:\n",
" current_dict[nested_key] = {}\n",
" current_dict = current_dict[nested_key]\n",
"\n",
" current_dict[nested_keys[-1]] = value\n",
"\n",
" # Combine dataset metadata\n",
" metadata['acquisition']['dataset'] = []\n",
" for dataset in dataset_metadata:\n",
" dataset_dict = {}\n",
" for key, value in dataset.items():\n",
" nested_keys = key.split('.')\n",
" nested_keys.remove('acquisition')\n",
" nested_keys.remove('dataset')\n",
" current_dict = dataset_dict\n",
"\n",
" for nested_key in nested_keys[:-1]:\n",
" if nested_key not in current_dict:\n",
" current_dict[nested_key] = {}\n",
" current_dict = current_dict[nested_key]\n",
"\n",
" current_dict[nested_keys[-1]] = value\n",
"\n",
" metadata['acquisition']['dataset'].append(dataset_dict)\n",
"\n",
" # Combine image metadata\n",
" for i, images in enumerate(image_metadata):\n",
" metadata['acquisition']['dataset'][i]['images'] = []\n",
" for image in images:\n",
" image_dict = {}\n",
" for key, value in image.items():\n",
" nested_keys = key.split('.')\n",
" nested_keys.remove('acquisition')\n",
" nested_keys.remove('dataset')\n",
" nested_keys.remove('images')\n",
" current_dict = image_dict\n",
"\n",
" for nested_key in nested_keys[:-1]:\n",
" if nested_key not in current_dict:\n",
" current_dict[nested_key] = {}\n",
" current_dict = current_dict[nested_key]\n",
"\n",
" current_dict[nested_keys[-1]] = value\n",
"\n",
" metadata['acquisition']['dataset'][i]['images'].append(image_dict)\n",
" return metadata"
]
},
{
"cell_type": "code",
"execution_count": 62,
"id": "07e28c03",
"metadata": {},
"outputs": [],
"source": [
"def save_metadata_as_json(metadata, save_path):\n",
" filename = os.path.join(save_path, \"combined.json\")\n",
" with open(filename, 'w') as file:\n",
" json.dump(metadata, file, indent=4)\n",
" print(f\"Metadata saved as {filename}\")"
]
},
{
"cell_type": "code",
"execution_count": 77,
"id": "0f181043",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Metadata saved as /Users/elias/Desktop/PP13_Mapping/pp13-mapper/result_jsons/combined.json\n"
]
}
],
"source": [
"output_path = '/Users/elias/Desktop/PP13_Mapping/pp13-mapper/result_jsons'\n",
"combinedMetadata = combineMetadata(acquisition_metadata, dataset_metadata, image_metadata)\n",
"save_metadata_as_json(metadata, output_path)"
]
},
{
"cell_type": "code",
"execution_count": 44,
"id": "c84cd04c",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'acquisition': {'genericMetadata': {'program': {'programName': 'Auto Slice & View 4',\n",
" 'programVersion': '4.2.1.1982'},\n",
" 'applicationId': {'identifierValue': 'ASV'},\n",
" 'fileVersion': '1.2',\n",
" 'projectName': '20200818_AlSi13 XRM tomo2',\n",
" 'numberOfCuts': '719'},\n",
" 'dataset': {'rows': '1',\n",
" 'columns': '1',\n",
" 'images': {'creationTime': '18.08.2020 18:09:06',\n",
" 'stage': {'workingDistance': {'value': '0.00403773'}}}}}}"
]
},
"execution_count": 44,
"metadata": {},
"output_type": "execute_result"
}
],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"id": "cad5a1c6",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.9"
}
},
"nbformat": 4,
"nbformat_minor": 5
}

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