JSON/TOML backend: introduce abbreviated IO modes #1493
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| switch (j.type()) | ||
| { | ||
| case nlohmann::json::value_t::null: | ||
| throw std::runtime_error( | ||
| "[JSON backend] Attribute must not be null: '" + | ||
| nameForErrorMessages + "'."); | ||
| case nlohmann::json::value_t::object: | ||
| throw std::runtime_error( | ||
| "[JSON backend] Shorthand-style attribute must not be an " | ||
| "object: '" + | ||
| nameForErrorMessages + "'."); | ||
| case nlohmann::json::value_t::array: | ||
| if (j.empty()) | ||
| { | ||
| std::cerr << "Cannot recover datatype of empty vector without " | ||
| "explicit type annotation for attribute '" | ||
| << nameForErrorMessages | ||
| << "'. Will continue with VEC_INT datatype." | ||
| << std::endl; | ||
| return std::vector<int>{}; | ||
| } | ||
| else | ||
| { | ||
| auto valueType = j[0].type(); | ||
| /* | ||
| * If the vector is of numeric type, it might happen that the | ||
| * first entry is an integer, but a later entry is a float. | ||
| * We need to pick the most generic datatype in that case. | ||
| */ | ||
| if (valueType == nlohmann::json::value_t::number_float || | ||
| valueType == nlohmann::json::value_t::number_unsigned || | ||
| valueType == nlohmann::json::value_t::number_integer) | ||
| { | ||
| valueType = unifyNumericType(j); | ||
| } | ||
| switch (valueType) | ||
| { | ||
| case nlohmann::json::value_t::null: | ||
| throw std::runtime_error( | ||
| "[JSON backend] Attribute must not be null: '" + | ||
| nameForErrorMessages + "'."); | ||
| case nlohmann::json::value_t::object: | ||
| throw std::runtime_error( | ||
| "[JSON backend] Invalid contained datatype (object) " | ||
| "inside vector-type attribute: '" + | ||
| nameForErrorMessages + "'."); | ||
| case nlohmann::json::value_t::array: | ||
| throw std::runtime_error( | ||
| "[JSON backend] Invalid contained datatype (array) " | ||
| "inside vector-type attribute: '" + | ||
| nameForErrorMessages + "'."); | ||
| case nlohmann::json::value_t::string: | ||
| return recoverVectorAttributeFromJson<std::string>(j); | ||
| case nlohmann::json::value_t::boolean: | ||
| throw std::runtime_error( | ||
| "[JSON backend] Attribute must not be vector of bool: " | ||
| "'" + | ||
| nameForErrorMessages + "'."); | ||
| case nlohmann::json::value_t::number_integer: | ||
| return recoverVectorAttributeFromJson< | ||
| nlohmann::json::number_integer_t>(j); | ||
| case nlohmann::json::value_t::number_unsigned: | ||
| return recoverVectorAttributeFromJson< | ||
| nlohmann::json::number_unsigned_t>(j); | ||
| case nlohmann::json::value_t::number_float: | ||
| return recoverVectorAttributeFromJson< | ||
| nlohmann::json::number_float_t>(j); | ||
| case nlohmann::json::value_t::binary: | ||
| throw std::runtime_error( | ||
| "[JSON backend] Attribute must not have binary type: " | ||
| "'" + | ||
| nameForErrorMessages + "'."); | ||
| case nlohmann::json::value_t::discarded: | ||
| throw std::runtime_error( | ||
| "Internal JSON parser datatype leaked into JSON " | ||
| "value."); | ||
| } | ||
| throw std::runtime_error("Unreachable!"); | ||
| } | ||
| case nlohmann::json::value_t::string: | ||
| return j.get<std::string>(); | ||
| case nlohmann::json::value_t::boolean: | ||
| return j.get<bool>(); | ||
| case nlohmann::json::value_t::number_integer: | ||
| return j.get<nlohmann::json::number_integer_t>(); | ||
| case nlohmann::json::value_t::number_unsigned: | ||
| return j.get<nlohmann::json::number_unsigned_t>(); | ||
| case nlohmann::json::value_t::number_float: | ||
| return j.get<nlohmann::json::number_float_t>(); | ||
| case nlohmann::json::value_t::binary: | ||
| throw std::runtime_error( | ||
| "[JSON backend] Attribute must not have binary type: '" + | ||
| nameForErrorMessages + "'."); | ||
| case nlohmann::json::value_t::discarded: | ||
| throw std::runtime_error( | ||
| "Internal JSON parser datatype leaked into JSON value."); | ||
| } |
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| // std::string config = R"( | ||
| // { | ||
| // "iteration_encoding": "variable_based", | ||
| // "toml": { | ||
| // "dataset": {"mode": "template"}, | ||
| // "attribute": {"mode": "short"} | ||
| // } | ||
| // } | ||
| // )"; |
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|
With this, the JSON backend is now sensibly usable from codes such as PIConGPU: {
"__openPMD_internal": {
"attribute_mode": "short",
"dataset_mode": "template"
},
"attributes": {
"basePath": "/data/%T/",
"date": "2023-10-11 09:57:53 +0200",
"iterationEncoding": "fileBased",
"iterationFormat": "simData_%06T",
"meshesPath": "fields/",
"openPMD": "1.1.0",
"openPMDextension": 0,
"particlesPath": "particles/",
"picongpuIOVersionMajor": 2,
"picongpuIOVersionMinor": 0,
"software": "PIConGPU",
"softwareVersion": "0.7.0-dev"
},
"data": {
"100": {
"attributes": {
"cell_depth": 4.252342224121094,
"cell_height": 1.0630855560302734,
"cell_width": 4.252342224121094,
"dt": 1,
"eps0": 169.19711303710938,
"iteration": 100,
"mue0": 0.005910266190767288,
"particleBoundary": [
"absorbing",
"absorbing",
"absorbing",
"absorbing",
"absorbing",
"absorbing"
],
"particleBoundaryParameters": [
"without field correction",
"without field correction",
"without field correction",
"without field correction",
"without field correction",
"without field correction"
],
"sim_slides": 0,
"time": 100,
"timeUnitSI": 1.39e-16,
"unit_bfield": 40903.82224060171,
"unit_charge": 1.1143237516482563e-15,
"unit_efield": 12262657411105.05,
"unit_energy": 5.694183860145225e-10,
"unit_length": 4.1671151662e-08,
"unit_mass": 6.335633991170193e-27,
"unit_speed": 299792458,
"unit_time": 1.39e-16
},
"fields": {
"B": {
"attributes": {
"axisLabels": [
"z",
"y",
"x"
],
"dataOrder": "C",
"fieldSmoothing": "none",
"geometry": "cartesian",
"gridGlobalOffset": [
0,
0,
0
],
"gridSpacing": [
4.252342224121094,
1.0630855560302734,
4.252342224121094
],
"gridUnitSI": 4.1671151662e-08,
"timeOffset": 0,
"unitDimension": [
0,
1,
-2,
-1,
0,
0,
0
]
},
"x": {
"attributes": {
"position": [
0,
0.5,
0.5
],
"unitSI": 40903.82224060171
},
"datatype": "FLOAT",
"extent": [
32,
32,
32
]
},
"y": {
"attributes": {
"position": [
0.5,
0,
0.5
],
"unitSI": 40903.82224060171
},
"datatype": "FLOAT",
"extent": [
32,
32,
32
]
},
"z": {
"attributes": {
"position": [
0.5,
0.5,
0
],
"unitSI": 40903.82224060171
},
"datatype": "FLOAT",
"extent": [
32,
32,
32
]
}
},
"E": {
"attributes": {
"axisLabels": [
"z",
"y",
"x"
],
"dataOrder": "C",
"fieldSmoothing": "none",
"geometry": "cartesian",
"gridGlobalOffset": [
0,
0,
0
],
"gridSpacing": [
4.252342224121094,
1.0630855560302734,
4.252342224121094
],
"gridUnitSI": 4.1671151662e-08,
"timeOffset": 0,
"unitDimension": [
1,
1,
-3,
-1,
0,
0,
0
]
},
"x": {
"attributes": {
"position": [
0.5,
0,
0
],
"unitSI": 12262657411105.05
},
"datatype": "FLOAT",
"extent": [
32,
32,
32
]
},
"y": {
"attributes": {
"position": [
0,
0.5,
0
],
"unitSI": 12262657411105.05
},
"datatype": "FLOAT",
"extent": [
32,
32,
32
]
},
"z": {
"attributes": {
"position": [
0,
0,
0.5
],
"unitSI": 12262657411105.05
},
"datatype": "FLOAT",
"extent": [
32,
32,
32
]
}
},
"attributes": {
"chargeCorrection": "none",
"currentSmoothing": "none",
"fieldBoundary": [
"open",
"open",
"open",
"open",
"open",
"open"
],
"fieldBoundaryParameters": [
"convolutional PML over 12 cells",
"convolutional PML over 12 cells",
"convolutional PML over 12 cells",
"convolutional PML over 12 cells",
"convolutional PML over 12 cells",
"convolutional PML over 12 cells"
],
"fieldSolver": "Yee"
},
"e_all_chargeDensity": {
"attributes": {
"axisLabels": [
"z",
"y",
"x"
],
"dataOrder": "C",
"fieldSmoothing": "none",
"geometry": "cartesian",
"gridGlobalOffset": [
0,
0,
0
],
"gridSpacing": [
4.252342224121094,
1.0630855560302734,
4.252342224121094
],
"gridUnitSI": 4.1671151662e-08,
"position": [
0,
0,
0
],
"timeOffset": 0,
"unitDimension": [
-3,
0,
1,
1,
0,
0,
0
],
"unitSI": 15399438.226078901
},
"datatype": "FLOAT",
"extent": [
32,
32,
32
]
},
"e_all_energyDensity": {
"attributes": {
"axisLabels": [
"z",
"y",
"x"
],
"dataOrder": "C",
"fieldSmoothing": "none",
"geometry": "cartesian",
"gridGlobalOffset": [
0,
0,
0
],
"gridSpacing": [
4.252342224121094,
1.0630855560302734,
4.252342224121094
],
"gridUnitSI": 4.1671151662e-08,
"position": [
0,
0,
0
],
"timeOffset": 0,
"unitDimension": [
-1,
1,
-2,
0,
0,
0,
0
],
"unitSI": 7869098408118.734
},
"datatype": "FLOAT",
"extent": [
32,
32,
32
]
},
"picongpu_idProvider": {
"attributes": {
"axisLabels": [
"x"
],
"dataOrder": "C",
"geometry": "cartesian",
"gridGlobalOffset": [
0
],
"gridSpacing": [
1
],
"gridUnitSI": 1,
"timeOffset": 0,
"unitDimension": [
0,
0,
0,
0,
0,
0,
0
]
},
"nextId": {
"attributes": {
"position": [
0
],
"unitSI": 1
},
"datatype": "ULONG",
"extent": [
1,
1,
1
]
},
"startId": {
"attributes": {
"maxNumProc": 1,
"position": [
0
],
"unitSI": 1
},
"datatype": "ULONG",
"extent": [
1,
1,
1
]
}
}
},
"particles": {
"e": {
"attributes": {
"currentDeposition": "Esirkepov",
"particleInterpolation": "uniform",
"particlePush": "Boris",
"particleShape": 2,
"particleSmoothing": "none"
},
"charge": {
"attributes": {
"macroWeighted": 0,
"shape": [
0
],
"timeOffset": 0,
"unitDimension": [
0,
0,
1,
1,
0,
0,
0
],
"unitSI": 1.1143237516482563e-15,
"value": -0.0001437801111023873,
"weightingPower": 1
}
},
"mass": {
"attributes": {
"macroWeighted": 0,
"shape": [
0
],
"timeOffset": 0,
"unitDimension": [
0,
1,
0,
0,
0,
0,
0
],
"unitSI": 6.335633991170193e-27,
"value": 0.0001437801111023873,
"weightingPower": 1
}
},
"momentum": {
"attributes": {
"macroWeighted": 1,
"timeOffset": 0,
"unitDimension": [
1,
1,
-1,
0,
0,
0,
0
],
"weightingPower": 1
},
"x": {
"attributes": {
"shape": [
0
],
"unitSI": 1.8993752872012626e-18,
"value": 0
}
},
"y": {
"attributes": {
"shape": [
0
],
"unitSI": 1.8993752872012626e-18,
"value": 0
}
},
"z": {
"attributes": {
"shape": [
0
],
"unitSI": 1.8993752872012626e-18,
"value": 0
}
}
},
"particlePatches": {
"extent": {
"attributes": {
"unitDimension": [
0,
0,
0,
0,
0,
0,
0
]
},
"x": {
"attributes": {
"unitSI": 1
},
"datatype": "ULONG",
"extent": [
1
]
},
"y": {
"attributes": {
"unitSI": 1
},
"datatype": "ULONG",
"extent": [
1
]
},
"z": {
"attributes": {
"unitSI": 1
},
"datatype": "ULONG",
"extent": [
1
]
}
},
"numParticles": {
"attributes": {
"unitSI": 1
},
"datatype": "ULONG",
"extent": [
1
]
},
"numParticlesOffset": {
"attributes": {
"unitSI": 1
},
"datatype": "ULONG",
"extent": [
1
]
},
"offset": {
"attributes": {
"unitDimension": [
0,
0,
0,
0,
0,
0,
0
]
},
"x": {
"attributes": {
"unitSI": 1
},
"datatype": "ULONG",
"extent": [
1
]
},
"y": {
"attributes": {
"unitSI": 1
},
"datatype": "ULONG",
"extent": [
1
]
},
"z": {
"attributes": {
"unitSI": 1
},
"datatype": "ULONG",
"extent": [
1
]
}
}
},
"position": {
"attributes": {
"macroWeighted": 0,
"timeOffset": 0,
"unitDimension": [
1,
0,
0,
0,
0,
0,
0
],
"weightingPower": 0
},
"x": {
"attributes": {
"shape": [
0
],
"unitSI": 1.7719999774007647e-07,
"value": 0
}
},
"y": {
"attributes": {
"shape": [
0
],
"unitSI": 4.429999943501912e-08,
"value": 0
}
},
"z": {
"attributes": {
"shape": [
0
],
"unitSI": 1.7719999774007647e-07,
"value": 0
}
}
},
"positionOffset": {
"attributes": {
"macroWeighted": 0,
"timeOffset": 0,
"unitDimension": [
1,
0,
0,
0,
0,
0,
0
],
"weightingPower": 0
},
"x": {
"attributes": {
"shape": [
0
],
"unitSI": 1.7719999774007647e-07,
"value": 0
}
},
"y": {
"attributes": {
"shape": [
0
],
"unitSI": 4.429999943501912e-08,
"value": 0
}
},
"z": {
"attributes": {
"shape": [
0
],
"unitSI": 1.7719999774007647e-07,
"value": 0
}
}
},
"weighting": {
"attributes": {
"macroWeighted": 1,
"shape": [
0
],
"timeOffset": 0,
"unitDimension": [
0,
0,
0,
0,
0,
0,
0
],
"unitSI": 1,
"value": 0,
"weightingPower": 1
}
}
}
}
}
}
} |
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src/IO/JSON/JSONIOHandlerImpl.cpp
Outdated
| @@ -1269,40 +2009,165 @@ | |||
| return (*obtainJsonContents(file))[filePosition->id]; | |||
| } | |||
|
|
|||
| void JSONIOHandlerImpl::putJsonContents( | |||
| auto JSONIOHandlerImpl::putJsonContents( | |||
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Poorly documented large function Warning
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| @@ -1560,12 +1603,13 @@ | |||
| } | |||
| }; | |||
|
|
|||
| inline void write_test(const std::string &backend) | |||
| inline void write_test( | |||
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Reading the chunk table requires NOT using template mode, otherwise the string just consists of '\0' bytes.
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Factored out of #1277, based on #1436
Introduces two options:
json.dataset.mode = "template"(default:= "dataset"), write just the dataset extent and not the actual contentjson.attribute.mode = "short"(default:= "long"), write an attribute as{"software": "openPMD-api"}instead of{"software": {"value": "openPMD-api", "type": "STRING"}}TODO:
Diff: https://github.com/franzpoeschel/openPMD-api/compare/parallel-json..topic-json-short-modes