Storage¶
Saving and loading traces and results objects.
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class
pypesto.store.OptimizationResultHDF5Reader(storage_filename: str)[source]¶ Bases:
objectReader of the HDF5 result files written by OptimizationResultHDF5Writer.
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storage_filename¶ HDF5 result file name
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class
pypesto.store.OptimizationResultHDF5Writer(storage_filename: str)[source]¶ Bases:
objectWriter of the HDF5 result files.
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storage_filename¶ HDF5 result file name
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class
pypesto.store.ProblemHDF5Reader(storage_filename: str)[source]¶ Bases:
objectReader of the HDF5 problem files written by ProblemHDF5Writer.
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storage_filename¶ HDF5 problem file name
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__init__(storage_filename: str)[source]¶ Initialize reader.
- Parameters
storage_filename (str) – HDF5 problem file name
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read(objective: Optional[pypesto.objective.base.ObjectiveBase] = None) → pypesto.problem.Problem[source]¶ Read HDF5 problem file and return pyPESTO problem object.
- Parameters
objective – Objective function which is currently not saved to storage.
- Returns
A problem instance with all attributes read in.
- Return type
problem
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class
pypesto.store.ProblemHDF5Writer(storage_filename: str)[source]¶ Bases:
objectWriter of the HDF5 problem files.
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storage_filename¶ HDF5 result file name
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class
pypesto.store.ProfileResultHDF5Reader(storage_filename: str)[source]¶ Bases:
objectReader of the HDF5 result files written by OptimizationResultHDF5Writer.
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storage_filename¶ HDF5 result file name
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class
pypesto.store.ProfileResultHDF5Writer(storage_filename: str)[source]¶ Bases:
objectWriter of the HDF5 result files.
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storage_filename¶ HDF5 result file name
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class
pypesto.store.SamplingResultHDF5Reader(storage_filename: str)[source]¶ Bases:
objectReader of the HDF5 result files written by SamplingResultHDF5Writer.
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storage_filename¶ HDF5 result file name
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class
pypesto.store.SamplingResultHDF5Writer(storage_filename: str)[source]¶ Bases:
objectWriter of the HDF5 sampling files.
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storage_filename¶ HDF5 result file name
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pypesto.store.autosave(filename: Optional[Union[str, Callable]], result: pypesto.result.result.Result, store_type: str, overwrite: bool = False)[source]¶ Save the result of optimization, profiling or sampling automatically.
- Parameters
filename – Either the filename to save to or “Auto”, in which case it will automatically generate a file named year_month_day_{type}_result.hdf5. A method can also be provided. All input to the autosave method will be passed to the filename method. The output should be the filename (str).
result – The result to be saved.
store_type – Either optimize, sample or profile. Depending on the method the function is called in.
overwrite – Whether to overwrite the currently existing results.
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pypesto.store.get_or_create_group(f: Union[h5py._hl.files.File, h5py._hl.group.Group], group_path: str) → h5py._hl.group.Group[source]¶ Return/create a group object for the group with group_path relative to f.
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pypesto.store.f¶ should be checked
- Type
file or group where existence of a group with the path group_path
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pypesto.store.group_path¶ - Type
the path or simply the name of the group that should exist in f
- Returns
hdf5 group object with specified path relative to f.
- Return type
grp
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pypesto.store.load_objective_config(filename: str)[source]¶ Load the objective information stored in f.
- Parameters
filename – The name of the file in which the information are stored.
- Returns
A dictionary of the information, stored instead of the
actual objective in problem.objective.
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pypesto.store.read_result(filename: str, problem: bool = True, optimize: bool = False, profile: bool = False, sample: bool = False) → pypesto.result.result.Result[source]¶ Save the whole pypesto.Result object in an HDF5 file.
- Parameters
filename – The HDF5 filename.
problem – Read the problem.
optimize – Read the optimize result.
profile – Read the profile result.
sample – Read the sample result.
- Returns
Result object containing the results stored in HDF5 file.
- Return type
result
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pypesto.store.write_array(f: h5py._hl.group.Group, path: str, values: Collection) → None[source]¶ Write array to hdf5.
- Parameters
f – h5py.Group where dataset should be created
path – path of the dataset to create
values – array to write
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pypesto.store.write_result(result: pypesto.result.result.Result, filename: str, overwrite: bool = False, problem: bool = True, optimize: bool = False, profile: bool = False, sample: bool = False)[source]¶ Save whole pypesto.Result to hdf5 file.
Boolean indicators allow specifying what to save.
- Parameters
result – The
pypesto.Resultobject to be saved.filename – The HDF5 filename.
overwrite – Boolean, whether already existing results should be overwritten.
problem – Read the problem.
optimize – Read the optimize result.
profile – Read the profile result.
sample – Read the sample result.