pypesto.store

Storage

Saving and loading traces and results objects.

class pypesto.store.OptimizationResultHDF5Reader(storage_filename: str)[source]

Bases: object

Reader of the HDF5 result files written by OptimizationResultHDF5Writer.

storage_filename: HDF5 result file name

__init__(storage_filename: str)[source]

Initialize reader.

Parameters:: storage_filename (str) – HDF5 result file name

read() → Result[source]: Read HDF5 result file and return pyPESTO result object.

class pypesto.store.OptimizationResultHDF5Writer(storage_filename: str)[source]

Bases: object

Writer of the HDF5 result files.

storage_filename: HDF5 result file name

__init__(storage_filename: str)[source]

Initialize Writer.

Parameters:: storage_filename (str) – HDF5 result file name

write(result: Result, overwrite=False)[source]: Write HDF5 result file from pyPESTO result object.

class pypesto.store.ProblemHDF5Reader(storage_filename: str)[source]

Bases: object

Reader of the HDF5 problem files written by ProblemHDF5Writer.

storage_filename: HDF5 problem file name

__init__(storage_filename: str)[source]

Initialize reader.

Parameters:: storage_filename (str) – HDF5 problem file name

read(objective: ObjectiveBase | None = None) → 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

class pypesto.store.ProblemHDF5Writer(storage_filename: str)[source]

Bases: object

Writer of the HDF5 problem files.

storage_filename: HDF5 result file name

__init__(storage_filename: str)[source]

Initialize writer.

Parameters:: storage_filename (str) – HDF5 problem file name

write(problem, overwrite: bool = False)[source]: Write HDF5 problem file from pyPESTO problem object.

class pypesto.store.ProfileResultHDF5Reader(storage_filename: str)[source]

Bases: object

Reader of the HDF5 result files written by OptimizationResultHDF5Writer.

storage_filename: HDF5 result file name

__init__(storage_filename: str)[source]

Initialize reader.

Parameters:: storage_filename – HDF5 result file name

read() → Result[source]: Read HDF5 result file and return pyPESTO result object.

class pypesto.store.ProfileResultHDF5Writer(storage_filename: str)[source]

Bases: object

Writer of the HDF5 result files.

storage_filename: HDF5 result file name

__init__(storage_filename: str)[source]

Initialize Writer.

Parameters:: storage_filename (str) – HDF5 result file name

write(result: Result, overwrite: bool = False)[source]: Write HDF5 result file from pyPESTO result object.

class pypesto.store.SamplingResultHDF5Reader(storage_filename: str)[source]

Bases: object

Reader of the HDF5 result files written by SamplingResultHDF5Writer.

storage_filename: HDF5 result file name

__init__(storage_filename: str)[source]

Initialize reader.

Parameters:: storage_filename (str) – HDF5 result file name

read() → Result[source]: Read HDF5 result file and return pyPESTO result object.

class pypesto.store.SamplingResultHDF5Writer(storage_filename: str)[source]

Bases: object

Writer of the HDF5 sampling files.

storage_filename: HDF5 result file name

__init__(storage_filename: str)[source]

Initialize Writer.

Parameters:: storage_filename (str) – HDF5 result file name

write(result: Result, overwrite: bool = False)[source]: Write HDF5 sampling file from pyPESTO result object.

pypesto.store.autosave(filename: str | Callable | None, 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.

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.

pypesto.store.read_result(filename: str, problem: bool = True, optimize: bool = False, profile: bool = False, sample: bool = False) → Result[source]

Save the whole pypesto.Result object in an HDF5 file.

By default, loads everything. If any of optimize, profile, sample is explicitly set to true, loads only this one.

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

pypesto.store.write_array(f: 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

pypesto.store.write_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.Result object 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.