qcodes_loop.data.hdf5_format

class qcodes_loop.data.hdf5_format.HDF5Format

HDF5 formatter for saving qcodes datasets.

Capable of storing (write) and recovering (read) qcodes datasets.

close_file(data_set: qcodes_loop.data.data_set.DataSet)

Closes the hdf5 file open in the dataset.

Parameters:

data_set – DataSet object

read(data_set: qcodes_loop.data.data_set.DataSet, location=None)

Reads an hdf5 file specified by location into a data_set object. If no data_set is provided will create an empty data_set to read into.

Parameters:

  • data_set – the data to read into. Should already have attributes io (an io manager), location (string), and arrays (dict of {array_id: array}, can be empty or can already have some or all of the arrays present, they expect to be overwritten)

  • location (None or str) – Location to write the data. If no location is provided will use the location specified in the dataset.

read_dict_from_hdf5(data_dict, h5_group)

Read a dictionary from HDF5

Parameters:

  • data_dict (dict) – Dataset to read from

  • h5_group (object) – HDF5 object to read from

read_metadata(data_set: qcodes_loop.data.data_set.DataSet)

Reads in the metadata, this is also called at the end of a read statement so there should be no need to call this explicitly.

Parameters:

data_set – Dataset object to read the metadata into

write(data_set, io_manager=None, location=None, force_write=False, flush=True, write_metadata=True, only_complete=False)

Writes a data_set to an hdf5 file.

Parameters:

  • data_set – qcodes data_set to write to hdf5 file

  • io_manager – io_manger used for providing path

  • location – location can be used to specify custom location

  • force_write (bool) – if True creates a new file to write to

  • flush (bool) – whether to flush after writing, can be disabled for testing or performance reasons

  • write_metadata (bool) – If True write the dataset metadata to disk

  • only_complete (bool) – Not used by this formatter, but must be included in the call signature to avoid an “unexpected keyword argument” TypeError.

N.B. It is recommended to close the file after writing, this can be done by calling HDF5Format.close_file(data_set) or data_set.finalize() if the data_set formatter is set to an hdf5 formatter. Note that this is not required if the dataset is created from a Loop as this includes a data_set.finalize() statement.

The write function consists of two parts, writing DataArrays and writing metadata.

  • The main part of write consists of writing and resizing arrays, the resizing providing support for incremental writes.

  • write_metadata is called at the end of write and dumps a dictionary to an hdf5 file. If there already is metadata it will delete this and overwrite it with current metadata.

write_dict_to_hdf5(data_dict, entry_point)

Write a (nested) dictionary to HDF5

Parameters:

  • data_dict (dict) – Dicionary to be written

  • entry_point (object) – Object to write to

write_metadata(data_set, io_manager=None, location=None, read_first=True, **kwargs)

Writes metadata of dataset to file using write_dict_to_hdf5 method

Note that io and location are arguments that are only here because of backwards compatibility with the loop. This formatter uses io and location as specified for the main dataset. The read_first argument is ignored.

class qcodes_loop.data.hdf5_format.HDF5FormatMetadata
read_metadata(data_set)

Reads in the metadata, this is also called at the end of a read statement so there should be no need to call this explicitly.

Parameters:

data_set – Dataset object to read the metadata into

write_metadata(data_set: qcodes_loop.data.data_set.DataSet, io_manager=None, location=None, read_first=False, **kwargs)

Write all metadata in this DataSet to storage.

Parameters:

  • data_set – the data we’re storing

  • io_manager (io_manager) – the base location to write to

  • location (str) – the file location within io_manager

  • read_first (Optional[bool]) – read previously saved metadata before writing? The current metadata will still be the used if there are changes, but if the saved metadata has information not present in the current metadata, it will be retained. Default True.

  • kwargs (dict) – From the dicionary the key sort_keys is extracted (default value: False). If True, then the keys of the metadata will be stored sorted in the json file. Note: sorting is only possible if the keys of the metadata dictionary can be compared.